WorldWideScience

Sample records for genetic programming techniques

  1. Towards Merging Binary Integer Programming Techniques with Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Reza Zamani

    2017-01-01

    Full Text Available This paper presents a framework based on merging a binary integer programming technique with a genetic algorithm. The framework uses both lower and upper bounds to make the employed mathematical formulation of a problem as tight as possible. For problems whose optimal solutions cannot be obtained, precision is traded with speed through substituting the integrality constrains in a binary integer program with a penalty. In this way, instead of constraining a variable u with binary restriction, u is considered as real number between 0 and 1, with the penalty of Mu(1-u, in which M is a large number. Values not near to the boundary extremes of 0 and 1 make the component of Mu(1-u large and are expected to be avoided implicitly. The nonbinary values are then converted to priorities, and a genetic algorithm can use these priorities to fill its initial pool for producing feasible solutions. The presented framework can be applied to many combinatorial optimization problems. Here, a procedure based on this framework has been applied to a scheduling problem, and the results of computational experiments have been discussed, emphasizing the knowledge generated and inefficiencies to be circumvented with this framework in future.

  2. Developing close combat behaviors for simulated soldiers using genetic programming techniques.

    Energy Technology Data Exchange (ETDEWEB)

    Pryor, Richard J.; Schaller, Mark J.

    2003-10-01

    Genetic programming is a powerful methodology for automatically producing solutions to problems in a variety of domains. It has been used successfully to develop behaviors for RoboCup soccer players and simple combat agents. We will attempt to use genetic programming to solve a problem in the domain of strategic combat, keeping in mind the end goal of developing sophisticated behaviors for compound defense and infiltration. The simplified problem at hand is that of two armed agents in a small room, containing obstacles, fighting against each other for survival. The base case and three changes are considered: a memory of positions using stacks, context-dependent genetic programming, and strongly typed genetic programming. Our work demonstrates slight improvements from the first two techniques, and no significant improvement from the last.

  3. System Response Analysis and Model Order Reduction, Using Conventional Method, Bond Graph Technique and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lubna Moin

    2009-04-01

    Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and

  4. On the Reliability of Nonlinear Modeling using Enhanced Genetic Programming Techniques

    Science.gov (United States)

    Winkler, S. M.; Affenzeller, M.; Wagner, S.

    The use of genetic programming (GP) in nonlinear system identification enables the automated search for mathematical models that are evolved by an evolutionary process using the principles of selection, crossover and mutation. Due to the stochastic element that is intrinsic to any evolutionary process, GP cannot guarantee the generation of similar or even equal models in each GP process execution; still, if there is a physical model underlying to the data that are analyzed, then GP is expected to find these structures and produce somehow similar results. In this paper we define a function for measuring the syntactic similarity of mathematical models represented as structure trees; using this similarity function we compare the results produced by GP techniques for a data set representing measurement data of a BMW Diesel engine.

  5. Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique

    Science.gov (United States)

    Matsumura, Koki; Tamekuni, Yuji; Kimura, Shuhei

    There are a lot of constructional differences in an English-Japanese phrase template, and that often makes the act of translation difficult. Moreover, there exist various and tremendous phrase templates and sentence to be refered to. It is not easy to prepare the corpus that covers the all. Therefore, it is very significant to generate the translation pattern of the sentence pattern automatically from a viewpoint of the translation success rate and the capacity of the pattern dictionary. Then, for the purpose of realizing the automatic generation of the translation pattern, this paper proposed the new method for the generation of the translation pattern by using the genetic programming technique (GP). The technique tries to generate the translation pattern of various sentences which are not registered in the phrase template dictionary automatically by giving the genetic operation to the parsing tree of a basic pattern. The tree consists of the pair of the English-Japanese sentence generated as the first stage population. The analysis tree data base with 50,100,150,200 pairs was prepared as the first stage population. And this system was applied and executed for an English input of 1,555 sentences. As a result, the analysis tree increases from 200 to 517, and the accuracy rate of the translation pattern has improved from 42.57% to 70.10%. And, 86.71% of the generated translations was successfully done, whose meanings are enough acceptable and understandable. It seemed that this proposal technique became a clue to raise the translation success rate, and to find the possibility of the reduction of the analysis tree data base.

  6. Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques

    Science.gov (United States)

    Kisi, Ozgur; Sanikhani, Hadi; Cobaner, Murat

    2017-08-01

    The applicability of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) techniques in estimating soil temperatures (ST) at different depths is investigated in this study. Weather data from two stations, Mersin and Adana, Turkey, were used as inputs to the applied models in order to model monthly STs. The first part of the study focused on comparison of ANN, ANFIS, and GP models in modeling ST of two stations at the depths of 10, 50, and 100 cm. GP was found to perform better than the ANN and ANFIS-SC in estimating monthly ST. The effect of periodicity (month of the year) on models' accuracy was also investigated. Including periodicity component in models' inputs considerably increased their accuracies. The root mean square error (RMSE) of ANN models was respectively decreased by 34 and 27 % for the depths of 10 and 100 cm adding the periodicity input. In the second part of the study, the accuracies of the ANN, ANFIS, and GP models were compared in estimating ST of Mersin Station using the climatic data of Adana Station. The ANN models generally performed better than the ANFIS-SC and GP in modeling ST of Mersin Station without local climatic inputs.

  7. Genetic programming in microorganisms

    Energy Technology Data Exchange (ETDEWEB)

    Hopwood, D A

    1981-11-01

    Formerly, when microbiologists had only existing organisms at their disposal whose characteristics could only be changed randomly by genetic experiments, they used to dream of programmed genetic changes. This dream has come true with modern genetic engineering.

  8. New horizontal global solar radiation estimation models for Turkey based on robust coplot supported genetic programming technique

    International Nuclear Information System (INIS)

    Demirhan, Haydar; Kayhan Atilgan, Yasemin

    2015-01-01

    Highlights: • Precise horizontal global solar radiation estimation models are proposed for Turkey. • Genetic programming technique is used to construct the models. • Robust coplot analysis is applied to reduce the impact of outlier observations. • Better estimation and prediction properties are observed for the models. - Abstract: Renewable energy sources have been attracting more and more attention of researchers due to the diminishing and harmful nature of fossil energy sources. Because of the importance of solar energy as a renewable energy source, an accurate determination of significant covariates and their relationships with the amount of global solar radiation reaching the Earth is a critical research problem. There are numerous meteorological and terrestrial covariates that can be used in the analysis of horizontal global solar radiation. Some of these covariates are highly correlated with each other. It is possible to find a large variety of linear or non-linear models to explain the amount of horizontal global solar radiation. However, models that explain the amount of global solar radiation with the smallest set of covariates should be obtained. In this study, use of the robust coplot technique to reduce the number of covariates before going forward with advanced modelling techniques is considered. After reducing the dimensionality of model space, yearly and monthly mean daily horizontal global solar radiation estimation models for Turkey are built by using the genetic programming technique. It is observed that application of robust coplot analysis is helpful for building precise models that explain the amount of global solar radiation with the minimum number of covariates without suffering from outlier observations and the multicollinearity problem. Consequently, over a dataset of Turkey, precise yearly and monthly mean daily global solar radiation estimation models are introduced using the model spaces obtained by robust coplot technique and

  9. Partial discharge localization in power transformers based on the sequential quadratic programming-genetic algorithm adopting acoustic emission techniques

    Science.gov (United States)

    Liu, Hua-Long; Liu, Hua-Dong

    2014-10-01

    Partial discharge (PD) in power transformers is one of the prime reasons resulting in insulation degradation and power faults. Hence, it is of great importance to study the techniques of the detection and localization of PD in theory and practice. The detection and localization of PD employing acoustic emission (AE) techniques, as a kind of non-destructive testing, plus due to the advantages of powerful capability of locating and high precision, have been paid more and more attention. The localization algorithm is the key factor to decide the localization accuracy in AE localization of PD. Many kinds of localization algorithms exist for the PD source localization adopting AE techniques including intelligent and non-intelligent algorithms. However, the existed algorithms possess some defects such as the premature convergence phenomenon, poor local optimization ability and unsuitability for the field applications. To overcome the poor local optimization ability and easily caused premature convergence phenomenon of the fundamental genetic algorithm (GA), a new kind of improved GA is proposed, namely the sequence quadratic programming-genetic algorithm (SQP-GA). For the hybrid optimization algorithm, SQP-GA, the sequence quadratic programming (SQP) algorithm which is used as a basic operator is integrated into the fundamental GA, so the local searching ability of the fundamental GA is improved effectively and the premature convergence phenomenon is overcome. Experimental results of the numerical simulations of benchmark functions show that the hybrid optimization algorithm, SQP-GA, is better than the fundamental GA in the convergence speed and optimization precision, and the proposed algorithm in this paper has outstanding optimization effect. At the same time, the presented SQP-GA in the paper is applied to solve the ultrasonic localization problem of PD in transformers, then the ultrasonic localization method of PD in transformers based on the SQP-GA is proposed. And

  10. Applications of Genetic Programming

    DEFF Research Database (Denmark)

    Gaunholt, Hans; Toma, Laura

    1996-01-01

    In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc.......In this report a study of genetic programming (GP) has been performed with respect to a number of applications such as Symbolic function regression, Solving Symbolic Differential Equations, Image encoding, the ant problem etc....

  11. Linear genetic programming

    CERN Document Server

    Brameier, Markus

    2007-01-01

    Presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. This book serves as a reference for researchers, but also contains sufficient introduction for students and those who are new to the field

  12. Scientific discovery using genetic programming

    DEFF Research Database (Denmark)

    Keijzer, Maarten

    2001-01-01

    programming paradigm. The induction of mathematical expressions based on data is called symbolic regression. In this work, genetic programming is extended to not just fit the data i.e., get the numbers right, but also to get the dimensions right. For this units of measurement are used. The main contribution......Genetic Programming is capable of automatically inducing symbolic computer programs on the basis of a set of examples or their performance in a simulation. Mathematical expressions are a well-defined subset of symbolic computer programs and are also suitable for optimization using the genetic...... in this work can be summarized as: The symbolic expressions produced by genetic programming can be made suitable for analysis and interpretation by using units of measurements to guide or restrict the search. To achieve this, the following has been accomplished: A standard genetic programming system...

  13. Hybrid of Genetic Programming with PBIL

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2005-01-01

    Genetic programming and PBIL (Population-Based Incremental Learning) are evolutionary algorithms that have found applications in several fields of application. The Genetic Programming searches a solution allowing that the individuals of a population modify, mainly, its structures. The PBIL, on the other hand, works with individuals of fixed structure and is particularly successful in finding numerical solutions. There are problems where the simultaneous adjustment of the structure and numerical constants in a solution is essential. The Symbolic Regression is an example where both the form and the constants of a mathematical expression must be found. Although the traditional Genetic Programming is capable to solve this problem by itself, it is interesting to explore a cooperation with the PBIL, allowing each algorithm to do only that they do best: the Genetic Programming tries to find a structure while the PBIL adjust the constants that will be enclosed in the structure. In this work, the benchmark 'the sextic polynomial regression problem' is used to compare some traditional techniques of Genetic Programming with the proposed Hybrid of Genetic Programming with PBIL. The results are presented and discussed. (author)

  14. Behavioral program synthesis with genetic programming

    CERN Document Server

    Krawiec, Krzysztof

    2016-01-01

    Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subs...

  15. Genetic technologies to enhance the Sterile Insect Technique (SIT)

    International Nuclear Information System (INIS)

    Alphey, Luke; Baker, Pam; Condon, George C.; Condon, Kirsty C.; Dafa'alla, Tarig H.; Fu, Guoliang; Jin, Li; Labbe, Genevieve; Morrison, Neil M.; Nimmo, Derric D.; O'Connell, Sinead; Phillips, Caroline E.; Plackett, Andrew; Scaife, Sarah; Woods, Alexander; Burton, Rosemary S.; Epton, Matthew J.; Gong, Peng

    2006-01-01

    The Sterile Insect Technique (SIT) has been used very successfully against range of pest insects, including various tephritid fruit flies, several moths and a small number of livestock pests. However, modern genetics could potentially provide several improvements that would increase the cost-effectiveness of SIT, and extend the range of suitable species. These include improved identification of released individuals by incorporation of a stable, heritable, genetic marker; built-in sex separation (genetic sexing); reduction of the hazard posed by non-irradiated accidental releases from mass-rearing facility (fail-safe); elimination of the need for sterilization by irradiation (genetic sterilization). We discuss applications of these methods and the state of the art, at the time of this meeting, in developing suitable strains. We have demonstrated, in several key pest species, that the required strains can be constructed by introducing a repressible dominant lethal genetic system, a method known as RIDL(trade mark). Based on field experience with Medfly, incorporation of a genetic sexing system into SIT programs for other tephritids could potentially provide a very significant improvement in cost-effectiveness. We have now been able to make efficient female-lethal strains for Medfly. One advantage of our approach is that it should be possible rapidly to extend this technology to other fruit fly species; indeed we have recently been able also to make genetic sexing strains of Medfly (Anastrepha ludens). (author)

  16. Genetic technologies to enhance the Sterile Insect Technique (SIT)

    Energy Technology Data Exchange (ETDEWEB)

    Alphey, Luke; Baker, Pam; Condon, George C; Condon, Kirsty C; Dafa' alla, Tarig H; Fu, Guoliang; Jin, Li; Labbe, Genevieve; Morrison, Neil M; Nimmo, Derric D; O' Connell, Sinead; Phillips, Caroline E; Plackett, Andrew; Scaife, Sarah; Woods, Alexander [Oxitec Ltd., Oxford (United Kingdom); Burton, Rosemary S; Epton, Matthew J; Gong, Peng [University of Oxford (United Kingdom). Dept. of Zoology

    2006-07-01

    The Sterile Insect Technique (SIT) has been used very successfully against range of pest insects, including various tephritid fruit flies, several moths and a small number of livestock pests. However, modern genetics could potentially provide several improvements that would increase the cost-effectiveness of SIT, and extend the range of suitable species. These include improved identification of released individuals by incorporation of a stable, heritable, genetic marker; built-in sex separation (genetic sexing); reduction of the hazard posed by non-irradiated accidental releases from mass-rearing facility (fail-safe); elimination of the need for sterilization by irradiation (genetic sterilization). We discuss applications of these methods and the state of the art, at the time of this meeting, in developing suitable strains. We have demonstrated, in several key pest species, that the required strains can be constructed by introducing a repressible dominant lethal genetic system, a method known as RIDL(trade mark). Based on field experience with Medfly, incorporation of a genetic sexing system into SIT programs for other tephritids could potentially provide a very significant improvement in cost-effectiveness. We have now been able to make efficient female-lethal strains for Medfly. One advantage of our approach is that it should be possible rapidly to extend this technology to other fruit fly species; indeed we have recently been able also to make genetic sexing strains of Medfly (Anastrepha ludens). (author)

  17. Genetic basis of the sterile insect technique

    International Nuclear Information System (INIS)

    Robinson, A.S.

    2005-01-01

    The use of the sterile insect technique (SIT) for insect control relies on the introduction of sterility in the females of the wild population. This sterility is produced following the mating of these females with released males carrying, in their sperm, dominant lethal mutations that have been induced by ionizing radiation. The reasons why the SIT can only be effective when the induced sterility in the released males is in the form of dominant lethal mutations, and not some form of sperm inactivation, are discussed, together with the relationship of dominant lethal mutations to dose, sex, developmental stage and the particular species. The combination of genetic sterility with that induced by radiation is also discussed in relation to the use of genetic sexing strains of the Mediterranean fruit fly Ceratitis capitata (Wiedemann) in area-wide integrated pest management (AW-IPM) programmes that integrate the SIT. A case is made to lower the radiation dose used in such programmes so as to produce a more competitive sterile insect. Increased competitiveness can also be achieved by using different radiation environments. As well as radiation-induced sterility, natural mechanisms can be recruited, especially the use of hybrid sterility exemplified by a successful field trial with tsetse flies Glossina spp. in the 1940s. Genetic transformation will make some impact on the SIT, especially regarding the introduction of markers for released flies, and the construction of genetic sexing strains. It is concluded that using a physical process, such as radiation, will always have significant advantages over genetic and other methods of sterilization for the large-scale application of the SIT. (author)

  18. Genetic engineering possibilities for CELSS: A bibliography and summary of techniques

    Science.gov (United States)

    Johnson, E. J.

    1982-01-01

    A bibliography of the most useful techniques employed in genetic engineering of higher plants, bacteria associated with plants, and plant cell cultures is provided. A resume of state-of-the-art genetic engineering of plants and bacteria is presented. The potential application of plant bacterial genetic engineering to CELSS (Controlled Ecological Life Support System) program and future research needs are discussed.

  19. Genetic programming theory and practice XII

    CERN Document Server

    Riolo, Rick; Kotanchek, Mark

    2015-01-01

    These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: gene expression regulation, novel genetic models for glaucoma, inheritable epigenetics, combinators in genetic programming, sequential symbolic regression, system dynamics, sliding window symbolic regression, large feature problems, alignment in the error space, HUMIE winners, Boolean multiplexer funct

  20. DOE transporation programs - computerized techniques

    Energy Technology Data Exchange (ETDEWEB)

    Joy, D.S.; Johnson, P.E.; Fore, C.S.; Peterson, B.E.

    1983-01-01

    One of the major thrusts of the transportation programs at the Oak Ridge National Laboratory has been the development of a number of computerized transportation programs and data bases. The U.S. Department of Energy (DOE) is supporting these efforts through the Transportation Technology Center at Sandia National Laboratories and the Tranportation Operations and Traffic Management (TOTM) organization at DOE Headquarters. Initially this project was centered upon research activities. However, since these tools provide traffic managers and key personnel involved in preshipment planning with a unique resource for ensuring that the movement of radioactive materials can be properly accomplished, additional interest and support is coming from the operational side of DOE. The major accomplishments include the development of two routing models (one for rail shipments and the other for highway shipments), an emergency response assistance program, and two data bases containing pertinent legislative and regulatory information. This paper discusses the mose recent advances in, and additions to, these computerized techniques and provides examples of how they are used.

  1. Genetic basis of the sterile insect technique

    International Nuclear Information System (INIS)

    Robinson, A.S.

    2014-01-01

    The use of the sterile insect technique for insect control relies on the introduction of sterility in the females of the wild population. This sterility is produced following the mating of these females with released males carrying, in their sperm, dominant lethal mutations that have been induced by ionizing radiation. As well as radiation-induced sterility, natural mechanisms can be recruited, especially the use of hybrid sterility. Radiation is usually one of the last procedures that insects undergo before leaving mass-rearing facilities for release in the field. It is essential that the dosimetry of the radiation source be checked to ensure that all the insects receive the required minimum dose. A dose should be chosen that maximizes the level of introduced sterility in the wild females in the field. Irradiation in nitrogen can provide protection against the detrimental somatic effects of radiation. Currently, the development of molecular methods to sterilize pest insects in the field, by the release of fertile insects carrying trans genes, is very much in vogue. It is concluded that using a physical process, such as radiation, will always have significant advantages over genetic and other methods of sterilization for the large-scale application of the sterile insect technique. (author)

  2. Primer on molecular genetics. DOE Human Genome Program

    Energy Technology Data Exchange (ETDEWEB)

    1992-04-01

    This report is taken from the April 1992 draft of the DOE Human Genome 1991--1992 Program Report, which is expected to be published in May 1992. The primer is intended to be an introduction to basic principles of molecular genetics pertaining to the genome project. The material contained herein is not final and may be incomplete. Techniques of genetic mapping and DNA sequencing are described.

  3. Algorithmic Trading with Developmental and Linear Genetic Programming

    Science.gov (United States)

    Wilson, Garnett; Banzhaf, Wolfgang

    A developmental co-evolutionary genetic programming approach (PAM DGP) and a standard linear genetic programming (LGP) stock trading systemare applied to a number of stocks across market sectors. Both GP techniques were found to be robust to market fluctuations and reactive to opportunities associated with stock price rise and fall, with PAMDGP generating notably greater profit in some stock trend scenarios. Both algorithms were very accurate at buying to achieve profit and selling to protect assets, while exhibiting bothmoderate trading activity and the ability to maximize or minimize investment as appropriate. The content of the trading rules produced by both algorithms are also examined in relation to stock price trend scenarios.

  4. Improvements of methanogenesis by genetic techniques

    International Nuclear Information System (INIS)

    Baresi, L.

    1985-01-01

    The objective of this research is to characterize the genetic system of one or two strains of methanogenic bacteria. Both ultraviolet exposure and chemical screening will be used to isolate mutant species. These species will be tested for genetic recombination. Bacteriophages and plasmids will be sought. Two species, Methanococcus voltae and Methanobacterium thermoautotrophicum, will be subjected to extensive screening and manipulation. Nutritional mutants of these two strains will be studied to determine uptake rates. Once a set of satisfactory mutants is obtained, two types of genetic recombination experiments (conjugation and DNA transformation) will be carried out

  5. Genetically programmed chiral organoborane synthesis

    Science.gov (United States)

    Kan, S. B. Jennifer; Huang, Xiongyi; Gumulya, Yosephine; Chen, Kai; Arnold, Frances H.

    2017-12-01

    Recent advances in enzyme engineering and design have expanded nature’s catalytic repertoire to functions that are new to biology. However, only a subset of these engineered enzymes can function in living systems. Finding enzymatic pathways that form chemical bonds that are not found in biology is particularly difficult in the cellular environment, as this depends on the discovery not only of new enzyme activities, but also of reagents that are both sufficiently reactive for the desired transformation and stable in vivo. Here we report the discovery, evolution and generalization of a fully genetically encoded platform for producing chiral organoboranes in bacteria. Escherichia coli cells harbouring wild-type cytochrome c from Rhodothermus marinus (Rma cyt c) were found to form carbon-boron bonds in the presence of borane-Lewis base complexes, through carbene insertion into boron-hydrogen bonds. Directed evolution of Rma cyt c in the bacterial catalyst provided access to 16 novel chiral organoboranes. The catalyst is suitable for gram-scale biosynthesis, providing up to 15,300 turnovers, a turnover frequency of 6,100 h-1, a 99:1 enantiomeric ratio and 100% chemoselectivity. The enantiopreference of the biocatalyst could also be tuned to provide either enantiomer of the organoborane products. Evolved in the context of whole-cell catalysts, the proteins were more active in the whole-cell system than in purified forms. This study establishes a DNA-encoded and readily engineered bacterial platform for borylation; engineering can be accomplished at a pace that rivals the development of chemical synthetic methods, with the ability to achieve turnovers that are two orders of magnitude (over 400-fold) greater than those of known chiral catalysts for the same class of transformation. This tunable method for manipulating boron in cells could expand the scope of boron chemistry in living systems.

  6. Non-linear nuclear engineering models as genetic programming application

    International Nuclear Information System (INIS)

    Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.

    1997-01-01

    This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs

  7. Using genetic programming to find Lyapunov functions

    NARCIS (Netherlands)

    Soute, I.A.C.; Molengraft, van de M.J.G.; Angelis, G.Z.; Ryan, C; Spector, L.

    2001-01-01

    In this paper Genetic Programming is used to find Lyapunov functions for (non)linear dif ferential equations of autonomous systems. As Lyapunov functions can be difficult to find, we use OP to make the decisions concerning the form of the Lyapunov function. As an e5cample two systems are taken to

  8. Genetic Network Programming with Reconstructed Individuals

    Science.gov (United States)

    Ye, Fengming; Mabu, Shingo; Wang, Lutao; Eto, Shinji; Hirasawa, Kotaro

    A lot of research on evolutionary computation has been done and some significant classical methods such as Genetic Algorithm (GA), Genetic Programming (GP), Evolutionary Programming (EP), and Evolution Strategies (ES) have been studied. Recently, a new approach named Genetic Network Programming (GNP) has been proposed. GNP can evolve itself and find the optimal solution. It is based on the idea of Genetic Algorithm and uses the data structure of directed graphs. Many papers have demonstrated that GNP can deal with complex problems in the dynamic environments very efficiently and effectively. As a result, recently, GNP is getting more and more attentions and is used in many different areas such as data mining, extracting trading rules of stock markets, elevator supervised control systems, etc., and GNP has obtained some outstanding results. Focusing on the GNP's distinguished expression ability of the graph structure, this paper proposes a method named Genetic Network Programming with Reconstructed Individuals (GNP-RI). The aim of GNP-RI is to balance the exploitation and exploration of GNP, that is, to strengthen the exploitation ability by using the exploited information extensively during the evolution process of GNP and finally obtain better performances than that of GNP. In the proposed method, the worse individuals are reconstructed and enhanced by the elite information before undergoing genetic operations (mutation and crossover). The enhancement of worse individuals mimics the maturing phenomenon in nature, where bad individuals can become smarter after receiving a good education. In this paper, GNP-RI is applied to the tile-world problem which is an excellent bench mark for evaluating the proposed architecture. The performance of GNP-RI is compared with that of the conventional GNP. The simulation results show some advantages of GNP-RI demonstrating its superiority over the conventional GNPs.

  9. Feature extraction from multiple data sources using genetic programming.

    Energy Technology Data Exchange (ETDEWEB)

    Szymanski, J. J. (John J.); Brumby, Steven P.; Pope, P. A. (Paul A.); Eads, D. R. (Damian R.); Galassi, M. C. (Mark C.); Harvey, N. R. (Neal R.); Perkins, S. J. (Simon J.); Porter, R. B. (Reid B.); Theiler, J. P. (James P.); Young, A. C. (Aaron Cody); Bloch, J. J. (Jeffrey J.); David, N. A. (Nancy A.); Esch-Mosher, D. M. (Diana M.)

    2002-01-01

    Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

  10. Evolution of Genetic Techniques: Past, Present, and Beyond

    Directory of Open Access Journals (Sweden)

    Asude Alpman Durmaz

    2015-01-01

    Full Text Available Genetics is the study of heredity, which means the study of genes and factors related to all aspects of genes. The scientific history of genetics began with the works of Gregor Mendel in the mid-19th century. Prior to Mendel, genetics was primarily theoretical whilst, after Mendel, the science of genetics was broadened to include experimental genetics. Developments in all fields of genetics and genetic technology in the first half of the 20th century provided a basis for the later developments. In the second half of the 20th century, the molecular background of genetics has become more understandable. Rapid technological advancements, followed by the completion of Human Genome Project, have contributed a great deal to the knowledge of genetic factors and their impact on human life and diseases. Currently, more than 1800 disease genes have been identified, more than 2000 genetic tests have become available, and in conjunction with this at least 350 biotechnology-based products have been released onto the market. Novel technologies, particularly next generation sequencing, have dramatically accelerated the pace of biological research, while at the same time increasing expectations. In this paper, a brief summary of genetic history with short explanations of most popular genetic techniques is given.

  11. Genetic Programming for Automatic Hydrological Modelling

    Science.gov (United States)

    Chadalawada, Jayashree; Babovic, Vladan

    2017-04-01

    One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

  12. Applications of genetic programming in cancer research.

    Science.gov (United States)

    Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

    2009-02-01

    The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

  13. Genetic programming theory and practice X

    CERN Document Server

    Riolo, Rick; Ritchie, Marylyn D; Moore, Jason H

    2013-01-01

    These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: evolutionary constraints, relaxation of selection mechanisms, diversity preservation strategies, flexing fitness evaluation, evolution in dynamic environments, multi-objective and multi-modal selection, foundations of evolvability, evolvable and adaptive evolutionary operators, foundation of  injecting

  14. Genetic Programming for Sea Level Predictions in an Island Environment

    Directory of Open Access Journals (Sweden)

    M.A. Ghorbani

    2010-03-01

    Full Text Available Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP and artificial neural networks (ANNs were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.

  15. Multigene Genetic Programming for Estimation of Elastic Modulus of Concrete

    Directory of Open Access Journals (Sweden)

    Alireza Mohammadi Bayazidi

    2014-01-01

    Full Text Available This paper presents a new multigene genetic programming (MGGP approach for estimation of elastic modulus of concrete. The MGGP technique models the elastic modulus behavior by integrating the capabilities of standard genetic programming and classical regression. The main aim is to derive precise relationships between the tangent elastic moduli of normal and high strength concrete and the corresponding compressive strength values. Another important contribution of this study is to develop a generalized prediction model for the elastic moduli of both normal and high strength concrete. Numerous concrete compressive strength test results are obtained from the literature to develop the models. A comprehensive comparative study is conducted to verify the performance of the models. The proposed models perform superior to the existing traditional models, as well as those derived using other powerful soft computing tools.

  16. Role of population genetics in the sterile insect technique

    International Nuclear Information System (INIS)

    Krafsur, E.S.

    2005-01-01

    The detection and analysis of genetic variation in natural and laboratory populations are reviewed. The application of population genetic methods and theory can help to plan and evaluate the implementation of area-wide integrated pest management (AW-IPM) programmes that use the sterile insect technique (SIT). Population genetic studies can play an important role in estimating dispersal rates and thus gene flow among target populations, determining if sibling species exist, establishing the origin of outbreaks or reintroductions, and supporting the quality control of mass-reared colonies. The target's population history may be examined, in terms of 'bottlenecks', range fragmentations, and expansions. Genetic methods can be helpful in distinguishing wild insects from released sterile or substerile ones, and in ascertaining, together with mating cross-compatibility studies, the compatibility of mass-reared colonies with target wild insects. (author)

  17. A NEW MUTATION OPERATOR IN GENETIC PROGRAMMING

    Directory of Open Access Journals (Sweden)

    Anuradha Purohit

    2013-01-01

    Full Text Available This paper proposes a new type of mutation operator, FEDS (Fitness, Elitism, Depth, and Size mutation in genetic programming. The concept behind the new mutation operator is inspired from already introduced FEDS crossover operator to handle the problem of code bloating. FEDS mutation operates by using local elitism replacement in combination with depth limit and size of the trees to reduce bloat with a subsequent improvement in the performance of trees (program structures. We have designed a multiclass classifier for some benchmark datasets to test the performance of proposed mutation. The results show that when the initial run uses FEDS crossover and the concluding run uses FEDS mutation, then not only is the final result significantly improved but there is reduction in bloat also.

  18. Testing the structure of a hydrological model using Genetic Programming

    Science.gov (United States)

    Selle, Benny; Muttil, Nitin

    2011-01-01

    SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  19. Forecasting tourist arrivals to balearic islands using genetic programming

    Directory of Open Access Journals (Sweden)

    Rosselló-Nadal, Jaume

    2007-01-01

    Full Text Available Traditionally, univariate time-series models have largely dominated forecasting for international tourism demand. In this paper, the ability of a Genetic Program (GP to predict monthly tourist arrivals from UK and Germany to Balearic Islands (Spain is explored. GP has already been employed satisfactorily in different scientific areas, including economics. The technique shows different advantages regarding to other forecasting methods. Firstly, it does not assume a priori a rigid functional form of the model. Secondly, it is more robust and easy-to-use than other non-parametric methods. Finally, it provides explicitly a mathematical equation which allows a simple ad hoc interpretation of the results. Comparing the performance of the proposed technique against other method commonly used in tourism forecasting (no-change model, Moving Average and ARIMA, the empirical results reveal that GP can be a valuable tool in this field.

  20. Guidelines on the use of molecular genetics in reintroduction programs

    Science.gov (United States)

    Michael K. Schwartz

    2005-01-01

    The use of molecular genetics can play a key role in reintroduction efforts. Prior to the introduction of any individuals, molecular genetics can be used to identify the most appropriate source population for the reintroduction, ensure that no relic populations exist in the reintroduction area, and guide captive breeding programs. The use of molecular genetics post-...

  1. The sheep blowfly genetic control program in Australia

    International Nuclear Information System (INIS)

    Foster, Geoffrey G.

    1989-01-01

    The blowfly Lucilia cuprina is the most important myiasis pet of sheep in Australia. Other species are associated with sheep myiasis, but L. cuprina is probably responsible for initiating more than 90% of infestations. Annual costs of production losses, prevention and treatment have been estimated at $149 millions in 1985. Prevention and treatment encompass both insecticidal applications to sheep and non-chemical management practices. In the absence of effective preventive measures, the sheep industry would be non-viable over much of Australia. Insecticide usage against L. cuprina has been marked by the appearance of widespread resistance to cyclodienes in 1956, the organophosphates in 1965, and carbamates in 1966. Resistance has not yet been reported against the triazine compounds introduced for blowfly control in 1981. The most effective non-chemical control measures are surgical (removal of skin from the breech in certain breeds of sheep, and tail-docking). They protect sheep by reducing favourable oviposition sites (dung and urine-stained wool). The spectre of insecticide resistance and the early success of the sterile insect technique (SIT) against screwworm fly in the U.S.A., led this Division to consider SIT and other autocidal methods in the 1960s. The L. cuprina genetics research program was established in 1966 and subsequently expanded in 1971. More recently, lobbying by animal welfare groups against surgical blowfly control practices, as well as increasing consumer awareness of insecticide residues in animal products, have accelerated the search for alternatives to chemical control. When SIT was first considered for L. cuprina control in 1960, little was known about the population dynamics of L. cuprina. There were insufficient ecological data to evaluate the prospects of alternative strategies such as suppression or containment. The number of flies which would have to be released in a SIT program was unknown, as were the costs. Assuming that the cost of

  2. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    Science.gov (United States)

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Labview advanced programming techniques, second edition

    CERN Document Server

    Bitter, Rick; Nawrocki, Matt

    2006-01-01

    Whether seeking deeper knowledge of LabVIEW®'s capabilities or striving to build enhanced VIs, professionals know they will find everything they need in LabVIEW: Advanced Programming Techniques. Now accompanied by LabVIEW 2011, this classic second edition, focusing on LabVIEW 8.0, delves deeply into the classic features that continue to make LabVIEW one of the most popular and widely used graphical programming environments across the engineering community. The authors review the front panel controls, the Standard State Machine template, drivers, the instrument I/O assistant, error handling functions, hyperthreading, and Express VIs. It covers the introduction of the Shared Variables function in LabVIEW 8.0 and explores the LabVIEW project view. The chapter on ActiveX includes discussion of the Microsoft™ .NET® framework and new examples of programming in LabVIEW using .NET. Numerous illustrations and step-by-step explanations provide hands-on guidance. Reviewing LabVIEW 8.0 and accompanied by the latest s...

  4. Testing the Structure of Hydrological Models using Genetic Programming

    Science.gov (United States)

    Selle, B.; Muttil, N.

    2009-04-01

    Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  5. Developing robotic behavior using a genetic programming model

    International Nuclear Information System (INIS)

    Pryor, R.J.

    1998-01-01

    This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle's on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study

  6. Genetics Education in Nurse Residency Programs: A Natural Fit.

    Science.gov (United States)

    Hamilton, Nalo M; Stenman, Christina W; Sang, Elaine; Palmer, Christina

    2017-08-01

    Scientific advances are shedding light on the genetic underpinning of common diseases. With such insight, the entire health care team is faced with the need to address patient questions regarding genetic risk, testing, and the psychosocial aspects of genetics information. Nurses are in a prime position to help with patient education about genetic conditions, yet they often lack adequate genetics education within their nursing curriculum to address patient questions and provide resources. One mechanism to address this knowledge deficit is the incorporation of a genetics-based curriculum into nurse residency programs. This article describes a novel genetics-based curriculum designed and implemented in the UCLA Health System Nurse Residency Program. J Contin Educ Nurs. 2017;48(8):379-384. Copyright 2017, SLACK Incorporated.

  7. A Heuristics Approach for Classroom Scheduling Using Genetic Algorithm Technique

    Science.gov (United States)

    Ahmad, Izah R.; Sufahani, Suliadi; Ali, Maselan; Razali, Siti N. A. M.

    2018-04-01

    Reshuffling and arranging classroom based on the capacity of the audience, complete facilities, lecturing time and many more may lead to a complexity of classroom scheduling. While trying to enhance the productivity in classroom planning, this paper proposes a heuristic approach for timetabling optimization. A new algorithm was produced to take care of the timetabling problem in a university. The proposed of heuristics approach will prompt a superior utilization of the accessible classroom space for a given time table of courses at the university. Genetic Algorithm through Java programming languages were used in this study and aims at reducing the conflicts and optimizes the fitness. The algorithm considered the quantity of students in each class, class time, class size, time accessibility in each class and lecturer who in charge of the classes.

  8. Recent trends on crop genetic improvement using mutation techniques

    International Nuclear Information System (INIS)

    Kang, Siyong

    2008-01-01

    The radiation breeding technology has been significantly achieved on creation of mutation genetic resources of plants for commercial cultivation and genomic study since 1920s. According to the FAO-IAEA Mutant Variety Database, more than 2600 varieties have been released in the world. Induction of mutations with radiation has been the most frequently used by sources of X-ray and gamma ray, but in recent Japanese scientist have been used the heavy ion beam as a new radiation sources. And China has been made remarkable outcomes in the mutant creation using new space breeding technology since 1990s. In Korea, more about 40 varieties have been developed by using the mutation breeding method since the mid-1960s. Most of the released mutant varieties in Korea were food and oil seed crops, especially for improving agronomic traits such as yield, lodging tolerance, maturity, and functional compounds. Currently the mutation breeding program in Korea has assigned more resources to develop high functional crops and ornamental plants. These functional and ornamental plants are ideal systems for a mutation breeding. A research program for the development of potential varieties of flowering and ornamental crops as rose, chrysanthemum, lily, carnation, orchids, and wild flowers was started with financial support from the Bio green 21 project of Korean government. The potential outcomes from the program will be new highly valued-added varieties which will provide greater money gains to Korean farmers and lots of valued mutants used for a gene isolation of interest and reverse genetics or functional genomic. Scientific interest in mutation breeding has drastically be ed focused to the field of functional genomic. Scientific interest in mutation breeding has drastically be ed focused to the field of functional genomic after a completion of genome sequencing of some model plant species. A direct approach of discovering the function of a novel gene is to use a mutant which has altered

  9. Recent trends on crop genetic improvement using mutation techniques

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Siyong [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2008-04-15

    The radiation breeding technology has been significantly achieved on creation of mutation genetic resources of plants for commercial cultivation and genomic study since 1920s. According to the FAO-IAEA Mutant Variety Database, more than 2600 varieties have been released in the world. Induction of mutations with radiation has been the most frequently used by sources of X-ray and gamma ray, but in recent Japanese scientist have been used the heavy ion beam as a new radiation sources. And China has been made remarkable outcomes in the mutant creation using new space breeding technology since 1990s. In Korea, more about 40 varieties have been developed by using the mutation breeding method since the mid-1960s. Most of the released mutant varieties in Korea were food and oil seed crops, especially for improving agronomic traits such as yield, lodging tolerance, maturity, and functional compounds. Currently the mutation breeding program in Korea has assigned more resources to develop high functional crops and ornamental plants. These functional and ornamental plants are ideal systems for a mutation breeding. A research program for the development of potential varieties of flowering and ornamental crops as rose, chrysanthemum, lily, carnation, orchids, and wild flowers was started with financial support from the Bio green 21 project of Korean government. The potential outcomes from the program will be new highly valued-added varieties which will provide greater money gains to Korean farmers and lots of valued mutants used for a gene isolation of interest and reverse genetics or functional genomic. Scientific interest in mutation breeding has drastically be ed focused to the field of functional genomic. Scientific interest in mutation breeding has drastically be ed focused to the field of functional genomic after a completion of genome sequencing of some model plant species. A direct approach of discovering the function of a novel gene is to use a mutant which has altered

  10. Evaluating Dynamic Analysis Techniques for Program Comprehension

    NARCIS (Netherlands)

    Cornelissen, S.G.M.

    2009-01-01

    Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis.

  11. Functional Programming in C# Classic Programming Techniques for Modern Projects

    CERN Document Server

    Sturm, Oliver

    2011-01-01

    Take advantage of the growing trend in functional programming. C# is the number-one language used by .NET developers and one of the most popular programming languages in the world. It has many built-in functional programming features, but most are complex and little understood. With the shift to functional programming increasing at a rapid pace, you need to know how to leverage your existing skills to take advantage of this trend. Functional Programming in C# leads you along a path that begins with the historic value of functional ideas. Inside, C# MVP and functional programming expert Oli

  12. Resizing Technique-Based Hybrid Genetic Algorithm for Optimal Drift Design of Multistory Steel Frame Buildings

    Directory of Open Access Journals (Sweden)

    Hyo Seon Park

    2014-01-01

    Full Text Available Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.

  13. A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.

    Science.gov (United States)

    Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie

    2018-06-04

    Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.

  14. Academic training: From Evolution Theory to Parallel and Distributed Genetic Programming

    CERN Multimedia

    2007-01-01

    2006-2007 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 15, 16 March From 11:00 to 12:00 - Main Auditorium, bldg. 500 From Evolution Theory to Parallel and Distributed Genetic Programming F. FERNANDEZ DE VEGA / Univ. of Extremadura, SP Lecture No. 1: From Evolution Theory to Evolutionary Computation Evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) involving combinatorial optimization problems, which are based to some degree on the evolution of biological life in the natural world. In this tutorial we will review the source of inspiration for this metaheuristic and its capability for solving problems. We will show the main flavours within the field, and different problems that have been successfully solved employing this kind of techniques. Lecture No. 2: Parallel and Distributed Genetic Programming The successful application of Genetic Programming (GP, one of the available Evolutionary Algorithms) to optimization problems has encouraged an ...

  15. Polyglot programming in applications used for genetic data analysis.

    Science.gov (United States)

    Nowak, Robert M

    2014-01-01

    Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development.

  16. A Simulation of AI Programming Techniques in BASIC.

    Science.gov (United States)

    Mandell, Alan

    1986-01-01

    Explains the functions of and the techniques employed in expert systems. Offers the program "The Periodic Table Expert," as a model for using artificial intelligence techniques in BASIC. Includes the program listing and directions for its use on: Tandy 1000, 1200, and 2000; IBM PC; PC Jr; TRS-80; and Apple computers. (ML)

  17. Mendelian Genetics: Paradigm, Conjecture, or Research Program.

    Science.gov (United States)

    Oldham, V.; Brouwer, W.

    1984-01-01

    Applies Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos' methodology of competing research programs to a historical biological episode. Suggests using Kuhn's model (emphasizing the nonrational basis of science) and Popper's model (emphasizing the rational basis of science) in…

  18. Improvement of ECM Techniques through Implementation of a Genetic Algorithm

    National Research Council Canada - National Science Library

    Townsend, James D

    2008-01-01

    This research effort develops the necessary interfaces between the radar signal processing components and an optimization routine, such as genetic algorithms, to develop Electronic Countermeasure (ECM...

  19. Integer programming techniques for educational timetabling

    DEFF Research Database (Denmark)

    Fonseca, George H.G.; Santos, Haroldo G.; Carrano, Eduardo G.

    2017-01-01

    in recent studies in the field. This work presents new cuts and reformulations for the existing integer programming model for XHSTT. The proposed cuts improved hugely the linear relaxation of the formulation, leading to an average gap reduction of 32%. Applied to XHSTT-2014 instance set, the alternative...... formulation provided four new best known lower bounds and, used in a matheuristic framework, improved eleven best known solutions. The computational experiments also show that the resulting integer programming models from the proposed formulation are more effectively solved for most of the instances....

  20. Genetic Programming for Medicinal Plant Family Identification System

    Directory of Open Access Journals (Sweden)

    Indra Laksmana

    2014-11-01

    Full Text Available Information about medicinal plants that is available in text documents is generally quite easy to access, however, one needs some efforts to use it. This research was aimed at utilizing crucial information taken from a text document to identify the family of several species of medicinal plants using a heuristic approach, i.e. genetic programming. Each of the species has its unique features. The genetic program puts the characteristics or special features of each family into a tree form. There are a number of processes involved in the investigated method, i.e. data acquisition, booleanization, grouping of training and test data, evaluation, and analysis. The genetic program uses a training process to select the best individual, initializes a generate-rule process to create several individuals and then executes a fitness evaluation. The next procedure is a genetic operation process, which consists of tournament selection to choose the best individual based on a fitness value, the crossover operation and the mutation operation. These operations have the purpose of complementing the individual. The best individual acquired is the expected solution, which is a rule for classifying medicinal plants. This process produced three rules, one for each plant family, displaying a feature structure that distinguishes each of the families from each other. The genetic program then used these rules to identify the medicinal plants, achieving an average accuracy of 86.47%.

  1. Breeding technique of Anastrepha fraterculus (Wied.) for genetic studies

    International Nuclear Information System (INIS)

    Manso, F.

    1999-01-01

    Various samples of Anastrepha fraterculus from different areas in Argentina were obtained to develop artificial breeding in the laboratory. Based on a modification of Salles's method, an improved artificial rearing of the species was developed with satisfactory results for genetic analysis. The advances made will contribute towards the search for genetic mechanisms for control. (author)

  2. Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

    Directory of Open Access Journals (Sweden)

    Paul Jean Etienne Jeszensky

    2005-02-01

    Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

  3. Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

    Directory of Open Access Journals (Sweden)

    Mauro Castelli

    2015-01-01

    Full Text Available Energy consumption forecasting (ECF is an important policy issue in today’s economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

  4. Genetic programming applied to RFI mitigation in radio astronomy

    Science.gov (United States)

    Staats, K.

    2016-12-01

    Genetic Programming is a type of machine learning that employs a stochastic search of a solutions space, genetic operators, a fitness function, and multiple generations of evolved programs to resolve a user-defined task, such as the classification of data. At the time of this research, the application of machine learning to radio astronomy was relatively new, with a limited number of publications on the subject. Genetic Programming had never been applied, and as such, was a novel approach to this challenging arena. Foundational to this body of research, the application Karoo GP was developed in the programming language Python following the fundamentals of tree-based Genetic Programming described in "A Field Guide to Genetic Programming" by Poli, et al. Karoo GP was tasked with the classification of data points as signal or radio frequency interference (RFI) generated by instruments and machinery which makes challenging astronomers' ability to discern the desired targets. The training data was derived from the output of an observation run of the KAT-7 radio telescope array built by the South African Square Kilometre Array (SKA-SA). Karoo GP, kNN, and SVM were comparatively employed, the outcome of which provided noteworthy correlations between input parameters, the complexity of the evolved hypotheses, and performance of raw data versus engineered features. This dissertation includes description of novel approaches to GP, such as upper and lower limits to the size of syntax trees, an auto-scaling multiclass classifier, and a Numpy array element manager. In addition to the research conducted at the SKA-SA, it is described how Karoo GP was applied to fine-tuning parameters of a weather prediction model at the South African Astronomical Observatory (SAAO), to glitch classification at the Laser Interferometer Gravitational-wave Observatory (LIGO), and to astro-particle physics at The Ohio State University.

  5. Considering genetic characteristics in German Holstein breeding programs.

    Science.gov (United States)

    Segelke, D; Täubert, H; Reinhardt, F; Thaller, G

    2016-01-01

    Recently, several research groups have demonstrated that several haplotypes may cause embryonic loss in the homozygous state. Up to now, carriers of genetic disorders were often excluded from mating, resulting in a decrease of genetic gain and a reduced number of sires available for the breeding program. Ongoing research is very likely to identify additional genetic defects causing embryonic loss and calf mortality by genotyping a large proportion of the female cattle population and sequencing key ancestors. Hence, a clear demand is present to develop a method combining selection against recessive defects (e.g., Holstein haplotypes HH1-HH5) with selection for economically beneficial traits (e.g., polled) for mating decisions. Our proposed method is a genetic index that accounts for the allele frequencies in the population and the economic value of the genetic characteristic without excluding carriers from breeding schemes. Fertility phenotypes from routine genetic evaluations were used to determine the economic value per embryo lost. Previous research has shown that embryo loss caused by HH1 and HH2 occurs later than the loss for HH3, HH4, and HH5. Therefore, an economic value of € 97 was used against HH1 and HH2 and € 70 against HH3, HH4, and HH5. For polled, € 7 per polled calf was considered. Minor allele frequencies of the defects ranged between 0.8 and 3.3%. The polled allele has a frequency of 4.1% in the German Holstein population. A genomic breeding program was simulated to study the effect of changing the selection criteria from assortative mating based on breeding values to selecting the females using the genetic index. Selection for a genetic index on the female path is a useful method to control the allele frequencies by reducing undesirable alleles and simultaneously increasing economical beneficial characteristics maintaining most of the genetic gain in production and functional traits. Additionally, we applied the genetic index to real data and

  6. Mathematical programming models for solving in equal-sized facilities layout problems. A genetic search method

    International Nuclear Information System (INIS)

    Tavakkoli-Moghaddam, R.

    1999-01-01

    This paper present unequal-sized facilities layout solutions generated by a genetic search program. named Layout Design using a Genetic Algorithm) 9. The generalized quadratic assignment problem requiring pre-determined distance and material flow matrices as the input data and the continuous plane model employing a dynamic distance measure and a material flow matrix are discussed. Computational results on test problems are reported as compared with layout solutions generated by the branch - and bound algorithm a hybrid method merging simulated annealing and local search techniques, and an optimization process of an enveloped block

  7. Genetic algorithms - A new technique for solving the neutron spectrum unfolding problem

    International Nuclear Information System (INIS)

    Freeman, David W.; Edwards, D. Ray; Bolon, Albert E.

    1999-01-01

    A new technique utilizing genetic algorithms has been applied to the Bonner sphere neutron spectrum unfolding problem. Genetic algorithms are part of a relatively new field of 'evolutionary' solution techniques that mimic living systems with computer-simulated 'chromosome' solutions. Solutions mate and mutate to create better solutions. Several benchmark problems, considered representative of radiation protection environments, have been evaluated using the newly developed UMRGA code which implements the genetic algorithm unfolding technique. The results are compared with results from other well-established unfolding codes. The genetic algorithm technique works remarkably well and produces solutions with relatively high spectral qualities. UMRGA appears to be a superior technique in the absence of a priori data - it does not rely on 'lucky' guesses of input spectra. Calculated personnel doses associated with the unfolded spectra match benchmark values within a few percent

  8. Techniques for detecting genetically modified crops and products ...

    African Journals Online (AJOL)

    The cultivation of genetically modified crops is becoming increasingly important; more traits are emerging and more acres than ever before are being planted with GM varieties. The release of GM crops and products in the markets worldwide has increased the regulatory need to monitor and verify the presence and the ...

  9. Data verification and evaluation techniques for groundwater monitoring programs

    International Nuclear Information System (INIS)

    Mercier, T.M.; Turner, R.R.

    1990-12-01

    To ensure that data resulting from groundwater monitoring programs are of the quality required to fulfill program objectives, it is suggested that a program of data verification and evaluation be implemented. These procedures are meant to supplement and support the existing laboratory quality control/quality assurance programs by identifying aberrant data resulting from a variety of unforeseen circumstances: sampling problems, data transformations in the lab, data input at the lab, data transfer, end-user data input. Using common-sense principles, pattern recognition techniques, and hydrogeological principles, a computer program was written which scans the data for suspected abnormalities and produces a text file stating sample identifiers, the suspect data, and a statement of how the data has departed from the expected. The techniques described in this paper have been developed to support the Y-12 Plant Groundwater Protection Program Management Plan

  10. Tracking the Genetic Stability of a Honey Bee (Hymenoptera: Apidae) Breeding Program With Genetic Markers.

    Science.gov (United States)

    Bourgeois, Lelania; Beaman, Lorraine

    2017-08-01

    A genetic stock identification (GSI) assay was developed in 2008 to distinguish Russian honey bees from other honey bee stocks that are commercially produced in the United States. Probability of assignment (POA) values have been collected and maintained since the stock release in 2008 to the Russian Honey Bee Breeders Association. These data were used to assess stability of the breeding program and the diversity levels of the contemporary breeding stock through comparison of POA values and genetic diversity parameters from the initial release to current values. POA values fluctuated throughout 2010-2016, but have recovered to statistically similar levels in 2016 (POA(2010) = 0.82, POA(2016) = 0.74; P = 0.33). Genetic diversity parameters (i.e., allelic richness and gene diversity) in 2016 also remained at similar levels when compared to those in 2010. Estimates of genetic structure revealed stability (FST(2009/2016) = 0.0058) with a small increase in the estimate of the inbreeding coefficient (FIS(2010) = 0.078, FIS(2016) = 0.149). The relationship among breeding lines, based on genetic distance measurement, was similar in 2008 and 2016 populations, but with increased homogeneity among lines (i.e., decreased genetic distance). This was expected based on the closed breeding system used for Russian honey bees. The successful application of the GSI assay in a commercial breeding program demonstrates the utility and stability of such technology to contribute to and monitor the genetic integrity of a breeding stock of an insect species. Published by Oxford University Press on behalf of Entomological Society of America 2017. This work is written by US Government employees and is in the public domain in the US.

  11. Genetic variability of broodstocks of restocking programs in Brazil

    Directory of Open Access Journals (Sweden)

    Nelson Lopera-Barrero

    2015-09-01

    Full Text Available Objective. The aim of this study was evaluate the genetic diversity of the following broodstocks: piapara (Leporinus elongatus, dourado (Salminus brasiliensis, jundiá (Rhamdia quelen and cachara (Pseudoplatystoma fasciatum already useful for restocking programs in the Paranapanema, Iguaçu and Paraná Brazilian Rivers. Materials and methods. Samples from the caudal fin of 122 fish were analyzed. DNA was extracted by NaCl protocol. PCR products were separated by a horizontal agarose gel electrophoresis. The fragments were visualized by staining with ethidium bromide. Results. The amplification of 25 primers generated different fragments in studied species that allowed characterizing 440 fragments of 100-2900 bp. High percentage of polymorphic fragments (66.67 to 86.29, Shannon index (0.365 to 0.486 and genetic diversity of Nei (0.248 to 0.331 were detected. Conclusions. The level of genetic variability in the broodstocks was adequate for allowing their use in restocking programs in the studied Rivers. However, periodical monitoring studies of genetic variability in these stocks, the mating system, reproductive system and general management must be made to guarantee the preservation of wild populations.

  12. Efficient Feedforward Linearization Technique Using Genetic Algorithms for OFDM Systems

    Directory of Open Access Journals (Sweden)

    García Paloma

    2010-01-01

    Full Text Available Feedforward is a linearization method that simultaneously offers wide bandwidth and good intermodulation distortion suppression; so it is a good choice for Orthogonal Frequency Division Multiplexing (OFDM systems. Feedforward structure consists of two loops, being necessary an accurate adjustment between them along the time, and when temperature, environmental, or operating changes are produced. Amplitude and phase imbalances of the circuit elements in both loops produce mismatched effects that lead to degrade its performance. A method is proposed to compensate these mismatches, introducing two complex coefficients calculated by means of a genetic algorithm. A full study is carried out to choose the optimal parameters of the genetic algorithm applied to wideband systems based on OFDM technologies, which are very sensitive to nonlinear distortions. The method functionality has been verified by means of simulation.

  13. Molecular profiling techniques as tools to detect potential unintended effects in genetically engineered maize

    CSIR Research Space (South Africa)

    Barros, E

    2010-05-01

    Full Text Available Molecular Profiling Techniques as Tools to Detect Potential Unintended Effects in Genetically Engineered Maize Eugenia Barros Introduction In the early stages of production and commercialization of foods derived from genetically engineered (GE) plants... systems. In a recent paper published in Plant Biotechnology Journal,4 we compared two transgenic white maize lines with the non-transgenic counterpart to investigate two possible sources of variation: genetic engineering and environmental variation...

  14. Geometric Semantic Genetic Programming Algorithm and Slump Prediction

    OpenAIRE

    Xu, Juncai; Shen, Zhenzhong; Ren, Qingwen; Xie, Xin; Yang, Zhengyu

    2017-01-01

    Research on the performance of recycled concrete as building material in the current world is an important subject. Given the complex composition of recycled concrete, conventional methods for forecasting slump scarcely obtain satisfactory results. Based on theory of nonlinear prediction method, we propose a recycled concrete slump prediction model based on geometric semantic genetic programming (GSGP) and combined it with recycled concrete features. Tests show that the model can accurately p...

  15. Genetic diversity of tambaqui broodstocks in stock enhancement programs

    Directory of Open Access Journals (Sweden)

    Americo Moraes Neto

    2017-06-01

    Full Text Available Natural populations of tambaqui (Colossoma macropomum have significantly decreased in recent decades especially due to human extraction activities. So that the environmental impact may be reduced, the restocking of fish and increase in fish production are enhanced. Genetic evaluations using molecular markers are essential for this purpose. Current study evaluates the genetic variability of two tambaqui broodstocks used in restocking programs. Sixty-five samples (33 samples from broodstock A and 32 samples from broodstock B were collected. DNA was extracted from caudal fin samples, with the amplification of four microsatellite loci: Cm1A11 (EU685307 Cm1C8 (EU685308 Cm1F4 (EU685311 and Cm1H8 (EU685315. Fourteen alleles in the stock of broodstock A were produced, five alleles for Cm1A11 locus (230, 255, 260, 270 and 276 bp, three alleles Cm1C8 (239, 260, and 273 bp, two alleles Cm1F4 (211 and 245 bp, four alleles for Cm1H8 (275, 290, 320 and 331 bp and two unique alleles were found for Cm1A11 loci (alleles 270 and 276 bp and Cm1H8 (alleles 275 and 331 bp. In broodstock B, ten alleles were produced, the same alleles of the first stock except for alleles 270 and 276 bp in Cm1A11 locus and 275 and 331 bp in Cm1H8 locus. Broodstock A revealed low frequency alleles in Cm1A11 loci, Cm1C8, Cm1F4 and Cm1H8, whereas broodstock B had no locus with low allelic frequency. Loci Cm1A11, Cm1C8 and Cm1H8 exhibited significant deficit of heterozygotes in both broodstocks, revealing changes in Hardy-Weinberg equilibrium. Genetic diversity between stocks was 0.1120, whilst genetic similarity was 0.894, with FST rate = 0.05, and Nm = 3.93, indicating gene flow between the two broodstocks. Results show that broodstocks are genetically closely related, with no great genetic variability. Strategies such as a previous genetic analysis of breeding with its marking, use of a large Ne crossing between the most genetically divergent specimens, and the introduction of new

  16. Genetic Tools and Techniques for Recombinant Expression in Thermophilic Bacillaceae

    Directory of Open Access Journals (Sweden)

    Eivind B. Drejer

    2018-05-01

    Full Text Available Although Escherichia coli and Bacillus subtilis are the most prominent bacterial hosts for recombinant protein production by far, additional species are being explored as alternatives for production of difficult-to-express proteins. In particular, for thermostable proteins, there is a need for hosts able to properly synthesize, fold, and excrete these in high yields, and thermophilic Bacillaceae represent one potentially interesting group of microorganisms for such purposes. A number of thermophilic Bacillaceae including B. methanolicus, B. coagulans, B. smithii, B. licheniformis, Geobacillus thermoglucosidasius, G. kaustophilus, and G. stearothermophilus are investigated concerning physiology, genomics, genetic tools, and technologies, altogether paving the way for their utilization as hosts for recombinant production of thermostable and other difficult-to-express proteins. Moreover, recent successful deployments of CRISPR/Cas9 in several of these species have accelerated the progress in their metabolic engineering, which should increase their attractiveness for future industrial-scale production of proteins. This review describes the biology of thermophilic Bacillaceae and in particular focuses on genetic tools and methods enabling use of these organisms as hosts for recombinant protein production.

  17. Chapter VIII. Contributions of propagation techniques and genetic modification to breeding - genetic engineering for disease resistance

    Science.gov (United States)

    Genetic engineering offers an opportunity to develop flower bulb crops with resistance to fungal, viral, and bacterial pathogens. Several of the flower bulb crops, Lilium spp., Gladiolus, Zantedeschia, Muscari, Hyacinthus, Narcissus, Ornithogalum, Iris, and Alstroemeria, have been transformed with t...

  18. US Department of Energy transportation programs: computerized techniques

    International Nuclear Information System (INIS)

    Joy, D.S.; Johnson, P.E.; Fore, C.S.; Peterson, B.E.

    1984-01-01

    The US Department of Energy is currently sponsoring the development of four specialized computer-based transportation programs at Oak Ridge National Laboratory. The programs function as research tools that provide unique computerized techniques for planning the safe shipment of radioactive and hazardous materials. Major achievements include the development of interactive rail and highway routing models, an emergency response assistance program, a data base focusing on legislative requirements, and a resource file identifying key state and local contacts. A discussion of the programs and data bases is presented, and several examples reflecting each project's applications to the overall DOE transportation program are provided. The interface of these programs offers a dynamic resource of data for use during preshipment planning stages. 10 refs., 4 figs., 2 tabs

  19. Learning Programming Technique through Visual Programming Application as Learning Media with Fuzzy Rating

    Science.gov (United States)

    Buditjahjanto, I. G. P. Asto; Nurlaela, Luthfiyah; Ekohariadi; Riduwan, Mochamad

    2017-01-01

    Programming technique is one of the subjects at Vocational High School in Indonesia. This subject contains theory and application of programming utilizing Visual Programming. Students experience some difficulties to learn textual learning. Therefore, it is necessary to develop media as a tool to transfer learning materials. The objectives of this…

  20. Depauperate genetic variability detected in the American and European bison using genomic techniques

    DEFF Research Database (Denmark)

    Pertoldi, Cino; Tokarska, Magorzata; Wójcik, Jan M

    2009-01-01

    , likely reflecting drift overwhelming selection. We suggest that utilization of genome-wide screening technologies, followed by utilization of less expensive techniques (e.g. VeraCode and Fluidigm EP1), holds large potential for genetic monitoring of populations. Additionally, these techniques will allow...

  1. Stream Flow Prediction by Remote Sensing and Genetic Programming

    Science.gov (United States)

    Chang, Ni-Bin

    2009-01-01

    A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

  2. Genetic divergence of rubber tree estimated by multivariate techniques and microsatellite markers

    Directory of Open Access Journals (Sweden)

    Lígia Regina Lima Gouvêa

    2010-01-01

    Full Text Available Genetic diversity of 60 Hevea genotypes, consisting of Asiatic, Amazonian, African and IAC clones, and pertaining to the genetic breeding program of the Agronomic Institute (IAC, Brazil, was estimated. Analyses were based on phenotypic multivariate parameters and microsatellites. Five agronomic descriptors were employed in multivariate procedures, such as Standard Euclidian Distance, Tocher clustering and principal component analysis. Genetic variability among the genotypes was estimated with 68 selected polymorphic SSRs, by way of Modified Rogers Genetic Distance and UPGMA clustering. Structure software in a Bayesian approach was used in discriminating among groups. Genetic diversity was estimated through Nei's statistics. The genotypes were clustered into 12 groups according to the Tocher method, while the molecular analysis identified six groups. In the phenotypic and microsatellite analyses, the Amazonian and IAC genotypes were distributed in several groups, whereas the Asiatic were in only a few. Observed heterozygosity ranged from 0.05 to 0.96. Both high total diversity (H T' = 0.58 and high gene differentiation (Gst' = 0.61 were observed, and indicated high genetic variation among the 60 genotypes, which may be useful for breeding programs. The analyzed agronomic parameters and SSRs markers were effective in assessing genetic diversity among Hevea genotypes, besides proving to be useful for characterizing genetic variability.

  3. Molecular genetic techniques for gene manipulation in Candida albicans.

    Science.gov (United States)

    Xu, Qiu-Rong; Yan, Lan; Lv, Quan-Zhen; Zhou, Mi; Sui, Xue; Cao, Yong-Bing; Jiang, Yuan-Ying

    2014-05-15

    Candida albicans is one of the most common fungal pathogen in humans due to its high frequency as an opportunistic and pathogenic fungus causing superficial as well as invasive infections in immunocompromised patients. An understanding of gene function in C. albicans is necessary to study the molecular basis of its pathogenesis, virulence and drug resistance. Several manipulation techniques have been used for investigation of gene function in C. albicans, including gene disruption, controlled gene expression, protein tagging, gene reintegration, and overexpression. In this review, the main cassettes containing selectable markers used for gene manipulation in C. albicans are summarized; the advantages and limitations of these cassettes are discussed concerning the influences on the target gene expression and the virulence of the mutant strains.

  4. Metabolic Engineering: Techniques for analysis of targets for genetic manipulations

    DEFF Research Database (Denmark)

    Nielsen, Jens Bredal

    1998-01-01

    Metabolic engineering has been defined as the purposeful modification of intermediary metabolism using recombinant DNA techniques. With this definition metabolic engineering includes: (1) inserting new pathways in microorganisms with the aim of producing novel metabolites, e.g., production...... of polyketides by Streptomyces; (2) production of heterologous peptides, e.g., production of human insulin, erythropoitin, and tPA; and (3) improvement of both new and existing processes, e.g., production of antibiotics and industrial enzymes. Metabolic engineering is a multidisciplinary approach, which involves...... input from chemical engineers, molecular biologists, biochemists, physiologists, and analytical chemists. Obviously, molecular biology is central in the production of novel products, as well as in the improvement of existing processes. However, in the latter case, input from other disciplines is pivotal...

  5. Programming peptidomimetic syntheses by translating genetic codes designed de novo.

    Science.gov (United States)

    Forster, Anthony C; Tan, Zhongping; Nalam, Madhavi N L; Lin, Hening; Qu, Hui; Cornish, Virginia W; Blacklow, Stephen C

    2003-05-27

    Although the universal genetic code exhibits only minor variations in nature, Francis Crick proposed in 1955 that "the adaptor hypothesis allows one to construct, in theory, codes of bewildering variety." The existing code has been expanded to enable incorporation of a variety of unnatural amino acids at one or two nonadjacent sites within a protein by using nonsense or frameshift suppressor aminoacyl-tRNAs (aa-tRNAs) as adaptors. However, the suppressor strategy is inherently limited by compatibility with only a small subset of codons, by the ways such codons can be combined, and by variation in the efficiency of incorporation. Here, by preventing competing reactions with aa-tRNA synthetases, aa-tRNAs, and release factors during translation and by using nonsuppressor aa-tRNA substrates, we realize a potentially generalizable approach for template-encoded polymer synthesis that unmasks the substantially broader versatility of the core translation apparatus as a catalyst. We show that several adjacent, arbitrarily chosen sense codons can be completely reassigned to various unnatural amino acids according to de novo genetic codes by translating mRNAs into specific peptide analog polymers (peptidomimetics). Unnatural aa-tRNA substrates do not uniformly function as well as natural substrates, revealing important recognition elements for the translation apparatus. Genetic programming of peptidomimetic synthesis should facilitate mechanistic studies of translation and may ultimately enable the directed evolution of small molecules with desirable catalytic or pharmacological properties.

  6. Experimental control of a fluidic pinball using genetic programming

    Science.gov (United States)

    Raibaudo, Cedric; Zhong, Peng; Noack, Bernd R.; Martinuzzi, Robert J.

    2017-11-01

    The wake stabilization of a triangular cluster of three rotating cylinders was investigated in the present study. Experiments were performed at Reynolds number Re 6000, and compared with URANS-2D simulations at same flow conditions. 2D2C PIV measurements and constant temperature anemometry were used to characterize the flow without and with actuation. Open-loop actuation was first considered for the identification of particular control strategies. Machine learning control was also implemented for the experimental study. Linear genetic programming has been used for the optimization of open-loop parameters and closed-loop controllers. Considering a cost function J based on the fluctuations of the velocity measured by the hot-wire sensor, significant performances were achieved using the machine learning approach. The present work is supported by the senior author's (R. J. Martinuzzi) NSERC discovery Grant. C. Raibaudo acknowledges the financial support of the University of Calgary Eyes-High PDF program.

  7. Home visit program improves technique survival in peritoneal dialysis.

    Science.gov (United States)

    Martino, Francesca; Adıbelli, Z; Mason, G; Nayak, A; Ariyanon, W; Rettore, E; Crepaldi, Carlo; Rodighiero, Mariapia; Ronco, Claudio

    2014-01-01

    Peritoneal dialysis (PD) is a home therapy, and technique survival is related to the adherence to PD prescription at home. The presence of a home visit program could improve PD outcomes. We evaluated its effects on clinical outcome during 1 year of follow-up. This was a case-control study. The case group included all 96 patients who performed PD in our center on January 1, 2013, and who attended a home visit program; the control group included all 92 patients who performed PD on January 1, 2008. The home visit program consisted of several additional visits to reinforce patients' confidence in PD management in their own environment. Outcomes were defined as technique failure, peritonitis episode, and hospitalization. Clinical and dialysis features were evaluated for each patient. The case group was significantly older (p = 0.048), with a lower grade of autonomy (p = 0.033), but a better hemoglobin level (p = 0.02) than the control group. During the observational period, we had 11 episodes of technique failure. We found a significant reduction in the rate of technique failure in the case group (p = 0.004). Furthermore, survival analysis showed a significant extension of PD treatment in the patients supported by the home visit program (52 vs. 48.8 weeks, p = 0.018). We did not find any difference between the two groups in terms of peritonitis and hospitalization rate; however, trends toward a reduction of Gram-positive peritonitis rates as well as prevalence and duration of hospitalization related to PD problems were identified in the case group. The retrospective nature of the analysis was a limitation of this study. The home visit program improves the survival of PD patients and could reduce the rate of Gram-positive peritonitis and hospitalization. Video Journal Club "Cappuccino with Claudio Ronco" at http://www.karger.com/?doi=365168.

  8. Object oriented programming techniques applied to device access and control

    International Nuclear Information System (INIS)

    Goetz, A.; Klotz, W.D.; Meyer, J.

    1992-01-01

    In this paper a model, called the device server model, has been presented for solving the problem of device access and control faced by all control systems. Object Oriented Programming techniques were used to achieve a powerful yet flexible solution. The model provides a solution to the problem which hides device dependancies. It defines a software framework which has to be respected by implementors of device classes - this is very useful for developing groupware. The decision to implement remote access in the root class means that device servers can be easily integrated in a distributed control system. A lot of the advantages and features of the device server model are due to the adoption of OOP techniques. The main conclusion that can be drawn from this paper is that 1. the device access and control problem is adapted to being solved with OOP techniques, 2. OOP techniques offer a distinct advantage over traditional programming techniques for solving the device access problem. (J.P.N.)

  9. When Darwin meets Lorenz: Evolving new chaotic attractors through genetic programming

    International Nuclear Information System (INIS)

    Pan, Indranil; Das, Saptarshi

    2015-01-01

    Highlights: •New 3D continuous time chaotic systems with analytical expressions are obtained. •The multi-gene genetic programming (MGGP) paradigm is employed to achieve this. •Extends earlier works for evolving generalised family of Lorenz attractors. •Over one hundred of new chaotic attractors along with their parameters are reported. •The MGGP method have the potential for finding other similar chaotic attractors. -- Abstract: In this paper, we propose a novel methodology for automatically finding new chaotic attractors through a computational intelligence technique known as multi-gene genetic programming (MGGP). We apply this technique to the case of the Lorenz attractor and evolve several new chaotic attractors based on the basic Lorenz template. The MGGP algorithm automatically finds new nonlinear expressions for the different state variables starting from the original Lorenz system. The Lyapunov exponents of each of the attractors are calculated numerically based on the time series of the state variables using time delay embedding techniques. The MGGP algorithm tries to search the functional space of the attractors by aiming to maximise the largest Lyapunov exponent (LLE) of the evolved attractors. To demonstrate the potential of the proposed methodology, we report over one hundred new chaotic attractor structures along with their parameters, which are evolved from just the Lorenz system alone

  10. [Training program design of acupuncture and moxibustion manipulation techniques].

    Science.gov (United States)

    Dong, Qin

    2009-12-01

    As an important component of acupuncture-moxibustion science, needling and moxibustion is one methodology and technology and its technical characteristics determine its special status and role in training programs. It is closely ralated to meridians-collaterals-acupoints and acupuncture treatment. Therefore, it demands an overall planning for acupuncture professional skills that consists of meridians-collaterals-acupoints knowledge and acupuncture treatment techniques. The practical training courses are the step by step progress involving repeated practices.

  11. ActionScript 30 Design Patterns Object Oriented Programming Techniques

    CERN Document Server

    Sanders, William

    2008-01-01

    If you're an experienced Flash or Flex developer ready to tackle sophisticated programming techniques with ActionScript 3.0, this hands-on introduction to design patterns takes you step by step through the process. You learn about various types of design patterns and construct small abstract examples before trying your hand at building full-fledged working applications outlined in the book.

  12. Comprehensive bidding strategies with genetic programming/finite state automata

    International Nuclear Information System (INIS)

    Richter, C.W. Jr.; Sheble, G.B.; Ashlock, D.

    1999-01-01

    This research is an extension of the authors' previous work in double auctions aimed at developing bidding strategies for electric utilities which trade electricity competitively. The improvements detailed in this paper come from using data structures which combine genetic programming and finite state automata termed GP-Automata. The strategies developed by the method described here are adaptive--reacting to inputs--whereas the previously developed strategies were only suitable in the particular scenario for which they had been designed. The strategies encoded in the GP-Automata are tested in an auction simulator. The simulator pits them against other distribution companies (distcos) and generation companies (gencos), buying and selling power via double auctions implemented in regional commodity exchanges. The GP-Automata are evolved with a genetic algorithm so that they possess certain characteristics. In addition to designing successful bidding strategies (whose usage would result in higher profits) the resulting strategies can also be designed to imitate certain types of trading behaviors. The resulting strategies can be implemented directly in on-line trading, or can be used as realistic competitors in an off-line trading simulator

  13. A Comparison of Genetic Programming Variants for Hyper-Heuristics

    Energy Technology Data Exchange (ETDEWEB)

    Harris, Sean [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved, such as routing vehicles over highways with constantly changing traffic flows, because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. Hyper-heuristics typically employ Genetic Programming (GP) and this project has investigated the relationship between the choice of GP and performance in Hyper-heuristics. Results are presented demonstrating the existence of problems for which there is a statistically significant performance differential between the use of different types of GP.

  14. Genetic Programming and Standardization in Water Temperature Modelling

    Directory of Open Access Journals (Sweden)

    Maritza Arganis

    2009-01-01

    Full Text Available An application of Genetic Programming (an evolutionary computational tool without and with standardization data is presented with the aim of modeling the behavior of the water temperature in a river in terms of meteorological variables that are easily measured, to explore their explanatory power and to emphasize the utility of the standardization of variables in order to reduce the effect of those with large variance. Recorded data corresponding to the water temperature behavior at the Ebro River, Spain, are used as analysis case, showing a performance improvement on the developed model when data are standardized. This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes.

  15. Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

    International Nuclear Information System (INIS)

    Ortiz R, J. M.; Martinez B, M. R.; Vega C, H. R.; Gallego D, E.; Lorente F, A.; Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E.

    2011-01-01

    With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

  16. A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

    Science.gov (United States)

    Kobayashi, Takahisa; Simon, Donald L.

    2001-01-01

    In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

  17. Comparative Analysis of Rank Aggregation Techniques for Metasearch Using Genetic Algorithm

    Science.gov (United States)

    Kaur, Parneet; Singh, Manpreet; Singh Josan, Gurpreet

    2017-01-01

    Rank Aggregation techniques have found wide applications for metasearch along with other streams such as Sports, Voting System, Stock Markets, and Reduction in Spam. This paper presents the optimization of rank lists for web queries put by the user on different MetaSearch engines. A metaheuristic approach such as Genetic algorithm based rank…

  18. Comparison of collinearity mitigation techniques used in predicting BLUP breeding values and genetic gains over generations

    CSIR Research Space (South Africa)

    Eatwell, KA

    2011-01-01

    Full Text Available techniques and of two computational numerical precisions on the genetic gains in breeding populations. Multiple-trait, multiple-trial BLUP selection scenarios were run on Eucalyptus grandis (F1, F2 and F3) and Pinus patula (F1 and F2) data, comparing...

  19. The Mouse House: A brief history of the ORNL mouse-genetics program, 1947–2009

    Energy Technology Data Exchange (ETDEWEB)

    Russell, Liane B.

    2013-10-01

    The large mouse genetics program at the Oak Ridge National Lab is often re-membered chiefly for the germ-cell mutation-rate data it generated and their uses in estimating the risk of heritable radiation damage. In fact, it soon became a multi-faceted research effort that, over a period of almost 60 years, generated a wealth of information in the areas of mammalian mutagenesis, basic genetics (later enriched by molecular techniques), cytogenetics, reproductive biology, biochemistry of germ cells, and teratology. Research in the area of germ-cell mutagenesis explored the important physical and biological factors that affect the frequency and nature of induced mutations and made several unexpected discoveries, such as the major importance of the perigametic interval (the zygote stage) for the origin of spontaneous mutations and for the sensitivity to induced genetic change. Of practical value was the discovery that ethylnitrosourea was a supermutagen for point mutations, making high-efficiency mutagenesis in the mouse feasible worldwide. Teratogenesis findings resulted in recommendations still generally accepted in radiological practice. Studies supporting the mutagenesis research added whole bodies of information about mammalian germ-cell development and about molecular targets in germ cells. The early decision to not merely count but propagate genetic variants of all sorts made possible further discoveries, such as the Y-Chromosome s importance in mammalian sex determination and the identification of rare X-autosome translocations, which, in turn, led to the formulation of the single-active-X hypothesis and provided tools for studies of functional mosaicism for autosomal genes, male sterility, and chromosome-pairing mechanism. Extensive genetic and then molecular analyses of large numbers of induced specific-locus mutants resulted in fine-structure physical and correlated functional mapping of significant portions of the mouse genome and constituted a valuable

  20. The Mouse House: a brief history of the ORNL mouse-genetics program, 1947-2009.

    Science.gov (United States)

    Russell, Liane B

    2013-01-01

    The large mouse genetics program at the Oak Ridge National Laboratory (ORNL) is often remembered chiefly for the germ-cell mutation-rate data it generated and their uses in estimating the risk of heritable radiation damage. In fact, it soon became a multi-faceted research effort that, over a period of almost 60 years, generated a wealth of information in the areas of mammalian mutagenesis, basic genetics (later enriched by molecular techniques), cytogenetics, reproductive biology, biochemistry of germ cells, and teratology. Research in the area of germ-cell mutagenesis explored the important physical and biological factors that affect the frequency and nature of induced mutations and made several unexpected discoveries, such as the major importance of the perigametic interval (the zygote stage) for the origin of spontaneous mutations and for the sensitivity to induced genetic change. Of practical value was the discovery that ethylnitrosourea was a supermutagen for point mutations, making high-efficiency mutagenesis in the mouse feasible worldwide. Teratogenesis findings resulted in recommendations still generally accepted in radiological practice. Studies supporting the mutagenesis research added whole bodies of information about mammalian germ-cell development and about molecular targets in germ cells. The early decision to not merely count but propagate genetic variants of all sorts made possible further discoveries, such as the Y-chromosome's importance in mammalian sex determination and the identification of rare X-autosome translocations, which, in turn, led to the formulation of the single-active-X hypothesis and provided tools for studies of functional mosaicism for autosomal genes, male sterility, and chromosome-pairing mechanism. Extensive genetic and then molecular analyses of large numbers of induced specific-locus mutants resulted in fine-structure physical and correlated functional mapping of significant portions of the mouse genome and constituted a

  1. Analysis of Program Obfuscation Schemes with Variable Encoding Technique

    Science.gov (United States)

    Fukushima, Kazuhide; Kiyomoto, Shinsaku; Tanaka, Toshiaki; Sakurai, Kouichi

    Program analysis techniques have improved steadily over the past several decades, and software obfuscation schemes have come to be used in many commercial programs. A software obfuscation scheme transforms an original program or a binary file into an obfuscated program that is more complicated and difficult to analyze, while preserving its functionality. However, the security of obfuscation schemes has not been properly evaluated. In this paper, we analyze obfuscation schemes in order to clarify the advantages of our scheme, the XOR-encoding scheme. First, we more clearly define five types of attack models that we defined previously, and define quantitative resistance to these attacks. Then, we compare the security, functionality and efficiency of three obfuscation schemes with encoding variables: (1) Sato et al.'s scheme with linear transformation, (2) our previous scheme with affine transformation, and (3) the XOR-encoding scheme. We show that the XOR-encoding scheme is superior with regard to the following two points: (1) the XOR-encoding scheme is more secure against a data-dependency attack and a brute force attack than our previous scheme, and is as secure against an information-collecting attack and an inverse transformation attack as our previous scheme, (2) the XOR-encoding scheme does not restrict the calculable ranges of programs and the loss of efficiency is less than in our previous scheme.

  2. Traditional genetic improvement and use of biotechnological techniques in searching of resistance to main fungi pathogens of Musa spp.

    Directory of Open Access Journals (Sweden)

    Michel Leiva-Mora

    2006-07-01

    Full Text Available Bananas and plantain are important food staple in human diet, even cooked or consumed fresh. Fungal diseases caused by Fusarium oxysporum f. sp. cubense (Foc and Mycosphaerella fijiensis have threated to distroy Musa spp. Those crops are difficult to breed genetically because they are steriles, do not produce fertil seeds and they are partenocarpic. Genetic crossing by hibridization have been used successfully in FHIA and IITA Musa breeding programs, they have released numerous improved hybrids to those diseases. Plant Biotechnology has developed a set of techniques for Musa micropropagation to increase multiplication rates, healthy and safety plant material for plantation. Mutagenic techniques, somaclonal variation, somatic embryogenesis and more recient genetic transformation have enabled advances and complementation with clasical Musa breeding for searching resistance to principal fungal pathogen of Musa spp. Field evaluation systems to find Musa resistant genotypes to Foc and M. fijiensis have demostrated to be usefull but laborious. Nevertheless to enhance eficacy in selection of promissory genotypes the development of reproducible early evaluation methodologies by using fungal pathogens or their derivates is needed. Key words: evaluation and selection, Fusarium oxysporum, improvement

  3. Structural health monitoring feature design by genetic programming

    International Nuclear Information System (INIS)

    Harvey, Dustin Y; Todd, Michael D

    2014-01-01

    Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems. (paper)

  4. Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

    Science.gov (United States)

    Bellucci, Michael A; Coker, David F

    2011-07-28

    We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

  5. Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

    International Nuclear Information System (INIS)

    Chung, K K; Do, D Q

    2010-01-01

    In order to model relationships between chemical structures and biological effects in quantitative structure–activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data

  6. System safety and reliability using object-oriented programming techniques

    International Nuclear Information System (INIS)

    Patterson-Hine, F.A.; Koen, B.V.

    1987-01-01

    Direct evaluation fault tree codes have been written in recursive, list-processing computer languages such as PL/1 (PATREC-I) and LISP (PATREC-L). The pattern-matching strategy implemented in these codes has been used extensively in France to evaluate system reliability. Recent reviews of the risk management process suggest that a data base containing plant-specific information be integrated with a package of codes used for probabilistic risk assessment (PRA) to alleviate some of the difficulties that make a PRA so costly and time-intensive. A new programming paradigm, object-oriented programming, is uniquely suited for the development of such a software system. A knowledge base and fault tree evaluation algorithm, based on previous experience with PATREC-L, have been implemented using object-oriented techniques, resulting in a reliability assessment environment that is easy to develop, modify, and extend

  7. APPLICATION OF OBJECT ORIENTED PROGRAMMING TECHNIQUES IN FRONT END COMPUTERS

    International Nuclear Information System (INIS)

    SKELLY, J.F.

    1997-01-01

    The Front End Computer (FEC) environment imposes special demands on software, beyond real time performance and robustness. FEC software must manage a diverse inventory of devices with individualistic timing requirements and hardware interfaces. It must implement network services which export device access to the control system at large, interpreting a uniform network communications protocol into the specific control requirements of the individual devices. Object oriented languages provide programming techniques which neatly address these challenges, and also offer benefits in terms of maintainability and flexibility. Applications are discussed which exhibit the use of inheritance, multiple inheritance and inheritance trees, and polymorphism to address the needs of FEC software

  8. 76 FR 72424 - Submission for OMB Review; Comment Request Information Program on the Genetic Testing Registry

    Science.gov (United States)

    2011-11-23

    ... particular tests; and (3) facilitating genetic and genomic data-sharing for research and new scientific...; Comment Request Information Program on the Genetic Testing Registry AGENCY: National Institutes of Health... currently valid OMB control number. Proposed Collection: Title: The Genetic Testing Registry; Type of...

  9. Moving Speciation Genetics Forward: Modern Techniques Build on Foundational Studies in Drosophila.

    Science.gov (United States)

    Castillo, Dean M; Barbash, Daniel A

    2017-11-01

    The question of how new species evolve has been examined at every level, from macroevolutionary patterns of diversification to molecular population genetic analyses of specific genomic regions between species pairs. Drosophila has been at the center of many of these research efforts. Though our understanding of the speciation process has grown considerably over the past few decades, very few genes have been identified that contribute to barriers to reproduction. The development of advanced molecular genetic and genomic methods provides promising avenues for the rapid discovery of more genes that contribute to speciation, particularly those involving prezygotic isolation. The continued expansion of tools and resources, especially for species other than Drosophila melanogaster , will be most effective when coupled with comparative approaches that reveal the genetic basis of reproductive isolation across a range of divergence times. Future research programs in Drosophila have high potential to answer long-standing questions in speciation. These include identifying the selective forces that contribute to divergence between populations and the genetic basis of traits that cause reproductive isolation. The latter can be expanded upon to understand how the genetic basis of reproductive isolation changes over time and whether certain pathways and genes are more commonly involved. Copyright © 2017 by the Genetics Society of America.

  10. Genetic programming over context-free languages with linear constraints for the knapsack problem: first results.

    Science.gov (United States)

    Bruhn, Peter; Geyer-Schulz, Andreas

    2002-01-01

    In this paper, we introduce genetic programming over context-free languages with linear constraints for combinatorial optimization, apply this method to several variants of the multidimensional knapsack problem, and discuss its performance relative to Michalewicz's genetic algorithm with penalty functions. With respect to Michalewicz's approach, we demonstrate that genetic programming over context-free languages with linear constraints improves convergence. A final result is that genetic programming over context-free languages with linear constraints is ideally suited to modeling complementarities between items in a knapsack problem: The more complementarities in the problem, the stronger the performance in comparison to its competitors.

  11. Flow discharge prediction in compound channels using linear genetic programming

    Science.gov (United States)

    Azamathulla, H. Md.; Zahiri, A.

    2012-08-01

    SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

  12. Future strategy and puzzles of heavy ion beam mediated technique in genetic improvement of biological bodies

    International Nuclear Information System (INIS)

    Huang Qunce

    2007-01-01

    The 7 research puzzles in the genetic improvement of biological bodies made by ion beam mediated technique, are worth noticed. The technical ideas, including one mediated technique in physics, 2 significant subjects, 3 effective changes, the mediated evidences of 4 aspects and 5 biological characteristics, were particularly put forward according to the existing states in the field. The 2 significant subjects consist of the mechanics of the allogenetic materials entering into the acceptor and they being to be recombined. The 3 effective changes include from studying morphology to genetic laws, from researching M1 generation to the next generations, from determining the single character to the synthetic traits. The mediated evidences of 4 aspects come from morphology, physiology and biochemistry, molecule biology. The 5 biological characteristics are mainly reproduction, development, photosynthesis, bad condition-resistant and quality. (authors)

  13. A Novel Technique for Steganography Method Based on Improved Genetic Algorithm Optimization in Spatial Domain

    Directory of Open Access Journals (Sweden)

    M. Soleimanpour-moghadam

    2013-06-01

    Full Text Available This paper devotes itself to the study of secret message delivery using cover image and introduces a novel steganographic technique based on genetic algorithm to find a near-optimum structure for the pair-wise least-significant-bit (LSB matching scheme. A survey of the related literatures shows that the LSB matching method developed by Mielikainen, employs a binary function to reduce the number of changes of LSB values. This method verifiably reduces the probability of detection and also improves the visual quality of stego images. So, our proposal draws on the Mielikainen's technique to present an enhanced dual-state scoring model, structured upon genetic algorithm which assesses the performance of different orders for LSB matching and searches for a near-optimum solution among all the permutation orders. Experimental results confirm superiority of the new approach compared to the Mielikainen’s pair-wise LSB matching scheme.

  14. Population genetics analysis using R and the Geneland program

    DEFF Research Database (Denmark)

    Guillot, Gilles; Santos, Filipe; Estoup, Arnaud

    2011-01-01

    Geneland program documentation 2011 Program distributed under GNU license as an R package on the Comprehensive R Archive Network.......Geneland program documentation 2011 Program distributed under GNU license as an R package on the Comprehensive R Archive Network....

  15. Lesbian motherhood and mitochondrial replacement techniques: reproductive freedom and genetic kinship.

    Science.gov (United States)

    Cavaliere, Giulia; Palacios-González, César

    2018-02-28

    In this paper, we argue that lesbian couples who wish to have children who are genetically related to both of them should be allowed access to mitochondrial replacement techniques (MRTs). First, we provide a brief explanation of mitochondrial diseases and MRTs. We then present the reasons why MRTs are not, by nature, therapeutic. The upshot of the view that MRTs are non-therapeutic techniques is that their therapeutic potential cannot be invoked for restricting their use only to those cases where a mitochondrial DNA disease could be 'cured'. We then argue that a positive case for MRTs is justified by an appeal to reproductive freedom, and that the criteria to access these techniques should hence be extended to include lesbian couples who wish to share genetic parenthood. Finally, we consider a potential objection to our argument: that the desire to have genetically related kin is not a morally sufficient reason to allow lesbian couples to access MRTs. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  16. Control of Angra 1' PZR by a fuzzy rule base build through genetic programming

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2002-01-01

    There is an optimum pressure for the normal operation of nuclear power plant reactors and thresholds that must be respected during transients, what make the pressurizer an important control mechanism. Inside a pressurizer there are heaters and a shower. From their actuation levels, they control the vapor pressure inside the pressurizer and, consequently, inside the primary circuit. Therefore, the control of the pressurizer consists in controlling the actuation levels of the heaters and of the shower. In the present work this function is implemented through a fuzzy controller. Besides the efficient way of exerting control, this approach presents the possibility of extracting knowledge of how this control is been made. A fuzzy controller consists basically in an inference machine and a rule base, the later been constructed with specialized knowledge. In some circumstances, however, this knowledge is not accurate, and may lead to non-efficient results. With the development of artificial intelligence techniques, there wore found methods to substitute specialists, simulating its knowledge. Genetic programming is an evolutionary algorithm particularly efficient in manipulating rule base structures. In this work genetic programming was used as a substitute for the specialist. The goal is to test if an irrational object, a computer, is capable, by it self, to find out a rule base reproducing a pre-established actuation levels profile. The result is positive, with the discovery of a fuzzy rule base presenting an insignificant error. A remarkable result that proves the efficiency of the approach. (author)

  17. Drag reduction of a car model by linear genetic programming control

    Science.gov (United States)

    Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

    2017-08-01

    We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.

  18. Screening Out Controversy: Human Genetics, Emerging Techniques of Diagnosis, and the Origins of the Social Issues Committee of the American Society of Human Genetics, 1964-1973.

    Science.gov (United States)

    Mitchell, M X

    2017-05-01

    In the years following World War II, and increasingly during the 1960s and 1970s, professional scientific societies developed internal sub-committees to address the social implications of their scientific expertise (Moore, Disrupting Science: Social Movements, American Scientists, and the Politics of the Military, 1945-1975. Princeton: Princeton University Press, 2008). This article explores the early years of one such committee, the American Society of Human Genetics' "Social Issues Committee," founded in 1967. Although the committee's name might suggest it was founded to increase the ASHG's public and policy engagement, exploration of the committee's early years reveals a more complicated reality. Affronted by legislators' recent unwillingness to seek the expert advice of human geneticists before adopting widespread neonatal screening programs for phenylketonuria (PKU), and feeling pressed to establish their relevance in an increasingly resource-scarce funding environment, committee members sought to increase the discipline's expert authority. Painfully aware of controversy over abortion rights and haunted by the taint of the discipline's eugenic past, however, the committee proceeded with great caution. Seeking to harness interest in and assert professional control over emerging techniques of genetic diagnosis, the committee strove to protect the society's image by relegating ethical and policy questions about their use to the individual consciences of member scientists. It was not until 1973, after the committee's modest success in organizing support for a retrospective public health study of PKU screening and following the legalization of abortion on demand, that the committee decided to take a more publicly engaged stance.

  19. Linear genetic programming application for successive-station monthly streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

    2014-09-01

    In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

  20. Stigmatization of carrier status: social implications of heterozygote genetic screening programs.

    Science.gov (United States)

    Kenen, R H; Schmidt, R M

    1978-01-01

    Possible latent psychological and social consequences ensuing from genetic screening programs need to be investigated during the planning phase of national genetic screening programs. The relatively few studies which have been performed to determine psychological, social, and economic consequences resulting from a genetic screening program are reviewed. Stigmatization of carrier-status, having major psychosocial implications in heterozygote genetic screening programs, is discussed and related to Erving Goffman's work in the area of stigmatization. Questions are raised regarding the relationship between such variables as religiosity and sex of the individual and acceptance of the status of newly identified carrier of a mutant gene. Severity of the deleterious gene and visibility of the carrier status are two important factors to consider in an estimation of potential stigma. Specific implications are discussed for four genetic diseases: Tay-Sachs, Sickle-Cell Anemia, Huntington's disease and Hemophilia. PMID:152585

  1. Genetic analysis of seasonal runoff based on automatic techniques of hydrometeorological data processing

    Science.gov (United States)

    Kireeva, Maria; Sazonov, Alexey; Rets, Ekaterina; Ezerova, Natalia; Frolova, Natalia; Samsonov, Timofey

    2017-04-01

    Detection of the rivers' feeding type is a complex and multifactor task. Such partitioning should be based, on the one hand, on the genesis of the feeding water, on the other hand, on its physical path. At the same time it should consider relationship of the feeding type with corresponding phase of the water regime. Due to the above difficulties and complexity of the approach, there are many different variants of separation of flow hydrograph for feeding types. The most common method is extraction of so called basic component which in one way or another reflects groundwater feeding of the river. In this case, the selection most often is based on the principle of local minima or graphic separation of this component. However, in this case neither origin of the water nor corresponding phase of water regime is considered. In this paper, the authors offer a method of complex automated analysis of genetic components of the river's feeding together with the separation of specific phases of the water regime. The objects of the study are medium and large rivers of European Russia having a pronounced spring flood, formed due to melt water, and summer-autumn and winter low water which is periodically interrupted by rain or thaw flooding. The method is based on genetic separation of hydrograph proposed in 1960s years by B. I. Kudelin. This technique is considered for large rivers having hydraulic connection with groundwater horizons during flood. For better detection of floods genesis the analysis involves reanalysis data on temperature and precipitation. Separation is based on the following fundamental graphic-analytical principles: • Ground feeding during the passage of flood peak tends to zero • Beginning of the flood is determined as the exceeding of critical value of low water discharge • Flood periods are determined on the basis of exceeding the critical low-water discharge; they relate to thaw in case of above-zero temperatures • During thaw and rain floods

  2. A genetic programming approach to oral cancer prognosis

    Directory of Open Access Journals (Sweden)

    Mei Sze Tan

    2016-09-01

    Full Text Available Background The potential of genetic programming (GP on various fields has been attained in recent years. In bio-medical field, many researches in GP are focused on the recognition of cancerous cells and also on gene expression profiling data. In this research, the aim is to study the performance of GP on the survival prediction of a small sample size of oral cancer prognosis dataset, which is the first study in the field of oral cancer prognosis. Method GP is applied on an oral cancer dataset that contains 31 cases collected from the Malaysia Oral Cancer Database and Tissue Bank System (MOCDTBS. The feature subsets that is automatically selected through GP were noted and the influences of this subset on the results of GP were recorded. In addition, a comparison between the GP performance and that of the Support Vector Machine (SVM and logistic regression (LR are also done in order to verify the predictive capabilities of the GP. Result The result shows that GP performed the best (average accuracy of 83.87% and average AUROC of 0.8341 when the features selected are smoking, drinking, chewing, histological differentiation of SCC, and oncogene p63. In addition, based on the comparison results, we found that the GP outperformed the SVM and LR in oral cancer prognosis. Discussion Some of the features in the dataset are found to be statistically co-related. This is because the accuracy of the GP prediction drops when one of the feature in the best feature subset is excluded. Thus, GP provides an automatic feature selection function, which chooses features that are highly correlated to the prognosis of oral cancer. This makes GP an ideal prediction model for cancer clinical and genomic data that can be used to aid physicians in their decision making stage of diagnosis or prognosis.

  3. A genetic programming approach to oral cancer prognosis.

    Science.gov (United States)

    Tan, Mei Sze; Tan, Jing Wei; Chang, Siow-Wee; Yap, Hwa Jen; Abdul Kareem, Sameem; Zain, Rosnah Binti

    2016-01-01

    The potential of genetic programming (GP) on various fields has been attained in recent years. In bio-medical field, many researches in GP are focused on the recognition of cancerous cells and also on gene expression profiling data. In this research, the aim is to study the performance of GP on the survival prediction of a small sample size of oral cancer prognosis dataset, which is the first study in the field of oral cancer prognosis. GP is applied on an oral cancer dataset that contains 31 cases collected from the Malaysia Oral Cancer Database and Tissue Bank System (MOCDTBS). The feature subsets that is automatically selected through GP were noted and the influences of this subset on the results of GP were recorded. In addition, a comparison between the GP performance and that of the Support Vector Machine (SVM) and logistic regression (LR) are also done in order to verify the predictive capabilities of the GP. The result shows that GP performed the best (average accuracy of 83.87% and average AUROC of 0.8341) when the features selected are smoking, drinking, chewing, histological differentiation of SCC, and oncogene p63. In addition, based on the comparison results, we found that the GP outperformed the SVM and LR in oral cancer prognosis. Some of the features in the dataset are found to be statistically co-related. This is because the accuracy of the GP prediction drops when one of the feature in the best feature subset is excluded. Thus, GP provides an automatic feature selection function, which chooses features that are highly correlated to the prognosis of oral cancer. This makes GP an ideal prediction model for cancer clinical and genomic data that can be used to aid physicians in their decision making stage of diagnosis or prognosis.

  4. A genetic programming approach for Burkholderia Pseudomallei diagnostic pattern discovery

    Science.gov (United States)

    Yang, Zheng Rong; Lertmemongkolchai, Ganjana; Tan, Gladys; Felgner, Philip L.; Titball, Richard

    2009-01-01

    Motivation: Finding diagnostic patterns for fighting diseases like Burkholderia pseudomallei using biomarkers involves two key issues. First, exhausting all subsets of testable biomarkers (antigens in this context) to find a best one is computationally infeasible. Therefore, a proper optimization approach like evolutionary computation should be investigated. Second, a properly selected function of the antigens as the diagnostic pattern which is commonly unknown is a key to the diagnostic accuracy and the diagnostic effectiveness in clinical use. Results: A conversion function is proposed to convert serum tests of antigens on patients to binary values based on which Boolean functions as the diagnostic patterns are developed. A genetic programming approach is designed for optimizing the diagnostic patterns in terms of their accuracy and effectiveness. During optimization, it is aimed to maximize the coverage (the rate of positive response to antigens) in the infected patients and minimize the coverage in the non-infected patients while maintaining the fewest number of testable antigens used in the Boolean functions as possible. The final coverage in the infected patients is 96.55% using 17 of 215 (7.4%) antigens with zero coverage in the non-infected patients. Among these 17 antigens, BPSL2697 is the most frequently selected one for the diagnosis of Burkholderia Pseudomallei. The approach has been evaluated using both the cross-validation and the Jack–knife simulation methods with the prediction accuracy as 93% and 92%, respectively. A novel approach is also proposed in this study to evaluate a model with binary data using ROC analysis. Contact: z.r.yang@ex.ac.uk PMID:19561021

  5. CDPOP: A spatially explicit cost distance population genetics program

    Science.gov (United States)

    Erin L. Landguth; S. A. Cushman

    2010-01-01

    Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

  6. Advanced network programming principles and techniques : network application programming with Java

    CERN Document Server

    Ciubotaru, Bogdan

    2013-01-01

    Answering the need for an accessible overview of the field, this text/reference presents a manageable introduction to both the theoretical and practical aspects of computer networks and network programming. Clearly structured and easy to follow, the book describes cutting-edge developments in network architectures, communication protocols, and programming techniques and models, supported by code examples for hands-on practice with creating network-based applications. Features: presents detailed coverage of network architectures; gently introduces the reader to the basic ideas underpinning comp

  7. The use of genetic programming to develop a predictor of swash excursion on sandy beaches

    Directory of Open Access Journals (Sweden)

    M. Passarella

    2018-02-01

    Full Text Available We use genetic programming (GP, a type of machine learning (ML approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation. Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches and providing physical insight into coastal processes.

  8. The use of genetic programming to develop a predictor of swash excursion on sandy beaches

    Science.gov (United States)

    Passarella, Marinella; Goldstein, Evan B.; De Muro, Sandro; Coco, Giovanni

    2018-02-01

    We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation). Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches) and providing physical insight into coastal processes.

  9. Improved Genetic and Simulating Annealing Algorithms to Solve the Traveling Salesman Problem Using Constraint Programming

    Directory of Open Access Journals (Sweden)

    M. Abdul-Niby

    2016-04-01

    Full Text Available The Traveling Salesman Problem (TSP is an integer programming problem that falls into the category of NP-Hard problems. As the problem become larger, there is no guarantee that optimal tours will be found within reasonable computation time. Heuristics techniques, like genetic algorithm and simulating annealing, can solve TSP instances with different levels of accuracy. Choosing which algorithm to use in order to get a best solution is still considered as a hard choice. This paper suggests domain reduction as a tool to be combined with any meta-heuristic so that the obtained results will be almost the same. The hybrid approach of combining domain reduction with any meta-heuristic encountered the challenge of choosing an algorithm that matches the TSP instance in order to get the best results.

  10. Amount of Genetics Education is Low Among Didactic Programs in Dietetics.

    Science.gov (United States)

    Beretich, Kaitlan; Pope, Janet; Erickson, Dawn; Kennedy, Angela

    2017-01-01

    Nutritional genomics is a growing area of research. Research has shown registered dietitian nutritionists (RDNs) have limited knowledge of genetics. Limited research is available regarding how didactic programs in dietetics (DPDs) meet the genetics knowledge requirement of the Accreditation Council for Education in Nutrition and Dietetics (ACEND®). The purpose of this study was to determine the extent to which the study of nutritional genomics is incorporated into undergraduate DPDs in response to the Academy of Nutrition and Dietetics position statement on nutritional genomics. The sample included 62 DPD directors in the U.S. Most programs (63.9%) reported the ACEND genetics knowledge requirement was being met by integrating genetic information into the current curriculum. However, 88.7% of programs reported devoting only 1-10 clock hours to genetics education. While 60.3% of directors surveyed reported they were confident in their program's ability to teach information related to genetics, only 6 directors reported having specialized training in genetics. The overall amount of clock hours devoted to genetics education is low. DPD directors, faculty, and instructors are not adequately trained to provide this education to students enrolled in DPDs. Therefore, the primary recommendation of this study is the development of a standardized curriculum for genetics education in DPDs.

  11. Portfolio optimization by using linear programing models based on genetic algorithm

    Science.gov (United States)

    Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

    2018-01-01

    In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

  12. Genetic Techniques for Manipulation of the Phytosterol Biotransformation Strain Mycobacterium neoaurum NRRL B-3805.

    Science.gov (United States)

    Loraine, Jessica K; Smith, Margaret C M

    2017-01-01

    Mycobacterium neoaurum is a saprophytic, soil-dwelling bacterium. The strain NRRL B-3805 converts phytosterols to androst-4-ene-3,17-dione (androstenedione; AD), a precursor of multiple C19 steroids of importance to industry. NRRL B-3805 itself is able to convert AD to other steroid products, including testosterone (Ts) and androst-1,4-diene-3,17-dione (androstadienedione; ADD). However to improve this strain for industrial use, genetic modification is a priority. In this chapter, we describe a range of genetic techniques that can be used for M. neoaurum NRRL B-3805. Methods for transformation, expression, and gene knockouts are presented as well as plasmid maintenance and stability.

  13. Genetics of the Mediterranean fruit fly in the sterile insect technique

    International Nuclear Information System (INIS)

    Roessler, Y.

    1997-01-01

    Altogether 27 morphological mutations on the five autosomes of the Mediterranean fruit fly, Ceratitis capitata (Wied.), have been isolated and studied in the author's laboratory during 22 years of research on the genetics of this species. Of the 27 loci, 18 were located on chromosomes 4 and 5. No mutant loci were identified on the sex chromosome in the laboratory. Linkage relations, map distances and linear arrangements on the respective chromosomes were established for most of the 27 mutant traits. The wp and dp traits were utilized in the construction of genetic sexing lines in laboratories involved in studies of the sterile insect technique. The occurrence and consequences of male recombination are discussed. (author)

  14. A Genetic-Algorithms-Based Approach for Programming Linear and Quadratic Optimization Problems with Uncertainty

    Directory of Open Access Journals (Sweden)

    Weihua Jin

    2013-01-01

    Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.

  15. Biochemical and genetic variation of some Syrian wheat varieties using NIR, RAPD and AFLPs techniques

    International Nuclear Information System (INIS)

    Saleh, B.

    2012-01-01

    This study was performed to assess chemical components and genetic variability of five Syrian wheat varieties using NIR, RAPD and AFLP techniques. NIR technique showed that Cham6 was the best variety in term of wheat grain quality due to their lowest protein (%), hardness, water uptake and baking volume and the highest starch (%) compared to the other tested varieties. PCR amplifications with 21 RAPD primers and 13 AFLP PCs primer combinations gave 104 and 466 discernible loci of which 24 (18.823%) and 199 (45.527%) were polymorphic for the both techniques respectively. Our data indicated that the three techniques gave similar results regarding the degree of relatedness among the tested varieties. In the present investigation, AFLP fingerprinting was more efficient than the RAPD assay. Where the letter exhibited lower Marker Index (MI) average (0.219) compared to AFLP one (3.203). The pattern generated by RAPD, AFLPs markers or by NIR separated the five wheat varieties into two groups. The first group consists of two subclusters. The first subcluster involved Cham8 and Bohous6, while the second one includes Cham6 that is very closed to precedent varieties. The second group consists of Bohous9 and Cham7 that were also closely related. Based on this study, the use of NIR, RAPD and AFLP techniques could be a powerful tool to detect the effectiveness relationships of these technologies. (author)

  16. Application of Genetic Algorithm and Particle Swarm Optimization techniques for improved image steganography systems

    Directory of Open Access Journals (Sweden)

    Jude Hemanth Duraisamy

    2016-01-01

    Full Text Available Image steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA and Particle Swarm Optimization (PSO have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT and Finite Ridgelet Transform (FRIT are used in combination with GA and PSO to improve the efficiency of the image steganography system.

  17. Momentum--"Evaluating Your Marketing Program: Measuring and Tracking Techniques."

    Science.gov (United States)

    Meservey, Lynne D.

    1990-01-01

    Suggests 10 tracking techniques for evaluating marketing performance. Techniques involve utilization rate, inquiry and source of inquiry tracking, appointment and interview tracking, enrollment conversion, cost per inquiry and per enrollment, retention rate, survey results, and "mystery shopper." (RJC)

  18. DNA fingerprinting techniques for the analysis of genetic and epigenetic alterations in colorectal cancer.

    Science.gov (United States)

    Samuelsson, Johanna K; Alonso, Sergio; Yamamoto, Fumiichiro; Perucho, Manuel

    2010-11-10

    Genetic somatic alterations are fundamental hallmarks of cancer. In addition to point and other small mutations targeting cancer genes, solid tumors often exhibit aneuploidy as well as multiple chromosomal rearrangements of large fragments of the genome. Whether somatic chromosomal alterations and aneuploidy are a driving force or a mere consequence of tumorigenesis remains controversial. Recently it became apparent that not only genetic but also epigenetic alterations play a major role in carcinogenesis. Epigenetic regulation mechanisms underlie the maintenance of cell identity crucial for development and differentiation. These epigenetic regulatory mechanisms have been found substantially altered during cancer development and progression. In this review, we discuss approaches designed to analyze genetic and epigenetic alterations in colorectal cancer, especially DNA fingerprinting approaches to detect changes in DNA copy number and methylation. DNA fingerprinting techniques, despite their modest throughput, played a pivotal role in significant discoveries in the molecular basis of colorectal cancer. The aim of this review is to revisit the fingerprinting technologies employed and the oncogenic processes that they unveiled. 2010 Elsevier B.V. All rights reserved.

  19. Phenotypic and Genetic Characterization of Circulating Tumor Cells by Combining Immunomagnetic Selection and FICTION Techniques

    Science.gov (United States)

    Campos, María; Prior, Celia; Warleta, Fernando; Zudaire, Isabel; Ruíz-Mora, Jesús; Catena, Raúl; Calvo, Alfonso; Gaforio, José J.

    2008-01-01

    The presence of circulating tumor cells (CTCs) in breast cancer patients has been proven to have clinical relevance. Cytogenetic characterization of these cells could have crucial relevance for targeted cancer therapies. We developed a method that combines an immunomagnetic selection of CTCs from peripheral blood with the fluorescence immunophenotyping and interphase cytogenetics as a tool for investigation of neoplasm (FICTION) technique. Briefly, peripheral blood (10 ml) from healthy donors was spiked with a predetermined number of human breast cancer cells. Nucleated cells were separated by double density gradient centrifugation of blood samples. Tumor cells (TCs) were immunomagnetically isolated with an anti-cytokeratin antibody and placed onto slides for FICTION analysis. For immunophenotyping and genetic characterization of TCs, a mixture of primary monoclonal anti-pancytokeratin antibodies was used, followed by fluorescent secondary antibodies, and finally hybridized with a TOP2A/HER-2/CEP17 multicolor probe. Our results show that TCs can be efficiently isolated from peripheral blood and characterized by FICTION. Because genetic amplification of TOP2A and ErbB2 (HER-2) in breast cancer correlates with response to anthracyclines and herceptin therapies, respectively, this novel methodology could be useful for a better classification of patients according to the genetic alterations of CTCs and for the application of targeted therapies. (J Histochem Cytochem 56:667–675, 2008) PMID:18413646

  20. Applying genetic algorithms for programming manufactoring cell tasks

    Directory of Open Access Journals (Sweden)

    Efredy Delgado

    2005-05-01

    Full Text Available This work was aimed for developing computational intelligence for scheduling a manufacturing cell's tasks, based manily on genetic algorithms. The manufacturing cell was modelled as beign a production-line; the makespan was calculated by using heuristics adapted from several libraries for genetic algorithms computed in C++ builder. Several problems dealing with small, medium and large list of jobs and machinery were resolved. The results were compared with other heuristics. The approach developed here would seem to be promising for future research concerning scheduling manufacturing cell tasks involving mixed batches.

  1. 34 CFR 429.1 - What is the Bilingual Vocational Materials, Methods, and Techniques Program?

    Science.gov (United States)

    2010-07-01

    ... techniques for bilingual vocational training for individuals with limited English proficiency. (Authority..., and Techniques Program? 429.1 Section 429.1 Education Regulations of the Offices of the Department of... MATERIALS, METHODS, AND TECHNIQUES PROGRAM General § 429.1 What is the Bilingual Vocational Materials...

  2. The Use of TILLING Technique to Detect Mutations and genetic diversity in Potato

    International Nuclear Information System (INIS)

    Elias, R; Al-Safadi, B; Till, B

    2008-01-01

    TILLING technique has been used, for the first time, to detect genetic variation, at the molecular level, among potato mutants (induced by gamma irradiation) and genetic diversity among 3 potato cultivars. Three potato mutant lines (every mutant represents a cultivar) tolerant to salinity have been used along with their controls. Three primer pairs were designed with the help of Potato Genome Sequencing Consortium on the web and were evaluated using agarose gel then sequencing. Primer pairs passing these tests were fluorescently labeled. Li-Cor based TILLING was applied using 2 forward primers one of them is labeled and 2 reverse primers one of them is labeled. The results have shown the success of using this technique on potato (tetraploid species) where the average density of nucleotide polymorphisms per sample was 16 polymorphisms per 1 kb. The optimal concentration was also determined between 0.1 and 1 ng/ul for potato genomic DNAs to be used in Li-Cor based TILLING assays. (author)

  3. Team teaching fire prevention program: evaluation of an education technique

    Science.gov (United States)

    Frank L. Ryan; Frank H. Gladen; William S. Folkman

    1978-01-01

    The California Department of Forestry's Team Teaching Fire Prevention Program consists of small-group discussions, slides or films, and a visit by Smokey Bear to school classrooms. In a survey, teachers and principals who had experienced the program responded favorably to it. The conduct by team members also received approval. The limited criticisms of the Program...

  4. The potential use of genetics to increase the effectiveness of treatment programs for criminal offenders.

    Science.gov (United States)

    Beaver, Kevin M; Jackson, Dylan B; Flesher, Dillon

    2014-01-01

    During the past couple of decades, the amount of research examining the genetic underpinnings to antisocial behaviors, including crime, has exploded. Findings from this body of work have generated a great deal of information linking genetics to criminal involvement. As a partial result, there is now a considerable amount of interest in how these findings should be integrated into the criminal justice system. In the current paper, we outline the potential ways that genetic information can be used to increase the effectiveness of treatment programs designed to reduce recidivism among offenders. We conclude by drawing attention to how genetic information can be used by rehabilitation programs to increase program effectiveness, reduce offender recidivism rates, and enhance public safety.

  5. Genetic programs can be compressed and autonomously decompressed in live cells

    Science.gov (United States)

    Lapique, Nicolas; Benenson, Yaakov

    2018-04-01

    Fundamental computer science concepts have inspired novel information-processing molecular systems in test tubes1-13 and genetically encoded circuits in live cells14-21. Recent research has shown that digital information storage in DNA, implemented using deep sequencing and conventional software, can approach the maximum Shannon information capacity22 of two bits per nucleotide23. In nature, DNA is used to store genetic programs, but the information content of the encoding rarely approaches this maximum24. We hypothesize that the biological function of a genetic program can be preserved while reducing the length of its DNA encoding and increasing the information content per nucleotide. Here we support this hypothesis by describing an experimental procedure for compressing a genetic program and its subsequent autonomous decompression and execution in human cells. As a test-bed we choose an RNAi cell classifier circuit25 that comprises redundant DNA sequences and is therefore amenable for compression, as are many other complex gene circuits15,18,26-28. In one example, we implement a compressed encoding of a ten-gene four-input AND gate circuit using only four genetic constructs. The compression principles applied to gene circuits can enable fitting complex genetic programs into DNA delivery vehicles with limited cargo capacity, and storing compressed and biologically inert programs in vivo for on-demand activation.

  6. Genetic counseling for schizophrenia: a review of referrals to a provincial medical genetics program from 1968–2007

    Science.gov (United States)

    Hunter, MJ; Hippman, Catriona; Honer, William G; Austin, Jehannine C.

    2014-01-01

    Purpose Recent studies have shown that individuals with schizophrenia and their family members are interested in genetic counseling, but few have received this service. We conducted an exploratory, retrospective study to describe (a) the population of individuals who were referred to the provincial program for genetic counseling for a primary indication of schizophrenia, and (b) trends in number of referrals between 1968 and 2007. Methods Referrals for a primary indication of schizophrenia were identified through the provincial program database. Charts were reviewed and the following information was recorded: discipline of referring physician, demographics, psychiatric diagnosis, referred individual’s and partner’s (if applicable) family history, and any current pregnancy history. Data were characterized using descriptive statistics. Results Between 1968 and 2007, 288 referrals were made for a primary indication of schizophrenia. Most referrals were made: (a) for individuals who had a first-degree family member with schizophrenia, rather than for affected individuals, (b) for preconception counseling, and (c) by family physicians (69%), with only 2% by psychiatrists. Conclusions In British Columbia, individuals affected with schizophrenia and their family members are rarely referred for psychiatric genetic counseling. There is a need to identify barriers to psychiatric genetic counseling and develop strategies to improve access. PMID:20034078

  7. Ifuzzer : An evolutionary interpreter fuzzer using genetic programming

    NARCIS (Netherlands)

    Veggalam, Spandan; Rawat, Sanjay; Haller, Istvan; Bos, Herbert

    We present an automated evolutionary fuzzing technique to find bugs in JavaScript interpreters. Fuzzing is an automated black box testing technique used for finding security vulnerabilities in the software by providing random data as input. However, in the case of an interpreter, fuzzing is

  8. Performance improvement of developed program by using multi-thread technique

    Directory of Open Access Journals (Sweden)

    Surasak Jabal

    2015-03-01

    Full Text Available This research presented how to use a multi-thread programming technique to improve the performance of a program written by Windows Presentation Foundation (WPF. The Computer Assisted Instruction (CAI software, named GAME24, was selected to use as a case study. This study composed of two main parts. The first part was about design and modification of the program structure upon the Object Oriented Programing (OOP approach. The second part was about coding the program using the multi-thread technique which the number of threads were based on the calculated Catalan number. The result showed that the multi-thread programming technique increased the performance of the program 44%-88% compared to the single-thread technique. In addition, it has been found that the number of cores in the CPU also increase the performance of multithreaded program proportionally.

  9. FORTRAN programs for transient eddy current calculations using a perturbation-polynomial expansion technique

    International Nuclear Information System (INIS)

    Carpenter, K.H.

    1976-11-01

    A description is given of FORTRAN programs for transient eddy current calculations in thin, non-magnetic conductors using a perturbation-polynomial expansion technique. Basic equations are presented as well as flow charts for the programs implementing them. The implementation is in two steps--a batch program to produce an intermediate data file and interactive programs to produce graphical output. FORTRAN source listings are included for all program elements, and sample inputs and outputs are given for the major programs

  10. Artificial intelligence programming with LabVIEW: genetic algorithms for instrumentation control and optimization.

    Science.gov (United States)

    Moore, J H

    1995-06-01

    A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.

  11. PND fuel handling decontamination program: specialized techniques and results

    International Nuclear Information System (INIS)

    Pan, R.; Hobbs, K.; Minnis, M.; Graham, K.

    1995-01-01

    The use of various decontamination techniques and equipment has become a critical part of Fuel Handling maintenance work at the Pickering Nuclear Station, an eight unit CANDU station located about 30 km east of Toronto. This paper presents an overview of the set up and techniques used for cleaning in the PND Fuel Handling Maintenance Facility, and the results achieved. (author)

  12. Routine human-competitive machine intelligence by means of genetic programming

    Science.gov (United States)

    Koza, John R.; Streeter, Matthew J.; Keane, Martin

    2004-01-01

    Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

  13. Forecasting Shaharchay River Flow in Lake Urmia Basin using Genetic Programming and M5 Model Tree

    Directory of Open Access Journals (Sweden)

    S. Samadianfard

    2017-01-01

    Full Text Available Introduction: Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering. In the recent years, applications of intelligent methods such as artificial neural networks, fuzzy systems and genetic programming in water science and engineering have been grown extensively. These mentioned methods are able to model nonlinear process of river flows without any need to geometric properties. A huge number of studies have been reported in the field of using intelligent methods in water resource engineering. For example, Noorani and Salehi (23 presented a model for predicting runoff in Lighvan basin using adaptive neuro-fuzzy network and compared the performance of it with neural network and fuzzy inference methods in east Azerbaijan, Iran. Nabizadeh et al. (21 used fuzzy inference system and adaptive neuro-fuzzy inference system in order to predict river flow in Lighvan river. Khalili et al. (13 proposed a BL-ARCH method for prediction of flows in Shaharchay River in Urmia. Khu et al. (16 used genetic programming for runoff prediction in Orgeval catchment in France. Firat and Gungor (11 evaluated the fuzzy-neural model for predicting Mendes river flow in Turkey. The goal of present study is comparing the performance of genetic programming and M5 model trees for prediction of Shaharchay river flow in the basin of Lake Urmia and obtaining a comprehensive insight of their abilities. Materials and Methods: Shaharchay river as a main source of providing drinking water of Urmia city and agricultural needs of surrounding lands and finally one of the main input sources of Lake Urmia is quite important in the region. For obtaining the predetermined goals of present study, average monthly flows of Shaharchay River in Band hydrometric station has been gathered from 1951 to 2011. Then, two third of mentioned

  14. Application of genetic algorithm (GA) technique on demand estimation of fossil fuels in Turkey

    International Nuclear Information System (INIS)

    Canyurt, Olcay Ersel; Ozturk, Harun Kemal

    2008-01-01

    The main objective is to investigate Turkey's fossil fuels demand, projection and supplies by using the structure of the Turkish industry and economic conditions. This study develops scenarios to analyze fossil fuels consumption and makes future projections based on a genetic algorithm (GA). The models developed in the nonlinear form are applied to the coal, oil and natural gas demand of Turkey. Genetic algorithm demand estimation models (GA-DEM) are developed to estimate the future coal, oil and natural gas demand values based on population, gross national product, import and export figures. It may be concluded that the proposed models can be used as alternative solutions and estimation techniques for the future fossil fuel utilization values of any country. In the study, coal, oil and natural gas consumption of Turkey are projected. Turkish fossil fuel demand is increased dramatically. Especially, coal, oil and natural gas consumption values are estimated to increase almost 2.82, 1.73 and 4.83 times between 2000 and 2020. In the figures GA-DEM results are compared with World Energy Council Turkish National Committee (WECTNC) projections. The observed results indicate that WECTNC overestimates the fossil fuel consumptions. (author)

  15. Near infrared spectrometric technique for testing fruit quality: optimisation of regression models using genetic algorithms

    Science.gov (United States)

    Isingizwe Nturambirwe, J. Frédéric; Perold, Willem J.; Opara, Umezuruike L.

    2016-02-01

    Near infrared (NIR) spectroscopy has gained extensive use in quality evaluation. It is arguably one of the most advanced spectroscopic tools in non-destructive quality testing of food stuff, from measurement to data analysis and interpretation. NIR spectral data are interpreted through means often involving multivariate statistical analysis, sometimes associated with optimisation techniques for model improvement. The objective of this research was to explore the extent to which genetic algorithms (GA) can be used to enhance model development, for predicting fruit quality. Apple fruits were used, and NIR spectra in the range from 12000 to 4000 cm-1 were acquired on both bruised and healthy tissues, with different degrees of mechanical damage. GAs were used in combination with partial least squares regression methods to develop bruise severity prediction models, and compared to PLS models developed using the full NIR spectrum. A classification model was developed, which clearly separated bruised from unbruised apple tissue. GAs helped improve prediction models by over 10%, in comparison with full spectrum-based models, as evaluated in terms of error of prediction (Root Mean Square Error of Cross-validation). PLS models to predict internal quality, such as sugar content and acidity were developed and compared to the versions optimized by genetic algorithm. Overall, the results highlighted the potential use of GA method to improve speed and accuracy of fruit quality prediction.

  16. A high-resolution neutron spectra unfolding method using the Genetic Algorithm technique

    CERN Document Server

    Mukherjee, B

    2002-01-01

    The Bonner sphere spectrometers (BSS) are commonly used to determine the neutron spectra within various nuclear facilities. Sophisticated mathematical tools are used to unfold the neutron energy distribution from the output data of the BSS. This paper highlights a novel high-resolution neutron spectra-unfolding method using the Genetic Algorithm (GA) technique. The GA imitates the biological evolution process prevailing in the nature to solve complex optimisation problems. The GA method was utilised to evaluate the neutron energy distribution, average energy, fluence and equivalent dose rates at important work places of a DIDO class research reactor and a high-energy superconducting heavy ion cyclotron. The spectrometer was calibrated with a sup 2 sup 4 sup 1 Am/Be (alpha,n) neutron standard source. The results of the GA method agreed satisfactorily with the results obtained by using the well-known BUNKI neutron spectra unfolding code.

  17. Optimal Draft requirement for vibratory tillage equipment using Genetic Algorithm Technique

    Science.gov (United States)

    Rao, Gowripathi; Chaudhary, Himanshu; Singh, Prem

    2018-03-01

    Agriculture is an important sector of Indian economy. Primary and secondary tillage operations are required for any land preparation process. Conventionally different tractor-drawn implements such as mouldboard plough, disc plough, subsoiler, cultivator and disc harrow, etc. are used for primary and secondary manipulations of soils. Among them, oscillatory tillage equipment is one such type which uses vibratory motion for tillage purpose. Several investigators have reported that the requirement for draft consumption in primary tillage implements is more as compared to oscillating one because they are always in contact with soil. Therefore in this paper, an attempt is made to find out the optimal parameters from the experimental data available in the literature to obtain minimum draft consumption through genetic algorithm technique.

  18. Three different applications of genetic algorithm (GA) search techniques on oil demand estimation

    International Nuclear Information System (INIS)

    Canyurt, Olcay Ersel; Oztuerk, Harun Kemal

    2006-01-01

    This present study develops three scenarios to analyze oil consumption and make future projections based on the Genetic algorithm (GA) notion, and examines the effect of the design parameters on the oil utilization values. The models developed in the non-linear form are applied to the oil demand of Turkey. The GA Oil Demand Estimation Model (GAODEM) is developed to estimate the future oil demand values based on Gross National Product (GNP), population, import, export, oil production, oil import and car, truck and bus sales figures. Among these models, the GA-PGOiTI model, which uses population, GNP, oil import, truck sales and import as design parameters/indicators, was found to provide the best fit solution with the observed data. It may be concluded that the proposed models can be used as alternative solution and estimation techniques for the future oil utilization values of any country

  19. Evolving rule-based systems in two medical domains using genetic programming.

    Science.gov (United States)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

    2004-11-01

    To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

  20. Towards programming languages for genetic engineering of living cells.

    Science.gov (United States)

    Pedersen, Michael; Phillips, Andrew

    2009-08-06

    Synthetic biology aims at producing novel biological systems to carry out some desired and well-defined functions. An ultimate dream is to design these systems at a high level of abstraction using engineering-based tools and programming languages, press a button, and have the design translated to DNA sequences that can be synthesized and put to work in living cells. We introduce such a programming language, which allows logical interactions between potentially undetermined proteins and genes to be expressed in a modular manner. Programs can be translated by a compiler into sequences of standard biological parts, a process that relies on logic programming and prototype databases that contain known biological parts and protein interactions. Programs can also be translated to reactions, allowing simulations to be carried out. While current limitations on available data prevent full use of the language in practical applications, the language can be used to develop formal models of synthetic systems, which are otherwise often presented by informal notations. The language can also serve as a concrete proposal on which future language designs can be discussed, and can help to guide the emerging standard of biological parts which so far has focused on biological, rather than logical, properties of parts.

  1. Owning genetic information and gene enhancement techniques: why privacy and property rights may undermine social control of the human genome.

    Science.gov (United States)

    Moore, A D

    2000-04-01

    In this article I argue that the proper subjects of intangible property claims include medical records, genetic profiles, and gene enhancement techniques. Coupled with a right to privacy these intangible property rights allow individuals a zone of control that will, in most cases, justifiably exclude governmental or societal invasions into private domains. I argue that the threshold for overriding privacy rights and intangible property rights is higher, in relation to genetic enhancement techniques and sensitive personal information, than is commonly suggested. Once the bar is raised, so-to-speak, the burden of overriding it is formidable. Thus many policy decisions that have been recently proposed or enacted--citywide audio and video surveillance, law enforcement DNA sweeps, genetic profiling, national bans on genetic testing and enhancement of humans, to name a few--will have to be backed by very strong arguments.

  2. Estimation of genetic variability and heritability of wheat agronomic traits resulted from some gamma rays irradiation techniques

    International Nuclear Information System (INIS)

    Wijaya Murti Indriatama; Trikoesoemaningtyas; Syarifah Iis Aisyah; Soeranto Human

    2016-01-01

    Gamma irradiation techniques have significant effect on frequency and spectrum of macro-mutation but the study of its effect on micro-mutation that related to genetic variability on mutated population is very limited. The aim of this research was to study the effect of gamma irradiation techniques on genetic variability and heritability of wheat agronomic characters at M2 generation. This research was conducted from July to November 2014, at Cibadak experimental station, Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development, Ministry of Agriculture. Three introduced wheat breeding lines (F-44, Kiran-95 & WL-711) were treated by 3 gamma irradiation techniques (acute, fractionated and intermittent). M1 generation of combination treatments were planted and harvested its spike individually per plants. As M2 generation, seeds of 75 M1 spike were planted at the field with one row one spike method and evaluated on the agronomic characters and its genetic components. The used of gamma irradiation techniques decreased mean but increased range values of agronomic traits in M2 populations. Fractionated irradiation induced higher mean and wider range on spike length and number of spike let per spike than other irradiation techniques. Fractionated and intermittent irradiation resulted greater variability of grain weight per plant than acute irradiation. The number of tillers, spike weight, grain weight per spike and grain weight per plant on M2 population resulted from induction of three gamma irradiation techniques have high estimated heritability and broad sense of genetic variability coefficient values. The three gamma irradiation techniques increased genetic variability of agronomic traits on M2 populations, except plant height. (author)

  3. System network planning expansion using mathematical programming, genetic algorithms and tabu search

    International Nuclear Information System (INIS)

    Sadegheih, A.; Drake, P.R.

    2008-01-01

    In this paper, system network planning expansion is formulated for mixed integer programming, a genetic algorithm (GA) and tabu search (TS). Compared with other optimization methods, GAs are suitable for traversing large search spaces, since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will tend to become more common as the search space increases in size. GA's give an excellent trade off between solution quality and computing time and flexibility for taking into account specific constraints in real situations. TS has emerged as a new, highly efficient, search paradigm for finding quality solutions to combinatorial problems. It is characterized by gathering knowledge during the search and subsequently profiting from this knowledge. The attractiveness of the technique comes from its ability to escape local optimality. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The DC load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions and also provides information regarding the optimal generation at each generation point. This method of solution is demonstrated on the expansion of a 10 bus bar system to 18 bus bars. Finally, a steady-state genetic algorithm is employed rather than generational replacement, also uniform crossover is used

  4. Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Wafa Abdelmalek

    2009-01-01

    Full Text Available The volatility is a crucial variable in option pricing and hedging strategies. The aim of this paper is to provide some initial evidence of the empirical relevance of genetic programming to volatility's forecasting. By using real data from S&P500 index options, the genetic programming's ability to forecast Black and Scholes-implied volatility is compared between time series samples and moneyness-time to maturity classes. Total and out-of-sample mean squared errors are used as forecasting's performance measures. Comparisons reveal that the time series model seems to be more accurate in forecasting-implied volatility than moneyness time to maturity models. Overall, results are strongly encouraging and suggest that the genetic programming approach works well in solving financial problems.

  5. Techniques for overcoming community resistance to family planning programs.

    Science.gov (United States)

    Palley, H A

    1968-01-01

    Methods of overcoming resistance to publicly subsidized family planning programs are discussed. The main sources of opposition include groups that oppose family planning for moral reasons, and those who object to the spending of government funds to provide services and information. Such opposition can be weakened by indicating that family planning clinics fulf: 11 important medical needs. Presenting social justification for family planning can help to lower oppostion. In order to secure participation in the programs by low income groups it is essential to have community leaders involved in policy decisions and to use indigenous community paraprofessionals in the clinics. A coalition of representatives of the poor community and the health and welfare system, aided by the community organization, can lead to an effective family planning program.

  6. Development of new techniques of using irradiation in the genetic improvement of warm season grasses, the assessment of their genetic and cytogenetic effects and biomass production from grass. Annual progress report, November 1, 1979 to October 31, 1980

    International Nuclear Information System (INIS)

    Burton, G.W.; Hanna, W.W.

    1980-01-01

    New techniques are described for using irradiation and chemical mutagens in the genetic improvement of several warm season grasses. Genetic and cytogenetic effects of these treatments are also being studied

  7. Program of nuclear techniques application (triennial 88-89-90)

    International Nuclear Information System (INIS)

    1988-01-01

    A real analysis of the potentiality and the possibility from Nuclear Energetic Research Institute (IPEN) Sao Paulo, Brazil in realize the researches and developments for offering specialized services of nuclear techniques for using in bioengineering, industry, isotope production, IEA-R1 reactor irradiation and radiation detectors and sensors are described. (author)

  8. Vulnerabilities of Software for Mobile Phones and Secure Programming Techniques

    Directory of Open Access Journals (Sweden)

    T. R. Khabibullin

    2012-09-01

    Full Text Available The article reviews the most common mistakes made by developers when writing software for mobile platforms which lead to appearing vulnerabilities that allow attackers to perform various types of attacks. The basic principles of defensive programming are presented.

  9. Automated Feature Design for Time Series Classification by Genetic Programming

    OpenAIRE

    Harvey, Dustin Yewell

    2014-01-01

    Time series classification (TSC) methods discover and exploit patterns in time series and other one-dimensional signals. Although many accurate, robust classifiers exist for multivariate feature sets, general approaches are needed to extend machine learning techniques to make use of signal inputs. Numerous applications of TSC can be found in structural engineering, especially in the areas of structural health monitoring and non-destructive evaluation. Additionally, the fields of process contr...

  10. Decomposition techniques in mathematical programming engineering and science applications

    CERN Document Server

    Conejo, Antonio J; Minguez, Roberto; Garcia-Bertrand, Raquel

    2006-01-01

    Optimization plainly dominates the design, planning, operation, and c- trol of engineering systems. This is a book on optimization that considers particular cases of optimization problems, those with a decomposable str- ture that can be advantageously exploited. Those decomposable optimization problems are ubiquitous in engineering and science applications. The book considers problems with both complicating constraints and complicating va- ables, and analyzes linear and nonlinear problems, with and without in- ger variables. The decomposition techniques analyzed include Dantzig-Wolfe, Benders, Lagrangian relaxation, Augmented Lagrangian decomposition, and others. Heuristic techniques are also considered. Additionally, a comprehensive sensitivity analysis for characterizing the solution of optimization problems is carried out. This material is particularly novel and of high practical interest. This book is built based on many clarifying, illustrative, and compu- tional examples, which facilitate the learning p...

  11. Real Time Wave Forecasting Using Wind Time History and Genetic Programming

    Directory of Open Access Journals (Sweden)

    A.R. Kambekar

    2014-12-01

    Full Text Available The significant wave height and average wave period form an essential input for operational activities in ocean and coastal areas. Such information is important in issuing appropriate warnings to people planning any construction or instillation works in the oceanic environment. Many countries over the world routinely collect wave and wind data through a network of wave rider buoys. The data collecting agencies transmit the resulting information online to their registered users through an internet or a web-based system. Operational wave forecasts in addition to the measured data are also made and supplied online to the users. This paper discusses operational wave forecasting in real time mode at locations where wind rather than wave data are continuously recorded. It is based on the time series modeling and incorporates an artificial intelligence technique of genetic programming. The significant wave height and average wave period values are forecasted over a period of 96 hr in future from the observations of wind speed and directions extending to a similar time scale in the past. Wind measurements made by floating buoys at eight different locations around India over a period varying from 1.5 yr to 9.0 yr were considered. The platform of Matlab and C++ was used to develop a graphical user interface that will extend an internet based user-friendly access of the forecasts to any registered user of the data dissemination authority.

  12. A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

    Science.gov (United States)

    Zhang, Yang; Rockett, Peter I

    2009-01-01

    In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.

  13. Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

    Science.gov (United States)

    Sastry, Kumara Narasimha

    2007-03-01

    Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

  14. Non-linear nuclear engineering models as genetic programming application; Modelos nao-lineares de engenharia nuclear como aplicacao de programacao genetica

    Energy Technology Data Exchange (ETDEWEB)

    Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1997-12-01

    This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs.

  15. Aerobic Exercise Combined with Techniques Programe Can Be Increased Groundstroke Skill of Tennis Athlet

    OpenAIRE

    Nasrulloh, Ahmad

    2012-01-01

    Professional tennis athletes should be able to master all the basic techniques of playing tennis and having physical fitness. Therefore, it is necessary to get an exercise that can give meaning to the skills and physical fitness. One of the proper exercises is with aerobic exercise combined with the technique.Aerobic exercise program combined with techniques is: (1) a number of players consisting of six to seven people with backward sequential formation techniques performing forehand and back...

  16. Analysis of the efficiency of the linearization techniques for solving multi-objective linear fractional programming problems by goal programming

    Directory of Open Access Journals (Sweden)

    Tunjo Perić

    2017-01-01

    Full Text Available This paper presents and analyzes the applicability of three linearization techniques used for solving multi-objective linear fractional programming problems using the goal programming method. The three linearization techniques are: (1 Taylor’s polynomial linearization approximation, (2 the method of variable change, and (3 a modification of the method of variable change proposed in [20]. All three linearization techniques are presented and analyzed in two variants: (a using the optimal value of the objective functions as the decision makers’ aspirations, and (b the decision makers’ aspirations are given by the decision makers. As the criteria for the analysis we use the efficiency of the obtained solutions and the difficulties the analyst comes upon in preparing the linearization models. To analyze the applicability of the linearization techniques incorporated in the linear goal programming method we use an example of a financial structure optimization problem.

  17. Induced mutation and in vitro culture techniques for the genetic improvement of ornamentals

    International Nuclear Information System (INIS)

    Lapade, Avelina G.; Veluz, Ana Maria S.; Marbella, Lucia J.; Rama, Manny G.

    2001-01-01

    Mutation breeding using cobalt-60 ( 60 Co) gamma radiation coupled with tissue culture techniques is undertaken for genetic improvement of foliage ornamentals (Dracaena sp. and Murraya exotica L.) and cutflowers (Chrysanthemum morifolium and orchids; Vanda sanderiana, Dendrobium Pattaya Beauty and Phalenopsis schilleriana). Gamma radiation (10-30 Gy) induced chlorophyll mutations and several morphological changes in D. sanderiana. For D. godseffiana, irradiated cuttings resulted in reduction of leaf size and chlorophyll mutations. Reduction in height was observed in the M 2 generation of Murraya exotica L. irradiated at doses ranging from 10 to 30 Gy. The dwarf Murraya mutant was multiplied through the use of seeds and presently 116 plants are commercially available and are ''test marketed'' to the public. Tissue culture technique was used to induce mutation and as a means of micropropagation in two ornamental crops (orchids and chrysanthemum). Effects of different doses of gamma radiation on callus induction from nodal sections of chrysanthemum grown in Murashige and Skoog's (MS) with naphthalene acetic acid (NAA) and benzyl adenine (BA) were studied. Micropropagation of irradiated and unirradiated chrysanthemum using MS basal medium is presently being studied. Whorling and changes in leaf color were observed at 10 Gy and doubling of leaf growth at the node at 20 Gy for vegetatively generated V 3 plant. In orchids, irradiation of immature embryo with gamma rays ranging from 5 to 10 Gy increased the percentage of germination in Dendrobium Pattaya Beauty and P. schilleriana. Protocorms of Vanda sanderiana irradiated at 10 Gy and grown in Knudson C medium developed into plantlets that are bigger and more vigorous than those irradiated at 20 GY and from the control plant. A decrease in seedling height was observed with increasing dose of gamma radiation. (Author)

  18. A CAL Program to Teach the Basic Principles of Genetic Engineering--A Change from the Traditional Approach.

    Science.gov (United States)

    Dewhurst, D. G.; And Others

    1989-01-01

    An interactive computer-assisted learning program written for the BBC microcomputer to teach the basic principles of genetic engineering is described. Discussed are the hardware requirements software, use of the program, and assessment. (Author/CW)

  19. Evolving Rule-Based Systems in two Medical Domains using Genetic Programming

    DEFF Research Database (Denmark)

    Tsakonas, A.; Dounias, G.; Jantzen, Jan

    2004-01-01

    We demonstrate, compare and discuss the application of two genetic programming methodologies for the construction of rule-based systems in two medical domains: the diagnosis of Aphasia's subtypes and the classification of Pap-Smear Test examinations. The first approach consists of a scheme...

  20. Model-based problem solving through symbolic regression via pareto genetic programming

    NARCIS (Netherlands)

    Vladislavleva, E.

    2008-01-01

    Pareto genetic programming methodology is extended by additional generic model selection and generation strategies that (1) drive the modeling engine to creation of models of reduced non-linearity and increased generalization capabilities, and (2) improve the effectiveness of the search for robust

  1. Evaluation of two-year Jewish genetic disease screening program in Atlanta: insight into community genetic screening approaches.

    Science.gov (United States)

    Shao, Yunru; Liu, Shuling; Grinzaid, Karen

    2015-04-01

    Improvements in genetic testing technologies have led to the development of expanded carrier screening panels for the Ashkenazi Jewish population; however, there are major inconsistencies in current screening practices. A 2-year pilot program was launched in Atlanta in 2010 to promote and facilitate screening for 19 Jewish genetic diseases. We analyzed data from this program, including participant demographics and outreach efforts. This retrospective analysis is based on a de-identified dataset of 724 screenees. Data were obtained through medical chart review and questionnaires and included demographic information, screening results, response to outreach efforts, and follow-up behavior and preferences. We applied descriptive analysis, chi-square tests, and logistic regression to analyze the data and compare findings with published literature. The majority of participants indicated that they were not pregnant or did not have a partner who was pregnant were affiliated with Jewish organizations and reported 100 % AJ ancestry. Overall, carrier frequency was 1 in 3.9. Friends, rabbis, and family members were the most common influencers of the decision to receive screening. People who were older, had a history of pregnancy, and had been previously screened were more likely to educate others (all p influencers who then encouraged screening in the target population. Educating influencers and increasing overall awareness were the most effective outreach strategies.

  2. Sex determination of Pohnpei Micronesian kingfishers using morphological and molecular genetic techniques

    Science.gov (United States)

    Kesler, Dylan C.; Lopes, I.F.; Haig, Susan M.

    2006-01-01

    Conservation-oriented studies of Micronesian Kingfishers (Todiramphus cinnamominus) have been hindered by a lack of basic natural history information, despite the status of the Guam subspecies (T. c. cinnamominus) as one of the most endangered species in the world. We used tissue samples and morphometric measures from museum specimens and wild-captured Pohnpei Micronesian Kingfishers (T. c. reichenbachii) to develop methods for sex determination. We present a modified molecular protocol and a discriminant function that yields the probability that a particular individual is male or female. Our results revealed that females were significantly larger than males, and the discriminant function correctly predicted sex in 73% (30/41) of the individuals. The sex of 86% (18/21) of individuals was correctly assigned when a moderate reliability threshold was set. Sex determination using molecular genetic techniques was more reliable than methods based on morphology. Our results will facilitate recovery efforts for the critically endangered Guam Micronesian Kingfisher and provide a basis for sex determination in the 11 other endangered congeners in the Pacific Basin.

  3. In vivo diagnosis of cervical precancer using Raman spectroscopy and genetic algorithm techniques.

    Science.gov (United States)

    Duraipandian, Shiyamala; Zheng, Wei; Ng, Joseph; Low, Jeffrey J H; Ilancheran, A; Huang, Zhiwei

    2011-10-21

    This study aimed to evaluate the clinical utility of applying near-infrared (NIR) Raman spectroscopy and genetic algorithm-partial least squares-discriminant analysis (GA-PLS-DA) to identify biomolecular changes of cervical tissues associated with dysplastic transformation during colposcopic examination. A total of 105 in vivo Raman spectra were measured from 57 cervical sites (35 normal and 22 precancer sites) of 29 patients recruited, in which 65 spectra were from normal sites, while 40 spectra were from cervical precancerous lesions (i.e., 7 low-grade CIN and 33 high-grade CIN). The GA feature selection technique incorporated with PLS was utilized to study the significant biochemical Raman bands for differentiation between normal and precancer cervical tissues. The GA-PLS-DA algorithm with double cross-validation (dCV) identified seven diagnostically significant Raman bands in the ranges of 925-935, 979-999, 1080-1090, 1240-1260, 1320-1340, 1400-1420, and 1625-1645 cm(-1) related to proteins, nucleic acids and lipids in tissue, and yielded a diagnostic accuracy of 82.9% (sensitivity of 72.5% (29/40) and specificity of 89.2% (58/65)) for precancer detection. The results of this exploratory study suggest that Raman spectroscopy in conjunction with GA-PLS-DA and dCV methods has the potential to provide clinically significant discrimination between normal and precancer cervical tissues at the molecular level.

  4. Object-oriented programming techniques for the AGS Booster

    International Nuclear Information System (INIS)

    Skelly, J.F.

    1991-01-01

    The applications software developed for the control system of the AGS Booster Project was written in the object-oriented language, C++. A the start of the Booster Project, the programming staff of the AGS Controls Section comprised some dozen programmer/analysts, all highly fluent in C but novices in C++. During the coarse of this project, nearly the entire staff converted to using C++ for a large fraction of their assignments. Over 100 C++ software modules are now available for Booster and general AGS use, of which a large fraction are broadly applicable tools. The transition from C to C++ from a managerial perspective is discussed and an overview is provided of the ways in which object classes have been applied in Booster software development

  5. Object-oriented programming techniques for the AGS Booster

    International Nuclear Information System (INIS)

    Skelly, J.F.

    1992-01-01

    The applications software developed for the control system of the AGS Booster Project was written in the object-oriented language, C++. At the start of the Booster Project, the programming staff of the AGS Controls Section comprised some dozen programmer/analysts, all highly fluent in C but novices in C++. During the course of this project, nearly the entire staff converted to using C++ for a large fraction of their assignments. Over 100 C++ software modules are now available both for Booster and general AGS use, of which a large fraction are broadly applicable tools. The transition from C to C++ from a managerial perspective is discussed and an overview is provided of the ways in which object classes have been applied in Booster software development. (author)

  6. Report on an Investigation into an Entry Level Clinical Doctorate for the Genetic Counseling Profession and a Survey of the Association of Genetic Counseling Program Directors.

    Science.gov (United States)

    Reiser, Catherine; LeRoy, Bonnie; Grubs, Robin; Walton, Carol

    2015-10-01

    The master's degree is the required entry-level degree for the genetic counseling profession in the US and Canada. In 2012 the Association of Genetic Counseling Program Directors (AGCPD) passed resolutions supporting retention of the master's as the entry-level and terminal degree and opposing introduction of an entry-level clinical doctorate (CD) degree. An AGCPD workgroup surveyed directors of all 34 accredited training programs with the objective of providing the Genetic Counseling Advanced Degrees Task Force (GCADTF) with information regarding potential challenges if master's programs were required to transition to an entry-level CD. Program demographics, projected ability to transition to an entry-level CD, factors influencing ability to transition, and potential effects of transition on programs, students and the genetic counseling workforce were characterized. Two programs would definitely be able to transition, four programs would close, thirteen programs would be at risk to close and fourteen programs would probably be able to transition with varying degrees of difficulty. The most frequently cited limiting factors were economic, stress on clinical sites, and administrative approval of a new degree/program. Student enrollment under an entry-level CD model was projected to decrease by 26.2 %, negatively impacting the workforce pipeline. The results further illuminate and justify AGCPD's position to maintain the master's as the entry-level degree.

  7. The genetic algorithm for the nonlinear programming of water pollution control system

    Energy Technology Data Exchange (ETDEWEB)

    Wei, J.; Zhang, J. [China University of Geosciences (China)

    1999-08-01

    In the programming of water pollution control system the combined method of optimization with simulation is used generally. It is not only laborious in calculation, but also the global optimum of the obtained solution is guaranteed difficult. In this paper, the genetic algorithm (GA) used in the nonlinear programming of water pollution control system is given, by which the preferred conception for the programming of waste water system is found in once-through operation. It is more succinct than the conventional method and the global optimum of the obtained solution could be ensured. 6 refs., 4 figs., 3 tabs.

  8. Translation techniques for distributed-shared memory programming models

    Energy Technology Data Exchange (ETDEWEB)

    Fuller, Douglas James [Iowa State Univ., Ames, IA (United States)

    2005-01-01

    The high performance computing community has experienced an explosive improvement in distributed-shared memory hardware. Driven by increasing real-world problem complexity, this explosion has ushered in vast numbers of new systems. Each new system presents new challenges to programmers and application developers. Part of the challenge is adapting to new architectures with new performance characteristics. Different vendors release systems with widely varying architectures that perform differently in different situations. Furthermore, since vendors need only provide a single performance number (total MFLOPS, typically for a single benchmark), they only have strong incentive initially to optimize the API of their choice. Consequently, only a fraction of the available APIs are well optimized on most systems. This causes issues porting and writing maintainable software, let alone issues for programmers burdened with mastering each new API as it is released. Also, programmers wishing to use a certain machine must choose their API based on the underlying hardware instead of the application. This thesis argues that a flexible, extensible translator for distributed-shared memory APIs can help address some of these issues. For example, a translator might take as input code in one API and output an equivalent program in another. Such a translator could provide instant porting for applications to new systems that do not support the application's library or language natively. While open-source APIs are abundant, they do not perform optimally everywhere. A translator would also allow performance testing using a single base code translated to a number of different APIs. Most significantly, this type of translator frees programmers to select the most appropriate API for a given application based on the application (and developer) itself instead of the underlying hardware.

  9. A METHOD FOR SOLVING LINEAR PROGRAMMING PROBLEMS WITH FUZZY PARAMETERS BASED ON MULTIOBJECTIVE LINEAR PROGRAMMING TECHNIQUE

    OpenAIRE

    M. ZANGIABADI; H. R. MALEKI

    2007-01-01

    In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...

  10. Recognizing and Managing Complexity: Teaching Advanced Programming Concepts and Techniques Using the Zebra Puzzle

    OpenAIRE

    Xihui "Paul" Zhang; John D. Crabtree

    2015-01-01

    Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We present a classic brain teaser that is used to communicate and demonstrate advanced software development concepts and techniques. Our results show th...

  11. Genetic similarity of polyploids - A new version of the computer program POPDIST (ver. 1.2.0) considers intraspecific genetic differentiation

    DEFF Research Database (Denmark)

    Tomiuk, Jürgen; Guldbrandtsen, Bernt; Loeschcke, Volker

    2009-01-01

    For evolutionary studies of polyploid species estimates of the genetic identity between species with different degrees of ploidy are particularly required because gene counting in samples of polyploid individuals often cannot be done, e.g., in triploids the phenotype AB can be genotypically either...... ABB or AAB. We recently suggested a genetic distance measure that is based on phenotype counting and made available the computer program POPDIST. The program provides maximum-likelihood estimates of the genetic identities and distances between polyploid populations, but this approach...

  12. Implementation of genetic conservation practices in a muskellunge propagation and stocking program

    Science.gov (United States)

    Jennings, Martin J.; Sloss, Brian L.; Hatzenbeler, Gene R.; Kampa, Jeffrey M.; Simonson, Timothy D.; Avelallemant, Steven P.; Lindenberger, Gary A.; Underwood, Bruce D.

    2010-01-01

    Conservation of genetic resources is a challenging issue for agencies managing popular sport fishes. To address the ongoing potential for genetic risks, we developed a comprehensive set of recommendations to conserve genetic diversity of muskellunge (Esox masquinongy) in Wisconsin, and evaluated the extent to which the recommendations can be implemented. Although some details are specific to Wisconsin's muskellunge propagation program, many of the practical issues affecting implementation are applicable to other species and production systems. We developed guidelines to restrict future broodstock collection operations to lakes with natural reproduction and to develop a set of brood lakes to use on a rotational basis within regional stock boundaries, but implementation will require considering lakes with variable stocking histories. Maintaining an effective population size sufficient to minimize the risk of losing alleles requires limiting broodstock collection to large lakes. Recommendations to better approximate the temporal distribution of spawning in hatchery operations and randomize selection of brood fish are feasible. Guidelines to modify rearing and distribution procedures face some logistic constraints. An evaluation of genetic diversity of hatchery-produced fish during 2008 demonstrated variable success representing genetic variation of the source population. Continued evaluation of hatchery operations will optimize operational efficiency while moving toward genetic conservation goals.

  13. Management of insect pests: Nuclear and related molecular and genetic techniques

    International Nuclear Information System (INIS)

    1993-01-01

    The conference was organized in eight sessions: opening, genetic engineering and molecular biology, genetics, operational programmes, F 1 sterility and insect behaviour, biocontrol, research and development on the tsetse fly, and quarantine. The 64 individual contributions have been indexed separately for INIS. Refs, figs and tabs

  14. Recognizing and Managing Complexity: Teaching Advanced Programming Concepts and Techniques Using the Zebra Puzzle

    Science.gov (United States)

    Crabtree, John; Zhang, Xihui

    2015-01-01

    Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We…

  15. Monthly streamflow forecasting using continuous wavelet and multi-gene genetic programming combination

    Science.gov (United States)

    Hadi, Sinan Jasim; Tombul, Mustafa

    2018-06-01

    Streamflow is an essential component of the hydrologic cycle in the regional and global scale and the main source of fresh water supply. It is highly associated with natural disasters, such as droughts and floods. Therefore, accurate streamflow forecasting is essential. Forecasting streamflow in general and monthly streamflow in particular is a complex process that cannot be handled by data-driven models (DDMs) only and requires pre-processing. Wavelet transformation is a pre-processing technique; however, application of continuous wavelet transformation (CWT) produces many scales that cause deterioration in the performance of any DDM because of the high number of redundant variables. This study proposes multigene genetic programming (MGGP) as a selection tool. After the CWT analysis, it selects important scales to be imposed into the artificial neural network (ANN). A basin located in the southeast of Turkey is selected as case study to prove the forecasting ability of the proposed model. One month ahead downstream flow is used as output, and downstream flow, upstream, rainfall, temperature, and potential evapotranspiration with associated lags are used as inputs. Before modeling, wavelet coherence transformation (WCT) analysis was conducted to analyze the relationship between variables in the time-frequency domain. Several combinations were developed to investigate the effect of the variables on streamflow forecasting. The results indicated a high localized correlation between the streamflow and other variables, especially the upstream. In the models of the standalone layout where the data were entered to ANN and MGGP without CWT, the performance is found poor. In the best-scale layout, where the best scale of the CWT identified as the highest correlated scale is chosen and enters to ANN and MGGP, the performance increased slightly. Using the proposed model, the performance improved dramatically particularly in forecasting the peak values because of the inclusion

  16. Detonation of high explosives in Lagrangian hydrodynamic codes using the programmed burn technique

    International Nuclear Information System (INIS)

    Berger, M.E.

    1975-09-01

    Two initiation methods were developed for improving the programmed burn technique for detonation of high explosives in smeared-shock Lagrangian hydrodynamic codes. The methods are verified by comparing the improved programmed burn with existing solutions in one-dimensional plane, converging, and diverging geometries. Deficiencies in the standard programmed burn are described. One of the initiation methods has been determined to be better for inclusion in production hydrodynamic codes

  17. Towards ABET accreditation for a SWE program: alternative student assessment techniques

    International Nuclear Information System (INIS)

    Alghamdi, A.; Nasir, M.; Alnafjan, K.

    2011-01-01

    This paper describes assessment techniques utilized for assessing undergraduate students studying in a software engineering program. The purpose behind this work is to get the program accredited by the Accreditation Board of Engineering and Technology (ABET). Therefore, a number of applied direct and indirect assessment techniques are described. These techniques are implemented towards the end of the semester to assess the extent to which the student and course outcomes are satisfied. Consequently, results are obtained and analyzed and various learning issues are eventually identified. Finally, the paper provides suggestions for improvement in course delivery as well as learning mechanism. (author)

  18. Simplification of genotyping techniques of the ABO blood type experiment and exploration of population genetics.

    Science.gov (United States)

    Hu, Jian; Zhou, Yi-ren; Ding, Jia-lin; Wang, Zhi-yuan; Liu, Ling; Wang, Ye-kai; Lou, Hui-ling; Qiao, Shou-yi; Wu, Yan-hua

    2017-05-20

    The ABO blood type is one of the most common and widely used genetic traits in humans. Three glycosyltransferase-encoding gene alleles, I A , I B and i, produce three red blood cell surface antigens, by which the ABO blood type is classified. By using the ABO blood type experiment as an ideal case for genetics teaching, we can easily introduce to the students several genetic concepts, including multiple alleles, gene interaction, single nucleotide polymorphism (SNP) and gene evolution. Herein we have innovated and integrated our ABO blood type genetics experiments. First, in the section of Molecular Genetics, a new method of ABO blood genotyping was established: specific primers based on SNP sites were designed to distinguish three alleles through quantitative real-time PCR. Next, the experimental teaching method of Gene Evolution was innovated in the Population Genetics section: a gene-evolution software was developed to simulate the evolutionary tendency of the ABO genotype encoding alleles under diverse conditions. Our reform aims to extend the contents of genetics experiments, to provide additional teaching approaches, and to improve the learning efficiency of our students eventually.

  19. Research on non-uniform strain profile reconstruction along fiber Bragg grating via genetic programming algorithm and interrelated experimental verification

    Science.gov (United States)

    Zheng, Shijie; Zhang, Nan; Xia, Yanjun; Wang, Hongtao

    2014-03-01

    A new heuristic strategy for the non-uniform strain profile reconstruction along Fiber Bragg Gratings is proposed in this paper, which is based on the modified transfer matrix and Genetic Programming(GP) algorithm. The present method uses Genetic Programming to determine the applied strain field as a function of position along the fiber length. The structures that undergo adaptation in genetic programming are hierarchical structures which are different from that of conventional genetic algorithm operating on strings. GP regress the strain profile function which matches the 'measured' spectrum best and makes space resolution of strain reconstruction arbitrarily high, or even infinite. This paper also presents an experimental verification of the reconstruction of non-homogeneous strain fields using GP. The results are compared with numerical calculations of finite element method. Both the simulation examples and experimental results demonstrate that Genetic Programming can effectively reconstruct continuous profile expression along the whole FBG, and greatly improves its computational efficiency and accuracy.

  20. An integrated biochemistry and genetics outreach program designed for elementary school students.

    Science.gov (United States)

    Ross, Eric D; Lee, Sarah K; Radebaugh, Catherine A; Stargell, Laurie A

    2012-02-01

    Exposure to genetic and biochemical experiments typically occurs late in one's academic career. By the time students have the opportunity to select specialized courses in these areas, many have already developed negative attitudes toward the sciences. Given little or no direct experience with the fields of genetics and biochemistry, it is likely that many young people rule these out as potential areas of study or career path. To address this problem, we developed a 7-week (~1 hr/week) hands-on course to introduce fifth grade students to basic concepts in genetics and biochemistry. These young students performed a series of investigations (ranging from examining phenotypic variation, in vitro enzymatic assays, and yeast genetic experiments) to explore scientific reasoning through direct experimentation. Despite the challenging material, the vast majority of students successfully completed each experiment, and most students reported that the experience increased their interest in science. Additionally, the experiments within the 7-week program are easily performed by instructors with basic skills in biological sciences. As such, this program can be implemented by others motivated to achieve a broader impact by increasing the accessibility of their university and communicating to a young audience a positive impression of the sciences and the potential for science as a career.

  1. Mitigation of inbreeding while preserving genetic gain in genomic breeding programs for outbred plants.

    Science.gov (United States)

    Lin, Zibei; Shi, Fan; Hayes, Ben J; Daetwyler, Hans D

    2017-05-01

    Heuristic genomic inbreeding controls reduce inbreeding in genomic breeding schemes without reducing genetic gain. Genomic selection is increasingly being implemented in plant breeding programs to accelerate genetic gain of economically important traits. However, it may cause significant loss of genetic diversity when compared with traditional schemes using phenotypic selection. We propose heuristic strategies to control the rate of inbreeding in outbred plants, which can be categorised into three types: controls during mate allocation, during selection, and simultaneous selection and mate allocation. The proposed mate allocation measure GminF allocates two or more parents for mating in mating groups that minimise coancestry using a genomic relationship matrix. Two types of relationship-adjusted genomic breeding values for parent selection candidates ([Formula: see text]) and potential offspring ([Formula: see text]) are devised to control inbreeding during selection and even enabling simultaneous selection and mate allocation. These strategies were tested in a case study using a simulated perennial ryegrass breeding scheme. As compared to the genomic selection scheme without controls, all proposed strategies could significantly decrease inbreeding while achieving comparable genetic gain. In particular, the scenario using [Formula: see text] in simultaneous selection and mate allocation reduced inbreeding to one-third of the original genomic selection scheme. The proposed strategies are readily applicable in any outbred plant breeding program.

  2. Epileptic MEG Spike Detection Using Statistical Features and Genetic Programming with KNN

    Directory of Open Access Journals (Sweden)

    Turky N. Alotaiby

    2017-01-01

    Full Text Available Epilepsy is a neurological disorder that affects millions of people worldwide. Monitoring the brain activities and identifying the seizure source which starts with spike detection are important steps for epilepsy treatment. Magnetoencephalography (MEG is an emerging epileptic diagnostic tool with high-density sensors; this makes manual analysis a challenging task due to the vast amount of MEG data. This paper explores the use of eight statistical features and genetic programing (GP with the K-nearest neighbor (KNN for interictal spike detection. The proposed method is comprised of three stages: preprocessing, genetic programming-based feature generation, and classification. The effectiveness of the proposed approach has been evaluated using real MEG data obtained from 28 epileptic patients. It has achieved a 91.75% average sensitivity and 92.99% average specificity.

  3. Extracting classification rules from an informatic security incidents repository by genetic programming

    Directory of Open Access Journals (Sweden)

    Carlos Javier Carvajal Montealegre

    2015-04-01

    Full Text Available This paper describes the data mining process to obtain classification rules over an information security incident data collection, explaining in detail the use of genetic programming as a mean to model the incidents behavior and representing such rules as decision trees. The described mining process includes several tasks, such as the GP (Genetic Programming approach evaluation, the individual's representation and the algorithm parameters tuning to upgrade the performance. The paper concludes with the result analysis and the description of the rules obtained, suggesting measures to avoid the occurrence of new informatics attacks. This paper is a part of the thesis work degree: Information Security Incident Analytics by Data Mining for Behavioral Modeling and Pattern Recognition (Carvajal, 2012.

  4. The use of genetic programming to develop a predictor of swash excursion on sandy beaches

    OpenAIRE

    M. Passarella; E. B. Goldstein; S. De Muro; G. Coco

    2018-01-01

    We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared ...

  5. New technique for global solar radiation forecasting by simulated annealing and genetic algorithms using

    International Nuclear Information System (INIS)

    Tolabi, H.B.; Ayob, S.M.

    2014-01-01

    In this paper, a novel approach based on simulated annealing algorithm as a meta-heuristic method is implemented in MATLAB software to estimate the monthly average daily global solar radiation on a horizontal surface for six different climate cities of Iran. A search method based on genetic algorithm is applied to accelerate problem solving. Results show that simulated annealing based on genetic algorithm search is a suitable method to find the global solar radiation. (author)

  6. DNA Fingerprinting Techniques for the Analysis of Genetic and Epigenetic Alterations in Colorectal Cancer

    OpenAIRE

    Samuelsson, Johanna K.; Alonso, Sergio; Yamamoto, Fumiichiro; Perucho, Manuel

    2010-01-01

    Genetic somatic alterations are fundamental hallmarks of cancer. In addition to point and other small mutations targeting cancer genes, solid tumors often exhibit aneuploidy as well as multiple chromosomal rearrangements of large fragments of the genome. Whether somatic chromosomal alterations and aneuploidy are a driving force or a mere consequence of tumorigenesis remains controversial. Recently it became apparent that not only genetic but also epigenetic alterations play a major role in ca...

  7. Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

    Science.gov (United States)

    Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.

    2018-03-01

    Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.

  8. Empirical study of self-configuring genetic programming algorithm performance and behaviour

    International Nuclear Information System (INIS)

    KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" data-affiliation=" (Siberian State Aerospace University named after Academician M.F. Reshetnev 31 KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" >Semenkin, E; KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" data-affiliation=" (Siberian State Aerospace University named after Academician M.F. Reshetnev 31 KrasnoyarskiyRabochiy prospect, Krasnoyarsk, 660014 (Russian Federation))" >Semenkina, M

    2015-01-01

    The behaviour of the self-configuring genetic programming algorithm with a modified uniform crossover operator that implements a selective pressure on the recombination stage, is studied over symbolic programming problems. The operator's probabilistic rates interplay is studied and the role of operator variants on algorithm performance is investigated. Algorithm modifications based on the results of investigations are suggested. The performance improvement of the algorithm is demonstrated by the comparative analysis of suggested algorithms on the benchmark and real world problems

  9. Studies of Genetic Differences between KDML 105 and its Photo period-insensitive Mutants using DNA techniques

    International Nuclear Information System (INIS)

    Boonsirichai, Kanokporn; Klakhaeng, Kanchana; Phadvibulya, Valailak

    2007-08-01

    Full text: Photo period-insensitive mutants of KDML 105 could be planted for grains during and outside the regular cropping season. From genetic studies, the mutant characteristics appeared recessive. A DNA-fingerprinting technique was used to compare gene expression profiles in the leaves of mutants and KDML 105. Differences in the level of expression were found for several loci. Examination of the essential part of the gene for fragrance showed no differences between the mutants and the parental KDML 105

  10. A High Precision Comprehensive Evaluation Method for Flood Disaster Loss Based on Improved Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    ZHOU Yuliang; LU Guihua; JIN Juliang; TONG Fang; ZHOU Ping

    2006-01-01

    Precise comprehensive evaluation of flood disaster loss is significant for the prevention and mitigation of flood disasters. Here, one of the difficulties involved is how to establish a model capable of describing the complex relation between the input and output data of the system of flood disaster loss. Genetic programming (GP) solves problems by using ideas from genetic algorithm and generates computer programs automatically. In this study a new method named the evaluation of the grade of flood disaster loss (EGFD) on the basis of improved genetic programming (IGP) is presented (IGPEGFD). The flood disaster area and the direct economic loss are taken as the evaluation indexes of flood disaster loss. Obviously that the larger the evaluation index value, the larger the corresponding value of the grade of flood disaster loss is. Consequently the IGP code is designed to make the value of the grade of flood disaster be an increasing function of the index value. The result of the application of the IGP-EGFD model to Henan Province shows that a good function expression can be obtained within a bigger searched function space; and the model is of high precision and considerable practical significance.Thus, IGP-EGFD can be widely used in automatic modeling and other evaluation systems.

  11. Modeling the Isentropic Head Value of Centrifugal Gas Compressor using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Safiyullah Ferozkhan

    2016-01-01

    Full Text Available Gas compressor performance is vital in oil and gas industry because of the equipment criticality which requires continuous operations. Plant operators often face difficulties in predicting appropriate time for maintenance and would usually rely on time based predictive maintenance intervals as recommended by original equipment manufacturer (OEM. The objective of this work is to develop the computational model to find the isentropic head value using genetic programming. The isentropic head value is calculated from the OEM performance chart. Inlet mass flow rate and speed of the compressor are taken as the input value. The obtained results from the GP computational models show good agreement with experimental and target data with the average prediction error of 1.318%. The genetic programming computational model will assist machinery engineers to quantify performance deterioration of gas compressor and the results from this study will be then utilized to estimate future maintenance requirements based on the historical data. In general, this genetic programming modelling provides a powerful solution for gas compressor operators to realize predictive maintenance approach in their operations.

  12. Designing a Web Spam Classifier Based on Feature Fusion in the Layered Multi-Population Genetic Programming Framework

    Directory of Open Access Journals (Sweden)

    Amir Hosein KEYHANIPOUR

    2013-11-01

    Full Text Available Nowadays, Web spam pages are a critical challenge for Web retrieval systems which have drastic influence on the performance of such systems. Although these systems try to combat the impact of spam pages on their final results list, spammers increasingly use more sophisticated techniques to increase the number of views for their intended pages in order to have more commercial success. This paper employs the recently proposed Layered Multi-population Genetic Programming model for Web spam detection task as well application of correlation coefficient analysis for feature space reduction. Based on our tentative results, the designed classifier, which is based on a combination of easy to compute features, has a very reasonable performance in comparison with similar methods.

  13. Including nonadditive genetic effects in mating programs to maximize dairy farm profitability.

    Science.gov (United States)

    Aliloo, H; Pryce, J E; González-Recio, O; Cocks, B G; Goddard, M E; Hayes, B J

    2017-02-01

    We compared the outcome of mating programs based on different evaluation models that included nonadditive genetic effects (dominance and heterozygosity) in addition to additive effects. The additive and dominance marker effects and the values of regression on average heterozygosity were estimated using 632,003 single nucleotide polymorphisms from 7,902 and 7,510 Holstein cows with calving interval and production (milk, fat, and protein yields) records, respectively. Expected progeny values were computed based on the estimated genetic effects and genotype probabilities of hypothetical progeny from matings between the available genotyped cows and the top 50 young genomic bulls. An index combining the traits based on their economic values was developed and used to evaluate the performance of different mating scenarios in terms of dollar profit. We observed that mating programs with nonadditive genetic effects performed better than a model with only additive effects. Mating programs with dominance and heterozygosity effects increased milk, fat, and protein yields by up to 38, 1.57, and 1.21 kg, respectively. The inclusion of dominance and heterozygosity effects decreased calving interval by up to 0.70 d compared with random mating. The average reduction in progeny inbreeding by the inclusion of nonadditive genetic effects in matings compared with random mating was between 0.25 to 1.57 and 0.64 to 1.57 percentage points for calving interval and production traits, respectively. The reduction in inbreeding was accompanied by an average of A$8.42 (Australian dollars) more profit per mating for a model with additive, dominance, and heterozygosity effects compared with random mating. Mate allocations that benefit from nonadditive genetic effects can improve progeny performance only in the generation where it is being implemented, and the gain from specific combining abilities cannot be accumulated over generations. Continuous updating of genomic predictions and mate

  14. Genetic Manipulation of NK Cells for Cancer Immunotherapy: Techniques and Clinical Implications.

    Science.gov (United States)

    Carlsten, Mattias; Childs, Richard W

    2015-01-01

    Given their rapid and efficient capacity to recognize and kill tumor cells, natural killer (NK) cells represent a unique immune cell to genetically reprogram in an effort to improve the outcome of cell-based cancer immunotherapy. However, technical and biological challenges associated with gene delivery into NK cells have significantly tempered this approach. Recent advances in viral transduction and electroporation have now allowed detailed characterization of genetically modified NK cells and provided a better understanding for how these cells can be utilized in the clinic to optimize their capacity to induce tumor regression in vivo. Improving NK cell persistence in vivo via autocrine IL-2 and IL-15 stimulation, enhancing tumor targeting by silencing inhibitory NK cell receptors such as NKG2A, and redirecting tumor killing via chimeric antigen receptors, all represent approaches that hold promise in preclinical studies. This review focuses on available methods for genetic reprograming of NK cells and the advantages and challenges associated with each method. It also gives an overview of strategies for genetic reprograming of NK cells that have been evaluated to date and an outlook on how these strategies may be best utilized in clinical protocols. With the recent advances in our understanding of the complex biological networks that regulate the ability of NK cells to target and kill tumors in vivo, we foresee genetic engineering as an obligatory pathway required to exploit the full potential of NK-cell based immunotherapy in the clinic.

  15. Genetics

    International Nuclear Information System (INIS)

    Hubitschek, H.E.

    1975-01-01

    Progress is reported on the following research projects: genetic effects of high LET radiations; genetic regulation, alteration, and repair; chromosome replication and the division cycle of Escherichia coli; effects of radioisotope decay in the DNA of microorganisms; initiation and termination of DNA replication in Bacillus subtilis; mutagenesis in mouse myeloma cells; lethal and mutagenic effects of near-uv radiation; effect of 8-methoxypsoralen on photodynamic lethality and mutagenicity in Escherichia coli; DNA repair of the lethal effects of far-uv; and near uv irradiation of bacterial cells

  16. Development of a Temperature Programmed Identification Technique to Characterize the Organic Sulphur Functional Groups in Coal

    Directory of Open Access Journals (Sweden)

    Moinuddin Ghauri

    2017-06-01

    Full Text Available The Temperature Programmed Reduction (TPR technique is employed for the characterisation of various organic sulphur functional groups in coal. The TPR technique is modified into the Temperature Programmed Identification technique to investigate whether this method can detect various functional groups corresponding to their reduction temperatures. Ollerton, Harworth, Silverdale, Prince of Wales coal and Mequinenza lignite were chosen for this study. High pressure oxydesulphurisation of the coal samples was also done. The characterization of various organic sulphur functional groups present in untreated and treated coal by the TPR method and later by the TPI method confirmed that these methods can identify the organic sulphur groups in coal and that the results based on total sulphur are comparable with those provided by standard analytical techniques. The analysis of the untreated and treated coal samples showed that the structural changes in the organic sulphur matrix due to a reaction can be determined.

  17. Genetics

    DEFF Research Database (Denmark)

    Christensen, Kaare; McGue, Matt

    2016-01-01

    The sequenced genomes of individuals aged ≥80 years, who were highly educated, self-referred volunteers and with no self-reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect...

  18. Application gives the technique the analytic tree in the evaluation the effectiveness programs to radiological protection

    International Nuclear Information System (INIS)

    Perez Gonzalez, F.; Perez Velazquez, R.S.; Fornet Rodriguez, O.; Mustelier Hechevarria, A.; Miller Clemente, A.

    1998-01-01

    In the work we develop the IAEA recommendations in the application the analytic tree as instrument for the evaluation the effectiveness the occupational radiological protection programs. Is reflected like it has been assimilated and converted that technique in daily work istruments in the evaluation process the security conditions in the institutions that apply the nuclear techniques with a view to its autorization on the part of the regulatory organ

  19. Implementation of the program for conservation and sustainable utilization of forest genetic resources in Republic of Serbia

    Directory of Open Access Journals (Sweden)

    Šijačić-Nikolić Mirjana

    2017-01-01

    Full Text Available Program for conservation and sustainable utilization of forest genetic resources has been defined for 2016-2025 period and it is a base for concrete activities in this field. This Program could be divided into several parts that deal with: the legal framework for the conservation and sustainable utilization of forest genetic resources; status of forest genetic resources in Serbia; previous activities on the conservation of forest genetic resources; and objectives, priorities and measures of conservation. The Program should have an impact on the development of the forestry sector through the following activities: conservation and sustainable utilization of the available gene pool; improving forest management in accordance with conservation principles; improving the production of reproductive material of forest trees; make the public awareness of the need for conservation and sustainable utilization of forest genetic resources; fulfillment of international obligations related to this field and the possibility of joining FAO activities related to forest genetic resources - development of the national report as a part of the publication The State of the World's Forest Genetic Resources. Implementation of the Program will depend upon raising the awareness on the importance, conservation and sustainable utilization of forest genetic resources, as a precondition for the forests survival; it will depend of funds that will be allocated for this purpose and enthusiasm of people who deal with these issues.

  20. Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data

    DEFF Research Database (Denmark)

    Dounias, George; Tsakonas, Athanasios; Jantzen, Jan

    2002-01-01

    This paper demonstrates two methodologies for the construction of rule-based systems in medical decision making. The first approach consists of a method combining genetic programming and heuristic hierarchical rule-base construction. The second model is composed by a strongly-typed genetic...

  1. Genetic evaluation of reproductive potential in the Zatorska goose under a conservation program.

    Science.gov (United States)

    Graczyk, Magdalena; Andres, Krzysztof; Kapkowska, Ewa; Szwaczkowski, Tomasz

    2018-05-01

    The aim of this study was to estimate the genetic parameters and inbreeding effect on the fertility, embryo mortality and hatchability traits in the Zatorska goose covered by the animal genetic resources conservation program. The material for this study contains information about results of hatching of 18 863 eggs from 721 dams and 168 sires, laid between 1998-2015. Genetic parameters were estimated based on the threshold animal model by the use of Restricted Maximum Likelihood and Gibbs sampling. The percentage of fertilized eggs ranged yearly between 37-80%. The percentage of embryo mortality was very low, ranging between 4.63-23.73%. The percentage of the hatched goslings from the total number of analyzed eggs was on average 33.18%, and 53.72% from fertilized eggs. On average based on both methods, the heritability estimates of the fertility, embryo mortality and hatchability reached 0.36, 0.07, 0.24 for males and 0.44, 0.11, 0.32 for females. The genetic trend had increasing tendency for fertility and hatchability and was stable for embryo mortality for both sexes. The obtained result shows that the Zatorska goose can be still maintained in the reserves of the local gene pool according to current rules and use in the local market as a breed with good reproductive potential. © 2018 Japanese Society of Animal Science.

  2. Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming

    Science.gov (United States)

    Devra, Amit; Prabhu, Prithviraj; Singh, Harpreet; Arvind; Dorai, Kavita

    2018-03-01

    We have designed efficient quantum circuits for the three-qubit Toffoli (controlled-controlled-NOT) and the Fredkin (controlled-SWAP) gate, optimized via genetic programming methods. The gates thus obtained were experimentally implemented on a three-qubit NMR quantum information processor, with a high fidelity. Toffoli and Fredkin gates in conjunction with the single-qubit Hadamard gates form a universal gate set for quantum computing and are an essential component of several quantum algorithms. Genetic algorithms are stochastic search algorithms based on the logic of natural selection and biological genetics and have been widely used for quantum information processing applications. We devised a new selection mechanism within the genetic algorithm framework to select individuals from a population. We call this mechanism the "Luck-Choose" mechanism and were able to achieve faster convergence to a solution using this mechanism, as compared to existing selection mechanisms. The optimization was performed under the constraint that the experimentally implemented pulses are of short duration and can be implemented with high fidelity. We demonstrate the advantage of our pulse sequences by comparing our results with existing experimental schemes and other numerical optimization methods.

  3. A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

    Directory of Open Access Journals (Sweden)

    David Lennartsson

    2004-01-01

    Full Text Available A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

  4. The use of PCR techniques to detect genetic variations in Cassava (Manihot esculenta L. Crantz): minisatellite and RAPD analysis

    International Nuclear Information System (INIS)

    Pawlicki, N.; Sangwan, R.S.; Sangwan-Norreel, B.; Koffi Konan, N.

    1998-01-01

    Cassava is an important tuber crop grown in the tropical and subtropical regions. Recently, we developed protocols for efficient somatic embryogenesis using zygotic embryos and nodal axillary meristems in order to reduce the genotype effect. Thereafter flow cytophotometry and randomly amplified polymorphic DNA (RAPD) markers were used to assess the ploidy level and the genetic fidelity of cassava plants regenerated by somatic embryogenesis. No change in the ploidy level of the regenerated plants was observed in comparison with the control plants. In the same way, monomorphic profiles of RAPD were obtained for the different cassava plants regenerated by somatic embryogenesis. The genetic analysis of calli showed only a few differences. Using two pairs of heterologous micro satellite primers developed in a wild African grass, a monomorphic pattern was also detected. Moreover, cultivars of different origins were also analysed using these PCR techniques. Our data from RAPD and materialistic analyses suggested that these techniques can be efficiently used to detect genetic variations in cassava. (author)

  5. Transference of microsatellite markers from Eucalyptus spp to Acca sellowiana and the successful use of this technique in genetic characterization

    Directory of Open Access Journals (Sweden)

    Karine Louise dos Santos

    2007-01-01

    Full Text Available The pineapple guava (Acca sellowiana, known in portuguese as the goiabeira-serrana or "Feijoa", is a native fruit tree from southern Brazil and northern Uruguay that has commercial potential due to the quality and unique flavor of its fruits. Knowledge of genetic variability is an important tool in various steps of a breeding program, which can be facilitated by the use of molecular markers. The conservation of repeated sequences among related species permits the transferability of microsatellite markers from Eucalyptus spp. to A. sellowiana for testing. We used primers developed for Eucalyptus to characterize A. sellowiana accessions. Out of 404 primers tested, 180 amplified visible products and 38 were polymorphic. A total of 48 alleles were detected with ten Eucalyptus primer pairs against DNA from 119 A. sellowiana accessions. The mean expected heterozygosity among accessions was 0.64 and the mean observed heterozygosity 0.55. A high level of genetic diversity was also observed in the dendrogram, where the degree of genetic dissimilarity ranged from 0 to 65% among the 119 genotypes tested. This study demonstrates the possibility of transferring microsatellite markers between species of different genera in addition to evaluating the extent of genetic variability among plant accessions.

  6. Fast implementations of 3D PET reconstruction using vector and parallel programming techniques

    International Nuclear Information System (INIS)

    Guerrero, T.M.; Cherry, S.R.; Dahlbom, M.; Ricci, A.R.; Hoffman, E.J.

    1993-01-01

    Computationally intensive techniques that offer potential clinical use have arisen in nuclear medicine. Examples include iterative reconstruction, 3D PET data acquisition and reconstruction, and 3D image volume manipulation including image registration. One obstacle in achieving clinical acceptance of these techniques is the computational time required. This study focuses on methods to reduce the computation time for 3D PET reconstruction through the use of fast computer hardware, vector and parallel programming techniques, and algorithm optimization. The strengths and weaknesses of i860 microprocessor based workstation accelerator boards are investigated in implementations of 3D PET reconstruction

  7. PhyloGeoViz: a web-based program that visualizes genetic data on maps.

    Science.gov (United States)

    Tsai, Yi-Hsin E

    2011-05-01

    The first step of many population genetic studies is the simple visualization of allele frequencies on a landscape. This basic data exploration can be challenging without proprietary software, and the manual plotting of data is cumbersome and unfeasible at large sample sizes. I present an open source, web-based program that plots any kind of frequency or count data as pie charts in Google Maps (Google Inc., Mountain View, CA). Pie polygons are then exportable to Google Earth (Google Inc.), a free Geographic Information Systems platform. Import of genetic data into Google Earth allows phylogeographers access to a wealth of spatial information layers integral to forming hypotheses and understanding patterns in the data. © 2010 Blackwell Publishing Ltd.

  8. Experimental program for development and evaluation of nondestructive assay techniques for plutonium holdup

    International Nuclear Information System (INIS)

    Brumbach, S.B.

    1977-05-01

    An outline is presented for an experimental program to develop and evaluate nondestructive assay techniques applicable to holdup measurement in plutonium-containing fuel fabrication facilities. The current state-of-the-art in holdup measurements is reviewed. Various aspects of the fuel fabrication process and the fabrication facility are considered for their potential impact on holdup measurements. The measurement techniques considered are those using gamma-ray counting, neutron counting, and temperature measurement. The advantages and disadvantages of each technique are discussed. Potential difficulties in applying the techniques to holdup measurement are identified. Experiments are proposed to determine the effects of such problems as variation in sample thickness, in sample distribution, and in background radiation. These experiments are also directed toward identification of techniques most appropriate to various applications. Also proposed are experiments to quantify the uncertainties expected for each measurement

  9. DNAStat, version 2.1--a computer program for processing genetic profile databases and biostatistical calculations.

    Science.gov (United States)

    Berent, Jarosław

    2010-01-01

    This paper presents the new DNAStat version 2.1 for processing genetic profile databases and biostatistical calculations. The popularization of DNA studies employed in the judicial system has led to the necessity of developing appropriate computer programs. Such programs must, above all, address two critical problems, i.e. the broadly understood data processing and data storage, and biostatistical calculations. Moreover, in case of terrorist attacks and mass natural disasters, the ability to identify victims by searching related individuals is very important. DNAStat version 2.1 is an adequate program for such purposes. The DNAStat version 1.0 was launched in 2005. In 2006, the program was updated to 1.1 and 1.2 versions. There were, however, slight differences between those versions and the original one. The DNAStat version 2.0 was launched in 2007 and the major program improvement was an introduction of the group calculation options with the potential application to personal identification of mass disasters and terrorism victims. The last 2.1 version has the option of language selection--Polish or English, which will enhance the usage and application of the program also in other countries.

  10. A Computer Program for Simplifying Incompletely Specified Sequential Machines Using the Paull and Unger Technique

    Science.gov (United States)

    Ebersole, M. M.; Lecoq, P. E.

    1968-01-01

    This report presents a description of a computer program mechanized to perform the Paull and Unger process of simplifying incompletely specified sequential machines. An understanding of the process, as given in Ref. 3, is a prerequisite to the use of the techniques presented in this report. This process has specific application in the design of asynchronous digital machines and was used in the design of operational support equipment for the Mariner 1966 central computer and sequencer. A typical sequential machine design problem is presented to show where the Paull and Unger process has application. A description of the Paull and Unger process together with a description of the computer algorithms used to develop the program mechanization are presented. Several examples are used to clarify the Paull and Unger process and the computer algorithms. Program flow diagrams, program listings, and a program user operating procedures are included as appendixes.

  11. Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

    Science.gov (United States)

    Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

  12. Affirmative Action. Module Number 16. Work Experience Program Modules. Coordination Techniques Series.

    Science.gov (United States)

    Shawhan, Carl; Morley, Ray

    This self-instructional module, the last in a series of 16 on techniques for coordinating work experience programs, deals with affirmative action. Addressed in the module are the following topics: the nature of affirmative action legislation and regulations, the role of the teacher-coordinator as a resource person for affirmative action…

  13. Using GPS instruments and GIS techniques in data management for insect pest control programs

    International Nuclear Information System (INIS)

    2006-01-01

    This interactive tutorial CD entitled 'Using GPS Instruments and GIS Techniques in Data Management for Insect Pest Control Programs' was developed by Micha silver of the Arava Development Co., Sapir, Israel, and includes step-by-step hands on lessons on the use of GPS/GIS in support of area-wide pest control operations

  14. Development of new techniques of using irradiation in the genetic improvement of warm season grasses and an assessment of the genetic and cytogenetic effects. Annual report, August 1, 1976--October 31, 1977

    International Nuclear Information System (INIS)

    Burton, G.W.; Hanna, W.W.

    1977-08-01

    New techniques of using irradiation in the genetic improvement of several warm season grasses are described. The economic value of radiation induced plant mutants and the genetic and cytogenetic effects of these treatments are discussed. Alterations in protein quality in pearl millet grain and improved varieties of Bermuda grass following radiation treatment are reported

  15. Genetic Characterization Of Syrian Erwinia Amylovora Strains By Amplified Fragment Length Polymorphism Technique

    International Nuclear Information System (INIS)

    Ammouneh, H.; Arabi, M.; Shoaib, A.

    2011-01-01

    Thirty Erwinia amylovora strains, collected from the main rosaceous crop-growing regions in Syria, were chosen as representatives of all major pathogenicity groups and were genetically studied by AFLP. Eight primer combinations were utilized and approximately 300 scorable bands in total were generated. Based on similarity coefficient, E. amylovora strains were placed into a main cluster containing two sub clusters, indicating very low genetic variations among the studied pathogen. The existence of two plasmids, pEA29 (present in nearly all E. amylovora isolates) and pEL60 (present mainly in Lebanese strains), was confirmed using multiplex PCR in all tested Syrian E. amylovora strains, indicating that Lebanese and Syrian isolates may share a common origin.(author)

  16. Chickpea and cowpea grain improvement using mutation and other advanced genetic techniques

    Energy Technology Data Exchange (ETDEWEB)

    Filippone, E; Monti, L [Department of Agronomy and Plant Genetics, Univ. of Naples Federico 2, Naples (Italy)

    1997-12-01

    The use of genetic engineering methodologies in breeding programmes seems to be very promising to find new resistance-related genes present in other phyla, to clone and transfer them into plants; and, to shorten the time to obtain an improved genotype since only a single gene is involved in this process. The main ``bottle-neck`` to apply this scheme in chickpea and cowpea is the absence of a reliable protocol of regeneration and genetic transformation. In this frame, following some pilot experiments on these grain legumes to induce regeneration and gene transfer, we attempted to find a regeneration medium, assay the effect of different hormones on young tissues; and, to select the best procedures for transfer of genes into the plant genome.

  17. Increasing the genetic variance of rice protein through mutation breeding techniques

    International Nuclear Information System (INIS)

    Ismachin, M.

    1975-01-01

    Recommended rice variety in Indonesia, Pelita I/1 was treated with gamma rays at the doses of 20 krad, 30 krad, and 40 krad. The seeds were also treated with EMS 1%. In M 2 generation, the protein content of seeds from the visible mutants and from the normal looking plants were analyzed by DBC method. No significant increase in the genetic variance was found on the samples treated with 20 krad gamma, and on the normal looking plants treated by EMS 1%. The mean value of the treated samples were mostly significant decrease compared with the mean value of the protein distribution in untreated samples (control). Since significant increase in genetic variance was also found in M 2 normal looking plants - treated with gamma at the doses of 30 krad and 40 krad -selection of protein among these materials could be more valuable. (author)

  18. Chickpea and cowpea grain improvement using mutation and other advanced genetic techniques

    International Nuclear Information System (INIS)

    Filippone, E.; Monti, L.

    1997-01-01

    The use of genetic engineering methodologies in breeding programmes seems to be very promising to find new resistance-related genes present in other phyla, to clone and transfer them into plants; and, to shorten the time to obtain an improved genotype since only a single gene is involved in this process. The main ''bottle-neck'' to apply this scheme in chickpea and cowpea is the absence of a reliable protocol of regeneration and genetic transformation. In this frame, following some pilot experiments on these grain legumes to induce regeneration and gene transfer, we attempted to find a regeneration medium, assay the effect of different hormones on young tissues; and, to select the best procedures for transfer of genes into the plant genome

  19. Safe genetic modification of cardiac stem cells using a site-specific integration technique.

    Science.gov (United States)

    Lan, Feng; Liu, Junwei; Narsinh, Kazim H; Hu, Shijun; Han, Leng; Lee, Andrew S; Karow, Marisa; Nguyen, Patricia K; Nag, Divya; Calos, Michele P; Robbins, Robert C; Wu, Joseph C

    2012-09-11

    Human cardiac progenitor cells (hCPCs) are a promising cell source for regenerative repair after myocardial infarction. Exploitation of their full therapeutic potential may require stable genetic modification of the cells ex vivo. Safe genetic engineering of stem cells, using facile methods for site-specific integration of transgenes into known genomic contexts, would significantly enhance the overall safety and efficacy of cellular therapy in a variety of clinical contexts. We used the phiC31 site-specific recombinase to achieve targeted integration of a triple fusion reporter gene into a known chromosomal context in hCPCs and human endothelial cells. Stable expression of the reporter gene from its unique chromosomal integration site resulted in no discernible genomic instability or adverse changes in cell phenotype. Namely, phiC31-modified hCPCs were unchanged in their differentiation propensity, cellular proliferative rate, and global gene expression profile when compared with unaltered control hCPCs. Expression of the triple fusion reporter gene enabled multimodal assessment of cell fate in vitro and in vivo using fluorescence microscopy, bioluminescence imaging, and positron emission tomography. Intramyocardial transplantation of genetically modified hCPCs resulted in significant improvement in myocardial function 2 weeks after cell delivery, as assessed by echocardiography (P=0.002) and MRI (P=0.001). We also demonstrated the feasibility and therapeutic efficacy of genetically modifying differentiated human endothelial cells, which enhanced hind limb perfusion (Pmodification system is a safe, efficient tool to enable site-specific integration of reporter transgenes in progenitor and differentiated cell types.

  20. GAPscreener: An automatic tool for screening human genetic association literature in PubMed using the support vector machine technique

    Directory of Open Access Journals (Sweden)

    Khoury Muin J

    2008-04-01

    Full Text Available Abstract Background Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM, a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software tool, can be used to assist in screening PubMed abstracts for human genetic association studies. Results The data source for this research was the HuGE Navigator, formerly known as the HuGE Pub Lit database. Weighted SVM feature selection based on a keyword list obtained by the two-way z score method demonstrated the best screening performance, achieving 97.5% recall, 98.3% specificity and 31.9% precision in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the 4-week test period. We examined the literature on genetic associations with preterm birth as an example. Compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy. Conclusion GAPscreener is the first free SVM-based application available for screening the human genetic association literature in PubMed with high recall and specificity. The user-friendly graphical user interface makes this a practical, stand-alone application. The software can be downloaded at no charge.

  1. Multi-objective genetic algorithm for solving N-version program design problem

    International Nuclear Information System (INIS)

    Yamachi, Hidemi; Tsujimura, Yasuhiro; Kambayashi, Yasushi; Yamamoto, Hisashi

    2006-01-01

    N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost

  2. Multi-objective genetic algorithm for solving N-version program design problem

    Energy Technology Data Exchange (ETDEWEB)

    Yamachi, Hidemi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan) and Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamachi@nit.ac.jp; Tsujimura, Yasuhiro [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: tujimr@nit.ac.jp; Kambayashi, Yasushi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: yasushi@nit.ac.jp; Yamamoto, Hisashi [Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamamoto@cc.tmit.ac.jp

    2006-09-15

    N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost.

  3. Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass

    Directory of Open Access Journals (Sweden)

    Zibei Lin

    2016-03-01

    Full Text Available Genomic selection (GS provides an attractive option for accelerating genetic gain in perennial ryegrass ( improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time. Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot. Genomic estimated breeding values (GEBVs for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively. Higher accuracy of GEBVs was obtained for flowering time (up to 0.7, partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.

  4. Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

    Science.gov (United States)

    Lin, Zibei; Cogan, Noel O I; Pembleton, Luke W; Spangenberg, German C; Forster, John W; Hayes, Ben J; Daetwyler, Hans D

    2016-03-01

    Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass () improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy. Copyright © 2016 Crop Science Society of America.

  5. Development of programming techniques for behaviors of nuclear robot in real environment

    International Nuclear Information System (INIS)

    Tsukune, Hideo; Ogasawara, Tsukasa; Hirukawa, Hirohisa; Kitagaki, Kosei; Onda, Hiromu; Nakamura, Akira

    1999-01-01

    This study aims at establishment of synthetic autonomous technique on nuclear robot for a basic technique to realize remote control and automation of works in a nuclear plant by means of development on action programming function under actual environment. Before 1997 fiscal year, development of manipulation description system due to contact state transition series, development of mechanical assembly work instruction system using contact actuating system, development of new manipulator system with excellent controllability, development of quasi contact point monitoring method, and development of environmental model construction method using range finder and instruction tree, had been conducted. In 1997 fiscal year, probability of nuclear robot, on synthetic autonomous technique was shown by synthesis of many results on action programming planning function into a prototype system under an actual environment obtained by those developments. (G.K.)

  6. A research on applications of qualitative reasoning techniques in Human Acts Simulation Program

    International Nuclear Information System (INIS)

    Far, B.H.

    1992-04-01

    Human Acts Simulation Program (HASP) is a ten-year research project of the Computing and Information Systems Center of JAERI. In HASP the goal is developing programs for an advanced intelligent robot to accomplish multiple instructions (for instance, related to surveillance, inspection and maintenance) in nuclear power plants. Some recent artificial intelligence techniques can contribute to this project. This report introduces some original contributions concerning application of Qualitative Reasoning (QR) techniques in HASP. The focus is on the knowledge-intensive tasks, including model-based reasoning, analytic learning, fault diagnosis and functional reasoning. The multi-level extended qualitative modeling for the Skill-Rule-Knowledge (S-R-K) based reasoning, that included the coordination and timing of events, Qualitative Sensitivity analysis (Q S A), Subjective Qualitative Fault Diagnosis (S Q F D) and Qualitative Function Formation (Q F F ) techniques are introduced. (author) 123 refs

  7. Recognizing and Managing Complexity: Teaching Advanced Programming Concepts and Techniques Using the Zebra Puzzle

    Directory of Open Access Journals (Sweden)

    Xihui "Paul" Zhang

    2015-06-01

    Full Text Available Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We present a classic brain teaser that is used to communicate and demonstrate advanced software development concepts and techniques. Our results show that students with varied academic experiences and goals, assuming at least one procedural/structured programming pre-requisite, can benefit from and also be challenged by such an exercise. Although this problem has been used by others in the classroom, we believe that our use of this problem in imparting such a broad range of topics to a diverse student population is unique.

  8. Reactor Network Synthesis Using Coupled Genetic Algorithm with the Quasi-linear Programming Method

    OpenAIRE

    Soltani, H.; Shafiei, S.; Edraki, J.

    2016-01-01

    This research is an attempt to develop a new procedure for the synthesis of reactor networks (RNs) using a genetic algorithm (GA) coupled with the quasi-linear programming (LP) method. The GA is used to produce structural configuration, whereas continuous variables are handled using a quasi-LP formulation for finding the best objective function. Quasi-LP consists of LP together with a search loop to find the best reactor conversions (xi), as well as split and recycle ratios (yi). Quasi-LP rep...

  9. Genetic programming for evolving due-date assignment models in job shop environments.

    Science.gov (United States)

    Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

    2014-01-01

    Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

  10. Automatic Creation of Machine Learning Workflows with Strongly Typed Genetic Programming

    Czech Academy of Sciences Publication Activity Database

    Křen, T.; Pilát, M.; Neruda, Roman

    2017-01-01

    Roč. 26, č. 5 (2017), č. článku 1760020. ISSN 0218-2130 R&D Projects: GA ČR GA15-19877S Grant - others:GA MŠk(CZ) LM2015042 Institutional support: RVO:67985807 Keywords : genetic programming * machine learning workflows * asynchronous evolutionary algorithm Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.778, year: 2016

  11. The use of recombinant DNA techniques to study radiation-induced damage, repair and genetic change in mammalian cells

    International Nuclear Information System (INIS)

    Thacker, J.

    1986-01-01

    A brief introduction is given to appropriate elements of recombinant DNA techniques and applications to problems in radiobiology are reviewed with illustrative detail. Examples are included of studies with both 254 nm ultraviolet light and ionizing radiation and the review progresses from the molecular analysis of DNA damage in vitro through to the nature of consequent cellular responses. The review is dealt with under the following headings: Molecular distribution of DNA damage, The use of DNA-mediated gene transfer to assess damage and repair, The DNA double strand break: use of restriction endonucleases to model radiation damage, Identification and cloning of DNA repair genes, Analysis of radiation-induced genetic change. (UK)

  12. Evaluation of molecular typing techniques to assign genetic diversity among Saccharomyces cerevisiae strains

    NARCIS (Netherlands)

    Baleiras Couto, M.M.; Eijsma, B.; Hofstra, H.; Huis in 't Veld, J.H.J.; Vossen, J.M.B.M. van der

    1996-01-01

    Discrimination of strains within the species Saccharomyces cerevisiae was demonstrated by the use of four different techniques to type 15 strains isolated from spoiled wine and beer. Random amplified polymorphic DNA with specific oligonucleotides and PCR fingerprinting with the microsatellite

  13. Adaptive Test Selection for Factorization-based Surrogate Fitness in Genetic Programming

    Directory of Open Access Journals (Sweden)

    Krawiec Krzysztof

    2017-12-01

    Full Text Available Genetic programming (GP is a variant of evolutionary algorithm where the entities undergoing simulated evolution are computer programs. A fitness function in GP is usually based on a set of tests, each of which defines the desired output a correct program should return for an exemplary input. The outcomes of interactions between programs and tests in GP can be represented as an interaction matrix, with rows corresponding to programs in the current population and columns corresponding to tests. In previous work, we proposed SFIMX, a method that performs only a fraction of interactions and employs non-negative matrix factorization to estimate the outcomes of remaining ones, shortening GP’s runtime. In this paper, we build upon that work and propose three extensions of SFIMX, in which the subset of tests drawn to perform interactions is selected with respect to test difficulty. The conducted experiment indicates that the proposed extensions surpass the original SFIMX on a suite of discrete GP benchmarks.

  14. Managing complex processing of medical image sequences by program supervision techniques

    Science.gov (United States)

    Crubezy, Monica; Aubry, Florent; Moisan, Sabine; Chameroy, Virginie; Thonnat, Monique; Di Paola, Robert

    1997-05-01

    Our objective is to offer clinicians wider access to evolving medical image processing (MIP) techniques, crucial to improve assessment and quantification of physiological processes, but difficult to handle for non-specialists in MIP. Based on artificial intelligence techniques, our approach consists in the development of a knowledge-based program supervision system, automating the management of MIP libraries. It comprises a library of programs, a knowledge base capturing the expertise about programs and data and a supervision engine. It selects, organizes and executes the appropriate MIP programs given a goal to achieve and a data set, with dynamic feedback based on the results obtained. It also advises users in the development of new procedures chaining MIP programs.. We have experimented the approach for an application of factor analysis of medical image sequences as a means of predicting the response of osteosarcoma to chemotherapy, with both MRI and NM dynamic image sequences. As a result our program supervision system frees clinical end-users from performing tasks outside their competence, permitting them to concentrate on clinical issues. Therefore our approach enables a better exploitation of possibilities offered by MIP and higher quality results, both in terms of robustness and reliability.

  15. IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS

    Science.gov (United States)

    Fogle, F. R.

    1994-01-01

    IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.

  16. Internal combustion engine control for series hybrid electric vehicles by parallel and distributed genetic programming/multiobjective genetic algorithms

    Science.gov (United States)

    Gladwin, D.; Stewart, P.; Stewart, J.

    2011-02-01

    This article addresses the problem of maintaining a stable rectified DC output from the three-phase AC generator in a series-hybrid vehicle powertrain. The series-hybrid prime power source generally comprises an internal combustion (IC) engine driving a three-phase permanent magnet generator whose output is rectified to DC. A recent development has been to control the engine/generator combination by an electronically actuated throttle. This system can be represented as a nonlinear system with significant time delay. Previously, voltage control of the generator output has been achieved by model predictive methods such as the Smith Predictor. These methods rely on the incorporation of an accurate system model and time delay into the control algorithm, with a consequent increase in computational complexity in the real-time controller, and as a necessity relies to some extent on the accuracy of the models. Two complementary performance objectives exist for the control system. Firstly, to maintain the IC engine at its optimal operating point, and secondly, to supply a stable DC supply to the traction drive inverters. Achievement of these goals minimises the transient energy storage requirements at the DC link, with a consequent reduction in both weight and cost. These objectives imply constant velocity operation of the IC engine under external load disturbances and changes in both operating conditions and vehicle speed set-points. In order to achieve these objectives, and reduce the complexity of implementation, in this article a controller is designed by the use of Genetic Programming methods in the Simulink modelling environment, with the aim of obtaining a relatively simple controller for the time-delay system which does not rely on the implementation of real time system models or time delay approximations in the controller. A methodology is presented to utilise the miriad of existing control blocks in the Simulink libraries to automatically evolve optimal control

  17. Genetic diversity of Prochilodus lineatus stocks using in the stocking program of Tietê River, Brazil

    Directory of Open Access Journals (Sweden)

    Ricardo Ribeiro

    2013-11-01

    Full Text Available Objective. Assess the genetic diversity in four brood stocks and one juvenile stock of curimba Prochilodus lineatus in a Hydropower plant in São Paulo - Brazil, using the Tietê River stocking program. Materials and methods. Five RAPD primers were used to amplify the extracted DNA from 150 fin-clip samples. Results. Fifty-nine fragments were polymorphic, 52 had frequencies with significant differences (p<0.05, 45 had low frequencies, 54 were excluded, and two were fixed fragments. High values for polymorphic fragments (71.19% to 91.53% and Shannon index (0.327 to 0.428 were observed. The genetic divergence values within each stock were greater than 50%. Most of the genetic variation was found within the groups through the AMOVA analysis, which was confirmed by the results of the identity and genetic distance. High ancestry levels (FST among the groups value indicated high and moderate genetic differentiation. The estimates of number of migrants by generation (Nm indicated low levels of gene flow. High and moderate genetic divergence between groups (0.58 to 0.83 was observed. Conclusions. The results indicate high variability within the stocks, and genetic differentiation among them. The fish stocks analyzed represent a large genetic base that will allow the fish technicians to release juveniles without genetic risks to wild populations present in the river. These genetic procedures may be used as models for other migratory species, including those threatened by extinction.

  18. A Constraint programming-based genetic algorithm for capacity output optimization

    Directory of Open Access Journals (Sweden)

    Kate Ean Nee Goh

    2014-10-01

    Full Text Available Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company.Design/methodology/approach: In the first stage, constraint programming defining the relationships between variables was formulated into the objective function. A genetic algorithm model was created in the second stage to optimize capacity output. Three demand scenarios were applied to test the robustness of the proposed algorithm.Findings: CPGA improved both the machine utilization and capacity output once the minimum requirements of a demand scenario were fulfilled. Capacity outputs of the three scenarios were improved by 157%, 7%, and 69%, respectively.Research limitations/implications: The work relates to aggregate planning of machine capacity in a single case study. The constraints and constructed scenarios were therefore industry-specific.Practical implications: Capacity planning in a semiconductor manufacturing facility need to consider multiple mutually influenced constraints in resource availability, process flow and product demand. The findings prove that CPGA is a practical and an efficient alternative to optimize the capacity output and to allow the company to review its capacity with quick feedback.Originality/value: The work integrates two contemporary computational methods for a real industry application conventionally reliant on human judgement.

  19. Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

    Science.gov (United States)

    Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

    2017-06-01

    The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

  20. Prediksi Nilai Tukar Rupiah Terhadap US Dollar Menggunakan Metode Genetic Programming

    Directory of Open Access Journals (Sweden)

    Daneswara Jauhari

    2016-12-01

    Exchange currency rate has a wide influence in the economy of a country, both domestically or internationally. The importance of knowing the pattern of exchange rate against the IDR to USD could help the economic growth due to foreign trade involves the use of currencies of different countries. Therefore, we need an application that can predict the value of IDR against the USD in the future. In this research, the authors use genetic programming (GP method which produces solutions (chromosome that obtained from the evaluation of exchange rate and then this solution used as an approximation or prediction of currency exchange rate in the future. These solutions formed from the combination of the set terminal and the set of function that generated randomly. After testing by the number popsize and different iterations, it was found that the GP algorithm can predict the value of the rupiah against the US Dollar with a very good, judging from the value of Mean Absolute Percentage Error (MAPE generated by 0.08%. This research can be developed even better by adding terminal parameters and operating parameters so they can add variation calculation results. Keywords:  prediction, exchange currency rate, genetic programming, MAPE.

  1. Extraction of Static and Dynamic Reservoir Operation Rules by Genetic Programming

    Directory of Open Access Journals (Sweden)

    Habib Akbari Alashti

    2014-11-01

    Full Text Available Considering the necessity of desirable operation of limited water resources and assuming the significant role of dams in controlling and consuming the surface waters, highlights the advantageous of suitable operation rules for optimal and sustainable operation of dams. This study investigates the hydroelectric supply of a one-reservoir system of Karoon3 using nonlinear programming (NLP, genetic algorithm (GA, genetic programming (GP and fixed length gen GP (FLGGP in real-time operation of dam considering two approaches of static and dynamic operation rules. In static operation rule, only one rule curve is extracted for all months in a year whereas in dynamic operation rule, monthly rule curves (12 rules are extracted for each month of a year. In addition, nonlinear decision rule (NLDR curves are considered, and the total deficiency function as the target (objective function have been used for evaluating the performance of each method and approach. Results show appropriate efficiency of GP and FLGGP methods in extracting operation rules in both approaches. Superiority of these methods to operation methods yielded by GA and NLP is 5%. Moreover, according to the results, it can be remarked that, FLGGP method is an alternative for GP method, whereas the GP method cannot be used due to its limitations. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rule to static operation rule (about 10% and therefore this method has more capabilities in real-time operation of the reservoirs systems.

  2. Rim 2/Hipa CACTA transposon display ; A new genetic marker technique in Oryza species

    Directory of Open Access Journals (Sweden)

    Lee Ju

    2005-03-01

    Full Text Available Abstract Background Transposons constitute the major fractions of repetitive sequences in eukaryotes, and have been crucial in the shaping of current genomes. Transposons are generally divided into two classes according to the mechanism underlying their transposition: RNA intermediate class 1 and DNA intermediate class 2. CACTA is a class 2 transposon superfamily, which is found exclusively in plants. As some transposons, including the CACTA superfamily, are highly abundant in plant species, and their nucleotide sequences are highly conserved within a family, they can be utilized as genetic markers, using a slightly modified version of the conventional AFLP protocol. Rim2 /Hipa is a CACTA transposon family having 16 bp consensus TIR sequences to be present in high copy numbers in rice genome. This research was carried out in order to develop a Rim2/Hipa CACTA-AFLP or Rim2/Hipa CACTA-TD (transposon display, hereafter Rim2/Hipa-TD protocol for the study of genetic markers in map construction and the study of genetic diversity in rice. Results Rim2/Hipa-TD generated ample polymorphic profiles among the different rice accessions, and the amplification profiles were highly reproducible between different thermocyclers and Taq polymerases. These amplification profiles allowed for clear distinction between two different ecotypes, Japonica and Indica, of Oryza sativa. In the analysis of RIL populations, the Rim2/Hipa-TD markers were found to be segregated largely in a dominant manner, although in a few cases, non-parental bands were observed in the segregating populations. Upon linkage analysis, the Rim2/Hipa-TD markers were found to be distributed in the regions proximal to the centromeres of the chromosomes. The distribution of the Rim2/Hipa CACTA elements was surveyed in 15 different Oryza species via Rim2/Hipa-TD. While Rim2/Hipa-TD yielded ample amplification profiles between 100 to 700 bp in the AA diploid Oryza species, other species having BB, CC

  3. Inclusion of the fitness sharing technique in an evolutionary algorithm to analyze the fitness landscape of the genetic code adaptability.

    Science.gov (United States)

    Santos, José; Monteagudo, Ángel

    2017-03-27

    The canonical code, although prevailing in complex genomes, is not universal. It was shown the canonical genetic code superior robustness compared to random codes, but it is not clearly determined how it evolved towards its current form. The error minimization theory considers the minimization of point mutation adverse effect as the main selection factor in the evolution of the code. We have used simulated evolution in a computer to search for optimized codes, which helps to obtain information about the optimization level of the canonical code in its evolution. A genetic algorithm searches for efficient codes in a fitness landscape that corresponds with the adaptability of possible hypothetical genetic codes. The lower the effects of errors or mutations in the codon bases of a hypothetical code, the more efficient or optimal is that code. The inclusion of the fitness sharing technique in the evolutionary algorithm allows the extent to which the canonical genetic code is in an area corresponding to a deep local minimum to be easily determined, even in the high dimensional spaces considered. The analyses show that the canonical code is not in a deep local minimum and that the fitness landscape is not a multimodal fitness landscape with deep and separated peaks. Moreover, the canonical code is clearly far away from the areas of higher fitness in the landscape. Given the non-presence of deep local minima in the landscape, although the code could evolve and different forces could shape its structure, the fitness landscape nature considered in the error minimization theory does not explain why the canonical code ended its evolution in a location which is not an area of a localized deep minimum of the huge fitness landscape.

  4. The use of genetic engineering techniques to improve the lipid composition in meat, milk and fish products: a review.

    Science.gov (United States)

    Świątkiewicz, S; Świątkiewicz, M; Arczewska-Włosek, A; Józefiak, D

    2015-04-01

    The health-promoting properties of dietary long-chain n-3 polyunsaturated fatty acids (n-3 LCPUFAs) for humans are well-known. Products of animal-origin enriched with n-3 LCPUFAs can be a good example of functional food, that is food that besides traditionally understood nutritional value may have a beneficial influence on the metabolism and health of consumers, thus reducing the risk of various lifestyle diseases such as atherosclerosis and coronary artery disease. The traditional method of enriching meat, milk or eggs with n-3 LCPUFA is the manipulation of the composition of animal diets. Huge progress in the development of genetic engineering techniques, for example transgenesis, has enabled the generation of many kinds of genetically modified animals. In recent years, one of the aims of animal transgenesis has been the modification of the lipid composition of meat and milk in order to improve the dietetic value of animal-origin products. This article reviews and discusses the data in the literature concerning studies where techniques of genetic engineering were used to create animal-origin products modified to contain health-promoting lipids. These studies are still at the laboratory stage, but their results have demonstrated that the transgenesis of pigs, cows, goats and fishes can be used in the future as efficient methods of production of healthy animal-origin food of high dietetic value. However, due to high costs and a low level of public acceptance, the introduction of this technology to commercial animal production and markets seems to be a distant prospect.

  5. Trading Rules on Stock Markets Using Genetic Network Programming with Reinforcement Learning and Importance Index

    Science.gov (United States)

    Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki

    Genetic Network Programming (GNP) is an evolutionary computation which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, it has been clarified that GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is a new element which is a criterion for decision making. In this paper, we combined GNP-IMX with Actor-Critic (GNP-IMX&AC) and create trading rules on stock markets. Evolution-based methods evolve their programs after enough period of time because they must calculate fitness values, however reinforcement learning can change programs during the period, therefore the trading rules can be created efficiently. In the simulation, the proposed method is trained using the stock prices of 10 brands in 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. The simulation results show that the proposed method can obtain larger profits than GNP-IMX without AC and Buy&Hold.

  6. A structured, extended training program to facilitate adoption of new techniques for practicing surgeons.

    Science.gov (United States)

    Greenberg, Jacob A; Jolles, Sally; Sullivan, Sarah; Quamme, Sudha Pavuluri; Funk, Luke M; Lidor, Anne O; Greenberg, Caprice; Pugh, Carla M

    2018-01-01

    Laparoscopic inguinal hernia repair has been shown to have significant benefits when compared to open inguinal hernia repair, yet remains underutilized in the United States. The traditional model of short, hands-on, cognitive courses to enhance the adoption of new techniques fails to lead to significant levels of practice implementation for most surgeons. We hypothesized that a comprehensive program would facilitate the adoption of laparoscopic inguinal hernia repair (TEP) for practicing surgeons. A team of experts in simulation, coaching, and hernia care created a comprehensive training program to facilitate the adoption of TEP. Three surgeons who routinely performed open inguinal hernia repair with greater than 50 cases annually were recruited to participate in the program. Coaches were selected based on their procedural expertise and underwent formal training in surgical coaching. Participants were required to evaluate all aspects of the educational program and were surveyed out to one year following completion of the program to assess for sustained adoption of TEP. All three participants successfully completed the first three steps of the seven-step program. Two participants completed the full course, while the third dropped out of the program due to time constraints and low case volume. Participant surgeons rated Orientation (4.7/5), GlovesOn training (5/5), and Preceptored Cases (5/5) as highly important training activities that contributed to advancing their knowledge and technical performance of the TEP procedure. At one year, both participants were performing TEPs for "most of their cases" and were confident in their ability to perform the procedure. The total cost of the program including all travel, personal coaching, and simulation was $8638.60 per participant. Our comprehensive educational program led to full and sustained adoption of TEP for those who completed the course. Time constraints, travel costs, and case volume are major considerations for

  7. Fuel spill identification by gas chromatography -- genetic algorithms/pattern recognition techniques

    International Nuclear Information System (INIS)

    Lavine, B.K.; Moores, A.J.; Faruque, A.

    1998-01-01

    Gas chromatography and pattern recognition methods were used to develop a potential method for typing jet fuels so a spill sample in the environment can be traced to its source. The test data consisted of 256 gas chromatograms of neat jet fuels. 31 fuels that have undergone weathering in a subsurface environment were correctly identified by type using discriminants developed from the gas chromatograms of the neat jet fuels. Coalescing poorly resolved peaks, which occurred during preprocessing, diminished the resolution and hence information content of the GC profiles. Nevertheless a genetic algorithm was able to extract enough information from these profiles to correctly classify the chromatograms of weathered fuels. This suggests that cheaper and simpler GC instruments ca be used to type jet fuels

  8. Microchip capillary gel electrophoresis using programmed field strength gradients for the ultra-fast analysis of genetically modified organisms in soybeans.

    Science.gov (United States)

    Kim, Yun-Jeong; Chae, Joon-Seok; Chang, Jun Keun; Kang, Seong Ho

    2005-08-12

    We have developed a novel method for the ultra-fast analysis of genetically modified organisms (GMOs) in soybeans by microchip capillary gel electrophoresis (MCGE) using programmed field strength gradients (PFSG) in a conventional glass double-T microchip. Under the programmed electric field strength and 0.3% poly(ethylene oxide) sieving matrix, the GMO in soybeans was analyzed within only 11 s of the microchip. The MCGE-PFSG method was a program that changes the electric field strength during GMO analysis, and was also applied to the ultra-fast analysis of PCR products. Compared to MCGE using a conventional and constantly applied electric field, the MCGE-PFSG analysis generated faster results without the loss of resolving power and reproducibility for specific DNA fragments (100- and 250-bp DNA) of GM-soybeans. The MCGE-PFSG technique may prove to be a new tool in the GMO analysis due to its speed, simplicity, and high efficiency.

  9. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan

    2017-06-01

    Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

  10. A Unique Technique to get Kaprekar Iteration in Linear Programming Problem

    Science.gov (United States)

    Sumathi, P.; Preethy, V.

    2018-04-01

    This paper explores about a frivolous number popularly known as Kaprekar constant and Kaprekar numbers. A large number of courses and the different classroom capacities with difference in study periods make the assignment between classrooms and courses complicated. An approach of getting the minimum value of number of iterations to reach the Kaprekar constant for four digit numbers and maximum value is also obtained through linear programming techniques.

  11. Comparison of acrylamide intake from Western and guideline based diets using probabilistic techniques and linear programming.

    Science.gov (United States)

    Katz, Josh M; Winter, Carl K; Buttrey, Samuel E; Fadel, James G

    2012-03-01

    Western and guideline based diets were compared to determine if dietary improvements resulting from following dietary guidelines reduce acrylamide intake. Acrylamide forms in heat treated foods and is a human neurotoxin and animal carcinogen. Acrylamide intake from the Western diet was estimated with probabilistic techniques using teenage (13-19 years) National Health and Nutrition Examination Survey (NHANES) food consumption estimates combined with FDA data on the levels of acrylamide in a large number of foods. Guideline based diets were derived from NHANES data using linear programming techniques to comport to recommendations from the Dietary Guidelines for Americans, 2005. Whereas the guideline based diets were more properly balanced and rich in consumption of fruits, vegetables, and other dietary components than the Western diets, acrylamide intake (mean±SE) was significantly greater (Plinear programming and results demonstrate that linear programming techniques can be used to model specific diets for the assessment of toxicological and nutritional dietary components. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Structured behavioral observation techniques as components of an effective fitness-for-duty program

    International Nuclear Information System (INIS)

    Hauth, J.T.; Barnes, V.E.; Moore, C.J.; Toquam, J.L.

    1989-01-01

    Performance-based tests are designed to evaluate physical and cognitive performance and have several attractive features that may be useful in nuclear power plant fitness-for-duty programs. Three types of performance-based testing that may eventually be useful in the nuclear power industry are reviewed in this paper: (a) the Los Angeles Police Department's Drug Recognition Expert program, (b) performance assessment batteries, and (c) performance assessment devices. Each of these techniques is evaluated here in terms of the following measures of effectiveness: (1) scope, or the range of potential problems that can be detected; (2) reliability, or the consistency of results; (3) sensitivity, or the ability of the test to detect impairment or the presence of drugs at low levels; (4) specificity, or the ability of the test to correctly identify the source of impairment or the drug present; (5) implementation, or the practicality of using the technique in the nuclear power plant setting. This information analyzed in this paper indicates that although performance and cognitive assessment techniques currently lack the reliability, sensitivity, and specificity of random chemical screening to detect and deter substance abuse, they can address a variety of fitness-for-duty concerns that may not be adequately addressed by a urinalysis testing program alone. These include detection of drug use not detected by urinalysis, psychological stress, or physical injury or illness

  13. Risk-informed decision making in the nuclear industry: Application and effectiveness comparison of different genetic algorithm techniques

    International Nuclear Information System (INIS)

    Gjorgiev, Blaže; Kančev, Duško; Čepin, Marko

    2012-01-01

    Highlights: ► Multi-objective optimization of STI based on risk-informed decision making. ► Four different genetic algorithms (GAs) techniques are used as optimization tool. ► Advantages/disadvantages among the four different GAs applied are emphasized. - Abstract: The risk-informed decision making (RIDM) process, where insights gained from the probabilistic safety assessment are contemplated together with other engineering insights, is gaining an ever-increasing attention in the process industries. Increasing safety systems availability by applying RIDM is one of the prime goals for the authorities operating with nuclear power plants. Additionally, equipment ageing is gradually becoming a major concern in the process industries and especially in the nuclear industry, since more and more safety-related components are approaching or are already in their wear-out phase. A significant difficulty regarding the consideration of ageing effects on equipment (un)availability is the immense uncertainty the available equipment ageing data are associated to. This paper presents an approach for safety system unavailability reduction by optimizing the related test and maintenance schedule suggested by the technical specifications in the nuclear industry. Given the RIDM philosophy, two additional insights, i.e. ageing data uncertainty and test and maintenance costs, are considered along with unavailability insights gained from the probabilistic safety assessment for a selected standard safety system. In that sense, an approach for multi-objective optimization of the equipment surveillance test interval is proposed herein. Three different objective functions related to each one of the three different insights discussed above comprise the multi-objective nature of the optimization process. Genetic algorithm technique is utilized as an optimization tool. Four different types of genetic algorithms are utilized and consequently comparative analysis is conducted given the

  14. Object matching using a locally affine invariant and linear programming techniques.

    Science.gov (United States)

    Li, Hongsheng; Huang, Xiaolei; He, Lei

    2013-02-01

    In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.

  15. A comparison of fitness-case sampling methods for genetic programming

    Science.gov (United States)

    Martínez, Yuliana; Naredo, Enrique; Trujillo, Leonardo; Legrand, Pierrick; López, Uriel

    2017-11-01

    Genetic programming (GP) is an evolutionary computation paradigm for automatic program induction. GP has produced impressive results but it still needs to overcome some practical limitations, particularly its high computational cost, overfitting and excessive code growth. Recently, many researchers have proposed fitness-case sampling methods to overcome some of these problems, with mixed results in several limited tests. This paper presents an extensive comparative study of four fitness-case sampling methods, namely: Interleaved Sampling, Random Interleaved Sampling, Lexicase Selection and Keep-Worst Interleaved Sampling. The algorithms are compared on 11 symbolic regression problems and 11 supervised classification problems, using 10 synthetic benchmarks and 12 real-world data-sets. They are evaluated based on test performance, overfitting and average program size, comparing them with a standard GP search. Comparisons are carried out using non-parametric multigroup tests and post hoc pairwise statistical tests. The experimental results suggest that fitness-case sampling methods are particularly useful for difficult real-world symbolic regression problems, improving performance, reducing overfitting and limiting code growth. On the other hand, it seems that fitness-case sampling cannot improve upon GP performance when considering supervised binary classification.

  16. Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm

    Directory of Open Access Journals (Sweden)

    Narong Wichapa

    2018-01-01

    Full Text Available Infectious waste disposal remains one of the most serious problems in the medical, social and environmental domains of almost every country. Selection of new suitable locations and finding the optimal set of transport routes for a fleet of vehicles to transport infectious waste material, location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Determining locations for infectious waste disposal is a difficult and complex process, because it requires combining both intangible and tangible factors. Additionally, it depends on several criteria and various regulations. This facility location problem for infectious waste disposal is complicated, and it cannot be addressed using any stand-alone technique. Based on a case study, 107 hospitals and 6 candidate municipalities in Upper-Northeastern Thailand, we considered criteria such as infrastructure, geology and social & environmental criteria, evaluating global priority weights using the fuzzy analytical hierarchy process (Fuzzy AHP. After that, a new multi-objective facility location problem model which hybridizes fuzzy AHP and goal programming (GP, namely the HGP model, was tested. Finally, the vehicle routing problem (VRP for a case study was formulated, and it was tested using a hybrid genetic algorithm (HGA which hybridizes the push forward insertion heuristic (PFIH, genetic algorithm (GA and three local searches including 2-opt, insertion-move and interexchange-move. The results show that both the HGP and HGA can lead to select new suitable locations and to find the optimal set of transport routes for vehicles delivering infectious waste material. The novelty of the proposed methodologies, HGP, is the simultaneous combination of relevant factors that are difficult to interpret and cost factors in order to determine new suitable locations, and HGA can be applied to determine the transport routes which provide a minimum number of vehicles

  17. Genetic engineering technology for the improvement of the sterile insect technique. Proceedings of a final research co-ordination meeting

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-01-01

    Since the beginning of the joint FAO/IAEA programme on the research and development of insect pest control methodology, emphasis has been placed on the basic and applied aspects of implementing the sterile insect technique (SIT). Special emphasis has always been directed at the assembly of technological progress into workable systems that can be implemented in developing countries. The general intention is to solve problems associated with insect pests that have an adverse impact on production of food and fibre. For several insect species SIT has proven to be a powerful method for control. This includes the New World screwworm fly (Cochliomyia hominivorox), the Mediterranean fruit fly (Ceratitis capitata), the melon fly (Bactrocera cucurbitae), the Queensland fruit fly (Bactrocera tryoni) and one tsetse fly species (Glossina austeni). Improvements of the SIT are possible, especially through the use of molecular techniques. The final report of the Co-ordinated Research Programme on ``Genetic Engineering Technology for the Improvement of the Sterile Insect Technique`` highlights the progress made towards the development of transformation systems for non-drosophilid insects and the research aimed at the identification and engineering of potential target genes or traits. Refs, figs, tabs.

  18. Genetic engineering technology for the improvement of the sterile insect technique. Proceedings of a final research co-ordination meeting

    International Nuclear Information System (INIS)

    1998-01-01

    Since the beginning of the joint FAO/IAEA programme on the research and development of insect pest control methodology, emphasis has been placed on the basic and applied aspects of implementing the sterile insect technique (SIT). Special emphasis has always been directed at the assembly of technological progress into workable systems that can be implemented in developing countries. The general intention is to solve problems associated with insect pests that have an adverse impact on production of food and fibre. For several insect species SIT has proven to be a powerful method for control. This includes the New World screwworm fly (Cochliomyia hominivorox), the Mediterranean fruit fly (Ceratitis capitata), the melon fly (Bactrocera cucurbitae), the Queensland fruit fly (Bactrocera tryoni) and one tsetse fly species (Glossina austeni). Improvements of the SIT are possible, especially through the use of molecular techniques. The final report of the Co-ordinated Research Programme on ''Genetic Engineering Technology for the Improvement of the Sterile Insect Technique'' highlights the progress made towards the development of transformation systems for non-drosophilid insects and the research aimed at the identification and engineering of potential target genes or traits

  19. Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

    Science.gov (United States)

    Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

    2014-07-01

    Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

  20. Using Fuzzy Gaussian Inference and Genetic Programming to Classify 3D Human Motions

    Science.gov (United States)

    Khoury, Mehdi; Liu, Honghai

    This research introduces and builds on the concept of Fuzzy Gaussian Inference (FGI) (Khoury and Liu in Proceedings of UKCI, 2008 and IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS 2009), 2009) as a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions. This method is now combined with a Genetic Programming Fuzzy rule-based system in order to classify boxing moves from natural human Motion Capture data. In this experiment, FGI alone is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that adding an evolutionary Fuzzy Inference Engine on top of FGI improves the accuracy of the classifier in a consistent way.

  1. LPmerge: an R package for merging genetic maps by linear programming.

    Science.gov (United States)

    Endelman, Jeffrey B; Plomion, Christophe

    2014-06-01

    Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Prediction of Layer Thickness in Molten Borax Bath with Genetic Evolutionary Programming

    Science.gov (United States)

    Taylan, Fatih

    2011-04-01

    In this study, the vanadium carbide coating in molten borax bath process is modeled by evolutionary genetic programming (GEP) with bath composition (borax percentage, ferro vanadium (Fe-V) percentage, boric acid percentage), bath temperature, immersion time, and layer thickness data. Five inputs and one output data exist in the model. The percentage of borax, Fe-V, and boric acid, temperature, and immersion time parameters are used as input data and the layer thickness value is used as output data. For selected bath components, immersion time, and temperature variables, the layer thicknesses are derived from the mathematical expression. The results of the mathematical expressions are compared to that of experimental data; it is determined that the derived mathematical expression has an accuracy of 89%.

  3. Surrogate-Assisted Genetic Programming With Simplified Models for Automated Design of Dispatching Rules.

    Science.gov (United States)

    Nguyen, Su; Zhang, Mengjie; Tan, Kay Chen

    2017-09-01

    Automated design of dispatching rules for production systems has been an interesting research topic over the last several years. Machine learning, especially genetic programming (GP), has been a powerful approach to dealing with this design problem. However, intensive computational requirements, accuracy and interpretability are still its limitations. This paper aims at developing a new surrogate assisted GP to help improving the quality of the evolved rules without significant computational costs. The experiments have verified the effectiveness and efficiency of the proposed algorithms as compared to those in the literature. Furthermore, new simplification and visualisation approaches have also been developed to improve the interpretability of the evolved rules. These approaches have shown great potentials and proved to be a critical part of the automated design system.

  4. Tools and techniques used in US Department of Energy decommissioning programs

    International Nuclear Information System (INIS)

    Miller, R. L.

    1988-01-01

    Since the decommissioning projects are located at various sites across the United States, a centralized technology transfer program was established to ensure that information on new technologies and techniques developed to support specific tasks is available to all contractors performing similar decommissioning work. This sharing of information avoids duplication of effort and helps to avoid the expenditure of resources on tools or techniques that are not cost effective. This article discusses several of the tools and techniques that have been successfully used for various tasks during the course of decommissioning nuclear facilities. Since decommissioning is labor-intensive work, tools and techniques that reduce either personnel radiation exposure or time required to perform a task are desirable. Other factors that are considered when selecting particular tools or techniques are waste volume reduction, recontamination avoidance, simplicity or operation, and avoiding introduction of large quantities of hazardous/toxic materials that may require special handling and disposal. Finally, the tool, depending on the intended work environment, must be cost effective, easily disposable or easily decontaminated for reuse

  5. A study on maintenance reliability allocation of urban transit brake system using hybrid neuro-genetic technique

    International Nuclear Information System (INIS)

    Bae, Chul Ho; Kim, Hyun Jun; Lee, Jung Hwan; Suh, Myung Won; Chu, Yul

    2007-01-01

    For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. In this paper, the concept of system reliability introduces and optimizes as the key of reasonable maintenance strategies. This study aims at optimizing component's reliability that satisfies the target reliability of brake system in the urban transit. First of all, constructed reliability evaluation system is used to predict and analyze reliability. This data is used for the optimization. To identify component reliability in a system, a method is presented in this paper which uses hybrid neuro-genetic technique. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between component reliability (input) and system reliability (output) of a structural system. The inverse problem can be formulated by using neural network. Genetic algorithm is used to find the minimum square error. Finally, this paper presents reasonable maintenance cycle of urban transit brake system by using optimal system reliability

  6. Translocation-based genetic sexing system to enhance the sterile insect technique against the melon fly (Diptera: Tephritidae)

    International Nuclear Information System (INIS)

    McCombs, S.D.; Lee, S.G.; Saul, S.H.

    1993-01-01

    The autosomal recessive bubble wing (bw) mutant was used to construct a translocation-based genetic sex sorting system in the melon fly, Bactrocera cucurbitae (Coquillett). The translocation stock has females with the bubble wing phenotype that are unable to fly, but the males are wild-type and fly normally. The bubble wing translocation strain has lower egg hatch, larval viability, and eclosion rates than the wild-type strain. Expression of the bubble wing trait is temperature-dependent, with high expression of the trait in 92% of adults at 23°C but in only 15% of adults at 28°C. This translocation-based sex sorting system is the only method available for automatic separation of male and female melon flies in sterile insect release programs

  7. Genetic Modulation of Lipid Profiles following Lifestyle Modification or Metformin Treatment: The Diabetes Prevention Program

    Science.gov (United States)

    Jablonski, Kathleen A.; de Bakker, Paul I. W.; Taylor, Andrew; McAteer, Jarred; Pan, Qing; Horton, Edward S.; Delahanty, Linda M.; Altshuler, David; Shuldiner, Alan R.; Goldberg, Ronald B.; Florez, Jose C.; Bray, George A.; Culbert, Iris W.; Champagne, Catherine M.; Eberhardt, Barbara; Greenway, Frank; Guillory, Fonda G.; Herbert, April A.; Jeffirs, Michael L.; Kennedy, Betty M.; Lovejoy, Jennifer C.; Morris, Laura H.; Melancon, Lee E.; Ryan, Donna; Sanford, Deborah A.; Smith, Kenneth G.; Smith, Lisa L.; Amant, Julia A. St.; Tulley, Richard T.; Vicknair, Paula C.; Williamson, Donald; Zachwieja, Jeffery J.; Polonsky, Kenneth S.; Tobian, Janet; Ehrmann, David; Matulik, Margaret J.; Clark, Bart; Czech, Kirsten; DeSandre, Catherine; Hilbrich, Ruthanne; McNabb, Wylie; Semenske, Ann R.; Caro, Jose F.; Watson, Pamela G.; Goldstein, Barry J.; Smith, Kellie A.; Mendoza, Jewel; Liberoni, Renee; Pepe, Constance; Spandorfer, John; Donahue, Richard P.; Goldberg, Ronald B.; Prineas, Ronald; Rowe, Patricia; Calles, Jeanette; Cassanova-Romero, Paul; Florez, Hermes J.; Giannella, Anna; Kirby, Lascelles; Larreal, Carmen; McLymont, Valerie; Mendez, Jadell; Ojito, Juliet; Perry, Arlette; Saab, Patrice; Haffner, Steven M.; Montez, Maria G.; Lorenzo, Carlos; Martinez, Arlene; Hamman, Richard F.; Nash, Patricia V.; Testaverde, Lisa; Anderson, Denise R.; Ballonoff, Larry B.; Bouffard, Alexis; Calonge, B. Ned; Delve, Lynne; Farago, Martha; Hill, James O.; Hoyer, Shelley R.; Jortberg, Bonnie T.; Lenz, Dione; Miller, Marsha; Price, David W.; Regensteiner, Judith G.; Seagle, Helen; Smith, Carissa M.; Steinke, Sheila C.; VanDorsten, Brent; Horton, Edward S.; Lawton, Kathleen E.; Arky, Ronald A.; Bryant, Marybeth; Burke, Jacqueline P.; Caballero, Enrique; Callaphan, Karen M.; Ganda, Om P.; Franklin, Therese; Jackson, Sharon D.; Jacobsen, Alan M.; Jacobsen, Alan M.; Kula, Lyn M.; Kocal, Margaret; Malloy, Maureen A.; Nicosia, Maryanne; Oldmixon, Cathryn F.; Pan, Jocelyn; Quitingon, Marizel; Rubtchinsky, Stacy; Seely, Ellen W.; Schweizer, Dana; Simonson, Donald; Smith, Fannie; Solomon, Caren G.; Warram, James; Kahn, Steven E.; Montgomery, Brenda K.; Fujimoto, Wilfred; Knopp, Robert H.; Lipkin, Edward W.; Marr, Michelle; Trence, Dace; Kitabchi, Abbas E.; Murphy, Mary E.; Applegate, William B.; Bryer-Ash, Michael; Frieson, Sandra L.; Imseis, Raed; Lambeth, Helen; Lichtermann, Lynne C.; Oktaei, Hooman; Rutledge, Lily M.K.; Sherman, Amy R.; Smith, Clara M.; Soberman, Judith E.; Williams-Cleaves, Beverly; Metzger, Boyd E.; Johnson, Mariana K.; Behrends, Catherine; Cook, Michelle; Fitzgibbon, Marian; Giles, Mimi M.; Heard, Deloris; Johnson, Cheryl K.H.; Larsen, Diane; Lowe, Anne; Lyman, Megan; McPherson, David; Molitch, Mark E.; Pitts, Thomas; Reinhart, Renee; Roston, Susan; Schinleber, Pamela A.; Nathan, David M.; McKitrick, Charles; Turgeon, Heather; Abbott, Kathy; Anderson, Ellen; Bissett, Laurie; Cagliero, Enrico; Florez, Jose C.; Delahanty, Linda; Goldman, Valerie; Poulos, Alexandra; Olefsky, Jerrold M.; Carrion-Petersen, Mary Lou; Barrett-Connor, Elizabeth; Edelman, Steven V.; Henry, Robert R.; Horne, Javiva; Janesch, Simona Szerdi; Leos, Diana; Mudaliar, Sundar; Polonsky, William; Smith, Jean; Vejvoda, Karen; Pi-Sunyer, F. Xavier; Lee, Jane E.; Allison, David B.; Aronoff, Nancy J.; Crandall, Jill P.; Foo, Sandra T.; Pal, Carmen; Parkes, Kathy; Pena, Mary Beth; Rooney, Ellen S.; Wye, Gretchen E.H. Van; Viscovich, Kristine A.; Marrero, David G.; Prince, Melvin J.; Kelly, Susie M.; Dotson, Yolanda F.; Fineberg, Edwin S.; Guare, John C; Hadden, Angela M.; Ignaut, James M.; Jackson, Marcia L.; Kirkman, Marion S.; Mather, Kieren J.; Porter, Beverly D.; Roach, Paris J.; Rowland, Nancy D.; Wheeler, Madelyn L.; Ratner, Robert E.; Youssef, Gretchen; Shapiro, Sue; Bavido-Arrage, Catherine; Boggs, Geraldine; Bronsord, Marjorie; Brown, Ernestine; Cheatham, Wayman W.; Cola, Susan; Evans, Cindy; Gibbs, Peggy; Kellum, Tracy; Levatan, Claresa; Nair, Asha K.; Passaro, Maureen; Uwaifo, Gabriel; Saad, Mohammed F.; Budget, Maria; Jinagouda, Sujata; Akbar, Khan; Conzues, Claudia; Magpuri, Perpetua; Ngo, Kathy; Rassam, Amer; Waters, Debra; Xapthalamous, Kathy; Santiago, Julio V.; Dagogo-Jack, Samuel; White, Neil H.; Das, Samia; Santiago, Ana; Brown, Angela; Fisher, Edwin; Hurt, Emma; Jones, Tracy; Kerr, Michelle; Ryder, Lucy; Wernimont, Cormarie; Saudek, Christopher D.; Bradley, Vanessa; Sullivan, Emily; Whittington, Tracy; Abbas, Caroline; Brancati, Frederick L.; Clark, Jeanne M.; Charleston, Jeanne B.; Freel, Janice; Horak, Katherine; Jiggetts, Dawn; Johnson, Deloris; Joseph, Hope; Loman, Kimberly; Mosley, Henry; Rubin, Richard R.; Samuels, Alafia; Stewart, Kerry J.; Williamson, Paula; Schade, David S.; Adams, Karwyn S.; Johannes, Carolyn; Atler, Leslie F.; Boyle, Patrick J.; Burge, Mark R.; Canady, Janene L.; Chai, Lisa; Gonzales, Ysela; Hernandez-McGinnis, Doris A.; Katz, Patricia; King, Carolyn; Rassam, Amer; Rubinchik, Sofya; Senter, Willette; Waters, Debra; Shamoon, Harry; Brown, Janet O.; Adorno, Elsie; Cox, Liane; Crandall, Jill; Duffy, Helena; Engel, Samuel; Friedler, Allison; Howard-Century, Crystal J.; Kloiber, Stacey; Longchamp, Nadege; Martinez, Helen; Pompi, Dorothy; Scheindlin, Jonathan; Violino, Elissa; Walker, Elizabeth; Wylie-Rosett, Judith; Zimmerman, Elise; Zonszein, Joel; Orchard, Trevor; Wing, Rena R.; Koenning, Gaye; Kramer, M. Kaye; Barr, Susan; Boraz, Miriam; Clifford, Lisa; Culyba, Rebecca; Frazier, Marlene; Gilligan, Ryan; Harrier, Susan; Harris, Louann; Jeffries, Susan; Kriska, Andrea; Manjoo, Qurashia; Mullen, Monica; Noel, Alicia; Otto, Amy; Semler, Linda; Smith, Cheryl F.; Smith, Marie; Venditti, Elizabeth; Weinzierl, Valarie; Williams, Katherine V.; Wilson, Tara; Arakaki, Richard F.; Latimer, Renee W.; Baker-Ladao, Narleen K.; Beddow, Ralph; Dias, Lorna; Inouye, Jillian; Mau, Marjorie K.; Mikami, Kathy; Mohideen, Pharis; Odom, Sharon K.; Perry, Raynette U.; Knowler, William C.; Cooeyate, Norman; Hoskin, Mary A.; Percy, Carol A.; Acton, Kelly J.; Andre, Vickie L.; Barber, Rosalyn; Begay, Shandiin; Bennett, Peter H.; Benson, Mary Beth; Bird, Evelyn C.; Broussard, Brenda A.; Chavez, Marcella; Dacawyma, Tara; Doughty, Matthew S.; Duncan, Roberta; Edgerton, Cyndy; Ghahate, Jacqueline M.; Glass, Justin; Glass, Martia; Gohdes, Dorothy; Grant, Wendy; Hanson, Robert L.; Horse, Ellie; Ingraham, Louise E.; Jackson, Merry; Jay, Priscilla; Kaskalla, Roylen S.; Kessler, David; Kobus, Kathleen M.; Krakoff, Jonathan; Manus, Catherine; Michaels, Sara; Morgan, Tina; Nashboo, Yolanda; Nelson, Julie A.; Poirier, Steven; Polczynski, Evette; Reidy, Mike; Roumain, Jeanine; Rowse, Debra; Sangster, Sandra; Sewenemewa, Janet; Tonemah, Darryl; Wilson, Charlton; Yazzie, Michelle; Bain, Raymond; Fowler, Sarah; Brenneman, Tina; Abebe, Solome; Bamdad, Julie; Callaghan, Jackie; Edelstein, Sharon L.; Gao, Yuping; Grimes, Kristina L.; Grover, Nisha; Haffner, Lori; Jones, Steve; Jones, Tara L.; Katz, Richard; Lachin, John M.; Mucik, Pamela; Orlosky, Robert; Rochon, James; Sapozhnikova, Alla; Sherif, Hanna; Stimpson, Charlotte; Temprosa, Marinella; Walker-Murray, Fredricka; Marcovina, Santica; Strylewicz, Greg; Aldrich, F. Alan; O'Leary, Dan; Stamm, Elizabeth; Rautaharju, Pentti; Prineas, Ronald J.; Alexander, Teresa; Campbell, Charles; Hall, Sharon; Li, Yabing; Mills, Margaret; Pemberton, Nancy; Rautaharju, Farida; Zhang, Zhuming; Mayer-Davis, Elizabeth; Moran, Robert R.; Ganiats, Ted; David, Kristin; Sarkin, Andrew J.; Eastman, R.; Fradkin, Judith; Garfield, Sanford; Gregg, Edward; Zhang, Ping; Herman, William; Florez, Jose C.; Altshuler, David; de Bakker, Paul I.W.; Franks, Paul W.; Hanson, Robert L.; Jablonski, Kathleen; Knowler, William C.; McAteer, Jarred B.; Pollin, Toni I.; Shuldiner, Alan R.

    2012-01-01

    Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, P interaction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; P interaction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, P interaction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; P interaction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss. PMID:22951888

  8. Genetic modulation of lipid profiles following lifestyle modification or metformin treatment: the Diabetes Prevention Program.

    Directory of Open Access Journals (Sweden)

    Toni I Pollin

    Full Text Available Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04-1 × 10(-17. Except for total HDL particles (r = -0.03, P = 0.26, all components of the lipid profile correlated with the GRS (partial |r| = 0.07-0.17, P = 5 × 10(-5-1 10(-19. The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE ± 0.22 mg/dl/allele, P = 8 × 10(-5, P(interaction = 0.02 in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE ± 0.22 mg/dl/allele, P = 0.35 or metformin (β = -0.03, SEE ± 0.22 mg/dl/allele, P = 0.90; P(interaction = 0.64 groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE ± 0.012 ln nmol/L/allele, P = 0.01, P(interaction = 0.01 but not in the placebo (β = -0.002, SEE ± 0.008 ln nmol/L/allele, P = 0.74 or metformin (β = +0.013, SEE ± 0.008 nmol/L/allele, P = 0.12; P(interaction = 0.24 groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.

  9. Symbolic regression via genetic programming for data driven derivation of confinement scaling laws without any assumption on their mathematical form

    International Nuclear Information System (INIS)

    Murari, A; Peluso, E; Gelfusa, M; Lupelli, I; Lungaroni, M; Gaudio, P

    2015-01-01

    Many measurements are required to control thermonuclear plasmas and to fully exploit them scientifically. In the last years JET has shown the potential to generate about 50 GB of data per shot. These amounts of data require more sophisticated data analysis methodologies to perform correct inference and various techniques have been recently developed in this respect. The present paper covers a new methodology to extract mathematical models directly from the data without any a priori assumption about their expression. The approach, based on symbolic regression via genetic programming, is exemplified using the data of the International Tokamak Physics Activity database for the energy confinement time. The best obtained scaling laws are not in power law form and suggest a revisiting of the extrapolation to ITER. Indeed the best non-power law scalings predict confinement times in ITER approximately between 2 and 3 s. On the other hand, more comprehensive and better databases are required to fully profit from the power of these new methods and to discriminate between the hundreds of thousands of models that they can generate. (paper)

  10. Evaluation of liquefaction potential of soil based on standard penetration test using multi-gene genetic programming model

    Science.gov (United States)

    Muduli, Pradyut; Das, Sarat

    2014-06-01

    This paper discusses the evaluation of liquefaction potential of soil based on standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). The liquefaction classification accuracy (94.19%) of the developed liquefaction index (LI) model is found to be better than that of available artificial neural network (ANN) model (88.37%) and at par with the available support vector machine (SVM) model (94.19%) on the basis of the testing data. Further, an empirical equation is presented using MGGP to approximate the unknown limit state function representing the cyclic resistance ratio (CRR) of soil based on developed LI model. Using an independent database of 227 cases, the overall rates of successful prediction of occurrence of liquefaction and non-liquefaction are found to be 87, 86, and 84% by the developed MGGP based model, available ANN and the statistical models, respectively, on the basis of calculated factor of safety (F s) against the liquefaction occurrence.

  11. Searching for globally optimal functional forms for interatomic potentials using genetic programming with parallel tempering.

    Science.gov (United States)

    Slepoy, A; Peters, M D; Thompson, A P

    2007-11-30

    Molecular dynamics and other molecular simulation methods rely on a potential energy function, based only on the relative coordinates of the atomic nuclei. Such a function, called a force field, approximately represents the electronic structure interactions of a condensed matter system. Developing such approximate functions and fitting their parameters remains an arduous, time-consuming process, relying on expert physical intuition. To address this problem, a functional programming methodology was developed that may enable automated discovery of entirely new force-field functional forms, while simultaneously fitting parameter values. The method uses a combination of genetic programming, Metropolis Monte Carlo importance sampling and parallel tempering, to efficiently search a large space of candidate functional forms and parameters. The methodology was tested using a nontrivial problem with a well-defined globally optimal solution: a small set of atomic configurations was generated and the energy of each configuration was calculated using the Lennard-Jones pair potential. Starting with a population of random functions, our fully automated, massively parallel implementation of the method reproducibly discovered the original Lennard-Jones pair potential by searching for several hours on 100 processors, sampling only a minuscule portion of the total search space. This result indicates that, with further improvement, the method may be suitable for unsupervised development of more accurate force fields with completely new functional forms. Copyright (c) 2007 Wiley Periodicals, Inc.

  12. Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks.

    Science.gov (United States)

    Beal, Jacob; Lu, Ting; Weiss, Ron

    2011-01-01

    The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes (~ 50%) and latency of the optimized engineered gene networks. Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.

  13. Genetic variations in phosphorus utilization in rice investigation by tracer technique using Phosphorus-32

    International Nuclear Information System (INIS)

    Sanjivkumar, V.; Malarvizhi, P.; Meena, S.; Latha, K.R.

    2012-01-01

    In most soils, soil and fertilizer P are easily bound by either soil organic matter or chemicals and thus are unavailable to plants unless hydrolyzed to release inorganic phosphate. Therefore, the development of P-efficient rice varieties that can grow and yield better with low P supply is a key to improve crop production. P efficient plants play a major role in increasing crop yields due to shortage of inorganic P fertilizer resources, limited land and water resources and increasing environmental concerns. Based on the P uptake efficiency, four rice genotypes were selected from the field experiment and used in pot culture experiment with three levels of P using radio isotope technique to quantify the P acquisition efficiency (PAE) and P use efficiency (PUE) and also to determine the native P supplying power of the soils using 32 P in low P soils. Growth and yield parameters, grain and straw yield and major nutrients uptake of rice genotypes were increased with enhanced level of phosphorus application. Among the four genotypes, TNRH 180 recorded the highest grain yield and uptake. Increasing the P application rate from 25 to 50 kg P 2 O 5 ha -1 increased the %Pdff in grain and straw for all the genotypes. The mean per cent phosphorus utilization (PPU) ranged between 18.74 and 23.72. The PPU of the genotypes followed the order TNRH 180 (23.72 %) > CO08504 (23.36 %) > CO06732 (20.54%) > ADT 47 (18.74%) . The PPU values were higher at lower level of P application (25 kg P 2 O 5 ha -1 ) for the genotypes TNRH 180, CB08504 and CB06732. (author)

  14. Estimating Typhoon Rainfall over Sea from SSM/I Satellite Data Using an Improved Genetic Programming

    Science.gov (United States)

    Yeh, K.; Wei, H.; Chen, L.; Liu, G.

    2010-12-01

    Estimating Typhoon Rainfall over Sea from SSM/I Satellite Data Using an Improved Genetic Programming Keh-Chia Yeha, Hsiao-Ping Weia,d, Li Chenb, and Gin-Rong Liuc a Department of Civil Engineering, National Chiao Tung University, Hsinchu, Taiwan, 300, R.O.C. b Department of Civil Engineering and Engineering Informatics, Chung Hua University, Hsinchu, Taiwan, 300, R.O.C. c Center for Space and Remote Sensing Research, National Central University, Tao-Yuan, Taiwan, 320, R.O.C. d National Science and Technology Center for Disaster Reduction, Taipei County, Taiwan, 231, R.O.C. Abstract This paper proposes an improved multi-run genetic programming (GP) and applies it to predict the rainfall using meteorological satellite data. GP is a well-known evolutionary programming and data mining method, used to automatically discover the complex relationships among nonlinear systems. The main advantage of GP is to optimize appropriate types of function and their associated coefficients simultaneously. This study makes an improvement to enhance escape ability from local optimums during the optimization procedure. The GP continuously runs several times by replacing the terminal nodes at the next run with the best solution at the current run. The current novel model improves GP, obtaining a highly nonlinear mathematical equation to estimate the rainfall. In the case study, this improved GP described above combining with SSM/I satellite data is employed to establish a suitable method for estimating rainfall at sea surface during typhoon periods. These estimated rainfalls are then verified with the data from four rainfall stations located at Peng-Jia-Yu, Don-Gji-Dao, Lan-Yu, and Green Island, which are four small islands around Taiwan. From the results, the improved GP can generate sophisticated and accurate nonlinear mathematical equation through two-run learning procedures which outperforms the traditional multiple linear regression, empirical equations and back-propagated network

  15. A minimax technique for time-domain design of preset digital equalizers using linear programming

    Science.gov (United States)

    Vaughn, G. L.; Houts, R. C.

    1975-01-01

    A linear programming technique is presented for the design of a preset finite-impulse response (FIR) digital filter to equalize the intersymbol interference (ISI) present in a baseband channel with known impulse response. A minimax technique is used which minimizes the maximum absolute error between the actual received waveform and a specified raised-cosine waveform. Transversal and frequency-sampling FIR digital filters are compared as to the accuracy of the approximation, the resultant ISI and the transmitted energy required. The transversal designs typically have slightly better waveform accuracy for a given distortion; however, the frequency-sampling equalizer uses fewer multipliers and requires less transmitted energy. A restricted transversal design is shown to use the least number of multipliers at the cost of a significant increase in energy and loss of waveform accuracy at the receiver.

  16. Direct evaluation of fault trees using object-oriented programming techniques

    Science.gov (United States)

    Patterson-Hine, F. A.; Koen, B. V.

    1989-01-01

    Object-oriented programming techniques are used in an algorithm for the direct evaluation of fault trees. The algorithm combines a simple bottom-up procedure for trees without repeated events with a top-down recursive procedure for trees with repeated events. The object-oriented approach results in a dynamic modularization of the tree at each step in the reduction process. The algorithm reduces the number of recursive calls required to solve trees with repeated events and calculates intermediate results as well as the solution of the top event. The intermediate results can be reused if part of the tree is modified. An example is presented in which the results of the algorithm implemented with conventional techniques are compared to those of the object-oriented approach.

  17. Remote sensing techniques for monitoring the Rio Grande Valley cotton stalk destruction program

    Energy Technology Data Exchange (ETDEWEB)

    Richardson, A.J.; Gerbermann, A.H.; Summy, K.R.; Anderson, G.L. (Department of Agriculture, Weslaco, TX (United States))

    1993-09-01

    Post harvest cotton (Gossypium hirsutum L.) stalk destruction is a cultural practice used in the Rio Grande Valley to suppress over wintering populations of boll weevils (Anthonomus grandis Boheman) without using chemicals. Consistent application of this practice could substantially reduce insecticide usage, thereby minimizing environmental hazards and increasing cotton production profits. Satellite imagery registered within a geographic information system was used to monitor the cotton stalk destruction program in the Rio Grande Valley. We found that cotton stalk screening procedures based on standard multispectral classification techniques could not reliably distinguish cotton from sorghum. Greenness screening for cotton plant stalks after the stalk destruction deadline was possible only where ground observations locating cotton fields were available. These findings indicate that a successful cotton stalk destruction monitoring program will require satellite images and earth referenced data bases showing cotton field locations.

  18. Use of the analytical tree technique to develop a radiological protection program

    International Nuclear Information System (INIS)

    Domenech N, H.; Jova S, L.

    1996-01-01

    The results obtained by the Cuban Center for Radiological Protection and Hygiene by using an analytical tree technique to develop its general operational radiation protection program are presented. By the application of this method, some factors such as the organization of the radiation protection services, the provision of administrative requirements, the existing general laboratories requirements, the viability of resources and the current documentation was evaluated. Main components were considered such as: complete normative and regulatory documentation; automatic radiological protection data management; scope of 'on the-job'and radiological protection training for the personnel; previous radiological appraisal for the safety performance of the works and application of dose constrains for the personnel and the public. The detailed development of the program allowed to identify the basic aims to be achieved in its maintenance and improvement. (authors). 3 refs

  19. Application of virtual reality technique to a radiation protection training program

    International Nuclear Information System (INIS)

    Hajek, Brian K.; Kang, Ki Doo; Shin, Yoo Jin; Lee, Yon Sik

    2003-01-01

    Using an Internet Virtual Reality (IVR) technique, a 3-dimensional (3-D) model for the radiation controlled area in a nuclear power plant was developed, and a feasibility study to develop a computational program to estimate radiation dose was performed. For this purpose, a pilot model with a dynamic function and bi-directional communication was developed. This model was enhanced from the existing 3-D single-directional communication. In this pilot model, a plant visitor needs to first pass a series of security checks. If the visitor enters the controlled area and approaches a radiation hazard area, alarms with a warning lamp will be initiated automatically. Throughout the test to connect this model from both domestic and international sites in various time zones, it has proven to perform well. Therefore, this model can be applied to broad fields as radiation protection procedures or radiation protection training with photographic data, and on-line dose assessment programs

  20. The VALMONT Program: Accurate experimental techniques to support the neutronics qualification of UMo/AL

    International Nuclear Information System (INIS)

    Hedelot, J.P.; Doederlein, C.; Antony, M.; Girard, J.M.; Laval, V.; Fougeras, P.; Willermoz, G.; Leconte, P.

    2005-01-01

    The VALMONT program aimed at qualifying the HORUS3D (HOrowitz Reactor simulation Unified System) neutronics calculation route that is used for the development of the JHR core, and to verify the correct treatment of UMo/Al (20% enrichment in 235 U) fuel. The program is composed of two parts. The first part was devoted to the measurement by the oscillation technique of the reactivity effect of UAl/Mo fuel with an accuracy around 1% (1□). The second part consisted of gamma-spectroscopy experiments on a dedicated UMo/Al fuel sample in order to characterize, through axial power profiles and modified conversion ratio of 238 U measurements, the production and absorption effects inside the UAl/Mo fuel. The overall excellent agreement between high accuracy experiments and calculations allowed to qualify the HORUS3D neutronics calculation route for UMo/Al fuel. (author)

  1. From a genetic innovation to mass health programmes: the diffusion of Down's Syndrome prenatal screening and diagnostic techniques in France.

    Science.gov (United States)

    Vassy, Carine

    2006-10-01

    Down's Syndrome prenatal diagnostic and screening techniques have spread widely in France over the last 30 years and are now part of the routine clinical practice of prenatal care. These techniques, which originated in the field of genetics, ultrasonography and biochemistry, were the first to provide the possibility of choosing the features of the foetus, or at least to reject some of its characteristics. They lead to new norms of healthy foetuses and a progressive acceptance of medical abortions. The aim of this paper is to understand how the use of these tests has been generalised in France despite scientific controversies about their risks and ethical questioning about a potential renewal of eugenics. It analyses the representations of public needs that have been articulated by key players in the scientific and medical fields. This research explores political and administrative decision making processes to understand how progressively widening public access to prenatal testing has been organised and funded. The results highlight the scientific and political role of biomedical researchers, the forms of involvement of health authorities and politicians, and the passive participation of the vast majority of the users. The paper also examines the characteristics of the French health system that facilitated the generalised use of the technology.

  2. Application of Fluorescence In Situ Hybridization (FISH) Technique for the Detection of Genetic Aberration in Medical Science

    Science.gov (United States)

    Ratan, Zubair Ahmed; Zaman, Sojib Bin; Haidere, Mohammad Faisal; Runa, Nusrat Jahan; Akter, Nasrin

    2017-01-01

    Fluorescence in situ hybridization (FISH) is a macromolecule recognition technique, which is considered as a new advent in the field of cytology. Initially, it was developed as a physical mapping tool to delineate genes within chromosomes. The accuracy and versatility of FISH were subsequently capitalized upon in biological and medical research. This visually appealing technique provides an intermediate degree of resolution between DNA analysis and chromosomal investigations. FISH consists of a hybridizing DNA probe, which can be labeled directly or indirectly. In the case of direct labeling, fluorescent nucleotides are used, while indirect labeling is incorporated with reporter molecules that are subsequently detected by fluorescent antibodies or other affinity molecules. FISH is applied to detect genetic abnormalities that include different characteristic gene fusions or the presence of an abnormal number of chromosomes in a cell or loss of a chromosomal region or a whole chromosome. It is also applied in different research applications, such as gene mapping or the identification of novel oncogenes. This article reviews the concept of FISH, its application, and its advantages in medical science.  PMID:28690958

  3. A Robust Computational Technique for Model Order Reduction of Two-Time-Scale Discrete Systems via Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Othman M. K. Alsmadi

    2015-01-01

    Full Text Available A robust computational technique for model order reduction (MOR of multi-time-scale discrete systems (single input single output (SISO and multi-input multioutput (MIMO is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.

  4. A method for digital image registration using a mathematical programming technique

    Science.gov (United States)

    Yao, S. S.

    1973-01-01

    A new algorithm based on a nonlinear programming technique to correct the geometrical distortions of one digital image with respect to another is discussed. This algorithm promises to be superior to existing ones in that it is capable of treating localized differential scaling, translational and rotational errors over the whole image plane. A series of piece-wise 'rubber-sheet' approximations are used, constrained in such a manner that a smooth approximation over the entire image can be obtained. The theoretical derivation is included. The result of using the algorithm to register four channel S065 Apollo IX digitized photography over Imperial Valley, California, is discussed in detail.

  5. Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1989-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

  6. Effects of genetic variants previously associated with fasting glucose and insulin in the Diabetes Prevention Program.

    Directory of Open Access Journals (Sweden)

    Jose C Florez

    Full Text Available Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001, G6PC2 (P = 0.002 and GCKR (P = 0.001. We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001, and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001. The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001. We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.

  7. Water Curtain System Pre-design for Crude Oil Storage URCs : A Numerical Modeling and Genetic Programming Approach

    NARCIS (Netherlands)

    Ghotbi Ravandi, Ebrahim; Rahmannejad, Reza; Karimi-Nasab, Saeed; Sarrafi, Amir; Raoof, Amir

    In this paper the main criteria of the water curtain system for unlined rock caverns (URCs) is described. By the application of numerical modeling and genetic programming (GP), a method for water curtain system pre-design for Iranian crude oil storage URCs (common dimension worldwide) is presented.

  8. A Novel Idea for Optimizing Condition-Based Maintenance Using Genetic Algorithms and Continuous Event Simulation Techniques

    Directory of Open Access Journals (Sweden)

    Mansoor Ahmed Siddiqui

    2017-01-01

    Full Text Available Effective maintenance strategies are of utmost significance for system engineering due to their direct linkage with financial aspects and safety of the plants’ operation. At a point where the state of a system, for instance, level of its deterioration, can be constantly observed, a strategy based on condition-based maintenance (CBM may be affected; wherein upkeep of the system is done progressively on the premise of monitored state of the system. In this article, a multicomponent framework is considered that is continuously kept under observation. In order to decide an optimal deterioration stage for the said system, Genetic Algorithm (GA technique has been utilized that figures out when its preventive maintenance should be carried out. The system is configured into a multiobjective problem that is aimed at optimizing the two desired objectives, namely, profitability and accessibility. For the sake of reality, a prognostic model portraying the advancements of deteriorating system has been employed that will be based on utilization of continuous event simulation techniques. In this regard, Monte Carlo (MC simulation has been shortlisted as it can take into account a wide range of probable options that can help in reducing uncertainty. The inherent benefits proffered by the said simulation technique are fully utilized to display various elements of a deteriorating system working under stressed environment. The proposed synergic model (GA and MC is considered to be more effective due to the employment of “drop-by-drop approach” that permits successful drive of the related search process with regard to the best optimal solutions.

  9. Detecting high-order interactions of single nucleotide polymorphisms using genetic programming.

    Science.gov (United States)

    Nunkesser, Robin; Bernholt, Thorsten; Schwender, Holger; Ickstadt, Katja; Wegener, Ingo

    2007-12-15

    Not individual single nucleotide polymorphisms (SNPs), but high-order interactions of SNPs are assumed to be responsible for complex diseases such as cancer. Therefore, one of the major goals of genetic association studies concerned with such genotype data is the identification of these high-order interactions. This search is additionally impeded by the fact that these interactions often are only explanatory for a relatively small subgroup of patients. Most of the feature selection methods proposed in the literature, unfortunately, fail at this task, since they can either only identify individual variables or interactions of a low order, or try to find rules that are explanatory for a high percentage of the observations. In this article, we present a procedure based on genetic programming and multi-valued logic that enables the identification of high-order interactions of categorical variables such as SNPs. This method called GPAS cannot only be used for feature selection, but can also be employed for discrimination. In an application to the genotype data from the GENICA study, an association study concerned with sporadic breast cancer, GPAS is able to identify high-order interactions of SNPs leading to a considerably increased breast cancer risk for different subsets of patients that are not found by other feature selection methods. As an application to a subset of the HapMap data shows, GPAS is not restricted to association studies comprising several 10 SNPs, but can also be employed to analyze whole-genome data. Software can be downloaded from http://ls2-www.cs.uni-dortmund.de/~nunkesser/#Software

  10. Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

    International Nuclear Information System (INIS)

    Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

    2017-01-01

    Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

  11. A singular value decomposition linear programming (SVDLP) optimization technique for circular cone based robotic radiotherapy

    Science.gov (United States)

    Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen

    2018-01-01

    With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP

  12. A singular value decomposition linear programming (SVDLP) optimization technique for circular cone based robotic radiotherapy.

    Science.gov (United States)

    Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen

    2018-01-05

    With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP

  13. The use of automatic programming techniques for fault tolerant computing systems

    Science.gov (United States)

    Wild, C.

    1985-01-01

    It is conjectured that the production of software for ultra-reliable computing systems such as required by Space Station, aircraft, nuclear power plants and the like will require a high degree of automation as well as fault tolerance. In this paper, the relationship between automatic programming techniques and fault tolerant computing systems is explored. Initial efforts in the automatic synthesis of code from assertions to be used for error detection as well as the automatic generation of assertions and test cases from abstract data type specifications is outlined. Speculation on the ability to generate truly diverse designs capable of recovery from errors by exploring alternate paths in the program synthesis tree is discussed. Some initial thoughts on the use of knowledge based systems for the global detection of abnormal behavior using expectations and the goal-directed reconfiguration of resources to meet critical mission objectives are given. One of the sources of information for these systems would be the knowledge captured during the automatic programming process.

  14. Development of plasma arc cutting technique for dismantlement of reactor internals in JPDR decommissioning program

    International Nuclear Information System (INIS)

    Yanagihara, Satoshi; Tanaka, Mitsugu; Ujihara, Norio.

    1988-01-01

    The decommissioning program for JPDR has been conducted by JAERI since 1981 under contact with the Science and Technology Agency of Japan. The development of cutting tools for dismantling the JPDR is one of the important items in the program. An underwater plasma arc cutting technique was selected for dismantling the JPDR core internals. The study was concentrated on improving the cutting ability in water. Various cutting tests were conducted changing the parameters such as arc current, supply gas and cutting speed to evaluate the most effective cutting condition. Through the study, it has been achieved to be able to cut a 130 mm thick stainless steel plate in water. In addition, the amount and the characteristics of by-products were measured during the cutting tests for the safety evaluation of the dismantling activities. Final cutting tests and checkout of whole plasma arc cutting system were conducted using a mockup water pool and test pieces simulating the JPDR core internals. It was proved from the tests that the cutting system developed in the program will be applicable for the JPDR core internals dismantlement. (author)

  15. Estimation of genetic parameters for growth traits in a breeding program for rainbow trout (Oncorhynchus mykiss) in China.

    Science.gov (United States)

    Hu, G; Gu, W; Bai, Q L; Wang, B Q

    2013-04-26

    Genetic parameters and breeding values for growth traits were estimated in the first and, currently, the only family selective breeding program for rainbow trout (Oncorhynchus mykiss) in China. Genetic and phenotypic data were collected for growth traits from 75 full-sibling families with a 2-generation pedigree. Genetic parameters and breeding values for growth traits of rainbow trout were estimated using the derivative-free restricted maximum likelihood method. The goodness-of-fit of the models was tested using Akaike and Bayesian information criteria. Genetic parameters and breeding values were estimated using the best-fit model for each trait. The values for heritability estimating body weight and length ranged from 0.20 to 0.45 and from 0.27 to 0.60, respectively, and the heritability of condition factor was 0.34. Our results showed a moderate degree of heritability for growth traits in this breeding program and suggested that the genetic and phenotypic tendency of body length, body weight, and condition factor were similar. Therefore, the selection of phenotypic values based on pedigree information was also suitable in this research population.

  16. Review: fetal programming of polycystic ovary syndrome by androgen excess: evidence from experimental, clinical, and genetic association studies.

    Science.gov (United States)

    Xita, Nectaria; Tsatsoulis, Agathocles

    2006-05-01

    Polycystic ovary syndrome (PCOS) is a common endocrine disorder of premenopausal women, characterized by hyperandrogenism, polycystic ovaries, and chronic anovulation along with insulin resistance and abdominal obesity as frequent metabolic traits. Although PCOS manifests clinically during adolescence, emerging data suggest that the natural history of PCOS may originate in intrauterine life. Evidence from experimental, clinical, and genetic research supporting the hypothesis for the fetal origins of PCOS has been analyzed. Female primates, exposed in utero to androgen excess, exhibit the phenotypic features of PCOS during adult life. Clinical observations also support a potential fetal origin of PCOS. Women with fetal androgen excess disorders, including congenital 21-hydroxylase deficiency and congenital adrenal virilizing tumors, develop features characteristic of PCOS during adulthood despite the normalization of androgen excess after birth. The potential mechanisms of fetal androgen excess leading to a PCOS phenotype in humans are not clearly understood. However, maternal and/or fetal hyperandrogenism can provide a plausible mechanism for fetal programing of PCOS, and this, in part, may be genetically determined. Thus, genetic association studies have indicated that common polymorphic variants of genes determining androgen activity or genes that influence the availability of androgens to target tissues are associated with PCOS and increased androgen levels. These genomic variants may provide the genetic link to prenatal androgenization in human PCOS. Prenatal androgenization of the female fetus induced by genetic and environmental factors, or the interaction of both, may program differentiating target tissues toward the development of PCOS phenotype in adult life.

  17. Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming.

    Science.gov (United States)

    Luna, Jose Maria; Pechenizkiy, Mykola; Del Jesus, Maria Jose; Ventura, Sebastian

    2017-09-25

    Real-world data usually comprise features whose interpretation depends on some contextual information. Such contextual-sensitive features and patterns are of high interest to be discovered and analyzed in order to obtain the right meaning. This paper formulates the problem of mining context-aware association rules, which refers to the search for associations between itemsets such that the strength of their implication depends on a contextual feature. For the discovery of this type of associations, a model that restricts the search space and includes syntax constraints by means of a grammar-based genetic programming methodology is proposed. Grammars can be considered as a useful way of introducing subjective knowledge to the pattern mining process as they are highly related to the background knowledge of the user. The performance and usefulness of the proposed approach is examined by considering synthetically generated datasets. A posteriori analysis on different domains is also carried out to demonstrate the utility of this kind of associations. For example, in educational domains, it is essential to identify and understand contextual and context-sensitive factors that affect overall and individual student behavior and performance. The results of the experiments suggest that the approach is feasible and it automatically identifies interesting context-aware associations from real-world datasets.

  18. Genetic Programming for the Downscaling of Extreme Rainfall Events on the East Coast of Peninsular Malaysia

    Directory of Open Access Journals (Sweden)

    Sahar Hadi Pour

    2014-11-01

    Full Text Available A genetic programming (GP-based logistic regression method is proposed in the present study for the downscaling of extreme rainfall indices on the east coast of Peninsular Malaysia, which is considered one of the zones in Malaysia most vulnerable to climate change. A National Centre for Environmental Prediction reanalysis dataset at 42 grid points surrounding the study area was used to select the predictors. GP models were developed for the downscaling of three extreme rainfall indices: days with larger than or equal to the 90th percentile of rainfall during the north-east monsoon; consecutive wet days; and consecutive dry days in a year. Daily rainfall data for the time periods 1961–1990 and 1991–2000 were used for the calibration and validation of models, respectively. The results are compared with those obtained using the multilayer perceptron neural network (ANN and linear regression-based statistical downscaling model (SDSM. It was found that models derived using GP can predict both annual and seasonal extreme rainfall indices more accurately compared to ANN and SDSM.

  19. Elevator Group Supervisory Control System Using Genetic Network Programming with Macro Nodes and Reinforcement Learning

    Science.gov (United States)

    Zhou, Jin; Yu, Lu; Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Markon, Sandor

    Elevator Group Supervisory Control System (EGSCS) is a very large scale stochastic dynamic optimization problem. Due to its vast state space, significant uncertainty and numerous resource constraints such as finite car capacities and registered hall/car calls, it is hard to manage EGSCS using conventional control methods. Recently, many solutions for EGSCS using Artificial Intelligence (AI) technologies have been reported. Genetic Network Programming (GNP), which is proposed as a new evolutionary computation method several years ago, is also proved to be efficient when applied to EGSCS problem. In this paper, we propose an extended algorithm for EGSCS by introducing Reinforcement Learning (RL) into GNP framework, and an improvement of the EGSCS' performances is expected since the efficiency of GNP with RL has been clarified in some other studies like tile-world problem. Simulation tests using traffic flows in a typical office building have been made, and the results show an actual improvement of the EGSCS' performances comparing to the algorithms using original GNP and conventional control methods. Furthermore, as a further study, an importance weight optimization algorithm is employed based on GNP with RL and its efficiency is also verified with the better performances.

  20. Application of genetic programming in shape optimization of concrete gravity dams by metaheuristics

    Directory of Open Access Journals (Sweden)

    Abdolhossein Baghlani

    2014-12-01

    Full Text Available A gravity dam maintains its stability against the external loads by its massive size. Hence, minimization of the weight of the dam can remarkably reduce the construction costs. In this paper, a procedure for finding optimal shape of concrete gravity dams with a computationally efficient approach is introduced. Genetic programming (GP in conjunction with metaheuristics is used for this purpose. As a case study, shape optimization of the Bluestone dam is presented. Pseudo-dynamic analysis is carried out on a total number of 322 models in order to establish a database of the results. This database is then used to find appropriate relations based on GP for design criteria of the dam. This procedure eliminates the necessity of the time-consuming process of structural analyses in evolutionary optimization methods. The method is hybridized with three different metaheuristics, including particle swarm optimization, firefly algorithm (FA, and teaching–learning-based optimization, and a comparison is made. The results show that although all algorithms are very suitable, FA is slightly superior to other two algorithms in finding a lighter structure in less number of iterations. The proposed method reduces the weight of dam up to 14.6% with very low computational effort.

  1. Comparison between Decision Tree and Genetic Programming to distinguish healthy from stroke postural sway patterns.

    Science.gov (United States)

    Marrega, Luiz H G; Silva, Simone M; Manffra, Elisangela F; Nievola, Julio C

    2015-01-01

    Maintaining balance is a motor task of crucial importance for humans to perform their daily activities safely and independently. Studies in the field of Artificial Intelligence have considered different classification methods in order to distinguish healthy subjects from patients with certain motor disorders based on their postural strategies during the balance control. The main purpose of this paper is to compare the performance between Decision Tree (DT) and Genetic Programming (GP) - both classification methods of easy interpretation by health professionals - to distinguish postural sway patterns produced by healthy and stroke individuals based on 16 widely used posturographic variables. For this purpose, we used a posturographic dataset of time-series of center-of-pressure displacements derived from 19 stroke patients and 19 healthy matched subjects in three quiet standing tasks of balance control. Then, DT and GP models were trained and tested under two different experiments where accuracy, sensitivity and specificity were adopted as performance metrics. The DT method has performed statistically significant (P < 0.05) better in both cases, showing for example an accuracy of 72.8% against 69.2% from GP in the second experiment of this paper.

  2. Online Learning of Genetic Network Programming and its Application to Prisoner’s Dilemma Game

    Science.gov (United States)

    Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

    A new evolutionary model with the network structure named Genetic Network Programming (GNP) has been proposed recently. GNP, that is, an expansion of GA and GP, represents solutions as a network structure and evolves it by using “offline learning (selection, mutation, crossover)”. GNP can memorize the past action sequences in the network flow, so it can deal with Partially Observable Markov Decision Process (POMDP) well. In this paper, in order to improve the ability of GNP, Q learning (an off-policy TD control algorithm) that is one of the famous online methods is introduced for online learning of GNP. Q learning is suitable for GNP because (1) in reinforcement learning, the rewards an agent will get in the future can be estimated, (2) TD control doesn’t need much memory and can learn quickly, and (3) off-policy is suitable in order to search for an optimal solution independently of the policy. Finally, in the simulations, online learning of GNP is applied to a player for “Prisoner’s dilemma game” and its ability for online adaptation is confirmed.

  3. Comparison between dynamic programming and genetic algorithm for hydro unit economic load dispatch

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2014-10-01

    Full Text Available The hydro unit economic load dispatch (ELD is of great importance in energy conservation and emission reduction. Dynamic programming (DP and genetic algorithm (GA are two representative algorithms for solving ELD problems. The goal of this study was to examine the performance of DP and GA while they were applied to ELD. We established numerical experiments to conduct performance comparisons between DP and GA with two given schemes. The schemes included comparing the CPU time of the algorithms when they had the same solution quality, and comparing the solution quality when they had the same CPU time. The numerical experiments were applied to the Three Gorges Reservoir in China, which is equipped with 26 hydro generation units. We found the relation between the performance of algorithms and the number of units through experiments. Results show that GA is adept at searching for optimal solutions in low-dimensional cases. In some cases, such as with a number of units of less than 10, GA's performance is superior to that of a coarse-grid DP. However, GA loses its superiority in high-dimensional cases. DP is powerful in obtaining stable and high-quality solutions. Its performance can be maintained even while searching over a large solution space. Nevertheless, due to its exhaustive enumerating nature, it costs excess time in low-dimensional cases.

  4. Generating and repairing genetically programmed DNA breaks during immunoglobulin class switch recombination

    Science.gov (United States)

    Nicolas, Laura; Cols, Montserrat; Choi, Jee Eun; Chaudhuri, Jayanta; Vuong, Bao

    2018-01-01

    Adaptive immune responses require the generation of a diverse repertoire of immunoglobulins (Igs) that can recognize and neutralize a seemingly infinite number of antigens. V(D)J recombination creates the primary Ig repertoire, which subsequently is modified by somatic hypermutation (SHM) and class switch recombination (CSR). SHM promotes Ig affinity maturation whereas CSR alters the effector function of the Ig. Both SHM and CSR require activation-induced cytidine deaminase (AID) to produce dU:dG mismatches in the Ig locus that are transformed into untemplated mutations in variable coding segments during SHM or DNA double-strand breaks (DSBs) in switch regions during CSR. Within the Ig locus, DNA repair pathways are diverted from their canonical role in maintaining genomic integrity to permit AID-directed mutation and deletion of gene coding segments. Recently identified proteins, genes, and regulatory networks have provided new insights into the temporally and spatially coordinated molecular interactions that control the formation and repair of DSBs within the Ig locus. Unravelling the genetic program that allows B cells to selectively alter the Ig coding regions while protecting non-Ig genes from DNA damage advances our understanding of the molecular processes that maintain genomic integrity as well as humoral immunity. PMID:29744038

  5. Predicting temperature drop rate of mass concrete during an initial cooling period using genetic programming

    Science.gov (United States)

    Bhattarai, Santosh; Zhou, Yihong; Zhao, Chunju; Zhou, Huawei

    2018-02-01

    Thermal cracking on concrete dams depends upon the rate at which the concrete is cooled (temperature drop rate per day) within an initial cooling period during the construction phase. Thus, in order to control the thermal cracking of such structure, temperature development due to heat of hydration of cement should be dropped at suitable rate. In this study, an attempt have been made to formulate the relation between cooling rate of mass concrete with passage of time (age of concrete) and water cooling parameters: flow rate and inlet temperature of cooling water. Data measured at summer season (April-August from 2009 to 2012) from recently constructed high concrete dam were used to derive a prediction model with the help of Genetic Programming (GP) software “Eureqa”. Coefficient of Determination (R) and Mean Square Error (MSE) were used to evaluate the performance of the model. The value of R and MSE is 0.8855 and 0.002961 respectively. Sensitivity analysis was performed to evaluate the relative impact on the target parameter due to input parameters. Further, testing the proposed model with an independent dataset those not included during analysis, results obtained from the proposed GP model are close enough to the real field data.

  6. Genetic Algorithm for Mixed Integer Nonlinear Bilevel Programming and Applications in Product Family Design

    Directory of Open Access Journals (Sweden)

    Chenlu Miao

    2016-01-01

    Full Text Available Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP, which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.

  7. Using modern imaging techniques to old HST data: a summary of the ALICE program.

    Science.gov (United States)

    Choquet, Elodie; Soummer, Remi; Perrin, Marshall; Pueyo, Laurent; Hagan, James Brendan; Zimmerman, Neil; Debes, John Henry; Schneider, Glenn; Ren, Bin; Milli, Julien; Wolff, Schuyler; Stark, Chris; Mawet, Dimitri; Golimowski, David A.; Hines, Dean C.; Roberge, Aki; Serabyn, Eugene

    2018-01-01

    Direct imaging of extrasolar systems is a powerful technique to study the physical properties of exoplanetary systems and understand their formation and evolution mechanisms. The detection and characterization of these objects are challenged by their high contrast with their host star. Several observing strategies and post-processing algorithms have been developed for ground-based high-contrast imaging instruments, enabling the discovery of directly-imaged and spectrally-characterized exoplanets. The Hubble Space Telescope (HST), pioneer in directly imaging extrasolar systems, has yet been often limited to the detection of bright debris disks systems, with sensitivity limited by the difficulty to implement an optimal PSF subtraction stategy, which is readily offered on ground-based telescopes in pupil tracking mode.The Archival Legacy Investigations of Circumstellar Environments (ALICE) program is a consistent re-analysis of the 10 year old coronagraphic archive of HST's NICMOS infrared imager. Using post-processing methods developed for ground-based observations, we used the whole archive to calibrate PSF temporal variations and improve NICMOS's detection limits. We have now delivered ALICE-reprocessed science products for the whole NICMOS archival data back to the community. These science products, as well as the ALICE pipeline, were used to prototype the JWST coronagraphic data and reduction pipeline. The ALICE program has enabled the detection of 10 faint debris disk systems never imaged before in the near-infrared and several substellar companion candidates, which we are all in the process of characterizing through follow-up observations with both ground-based facilities and HST-STIS coronagraphy. In this publication, we provide a summary of the results of the ALICE program, advertise its science products and discuss the prospects of the program.

  8. Propagation and conservation of native forest genetic resources of medicinal use by means of in vitro and ex vitro techniques.

    Science.gov (United States)

    Sharry, Sandra; Adema, Marina; Basiglio Cordal, María A; Villarreal, Blanca; Nikoloff, Noelia; Briones, Valentina; Abedini, Walter

    2011-07-01

    In Argentina, there are numerous native species which are an important source of natural products and which are traditionally used in medicinal applications. Some of these species are going through an intense extraction process in their natural habitat which may affect their genetic diversity. The aim of this study was to establish vegetative propagation systems for three native forestal species of medicinal interest. This will allow the rapid obtainment of plants to preserve the germplasm. This study included the following species which are widely used in folk medicine and its applications: Erythrina crista-galli or "seibo" (astringent, used for its cicatrizant properties and for bronchiolitic problems); Acacia caven or "espinillo" (antirheumatic, digestive, diuretic and with cicatrizant properties) and Salix humboldtiana or "sauce criollo" (antipyretic, sedative, antispasmodic, astringent). The methodology included the micropropagation of seibo, macro and micropropagation of Salix humboldtiana and the somatic embryogenesis of Acacia caven. The protocol for seibo regeneration was adjusted from nodal sections of seedlings which were obtained from seeds germinated in vitro. The macropropagation through rooted cuttings of "sauce criollo" was achieved and complete plants of this same species were obtained through both direct and indirect organogenesis using in vitro cultures. The somatic embryogenesis for Acacia caven was optimized and this led to obtain a high percentage of embryos in different stages of development. We are able to support the conservation of native forest resources of medicinal use by means of vegetative propagation techniques.

  9. Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran

    International Nuclear Information System (INIS)

    Assareh, E.; Behrang, M.A.; Assari, M.R.; Ghanbarzadeh, A.

    2010-01-01

    This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO-DEM and GA-DEM (PSO and GA demand estimation models) are developed to estimate the future oil demand values based on population, GDP (gross domestic product), import and export data. Oil consumption in Iran from 1981 to 2005 is considered as the case of this study. The available data is partly used for finding the optimal, or near optimal values of the weighting parameters (1981-1999) and partly for testing the models (2000-2005). For the best results of GA, the average relative errors on testing data were 2.83% and 1.72% for GA-DEM exponential and GA-DEM linear , respectively. The corresponding values for PSO were 1.40% and 1.36% for PSO-DEM exponential and PSO-DEM linear , respectively. Oil demand in Iran is forecasted up to year 2030. (author)

  10. Revealing −1 Programmed Ribosomal Frameshifting Mechanisms by Single-Molecule Techniques and Computational Methods

    Directory of Open Access Journals (Sweden)

    Kai-Chun Chang

    2012-01-01

    Full Text Available Programmed ribosomal frameshifting (PRF serves as an intrinsic translational regulation mechanism employed by some viruses to control the ratio between structural and enzymatic proteins. Most viral mRNAs which use PRF adapt an H-type pseudoknot to stimulate −1 PRF. The relationship between the thermodynamic stability and the frameshifting efficiency of pseudoknots has not been fully understood. Recently, single-molecule force spectroscopy has revealed that the frequency of −1 PRF correlates with the unwinding forces required for disrupting pseudoknots, and that some of the unwinding work dissipates irreversibly due to the torsional restraint of pseudoknots. Complementary to single-molecule techniques, computational modeling provides insights into global motions of the ribosome, whose structural transitions during frameshifting have not yet been elucidated in atomic detail. Taken together, recent advances in biophysical tools may help to develop antiviral therapies that target the ubiquitous −1 PRF mechanism among viruses.

  11. Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs

    Energy Technology Data Exchange (ETDEWEB)

    Infanger, G.

    1993-11-01

    The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.

  12. Macro-assembler technique for generating control words for a micro-programmed processor

    International Nuclear Information System (INIS)

    Lesny, D.D.; Wray, J.J.

    1981-01-01

    To produce microcode for an experimental system, such as FASTBUS interfaces, with wide control words and many micro-fields, one needs a micro-assembler which (1) allows wide flexibility in defining defaults for microcode fields, (2) does a significant amount of error checking to prevent multiple or inconsistant definitions of fields, (3) allows macro expansions which define several microcode words for frequently used sequences, and (4) is easily modified as hardware definitions are refined. Using MACRO-11 on DEC PDP-11 computers, a library of macros has been created, which can be used to generate the 80-bit microcode words needed for a Unibus to FASTBUS micro-programmed interface and which meets the above requirements. The same technique could easily be used to develop libraries appropriate for other microcoded devices

  13. Monitoring programmed cell death of living plant tissues in microfluidics using electrochemical and optical techniques

    DEFF Research Database (Denmark)

    Mark, Christina; Zor, Kinga; Heiskanen, Arto

    such as redox activity, O2 and H2O2 concentration, pH, cell viability and release of target enzymes such as α-amylase. We have optimised an intracellular, whole-cell redox activity assay[3] that detects changes in redox activity in barley aleurone layer during PCD. The assay uses a double mediator......This project focuses on developing and applying a tissue culture system with electrochemical and optical detection techniques for tissue culture of barley aleurone layer to increase understanding of the underlying mechanisms of programmed cell death (PCD) in plants. The major advantage......-system to electrochemically measure redox activity via changes in the NADP:NADPH ratio. Experiments show that redox activity changes depend on phytohormone activation or inactivation of aleurone layer metabolism and subsequent PCD. We have also successfully detected PCD induced by phytohormones in barley aleurone layer using...

  14. Loss of genetic diversity in Culex quinquefasciatus targeted by a lymphatic filariasis vector control program in Recife, Brazil.

    Science.gov (United States)

    Cartaxo, Marina F S; Ayres, Constância F J; Weetman, David

    2011-09-01

    Recife is one of the largest cities in north-eastern Brazil and is endemic for lymphatic filariasis transmitted by Culex quinquefasciatus. Since 2003 a control program has targeted mosquito larvae by elimination of breeding sites and bimonthly application of Bacillus sphaericus. To assess the impact of this program on the local vector population we monitored the genetic diversity and differentiation of Cx. quinquefasciatus using microsatellites and a B. sphaericus-resistance associated mutation (cqm1(REC)) over a 3-year period. We detected a significant but gradual decline in allelic diversity, which, coupled with subtle temporal genetic structure, suggests a major impact of the control program on the vector population. Selection on cqm1(REC) does not appear to be involved with loss of neutral diversity from the population, with no temporal trend in resistant allele frequency and no correlation with microsatellite differentiation. The evidence for short-term genetic drift we detected suggests a low ratio of effective population size: census population size for Cx. quinquefasciatus, perhaps coupled with strong geographically-restricted population structure. Spatial definition of populations will be an important step for success of an expanded vector control program. Copyright © 2011 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.

  15. Short-term streamflow forecasting with global climate change implications A comparative study between genetic programming and neural network models

    Science.gov (United States)

    Makkeasorn, A.; Chang, N. B.; Zhou, X.

    2008-05-01

    SummarySustainable water resources management is a critically important priority across the globe. While water scarcity limits the uses of water in many ways, floods may also result in property damages and the loss of life. To more efficiently use the limited amount of water under the changing world or to resourcefully provide adequate time for flood warning, the issues have led us to seek advanced techniques for improving streamflow forecasting on a short-term basis. This study emphasizes the inclusion of sea surface temperature (SST) in addition to the spatio-temporal rainfall distribution via the Next Generation Radar (NEXRAD), meteorological data via local weather stations, and historical stream data via USGS gage stations to collectively forecast discharges in a semi-arid watershed in south Texas. Two types of artificial intelligence models, including genetic programming (GP) and neural network (NN) models, were employed comparatively. Four numerical evaluators were used to evaluate the validity of a suite of forecasting models. Research findings indicate that GP-derived streamflow forecasting models were generally favored in the assessment in which both SST and meteorological data significantly improve the accuracy of forecasting. Among several scenarios, NEXRAD rainfall data were proven its most effectiveness for a 3-day forecast, and SST Gulf-to-Atlantic index shows larger impacts than the SST Gulf-to-Pacific index on the streamflow forecasts. The most forward looking GP-derived models can even perform a 30-day streamflow forecast ahead of time with an r-square of 0.84 and RMS error 5.4 in our study.

  16. Application of Genetic Programing to Develop a Modular Model for the Simulation of Stream Flow Time Series

    Science.gov (United States)

    Meshgi, A.; Babovic, V.; Chui, T. F. M.; Schmitter, P.

    2014-12-01

    Developing reliable methods to estimate stream flow has been a subject of interest due to its importance in planning, design and management of water resources within a basin. Machine learning tools such as Artificial Neural Network (ANN) and Genetic Programming (GP) have been widely applied for rainfall-runoff modeling as they require less computational time as compared to physically-based models. As GP is able to generate a function with understandable structure, it may offer advantages over other data driven techniques and therefore has been used in different studies to generate rainfall-runoff functions. However, to date, proposed formulations only contain rainfall and/or streamflow data and consequently are local and cannot be generalized and adopted in other catchments which have different physical characteristics. This study investigated the capability of GP in developing a physically interpretable model with understandable structure to simulate stream flow based on hydrological parameters (e.g. precipitation) and catchment conditions (e.g., initial groundwater table elevation and area of the catchment) by following a modular approach. The modular model resulted in two sub-models where the baseflow was first predicted and the direct runoff was then estimated for a semi-urban catchment in Singapore. The simulated results matched very well with observed data in both the training and the testing of data sets, giving NSEs of 0.97 and 0.96 respectively demonstrated the successful estimation of stream flow using the modular model derived in this study. The results of this study indicate that GP is an effective tool in developing a physically interpretable model with understandable structure to simulate stream flow that can be transferred to other catchments.

  17. Seasonal change detection of riparian zones with remote sensing images and genetic programming in a semi-arid watershed.

    Science.gov (United States)

    Makkeasorn, Ammarin; Chang, Ni-Bin; Li, Jiahong

    2009-02-01

    Riparian zones are deemed significant due to their interception capability of non-point source impacts and the maintenance of ecosystem integrity region wide. To improve classification and change detection of riparian buffers, this paper developed an evolutionary computational, supervised classification method--the RIparian Classification Algorithm (RICAL)--to conduct the seasonal change detection of riparian zones in a vast semi-arid watershed, South Texas. RICAL uniquely demonstrates an integrative effort to incorporate both vegetation indices and soil moisture images derived from LANDSAT 5 TM and RADARSAT-1 satellite images, respectively. First, an estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) images was conducted via the first-stage genetic programming (GP) practice. Second, for the statistical analyses and image classification, eight vegetation indices were prepared based on reflectance factors that were calculated as the response of the instrument on LANDSAT. These spectral vegetation indices were then independently used for discriminate analysis along with soil moisture images to classify the riparian zones via the second-stage GP practice. The practical implementation was assessed by a case study in the Choke Canyon Reservoir Watershed (CCRW), South Texas, which is mostly agricultural and range land in a semi-arid coastal environment. To enhance the application potential, a combination of Iterative Self-Organizing Data Analysis Techniques (ISODATA) and maximum likelihood supervised classification was also performed for spectral discrimination and classification of riparian varieties comparatively. Research findings show that the RICAL algorithm may yield around 90% accuracy based on the unseen ground data. But using different vegetation indices would not significantly improve the final quality of the spectral discrimination and classification. Such practices may lead to the formulation of more effective management strategies

  18. Development of a genetically programed vanillin-sensing bacterium for high-throughput screening of lignin-degrading enzyme libraries.

    Science.gov (United States)

    Sana, Barindra; Chia, Kuan Hui Burton; Raghavan, Sarada S; Ramalingam, Balamurugan; Nagarajan, Niranjan; Seayad, Jayasree; Ghadessy, Farid J

    2017-01-01

    Lignin is a potential biorefinery feedstock for the production of value-added chemicals including vanillin. A huge amount of lignin is produced as a by-product of the paper industry, while cellulosic components of plant biomass are utilized for the production of paper pulp. In spite of vast potential, lignin remains the least exploited component of plant biomass due to its extremely complex and heterogenous structure. Several enzymes have been reported to have lignin-degrading properties and could be potentially used in lignin biorefining if their catalytic properties could be improved by enzyme engineering. The much needed improvement of lignin-degrading enzymes by high-throughput selection techniques such as directed evolution is currently limited, as robust methods for detecting the conversion of lignin to desired small molecules are not available. We identified a vanillin-inducible promoter by RNAseq analysis of Escherichia coli cells treated with a sublethal dose of vanillin and developed a genetically programmed vanillin-sensing cell by placing the 'very green fluorescent protein' gene under the control of this promoter. Fluorescence of the biosensing cell is enhanced significantly when grown in the presence of vanillin and is readily visualized by fluorescence microscopy. The use of fluorescence-activated cell sorting analysis further enhances the sensitivity, enabling dose-dependent detection of as low as 200 µM vanillin. The biosensor is highly specific to vanillin and no major response is elicited by the presence of lignin, lignin model compound, DMSO, vanillin analogues or non-specific toxic chemicals. We developed an engineered E. coli cell that can detect vanillin at a concentration as low as 200 µM. The vanillin-sensing cell did not show cross-reactivity towards lignin or major lignin degradation products including vanillin analogues. This engineered E. coli cell could potentially be used as a host cell for screening lignin-degrading enzymes that

  19. Analysis of behavioral change techniques in community-led total sanitation programs.

    Science.gov (United States)

    Sigler, Rachel; Mahmoudi, Lyana; Graham, Jay Paul

    2015-03-01

    The lack of sanitation facilitates the spread of diarrheal diseases-a leading cause of child deaths worldwide. As of 2012, an estimated 1 billion people still practiced open defecation (OD). To address this issue, one behavioral change approach used is community-led total sanitation (CLTS). It is now applied in an estimated 66 countries worldwide, and many countries have adopted this approach as their main strategy for scaling up rural sanitation coverage. While it appears that many of the activities used in CLTS-that target community-level changes in sanitation behaviors instead of household-level changes-have evolved out of existing behavior change frameworks and techniques, it is less clear how these activities are adapted by different organizations and applied in different country contexts. The aims of this study are to (i) show which behavior change frameworks and techniques are the most common in CLTS interventions; (ii) describe how activities are implemented in CLTS interventions by region and context; and (3) determine which activities program implementers considered the most valuable in achieving open defecation free (ODF) status and sustaining it. The results indicate that a wide range of activities are conducted across the different programs and often go beyond standard CLTS activities. CLTS practitioners ranked follow-up and monitoring activities as the most important activities for achieving an ODF community, yet only 1 of 10 organizations conducted monitoring and follow-up throughout their project. Empirical studies are needed to determine which specific behavioral change activities are most effective at ending OD and sustaining it. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  20. Genetics and bioethics: how our thinking has changed since 1969.

    Science.gov (United States)

    Walters, LeRoy

    2012-02-01

    In 1969, the field of human genetics was in its infancy. Amniocentesis was a new technique for prenatal diagnosis, and a newborn genetic screening program had been established in one state. There were also concerns about the potential hazards of genetic engineering. A research group at the Hastings Center and Paul Ramsey pioneered in the discussion of genetics and bioethics. Two principal techniques have emerged as being of enduring importance: human gene transfer research and genetic testing and screening. This essay tracks the development and use of these techniques and considers the ethical issues that they raise.

  1. Long-term program for research and development of group separation and disintegration techniques

    International Nuclear Information System (INIS)

    1988-01-01

    In Japan, the basic guidelines state that high-level radioactive wastes released from reprocessing of spent fuel should be processed into stable solid material, followed by storage for cooling for 30-50 years and disposal in the ground at a depth of several hundreds of meters. The Long-Term Program for Research and Development of Group Separation and Disintegration Techniques is aimed at efficient disposal of high-level wastes, reutilization of useful substances contained, and improved safety. Important processes include separation of nuclides (group separation, individual nuclide separation) and conversion (disintegration) of long-lived nuclides into short-lived or non-radioactive one. These processes can reduce the volume of high-level wastes to be left for final disposal. Research and development projects have been under way to provide techniques to separate high-level waste substances into four groups (transuranic elements, strontium/cesium, technetium/platinum group elements, and others). These projects also cover recovery of useful metals and efficient utilization of separated substances. For disintegration, conceptual studies have been carried out for the application of fast neutron beams to conversion of long half-life transuranium elements into short half-life or non-radioactive elements. (N.K.)

  2. An improved exploratory search technique for pure integer linear programming problems

    Science.gov (United States)

    Fogle, F. R.

    1990-01-01

    The development is documented of a heuristic method for the solution of pure integer linear programming problems. The procedure draws its methodology from the ideas of Hooke and Jeeves type 1 and 2 exploratory searches, greedy procedures, and neighborhood searches. It uses an efficient rounding method to obtain its first feasible integer point from the optimal continuous solution obtained via the simplex method. Since this method is based entirely on simple addition or subtraction of one to each variable of a point in n-space and the subsequent comparison of candidate solutions to a given set of constraints, it facilitates significant complexity improvements over existing techniques. It also obtains the same optimal solution found by the branch-and-bound technique in 44 of 45 small to moderate size test problems. Two example problems are worked in detail to show the inner workings of the method. Furthermore, using an established weighted scheme for comparing computational effort involved in an algorithm, a comparison of this algorithm is made to the more established and rigorous branch-and-bound method. A computer implementation of the procedure, in PC compatible Pascal, is also presented and discussed.

  3. A heuristic ranking approach on capacity benefit margin determination using Pareto-based evolutionary programming technique.

    Science.gov (United States)

    Othman, Muhammad Murtadha; Abd Rahman, Nurulazmi; Musirin, Ismail; Fotuhi-Firuzabad, Mahmud; Rajabi-Ghahnavieh, Abbas

    2015-01-01

    This paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP) technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE) in various conditions. Eventually, the power transfer based available transfer capability (ATC) is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.

  4. A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique

    Directory of Open Access Journals (Sweden)

    Muhammad Murtadha Othman

    2015-01-01

    Full Text Available This paper introduces a novel multiobjective approach for capacity benefit margin (CBM assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE in various conditions. Eventually, the power transfer based available transfer capability (ATC is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.

  5. Study of flood defense structural measures priorities using Compromise Programming technique

    Science.gov (United States)

    Lim, D.; Jeong, S.

    2017-12-01

    Recent climate change of global warming has led to the frequent occurrence of heavy regional rainfalls. As such, inundation vulnerability increases in urban areas with high population density due to the low runoff carrying capacity. This study selects a sample area (Janghang-eup, the Republic of Korea), which is one of the most vulnerable areas to flooding, analyzing the urban flood runoff model (XP-SWMM) and using the MCDM (Multi-Criteria Decision Making) technique to establish flood protection structural measures. To this end, we compare the alternatives and choose the optimal flood defense measure: our model is utilized with three flood prevention structural measures; (i) drainage pipe construction; (ii) water detention; and (iii) flood pumping station. Dividing the target area into three small basins, we propose flood evaluations for an inundation decrease by studying the flooded area, the maximum inundation depth, the damaged residential area, and the construction cost. In addition, Compromise Programming determines the priority of the alternatives. As a consequent, this study suggests flood pumping station for Zone 1 and drainage pipe construction for Zone 2 and Zone 3, respectively, as the optimal flood defense alternative. Keywords : MCDM; Compromise Programming; Urban Flood Prevention; This research was supported by a grant [MPSS-DP-2013-62] through the Disaster and Safety Management Institute funded by Ministry of Public Safety and Security of Korean government.

  6. Genetic Parameters and the Impact of Off-Types for Theobroma cacao L. in a Breeding Program in Brazil

    Science.gov (United States)

    DuVal, Ashley; Gezan, Salvador A.; Mustiga, Guiliana; Stack, Conrad; Marelli, Jean-Philippe; Chaparro, José; Livingstone, Donald; Royaert, Stefan; Motamayor, Juan C.

    2017-01-01

    Breeding programs of cacao (Theobroma cacao L.) trees share the many challenges of breeding long-living perennial crops, and genetic progress is further constrained by both the limited understanding of the inheritance of complex traits and the prevalence of technical issues, such as mislabeled individuals (off-types). To better understand the genetic architecture of cacao, in this study, 13 years of phenotypic data collected from four progeny trials in Bahia, Brazil were analyzed jointly in a multisite analysis. Three separate analyses (multisite, single site with and without off-types) were performed to estimate genetic parameters from statistical models fitted on nine important agronomic traits (yield, seed index, pod index, % healthy pods, % pods infected with witches broom, % of pods other loss, vegetative brooms, diameter, and tree height). Genetic parameters were estimated along with variance components and heritabilities from the multisite analysis, and a trial was fingerprinted with low-density SNP markers to determine the impact of off-types on estimations. Heritabilities ranged from 0.37 to 0.64 for yield and its components and from 0.03 to 0.16 for disease resistance traits. A weighted index was used to make selections for clonal evaluation, and breeding values estimated for the parental selection and estimation of genetic gain. The impact of off-types to breeding progress in cacao was assessed for the first time. Even when present at <5% of the total population, off-types altered selections by 48%, and impacted heritability estimations for all nine of the traits analyzed, including a 41% difference in estimated heritability for yield. These results show that in a mixed model analysis, even a low level of pedigree error can significantly alter estimations of genetic parameters and selections in a breeding program. PMID:29250097

  7. Genetic diversity analysis in Malaysian giant prawns using expressed sequence tag microsatellite markers for stock improvement program.

    Science.gov (United States)

    Atin, K H; Christianus, A; Fatin, N; Lutas, A C; Shabanimofrad, M; Subha, B

    2017-08-17

    The Malaysian giant prawn is among the most commonly cultured species of the genus Macrobrachium. Stocks of giant prawns from four rivers in Peninsular Malaysia have been used for aquaculture over the past 25 years, which has led to repeated harvesting, restocking, and transplantation between rivers. Consequently, a stock improvement program is now important to avoid the depletion of wild stocks and the loss of genetic diversity. However, the success of such an improvement program depends on our knowledge of the genetic variation of these base populations. The aim of the current study was to estimate genetic variation and differentiation of these riverine sources using novel expressed sequence tag-microsatellite (EST-SSR) markers, which not only are informative on genetic diversity but also provide information on immune and metabolic traits. Our findings indicated that the tested stocks have inbreeding depression due to a significant deficiency in heterozygotes, and F IS was estimated as 0.15538 to 0.31938. An F-statistics analysis suggested that the stocks are composed of one large panmictic population. Among the four locations, stocks from Johor, in the southern region of the peninsular, showed higher allelic and genetic diversity than the other stocks. To overcome inbreeding problems, the Johor population could be used as a base population in a stock improvement program by crossing to the other populations. The study demonstrated that EST-SSR markers can be incorporated in future marker assisted breeding to aid the proper management of the stocks by breeders and stakeholders in Malaysia.

  8. Diversity and genetic stability in banana genotypes in a breeding program using inter simple sequence repeats (ISSR) markers.

    Science.gov (United States)

    Silva, A V C; Nascimento, A L S; Vitória, M F; Rabbani, A R C; Soares, A N R; Lédo, A S

    2017-02-23

    Banana (Musa spp) is a fruit species frequently cultivated and consumed worldwide. Molecular markers are important for estimating genetic diversity in germplasm and between genotypes in breeding programs. The objective of this study was to analyze the genetic diversity of 21 banana genotypes (FHIA 23, PA42-44, Maçã, Pacovan Ken, Bucaneiro, YB42-47, Grand Naine, Tropical, FHIA 18, PA94-01, YB42-17, Enxerto, Japira, Pacovã, Prata-Anã, Maravilha, PV79-34, Caipira, Princesa, Garantida, and Thap Maeo), by using inter-simple sequence repeat (ISSR) markers. Material was generated from the banana breeding program of Embrapa Cassava & Fruits and evaluated at Embrapa Coastal Tablelands. The 12 primers used in this study generated 97.5% polymorphism. Four clusters were identified among the different genotypes studied, and the sum of the first two principal components was 48.91%. From the Unweighted Pair Group Method using Arithmetic averages (UPGMA) dendrogram, it was possible to identify two main clusters and subclusters. Two genotypes (Garantida and Thap Maeo) remained isolated from the others, both in the UPGMA clustering and in the principal cordinate analysis (PCoA). Using ISSR markers, we could analyze the genetic diversity of the studied material and state that these markers were efficient at detecting sufficient polymorphism to estimate the genetic variability in banana genotypes.

  9. How Am I Driving? Using Genetic Programming to Generate Scoring Functions for Urban Driving Behavior

    Directory of Open Access Journals (Sweden)

    Roberto López

    2018-04-01

    Full Text Available Road traffic injuries are a serious concern in emerging economies. Their death toll and economic impact are shocking, with 9 out of 10 deaths occurring in low or middle-income countries; and road traffic crashes representing 3% of their gross domestic product. One way to mitigate these issues is to develop technology to effectively assist the driver, perhaps making him more aware about how her (his decisions influence safety. Following this idea, in this paper we evaluate computational models that can score the behavior of a driver based on a risky-safety scale. Potential applications of these models include car rental agencies, insurance companies or transportation service providers. In a previous work, we showed that Genetic Programming (GP was a successful methodology to evolve mathematical functions with the ability to learn how people subjectively score a road trip. The input to this model was a vector of frequencies of risky maneuvers, which were supposed to be detected in a sensor layer. Moreover, GP was shown, even with statistical significance, to be better than six other Machine Learning strategies, including Neural Networks, Support Vector Regression and a Fuzzy Inference system, among others. A pending task, since then, was to evaluate if a more detailed comparison of different strategies based on GP could improve upon the best GP model. In this work, we evaluate, side by side, scoring functions evolved by three different variants of GP. In the end, the results suggest that two of these strategies are very competitive in terms of accuracy and simplicity, both generating models that could be implemented in current technology that seeks to assist the driver in real-world scenarios.

  10. Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

    Science.gov (United States)

    Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

    2015-11-13

    The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science

  11. Genetic diversity of pacu and piapara broodstocks in restocking programs in the rivers Paraná and Paranapanema (Brazil

    Directory of Open Access Journals (Sweden)

    Nelson Mauricio Lopera-Barrero

    2016-09-01

    Full Text Available The genetic diversity of Piaractus mesopotamicus (pacu and Leporinus elongatus (piapara broodstocks used in restocking programs in the rivers Paraná and Paranapanema is analyzed. One hundred and twenty specimens (two broodstocks of each species from fish ponds in Palotina PR Brazil and in Salto Grande SP Brazil were assessed. Ten primers produced 96 fragments, comprising 68 (70.83% and 94 (97.92% polymorphic fragments for P. mesopotamicus and L. elongatus broodstocks, respectively. Differences (p < 0.05 in the frequency of 15 and 27 fragments were detected for each species, without exclusive fragments. Shannon Index (0.347 - 0.572 and the percentage of polymorphic fragments (57.3% - 94.8% revealed high intra-population genetic variability for all broodstocks. Results of molecular variance analyses (AMOVA showed that most variations do not lie between the broodstocks but within each broodstock (89%. Genetic (0.088 and 0.142 and identity (0.916 and 0.868 distance rates demonstrated similarity between the broodstocks of each species, corroborated by Fst (0.1023 and 010.27 and Nm (4.18 and 4.33 rates, with a slight genetic difference due to genic flux. High intrapopulation genetic variability and similarity between the broodstocks of each species was also detected, proving a common ancestry.

  12. Studies of osteoporosis within the Debrecen regional osteoporosis program (drop) in Hungary using isotope related techniques

    International Nuclear Information System (INIS)

    Balogh, A.; Jozsa, Z.; Balogh, Z.; Kiss, A.Z.; Bettembuk, P.

    1996-01-01

    Estimates of the annual incidence of various osteoporotic fractures in Hungary only recently became available. Further prospective data are needed in order to get an estimate on the public health impact of osteoporosis. It has been postulated that beyond genetic factors, environmental effects play important roles in determining the peak bone mass. Many of the influential environmental factors and also the normal course of the development of peak bone mass need further investigation in our region, also to explore suspected interregional differences in bone health. This study will take place in a centre as participant of a multicentre international population study and aims to draw a random sample of the minimum of 105 persons of both sexes from the urban population (15 to 50) of Debrecen, a town of 220 thousand inhabitants in the Eastern region of Hungary and measure bone density of the spine, hip and total body using isotope related techniques. Further goal is to review major lifestyle variables, such as nutrition and exercise. Laboratory markers of bone metabolism will be assayed and bone samples obtained from victims of accidents to analyze bone quality and elemental composition. Alternative bone sites, such as teeth and oral alveolar bone will be also considered sources of bone samples for comparison to other bone regions. The duration of the study will be 4 years and the study subjects will be followed by repeated measurements and clinical assessment. The data will be collected and analyzed according to a common protocol supported by the IAEA. This makes possible comparing data from the participating countries. Experiences of previous work in this Institute on similar subject is also reviewed briefly. (author)

  13. Detection of genetically modified organisms in foods by protein- and DNA-based techniques : bridging the methods

    NARCIS (Netherlands)

    Duijn, G. van; Biert, R. van; Bleeker-Marcelis, H.; Boeijen, I. van; Adan, A.J.; Jhakrie, S.; Hessing, M.

    2002-01-01

    According to European Commission (EC) Regulation 1139/98, foods and food ingredients that are to be delivered to the final consumer in which either protein or DNA resulting from genetic modification is present, shall be subject to additional specific labeling requirements. Since 1994, genetically

  14. An Interactive Learning Environment for Teaching the Imperative and Object-Oriented Programming Techniques in Various Learning Contexts

    Science.gov (United States)

    Xinogalos, Stelios

    The acquisition of problem-solving and programming skills in the era of knowledge society seems to be particularly important. Due to the intrinsic difficulty of acquiring such skills various educational tools have been developed. Unfortunately, most of these tools are not utilized. In this paper we present the programming microworlds Karel and objectKarel that support the procedural-imperative and Object-Oriented Programming (OOP) techniques and can be used for supporting the teaching and learning of programming in various learning contexts and audiences. The paper focuses on presenting the pedagogical features that are common to both environments and mainly on presenting the potential uses of these environments.

  15. Security Transition Program Office (STPO), technology transfer of the STPO process, tools, and techniques

    Energy Technology Data Exchange (ETDEWEB)

    Hauth, J.T.; Forslund, C.R.J.; Underwood, J.A.

    1994-09-01

    In 1990, with the transition from a defense mission to environmental restoration, the U.S. Department of Energy`s (DOE`s) Hanford Site began a significant effort to diagnose, redesign, and implement new safeguards and security (SAS) processes. In 1992 the Security Transition Program Office (STPO) was formed to address the sweeping changes that were being identified. Comprised of SAS and other contractor staff with extensive experience and supported by staff experienced in organizational analysis and work process redesign, STPO undertook a series of tasks designed to make fundamental changes to SAS processes throughout the Hanford Site. The goal of STPO is to align the SAS work and organization with the new Site mission. This report describes the key strategy, tools, methods, and techniques used by STPO to change SAS processes at Hanford. A particular focus of this review is transferring STPO`s experience to other DOE sites and federal agency efforts: that is, to extract, analyze, and provide a critical review of the approach, tools, and techniques used by STPO that will be useful to other DOE sites and national laboratories in transitioning from a defense production mode to environmental restoration and other missions. In particular, what lessons does STPO provide as a pilot study or model for implementing change in other transition activities throughout the DOE complex? More broadly, what theoretical and practical contributions do DOE transition efforts, such as STPO, provide to federal agency streamlining efforts and attempts to {open_quotes}reinvent{close_quotes} government enterprises in the public sector? The approach used by STPO should provide valuable information to those examining their own processes in light of new mission requirements.

  16. Evaluation of genetically altered medflies for use in sterile insect technique programmes. Proceedings of the final research co-ordination meeting

    International Nuclear Information System (INIS)

    1997-01-01

    Although the medfly is a key pest in many areas of the world, there are important fruit growing areas where other fruit flies are key pests. It was concluded that it would be of value for any future CRP on genetic sexing to include these species. For the development of genetic sexing systems in these species much can be gained from the experiences with the medfly. However, at present, a similar procedure will have to be followed which will entail the construction of genetic maps, the development of cytological techniques and the induction of male linked translocation. In future, the availability of molecular methods could enable sexing systems to be transferred between species. The proceedings contain 11 papers, which range from an initial molecular analysis of the genome of the fly to a field experiment to assess the impact of an all-male release

  17. Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

    Science.gov (United States)

    Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

    2012-03-01

    Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Using actual and ultrasound carcass information in beef genetic evaluation programs

    OpenAIRE

    Bertrand,Joseph Keith

    2009-01-01

    Increased movement toward alliances and grid pricing in the U.S. has led to an increase interest in genetic values for carcass traits. The literature suggests that carcass genetic values are an effective tool to enhance selection for carcass traits, and that it is possible to select sires within a breed that can increase marbling score without adversely affecting external fat thickness or percent retail product relative to the breed mean. Ultrasound has been investigated as a cheaper means of...

  19. Korean round-robin result for new international program to assess the reliability of emerging nondestructive techniques

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kyung Cho; Kim, Jin Gyum; Kang, Sung Sik; Jhung, Myung Jo [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2017-04-15

    The Korea Institute of Nuclear Safety, as a representative organization of Korea, in February 2012 participated in an international Program to Assess the Reliability of Emerging Nondestructive Techniques initiated by the U.S. Nuclear Regulatory Commission. The goal of the Program to Assess the Reliability of Emerging Nondestructive Techniques is to investigate the performance of emerging and prospective novel nondestructive techniques to find flaws in nickel-alloy welds and base materials. In this article, Korean round-robin test results were evaluated with respect to the test blocks and various nondestructive examination techniques. The test blocks were prepared to simulate large-bore dissimilar metal welds, small-bore dissimilar metal welds, and bottom-mounted instrumentation penetration welds in nuclear power plants. Also, lessons learned from the Korean round-robin test were summarized and discussed.

  20. Combining machine learning and matching techniques to improve causal inference in program evaluation.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2016-12-01

    Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balance is assessed before estimating treatment effects. This paper introduces a novel analytic framework utilizing a machine learning algorithm called optimal discriminant analysis (ODA) for assessing covariate balance and estimating treatment effects, once the matching strategy has been implemented. This framework holds several key advantages over the conventional approach: application to any variable metric and number of groups; insensitivity to skewed data or outliers; and use of accuracy measures applicable to all prognostic analyses. Moreover, ODA accepts analytic weights, thereby extending the methodology to any study design where weights are used for covariate adjustment or more precise (differential) outcome measurement. One-to-one matching on the propensity score was used as the matching strategy. Covariate balance was assessed using standardized difference in means (conventional approach) and measures of classification accuracy (ODA). Treatment effects were estimated using ordinary least squares regression and ODA. Using empirical data, ODA produced results highly consistent with those obtained via the conventional methodology for assessing covariate balance and estimating treatment effects. When ODA is combined with matching techniques within a treatment effects framework, the results are consistent with conventional approaches. However, given that it provides additional dimensions and robustness to the analysis versus what can currently be achieved using conventional approaches, ODA offers an appealing alternative. © 2016 John Wiley & Sons, Ltd.

  1. Master plan nurse duty roster using the 0-1 goal programming technique

    Science.gov (United States)

    Ismail, Wan Rosmanira; Jenal, Ruzzakiah

    2013-04-01

    The scheduling of nurses is particularly challenging because of the nature of the work which is around the clock. In addition, inefficient duty roster can have an effect on the nurses well being as well as their job satisfaction. In nurse scheduling problem (NSP), nurses are generally allocated to periods of work over a specified time horizon. A typical length of the schedule varies from a few weeks to a month. The schedule will be consistently rebuilt after the specified time period and will result in a time-consuming task for the administrative staff involved. Moreover, the task becomes overwhelming when the staff needs to consider the previous duty rosters in order to maintain the quality of schedules. Therefore, this study suggests the development of a master plan for a nurse duty roster for approximately one year. The master plan starts with the development of a blue print for the nurse duty roster using a 0-1 goal programming technique. The appropriate working period for this blue print is formulated based on the number of night shifts and the number of required nurses for night shift per schedule. Subsequently, the blue print is repeated to complete the annual nurse duty roster. These newly developed procedures were then tested on several data sets. The test results found that the master plan has successfully distributed the annual workload evenly among nurses. In addition, the master plan allows nurses to arrange their career and social activities in advance.

  2. Development of new techniques of using irradiation in the genetic improvement of warm season grasses and an assessment of the genetic and cytogenetic effects. Progress report, November 1, 1977--October 31, 1978

    International Nuclear Information System (INIS)

    Hanna, W.W.; Burton, G.W.

    1978-05-01

    Progress is reported on plant breeding programs for the genetic improvement of warm season grasses using irradiation as a tool. Data are included from studies on alteration of the protein quantity and quality in pearl millet grain by irradiation and mutation breeding; the effects of nitrogen and genotype on pearl millet grain; the effects of seed size on quality in pearl millet; irradiation breeding of sterile triploid turf Bermuda grasses; irradiation breeding of sterile coastcross-1, a forage grass, to increase winter hardiness; use of irradiation to induce resistance to rust disease; and an economic assessment of irradiation-induced mutants for plant breeding programs

  3. Towards mosquito sterile insect technique programmes: Exploring genetic, molecular, mechanical and behavioural methods of sex separation in mosquitoes

    Czech Academy of Sciences Publication Activity Database

    Gilles, J. R. L.; Schetelig, M. F.; Scolari, F.; Marec, František; Capurro, M.L.; Franz, G.; Bourtzis, K.

    132S, č. 1 (2014), S178-S187 ISSN 0001-706X R&D Projects: GA ČR GA523/09/2106 Grant - others:Deutsche Forschungsgemeinschalft(DE) SCHE 1833/1 Institutional support: RVO:60077344 Keywords : female elimination * vector control * genetic sexing strains (GSS) Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.270, year: 2014 http://www.sciencedirect.com/science/article/pii/S0001706X13002209?via=ihub

  4. Genetic sexing strains in Mediterranean fruit fly, an example for other species amenable to large-scale rearing for the sterile insect technique

    International Nuclear Information System (INIS)

    Franz, G.

    2005-01-01

    Through genetic and molecular manipulations, strains can be developed that are more suitable for the sterile insect technique (SIT). In this chapter the development of genetic sexing strains (GSSs) is given as an example. GSSs increase the effectiveness of area-wide integrated pest management (AW-IPM) programmes that use the SIT by enabling the large-scale release of only sterile males. For species that transmit disease, the removal of females is mandatory. For the Mediterranean fruit fly Ceratitis capitata (Wiedemann), genetic sexing systems have been developed; they are stable enough to be used in operational programmes for extended periods of time. Until recently, the only way to generate such strains was through Mendelian genetics. In this chapter, the basic principle of translocation-based sexing strains is described, and Mediterranean fruit fly strains are used as examples to indicate the problems encountered in such strains. Furthermore, the strategies used to solve these problems are described. The advantages of following molecular strategies in the future development of sexing strains are outlined, especially for species where little basic knowledge of genetics exists. (author)

  5. Use of novel DNA fingerprinting techniques for the detection and characterization of genetic variation in vegetatively propagated crops. Proceedings of a final research co-ordination meeting

    International Nuclear Information System (INIS)

    1998-10-01

    Vegetative propagated crops, such as banana and platain, sweet potato, yam, sugarcane and cassava, represent important sources of food in the developing countries. Although some of these crops may produce seeds, they must for practical purposes be propagated vegetatively. As normal plant breeding strategies based on genetic hybridization are of limited value or not applicable to such crops, it is necessary to assess the genetic diversity already existing in these crops and to design breeding strategies accordingly. If the existing genetic variation is shown to be too narrow for breeding purposes, one promising possibility for the introduction of genetic variability is the use of mutations induced by radiation or chemical mutagens. This CRP focused on: the detection of genetic diversity induced by mutagenic treatment or in vitro culture; the development of crop-specific markers; and increasing co-operation between molecular biologists in advanced laboratories and plant breeders and molecular biologists in the developing countries. The success of this CRP is evidenced by the introduction and application of new molecular methods by laboratories in developing countries, specially for the analysis of local crop genetic diversity. These exciting preliminary results show the potential for applications in crop improvement but much work remains to be done. Many of the vegetatively propagated species are ''orphan crops'', under-investigated on the international level. The development of new uses of transgenesis for the development of edible vaccines should not be overlooked. The challenge that remains is in the application of these new tools for practical end-user oriented improvements in vegetatively propagated crops. The present publication summarizes the third and final Research Co-ordination Meeting on the Use of Novel DNA Fingerprinting Techniques for the Detection and Characterization of Genetic Variation in Vegetatively Propagated Crops

  6. Use of novel DNA fingerprinting techniques for the detection and characterization of genetic variation in vegetatively propagated crops. Proceedings of a final research co-ordination meeting

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-10-01

    Vegetative propagated crops, such as banana and platain, sweet potato, yam, sugarcane and cassava, represent important sources of food in the developing countries. Although some of these crops may produce seeds, they must for practical purposes be propagated vegetatively. As normal plant breeding strategies based on genetic hybridization are of limited value or not applicable to such crops, it is necessary to assess the genetic diversity already existing in these crops and to design breeding strategies accordingly. If the existing genetic variation is shown to be too narrow for breeding purposes, one promising possibility for the introduction of genetic variability is the use of mutations induced by radiation or chemical mutagens. This CRP focused on: the detection of genetic diversity induced by mutagenic treatment or in vitro culture; the development of crop-specific markers; and increasing co-operation between molecular biologists in advanced laboratories and plant breeders and molecular biologists in the developing countries. The success of this CRP is evidenced by the introduction and application of new molecular methods by laboratories in developing countries, specially for the analysis of local crop genetic diversity. These exciting preliminary results show the potential for applications in crop improvement but much work remains to be done. Many of the vegetatively propagated species are ``orphan crops``, under-investigated on the international level. The development of new uses of transgenesis for the development of edible vaccines should not be overlooked. The challenge that remains is in the application of these new tools for practical end-user oriented improvements in vegetatively propagated crops. The present publication summarizes the third and final Research Co-ordination Meeting on the Use of Novel DNA Fingerprinting Techniques for the Detection and Characterization of Genetic Variation in Vegetatively Propagated Crops Refs, figs, tabs

  7. The application of neutral network integrated with genetic algorithm and simulated annealing for the simulation of rare earths separation processes by the solvent extraction technique using EHEHPA agent

    International Nuclear Information System (INIS)

    Tran Ngoc Ha; Pham Thi Hong Ha

    2003-01-01

    In the present work, neutral network has been used for mathematically modeling equilibrium data of the mixture of two rare earth elements, namely Nd and Pr with PC88A agent. Thermo-genetic algorithm based on the idea of the genetic algorithm and the simulated annealing algorithm have been used in the training procedure of the neutral networks, giving better result in comparison with the traditional modeling approach. The obtained neutral network modeling the experimental data is further used in the computer program to simulate the solvent extraction process of two elements Nd and Pr. Based on this computer program, various optional schemes for the separation of Nd and Pr have been investigated and proposed. (author)

  8. Novel Techniques and Their Wide Applications to Health Foods, Medical and Agricultural Biotechnology in Relation to Policy Making on Genetically Modified Crops and Foods

    CERN Document Server

    Baianu, I C; Lozano, P; Lin, H C

    2004-01-01

    Selected applications of novel techniques in Agricultural Biotechnology, Health Food formulations and Medical Biotechnology are being reviewed with the aim of unraveling future developments and policy changes that are likely to open new markets for Biotechnology and prevent the shrinking or closing of existing ones. Amongst the selected novel techniques with applications in both Agricultural and Medical Biotechnology are: immobilized bacterial cells and enzymes, microencapsulation and liposome production, genetic manipulation of microorganisms, development of novel vaccines from plants, epigenomics of mammalian cells and organisms, and biocomputational tools for molecular modeling related to disease and Bioinformatics. Both fundamental and applied aspects of the emerging new techniques are being discussed in relation to their anticipated, marked impact on future markets and present policy changes that are needed for success in either Agricultural or Medical Biotechnology. The novel techniques are illustrated ...

  9. Comparison the Impact of Spark Motor Program and Basketball Techniques on Improving Gross Motor Skills in Educable Intellectually Disabled Boys

    Directory of Open Access Journals (Sweden)

    Hashem Faal Moghanlo

    2014-09-01

    Full Text Available Background & objectives : Different types of practises are known for improving motor skills in intellectually disabled boys. The purpose of this study was to compar e the impact of spark motor program and basketball on improving of gross motor skills in this people.   Methods: In this semi-experimental study , from 98 educable intellectually disabled students who studied in special school in Urmia, 30 children ( age range of 9 to 13 years and IQ mean 64.4 were selected objectively and divided in three groups (2 experimental and 1 control based on pre - test. BOTMP was used as a measurement of motor ability. Selected motor program (Spark motor program including strengthening training, games, sports and basketball techniques was performed for 24 sessions. T-tests (dependent and co-variance were used to comparison of results.   Results: In Spark group after 24 sessions, there were significant effects on balance (p= 0.000, bilateral coordination (p=0.000 and strength (p=0.001. There was no significant effect in agility and speed (p= 0.343 in basketball techniques group after 24 sessions, there were significant effects in agility and speed (p= 0.001, balance (p= 0.000, bilateral coordination (p= 0.013 and strength (p= 0.007.   Conclusion: Based on the results of this study, it can be claimed that the Spark program and basketball techniques improve gross motor skills in educable intellectually disabled students. We also found a significant difference between the Spark program and basketball techniques efficacy on the improved skills. Furthermore, the efficacy of Spark program was significantly higher than basketball techniques (p<0.05.

  10. Validating competencies for an undergraduate training program in rural medicine using the Delphi technique.

    Science.gov (United States)

    Gouveia, Eneline Ah; Braga, Taciana D; Heráclio, Sandra A; Pessoa, Bruno Henrique S

    2016-01-01

    Worldwide, half the population lives in rural or remote areas; however, less than 25% of doctors work in such regions. Despite the continental dimensions of Brazil and its enormous cultural diversity, only some medical schools in this country offer students the opportunity to acquire work experience focused on medicine in rural or remote areas. The objective of the present study was to develop a framework of competencies for a longitudinal medical training program in rural medicine as an integrated part of medical training in Brazil. Two rounds of a modified version of the Delphi technique were conducted. Initially, a structured questionnaire was elaborated, based on a literature review. This questionnaire was submitted to the opinion of 20 panelists affiliated with the Rural Medicine Working Party of the Brazilian Society of Family and Community Medicine. The panelists were asked to evaluate the relevance of the competencies using a five-point Likert-type scale. In this study, the consensus criterion for a competency to be included in the framework was it being deemed 'very important' or 'indispensable' by a simple majority of the participants, while the criterion for excluding a competency was that a simple majority of the panel members considered that it 'should not be included' or was 'of little importance'. When a consensus was not reached regarding a given competency, it was submitted to a second round to enable the panelists to re-evaluate the now dichotomized questions. Compliance in responding to the questionnaire was better among the panelists predominantly involved in teaching activities (85%; n=12) compared to those working principally in patient care (45%; n=8). The questionnaire consisted of 26 core competencies and 165 secondary competencies. After evaluation by the specialists, all the 26 core competencies were classified as relevant, with none being excluded and only eight secondary competencies failing to achieve a consensus. No new competencies

  11. Genetic, nongenetic and epigenetic risk determinants in developmental programming of type 2 diabetes

    DEFF Research Database (Denmark)

    Vaag, Allan; Brøns, Charlotte; Gillberg, Linn

    2014-01-01

    Low birthweight (LBW) individuals and offspring of women with gestational diabetes mellitus (GDM) exhibit increased risk of developing type 2 diabetes (T2D) and associated cardiometabolic traits in adulthood, which for both groups may be mediated by adverse events and developmental changes in fetal...... factors. Indeed, it has been shown that genetic changes influencing risk of diabetes may also be associated with reduced fetal growth as a result of reduced insulin secretion and/or action. Similarly, increased risk of T2D among offspring could be explained by T2D susceptibility genes shared between...... life. T2D is a multifactorial disease occurring as a result of complicated interplay between genetic and both prenatal and postnatal nongenetic factors, and it remains unknown to what extent the increased risk of T2D associated with LBW or GDM in the mother may be due to, or confounded by, genetic...

  12. Genetics of the Mediterranean fruit fly, Ceratitis capitata (Wied.), as a tool in the sterile insect technique

    International Nuclear Information System (INIS)

    Roessler, Y.; Rosenthal, H.

    1990-01-01

    The report covers a period of five years of studies on the genetics of the Mediterranean fruit fly (medfly), Ceratitis capitata (Wied.), and genetic sexing. Fourteen morphological mutants were isolated during that period, including gr, ru, ro Sr, Sp, ew, br, sb and six yet unstudied mutants. Additional data were accumulated on genetic recombination between the various marked loci in males and females, and genetic maps were constructed. Recombination in males were found to be rather common in the medfly and not associated with the presence of chromosomal aberrations or with a particular chromosome. It seemed, however, that the dominant mutants that have been studied had a higher frequency of recombination in males, which almost matched the recombination levels encountered in the females. Initial steps towards the construction of genetic sexing strains were conducted. Selection for resistance to certain chemicals (potassium sorbate, Avermectin and Cyromazine) was carried out with limited success. Lines with high immunity to the three chemicals were established, and the mode of inheritance to Cyromazine and potassium sorbate was studied. Indications were that Cyromazine resistance was recessive and governed by a single gene whereas potassium sorbate resistance seemed to be a quantitative trait. (author). 14 refs, 8 tabs

  13. Problem Based Learning Technique and Its Effect on Acquisition of Linear Programming Skills by Secondary School Students in Kenya

    Science.gov (United States)

    Nakhanu, Shikuku Beatrice; Musasia, Amadalo Maurice

    2015-01-01

    The topic Linear Programming is included in the compulsory Kenyan secondary school mathematics curriculum at form four. The topic provides skills for determining best outcomes in a given mathematical model involving some linear relationship. This technique has found application in business, economics as well as various engineering fields. Yet many…

  14. Assessing and mitigating risks of engineering programs with lean management techniques

    DEFF Research Database (Denmark)

    Fritz, A.; Oehmen, Josef; Rebentisch, E.

    2014-01-01

    for a specific program are identified and how the effort for implementation of these lean best practices is estimated. Large-scale engineering programs have as results usually complex technical products or systems such as airplanes, satellites (GPS) or software programs, immense infrastructure efforts like...

  15. Cost avoidance techniques through the Fernald controlled area trash segregation program and the RIMIA solid waste reduction program

    International Nuclear Information System (INIS)

    Menche, C.E.

    1997-01-01

    The Fernald Environmental Management Project is a Department of Energy owned facility that produced high quality uranium metals for military defense. The Fernald mission has changed from one of production to remediation. Remediation is intended to clean up legacy (primary) waste from past practices. Little opportunity is available to reduce the amount of primary waste. However, there is an opportunity to reduce secondary waste generation, primarily through segregation. Two programs which accomplish this are the Controlled Area Trash Segregation Program and the RIMIA Solid Waste Reduction Program. With these two programs now in place at the FEMP, it has been estimated that a 60% reduction has been achieved in unnecessary clean waste being disposed as Low Level Waste at the Nevada Test Site. The cost savings associated with these programs (currently 79,000 cubic feet, $428,000) could easily run into the millions of dollars based on the upcoming restoration activities to be undertaken. The segregation of non-radiological waste in the radiologically Controlled Area not only establishes a firm commitment to send only low-level radioactive waste to the Nevada Test Site, but also results in substantial cost avoidance

  16. Genetics of tsetse fly. Part of a coordinated programme on sterile insect techniques for tsetse fly control or eradication

    International Nuclear Information System (INIS)

    Helle, W.

    1977-08-01

    Genetic variation in the tsetse fly, Glossina m. morsitans was studied using isoenzyme patterns. As the investigators intended to show that the method could be used for field collected material, several factors which may affect isoenzyme analysis such as fly age, reproductive status, nutrition, storage at low temperatures etc. were studied. Fifteen enzyme systems were included. Seven of these showed genetic polymorphism and some differences were related to geographic distribution. Because of interference from various factors, it is recommended that pupae be collected and that flies be analyzed at least 24 hours after the last blood meal. Methods of holding material for analysis are suggested

  17. Improving the sterile sperm identification method for its implementation in the area-wide sterile insect technique program against Ceratitis capitata (Diptera: Tephritidae) in Spain

    International Nuclear Information System (INIS)

    Juan-Blasco, M.; Urbaneja, A.; San Andrés, V.; Sabater-Muñoz, B.; Castañera, P.

    2014-01-01

    The success of sterile males in area-wide sterile insect technique (aw-SIT) programs against Ceratitis capitata (Wiedemann) is currently measured by using indirect methods as the wild: sterile male ratio captured in monitoring traps. In the past decade, molecular techniques have been used to improve these methods. The development of a polymerase chain reaction-restriction fragment-length polymorphism- based method to identify the transfer of sterile sperm to wild females, the target of SIT, was considered a significant step in this direction. This method relies on identification of sperm by detecting the presence of Y chromosomes in spermathecae DNA extract complemented by the identification of the genetic origin of this sperm: Vienna-8 males or wild haplotype. However, the application of this protocol to aw-SIT programs is limited by handling time and personnel cost. The objective of this work was to obtain a high-throughput protocol to facilitate the routine measurement in a pest population of sterile sperm presence in wild females. The polymerase chain reactionrestriction fragment-length polymorphism markers previously developed were validated in Mediterranean fruit by samples collected from various locations worldwide. A laboratory protocol previously published was modified to allow for the analysis of more samples at the same time. Preservation methods and preservation times commonly used for Mediterranean fruit by female samples were assessed for their influence on the correct molecular detection of sterile sperm. This high-throughput methodology, as well as the results of sample management presented here, provide a robust, efficient, fast, and economical sterile sperm identification method ready to be used in all Mediterranean fruit by SIT programs. (author)

  18. Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

    Science.gov (United States)

    Qiu, J. P.; Niu, D. X.

    Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

  19. Fungal Genetics and Functional Diversity of Microbial Communities in the Soil under Long-Term Monoculture of Maize Using Different Cultivation Techniques

    Directory of Open Access Journals (Sweden)

    Anna Gałązka

    2018-01-01

    Full Text Available Fungal diversity in the soil may be limited under natural conditions by inappropriate environmental factors such as: nutrient resources, biotic and abiotic factors, tillage system and microbial interactions that prevent the occurrence or survival of the species in the environment. The aim of this paper was to determine fungal genetic diversity and community level physiological profiling of microbial communities in the soil under long-term maize monoculture. The experimental scheme involved four cultivation techniques: direct sowing (DS, reduced tillage (RT, full tillage (FT, and crop rotation (CR. Soil samples were taken in two stages: before sowing of maize (DSBS-direct sowing, RTBS-reduced tillage, FTBS-full tillage, CRBS-crop rotation and the flowering stage of maize growth (DSF-direct sowing, RTF-reduced tillage, FTF-full tillage, CRF-crop rotation. The following plants were used in the crop rotation: spring barley, winter wheat and maize. The study included fungal genetic diversity assessment by ITS-1 next generation sequencing (NGS analyses as well as the characterization of the catabolic potential of microbial communities (Biolog EcoPlates in the soil under long-term monoculture of maize using different cultivation techniques. The results obtained from the ITS-1 NGS technique enabled to classify and correlate the fungi species or genus to the soil metabolome. The research methods used in this paper have contributed to a better understanding of genetic diversity and composition of the population of fungi in the soil under the influence of the changes that have occurred in the soil under long-term maize cultivation. In all cultivation techniques, the season had a great influence on the fungal genetic structure in the soil. Significant differences were found on the family level (P = 0.032, F = 3.895, genus level (P = 0.026, F = 3.313 and on the species level (P = 0.033, F = 2.718. This study has shown that: (1 fungal diversity was changed

  20. Determination of genetic differences between fluid and nonfluid variants of Clavibacter michiganensis subsp. sepedonicus using rep-PCR technique

    Czech Academy of Sciences Publication Activity Database

    Fousek, Jan; Mráz, Ivan

    2003-01-01

    Roč. 48, - (2003), s. 682-686 ISSN 0015-5632 R&D Projects: GA ČR GA522/00/0887; GA AV ČR IBS5051014 Keywords : Clavibacter michiganensis * genetic markers Subject RIV: EE - Microbiology, Virology Impact factor: 0.857, year: 2003

  1. DNA Commission of the International Society for Forensic Genetics: Recommendations on the validation of software programs performing biostatistical calculations for forensic genetics applications.

    Science.gov (United States)

    Coble, M D; Buckleton, J; Butler, J M; Egeland, T; Fimmers, R; Gill, P; Gusmão, L; Guttman, B; Krawczak, M; Morling, N; Parson, W; Pinto, N; Schneider, P M; Sherry, S T; Willuweit, S; Prinz, M

    2016-11-01

    The use of biostatistical software programs to assist in data interpretation and calculate likelihood ratios is essential to forensic geneticists and part of the daily case work flow for both kinship and DNA identification laboratories. Previous recommendations issued by the DNA Commission of the International Society for Forensic Genetics (ISFG) covered the application of bio-statistical evaluations for STR typing results in identification and kinship cases, and this is now being expanded to provide best practices regarding validation and verification of the software required for these calculations. With larger multiplexes, more complex mixtures, and increasing requests for extended family testing, laboratories are relying more than ever on specific software solutions and sufficient validation, training and extensive documentation are of upmost importance. Here, we present recommendations for the minimum requirements to validate bio-statistical software to be used in forensic genetics. We distinguish between developmental validation and the responsibilities of the software developer or provider, and the internal validation studies to be performed by the end user. Recommendations for the software provider address, for example, the documentation of the underlying models used by the software, validation data expectations, version control, implementation and training support, as well as continuity and user notifications. For the internal validations the recommendations include: creating a validation plan, requirements for the range of samples to be tested, Standard Operating Procedure development, and internal laboratory training and education. To ensure that all laboratories have access to a wide range of samples for validation and training purposes the ISFG DNA commission encourages collaborative studies and public repositories of STR typing results. Published by Elsevier Ireland Ltd.

  2. Sectoral programming mission isotope techniques for geothermal development. Philippines. UNDP sectoral support

    International Nuclear Information System (INIS)

    Froehlich, K.; Sun, Y.

    1995-10-01

    This report discusses the accomplishments of IAEA Technical Cooperation project PHI/8/016 ''Isotope Techniques in Geothermal Hydrology''. It is intended to help Philippine National Oil Company's Energy Development Corporation (PNOC-EDC) in use of isotope techniques for geothermal development. This report discusses outcomes of the mission, conclusions and recommendations on applications of isotopes techniques in geothermal agro-industrial plants and geothermal hydrology

  3. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

  4. Evaluating the Accreditation Council on Graduate Medical Education core clinical competencies: techniques and feasibility in a urology training program.

    Science.gov (United States)

    Miller, David C; Montie, James E; Faerber, Gary J

    2003-10-01

    We describe several traditional and novel techniques for teaching and evaluating the Accreditation Council on Graduate Medical Education (ACGME) core clinical competencies in a urology residency training program. The evolution and underpinnings of the ACGME Outcome Project were reviewed. Several publications related to the evaluation of clinical competencies as well as current assessment techniques at our institution were also analyzed. Several tools for the assessment of clinical competencies have been developed and refined in response to the ACGME Outcome project. Standardized patient encounters and expanded patient satisfaction surveys may prove useful with regard to assessing resident professionalism, patient care and communication skills. A feasible and possibly undervalued technique for evaluating a number of core competencies is the implementation of formal written appraisals of the nature and quality of resident performance at departmental conferences. The assessment of competency in practice based learning and systems based practice may be achieved through innovative exercises, such as practice guideline development, that assess the evidence for various urologic interventions as well as the financial and administrative aspects of such care. We describe several contemporary methods for teaching and evaluating the core clinical competencies in a urology training program. While the techniques described are neither comprehensive nor feasible for every program, they nevertheless provide an important starting point for a meaningful exchange of ideas in the urological graduate medical education community.

  5. The Potential of the Sterile Insect Technique and other Genetic Methods for Control of Malaria-Transmitting Mosquitoes. Report of a Consultants Meeting

    International Nuclear Information System (INIS)

    1996-01-01

    This report updates information provided by a 1993 consultant group on the use of genetic methods for control of malaria-transmitting mosquitoes. Human malaria parasites of the genus Plasmodium are exclusively transmitted by mosquitoes of the genus Anopheles. Where these two groups co-exist, the transmission of the parasite to humans can create a major health problem. Malaria currently causes 2 million deaths world-wide and approximately 400 million clinical cases annually. There are ca. 15 major vector species and 30-40 vectors of lesser importance. This report considers the practicality of developing the sterile insect technique (SIT) or other genetic mechanisms in order to eradicate mosquito vectors from specific areas. This would interrupt transmission and eliminate malaria in those areas.

  6. Complex polarimetric and spectral techniques in diagnostics of blood plasma of patients with ovarian cancer as a preliminary stage molecular genetic screening

    Science.gov (United States)

    Grzegorzewski, B.; Peresunko, O. P.; Yermolenko, S. B.

    2018-01-01

    This work is devoted to the substantiation and selection of patients with ovarian cancer (OC) for the purpose of conducting expensive molecular genetic studies on genotyping. As diagnostic methods have been used ultraviolet spectrometry samples of blood plasma in the liquid state, infrared spectroscopy middle range (2,5 - 25 microns) dry residue of plasma polarization and laser diagnostic technique of thin histological sections of biological tissues. Obtained results showed that the use of spectrophotometry in the range of 1000-3000 cm-1 allowed to establish quantitative parameters of the plasma absorption rate of blood of patients in the third group in different ranges, which would allow in the future to conduct an express analysis of the patient's condition (procedure screening) for further molecular-genetic typing on BRCA I and II.

  7. Area program in population genetics. Final report, November 1, 1975-August 31, 1982

    International Nuclear Information System (INIS)

    Chu, E.H.Y.; Gershowitz, H.; Meisler, M.H.; Mohrenweiser, H.W.; Neel, J.V.; Rothman, E.D.; Sing, C.S.

    1982-01-01

    Research results are summarized for the following task areas: (1) Amerindian mutation rates; (2) pilot study of monitoring populations for the frequency of mutation; (3) interdigitation with the biochemical genetics study of the Radiation Effects Research Foundation (Hiroshima, Japan); (4) intraindividual variation in erythrocyte blood group antigens as indicators of somatic mutation; (5) in vitro studies of somatic cell mutation rates; (6) development of approaches to the study of mutation rates; and (7) statistical problems associated with the study of mutation and selection

  8. Intra-Day Trading System Design Based on the Integrated Model of Wavelet De-Noise and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Hongguang Liu

    2016-12-01

    Full Text Available Technical analysis has been proved to be capable of exploiting short-term fluctuations in financial markets. Recent results indicate that the market timing approach beats many traditional buy-and-hold approaches in most of the short-term trading periods. Genetic programming (GP was used to generate short-term trade rules on the stock markets during the last few decades. However, few of the related studies on the analysis of financial time series with genetic programming considered the non-stationary and noisy characteristics of the time series. In this paper, to de-noise the original financial time series and to search profitable trading rules, an integrated method is proposed based on the Wavelet Threshold (WT method and GP. Since relevant information that affects the movement of the time series is assumed to be fully digested during the market closed periods, to avoid the jumping points of the daily or monthly data, in this paper, intra-day high-frequency time series are used to fully exploit the short-term forecasting advantage of technical analysis. To validate the proposed integrated approach, an empirical study is conducted based on the China Securities Index (CSI 300 futures in the emerging China Financial Futures Exchange (CFFEX market. The analysis outcomes show that the wavelet de-noise approach outperforms many comparative models.

  9. Population prevalence of hereditary breast cancer phenotypes and implementation of a genetic cancer risk assessment program in southern Brazil

    Science.gov (United States)

    2009-01-01

    In 2004, a population-based cohort (the Núcleo Mama Porto Alegre - NMPOA Cohort) was started in Porto Alegre, southern Brazil and within that cohort, a hereditary breast cancer study was initiated, aiming to determine the prevalence of hereditary breast cancer phenotypes and evaluate acceptance of a genetic cancer risk assessment (GCRA) program. Women from that cohort who reported a positive family history of cancer were referred to GCRA. Of the 9218 women enrolled, 1286 (13.9%) reported a family history of cancer. Of the 902 women who attended GCRA, 55 (8%) had an estimated lifetime risk of breast cancer ≥ 20% and 214 (23.7%) had pedigrees suggestive of a breast cancer predisposition syndrome; an unexpectedly high number of these fulfilled criteria for Li-Fraumeni-like syndrome (122 families, 66.7%). The overall prevalence of a hereditary breast cancer phenotype was 6.2% (95%CI: 5.67-6.65). These findings identified a problem of significant magnitude in the region and indicate that genetic cancer risk evaluation should be undertaken in a considerable proportion of the women from this community. The large proportion of women who attended GCRA (72.3%) indicates that the program was well-accepted by the community, regardless of the potential cultural, economic and social barriers. PMID:21637504

  10. The retinoblastoma protein regulates hypoxia-inducible genetic programs, tumor cell invasiveness and neuroendocrine differentiation in prostate cancer cells

    Science.gov (United States)

    Labrecque, Mark P.; Takhar, Mandeep K.; Nason, Rebecca; Santacruz, Stephanie; Tam, Kevin J.; Massah, Shabnam; Haegert, Anne; Bell, Robert H.; Altamirano-Dimas, Manuel; Collins, Colin C.; Lee, Frank J.S.; Prefontaine, Gratien G.; Cox, Michael E.; Beischlag, Timothy V.

    2016-01-01

    Loss of tumor suppressor proteins, such as the retinoblastoma protein (Rb), results in tumor progression and metastasis. Metastasis is facilitated by low oxygen availability within the tumor that is detected by hypoxia inducible factors (HIFs). The HIF1 complex, HIF1α and dimerization partner the aryl hydrocarbon receptor nuclear translocator (ARNT), is the master regulator of the hypoxic response. Previously, we demonstrated that Rb represses the transcriptional response to hypoxia by virtue of its association with HIF1. In this report, we further characterized the role Rb plays in mediating hypoxia-regulated genetic programs by stably ablating Rb expression with retrovirally-introduced short hairpin RNA in LNCaP and 22Rv1 human prostate cancer cells. DNA microarray analysis revealed that loss of Rb in conjunction with hypoxia leads to aberrant expression of hypoxia-regulated genetic programs that increase cell invasion and promote neuroendocrine differentiation. For the first time, we have established a direct link between hypoxic tumor environments, Rb inactivation and progression to late stage metastatic neuroendocrine prostate cancer. Understanding the molecular pathways responsible for progression of benign prostate tumors to metastasized and lethal forms will aid in the development of more effective prostate cancer therapies. PMID:27015368

  11. Development of a New Aprepitant Liquisolid Formulation with the Aid of Artificial Neural Networks and Genetic Programming.

    Science.gov (United States)

    Barmpalexis, Panagiotis; Grypioti, Agni; Eleftheriadis, Georgios K; Fatouros, Dimitris G

    2018-02-01

    In the present study, liquisolid formulations were developed for improving dissolution profile of aprepitant (APT) in a solid dosage form. Experimental studies were complemented with artificial neural networks and genetic programming. Specifically, the type and concentration of liquid vehicle was evaluated through saturation-solubility studies, while the effect of the amount of viscosity increasing agent (HPMC), the type of wetting (Soluplus® vs. PVP) and solubilizing (Poloxamer®407 vs. Kolliphor®ELP) agents, and the ratio of solid coating (microcrystalline cellulose) to carrier (colloidal silicon dioxide) were evaluated based on in vitro drug release studies. The optimum liquisolid formulation exhibited improved dissolution characteristics compared to the marketed product Emend®. X-ray diffraction (XRD), scanning electron microscopy (SEM) and a novel method combining particle size analysis by dynamic light scattering (DLS) and HPLC, revealed that the increase in dissolution rate of APT in the optimum liquisolid formulation was due to the formation of stable APT nanocrystals. Differential scanning calorimetry (DSC) and attenuated total reflection FTIR spectroscopy (ATR-FTIR) revealed the presence of intermolecular interactions between APT and liquisolid formulation excipients. Multilinear regression analysis (MLR), artificial neural networks (ANNs), and genetic programming (GP) were used to correlate several formulation variables with dissolution profile parameters (Y 15min and Y 30min ) using a full factorial experimental design. Results showed increased correlation efficacy for ANNs and GP (RMSE of 0.151 and 0.273, respectively) compared to MLR (RMSE = 0.413).

  12. Public Relations for Brazilian Libraries: Process, Principles, Program Planning, Planning Techniques and Suggestions.

    Science.gov (United States)

    Kies, Cosette N.

    A brief overview of the functions of public relations in libraries introduces this manual, which provides an explanation of the public relations (PR) process, including fact-finding, planning, communicating, evaluating, and marketing; some PR principles; a 10-step program that could serve as a model for planning a PR program; a discussion of PR…

  13. An Examination of the Feasibility of Integrating Motivational Interviewing Techniques into FCS Cooperative Extension Programming

    Science.gov (United States)

    Radunovich, Heidi Liss; Ellis, Sarah; Spangler, Taylor

    2017-01-01

    Demonstrating program impact through behavior change is critical for the continued success of Family and Consumer Sciences (FCS) Cooperative Extension programming. However, the literature suggests that simply providing information to participants does not necessarily lead to behavior change. This study pilot tested the integration of Motivational…

  14. Surveillance in Programming Plagiarism beyond Techniques: An Incentive-Based Fishbone Model

    Science.gov (United States)

    Wang, Yanqing; Chen, Min; Liang, Yaowen; Jiang, Yu

    2013-01-01

    Lots of researches have showed that plagiarism becomes a severe problem in higher education around the world, especially in programming learning for its essence. Therefore, an effective strategy for plagiarism surveillance in program learning is much essential. Some literature focus on code similarity algorithm and the related tools can help to…

  15. TCV software test and validation tools and technique. [Terminal Configured Vehicle program for commercial transport aircraft operation

    Science.gov (United States)

    Straeter, T. A.; Williams, J. R.

    1976-01-01

    The paper describes techniques for testing and validating software for the TCV (Terminal Configured Vehicle) program which is intended to solve problems associated with operating a commercial transport aircraft in the terminal area. The TCV research test bed is a Boeing 737 specially configured with digital computer systems to carry out automatic navigation, guidance, flight controls, and electronic displays research. The techniques developed for time and cost reduction include automatic documentation aids, an automatic software configuration, and an all software generation and validation system.

  16. Development of quality control procedures for mass produced and released Bactrocera Philippinensis (Diptera: Tephritidae) for sterile insect technique programs

    International Nuclear Information System (INIS)

    Resilva, S.; Obra, G.; Zamora, N.; Gaitan, E.

    2007-01-01

    Quality control procedures for Bactrocera philippinensis Drew and Hancock 1994 (Diptera: Tephritidae) used in sterile insect technique (SIT) programs were established in the mass rearing facility at the Philippine Nuclear Research Institute. Basic studies on pupal irradiation, holding/packaging systems, shipping procedures, longevity, sterility studies, and pupal eye color determination in relation to physiological development at different temperature regimes were investigated. These studies will provide baseline data for the development of quality control protocols for an expansion of B. philippinensis field programs with an SIT component in the future. (author) [es

  17. Visceral angiography with intra-arterial DSA and a programmed 100 mm technique

    International Nuclear Information System (INIS)

    Triller, J.; Ackermann, B.; Jung, H.

    1988-01-01

    One hundred and seventy specially selected visceral angiograms were carried out of 96 patients using I-A DSA and 100 mm technique. 85.2% of the I-A DSA and 91.7% of the 100 mm images were of good quality. I-A DSA produced comparable or better quality than the 100 mm technique in 66% during the arterial phase, in 79% during the paranchymatous phase and in 70% during the venous phase. The 100 mm technique produced better quality in a third of the cases during the arterial phase and in a quarter of the cases during the parenchymal and venous phases. The indications for the 100 mm technique are failure of I-A DSA or the need for high spatial resolution. (orig.) [de

  18. Ethical dilemmas in genetic testing: examples from the Cuban program for predictive diagnosis of hereditary ataxias.

    Science.gov (United States)

    Mariño, Tania Cruz; Armiñán, Rubén Reynaldo; Cedeño, Humberto Jorge; Mesa, José Miguel Laffita; Zaldivar, Yanetza González; Rodríguez, Raúl Aguilera; Santos, Miguel Velázquez; Mederos, Luis Enrique Almaguer; Herrera, Milena Paneque; Pérez, Luis Velázquez

    2011-06-01

    Predictive testing protocols are intended to help patients affected with hereditary conditions understand their condition and make informed reproductive choices. However, predictive protocols may expose clinicians and patients to ethical dilemmas that interfere with genetic counseling and the decision making process. This paper describes ethical dilemmas in a series of five cases involving predictive testing for hereditary ataxias in Cuba. The examples herein present evidence of the deeply controversial situations faced by both individuals at risk and professionals in charge of these predictive studies, suggesting a need for expanded guidelines to address such complexities.

  19. Application of Fluorescence In Situ Hybridization (FISH) Technique for the Detection of Genetic Aberration in Medical Science

    OpenAIRE

    Ratan, Zubair Ahmed; Zaman, Sojib Bin; Mehta, Varshil; Haidere, Mohammad Faisal; Runa, Nusrat Jahan; Akter, Nasrin

    2017-01-01

    Fluorescence in situ hybridization (FISH) is a macromolecule recognition technique, which is considered as a new advent in the field of cytology.?Initially, it was developed as a physical mapping tool to delineate genes within chromosomes. The accuracy and versatility of FISH were subsequently capitalized upon in biological and medical research. This visually appealing technique provides an intermediate degree of resolution between DNA analysis and chromosomal investigations. FISH consists of...

  20. A Comparison of Functional and Imperative Programming Techniques for Mathematical Software Development

    Directory of Open Access Journals (Sweden)

    Scott Frame

    2014-04-01

    Full Text Available Functional programming has traditionally been considered elegant and powerful, but also somewhat impractical for ordinary computing. Proponents of functional programming claim that the evolution of functional languages makes their use feasible in many domains. In this work, a popular imperative language (C++ and the leading functional language (Haskell are compared in a math-intensive, real-world application using a variety of criteria: ease of implementation, efficiency, and readability. The programming tasks that were used as benchmarks involved mathematical transformations between local and global coordinate systems. Details regarding the application area and how language features of both languages were used to solve critical problems are described. The paper closes with some conclusions regarding applicability of functional programming for mathematical applications.

  1. Multi-image screening technique applied to a general orientation training program

    International Nuclear Information System (INIS)

    Hajek, B.K.; Campbell, T.O.; Evans, A.D.; Hickey, J.M.

    1979-01-01

    A general orientation and training program is a prerequisite for personnel to have unescorted access to various site locations at a nuclear power plant. A new general orientation and training program is being developed for the Toledo Edison Company to be used at the Davis-Besse Nuclear Power Station. The program is presented in a multi-image and stereo sound format that has the unique capability to present the magnitude and scale of the plant, to arouse and maintain the interest of the viewer, and to instill in him a feeling of importance and pride about his job. Satisfactory completion of the program by individuals is assessed and certified by a machine scored test that is administered as an integral part of the presentation

  2. Design and performance evaluations of generic programming techniques in a R and D prototype of Geant4 physics

    Energy Technology Data Exchange (ETDEWEB)

    Pia, M G; Saracco, P; Sudhakar, M [INFN Sezione di Genova, Via Dodecaneso 33, 16146 Genova (Italy); Zoglauer, A [University of California at Berkeley, Berkeley, CA 94720-7450 (United States); Augelli, M [CNES, 18 Av. Edouard Belin, 31401 Toulouse (France); Gargioni, E [University Medical Center Hamburg-Eppendorf, D-20246 Hamburg (Germany); Kim, C H [Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul, 133-791 (Korea, Republic of); Quintieri, L [INFN Laboratori Nazionali di Frascati, Via Enrico Fermi 40, I-00044 Frascati (Italy); Filho, P P de Queiroz; Santos, D de Souza [IRD, Av. Salvador Allende, s/n. 22780-160, Rio de Janeiro, RJ (Brazil); Weidenspointner, G [MPI fuer extraterrestrische Physik Postfach 1603, D-85740 Garching (Germany); Begalli, M, E-mail: mariagrazia.pia@ge.infn.i [UERJ, R. Sao Francisco Xavier, 524. 20550-013, Rio de Janeiro, RJ (Brazil)

    2010-04-01

    A R and D project has been recently launched to investigate Geant4 architectural design in view of addressing new experimental issues in HEP and other related physics disciplines. In the context of this project the use of generic programming techniques besides the conventional object oriented is investigated. Software design features and preliminary results from a new prototype implementation of Geant4 electromagnetic physics are illustrated. Performance evaluations are presented. Issues related to quality assurance in Geant4 physics modelling are discussed.

  3. Application of the successive linear programming technique to the optimum design of a high flux reactor using LEU fuel

    International Nuclear Information System (INIS)

    Mo, S.C.

    1991-01-01

    The successive linear programming technique is applied to obtain the optimum thermal flux in the reflector region of a high flux reactor using LEU fuel. The design variables are the reactor power, core radius and coolant channel thickness. The constraints are the cycle length, average heat flux and peak/average power density ratio. The characteristics of the optimum solutions with various constraints are discussed

  4. The effect of a 3-month prevention program on the jump-landing technique in basketball: a randomized controlled trial.

    Science.gov (United States)

    Aerts, Inne; Cumps, Elke; Verhagen, Evert; Wuyts, Bram; Van De Gucht, Sam; Meeusen, Romain

    2015-02-01

    In jump-landing sports, the injury mechanism that most frequently results in an injury is the jump-landing movement. Influencing the movement patterns and biomechanical predisposing factors are supposed to decrease injury occurrence. To evaluate the influence of a 3-mo coach-supervised jump-landing prevention program on jump-landing technique using the jump-landing scoring (JLS) system. Randomized controlled trial. On-field. 116 athletes age 15-41 y, with 63 athletes in the control group and 53 athletes in the intervention group. The intervention program in this randomized control trial was administered at the start of the basketball season 2010-11. The jump-landing training program, supervised by the athletic trainers, was performed for a period of 3 mo. The jump-landing technique was determined by registering the jump-landing technique of all athletes with the JLS system, pre- and postintervention. After the prevention program, the athletes of the male and female intervention groups landed with a significantly less erect position than those in the control groups (P < .05). This was presented by a significant improvement in maximal hip flexion, maximal knee flexion, hip active range of motion, and knee active range of motion. Another important finding was that postintervention, knee valgus during landing diminished significantly (P < .05) in the female intervention group compared with their control group. Furthermore, the male intervention group significantly improved (P < .05) the scores of the JLS system from pre- to postintervention. Malalignments such as valgus position and insufficient knee flexion and hip flexion, previously identified as possible risk factors for lower-extremity injuries, improved significantly after the completion of the prevention program. The JLS system can help in identifying these malalignments. Therapy, prevention, level 1b.

  5. Neutron radiography activity in the european program cost 524: Neutron imaging techniques

    International Nuclear Information System (INIS)

    Chirco, P.; Bach, P.; Lehmann, E.; Balasko, M.

    2001-01-01

    COST is a framework for scientific and technical cooperation, allowing the coordination of national research on a European level, including 32 member countries. Participation of institutes from non-COST countries is possible. From an initial 7 Actions in 1971, COST has grown to 200 Actions at the beginning of 2000. COST Action 524 is under materials domain, the title of which being 'Neutron Imaging Techniques for the Detection of Defects in Materials', under the Chairmanship of Dr. P. Chirco (I.N.F.N.). The following countries are represented in the Management Committee of Action 524: Italy, France, Austria, Germany, United Kingdom, Hungary, Switzerland, Spain, Czech Republic, Slovenia, and Russia. The six working groups of this Action are working respectively on standardization of neutron radiography techniques, on aerospace application, on civil engineering applications, on comparison and integration of neutron imaging techniques with other NDT, on neutron tomography, and on non radiographic techniques such as neutron scattering techniques. A specific effort is devoted to standardization issues, with respect to other non European standards. Results of work performed in the COST frame are published or will be published in the review INSIGHT, edited by the British Institute of Non Destructive Testing

  6. Genetic improvement of under-utilized and neglected crops in low income food deficit countries through irradiation and related techniques. Proceedings of a final research coordination meeting

    International Nuclear Information System (INIS)

    2004-11-01

    The majority of the world's food is produced from only a few crops, and yet many neglected and under-utilized crops are extremely important for food production in low income food deficit countries (LIFDCs). As the human population grows at an alarming rate in LIFDCs, food availability has declined and is also affected due to environmental factors, lack of improvement of local crop species, erosion of genetic diversity and dependence on a few crop species for food supply. Neglected crops are traditionally grown by farmers in their centres of origin or centres of diversity, where they are still important for the subsistence of local communities, and maintained by socio-cultural preferences and traditional uses. These crops remain inadequately characterised and, until very recently, have been largely ignored by research and conservation. Farmers are losing these crops because they are less competitive with improved major crop species. Radiation-induced mutation techniques have successfully been used that benefited the most genetic improvement of 'major crops' and their know-how have a great potential for enhancing the use of under-utilized and neglected species and speeding up their domestication and crop improvement. The FAO/IAEA efforts on genetic improvement of under-utilized and neglected species play a strategic role in complementing the work that is being carried out worldwide in their promotion. This CRP entitled Genetic Improvement of Under-utilized and Neglected Crops in LIFDCs through Irradiation and Related Techniques was initiated in 1998 with an overall objective to improve food security, enhance nutritional balance, and promote sustainable agriculture in LIFDCs. Specific objectives addressed major constraints to productivity of neglected and under-utilized crops by genetic improvement with radiation-induced mutations and biotechnology in order to enhance economic viability and sustain crop species diversity, and in future to benefit small farmers. This

  7. THE USE THE GENETICALLY DIFFICULTLY INHERITED TRAIT OF PURPLE ROOT COLOR IN BREEDING PROGRAM FOR THE COMPLICATED TRAIT IN RADISH

    Directory of Open Access Journals (Sweden)

    S. V. Ugarova

    2017-01-01

    Full Text Available The understanding the nature of trait inheritance in any crops is that determines the quality of results in breeding program. According to reference on previous publication, it is known that phenotypic manifestation of purple root color in radish was caused by regulatory interrelationship mechanisms of genetic control that is difficult to be used directly in breeding program. From literature sources and on the basis of their own research work the authors have proven the practice to maintain the trait in generations, and implementations of development of purple radish breeding accessions have been presented. At first stage of breeding program the selection of initial breeding accessions was carried out, where 14 varieties (red x white were regarded on the basis of top-crosses to obtain F1 and F2 progenies to be analyzed. Thus, four best combinations from crossing were chosen with 100% of hybridity. Through analysis of hybrids for individual progenies the hybrid population F1 of radish ‘Konfeti’ with different root colors was developed. As result of the individual inbreeding selection on seed plants with pigmented stems and the colored flower rim, the stable breeding accession with purple root was obtained. Thus, in breeding practice in radish it was succeeded to obtain the stably inheriting purple root color in radish accessions, variety ‘Siniiy Iniey’. 

  8. Constraint Solver Techniques for Implementing Precise and Scalable Static Program Analysis

    DEFF Research Database (Denmark)

    Zhang, Ye

    solver using unification we could make a program analysis easier to design and implement, much more scalable, and still as precise as expected. We present an inclusion constraint language with the explicit equality constructs for specifying program analysis problems, and a parameterized framework...... developers to build reliable software systems more quickly and with fewer bugs or security defects. While designing and implementing a program analysis remains a hard work, making it both scalable and precise is even more challenging. In this dissertation, we show that with a general inclusion constraint...... data flow analyses for C language, we demonstrate a large amount of equivalences could be detected by off-line analyses, and they could then be used by a constraint solver to significantly improve the scalability of an analysis without sacrificing any precision....

  9. Intuitionistic Fuzzy Goal Programming Technique for Solving Non-Linear Multi-objective Structural Problem

    Directory of Open Access Journals (Sweden)

    Samir Dey

    2015-07-01

    Full Text Available This paper proposes a new multi-objective intuitionistic fuzzy goal programming approach to solve a multi-objective nonlinear programming problem in context of a structural design. Here we describe some basic properties of intuitionistic fuzzy optimization. We have considered a multi-objective structural optimization problem with several mutually conflicting objectives. The design objective is to minimize weight of the structure and minimize the vertical deflection at loading point of a statistically loaded three-bar planar truss subjected to stress constraints on each of the truss members. This approach is used to solve the above structural optimization model based on arithmetic mean and compare with the solution by intuitionistic fuzzy goal programming approach. A numerical solution is given to illustrate our approach.

  10. Management intensity and genetics affect loblolly pine seedling performance

    Science.gov (United States)

    Scott D. Roberts; Randall J. Rousseau; B. Landis Herrin

    2012-01-01

    Capturing potential genetic gains from tree improvement programs requires selection of the appropriate genetic stock and application of appropriate silvicultural management techniques. Limited information is available on how specific loblolly pine varietal genotypes perform under differing growing environments and management approaches. This study was established in...

  11. A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

    Directory of Open Access Journals (Sweden)

    Chandra Nagasuma R

    2009-02-01

    Full Text Available Abstract Background A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN from transcript profiling data. Results The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting problem and solved finally by formulating a Linear Program (LP. A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known

  12. Quality Assurance Audit of Technique Failure and 90-Day Mortality after Program Discharge in a Canadian Home Hemodialysis Program.

    Science.gov (United States)

    Shah, Nikhil; Reintjes, Frances; Courtney, Mark; Klarenbach, Scott W; Ye, Feng; Schick-Makaroff, Kara; Jindal, Kailash; Pauly, Robert P

    2017-07-24

    Little is known about patients exiting home hemodialysis. We sought to characterize the reasons, clinical characteristics, and pre-exit health care team interactions of patients on home hemodialysis who died or underwent modality conversion (negative disposition) compared with prevalent patients and those who were transplanted (positive disposition). We conducted an audit of all consecutive patients incident to home hemodialysis from January of 2010 to December of 2014 as part of ongoing quality assurance. Records were reviewed for the 6 months before exit, and vital statistics were assessed up to 90 days postexit. Ninety-four patients completed training; 25 (27%) received a transplant, 11 (12%) died, and 23 (25%) were transferred to in-center hemodialysis. Compared with the positive disposition group, patients in the negative disposition group had a longer mean dialysis vintage (3.15 [SD=4.98] versus 1.06 [SD=1.16] years; P =0.003) and were performing conventional versus a more intensive hemodialysis prescription (23 of 34 versus 23 of 60; P <0.01). In the 6 months before exit, the negative disposition group had significantly more in-center respite dialysis sessions, had more and longer hospitalizations, and required more on-call care team support in terms of phone calls and drop-in visits (each P <0.05). The most common reason for modality conversion was medical instability in 15 of 23 (65%) followed by caregiver or care partner burnout in three of 23 (13%) each. The 90-day mortality among patients undergoing modality conversion was 26%. Over a 6-year period, approximately one third of patients exited the program due to death or modality conversion. Patients who die or transfer to another modality have significantly higher health care resource utilization ( e.g. , hospitalization, respite treatments, nursing time, etc. ). Copyright © 2017 by the American Society of Nephrology.

  13. Energy management of a power-split plug-in hybrid electric vehicle based on genetic algorithm and quadratic programming

    Science.gov (United States)

    Chen, Zheng; Mi, Chris Chunting; Xiong, Rui; Xu, Jun; You, Chenwen

    2014-02-01

    This paper introduces an online and intelligent energy management controller to improve the fuel economy of a power-split plug-in hybrid electric vehicle (PHEV). Based on analytic analysis between fuel-rate and battery current at different driveline power and vehicle speed, quadratic equations are applied to simulate the relationship between battery current and vehicle fuel-rate. The power threshold at which engine is turned on is optimized by genetic algorithm (GA) based on vehicle fuel-rate, battery state of charge (SOC) and driveline power demand. The optimal battery current when the engine is on is calculated using quadratic programming (QP) method. The proposed algorithm can control the battery current effectively, which makes the engine work more efficiently and thus reduce the fuel-consumption. Moreover, the controller is still applicable when the battery is unhealthy. Numerical simulations validated the feasibility of the proposed controller.

  14. Genetic programming-based mathematical modeling of influence of weather parameters in BOD5 removal by Lemna minor.

    Science.gov (United States)

    Chandrasekaran, Sivapragasam; Sankararajan, Vanitha; Neelakandhan, Nampoothiri; Ram Kumar, Mahalakshmi

    2017-11-04

    This study, through extensive experiments and mathematical modeling, reveals that other than retention time and wastewater temperature (T w ), atmospheric parameters also play important role in the effective functioning of aquatic macrophyte-based treatment system. Duckweed species Lemna minor is considered in this study. It is observed that the combined effect of atmospheric temperature (T atm ), wind speed (U w ), and relative humidity (RH) can be reflected through one parameter, namely the "apparent temperature" (T a ). A total of eight different models are considered based on the combination of input parameters and the best mathematical model is arrived at which is validated through a new experimental set-up outside the modeling period. The validation results are highly encouraging. Genetic programming (GP)-based models are found to reveal deeper understandings of the wetland process.

  15. MetaJC++: A flexible and automatic program transformation technique using meta framework

    Science.gov (United States)

    Beevi, Nadera S.; Reghu, M.; Chitraprasad, D.; Vinodchandra, S. S.

    2014-09-01

    Compiler is a tool to translate abstract code containing natural language terms to machine code. Meta compilers are available to compile more than one languages. We have developed a meta framework intends to combine two dissimilar programming languages, namely C++ and Java to provide a flexible object oriented programming platform for the user. Suitable constructs from both the languages have been combined, thereby forming a new and stronger Meta-Language. The framework is developed using the compiler writing tools, Flex and Yacc to design the front end of the compiler. The lexer and parser have been developed to accommodate the complete keyword set and syntax set of both the languages. Two intermediate representations have been used in between the translation of the source program to machine code. Abstract Syntax Tree has been used as a high level intermediate representation that preserves the hierarchical properties of the source program. A new machine-independent stack-based byte-code has also been devised to act as a low level intermediate representation. The byte-code is essentially organised into an output class file that can be used to produce an interpreted output. The results especially in the spheres of providing C++ concepts in Java have given an insight regarding the potential strong features of the resultant meta-language.

  16. Neurolinguistic Programming: Add It To Your Tool Chest of Interpretive Techniques.

    Science.gov (United States)

    Parratt, Smitty

    1997-01-01

    Highlights the importance of using verbal and nonverbal neurolinguistic programming to maximize the potential of interactions between interpreters and the general public and to improve long-term interactions. Discusses the power of mirroring and representational systems. Contains 29 references. (JRH)

  17. DNA extraction techniques compared for accurate detection of genetically modified organisms (GMOs) in maize food and feed products.

    Science.gov (United States)

    Turkec, Aydin; Kazan, Hande; Karacanli, Burçin; Lucas, Stuart J

    2015-08-01

    In this paper, DNA extraction methods have been evaluated to detect the presence of genetically modified organisms (GMOs) in maize food and feed products commercialised in Turkey. All the extraction methods tested performed well for the majority of maize foods and feed products analysed. However, the highest DNA content was achieved by the Wizard, Genespin or the CTAB method, all of which produced optimal DNA yield and purity for different maize food and feed products. The samples were then screened for the presence of GM elements, along with certified reference materials. Of the food and feed samples, 8 % tested positive for the presence of one GM element (NOS terminator), of which half (4 % of the total) also contained a second element (the Cauliflower Mosaic Virus 35S promoter). The results obtained herein clearly demonstrate the presence of GM maize in the Turkish market, and that the Foodproof GMO Screening Kit provides reliable screening of maize food and feed products.

  18. Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

    Science.gov (United States)

    Kashid, Satishkumar S.; Maity, Rajib

    2012-08-01

    SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

  19. Recommended safety, reliability, quality assurance and management aerospace techniques with possible application by the DOE to the high-level radioactive waste repository program

    International Nuclear Information System (INIS)

    Bland, W.M. Jr.

    1985-05-01

    Aerospace SRQA and management techniques, principally those developed and used by the NASA Lyndon B. Johnson Space Center on the manned space flight programs, have been assessed for possible application by the DOE and the DOE-contractors to the high level radioactive waste repository program that results from the implementation of the NWPA of 1982. Those techniques believed to have the greatest potential for usefulness to the DOE and the DOE-contractors have been discussed in detail and are recommended to the DOE for adoption; discussion is provided for the manner in which this transfer of technology can be implemented. Six SRQA techniques and two management techniques are recommended for adoption by the DOE; included with the management techniques is a recommendation for the DOE to include a licensing interface with the NRC in the application of the milestone reviews technique. Three other techniques are recommended for study by the DOE for possible adaptation to the DOE program

  20. Genetic Algorithm for Mixed Integer Nonlinear Bilevel Programming and Applications in Product Family Design

    OpenAIRE

    Chenlu Miao; Gang Du; Yi Xia; Danping Wang

    2016-01-01

    Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP) to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP), which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard pr...

  1. Genetic screening: programs, principles, and research--thirty years later. Reviewing the recommendations of the Committee for the Study of Inborn Errors of Metabolism (SIEM).

    Science.gov (United States)

    Simopoulos, A P

    2009-01-01

    Screening programs for genetic diseases and characteristics have multiplied in the last 50 years. 'Genetic Screening: Programs, Principles, and Research' is the report of the Committee for the Study of Inborn Errors of Metabolism (SIEM Committee) commissioned by the Division of Medical Sciences of the National Research Council at the National Academy of Sciences in Washington, DC, published in 1975. The report is considered a classic in the field worldwide, therefore it was thought appropriate 30 years later to present the Committee's modus operandi and bring the Committee's recommendations to the attention of those involved in genetics, including organizational, educational, legal, and research aspects of genetic screening. The Committee's report anticipated many of the legal, ethical, economic, social, medical, and policy aspects of genetic screening. The recommendations are current, and future committees should be familiar with them. In 1975 the Committee stated: 'As new screening tests are devised, they should be carefully reviewed. If the experimental rate of discovery of new genetic characteristics means an accelerating rate of appearance of new screening tests, now is the time to develop the medical and social apparatus to accommodate what later on may otherwise turn out to be unmanageable growth.' What a prophetic statement that was. If the Committee's recommendations had been implemented on time, there would be today a federal agency in existence, responsive and responsible to carry out the programs and support research on various aspects of genetic screening, including implementation of a federal law that protects consumers from discrimination by their employers and the insurance industry on the basis of genetic information. Copyright 2008 S. Karger AG, Basel.

  2. Addressing national priorities through nuclear technology: Application of stable isotope techniques in evaluating nutritional intervention programs

    International Nuclear Information System (INIS)

    Mwangi, C.; Ndemwa, P.

    2008-01-01

    The concept is a new concept in Kenya that need driven technology. A paradigm shift from the conventional methods of measuring breast milk intake by means of weighing infants before and after feeding. A validation tool against anthropometrical measures of body fat through body density and skin-fold measurements. A reliable, accurate and non-invasive tool for monitoring lean body mass changes in clinical assessments.Isotopes Techniques in Body composition assessment.Technique-based Parameters of efficacy and/or effect are: Isotope (deuterium) dose given orally to subject (about 30 grams),Saliva (or urine) samples collected after 3-4 hrs, Concentration of isotope in saliva is measured using Fourier Transformed Infra-red Spectrophotometer (FTIR), Concentration gives the Total Body Water (TBW) component in the body, TBW = 73% Fat Free Mass (FFM), Calculate FFM (kg) from equation and subtract from Total Body Weight (kg) to get value of Fat Mass (kg)

  3. Oak Ridge TNS program: study of fueling techniques in support of TNS development

    International Nuclear Information System (INIS)

    Simpson, W.

    1979-12-01

    The objective of this study was to survey fueling techniques and determine which approaches were compatible with the TNS requirements. Specifically, the following tasks were undertaken: survey of existing fueling concepts for use in TNS, determination of available physical properties for D-T fuel pellets, performance of preliminary load analysis of selected pellet acceleration machines, preparation of conceptual designs, and recommendations for follow-up work

  4. The ``SILVA`` program; Le cycle du combustible (evolution des techniques d`enrichissement isotopique)

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, M.

    1996-12-31

    The ``SILVA`` process (Uranium Atomic Vapor Laser Isotopic Separation) is an innovating system of enriched uranium (electronuclear reactors fuel) production. Its great interest comes from its selectivity. The aim is to divide by a factor of three the costs of production compared with those of the current plants. The stakes of this research program, its principle, the main research axis, the material means and the future prospects beyond 1997 are given as well as its technical advancement state. (O.M.).

  5. A multinational Andean genetic and health program: growth and development in an hypoxic environment.

    Science.gov (United States)

    Mueller, W H; Schull, V N; Schull, W J; Soto, P; Rothhammer, F

    1978-07-01

    In 1972 a multidisciplinary study sought to assess the health status of the indigenous peoples of the Department of Arica in northern Chile, the Aymara, and to relate disease, morphological, physiological and biochemical variation, to the wide changes in altitude of the region. Presented here are the morphological changes which accompany age, altitude and ethnicity amoung 1047 children and adults, permanent residents of the coast, sierra and altiplano. At comparable ages, high-altitude residents were shorter, lighter and leaner but with more expansive and rounder chests than sea-level controls. None of these effects was systematically related to ethnicity (Spanish-Aymara surname), although when stature was held constant, children with greater Aymara ancestry had largest chest circumferences and longer bones. These results suggest that (1) altitude confers allometric growth changes (expensive growth of the chest and diminished growth of the structures less related to oxygen transport); and (2) size changes associated with altitude are acquired during development while shape changes may be under genetic control. Altitude appears to account for less of the variation in growth in this relatively homogeneous Chilean sample than has been reported for other Andean samples, suggesting other concomitants confounding the effects of hypoxia in Andean South America.

  6. Invesitgation of Drilling Parameters on Thrust Force on AZ91 Magnesium Alloy by Genetic Expression Programming

    Directory of Open Access Journals (Sweden)

    Kemal ALDAŞ

    2014-09-01

    Full Text Available Bu çalışmada AZ91 magnezyum alaşımının farklı parametreler altında işlenmesi ile oluşan kesme kuvvetlerinin deneysel tabanlı teorik bir model ile tahmin edilmesi sunulmuştur. Modelleme için gerekli deneyler kuru işleme ortamında ve işleme devri ilerleme hızı ve 4 farklı matkap ucunun tam faktöriyel deney tasarımı kullanarak gerçekleştirilmiştir. Deneyler sonucunca elde edilen veriler Genetic Expression yazılımı ile modellenerek kesme kuvveti tahmini için formulasyon oluşturulmuştur. Bu formulasyon kullanılarak deneyde kullanılan parametrelerin kesme kuvveti üzerindeki etkileri detaylı olarak analiz edilmiştir

  7. Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach.

    Science.gov (United States)

    Mridula, Meenu R; Nair, Ashalatha S; Kumar, K Satheesh

    2018-02-01

    In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for establishing in vitro culture protocols as these models will have significant potential for saving time and expenditure in plant tissue culture laboratories, and it further reduces the need for specialised background.

  8. Genetic algorithms applied to nuclear reactor design optimization

    International Nuclear Information System (INIS)

    Pereira, C.M.N.A.; Schirru, R.; Martinez, A.S.

    2000-01-01

    A genetic algorithm is a powerful search technique that simulates natural evolution in order to fit a population of computational structures to the solution of an optimization problem. This technique presents several advantages over classical ones such as linear programming based techniques, often used in nuclear engineering optimization problems. However, genetic algorithms demand some extra computational cost. Nowadays, due to the fast computers available, the use of genetic algorithms has increased and its practical application has become a reality. In nuclear engineering there are many difficult optimization problems related to nuclear reactor design. Genetic algorithm is a suitable technique to face such kind of problems. This chapter presents applications of genetic algorithms for nuclear reactor core design optimization. A genetic algorithm has been designed to optimize the nuclear reactor cell parameters, such as array pitch, isotopic enrichment, dimensions and cells materials. Some advantages of this genetic algorithm implementation over a classical method based on linear programming are revealed through the application of both techniques to a simple optimization problem. In order to emphasize the suitability of genetic algorithms for design optimization, the technique was successfully applied to a more complex problem, where the classical method is not suitable. Results and comments about the applications are also presented. (orig.)

  9. Genetic and environmental variation in a commercial breeding program of perennial ryegrass

    DEFF Research Database (Denmark)

    Fé, Dario; Pedersen, Morten Greve; Jensen, Christian S

    2015-01-01

    on forage yield (green and dry matter) and six traits scored by visual inspection (i.e., rust resistance, aftermath heading, spring growth, density, winter hardiness, and heading date). Data were analyzed with linear mixed models, including fixed effects (trial and control varieties, within year...... for future GSbased breeding programs. Forage yield showed family heritabilities of up to 0.30 across locations and up to 0.60 within a location. Similar or moderately lower values were found for the other traits. In particular, the heritabilities of rust resistance and aftermath heading were very promising...

  10. Using AFLP markers and the Geneland program for the inference of population genetic structure

    DEFF Research Database (Denmark)

    Guillot, Gilles; Santos, Filipe

    2010-01-01

    the computer program Geneland designed to infer population structure has been adapted to deal with dominant markers; and (ii) we use Geneland for numerical comparison of dominant and codominant markers to perform clustering. AFLP markers lead to less accurate results than bi-allelic codominant markers...... such as single nucleotide polymorphisms (SNP) markers but this difference becomes negligible for data sets of common size (number of individuals n≥100, number of markers L≥200). The latest Geneland version (3.2.1) handling dominant markers is freely available as an R package with a fully clickable graphical...

  11. Modelling of the Elasticity Modulus for Rock Using Genetic Expression Programming

    Directory of Open Access Journals (Sweden)

    Umit Atici

    2016-01-01

    Full Text Available In rock engineering projects, statically determined parameters are more reflective of actual load conditions than dynamic parameters. This study reports a new and efficient approach to the formulation of the static modulus of elasticity Es applying gene expression programming (GEP with nondestructive testing (NDT methods. The results obtained using GEP are compared with the results of multivariable linear regression analysis (MRA, univariate nonlinear regression analysis (URA, and the dynamic elasticity modulus (Ed. The GEP model was found to produce the most accurate calculation of Es. The proposed approach is a simple, nondestructive, and practical way to determine Es for anisotropic and heterogeneous rocks.

  12. A Hybrid Genetic Programming Method in Optimization and Forecasting: A Case Study of the Broadband Penetration in OECD Countries

    Directory of Open Access Journals (Sweden)

    Konstantinos Salpasaranis

    2012-01-01

    Full Text Available The introduction of a hybrid genetic programming method (hGP in fitting and forecasting of the broadband penetration data is proposed. The hGP uses some well-known diffusion models, such as those of Gompertz, Logistic, and Bass, in the initial population of the solutions in order to accelerate the algorithm. The produced solutions models of the hGP are used in fitting and forecasting the adoption of broadband penetration. We investigate the fitting performance of the hGP, and we use the hGP to forecast the broadband penetration in OECD (Organisation for Economic Co-operation and Development countries. The results of the optimized diffusion models are compared to those of the hGP-generated models. The comparison indicates that the hGP manages to generate solutions with high-performance statistical indicators. The hGP cooperates with the existing diffusion models, thus allowing multiple approaches to forecasting. The modified algorithm is implemented in the Python programming language, which is fast in execution time, compact, and user friendly.

  13. Profitability of a dairy sheep genetic improvement program using artificial insemination.

    Science.gov (United States)

    Valergakis, G E; Gelasakis, A I; Oikonomou, G; Arsenos, G; Fortomaris, P; Banos, G

    2010-10-01

    This simulation study investigated the farm-level economic benefits of a genetic improvement scheme using artificial insemination (AI) with fresh ram semen in dairy sheep of the Chios breed in Greece. Data were collected from 67 farms associated with the Chios Sheep Breeders' Cooperative 'Macedonia', describing the percentage of ewes that would be artificially inseminated in the flock, pregnancy rate, annual ram costs that could be saved using AI rather than natural mating, expected improvement in milk production, annual costs of semen and feed, milk price and number of years of AI usage. The study considered 77 760 possible scenarios in a 3 × 4 × 4 × 3 × 3 × 3 × 4 × 15 factorial arrangement. Analysis of variance was used to investigate the effect of each factor on farm profitability. All factors considered were statistically significant (P profitability and farmers should become aware that using AI is a long-term investment. Semen price, pregnancy rate and improvement in milk production also had substantial effects. The price of milk and feed had a considerably lower effect on profitability, as did the annual cost of maintaining rams that would be replaced by AI. A positive annual and cumulative return was achieved in the model within the first 6 years. The cost of semen was estimated at 8€ to 10€ per dose for the first 5 years. Where the annual improvement in milk production was 1% of annual phenotypic mean (e.g. 3.0 kg) profitability of the scheme was improved greatly.

  14. EPRI research program NDE techniques for crack initiation of steam turbine rotor

    International Nuclear Information System (INIS)

    Goto, T.; Kimura, J.; Kawamoto, K.; Kadoya, Y.; Viswanathan, R.

    1990-01-01

    EPRI RP 2481-8 aims at the development of nondestructive methods for the life assessment of steam turbine rotor for its crack initiation caused by creep and/or fatigue. As a part of the research project, the demonstration of the state of the art NDE techniques was conducted during June to August of 1988 at EPRI NDE Center, Charlotte, N.C. by Mitsubishi Heavy Industries, Ltd. using four rotors retired after long term service (16-22x10 4 hr). This paper introduces the results of the demonstration

  15. MAKSIMA-CHEMIST: a program for Mass Action Kinetics Simulation by Automatic Chemical Equation Manipulation and Integration using Stiff Techniques

    International Nuclear Information System (INIS)

    Carver, M.B.; Hanley, D.V.; Chaplin, K.R.

    1979-02-01

    MAKSIMA-CHEMIST was written to compute the kinetics of simultaneous chemical reactions. The ordinary differential equations, which are automatically derived from the stated chemical equations, are difficult to integrate, as they are coupled in a highly nonlinear manner and frequently involve a large range in the magnitude of the reaction rates. They form a classic 'stiff' differential equaton set which can be integrated efficiently only by recently developed advanced techniques. The new program also contains provision for higher order chemical reactions, and has a dynamic storage and decision feature. This permits it to accept any number of chemical reactions and species, and choose an integraton scheme which will perform most efficiently within the available memory. Sparse matrix techniques are used when the size and structure of the equation set is suitable. Finally, a number of post-analysis options are available, including printer and Calcomp plots of transient response of selected species, and graphical representation of the reaction matrix. (auth)

  16. Evaluation and study of advanced optical contamination, deposition, measurement, and removal techniques. [including computer programs and ultraviolet reflection analysis

    Science.gov (United States)

    Linford, R. M. F.; Allen, T. H.; Dillow, C. F.

    1975-01-01

    A program is described to design, fabricate and install an experimental work chamber assembly (WCA) to provide a wide range of experimental capability. The WCA incorporates several techniques for studying the kinetics of contaminant films and their effect on optical surfaces. It incorporates the capability for depositing both optical and contaminant films on temperature-controlled samples, and for in-situ measurements of the vacuum ultraviolet reflectance. Ellipsometer optics are mounted on the chamber for film thickness determinations, and other features include access ports for radiation sources and instrumentation. Several supporting studies were conducted to define specific chamber requirements, to determine the sensitivity of the measurement techniques to be incorporated in the chamber, and to establish procedures for handling samples prior to their installation in the chamber. A bibliography and literature survey of contamination-related articles is included.

  17. The use of linear programming techniques to design optimal digital filters for pulse shaping and channel equalization

    Science.gov (United States)

    Houts, R. C.; Burlage, D. W.

    1972-01-01

    A time domain technique is developed to design finite-duration impulse response digital filters using linear programming. Two related applications of this technique in data transmission systems are considered. The first is the design of pulse shaping digital filters to generate or detect signaling waveforms transmitted over bandlimited channels that are assumed to have ideal low pass or bandpass characteristics. The second is the design of digital filters to be used as preset equalizers in cascade with channels that have known impulse response characteristics. Example designs are presented which illustrate that excellent waveforms can be generated with frequency-sampling filters and the ease with which digital transversal filters can be designed for preset equalization.

  18. Applications of ultrasonic phased array technique during fabrication of nuclear tubing and other components for the Indian nuclear power program

    International Nuclear Information System (INIS)

    Kapoor, K.

    2015-01-01

    Ultrasonic phased array technique has been applied in fabrication of nuclear fuel and structural at NFC. The integrity of the nuclear fuel and structural components is most crucial as they are exposed to severe environment during operation leading to rapid degradation of its properties during its lifecycle. Nuclear Fuel Complex has mandate for the fabrication of the nuclear fuel and core structurals for Indian PHWRs/BWR, sub-assemblies for the PFBR and steam generator tubing for PFBR and PHWRs which are the most critical materials for the Indian Nuclear Power program. NDE during fabrication of these materials is thus most crucial as it provides the confidence to the designer for safe operation during its lifetime. Many of these techniques have to be developed in-house to meet unique requirements of high sensitivity, resolution and shape of the components. Some of the advancements in the NDE during the fabrication include use of ultrasonic phased array which is detailed in this paper

  19. Seafood Wars: Reviving a Tired Sustainability Education Program with Pop Culture Techniques

    Science.gov (United States)

    Peart, L. W.

    2016-02-01

    Texas State Aquarium revived its sustainable seafood education program by embedding expert speakers into the pop culture chef competition. Chefs are nominated by diners and vetted by Aquarium staff. Seafood selections are made in consultation with fishery experts and sustainability partners including Gulf United for Lasting Fisheries. Through these efforts, the Seafood Wars audience has expanded from the over-40 set to college and graduate students, families, and adults of all ages. Surveyed participants at these sell-out events are 100% as, or more likely to purchase and consume featured sustainable selections.

  20. Monitoring programmed cell death of living plant tissues in microfluidics using electrochemical and optical techniques

    DEFF Research Database (Denmark)

    Mark, Christina; Heiskanen, Arto; Svensson, Birte

    Programmed cell death (PCD) in plants can influence the outcome of yield and quality of crops through its important role in seed germination and the defence process against pathogens. The main scope of the project is to apply microfluidic cell culture for the measurement of electrochemically......, since it is known that reactive oxygen species, which are affected by changes in the redox activity of the cells3, are involved in PCD in plants, but the relationship between and mechanisms behind ROS and PCD is only poorly understood in plant cells4. Recently, it has been shown, using optical detection...

  1. Research on Innovating, Applying Multiple Paths Routing Technique Based on Fuzzy Logic and Genetic Algorithm for Routing Messages in Service - Oriented Routing

    Directory of Open Access Journals (Sweden)

    Nguyen Thanh Long

    2015-02-01

    Full Text Available MANET (short for Mobile Ad-Hoc Network consists of a set of mobile network nodes, network configuration changes very fast. In content based routing, data is transferred from source node to request nodes is not based on destination addresses. Therefore, it is very flexible and reliable, because source node does not need to know destination nodes. If We can find multiple paths that satisfies bandwidth requirement, split the original message into multiple smaller messages to transmit concurrently on these paths. On destination nodes, combine separated messages into the original message. Hence it can utilize better network resources, causes data transfer rate to be higher, load balancing, failover. Service Oriented Routing is inherited from the model of content based routing (CBR, combined with several advanced techniques such as Multicast, multiple path routing, Genetic algorithm to increase the data rate, and data encryption to ensure information security. Fuzzy logic is a logical field study evaluating the accuracy of the results based on the approximation of the components involved, make decisions based on many factors relative accuracy based on experimental or mathematical proof. This article presents some techniques to support multiple path routing from one network node to a set of nodes with guaranteed quality of service. By using these techniques can decrease the network load, congestion, use network resources efficiently.

  2. A study of the use of linear programming techniques to improve the performance in design optimization problems

    Science.gov (United States)

    Young, Katherine C.; Sobieszczanski-Sobieski, Jaroslaw

    1988-01-01

    This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.

  3. The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer

    International Nuclear Information System (INIS)

    Mitra, Anirban P; Almal, Arpit A; George, Ben; Fry, David W; Lenehan, Peter F; Pagliarulo, Vincenzo; Cote, Richard J; Datar, Ram H; Worzel, William P

    2006-01-01

    Previous studies on bladder cancer have shown nodal involvement to be an independent indicator of prognosis and survival. This study aimed at developing an objective method for detection of nodal metastasis from molecular profiles of primary urothelial carcinoma tissues. The study included primary bladder tumor tissues from 60 patients across different stages and 5 control tissues of normal urothelium. The entire cohort was divided into training and validation sets comprised of node positive and node negative subjects. Quantitative expression profiling was performed for a panel of 70 genes using standardized competitive RT-PCR and the expression values of the training set samples were run through an iterative machine learning process called genetic programming that employed an N-fold cross validation technique to generate classifier rules of limited complexity. These were then used in a voting algorithm to classify the validation set samples into those associated with or without nodal metastasis. The generated classifier rules using 70 genes demonstrated 81% accuracy on the validation set when compared to the pathological nodal status. The rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive cases. Additionally, the motifs showed CDK8 to be lower relative to ICAM1, and ANXA5 to be relatively high by itself in node positive tumors. Rules generated using only ICAM1, MAP2K6 and KDR were comparably robust, with a single representative rule producing an accuracy of 90% when used by itself on the validation set, suggesting a crucial role for these genes in nodal metastasis. Our study demonstrates the use of standardized quantitative gene expression values from primary bladder tumor tissues as inputs in a genetic programming system to generate classifier rules for determining the nodal status. Our method also suggests the involvement of ICAM1, MAP2K6, KDR

  4. Three example applications of optimization techniques to Department of Energy contractor radiation protection programs

    International Nuclear Information System (INIS)

    Merwin, S.E.; Martin, J.B.; Tawil, J.J.; Selby, J.M.

    1989-01-01

    Six numerical examples of optimization of radiation protection are provided in the appendices of International Commission on Radiological Protection (ICRP) Publication No. 37 (1983). In each case, the calculations were based on well-defined parameters and assumptions. In this paper, we examined three different numerical examples that were based on empirical data and less-certain assumptions. In the first example, the optimum sampling frequency for a typical 3H bioassay program was found to be once every 2 mo. However, this result depended on assumed values for several variables that were difficult to evaluate. The second example showed that the optimum frequency for recalibrating a group of cutie pie (CP) ionization chamber survey instruments was once every 85 d. This result depended largely on the assumption that an improperly operating CP instrument could lead to a serious overexposure. In the third example, one continuous air monitor (CAM) was determined to be the optimum number in a workplace at a Department of Energy (DOE) Pu facility. The optimum location of the CAM was determined from past glove-box release studies. These examples demonstrated that cost-benefit analysis of individual elements of radiation protection programs can be useful even if limited data are available

  5. Two example applications of optimization techniques to US Department of Energy contractor radiation protection programs

    International Nuclear Information System (INIS)

    Merwin, S.E.; Martin, J.B.; Selby, J.M.; Vallario, E.J.

    1986-01-01

    Six numerical examples of optimization of radiation protection are provided in the appendices of ICRP Publication 37. In each case, the calculations are based on fairly well defined parameters and assumptions that were well understood. In this paper, we have examined two numerical examples that are based on empirical data and less certain assumptions. These examples may represent typical applications of optimization principles to the evaluation of specific elements of a radiation protection program. In the first example, the optimum bioassay frequency for tritium workers was found to be once every 95 days, which compared well with ICRP Publication 10 recommendations. However, this result depended heavily on the assumption that the value of a potential undetected rem was US $1000. The second example showed that the optimum frequency for recalibrating Cutie Pie (CP) type ionization chamber survey instruments was once every 102 days, which compared well with the Hanford standard frequency of once every 90 days. This result depended largely on the assumption that an improperly operating CP instrument could lead to a serious overexposure. These examples have led us to conclude that optimization of radiation protection programs must be a very dynamic process. Examples must be recalculated as empirical data expand and improve and as the uncertainties surrounding assumptions are reduced

  6. Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

    Science.gov (United States)

    Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

    2017-03-01

    Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

  7. Pulsed Field Gel Electrophoresis (PFGE: a DNA finger printing technique to study the genetic diversity of blood disease bacterium of banana

    Directory of Open Access Journals (Sweden)

    HADIWIYONO

    2011-01-01

    Full Text Available Hadiwiyono, Widada J, Subandiyah S, Fegan F (2011 Pulsed Field Gel Electrophoresis (PFGE: a DNA finger printing technique to study the genetic diversity of blood disease bacterium of banana. Biodiversitas 12: 12-16. Blood disease bacterium (BDB is the most important pathogen of bananas in Indonesia. In some field, the disease incidence reaches over 80%. Epidemiologically, the disease is similar to moko disease in South America and bugtok disease in the Philippines caused by Ralstonia solanacearum race 2. However, BDB is different in phenotype and genotype from the two diseases. Previously BDB was limited in South Sulawesi since 1920s – 1980s and recently was reported in 27 of 30 provinces in Indonesia. Pulsed-Field Gel Electrophoresis (PFGE is a genomic DNA fingerprinting method, which employs rare cutting restriction endonucleases to digest genome prior to electrophoresis using specialized condition to separate of large DNA fragments. The results showed that PFGE analysis was a discriminative tool to study the genetic diversity of BDB. Based on the PFGE analysis, BDB isolates obtained from different localities in Yogyakarta and Central Java were quit diverse.

  8. Detection of the genetic variation of polygalacturonase-inhibiting protein gene 2 in autotetraploid alfalfa (Medicago sativa) using an improved SSCP technique.

    Science.gov (United States)

    Gui, Z; Liu, H Q; Wang, Y; Yuan, Q H; Xin, N; Zhang, X; Li, X L; Pi, Y S; Gao, J M

    2014-12-04

    In this study, 2 approaches were adopted to obtain good single-strand conformation polymorphism (SSCP) data for autotetraploid alfalfa; primers were added to PCR products, and fluorescent-labeled primers were utilized. PCR-SSCP conditions for a 331-bp fragment in the coding region of polygalacturonase-inhibiting protein gene 2 in alfalfa (MsPGIP2) were optimized, and the results showed that the best SSCP gel pattern could be obtained when the loading mixture was made by mixing 1 μL PCR products, 0.2 to 0.8 μL unlabeled primers (50 μM) and 4 to 16 μL loading buffer. Furthermore, the use of the fluorescent-labeled primers resulted in 2 separated electrophoresis images from 2 complementary single DNA strands, thus making the determination of alleles and idiotypes a relatively easy task. In addition, the results of sequencing prove that the determination of alleles and idiotypes were accurate based on SSCP analysis. Finally, a total of 9 alleles with 18 SNP sites were identified for MsPGIP2 in the alfalfa variety 'Algonquin'. In conclusion, MsPGIP2 possessed great genetic variation, and the addition of primers to the PCR products in combination with the fluorescent labeling of primers could significantly improve the sensitivity and resolution of SSCP analysis. This technique could be used for genetic diversity detection and marker-assisted breeding of useful genes in autopolyploid species such as alfalfa.

  9. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

    Energy Technology Data Exchange (ETDEWEB)

    Wichapa, Narong; Khokhajaikiat, Porntep

    2017-07-01

    Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  10. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

    International Nuclear Information System (INIS)

    Wichapa, Narong; Khokhajaikiat, Porntep

    2017-01-01

    Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  11. Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

    Directory of Open Access Journals (Sweden)

    Narong Wichapa

    2017-11-01

    Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

  12. Computation techniques and computer programs to analyze Stirling cycle engines using characteristic dynamic energy equations

    Science.gov (United States)

    Larson, V. H.

    1982-01-01

    The basic equations that are used to describe the physical phenomena in a Stirling cycle engine are the general energy equations and equations for the conservation of mass and conversion of momentum. These equations, together with the equation of state, an analytical expression for the gas velocity, and an equation for mesh temperature are used in this computer study of Stirling cycle characteristics. The partial differential equations describing the physical phenomena that occurs in a Stirling cycle engine are of the hyperbolic type. The hyperbolic equations have real characteristic lines. By utilizing appropriate points along these curved lines the partial differential equations can be reduced to ordinary differential equations. These equations are solved numerically using a fourth-fifth order Runge-Kutta integration technique.

  13. On the Impact of using Mixed Integer Programming Techniques on Real-world Offshore Wind Parks

    DEFF Research Database (Denmark)

    Fischetti, Martina; Pisinger, David

    2017-01-01

    Wind power is a leading technology in the transition to sustainable energy. Being a new and still more competitive field, it is of major interest to investigate new techniques to solve the design challenges involved. In this paper, we consider optimization of the inter-array cable routing...... optimization problem considers two objectives: minimizing immediate costs (CAPEX) and minimizing costs due to power losses. This makes it possible to perform various what-if analyses to evaluate the impact of different preferences to CAPEX versus reduction of power losses. Thanks to the close collaboration...... with a leading energy company, we have been able to report results on a set of real-world instances, based on six existing wind parks, studying the economical impact of considering power losses in the cable routing design phase....

  14. Genetic variability in dinitrogen fixation between cowpea [Vigna unguiculata (L.) Walp] cultivars determined using the nitrogen-15 isotope dilution technique

    International Nuclear Information System (INIS)

    Ndiaye, M.A.F.; Spencer, M.M.; Gueye, M.

    2000-01-01

    N fixed in 16 cultivars of cowpea [Vigna unguiculata (L.) Walp] inoculated with effective Bradyrhizobium strains collected from the West African MIRCEN culture collection was measured by 15N isotope dilution technique. In all plant parts, significant differences in the percentage of N derived from the atmosphere (%Ndfa) and the amount of Ndfa occurred between the cultivars. Ndoute variety exhibited the highest %Ndfa (74.33% in shoots; 60.90% in roots) and accumulated more fixed N (960 mg N plant–1 and 38 mg N plant–1 in shoots and roots, respectively). Therefore this cultivar should be selected as the highest N-fixing cowpea cultivar. It also should be used in a breeding programme to contribute to the development of cultivars that could stimulate an intensive use of cowpea in many different cropping systems in Africa with a view to maintaining soil fertility. (Authors)

  15. Possibility of choosing development investment programs of a production company by applying discounted investment appraisal technique

    Directory of Open Access Journals (Sweden)

    Vesić-Vasović Jasmina

    2014-01-01

    Full Text Available The selection of development investment programs is one of the most important decisions in industrial production. The paper sets out the possibilities of applying dynamic criteria for investment decision making. It presents a practical numerical example for the value calculation of investment criteria Net Present Value and Internal Rate of Return for the reviewed investment project solutions. In this manner it is possible to make an orderly set of alternatives with clear preferences for the most suitable alternative in comparison with other ones. Such rating of project solutions will enable the decision maker to emphasize advantages with more arguments and select the most suitable project solution in accordance with the established criteria, conditions and limitations.

  16. Parameter identification using optimization techniques in the continuous simulation programs FORSIM and MACKSIM

    International Nuclear Information System (INIS)

    Carver, M.B.; Austin, C.F.; Ross, N.E.

    1980-02-01

    This report discusses the mechanics of automated parameter identification in simulation packages, and reviews available integration and optimization algorithms and their interaction within the recently developed optimization options in the FORSIM and MACKSIM simulation packages. In the MACKSIM mass-action chemical kinetics simulation package, the form and structure of the ordinary differential equations involved is known, so the implementation of an optimizing option is relatively straightforward. FORSIM, however, is designed to integrate ordinary and partial differential equations of abritrary definition. As the form of the equations is not known in advance, the design of the optimizing option is more intricate, but the philosophy could be applied to most simulation packages. In either case, however, the invocation of the optimizing interface is simple and user-oriented. Full details for the use of the optimizing mode for each program are given; specific applications are used as examples. (O.T.)

  17. The Application of Adaptive Sampling and Analysis Program (ASAP) Techniques to NORM Sites; FINAL

    International Nuclear Information System (INIS)

    Johnson, Robert; Smith, Karen P.; Quinn, John

    1999-01-01

    The results from the Michigan demonstration establish that this type of approach can be very effective for NORM sites. The advantages include (1) greatly reduced per sample analytical costs; (2) a reduced reliance on soil sampling and ex situ gamma spectroscopy analyses; (3) the ability to combine characterization with remediation activities in one fieldwork cycle; (4) improved documentation; and (5) ultimately better remediation, as measured by greater precision in delineating soils that are not in compliance with requirements from soils that are in compliance. In addition, the demonstration showed that the use of real-time technologies, such as the RadInSoil, can facilitate the implementation of a Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM)-based final status survey program

  18. Implementation of visual programming methods for numerical techniques used in electromagnetic field theory

    Directory of Open Access Journals (Sweden)

    Metin Varan

    2017-08-01

    Full Text Available Field theory is one of the two sub-field theories in electrical and electronics engineering that for creates difficulties for undergraduate students. In undergraduate period, field theory has been taught under the theory of electromagnetic fields by which describes using partial differential equations and integral methods. Analytical methods for solution of field problems on the basis of a mathematical model may result the understanding difficulties for undergraduate students due to their mathematical and physical infrastructure. The analytical methods which can be applied in simple model lose their applicability to more complex models. In this case, the numerical methods are used to solve more complex equations. In this study, by preparing some field theory‘s web-based graphical user interface numerical methods of applications it has been aimed to increase learning levels of field theory problems for undergraduate and graduate students while taking in mind their computer programming capabilities.

  19. Reorientation of the Brazilian nuclear program and the function of technique community

    International Nuclear Information System (INIS)

    Ishiguro, Y.; Nascimento, J.A. do

    1988-01-01

    Once the available hydroelectric potentials have been developed, probably in 30 years, Brazil will need an alternative source for electric generation. Fossil fuels are limited in quantity and present serious health and environmental problems. Other sources such as solar and fusion energies are yet to be proved technologically and socio-economically and cannot be relied on in a rational planning for the future. Nuclear energy generated in Liquid metal fast breeder reactors is technologically proven, present minimum adverse effects, is economically competitive today, and has the capacity to supply all the electric power for centuries based on domestic resources. The nuclear community has the responsability to formulate and execute a program for technology development as soon as possible and to communicate to the people the necessity and merits of nuclear energy. (author) [pt

  20. A stimulus control technique for improving the efficacy of an established toilet training program.

    Science.gov (United States)

    Taylor, S; Cipani, E; Clardy, A

    1994-06-01

    Standard toilet training regimens used with children with developmental disabilities have demonstrated effectiveness at achieving bladder and bowel continence. However, in some clinical applications in everyday practice, success has not been achieved, necessitating research into possible modifications of the current approaches. A widely used toilet training program was modified to reduce toileting accidents of a referred child. The modification involved the assessment of the discriminative stimulus for eliminating, namely, his undergarments. By removing the undergarments when an elimination became imminent, an "errorless" learning paradigm was established that allowed for more rapid and enduring acquisition of toileting skills than seen in previous training attempts. The results indicate the present procedure could expedite training for individuals who are difficult to teach appropriate toileting skills through an analysis of the controlling antecedent stimulus for accidents and subsequent manipulation of such stimuli.

  1. Mapping of Primary Instructional Methods and Teaching Techniques for Regularly Scheduled, Formal Teaching Sessions in an Anesthesia Residency Program.

    Science.gov (United States)

    Vested Madsen, Matias; Macario, Alex; Yamamoto, Satoshi; Tanaka, Pedro

    2016-06-01

    In this study, we examined the regularly scheduled, formal teaching sessions in a single anesthesiology residency program to (1) map the most common primary instructional methods, (2) map the use of 10 known teaching techniques, and (3) assess if residents scored sessions that incorporated active learning as higher quality than sessions with little or no verbal interaction between teacher and learner. A modified Delphi process was used to identify useful teaching techniques. A representative sample of each of the formal teaching session types was mapped, and residents anonymously completed a 5-question written survey rating the session. The most common primary instructional methods were computer slides-based classroom lectures (66%), workshops (15%), simulations (5%), and journal club (5%). The number of teaching techniques used per formal teaching session averaged 5.31 (SD, 1.92; median, 5; range, 0-9). Clinical applicability (85%) and attention grabbers (85%) were the 2 most common teaching techniques. Thirty-eight percent of the sessions defined learning objectives, and one-third of sessions engaged in active learning. The overall survey response rate equaled 42%, and passive sessions had a mean score of 8.44 (range, 5-10; median, 9; SD, 1.2) compared with a mean score of 8.63 (range, 5-10; median, 9; SD, 1.1) for active sessions (P = 0.63). Slides-based classroom lectures were the most common instructional method, and faculty used an average of 5 known teaching techniques per formal teaching session. The overall education scores of the sessions as rated by the residents were high.

  2. Genetics and ecology of colonization and mass rearing of Hawaiian fruit flies (Diptera: Tephritidae) for use in sterile insect control programs

    International Nuclear Information System (INIS)

    Saul, S.H.; McCombs, S.D.

    1995-01-01

    It is critical to maintain the genetic, physiological and behavioral competence of colonized populations of insect species, such as fruit flies, which are reared for release in sterile insect and other genetic control programs. Selective pressures associated with the mass rearing process affect this competence, but the underlying mechanisms of genetic change arc largely unknown. However, competence is often an operational goal achieved by manipulating environmental factors without possessing precise genetic knowledge of alleles and their marginal effects on the desired traits. One goal of this paper is to show that the precise genetic and statistical analysis of components that determine competence in a broad sense or fitness in the narrower ecological sense, is extremely difficult. We can gel contradictory results from the different methods for estimating genetic variation in tephritid populations. We observe low levels of allozyme variation, but high levels of recessive mutants in inbred populations. We propose that genetic variability may be maintained in colonized and mass reared laboratory populations by balanced lethal systems and that the introduction of fresh genetic material may reduce, not increase, fitness. We require rigorous and precise models of directional selection in the laboratory and selective forces in the natural environment to aid our understanding of dynamic changes in courtship and mating behavior under artificial conditions. We have chosen to examine the lek model as an example of an idea whose usefulness has yet to be determined by test ing and validation. The inclusion of lek forming ability in genetic models will be depen dent on rigorously establishing the validity of the lek model for each tephritid species

  3. Determination of the genetic structure of remnant Morus boninensis Koidz. trees to establish a conservation program on the Bonin Islands, Japan

    Directory of Open Access Journals (Sweden)

    Nobushima Fuyuo

    2006-10-01

    Full Text Available Abstract Background Morus boninensis, is an endemic plant of the Bonin (Ogasawara Islands of Japan and is categorized as "critically endangered" in the Japanese red data book. However, little information is available about its ecological, evolutionary and genetic status, despite the urgent need for guidelines for the conservation of the species. Therefore, we adopted Moritz's MU concept, based on the species' current genetic structure, to define management units and to select mother tree candidates for seed orchards. Results Nearly all individuals of the species were genotyped on the basis of seven microsatellite markers. Genetic diversity levels in putative natural populations were higher than in putative man-made populations with the exception of those on Otouto-jima Island. This is because a limited number of maternal trees are likely to have been used for seed collection to establish the man-made populations. A model-based clustering analysis clearly distinguished individuals into nine clusters, with a large difference in genetic composition between the population on Otouto-jima Island, the putative natural populations and the putative man-made populations. The Otouto-jima population appeared to be genetically differentiated from the others; a finding that was also supported by pairwise FST and RST analysis. Although multiple clusters were detected in the putative man-made populations, the pattern of genetic diversity was monotonous in comparison to the natural populations. Conclusion The genotyping by microsatellite markers revealed strong genetic structures. Typically, artificial propagation of this species has ignored the genetic structure, relying only on seeds from Otouto-jima for replanting on other islands, because of a problem with inter-specific hybridization on Chichi-jima and Haha-jima Islands. However, this study demonstrates that we should be taking into consideration the genetic structure of the species when designing a

  4. Determination of the genetic structure of remnant Morus boninensis Koidz. trees to establish a conservation program on the Bonin Islands, Japan.

    Science.gov (United States)

    Tani, Naoki; Yoshimaru, Hiroshi; Kawahara, Takayuki; Hoshi, Yoshio; Nobushima, Fuyuo; Yasui, Takaya

    2006-10-11

    Morus boninensis, is an endemic plant of the Bonin (Ogasawara) Islands of Japan and is categorized as "critically endangered" in the Japanese red data book. However, little information is available about its ecological, evolutionary and genetic status, despite the urgent need for guidelines for the conservation of the species. Therefore, we adopted Moritz's MU concept, based on the species' current genetic structure, to define management units and to select mother tree candidates for seed orchards. Nearly all individuals of the species were genotyped on the basis of seven microsatellite markers. Genetic diversity levels in putative natural populations were higher than in putative man-made populations with the exception of those on Otouto-jima Island. This is because a limited number of maternal trees are likely to have been used for seed collection to establish the man-made populations. A model-based clustering analysis clearly distinguished individuals into nine clusters, with a large difference in genetic composition between the population on Otouto-jima Island, the putative natural populations and the putative man-made populations. The Otouto-jima population appeared to be genetically differentiated from the others; a finding that was also supported by pairwise FST and RST analysis. Although multiple clusters were detected in the putative man-made populations, the pattern of genetic diversity was monotonous in comparison to the natural populations. The genotyping by microsatellite markers revealed strong genetic structures. Typically, artificial propagation of this species has ignored the genetic structure, relying only on seeds from Otouto-jima for replanting on other islands, because of a problem with inter-specific hybridization on Chichi-jima and Haha-jima Islands. However, this study demonstrates that we should be taking into consideration the genetic structure of the species when designing a propagation program for the conservation of this species.

  5. Genetic diversity of wheat grain quality and determination the best clustering technique and data type for diversity assessment

    Directory of Open Access Journals (Sweden)

    Khodadadi Mostafa

    2014-01-01

    Full Text Available Wheat is an important staple in human nutrition and improvement of its grain quality characters will have high impact on population's health. The objectives of this study were assessing variation of some grain quality characteristics in the Iranian wheat genotypes and identify the best type of data and clustering method for grouping genotypes. In this study 30 spring wheat genotypes were cultivated through randomized complete block design with three replications in 2009 and 2010 years. High significant difference among genotypes for all traits except for Sulfate, K, Br and Cl content, also deference among two years mean for all traits were no significant. Meanwhile there were significant interaction between year and genotype for all traits except Sulfate and F content. Mean values for crude protein, Zn, Fe and Ca in Mahdavi, Falat, Star, Sistan genotypes were the highest. The Ca and Br content showed the highest and the lowest broadcast heritability respectively. In this study indicated that the Root Mean Square Standard Deviation is efficient than R Squared and R Squared efficient than Semi Partial R Squared criteria for determining the best clustering technique. Also Ward method and canonical scores identified as the best clustering method and data type for grouping genotypes, respectively. Genotypes were grouped into six completely separate clusters and Roshan, Niknejad and Star genotypes from the fourth, fifth and sixth clusters had high grain quality characters in overall.

  6. Weighted thinned linear array design with the iterative FFT technique

    CSIR Research Space (South Africa)

    Du Plessis, WP

    2011-09-01

    Full Text Available techniques utilise simulated annealing [3]?[5], [10], mixed integer linear programming [7], genetic algorithms [9], and a hyrid approach combining a genetic algorithm and a local optimiser [8]. The iterative Fourier technique (IFT) developed by Keizer [2... algorithm being well- suited to obtaining low CTRs. Test problems from the literature are considered, and the results obtained with the IFT considerably exceed those achieved with other algorithms. II. DESCRIPTION OF THE ALGORITHM A flowchart describing...

  7. Three example applications of optimization techniques to Department of Energy contractor radiation protection programs

    International Nuclear Information System (INIS)

    Merwin, S.E.; Martin, J.B.; Tawil, J.J.; Selby, J.M.

    1986-06-01

    Six numerical examples of optimization of radiation protection are provided in the appendices of International Commission on Radiological Protection (ICRP) Publication 37 (ICRP83). In each case, the calculations are based on fairly well-defined parameters and assumptions that were well understood. In this paper, we have examined three different numerical examples that are based on empirical data and less certain assumptions. These examples are intended to represent typical applications of optimization principles to the evaluation of specific elements of a radiation protection program. In the first example, the optimum bioassay frequency for certain tritium workers was found to be once every 95 days, which compared well with the recommendations of ICRP Publication 10 (ICRP67). The second example showed that the optimum frequency for recalibrating a group of ''Cutie-Pie'' (CP)-type ionization chamber survey instruments was once every 102 days. In the third example, one continuous air monitor (CAM) was determined to be the optimum number in a workplace of a Department of Energy (DOE) plutonium facility. The optimum location of the CAM was determined from past glovebox release studies

  8. Continuous Modeling Technique of Fiber Pullout from a Cement Matrix with Different Interface Mechanical Properties Using Finite Element Program

    Directory of Open Access Journals (Sweden)

    Leandro Ferreira Friedrich

    Full Text Available Abstract Fiber-matrix interface performance has a great influence on the mechanical properties of fiber reinforced composite. This influence is mainly presented during fiber pullout from the matrix. As fiber pullout process consists of fiber debonding stage and pullout stage which involve complex contact problem, numerical modeling is a best way to investigate the interface influence. Although many numerical research works have been conducted, practical and effective technique suitable for continuous modeling of fiber pullout process is still scarce. The reason is in that numerical divergence frequently happens, leading to the modeling interruption. By interacting the popular finite element program ANSYS with the MATLAB, we proposed continuous modeling technique and realized modeling of fiber pullout from cement matrix with desired interface mechanical performance. For debonding process, we used interface elements with cohesive surface traction and exponential failure behavior. For pullout process, we switched interface elements to spring elements with variable stiffness, which is related to the interface shear stress as a function of the interface slip displacement. For both processes, the results obtained are very good in comparison with other numerical or analytical models and experimental tests. We suggest using the present technique to model toughening achieved by randomly distributed fibers.

  9. A Partnership Training Program in Breast Cancer Diagnosis: Concept Development of the Next Generation Diagnostic Breast Imaging Using Digital Image Library and Networking Techniques

    National Research Council Canada - National Science Library

    Chouikha, Mohamed F

    2004-01-01

    ...); and Georgetown University (Image Science and Information Systems, ISIS). In this partnership training program, we will train faculty and students in breast cancer imaging, digital image database library techniques and network communication strategy...

  10. Design optimization of tailor-rolled blank thin-walled structures based on ɛ-support vector regression technique and genetic algorithm

    Science.gov (United States)

    Duan, Libin; Xiao, Ning-cong; Li, Guangyao; Cheng, Aiguo; Chen, Tao

    2017-07-01

    Tailor-rolled blank thin-walled (TRB-TH) structures have become important vehicle components owing to their advantages of light weight and crashworthiness. The purpose of this article is to provide an efficient lightweight design for improving the energy-absorbing capability of TRB-TH structures under dynamic loading. A finite element (FE) model for TRB-TH structures is established and validated by performing a dynamic axial crash test. Different material properties for individual parts with different thicknesses are considered in the FE model. Then, a multi-objective crashworthiness design of the TRB-TH structure is constructed based on the ɛ-support vector regression (ɛ-SVR) technique and non-dominated sorting genetic algorithm-II. The key parameters (C, ɛ and σ) are optimized to further improve the predictive accuracy of ɛ-SVR under limited sample points. Finally, the technique for order preference by similarity to the ideal solution method is used to rank the solutions in Pareto-optimal frontiers and find the best compromise optima. The results demonstrate that the light weight and crashworthiness performance of the optimized TRB-TH structures are superior to their uniform thickness counterparts. The proposed approach provides useful guidance for designing TRB-TH energy absorbers for vehicle bodies.

  11. Sterilization of fruit flies (Diptera: Tephritidae) with X-rays for sterile insect technique programs

    International Nuclear Information System (INIS)

    Mastrangelo, Thiago de Araujo

    2009-01-01

    effectiveness exist for both kinds of radiations in the usual range of doses applied to produce sterile flies. A new generation of X-rays irradiators can attend now pest control programs of UN member states. (author)

  12. Race, Ethnicity and Ancestry in Unrelated Transplant Matching for the National Marrow Donor Program: A Comparison of Multiple Forms of Self-Identification with Genetics

    Science.gov (United States)

    Hollenbach, Jill A.; Saperstein, Aliya; Albrecht, Mark; Vierra-Green, Cynthia; Parham, Peter; Norman, Paul J.; Maiers, Martin

    2015-01-01

    We conducted a nationwide study comparing self-identification to genetic ancestry classifications in a large cohort (n = 1752) from the National Marrow Donor Program. We sought to determine how various measures of self-identification intersect with genetic ancestry, with the aim of improving matching algorithms for unrelated bone marrow transplant. Multiple dimensions of self-identification, including race/ethnicity and geographic ancestry were compared to classifications based on ancestry informative markers (AIMs), and the human leukocyte antigen (HLA) genes, which are required for transplant matching. Nearly 20% of responses were inconsistent between reporting race/ethnicity versus geographic ancestry. Despite strong concordance between AIMs and HLA, no measure of self-identification shows complete correspondence with genetic ancestry. In certain cases geographic ancestry reporting matches genetic ancestry not reflected in race/ethnicity identification, but in other cases geographic ancestries show little correspondence to genetic measures, with important differences by gender. However, when respondents assign ancestry to grandparents, we observe sub-groups of individuals with well- defined genetic ancestries, including important differences in HLA frequencies, with implications for transplant matching. While we advocate for tailored questioning to improve accuracy of ancestry ascertainment, collection of donor grandparents’ information will improve the chances of finding matches for many patients, particularly for mixed-ancestry individuals. PMID:26287376

  13. Race, Ethnicity and Ancestry in Unrelated Transplant Matching for the National Marrow Donor Program: A Comparison of Multiple Forms of Self-Identification with Genetics.

    Directory of Open Access Journals (Sweden)

    Jill A Hollenbach

    Full Text Available We conducted a nationwide study comparing self-identification to genetic ancestry classifications in a large cohort (n = 1752 from the National Marrow Donor Program. We sought to determine how various measures of self-identification intersect with genetic ancestry, with the aim of improving matching algorithms for unrelated bone marrow transplant. Multiple dimensions of self-identification, including race/ethnicity and geographic ancestry were compared to classifications based on ancestry informative markers (AIMs, and the human leukocyte antigen (HLA genes, which are required for transplant matching. Nearly 20% of responses were inconsistent between reporting race/ethnicity versus geographic ancestry. Despite strong concordance between AIMs and HLA, no measure of self-identification shows complete correspondence with genetic ancestry. In certain cases geographic ancestry reporting matches genetic ancestry not reflected in race/ethnicity identification, but in other cases geographic ancestries show little correspondence to genetic measures, with important differences by gender. However, when respondents assign ancestry to grandparents, we observe sub-groups of individuals with well- defined genetic ancestries, including important differences in HLA frequencies, with implications for transplant matching. While we advocate for tailored questioning to improve accuracy of ancestry ascertainment, collection of donor grandparents' information will improve the chances of finding matches for many patients, particularly for mixed-ancestry individuals.

  14. A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events

    Science.gov (United States)

    Danandeh Mehr, Ali; Nourani, Vahid; Hrnjica, Bahrudin; Molajou, Amir

    2017-12-01

    The effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The model was trained and tested using SST series of Black Sea, Mediterranean Sea, and Red Sea as potential predictors as well as classified MMR events at two locations in Iran as predictand. Skill of the model was measured in regard to different rainfall thresholds and SST lags and compared to that of the hybrid decision tree-association rule (DTAR) model available in the literature. The results indicated that the proposed model can identify potential teleconnection signals of surrounding seas beneficial to long-term forecasting of the occurrence of the classified MMR events.

  15. An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

    Science.gov (United States)

    Hsu, Chih-Ming

    2014-12-01

    Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

  16. A Double-Deck Elevator Group Supervisory Control System with Destination Floor Guidance System Using Genetic Network Programming

    Science.gov (United States)

    Yu, Lu; Zhou, Jin; Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Markon, Sandor

    The Elevator Group Supervisory Control Systems (EGSCS) are the control systems that systematically manage three or more elevators in order to efficiently transport the passengers in buildings. Double-deck elevators, where two elevators are connected with each other, serve passengers at two consecutive floors simultaneously. Double-deck Elevator systems (DDES) become more complex in their behavior than conventional single-deck elevator systems (SDES). Recently, Artificial Intelligence (AI) technology has been used in such complex systems. Genetic Network Programming (GNP), a graph-based evolutionary method, has been applied to EGSCS and its advantages are shown in some papers. GNP can obtain the strategy of a new hall call assignment to the optimal elevator when it performs crossover and mutation operations to judgment nodes and processing nodes. Meanwhile, Destination Floor Guidance System (DFGS) is installed in DDES, so that passengers can also input their destinations at elevator halls. In this paper, we have applied GNP to DDES and compared DFGS with normal systems. The waiting time and traveling time of DFGS are all improved because of getting more information from DFGS. The simulations showed the effectiveness of the double-deck elevators with DFGS in different building traffics.

  17. From Heuristic to Mathematical Modeling of Drugs Dissolution Profiles: Application of Artificial Neural Networks and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Aleksander Mendyk

    2015-01-01

    Full Text Available The purpose of this work was to develop a mathematical model of the drug dissolution (Q from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs and genetic programming (GP tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1 direct modeling of Q versus extrudate diameter (d and the time variable (t and (2 indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations’ parameters. Two inputs were found important for the drug dissolution: d and t. The extrudates length (L was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE from 2.19 to 2.33. The direct mode of GP modeling of Q versus d and t resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs’ black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies.

  18. Development of a computational program for treatment of texture data by the X-ray diffraction technique

    International Nuclear Information System (INIS)

    Galego, Eguiberto

    2004-01-01

    In this work it has been developed a computational program for treatment of texture data by the X-ray diffraction technique using pole figures. It has been applied the resolution method by spherical harmonical series expansion for cubic and hexagonal microscopic symmetry and orthorhombic macroscopic symmetry. For yielding the microscopic symmetries it has been necessary the implementation of algorithmic for calculation the spherical harmonic of specific surface. The generation of Legendre Polynomial, based on the experimental data in relation to a and β step angles, is execution in real time. In the introduction of data, the graphical representation of pole figure is drawn in stereo graphic projection, being possible to the analyst three dimensional (3D) visualization. An internal routine verify validity of the Miller indexes, being possible to analyst the correction. The program exhibit the possible corrections applied to experimental data: defocusing, background and orientation of lamination direction (β angle). The correction of the defocusing and background is the executed automatically based on the optic used in the X-ray equipment (Schulz geometric). It has been implemented a routine of graphic manipulation of the contour iso lines for generation of the orientation distribution function (ODF), with easy manipulation of the number of lines and colors. In the ODF graphic, with the action of the mouse cursor on any section, it is visualized the values of Euler angles (φ 1 , Φ, φ 2 ) and of the respective f(g) intensity. Concomitantly, there is 3D graphic visualization of the crystal position in relation to the rolling direction. There is the possibility of graphic visualization in 3D of any section of the ODF. It is also possible the graphic visualization of the texture fiber. This program was named Texture Analysis Program (TAP). (author)

  19. Assessing the Effectiveness of Statistical Classification Techniques in Predicting Future Employment of Participants in the Temporary Assistance for Needy Families Program

    Science.gov (United States)

    Montoya, Isaac D.

    2008-01-01

    Three classification techniques (Chi-square Automatic Interaction Detection [CHAID], Classification and Regression Tree [CART], and discriminant analysis) were tested to determine their accuracy in predicting Temporary Assistance for Needy Families program recipients' future employment. Technique evaluation was based on proportion of correctly…

  20. Use of behavioral change techniques in web-based self-management programs for type 2 diabetes patients: systematic review.

    Science.gov (United States)

    van Vugt, Michael; de Wit, Maartje; Cleijne, Wilmy H J J; Snoek, Frank J

    2013-12-13

    Type 2 diabetes mellitus (T2DM) is a highly prevalent chronic metabolic disease characterized by hyperglycemia and cardiovascular risks. Without proper treatment, T2DM can lead to long-term complications. Diabetes self-management is recognized as the cornerstone of overall diabetes management. Web-based self-management programs for T2DM patients can help to successfully improve patient health behaviors and health-related outcomes. Theories can help to specify key determinants of the target behaviors and behavior change strategies required to arrive at the desired health outcomes, which can then be translated into specific behavioral techniques or strategies that patients can learn to apply in their daily life. From previous reviews of a wide range of online diabetes self-management tools and programs, it appears that it is still unclear which behavioral change techniques (BCTs) are primarily used and are most effective when it comes to improving diabetes self-management behaviors and related health outcomes. We set out to identify which BCTs are being applied in online self-management programs for T2DM and whether there is indication of their effectiveness in relation to predefined health outcomes. Articles were systematically searched and screened on the mentioned use of 40 BCTs, which were then linked to reported statistically significant improvements in study outcomes. We found 13 randomized controlled trials reporting on 8 online self-management interventions for T2DM. The BCTs used were feedback on performance, providing information on consequences of behavior, barrier identification/problem solving, and self-monitoring of behavior. These BCTs were also linked to positive outcomes for health behavior change, psychological well-being, or clinical parameters. A relatively small number of theory-based online self-management support programs for T2DM have been reported using only a select number of BCTs. The development of future online self

  1. The Turn the Tables Technique (T[cube]): A Program Activity to Provide Group Facilitators Insight into Teen Sexual Behaviors and Beliefs

    Science.gov (United States)

    Sclafane, Jamie Heather; Merves, Marni Loiacono; Rivera, Angelic; Long, Laura; Wilson, Ken; Bauman, Laurie J.

    2012-01-01

    The Turn the Tables Technique (T[cube]) is an activity designed to provide group facilitators who lead HIV/STI prevention and sexual health promotion programs with detailed and current information on teenagers' sexual behaviors and beliefs. This information can be used throughout a program to tailor content. Included is a detailed lesson plan of…

  2. [Establishment of a novel HLA genotyping method for preimplantation genetic diagnonis using multiple displacement amplification-polymerase chain reaction-sequencing based technique].

    Science.gov (United States)

    Zhang, Yinfeng; Luo, Haining; Zhang, Yunshan

    2015-12-01

    To establish a novel HLA genotyping method for preimplantation genetic diagnonis (PGD) using multiple displacement amplification-polymerase chain reaction-sequencing based technique (MDA-PCR-SBT). Peripheral blood samples and 76 1PN, 2PN, 3PN discarded embryos from 9 couples were collected. The alleles of HLA-A, B, DR loci were detected from the MDA product with the PCR-SBT method. The HLA genotypes of the parental peripheral blood samples were analyzed with the same protocol. The genotypes of specific HLA region were evaluated for distinguishing the segregation of haplotypes among the family members, and primary HLA matching was performed between the embryos. The 76 embryos were subjected to MDA and 74 (97.4%) were successfully amplified. For the 34 embryos from the single blastomere group, the amplification rate was 94.1%, and for the 40 embryos in the two blastomeres group, the rate was 100%. The dropout rates for DQ allele and DR allele were 1.3% and 0, respectively. The positive rate for MDA in the single blastomere group was 100%, with the dropout rates for DQ allele and DR allele being 1.5% and 0, respectively. The positive rate of MDA for the two blastomere group was 100%, with the dropout rates for both DQ and DR alleles being 0. The recombination rate of fetal HLA was 20.2% (30/148). Due to the improper classification and abnormal fertilized embryos, the proportion of matched embryos HLA was 20.3% (15/74),which was lower than the theoretical value of 25%. PGD with HLA matching can facilitate creation of a HLA-identical donor (saviour child) for umbilical cord blood or bone marrow stem cells for its affected sibling with a genetic disease. Therefore, preimplantation HLA matching may provide a tool for couples desiring to conceive a potential donor progeny for transplantation for its sibling with a life-threatening disorder.

  3. Evaluation of geophysical techniques for identifying fractures in program wells in Deaf Smith County, Texas: Revision 1, Topical report

    International Nuclear Information System (INIS)

    Gillespie, R.P.; Siminitz, P.C.

    1987-08-01

    Quantitative information about the presence and orientation of fractures is essential for the understanding of the geomechanical and geohydrological behavior of rocks. This report evaluates various borehole geophysical techniques for characterizing fractures in three Civilian Radioactive Waste Management (CRWM) Program test wells in the Palo Duro Basin in Deaf Smith County, Texas. Emphasis has been placed on the Schlumberger Fracture Identification Log (FIL) which detects vertical fractures and provides data for calculation of orientation. Depths of FIL anomalies were compared to available core. It was found that the application of FIL results to characterize fracture frequency or orientation is inappropriate at this time. The uncertainties associated with the FIL information render the information unreliable. No geophysical logging tool appears to unequivocally determine the location and orientation of fractures in a borehole. Geologic mapping of the exploratory shafts will ultimately provide the best data on fracture frequency and orientation at the proposed repository site. 22 refs., 6 figs., 3 tabs

  4. Airway Clearance Techniques (ACTs)

    Medline Plus

    Full Text Available ... closer to a cure. Basics of the CFTR Protein Role of Genetics in CF CF Genetics The ... CF Foundation Biorepository CFTR Chemical Compound Program CFTR Protein Domains Patient Registry Data Requests Get Involved X ...

  5. Airway Clearance Techniques (ACTs)

    Medline Plus

    Full Text Available ... closer to a cure. Basics of the CFTR Protein Role of Genetics in CF CF Genetics The ... Assays CFFT Biorepository CFTR Chemical Compound Program CFTR Protein Domains Patient Registry Data Requests Get Involved X ...

  6. Testing of chemicals for genetic activity with Saccharomyces cerevisiae: a report of the U. S. Environmental Protection Agency Gene-Tox Program

    Energy Technology Data Exchange (ETDEWEB)

    Zimmermann, F.K.; von Borstel, R.C.; von Halle, E.S.; Parry, J.M.; Siebert, D.; Zetterberg, G.; Barale, R.; Loprieno, N.

    1984-01-01

    This review article with over 200 references summarizes the results of mutation screening tests with 492 chemicals using saccharomyces cerevisiae as the test organism. In addition, an extensive description of S. cerevisiae as a test organism is given. Yeast can be used to study genetic effects both in mitotic and in meiotic cells because it can be cultured as a stable haploid or a stable diploid. The most commonly used genetic endpoint has been mitotic recombination either as mitotic crossing-over or mitotic gene conversion. Data were available on tests with 492 chemicals, of which 249 were positive, as reported in 173 articles or reports. The genetic test/carcinogenicity accuracy was 0.74, based on the carcinogen listing established in the gene-tox program. The yeast tests supplement the bacterial tests for detecting agents that act via radical formation, antibacterial drugs, and other chemicals interfering with chromosome segregation and recombination processes.

  7. Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs

    Science.gov (United States)

    Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.

    2016-08-01

    Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.

  8. A method of evolving novel feature extraction algorithms for detecting buried objects in FLIR imagery using genetic programming

    Science.gov (United States)

    Paino, A.; Keller, J.; Popescu, M.; Stone, K.

    2014-06-01

    In this paper we present an approach that uses Genetic Programming (GP) to evolve novel feature extraction algorithms for greyscale images. Our motivation is to create an automated method of building new feature extraction algorithms for images that are competitive with commonly used human-engineered features, such as Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). The evolved feature extraction algorithms are functions defined over the image space, and each produces a real-valued feature vector of variable length. Each evolved feature extractor breaks up the given image into a set of cells centered on every pixel, performs evolved operations on each cell, and then combines the results of those operations for every cell using an evolved operator. Using this method, the algorithm is flexible enough to reproduce both LBP and HOG features. The dataset we use to train and test our approach consists of a large number of pre-segmented image "chips" taken from a Forward Looking Infrared Imagery (FLIR) camera mounted on the hood of a moving vehicle. The goal is to classify each image chip as either containing or not containing a buried object. To this end, we define the fitness of a candidate solution as the cross-fold validation accuracy of the features generated by said candidate solution when used in conjunction with a Support Vector Machine (SVM) classifier. In order to validate our approach, we compare the classification accuracy of an SVM trained using our evolved features with the accuracy of an SVM trained using mainstream feature extraction algorithms, including LBP and HOG.

  9. Genetic expression programming-based DBA for enhancing peer-assisted music-on-demand service in EPON

    Science.gov (United States)

    Liem, Andrew Tanny; Hwang, I.-Shyan; Nikoukar, AliAkbar; Lee, Jhong-Yue

    2015-03-01

    Today, the popularity of peer-assisted music-on-demand (MoD) has increased significantly worldwide. This service allows users to access large music library tracks, listen to music, and share their playlist with other users. Unlike the conventional voice traffic, such an application maintains music quality that ranges from 160 kbps to 320 kbps, which most likely consumes more bandwidth than other traffics. In the access network, Ethernet passive optical network (EPON) is one of the best candidates for delivering such a service because of being cost-effective and with high bandwidth. To maintain music quality, a stutter needs to be prevented because of either network effects or when the due user was not receiving enough resources to play in a timely manner. Therefore, in this paper, we propose two genetic expression programming (GEP)-based dynamic bandwidth allocations (DBAs). The first DBA is a generic DBA that aims to find an optimum formula for voice, video, and data services. The second DBA aims to find optimum formulas so that Optical Line Terminal (OLT) can satisfy not only the voice and Peer-to-Peer (P2P) MoD traffics but also reduce the stutter. Optical Network Unit (ONU) traits such as REPORT and GATE messages, cycle time, and mean packet delay are set to be predictor variables. Simulation results show that our proposed DBAs can satisfy the voice and P2P MoD services packet delay and monitor other overall system performances such as expedited forwarding (EF) jitter, packet loss, bandwidth waste, and system throughputs.

  10. Generating information-rich high-throughput experimental materials genomes using functional clustering via multitree genetic programming and information theory.

    Science.gov (United States)

    Suram, Santosh K; Haber, Joel A; Jin, Jian; Gregoire, John M

    2015-04-13

    High-throughput experimental methodologies are capable of synthesizing, screening and characterizing vast arrays of combinatorial material libraries at a very rapid rate. These methodologies strategically employ tiered screening wherein the number of compositions screened decreases as the complexity, and very often the scientific information obtained from a screening experiment, increases. The algorithm used for down-selection of samples from higher throughput screening experiment to a lower throughput screening experiment is vital in achieving information-rich experimental materials genomes. The fundamental science of material discovery lies in the establishment of composition-structure-property relationships, motivating the development of advanced down-selection algorithms which consider the information value of the selected compositions, as opposed to simply selecting the best performing compositions from a high throughput experiment. Identification of property fields (composition regions with distinct composition-property relationships) in high throughput data enables down-selection algorithms to employ advanced selection strategies, such as the selection of representative compositions from each field or selection of compositions that span the composition space of the highest performing field. Such strategies would greatly enhance the generation of data-driven discoveries. We introduce an informatics-based clustering of composition-property functional relationships using a combination of information theory and multitree genetic programming concepts for identification of property fields in a composition library. We demonstrate our approach using a complex synthetic composition-property map for a 5 at. % step ternary library consisting of four distinct property fields and finally explore the application of this methodology for capturing relationships between composition and catalytic activity for the oxygen evolution reaction for 5429 catalyst compositions in a

  11. Evolutionary Computation Techniques for Predicting Atmospheric Corrosion

    Directory of Open Access Journals (Sweden)

    Amine Marref

    2013-01-01

    Full Text Available Corrosion occurs in many engineering structures such as bridges, pipelines, and refineries and leads to the destruction of materials in a gradual manner and thus shortening their lifespan. It is therefore crucial to assess the structural integrity of engineering structures which are approaching or exceeding their designed lifespan in order to ensure their correct functioning, for example, carrying ability and safety. An understanding of corrosion and an ability to predict corrosion rate of a material in a particular environment plays a vital role in evaluating the residual life of the material. In this paper we investigate the use of genetic programming and genetic algorithms in the derivation of corrosion-rate expressions for steel and zinc. Genetic programming is used to automatically evolve corrosion-rate expressions while a genetic algorithm is used to evolve the parameters of an already engineered corrosion-rate expression. We show that both evolutionary techniques yield corrosion-rate expressions that have good accuracy.

  12. A wireless batteryless in vivo EKG and core body temperature sensing microsystem with 60 Hz suppression technique for untethered genetically engineered mice real-time monitoring.

    Science.gov (United States)

    Chaimanonart, Nattapon; Young, Darrin J

    2009-01-01

    A wireless, batteryless, and implantable EKG and core body temperature sensing microsystem with adaptive RF powering for untethered genetically engineered mice real-time monitoring is designed, implemented, and in vivo characterized. A packaged microsystem, exhibiting a total size of 9 mm x 7 mm x 3 mm with a weight of 400 mg including a pair of stainless-steel EKG electrodes, is implanted in a mouse abdomen for real-time monitoring. A low power 2 mm x 2 mm ASIC, consisting of an EKG amplifier, a proportional-to-absolute-temperature (PTAT)-based temperature sensor, an RF power sensing circuit, an RF-DC power converter, an 8-bit ADC, digital control circuitry, and a 433 MHz FSK transmitter, is powered by an adaptively controlled external RF energy source at 4 MHz to ensure a stable 2V supply with 156microA current driving capability for the overall microsystem. An electrical model for analyzing 60 Hz interference based on 2-electrode and 3-electrode configurations is proposed and compared with in vivo evaluation results. Due to the small laboratory animal chest area, a 60 Hz suppression technique by employing input termination resistors is chosen for two-EKG-electrode implant configuration.

  13. Optimal platform design using non-dominated sorting genetic algorithm II and technique for order of preference by similarity to ideal solution; application to automotive suspension system

    Science.gov (United States)

    Shojaeefard, Mohammad Hassan; Khalkhali, Abolfazl; Faghihian, Hamed; Dahmardeh, Masoud

    2018-03-01

    Unlike conventional approaches where optimization is performed on a unique component of a specific product, optimum design of a set of components for employing in a product family can cause significant reduction in costs. Increasing commonality and performance of the product platform simultaneously is a multi-objective optimization problem (MOP). Several optimization methods are reported to solve these MOPs. However, what is less discussed is how to find the trade-off points among the obtained non-dominated optimum points. This article investigates the optimal design of a product family using non-dominated sorting genetic algorithm II (NSGA-II) and proposes the employment of technique for order of preference by similarity to ideal solution (TOPSIS) method to find the trade-off points among the obtained non-dominated results while compromising all objective functions together. A case study for a family of suspension systems is presented, considering performance and commonality. The results indicate the effectiveness of the proposed method to obtain the trade-off points with the best possible performance while maximizing the common parts.

  14. Developmental status of bioassays in genetic toxicology: a report of Phase II of the US Environmental Protection Agency Gene-Tox program

    Energy Technology Data Exchange (ETDEWEB)

    Brusick, D; Auletta, A

    1985-01-01

    The Gene-Tox Program was structured around two phases of genetic test data evaluation. The first phase consisted of 36 Work Group reports, each evaluating the results and performance of a specific bioassay. The second phase consisted of a plan to summarize the information provided by the Work Groups. The Gene-Tox Coordinating Committee was to be responsible for Phase II, and several subgroups were assigned specific goals in implementing this analysis. This report deals with Goal I which is to identify the developmental status of the individual bioassays reviewed by the Gene-Tox Work Groups in the first phase of the Program. 5 references, 6 tables.

  15. Temperature based daily incoming solar radiation modeling based on gene expression programming, neuro-fuzzy and neural network computing techniques.

    Science.gov (United States)

    Landeras, G.; López, J. J.; Kisi, O.; Shiri, J.

    2012-04-01

    The correct observation/estimation of surface incoming solar radiation (RS) is very important for many agricultural, meteorological and hydrological related applications. While most weather stations are provided with sensors for air temperature detection, the presence of sensors necessary for the detection of solar radiation is not so habitual and the data quality provided by them is sometimes poor. In these cases it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using Gene Expression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Traditional temperature based solar radiation equations were also included in this study and compared with artificial intelligence based approaches. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models' performances. An ANN (a four-input multilayer perceptron with ten neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m-2 d-1 of RMSE). A four-input ANFIS model revealed as an interesting alternative to ANNs (3.14 MJ m-2 d-1 of RMSE). Very limited number of studies has been done on estimation of solar radiation based on ANFIS, and the present one demonstrated the ability of ANFIS to model solar radiation based on temperatures and extraterrestrial radiation. By the way this study demonstrated, for the first time, the ability of GEP models to model solar radiation based on daily atmospheric variables. Despite the accuracy of GEP models was slightly lower than the ANFIS and ANN models the genetic programming models (i.e., GEP) are superior to other artificial intelligence models in giving a simple explicit equation for the

  16. Within a smoking-cessation program, what impact does genetic information on lung cancer need to have to demonstrate cost-effectiveness?

    Directory of Open Access Journals (Sweden)

    Gordon Louisa G

    2010-09-01

    Full Text Available Abstract Background Many smoking-cessation programs and pharmaceutical aids demonstrate substantial health gains for a relatively low allocation of resources. Genetic information represents a type of individualized or personal feedback regarding the risk of developing lung cancer, and hence the potential benefits from stopping smoking, may motivate the person to remain smoke-free. The purpose of this study was to explore what the impact of a genetic test needs to have within a typical smoking-cessation program aimed at heavy smokers in order to be cost-effective. Methods Two strategies were modelled for a hypothetical cohort of heavy smokers aged 50 years; individuals either received or did not receive a genetic test within the course of a usual smoking-cessation intervention comprising nicotine replacement therapy (NRT and counselling. A Markov model was constructed using evidence from published randomized controlled trials and meta-analyses for estimates on 12-month quit rates and long-term relapse rates. Epidemiological data were used for estimates on lung cancer risk stratified by time since quitting and smoking patterns. Extensive sensitivity analyses were used to explore parameter uncertainty. Results The discounted incremental cost per QALY was AU$34,687 (95% CI $12,483, $87,734 over 35 years. At a willingness-to-pay of AU$20,000 per QALY gained, the genetic testing strategy needs to produce a 12-month quit rate of at least 12.4% or a relapse rate 12% lower than NRT and counselling alone for it to be equally cost-effective. The likelihood that adding a genetic test to the usual smoking-cessation intervention is cost-effective was 20.6% however cost-effectiveness ratios were favourable in certain situations (e.g., applied to men only, a 60 year old cohort. Conclusions The findings were sensitive to small changes in critical variables such as the 12-month quit rates and relapse rates. As such, the cost-effectiveness of the genetic testing

  17. Which Individuals To Choose To Update the Reference Population? Minimizing the Loss of Genetic Diversity in Animal Genomic Selection Programs

    Directory of Open Access Journals (Sweden)

    Sonia E. Eynard

    2018-01-01

    Full Text Available Genomic selection (GS is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a potential loss of genetic diversity. Existing methods to conserve genetic diversity depend mostly on the choice of the breeding individuals. In this study, we propose a modification of the reference population composition to mitigate diversity loss. Since the high cost of phenotyping is the limiting factor for GS, our findings are of major economic interest. This study aims to answer the following questions: how would decisions on the reference population affect the breeding population, and how to best select individuals to update the reference population and balance maximizing genetic gain and minimizing loss of genetic diversity? We investigated three updating strategies for the reference population: random, truncation, and optimal contribution (OC strategies. OC maximizes genetic merit for a fixed loss of genetic diversity. A French Montbéliarde dairy cattle population with 50K SNP chip genotypes and simulations over 10 generations were used to compare these different strategies using milk production as the trait of interest. Candidates were selected to update the reference population. Prediction bias and both genetic merit and diversity were measured. Changes in the reference population composition slightly affected the breeding population. Optimal contribution strategy appeared to be an acceptable compromise to maintain both genetic gain and diversity in the reference and the breeding populations.

  18. Which Individuals To Choose To Update the Reference Population? Minimizing the Loss of Genetic Diversity in Animal Genomic Selection Programs.

    Science.gov (United States)

    Eynard, Sonia E; Croiseau, Pascal; Laloë, Denis; Fritz, Sebastien; Calus, Mario P L; Restoux, Gwendal

    2018-01-04

    Genomic selection (GS) is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a potential loss of genetic diversity. Existing methods to conserve genetic diversity depend mostly on the choice of the breeding individuals. In this study, we propose a modification of the reference population composition to mitigate diversity loss. Since the high cost of phenotyping is the limiting factor for GS, our findings are of major economic interest. This study aims to answer the following questions: how would decisions on the reference population affect the breeding population, and how to best select individuals to update the reference population and balance maximizing genetic gain and minimizing loss of genetic diversity? We investigated three updating strategies for the reference population: random, truncation, and optimal contribution (OC) strategies. OC maximizes genetic merit for a fixed loss of genetic diversity. A French Montbéliarde dairy cattle population with 50K SNP chip genotypes and simulations over 10 generations were used to compare these different strategies using milk production as the trait of interest. Candidates were selected to update the reference population. Prediction bias and both genetic merit and diversity were measured. Changes in the reference population composition slightly affected the breeding population. Optimal contribution strategy appeared to be an acceptable compromise to maintain both genetic gain and diversity in the reference and the breeding populations. Copyright © 2018 Eynard et al.

  19. Facilitating Breast Cancer Genetic Counseling Through Information, Preparation and Referral: A Pilot Program Using the Cancer Information Service

    National Research Council Canada - National Science Library

    Miller, Suzanne

    2001-01-01

    Previous research has shown that women often lack knowledge regarding the kinds of information that are required to determine inherited risk as well as on the process and content of risk assessment/genetic testing...

  20. Facilitating Breast Cancer Genetic Couseling through Information, Preparation and Referral: A Pilot Program Using the Cancer Information Service

    National Research Council Canada - National Science Library

    Miller, Suzanne

    2000-01-01

    Previous research has shown that women often lack knowledge regarding the kinds of information that are required to determine inherited risk as well as on the process and content of risk assessment/genetic testing...