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Sample records for soft computing based

  1. Detecting Soft Errors in Stencil based Computations

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, V. [Univ. of Utah, Salt Lake City, UT (United States); Gopalkrishnan, G. [Univ. of Utah, Salt Lake City, UT (United States); Bronevetsky, G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-05-06

    Given the growing emphasis on system resilience, it is important to develop software-level error detectors that help trap hardware-level faults with reasonable accuracy while minimizing false alarms as well as the performance overhead introduced. We present a technique that approaches this idea by taking stencil computations as our target, and synthesizing detectors based on machine learning. In particular, we employ linear regression to generate computationally inexpensive models which form the basis for error detection. Our technique has been incorporated into a new open-source library called SORREL. In addition to reporting encouraging experimental results, we demonstrate techniques that help reduce the size of training data. We also discuss the efficacy of various detectors synthesized, as well as our future plans.

  2. Phoneme-based speech segmentation using hybrid soft computing framework

    CERN Document Server

    Sarma, Mousmita

    2014-01-01

    The book discusses intelligent system design using soft computing and similar systems and their interdisciplinary applications. It also focuses on the recent trends to use soft computing as a versatile tool for designing a host of decision support systems.

  3. A Simulation-Based Soft Error Estimation Methodology for Computer Systems

    OpenAIRE

    Sugihara, Makoto; Ishihara, Tohru; Hashimoto, Koji; Muroyama, Masanori

    2006-01-01

    This paper proposes a simulation-based soft error estimation methodology for computer systems. Accumulating soft error rates (SERs) of all memories in a computer system results in pessimistic soft error estimation. This is because memory cells are used spatially and temporally and not all soft errors in them make the computer system faulty. Our soft-error estimation methodology considers the locations and the timings of soft errors occurring at every level of memory hierarchy and estimates th...

  4. Modeling soft factors in computer-based wargames

    Science.gov (United States)

    Alexander, Steven M.; Ross, David O.; Vinarskai, Jonathan S.; Farr, Steven D.

    2002-07-01

    Computer-based wargames have seen much improvement in recent years due to rapid increases in computing power. Because these games have been developed for the entertainment industry, most of these advances have centered on the graphics, sound, and user interfaces integrated into these wargames with less attention paid to the game's fidelity. However, for a wargame to be useful to the military, it must closely approximate as many of the elements of war as possible. Among the elements that are typically not modeled or are poorly modeled in nearly all military computer-based wargames are systematic effects, command and control, intelligence, morale, training, and other human and political factors. These aspects of war, with the possible exception of systematic effects, are individually modeled quite well in many board-based commercial wargames. The work described in this paper focuses on incorporating these elements from the board-based games into a computer-based wargame. This paper will also address the modeling and simulation of the systemic paralysis of an adversary that is implied by the concept of Effects Based Operations (EBO). Combining the fidelity of current commercial board wargames with the speed, ease of use, and advanced visualization of the computer can significantly improve the effectiveness of military decision making and education. Once in place, the process of converting board wargames concepts to computer wargames will allow the infusion of soft factors into military training and planning.

  5. Microarray-based cancer prediction using soft computing approach.

    Science.gov (United States)

    Wang, Xiaosheng; Gotoh, Osamu

    2009-05-26

    One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

  6. Problems and Issues in Using Computer- Based Support Tools to Enhance 'Soft' Systems Methodologies

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    Mark Stansfield

    2001-11-01

    Full Text Available This paper explores the issue of whether computer-based support tools can enhance the use of 'soft' systems methodologies as applied to real-world problem situations. Although work has been carried out by a number of researchers in applying computer-based technology to concepts and methodologies relating to 'soft' systems thinking such as Soft Systems Methodology (SSM, such attempts appear to be still in their infancy and have not been applied widely to real-world problem situations. This paper will highlight some of the problems that may be encountered in attempting to develop computer-based support tools for 'soft' systems methodologies. Particular attention will be paid to an attempt by the author to develop a computer-based support tool for a particular 'soft' systems method of inquiry known as the Appreciative Inquiry Method that is based upon Vickers' notion of 'appreciation' (Vickers, 196S and Checkland's SSM (Checkland, 1981. The final part of the paper will explore some of the lessons learnt from developing and applying the computer-based support tool to a real world problem situation, as well as considering the feasibility of developing computer-based support tools for 'soft' systems methodologies. This paper will put forward the point that a mixture of manual and computer-based tools should be employed to allow a methodology to be used in an unconstrained manner, but the benefits provided by computer-based technology should be utilised in supporting and enhancing the more mundane and structured tasks.

  7. The soft computing-based approach to investigate allergic diseases: a systematic review.

    Science.gov (United States)

    Tartarisco, Gennaro; Tonacci, Alessandro; Minciullo, Paola Lucia; Billeci, Lucia; Pioggia, Giovanni; Incorvaia, Cristoforo; Gangemi, Sebastiano

    2017-01-01

    Early recognition of inflammatory markers and their relation to asthma, adverse drug reactions, allergic rhinitis, atopic dermatitis and other allergic diseases is an important goal in allergy. The vast majority of studies in the literature are based on classic statistical methods; however, developments in computational techniques such as soft computing-based approaches hold new promise in this field. The aim of this manuscript is to systematically review the main soft computing-based techniques such as artificial neural networks, support vector machines, bayesian networks and fuzzy logic to investigate their performances in the field of allergic diseases. The review was conducted following PRISMA guidelines and the protocol was registered within PROSPERO database (CRD42016038894). The research was performed on PubMed and ScienceDirect, covering the period starting from September 1, 1990 through April 19, 2016. The review included 27 studies related to allergic diseases and soft computing performances. We observed promising results with an overall accuracy of 86.5%, mainly focused on asthmatic disease. The review reveals that soft computing-based approaches are suitable for big data analysis and can be very powerful, especially when dealing with uncertainty and poorly characterized parameters. Furthermore, they can provide valuable support in case of lack of data and entangled cause-effect relationships, which make it difficult to assess the evolution of disease. Although most works deal with asthma, we believe the soft computing approach could be a real breakthrough and foster new insights into other allergic diseases as well.

  8. Microscope self-calibration based on micro laser line imaging and soft computing algorithms

    Science.gov (United States)

    Apolinar Muñoz Rodríguez, J.

    2018-06-01

    A technique to perform microscope self-calibration via micro laser line and soft computing algorithms is presented. In this technique, the microscope vision parameters are computed by means of soft computing algorithms based on laser line projection. To implement the self-calibration, a microscope vision system is constructed by means of a CCD camera and a 38 μm laser line. From this arrangement, the microscope vision parameters are represented via Bezier approximation networks, which are accomplished through the laser line position. In this procedure, a genetic algorithm determines the microscope vision parameters by means of laser line imaging. Also, the approximation networks compute the three-dimensional vision by means of the laser line position. Additionally, the soft computing algorithms re-calibrate the vision parameters when the microscope vision system is modified during the vision task. The proposed self-calibration improves accuracy of the traditional microscope calibration, which is accomplished via external references to the microscope system. The capability of the self-calibration based on soft computing algorithms is determined by means of the calibration accuracy and the micro-scale measurement error. This contribution is corroborated by an evaluation based on the accuracy of the traditional microscope calibration.

  9. Driving profile modeling and recognition based on soft computing approach.

    Science.gov (United States)

    Wahab, Abdul; Quek, Chai; Tan, Chin Keong; Takeda, Kazuya

    2009-04-01

    Advancements in biometrics-based authentication have led to its increasing prominence and are being incorporated into everyday tasks. Existing vehicle security systems rely only on alarms or smart card as forms of protection. A biometric driver recognition system utilizing driving behaviors is a highly novel and personalized approach and could be incorporated into existing vehicle security system to form a multimodal identification system and offer a greater degree of multilevel protection. In this paper, detailed studies have been conducted to model individual driving behavior in order to identify features that may be efficiently and effectively used to profile each driver. Feature extraction techniques based on Gaussian mixture models (GMMs) are proposed and implemented. Features extracted from the accelerator and brake pedal pressure were then used as inputs to a fuzzy neural network (FNN) system to ascertain the identity of the driver. Two fuzzy neural networks, namely, the evolving fuzzy neural network (EFuNN) and the adaptive network-based fuzzy inference system (ANFIS), are used to demonstrate the viability of the two proposed feature extraction techniques. The performances were compared against an artificial neural network (NN) implementation using the multilayer perceptron (MLP) network and a statistical method based on the GMM. Extensive testing was conducted and the results show great potential in the use of the FNN for real-time driver identification and verification. In addition, the profiling of driver behaviors has numerous other potential applications for use by law enforcement and companies dealing with buses and truck drivers.

  10. Controller Design of DFIG Based Wind Turbine by Using Evolutionary Soft Computational Techniques

    Directory of Open Access Journals (Sweden)

    O. P. Bharti

    2017-06-01

    Full Text Available This manuscript illustrates the controller design for a doubly fed induction generator based variable speed wind turbine by using a bioinspired scheme. This methodology is based on exploiting two proficient swarm intelligence based evolutionary soft computational procedures. The particle swarm optimization (PSO and bacterial foraging optimization (BFO techniques are employed to design the controller intended for small damping plant of the DFIG. Wind energy overview and DFIG operating principle along with the equivalent circuit model is adequately discussed in this paper. The controller design for DFIG based WECS using PSO and BFO are described comparatively in detail. The responses of the DFIG system regarding terminal voltage, current, active-reactive power, and DC-Link voltage have slightly improved with the evolutionary soft computational procedure. Lastly, the obtained output is equated with a standard technique for performance improvement of DFIG based wind energy conversion system.

  11. Soft computing for business intelligence

    CERN Document Server

    Pérez, Rafael; Cobo, Angel; Marx, Jorge; Valdés, Ariel

    2014-01-01

    The book Soft Computing for Business Intelligence is the remarkable output of a program based on the idea of joint trans-disciplinary research as supported by the Eureka Iberoamerica Network and the University of Oldenburg. It contains twenty-seven papers allocated to three sections: Soft Computing, Business Intelligence and Knowledge Discovery, and Knowledge Management and Decision Making. Although the contents touch different domains they are similar in so far as they follow the BI principle “Observation and Analysis” while keeping a practical oriented theoretical eye on sound methodologies, like Fuzzy Logic, Compensatory Fuzzy Logic (CFL), Rough Sets and other softcomputing elements. The book tears down the traditional focus on business, and extends Business Intelligence techniques in an impressive way to a broad range of fields like medicine, environment, wind farming, social collaboration and interaction, car sharing and sustainability.

  12. Soft computing techniques in engineering applications

    CERN Document Server

    Zhong, Baojiang

    2014-01-01

    The Soft Computing techniques, which are based on the information processing of biological systems are now massively used in the area of pattern recognition, making prediction & planning, as well as acting on the environment. Ideally speaking, soft computing is not a subject of homogeneous concepts and techniques; rather, it is an amalgamation of distinct methods that confirms to its guiding principle. At present, the main aim of soft computing is to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness and low solutions cost. The principal constituents of soft computing techniques are probabilistic reasoning, fuzzy logic, neuro-computing, genetic algorithms, belief networks, chaotic systems, as well as learning theory. This book covers contributions from various authors to demonstrate the use of soft computing techniques in various applications of engineering.  

  13. 4th World Conference on Soft Computing

    CERN Document Server

    Abbasov, Ali; Yager, Ronald; Shahbazova, Shahnaz; Reformat, Marek

    2016-01-01

    This book reports on advanced theories and cutting-edge applications in the field of soft computing. The individual chapters, written by leading researchers, are based on contributions presented during the 4th World Conference on Soft Computing, held May 25-27, 2014, in Berkeley. The book covers a wealth of key topics in soft computing, focusing on both fundamental aspects and applications. The former include fuzzy mathematics, type-2 fuzzy sets, evolutionary-based optimization, aggregation and neural networks, while the latter include soft computing in data analysis, image processing, decision-making, classification, series prediction, economics, control, and modeling. By providing readers with a timely, authoritative view on the field, and by discussing thought-provoking developments and challenges, the book will foster new research directions in the diverse areas of soft computing. .

  14. Image Analysis Based on Soft Computing and Applied on Space Shuttle During the Liftoff Process

    Science.gov (United States)

    Dominquez, Jesus A.; Klinko, Steve J.

    2007-01-01

    Imaging techniques based on Soft Computing (SC) and developed at Kennedy Space Center (KSC) have been implemented on a variety of prototype applications related to the safety operation of the Space Shuttle during the liftoff process. These SC-based prototype applications include detection and tracking of moving Foreign Objects Debris (FOD) during the Space Shuttle liftoff, visual anomaly detection on slidewires used in the emergency egress system for the Space Shuttle at the laJlIlch pad, and visual detection of distant birds approaching the Space Shuttle launch pad. This SC-based image analysis capability developed at KSC was also used to analyze images acquired during the accident of the Space Shuttle Columbia and estimate the trajectory and velocity of the foam that caused the accident.

  15. Enhancing performance of next generation FSO communication systems using soft computing-based predictions.

    Science.gov (United States)

    Kazaura, Kamugisha; Omae, Kazunori; Suzuki, Toshiji; Matsumoto, Mitsuji; Mutafungwa, Edward; Korhonen, Timo O; Murakami, Tadaaki; Takahashi, Koichi; Matsumoto, Hideki; Wakamori, Kazuhiko; Arimoto, Yoshinori

    2006-06-12

    The deterioration and deformation of a free-space optical beam wave-front as it propagates through the atmosphere can reduce the link availability and may introduce burst errors thus degrading the performance of the system. We investigate the suitability of utilizing soft-computing (SC) based tools for improving performance of free-space optical (FSO) communications systems. The SC based tools are used for the prediction of key parameters of a FSO communications system. Measured data collected from an experimental FSO communication system is used as training and testing data for a proposed multi-layer neural network predictor (MNNP) used to predict future parameter values. The predicted parameters are essential for reducing transmission errors by improving the antenna's accuracy of tracking data beams. This is particularly essential for periods considered to be of strong atmospheric turbulence. The parameter values predicted using the proposed tool show acceptable conformity with original measurements.

  16. Engineering applications of soft computing

    CERN Document Server

    Díaz-Cortés, Margarita-Arimatea; Rojas, Raúl

    2017-01-01

    This book bridges the gap between Soft Computing techniques and their applications to complex engineering problems. In each chapter we endeavor to explain the basic ideas behind the proposed applications in an accessible format for readers who may not possess a background in some of the fields. Therefore, engineers or practitioners who are not familiar with Soft Computing methods will appreciate that the techniques discussed go beyond simple theoretical tools, since they have been adapted to solve significant problems that commonly arise in such areas. At the same time, the book will show members of the Soft Computing community how engineering problems are now being solved and handled with the help of intelligent approaches. Highlighting new applications and implementations of Soft Computing approaches in various engineering contexts, the book is divided into 12 chapters. Further, it has been structured so that each chapter can be read independently of the others.

  17. COOBBO: A Novel Opposition-Based Soft Computing Algorithm for TSP Problems

    Directory of Open Access Journals (Sweden)

    Qingzheng Xu

    2014-12-01

    Full Text Available In this paper, we propose a novel definition of opposite path. Its core feature is that the sequence of candidate paths and the distances between adjacent nodes in the tour are considered simultaneously. In a sense, the candidate path and its corresponding opposite path have the same (or similar at least distance to the optimal path in the current population. Based on an accepted framework for employing opposition-based learning, Oppositional Biogeography-Based Optimization using the Current Optimum, called COOBBO algorithm, is introduced to solve traveling salesman problems. We demonstrate its performance on eight benchmark problems and compare it with other optimization algorithms. Simulation results illustrate that the excellent performance of our proposed algorithm is attributed to the distinct definition of opposite path. In addition, its great strength lies in exploitation for enhancing the solution accuracy, not exploration for improving the population diversity. Finally, by comparing different version of COOBBO, another conclusion is that each successful opposition-based soft computing algorithm needs to adjust and remain a good balance between backward adjacent node and forward adjacent node.

  18. Hardware for soft computing and soft computing for hardware

    CERN Document Server

    Nedjah, Nadia

    2014-01-01

    Single and Multi-Objective Evolutionary Computation (MOEA),  Genetic Algorithms (GAs), Artificial Neural Networks (ANNs), Fuzzy Controllers (FCs), Particle Swarm Optimization (PSO) and Ant colony Optimization (ACO) are becoming omnipresent in almost every intelligent system design. Unfortunately, the application of the majority of these techniques is complex and so requires a huge computational effort to yield useful and practical results. Therefore, dedicated hardware for evolutionary, neural and fuzzy computation is a key issue for designers. With the spread of reconfigurable hardware such as FPGAs, digital as well as analog hardware implementations of such computation become cost-effective. The idea behind this book is to offer a variety of hardware designs for soft computing techniques that can be embedded in any final product. Also, to introduce the successful application of soft computing technique to solve many hard problem encountered during the design of embedded hardware designs. Reconfigurable em...

  19. Temperature-based estimation of global solar radiation using soft computing methodologies

    Science.gov (United States)

    Mohammadi, Kasra; Shamshirband, Shahaboddin; Danesh, Amir Seyed; Abdullah, Mohd Shahidan; Zamani, Mazdak

    2016-07-01

    Precise knowledge of solar radiation is indeed essential in different technological and scientific applications of solar energy. Temperature-based estimation of global solar radiation would be appealing owing to broad availability of measured air temperatures. In this study, the potentials of soft computing techniques are evaluated to estimate daily horizontal global solar radiation (DHGSR) from measured maximum, minimum, and average air temperatures ( T max, T min, and T avg) in an Iranian city. For this purpose, a comparative evaluation between three methodologies of adaptive neuro-fuzzy inference system (ANFIS), radial basis function support vector regression (SVR-rbf), and polynomial basis function support vector regression (SVR-poly) is performed. Five combinations of T max, T min, and T avg are served as inputs to develop ANFIS, SVR-rbf, and SVR-poly models. The attained results show that all ANFIS, SVR-rbf, and SVR-poly models provide favorable accuracy. Based upon all techniques, the higher accuracies are achieved by models (5) using T max- T min and T max as inputs. According to the statistical results, SVR-rbf outperforms SVR-poly and ANFIS. For SVR-rbf (5), the mean absolute bias error, root mean square error, and correlation coefficient are 1.1931 MJ/m2, 2.0716 MJ/m2, and 0.9380, respectively. The survey results approve that SVR-rbf can be used efficiently to estimate DHGSR from air temperatures.

  20. A Soft Computing Based Approach Using Modified Selection Strategy for Feature Reduction of Medical Systems

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    Kursat Zuhtuogullari

    2013-01-01

    Full Text Available The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data.

  1. A soft computing based approach using modified selection strategy for feature reduction of medical systems.

    Science.gov (United States)

    Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

    2013-01-01

    The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data.

  2. Soft computing in computer and information science

    CERN Document Server

    Fray, Imed; Pejaś, Jerzy

    2015-01-01

    This book presents a carefully selected and reviewed collection of papers presented during the 19th Advanced Computer Systems conference ACS-2014. The Advanced Computer Systems conference concentrated from its beginning on methods and algorithms of artificial intelligence. Further future brought new areas of interest concerning technical informatics related to soft computing and some more technological aspects of computer science such as multimedia and computer graphics, software engineering, web systems, information security and safety or project management. These topics are represented in the present book under the categories Artificial Intelligence, Design of Information and Multimedia Systems, Information Technology Security and Software Technologies.

  3. Impact of Computed Tomography Image Quality on Image-Guided Radiation Therapy Based on Soft Tissue Registration

    International Nuclear Information System (INIS)

    Morrow, Natalya V.; Lawton, Colleen A.; Qi, X. Sharon; Li, X. Allen

    2012-01-01

    Purpose: In image-guided radiation therapy (IGRT), different computed tomography (CT) modalities with varying image quality are being used to correct for interfractional variations in patient set-up and anatomy changes, thereby reducing clinical target volume to the planning target volume (CTV-to-PTV) margins. We explore how CT image quality affects patient repositioning and CTV-to-PTV margins in soft tissue registration-based IGRT for prostate cancer patients. Methods and Materials: Four CT-based IGRT modalities used for prostate RT were considered in this study: MV fan beam CT (MVFBCT) (Tomotherapy), MV cone beam CT (MVCBCT) (MVision; Siemens), kV fan beam CT (kVFBCT) (CTVision, Siemens), and kV cone beam CT (kVCBCT) (Synergy; Elekta). Daily shifts were determined by manual registration to achieve the best soft tissue agreement. Effect of image quality on patient repositioning was determined by statistical analysis of daily shifts for 136 patients (34 per modality). Inter- and intraobserver variability of soft tissue registration was evaluated based on the registration of a representative scan for each CT modality with its corresponding planning scan. Results: Superior image quality with the kVFBCT resulted in reduced uncertainty in soft tissue registration during IGRT compared with other image modalities for IGRT. The largest interobserver variations of soft tissue registration were 1.1 mm, 2.5 mm, 2.6 mm, and 3.2 mm for kVFBCT, kVCBCT, MVFBCT, and MVCBCT, respectively. Conclusions: Image quality adversely affects the reproducibility of soft tissue-based registration for IGRT and necessitates a careful consideration of residual uncertainties in determining different CTV-to-PTV margins for IGRT using different image modalities.

  4. Impact of Computed Tomography Image Quality on Image-Guided Radiation Therapy Based on Soft Tissue Registration

    Energy Technology Data Exchange (ETDEWEB)

    Morrow, Natalya V.; Lawton, Colleen A. [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin (United States); Qi, X. Sharon [Department of Radiation Oncology, University of Colorado Denver, Denver, Colorado (United States); Li, X. Allen, E-mail: ali@mcw.edu [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin (United States)

    2012-04-01

    Purpose: In image-guided radiation therapy (IGRT), different computed tomography (CT) modalities with varying image quality are being used to correct for interfractional variations in patient set-up and anatomy changes, thereby reducing clinical target volume to the planning target volume (CTV-to-PTV) margins. We explore how CT image quality affects patient repositioning and CTV-to-PTV margins in soft tissue registration-based IGRT for prostate cancer patients. Methods and Materials: Four CT-based IGRT modalities used for prostate RT were considered in this study: MV fan beam CT (MVFBCT) (Tomotherapy), MV cone beam CT (MVCBCT) (MVision; Siemens), kV fan beam CT (kVFBCT) (CTVision, Siemens), and kV cone beam CT (kVCBCT) (Synergy; Elekta). Daily shifts were determined by manual registration to achieve the best soft tissue agreement. Effect of image quality on patient repositioning was determined by statistical analysis of daily shifts for 136 patients (34 per modality). Inter- and intraobserver variability of soft tissue registration was evaluated based on the registration of a representative scan for each CT modality with its corresponding planning scan. Results: Superior image quality with the kVFBCT resulted in reduced uncertainty in soft tissue registration during IGRT compared with other image modalities for IGRT. The largest interobserver variations of soft tissue registration were 1.1 mm, 2.5 mm, 2.6 mm, and 3.2 mm for kVFBCT, kVCBCT, MVFBCT, and MVCBCT, respectively. Conclusions: Image quality adversely affects the reproducibility of soft tissue-based registration for IGRT and necessitates a careful consideration of residual uncertainties in determining different CTV-to-PTV margins for IGRT using different image modalities.

  5. Advance Trends in Soft Computing

    CERN Document Server

    Kreinovich, Vladik; Kacprzyk, Janusz; WCSC 2013

    2014-01-01

    This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary co...

  6. Seismic Response Prediction of Buildings with Base Isolation Using Advanced Soft Computing Approaches

    Directory of Open Access Journals (Sweden)

    Mosbeh R. Kaloop

    2017-01-01

    Full Text Available Modeling response of structures under seismic loads is an important factor in Civil Engineering as it crucially affects the design and management of structures, especially for the high-risk areas. In this study, novel applications of advanced soft computing techniques are utilized for predicting the behavior of centrically braced frame (CBF buildings with lead-rubber bearing (LRB isolation system under ground motion effects. These techniques include least square support vector machine (LSSVM, wavelet neural networks (WNN, and adaptive neurofuzzy inference system (ANFIS along with wavelet denoising. The simulation of a 2D frame model and eight ground motions are considered in this study to evaluate the prediction models. The comparison results indicate that the least square support vector machine is superior to other techniques in estimating the behavior of smart structures.

  7. Discussion on Soft Computing at FLINS '96

    NARCIS (Netherlands)

    Ruan, D.; Wal, A.J. van der

    1998-01-01

    This is a report on the discussion about soft computing (SC) during FLINS'96. The discussion is based on the five questions formulated by X. Li, viz. (1) What is SC? (2) What are the characteristics of SC? (3) What are the principal achievements of SC? (4) What are the typical problems of SC and

  8. Genetic networks and soft computing.

    Science.gov (United States)

    Mitra, Sushmita; Das, Ranajit; Hayashi, Yoichi

    2011-01-01

    The analysis of gene regulatory networks provides enormous information on various fundamental cellular processes involving growth, development, hormone secretion, and cellular communication. Their extraction from available gene expression profiles is a challenging problem. Such reverse engineering of genetic networks offers insight into cellular activity toward prediction of adverse effects of new drugs or possible identification of new drug targets. Tasks such as classification, clustering, and feature selection enable efficient mining of knowledge about gene interactions in the form of networks. It is known that biological data is prone to different kinds of noise and ambiguity. Soft computing tools, such as fuzzy sets, evolutionary strategies, and neurocomputing, have been found to be helpful in providing low-cost, acceptable solutions in the presence of various types of uncertainties. In this paper, we survey the role of these soft methodologies and their hybridizations, for the purpose of generating genetic networks.

  9. Soft computing based on hierarchical evaluation approach and criteria interdependencies for energy decision-making problems: A case study

    International Nuclear Information System (INIS)

    Gitinavard, Hossein; Mousavi, S. Meysam; Vahdani, Behnam

    2017-01-01

    In numerous real-world energy decision problems, decision makers often encounter complex environments, in which existent imprecise data and uncertain information lead us to make an appropriate decision. In this paper, a new soft computing group decision-making approach is introduced based on novel compromise ranking method and interval-valued hesitant fuzzy sets (IVHFSs) for energy decision-making problems under multiple criteria. In the proposed approach, the assessment information is provided by energy experts or decision makers based on interval-valued hesitant fuzzy elements under incomplete criteria weights. In this respect, a new ranking index is presented respecting to interval-valued hesitant fuzzy Hamming distance measure to prioritize energy candidates, and criteria weights are computed based on an extended maximizing deviation method by considering the preferences experts' judgments about the relative importance of each criterion. Also, a decision making trial and evaluation laboratory (DEMATEL) method is extended under an IVHF-environment to compute the interdependencies between and within the selected criteria in the hierarchical structure. Accordingly, to demonstrate the applicability of the presented approach a case study and a practical example are provided regarding to hierarchical structure and criteria interdependencies relations for renewable energy and energy policy selection problems. Hence, the obtained computational results are compared with a fuzzy decision-making method from the recent literature based on some comparison parameters to show the advantages and constraints of the proposed approach. Finally, a sensitivity analysis is prepared to indicate effects of different criteria weights on ranking results to present the robustness or sensitiveness of the proposed soft computing approach versus the relative importance of criteria. - Highlights: • Introducing a novel interval-valued hesitant fuzzy compromise ranking method. • Presenting

  10. Soft-computing base analyses of the relationship between annoyance and coping with noise and odor.

    Science.gov (United States)

    Botteldooren, Dick; Lercher, Peter

    2004-06-01

    The majority of research on annoyance as an important impact of noise, odor, and other stressors on man, has regarded the person as a passive receptor. It was however recognized that this person is an active participant trying to alter a troubled person-environment relationship or to sustain a desirable one. Coping has to be incorporated. This is of particular importance in changing exposure situations. For large populations a lot of insight can be gained by looking at average effects only. To investigate changes in annoyance and effects of coping, the individual or small group has to be studied. Then it becomes imperative to recognize the inherent vagueness in perception and human behavior. Fortunately, tools have been developed over the past decades that allow doing this in a mathematically precise way. These tools are sometimes referred to by the common label: soft-computing, hence the title of this paper. This work revealed different styles of coping both by blind clustering and by (fuzzy) logical aggregation of different actions reported in a survey. The relationship between annoyance and the intensity of coping it generates was quantified after it was recognized that the possibility for coping is created by the presence of the stressor rather than the actual fact of coping. It was further proven that refinement of this relationship is possible if a person can be identified as a coper. This personal factor can be extracted from a known reaction to one stressor and be used for predicting coping intensity and style in another situation. The effect of coping on a perceived change in annoyance is quantified by a set of fuzzy linguistic rules. This closes the loop that is responsible for at least some of the dynamics of the response to a stressor. This work thus provides all essential building blocks for designing models for annoyance in changing environments.

  11. Soft Computing Methods for Disulfide Connectivity Prediction.

    Science.gov (United States)

    Márquez-Chamorro, Alfonso E; Aguilar-Ruiz, Jesús S

    2015-01-01

    The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Determining the disulfide bond connectivity between the cysteines of a protein is desirable as a previous step of the 3D PSP, as the protein conformational search space is highly reduced. The most representative soft computing approaches for the disulfide bonds connectivity prediction problem of the last decade are summarized in this paper. Certain aspects, such as the different methodologies based on soft computing approaches (artificial neural network or support vector machine) or features of the algorithms, are used for the classification of these methods.

  12. RNA secondary structure prediction using soft computing.

    Science.gov (United States)

    Ray, Shubhra Sankar; Pal, Sankar K

    2013-01-01

    Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

  13. New Concepts and Applications in Soft Computing

    CERN Document Server

    Fodor, János; Várkonyi-Kóczy, Annamária

    2013-01-01

                  The book provides a sample of research on the innovative theory and applications of soft computing paradigms.             The idea of Soft Computing was initiated in 1981 when Professor Zadeh published his first paper on soft data analysis and constantly evolved ever since. Professor Zadeh defined Soft Computing as the fusion of the fields of fuzzy logic (FL), neural network theory (NN) and probabilistic reasoning (PR), with the latter subsuming belief networks, evolutionary computing including DNA computing, chaos theory and parts of learning theory into one multidisciplinary system. As Zadeh said the essence of soft computing is that unlike the traditional, hard computing, soft computing is aimed at an accommodation with the pervasive imprecision of the real world. Thus, the guiding principle of soft computing is to exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness, low solution cost and better rapport with reality. ...

  14. Complex system modelling and control through intelligent soft computations

    CERN Document Server

    Azar, Ahmad

    2015-01-01

    The book offers a snapshot of the theories and applications of soft computing in the area of complex systems modeling and control. It presents the most important findings discussed during the 5th International Conference on Modelling, Identification and Control, held in Cairo, from August 31-September 2, 2013. The book consists of twenty-nine selected contributions, which have been thoroughly reviewed and extended before their inclusion in the volume. The different chapters, written by active researchers in the field, report on both current theories and important applications of soft-computing. Besides providing the readers with soft-computing fundamentals, and soft-computing based inductive methodologies/algorithms, the book also discusses key industrial soft-computing applications, as well as multidisciplinary solutions developed for a variety of purposes, like windup control, waste management, security issues, biomedical applications and many others. It is a perfect reference guide for graduate students, r...

  15. Practical applications of soft computing in engineering

    CERN Document Server

    2001-01-01

    Soft computing has been presented not only with the theoretical developments but also with a large variety of realistic applications to consumer products and industrial systems. Application of soft computing has provided the opportunity to integrate human-like vagueness and real-life uncertainty into an otherwise hard computer program. This book highlights some of the recent developments in practical applications of soft computing in engineering problems. All the chapters have been sophisticatedly designed and revised by international experts to achieve wide but in-depth coverage. Contents: Au

  16. Developing a multimodal biometric authentication system using soft computing methods.

    Science.gov (United States)

    Malcangi, Mario

    2015-01-01

    Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.

  17. Fuzzy logic, neural networks, and soft computing

    Science.gov (United States)

    Zadeh, Lofti A.

    1994-01-01

    The past few years have witnessed a rapid growth of interest in a cluster of modes of modeling and computation which may be described collectively as soft computing. The distinguishing characteristic of soft computing is that its primary aims are to achieve tractability, robustness, low cost, and high MIQ (machine intelligence quotient) through an exploitation of the tolerance for imprecision and uncertainty. Thus, in soft computing what is usually sought is an approximate solution to a precisely formulated problem or, more typically, an approximate solution to an imprecisely formulated problem. A simple case in point is the problem of parking a car. Generally, humans can park a car rather easily because the final position of the car is not specified exactly. If it were specified to within, say, a few millimeters and a fraction of a degree, it would take hours or days of maneuvering and precise measurements of distance and angular position to solve the problem. What this simple example points to is the fact that, in general, high precision carries a high cost. The challenge, then, is to exploit the tolerance for imprecision by devising methods of computation which lead to an acceptable solution at low cost. By its nature, soft computing is much closer to human reasoning than the traditional modes of computation. At this juncture, the major components of soft computing are fuzzy logic (FL), neural network theory (NN), and probabilistic reasoning techniques (PR), including genetic algorithms, chaos theory, and part of learning theory. Increasingly, these techniques are used in combination to achieve significant improvement in performance and adaptability. Among the important application areas for soft computing are control systems, expert systems, data compression techniques, image processing, and decision support systems. It may be argued that it is soft computing, rather than the traditional hard computing, that should be viewed as the foundation for artificial

  18. Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

    Directory of Open Access Journals (Sweden)

    J. Bhardwaj

    2018-02-01

    Full Text Available New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

  19. Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

    Science.gov (United States)

    Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

    2018-02-01

    New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

  20. Data mining in soft computing framework: a survey.

    Science.gov (United States)

    Mitra, S; Pal, S K; Mitra, P

    2002-01-01

    The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the different soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are nonparametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide efficient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling different types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included.

  1. Soft computing methods for geoidal height transformation

    Science.gov (United States)

    Akyilmaz, O.; Özlüdemir, M. T.; Ayan, T.; Çelik, R. N.

    2009-07-01

    Soft computing techniques, such as fuzzy logic and artificial neural network (ANN) approaches, have enabled researchers to create precise models for use in many scientific and engineering applications. Applications that can be employed in geodetic studies include the estimation of earth rotation parameters and the determination of mean sea level changes. Another important field of geodesy in which these computing techniques can be applied is geoidal height transformation. We report here our use of a conventional polynomial model, the Adaptive Network-based Fuzzy (or in some publications, Adaptive Neuro-Fuzzy) Inference System (ANFIS), an ANN and a modified ANN approach to approximate geoid heights. These approximation models have been tested on a number of test points. The results obtained through the transformation processes from ellipsoidal heights into local levelling heights have also been compared.

  2. Hybrid soft computing approaches research and applications

    CERN Document Server

    Dutta, Paramartha; Chakraborty, Susanta

    2016-01-01

    The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

  3. 4th International Conference on Soft Computing for Problem Solving

    CERN Document Server

    Deep, Kusum; Pant, Millie; Bansal, Jagdish; Nagar, Atulya

    2015-01-01

    This two volume book is based on the research papers presented at the 4th International Conference on Soft Computing for Problem Solving (SocProS 2014) and covers a variety of topics, including mathematical modelling, image processing, optimization methods, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, medical and healthcare, data mining, etc. Mainly the emphasis is on Soft Computing and its applications in diverse areas. The prime objective of this book is to familiarize the reader with the latest scientific developments in various fields of Science, Engineering and Technology and is directed to the researchers and scientists engaged in various real-world applications of ‘Soft Computing’.

  4. Experimental and Computational Techniques in Soft Condensed Matter Physics

    Science.gov (United States)

    Olafsen, Jeffrey

    2010-09-01

    1. Microscopy of soft materials Eric R. Weeks; 2. Computational methods to study jammed Systems Carl F. Schrek and Corey S. O'Hern; 3. Soft random solids: particulate gels, compressed emulsions and hybrid materials Anthony D. Dinsmore; 4. Langmuir monolayers Michael Dennin; 5. Computer modeling of granular rheology Leonardo E. Silbert; 6. Rheological and microrheological measurements of soft condensed matter John R. de Bruyn and Felix K. Oppong; 7. Particle-based measurement techniques for soft matter Nicholas T. Ouellette; 8. Cellular automata models of granular flow G. William Baxter; 9. Photoelastic materials Brian Utter; 10. Image acquisition and analysis in soft condensed matter Jeffrey S. Olafsen; 11. Structure and patterns in bacterial colonies Nicholas C. Darnton.

  5. International Conference on Soft Computing Systems

    CERN Document Server

    Panigrahi, Bijaya

    2016-01-01

    The book is a collection of high-quality peer-reviewed research papers presented in International Conference on Soft Computing Systems (ICSCS 2015) held at Noorul Islam Centre for Higher Education, Chennai, India. These research papers provide the latest developments in the emerging areas of Soft Computing in Engineering and Technology. The book is organized in two volumes and discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

  6. 6th International Workshop Soft Computing Applications

    CERN Document Server

    Jain, Lakhmi; Kovačević, Branko

    2016-01-01

    These volumes constitute the Proceedings of the 6th International Workshop on Soft Computing Applications, or SOFA 2014, held on 24-26 July 2014 in Timisoara, Romania. This edition was organized by the University of Belgrade, Serbia in conjunction with Romanian Society of Control Engineering and Technical Informatics (SRAIT) - Arad Section, The General Association of Engineers in Romania - Arad Section, Institute of Computer Science, Iasi Branch of the Romanian Academy and IEEE Romanian Section.                 The Soft Computing concept was introduced by Lotfi Zadeh in 1991 and serves to highlight the emergence of computing methodologies in which the accent is on exploiting the tolerance for imprecision and uncertainty to achieve tractability, robustness and low solution cost. Soft computing facilitates the use of fuzzy logic, neurocomputing, evolutionary computing and probabilistic computing in combination, leading to the concept of hybrid intelligent systems.        The combination of ...

  7. Optical character recognition systems for different languages with soft computing

    CERN Document Server

    Chaudhuri, Arindam; Badelia, Pratixa; K Ghosh, Soumya

    2017-01-01

    The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.

  8. Thermal sensation prediction by soft computing methodology.

    Science.gov (United States)

    Jović, Srđan; Arsić, Nebojša; Vilimonović, Jovana; Petković, Dalibor

    2016-12-01

    Thermal comfort in open urban areas is very factor based on environmental point of view. Therefore it is need to fulfill demands for suitable thermal comfort during urban planning and design. Thermal comfort can be modeled based on climatic parameters and other factors. The factors are variables and they are changed throughout the year and days. Therefore there is need to establish an algorithm for thermal comfort prediction according to the input variables. The prediction results could be used for planning of time of usage of urban areas. Since it is very nonlinear task, in this investigation was applied soft computing methodology in order to predict the thermal comfort. The main goal was to apply extreme leaning machine (ELM) for forecasting of physiological equivalent temperature (PET) values. Temperature, pressure, wind speed and irradiance were used as inputs. The prediction results are compared with some benchmark models. Based on the results ELM can be used effectively in forecasting of PET. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Soft computing in artificial intelligence

    CERN Document Server

    Matson, Eric

    2014-01-01

    This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

  10. Intelligent systems and soft computing for nuclear science and industry

    International Nuclear Information System (INIS)

    Ruan, D.; D'hondt, P.; Govaerts, P.; Kerre, E.E.

    1996-01-01

    The second international workshop on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS) addresses topics related to intelligent systems and soft computing for nuclear science and industry. The proceedings contain 52 papers in different fields such as radiation protection, nuclear safety (human factors and reliability), safeguards, nuclear reactor control, production processes in the fuel cycle, dismantling, waste and disposal, decision making, and nuclear reactor control. A clear link is made between theory and applications of fuzzy logic such as neural networks, expert systems, robotics, man-machine interfaces, and decision-support techniques by using modern and advanced technologies and tools. The papers are grouped in three sections. The first section (Soft computing techniques) deals with basic tools to treat fuzzy logic, neural networks, genetic algorithms, decision-making, and software used for general soft-computing aspects. The second section (Intelligent engineering systems) includes contributions on engineering problems such as knowledge-based engineering, expert systems, process control integration, diagnosis, measurements, and interpretation by soft computing. The third section (Nuclear applications) focusses on the application of soft computing and intelligent systems in nuclear science and industry

  11. Soft computing in advanced robotics

    CERN Document Server

    Kobayashi, Ichiro; Kim, Euntai

    2014-01-01

    Intelligent system and robotics are inevitably bound up; intelligent robots makes embodiment of system integration by using the intelligent systems. We can figure out that intelligent systems are to cell units, while intelligent robots are to body components. The two technologies have been synchronized in progress. Making leverage of the robotics and intelligent systems, applications cover boundlessly the range from our daily life to space station; manufacturing, healthcare, environment, energy, education, personal assistance, logistics. This book aims at presenting the research results in relevance with intelligent robotics technology. We propose to researchers and practitioners some methods to advance the intelligent systems and apply them to advanced robotics technology. This book consists of 10 contributions that feature mobile robots, robot emotion, electric power steering, multi-agent, fuzzy visual navigation, adaptive network-based fuzzy inference system, swarm EKF localization and inspection robot. Th...

  12. Soft computing in machine learning

    CERN Document Server

    Park, Jooyoung; Inoue, Atsushi

    2014-01-01

    As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It...

  13. Soft Computing Methods in Design of Superalloys

    Science.gov (United States)

    Cios, K. J.; Berke, L.; Vary, A.; Sharma, S.

    1996-01-01

    Soft computing techniques of neural networks and genetic algorithms are used in the design of superalloys. The cyclic oxidation attack parameter K(sub a), generated from tests at NASA Lewis Research Center, is modelled as a function of the superalloy chemistry and test temperature using a neural network. This model is then used in conjunction with a genetic algorithm to obtain an optimized superalloy composition resulting in low K(sub a) values.

  14. Osteotomy simulation and soft tissue prediction using computer tomography scans

    International Nuclear Information System (INIS)

    Teschner, M.; Girod, S.; Girod, B.

    1999-01-01

    In this paper, a system is presented that can be used to simulate osteotomies of the skull and to estimate the resulting of tissue changes. Thus, the three-dimensional, photorealistic, postoperative appearance of a patient can be assessed. The system is based on a computer tomography scan and a photorealistic laser scan of the patient's face. In order to predict the postoperative appearance of a patient the soft tissue must follow the movement of the underlying bone. In this paper, a multi-layer soft tissue model is proposed that is based on springs. It incorporates features like skin turgor, gravity and sliding bone contact. The prediction of soft tissue changes due to bone realignments is computed using a very efficient and robust optimization method. The system can handle individual patient data sets and has been tested with several clinical cases. (author)

  15. 5th International Conference on Soft Computing for Problem Solving

    CERN Document Server

    Deep, Kusum; Bansal, Jagdish; Nagar, Atulya; Das, Kedar

    2016-01-01

    This two volume book is based on the research papers presented at the 5th International Conference on Soft Computing for Problem Solving (SocProS 2015) and covers a variety of topics, including mathematical modelling, image processing, optimization methods, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, medical and health care, data mining, etc. Mainly the emphasis is on Soft Computing and its applications in diverse areas. The prime objective of this book is to familiarize the reader with the latest scientific developments in various fields of Science, Engineering and Technology and is directed to the researchers and scientists engaged in various real-world applications of ‘Soft Computing’.

  16. 22nd International Conference on Soft Computing

    CERN Document Server

    2017-01-01

    This proceeding book contains a collection of selected accepted papers of the Mendel conference held in Brno, Czech Republic in June 2016. The proceedings book contains three chapters which present recent advances in soft computing including intelligent image processing. The Mendel conference was established in 1995 and is named after the scientist and Augustinian priest Gregor J. Mendel who discovered the famous Laws of Heredity. The main aim of the conference is to create a regular possibility for students, academics and researchers to exchange ideas and novel research methods on a yearly basis.

  17. Soft Computing Applications : Proceedings of the 5th International Workshop Soft Computing Applications

    CERN Document Server

    Fodor, János; Várkonyi-Kóczy, Annamária; Dombi, Joszef; Jain, Lakhmi

    2013-01-01

                    This volume contains the Proceedings of the 5thInternational Workshop on Soft Computing Applications (SOFA 2012).                                The book covers a broad spectrum of soft computing techniques, theoretical and practical applications employing knowledge and intelligence to find solutions for world industrial, economic and medical problems. The combination of such intelligent systems tools and a large number of applications introduce a need for a synergy of scientific and technological disciplines in order to show the great potential of Soft Computing in all domains.                   The conference papers included in these proceedings, published post conference, were grouped into the following area of research: ·         Soft Computing and Fusion Algorithms in Biometrics, ·         Fuzzy Theory, Control andApplications, ·         Modelling and Control Applications, ·         Steps towa...

  18. Prediction of Software Reliability using Bio Inspired Soft Computing Techniques.

    Science.gov (United States)

    Diwaker, Chander; Tomar, Pradeep; Poonia, Ramesh C; Singh, Vijander

    2018-04-10

    A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing

  19. Diffusible iodine-based contrast-enhanced computed tomography (diceCT): an emerging tool for rapid, high-resolution, 3-D imaging of metazoan soft tissues.

    Science.gov (United States)

    Gignac, Paul M; Kley, Nathan J; Clarke, Julia A; Colbert, Matthew W; Morhardt, Ashley C; Cerio, Donald; Cost, Ian N; Cox, Philip G; Daza, Juan D; Early, Catherine M; Echols, M Scott; Henkelman, R Mark; Herdina, A Nele; Holliday, Casey M; Li, Zhiheng; Mahlow, Kristin; Merchant, Samer; Müller, Johannes; Orsbon, Courtney P; Paluh, Daniel J; Thies, Monte L; Tsai, Henry P; Witmer, Lawrence M

    2016-06-01

    Morphologists have historically had to rely on destructive procedures to visualize the three-dimensional (3-D) anatomy of animals. More recently, however, non-destructive techniques have come to the forefront. These include X-ray computed tomography (CT), which has been used most commonly to examine the mineralized, hard-tissue anatomy of living and fossil metazoans. One relatively new and potentially transformative aspect of current CT-based research is the use of chemical agents to render visible, and differentiate between, soft-tissue structures in X-ray images. Specifically, iodine has emerged as one of the most widely used of these contrast agents among animal morphologists due to its ease of handling, cost effectiveness, and differential affinities for major types of soft tissues. The rapid adoption of iodine-based contrast agents has resulted in a proliferation of distinct specimen preparations and scanning parameter choices, as well as an increasing variety of imaging hardware and software preferences. Here we provide a critical review of the recent contributions to iodine-based, contrast-enhanced CT research to enable researchers just beginning to employ contrast enhancement to make sense of this complex new landscape of methodologies. We provide a detailed summary of recent case studies, assess factors that govern success at each step of the specimen storage, preparation, and imaging processes, and make recommendations for standardizing both techniques and reporting practices. Finally, we discuss potential cutting-edge applications of diffusible iodine-based contrast-enhanced computed tomography (diceCT) and the issues that must still be overcome to facilitate the broader adoption of diceCT going forward. © 2016 The Authors. Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.

  20. Second International Conference on Soft Computing for Problem Solving

    CERN Document Server

    Nagar, Atulya; Deep, Kusum; Pant, Millie; Bansal, Jagdish; Ray, Kanad; Gupta, Umesh

    2014-01-01

    The present book is based on the research papers presented in the International Conference on Soft Computing for Problem Solving (SocProS 2012), held at JK Lakshmipat University, Jaipur, India. This book provides the latest developments in the area of soft computing and covers a variety of topics, including mathematical modeling, image processing, optimization, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, data mining, etc. The objective of the book is to familiarize the reader with the latest scientific developments that are taking place in various fields and the latest sophisticated problem solving tools that are being developed to deal with the complex and intricate problems that are otherwise difficult to solve by the usual and traditional methods. The book is directed to the researchers and scientists engaged in various fields of Science and Technology.

  1. Third International Conference on Soft Computing for Problem Solving

    CERN Document Server

    Deep, Kusum; Nagar, Atulya; Bansal, Jagdish

    2014-01-01

    The present book is based on the research papers presented in the 3rd International Conference on Soft Computing for Problem Solving (SocProS 2013), held as a part of the golden jubilee celebrations of the Saharanpur Campus of IIT Roorkee, at the Noida Campus of Indian Institute of Technology Roorkee, India. This book is divided into two volumes and covers a variety of topics including mathematical modelling, image processing, optimization, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, medical and health care, data mining etc. Particular emphasis is laid on soft computing and its application to diverse fields. The prime objective of the book is to familiarize the reader with the latest scientific developments that are taking place in various fields and the latest sophisticated problem solving tools that are being developed to deal with the complex and intricate problems, which are otherwise difficult to solve by the usual and traditional methods. The book is directed ...

  2. 6th International Conference on Soft Computing for Problem Solving

    CERN Document Server

    Bansal, Jagdish; Das, Kedar; Lal, Arvind; Garg, Harish; Nagar, Atulya; Pant, Millie

    2017-01-01

    This two-volume book gathers the proceedings of the Sixth International Conference on Soft Computing for Problem Solving (SocProS 2016), offering a collection of research papers presented during the conference at Thapar University, Patiala, India. Providing a veritable treasure trove for scientists and researchers working in the field of soft computing, it highlights the latest developments in the broad area of “Computational Intelligence” and explores both theoretical and practical aspects using fuzzy logic, artificial neural networks, evolutionary algorithms, swarm intelligence, soft computing, computational intelligence, etc.

  3. Recent developments and new directions in soft computing

    CERN Document Server

    Abbasov, Ali; Yager, Ronald; Shahbazova, Shahnaz; Reformat, Marek

    2014-01-01

    The book reports on the latest advances and challenges of soft computing. It  gathers original scientific contributions written by top scientists in the field and covering theories, methods and applications in a number of research areas related to soft-computing, such as decision-making, probabilistic reasoning, image processing, control, neural networks and data analysis.  

  4. 2nd International Conference on Soft Computing and Data Mining

    CERN Document Server

    Ghazali, Rozaida; Nawi, Nazri; Deris, Mustafa

    2017-01-01

    This book provides a comprehensive introduction and practical look at the concepts and techniques readers need to get the most out of their data in real-world, large-scale data mining projects. It also guides readers through the data-analytic thinking necessary for extracting useful knowledge and business value from the data. The book is based on the Soft Computing and Data Mining (SCDM-16) conference, which was held in Bandung, Indonesia on August 18th–20th 2016 to discuss the state of the art in soft computing techniques, and offer participants sufficient knowledge to tackle a wide range of complex systems. The scope of the conference is reflected in the book, which presents a balance of soft computing techniques and data mining approaches. The two constituents are introduced to the reader systematically and brought together using different combinations of applications and practices. It offers engineers, data analysts, practitioners, scientists and managers the insights into the concepts, tools and techni...

  5. SoftLab: A Soft-Computing Software for Experimental Research with Commercialization Aspects

    Science.gov (United States)

    Akbarzadeh-T, M.-R.; Shaikh, T. S.; Ren, J.; Hubbell, Rob; Kumbla, K. K.; Jamshidi, M

    1998-01-01

    SoftLab is a software environment for research and development in intelligent modeling/control using soft-computing paradigms such as fuzzy logic, neural networks, genetic algorithms, and genetic programs. SoftLab addresses the inadequacies of the existing soft-computing software by supporting comprehensive multidisciplinary functionalities from management tools to engineering systems. Furthermore, the built-in features help the user process/analyze information more efficiently by a friendly yet powerful interface, and will allow the user to specify user-specific processing modules, hence adding to the standard configuration of the software environment.

  6. Advances in soft computing, intelligent robotics and control

    CERN Document Server

    Fullér, Robert

    2014-01-01

    Soft computing, intelligent robotics and control are in the core interest of contemporary engineering. Essential characteristics of soft computing methods are the ability to handle vague information, to apply human-like reasoning, their learning capability, and ease of application. Soft computing techniques are widely applied in the control of dynamic systems, including mobile robots. The present volume is a collection of 20 chapters written by respectable experts of the fields, addressing various theoretical and practical aspects in soft computing, intelligent robotics and control. The first part of the book concerns with issues of intelligent robotics, including robust xed point transformation design, experimental verification of the input-output feedback linearization of differentially driven mobile robot and applying kinematic synthesis to micro electro-mechanical systems design. The second part of the book is devoted to fundamental aspects of soft computing. This includes practical aspects of fuzzy rule ...

  7. 4th International Conference on Quantitative Logic and Soft Computing

    CERN Document Server

    Chen, Shui-Li; Wang, San-Min; Li, Yong-Ming

    2017-01-01

    This book is the proceedings of the Fourth International Conference on Quantitative Logic and Soft Computing (QLSC2016) held 14-17, October, 2016 in Zhejiang Sci-Tech University, Hangzhou, China. It includes 61 papers, of which 5 are plenary talks( 3 abstracts and 2 full length talks). QLSC2016 was the fourth in a series of conferences on Quantitative Logic and Soft Computing. This conference was a major symposium for scientists, engineers and practitioners to present their updated results, ideas, developments and applications in all areas of quantitative logic and soft computing. The book aims to strengthen relations between industry research laboratories and universities in fields such as quantitative logic and soft computing worldwide as follows: (1) Quantitative Logic and Uncertainty Logic; (2) Automata and Quantification of Software; (3) Fuzzy Connectives and Fuzzy Reasoning; (4) Fuzzy Logical Algebras; (5) Artificial Intelligence and Soft Computing; (6) Fuzzy Sets Theory and Applications.

  8. Role of Soft Computing Approaches in HealthCare Domain: A Mini Review.

    Science.gov (United States)

    Gambhir, Shalini; Malik, Sanjay Kumar; Kumar, Yugal

    2016-12-01

    In the present era, soft computing approaches play a vital role in solving the different kinds of problems and provide promising solutions. Due to popularity of soft computing approaches, these approaches have also been applied in healthcare data for effectively diagnosing the diseases and obtaining better results in comparison to traditional approaches. Soft computing approaches have the ability to adapt itself according to problem domain. Another aspect is a good balance between exploration and exploitation processes. These aspects make soft computing approaches more powerful, reliable and efficient. The above mentioned characteristics make the soft computing approaches more suitable and competent for health care data. The first objective of this review paper is to identify the various soft computing approaches which are used for diagnosing and predicting the diseases. Second objective is to identify various diseases for which these approaches are applied. Third objective is to categories the soft computing approaches for clinical support system. In literature, it is found that large number of soft computing approaches have been applied for effectively diagnosing and predicting the diseases from healthcare data. Some of these are particle swarm optimization, genetic algorithm, artificial neural network, support vector machine etc. A detailed discussion on these approaches are presented in literature section. This work summarizes various soft computing approaches used in healthcare domain in last one decade. These approaches are categorized in five different categories based on the methodology, these are classification model based system, expert system, fuzzy and neuro fuzzy system, rule based system and case based system. Lot of techniques are discussed in above mentioned categories and all discussed techniques are summarized in the form of tables also. This work also focuses on accuracy rate of soft computing technique and tabular information is provided for

  9. Fuzzy systems and soft computing in nuclear engineering

    International Nuclear Information System (INIS)

    Ruan, D.

    2000-01-01

    This book is an organized edited collection of twenty-one contributed chapters covering nuclear engineering applications of fuzzy systems, neural networks, genetic algorithms and other soft computing techniques. All chapters are either updated review or original contributions by leading researchers written exclusively for this volume. The volume highlights the advantages of applying fuzzy systems and soft computing in nuclear engineering, which can be viewed as complementary to traditional methods. As a result, fuzzy sets and soft computing provide a powerful tool for solving intricate problems pertaining in nuclear engineering. Each chapter of the book is self-contained and also indicates the future research direction on this topic of applications of fuzzy systems and soft computing in nuclear engineering. (orig.)

  10. Soft computing trends in nuclear energy system

    International Nuclear Information System (INIS)

    Paramasivan, B.

    2012-01-01

    In spite of so many advancements in the power and energy sector over the last two decades, its survival to cater quality power with due consideration for planning, coordination, marketing, safety, stability, optimality and reliability is still believed to remain critical. Though it appears simple from the outside, yet the internal structure of large scale power systems is so complex that event management and decision making requires a formidable preliminary preparation, which gets still worsened in the presence of uncertainties and contingencies. These aspects have attracted several researchers to carryout continued research in this field and their valued contributions have been significantly helping the newcomers in understanding the evolutionary growth in this sector, starting from phenomena, tools, methodologies to strategies so as to ensure smooth, stable, safe, reliable and economic operation. The usage of soft computing would accelerate interaction between the energy and technology research community with an aim to foster unified development in the next generation. Monitoring the mechanical impact of a loose (detached or drifting) part in the reactor coolant system of a nuclear power plant is one of the essential functions for operation and maintenance of the plant. Large data tables are generated during this monitoring process. This data can be 'mined' to reveal latent patterns of interest to operation and maintenance. Rough set theory has been applied successfully to data mining. It can be used in the nuclear power industry and elsewhere to identify classes in datasets, finding dependencies in relations and discovering rules which are hidden in databases. An important role may be played by nuclear energy, provided that major safety, waste and proliferation issues affecting current nuclear reactors are satisfactorily addressed. In this respect, a large effort is under way since a few years towards the development of advanced nuclear systems that would use

  11. Experimental investigation of halogen-bond hard-soft acid-base complementarity.

    Science.gov (United States)

    Riel, Asia Marie S; Jessop, Morly J; Decato, Daniel A; Massena, Casey J; Nascimento, Vinicius R; Berryman, Orion B

    2017-04-01

    The halogen bond (XB) is a topical noncovalent interaction of rapidly increasing importance. The XB employs a `soft' donor atom in comparison to the `hard' proton of the hydrogen bond (HB). This difference has led to the hypothesis that XBs can form more favorable interactions with `soft' bases than HBs. While computational studies have supported this suggestion, solution and solid-state data are lacking. Here, XB soft-soft complementarity is investigated with a bidentate receptor that shows similar associations with neutral carbonyls and heavy chalcogen analogs. The solution speciation and XB soft-soft complementarity is supported by four crystal structures containing neutral and anionic soft Lewis bases.

  12. Advanced soft computing diagnosis method for tumour grading.

    Science.gov (United States)

    Papageorgiou, E I; Spyridonos, P P; Stylios, C D; Ravazoula, P; Groumpos, P P; Nikiforidis, G N

    2006-01-01

    To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability.

  13. Soft computing integrating evolutionary, neural, and fuzzy systems

    CERN Document Server

    Tettamanzi, Andrea

    2001-01-01

    Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

  14. Prostate positioning using cone-beam computer tomography based on manual soft-tissue registration. Interobserver agreement between radiation oncologists and therapists

    Energy Technology Data Exchange (ETDEWEB)

    Jereczek-Fossa, B.A.; Pobbiati, C.; Fanti, P. [European Institute of Oncology, Department of Radiation Oncology, Milan (Italy); University of Milan, Milan (Italy); Santoro, L. [European Institute of Oncology, Department of Epidemiology and Biostatistics, Milan (Italy); Fodor, C.; Zerini, D. [European Institute of Oncology, Department of Radiation Oncology, Milan (Italy); Vigorito, S. [European Institute of Oncology, Department of Medical Physics, Milan (Italy); Baroni, G. [Politecnico di Milano, Department of Electronics Information and Bioengineering, Milan (Italy); De Cobelli, O. [European Institute of Oncology, Department of Urology, Milan (Italy); University of Milan, Milan (Italy); Orecchia, R. [European Institute of Oncology, Department of Radiation Oncology, Milan (Italy); National Center for Oncological Hadrontherapy (CNAO) Foundation, Pavia (Italy); University of Milan, Milan (Italy)

    2014-01-15

    To check the interobserver agreement between radiation oncologists and therapists (RTT) using an on- and off-line cone-beam computer tomography (CBCT) protocol for setup verification in the radiotherapy of prostate cancer. The CBCT data from six prostate cancer patients treated with hypofractionated intensity-modulated radiotherapy (IMRT) were independently reviewed off-line by four observers (one radiation oncologist, one junior and two senior RTTs) and benchmarked with on-line CBCT positioning performed by a radiation oncologist immediately prior to treatment. CBCT positioning was based on manual soft-tissue registration. Agreement between observers was evaluated using weighted Cohen's kappa statistics. In total, 152 CBCT-based prostate positioning procedures were reviewed by each observer. The mean (± standard deviation) of the differences between off- and on-line CBCT-simCT registration translations along the three directions (antero-posterior, latero-lateral and cranio-caudal) and rotation around the antero-posterior axis were - 0.7 (3.6) mm, 1.9 (2.7) mm, 0.9 (3.6) mm and - 1.8 (5.0) degrees, respectively. Satisfactory interobserver agreement was found, being substantial (weighted kappa > 0.6) in 10 of 16 comparisons and moderate (0.41-0.60) in the remaining six comparisons. CBCT interpretation performed by RTTs is comparable to that of radiation oncologists. Our study might be helpful in the quality assurance of radiotherapy and the optimization of competencies. Further investigation should include larger sample sizes, a greater number of observers and validated methodology in order to assess interobserver variability and its impact on high-precision prostate cancer IGRT. In the future, it should enable the wider implementation of complex and evolving radiotherapy technologies. (orig.)

  15. The role of soft computing in intelligent machines.

    Science.gov (United States)

    de Silva, Clarence W

    2003-08-15

    An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.

  16. Hybrid soft computing systems for electromyographic signals analysis: a review

    Science.gov (United States)

    2014-01-01

    Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979

  17. Hybrid soft computing systems for electromyographic signals analysis: a review.

    Science.gov (United States)

    Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates

    2014-02-03

    Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

  18. Soft Tissue Biomechanical Modeling for Computer Assisted Surgery

    CERN Document Server

    2012-01-01

      This volume focuses on the biomechanical modeling of biological tissues in the context of Computer Assisted Surgery (CAS). More specifically, deformable soft tissues are addressed since they are the subject of the most recent developments in this field. The pioneering works on this CAS topic date from the 1980's, with applications in orthopaedics and biomechanical models of bones. More recently, however, biomechanical models of soft tissues have been proposed since most of the human body is made of soft organs that can be deformed by the surgical gesture. Such models are much more complicated to handle since the tissues can be subject to large deformations (non-linear geometrical framework) as well as complex stress/strain relationships (non-linear mechanical framework). Part 1 of the volume presents biomechanical models that have been developed in a CAS context and used during surgery. This is particularly new since most of the soft tissues models already proposed concern Computer Assisted Planning, with ...

  19. The First International Conference on Soft Computing and Data Mining

    CERN Document Server

    Ghazali, Rozaida; Deris, Mustafa

    2014-01-01

    This book constitutes the refereed proceedings of the First International Conference on Soft Computing and Data Mining, SCDM 2014, held in Universiti Tun Hussein Onn Malaysia, in June 16th-18th, 2014. The 65 revised full papers presented in this book were carefully reviewed and selected from 145 submissions, and organized into two main topical sections; Data Mining and Soft Computing. The goal of this book is to provide both theoretical concepts and, especially, practical techniques on these exciting fields of soft computing and data mining, ready to be applied in real-world applications. The exchanges of views pertaining future research directions to be taken in this field and the resultant dissemination of the latest research findings makes this work of immense value to all those having an interest in the topics covered.    

  20. Soft computing for fault diagnosis in power plants

    International Nuclear Information System (INIS)

    Ciftcioglu, O.; Turkcan, E.

    1998-01-01

    Considering the advancements in the AI technology, there arises a new concept known as soft computing. It can be defined as the processing of uncertain information with the AI methods, that refers to explicitly the methods using neural networks, fuzzy logic and evolutionary algorithms. In this respect, soft computing is a new dimension in information processing technology where linguistic information can also be processed in contrast with the classical stochastic and deterministic treatments of data. On one hand it can process uncertain/incomplete information and on the other hand it can deal with non-linearity of large-scale systems where uncertainty is particularly relevant with respect to linguistic information and incompleteness is related to fault tolerance in fault diagnosis. In this perspective, the potential role of soft computing in power plant operation is presented. (author)

  1. A comparative analysis of soft computing techniques for gene prediction.

    Science.gov (United States)

    Goel, Neelam; Singh, Shailendra; Aseri, Trilok Chand

    2013-07-01

    The rapid growth of genomic sequence data for both human and nonhuman species has made analyzing these sequences, especially predicting genes in them, very important and is currently the focus of many research efforts. Beside its scientific interest in the molecular biology and genomics community, gene prediction is of considerable importance in human health and medicine. A variety of gene prediction techniques have been developed for eukaryotes over the past few years. This article reviews and analyzes the application of certain soft computing techniques in gene prediction. First, the problem of gene prediction and its challenges are described. These are followed by different soft computing techniques along with their application to gene prediction. In addition, a comparative analysis of different soft computing techniques for gene prediction is given. Finally some limitations of the current research activities and future research directions are provided. Copyright © 2013 Elsevier Inc. All rights reserved.

  2. Soft computing in green and renewable energy systems

    Energy Technology Data Exchange (ETDEWEB)

    Gopalakrishnan, Kasthurirangan [Iowa State Univ., Ames, IA (United States). Iowa Bioeconomy Inst.; US Department of Energy, Ames, IA (United States). Ames Lab; Kalogirou, Soteris [Cyprus Univ. of Technology, Limassol (Cyprus). Dept. of Mechanical Engineering and Materials Sciences and Engineering; Khaitan, Siddhartha Kumar (eds.) [Iowa State Univ. of Science and Technology, Ames, IA (United States). Dept. of Electrical Engineering and Computer Engineering

    2011-07-01

    Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems. Research is proceeding at jet speed on renewable energy (energy derived from natural resources such as sunlight, wind, tides, rain, geothermal heat, biomass, hydrogen, etc.) as policy makers, researchers, economists, and world agencies have joined forces in finding alternative sustainable energy solutions to current critical environmental, economic, and social issues. The innovative models, environmentally benign processes, data analytics, etc. employed in renewable energy systems are computationally-intensive, non-linear and complex as well as involve a high degree of uncertainty. Soft computing technologies, such as fuzzy sets and systems, neural science and systems, evolutionary algorithms and genetic programming, and machine learning, are ideal in handling the noise, imprecision, and uncertainty in the data, and yet achieve robust, low-cost solutions. As a result, intelligent and soft computing paradigms are finding increasing applications in the study of renewable energy systems. Researchers, practitioners, undergraduate and graduate students engaged in the study of renewable energy systems will find this book very useful. (orig.)

  3. Soft Computing Techniques in Vision Science

    CERN Document Server

    Yang, Yeon-Mo

    2012-01-01

    This Special Edited Volume is a unique approach towards Computational solution for the upcoming field of study called Vision Science. From a scientific firmament Optics, Ophthalmology, and Optical Science has surpassed an Odyssey of optimizing configurations of Optical systems, Surveillance Cameras and other Nano optical devices with the metaphor of Nano Science and Technology. Still these systems are falling short of its computational aspect to achieve the pinnacle of human vision system. In this edited volume much attention has been given to address the coupling issues Computational Science and Vision Studies.  It is a comprehensive collection of research works addressing various related areas of Vision Science like Visual Perception and Visual system, Cognitive Psychology, Neuroscience, Psychophysics and Ophthalmology, linguistic relativity, color vision etc. This issue carries some latest developments in the form of research articles and presentations. The volume is rich of contents with technical tools ...

  4. Soft Computing in Construction Information Technology

    NARCIS (Netherlands)

    Ciftcioglu, O.; Durmisevic, S.; Sariyildiz, S.

    2001-01-01

    The last decade, civil engineering has exercised a rapidly growing interest in the application of neurally inspired computing techniques. The motive for this interest was the promises of certain information processing characteristics, which are similar to some extend, to those of human brain. The

  5. Water demand forecasting: review of soft computing methods.

    Science.gov (United States)

    Ghalehkhondabi, Iman; Ardjmand, Ehsan; Young, William A; Weckman, Gary R

    2017-07-01

    Demand forecasting plays a vital role in resource management for governments and private companies. Considering the scarcity of water and its inherent constraints, demand management and forecasting in this domain are critically important. Several soft computing techniques have been developed over the last few decades for water demand forecasting. This study focuses on soft computing methods of water consumption forecasting published between 2005 and 2015. These methods include artificial neural networks (ANNs), fuzzy and neuro-fuzzy models, support vector machines, metaheuristics, and system dynamics. Furthermore, it was discussed that while in short-term forecasting, ANNs have been superior in many cases, but it is still very difficult to pick a single method as the overall best. According to the literature, various methods and their hybrids are applied to water demand forecasting. However, it seems soft computing has a lot more to contribute to water demand forecasting. These contribution areas include, but are not limited, to various ANN architectures, unsupervised methods, deep learning, various metaheuristics, and ensemble methods. Moreover, it is found that soft computing methods are mainly used for short-term demand forecasting.

  6. Darwinian Spacecraft: Soft Computing Strategies Breeding Better, Faster Cheaper

    Science.gov (United States)

    Noever, David A.; Baskaran, Subbiah

    1999-01-01

    Computers can create infinite lists of combinations to try to solve a particular problem, a process called "soft-computing." This process uses statistical comparables, neural networks, genetic algorithms, fuzzy variables in uncertain environments, and flexible machine learning to create a system which will allow spacecraft to increase robustness, and metric evaluation. These concepts will allow for the development of a spacecraft which will allow missions to be performed at lower costs.

  7. A new paradigm of knowledge engineering by soft computing

    CERN Document Server

    Ding, Liya

    2001-01-01

    Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms. The integration of those constituent methodologies forms the core of SC. In addition, the synergy allows SC to incorporate human knowledge effectively, deal with imprecision and uncertainty, and learn to adapt to unknown or changing environments for better performance. Together with other modern technologies, SC and its applications exert unprecedented influence on intelligent systems that mimic hum

  8. Research Update: Computational materials discovery in soft matter

    Directory of Open Access Journals (Sweden)

    Tristan Bereau

    2016-05-01

    Full Text Available Soft matter embodies a wide range of materials, which all share the common characteristics of weak interaction energies determining their supramolecular structure. This complicates structure-property predictions and hampers the direct application of data-driven approaches to their modeling. We present several aspects in which these methods play a role in designing soft-matter materials: drug design as well as information-driven computer simulations, e.g., histogram reweighting. We also discuss recent examples of rational design of soft-matter materials fostered by physical insight and assisted by data-driven approaches. We foresee the combination of data-driven and physical approaches a promising strategy to move the field forward.

  9. Control of Neutralization Process Using Soft Computing

    Directory of Open Access Journals (Sweden)

    G. Balasubramanian

    2008-03-01

    Full Text Available A novel model-based nonlinear control strategy is proposed using an experimental pH neutralization process. The control strategy involves a non linear neural network (NN model, in the context of internal model control (IMC. When integrated into the internal model control scheme, the resulting controller is shown to have favorable practical implications as well as superior performance. The designed model based online IMC controller was implemented to a laboratory scaled pH process in real time using dSPACE 1104 interface card. The responses of pH and acid flow rate shows good tracking for both the set point and load chances over the entire nonlinear region.

  10. A Study on Soft Computing Applications in I and C Systems of Nuclear Power Plant

    International Nuclear Information System (INIS)

    Kang, H. T.; Chung, H. Y.

    2006-01-01

    In the paper, the application of the soft computing based nuclear power plant(NPP) is discussed. Soft computing such as neural network(NN), fuzzy logic controller(FLC), and genetic algorithm(GA) and/or their hybrid will be a new frontier for the development of instrument and control(I and C) systems in NPP. The application includes several fields, for example, the diagnostics of system transient, optimal data selection in NN, and intelligent control etc. Two or more combining structure, hybrid system, is more efficient. The concept of FLC, NN, and GA is presented in Section 2. The applications of soft computing used in NPP are presented in Section 3

  11. Soft computing techniques toward modeling the water supplies of Cyprus.

    Science.gov (United States)

    Iliadis, L; Maris, F; Tachos, S

    2011-10-01

    This research effort aims in the application of soft computing techniques toward water resources management. More specifically, the target is the development of reliable soft computing models capable of estimating the water supply for the case of "Germasogeia" mountainous watersheds in Cyprus. Initially, ε-Regression Support Vector Machines (ε-RSVM) and fuzzy weighted ε-RSVMR models have been developed that accept five input parameters. At the same time, reliable artificial neural networks have been developed to perform the same job. The 5-fold cross validation approach has been employed in order to eliminate bad local behaviors and to produce a more representative training data set. Thus, the fuzzy weighted Support Vector Regression (SVR) combined with the fuzzy partition has been employed in an effort to enhance the quality of the results. Several rational and reliable models have been produced that can enhance the efficiency of water policy designers. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. International Conference on Soft Computing Techniques and Engineering Application

    CERN Document Server

    Li, Xiaolong

    2014-01-01

    The main objective of ICSCTEA 2013 is to provide a platform for researchers, engineers and academicians from all over the world to present their research results and development activities in soft computing techniques and engineering application. This conference provides opportunities for them to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration.

  13. Applications of the soft computing in the automated history matching

    Energy Technology Data Exchange (ETDEWEB)

    Silva, P.C.; Maschio, C.; Schiozer, D.J. [Unicamp (Brazil)

    2006-07-01

    Reservoir management is a research field in petroleum engineering that optimizes reservoir performance based on environmental, political, economic and technological criteria. Reservoir simulation is based on geological models that simulate fluid flow. Models must be constantly corrected to yield the observed production behaviour. The process of history matching is controlled by the comparison of production data, well test data and measured data from simulations. Parametrization, objective function analysis, sensitivity analysis and uncertainty analysis are important steps in history matching. One of the main challenges facing automated history matching is to develop algorithms that find the optimal solution in multidimensional search spaces. Optimization algorithms can be either global optimizers that work with noisy multi-modal functions, or local optimizers that cannot work with noisy multi-modal functions. The problem with global optimizers is the very large number of function calls, which is an inconvenience due to the long reservoir simulation time. For that reason, techniques such as least squared, thin plane spline, kriging and artificial neural networks (ANN) have been used as substitutes to reservoir simulators. This paper described the use of optimization algorithms to find optimal solution in automated history matching. Several ANN were used, including the generalized regression neural network, fuzzy system with subtractive clustering and radial basis network. The UNIPAR soft computing method was used along with a modified Hooke- Jeeves optimization method. Two case studies with synthetic and real reservoirs are examined. It was concluded that the combination of global and local optimization has the potential to improve the history matching process and that the use of substitute models can reduce computational efforts. 15 refs., 11 figs.

  14. A virtual surgical training system that simulates cutting of soft tissue using a modified pre-computed elastic model.

    Science.gov (United States)

    Toe, Kyaw Kyar; Huang, Weimin; Yang, Tao; Duan, Yuping; Zhou, Jiayin; Su, Yi; Teo, Soo-Kng; Kumar, Selvaraj Senthil; Lim, Calvin Chi-Wan; Chui, Chee Kong; Chang, Stephen

    2015-08-01

    This work presents a surgical training system that incorporates cutting operation of soft tissue simulated based on a modified pre-computed linear elastic model in the Simulation Open Framework Architecture (SOFA) environment. A precomputed linear elastic model used for the simulation of soft tissue deformation involves computing the compliance matrix a priori based on the topological information of the mesh. While this process may require a few minutes to several hours, based on the number of vertices in the mesh, it needs only to be computed once and allows real-time computation of the subsequent soft tissue deformation. However, as the compliance matrix is based on the initial topology of the mesh, it does not allow any topological changes during simulation, such as cutting or tearing of the mesh. This work proposes a way to modify the pre-computed data by correcting the topological connectivity in the compliance matrix, without re-computing the compliance matrix which is computationally expensive.

  15. Prediction of scour caused by 2D horizontal jets using soft computing techniques

    Directory of Open Access Journals (Sweden)

    Masoud Karbasi

    2017-12-01

    Full Text Available This paper presents application of five soft-computing techniques, artificial neural networks, support vector regression, gene expression programming, grouping method of data handling (GMDH neural network and adaptive-network-based fuzzy inference system, to predict maximum scour hole depth downstream of a sluice gate. The input parameters affecting the scour depth are the sediment size and its gradation, apron length, sluice gate opening, jet Froude number and the tail water depth. Six non-dimensional parameters were achieved to define a functional relationship between the input and output variables. Published data were used from the experimental researches. The results of soft-computing techniques were compared with empirical and regression based equations. The results obtained from the soft-computing techniques are superior to those of empirical and regression based equations. Comparison of soft-computing techniques showed that accuracy of the ANN model is higher than other models (RMSE = 0.869. A new GEP based equation was proposed.

  16. Soft and hard computing approaches for real-time prediction of currents in a tide-dominated coastal area

    Digital Repository Service at National Institute of Oceanography (India)

    Charhate, S.B.; Deo, M.C.; SanilKumar, V.

    . Owing to the complex real sea conditions, such methods may not always yield satisfactory results. This paper discusses a few alternative approaches based on the soft computing tools of artificial neural networks (ANNs) and genetic programming (GP...

  17. SUPRA SOFT SEPARATION AXIOMS AND SUPRA IRRESOLUTENESS BASED ON SUPRA B-SOFT SETS

    OpenAIRE

    Abd El-latif, Alaa Mohamed; Hosny, Rodyna Ahmed

    2016-01-01

    This paper introduces supra soft b-separation axioms based on the supra b-open soft sets which are more general than supra open soft sets. We investigate the relationships between these supra soft separation axioms. Furthermore, with the help of examples it is established that the converse does not hold. We show that, a supra soft topological space (X; t;E) is supra soft b-T1-space, if xE is supra b-closed soft set in for each x 2 X. Also, we prove that xE is supra b-closed soft set for each ...

  18. Soft Computing. Nové informatické paradigma, nebo módní slogan?

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr

    2000-01-01

    Roč. 79, č. 12 (2000), s. 683-685 ISSN 0042-4544 Institutional research plan: AV0Z1030915 Keywords : soft computing * fuzzy computing * neural computing * generic computing Subject RIV: BA - General Mathematics

  19. Satellite based Ocean Forecasting, the SOFT project

    Science.gov (United States)

    Stemmann, L.; Tintoré, J.; Moneris, S.

    2003-04-01

    The knowledge of future oceanic conditions would have enormous impact on human marine related areas. For such reasons, a number of international efforts are being carried out to obtain reliable and manageable ocean forecasting systems. Among the possible techniques that can be used to estimate the near future states of the ocean, an ocean forecasting system based on satellite imagery is developped through the Satelitte based Ocean ForecasTing project (SOFT). SOFT, established by the European Commission, considers the development of a forecasting system of the ocean space-time variability based on satellite data by using Artificial Intelligence techniques. This system will be merged with numerical simulation approaches, via assimilation techniques, to get a hybrid SOFT-numerical forecasting system of improved performance. The results of the project will provide efficient forecasting of sea-surface temperature structures, currents, dynamic height, and biological activity associated to chlorophyll fields. All these quantities could give valuable information on the planning and management of human activities in marine environments such as navigation, fisheries, pollution control, or coastal management. A detailed identification of present or new needs and potential end-users concerned by such an operational tool is being performed. The project would study solutions adapted to these specific needs.

  20. Examination of tapered plastic multimode fiber-based sensor performance with silver coating for different concentrations of calcium hypochlorite by soft computing methodologies--a comparative study.

    Science.gov (United States)

    Zakaria, Rozalina; Sheng, Ong Yong; Wern, Kam; Shamshirband, Shahaboddin; Wahab, Ainuddin Wahid Abdul; Petković, Dalibor; Saboohi, Hadi

    2014-05-01

    A soft methodology study has been applied on tapered plastic multimode sensors. This study basically used tapered plastic multimode fiber [polymethyl methacrylate (PMMA)] optics as a sensor. The tapered PMMA fiber was fabricated using an etching method involving deionized water and acetone to achieve a waist diameter and length of 0.45 and 10 mm, respectively. In addition, a tapered PMMA probe, which was coated by silver film, was fabricated and demonstrated using a calcium hypochlorite (G70) solution. The working mechanism of such a device is based on the observation increment in the transmission of the sensor that is immersed in solutions at high concentrations. As the concentration was varied from 0 to 6 ppm, the output voltage of the sensor increased linearly. The silver film coating increased the sensitivity of the proposed sensor because of the effective cladding refractive index, which increases with the coating and thus allows more light to be transmitted from the tapered fiber. In this study, the polynomial and radial basis function (RBF) were applied as the kernel function of the support vector regression (SVR) to estimate and predict the output voltage response of the sensors with and without silver film according to experimental tests. Instead of minimizing the observed training error, SVR_poly and SVR_rbf were used in an attempt to minimize the generalization error bound so as to achieve generalized performance. An adaptive neuro-fuzzy interference system (ANFIS) approach was also investigated for comparison. The experimental results showed that improvements in the predictive accuracy and capacity for generalization can be achieved by the SVR_poly approach in comparison to the SVR_rbf methodology. The same testing errors were found for the SVR_poly approach and the ANFIS approach.

  1. Soft Computing in Information Communication Technology Volume 2

    CERN Document Server

    2012-01-01

    This book is a collection of the accepted papers concerning soft computing in information communication technology. The resultant dissemination of the latest research results, and the exchanges of views concerning the future research directions to be taken in this field makes the work of immense value to all those having an interest in the topics covered. The present book represents a cooperative effort to seek out the best strategies for effecting improvements in the quality and the reliability of Fuzzy Logic, Machine Learning, Cryptography, Pattern Recognition, Bioinformatics, Biomedical Engineering, Advancements in ICT.

  2. The hierarchical expert tuning of PID controllers using tools of soft computing.

    Science.gov (United States)

    Karray, F; Gueaieb, W; Al-Sharhan, S

    2002-01-01

    We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.

  3. Verifying Stability of Dynamic Soft-Computing Systems

    Science.gov (United States)

    Wen, Wu; Napolitano, Marcello; Callahan, John

    1997-01-01

    Soft computing is a general term for algorithms that learn from human knowledge and mimic human skills. Example of such algorithms are fuzzy inference systems and neural networks. Many applications, especially in control engineering, have demonstrated their appropriateness in building intelligent systems that are flexible and robust. Although recent research have shown that certain class of neuro-fuzzy controllers can be proven bounded and stable, they are implementation dependent and difficult to apply to the design and validation process. Many practitioners adopt the trial and error approach for system validation or resort to exhaustive testing using prototypes. In this paper, we describe our on-going research towards establishing necessary theoretic foundation as well as building practical tools for the verification and validation of soft-computing systems. A unified model for general neuro-fuzzy system is adopted. Classic non-linear system control theory and recent results of its applications to neuro-fuzzy systems are incorporated and applied to the unified model. It is hoped that general tools can be developed to help the designer to visualize and manipulate the regions of stability and boundedness, much the same way Bode plots and Root locus plots have helped conventional control design and validation.

  4. Use of Soft Computing Technologies For Rocket Engine Control

    Science.gov (United States)

    Trevino, Luis C.; Olcmen, Semih; Polites, Michael

    2003-01-01

    The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to further improve overall engine system reliability and performance. Specifically, this will be presented by enhancing rocket engine control and engine health management (EHM) using SCT coupled with conventional control technologies, and sound software engineering practices used in Marshall s Flight Software Group. The principle goals are to improve software management, software development time and maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control and EHM methodologies, but to provide alternative design choices for control, EHM, implementation, performance, and sustaining engineering. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion, software engineering for embedded systems, and soft computing technologies (i.e., neural networks, fuzzy logic, and Bayesian belief networks), much of which is presented in this paper. The first targeted demonstration rocket engine platform is the MC-1 (formerly FASTRAC Engine) which is simulated with hardware and software in the Marshall Avionics & Software Testbed laboratory that

  5. International Conference on Soft Computing in Information Communication Technology

    CERN Document Server

    Soft Computing in Information Communication Technology

    2012-01-01

      This is a collection of the accepted papers concerning soft computing in information communication technology. All accepted papers are subjected to strict peer-reviewing by 2 expert referees. The resultant dissemination of the latest research results, and the exchanges of views concerning the future research directions to be taken in this field makes the work of immense value to all those having an interest in the topics covered. The present book represents a cooperative effort to seek out the best strategies for effecting improvements in the quality and the reliability of Neural Networks, Swarm Intelligence, Evolutionary Computing, Image Processing Internet Security, Data Security, Data Mining, Network Security and Protection of data and Cyber laws. Our sincere appreciation and thanks go to these authors for their contributions to this conference. I hope you can gain lots of useful information from the book.

  6. Application of Soft Computing in Coherent Communications Phase Synchronization

    Science.gov (United States)

    Drake, Jeffrey T.; Prasad, Nadipuram R.

    2000-01-01

    The use of soft computing techniques in coherent communications phase synchronization provides an alternative to analytical or hard computing methods. This paper discusses a novel use of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for phase synchronization in coherent communications systems utilizing Multiple Phase Shift Keying (MPSK) modulation. A brief overview of the M-PSK digital communications bandpass modulation technique is presented and it's requisite need for phase synchronization is discussed. We briefly describe the hybrid platform developed by Jang that incorporates fuzzy/neural structures namely the, Adaptive Neuro-Fuzzy Interference Systems (ANFIS). We then discuss application of ANFIS to phase estimation for M-PSK. The modeling of both explicit, and implicit phase estimation schemes for M-PSK symbols with unknown structure are discussed. Performance results from simulation of the above scheme is presented.

  7. Soft computing in design and manufacturing of advanced materials

    Science.gov (United States)

    Cios, Krzysztof J.; Baaklini, George Y; Vary, Alex

    1993-01-01

    The potential of fuzzy sets and neural networks, often referred to as soft computing, for aiding in all aspects of manufacturing of advanced materials like ceramics is addressed. In design and manufacturing of advanced materials, it is desirable to find which of the many processing variables contribute most to the desired properties of the material. There is also interest in real time quality control of parameters that govern material properties during processing stages. The concepts of fuzzy sets and neural networks are briefly introduced and it is shown how they can be used in the design and manufacturing processes. These two computational methods are alternatives to other methods such as the Taguchi method. The two methods are demonstrated by using data collected at NASA Lewis Research Center. Future research directions are also discussed.

  8. Technical Development and Application of Soft Computing in Agricultural and Biological Engineering

    Science.gov (United States)

    Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...

  9. Development of Soft Computing and Applications in Agricultural and Biological Engineering

    Science.gov (United States)

    Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...

  10. Wearable Intrinsically Soft, Stretchable, Flexible Devices for Memories and Computing.

    Science.gov (United States)

    Rajan, Krishna; Garofalo, Erik; Chiolerio, Alessandro

    2018-01-27

    A recent trend in the development of high mass consumption electron devices is towards electronic textiles (e-textiles), smart wearable devices, smart clothes, and flexible or printable electronics. Intrinsically soft, stretchable, flexible, Wearable Memories and Computing devices (WMCs) bring us closer to sci-fi scenarios, where future electronic systems are totally integrated in our everyday outfits and help us in achieving a higher comfort level, interacting for us with other digital devices such as smartphones and domotics, or with analog devices, such as our brain/peripheral nervous system. WMC will enable each of us to contribute to open and big data systems as individual nodes, providing real-time information about physical and environmental parameters (including air pollution monitoring, sound and light pollution, chemical or radioactive fallout alert, network availability, and so on). Furthermore, WMC could be directly connected to human brain and enable extremely fast operation and unprecedented interface complexity, directly mapping the continuous states available to biological systems. This review focuses on recent advances in nanotechnology and materials science and pays particular attention to any result and promising technology to enable intrinsically soft, stretchable, flexible WMC.

  11. Assessment of traffic noise levels in urban areas using different soft computing techniques.

    Science.gov (United States)

    Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D

    2016-10-01

    Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.

  12. Vehicular traffic noise prediction using soft computing approach.

    Science.gov (United States)

    Singh, Daljeet; Nigam, S P; Agrawal, V P; Kumar, Maneek

    2016-12-01

    A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Soft Real-Time PID Control on a VME Computer

    Science.gov (United States)

    Karayan, Vahag; Sander, Stanley; Cageao, Richard

    2007-01-01

    microPID (uPID) is a computer program for real-time proportional + integral + derivative (PID) control of a translation stage in a Fourier-transform ultraviolet spectrometer. microPID implements a PID control loop over a position profile at sampling rate of 8 kHz (sampling period 125microseconds). The software runs in a strippeddown Linux operating system on a VersaModule Eurocard (VME) computer operating in real-time priority queue using an embedded controller, a 16-bit digital-to-analog converter (D/A) board, and a laser-positioning board (LPB). microPID consists of three main parts: (1) VME device-driver routines, (2) software that administers a custom protocol for serial communication with a control computer, and (3) a loop section that obtains the current position from an LPB-driver routine, calculates the ideal position from the profile, and calculates a new voltage command by use of an embedded PID routine all within each sampling period. The voltage command is sent to the D/A board to control the stage. microPID uses special kernel headers to obtain microsecond timing resolution. Inasmuch as microPID implements a single-threaded process and all other processes are disabled, the Linux operating system acts as a soft real-time system.

  14. Proceedings of the International Conference on Soft Computing for Problem Solving

    CERN Document Server

    Nagar, Atulya; Pant, Millie; Bansal, Jagdish

    2012-01-01

    The present book is based on the research papers presented in the International Conference on Soft Computing for Problem Solving (SocProS 2011), held at Roorkee, India. This book is divided into two volumes and covers a variety of topics, including mathematical modeling, image processing, optimization, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, data mining etc. Particular emphasis is laid on Soft Computing and its application to diverse fields. The prime objective of the book is to familiarize the reader with the latest scientific developments that are taking place in various fields and the latest sophisticated problem solving tools that are being developed to deal with the complex and intricate problems that are otherwise difficult to solve by the usual and traditional methods. The book is directed to the researchers and scientists engaged in various fields of Science and Technology.

  15. Proceedings of the International Conference on Soft Computing for Problem Solving

    CERN Document Server

    Nagar, Atulya; Pant, Millie; Bansal, Jagdish

    2012-01-01

    The present book is based on the research papers presented in the International Conference on Soft Computing for Problem Solving (SocProS 2011), held at Roorkee, India. This book is divided into two volumes and covers a variety of topics, including mathematical modeling, image processing, optimization, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, data mining etc. Particular emphasis is laid on Soft Computing and its application to diverse fields. The prime objective of the book is to familiarize the reader with the latest scientific developments that are taking place in various fields and the latest sophisticated problem solving tools that are being developed to deal with the complex and intricate problems that are otherwise difficult to solve by the usual and traditional methods. The book is directed to the researchers and scientists engaged in various fields of Science and Technology.

  16. Iron-based superconductors via soft chemistry

    International Nuclear Information System (INIS)

    Friederichs, Gina Maya

    2015-01-01

    This thesis provides new soft chemistry approaches to Fe-based superconductors. Mild syntheses were demonstrated to be able to overcome difficulties, occurring in conventional synthesis and to enable the access to new metastable phases. A solvent-based metathesis reaction led to β-FeSe exclusively. Contrary to solid state syntheses, the formation of hexagonal α-FeSe could be avoided under mild conditions. The deintercalation of interstitial Fe (by formation of Fe 3 O 4 ) could be proven by low temperature O 2 -annealing of Fe 1+x Te 1-y Se y . By using redox (de)intercalations K 1-x Fe 2-y Se 2 , metastable Na 1-x Fe 2-y As 2 and Na 1-x ((Fe 1-y Co y ) 1-z As) 2 could successfully be obtained at room temperature. The mild synthesis conditions led to compounds like FeSe and K 1-x Fe 2-y Se 2 which exhibited different physical properties than found by conventional high temperature methods. In general, the developed (de)intercalation reactions represent a new, universally applicable tool in order to manipulate the structure along with the properties of Fe-based superconductors. The basic structural features of the characteristic FeX 4/4 tetrahedral layers, however, are preserved. Soft chemistry syntheses have been shown to allow the formation of a variety of phases, like Na 1-x Fe 2-y As 2 , Na 1-x ((Fe 1-y Co y ) 1-z As) 2 and K 1-x Fe 2-y Se 2 . Hence, especially low temperature approaches may enable the realization of complex stacking sequences, potentially leading to the fulfillment of the greatest goal in the research of superconductors - room temperature superconductivity.

  17. An electromechanical based deformable model for soft tissue simulation.

    Science.gov (United States)

    Zhong, Yongmin; Shirinzadeh, Bijan; Smith, Julian; Gu, Chengfan

    2009-11-01

    Soft tissue deformation is of great importance to surgery simulation. Although a significant amount of research efforts have been dedicated to simulating the behaviours of soft tissues, modelling of soft tissue deformation is still a challenging problem. This paper presents a new deformable model for simulation of soft tissue deformation from the electromechanical viewpoint of soft tissues. Soft tissue deformation is formulated as a reaction-diffusion process coupled with a mechanical load. The mechanical load applied to a soft tissue to cause a deformation is incorporated into the reaction-diffusion system, and consequently distributed among mass points of the soft tissue. Reaction-diffusion of mechanical load and non-rigid mechanics of motion are combined to govern the simulation dynamics of soft tissue deformation. An improved reaction-diffusion model is developed to describe the distribution of the mechanical load in soft tissues. A three-layer artificial cellular neural network is constructed to solve the reaction-diffusion model for real-time simulation of soft tissue deformation. A gradient based method is established to derive internal forces from the distribution of the mechanical load. Integration with a haptic device has also been achieved to simulate soft tissue deformation with haptic feedback. The proposed methodology does not only predict the typical behaviours of living tissues, but it also accepts both local and large-range deformations. It also accommodates isotropic, anisotropic and inhomogeneous deformations by simple modification of diffusion coefficients.

  18. Soft Sensors and Actuators based on Nanomaterials

    Science.gov (United States)

    Yao, Shanshan

    The focus of this research is using novel bottom-up synthesized nanomaterials and structures to build up devices for wearable sensors and soft actuators. The applications of the wearable sensors towards motion detection and health monitoring are investigated. In addition, flexible heaters for bimorph actuators and stretchable patches made of microgel depots containing drug-loaded nanoparticles (NPs) for stretch-triggered wearable drug delivery are studied. Considerable efforts have been made to achieve highly sensitive and wearable sensors that can simultaneously detect multiple stimuli such as stretch, pressure, temperature or touch. Highly stretchable multifunctional sensors that can detect strain (up to 50%), pressure (up to 1 MPa) and finger touch with good sensitivity, fast response time ( 40 ms) and good pressure mapping function were developed. The sensors were demonstrated for several wearable applications including monitoring thumb movements and knee motions, illustrating the potential utilities of such sensors in robotic systems, prosthetics, healthcare and flexible touch panels. In addition to mechanical sensors, a wearable skin hydration sensor made of silver nanowires (AgNWs) in a polydimethylsiloxane (PDMS) matrix was demonstrated based on skin impedance measurement. The hydration sensors were packaged into a flexible wristband for skin hydration monitoring and a chest patch consisting of a strain sensor, three electrocardiogram (ECG) electrodes and a skin hydration sensor for multimodal sensing. The wearable wristband and chest patch may be used for low-cost, wireless and continuous sensing of skin hydration and other health parameters. Two representative applications of the nanomaterials for soft actuators were investigated. In the first application on bimorph actuation, low-voltage and extremely flexible electrothermal bimorph actuators were fabricated in a simple, efficient and scalable process. The bimorph actuators were made of flexible Ag

  19. Application of Soft Computing Techniques and Multiple Regression Models for CBR prediction of Soils

    Directory of Open Access Journals (Sweden)

    Fatimah Khaleel Ibrahim

    2017-08-01

    Full Text Available The techniques of soft computing technique such as Artificial Neutral Network (ANN have improved the predicting capability and have actually discovered application in Geotechnical engineering. The aim of this research is to utilize the soft computing technique and Multiple Regression Models (MLR for forecasting the California bearing ratio CBR( of soil from its index properties. The indicator of CBR for soil could be predicted from various soils characterizing parameters with the assist of MLR and ANN methods. The data base that collected from the laboratory by conducting tests on 86 soil samples that gathered from different projects in Basrah districts. Data gained from the experimental result were used in the regression models and soft computing techniques by using artificial neural network. The liquid limit, plastic index , modified compaction test and the CBR test have been determined. In this work, different ANN and MLR models were formulated with the different collection of inputs to be able to recognize their significance in the prediction of CBR. The strengths of the models that were developed been examined in terms of regression coefficient (R2, relative error (RE% and mean square error (MSE values. From the results of this paper, it absolutely was noticed that all the proposed ANN models perform better than that of MLR model. In a specific ANN model with all input parameters reveals better outcomes than other ANN models.

  20. Understanding soft condensed matter via modeling and computation

    CERN Document Server

    Shi, An-Chang

    2011-01-01

    All living organisms consist of soft matter. For this reason alone, it is important to be able to understand and predict the structural and dynamical properties of soft materials such as polymers, surfactants, colloids, granular matter and liquids crystals. To achieve a better understanding of soft matter, three different approaches have to be integrated: experiment, theory and simulation. This book focuses on the third approach - but always in the context of the other two.

  1. Computational model of soft tissues in the human upper airway.

    Science.gov (United States)

    Pelteret, J-P V; Reddy, B D

    2012-01-01

    This paper presents a three-dimensional finite element model of the tongue and surrounding soft tissues with potential application to the study of sleep apnoea and of linguistics and speech therapy. The anatomical data was obtained from the Visible Human Project, and the underlying histological data was also extracted and incorporated into the model. Hyperelastic constitutive models were used to describe the material behaviour, and material incompressibility was accounted for. An active Hill three-element muscle model was used to represent the muscular tissue of the tongue. The neural stimulus for each muscle group was determined through the use of a genetic algorithm-based neural control model. The fundamental behaviour of the tongue under gravitational and breathing-induced loading is investigated. It is demonstrated that, when a time-dependent loading is applied to the tongue, the neural model is able to control the position of the tongue and produce a physiologically realistic response for the genioglossus.

  2. Challenges in Soft Computing: Case Study with Louisville MSD CSO Modeling

    Science.gov (United States)

    Ormsbee, L.; Tufail, M.

    2005-12-01

    The principal constituents of soft computing include fuzzy logic, neural computing, evolutionary computation, machine learning, and probabilistic reasoning. There are numerous applications of these constituents (both individually and combination of two or more) in the area of water resources and environmental systems. These range from development of data driven models to optimal control strategies to assist in more informed and intelligent decision making process. Availability of data is critical to such applications and having scarce data may lead to models that do not represent the response function over the entire domain. At the same time, too much data has a tendency to lead to over-constraining of the problem. This paper will describe the application of a subset of these soft computing techniques (neural computing and genetic algorithms) to the Beargrass Creek watershed in Louisville, Kentucky. The application include development of inductive models as substitutes for more complex process-based models to predict water quality of key constituents (such as dissolved oxygen) and use them in an optimization framework for optimal load reductions. Such a process will facilitate the development of total maximum daily loads for the impaired water bodies in the watershed. Some of the challenges faced in this application include 1) uncertainty in data sets, 2) model application, and 3) development of cause-and-effect relationships between water quality constituents and watershed parameters through use of inductive models. The paper will discuss these challenges and how they affect the desired goals of the project.

  3. Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures.

    Science.gov (United States)

    Llanes, Antonio; Muñoz, Andrés; Bueno-Crespo, Andrés; García-Valverde, Teresa; Sánchez, Antonia; Arcas-Túnez, Francisco; Pérez-Sánchez, Horacio; Cecilia, José M

    2016-01-01

    The protein-folding problem has been extensively studied during the last fifty years. The understanding of the dynamics of global shape of a protein and the influence on its biological function can help us to discover new and more effective drugs to deal with diseases of pharmacological relevance. Different computational approaches have been developed by different researchers in order to foresee the threedimensional arrangement of atoms of proteins from their sequences. However, the computational complexity of this problem makes mandatory the search for new models, novel algorithmic strategies and hardware platforms that provide solutions in a reasonable time frame. We present in this revision work the past and last tendencies regarding protein folding simulations from both perspectives; hardware and software. Of particular interest to us are both the use of inexact solutions to this computationally hard problem as well as which hardware platforms have been used for running this kind of Soft Computing techniques.

  4. What is Soft Computing? Bridging Gaps for 21st Century Science!

    Directory of Open Access Journals (Sweden)

    Rudolf Seising

    2010-06-01

    Full Text Available This contribution serves historical and philosophical reflecting cognitions on the role of Soft Computing in the 21st century. Referring to Magdalena's article in this issue, this paper considers the aspects of mixtures of techniques, the opposite pair qHard Computingq and qSoft Computingq, and Computational Intelligence. From the historical perspective the paper goes back to three articles by Warren Weaver that appeared after World War II. A concentrated study of these papers helps to understand that Soft Computing will be able to play a key role in the future development of science and technology.

  5. Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.

    Science.gov (United States)

    Zhang, Jinao; Zhong, Yongmin; Gu, Chengfan

    2018-05-30

    Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics.

  6. 17th Online World Conference on Soft Computing in Industrial Applications

    CERN Document Server

    Krömer, Pavel; Köppen, Mario; Schaefer, Gerald

    2014-01-01

    This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at WSC17, the 17th Online World Conference on Soft Computing in Industrial Applications, held from December 2012 to January 2013 on the Internet. WSC17 continues a successful series of scientific events started over a decade ago by the World Federation of Soft Computing. It brought together researchers from over the world interested in the ever advancing state of the art in the field. Continuous technological improvements make this online forum a viable gathering format for a world class conference. The aim of WSC17 was to disseminate excellent research results and contribute to building a global network of scientists interested in both theoretical foundations and practical applications of soft computing.   The 2012 edition of the Online World Conference on Soft Computing in Industrial Applications consisted of general track and special session on Continuous Features Discretization for Anomaly Intrusion Detectors...

  7. Soft Assembling Project-Based Learning and Leadership in Japan

    Science.gov (United States)

    Knight, Kevin; Murphey, Tim

    2017-01-01

    In this article, we initially focus on how the conceptualization of leadership by Knight (2013a) in his leadership seminars became the basis for choosing a project-based learning (PBL) approach. We then consider how soft assembling can enhance the leadership project activities of student teams and group-work in general classes. Soft assembling…

  8. Soft Computing Optimizer For Intelligent Control Systems Design: The Structure And Applications

    Directory of Open Access Journals (Sweden)

    Sergey A. Panfilov

    2003-10-01

    Full Text Available Soft Computing Optimizer (SCO as a new software tool for design of robust intelligent control systems is described. It is based on the hybrid methodology of soft computing and stochastic simulation. It uses as an input the measured or simulated data about the modeled system. SCO is used to design an optimal fuzzy inference system, which approximates a random behavior of control object with the certain accuracy. The task of the fuzzy inference system construction is reduced to the subtasks such as forming of the linguistic variables for each input and output variable, creation of rule data base, optimization of rule data base and refinement of the parameters of the membership functions. Each task by the corresponding genetic algorithm (with an appropriate fitness function is solved. The result of SCO application is the design of Knowledge Base of a Fuzzy Controller, which contains the value information about developed fuzzy inference system. Such value information can be downloaded into the actual fuzzy controller to perform online fuzzy control. Simulations results of robust fuzzy control of nonlinear dynamic systems and experimental results of application on automotive semi-active suspension control are demonstrated.

  9. Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.

    Science.gov (United States)

    Meng, Jianjun; Mundahl, John; Streitz, Taylor; Maile, Kaitlin; Gulachek, Nicholas; He, Jeffrey; He, Bin

    2017-01-01

    Motor imagery-based (MI based) brain-computer interface (BCI) using electroencephalography (EEG) allows users to directly control a computer or external device by modulating and decoding the brain waves. A variety of factors could potentially affect the performance of BCI such as the health status of subjects or the environment. In this study, we investigated the effects of soft drinks and regular coffee on EEG signals under resting state and on the performance of MI based BCI. Twenty-six healthy human subjects participated in three or four BCI sessions with a resting period in each session. During each session, the subjects drank an unlabeled soft drink with either sugar (Caffeine Free Coca-Cola), caffeine (Diet Coke), neither ingredient (Caffeine Free Diet Coke), or a regular coffee if there was a fourth session. The resting state spectral power in each condition was compared; the analysis showed that power in alpha and beta band after caffeine consumption were decreased substantially compared to control and sugar condition. Although the attenuation of powers in the frequency range used for the online BCI control signal was shown, group averaged BCI online performance after consuming caffeine was similar to those of other conditions. This work, for the first time, shows the effect of caffeine, sugar intake on the online BCI performance and resting state brain signal.

  10. Optimal reliability allocation for large software projects through soft computing techniques

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albeanu, Grigore; Popentiu-Vladicescu, Florin

    2012-01-01

    or maximizing the system reliability subject to budget constraints. These kinds of optimization problems were considered both in deterministic and stochastic frameworks in literature. Recently, the intuitionistic-fuzzy optimization approach was considered as a soft computing successful modelling approach....... Firstly, a review on existing soft computing approaches to optimization is given. The main section extends the results considering self-organizing migrating algorithms for solving intuitionistic-fuzzy optimization problems attached to complex fault-tolerant software architectures which proved...

  11. Exploiting short-term memory in soft body dynamics as a computational resource.

    Science.gov (United States)

    Nakajima, K; Li, T; Hauser, H; Pfeifer, R

    2014-11-06

    Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  12. Soft Legged Wheel-Based Robot with Terrestrial Locomotion Abilities

    Directory of Open Access Journals (Sweden)

    Ali Sadeghi

    2016-12-01

    Full Text Available In recent years robotics has been influenced by a new approach, soft-robotics, bringing the idea that safe interaction with user and more adaptation to the environment can be achieved by exploiting easily deformable materials and flexible components in the structure of robots. In 2016, the soft-robotics community has promoted a new robotics challenge, named RoboSoft Grand Challenge, with the aim of bringing together different opinions on the usefulness and applicability of softness and compliancy in robotics. In this paper we describe the design and implementation of a terrestrial robot based on two soft legged wheels. The tasks predefined by the challenge were set as targets in the robot design, which finally succeeded to accomplish all the tasks. The wheels of the robot can passively climb over stairs and adapt to slippery grounds using two soft legs embedded in their structure. The soft legs, fabricated by integration of soft and rigid materials and mounted on the circumference of a conventional wheel, succeed to enhance its functionality and easily adapt to unknown grounds. The robot has a semi stiff tail that helps in the stabilization and climbing of stairs. An active wheel is embedded at the extremity of the tail in order to increase the robot maneuverability in narrow environments. Moreover two parallelogram linkages let the robot to reconfigure and shrink its size allowing entering inside gates smaller than its initial dimensions.

  13. Multivariate Methods Based Soft Measurement for Wine Quality Evaluation

    Directory of Open Access Journals (Sweden)

    Shen Yin

    2014-01-01

    a decision. However, since the physicochemical indexes of wine can to some extent reflect the quality of wine, the multivariate statistical methods based soft measure can help the oenologist in wine evaluation.

  14. A soft-contact model for computing safety margins in human prehension.

    Science.gov (United States)

    Singh, Tarkeshwar; Ambike, Satyajit

    2017-10-01

    The soft human digit tip forms contact with grasped objects over a finite area and applies a moment about an axis normal to the area. These moments are important for ensuring stability during precision grasping. However, the contribution of these moments to grasp stability is rarely investigated in prehension studies. The more popular hard-contact model assumes that the digits exert a force vector but no free moment on the grasped object. Many sensorimotor studies use this model and show that humans estimate friction coefficients to scale the normal force to grasp objects stably, i.e. the smoother the surface, the tighter the grasp. The difference between the applied normal force and the minimal normal force needed to prevent slipping is called safety margin and this index is widely used as a measure of grasp planning. Here, we define and quantify safety margin using a more realistic contact model that allows digits to apply both forces and moments. Specifically, we adapt a soft-contact model from robotics and demonstrate that the safety margin thus computed is a more accurate and robust index of grasp planning than its hard-contact variant. Previously, we have used the soft-contact model to propose two indices of grasp planning that show how humans account for the shape and inertial properties of an object. A soft-contact based safety margin offers complementary insights by quantifying how humans may account for surface properties of the object and skin tissue during grasp planning and execution. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Determining flexor-tendon repair techniques via soft computing

    Science.gov (United States)

    Johnson, M.; Firoozbakhsh, K.; Moniem, M.; Jamshidi, M.

    2001-01-01

    An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.

  16. Development of Fuzzy Logic and Soft Computing Methodologies

    Science.gov (United States)

    Zadeh, L. A.; Yager, R.

    1999-01-01

    Our earlier research on computing with words (CW) has led to a new direction in fuzzy logic which points to a major enlargement of the role of natural languages in information processing, decision analysis and control. This direction is based on the methodology of computing with words and embodies a new theory which is referred to as the computational theory of perceptions (CTP). An important feature of this theory is that it can be added to any existing theory - especially to probability theory, decision analysis, and control - and enhance the ability of the theory to deal with real-world problems in which the decision-relevant information is a mixture of measurements and perceptions. The new direction is centered on an old concept - the concept of a perception - a concept which plays a central role in human cognition. The ability to reason with perceptions perceptions of time, distance, force, direction, shape, intent, likelihood, truth and other attributes of physical and mental objects - underlies the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Everyday examples of such tasks are parking a car, driving in city traffic, cooking a meal, playing golf and summarizing a story. Perceptions are intrinsically imprecise. Imprecision of perceptions reflects the finite ability of sensory organs and ultimately, the brain, to resolve detail and store information. More concretely, perceptions are both fuzzy and granular, or, for short, f-granular. Perceptions are f-granular in the sense that: (a) the boundaries of perceived classes are not sharply defined; and (b) the elements of classes are grouped into granules, with a granule being a clump of elements drawn together by indistinguishability, similarity. proximity or functionality. F-granularity of perceptions may be viewed as a human way of achieving data compression. In large measure, scientific progress has been, and continues to be

  17. A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications.

    Science.gov (United States)

    Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod

    2016-08-06

    In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively.

  18. Tendon-Based Stiffening for a Pneumatically Actuated Soft Manipulator

    OpenAIRE

    Shiva, A.; Stilli, A.; Noh, Y.; Faragasso, A.; Falco, I. D.; Gerboni, G.; Cianchetti, M.; Menciassi, A.; Althoefer, K.; Wurdemann, H. A.

    2016-01-01

    There is an emerging trend toward soft robotics due to its extended manipulation capabilities compared to traditionally rigid robot links, showing promise for an extended applicability to new areas. However, as a result of the inherent property of soft robotics being less rigid, the ability to control/obtain higher overall stiffness when required is yet to be further explored. In this letter, an innovative design is introduced which allows varying the stiffness of a continuum silicon-based ma...

  19. Hard and soft acids and bases: structure and process.

    Science.gov (United States)

    Reed, James L

    2012-07-05

    Under investigation is the structure and process that gives rise to hard-soft behavior in simple anionic atomic bases. That for simple atomic bases the chemical hardness is expected to be the only extrinsic component of acid-base strength, has been substantiated in the current study. A thermochemically based operational scale of chemical hardness was used to identify the structure within anionic atomic bases that is responsible for chemical hardness. The base's responding electrons have been identified as the structure, and the relaxation that occurs during charge transfer has been identified as the process giving rise to hard-soft behavior. This is in contrast the commonly accepted explanations that attribute hard-soft behavior to varying degrees of electrostatic and covalent contributions to the acid-base interaction. The ability of the atomic ion's responding electrons to cause hard-soft behavior has been assessed by examining the correlation of the estimated relaxation energies of the responding electrons with the operational chemical hardness. It has been demonstrated that the responding electrons are able to give rise to hard-soft behavior in simple anionic bases.

  20. Finding-specific display presets for computed radiography soft-copy reading.

    Science.gov (United States)

    Andriole, K P; Gould, R G; Webb, W R

    1999-05-01

    Much work has been done to optimize the display of cross-sectional modality imaging examinations for soft-copy reading (i.e., window/level tissue presets, and format presentations such as tile and stack modes, four-on-one, nine-on-one, etc). Less attention has been paid to the display of digital forms of the conventional projection x-ray. The purpose of this study is to assess the utility of providing presets for computed radiography (CR) soft-copy display, based not on the window/level settings, but on processing applied to the image optimized for visualization of specific findings, pathologies, etc (i.e., pneumothorax, tumor, tube location). It is felt that digital display of CR images based on finding-specific processing presets has the potential to: speed reading of digital projection x-ray examinations on soft copy; improve diagnostic efficacy; standardize display across examination type, clinical scenario, important key findings, and significant negatives; facilitate image comparison; and improve confidence in and acceptance of soft-copy reading. Clinical chest images are acquired using an Agfa-Gevaert (Mortsel, Belgium) ADC 70 CR scanner and Fuji (Stamford, CT) 9000 and AC2 CR scanners. Those demonstrating pertinent findings are transferred over the clinical picture archiving and communications system (PACS) network to a research image processing station (Agfa PS5000), where the optimal image-processing settings per finding, pathologic category, etc, are developed in conjunction with a thoracic radiologist, by manipulating the multiscale image contrast amplification (Agfa MUSICA) algorithm parameters. Soft-copy display of images processed with finding-specific settings are compared with the standard default image presentation for 50 cases of each category. Comparison is scored using a 5-point scale with the positive scale denoting the standard presentation is preferred over the finding-specific processing, the negative scale denoting the finding

  1. Current Trend Towards Using Soft Computing Approaches to Phase Synchronization in Communication Systems

    Science.gov (United States)

    Drake, Jeffrey T.; Prasad, Nadipuram R.

    1999-01-01

    This paper surveys recent advances in communications that utilize soft computing approaches to phase synchronization. Soft computing, as opposed to hard computing, is a collection of complementary methodologies that act in producing the most desirable control, decision, or estimation strategies. Recently, the communications area has explored the use of the principal constituents of soft computing, namely, fuzzy logic, neural networks, and genetic algorithms, for modeling, control, and most recently for the estimation of phase in phase-coherent communications. If the receiver in a digital communications system is phase-coherent, as is often the case, phase synchronization is required. Synchronization thus requires estimation and/or control at the receiver of an unknown or random phase offset.

  2. Web mining in soft computing framework: relevance, state of the art and future directions.

    Science.gov (United States)

    Pal, S K; Talwar, V; Mitra, P

    2002-01-01

    The paper summarizes the different characteristics of Web data, the basic components of Web mining and its different types, and the current state of the art. The reason for considering Web mining, a separate field from data mining, is explained. The limitations of some of the existing Web mining methods and tools are enunciated, and the significance of soft computing (comprising fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithms (GAs), and rough sets (RSs) are highlighted. A survey of the existing literature on "soft Web mining" is provided along with the commercially available systems. The prospective areas of Web mining where the application of soft computing needs immediate attention are outlined with justification. Scope for future research in developing "soft Web mining" systems is explained. An extensive bibliography is also provided.

  3. Multi-GPU Jacobian accelerated computing for soft-field tomography

    International Nuclear Information System (INIS)

    Borsic, A; Attardo, E A; Halter, R J

    2012-01-01

    Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use finite element models (FEMs) to represent the volume of interest and solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are 3D. Although the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in electrical impedance tomography (EIT) applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15–20 min with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Furthermore, providing high-speed reconstructions is essential for some promising clinical application of EIT. For 3D problems, 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In this work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with the use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20 times

  4. Multi-GPU Jacobian accelerated computing for soft-field tomography.

    Science.gov (United States)

    Borsic, A; Attardo, E A; Halter, R J

    2012-10-01

    Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use finite element models (FEMs) to represent the volume of interest and solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are 3D. Although the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in electrical impedance tomography (EIT) applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15-20 min with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Furthermore, providing high-speed reconstructions is essential for some promising clinical application of EIT. For 3D problems, 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In this work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with the use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20

  5. Computer tomography for rare soft tissue tumours of the extremities

    International Nuclear Information System (INIS)

    Boettger, E.; Semerak, M.; Stoltze, D.; Rossak, K.

    1979-01-01

    Five patients with undiagnosed soft tissue masses in the extremities were examined and in two a pathological diagnosis could be made. One was an extensive, invasive fibroma (desmoid) 22 cm long which could be followed from the thigh almost into the pelvis. It was sharply demarkated form the surrounding muscles and of higher density. The second case was a 12 cm long cavernous haemangioma in the semi-membranosus muscle. This was originally hypo-dense, but showed marked increase in its density after the administration of contrast. (orig.) [de

  6. On the possibility of non-invasive multilayer temperature estimation using soft-computing methods.

    Science.gov (United States)

    Teixeira, C A; Pereira, W C A; Ruano, A E; Ruano, M Graça

    2010-01-01

    This work reports original results on the possibility of non-invasive temperature estimation (NITE) in a multilayered phantom by applying soft-computing methods. The existence of reliable non-invasive temperature estimator models would improve the security and efficacy of thermal therapies. These points would lead to a broader acceptance of this kind of therapies. Several approaches based on medical imaging technologies were proposed, magnetic resonance imaging (MRI) being appointed as the only one to achieve the acceptable temperature resolutions for hyperthermia purposes. However, MRI intrinsic characteristics (e.g., high instrumentation cost) lead us to use backscattered ultrasound (BSU). Among the different BSU features, temporal echo-shifts have received a major attention. These shifts are due to changes of speed-of-sound and expansion of the medium. The originality of this work involves two aspects: the estimator model itself is original (based on soft-computing methods) and the application to temperature estimation in a three-layer phantom is also not reported in literature. In this work a three-layer (non-homogeneous) phantom was developed. The two external layers were composed of (in % of weight): 86.5% degassed water, 11% glycerin and 2.5% agar-agar. The intermediate layer was obtained by adding graphite powder in the amount of 2% of the water weight to the above composition. The phantom was developed to have attenuation and speed-of-sound similar to in vivo muscle, according to the literature. BSU signals were collected and cumulative temporal echo-shifts computed. These shifts and the past temperature values were then considered as possible estimators inputs. A soft-computing methodology was applied to look for appropriate multilayered temperature estimators. The methodology involves radial-basis functions neural networks (RBFNN) with structure optimized by the multi-objective genetic algorithm (MOGA). In this work 40 operating conditions were

  7. Hard and soft acids and bases: atoms and atomic ions.

    Science.gov (United States)

    Reed, James L

    2008-07-07

    The structural origin of hard-soft behavior in atomic acids and bases has been explored using a simple orbital model. The Pearson principle of hard and soft acids and bases has been taken to be the defining statement about hard-soft behavior and as a definition of chemical hardness. There are a number of conditions that are imposed on any candidate structure and associated property by the Pearson principle, which have been exploited. The Pearson principle itself has been used to generate a thermodynamically based scale of relative hardness and softness for acids and bases (operational chemical hardness), and a modified Slater model has been used to discern the electronic origin of hard-soft behavior. Whereas chemical hardness is a chemical property of an acid or base and the operational chemical hardness is an experimental measure of it, the absolute hardness is a physical property of an atom or molecule. A critical examination of chemical hardness, which has been based on a more rigorous application of the Pearson principle and the availability of quantitative measures of chemical hardness, suggests that the origin of hard-soft behavior for both acids and bases resides in the relaxation of the electrons not undergoing transfer during the acid-base interaction. Furthermore, the results suggest that the absolute hardness should not be taken as synonymous with chemical hardness but that the relationship is somewhat more complex. Finally, this work provides additional groundwork for a better understanding of chemical hardness that will inform the understanding of hardness in molecules.

  8. An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment.

    Science.gov (United States)

    Vilhena, João; Rosário Martins, M; Vicente, Henrique; Grañeda, José M; Caldeira, Filomena; Gusmão, Rodrigo; Neves, João; Neves, José

    2017-03-01

    The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%).

  9. Computer vision and soft computing for automatic skull-face overlay in craniofacial superimposition.

    Science.gov (United States)

    Campomanes-Álvarez, B Rosario; Ibáñez, O; Navarro, F; Alemán, I; Botella, M; Damas, S; Cordón, O

    2014-12-01

    Craniofacial superimposition can provide evidence to support that some human skeletal remains belong or not to a missing person. It involves the process of overlaying a skull with a number of ante mortem images of an individual and the analysis of their morphological correspondence. Within the craniofacial superimposition process, the skull-face overlay stage just focuses on achieving the best possible overlay of the skull and a single ante mortem image of the suspect. Although craniofacial superimposition has been in use for over a century, skull-face overlay is still applied by means of a trial-and-error approach without an automatic method. Practitioners finish the process once they consider that a good enough overlay has been attained. Hence, skull-face overlay is a very challenging, subjective, error prone, and time consuming part of the whole process. Though the numerical assessment of the method quality has not been achieved yet, computer vision and soft computing arise as powerful tools to automate it, dramatically reducing the time taken by the expert and obtaining an unbiased overlay result. In this manuscript, we justify and analyze the use of these techniques to properly model the skull-face overlay problem. We also present the automatic technical procedure we have developed using these computational methods and show the four overlays obtained in two craniofacial superimposition cases. This automatic procedure can be thus considered as a tool to aid forensic anthropologists to develop the skull-face overlay, automating and avoiding subjectivity of the most tedious task within craniofacial superimposition. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  10. A Soft Computing Approach to Kidney Diseases Evaluation.

    Science.gov (United States)

    Neves, José; Martins, M Rosário; Vilhena, João; Neves, João; Gomes, Sabino; Abelha, António; Machado, José; Vicente, Henrique

    2015-10-01

    Kidney renal failure means that one's kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient's history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the

  11. Soft silicone based interpenetrating networks as materials for actuators

    DEFF Research Database (Denmark)

    Yu, Liyun; Gonzalez, Lidia; Hvilsted, Søren

    2014-01-01

    A new approach based on silicone interpenetrating networks with orthogonal chemistries has been investigated with focus on developing soft and flexible elastomers with high energy densities and small viscous losses. The interpenetrating networks are made as simple two pot mixtures...... as for the commercial available silylation based elastomers such as Elastosil RT625. The resulting interpenetrating networks are formulated to be softer than RT625 to increase the actuation caused when applying a voltage due to their softness combined with the significantly higher permittivity than the pure silicone...

  12. SOFT COMPUTING SINGLE HIDDEN LAYER MODELS FOR SHELF LIFE PREDICTION OF BURFI

    Directory of Open Access Journals (Sweden)

    Sumit Goyal

    2012-05-01

    Full Text Available Burfi is an extremely popular sweetmeat, which is prepared by desiccating the standardized water buffalo milk. Soft computing feedforward single layer models were developed for predicting the shelf life of burfi stored at 30g.C. The data of the product relating to moisture, titratable acidity, free fatty acids, tyrosine, and peroxide value were used as input variables, and the overall acceptability score as output variable. The results showed excellent agreement between the experimental and the predicted data, suggesting that the developed soft computing model can alternatively be used for predicting the shelf life of burfi.

  13. Computational Modeling for Enhancing Soft Tissue Image Guided Surgery: An Application in Neurosurgery.

    Science.gov (United States)

    Miga, Michael I

    2016-01-01

    With the recent advances in computing, the opportunities to translate computational models to more integrated roles in patient treatment are expanding at an exciting rate. One area of considerable development has been directed towards correcting soft tissue deformation within image guided neurosurgery applications. This review captures the efforts that have been undertaken towards enhancing neuronavigation by the integration of soft tissue biomechanical models, imaging and sensing technologies, and algorithmic developments. In addition, the review speaks to the evolving role of modeling frameworks within surgery and concludes with some future directions beyond neurosurgical applications.

  14. Assessing the suitability of soft computing approaches for forest fires prediction

    Directory of Open Access Journals (Sweden)

    Samaher Al_Janabi

    2018-07-01

    Full Text Available Forest fires present one of the main causes of environmental hazards that have many negative results in different aspect of life. Therefore, early prediction, fast detection and rapid action are the key elements for controlling such phenomenon and saving lives. Through this work, 517 different entries were selected at different times for montesinho natural park (MNP in Portugal to determine the best predictor that has the ability to detect forest fires, The principle component analysis (PCA was applied to find the critical patterns and particle swarm optimization (PSO technique was used to segment the fire regions (clusters. In the next stage, five soft computing (SC Techniques based on neural network were used in parallel to identify the best technique that would potentially give more accurate and optimum results in predicting of forest fires, these techniques namely; cascade correlation network (CCN, multilayer perceptron neural network (MPNN, polynomial neural network (PNN, radial basis function (RBF and support vector machine (SVM In the final stage, the predictors and their performance were evaluated based on five quality measures including root mean squared error (RMSE, mean squared error (MSE, relative absolute error (RAE, mean absolute error (MAE and information gain (IG. The results indicate that SVM technique was more effective and efficient than the RBF, MPNN, PNN and CCN predictors. The results also show that the SVM algorithm provides more precise predictions compared with other predictors with small estimation error. The obtained results confirm that the SVM improves the prediction accuracy and suitable for forest fires prediction compared to other methods. Keywords: Forest fires, Soft computing, Prediction, Principle component analysis, Particle swarm optimization, Cascade correlation network, Multilayer perceptron neural network, Polynomial neural networks, Radial basis function, Support vector machine

  15. Design-based modeling of magnetically actuated soft diaphragm materials

    Science.gov (United States)

    Jayaneththi, V. R.; Aw, K. C.; McDaid, A. J.

    2018-04-01

    Magnetic polymer composites (MPC) have shown promise for emerging biomedical applications such as lab-on-a-chip and implantable drug delivery. These soft material actuators are capable of fast response, large deformation and wireless actuation. Existing MPC modeling approaches are computationally expensive and unsuitable for rapid design prototyping and real-time control applications. This paper proposes a macro-scale 1-DOF model capable of predicting force and displacement of an MPC diaphragm actuator. Model validation confirmed both blocked force and displacement can be accurately predicted in a variety of working conditions i.e. different magnetic field strengths, static/dynamic fields, and gap distances. The contribution of this work includes a comprehensive experimental investigation of a macro-scale diaphragm actuator; the derivation and validation of a new phenomenological model to describe MPC actuation; and insights into the proposed model’s design-based functionality i.e. scalability and generalizability in terms of magnetic filler concentration and diaphragm diameter. Due to the lumped element modeling approach, the proposed model can also be adapted to alternative actuator configurations, and thus presents a useful tool for design, control and simulation of novel MPC applications.

  16. Interior spatial layout with soft objectives using evolutionary computation

    NARCIS (Netherlands)

    Chatzikonstantinou, I.; Bengisu, E.

    2016-01-01

    This paper presents the design problem of furniture arrangement in a residential interior living space, and addresses it by means of evolutionary computation. Interior arrangement is an important and interesting problem that occurs commonly when designing living spaces. It entails determining the

  17. Prediction of monthly regional groundwater levels through hybrid soft-computing techniques

    Science.gov (United States)

    Chang, Fi-John; Chang, Li-Chiu; Huang, Chien-Wei; Kao, I.-Feng

    2016-10-01

    Groundwater systems are intrinsically heterogeneous with dynamic temporal-spatial patterns, which cause great difficulty in quantifying their complex processes, while reliable predictions of regional groundwater levels are commonly needed for managing water resources to ensure proper service of water demands within a region. In this study, we proposed a novel and flexible soft-computing technique that could effectively extract the complex high-dimensional input-output patterns of basin-wide groundwater-aquifer systems in an adaptive manner. The soft-computing models combined the Self Organized Map (SOM) and the Nonlinear Autoregressive with Exogenous Inputs (NARX) network for predicting monthly regional groundwater levels based on hydrologic forcing data. The SOM could effectively classify the temporal-spatial patterns of regional groundwater levels, the NARX could accurately predict the mean of regional groundwater levels for adjusting the selected SOM, the Kriging was used to interpolate the predictions of the adjusted SOM into finer grids of locations, and consequently the prediction of a monthly regional groundwater level map could be obtained. The Zhuoshui River basin in Taiwan was the study case, and its monthly data sets collected from 203 groundwater stations, 32 rainfall stations and 6 flow stations during 2000 and 2013 were used for modelling purpose. The results demonstrated that the hybrid SOM-NARX model could reliably and suitably predict monthly basin-wide groundwater levels with high correlations (R2 > 0.9 in both training and testing cases). The proposed methodology presents a milestone in modelling regional environmental issues and offers an insightful and promising way to predict monthly basin-wide groundwater levels, which is beneficial to authorities for sustainable water resources management.

  18. PhysarumSoft: An update based on rough set theory

    Science.gov (United States)

    Schumann, Andrew; Pancerz, Krzysztof

    2017-07-01

    PhysarumSoft is a software tool consisting of two modules developed for programming Physarum machines and simulating Physarum games, respectively. The paper briefly discusses what has been added since the last version released in 2015. New elements in both modules are based on rough set theory. Rough sets are used to model behaviour of Physarum machines and to describe strategy games.

  19. Computer Based Expert Systems.

    Science.gov (United States)

    Parry, James D.; Ferrara, Joseph M.

    1985-01-01

    Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

  20. Efficient Buffer Capacity and Scheduler Setting Computation for Soft Real-Time Stream Processing Applications

    NARCIS (Netherlands)

    Bekooij, Marco; Bekooij, Marco Jan Gerrit; Wiggers, M.H.; van Meerbergen, Jef

    2007-01-01

    Soft real-time applications that process data streams can often be intuitively described as dataflow process networks. In this paper we present a novel analysis technique to compute conservative estimates of the required buffer capacities in such process networks. With the same analysis technique

  1. A Computational Modeling Approach for Investigating Soft Tissue Balancing in Bicruciate Retaining Knee Arthroplasty

    Directory of Open Access Journals (Sweden)

    Shahram Amiri

    2012-01-01

    Full Text Available Bicruciate retaining knee arthroplasty, although has shown improved functions and patient satisfaction compared to other designs of total knee replacement, remains a technically demanding option for treating severe cases of arthritic knees. One of the main challenges in bicruciate retaining arthroplasty is proper balancing of the soft tissue during the surgery. In this study biomechanics of soft tissue balancing was investigated using a validated computational model of the knee joint with high fidelity definitions of the soft tissue structures along with a Taguchi method for design of experiments. The model was used to simulate intraoperative balancing of soft tissue structures following the combinations suggested by an orthogonal array design. The results were used to quantify the corresponding effects on the laxity of the joint under anterior-posterior, internal-external, and varus-valgus loads. These effects were ranked for each ligament bundle to identify the components of laxity which were most sensitive to the corresponding surgical modifications. The resulting map of sensitivity for all the ligament bundles determined the components of laxity most suitable for examination during intraoperative balancing of the soft tissue. Ultimately, a sequence for intraoperative soft tissue balancing was suggested for a bicruciate retaining knee arthroplasty.

  2. A Computational Modeling Approach for Investigating Soft Tissue Balancing in Bicruciate Retaining Knee Arthroplasty

    Science.gov (United States)

    Amiri, Shahram; Wilson, David R.

    2012-01-01

    Bicruciate retaining knee arthroplasty, although has shown improved functions and patient satisfaction compared to other designs of total knee replacement, remains a technically demanding option for treating severe cases of arthritic knees. One of the main challenges in bicruciate retaining arthroplasty is proper balancing of the soft tissue during the surgery. In this study biomechanics of soft tissue balancing was investigated using a validated computational model of the knee joint with high fidelity definitions of the soft tissue structures along with a Taguchi method for design of experiments. The model was used to simulate intraoperative balancing of soft tissue structures following the combinations suggested by an orthogonal array design. The results were used to quantify the corresponding effects on the laxity of the joint under anterior-posterior, internal-external, and varus-valgus loads. These effects were ranked for each ligament bundle to identify the components of laxity which were most sensitive to the corresponding surgical modifications. The resulting map of sensitivity for all the ligament bundles determined the components of laxity most suitable for examination during intraoperative balancing of the soft tissue. Ultimately, a sequence for intraoperative soft tissue balancing was suggested for a bicruciate retaining knee arthroplasty. PMID:23082090

  3. Measurement of facial soft tissues thickness using 3D computed tomographic images

    International Nuclear Information System (INIS)

    Jeong, Ho Gul; Kim, Kee Deog; Shin, Dong Won; Hu, Kyung Seok; Lee, Jae Bum; Park, Hyok; Park, Chang Seo; Han, Seung Ho

    2006-01-01

    To evaluate accuracy and reliability of program to measure facial soft tissue thickness using 3D computed tomographic images by comparing with direct measurement. One cadaver was scanned with a Helical CT with 3 mm slice thickness and 3 mm/sec table speed. The acquired data was reconstructed with 1.5 mm reconstruction interval and the images were transferred to a personal computer. The facial soft tissue thickness were measured using a program developed newly in 3D image. For direct measurement, the cadaver was cut with a bone cutter and then a ruler was placed above the cut side. The procedure was followed by taking pictures of the facial soft tissues with a high-resolution digital camera. Then the measurements were done in the photographic images and repeated for ten times. A repeated measure analysis of variance was adopted to compare and analyze the measurements resulting from the two different methods. Comparison according to the areas was analyzed by Mann-Whitney test. There were no statistically significant differences between the direct measurements and those using the 3D images(p>0.05). There were statistical differences in the measurements on 17 points but all the points except 2 points showed a mean difference of 0.5 mm or less. The developed software program to measure the facial soft tissue thickness using 3D images was so accurate that it allows to measure facial soft tissue thickness more easily in forensic science and anthropology

  4. Measurement of facial soft tissues thickness using 3D computed tomographic images

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Ho Gul; Kim, Kee Deog; Shin, Dong Won; Hu, Kyung Seok; Lee, Jae Bum; Park, Hyok; Park, Chang Seo [Yonsei Univ. Hospital, Seoul (Korea, Republic of); Han, Seung Ho [Catholic Univ. of Korea, Seoul (Korea, Republic of)

    2006-03-15

    To evaluate accuracy and reliability of program to measure facial soft tissue thickness using 3D computed tomographic images by comparing with direct measurement. One cadaver was scanned with a Helical CT with 3 mm slice thickness and 3 mm/sec table speed. The acquired data was reconstructed with 1.5 mm reconstruction interval and the images were transferred to a personal computer. The facial soft tissue thickness were measured using a program developed newly in 3D image. For direct measurement, the cadaver was cut with a bone cutter and then a ruler was placed above the cut side. The procedure was followed by taking pictures of the facial soft tissues with a high-resolution digital camera. Then the measurements were done in the photographic images and repeated for ten times. A repeated measure analysis of variance was adopted to compare and analyze the measurements resulting from the two different methods. Comparison according to the areas was analyzed by Mann-Whitney test. There were no statistically significant differences between the direct measurements and those using the 3D images(p>0.05). There were statistical differences in the measurements on 17 points but all the points except 2 points showed a mean difference of 0.5 mm or less. The developed software program to measure the facial soft tissue thickness using 3D images was so accurate that it allows to measure facial soft tissue thickness more easily in forensic science and anthropology.

  5. A Case for Soft Error Detection and Correction in Computational Chemistry.

    Science.gov (United States)

    van Dam, Hubertus J J; Vishnu, Abhinav; de Jong, Wibe A

    2013-09-10

    High performance computing platforms are expected to deliver 10(18) floating operations per second by the year 2022 through the deployment of millions of cores. Even if every core is highly reliable the sheer number of them will mean that the mean time between failures will become so short that most application runs will suffer at least one fault. In particular soft errors caused by intermittent incorrect behavior of the hardware are a concern as they lead to silent data corruption. In this paper we investigate the impact of soft errors on optimization algorithms using Hartree-Fock as a particular example. Optimization algorithms iteratively reduce the error in the initial guess to reach the intended solution. Therefore they may intuitively appear to be resilient to soft errors. Our results show that this is true for soft errors of small magnitudes but not for large errors. We suggest error detection and correction mechanisms for different classes of data structures. The results obtained with these mechanisms indicate that we can correct more than 95% of the soft errors at moderate increases in the computational cost.

  6. Critical Data Analysis Precedes Soft Computing Of Medical Data

    DEFF Research Database (Denmark)

    Keyserlingk, Diedrich Graf von; Jantzen, Jan; Berks, G.

    2000-01-01

    extracted. The factors had different relationships (loadings) to the symptoms. Although the factors were gained only by computations, they seemed to express some modular features of the language disturbances. This phenomenon, that factors represent superior aspects of data, is well known in factor analysis...... the deficits in communication. Sets of symptoms corresponding to the traditional symptoms in Broca and Wernicke aphasia may be represented in the factors, but the factor itself does not represent a syndrome. It is assumed that this kind of data analysis shows a new approach to the understanding of language...

  7. An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ

    Science.gov (United States)

    Yilmaz, Işik; Marschalko, Marian; Bednarik, Martin

    2013-04-01

    The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.

  8. Modeling of Groundwater Resources Heavy Metals Concentration Using Soft Computing Methods: Application of Different Types of Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Meysam Alizamir

    2017-09-01

    Full Text Available Nowadays, groundwater resources play a vital role as a source of drinking water in arid and semiarid regions and forecasting of pollutants content in these resources is very important. Therefore, this study aimed to compare two soft computing methods for modeling Cd, Pb and Zn concentration in groundwater resources of Asadabad Plain, Western Iran. The relative accuracy of several soft computing models, namely multi-layer perceptron (MLP and radial basis function (RBF for forecasting of heavy metals concentration have been investigated. In addition, Levenberg-Marquardt, gradient descent and conjugate gradient training algorithms were utilized for the MLP models. The ANN models for this study were developed using MATLAB R 2014 Software program. The MLP performs better than the other models for heavy metals concentration estimation. The simulation results revealed that MLP model was able to model heavy metals concentration in groundwater resources favorably. It generally is effectively utilized in environmental applications and in the water quality estimations. In addition, out of three algorithms, Levenberg-Marquardt was better than the others were. This study proposed soft computing modeling techniques for the prediction and estimation of heavy metals concentration in groundwater resources of Asadabad Plain. Based on collected data from the plain, MLP and RBF models were developed for each heavy metal. MLP can be utilized effectively in applications of prediction of heavy metals concentration in groundwater resources of Asadabad Plain.

  9. Computed Tomography and Magnetic Resonance Imaging of Myoepitheliloma in the Soft Palate: A Case Report

    International Nuclear Information System (INIS)

    Lim, Hun Cheol; Yu, In Kyu; Park, Mi Ja; Jang, Dong Sik

    2011-01-01

    We report the appearance of myoepithelioma arising from minor salivary glands in the soft palate observed on computed tomography (CT) and magnetic resonance imaging (MRI). CT, the tumor was round with a smooth and partial lobulating contour, and slightly marginal contrast enhancement. On T1-weighted images, the mass had heterogeneous iso-signal intensity compared to the pharyngeal muscle. Additionally, the tumor had heterogeneously high T2 signal intensity with heterogeneously strong enhancement on the Gd-enhanced T1-weighted image. Radiologists should consider myoepithelioma in the radiological differential diagnosis of soft palate tumors.

  10. 3D-SoftChip: A Novel Architecture for Next-Generation Adaptive Computing Systems

    Directory of Open Access Journals (Sweden)

    Lee Mike Myung-Ok

    2006-01-01

    Full Text Available This paper introduces a novel architecture for next-generation adaptive computing systems, which we term 3D-SoftChip. The 3D-SoftChip is a 3-dimensional (3D vertically integrated adaptive computing system combining state-of-the-art processing and 3D interconnection technology. It comprises the vertical integration of two chips (a configurable array processor and an intelligent configurable switch through an indium bump interconnection array (IBIA. The configurable array processor (CAP is an array of heterogeneous processing elements (PEs, while the intelligent configurable switch (ICS comprises a switch block, 32-bit dedicated RISC processor for control, on-chip program/data memory, data frame buffer, along with a direct memory access (DMA controller. This paper introduces the novel 3D-SoftChip architecture for real-time communication and multimedia signal processing as a next-generation computing system. The paper further describes the advanced HW/SW codesign and verification methodology, including high-level system modeling of the 3D-SoftChip using SystemC, being used to determine the optimum hardware specification in the early design stage.

  11. Applications of soft computing in time series forecasting simulation and modeling techniques

    CERN Document Server

    Singh, Pritpal

    2016-01-01

    This book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and governmen...

  12. Spintronics-based computing

    CERN Document Server

    Prenat, Guillaume

    2015-01-01

    This book provides a comprehensive introduction to spintronics-based computing for the next generation of ultra-low power/highly reliable logic, which is widely considered a promising candidate to replace conventional, pure CMOS-based logic. It will cover aspects from device to system-level, including magnetic memory cells, device modeling, hybrid circuit structure, design methodology, CAD tools, and technological integration methods. This book is accessible to a variety of readers and little or no background in magnetism and spin electronics are required to understand its content.  The multidisciplinary team of expert authors from circuits, devices, computer architecture, CAD and system design reveal to readers the potential of spintronics nanodevices to reduce power consumption, improve reliability and enable new functionality.  .

  13. Soft biometrics in conjunction with optics based biohashing

    Science.gov (United States)

    Saini, Nirmala; Sinha, Aloka

    2011-02-01

    Biometric systems are gaining importance because of increased reliability for authentication and identification. A biometric recognition technique has been proposed earlier, in which biohashing code has been generated by using a joint transform correlator. The main drawback of the base biohashing method is the low performance of the technique when an "impostor" steals the pseudo-random numbers of the genuine and tries to authenticate as genuine. In the proposed technique, soft biometrics of the same person has been used to improve the discrimination between the genuine and the impostor populations. The soft biometrics are those characteristics that provide some information about the individual, but lack the distinctiveness and permanence to sufficiently differentiate between any two individuals. In the enrolment process, biohash code of the target face images has been integrated with the different soft biometrics of the same person. The obtained code has been stored for verification. In the verification process, biohash code of the face image to be verified is again diffused with the soft biometric of the person. The obtained code is matched with the stored code of the target. The receiving operating characteristic (ROC) curve and the equal error rate (EER) have been used to evaluate the performance of the technique. A detailed study has been carried out to find out the optimum values of the weighting factor for the diffusion process.

  14. Multi-Attribute Decision-Making Method Based on Neutrosophic Soft Rough Information

    Directory of Open Access Journals (Sweden)

    Muhammad Akram

    2018-03-01

    Full Text Available Soft sets (SSs, neutrosophic sets (NSs, and rough sets (RSs are different mathematical models for handling uncertainties, but they are mutually related. In this research paper, we introduce the notions of soft rough neutrosophic sets (SRNSs and neutrosophic soft rough sets (NSRSs as hybrid models for soft computing. We describe a mathematical approach to handle decision-making problems in view of NSRSs. We also present an efficient algorithm of our proposed hybrid model to solve decision-making problems.

  15. Clinical usefulness of facial soft tissues thickness measurement using 3D computed tomographic images

    International Nuclear Information System (INIS)

    Jeong, Ho Gul; Kim, Kee Deog; Hu, Kyung Seok; Lee, Jae Bum; Park, Hyok; Han, Seung Ho; Choi, Seong Ho; Kim, Chong Kwan; Park, Chang Seo

    2006-01-01

    To evaluate clinical usefulness of facial soft tissue thickness measurement using 3D computed tomographic images. One cadaver that had sound facial soft tissues was chosen for the study. The cadaver was scanned with a Helical CT under following scanning protocols about slice thickness and table speed: 3 mm and 3 mm/sec, 5 mm and 5 mm/sec, 7 mm and 7 mm/sec. The acquired data were reconstructed 1.5, 2.5, 3.5 mm reconstruction interval respectively and the images were transferred to a personal computer. Using a program developed to measure facial soft tissue thickness in 3D image, the facial soft tissue thickness was measured. After the ten-time repeation of the measurement for ten times, repeated measure analysis of variance (ANOVA) was adopted to compare and analyze the measurements using the three scanning protocols. Comparison according to the areas was analysed by Mann-Whitney test. There were no statistically significant intraobserver differences in the measurements of the facial soft tissue thickness using the three scanning protocols (p>0.05). There were no statistically significant differences between measurements in the 3 mm slice thickness and those in the 5 mm, 7 mm slice thickness (p>0.05). There were statistical differences in the 14 of the total 30 measured points in the 5 mm slice thickness and 22 in the 7 mm slice thickness. The facial soft tissue thickness measurement using 3D images of 7 mm slice thickness is acceptable clinically, but those of 5 mm slice thickness is recommended for the more accurate measurement

  16. Development of fuzzy air quality index using soft computing approach.

    Science.gov (United States)

    Mandal, T; Gorai, A K; Pathak, G

    2012-10-01

    Proper assessment of air quality status in an atmosphere based on limited observations is an essential task for meeting the goals of environmental management. A number of classification methods are available for estimating the changing status of air quality. However, a discrepancy frequently arises from the quality criteria of air employed and vagueness or fuzziness embedded in the decision making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies like air quality index when describing integrated air quality conditions with respect to various pollutants parameters and time of exposure. In recent years, the fuzzy logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental issues. In the present study, a methodology based on fuzzy inference systems (FIS) to assess air quality is proposed. This paper presents a comparative study to assess status of air quality using fuzzy logic technique and that of conventional technique. The findings clearly indicate that the FIS may successfully harmonize inherent discrepancies and interpret complex conditions.

  17. Detection of Failure in Asynchronous Motor Using Soft Computing Method

    Science.gov (United States)

    Vinoth Kumar, K.; Sony, Kevin; Achenkunju John, Alan; Kuriakose, Anto; John, Ano P.

    2018-04-01

    This paper investigates the stator short winding failure of asynchronous motor also their effects on motor current spectrums. A fuzzy logic approach i.e., model based technique possibly will help to detect the asynchronous motor failure. Actually, fuzzy logic similar to humanoid intelligent methods besides expected linguistic empowering inferences through vague statistics. The dynamic model is technologically advanced for asynchronous motor by means of fuzzy logic classifier towards investigate the stator inter turn failure in addition open phase failure. A hardware implementation was carried out with LabVIEW for the online-monitoring of faults.

  18. Soft computing simulation tools for nuclear energy systems

    International Nuclear Information System (INIS)

    Kannan Balasubramanian, S.

    2012-01-01

    This chapter deals with simulation, a very powerful tool in designing, constructing and operating nuclear power generating facilities. There are very different types of power plants, and the examples mentioned in this chapter originate from experience with water cooled and water moderated thermal reactors, based on fission of uranium-235. Nevertheless, the methodological achievements in simulation mentioned below can definitely be used not only for this particular type of nuclear power generating reactor. Simulation means: investigation of processes in the time domain. We can calculate the characteristics and properties of different systems, e.g. we can design a bridge over a river, but if we calculate how it would respond to a thunderstorm with high winds, its movement can or can not evolve after a certain time into destructive oscillation - this type of calculations are called simulation

  19. A Hybrid Soft Computing Approach for Subset Problems

    Directory of Open Access Journals (Sweden)

    Broderick Crawford

    2013-01-01

    Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.

  20. Pattern recognition algorithms for data mining scalability, knowledge discovery and soft granular computing

    CERN Document Server

    Pal, Sankar K

    2004-01-01

    Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

  1. Soft drink effects on sensorimotor rhythm brain computer interface performance and resting-state spectral power.

    Science.gov (United States)

    Mundahl, John; Jianjun Meng; He, Jeffrey; Bin He

    2016-08-01

    Brain-computer interface (BCI) systems allow users to directly control computers and other machines by modulating their brain waves. In the present study, we investigated the effect of soft drinks on resting state (RS) EEG signals and BCI control. Eight healthy human volunteers each participated in three sessions of BCI cursor tasks and resting state EEG. During each session, the subjects drank an unlabeled soft drink with either sugar, caffeine, or neither ingredient. A comparison of resting state spectral power shows a substantial decrease in alpha and beta power after caffeine consumption relative to control. Despite attenuation of the frequency range used for the control signal, caffeine average BCI performance was the same as control. Our work provides a useful characterization of caffeine, the world's most popular stimulant, on brain signal frequencies and their effect on BCI performance.

  2. Claudio Moraga a passion for multi-valued logic and soft computing

    CERN Document Server

    Allende-Cid, Héctor

    2017-01-01

    The book is an authoritative collection of contributions by leading experts on the topics of fuzzy logic, multi-valued logic and neural network. Originally written as an homage to Claudio Moraga, seen by his colleagues as an example of concentration, discipline and passion for science, the book also represents a timely reference guide for advance students and researchers in the field of soft computing, and multiple-valued logic. .

  3. On an LAS-integrated soft PLC system based on WorldFIP fieldbus.

    Science.gov (United States)

    Liang, Geng; Li, Zhijun; Li, Wen; Bai, Yan

    2012-01-01

    Communication efficiency is lowered and real-time performance is not good enough in discrete control based on traditional WorldFIP field intelligent nodes in case that the scale of control in field is large. A soft PLC system based on WorldFIP fieldbus was designed and implemented. Link Activity Scheduler (LAS) was integrated into the system and field intelligent I/O modules acted as networked basic nodes. Discrete control logic was implemented with the LAS-integrated soft PLC system. The proposed system was composed of configuration and supervisory sub-systems and running sub-systems. The configuration and supervisory sub-system was implemented with a personal computer or an industrial personal computer; running subsystems were designed and implemented based on embedded hardware and software systems. Communication and schedule in the running subsystem was implemented with an embedded sub-module; discrete control and system self-diagnosis were implemented with another embedded sub-module. Structure of the proposed system was presented. Methodology for the design of the sub-systems was expounded. Experiments were carried out to evaluate the performance of the proposed system both in discrete and process control by investigating the effect of network data transmission delay induced by the soft PLC in WorldFIP network and CPU workload on resulting control performances. The experimental observations indicated that the proposed system is practically applicable. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Inference of Cancer-specific Gene Regulatory Networks Using Soft Computing Rules

    Directory of Open Access Journals (Sweden)

    Xiaosheng Wang

    2010-03-01

    Full Text Available Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

  5. Inference of cancer-specific gene regulatory networks using soft computing rules.

    Science.gov (United States)

    Wang, Xiaosheng; Gotoh, Osamu

    2010-03-24

    Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

  6. Monitoring the Microgravity Environment Quality On-Board the International Space Station Using Soft Computing Techniques

    Science.gov (United States)

    Jules, Kenol; Lin, Paul P.

    2001-01-01

    This paper presents an artificial intelligence monitoring system developed by the NASA Glenn Principal Investigator Microgravity Services project to help the principal investigator teams identify the primary vibratory disturbance sources that are active, at any moment in time, on-board the International Space Station, which might impact the microgravity environment their experiments are exposed to. From the Principal Investigator Microgravity Services' web site, the principal investigator teams can monitor via a graphical display, in near real time, which event(s) is/are on, such as crew activities, pumps, fans, centrifuges, compressor, crew exercise, platform structural modes, etc., and decide whether or not to run their experiments based on the acceleration environment associated with a specific event. This monitoring system is focused primarily on detecting the vibratory disturbance sources, but could be used as well to detect some of the transient disturbance sources, depending on the events duration. The system has built-in capability to detect both known and unknown vibratory disturbance sources. Several soft computing techniques such as Kohonen's Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

  7. Development of Semi-Automatic Lathe by using Intelligent Soft Computing Technique

    Science.gov (United States)

    Sakthi, S.; Niresh, J.; Vignesh, K.; Anand Raj, G.

    2018-03-01

    This paper discusses the enhancement of conventional lathe machine to semi-automated lathe machine by implementing a soft computing method. In the present scenario, lathe machine plays a vital role in the engineering division of manufacturing industry. While the manual lathe machines are economical, the accuracy and efficiency are not up to the mark. On the other hand, CNC machine provide the desired accuracy and efficiency, but requires a huge capital. In order to over come this situation, a semi-automated approach towards the conventional lathe machine is developed by employing stepper motors to the horizontal and vertical drive, that can be controlled by Arduino UNO -microcontroller. Based on the input parameters of the lathe operation the arduino coding is been generated and transferred to the UNO board. Thus upgrading from manual to semi-automatic lathe machines can significantly increase the accuracy and efficiency while, at the same time, keeping a check on investment cost and consequently provide a much needed escalation to the manufacturing industry.

  8. Soft computing approach for reliability optimization: State-of-the-art survey

    International Nuclear Information System (INIS)

    Gen, Mitsuo; Yun, Young Su

    2006-01-01

    In the broadest sense, reliability is a measure of performance of systems. As systems have grown more complex, the consequences of their unreliable behavior have become severe in terms of cost, effort, lives, etc., and the interest in assessing system reliability and the need for improving the reliability of products and systems have become very important. Most solution methods for reliability optimization assume that systems have redundancy components in series and/or parallel systems and alternative designs are available. Reliability optimization problems concentrate on optimal allocation of redundancy components and optimal selection of alternative designs to meet system requirement. In the past two decades, numerous reliability optimization techniques have been proposed. Generally, these techniques can be classified as linear programming, dynamic programming, integer programming, geometric programming, heuristic method, Lagrangean multiplier method and so on. A Genetic Algorithm (GA), as a soft computing approach, is a powerful tool for solving various reliability optimization problems. In this paper, we briefly survey GA-based approach for various reliability optimization problems, such as reliability optimization of redundant system, reliability optimization with alternative design, reliability optimization with time-dependent reliability, reliability optimization with interval coefficients, bicriteria reliability optimization, and reliability optimization with fuzzy goals. We also introduce the hybrid approaches for combining GA with fuzzy logic, neural network and other conventional search techniques. Finally, we have some experiments with an example of various reliability optimization problems using hybrid GA approach

  9. A Reconfigurable Omnidirectional Soft Robot Based on Caterpillar Locomotion.

    Science.gov (United States)

    Zou, Jun; Lin, Yangqiao; Ji, Chen; Yang, Huayong

    2018-04-01

    A pneumatically powered, reconfigurable omnidirectional soft robot based on caterpillar locomotion is described. The robot is composed of nine modules arranged as a three by three matrix and the length of this matrix is 154 mm. The robot propagates a traveling wave inspired by caterpillar locomotion, and it has all three degrees of freedom on a plane (X, Y, and rotation). The speed of the robot is about 18.5 m/h (two body lengths per minute) and it can rotate at a speed of 1.63°/s. The modules have neodymium-iron-boron (NdFeB) magnets embedded and can be easily replaced or combined into other configurations. Two different configurations are presented to demonstrate the possibilities of the modular structure: (1) by removing some modules, the omnidirectional robot can be reassembled into a form that can crawl in a pipe and (2) two omnidirectional robots can crawl close to each other and be assembled automatically into a bigger omnidirectional robot. Omnidirectional motion is important for soft robots to explore unstructured environments. The modular structure gives the soft robot the ability to cope with the challenges of different environments and tasks.

  10. Computed tomography of the soft tissues of the shoulder. Pt. 3

    International Nuclear Information System (INIS)

    Dihlmann, W.; Bandick, J.

    1988-01-01

    Computed tomography of the soft tissue of the shoulder in cases of calcifying tendinitis of the rotator cuff provides the following information: 1. Localisation of the calcium deposits within the rotator cuff. 2. Contours and density of the calcium deposits correlated with the clinical findings as described by Uhthoff et al. Ill-defined contours and non-homogeneous deposits are associated with more severe clinical features. 3. Computed tomography shows that apatite particles, which are not visible radiologically, may penetrate into the shoulder joint and produce synovitis with an effusion. This is of importance in local therapy. (orig.) [de

  11. Risk assessment through drinking water pathway via uncertainty modeling of contaminant transport using soft computing

    International Nuclear Information System (INIS)

    Datta, D.; Ranade, A.K.; Pandey, M.; Sathyabama, N.; Kumar, Brij

    2012-01-01

    The basic objective of an environmental impact assessment (EIA) is to build guidelines to reduce the associated risk or mitigate the consequences of the reactor accident at its source to prevent deterministic health effects, to reduce the risk of stochastic health effects (eg. cancer and severe hereditary effects) as much as reasonable achievable by implementing protective actions in accordance with IAEA guidance (IAEA Safety Series No. 115, 1996). The measure of exposure being the basic tool to take any appropriate decisions related to risk reduction, EIA is traditionally expressed in terms of radiation exposure to the member of the public. However, models used to estimate the exposure received by the member of the public are governed by parameters some of which are deterministic with relative uncertainty and some of which are stochastic as well as imprecise (insufficient knowledge). In an admixture environment of this type, it is essential to assess the uncertainty of a model to estimate the bounds of the exposure to the public to invoke a decision during an event of nuclear or radiological emergency. With a view to this soft computing technique such as evidence theory based assessment of model parameters is addressed to compute the risk or exposure to the member of the public. The possible pathway of exposure to the member of the public in the aquatic food stream is the drinking of water. Accordingly, this paper presents the uncertainty analysis of exposure via uncertainty analysis of the contaminated water. Evidence theory finally addresses the uncertainty in terms of lower bound as belief measure and upper bound of exposure as plausibility measure. In this work EIA is presented using evidence theory. Data fusion technique is used to aggregate the knowledge on the uncertain information. Uncertainty of concentration and exposure is expressed as an interval of belief, plausibility

  12. Computation of stress on the surface of a soft homogeneous arbitrarily shaped particle.

    Science.gov (United States)

    Yang, Minglin; Ren, Kuan Fang; Wu, Yueqian; Sheng, Xinqing

    2014-04-01

    Prediction of the stress on the surface of an arbitrarily shaped particle of soft material is essential in the study of elastic properties of the particles with optical force. It is also necessary in the manipulation and sorting of small particles with optical tweezers, since a regular-shaped particle, such as a sphere, may be deformed under the nonuniform optical stress on its surface. The stress profile on a spherical or small spheroidal soft particle trapped by shaped beams has been studied, however little work on computing the surface stress of an irregular-shaped particle has been reported. We apply in this paper the surface integral equation with multilevel fast multipole algorithm to compute the surface stress on soft homogeneous arbitrarily shaped particles. The comparison of the computed stress profile with that predicted by the generalized Lorenz-Mie theory for a water droplet of diameter equal to 51 wavelengths in a focused Gaussian beam show that the precision of our method is very good. Then stress profiles on spheroids with different aspect ratios are computed. The particles are illuminated by a Gaussian beam of different waist radius at different incidences. Physical analysis on the mechanism of optical stress is given with help of our recently developed vectorial complex ray model. It is found that the maximum of the stress profile on the surface of prolate spheroids is not only determined by the reflected and refracted rays (orders p=0,1) but also the rays undergoing one or two internal reflections where they focus. Computational study of stress on surface of a biconcave cell-like particle, which is a typical application in life science, is also undertaken.

  13. MRT letter: Contrast-enhanced computed tomographic imaging of soft callus formation in fracture healing.

    Science.gov (United States)

    Hayward, Lauren Nicole Miller; de Bakker, Chantal Marie-Jeanne; Lusic, Hrvoje; Gerstenfeld, Louis Charles; Grinstaff, Mark W; Morgan, Elise Feng-I

    2012-01-01

    Formation of a cartilaginous soft callus at the site of a bone fracture is a pivotal stage in the healing process. Noninvasive, or even nondestructive, imaging of soft callus formation can be an important tool in experimental and pre-clinical studies of fracture repair. However, the low X-ray attenuation of cartilage renders the soft callus nearly invisible in radiographs. This study utilized a recently developed, cationic, iodinated contrast agent in conjunction with micro-computed tomography to identify cartilage in fracture calluses in the femora of C57BL/6J and C3H/HeJ mice. Fracture calluses were scanned before and after incubation in the contrast agent. The set of pre-incubation images was registered against and then subtracted from the set of post-incubation images, resulting in a three-dimensional map of the locations of cartilage in the callus, as labeled by the contrast agent. This map was then compared to histology from a previous study. The results showed that the locations where the contrast agent collected in relatively high concentrations were similar to those of the cartilage. The contrast agent also identified a significant difference between the two strains of mice in the percentage of the callus occupied by cartilage, indicating that this method of contrast-enhanced computed tomography may be an effective technique for nondestructive, early evaluation of fracture healing. Copyright © 2011 Wiley Periodicals, Inc.

  14. A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling.

    Science.gov (United States)

    Knoops, Paul G M; Borghi, Alessandro; Ruggiero, Federica; Badiali, Giovanni; Bianchi, Alberto; Marchetti, Claudio; Rodriguez-Florez, Naiara; Breakey, Richard W F; Jeelani, Owase; Dunaway, David J; Schievano, Silvia

    2018-01-01

    Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the response of the soft tissue to the changes to the underlying skeleton. The clinical use of commercial prediction software remains controversial, likely due to the deterministic nature of these computational predictions. A novel probabilistic finite element model (FEM) for the prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM was developed and validated on a cohort of eight patients who underwent maxillary repositioning and had pre- and postoperative cone beam computed tomography (CBCT) scans taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a design of experiments (DOE) provided a range of potential outcomes based on uniformly distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration provided optimised predictions with a probability range. A range of 3D predictions was obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately include the true postoperative position, whereas the prediction under-estimates the position of the cheeks and lower lip. A probabilistic FEM has been developed and validated for the prediction of the facial appearance following orthognathic surgery. This method shows how inaccuracies in the modelling and uncertainties in executing surgical planning influence the soft tissue prediction and it provides a range of predictions including a minimum and maximum, which may be helpful for patients in understanding the impact of surgery on the face.

  15. Soft-error tolerance and energy consumption evaluation of embedded computer with magnetic random access memory in practical systems using computer simulations

    Science.gov (United States)

    Nebashi, Ryusuke; Sakimura, Noboru; Sugibayashi, Tadahiko

    2017-08-01

    We evaluated the soft-error tolerance and energy consumption of an embedded computer with magnetic random access memory (MRAM) using two computer simulators. One is a central processing unit (CPU) simulator of a typical embedded computer system. We simulated the radiation-induced single-event-upset (SEU) probability in a spin-transfer-torque MRAM cell and also the failure rate of a typical embedded computer due to its main memory SEU error. The other is a delay tolerant network (DTN) system simulator. It simulates the power dissipation of wireless sensor network nodes of the system using a revised CPU simulator and a network simulator. We demonstrated that the SEU effect on the embedded computer with 1 Gbit MRAM-based working memory is less than 1 failure in time (FIT). We also demonstrated that the energy consumption of the DTN sensor node with MRAM-based working memory can be reduced to 1/11. These results indicate that MRAM-based working memory enhances the disaster tolerance of embedded computers.

  16. Soft computing analysis of the possible correlation between temporal and energy release patterns in seismic activity

    Science.gov (United States)

    Konstantaras, Anthony; Katsifarakis, Emmanouil; Artzouxaltzis, Xristos; Makris, John; Vallianatos, Filippos; Varley, Martin

    2010-05-01

    Ben-Zion Y.: ‘Techniques and parameters to analyze seismicity patterns associated with large earthquakes', Geophysics Res., vol. 102, pp. 17785-17795, 1997a [3] Habermann R. E.: ‘Precursory seismic quiescence: past, present and future', Pure Applied Geophysics, vol. 126, pp. 279-318, 1988 [4] Matthews M. V. and Reasenberg P. A.: ‘Statistical methods for investigating quiescence and other temporal seismicity patterns', Pure Applied Geophysics, vol. 126, pp. 357-372, 1988 [5] Zubkov S. I.: ‘The appearance times of earthquake precursors', Izv. Akad. Nauk SSSR Fiz. Zemli (Solid Earth), No. 5, pp. 87-91, 1987 [6] Dobrovolsky I. P., Zubkov S. I. and Miachkin V. I.: ‘Estimation of the size of earthquake preparation zones', Pageoph, vol. 117, pp. 1025-1044, 1979 [7] Dobrovolsky I. P., Gershenzon N. I. And Gokhberg M. B.: ‘Theory of electrokinetic effects occurring at the final stage in the preparation of a tectonic earthquake', Physics of the Earth and Planetary Interiors, vol. 57, pp. 144-156, 1989 [8] Richter C. F.: ‘Elementary Seismology', W.H.Freeman and Co., San Francisco, 1958 [9] Choy G. L. and Boatwright J. L.: ‘Global patterns of radiated seismic energy and apparent stress', Journal of Geophysical Research, vol. 84 (B5), pp. 2348-2350, 1995 [10] Haykin S.: ‘Neural Networks', 2nd Edition, Prentice Hall, 1999 [11] Jang J., Sun T. and Mizutany E.: ‘Neuro-fuzzy and soft computing', Prentice Hall, Upper Saddle River, NJ, 1997 [12] Konstantaras A., Varley M.R., Vallianatos F., Collins G. and Holifield P.: ‘Detection of weak seismo-electric signals upon the recordings of the electrotelluric field by means of neuron-fuzzy technology', IEEE Geoscience and Remote Sensing Letters, vol. 4 (1), 2007 [13] Konstantaras A., Varley M.R., Vallianatos F., Collins G. and Holifield P.: ‘Neuro-fuzzy prediction-based adaptive filtering applied to severely distorted magnetic field recordings', IEEE Geoscience and Remote Sensing Letters, vol. 3 (4), 2006 [14

  17. Computed tomography in the evaluation of soft tissue tumors. Report in 124 cases

    Energy Technology Data Exchange (ETDEWEB)

    Torricelli, P; Calo, M; Boriani, S; De Santis, G

    1986-01-01

    In order to evaluate the role of Computed Tomography (CT) in prediction of nature, staging and follow-up of soft-tessue tumors, the authors examined by CT 124 patients with soft tissue neoplasms who later underwent surgery (116 cases) or fine needle biopsy (8 cases). Comparison between CT and surgical or anatomical results showed that CT was able to correctly predict the benignancy or malignancy of the masses in 76% of cases but it was very seldom able to allow an hystological prediction. On the contrary CT was found to be a very useful tool for pre-therapeutic staging and follow-up of the tumors, because it gave many diagnostic information which influenced therapeutic choiches and strategies. 39 refs.

  18. Soft Electronics Enabled Ergonomic Human-Computer Interaction for Swallowing Training

    Science.gov (United States)

    Lee, Yongkuk; Nicholls, Benjamin; Sup Lee, Dong; Chen, Yanfei; Chun, Youngjae; Siang Ang, Chee; Yeo, Woon-Hong

    2017-04-01

    We introduce a skin-friendly electronic system that enables human-computer interaction (HCI) for swallowing training in dysphagia rehabilitation. For an ergonomic HCI, we utilize a soft, highly compliant (“skin-like”) electrode, which addresses critical issues of an existing rigid and planar electrode combined with a problematic conductive electrolyte and adhesive pad. The skin-like electrode offers a highly conformal, user-comfortable interaction with the skin for long-term wearable, high-fidelity recording of swallowing electromyograms on the chin. Mechanics modeling and experimental quantification captures the ultra-elastic mechanical characteristics of an open mesh microstructured sensor, conjugated with an elastomeric membrane. Systematic in vivo studies investigate the functionality of the soft electronics for HCI-enabled swallowing training, which includes the application of a biofeedback system to detect swallowing behavior. The collection of results demonstrates clinical feasibility of the ergonomic electronics in HCI-driven rehabilitation for patients with swallowing disorders.

  19. In vivo X-Ray Computed Tomographic Imaging of Soft Tissue with Native, Intravenous, or Oral Contrast

    Science.gov (United States)

    Wathen, Connor A.; Foje, Nathan; van Avermaete, Tony; Miramontes, Bernadette; Chapaman, Sarah E.; Sasser, Todd A.; Kannan, Raghuraman; Gerstler, Steven; Leevy, W. Matthew

    2013-01-01

    X-ray Computed Tomography (CT) is one of the most commonly utilized anatomical imaging modalities for both research and clinical purposes. CT combines high-resolution, three-dimensional data with relatively fast acquisition to provide a solid platform for non-invasive human or specimen imaging. The primary limitation of CT is its inability to distinguish many soft tissues based on native contrast. While bone has high contrast within a CT image due to its material density from calcium phosphate, soft tissue is less dense and many are homogenous in density. This presents a challenge in distinguishing one type of soft tissue from another. A couple exceptions include the lungs as well as fat, both of which have unique densities owing to the presence of air or bulk hydrocarbons, respectively. In order to facilitate X-ray CT imaging of other structures, a range of contrast agents have been developed to selectively identify and visualize the anatomical properties of individual tissues. Most agents incorporate atoms like iodine, gold, or barium because of their ability to absorb X-rays, and thus impart contrast to a given organ system. Here we review the strategies available to visualize lung, fat, brain, kidney, liver, spleen, vasculature, gastrointestinal tract, and liver tissues of living mice using either innate contrast, or commercial injectable or ingestible agents with selective perfusion. Further, we demonstrate how each of these approaches will facilitate the non-invasive, longitudinal, in vivo imaging of pre-clinical disease models at each anatomical site. PMID:23711461

  20. COGNITIVE COMPUTER GRAPHICS AS A MEANS OF "SOFT" MODELING IN PROBLEMS OF RESTORATION OF FUNCTIONS OF TWO VARIABLES

    Directory of Open Access Journals (Sweden)

    A.N. Khomchenko

    2016-08-01

    Full Text Available The paper considers the problem of bi-cubic interpolation on the final element of serendipity family. With cognitive-graphical analysis the rigid model of Ergatoudis, Irons and Zenkevich (1968 compared with alternative models, obtained by the methods: direct geometric design, a weighted averaging of the basis polynomials, systematic generation of bases (advanced Taylor procedure. The emphasis is placed on the phenomenon of "gravitational repulsion" (Zenkevich paradox. The causes of rising of inadequate physical spectra nodal loads on serendipity elements of higher orders are investigated. Soft modeling allows us to build a lot of serendipity elements of bicubic interpolation, and you do not even need to know the exact form of the rigid model. The different interpretations of integral characteristics of the basis polynomials: geometrical, physical, probability are offered. Under the soft model in the theory of interpolation of function of two variables implies the model amenable to change through the choice of basis. Such changes in the family of Lagrangian finite elements of higher orders are excluded (hard simulation. Standard models of serendipity family (Zenkevich were also tough. It was found that the "responsibility" for the rigidity of serendipity model rests on ruled surfaces (zero Gaussian curvature - conoids that predominate in the base set. Cognitive portraits zero lines of standard serendipity surfaces suggested that in order to "mitigate" of serendipity pattern conoid should better be replaced by surfaces of alternating Gaussian curvature. The article shows the alternative (soft bases of serendipity models. The work is devoted to solving scientific and technological problems aimed at the creation, dissemination and use of cognitive computer graphics in teaching and learning. The results are of interest to students of specialties: "Computer Science and Information Technologies", "System Analysis", "Software Engineering", as well as

  1. A program to compute the soft Robinson-Foulds distance between phylogenetic networks.

    Science.gov (United States)

    Lu, Bingxin; Zhang, Louxin; Leong, Hon Wai

    2017-03-14

    Over the past two decades, phylogenetic networks have been studied to model reticulate evolutionary events. The relationships among phylogenetic networks, phylogenetic trees and clusters serve as the basis for reconstruction and comparison of phylogenetic networks. To understand these relationships, two problems are raised: the tree containment problem, which asks whether a phylogenetic tree is displayed in a phylogenetic network, and the cluster containment problem, which asks whether a cluster is represented at a node in a phylogenetic network. Both the problems are NP-complete. A fast exponential-time algorithm for the cluster containment problem on arbitrary networks is developed and implemented in C. The resulting program is further extended into a computer program for fast computation of the Soft Robinson-Foulds distance between phylogenetic networks. Two computer programs are developed for facilitating reconstruction and validation of phylogenetic network models in evolutionary and comparative genomics. Our simulation tests indicated that they are fast enough for use in practice. Additionally, the distribution of the Soft Robinson-Foulds distance between phylogenetic networks is demonstrated to be unlikely normal by our simulation data.

  2. Image Analysis via Soft Computing: Prototype Applications at NASA KSC and Product Commercialization

    Science.gov (United States)

    Dominguez, Jesus A.; Klinko, Steve

    2011-01-01

    This slide presentation reviews the use of "soft computing" which differs from "hard computing" in that it is more tolerant of imprecision, partial truth, uncertainty, and approximation and its use in image analysis. Soft computing provides flexible information processing to handle real life ambiguous situations and achieve tractability, robustness low solution cost, and a closer resemblance to human decision making. Several systems are or have been developed: Fuzzy Reasoning Edge Detection (FRED), Fuzzy Reasoning Adaptive Thresholding (FRAT), Image enhancement techniques, and visual/pattern recognition. These systems are compared with examples that show the effectiveness of each. NASA applications that are reviewed are: Real-Time (RT) Anomaly Detection, Real-Time (RT) Moving Debris Detection and the Columbia Investigation. The RT anomaly detection reviewed the case of a damaged cable for the emergency egress system. The use of these techniques is further illustrated in the Columbia investigation with the location and detection of Foam debris. There are several applications in commercial usage: image enhancement, human screening and privacy protection, visual inspection, 3D heart visualization, tumor detections and x ray image enhancement.

  3. Computed tomography in soft-tissue lesions of the hand and forearm

    International Nuclear Information System (INIS)

    Schmitt, R.; Warmuth-Metz, M.; Lucas, D.; Feyerabend, T.; Schindler, G.; Lanz, U.

    1990-01-01

    Computed tomography was carried out in 32 patients with clinically equivocal soft-tissue lesions of the hand (24 times) and forearm (8 times). The CT scans were performed with the patients in standard positions; thin slices and zoom technique were used. All soft-tissue tumors were correctly diagnosed with regard to localization, size and infiltration of the surrounding tissue. The histological diagnosis was correct in tendon-sheath proliferations, deposits caused by metabolic disorders, epithelial and ganglion cysts, hemangiomas, lipomas and in one schwannoma. A malignancy was suspected and was proven to be correct in two cases. False-positive diagnoses of a malignant soft-tissue tumor were made in one case of an aggressive fibromatosis, in a rapidly progressive, ossifying myositis, and three times in the presence of postoperative scar tissue following the resection of a sarcoma. Finally, a case of proliferative myositis regarded as semimalignant was underrated by CT. The hand surgeon considered CT diagnostics to be very helpful in planning operations in an anatomically complex organ such as the hand. (orig.) [de

  4. Rough set soft computing cancer classification and network: one stone, two birds.

    Science.gov (United States)

    Zhang, Yue

    2010-07-15

    Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

  5. Speed challenge: a case for hardware implementation in soft-computing

    Science.gov (United States)

    Daud, T.; Stoica, A.; Duong, T.; Keymeulen, D.; Zebulum, R.; Thomas, T.; Thakoor, A.

    2000-01-01

    For over a decade, JPL has been actively involved in soft computing research on theory, architecture, applications, and electronics hardware. The driving force in all our research activities, in addition to the potential enabling technology promise, has been creation of a niche that imparts orders of magnitude speed advantage by implementation in parallel processing hardware with algorithms made especially suitable for hardware implementation. We review our work on neural networks, fuzzy logic, and evolvable hardware with selected application examples requiring real time response capabilities.

  6. Live theater on a virtual stage: incorporating soft skills and teamwork in computer graphics education.

    Science.gov (United States)

    Schweppe, M; Geigel, J

    2011-01-01

    Industry has increasingly emphasized the need for "soft" or interpersonal skills development and team-building experience in the college curriculum. Here, we discuss our experiences with providing such opportunities via a collaborative project called the Virtual Theater. In this joint project between the Rochester Institute of Technology's School of Design and Department of Computer Science, the goal is to enable live performance in a virtual space with participants in different physical locales. Students work in teams, collaborating with other students in and out of their disciplines.

  7. Soft Sensor Modeling Based on Multiple Gaussian Process Regression and Fuzzy C-mean Clustering

    Directory of Open Access Journals (Sweden)

    Xianglin ZHU

    2014-06-01

    Full Text Available In order to overcome the difficulties of online measurement of some crucial biochemical variables in fermentation processes, a new soft sensor modeling method is presented based on the Gaussian process regression and fuzzy C-mean clustering. With the consideration that the typical fermentation process can be distributed into 4 phases including lag phase, exponential growth phase, stable phase and dead phase, the training samples are classified into 4 subcategories by using fuzzy C- mean clustering algorithm. For each sub-category, the samples are trained using the Gaussian process regression and the corresponding soft-sensing sub-model is established respectively. For a new sample, the membership between this sample and sub-models are computed based on the Euclidean distance, and then the prediction output of soft sensor is obtained using the weighting sum. Taking the Lysine fermentation as example, the simulation and experiment are carried out and the corresponding results show that the presented method achieves better fitting and generalization ability than radial basis function neutral network and single Gaussian process regression model.

  8. Elucidating the hard/soft acid/base principle: A perspective based on half-reactions

    International Nuclear Information System (INIS)

    Ayers, Paul W.; Parr, Robert G.; Pearson, Ralph G.

    2006-01-01

    A comprehensive analysis is presented for the acid-base double-exchange reaction as well as the associated acid-displacement and base-displacement 'half-reactions' with the goal of elucidating the meaning of the hard/soft acid/base (HSAB) principle and the conditions for its validity. When electron-transfer effects are important and other effects are negligible, the HSAB principle is driven by the surpassing stability of the soft acid/soft base product. When electrostatic effects dominate the reactivity, the HSAB principle is driven by the surpassing stability of the hard acid/hard base product. Because electron-transfer effects favor soft/soft interactions, while electrostatic effects favor hard/hard interactions, acid-base exchange reactions may be used to determine whether a reagent's reactivity is dominated by electron-transfer or by electrostatic effects. Because electron-transfer and electrostatic considerations separately favor the HSAB principle whenever the electronic chemical potentials of the acids and bases involved in the reaction are similar, our analysis provides strong support for the HSAB principle. The electronic chemical potential measures the intrinsic strength of acids and bases

  9. It's Hard Work Learning Soft Skills: Can Client Based Projects Teach the Soft Skills Students Need and Employers Want?

    Science.gov (United States)

    McCale, Christina

    2008-01-01

    The importance of business relevance in academia coupled with an increasingly challenging job market magnifies the importance for students to be better prepared for the marketplace. Client-based projects have been lauded for helping students gain the soft skills employers look for in entry-level employees, but little research supports this…

  10. Computation of integral bases

    NARCIS (Netherlands)

    Bauch, J.H.P.

    2015-01-01

    Let $A$ be a Dedekind domain, $K$ the fraction field of $A$, and $f\\in A[x]$ a monic irreducible separable polynomial. For a given non-zero prime ideal $\\mathfrak{p}$ of $A$ we present in this paper a new method to compute a $\\mathfrak{p}$-integral basis of the extension of $K$ determined by $f$.

  11. Free Software Development. 3. Numerical Description of Soft Acid with Soft Base Titration

    OpenAIRE

    Lorentz JÄNTSCHI; Horea Iustin NAŞCU

    2002-01-01

    The analytical methods of qualitative and quantitative determination of ions in solutions are very flexible to automation. The present work is focus on modeling the process of titration and presents a numerical simulation of acid-base titration. A PHP program to compute all iterations in titration process that solves a 3th rank equation to find value of pH for was built and is available through http internet protocol at the address: http://vl.academicdirect.org/molecular_dynamics/ab_titra...

  12. Optimization of chemical composition in the manufacturing process of flotation balls based on intelligent soft sensing

    Directory of Open Access Journals (Sweden)

    Dučić Nedeljko

    2016-01-01

    Full Text Available This paper presents an application of computational intelligence in modeling and optimization of parameters of two related production processes - ore flotation and production of balls for ore flotation. It is proposed that desired chemical composition of flotation balls (Mn=0.69%; Cr=2.247%; C=3.79%; Si=0.5%, which ensures minimum wear rate (0.47 g/kg during copper milling is determined by combining artificial neural network (ANN and genetic algorithm (GA. Based on the results provided by neuro-genetic combination, a second neural network was derived as an ‘intelligent soft sensor’ in the process of white cast iron production. The proposed ANN 12-16-12-4 model demonstrated favourable prediction capacity, and can be recommended as a ‘intelligent soft sensor’ in the alloying process intended for obtaining favourable chemical composition of white cast iron for production of flotation balls. In the development of intelligent soft sensor data from the two real production processes was used. [Projekat Ministarstva nauke Republike Srbije, br. TR35037 i br. TR35015

  13. Bacterial Infection Potato Tuber Soft Rot Disease Detection Based on Electronic Nose

    Directory of Open Access Journals (Sweden)

    Chang Zhiyong

    2017-11-01

    Full Text Available Soft rot is a severe bacterial disease of potatoes, and soft rot infection can cause significant economic losses during the storage period of potatoes. In this study, potato soft rot was selected as the research object, and a type of potato tuber soft rot disease early detection method based on the electronic nose technology was proposed. An optimized bionic electronic nose gas chamber and a scientific and reasonable sampling device were designed to detect a change in volatile substances of the infected soft rot disease of potato tuber. The infection of soft rot disease in potato tuber samples was detected and identified by using the RBF NN algorithm and SVM algorithm. The results revealed that the proposed bionic electronic nose system can be utilized for early detection of potato tuber soft rot disease. Through comparison and analysis, the recognition rate using the SVM algorithm reached up to 89.7%, and the results were superior to the RBF NN algorithm.

  14. Advanced computer-based training

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, H D; Martin, H D

    1987-05-01

    The paper presents new techniques of computer-based training for personnel of nuclear power plants. Training on full-scope simulators is further increased by use of dedicated computer-based equipment. An interactive communication system runs on a personal computer linked to a video disc; a part-task simulator runs on 32 bit process computers and shows two versions: as functional trainer or as on-line predictor with an interactive learning system (OPAL), which may be well-tailored to a specific nuclear power plant. The common goal of both develoments is the optimization of the cost-benefit ratio for training and equipment.

  15. Advanced computer-based training

    International Nuclear Information System (INIS)

    Fischer, H.D.; Martin, H.D.

    1987-01-01

    The paper presents new techniques of computer-based training for personnel of nuclear power plants. Training on full-scope simulators is further increased by use of dedicated computer-based equipment. An interactive communication system runs on a personal computer linked to a video disc; a part-task simulator runs on 32 bit process computers and shows two versions: as functional trainer or as on-line predictor with an interactive learning system (OPAL), which may be well-tailored to a specific nuclear power plant. The common goal of both develoments is the optimization of the cost-benefit ratio for training and equipment. (orig.) [de

  16. Capability-based computer systems

    CERN Document Server

    Levy, Henry M

    2014-01-01

    Capability-Based Computer Systems focuses on computer programs and their capabilities. The text first elaborates capability- and object-based system concepts, including capability-based systems, object-based approach, and summary. The book then describes early descriptor architectures and explains the Burroughs B5000, Rice University Computer, and Basic Language Machine. The text also focuses on early capability architectures. Dennis and Van Horn's Supervisor; CAL-TSS System; MIT PDP-1 Timesharing System; and Chicago Magic Number Machine are discussed. The book then describes Plessey System 25

  17. Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density

    Science.gov (United States)

    Nooruddin, Hasan A.; Anifowose, Fatai; Abdulraheem, Abdulazeez

    2014-03-01

    Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results.

  18. Use of Soft Computing Technologies for a Qualitative and Reliable Engine Control System for Propulsion Systems

    Science.gov (United States)

    Trevino, Luis; Brown, Terry; Crumbley, R. T. (Technical Monitor)

    2001-01-01

    The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to improve overall vehicle system safety, reliability, and rocket engine performance by development of a qualitative and reliable engine control system (QRECS). Specifically, this will be addressed by enhancing rocket engine control using SCT, innovative data mining tools, and sound software engineering practices used in Marshall's Flight Software Group (FSG). The principle goals for addressing the issue of quality are to improve software management, software development time, software maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control methodologies, but to provide alternative design choices for control, implementation, performance, and sustaining engineering, all relative to addressing the issue of reliability. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion (system level), software engineering for embedded flight software systems, and soft computing technologies (i.e., neural networks, fuzzy logic, data mining, and Bayesian belief networks); some of which are briefed in this paper. For this effort, the targeted demonstration rocket engine testbed is the MC-1 engine (formerly FASTRAC) which is simulated with hardware and software in the Marshall Avionics & Software Testbed (MAST) laboratory that currently resides at NASA's Marshall Space Flight Center, building 4476, and is managed by the Avionics Department. A brief plan of action for design, development, implementation, and testing a Phase One effort for QRECS is given, along with expected results. Phase One will focus on development of a Smart Start Engine Module and a Mainstage Engine Module for proper engine start and mainstage engine operations. The overall intent is to demonstrate that by

  19. Free Software Development. 3. Numerical Description of Soft Acid with Soft Base Titration

    Directory of Open Access Journals (Sweden)

    Lorentz JÄNTSCHI

    2002-12-01

    Full Text Available The analytical methods of qualitative and quantitative determination of ions in solutions are very flexible to automation. The present work is focus on modeling the process of titration and presents a numerical simulation of acid-base titration. A PHP program to compute all iterations in titration process that solves a 3th rank equation to find value of pH for was built and is available through http internet protocol at the address: http://vl.academicdirect.org/molecular_dynamics/ab_titrations/v1.1/ The method allows expressing the value of pH in any point of titration process and permits to observe the equivalence point of titration.

  20. In vivo X-Ray Computed Tomographic Imaging of Soft Tissue with Native, Intravenous, or Oral Contrast

    Directory of Open Access Journals (Sweden)

    W. Matthew Leevy

    2013-05-01

    Full Text Available X-ray Computed Tomography (CT is one of the most commonly utilized anatomical imaging modalities for both research and clinical purposes. CT combines high-resolution, three-dimensional data with relatively fast acquisition to provide a solid platform for non-invasive human or specimen imaging. The primary limitation of CT is its inability to distinguish many soft tissues based on native contrast. While bone has high contrast within a CT image due to its material density from calcium phosphate, soft tissue is less dense and many are homogenous in density. This presents a challenge in distinguishing one type of soft tissue from another. A couple exceptions include the lungs as well as fat, both of which have unique densities owing to the presence of air or bulk hydrocarbons, respectively. In order to facilitate X-ray CT imaging of other structures, a range of contrast agents have been developed to selectively identify and visualize the anatomical properties of individual tissues. Most agents incorporate atoms like iodine, gold, or barium because of their ability to absorb X-rays, and thus impart contrast to a given organ system. Here we review the strategies available to visualize lung, fat, brain, kidney, liver, spleen, vasculature, gastrointestinal tract, and liver tissues of living mice using either innate contrast, or commercial injectable or ingestible agents with selective perfusion. Further, we demonstrate how each of these approaches will facilitate the non-invasive, longitudinal, in vivo imaging of pre-clinical disease models at each anatomical site.

  1. Application of Soft Computing Tools for Wave Prediction at Specific Locations in the Arabian Sea Using Moored Buoy Observations

    Directory of Open Access Journals (Sweden)

    J. Vimala

    2012-12-01

    Full Text Available The knowledge of design and operational values of significant wave heights is perhaps the single most important input needed in ocean engineering studies. Conventionally such information is obtained using classical statistical analysis and stochastic methods. As the causative variables are innumerable and underlying physics is too complicated, the results obtained from the numerical models may not always be very satisfactory. Soft computing tools like Artificial Neural Network (ANN and Adaptive Network based Fuzzy Inference System (ANFIS may therefore be useful to predict significant wave heights in some situations. The study is aimed at forecasting of significant wave height values in real time over a period of 24hrs at certain locations in Indian seas using the models of ANN and ANFIS. The data for the work were collected by National Institute of Ocean Technology, Chennai. It was found that the predictions of wave heights can be done by both methods with equal efficiency and satisfaction.

  2. Computer Based Modelling and Simulation

    Indian Academy of Sciences (India)

    GENERAL I ARTICLE. Computer Based ... universities, and later did system analysis, ... sonal computers (PC) and low cost software packages and tools. They can serve as useful learning experience through student projects. Models are .... Let us consider a numerical example: to calculate the velocity of a trainer aircraft ...

  3. SOFT project: a new forecasting system based on satellite data

    Science.gov (United States)

    Pascual, Ananda; Orfila, A.; Alvarez, Alberto; Hernandez, E.; Gomis, D.; Barth, Alexander; Tintore, Joaquim

    2002-01-01

    The aim of the SOFT project is to develop a new ocean forecasting system by using a combination of satellite dat, evolutionary programming and numerical ocean models. To achieve this objective two steps are proved: (1) to obtain an accurate ocean forecasting system using genetic algorithms based on satellite data; and (2) to integrate the above new system into existing deterministic numerical models. Evolutionary programming will be employed to build 'intelligent' systems that, learning form the past ocean variability and considering the present ocean state, will be able to infer near future ocean conditions. Validation of the forecast skill will be carried out by comparing the forecasts fields with satellite and in situ observations. Validation with satellite observations will provide the expected errors in the forecasting system. Validation with in situ data will indicate the capabilities of the satellite based forecast information to improve the performance of the numerical ocean models. This later validation will be accomplished considering in situ measurements in a specific oceanographic area at two different periods of time. The first set of observations will be employed to feed the hybrid systems while the second set will be used to validate the hybrid and traditional numerical model results.

  4. The potential of soft computing methods in NPP instrumentation and control

    International Nuclear Information System (INIS)

    Hampel, R.; Chaker, N.; Kaestner, W.; Traichel, A.; Wagenknecht, M.; Gocht, U.

    2002-01-01

    The method of signal processing by soft computing include the application of fuzzy logic, synthetic neural networks, and evolutionary algorithms. The article contains an outline of the objectives and results of the application of fuzzy logic and methods of synthetic neural networks in nuclear measurement and control. The special requirements to be met by the software in safety-related areas with respect to reliability, evaluation, and validation are described. Possible uses may be in off-line applications in modeling, simulation, and reliability analysis as well as in on-line applications (real-time systems) for instrumentation and control. Safety-related aspects of signal processing are described and analyzed for the fuzzy logic and synthetic neural network concepts. Application are covered in selected examples. (orig.)

  5. Soft Computing Methods for Microwave and Millimeter-Wave Design Problems

    CERN Document Server

    Chauhan, Narendra; Mittal, Ankush

    2012-01-01

    The growing commercial market of Microwave/ Millimeter wave industry over the past decade has led to the explosion of interests and opportunities for the design and development of microwave components.The design of most microwave components requires the use of commercially available electromagnetic (EM) simulation tools for their analysis. In the design process, the simulations are carried out by varying the design parameters until the desired response is obtained. The optimization of design parameters by manual searching is a cumbersome and time consuming process. Soft computing methods such as Genetic Algorithm (GA), Artificial Neural Network (ANN) and Fuzzy Logic (FL) have been widely used by EM researchers for microwave design since last decade. The aim of these methods is to tolerate imprecision, uncertainty, and approximation to achieve robust and low cost solution in a small time frame.  Modeling and optimization are essential parts and powerful tools for the microwave/millimeter wave design. This boo...

  6. River suspended sediment estimation by climatic variables implication: Comparative study among soft computing techniques

    Science.gov (United States)

    Kisi, Ozgur; Shiri, Jalal

    2012-06-01

    Estimating sediment volume carried by a river is an important issue in water resources engineering. This paper compares the accuracy of three different soft computing methods, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Gene Expression Programming (GEP), in estimating daily suspended sediment concentration on rivers by using hydro-meteorological data. The daily rainfall, streamflow and suspended sediment concentration data from Eel River near Dos Rios, at California, USA are used as a case study. The comparison results indicate that the GEP model performs better than the other models in daily suspended sediment concentration estimation for the particular data sets used in this study. Levenberg-Marquardt, conjugate gradient and gradient descent training algorithms were used for the ANN models. Out of three algorithms, the Conjugate gradient algorithm was found to be better than the others.

  7. APPLICATION OF SOFT COMPUTING TECHNIQUES FOR PREDICTING COOLING TIME REQUIRED DROPPING INITIAL TEMPERATURE OF MASS CONCRETE

    Directory of Open Access Journals (Sweden)

    Santosh Bhattarai

    2017-07-01

    Full Text Available Minimizing the thermal cracks in mass concrete at an early age can be achieved by removing the hydration heat as quickly as possible within initial cooling period before the next lift is placed. Recognizing the time needed to remove hydration heat within initial cooling period helps to take an effective and efficient decision on temperature control plan in advance. Thermal properties of concrete, water cooling parameters and construction parameter are the most influencing factors involved in the process and the relationship between these parameters are non-linear in a pattern, complicated and not understood well. Some attempts had been made to understand and formulate the relationship taking account of thermal properties of concrete and cooling water parameters. Thus, in this study, an effort have been made to formulate the relationship for the same taking account of thermal properties of concrete, water cooling parameters and construction parameter, with the help of two soft computing techniques namely: Genetic programming (GP software “Eureqa” and Artificial Neural Network (ANN. Relationships were developed from the data available from recently constructed high concrete double curvature arch dam. The value of R for the relationship between the predicted and real cooling time from GP and ANN model is 0.8822 and 0.9146 respectively. Relative impact on target parameter due to input parameters was evaluated through sensitivity analysis and the results reveal that, construction parameter influence the target parameter significantly. Furthermore, during the testing phase of proposed models with an independent set of data, the absolute and relative errors were significantly low, which indicates the prediction power of the employed soft computing techniques deemed satisfactory as compared to the measured data.

  8. Fuzzy GML Modeling Based on Vague Soft Sets

    Directory of Open Access Journals (Sweden)

    Bo Wei

    2017-01-01

    Full Text Available The Open Geospatial Consortium (OGC Geography Markup Language (GML explicitly represents geographical spatial knowledge in text mode. All kinds of fuzzy problems will inevitably be encountered in spatial knowledge expression. Especially for those expressions in text mode, this fuzziness will be broader. Describing and representing fuzziness in GML seems necessary. Three kinds of fuzziness in GML can be found: element fuzziness, chain fuzziness, and attribute fuzziness. Both element fuzziness and chain fuzziness belong to the reflection of the fuzziness between GML elements and, then, the representation of chain fuzziness can be replaced by the representation of element fuzziness in GML. On the basis of vague soft set theory, two kinds of modeling, vague soft set GML Document Type Definition (DTD modeling and vague soft set GML schema modeling, are proposed for fuzzy modeling in GML DTD and GML schema, respectively. Five elements or pairs, associated with vague soft sets, are introduced. Then, the DTDs and the schemas of the five elements are correspondingly designed and presented according to their different chains and different fuzzy data types. While the introduction of the five elements or pairs is the basis of vague soft set GML modeling, the corresponding DTD and schema modifications are key for implementation of modeling. The establishment of vague soft set GML enables GML to represent fuzziness and solves the problem of lack of fuzzy information expression in GML.

  9. Soft, curved electrode systems capable of integration on the auricle as a persistent brain–computer interface

    Science.gov (United States)

    Norton, James J. S.; Lee, Dong Sup; Lee, Jung Woo; Lee, Woosik; Kwon, Ohjin; Won, Phillip; Jung, Sung-Young; Cheng, Huanyu; Jeong, Jae-Woong; Akce, Abdullah; Umunna, Stephen; Na, Ilyoun; Kwon, Yong Ho; Wang, Xiao-Qi; Liu, ZhuangJian; Paik, Ungyu; Huang, Yonggang; Bretl, Timothy; Yeo, Woon-Hong; Rogers, John A.

    2015-01-01

    Recent advances in electrodes for noninvasive recording of electroencephalograms expand opportunities collecting such data for diagnosis of neurological disorders and brain–computer interfaces. Existing technologies, however, cannot be used effectively in continuous, uninterrupted modes for more than a few days due to irritation and irreversible degradation in the electrical and mechanical properties of the skin interface. Here we introduce a soft, foldable collection of electrodes in open, fractal mesh geometries that can mount directly and chronically on the complex surface topology of the auricle and the mastoid, to provide high-fidelity and long-term capture of electroencephalograms in ways that avoid any significant thermal, electrical, or mechanical loading of the skin. Experimental and computational studies establish the fundamental aspects of the bending and stretching mechanics that enable this type of intimate integration on the highly irregular and textured surfaces of the auricle. Cell level tests and thermal imaging studies establish the biocompatibility and wearability of such systems, with examples of high-quality measurements over periods of 2 wk with devices that remain mounted throughout daily activities including vigorous exercise, swimming, sleeping, and bathing. Demonstrations include a text speller with a steady-state visually evoked potential-based brain–computer interface and elicitation of an event-related potential (P300 wave). PMID:25775550

  10. Soft, curved electrode systems capable of integration on the auricle as a persistent brain-computer interface.

    Science.gov (United States)

    Norton, James J S; Lee, Dong Sup; Lee, Jung Woo; Lee, Woosik; Kwon, Ohjin; Won, Phillip; Jung, Sung-Young; Cheng, Huanyu; Jeong, Jae-Woong; Akce, Abdullah; Umunna, Stephen; Na, Ilyoun; Kwon, Yong Ho; Wang, Xiao-Qi; Liu, ZhuangJian; Paik, Ungyu; Huang, Yonggang; Bretl, Timothy; Yeo, Woon-Hong; Rogers, John A

    2015-03-31

    Recent advances in electrodes for noninvasive recording of electroencephalograms expand opportunities collecting such data for diagnosis of neurological disorders and brain-computer interfaces. Existing technologies, however, cannot be used effectively in continuous, uninterrupted modes for more than a few days due to irritation and irreversible degradation in the electrical and mechanical properties of the skin interface. Here we introduce a soft, foldable collection of electrodes in open, fractal mesh geometries that can mount directly and chronically on the complex surface topology of the auricle and the mastoid, to provide high-fidelity and long-term capture of electroencephalograms in ways that avoid any significant thermal, electrical, or mechanical loading of the skin. Experimental and computational studies establish the fundamental aspects of the bending and stretching mechanics that enable this type of intimate integration on the highly irregular and textured surfaces of the auricle. Cell level tests and thermal imaging studies establish the biocompatibility and wearability of such systems, with examples of high-quality measurements over periods of 2 wk with devices that remain mounted throughout daily activities including vigorous exercise, swimming, sleeping, and bathing. Demonstrations include a text speller with a steady-state visually evoked potential-based brain-computer interface and elicitation of an event-related potential (P300 wave).

  11. Paper-Based and Computer-Based Concept Mappings: The Effects on Computer Achievement, Computer Anxiety and Computer Attitude

    Science.gov (United States)

    Erdogan, Yavuz

    2009-01-01

    The purpose of this paper is to compare the effects of paper-based and computer-based concept mappings on computer hardware achievement, computer anxiety and computer attitude of the eight grade secondary school students. The students were randomly allocated to three groups and were given instruction on computer hardware. The teaching methods used…

  12. Integrating Soft Skill Competencies through Project-Based Learning across the Information Systems Curriculum

    Science.gov (United States)

    Woodward, Belle S.; Sendall, Patricia; Ceccucci, Wendy

    2010-01-01

    Contemporary Information Systems graduates will be more marketable in the workplace upon graduation if they have combined competencies in both technical and soft skills: interpersonal communication, teamwork, time management, planning and organizational skills. Team and project-based learning can be used to incorporate soft skill competencies with…

  13. Peptide-based soft materials as potential drug delivery vehicles.

    Science.gov (United States)

    Verma, Sandeep; Joshi, K B; Ghosh, Surajit

    2007-11-01

    Emerging concepts in the construction of nanostructures hold immense potential in the areas of drug delivery and targeting. Such nanoscopic assemblies/structures, similar to natural proteins and self-associating systems, may lead to the formation of programmable soft structures with expanded drug delivery options and the capability to circumvent first-pass metabolism. This article aims to illustrate key recent developments and innovative bioinspired design paradigms pertaining to peptide-containing self-assembled tubular and vesicular soft structures. Soft structures are composed of components that self-assemble to reveal diverse morphologies stabilized by weak, noncovalent interactions. Morphological properties of such structures and their ability to encapsulate drugs, biologicals and bioactive small molecules, with the promise of targeted delivery, are discussed.

  14. Multiattribute Grey Target Decision Method Based on Soft Set Theory

    Directory of Open Access Journals (Sweden)

    Xia Wang

    2014-01-01

    Full Text Available With respect to the Multiattribute decision-making problems in which the evaluation attribute sets are different and the evaluating values of alternatives are interval grey numbers, a multiattribute grey target decision-making method in which the attribute sets are different was proposed. The concept of grey soft set was defined, and its “AND” operation was assigned by combining the intersection operation of grey number. The expression approach of new grey soft set of attribute sets considering by all decision makers were gained by applying the “AND” operation of grey soft set, and the weights of synthesis attribute were proved. The alternatives were ranked according to the size of distance of bull’s eyes of each alternative under synthetic attribute sets. The green supplier selection was illustrated to demonstrate the effectiveness of proposed model.

  15. Soft-Rt: software for IMRT simulations based on MCNPX

    International Nuclear Information System (INIS)

    Ferreira F, T. C.; Campos, T.

    2015-10-01

    Intensity Modulated Radiation Therapy (IMRT) is an advanced treatment technique, widely used in external radiotherapy. This paper presents the Soft-Rt which allows the simulation of an entire IMRT treatment protocol. The Soft-Rt performs a full three-dimensional rendering of a set of patient images, including the definitions of region of interest with organs in risk, and the target tumor volume and margins (PTV). Thus, a more accurate analysis and planning can be performed, taking into account the features and orientation of the radiation beams. The exposed tissues as well as the amount of absorbed dose is depicted in healthy and/or cancerous tissues. As conclusion, Soft-Rt can predict dose on the PTV accurately, preserving the surrounding healthy tissues. Soft-Rt is coupled with SISCODES code. The SISCODES code is firstly applied to segment the set of CT or MRI patient images in distinct tissues pointing out its respective density and chemical compositions. Later, the voxel model is export to the Soft-Rt IMRT planning module in which a full treatment planning is created. All geometrical parameters are sent to the general purpose Monte Carlo transport code - MCNP - to simulate the interaction of each incident beam towards to the PTV avoiding organs in risk. The normalized dose results are exported to the Soft-Rt out-module, in which the three-dimensional model visualization is shown in a transparent glass procedure adopting gray scale for the dependence on the mass density of the correlated tissue; while, a color scale to depict dose values in a superimpose protocol. (Author)

  16. Soft-Rt: software for IMRT simulations based on MCNPX

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira F, T. C. [Centro de Desenvolvimento da Tecnologia Nuclear / CNEN, Av. Pte. Antonio Carlos 6627, 31270-901 Belo Horizonte, Minas Gerais (Brazil); Campos, T., E-mail: tcff01@gmail.com [Universidade Federal de Minas Gerais, Departamento de Engenharia Nuclear, Programa de Pos Graduacao em Ciencias e Tecnicas Nucleares, Av. Pte. Antonio Carlos 6627, 31270-901 Belo Horizonte, Minas Gerais (Brazil)

    2015-10-15

    Intensity Modulated Radiation Therapy (IMRT) is an advanced treatment technique, widely used in external radiotherapy. This paper presents the Soft-Rt which allows the simulation of an entire IMRT treatment protocol. The Soft-Rt performs a full three-dimensional rendering of a set of patient images, including the definitions of region of interest with organs in risk, and the target tumor volume and margins (PTV). Thus, a more accurate analysis and planning can be performed, taking into account the features and orientation of the radiation beams. The exposed tissues as well as the amount of absorbed dose is depicted in healthy and/or cancerous tissues. As conclusion, Soft-Rt can predict dose on the PTV accurately, preserving the surrounding healthy tissues. Soft-Rt is coupled with SISCODES code. The SISCODES code is firstly applied to segment the set of CT or MRI patient images in distinct tissues pointing out its respective density and chemical compositions. Later, the voxel model is export to the Soft-Rt IMRT planning module in which a full treatment planning is created. All geometrical parameters are sent to the general purpose Monte Carlo transport code - MCNP - to simulate the interaction of each incident beam towards to the PTV avoiding organs in risk. The normalized dose results are exported to the Soft-Rt out-module, in which the three-dimensional model visualization is shown in a transparent glass procedure adopting gray scale for the dependence on the mass density of the correlated tissue; while, a color scale to depict dose values in a superimpose protocol. (Author)

  17. Soft Computing Approach to Evaluate and Predict Blast-Induced Ground Vibration

    Science.gov (United States)

    Khandelwal, Manoj

    2010-05-01

    the same excavation site, different predictors give different values of safe PPV vis-à-vis safe charge per delay. There is no uniformity in the predicted result by different predictors. All vibration predictor equations have their site specific constants. Therefore, they cannot be used in a generalized way with confidence and zero level of risk. To overcome on this aspect new soft computing tools like artificial neural network (ANN) has attracted because of its ability to learn from the pattern acquainted before. ANN has the ability to learn from patterns acquainted before. It is a highly interconnected network of a large number of processing elements called neurons in an architecture inspired by the brain. ANN can be massively parallel and hence said to exhibit parallel distributed processing. Once, the network has been trained, with sufficient number of sample data sets, it can make reliable and trustworthy predictions on the basis of its previous learning, about the output related to new input data set of similar pattern. This paper deals the application of ANN for the prediction of ground vibration by taking into consideration of maximum charge per delay and distance between blast face to monitoring point. To investigate the appropriateness of this approach, the predictions by ANN have been also compared with other vibration predictor equations.

  18. Using soft-X-ray energy spectrum to measure electronic temperature Te and primary research with computer data processing

    International Nuclear Information System (INIS)

    Wang Jingyao; Zhang Guangyang

    1993-01-01

    The authors reported the application of SCORPIO--2000 Computer detecting system on a nuclear fusion equipment, to measure the energy spectrum of soft X-ray from which the plasma electronic temperature was calculated. The authors processed systematically the data of the energy area of 1-4 Kev soft X-ray. The program edited was mostly made in FORTRAN, but only one SUBSB was made in assembly language. The program worked normally with convincing operation and easy correction of the data. The result obtained from calculation is the same as what was expected and the diagram obtained is the same as the expected one

  19. The lucky image-motion prediction for simple scene observation based soft-sensor technology

    Science.gov (United States)

    Li, Yan; Su, Yun; Hu, Bin

    2015-08-01

    High resolution is important to earth remote sensors, while the vibration of the platforms of the remote sensors is a major factor restricting high resolution imaging. The image-motion prediction and real-time compensation are key technologies to solve this problem. For the reason that the traditional autocorrelation image algorithm cannot meet the demand for the simple scene image stabilization, this paper proposes to utilize soft-sensor technology in image-motion prediction, and focus on the research of algorithm optimization in imaging image-motion prediction. Simulations results indicate that the improving lucky image-motion stabilization algorithm combining the Back Propagation Network (BP NN) and support vector machine (SVM) is the most suitable for the simple scene image stabilization. The relative error of the image-motion prediction based the soft-sensor technology is below 5%, the training computing speed of the mathematical predication model is as fast as the real-time image stabilization in aerial photography.

  20. GPU-based real-time soft tissue deformation with cutting and haptic feedback.

    Science.gov (United States)

    Courtecuisse, Hadrien; Jung, Hoeryong; Allard, Jérémie; Duriez, Christian; Lee, Doo Yong; Cotin, Stéphane

    2010-12-01

    This article describes a series of contributions in the field of real-time simulation of soft tissue biomechanics. These contributions address various requirements for interactive simulation of complex surgical procedures. In particular, this article presents results in the areas of soft tissue deformation, contact modelling, simulation of cutting, and haptic rendering, which are all relevant to a variety of medical interventions. The contributions described in this article share a common underlying model of deformation and rely on GPU implementations to significantly improve computation times. This consistency in the modelling technique and computational approach ensures coherent results as well as efficient, robust and flexible solutions. Copyright © 2010 Elsevier Ltd. All rights reserved.

  1. Simplified Soft-output Demapper Based on a Linear Transformation Technique for M-ary PSK

    Directory of Open Access Journals (Sweden)

    Jianping Li

    2014-10-01

    Full Text Available Combining channel coding with high-order modulation schemes, namely coded modulation (CM, is an efficient digital transmission technology. CM requires the demapper to provide a soft decision bit metric as a part of the inputs to the decoder. This paper proposes an efficient soft- output demapper for M-ary PSK. This novel demodulation algorithm continues to evolve the conventional MAX-Log-MAP algorithm and summarizes the final derivation into a form of matrix multiplication. The Computational complexity for getting one bit soft value of a signal by employing the proposed algorithm remains a constant with the increase of modulation order. Meanwhile, the theoretical analysis and simulation results prove that the novel simplified soft-output demapper can obtain the same performance as MAX-Log-MAP.

  2. Computer-Based Career Interventions.

    Science.gov (United States)

    Mau, Wei-Cheng

    The possible utilities and limitations of computer-assisted career guidance systems (CACG) have been widely discussed although the effectiveness of CACG has not been systematically considered. This paper investigates the effectiveness of a theory-based CACG program, integrating Sequential Elimination and Expected Utility strategies. Three types of…

  3. Computer Based Modelling and Simulation

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 6; Issue 3. Computer Based Modelling and Simulation - Modelling Deterministic Systems. N K Srinivasan. General Article Volume 6 Issue 3 March 2001 pp 46-54. Fulltext. Click here to view fulltext PDF. Permanent link:

  4. Soft Computing Technique and Conventional Controller for Conical Tank Level Control

    Directory of Open Access Journals (Sweden)

    Sudharsana Vijayan

    2016-03-01

    Full Text Available In many process industries the control of liquid level is mandatory. But the control of nonlinear process is difficult. Many process industries use conical tanks because of its non linear shape contributes better drainage for solid mixtures, slurries and viscous liquids. So, control of conical tank level is a challenging task due to its non-linearity and continually varying cross-section. This is due to relationship between controlled variable level and manipulated variable flow rate, which has a square root relationship. The main objective is to execute the suitable controller for conical tank system to maintain the desired level. System identification of the non-linear process is done using black box modelling and found to be first order plus dead time (FOPDT model. In this paper it is proposed to obtain the mathematical modelling of a conical tank system and to study the system using block diagram after that soft computing technique like fuzzy and conventional controller is also used for the comparison.

  5. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  6. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  7. Wind turbine power coefficient estimation by soft computing methodologies: Comparative study

    International Nuclear Information System (INIS)

    Shamshirband, Shahaboddin; Petković, Dalibor; Saboohi, Hadi; Anuar, Nor Badrul; Inayat, Irum; Akib, Shatirah; Ćojbašić, Žarko; Nikolić, Vlastimir; Mat Kiah, Miss Laiha; Gani, Abdullah

    2014-01-01

    Highlights: • Variable speed operation of wind turbine to increase power generation. • Changeability and fluctuation of wind has to be accounted. • To build an effective prediction model of wind turbine power coefficient. • The impact of the variation in the blade pitch angle and tip speed ratio. • Support vector regression methodology application as predictive methodology. - Abstract: Wind energy has become a large contender of traditional fossil fuel energy, particularly with the successful operation of multi-megawatt sized wind turbines. However, reasonable wind speed is not adequately sustainable everywhere to build an economical wind farm. In wind energy conversion systems, one of the operational problems is the changeability and fluctuation of wind. In most cases, wind speed can vacillate rapidly. Hence, quality of produced energy becomes an important problem in wind energy conversion plants. Several control techniques have been applied to improve the quality of power generated from wind turbines. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of support vector regression (SVR) to estimate optimal power coefficient value of the wind turbines. Instead of minimizing the observed training error, SVR p oly and SVR r bf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach in compare to other soft computing methodologies

  8. An appraisal of wind speed distribution prediction by soft computing methodologies: A comparative study

    International Nuclear Information System (INIS)

    Petković, Dalibor; Shamshirband, Shahaboddin; Anuar, Nor Badrul; Saboohi, Hadi; Abdul Wahab, Ainuddin Wahid; Protić, Milan; Zalnezhad, Erfan; Mirhashemi, Seyed Mohammad Amin

    2014-01-01

    Highlights: • Probabilistic distribution functions of wind speed. • Two parameter Weibull probability distribution. • To build an effective prediction model of distribution of wind speed. • Support vector regression application as probability function for wind speed. - Abstract: The probabilistic distribution of wind speed is among the more significant wind characteristics in examining wind energy potential and the performance of wind energy conversion systems. When the wind speed probability distribution is known, the wind energy distribution can be easily obtained. Therefore, the probability distribution of wind speed is a very important piece of information required in assessing wind energy potential. For this reason, a large number of studies have been established concerning the use of a variety of probability density functions to describe wind speed frequency distributions. Although the two-parameter Weibull distribution comprises a widely used and accepted method, solving the function is very challenging. In this study, the polynomial and radial basis functions (RBF) are applied as the kernel function of support vector regression (SVR) to estimate two parameters of the Weibull distribution function according to previously established analytical methods. Rather than minimizing the observed training error, SVR p oly and SVR r bf attempt to minimize the generalization error bound, so as to achieve generalized performance. According to the experimental results, enhanced predictive accuracy and capability of generalization can be achieved using the SVR approach compared to other soft computing methodologies

  9. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Science.gov (United States)

    Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

  10. Modeling and Experimental Study of Soft Error Propagation Based on Cellular Automaton

    Directory of Open Access Journals (Sweden)

    Wei He

    2016-01-01

    Full Text Available Aiming to estimate SEE soft error performance of complex electronic systems, a soft error propagation model based on cellular automaton is proposed and an estimation methodology based on circuit partitioning and error propagation is presented. Simulations indicate that different fault grade jamming and different coupling factors between cells are the main parameters influencing the vulnerability of the system. Accelerated radiation experiments have been developed to determine the main parameters for raw soft error vulnerability of the module and coupling factors. Results indicate that the proposed method is feasible.

  11. Ammonia-based quantum computer

    International Nuclear Information System (INIS)

    Ferguson, Andrew J.; Cain, Paul A.; Williams, David A.; Briggs, G. Andrew D.

    2002-01-01

    We propose a scheme for quantum computation using two eigenstates of ammonia or similar molecules. Individual ammonia molecules are confined inside fullerenes and used as two-level qubit systems. Interaction between these ammonia qubits takes place via the electric dipole moments, and in particular we show how a controlled-NOT gate could be implemented. After computation the qubit is measured with a single-electron electrometer sensitive enough to differentiate between the dipole moments of different states. We also discuss a possible implementation based on a quantum cellular automaton

  12. Accuracy and reliability of facial soft tissue depth measurements using cone beam computer tomography

    NARCIS (Netherlands)

    Fourie, Zacharias; Damstra, Janalt; Gerrits, Pieter; Ren, Yijin

    2010-01-01

    It is important to have accurate and reliable measurements of soft tissue thickness for specific landmarks of the face and scalp when producing a facial reconstruction. In the past several methods have been created to measure facial soft tissue thickness (FSTT) in cadavers and in the living. The

  13. Modeling and Experimental Study of Soft Error Propagation Based on Cellular Automaton

    OpenAIRE

    He, Wei; Wang, Yueke; Xing, Kefei; Yang, Jianwei

    2016-01-01

    Aiming to estimate SEE soft error performance of complex electronic systems, a soft error propagation model based on cellular automaton is proposed and an estimation methodology based on circuit partitioning and error propagation is presented. Simulations indicate that different fault grade jamming and different coupling factors between cells are the main parameters influencing the vulnerability of the system. Accelerated radiation experiments have been developed to determine the main paramet...

  14. Highly sensitive detection of the soft tissues based on refraction contrast by in-plane diffraction-enhanced imaging CT

    International Nuclear Information System (INIS)

    Yuasa, Tetsuya; Hashimoto, Eiko; Maksimenko, Anton; Sugiyama, Hiroshi; Arai, Yoshinori; Shimao, Daisuke; Ichihara, Shu; Ando, Masami

    2008-01-01

    We discuss the recently proposed computed tomography (CT) technique based on refractive effects for biomedical use, which reconstructs the in-plane refractive-index gradient vector field in a cross-sectional plane of interest by detecting the angular deviation of the beam, refracted by a sample, from the incident beam, using the diffraction-enhanced imaging (DEI) method. The CT has advantages for delineating biological weakly absorbing soft tissues over the conventional absorption-contrast CT because of the use of phase sensitive detection. The paper aims to define the imaging scheme rigidly and to demonstrate its efficacy for non-destructive measurement of biomedical soft-tissue samples without imaging agent. We first describe the imaging principle of in-plane DEI-CT from the physico-mathematical viewpoints in detail, and investigate what physical quantities are extracted from the reconstructed images. Then, we introduce the imaging system using the synchrotron radiation as a light source, constructed at beamline BL-14B in KEK, Japan. Finally, we demonstrate the advantage of the refraction-based image for non-destructive analysis of biological sample by investigating the image of human breast cancer tumors obtained using the imaging system. Here, the refraction- and the apparent absorption-based images obtained simultaneously by the in-plane DEI-CT are compared. Also, the conventional absorption-based image obtained using micro-computed tomography (μCT) imaging system is compared with them. Thereby, it is shown that the refraction contrast much more sensitively delineates the soft tissues than the absorption contrast. In addition, the radiologic-histologic correlation study not only validates the efficacy for imaging soft tissues, but also produces the potential that the pathological inspection for the breast cancer tumors may be feasible non-destructively

  15. Soft computing based feature selection for environmental sound classification

    NARCIS (Netherlands)

    Shakoor, A.; May, T.M.; Van Schijndel, N.H.

    2010-01-01

    Environmental sound classification has a wide range of applications,like hearing aids, mobile communication devices, portable media players, and auditory protection devices. Sound classification systemstypically extract features from the input sound. Using too many features increases complexity

  16. Design and development of AXUV-based soft X-ray diagnostic camera for Aditya Tokamak

    International Nuclear Information System (INIS)

    Raval, Jayesh V.; Purohit, Shishir; Joisa, Y. Shankara

    2015-01-01

    The hot tokamak plasma emits Soft X-rays (SXR) in accordance with the temperature and density which are important to be studied. A silicon photo diode array (AXUV16ELG, Opto-diode, USA) based prototype SXR diagnostics is designed and developed for ADITYA tokamak for the study of SXR radial intensity profile, internal disruption (Saw-tooth crash), MHD instabilities. The diagnostic is having an array of 16 detector of millimeter dimension in a linear configuration. Absolute Extreme Ultra Violate (AXUV) detector offers compact size, improved time response with considerably good quantum efficiency in the soft X-ray range (200 eV to 10 keV). The diagnostic is designed in competence with the ADITYA tokamak protocol. The diagnostic design geometry allows detector view the plasma through a slot hole (0.5 cm X 0.05 cm), 10 μm Beryllium foil filter window, cutting off energies below 750 eV. The diagnostic was installed on Aditya vacuum vessel at radial port no 7 enabling the diagnostics to view the core plasma. The spatial resolution designed for diagnostic configuration is 1.3 cm at plasma centre. The signal generated from SXR detector is acquired with a dedicated single board computer based data acquisition system at 50 kHz. The diagnostic took observation for the ohmically heated plasma. The data was then processed to construct spatial and temporal profile of SXR intensity for Aditya plasma. This information was complimentary to the Silicon surface barrier detector (SBD) based array for the same plasma discharge. The cross calibration between the two was considerably satisfactory under the assumptions considered. (author)

  17. Soft Robotics Week

    CERN Document Server

    Rossiter, Jonathan; Iida, Fumiya; Cianchetti, Matteo; Margheri, Laura

    2017-01-01

    This book offers a comprehensive, timely snapshot of current research, technologies and applications of soft robotics. The different chapters, written by international experts across multiple fields of soft robotics, cover innovative systems and technologies for soft robot legged locomotion, soft robot manipulation, underwater soft robotics, biomimetic soft robotic platforms, plant-inspired soft robots, flying soft robots, soft robotics in surgery, as well as methods for their modeling and control. Based on the results of the second edition of the Soft Robotics Week, held on April 25 – 30, 2016, in Livorno, Italy, the book reports on the major research lines and novel technologies presented and discussed during the event.

  18. Discrete polyphase matched filtering-based soft timing estimation for mobile wireless systems

    CSIR Research Space (South Africa)

    Olwal, TO

    2009-01-01

    Full Text Available of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft...

  19. Optimising Aesthetic Reconstruction of Scalp Soft Tissue by an Algorithm Based on Defect Size and Location.

    Science.gov (United States)

    Ooi, Adrian Sh; Kanapathy, Muholan; Ong, Yee Siang; Tan, Kok Chai; Tan, Bien Keem

    2015-11-01

    Scalp soft tissue defects are common and result from a variety of causes. Reconstructive methods should maximise cosmetic outcomes by maintaining hair-bearing tissue and aesthetic hairlines. This article outlines an algorithm based on a diverse clinical case series to optimise scalp soft tissue coverage. A retrospective analysis of scalp soft tissue reconstruction cases performed at the Singapore General Hospital between January 2004 and December 2013 was conducted. Forty-one patients were included in this study. The majority of defects aesthetic outcome while minimising complications and repeat procedures.

  20. Diagnosis of soft faults in analog integrated circuits based on fractional correlation

    International Nuclear Information System (INIS)

    Deng Yong; Shi Yibing; Zhang Wei

    2012-01-01

    Aiming at the problem of diagnosing soft faults in analog integrated circuits, an approach based on fractional correlation is proposed. First, the Volterra series of the circuit under test (CUT) decomposed by the fractional wavelet packet are used to calculate the fractional correlation functions. Then, the calculated fractional correlation functions are used to form the fault signatures of the CUT. By comparing the fault signatures, the different soft faulty conditions of the CUT are identified and the faults are located. Simulations of benchmark circuits illustrate the proposed method and validate its effectiveness in diagnosing soft faults in analog integrated circuits. (semiconductor integrated circuits)

  1. Automatic Generation of Agents using Reusable Soft Computing Code Libraries to develop Multi Agent System for Healthcare

    OpenAIRE

    Priti Srinivas Sajja

    2015-01-01

    This paper illustrates architecture for a multi agent system in healthcare domain. The architecture is generic and designed in form of multiple layers. One of the layers of the architecture contains many proactive, co-operative and intelligent agents such as resource management agent, query agent, pattern detection agent and patient management agent. Another layer of the architecture is a collection of libraries to auto-generate code for agents using soft computing techni...

  2. Screen-based sedentary time: Association with soft drink consumption and the moderating effect of parental education in European children : The ENERGY study

    NARCIS (Netherlands)

    Gebremariam, M.K.; Chinapaw, M.J.; Bringolf-Isler, B.; Bere, E.; Kovacs, E.; Verloigne, M.; Stok, F.M.; Manios, Y.; Brug, J.; Lien, N.

    2017-01-01

    Aim The aim of the present study was to explore if children who spend more time on screen-based sedentary behaviors (i.e.TV viewing and computer use) drink more sugar-sweetened soft drinks. The study also assessed whether these associations were independent of individual and home environmental

  3. Centrifugal forming and mechanical properties of silicone-based elastomers for soft robotic actuators

    Science.gov (United States)

    Kulkarni, Parth

    This thesis describes the centrifugal forming and resulting mechanical properties of silicone-based elastomers for the manufacture of soft robotic actuators. This process is effective at removing bubbles that get entrapped within 3D-printed, enclosed molds. Conventional methods for rapid prototyping of soft robotic actuators to remove entrapped bubbles typically involve degassing under vacuum, with open-faced molds that limit the layout of formed parts to raised 2D geometries. As the functionality and complexity of soft robots increase, there is a need to mold complete 3D structures with controlled thicknesses or curvatures on multiples surfaces. In addition, characterization of the mechanical properties of common elastomers for these soft robots has lagged the development of new designs. As such, relationships between resulting material properties and processing parameters are virtually non-existent. One of the goals of this thesis is to provide guidelines and physical insights to relate the design, processing conditions, and resulting properties of soft robotic components to each other. Centrifugal forming with accelerations on the order of 100 g's is capable of forming bubble-free, true 3D components for soft robotic actuators, and resulting demonstrations in this work include an aquatic locomotor, soft gripper, and an actuator that straightens when pressurized. Finally, this work shows that the measured mechanical properties of 3D geometries fabricated within enclosed molds through centrifugal forming possess comparable mechanical properties to vacuumed materials formed from open-faced molds with raised 2D features.

  4. Monitoring asthma control in children with allergies by soft computing of lung function and exhaled nitric oxide.

    Science.gov (United States)

    Pifferi, Massimo; Bush, Andrew; Pioggia, Giovanni; Di Cicco, Maria; Chinellato, Iolanda; Bodini, Alessandro; Macchia, Pierantonio; Boner, Attilio L

    2011-02-01

    Asthma control is emphasized by new guidelines but remains poor in many children. Evaluation of control relies on subjective patient recall and may be overestimated by health-care professionals. This study assessed the value of spirometry and fractional exhaled nitric oxide (FeNO) measurements, used alone or in combination, in models developed by a machine learning approach in the objective classification of asthma control according to Global Initiative for Asthma guidelines and tested the model in a second group of children with asthma. Fifty-three children with persistent atopic asthma underwent two to six evaluations of asthma control, including spirometry and FeNO. Soft computing evaluation was performed by means of artificial neural networks and principal component analysis. The model was then tested in a cross-sectional study in an additional 77 children with allergic asthma. The machine learning method was not able to distinguish different levels of control using either spirometry or FeNO values alone. However, their use in combination modeled by soft computing was able to discriminate levels of asthma control. In particular, the model is able to recognize all children with uncontrolled asthma and correctly identify 99.0% of children with totally controlled asthma. In the cross-sectional study, the model prospectively identified correctly all the uncontrolled children and 79.6% of the controlled children. Soft computing analysis of spirometry and FeNO allows objective categorization of asthma control status.

  5. A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor.

    Science.gov (United States)

    Tayara, Hilal; Ham, Woonchul; Chong, Kil To

    2016-12-15

    This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA). The pose calculation algorithm was implemented in a System on Chip (SoC) with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST) corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation.

  6. Real-time deformation of human soft tissues: A radial basis meshless 3D model based on Marquardt's algorithm.

    Science.gov (United States)

    Zhou, Jianyong; Luo, Zu; Li, Chunquan; Deng, Mi

    2018-01-01

    When the meshless method is used to establish the mathematical-mechanical model of human soft tissues, it is necessary to define the space occupied by human tissues as the problem domain and the boundary of the domain as the surface of those tissues. Nodes should be distributed in both the problem domain and on the boundaries. Under external force, the displacement of the node is computed by the meshless method to represent the deformation of biological soft tissues. However, computation by the meshless method consumes too much time, which will affect the simulation of real-time deformation of human tissues in virtual surgery. In this article, the Marquardt's Algorithm is proposed to fit the nodal displacement at the problem domain's boundary and obtain the relationship between surface deformation and force. When different external forces are applied, the deformation of soft tissues can be quickly obtained based on this relationship. The analysis and discussion show that the improved model equations with Marquardt's Algorithm not only can simulate the deformation in real-time but also preserve the authenticity of the deformation model's physical properties. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery.

    Science.gov (United States)

    Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir

    2015-06-01

    The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

  8. Characterization of nanophotonic soft contact lenses based on poly (2-hydroxyethyl methacrylate and fullerene

    Directory of Open Access Journals (Sweden)

    Debeljković Aleksandra D.

    2013-01-01

    Full Text Available This work presents comparative research of characteristics of a basic and new nanophotonic material, the latter of which was obtained by incorporation fullerene, C60, in the base material for soft contact lenses. The basic (SL38 and nanophotonic materials (SL38-A for soft contact lenses were obtained by radical polymerization of 2-hydroxyethyl methacrylate and 2-hydroxyethyl methacrylate and fullerene, which were derived by the technology in the production lab of the company Soleko (Milan, Italy. The materials were used for production of soft contact lenses in the company Optix (Belgrade, Serbia for the purposes of this research. Fullerene was used due to its apsorption transmission characteristics in ultraviolet, visible and near infrared spectrum. For the purposes of material characterization for potential application as soft contact lenses, network parameters were calculated and SEM analysis of the materials was performed while the optical properties of the soft contact lenses were measured by a Rotlex device. The values of the diffusion exponent, n, close to 0.5 indicated Fick's kinetics corresponding to diffusion. The investigated hydrogels could be classified as nonporous hydrogels. With Rotlex device, values of optical power and map of defects were showed. The obtained values of optical power and map of defects showed that the optical power of synthesized nanophotonic soft contact lens is identical to the nominal value while this was not the case for the basic lens. Also, the quality of the nanophotonic soft contact lens is better than the basic soft contact lens. Hence, it is possible to synthesize new nanophotonic soft contact lenses of desired optical characteristics, implying possibilities for their application in this field.

  9. Computed tomography of the soft tissues of the shoulder. Pt. 3. Calcifying tendinitis of the rotator cuff

    Energy Technology Data Exchange (ETDEWEB)

    Dihlmann, W.; Bandick, J.

    1988-01-01

    Computed tomography of the soft tissue of the shoulder in cases of calcifying tendinitis of the rotator cuff provides the following information: 1. Localisation of the calcium deposits within the rotator cuff. 2. Contours and density of the calcium deposits correlated with the clinical findings as described by Uhthoff et al. Ill-defined contours and non-homogeneous deposits are associated with more severe clinical features. 3. Computed tomography shows that apatite particles, which are not visible radiologically, may penetrate into the shoulder joint and produce synovitis with an effusion. This is of importance in local therapy.

  10. ZIVIS: A City Computing Platform Based on Volunteer Computing

    International Nuclear Information System (INIS)

    Antoli, B.; Castejon, F.; Giner, A.; Losilla, G.; Reynolds, J. M.; Rivero, A.; Sangiao, S.; Serrano, F.; Tarancon, A.; Valles, R.; Velasco, J. L.

    2007-01-01

    Abstract Volunteer computing has come up as a new form of distributed computing. Unlike other computing paradigms like Grids, which use to be based on complex architectures, volunteer computing has demonstrated a great ability to integrate dispersed, heterogeneous computing resources with ease. This article presents ZIVIS, a project which aims to deploy a city-wide computing platform in Zaragoza (Spain). ZIVIS is based on BOINC (Berkeley Open Infrastructure for Network Computing), a popular open source framework to deploy volunteer and desktop grid computing systems. A scientific code which simulates the trajectories of particles moving inside a stellarator fusion device, has been chosen as the pilot application of the project. In this paper we describe the approach followed to port the code to the BOINC framework as well as some novel techniques, based on standard Grid protocols, we have used to access the output data present in the BOINC server from a remote visualizer. (Author)

  11. Passive microrheology of soft materials with atomic force microscopy: A wavelet-based spectral analysis

    Energy Technology Data Exchange (ETDEWEB)

    Martinez-Torres, C.; Streppa, L. [CNRS, UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d' Italie, Université de Lyon, 69007 Lyon (France); Arneodo, A.; Argoul, F. [CNRS, UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d' Italie, Université de Lyon, 69007 Lyon (France); CNRS, UMR5798, Laboratoire Ondes et Matière d' Aquitaine, Université de Bordeaux, 351 Cours de la Libération, 33405 Talence (France); Argoul, P. [Université Paris-Est, Ecole des Ponts ParisTech, SDOA, MAST, IFSTTAR, 14-20 Bd Newton, Cité Descartes, 77420 Champs sur Marne (France)

    2016-01-18

    Compared to active microrheology where a known force or modulation is periodically imposed to a soft material, passive microrheology relies on the spectral analysis of the spontaneous motion of tracers inherent or external to the material. Passive microrheology studies of soft or living materials with atomic force microscopy (AFM) cantilever tips are rather rare because, in the spectral densities, the rheological response of the materials is hardly distinguishable from other sources of random or periodic perturbations. To circumvent this difficulty, we propose here a wavelet-based decomposition of AFM cantilever tip fluctuations and we show that when applying this multi-scale method to soft polymer layers and to living myoblasts, the structural damping exponents of these soft materials can be retrieved.

  12. Physics and numerical methods of OPTMAN. A coupled-channels method based on soft-rotator model for a description of collective nuclear structure and excitations

    International Nuclear Information System (INIS)

    Soukhovitskii, Efrem Sh.; Morogovskii, Gennadij B.; Chiba, Satoshi; Iwamoto, Osamu; Fukahori, Tokio

    2004-03-01

    This report gives a detailed description of the theory and computational algorithms of modernized coupled-channels optical model code OPTMAN based on the soft-rotator model for the collective nuclear structure and excitations. This work was performed under the Project Agreement B-521 with the International Science and Technology Center (Moscow), financing party of which is Japan. As a result of this work, the computational method of OPTMAN was totally updated, and an user-friendly interface was attached. (author)

  13. SoftAR: visually manipulating haptic softness perception in spatial augmented reality.

    Science.gov (United States)

    Punpongsanon, Parinya; Iwai, Daisuke; Sato, Kosuke

    2015-11-01

    We present SoftAR, a novel spatial augmented reality (AR) technique based on a pseudo-haptics mechanism that visually manipulates the sense of softness perceived by a user pushing a soft physical object. Considering the limitations of projection-based approaches that change only the surface appearance of a physical object, we propose two projection visual effects, i.e., surface deformation effect (SDE) and body appearance effect (BAE), on the basis of the observations of humans pushing physical objects. The SDE visualizes a two-dimensional deformation of the object surface with a controlled softness parameter, and BAE changes the color of the pushing hand. Through psychophysical experiments, we confirm that the SDE can manipulate softness perception such that the participant perceives significantly greater softness than the actual softness. Furthermore, fBAE, in which BAE is applied only for the finger area, significantly enhances manipulation of the perception of softness. We create a computational model that estimates perceived softness when SDE+fBAE is applied. We construct a prototype SoftAR system in which two application frameworks are implemented. The softness adjustment allows a user to adjust the softness parameter of a physical object, and the softness transfer allows the user to replace the softness with that of another object.

  14. Estimation of soft sediment thickness in Kuala Lumpur based on microtremor observation data

    Science.gov (United States)

    Chiew, Chang Chyau; Cheah, Yi Ben; Tan, Chin Guan; Lau, Tze Liang

    2017-10-01

    Seismic site effect is one of the major concerns in earthquake engineering. Soft ground tends to amplify the seismic wave in surficial geological layers. The determination of soft ground thickness on the surface layers of the earth is an important input for seismic hazard assessment. This paper presents an easy and convenient approach to estimate the soft sediment thickness at the site using microtremor observation technique. A total number of 133 survey points were conducted in selected sites around Kuala Lumpur area using a microtremor measuring instrument, but only 103 survey points contributed to the seismic microzonation and sediment thickness plots. The bedrock of Kuala Lumpur area is formed by Kenny Hill Formation, limestone, granite, and the Hawthornden Schist; however, the thickness of surface soft ground formed by alluvial deposits, mine tailings, and residual soils remains unknown. Hence, the predominant frequency of the ground in each site was determined based on Nakamura method. A total number of 14 sites with known depth to bedrock from the supply of geotechnical reports in the study area were determined. An empirical correlation was developed to relate the ground predominant frequency and soft ground thickness. This correlation may contribute to local soil underlying the subsurface of Kuala Lumpur area. The finding provides an important relationship for engineers to estimate the soft ground thickness in Kuala Lumpur area based on the dynamic characteristics of the ground measured from microtremor observation.

  15. Screen-based sedentary time: Association with soft drink consumption and the moderating effect of parental education in European children: The ENERGY study.

    Science.gov (United States)

    Gebremariam, Mekdes K; Chinapaw, Mai J; Bringolf-Isler, Bettina; Bere, Elling; Kovacs, Eva; Verloigne, Maïté; Stok, F Marijn; Manios, Yannis; Brug, Johannes; Lien, Nanna

    2017-01-01

    The aim of the present study was to explore if children who spend more time on screen-based sedentary behaviors (i.e.TV viewing and computer use) drink more sugar-sweetened soft drinks. The study also assessed whether these associations were independent of individual and home environmental correlates of soft drink consumption and whether they were moderated by parental education. Data were collected from 7886 children participating in the EuropeaN Energy balance Research to prevent excessive weight Gain among Youth (ENERGY) survey conducted in eight European countries. Self-report questionnaires were used. Multilevel linear regression analyses with soft drink consumption as dependent variable, TV viewing and computer use as independent variables and age, gender, parental education, attitude towards soft drinks, self-efficacy, parental modelling, parental rules and home availability of soft drinks as covariates were conducted. Further interactions were tested to explore if these associations were moderated by parental education. Country-specific analyses were conducted. In six of the eight included countries, a significant positive association was observed between TV viewing (min/day) and soft drink consumption (ml/day), independent of individual and home environmental correlates of soft drink consumption (B = 0.46 (0.26-0.66) in Greece, B = 0.77 (0.36-1.17) in Norway, B = 0.82 (0.12-1.51) in Hungary, B = 1.06 (0.67-1.46) in Spain, B = 1.21 (0.67-1.74) in Belgium and B = 1.49 (0.72-2.27) in Switzerland). There was no significant association between computer use and soft drink consumption in six of the eight included countries in the final models. Moderation effects of parental education in the association between TV viewing and soft drink consumption were found in Norway and Hungary, the association being stronger among those with low parental education. TV viewing appears to be independently associated with soft drink consumption and this association was moderated

  16. A feasibility study of the implementation of total quality management based on soft factor

    Directory of Open Access Journals (Sweden)

    Arash Shahin

    2011-07-01

    Full Text Available Purpose:  The aim of this paper is to examine the feasibility of implementing TQM based on soft factors, which can influence the successful implementation of TQM.Design/methodology/approach: A framework has been developed for the TQM soft factors based on literature review and respectively, questionnaires which are directly related to the addressed factors have been designed and distributed to the employees of an engineering service company as the main enablers of improving the effectiveness of TQM.Findings: The findings imply that committed leadership, closer customer relationship, benchmarking and process improvement have the most correlations amongst the TQM soft factors. Training is the only factor which is not correlated to other soft factors. Leadership has also the highest value among the soft factors.Research limitations/implications: The proposed framework is costly and time consuming due to the large number of questions it holds. In this study, it is assumed that sub factors have the same importance. But there is a possibility in which these subdivisions do not have the same relative importance weight. The study is also limited to one company and therefore, the findings should not be generalized.Practical implications: The proposed TQM soft factors framework can be useful for those organizations which consider TQM as an integrated quality management system as the major foundation for achievement of competitive advantage.Originality/value: A comprehensive framework for TQM soft factors has been presented since it involves almost all of the soft factors addressed in the literature.

  17. Face-based smoothed finite element method for real-time simulation of soft tissue

    Science.gov (United States)

    Mendizabal, Andrea; Bessard Duparc, Rémi; Bui, Huu Phuoc; Paulus, Christoph J.; Peterlik, Igor; Cotin, Stéphane

    2017-03-01

    In soft tissue surgery, a tumor and other anatomical structures are usually located using the preoperative CT or MR images. However, due to the deformation of the concerned tissues, this information suffers from inaccuracy when employed directly during the surgery. In order to account for these deformations in the planning process, the use of a bio-mechanical model of the tissues is needed. Such models are often designed using the finite element method (FEM), which is, however, computationally expensive, in particular when a high accuracy of the simulation is required. In our work, we propose to use a smoothed finite element method (S-FEM) in the context of modeling of the soft tissue deformation. This numerical technique has been introduced recently to overcome the overly stiff behavior of the standard FEM and to improve the solution accuracy and the convergence rate in solid mechanics problems. In this paper, a face-based smoothed finite element method (FS-FEM) using 4-node tetrahedral elements is presented. We show that in some cases, the method allows for reducing the number of degrees of freedom, while preserving the accuracy of the discretization. The method is evaluated on a simulation of a cantilever beam loaded at the free end and on a simulation of a 3D cube under traction and compression forces. Further, it is applied to the simulation of the brain shift and of the kidney's deformation. The results demonstrate that the method outperforms the standard FEM in a bending scenario and that has similar accuracy as the standard FEM in the simulations of the brain-shift and of the kidney's deformation.

  18. Reliability of Soft Tissue Model Based Implant Surgical Guides; A Methodological Mistake.

    Science.gov (United States)

    Sabour, Siamak; Dastjerdi, Elahe Vahid

    2012-08-20

    Abstract We were interested to read the paper by Maney P and colleagues published in the July 2012 issue of J Oral Implantol. The authors aimed to assess the reliability of soft tissue model based implant surgical guides reported that the accuracy was evaluated using software. 1 I found the manuscript title of Maney P, et al. incorrect and misleading. Moreover, they reported twenty-two sites (46.81%) were considered accurate (13 of 24 maxillary and 9 of 23 mandibular sites). As the authors point out in their conclusion, Soft tissue models do not always provide sufficient accuracy for implant surgical guide fabrication.Reliability (precision) and validity (accuracy) are two different methodological issues in researches. Sensitivity, specificity, PPV, NPV, likelihood ratio positive (true positive/false negative) and likelihood ratio negative (false positive/ true negative) as well as odds ratio (true results\\false results - preferably more than 50) are among the tests to evaluate the validity (accuracy) of a single test compared to a gold standard.2-4 It is not clear that the reported twenty-two sites (46.81%) which were considered accurate related to which of the above mentioned estimates for validity analysis. Reliability (repeatability or reproducibility) is being assessed by different statistical tests such as Pearson r, least square and paired t.test which all of them are among common mistakes in reliability analysis 5. Briefly, for quantitative variable Intra Class Correlation Coefficient (ICC) and for qualitative variables weighted kappa should be used with caution because kappa has its own limitation too. Regarding reliability or agreement, it is good to know that for computing kappa value, just concordant cells are being considered, whereas discordant cells should also be taking into account in order to reach a correct estimation of agreement (Weighted kappa).2-4 As a take home message, for reliability and validity analysis, appropriate tests should be

  19. Soft computing approach to 3D lung nodule segmentation in CT.

    Science.gov (United States)

    Badura, P; Pietka, E

    2014-10-01

    This paper presents a novel, multilevel approach to the segmentation of various types of pulmonary nodules in computed tomography studies. It is based on two branches of computational intelligence: the fuzzy connectedness (FC) and the evolutionary computation. First, the image and auxiliary data are prepared for the 3D FC analysis during the first stage of an algorithm - the masks generation. Its main goal is to process some specific types of nodules connected to the pleura or vessels. It consists of some basic image processing operations as well as dedicated routines for the specific cases of nodules. The evolutionary computation is performed on the image and seed points in order to shorten the FC analysis and improve its accuracy. After the FC application, the remaining vessels are removed during the postprocessing stage. The method has been validated using the first dataset of studies acquired and described by the Lung Image Database Consortium (LIDC) and by its latest release - the LIDC-IDRI (Image Database Resource Initiative) database. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

    Science.gov (United States)

    Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

    2017-07-20

    Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

  1. A New Screening Methodology for Improved Oil Recovery Processes Using Soft-Computing Techniques

    Science.gov (United States)

    Parada, Claudia; Ertekin, Turgay

    2010-05-01

    able to recognize the strong correlation between the displacement mechanism and the reservoir characteristics as they effectively forecast hydrocarbon production for different types of reservoir undergoing diverse recovery processes. The artificial neuron networks are able to capture the similarities between different displacement mechanisms as same network architecture is successfully applied in both CO2 and N2 injection. The neuro-simulation application tool is built within a graphical user interface to facilitate the display of the results. The developed soft-computing tool offers an innovative approach to design a variety of efficient and feasible IOR processes by using artificial intelligence. The tool provides appropriate guidelines to the reservoir engineer, it facilitates the appraisal of diverse field development strategies for oil reservoirs, and it helps to reduce the number of scenarios evaluated with conventional reservoir simulation.

  2. Inversion based on computational simulations

    International Nuclear Information System (INIS)

    Hanson, K.M.; Cunningham, G.S.; Saquib, S.S.

    1998-01-01

    A standard approach to solving inversion problems that involve many parameters uses gradient-based optimization to find the parameters that best match the data. The authors discuss enabling techniques that facilitate application of this approach to large-scale computational simulations, which are the only way to investigate many complex physical phenomena. Such simulations may not seem to lend themselves to calculation of the gradient with respect to numerous parameters. However, adjoint differentiation allows one to efficiently compute the gradient of an objective function with respect to all the variables of a simulation. When combined with advanced gradient-based optimization algorithms, adjoint differentiation permits one to solve very large problems of optimization or parameter estimation. These techniques will be illustrated through the simulation of the time-dependent diffusion of infrared light through tissue, which has been used to perform optical tomography. The techniques discussed have a wide range of applicability to modeling including the optimization of models to achieve a desired design goal

  3. Description of EMX computer code. System for measuring soft X rays

    International Nuclear Information System (INIS)

    Marty, D.A.; Smeulders, P.; Launois, D.

    1978-07-01

    After briefly describing the system for measuring soft X rays implanted in TFR 600, the objectives and principles of the E.M.X calculation programme are presented. This model is divided into two distinct parts. The ultimate aim of EMX 1, the first part, is to build the soft X ray photo of a plasma with varied characteristics, seen through a certain collimation system (in this case a slit). That of EMX 2, the second part, is to filter the previously built soft X ray photo, by means of the system of absorbents belonging to the measuring system and to calculate the currents generated by each detector aimed at a plasma chord. The first calculation results are commented and discussed [fr

  4. Computation of Difference Grobner Bases

    Directory of Open Access Journals (Sweden)

    Vladimir P. Gerdt

    2012-07-01

    Full Text Available This paper is an updated and extended version of our note \\cite{GR'06} (cf.\\ also \\cite{GR-ACAT}. To compute difference \\Gr bases of ideals generated by linear polynomials we adopt to difference polynomial rings the involutive algorithm based on Janet-like division. The algorithm has been implemented in Maple in the form of the package LDA (Linear Difference Algebra and we describe the main features of the package. Its applications are illustrated by generation of finite difference approximations to linear partial differential equations and by reduction of Feynman integrals. We also present the algorithm for an ideal generated by a finite set of nonlinear difference polynomials. If the algorithm terminates, then it constructs a \\Gr basis of the ideal.

  5. Systems competing for mobile factors: decision making based on hard vs. soft locational factors

    Directory of Open Access Journals (Sweden)

    Clodnițchi Roxana

    2017-12-01

    Full Text Available The paper explores the links between capital relocation and soft locational factors addressing the quality of the business environment and the quality of life within the European Union. System competition is viewed as a competition between countries for the mobile factors capital and labour. The issue of systems competition is topical and insufficiently explored by contemporary literature. The scarcity of scientific papers describing the links between system competition theories and contemporary corporate geography theories, especially of the ones including the analysis of soft location factors, is a challenging aspect, which motivates the choice of this subject. This paper’s primary aim is to deliver an overview of the basic corporate geography conceptions, stressing the importance of soft location factors in today’s competition between systems for the mobile factors capital and labour. The paper further contains an analysis of the correlations between indicators regarding the institutional design of countries as developed by the World Bank (Ease of Doing Business, the Happiness Scale and the latest available data of FDI Stocks for the EU countries (2016. The relevance of such a study is based on the evidence that the contemporary business education relies on an extensive knowledge of the business environment. In the circumstance of similar infrastructural conditions, the main difference between locations is made by soft location factors. Since developed economies are characterised by a high degree of ubiquity of soft factors, the paper concludes that developing and emerging economies should foster the development of their soft location factors.

  6. Use of synchrotron-based diffraction-enhanced imaging for visualization of soft tissues in invertebrates

    International Nuclear Information System (INIS)

    Rao, Donepudi V.; Swapna, Medasani; Cesareo, Roberto; Brunetti, Antonio; Zhong, Zhong; Akatsuka, Takao; Yuasa, Tetsuya; Takeda, Tohoru; Gigante, Giovanni E.

    2010-01-01

    Images of terrestrial and marine invertebrates (snails and bivalves) have been obtained by using an X-ray phase-contrast imaging technique, namely, synchrotron-based diffraction-enhanced imaging. Synchrotron X-rays of 20, 30 and 40 keV were used, which penetrate deep enough into animal soft tissues. The phase of X-ray photons shifts slightly as they traverse an object, such as animal soft tissue, and interact with its atoms. Biological features, such as shell morphology and animal physiology, have been visualized. The contrast of the images obtained at 40 keV is the best. This optimum energy provided a clear view of the internal structural organization of the soft tissue with better contrast. The contrast is higher at edges of internal soft-tissue structures. The image improvements achieved with the diffraction-enhanced imaging technique are due to extinction, i.e., elimination of ultra-small-angle scattering. They enabled us to identify a few embedded internal shell features, such as the origin of the apex, which is the firmly attached region of the soft tissue connecting the umbilicus to the external morphology. Diffraction-enhanced imaging can provide high-quality images of soft tissues valuable for biology.

  7. Use of synchrotron-based diffraction-enhanced imaging for visualization of soft tissues in invertebrates

    Energy Technology Data Exchange (ETDEWEB)

    Rao, Donepudi V., E-mail: donepudi_venkateswararao@rediffmail.co [Istituto di Matematica e Fisica, Universita degli Studi di Sassari, Via Vienna 2, 07100 Sassari (Italy); Swapna, Medasani, E-mail: medasanisw@gmail.co [Istituto di Matematica e Fisica, Universita degli Studi di Sassari, Via Vienna 2, 07100 Sassari (Italy); Cesareo, Roberto; Brunetti, Antonio [Istituto di Matematica e Fisica, Universita degli Studi di Sassari, Via Vienna 2, 07100 Sassari (Italy); Zhong, Zhong [National Synchrotron Light Source, Brookhaven National Laboratory, Upton, NY 11973 (United States); Akatsuka, Takao; Yuasa, Tetsuya [Department of Bio-System Engineering, Faculty of Engineering, Yamagata University, Yonezawa-shi, Yamagata-992-8510 (Japan); Takeda, Tohoru [Allied Health Science, Kitasato University 1-15-1 Kitasato, Sagamihara, Kanagawa 228-8555 (Japan); Gigante, Giovanni E. [Dipartimento di Fisica, Universita di Roma, La Sapienza, 00185 Roma (Italy)

    2010-09-15

    Images of terrestrial and marine invertebrates (snails and bivalves) have been obtained by using an X-ray phase-contrast imaging technique, namely, synchrotron-based diffraction-enhanced imaging. Synchrotron X-rays of 20, 30 and 40 keV were used, which penetrate deep enough into animal soft tissues. The phase of X-ray photons shifts slightly as they traverse an object, such as animal soft tissue, and interact with its atoms. Biological features, such as shell morphology and animal physiology, have been visualized. The contrast of the images obtained at 40 keV is the best. This optimum energy provided a clear view of the internal structural organization of the soft tissue with better contrast. The contrast is higher at edges of internal soft-tissue structures. The image improvements achieved with the diffraction-enhanced imaging technique are due to extinction, i.e., elimination of ultra-small-angle scattering. They enabled us to identify a few embedded internal shell features, such as the origin of the apex, which is the firmly attached region of the soft tissue connecting the umbilicus to the external morphology. Diffraction-enhanced imaging can provide high-quality images of soft tissues valuable for biology.

  8. A New Soft Computing Method for K-Harmonic Means Clustering.

    Science.gov (United States)

    Yeh, Wei-Chang; Jiang, Yunzhi; Chen, Yee-Fen; Chen, Zhe

    2016-01-01

    The K-harmonic means clustering algorithm (KHM) is a new clustering method used to group data such that the sum of the harmonic averages of the distances between each entity and all cluster centroids is minimized. Because it is less sensitive to initialization than K-means (KM), many researchers have recently been attracted to studying KHM. In this study, the proposed iSSO-KHM is based on an improved simplified swarm optimization (iSSO) and integrates a variable neighborhood search (VNS) for KHM clustering. As evidence of the utility of the proposed iSSO-KHM, we present extensive computational results on eight benchmark problems. From the computational results, the comparison appears to support the superiority of the proposed iSSO-KHM over previously developed algorithms for all experiments in the literature.

  9. Adaptive Channel Estimation based on Soft Information Processing in Broadband Spatial Multiplexing Receivers

    Directory of Open Access Journals (Sweden)

    P. Beinschob

    2010-11-01

    Full Text Available In this paper we present a novel approach in Multiple-Input Multiple Output (MIMO Orthogonal Frequency Division Multiplexing (OFDM channel estimation technique based on a Decision Directed Recursive Least Squares (RLS algorithm in which no pilot symbols need to be integrated in the data after a short initial preamble. The novelty and key concept of the proposed technique is the block-wise causal and anti-causal RLS processing that yields two independent processings of RLS along with the associated decisions. Due to the usage of low density parity check (LDPC channel code, the receiver operates with soft information, which enables us to introduce a new modification of the Turbo principle as well as a simple information combining approach based on approximated aposteriori log-likelihood ratios (LLRs. Although the computational complexity is increased by both of our approaches, the latter is relatively less complex than the former. Simulation results show that these implementations outperform the simple RLS-DDCE algorithm and yield lower bit error rates (BER and more accurate channel estimates.

  10. PVC gel soft actuator-based wearable assist wear for hip joint support during walking

    Science.gov (United States)

    Li, Yi; Hashimoto, Minoru

    2017-12-01

    Plasticized polyvinyl chloride (PVC) gel and mesh electrode-based soft actuators have considerable potential to provide new types of artificial muscle, exhibiting similar responsiveness to biological muscle in air, >10% deformation, >90 kPa output stress, variable stiffness, long cycle life (>5 million cycles), and low power consumption. We have designed and fabricated a prototype of walking assist wear using the PVC gel actuator in previous study. The system has several advantages compared with traditional motor-based exoskeletons, including lower weight and power consumption, and no requirement for rigid external structures that constrain the wearer’s joints. In this study, we designed and established a control and power system to making the whole system portable and wearable outdoors. And we designed two control strategies based on the characteristics of the assist wear and the biological kinematics. In a preliminary experimental evaluation, a hemiparetic stroke patient performed a 10 m to-and-fro straight line walking task with and without assist wear on the affected side. We found that the assist wear enabled natural movement, increasing step length and decreasing muscular activity during straight line walking. We demonstrated that the assistance effect could be adjusted by controlling the on-off time of the PVC gel soft actuators. The results show the effectiveness of the proposed system and suggest the feasibility of PVC gel soft actuators for developing practical soft wearable assistive devices, informing the development of future wearable robots and the other soft actuator technologies for human movement assistance and rehabilitation.

  11. SoftWAXS: a computational tool for modeling wide-angle X-ray solution scattering from biomolecules.

    Science.gov (United States)

    Bardhan, Jaydeep; Park, Sanghyun; Makowski, Lee

    2009-10-01

    This paper describes a computational approach to estimating wide-angle X-ray solution scattering (WAXS) from proteins, which has been implemented in a computer program called SoftWAXS. The accuracy and efficiency of SoftWAXS are analyzed for analytically solvable model problems as well as for proteins. Key features of the approach include a numerical procedure for performing the required spherical averaging and explicit representation of the solute-solvent boundary and the surface of the hydration layer. These features allow the Fourier transform of the excluded volume and hydration layer to be computed directly and with high accuracy. This approach will allow future investigation of different treatments of the electron density in the hydration shell. Numerical results illustrate the differences between this approach to modeling the excluded volume and a widely used model that treats the excluded-volume function as a sum of Gaussians representing the individual atomic excluded volumes. Comparison of the results obtained here with those from explicit-solvent molecular dynamics clarifies shortcomings inherent to the representation of solvent as a time-averaged electron-density profile. In addition, an assessment is made of how the calculated scattering patterns depend on input parameters such as the solute-atom radii, the width of the hydration shell and the hydration-layer contrast. These results suggest that obtaining predictive calculations of high-resolution WAXS patterns may require sophisticated treatments of solvent.

  12. Percutaneous computed tomography-guided core needle biopsy of soft tissue tumors: results and correlation with surgical specimen analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chojniak, Rubens; Grigio, Henrique Ramos; Bitencourt, Almir Galvao Vieira; Pinto, Paula Nicole Vieira; Tyng, Chiang J.; Cunha, Isabela Werneck da; Aguiar Junior, Samuel; Lopes, Ademar, E-mail: chojniak@uol.com.br [Hospital A.C. Camargo, Sao Paulo, SP (Brazil)

    2012-09-15

    Objective: To evaluate the efficacy of percutaneous computed tomography (CT)-guided core needle biopsy of soft tissue tumors in obtaining appropriate samples for histological analysis, and compare its diagnosis with the results of the surgical pathology as available. Materials and Methods: The authors reviewed medical records, imaging and histological reports of 262 patients with soft-tissue tumors submitted to CT-guided core needle biopsy in an oncologic reference center between 2003 and 2009. Results: Appropriate samples were obtained in 215 (82.1%) out of the 262 patients. The most prevalent tumors were sarcomas (38.6%), metastatic carcinomas (28.8%), benign mesenchymal tumors (20.5%) and lymphomas (9.3%). Histological grading was feasible in 92.8% of sarcoma patients, with the majority of them (77.9%) being classified as high grade tumors. Out of the total sample, 116 patients (44.3%) underwent surgical excision and diagnosis confirmation. Core biopsy demonstrated 94.6% accuracy in the identification of sarcomas, with 96.4% sensitivity and 89.5% specificity. A significant intermethod agreement about histological grading was observed between core biopsy and surgical resection (p < 0.001; kappa = 0.75). Conclusion: CT-guided core needle biopsy demonstrated a high diagnostic accuracy in the evaluation of soft tissue tumors as well as in the histological grading of sarcomas, allowing an appropriate therapeutic planning (author)

  13. Rod-based Fabrication of Customizable Soft Robotic Pneumatic Gripper Devices for Delicate Tissue Manipulation.

    Science.gov (United States)

    Low, Jin-Huat; Yeow, Chen-Hua

    2016-08-02

    Soft compliant gripping is essential in delicate surgical manipulation for minimizing the risk of tissue grip damage caused by high stress concentrations at the point of contact. It can be achieved by complementing traditional rigid grippers with soft robotic pneumatic gripper devices. This manuscript describes a rod-based approach that combined both 3D-printing and a modified soft lithography technique to fabricate the soft pneumatic gripper. In brief, the pneumatic featureless mold with chamber component is 3D-printed and the rods were used to create the pneumatic channels that connect to the chamber. This protocol eliminates the risk of channels occluding during the sealing process and the need for external air source or related control circuit. The soft gripper consists of a chamber filled with air, and one or more gripper arms with a pneumatic channel in each arm connected to the chamber. The pneumatic channel is positioned close to the outer wall to create different stiffness in the gripper arm. Upon compression of the chamber which generates pressure on the pneumatic channel, the gripper arm will bend inward to form a close grip posture because the outer wall area is more compliant. The soft gripper can be inserted into a 3D-printed handling tool with two different control modes for chamber compression: manual gripper mode with a movable piston, and robotic gripper mode with a linear actuator. The double-arm gripper with two actuatable arms was able to pick up objects of sizes up to 2 mm and yet generate lower compressive forces as compared to elastomer-coated and non-coated rigid grippers. The feasibility of having other designs, such as single-arm or hook gripper, was also demonstrated, which further highlighted the customizability of the soft gripper device, and it's potential to be used in delicate surgical manipulation to reduce the risk of tissue grip damage.

  14. Ultra-soft PDMS-based magnetoactive elastomers as dynamic cell culture substrata.

    Directory of Open Access Journals (Sweden)

    Matthias Mayer

    Full Text Available Mechanical cues such as extracellular matrix stiffness and movement have a major impact on cell differentiation and function. To replicate these biological features in vitro, soft substrata with tunable elasticity and the possibility for controlled surface translocation are desirable. Here we report on the use of ultra-soft (Young's modulus <100 kPa PDMS-based magnetoactive elastomers (MAE as suitable cell culture substrata. Soft non-viscous PDMS (<18 kPa is produced using a modified extended crosslinker. MAEs are generated by embedding magnetic microparticles into a soft PDMS matrix. Both substrata yield an elasticity-dependent (14 vs. 100 kPa modulation of α-smooth muscle actin expression in primary human fibroblasts. To allow for static or dynamic control of MAE material properties, we devise low magnetic field (≈40 mT stimulation systems compatible with cell-culture environments. Magnetic field-instigated stiffening (14 to 200 kPa of soft MAE enhances the spreading of primary human fibroblasts and decreases PAX-7 transcription in human mesenchymal stem cells. Pulsatile MAE movements are generated using oscillating magnetic fields and are well tolerated by adherent human fibroblasts. This MAE system provides spatial and temporal control of substratum material characteristics and permits novel designs when used as dynamic cell culture substrata or cell culture-coated actuator in tissue engineering applications or biomedical devices.

  15. Soft, chewable gelatin-based pharmaceutical oral formulations: a technical approach.

    Science.gov (United States)

    Dille, Morten J; Hattrem, Magnus N; Draget, Kurt I

    2018-06-01

    Hard tablets and capsules for oral drug delivery cause problems for people experiencing dysphagia. This work describes the formulation and properties of a gelatin based, self-preserved, and soft chewable tablet as an alternative and novel drug delivery format. Gelatin (8.8-10% in 24.7-29% water) constituted the matrix of the soft, semi-solid tablets. Three different pharmaceuticals (Ibuprofen 10%, Acetaminophen 15%, and Meloxicam 1.5%) were tested in this formulation. Microbial stability was controlled by lowering the water activity with a mixture of sorbitol and xylitol (45.6-55%). Rheological properties were tested applying small strain oscillation measurements. Taste masking of ibuprofen soft-chew tablets was achieved by keeping the ibuprofen insoluble at pH 4.5 and keeping the processing temperature below the crystalline-to-amorphous transition temperature. Soft-chew formulations showed good stability for all three pharmaceuticals (up to 24 months), and the ibuprofen containing formulation exhibited comparable dissolution to a standard oral tablet as well as good microbial stability. The rheological properties of the ibuprofen/gelatin formulation had the fingerprint of a true gelatin gel, albeit higher moduli, and melting temperature. The results suggest that easy-to-swallow and well taste-masked soft chewable tablet formulations with extended shelf life are within reach for several active pharmaceutical ingredients (APIs).

  16. Computer-Based Learning in Open and Distance Learning Institutions in Nigeria: Cautions on Use of Internet for Counseling

    Science.gov (United States)

    Okopi, Fidel Onjefu; Odeyemi, Olajumoke Janet; Adesina, Adewale

    2015-01-01

    The study has identified the areas of strengths and weaknesses in the current use of Computer Based Learning (CBL) tools in Open and Distance Learning (ODL) institutions in Nigeria. To achieve these objectives, the following research questions were proposed: (i) What are the computer-based learning tools (soft and hard ware) that are actually in…

  17. Constraint-Muse: A Soft-Constraint Based System for Music Therapy

    Science.gov (United States)

    Hölzl, Matthias; Denker, Grit; Meier, Max; Wirsing, Martin

    Monoidal soft constraints are a versatile formalism for specifying and solving multi-criteria optimization problems with dynamically changing user preferences. We have developed a prototype tool for interactive music creation, called Constraint Muse, that uses monoidal soft constraints to ensure that a dynamically generated melody harmonizes with input from other sources. Constraint Muse provides an easy to use interface based on Nintendo Wii controllers and is intended to be used in music therapy for people with Parkinson’s disease and for children with high-functioning autism or Asperger’s syndrome.

  18. Soft sensor development for Mooney viscosity prediction in rubber mixing process based on GMMDJITGPR algorithm

    Science.gov (United States)

    Yang, Kai; Chen, Xiangguang; Wang, Li; Jin, Huaiping

    2017-01-01

    In rubber mixing process, the key parameter (Mooney viscosity), which is used to evaluate the property of the product, can only be obtained with 4-6h delay offline. It is quite helpful for the industry, if the parameter can be estimate on line. Various data driven soft sensors have been used to prediction in the rubber mixing. However, it always not functions well due to the phase and nonlinear property in the process. The purpose of this paper is to develop an efficient soft sensing algorithm to solve the problem. Based on the proposed GMMD local sample selecting criterion, the phase information is extracted in the local modeling. Using the Gaussian local modeling method within Just-in-time (JIT) learning framework, nonlinearity of the process is well handled. Efficiency of the new method is verified by comparing the performance with various mainstream soft sensors, using the samples from real industrial rubber mixing process.

  19. An Enhanced Soft Vibrotactile Actuator Based on ePVC Gel with Silicon Dioxide Nanoparticles.

    Science.gov (United States)

    Park, Won-Hyeong; Shin, Eun-Jae; Yun, Sungryul; Kim, Sang-Youn

    2018-01-01

    In this paper, we propose a soft vibrotactile actuator made by mixing silicon dioxide nanoparticles and plasticized PVC gel. The effect of the silicon dioxide nanoparticles in the plasticized PVC gel for the haptic performance is investigated in terms of electric, dielectric, and mechanical properties. Furthermore, eight soft vibrotactile actuators are prepared as a function of the content. Experiments are conducted to examine the haptic performance of the prepared eight soft vibrotactile actuators and to find the best weight ratio of the plasticized PVC gel to the nanoparticles. The experiments should show that the plasticized PVC gel with silicon dioxide nanoparticles improves the haptic performance of the plasticized PVC gel-based vibrotactile actuator, and the proposed vibrotactile actuator can create a variety of haptic sensations in a wide frequency range.

  20. A development of laser-plasma-based soft x-ray microscope system

    International Nuclear Information System (INIS)

    Nam, Ki Yong; Kim, Kyong Woo; Kim, Kyu Gyeom; Kwon, Young Man; Yoon, Kwon Ha

    2003-01-01

    Soft x-ray nano-imaging microscopy system for biomedical application with a high resolution about 50 nm has been designed and described, and its integrated techniques also have been studied. The system is mainly composed of soft x-ray generation system, nano-scaled control system, x-ray optical device like a condenser or object mirror, a CCD camera coupled with multichannel plate (MCP) and vacuum system. In the system, soft x-ray is generated from the laser-based plasma by focusing Nd:YAG laser beam on tantalum (Ta) target. In an x-ray optical system, a wolter mirror has been considering condensing the x-ray beam on a biological specimen and zone plate was adapted as an object mirror. A Si 3 N 4 was used as specimen holder for keeping a biological sample alive in atmosphere conditions. A back-illuminated-CCD camera coupled with multichannel plate was determined to set up.

  1. A New Inverted Torsion Pendulum-Based Mechanical Spectrometer to Study Soft Matter

    Directory of Open Access Journals (Sweden)

    Lei M.L.

    2016-03-01

    Full Text Available A new multifunctional mechanical spectrometer is developed based on an inverted torsion pendulum showing high precision in a wide frequency range to study soft matter. Apart from measuring the internal friction of solids it can also be used to study viscoelasticity. In this report we describe basic principles of the novel instrument.

  2. Simulation of the soft-landing and adsorption of C{sub 60} molecules on a graphite substrate and computation of their scanning-tunnelling-microscopy-like images

    Energy Technology Data Exchange (ETDEWEB)

    Rafii-Tabar, H. [Computational Nano-Science Research Group, Centre for Numerical Modelling and Process Analysis, School of Computing and Mathematical Sciences, University of Greenwich, Greenwich, London (United Kingdom); Jurczyszyn, L.; Stankiewicz, B. [Institute of Experimental Physics, University of Wroclaw, Wroclaw (Poland)

    2000-07-03

    A constant-temperature molecular dynamics (MD) simulation was performed to model the soft-landing and adsorption of C{sub 60} molecules on a graphite substrate with the C{sub 60}s treated as soft molecules and released individually towards the substrate. The intra-molecular and intra-planar covalently bonding interactions were modelled by very accurate many-body potentials, and the non-bonding forces were derived from various pairwise potentials. The simulation extended over 1.6 million time steps covering a significant period of 160 picoseconds. The final alignment of the molecules on the surface agrees closely with that observed in an experiment based on scanning tunnelling microscopy (STM) on the same system, performed at room temperature and under ultrahigh-vacuum (UHV) conditions. Using a tungsten tip in a constant-current mode of imaging, we have also computed the STM-like images of one of the adsorbed molecules using a formulation of the STM tunnelling current based on Keldysh's non-equilibrium Green function formalism. Our aim has been to search for tip-induced states, which were speculated, on the basis of another STM-based experiment, performed in air, to form one of the possible origins of the extra features purported to have been observed in that experiment. We have not obtained any such states. (author)

  3. Fuzzy classification for strawberry diseases-infection using machine vision and soft-computing techniques

    Science.gov (United States)

    Altıparmak, Hamit; Al Shahadat, Mohamad; Kiani, Ehsan; Dimililer, Kamil

    2018-04-01

    Robotic agriculture requires smart and doable techniques to substitute the human intelligence with machine intelligence. Strawberry is one of the important Mediterranean product and its productivity enhancement requires modern and machine-based methods. Whereas a human identifies the disease infected leaves by his eye, the machine should also be capable of vision-based disease identification. The objective of this paper is to practically verify the applicability of a new computer-vision method for discrimination between the healthy and disease infected strawberry leaves which does not require neural network or time consuming trainings. The proposed method was tested under outdoor lighting condition using a regular DLSR camera without any particular lens. Since the type and infection degree of disease is approximated a human brain a fuzzy decision maker classifies the leaves over the images captured on-site having the same properties of human vision. Optimizing the fuzzy parameters for a typical strawberry production area at a summer mid-day in Cyprus produced 96% accuracy for segmented iron deficiency and 93% accuracy for segmented using a typical human instant classification approximation as the benchmark holding higher accuracy than a human eye identifier. The fuzzy-base classifier provides approximate result for decision making on the leaf status as if it is healthy or not.

  4. Multifractal Analysis of Seismically Induced Soft-Sediment Deformation Structures Imaged by X-Ray Computed Tomography

    Science.gov (United States)

    Nakashima, Yoshito; Komatsubara, Junko

    Unconsolidated soft sediments deform and mix complexly by seismically induced fluidization. Such geological soft-sediment deformation structures (SSDSs) recorded in boring cores were imaged by X-ray computed tomography (CT), which enables visualization of the inhomogeneous spatial distribution of iron-bearing mineral grains as strong X-ray absorbers in the deformed strata. Multifractal analysis was applied to the two-dimensional (2D) CT images with various degrees of deformation and mixing. The results show that the distribution of the iron-bearing mineral grains is multifractal for less deformed/mixed strata and almost monofractal for fully mixed (i.e. almost homogenized) strata. Computer simulations of deformation of real and synthetic digital images were performed using the egg-beater flow model. The simulations successfully reproduced the transformation from the multifractal spectra into almost monofractal spectra (i.e. almost convergence on a single point) with an increase in deformation/mixing intensity. The present study demonstrates that multifractal analysis coupled with X-ray CT and the mixing flow model is useful to quantify the complexity of seismically induced SSDSs, standing as a novel method for the evaluation of cores for seismic risk assessment.

  5. Computer-Based Linguistic Analysis.

    Science.gov (United States)

    Wright, James R.

    Noam Chomsky's transformational-generative grammar model may effectively be translated into an equivalent computer model. Phrase-structure rules and transformations are tested as to their validity and ordering by the computer via the process of random lexical substitution. Errors appearing in the grammar are detected and rectified, and formal…

  6. A Theoretical Framework for Soft-Information-Based Synchronization in Iterative (Turbo Receivers

    Directory of Open Access Journals (Sweden)

    Lottici Vincenzo

    2005-01-01

    Full Text Available This contribution considers turbo synchronization, that is to say, the use of soft data information to estimate parameters like carrier phase, frequency, or timing offsets of a modulated signal within an iterative data demodulator. In turbo synchronization, the receiver exploits the soft decisions computed at each turbo decoding iteration to provide a reliable estimate of some signal parameters. The aim of our paper is to show that such "turbo-estimation" approach can be regarded as a special case of the expectation-maximization (EM algorithm. This leads to a general theoretical framework for turbo synchronization that allows to derive parameter estimation procedures for carrier phase and frequency offset, as well as for timing offset and signal amplitude. The proposed mathematical framework is illustrated by simulation results reported for the particular case of carrier phase and frequency offsets estimation of a turbo-coded 16-QAM signal.

  7. A Computing Method to Determine the Performance of an Ionic Liquid Gel Soft Actuator.

    Science.gov (United States)

    He, Bin; Zhang, Chenghong; Zhou, Yanmin; Wang, Zhipeng

    2018-01-01

    A new type of soft actuator material-an ionic liquid gel (ILG) that consists of BMIMBF 4 , HEMA, DEAP, and ZrO 2 -is polymerized into a gel state under ultraviolet (UV) light irradiation. In this paper, we first propose that the ILG conforms to the assumptions of hyperelastic theory and that the Mooney-Rivlin model can be used to study the properties of the ILG. Under the five-parameter and nine-parameter Mooney-Rivlin models, the formulas for the calculation of the uniaxial tensile stress, plane uniform tensile stress, and 3D directional stress are deduced. The five-parameter and nine-parameter Mooney-Rivlin models of the ILG with a ZrO 2 content of 3 wt% were obtained by uniaxial tensile testing, and the parameters are denoted as c 10 , c 01 , c 20 , c 11 , and c 02 and c 10 , c 01 , c 20 , c 11 , c 02 , c 30 , c 21 , c 12 , and c 03 , respectively. Through the analysis and comparison of the uniaxial tensile stress between the calculated and experimental data, the error between the stress data calculated from the five-parameter Mooney-Rivlin model and the experimental data is less than 0.51%, and the error between the stress data calculated from the nine-parameter Mooney-Rivlin model and the experimental data is no more than 8.87%. Hence, our work presents a feasible and credible formula for the calculation of the stress of the ILG. This work opens a new path to assess the performance of a soft actuator composed of an ILG and will contribute to the optimized design of soft robots.

  8. HuRECA: Human Reliability Evaluator for Computer-based Control Room Actions

    International Nuclear Information System (INIS)

    Kim, Jae Whan; Lee, Seung Jun; Jang, Seung Cheol

    2011-01-01

    As computer-based design features such as computer-based procedures (CBP), soft controls (SCs), and integrated information systems are being adopted in main control rooms (MCR) of nuclear power plants, a human reliability analysis (HRA) method capable of dealing with the effects of these design features on human reliability is needed. From the observations of human factors engineering verification and validation experiments, we have drawn some major important characteristics on operator behaviors and design-related influencing factors (DIFs) from the perspective of human reliability. Firstly, there are new DIFs that should be considered in developing an HRA method for computer-based control rooms including especially CBP and SCs. In the case of the computer-based procedure rather than the paper-based procedure, the structural and managerial elements should be considered as important PSFs in addition to the procedural contents. In the case of the soft controllers, the so-called interface management tasks (or secondary tasks) should be reflected in the assessment of human error probability. Secondly, computer-based control rooms can provide more effective error recovery features than conventional control rooms. Major error recovery features for computer-based control rooms include the automatic logic checking function of the computer-based procedure and the information sharing feature of the general computer-based designs

  9. Towards 3D ultrasound image based soft tissue tracking: a transrectal ultrasound prostate image alignment system.

    Science.gov (United States)

    Baumann, Michael; Mozer, Pierre; Daanen, Vincent; Troccaz, Jocelyne

    2007-01-01

    The emergence of real-time 3D ultrasound (US) makes it possible to consider image-based tracking of subcutaneous soft tissue targets for computer guided diagnosis and therapy. We propose a 3D transrectal US based tracking system for precise prostate biopsy sample localisation. The aim is to improve sample distribution, to enable targeting of unsampled regions for repeated biopsies, and to make post-interventional quality controls possible. Since the patient is not immobilized, since the prostate is mobile and due to the fact that probe movements are only constrained by the rectum during biopsy acquisition, the tracking system must be able to estimate rigid transformations that are beyond the capture range of common image similarity measures. We propose a fast and robust multi-resolution attribute-vector registration approach that combines global and local optimization methods to solve this problem. Global optimization is performed on a probe movement model that reduces the dimensionality of the search space and thus renders optimization efficient. The method was tested on 237 prostate volumes acquired from 14 different patients for 3D to 3D and 3D to orthogonal 2D slices registration. The 3D-3D version of the algorithm converged correctly in 96.7% of all cases in 6.5s with an accuracy of 1.41mm (r.m.s.) and 3.84mm (max). The 3D to slices method yielded a success rate of 88.9% in 2.3s with an accuracy of 1.37mm (r.m.s.) and 4.3mm (max).

  10. Relationship between soft stratum thickness and predominant frequency of ground based on microtremor observation data

    Science.gov (United States)

    Chia, Kenny; Lau, Tze Liang

    2017-07-01

    Despite categorized as low seismicity group, until being affected by distant earthquake ground motion from Sumatra and the recent 2015 Sabah Earthquake, Malaysia has come to realize that seismic hazard in the country is real and has the potential to threaten the public safety and welfare. The major concern in this paper is to study the effect of local site condition, where it could amplify the magnitude of ground vibration at sites. The aim for this study is to correlate the thickness of soft stratum with the predominant frequency of soil. Single point microtremor measurements were carried out at 24 selected points where the site investigation reports are available. Predominant period and frequency at each site are determined by Nakamura's method. The predominant period varies from 0.22 s to 0.98 s. Generally, the predominant period increases when getting closer to the shoreline which has thicker sediments. As far as the thickness of the soft stratum could influence the amplification of seismic wave, the advancement of micotremor observation to predict the thickness of soft stratum (h) from predominant frequency (fr) is of the concern. Thus an empirical relationship h =54.917 fr-1.314 is developed based on the microtremor observation data. The empirical relationship will be benefited in the prediction of thickness of soft stratum based on microtremor observation for seismic design with minimal cost compared to conventional boring method.

  11. Novel fabrication of flexible graphene-based chemical sensors with heaters using soft lithographic patterning method.

    Science.gov (United States)

    Jung, Min Wook; Myung, Sung; Song, Wooseok; Kang, Min-A; Kim, Sung Ho; Yang, Cheol-Soo; Lee, Sun Sook; Lim, Jongsun; Park, Chong-Yun; Lee, Jeong-O; An, Ki-Seok

    2014-08-27

    We have fabricated graphene-based chemical sensors with flexible heaters for the highly sensitive detection of specific gases. We believe that increasing the temperature of the graphene surface significantly enhanced the electrical signal change of the graphene-based channel, and reduced the recovery time needed to obtain a normal state of equilibrium. In addition, a simple and efficient soft lithographic patterning process was developed via surface energy modification for advanced, graphene-based flexible devices, such as gas sensors. As a proof of concept, we demonstrated the high sensitivity of NO2 gas sensors based on graphene nanosheets. These devices were fabricated using a simple soft-lithographic patterning method, where flexible graphene heaters adjacent to the channel of sensing graphene were utilized to control graphene temperature.

  12. Soft magnetic properties of bulk amorphous Co-based samples

    International Nuclear Information System (INIS)

    Fuezer, J.; Bednarcik, J.; Kollar, P.

    2006-01-01

    Ball milling of melt-spun ribbons and subsequent compaction of the resulting powders in the supercooled liquid region were used to prepare disc shaped bulk amorphous Co-based samples. The several bulk samples have been prepared by hot compaction with subsequent heat treatment (500 deg C - 575 deg C). The influence of the consolidation temperature and follow-up heat treatment on the magnetic properties of bulk samples was investigated. The final heat treatment leads to decrease of the coercivity to the value between the 7.5 to 9 A/m (Authors)

  13. Computer-Based Learning in Chemistry Classes

    Science.gov (United States)

    Pietzner, Verena

    2014-01-01

    Currently not many people would doubt that computers play an essential role in both public and private life in many countries. However, somewhat surprisingly, evidence of computer use is difficult to find in German state schools although other countries have managed to implement computer-based teaching and learning in their schools. This paper…

  14. Evidence-Based Soft Tissue Rheumatology IV: Anserine Bursitis.

    Science.gov (United States)

    Alvarez-Nemegyei, Jose; Canoso, Juan J

    2004-08-01

    Anserine bursitis is a frequent cause of medial knee pain. Despite its name, the structure at fault causing the symptoms remains unknown. Diabetes mellitus is a known predisposing factor leading to the condition. Overweight and knee osteoarthritis are possible additional risk factors, but their role has yet to be assessed. Anserine bursitis is diagnosed clinically based on medial knee pain and localized tenderness at the inferomedial knee. Current treatment of anserine bursitis includes nonsteroidal anti-inflammatory dugs, physiotherapy, and local glucocorticoid injections. Of these, only the latter has been shown effective in clinical trials. Knowledge gaps in the epidemiology, pathology, and pathogenesis of anserine bursitis should lead to additional research efforts on this common and perplexing condition.

  15. Estimated intake of the sweeteners, acesulfame-K and aspartame, from soft drinks, soft drinks based on mineral waters and nectars for a group of Portuguese teenage students.

    Science.gov (United States)

    Lino, C M; Costa, I M; Pena, A; Ferreira, R; Cardoso, S M

    2008-11-01

    In a survey of levels of acesulfame-K and aspartame in soft drinks and in light nectars, the intake of these intense sweeteners was estimated for a group of teenage students. Acesulfame-K was detected in 72% of the soft drinks, with a mean concentration of 72 mg l(-1) and aspartame was found in 92% of the samples with a mean concentration of 89 mg l(-1). When data on the content of these sweeteners in soft drinks were analysed according to flavour, cola drinks had the highest mean levels for both sweeteners with 98 and 103 mg l(-1) for acesulfame-K and aspartame, respectively. For soft drinks based on mineral water, aspartame was found in 62% of the samples, with a mean concentration of 82 mg l(-1) and acesulfame-K was found in 77%, with a mean level of 48 mg l(-1). All samples of nectars contained acesulfame-K, with a mean concentration of 128 mg l(-1) and aspartame was detected in 80% of the samples with a mean concentration of 73 mg l(-1). A frequency questionnaire, designed to identify adolescents having high consumption of these drinks, was completed by a randomly selected sample of teenagers (n = 65) living in the city of Coimbra, in 2007. The estimated daily intakes (EDI) of acesulfame-K and aspartame for the average consumer were below the acceptable daily intakes (ADIs). For acesulfame-K, the EDI was 0.7 mg kg(-1) bw day(-1) for soft drinks, 0.2 mg kg(-1) bw day(-1) for soft drinks based on mineral waters, and 0.5 mg kg(-1) bw day(-1) for nectars, representing 8.0%, 2.2%, and 5.8% of the ADI, respectively. A similar situation was observed for aspartame. In this way, the EDI for soft drinks was 1.1 mg kg(-1) day(-1), representing only 2.9% of the ADI. In respect of nectars, the EDI was 0.2 mg kg(-1) bw day(-1), representing 0.5% of the ADI. Soft drinks based on mineral waters showed the lowest EDI values of 0.3 mg kg(-1) bw day(-1), accounting for 0.7% of the ADI.

  16. Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

    Directory of Open Access Journals (Sweden)

    Manish Biyani

    2015-07-01

    Full Text Available Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density, ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era.

  17. Soft Measurement Modeling Based on Chaos Theory for Biochemical Oxygen Demand (BOD

    Directory of Open Access Journals (Sweden)

    Junfei Qiao

    2016-12-01

    Full Text Available The precision of soft measurement for biochemical oxygen demand (BOD is always restricted due to various factors in the wastewater treatment plant (WWTP. To solve this problem, a new soft measurement modeling method based on chaos theory is proposed and is applied to BOD measurement in this paper. Phase space reconstruction (PSR based on Takens embedding theorem is used to extract more information from the limited datasets of the chaotic system. The WWTP is first testified as a chaotic system by the correlation dimension (D, the largest Lyapunov exponents (λ1, the Kolmogorov entropy (K of the BOD and other water quality parameters time series. Multivariate chaotic time series modeling method with principal component analysis (PCA and artificial neural network (ANN is then adopted to estimate the value of the effluent BOD. Simulation results show that the proposed approach has higher accuracy and better prediction ability than the corresponding modeling approaches not based on chaos theory.

  18. Development of Compact Soft X-ray Source Based on Laser Undulator

    CERN Document Server

    Kuroda, Ryunosuke; Minamiguchi, S; Saitô, T; Ueyama, D; Washio, Masakazu

    2004-01-01

    A compact soft X-ray source is required in various research fields such as material and biological science. The laser undulator based on backward Compton scattering has been developed as a compact soft X-ray source for the biological observation at Waseda University. It is performed in a water window region (250eV - 500 eV) using the interaction between 1047 nm Nd:YLF laser and 4 MeV high quality electron beam generated from rf gun system. The range of energy in the water window region has K-shell absorption edges of Oxygen, Carbon and Nitrogen, which mainly constitute of living body. Since the absorption coefficient of water is much smaller than the protein’s coefficient in this range, a dehydration of the specimens is not necessary. As a preliminary experiment, about 300 eV X-ray generation was carried out. As next step, soft X-ray optics with zone plate was proposed for Soft X-ray microscopy. In this conference, we will report details and results of the experiment.

  19. Computer Based Modelling and Simulation

    Indian Academy of Sciences (India)

    where x increases from zero to N, the saturation value. Box 1. Matrix Meth- ... such as Laplace transforms and non-linear differential equa- tions with .... atomic bomb project in the. US in the early ... his work on game theory and computers.

  20. Estimation of Rivers Dissolved Solids TDS by Soft Computing (Case Study: Upstream of Boukan Dam

    Directory of Open Access Journals (Sweden)

    S. Zaman Zad Ghavidel

    2017-01-01

    correlations for GEP5 models (R2 = 0.0011 for Anyan station and R2 = 0.0123 for safakhaneh station which are negligible small. Plots of the residuals versus model computed values can be more informative regarding model fitting to a data set. If the residuals appear to behave randomly it suggests that the model fits the data well. On the other hand, if non- random distribution is evident in the residuals, the model does not fit the data adequately. On the base of these results, we propose GEP, ANFIS-SC and ANN methods as effective tools for the computation of total dissolved solids in river water, respectively. Conclusion: It can be concluded that the ANN, ANFIS-GP, ANFIS-SC and GEP models can be considered as promising tools for forecasting TDS values, based on water quality parameters. It is notable from the results that the prediction accuracy of all applied models increases by increasing the number of input combinations. With attention to the aim of current research that is presenting the feasibility of artificial intelligence techniques for modeling TDS values, it is notable that the results presented in this paper are for research purpose and applying the abstained results for real-world needs some complicated steps and building artificial intelligences methods, based on complete data and parameters maybe affected the TDS values.

  1. Investigation of coupling of magnetohydrodynamic modes by soft x-ray computer tomography on the WT-3 tokamak

    International Nuclear Information System (INIS)

    Yoshimura, Satoru; Maekawa, Takashi; Terumichi, Yasushi

    2002-01-01

    The internal structure of the stationary m=1 and m=2 modes in an ohmic heating plasma and the double m=1 mode structure in a lower hybrid current drive plasma are investigated on the WT-3 tokamak [Maehara et al., Nucl. Fusion 38, 39 (1998)] using computer tomography after the application of the singular value decomposition to the soft x-ray signals. The results show that, in both cases, two coexisting modes have the same frequency and have a fixed mutual phase relation, indicating that two modes are coupled and rotate as one body in the toroidal direction. It is found that the mutual inductance of two loops of helical current filaments for producing magnetic islands always takes the maximum at the experimentally observed positions of two-mode structures. This result means not only that the electromagnetic coupling of two current loops is at the maximum, but also that the two loops are in the dynamically stable position

  2. Application of the Hard and Soft, Acids and Bases (HSAB) theory to toxicant--target interactions.

    Science.gov (United States)

    Lopachin, Richard M; Gavin, Terrence; Decaprio, Anthony; Barber, David S

    2012-02-20

    Many chemical toxicants and/or their active metabolites are electrophiles that cause cell injury by forming covalent bonds with nucleophilic targets on biological macromolecules. Covalent reactions between nucleophilic and electrophilic reagents are, however, discriminatory since there is a significant degree of selectivity associated with these interactions. Over the course of the past few decades, the theory of Hard and Soft, Acids and Bases (HSAB) has proven to be a useful tool in predicting the outcome of such reactions. This concept utilizes the inherent electronic characteristic of polarizability to define, for example, reacting electrophiles and nucleophiles as either hard or soft. These HSAB definitions have been successfully applied to chemical-induced toxicity in biological systems. Thus, according to this principle, a toxic electrophile reacts preferentially with biological targets of similar hardness or softness. The soft/hard classification of a xenobiotic electrophile has obvious utility in discerning plausible biological targets and molecular mechanisms of toxicity. The purpose of this perspective is to discuss the HSAB theory of electrophiles and nucleophiles within a toxicological framework. In principle, covalent bond formation can be described by using the properties of their outermost or frontier orbitals. Because these orbital energies for most chemicals can be calculated using quantum mechanical models, it is possible to quantify the relative softness (σ) or hardness (η) of electrophiles or nucleophiles and to subsequently convert this information into useful indices of reactivity. This atomic level information can provide insight into the design of corroborative laboratory research and thereby help investigators discern corresponding molecular sites and mechanisms of toxicant action. The use of HSAB parameters has also been instrumental in the development and identification of potential nucleophilic cytoprotectants that can scavenge toxic

  3. APPLICATION OF THE HARD AND SOFT, ACIDS AND BASES (HSAB) THEORY TO TOXICANT-TARGET INTERACTIONS

    Science.gov (United States)

    LoPachin, Richard M.; Gavin, Terrence; DeCaprio, Anthony; Barber, David S.

    2011-01-01

    Many chemical toxicants and/or their active metabolites are electrophiles that cause cell injury by forming covalent bonds with nucleophilic targets on biological macromolecules. Covalent reactions between nucleophilic and electrophilic reagents are however discriminatory, since there is a significant degree of selectivity associated with these interactions. Over the course of the past few decades, the theory of Hard and Soft, Acid and Bases (HSAB) has proven to be a useful tool in predicting the outcome of such reactions. This concept utilizes the inherent electronic characteristic of polarizability to define, for example, reacting electrophiles and nucleophiles as either hard or soft. These HSAB definitions have been successfully applied to chemical-induced toxicity in biological systems. Thus, according to this principle, a toxic electrophile reacts preferentially with biological targets of similar hardness or softness. The soft/hard classification of a xenobiotic electrophile has obvious utility in discerning plausible biological targets and molecular mechanisms of toxicity. The purpose of this Perspective is to discuss the HSAB theory of electrophiles and nucleophiles within a toxicological framework. In principle, covalent bond formation can be described by using the properties of their outermost or frontier orbitals. Because these orbital energies for most chemicals can be calculated using quantum mechanical models, it is possible to quantify the relative softness (σ) or hardness (η) of electrophiles or nucleophiles and to subsequently convert this information into useful indices of reactivity. This atomic level information can provide insight into the design of corroborative laboratory research and thereby help investigators discern corresponding molecular sites and mechanisms of toxicant action. The use of HSAB parameters has also been instrumental in the development and identification of potential nucleophilic cytoprotectants that can scavenge toxic

  4. Imaging of musculoskeletal soft tissue infections

    Energy Technology Data Exchange (ETDEWEB)

    Turecki, Marcin B.; Taljanovic, Mihra S.; Holden, Dean A.; Hunter, Tim B.; Rogers, Lee F. [University of Arizona HSC, Department of Radiology, Tucson, AZ (United States); Stubbs, Alana Y. [Southern Arizona VA Health Care System, Department of Radiology, Tucson, AZ (United States); Graham, Anna R. [University of Arizona HSC, Department of Pathology, Tucson, AZ (United States)

    2010-10-15

    Prompt and appropriate imaging work-up of the various musculoskeletal soft tissue infections aids early diagnosis and treatment and decreases the risk of complications resulting from misdiagnosis or delayed diagnosis. The signs and symptoms of musculoskeletal soft tissue infections can be nonspecific, making it clinically difficult to distinguish between disease processes and the extent of disease. Magnetic resonance imaging (MRI) is the imaging modality of choice in the evaluation of soft tissue infections. Computed tomography (CT), ultrasound, radiography and nuclear medicine studies are considered ancillary. This manuscript illustrates representative images of superficial and deep soft tissue infections such as infectious cellulitis, superficial and deep fasciitis, including the necrotizing fasciitis, pyomyositis/soft tissue abscess, septic bursitis and tenosynovitis on different imaging modalities, with emphasis on MRI. Typical histopathologic findings of soft tissue infections are also presented. The imaging approach described in the manuscript is based on relevant literature and authors' personal experience and everyday practice. (orig.)

  5. Imaging of musculoskeletal soft tissue infections

    International Nuclear Information System (INIS)

    Turecki, Marcin B.; Taljanovic, Mihra S.; Holden, Dean A.; Hunter, Tim B.; Rogers, Lee F.; Stubbs, Alana Y.; Graham, Anna R.

    2010-01-01

    Prompt and appropriate imaging work-up of the various musculoskeletal soft tissue infections aids early diagnosis and treatment and decreases the risk of complications resulting from misdiagnosis or delayed diagnosis. The signs and symptoms of musculoskeletal soft tissue infections can be nonspecific, making it clinically difficult to distinguish between disease processes and the extent of disease. Magnetic resonance imaging (MRI) is the imaging modality of choice in the evaluation of soft tissue infections. Computed tomography (CT), ultrasound, radiography and nuclear medicine studies are considered ancillary. This manuscript illustrates representative images of superficial and deep soft tissue infections such as infectious cellulitis, superficial and deep fasciitis, including the necrotizing fasciitis, pyomyositis/soft tissue abscess, septic bursitis and tenosynovitis on different imaging modalities, with emphasis on MRI. Typical histopathologic findings of soft tissue infections are also presented. The imaging approach described in the manuscript is based on relevant literature and authors' personal experience and everyday practice. (orig.)

  6. Identity-Based Authentication for Cloud Computing

    Science.gov (United States)

    Li, Hongwei; Dai, Yuanshun; Tian, Ling; Yang, Haomiao

    Cloud computing is a recently developed new technology for complex systems with massive-scale services sharing among numerous users. Therefore, authentication of both users and services is a significant issue for the trust and security of the cloud computing. SSL Authentication Protocol (SAP), once applied in cloud computing, will become so complicated that users will undergo a heavily loaded point both in computation and communication. This paper, based on the identity-based hierarchical model for cloud computing (IBHMCC) and its corresponding encryption and signature schemes, presented a new identity-based authentication protocol for cloud computing and services. Through simulation testing, it is shown that the authentication protocol is more lightweight and efficient than SAP, specially the more lightweight user side. Such merit of our model with great scalability is very suited to the massive-scale cloud.

  7. Simplexins P–S, Eunicellin-Based Diterpenes from the Soft Coral Klyxum simplex

    Science.gov (United States)

    Wu, Shwu-Li; Su, Jui-Hsin; Huang, Chiung-Yao; Tai, Chi-Jen; Sung, Ping-Jyun; Liaw, Chih-Chung; Sheu, Jyh-Horng

    2012-01-01

    Four new eunicellin-based diterpenes, simplexins P–S (1–4), and the known compound simplexin A (5), have been isolated from the soft coral Klyxum simplex. The structures of the new metabolites were determined on the basis of extensive spectroscopic analysis, particularly 1D and 2D NMR experiments. Compounds 1 and 3–5 were shown to exhibit cytotoxicity against a limited panel of cancer cell lines, 3 being the most cytotoxic. PMID:22822367

  8. Digital dissection - using contrast-enhanced computed tomography scanning to elucidate hard- and soft-tissue anatomy in the Common Buzzard Buteo buteo.

    Science.gov (United States)

    Lautenschlager, Stephan; Bright, Jen A; Rayfield, Emily J

    2014-04-01

    Gross dissection has a long history as a tool for the study of human or animal soft- and hard-tissue anatomy. However, apart from being a time-consuming and invasive method, dissection is often unsuitable for very small specimens and often cannot capture spatial relationships of the individual soft-tissue structures. The handful of comprehensive studies on avian anatomy using traditional dissection techniques focus nearly exclusively on domestic birds, whereas raptorial birds, and in particular their cranial soft tissues, are essentially absent from the literature. Here, we digitally dissect, identify, and document the soft-tissue anatomy of the Common Buzzard (Buteo buteo) in detail, using the new approach of contrast-enhanced computed tomography using Lugol's iodine. The architecture of different muscle systems (adductor, depressor, ocular, hyoid, neck musculature), neurovascular, and other soft-tissue structures is three-dimensionally visualised and described in unprecedented detail. The three-dimensional model is further presented as an interactive PDF to facilitate the dissemination and accessibility of anatomical data. Due to the digital nature of the data derived from the computed tomography scanning and segmentation processes, these methods hold the potential for further computational analyses beyond descriptive and illustrative proposes. © 2013 The Authors. Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.

  9. Fabrication of graphene-based flexible devices utilizing a soft lithographic patterning method

    Science.gov (United States)

    Jung, Min Wook; Myung, Sung; Kim, Ki Woong; Song, Wooseok; Jo, You-Young; Lee, Sun Suk; Lim, Jongsun; Park, Chong-Yun; An, Ki-Seok

    2014-07-01

    There has been considerable interest in soft lithographic patterning processing of large scale graphene sheets due to the low cost and simplicity of the patterning process along with the exceptional electrical or physical properties of graphene. These properties include an extremely high carrier mobility and excellent mechanical strength. Recently, a study has reported that single layer graphene grown via chemical vapor deposition (CVD) was patterned and transferred to a target surface by controlling the surface energy of the polydimethylsiloxane (PDMS) stamp. However, applications are limited because of the challenge of CVD-graphene functionalization for devices such as chemical or bio-sensors. In addition, graphene-based layers patterned with a micron scale width on the surface of biocompatible silk fibroin thin films, which are not suitable for conventional CMOS processes such as the patterning or etching of substrates, have yet to be reported. Herein, we developed a soft lithographic patterning process via surface energy modification for advanced graphene-based flexible devices such as transistors or chemical sensors. Using this approach, the surface of a relief-patterned elastomeric stamp was functionalized with hydrophilic dimethylsulfoxide molecules to enhance the surface energy of the stamp and to remove the graphene-based layer from the initial substrate and transfer it to a target surface. As a proof of concept using this soft lithographic patterning technique, we demonstrated a simple and efficient chemical sensor consisting of reduced graphene oxide and a metallic nanoparticle composite. A flexible graphene-based device on a biocompatible silk fibroin substrate, which is attachable to an arbitrary target surface, was also successfully fabricated. Briefly, a soft lithographic patterning process via surface energy modification was developed for advanced graphene-based flexible devices such as transistors or chemical sensors and attachable devices on a

  10. Fabrication of graphene-based flexible devices utilizing a soft lithographic patterning method

    International Nuclear Information System (INIS)

    Wook Jung, Min; Myung, Sung; Woong Kim, Ki; Song, Wooseok; Suk Lee, Sun; Lim, Jongsun; An, Ki-Seok; Jo, You-Young; Park, Chong-Yun

    2014-01-01

    There has been considerable interest in soft lithographic patterning processing of large scale graphene sheets due to the low cost and simplicity of the patterning process along with the exceptional electrical or physical properties of graphene. These properties include an extremely high carrier mobility and excellent mechanical strength. Recently, a study has reported that single layer graphene grown via chemical vapor deposition (CVD) was patterned and transferred to a target surface by controlling the surface energy of the polydimethylsiloxane (PDMS) stamp. However, applications are limited because of the challenge of CVD-graphene functionalization for devices such as chemical or bio-sensors. In addition, graphene-based layers patterned with a micron scale width on the surface of biocompatible silk fibroin thin films, which are not suitable for conventional CMOS processes such as the patterning or etching of substrates, have yet to be reported. Herein, we developed a soft lithographic patterning process via surface energy modification for advanced graphene-based flexible devices such as transistors or chemical sensors. Using this approach, the surface of a relief-patterned elastomeric stamp was functionalized with hydrophilic dimethylsulfoxide molecules to enhance the surface energy of the stamp and to remove the graphene-based layer from the initial substrate and transfer it to a target surface. As a proof of concept using this soft lithographic patterning technique, we demonstrated a simple and efficient chemical sensor consisting of reduced graphene oxide and a metallic nanoparticle composite. A flexible graphene-based device on a biocompatible silk fibroin substrate, which is attachable to an arbitrary target surface, was also successfully fabricated. Briefly, a soft lithographic patterning process via surface energy modification was developed for advanced graphene-based flexible devices such as transistors or chemical sensors and attachable devices on a

  11. Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing.

    Science.gov (United States)

    Frascaroli, Jacopo; Brivio, Stefano; Covi, Erika; Spiga, Sabina

    2018-05-08

    The development of devices that can modulate their conductance under the application of electrical stimuli constitutes a fundamental step towards the realization of synaptic connectivity in neural networks. Optimization of synaptic functionality requires the understanding of the analogue conductance update under different programming conditions. Moreover, properties of physical devices such as bounded conductance values and state-dependent modulation should be considered as they affect storage capacity and performance of the network. This work provides a study of the conductance dynamics produced by identical pulses as a function of the programming parameters in an HfO 2 memristive device. The application of a phenomenological model that considers a soft approach to the conductance boundaries allows the identification of different operation regimes and to quantify conductance modulation in the analogue region. Device non-linear switching kinetics is recognized as the physical origin of the transition between different dynamics and motivates the crucial trade-off between degree of analog modulation and memory window. Different kinetics for the processes of conductance increase and decrease account for device programming asymmetry. The identification of programming trade-off together with an evaluation of device variations provide a guideline for the optimization of the analogue programming in view of hardware implementation of neural networks.

  12. Time series analysis of reference crop evapotranspiration using soft computing techniques for Ganjam District, Odisha, India

    Science.gov (United States)

    Patra, S. R.

    2017-12-01

    Evapotranspiration (ET0) influences water resources and it is considered as a vital process in aridic hydrologic frameworks. It is one of the most important measure in finding the drought condition. Therefore, time series forecasting of evapotranspiration is very important in order to help the decision makers and water system mangers build up proper systems to sustain and manage water resources. Time series considers that -history repeats itself, hence by analysing the past values, better choices, or forecasts, can be carried out for the future. Ten years of ET0 data was used as a part of this study to make sure a satisfactory forecast of monthly values. In this study, three models: (ARIMA) mathematical model, artificial neural network model, support vector machine model are presented. These three models are used for forecasting monthly reference crop evapotranspiration based on ten years of past historical records (1991-2001) of measured evaporation at Ganjam region, Odisha, India without considering the climate data. The developed models will allow water resource managers to predict up to 12 months, making these predictions very useful to optimize the resources needed for effective water resources management. In this study multistep-ahead prediction is performed which is more complex and troublesome than onestep ahead. Our investigation proposed that nonlinear relationships may exist among the monthly indices, so that the ARIMA model might not be able to effectively extract the full relationship hidden in the historical data. Support vector machines are potentially helpful time series forecasting strategies on account of their strong nonlinear mapping capability and resistance to complexity in forecasting data. SVMs have great learning capability in time series modelling compared to ANN. For instance, the SVMs execute the structural risk minimization principle, which allows in better generalization as compared to neural networks that use the empirical risk

  13. An exploratory study of contrast agents for soft tissue visualization by means of high resolution X-ray computed tomography imaging.

    Science.gov (United States)

    Pauwels, E; Van Loo, D; Cornillie, P; Brabant, L; Van Hoorebeke, L

    2013-04-01

    High resolution X-ray computed tomography (CT), or microCT, is a promising and already widely used technique in various scientific fields. Also for histological purposes it has great potential. Although microCT has proven to be a valuable technique for the imaging of bone structures, the visualization of soft tissue structures is still an important challenge due to their low inherent X-ray contrast. One way to achieve contrast enhancement is to make use of contrast agents. However, contrary to light and electron microscopy, knowledge about contrast agents and staining procedures is limited for X-ray CT. The purpose of this paper is to identify useful X-ray contrast agents for soft tissue visualization, which can be applied in a simple way and are also suited for samples larger than (1 cm)(3) . And 28 chemical substances have been investigated. All chemicals were applied in the form of concentrated aqueous solutions in which the samples were immersed. First, strips of green Bacon were stained to evaluate contrast enhancement between muscle and adipose tissue. Furthermore it was also tested whether the contrast agents remained fixed in the tissue after staining by re-immersing them in water. Based on the results, 12 contrast agents were selected for further testing on postmortem mice hind legs, containing a variety of different tissues, including muscle, fat, bone, cartilage and tendons. It was evaluated whether the contrast agents allowed a clearer distinction between the different soft tissue structures present. Finally also penetration depth was measured. And 26 chemicals resulted in contrast enhancement between muscle and adipose tissue in the Bacon strips. Mercury(II)chloride (HgCl2 ), phosphotungstic acid (PTA), phosphomolybdic acid (PMA) and ammonium orthomolybdate ((NH4 )2 MoO4 ) remained fixed after re-immersion in water. The penetration tests showed that potassium iodide (KI) and sodium tungstate can be most efficiently used for large samples of the order

  14. A probabilistic model-based soft sensor to monitor lactic acid bacteria fermentations

    DEFF Research Database (Denmark)

    Spann, Robert; Roca, Christophe; Kold, David

    2018-01-01

    A probabilistic soft sensor based on a mechanistic model was designed to monitor S. thermophilus fermentations, and validated with experimental lab-scale data. It considered uncertainties in the initial conditions, on-line measurements, and model parameters by performing Monte Carlo simulations...... the model parameters that were then used as input to the mechanistic model. The soft sensor predicted both the current state variables, as well as the future course of the fermentation, e.g. with a relative mean error of the biomass concentration of 8 %. This successful implementation of a process...... within the monitoring system. It predicted, therefore, the probability distributions of the unmeasured states, such as biomass, lactose, and lactic acid concentrations. To this end, a mechanistic model was developed first, and a statistical parameter estimation was performed in order to assess parameter...

  15. Design and Characterization of a Three-Axis Hall Effect-Based Soft Skin Sensor

    Directory of Open Access Journals (Sweden)

    Tito Pradhono Tomo

    2016-04-01

    Full Text Available This paper presents an easy means to produce a 3-axis Hall effect–based skin sensor for robotic applications. It uses an off-the-shelf chip and is physically small and provides digital output. Furthermore, the sensor has a soft exterior for safe interactions with the environment; in particular it uses soft silicone with about an 8 mm thickness. Tests were performed to evaluate the drift due to temperature changes, and a compensation using the integral temperature sensor was implemented. Furthermore, the hysteresis and the crosstalk between the 3-axis measurements were evaluated. The sensor is able to detect minimal forces of about 1 gf. The sensor was calibrated and results with total forces up to 1450 gf in the normal and tangential directions of the sensor are presented. The test revealed that the sensor is able to measure the different components of the force vector.

  16. Level of Soft Skill in the Implementation of Work-Based Learning among Community College Students

    Directory of Open Access Journals (Sweden)

    Ali Azita Binti

    2018-01-01

    Full Text Available The issue of graduate unemployment often crops up in the mass media; and more often than not, the discussions have centred on the failure of tertiary educational institutions to churn out quality graduates. Thus, the method of work-based learning (WBL is seen as a way to improve the soft skills of the graduates. The study was conducted using quantitative research survey; the design of the study used an adapted questionnaire as an instrument. Data were analysed using Statistical Package of Social Science (SPSS version 20. The respondents consisted of 97 students who attended WBL programmes at a community college. Descriptive statistics was used to extract data from the questionnaires for the calculation of mean. The findings reveal that the level of soft skills among community college students was high, and they include these abilities: communication skills, problem-solving skills, learning and information management, professional ethics skills and leadership skills.

  17. Swimming Characteristics of Bioinspired Helical Microswimmers Based on Soft Lotus-Root Fibers

    Directory of Open Access Journals (Sweden)

    Jia Liu

    2017-11-01

    Full Text Available Various kinds of helical swimmers inspired by E. coli bacteria have been developed continually in many types of researches, but most of them are proposed by the rigid bodies. For the targeted drug delivery, the rigid body may hurt soft tissues of the working region with organs. Due to this problem, the biomedical applications of helical swimmers may be restricted. However, the helical microswimmers with the soft and deformable body are appropriate and highly adaptive in a confined environment. Thus, this paper presents a lotus-root-based helical microswimmer, which is fabricated by the fibers of lotus-root coated with magnetic nanoparticles to active under the magnetic fields. The helical microstructures are derived from the intrinsic biological structures of the fibers of the lotus-root. This paper aims to study the swimming characteristic of lotus-root-based microswimmers with deformable helical bodies. In the initial step under the uniform magnetic actuation, the helical microswimmers are bent lightly due to the heterogeneous distribution of the internal stress, and then they undergo a swimming motion which is a spindle-like rotation locomotion. Our experiments report that the microswimmers with soft bodies can locomote faster than those with rigid bodies. Moreover, we also find that the curvature of the shape decreases as a function of actuating field frequency which is related to the deformability of lotus-root fibers.

  18. Design Methodology for Magnetic Field-Based Soft Tri-Axis Tactile Sensors.

    Science.gov (United States)

    Wang, Hongbo; de Boer, Greg; Kow, Junwai; Alazmani, Ali; Ghajari, Mazdak; Hewson, Robert; Culmer, Peter

    2016-08-24

    Tactile sensors are essential if robots are to safely interact with the external world and to dexterously manipulate objects. Current tactile sensors have limitations restricting their use, notably being too fragile or having limited performance. Magnetic field-based soft tactile sensors offer a potential improvement, being durable, low cost, accurate and high bandwidth, but they are relatively undeveloped because of the complexities involved in design and calibration. This paper presents a general design methodology for magnetic field-based three-axis soft tactile sensors, enabling researchers to easily develop specific tactile sensors for a variety of applications. All aspects (design, fabrication, calibration and evaluation) of the development of tri-axis soft tactile sensors are presented and discussed. A moving least square approach is used to decouple and convert the magnetic field signal to force output to eliminate non-linearity and cross-talk effects. A case study of a tactile sensor prototype, MagOne, was developed. This achieved a resolution of 1.42 mN in normal force measurement (0.71 mN in shear force), good output repeatability and has a maximum hysteresis error of 3.4%. These results outperform comparable sensors reported previously, highlighting the efficacy of our methodology for sensor design.

  19. Music Learning Based on Computer Software

    OpenAIRE

    Baihui Yan; Qiao Zhou

    2017-01-01

    In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teach...

  20. Computing in the presence of soft bit errors. [caused by single event upset on spacecraft

    Science.gov (United States)

    Rasmussen, R. D.

    1984-01-01

    It is shown that single-event-upsets (SEUs) due to cosmic rays are a significant source of single bit error in spacecraft computers. The physical mechanism of SEU, electron hole generation by means of Linear Energy Transfer (LET), it discussed with reference made to the results of a study of the environmental effects on computer systems of the Galileo spacecraft. Techniques for making software more tolerant of cosmic ray effects are considered, including: reducing the number of registers used by the software; continuity testing of variables; redundant execution of major procedures for error detection; and encoding state variables to detect single-bit changes. Attention is also given to design modifications which may reduce the cosmic ray exposure of on-board hardware. These modifications include: shielding components operating in LEO; removing low-power Schottky parts; and the use of CMOS diodes. The SEU parameters of different electronic components are listed in a table.

  1. Positive Implicative Ideals of BCK-Algebras Based on Intersectional Soft Sets

    Directory of Open Access Journals (Sweden)

    Eun Hwan Roh

    2013-01-01

    Full Text Available The aim of this paper is to lay a foundation for providing a soft algebraic tool in considering many problems that contain uncertainties. In order to provide these soft algebraic structures, the notion of int-soft positive implicative ideals is introduced, and related properties are investigated. Relations between an int-soft ideal and an int-soft positive implicative ideal are established. Characterizations of an int-soft positive implicative ideal are obtained. Extension property for an int-soft positive implicative ideal is constructed. The ∧-product and ∨-product of int-soft positive implicative ideals are considered, and the soft intersection (resp., union of int-soft positive implicative ideals is discussed.

  2. Game based learning for computer science education

    NARCIS (Netherlands)

    Schmitz, Birgit; Czauderna, André; Klemke, Roland; Specht, Marcus

    2011-01-01

    Schmitz, B., Czauderna, A., Klemke, R., & Specht, M. (2011). Game based learning for computer science education. In G. van der Veer, P. B. Sloep, & M. van Eekelen (Eds.), Computer Science Education Research Conference (CSERC '11) (pp. 81-86). Heerlen, The Netherlands: Open Universiteit.

  3. Computer-based feedback in formative assessment

    NARCIS (Netherlands)

    van der Kleij, Fabienne

    2013-01-01

    Formative assessment concerns any assessment that provides feedback that is intended to support learning and can be used by teachers and/or students. Computers could offer a solution to overcoming obstacles encountered in implementing formative assessment. For example, computer-based assessments

  4. Soft, embodied, situated & connected: enriching interactions with soft wearbles

    NARCIS (Netherlands)

    Tomico Plasencia, O.; Wilde, D.

    2016-01-01

    Soft wearables include clothing and textile-based accessories that incorporate smart textiles and soft electronic interfaces to enable responsive and interactive experiences. When designed well, soft wearables leverage the cultural, sociological and material qualities of textiles, fashion and dress;

  5. Devising tissue ingrowth metrics: a contribution to the computational characterization of engineered soft tissue healing.

    Science.gov (United States)

    Alves, Antoine; Attik, Nina; Bayon, Yves; Royet, Elodie; Wirth, Carine; Bourges, Xavier; Piat, Alexis; Dolmazon, Gaëlle; Clermont, Gaëlle; Boutrand, Jean-Pierre; Grosgogeat, Brigitte; Gritsch, Kerstin

    2018-03-14

    differences not detected by the semi-quantitative assessment, demonstrating the importance of quantitative analysis in the performance evaluation of soft tissue healing. This automated and supervised method reduced operator dependency and proved to be simple, sensitive, cost-effective and time-effective. It supports objective therapeutic comparisons and helps to elucidate regeneration and the dynamics of a functional tissue.

  6. Simulation of a Magneto-Rheological Fluid Based, Jamming, Soft Gripper Using the Soft Sphere DEM in LIGGGHTS

    Science.gov (United States)

    Leps, Thomas; Hartzell, Christine; Wereley, Norman; Choi, Young

    2017-11-01

    Jamming soft grippers are excellent universal grippers due to their low dependence on the shape of objects to be grabbed, and low stiffness, mitigating the need for object shape data and expensive force control of a stiff system. These grippers now rely on jamming transitions of dry grains under atmospheric pressure to hold objects. In order to expand their use to space environments, a gripper using magnetic actuation of a magneto-rheological fluid (MR Gripper) is being developed. The MR fluid is a suspension of μm scale iron grains in a silicone oil. When un-magnetized the fluid behaves as a dense suspension with low Bagnold number. When magnetized, it behaves like a jammed granular material, with magnetic forces between the grains dominating. We are simulating the gripper using LIGGGHTS, an open-source soft sphere DEM code. We have modeled both the deformable gripper membrane and the MR fluid itself using the LIGGGHTS framework. To our knowledge, this is the first time that the induced magnetic dipoles required to accurately simulate the jamming behavior of MR fluids have been modeled in LIGGGHTS. This simulation allows the rapid optimization of the hardware and magnetic field geometries, as well as the fluid behavior, without time consuming, and costly prototype revisions.

  7. A development of laser-plasma-based soft x-ray microscope system

    Energy Technology Data Exchange (ETDEWEB)

    Nam, Ki Yong; Kim, Kyong Woo; Kim, Kyu Gyeom; Kwon, Young Man; Yoon, Kwon Ha [X-ray Microscopy Research Center, Wonkwang University, Iksan (Korea, Republic of)

    2003-07-01

    Soft x-ray nano-imaging microscopy system for biomedical application with a high resolution about 50 nm has been designed and described, and its integrated techniques also have been studied. The system is mainly composed of soft x-ray generation system, nano-scaled control system, x-ray optical device like a condenser or object mirror, a CCD camera coupled with multichannel plate (MCP) and vacuum system. In the system, soft x-ray is generated from the laser-based plasma by focusing Nd:YAG laser beam on tantalum (Ta) target. In an x-ray optical system, a wolter mirror has been considering condensing the x-ray beam on a biological specimen and zone plate was adapted as an object mirror. A Si{sub 3}N{sub 4} was used as specimen holder for keeping a biological sample alive in atmosphere conditions. A back-illuminated-CCD camera coupled with multichannel plate was determined to set up.

  8. MTA Computer Based Evaluation System.

    Science.gov (United States)

    Brenner, Lisa P.; And Others

    The MTA PLATO-based evaluation system, which has been implemented by a consortium of schools of medical technology, is designed to be general-purpose, modular, data-driven, and interactive, and to accommodate other national and local item banks. The system provides a comprehensive interactive item-banking system in conjunction with online student…

  9. Mastering the soft skills in the implementation of work based learning among community college students

    Science.gov (United States)

    Ali, Azita Binti; Islamiah Rosli, Doria; Sujadi, Imam; Usodo, Budi; Adie Perdana, Fengky

    2017-01-01

    Emphasizing the aspects of soft skills among students is an important element to produce graduates who are competitive when facing any situations in the workplace. Various efforts have been taken by the Ministry of Education (MOE) and the Ministry of Higher Education Malaysia (MOHE) to improve the education system in Malaysia. Learning methods were introduced to ensure the education systems achieve the educational goals and to produce individuals who are well-balanced with spiritually, emotionally and physically. However, the issue of unemployment among graduates often being spoken in the community and it was regarded as a failure of educational institutions to produce quality graduates. Thus, the method of Work-Based Learning (WBL) was seen as a way to improve the soft skills among the graduates. The study was conducted using quantitative research survey as the design of the study used a questionnaire that was adapted as an instrument. Data were analysed using Statistical Package of Social Science (SPSS) version 20.0. The respondents were consisted of 97 students who attended WBL programs at the community college. Data were obtained from questionnaires using descriptive statistics for the calculation of the mean and one-way ANOVA test. The findings of the level of soft skills among community colleges were high where the communication skills obtained (mean = 4.1218), critical and problem solving skills (mean = 4.0946), teamwork skills (mean = 4.2297), learning and information management (mean = 4.1219), entrepreneurial skills (mean = 4.0240), professional ethics and moral (mean = 3.9410) and leadership skills (mean = 4.2104). The findings also showed the differences in term of communication skills among the community colleges. This study was significant to the community colleges to identify the level of soft skills among students who performed WBL methods in order to reduce the number of unemployment.

  10. Soft, Embodied, Situated & Connected

    DEFF Research Database (Denmark)

    Tomico, Oscar; Wilde, Danielle

    2015-01-01

    Soft wearables include clothing and textile-based accessories that incorporate smart textiles and soft electronic interfaces to enable responsive and interactive experiences. When designed well, they leverage the cultural, sociological and material qualities of textiles, fashion and dress; divers...

  11. Soft, embodied, situated & connected

    NARCIS (Netherlands)

    Tomico Plasencia, O.; Wilde, D.

    2015-01-01

    Soft wearables include clothing and textile-based accessories that incorporate smart textiles and soft electronic interfaces to enable responsive and interactive experiences. When designed well, they leverage the cultural, sociological and material qualities of textiles, fashion and dress; diverse

  12. Computer-based multi-channel analyzer based on internet

    International Nuclear Information System (INIS)

    Zhou Xinzhi; Ning Jiaoxian

    2001-01-01

    Combined the technology of Internet with computer-based multi-channel analyzer, a new kind of computer-based multi-channel analyzer system which is based on browser is presented. Its framework and principle as well as its implementation are discussed

  13. Music Learning Based on Computer Software

    Directory of Open Access Journals (Sweden)

    Baihui Yan

    2017-12-01

    Full Text Available In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teachers have not found a reasonable countermeasure to them. Against this background, the introduction of computer music software to music learning is a new trial that can not only cultivate the students’ initiatives of music learning, but also enhance their abilities to learn music. Therefore, it is concluded that the computer software based music learning is of great significance to improving the current music learning modes and means.

  14. Knowledge-based computer security advisor

    International Nuclear Information System (INIS)

    Hunteman, W.J.; Squire, M.B.

    1991-01-01

    The rapid expansion of computer security information and technology has included little support to help the security officer identify the safeguards needed to comply with a policy and to secure a computing system. This paper reports that Los Alamos is developing a knowledge-based computer security system to provide expert knowledge to the security officer. This system includes a model for expressing the complex requirements in computer security policy statements. The model is part of an expert system that allows a security officer to describe a computer system and then determine compliance with the policy. The model contains a generic representation that contains network relationships among the policy concepts to support inferencing based on information represented in the generic policy description

  15. REAL TIME PULVERISED COAL FLOW SOFT SENSOR FOR THERMAL POWER PLANTS USING EVOLUTIONARY COMPUTATION TECHNIQUES

    Directory of Open Access Journals (Sweden)

    B. Raja Singh

    2015-01-01

    Full Text Available Pulverised coal preparation system (Coal mills is the heart of coal-fired power plants. The complex nature of a milling process, together with the complex interactions between coal quality and mill conditions, would lead to immense difficulties for obtaining an effective mathematical model of the milling process. In this paper, vertical spindle coal mills (bowl mill that are widely used in coal-fired power plants, is considered for the model development and its pulverised fuel flow rate is computed using the model. For the steady state coal mill model development, plant measurements such as air-flow rate, differential pressure across mill etc., are considered as inputs/outputs. The mathematical model is derived from analysis of energy, heat and mass balances. An Evolutionary computation technique is adopted to identify the unknown model parameters using on-line plant data. Validation results indicate that this model is accurate enough to represent the whole process of steady state coal mill dynamics. This coal mill model is being implemented on-line in a 210 MW thermal power plant and the results obtained are compared with plant data. The model is found accurate and robust that will work better in power plants for system monitoring. Therefore, the model can be used for online monitoring, fault detection, and control to improve the efficiency of combustion.

  16. CAMAC based computer--computer communications via microprocessor data links

    International Nuclear Information System (INIS)

    Potter, J.M.; Machen, D.R.; Naivar, F.J.; Elkins, E.P.; Simmonds, D.D.

    1976-01-01

    Communications between the central control computer and remote, satellite data acquisition/control stations at The Clinton P. Anderson Meson Physics Facility (LAMPF) is presently accomplished through the use of CAMAC based Data Link Modules. With the advent of the microprocessor, a new philosophy for digital data communications has evolved. Data Link modules containing microprocessor controllers provide link management and communication network protocol through algorithms executed in the Data Link microprocessor

  17. A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners

    Science.gov (United States)

    Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

    2013-01-01

    Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results. PMID:24083133

  18. A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners.

    Science.gov (United States)

    Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

    2013-01-01

    Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.

  19. Evaluating outcomes of computer-based classroom testing: Student acceptance and impact on learning and exam performance.

    Science.gov (United States)

    Zheng, Meixun; Bender, Daniel

    2018-03-13

    Computer-based testing (CBT) has made progress in health sciences education. In 2015, the authors led implementation of a CBT system (ExamSoft) at a dental school in the U.S. Guided by the Technology Acceptance Model (TAM), the purposes of this study were to (a) examine dental students' acceptance of ExamSoft; (b) understand factors impacting acceptance; and (c) evaluate the impact of ExamSoft on students' learning and exam performance. Survey and focus group data revealed that ExamSoft was well accepted by students as a testing tool and acknowledged by most for its potential to support learning. Regression analyses showed that perceived ease of use and perceived usefulness of ExamSoft significantly predicted student acceptance. Prior CBT experience and computer skills did not significantly predict acceptance of ExamSoft. Students reported that ExamSoft promoted learning in the first program year, primarily through timely and rich feedback on examination performance. t-Tests yielded mixed results on whether students performed better on computerized or paper examinations. The study contributes to the literature on CBT and the application of the TAM model in health sciences education. Findings also suggest ways in which health sciences institutions can implement CBT to maximize its potential as an assessment and learning tool.

  20. Soft-tissue perineurioma of the retroperitoneum in a 63-year-old man, computed tomography and magnetic resonance imaging findings: a case report

    Directory of Open Access Journals (Sweden)

    Yasumoto Mayumi

    2010-08-01

    Full Text Available Abstract Introduction Soft-tissue perineuriomas are rare benign peripheral nerve sheath tumors in the subcutis of the extremities and the trunks of young patients. To our knowledge, this the first presentation of the computed tomography and magnetic resonance imaging of a soft-tissue perineurioma in the retroperitoneum with pathologic correlation. Case presentation A 63-year-old Japanese man was referred for assessment of high blood pressure. Abdominal computed tomography and magnetic resonance imaging showed a well-defined, gradually enhancing tumor without focal degeneration or hemorrhage adjacent to the pancreatic body. Tumor excision with distal pancreatectomy and splenectomy was performed, as a malignant tumor of pancreatic origin could not be ruled out. No recurrence has been noted in the 16 months since the operation. Pathologic examination of the tumor revealed a soft-tissue perineurioma of the retroperitoneum. Conclusion Although the definitive diagnosis of soft-tissue perineurioma requires biopsy and immunohistochemical reactivity evaluation, the computed tomography and magnetic resonance imaging findings described in this report suggest inclusion of this rare tumor in the differential diagnosis when such findings occur in the retroperitoneum.

  1. Benchmarking gate-based quantum computers

    Science.gov (United States)

    Michielsen, Kristel; Nocon, Madita; Willsch, Dennis; Jin, Fengping; Lippert, Thomas; De Raedt, Hans

    2017-11-01

    With the advent of public access to small gate-based quantum processors, it becomes necessary to develop a benchmarking methodology such that independent researchers can validate the operation of these processors. We explore the usefulness of a number of simple quantum circuits as benchmarks for gate-based quantum computing devices and show that circuits performing identity operations are very simple, scalable and sensitive to gate errors and are therefore very well suited for this task. We illustrate the procedure by presenting benchmark results for the IBM Quantum Experience, a cloud-based platform for gate-based quantum computing.

  2. Computer-based diagnostic decisionmaking.

    Science.gov (United States)

    Miller, R A

    1987-12-01

    The three decisionmaking aids described by the authors attack the generic problem of "see no evil, hear no evil, speak no evil"--improving the detection, diagnosis, and therapy of psychiatric disorders in the primary care setting. The three systems represent interventions at different steps in the process of providing appropriate care to psychiatric patients. The DSPW system of Robins and Marcus offers the potential of increasing the recognition of psychiatric disease in the physician's office. Politser's IDS program is representative of the sort of sophisticated microcomputer-based decisionmaking support tools that will become available to physicians in the not-too-distant future. Erdman's study of the impact of explanation capabilities on the acceptability of therapy recommending systems points out the need for careful scientific evaluations of features added to diagnostic and therapeutic systems.

  3. Losses Approximation for Soft Magnetic Composites Based on a Homogenized Equivalent Conductivity

    Directory of Open Access Journals (Sweden)

    X. Ren

    2016-09-01

    Full Text Available Soft magnetic composites (SMC are a promising alternative to laminated steel in many Electrical Engineering applications. This is largely owing to their low level of eddy current losses. The electromagnetic behavior of SMC in electromagnetic devices cannot be easily predicted using standard numerical techniques such as the finite element method, mostly due to the computational cost required to model the material microstructure. Another difficulty lies in the high property contrast between the matrix and the inclusions. In this paper we propose a homogenization strategy to define the equivalent electromagnetic properties of SMC. For components made of SMC, the equivalent conductivity and permeability can be determined. These equivalent properties can be used to calculate eddy current losses or introduced into structural analysis tools to design electromagnetic devices.

  4. Enthalpy-based equation of state for highly porous materials employing modified soft sphere fluid model

    Science.gov (United States)

    Nayak, Bishnupriya; Menon, S. V. G.

    2018-01-01

    Enthalpy-based equation of state based on a modified soft sphere model for the fluid phase, which includes vaporization and ionization effects, is formulated for highly porous materials. Earlier developments and applications of enthalpy-based approach had not accounted for the fact that shocked states of materials with high porosity (e.g., porosity more than two for Cu) are in the expanded fluid region. We supplement the well known soft sphere model with a generalized Lennard-Jones formula for the zero temperature isotherm, with parameters determined from cohesive energy, specific volume and bulk modulus of the solid at normal condition. Specific heats at constant pressure, ionic and electronic enthalpy parameters and thermal excitation effects are calculated using the modified approach and used in the enthalpy-based equation of state. We also incorporate energy loss from the shock due to expansion of shocked material in calculating porous Hugoniot. Results obtained for Cu, even up to initial porosities ten, show good agreement with experimental data.

  5. Krempfielins Q and R, Two New Eunicellin-Based Diterpenoids from the Soft Coral Cladiella krempfi

    Directory of Open Access Journals (Sweden)

    Chi-Jen Tai

    2014-11-01

    Full Text Available Two new eunicellin-based diterpenoids, krempfielins Q and R (1 and 2, and one known compound cladieunicellin K (3 have been isolated from a Formosan soft coral Cladiella krempfi. The structures of these two new metabolites were elucidated by extensive spectroscopic analysis. Anti-inflammatory activity of new metabolites to inhibit the superoxide anion generation and elastase release in N-formyl-methionyl-leucyl phenylalanine/cytochalasin B (FMLP/CB-induced human neutrophil cells and cytotoxicity of both new compounds toward five cancer cell lines were reported.

  6. Fabrication of a solenoid-type inductor with Fe-based soft magnetic core

    International Nuclear Information System (INIS)

    Lei Chong; Zhou Yong; Gao Xiaoyu; Ding Wen; Cao Ying; Choi, Hyung; Won, Jonghwa

    2007-01-01

    A solenoid-type inductor was fabricated by MEMS (Microelectromechanical systems) technique. The fabrication process uses UV-LIGA, dry etching, fine polishing, and electroplating technique to achieve high performance of the solenoid-type inductor. Fe-based soft magnetic thin film was sputtered as the magnetic core, and polyimide was used as the insulation materials. The inductor was in size of 4x4 mm with coil width of 20 μm and space of 35 μm. The inductance is 1.61 μH at a frequency of 5 MHz with the maximum quality factor of 1.42

  7. Bioactive Eunicellin-Based Diterpenoids from the Soft Coral Cladiella krempfi

    Science.gov (United States)

    Tai, Chi-Jen; Su, Jui-Hsin; Huang, Ming-Shyan; Wen, Zhi-Hong; Dai, Chang-Feng; Sheu, Jyh-Horng

    2011-01-01

    Four new eunicellin-based diterpenoids, krempfielins A–D (1–4), along with two known compounds (5 and 6) have been isolated from a soft coral Cladiella krempfi. The structures of the new metabolites were elucidated by extensive spectroscopic analysis and by comparison with spectroscopic data of related known compounds. Compounds 5 and 6 were shown to exhibit cytotoxicity against a limited panel of cancer cell lines. Furthermore, compounds 2, 3, 5 and 6 were shown to exert significant in vitro anti-inflammatory activity against LPS-stimulated RAW264.7 macrophage cells. PMID:22073008

  8. Cytotoxic and Anti-Inflammatory Eunicellin-Based Diterpenoids from the Soft Coral Cladiella krempfi

    Science.gov (United States)

    Tai, Chi-Jen; Su, Jui-Hsin; Huang, Chiung-Yao; Huang, Ming-Shyan; Wen, Zhi-Hong; Dai, Chang-Feng; Sheu, Jyh-Horng

    2013-01-01

    Five new eunicellin-based diterpenoids, krempfielins E–I (1–5) and seven known compounds (6–12) were isolated from the organic extract of a Taiwanese soft coral Cladiella krempfi. The structures of the new metabolites were elucidated on the basis of extensive spectroscopic analysis. Metabolites 5, 6, 10 and 12 were shown to exhibit cytotoxicity against a limited panel of cancer cell lines. Furthermore, compounds 6 and 10 could potently inhibit the accumulation of the pro-inflammatory iNOS protein, and 6 and 12 could significantly reduce the expression of COX-2 protein in LPS-stimulated RAW264.7 macrophage cells. PMID:23481676

  9. Atmel Microcontroller Based Soft Switched PWM ZVS Full Bridge DC to DC Converter

    Directory of Open Access Journals (Sweden)

    DEEPAK KUMAR NAYAK

    2010-12-01

    Full Text Available This paper deals with the simulation and implementation of soft switched PWM ZVS full bridge DC to DC converter. The 48V DC is efficiently reduced to 12V DC using a DC to DC converter. This converter has advantages like reduced switching losses, stresses and EMI. Input DC is converted into high frequency AC and it is stepped down to 12V level. Later it is rectified using a full wave rectifier. Laboratory model of microcontroller based DC to DC converter is fabricated and tested. The experimental results are compared with the simulation results.

  10. Klymollins T-X, bioactive eunicellin-based diterpenoids from the soft coral Klyxum molle.

    Science.gov (United States)

    Chang, Fang-Yu; Hsu, Fang-Jung; Tai, Chi-Jen; Wei, Wen-Chi; Yang, Ning-Sun; Sheu, Jyh-Horng

    2014-05-22

    Five new eunicellin-based diterpenoids, klymollins T-X (1-5), along with two known compounds (6 and 7) have been isolated from the soft coral Klyxum molle. The structures of these new metabolites were elucidated by extensive spectroscopic analysis and by comparison with related known compounds. Compound 5 was found to exert significant in vitro anti-inflammatory activity against LPS-stimulated RAW264.7 macrophage cells. Furthermore, compounds 4 and 7 were shown to exhibit cytotoxicity against a limited panel of human cancer cell lines.

  11. Klymollins A-H, bioactive eunicellin-based diterpenoids from the formosan soft coral Klyxum molle.

    Science.gov (United States)

    Hsu, Fang-Jung; Chen, Bo-Wei; Wen, Zhi-Hong; Huang, Chiung-Yao; Dai, Chang-Feng; Su, Jui-Hsin; Wu, Yang-Chang; Sheu, Jyh-Horng

    2011-11-28

    Eight new eunicellin-based diterpenoids, klymollins A-H (1-8), were isolated during the chemical investigation of the soft coral Klyxum molle from Taiwan waters. Their structures were elucidated by extensive spectroscopic analysis. The absolute configuration of 4 was determined by Mosher's method. Bioassays of the new metabolites showed that compounds 3-8 displayed significant in vitro anti-inflammatory activity by inhibiting the expression of the iNOS protein, and compounds 3, 4, and 6-8 also could effectively reduce the accumulation of COX-2 protein in LPS-stimulated RAW264.7 macrophage cells.

  12. A Soft Computing Approach to Crack Detection and Impact Source Identification with Field-Programmable Gate Array Implementation

    Directory of Open Access Journals (Sweden)

    Arati M. Dixit

    2013-01-01

    Full Text Available The real-time nondestructive testing (NDT for crack detection and impact source identification (CDISI has attracted the researchers from diverse areas. This is apparent from the current work in the literature. CDISI has usually been performed by visual assessment of waveforms generated by a standard data acquisition system. In this paper we suggest an automation of CDISI for metal armor plates using a soft computing approach by developing a fuzzy inference system to effectively deal with this problem. It is also advantageous to develop a chip that can contribute towards real time CDISI. The objective of this paper is to report on efforts to develop an automated CDISI procedure and to formulate a technique such that the proposed method can be easily implemented on a chip. The CDISI fuzzy inference system is developed using MATLAB’s fuzzy logic toolbox. A VLSI circuit for CDISI is developed on basis of fuzzy logic model using Verilog, a hardware description language (HDL. The Xilinx ISE WebPACK9.1i is used for design, synthesis, implementation, and verification. The CDISI field-programmable gate array (FPGA implementation is done using Xilinx’s Spartan 3 FPGA. SynaptiCAD’s Verilog Simulators—VeriLogger PRO and ModelSim—are used as the software simulation and debug environment.

  13. Strength development in concrete with wood ash blended cement and use of soft computing models to predict strength parameters.

    Science.gov (United States)

    Chowdhury, S; Maniar, A; Suganya, O M

    2015-11-01

    In this study, Wood Ash (WA) prepared from the uncontrolled burning of the saw dust is evaluated for its suitability as partial cement replacement in conventional concrete. The saw dust has been acquired from a wood polishing unit. The physical, chemical and mineralogical characteristics of WA is presented and analyzed. The strength parameters (compressive strength, split tensile strength and flexural strength) of concrete with blended WA cement are evaluated and studied. Two different water-to-binder ratio (0.4 and 0.45) and five different replacement percentages of WA (5%, 10%, 15%, 18% and 20%) including control specimens for both water-to-cement ratio is considered. Results of compressive strength, split tensile strength and flexural strength showed that the strength properties of concrete mixture decreased marginally with increase in wood ash contents, but strength increased with later age. The XRD test results and chemical analysis of WA showed that it contains amorphous silica and thus can be used as cement replacing material. Through the analysis of results obtained in this study, it was concluded that WA could be blended with cement without adversely affecting the strength properties of concrete. Also using a new statistical theory of the Support Vector Machine (SVM), strength parameters were predicted by developing a suitable model and as a result, the application of soft computing in structural engineering has been successfully presented in this research paper.

  14. Strength development in concrete with wood ash blended cement and use of soft computing models to predict strength parameters

    Directory of Open Access Journals (Sweden)

    S. Chowdhury

    2015-11-01

    Full Text Available In this study, Wood Ash (WA prepared from the uncontrolled burning of the saw dust is evaluated for its suitability as partial cement replacement in conventional concrete. The saw dust has been acquired from a wood polishing unit. The physical, chemical and mineralogical characteristics of WA is presented and analyzed. The strength parameters (compressive strength, split tensile strength and flexural strength of concrete with blended WA cement are evaluated and studied. Two different water-to-binder ratio (0.4 and 0.45 and five different replacement percentages of WA (5%, 10%, 15%, 18% and 20% including control specimens for both water-to-cement ratio is considered. Results of compressive strength, split tensile strength and flexural strength showed that the strength properties of concrete mixture decreased marginally with increase in wood ash contents, but strength increased with later age. The XRD test results and chemical analysis of WA showed that it contains amorphous silica and thus can be used as cement replacing material. Through the analysis of results obtained in this study, it was concluded that WA could be blended with cement without adversely affecting the strength properties of concrete. Also using a new statistical theory of the Support Vector Machine (SVM, strength parameters were predicted by developing a suitable model and as a result, the application of soft computing in structural engineering has been successfully presented in this research paper.

  15. Soft computing modelling of moisture sorption isotherms of milk-foxtail millet powder and determination of thermodynamic properties.

    Science.gov (United States)

    Simha, H V Vikram; Pushpadass, Heartwin A; Franklin, Magdaline Eljeeva Emerald; Kumar, P Arun; Manimala, K

    2016-06-01

    Moisture sorption isotherms of spray-dried milk-foxtail millet powder were determined at 10, 25 and 40 °C. Sorption data was fitted using classical and soft-computing approaches. The isotherms were of type II, and equilibrium moisture content (EMC) was temperature dependent. The BET monolayer moisture content decreased from 3.30 to 2.67 % as temperature increased from 10 to 40 °C. Amongst the classical models, Ferro-Fontan gave the best fit of EMC-aw data. However, the Sugeno-type adaptive neuro-fuzzy inference system (ANFIS) with generalized bell-shaped membership function performed better than artificial neural network and classical models with RMSE as low as 0.0099. The isosteric heat of sorption decreased from 150.32 kJ mol(-1) at 1 % moisture content to 44.11 kJ mol(-1) at 15 % moisture. The enthalpy-entropy compensation theory was validated, and the isokinetic and harmonic mean temperatures were determined as 333.1 and 297.5 K, respectively.

  16. Semantic computing and language knowledge bases

    Science.gov (United States)

    Wang, Lei; Wang, Houfeng; Yu, Shiwen

    2017-09-01

    As the proposition of the next-generation Web - semantic Web, semantic computing has been drawing more and more attention within the circle and the industries. A lot of research has been conducted on the theory and methodology of the subject, and potential applications have also been investigated and proposed in many fields. The progress of semantic computing made so far cannot be detached from its supporting pivot - language resources, for instance, language knowledge bases. This paper proposes three perspectives of semantic computing from a macro view and describes the current status of affairs about the construction of language knowledge bases and the related research and applications that have been carried out on the basis of these resources via a case study in the Institute of Computational Linguistics at Peking University.

  17. Online Image-based Monitoring of Soft-tissue Displacements for Radiation Therapy of the Prostate

    International Nuclear Information System (INIS)

    Schlosser, Jeffrey; Salisbury, Kenneth; Hristov, Dimitre

    2012-01-01

    Purpose: Emerging prolonged, hypofractionated radiotherapy regimens rely on high-dose conformality to minimize toxicity and thus can benefit from image guidance systems that continuously monitor target position during beam delivery. To address this need we previously developed, as a potential add-on device for existing linear accelerators, a novel telerobotic ultrasound system capable of real-time, soft-tissue imaging. Expanding on this capability, the aim of this work was to develop and characterize an image-based technique for real-time detection of prostate displacements. Methods and Materials: Image processing techniques were implemented on spatially localized ultrasound images to generate two parameters representing prostate displacements in real time. In a phantom and five volunteers, soft-tissue targets were continuously imaged with a customized robotic manipulator while recording the two tissue displacement parameters (TDPs). Variations of the TDPs in the absence of tissue displacements were evaluated, as was the sensitivity of the TDPs to prostate translations and rotations. Robustness of the approach to probe force was also investigated. Results: With 95% confidence, the proposed method detected in vivo prostate displacements before they exceeded 2.3, 2.5, and 2.8 mm in anteroposterior, superoinferior, and mediolateral directions. Prostate pitch was detected before exceeding 4.7° at 95% confidence. Total system time lag averaged 173 ms, mostly limited by ultrasound acquisition rate. False positives (FPs) (FP) in the absence of displacements did not exceed 1.5 FP events per 10 min of continuous in vivo imaging time. Conclusions: The feasibility of using telerobotic ultrasound for real-time, soft-tissue–based monitoring of target displacements was confirmed in vivo. Such monitoring has the potential to detect small clinically relevant intrafractional variations of the prostate position during beam delivery.

  18. Finite Element Method-Based Kinematics and Closed-Loop Control of Soft, Continuum Manipulators.

    Science.gov (United States)

    Bieze, Thor Morales; Largilliere, Frederick; Kruszewski, Alexandre; Zhang, Zhongkai; Merzouki, Rochdi; Duriez, Christian

    2018-06-01

    This article presents a modeling methodology and experimental validation for soft manipulators to obtain forward kinematic model (FKM) and inverse kinematic model (IKM) under quasi-static conditions (in the literature, these manipulators are usually classified as continuum robots. However, their main characteristic of interest in this article is that they create motion by deformation, as opposed to the classical use of articulations). It offers a way to obtain the kinematic characteristics of this type of soft robots that is suitable for offline path planning and position control. The modeling methodology presented relies on continuum mechanics, which does not provide analytic solutions in the general case. Our approach proposes a real-time numerical integration strategy based on finite element method with a numerical optimization based on Lagrange multipliers to obtain FKM and IKM. To reduce the dimension of the problem, at each step, a projection of the model to the constraint space (gathering actuators, sensors, and end-effector) is performed to obtain the smallest number possible of mathematical equations to be solved. This methodology is applied to obtain the kinematics of two different manipulators with complex structural geometry. An experimental comparison is also performed in one of the robots, between two other geometric approaches and the approach that is showcased in this article. A closed-loop controller based on a state estimator is proposed. The controller is experimentally validated and its robustness is evaluated using Lypunov stability method.

  19. Computer vision based room interior design

    Science.gov (United States)

    Ahmad, Nasir; Hussain, Saddam; Ahmad, Kashif; Conci, Nicola

    2015-12-01

    This paper introduces a new application of computer vision. To the best of the author's knowledge, it is the first attempt to incorporate computer vision techniques into room interior designing. The computer vision based interior designing is achieved in two steps: object identification and color assignment. The image segmentation approach is used for the identification of the objects in the room and different color schemes are used for color assignment to these objects. The proposed approach is applied to simple as well as complex images from online sources. The proposed approach not only accelerated the process of interior designing but also made it very efficient by giving multiple alternatives.

  20. Agent-Based Computing: Promise and Perils

    OpenAIRE

    Jennings, N. R.

    1999-01-01

    Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more genrally, Computer Science. It has the potential to significantly improve the theory and practice of modelling, designing and implementing complex systems. Yet, to date, there has been little systematic analysis of what makes an agent such an appealing and powerful conceptual model. Moreover, even less effort has been devoted to exploring the inherent disadvantages that stem from adoptin...

  1. Performance-Based Seismic Retrofit of Soft-Story Woodframe Buildings

    Science.gov (United States)

    P. Bahmani; J.W. van de Lindt; S.E. Pryor; G.L. Mochizuki; M. Gershfeld; D. Rammer; J. Tian; D. Symans

    2013-01-01

    Soft-story woodframe buildings are recognizable by their large garage openings at the bottom story which are typically for parking and storage. In soft-story buildings the relative stiffness and strength of the soft-story, usually the bottom story, is significantly less than the upper stories due to the presence of large openings which reduce the available space for...

  2. Hybrid soft computing control strategies for improving the energy capture of a wind farm

    Directory of Open Access Journals (Sweden)

    Živković Predrag M.

    2012-01-01

    Full Text Available In this paper, a fuzzy controller is proposed for wind turbine control. A model is analyzed and combined with a stochastic wind model for simulation purposes. Based on the model, a fuzzy control of wind turbine is developed. Wind turbine control loop provides the reference inputs for the electric generator control loop in order to make the system run with maximum power. Since the wind speed involved in the aerodynamic equations is a stochastic variable, whose effective value cannot be measured directly, a wind speed estimator is also proposed.[Projekat Ministarstva nauke Republike Srbije, br. TR33036/2011: Development of new meteorological mast for turbulence parameters characterization and br. TR35005/2011: Research and development of new generation wind turbines of high-energy efficiency

  3. Review of RDC Soft Computing Techniques for Accurate Measurement of Resolver Rotor Angle

    Directory of Open Access Journals (Sweden)

    Chandra Mohan Reddy Sivappagari

    2013-03-01

    Full Text Available A resolver is a position sensor or transducer that measures the instantaneous angular position of the rotating shaft to which it is attached. Resolver produces two amplitude modulated signals; SIN and COS as output signals. These two signals need to be demodulated and converted to digital signals before they can be used for control. There are several techniques available in the literature to measure the rotor shaft angle. This paper focuses on the design of both hardware and software based resolver to digital converter (RDC techniques available in the literature. This literature review helps the researchers to know about all these methods and plan future work on RDCs to improve the angle tracking performance.

  4. Prediction of BP Reactivity to Talking Using Hybrid Soft Computing Approaches

    Directory of Open Access Journals (Sweden)

    Gurmanik Kaur

    2014-01-01

    Full Text Available High blood pressure (BP is associated with an increased risk of cardiovascular diseases. Therefore, optimal precision in measurement of BP is appropriate in clinical and research studies. In this work, anthropometric characteristics including age, height, weight, body mass index (BMI, and arm circumference (AC were used as independent predictor variables for the prediction of BP reactivity to talking. Principal component analysis (PCA was fused with artificial neural network (ANN, adaptive neurofuzzy inference system (ANFIS, and least square-support vector machine (LS-SVM model to remove the multicollinearity effect among anthropometric predictor variables. The statistical tests in terms of coefficient of determination (R2, root mean square error (RMSE, and mean absolute percentage error (MAPE revealed that PCA based LS-SVM (PCA-LS-SVM model produced a more efficient prediction of BP reactivity as compared to other models. This assessment presents the importance and advantages posed by PCA fused prediction models for prediction of biological variables.

  5. Prediction of BP reactivity to talking using hybrid soft computing approaches.

    Science.gov (United States)

    Kaur, Gurmanik; Arora, Ajat Shatru; Jain, Vijender Kumar

    2014-01-01

    High blood pressure (BP) is associated with an increased risk of cardiovascular diseases. Therefore, optimal precision in measurement of BP is appropriate in clinical and research studies. In this work, anthropometric characteristics including age, height, weight, body mass index (BMI), and arm circumference (AC) were used as independent predictor variables for the prediction of BP reactivity to talking. Principal component analysis (PCA) was fused with artificial neural network (ANN), adaptive neurofuzzy inference system (ANFIS), and least square-support vector machine (LS-SVM) model to remove the multicollinearity effect among anthropometric predictor variables. The statistical tests in terms of coefficient of determination (R (2)), root mean square error (RMSE), and mean absolute percentage error (MAPE) revealed that PCA based LS-SVM (PCA-LS-SVM) model produced a more efficient prediction of BP reactivity as compared to other models. This assessment presents the importance and advantages posed by PCA fused prediction models for prediction of biological variables.

  6. An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection

    Directory of Open Access Journals (Sweden)

    Sen Zhang

    2015-01-01

    Full Text Available The concentration of alumina in the electrolyte is of great significance during the production of aluminum; it may affect the stability of aluminum reduction cell and the current efficiency. However, the concentration of alumina is hard to be detected online because of the special circumstance in the aluminum reduction cell. At present, there is lack of fast and accurate soft sensing methods for alumina concentration and existing methods can not meet the needs for online measurement. In this paper, a novel soft sensing method based on a modified extreme learning machine (MELM for online measurement of the alumina concentration is proposed. The modified ELM algorithm is based on the enhanced random search which is called incremental extreme learning machine in some references. It randomly chooses the input weights and analytically determines the output weights without manual intervention. The simulation results show that the approach can give more accurate estimations of alumina concentration with faster learning speed compared with other methods such as BP and SVM.

  7. A simulation model for visitors’ thermal comfort at urban public squares using non-probabilistic binary-linear classifier through soft-computing methodologies

    International Nuclear Information System (INIS)

    Kariminia, Shahab; Shamshirband, Shahaboddin; Hashim, Roslan; Saberi, Ahmadreza; Petković, Dalibor; Roy, Chandrabhushan; Motamedi, Shervin

    2016-01-01

    Sustaining outdoor life in cities is decreasing because of the recent rapid urbanisation without considering climate-responsive urban design concepts. Such inadvertent climatic modifications at the indoor level have imposed considerable demand on the urban energy resources. It is important to provide comfortable ambient climate at open urban squares. Researchers need to predict the comfortable conditions at such outdoor squares. The main objective of this study is predict the visitors' outdoor comfort indices by using a developed computational model termed as SVM-WAVELET (Support Vector Machines combined with Discrete Wavelet Transform algorithm). For data collection, the field study was conducted in downtown Isfahan, Iran (51°41′ E, 32°37′ N) with hot and arid summers. Based on different environmental elements, four separate locations were monitored across two public squares. Meteorological data were measured simultaneously by surveying the visitors' thermal sensations. According to the subjects' thermal feeling and their characteristics, their level of comfort was estimated. Further, the adapted computational model was used to estimate the visitors’ thermal sensations in terms of thermal comfort indices. The SVM-WAVELET results indicate that R"2 value for input parameters, including Thermal Sensation, PMW (The predicted mean vote), PET (physiologically equivalent temperature), SET (standard effective temperature) and T_m_r_t were estimated at 0.482, 0.943, 0.988, 0.969 and 0.840, respectively. - Highlights: • To explore the visitors' thermal sensation at urban public squares. • This article introduces findings of outdoor comfort prediction. • The developed SVM-WAVELET soft-computing technique was used. • SVM-WAVELET estimation results are more reliable and accurate.

  8. Predicting groundwater level fluctuations with meteorological effect implications—A comparative study among soft computing techniques

    Science.gov (United States)

    Shiri, Jalal; Kisi, Ozgur; Yoon, Heesung; Lee, Kang-Kun; Hossein Nazemi, Amir

    2013-07-01

    The knowledge of groundwater table fluctuations is important in agricultural lands as well as in the studies related to groundwater utilization and management levels. This paper investigates the abilities of Gene Expression Programming (GEP), Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Networks (ANN) and Support Vector Machine (SVM) techniques for groundwater level forecasting in following day up to 7-day prediction intervals. Several input combinations comprising water table level, rainfall and evapotranspiration values from Hongcheon Well station (South Korea), covering a period of eight years (2001-2008) were used to develop and test the applied models. The data from the first six years were used for developing (training) the applied models and the last two years data were reserved for testing. A comparison was also made between the forecasts provided by these models and the Auto-Regressive Moving Average (ARMA) technique. Based on the comparisons, it was found that the GEP models could be employed successfully in forecasting water table level fluctuations up to 7 days beyond data records.

  9. A soft-computing methodology for noninvasive time-spatial temperature estimation.

    Science.gov (United States)

    Teixeira, César A; Ruano, Maria Graça; Ruano, António E; Pereira, Wagner C A

    2008-02-01

    The safe and effective application of thermal therapies is restricted due to lack of reliable noninvasive temperature estimators. In this paper, the temporal echo-shifts of backscattered ultrasound signals, collected from a gel-based phantom, were tracked and assigned with the past temperature values as radial basis functions neural networks input information. The phantom was heated using a piston-like therapeutic ultrasound transducer. The neural models were assigned to estimate the temperature at different intensities and points arranged across the therapeutic transducer radial line (60 mm apart from the transducer face). Model inputs, as well as the number of neurons were selected using the multiobjective genetic algorithm (MOGA). The best attained models present, in average, a maximum absolute error less than 0.5 degrees C, which is pointed as the borderline between a reliable and an unreliable estimator in hyperthermia/diathermia. In order to test the spatial generalization capacity, the best models were tested using spatial points not yet assessed, and some of them presented a maximum absolute error inferior to 0.5 degrees C, being "elected" as the best models. It should be also stressed that these best models present implementational low-complexity, as desired for real-time applications.

  10. Computer Based Road Accident Reconstruction Experiences

    Directory of Open Access Journals (Sweden)

    Milan Batista

    2005-03-01

    Full Text Available Since road accident analyses and reconstructions are increasinglybased on specific computer software for simulationof vehicle d1iving dynamics and collision dynamics, and forsimulation of a set of trial runs from which the model that bestdescribes a real event can be selected, the paper presents anoverview of some computer software and methods available toaccident reconstruction experts. Besides being time-saving,when properly used such computer software can provide moreauthentic and more trustworthy accident reconstruction, thereforepractical experiences while using computer software toolsfor road accident reconstruction obtained in the TransportSafety Laboratory at the Faculty for Maritime Studies andTransport of the University of Ljubljana are presented and discussed.This paper addresses also software technology for extractingmaximum information from the accident photo-documentationto support accident reconstruction based on the simulationsoftware, as well as the field work of reconstruction expertsor police on the road accident scene defined by this technology.

  11. Hybrid Carbon-Based Scaffolds for Applications in Soft Tissue Reconstruction

    Science.gov (United States)

    Lafdi, Khalid; Joseph, Robert M.; Tsonis, Panagiotis A.

    2012-01-01

    Current biomedical scaffolds utilized in surgery to repair soft tissues commonly fail to meet the optimal combination of biomechanical and tissue regenerative properties. Carbon is a scaffold alternative that potentially optimizes the balance between mechanical strength, durability, and function as a cell and biologics delivery vehicle that is necessary to restore tissue function while promoting tissue repair. The goals of this study were to investigate the feasibility of fabricating hybrid fibrous carbon scaffolds modified with biopolymer, polycaprolactone and to analyze their mechanical properties and ability to support cell growth and proliferation. Environmental scanning electron microscopy, micro-computed tomography, and cell adhesion and cell proliferation studies were utilized to test scaffold suitability as a cell delivery vehicle. Mechanical properties were tested to examine load failure and elastic modulus. Results were compared to an acellular dermal matrix scaffold control (GraftJacket® [GJ] Matrix), selected for its common use in surgery for the repair of soft tissues. Results indicated that carbon scaffolds exhibited similar mechanical maximums and capacity to support fibroblast adhesion and proliferation in comparison with GJ. Fibroblast adhesion and proliferation was collinear with carbon fiber orientation in regions of sparsely distributed fibers and occurred in clusters in regions of higher fiber density and low porosity. Overall, fibroblast adhesion and proliferation was greatest in lower porosity carbon scaffolds with highly aligned fibers. Stepwise multivariate regression showed that the variability in maximum load of carbon scaffolds and controls were dependent on unique and separate sets of parameters. These finding suggested that there were significant differences in the functional implications of scaffold design and material properties between carbon and dermis derived scaffolds that affect scaffold utility as a tissue replacement

  12. Analyzing Reliability and Performance Trade-Offs of HLS-Based Designs in SRAM-Based FPGAs Under Soft Errors

    Science.gov (United States)

    Tambara, Lucas Antunes; Tonfat, Jorge; Santos, André; Kastensmidt, Fernanda Lima; Medina, Nilberto H.; Added, Nemitala; Aguiar, Vitor A. P.; Aguirre, Fernando; Silveira, Marcilei A. G.

    2017-02-01

    The increasing system complexity of FPGA-based hardware designs and shortening of time-to-market have motivated the adoption of new designing methodologies focused on addressing the current need for high-performance circuits. High-Level Synthesis (HLS) tools can generate Register Transfer Level (RTL) designs from high-level software programming languages. These tools have evolved significantly in recent years, providing optimized RTL designs, which can serve the needs of safety-critical applications that require both high performance and high reliability levels. However, a reliability evaluation of HLS-based designs under soft errors has not yet been presented. In this work, the trade-offs of different HLS-based designs in terms of reliability, resource utilization, and performance are investigated by analyzing their behavior under soft errors and comparing them to a standard processor-based implementation in an SRAM-based FPGA. Results obtained from fault injection campaigns and radiation experiments show that it is possible to increase the performance of a processor-based system up to 5,000 times by changing its architecture with a small impact in the cross section (increasing up to 8 times), and still increasing the Mean Workload Between Failures (MWBF) of the system.

  13. PLA-based biodegradable and tunable soft elastomers for biomedical applications

    International Nuclear Information System (INIS)

    Harrane, Amine; Leroy, Adrien; Nouailhas, Hélène; Garric, Xavier; Coudane, Jean; Nottelet, Benjamin

    2011-01-01

    Although desirable for biomedical applications, soft degradable elastomers having balanced amphiphilic behaviour are rarely described in the literature. Indeed, mainly highly hydrophobic elastomers or very hydrophilic elastomers with hydrogel behaviours are found. In this work, we developed thermoset degradable elastomers based on the photo-cross-linking of poly(lactide)-poly(ethylene glycol)-poly(lactide) (PLA-PEG-PLA) triblock prepolymers. The originality of the proposed elastomers comes from the careful choice of the prepolymer amphiphilicity and from the possible modulation of their mechanical properties and degradation rates provided by cross-linkers of different nature. This is illustrated with the hydrophobic and rigid 2,4,6-triallyloxy-1,3,5-triazine compared to the hydrophilic and soft pentaerythritol triallyl ether. Thermal properties, mechanical properties, swelling behaviours, degradation rates and cytocompatibility have been evaluated. Results show that it is possible to generate a family of degradable elastomers covering a broad range of properties from a single biocompatible and biodegradable prepolymer.

  14. Enhanced Design of a Soft Thin-Film Vibrotactile Actuator Based on PVC Gel

    Directory of Open Access Journals (Sweden)

    Won-Hyeong Park

    2017-09-01

    Full Text Available We fabricated a soft thin-film vibrotactile actuator, which can be easily inserted into wearable devices, based on an electroactive PVC gel. One of the most important factors in fabricating a soft and thin vibrotactile actuator is to create vibrational force strong enough to stimulate human skin in a wide frequency range. To achieve this, we investigate the working principle of the PVC gel and suggest a new structure in which most of electric energy contributes to the deformation of the PVC gel. Due to this structure, the vibrational amplitude of the proposed PVC gel actuator could considerably increase (0.816 g (g = 9.8 m/s2 at resonant frequency. The vibrotactile amplitude is proportional to the amount of input voltage. It increased from 0.05 g up to 0.416 g with increasing applied voltages from 200 V to 1 kV at 1 Hz. The experimental results show that the proposed actuator can create a variety of haptic sensations.

  15. Stiffness Customization and Patterning for Property Modulation of Silicone-Based Soft Pneumatic Actuators.

    Science.gov (United States)

    Sun, Yi; Yap, Hong Kai; Liang, Xinquan; Guo, Jin; Qi, Peng; Ang, Marcelo H; Yeow, Chen-Hua

    2017-09-01

    Soft pneumatic actuators (SPAs), as novel types of motion drivers for robotic devices, excel in many applications, such as rehabilitation and biomimicry, which demand compliance and softness. To further expand their scope of utilization, the SPAs should be customizable to meet the distinctive requirements of different applications. This article proposes a novel perspective on the SPA working mechanism based on stiffness distribution and then presents a versatile method called stiffness customization and patterning (SCP) for SPA body stiffness layout as a novel attempt to customize SPAs with distinctive properties. We fabricated a hybrid type of material combining unstretchable material and silicone with customizable aggregated elasticity. The tensile results showed that embedding unstretchable material directly increases the stiffness of the hybrid material sample, and our stress-strain model for SCP is able to adequately predict the elasticity of hybrid samples with specific material ratios. By applying this approach to bending-type SPAs, we are able to mitigate SPA buckling, a main failure mode of SPAs, and improve the SPA tip force by using hybrid material with globally increased stiffness. We also diversify bending modalities with different stiffness configurations in the hybrid material. SCP offers numerous ways to engineer SPAs for more applications.

  16. Textile-Based, Interdigital, Capacitive, Soft-Strain Sensor for Wearable Applications

    Directory of Open Access Journals (Sweden)

    Ozgur Atalay

    2018-05-01

    Full Text Available The electronic textile area has gained considerable attention due to its implementation of wearable devices, and soft sensors are the main components of these systems. In this paper, a new sensor design is presented to create stretchable, capacitance-based strain sensors for human motion tracking. This involves the use of stretchable, conductive-knit fabric within the silicone elastomer matrix, as interdigitated electrodes. While conductive fabric creates a secure conductive network for electrodes, a silicone-based matrix provides encapsulation and dimensional-stability to the structure. During the benchtop characterization, sensors show linear output, i.e., R2 = 0.997, with high response time, i.e., 50 ms, and high resolution, i.e., 1.36%. Finally, movement of the knee joint during the different scenarios was successfully recorded.

  17. Characterization of LiF-based soft X-ray imaging detectors by confocal fluorescence microscopy

    International Nuclear Information System (INIS)

    Bonfigli, F; Gaudio, P; Lupelli, I; Nichelatti, E; Richetta, M; Vincenti, M A; Montereali, R M

    2010-01-01

    X-ray microscopy represents a powerful tool to obtain images of samples with very high spatial resolution. The main limitation of this technique is represented by the poor spatial resolution of standard imaging detectors. We proposed an innovative high-performance X-ray imaging detector based on the visible photoluminescence of colour centres in lithium fluoride. In this work, a confocal microscope in fluorescence mode was used to characterize LiF-based imaging detectors measuring CC integrated visible fluorescence signals of LiF crystals and films (grown on several kinds of substrates) irradiated by soft X-rays produced by a laser plasma source in different exposure conditions. The results are compared with the CC photoluminescence spectra measured on the same samples and discussed.

  18. Soft tissue-preserving computer-aided impression: a novel concept using ultrasonic 3D-scanning.

    Science.gov (United States)

    Vollborn, Thorsten; Habor, Daniel; Pekam, Fabrice Chuembou; Heger, Stefan; Marotti, Juliana; Reich, Sven; Wolfart, Stefan; Tinschert, Joachim; Radermacher, Klaus

    2014-01-01

    Subgingival preparations are often affected by blood and saliva during impression taking, regardless of whether one is using compound impression techniques or intraoral digital scanning methods. The latter are currently based on optical principles and therefore also need clean and dry surfaces. In contrast, ultrasonic waves are able to non-invasively penetrate gingiva, saliva, and blood, leading to decisive advantages, as cleaning and drying of the oral cavity becomes unnecessary. In addition, the application of ultrasound may facilitate the detection of subgingival structures without invasive manipulation, thereby reducing the risk of secondary infection and treatment time, and increasing patient comfort. Ultrasound devices commonly available for medical application and for the testing of materials are only suitable to a limited extent, as their resolution, precision, and design do not fulfill the requirements for intraoral scanning. The aim of this article is to describe the development of a novel ultrasound technology that enables soft tissue-preserving digital impressions of preparations for the CAD/CAM-based production of dental prostheses. The concept and development of the high-resolution ultrasound technique and the corresponding intraoral scanning system, as well as the integration into the CAD/CAM process chain, is presented.

  19. A navigation system for percutaneous needle interventions based on PET/CT images: design, workflow and error analysis of soft tissue and bone punctures.

    Science.gov (United States)

    Oliveira-Santos, Thiago; Klaeser, Bernd; Weitzel, Thilo; Krause, Thomas; Nolte, Lutz-Peter; Peterhans, Matthias; Weber, Stefan

    2011-01-01

    Percutaneous needle intervention based on PET/CT images is effective, but exposes the patient to unnecessary radiation due to the increased number of CT scans required. Computer assisted intervention can reduce the number of scans, but requires handling, matching and visualization of two different datasets. While one dataset is used for target definition according to metabolism, the other is used for instrument guidance according to anatomical structures. No navigation systems capable of handling such data and performing PET/CT image-based procedures while following clinically approved protocols for oncologic percutaneous interventions are available. The need for such systems is emphasized in scenarios where the target can be located in different types of tissue such as bone and soft tissue. These two tissues require different clinical protocols for puncturing and may therefore give rise to different problems during the navigated intervention. Studies comparing the performance of navigated needle interventions targeting lesions located in these two types of tissue are not often found in the literature. Hence, this paper presents an optical navigation system for percutaneous needle interventions based on PET/CT images. The system provides viewers for guiding the physician to the target with real-time visualization of PET/CT datasets, and is able to handle targets located in both bone and soft tissue. The navigation system and the required clinical workflow were designed taking into consideration clinical protocols and requirements, and the system is thus operable by a single person, even during transition to the sterile phase. Both the system and the workflow were evaluated in an initial set of experiments simulating 41 lesions (23 located in bone tissue and 18 in soft tissue) in swine cadavers. We also measured and decomposed the overall system error into distinct error sources, which allowed for the identification of particularities involved in the process as well

  20. The value of computed tomography in the diagnosis of the rotator cuff tears, and bone and soft tissue tumors

    International Nuclear Information System (INIS)

    Yoh, Sansen

    1984-01-01

    The usefulness of computed tomography (CT) in the diagnosis of rotator cuff tear was assessed. The rotator cuff could not be visualized in detail by CT unless introduction of contrast material into the joint cavity was performed. CT arthrography was performed on 21 cases of rotator cuff tears. The most detailed information was obtained when a relatively low concentration of contrast material (3.25% Angiografin) was filled in the joint cavity, and when the shoulder joint was rotated to the maximum outwards at the side. CT arthrography proved to be the most reliable method for assessing the extent and portion of the rotator cuff tears, so that it demonstrated conclusive evidence of diagnosis and management in 89% of patients studied. The usefulness of CT in the diagnosis of bone and soft tissue tumors was assessed. CT examination provided unique preoperative information which could imagine a more precise histological characteristics and anatomical localization of the lesion. Contrast enhancement (CE), when used, proved to be helpful in predicting the nature of tumors. The CE by intra-arterial infusion, or intravenous bolous injection of contrast material during the scan was more useful than that by intervenous drip infusion of the material. The information regarding change of tumor size, CT number and CE were appropriate indicators which directly corresponded to responsiveness of the tumor to the chemotheraphy and radiotherapy performed. Preoperative ABC classification of the tumor by information regarding its size, location, definition and anatomical relation of tumors to vital structures (neural, vescular, and visceral) was done by using CT. The classification clearly corresponded to the status of patients regarding the treatment required for the patients. (author)

  1. A comparison between ten advanced and soft computing models for groundwater qanat potential assessment in Iran using R and GIS

    Science.gov (United States)

    Naghibi, Seyed Amir; Pourghasemi, Hamid Reza; Abbaspour, Karim

    2018-02-01

    Considering the unstable condition of water resources in Iran and many other countries in arid and semi-arid regions, groundwater studies are very important. Therefore, the aim of this study is to model groundwater potential by qanat locations as indicators and ten advanced and soft computing models applied to the Beheshtabad Watershed, Iran. Qanat is a man-made underground construction which gathers groundwater from higher altitudes and transmits it to low land areas where it can be used for different purposes. For this purpose, at first, the location of the qanats was detected using extensive field surveys. These qanats were classified into two datasets including training (70%) and validation (30%). Then, 14 influence factors depicting the region's physical, morphological, lithological, and hydrological features were identified to model groundwater potential. Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), flexible discriminant analysis (FDA), penalized discriminant analysis (PDA), boosted regression tree (BRT), random forest (RF), artificial neural network (ANN), K-nearest neighbor (KNN), multivariate adaptive regression splines (MARS), and support vector machine (SVM) models were applied in R scripts to produce groundwater potential maps. For evaluation of the performance accuracies of the developed models, ROC curve and kappa index were implemented. According to the results, RF had the best performance, followed by SVM and BRT models. Our results showed that qanat locations could be used as a good indicator for groundwater potential. Furthermore, altitude, slope, plan curvature, and profile curvature were found to be the most important influence factors. On the other hand, lithology, land use, and slope aspect were the least significant factors. The methodology in the current study could be used by land use and terrestrial planners and water resource managers to reduce the costs of groundwater resource discovery.

  2. Computer-Game-Based Tutoring of Mathematics

    Science.gov (United States)

    Ke, Fengfeng

    2013-01-01

    This in-situ, descriptive case study examined the potential of implementing computer mathematics games as an anchor for tutoring of mathematics. Data were collected from middle school students at a rural pueblo school and an urban Hispanic-serving school, through in-field observation, content analysis of game-based tutoring-learning interactions,…

  3. A CAMAC-based laboratory computer system

    International Nuclear Information System (INIS)

    Westphal, G.P.

    1975-01-01

    A CAMAC-based laboratory computer network is described by sharing a common mass memory this offers distinct advantages over slow and core-consuming single-processor installations. A fast compiler-BASIC, with extensions for CAMAC and real-time, provides a convenient means for interactive experiment control

  4. Computer-Based Testing: Test Site Security.

    Science.gov (United States)

    Rosen, Gerald A.

    Computer-based testing places great burdens on all involved parties to ensure test security. A task analysis of test site security might identify the areas of protecting the test, protecting the data, and protecting the environment as essential issues in test security. Protecting the test involves transmission of the examinations, identifying the…

  5. PENINGKATAN SOFT SKILLS DAN HARD SKILLS MAHASISWA MELALUI PROJECT-BASED LEARNING PADA MATA KULIAH PERENCANAAN PEMBELAJARAN GEOGRAFI

    Directory of Open Access Journals (Sweden)

    Fitra Delita

    2016-08-01

    Full Text Available Penelitian ini dilakukan karena masih minimnya kemampuan soft skills dan hard skills mahasiswa. Penelitian ini bertujuan untuk meningkatkan soft skills dan hard skills mahasiswa melalui penerapan Project Based Learning pada mata kuliah Perencanaan Pembelajaran Geografi serta untuk mengetahui tanggapan mahasiswa terhadap penerapan Project Based Learning. Penelitian ini tergolong penelitian PTK dengan pengamatan selama 2 siklus. Indikator soft skills yang diamati adalah komunikasi lisan, kejujuran, partisipasi dan kreativitas. Sedangkan indikator hard skills yang digunakan adalah nilai mahasiswa, kemampuan merancang perangkat pembelajaran dan media. Data diperoleh melalui lembar observasi, kuesioner, penilaian product dan hasil tes. Hasil penelitian menunjukkan bahwa terjadi peningkatan indikator soft skill yaitu komunikasi lisan (0,54, partisipasi (0,92, kejujuran (0,42 dan kreativitas (1,4 Peningkatan jumlah mahasiswa yang mendapat nilai A pada Siklus II yaitu 8 orang (naik 25 % dari total mahasiswa, nilai B meningkat menjadi 2 orang (naik 6 % dari total mahasiswa. Indikator hard skills berupa kemampuan merancang perangkat pembelajaran dan media juga mengalami kenaikan pada Siklus II yaitu 21 orang (68 % kategori sangat baik dan 10 orang (32 % kategori baik. Mahasiswa memberi tanggapan positif terhadap penerapan Project Based Learning pada mata kuliah Perencanaan Pembelajaran Geografi. Kata kunci: Soft Skills, Hard Skills, Project Based Learning

  6. Detecting Silent Data Corruptions in Aerospace-Based Computing Using Program Invariants

    Directory of Open Access Journals (Sweden)

    Junchi Ma

    2016-01-01

    Full Text Available Soft error caused by single event upset has been a severe challenge to aerospace-based computing. Silent data corruption (SDC is one of the results incurred by soft error. SDC occurs when a program generates erroneous output with no indications. SDC is the most insidious type of results and very difficult to detect. To address this problem, we design and implement an invariant-based system called Radish. Invariants describe certain properties of a program; for example, the value of a variable equals a constant. Radish first extracts invariants at key program points and converts invariants into assertions. It then hardens the program by inserting the assertions into the source code. When a soft error occurs, assertions will be found to be false at run time and warn the users of soft error. To increase the coverage of SDC, we further propose an extension of Radish, named Radish_D, which applies software-based instruction duplication mechanism to protect the uncovered code sections. Experiments using architectural fault injections show that Radish achieves high SDC coverage with very low overhead. Furthermore, Radish_D provides higher SDC coverage than that of either Radish or pure instruction duplication.

  7. Computer based training: Technology and trends

    International Nuclear Information System (INIS)

    O'Neal, A.F.

    1986-01-01

    Computer Based Training (CBT) offers great potential for revolutionizing the training environment. Tremendous advances in computer cost performance, instructional design science, and authoring systems have combined to put CBT within the reach of all. The ability of today's CBT systems to implement powerful training strategies, simulate complex processes and systems, and individualize and control the training process make it certain that CBT will now, at long last, live up to its potential. This paper reviews the major technologies and trends involved and offers some suggestions for getting started in CBT

  8. Hybrid Multiple Soft-Sensor Models of Grinding Granularity Based on Cuckoo Searching Algorithm and Hysteresis Switching Strategy

    Directory of Open Access Journals (Sweden)

    Jie-Sheng Wang

    2015-01-01

    Full Text Available According to the characteristics of grinding process and accuracy requirements of technical indicators, a hybrid multiple soft-sensor modeling method of grinding granularity is proposed based on cuckoo searching (CS algorithm and hysteresis switching (HS strategy. Firstly, a mechanism soft-sensor model of grinding granularity is deduced based on the technique characteristics and a lot of experimental data of grinding process. Meanwhile, the BP neural network soft-sensor model and wavelet neural network (WNN soft-sensor model are set up. Then, the hybrid multiple soft-sensor model based on the hysteresis switching strategy is realized. That is to say, the optimum model is selected as the current predictive model according to the switching performance index at each sampling instant. Finally the cuckoo searching algorithm is adopted to optimize the performance parameters of hysteresis switching strategy. Simulation results show that the proposed model has better generalization results and prediction precision, which can satisfy the real-time control requirements of grinding classification process.

  9. Soft Sensor of Vehicle State Estimation Based on the Kernel Principal Component and Improved Neural Network

    Directory of Open Access Journals (Sweden)

    Haorui Liu

    2016-01-01

    Full Text Available In the car control systems, it is hard to measure some key vehicle states directly and accurately when running on the road and the cost of the measurement is high as well. To address these problems, a vehicle state estimation method based on the kernel principal component analysis and the improved Elman neural network is proposed. Combining with nonlinear vehicle model of three degrees of freedom (3 DOF, longitudinal, lateral, and yaw motion, this paper applies the method to the soft sensor of the vehicle states. The simulation results of the double lane change tested by Matlab/SIMULINK cosimulation prove the KPCA-IENN algorithm (kernel principal component algorithm and improved Elman neural network to be quick and precise when tracking the vehicle states within the nonlinear area. This algorithm method can meet the software performance requirements of the vehicle states estimation in precision, tracking speed, noise suppression, and other aspects.

  10. Fabrication of a zirconia MEMS-based microthruster by gel casting on PDMS soft molds

    International Nuclear Information System (INIS)

    Cheah, K H; Khiew, P S; Chin, J K

    2012-01-01

    A zirconia microelectromechanical-system-based microthruster was fabricated through a newly developed fabrication route. Gel casting of homogenously dispersed zirconia suspension on polydimethylsiloxane soft mold was utilized to replicate the geometries of microthruster design onto a ceramic layer of about 1.2 mm thick. Lamination of the patterned ceramic layer to another flat ceramic layer and subsequent sintering produced the microthruster. Characterizations on the fabricated prototype showed good shape retention on the replicated geometries and good quality of lamination. Shrinkage of about 10–15% was noted after sintering. The current fabrication route is particularly promising for the development of high-performance micropropulsion systems which require their structural material to survive in an extreme environment which is corrosive, of high temperature and highly oxidative. (paper)

  11. Preparation and properties of Cobalt-based soft magnetic material prepared by novel powder metallurgy

    Energy Technology Data Exchange (ETDEWEB)

    Srivastava, Yogesh, E-mail: 123209001_yogesh@manit.ac.in; Srivastava, Sanjay

    2017-02-01

    The present work deals with the development of nanocrystalline 60Co–26Fe–14Al (wt%) soft magnetic materials via mechanical milling of elemental powders. The evolution of solid solution during milling proceeded with continuous decrease in atomic order and the crystallite size, and an introduction of internal strain and dislocations. The milling-induced lattice defects, crystallite size reduction, and atomic disorder exhibited a decrease in saturation magnetization, remanence magnetization, squareness ratio, and blocking temperature with increasing milling time. It has been demonstrated that, at subzero temperatures, the magnetization decreases with increasing temperature due to the development of an effective anisotropy caused by an evolution of canted spin structure owing to the introduction of lattice defects during milling. - Highlights: • Co-based HA have been fabricated by mechanical alloying. • The effect of milling time was investigated. • The saturation magnetization can be reached up to 140.79 emu/g.

  12. Annealing effects on magnetic properties of silicone-coated iron-based soft magnetic composites

    Science.gov (United States)

    Wu, Shen; Sun, Aizhi; Zhai, Fuqiang; Wang, Jin; Zhang, Qian; Xu, Wenhuan; Logan, Philip; Volinsky, Alex A.

    2012-03-01

    This paper focuses on novel iron-based soft magnetic composites synthesis utilizing high thermal stability silicone resin to coat iron powder. The effect of an annealing treatment on the magnetic properties of synthesized magnets was investigated. The coated silicone insulating layer was characterized by scanning electron microscopy and energy dispersive X-ray spectroscopy. Silicone uniformly coated the powder surface, resulting in a reduction of the imaginary part of the permeability, thereby increasing the electrical resistivity and the operating frequency of the synthesized magnets. The annealing treatment increased the initial permeability, the maximum permeability, and the magnetic induction, and decreased the coercivity. Annealing at 580 °C increased the maximum permeability by 72.5%. The result of annealing at 580 °C shows that the ferromagnetic resonance frequency increased from 2 kHz for conventional epoxy resin coated samples to 80 kHz for the silicone resin insulated composites.

  13. A New Hybrid Viscoelastic Soft Tissue Model based on Meshless Method for Haptic Surgical Simulation

    Science.gov (United States)

    Bao, Yidong; Wu, Dongmei; Yan, Zhiyuan; Du, Zhijiang

    2013-01-01

    This paper proposes a hybrid soft tissue model that consists of a multilayer structure and many spheres for surgical simulation system based on meshless. To improve accuracy of the model, tension is added to the three-parameter viscoelastic structure that connects the two spheres. By using haptic device, the three-parameter viscoelastic model (TPM) produces accurate deformationand also has better stress-strain, stress relaxation and creep properties. Stress relaxation and creep formulas have been obtained by mathematical formula derivation. Comparing with the experimental results of the real pig liver which were reported by Evren et al. and Amy et al., the curve lines of stress-strain, stress relaxation and creep of TPM are close to the experimental data of the real liver. Simulated results show that TPM has better real-time, stability and accuracy. PMID:24339837

  14. Computer-based and web-based radiation safety training

    Energy Technology Data Exchange (ETDEWEB)

    Owen, C., LLNL

    1998-03-01

    The traditional approach to delivering radiation safety training has been to provide a stand-up lecture of the topic, with the possible aid of video, and to repeat the same material periodically. New approaches to meeting training requirements are needed to address the advent of flexible work hours and telecommuting, and to better accommodate individuals learning at their own pace. Computer- based and web-based radiation safety training can provide this alternative. Computer-based and web- based training is an interactive form of learning that the student controls, resulting in enhanced and focused learning at a time most often chosen by the student.

  15. Soft Cysteine Signaling Network: The Functional Significance of Cysteine in Protein Function and the Soft Acids/Bases Thiol Chemistry That Facilitates Cysteine Modification.

    Science.gov (United States)

    Wible, Ryan S; Sutter, Thomas R

    2017-03-20

    The unique biophysical and electronic properties of cysteine make this molecule one of the most biologically critical amino acids in the proteome. The defining sulfur atom in cysteine is much larger than the oxygen and nitrogen atoms more commonly found in the other amino acids. As a result of its size, the valence electrons of sulfur are highly polarizable. Unique protein microenvironments favor the polarization of sulfur, thus increasing the overt reactivity of cysteine. Here, we provide a brief overview of the endogenous generation of reactive oxygen and electrophilic species and specific examples of enzymes and transcription factors in which the oxidation or covalent modification of cysteine in those proteins modulates their function. The perspective concludes with a discussion of cysteine chemistry and biophysics, the hard and soft acids and bases model, and the proposal of the Soft Cysteine Signaling Network: a hypothesis proposing the existence of a complex signaling network governed by layered chemical reactivity and cross-talk in which the chemical modification of reactive cysteine in biological networks triggers the reorganization of intracellular biochemistry to mitigate spikes in endogenous or exogenous oxidative or electrophilic stress.

  16. A New Method of Multiattribute Decision-Making Based on Interval-Valued Hesitant Fuzzy Soft Sets and Its Application

    Directory of Open Access Journals (Sweden)

    Yan Yang

    2017-01-01

    Full Text Available Combining interval-valued hesitant fuzzy soft sets (IVHFSSs and a new comparative law, we propose a new method, which can effectively solve multiattribute decision-making (MADM problems. Firstly, a characteristic function of two interval values and a new comparative law of interval-valued hesitant fuzzy elements (IVHFEs based on the possibility degree are proposed. Then, we define two important definitions of IVHFSSs including the interval-valued hesitant fuzzy soft quasi subset and soft quasi equal based on the new comparative law. Finally, an algorithm is presented to solve MADM problems. We also use the method proposed in this paper to evaluate the importance of major components of the well drilling mud pump.

  17. A soft X-ray source based on a low divergence, high repetition rate ultraviolet laser

    Science.gov (United States)

    Crawford, E. A.; Hoffman, A. L.; Milroy, R. D.; Quimby, D. C.; Albrecht, G. F.

    The CORK code is utilized to evaluate the applicability of low divergence ultraviolet lasers for efficient production of soft X-rays. The use of the axial hydrodynamic code wih one ozone radial expansion to estimate radial motion and laser energy is examined. The calculation of ionization levels of the plasma and radiation rates by employing the atomic physics and radiation model included in the CORK code is described. Computations using the hydrodynamic code to determine the effect of laser intensity, spot size, and wavelength on plasma electron temperature are provided. The X-ray conversion efficiencies of the lasers are analyzed. It is observed that for a 1 GW laser power the X-ray conversion efficiency is a function of spot size, only weakly dependent on pulse length for time scales exceeding 100 psec, and better conversion efficiencies are obtained at shorter wavelengths. It is concluded that these small lasers focused to 30 micron spot sizes and 10 to the 14th W/sq cm intensities are useful sources of 1-2 keV radiation.

  18. Machinima and Video-Based Soft-Skills Training for Frontline Healthcare Workers.

    Science.gov (United States)

    Conkey, Curtis A; Bowers, Clint; Cannon-Bowers, Janis; Sanchez, Alicia

    2013-02-01

    Multimedia training methods have traditionally relied heavily on video-based technologies, and significant research has shown these to be very effective training tools. However, production of video is time and resource intensive. Machinima technologies are based on videogaming technology. Machinima technology allows videogame technology to be manipulated into unique scenarios based on entertainment or training and practice applications. Machinima is the converting of these unique scenarios into video vignettes that tell a story. These vignettes can be interconnected with branching points in much the same way that education videos are interconnected as vignettes between decision points. This study addressed the effectiveness of machinima-based soft-skills education using avatar actors versus the traditional video teaching application using human actors in the training of frontline healthcare workers. This research also investigated the difference between presence reactions when using avatar actor-produced video vignettes as compared with human actor-produced video vignettes. Results indicated that the difference in training and/or practice effectiveness is statistically insignificant for presence, interactivity, quality, and the skill of assertiveness. The skill of active listening presented a mixed result indicating the need for careful attention to detail in situations where body language and facial expressions are critical to communication. This study demonstrates that a significant opportunity exists for the exploitation of avatar actors in video-based instruction.

  19. Computer-Based Wireless Advertising Communication System

    Directory of Open Access Journals (Sweden)

    Anwar Al-Mofleh

    2009-10-01

    Full Text Available In this paper we developed a computer based wireless advertising communication system (CBWACS that enables the user to advertise whatever he wants from his own office to the screen in front of the customer via wireless communication system. This system consists of two PIC microcontrollers, transmitter, receiver, LCD, serial cable and antenna. The main advantages of the system are: the wireless structure and the system is less susceptible to noise and other interferences because it uses digital communication techniques.

  20. Computer-based theory of strategies

    Energy Technology Data Exchange (ETDEWEB)

    Findler, N V

    1983-01-01

    Some of the objectives and working tools of a new area of study, tentatively called theory of strategies, are described. It is based on the methodology of artificial intelligence, decision theory, operations research and digital gaming. The latter refers to computing activity that incorporates model building, simulation and learning programs in conflict situations. Three long-term projects which aim at automatically analyzing and synthesizing strategies are discussed. 27 references.

  1. Using Online Project-Based Capstone Experiences to Enhance Soft Skills Development

    Science.gov (United States)

    Britton, Gwendolyn Suzanne

    2013-01-01

    Employers of newly minted information technology graduates are concerned that students graduating with information technology degrees offered in online environments are lacking critical noncomputing skills (soft skills). Further, it is unclear whether online environments have the capacity to foster the "soft skills" necessary for…

  2. Facial soft-tissue asymmetry in three-dimensional cone-beam computed tomography images of children with surgically corrected unilateral clefts.

    Science.gov (United States)

    Starbuck, John Marlow; Ghoneima, Ahmed; Kula, Katherine

    2014-03-01

    Cleft lip with or without cleft palate (CL/P) is a relatively common craniofacial malformation involving bony and soft-tissue disruptions of the nasolabial and dentoalveolar regions. The combination of CL/P and subsequent craniofacial surgeries to close the cleft and improve appearance of the cutaneous upper lip and nose can cause scarring and muscle pull, possibly resulting in soft-tissue depth asymmetries across the face. We tested the hypothesis that tissue depths in children with unilateral CL/P exhibit differences in symmetry across the sides of the face. Twenty-eight tissue depths were measured on cone-beam computed tomography images of children with unilateral CL/P (n = 55), aged 7 to 17 years, using Dolphin software (version 11.5). Significant differences in tissue depth symmetry were found around the cutaneous upper lip and nose in patients with unilateral CL/P.

  3. Computing dispersion curves of elastic/viscoelastic transversely-isotropic bone plates coupled with soft tissue and marrow using semi-analytical finite element (SAFE) method.

    Science.gov (United States)

    Nguyen, Vu-Hieu; Tran, Tho N H T; Sacchi, Mauricio D; Naili, Salah; Le, Lawrence H

    2017-08-01

    We present a semi-analytical finite element (SAFE) scheme for accurately computing the velocity dispersion and attenuation in a trilayered system consisting of a transversely-isotropic (TI) cortical bone plate sandwiched between the soft tissue and marrow layers. The soft tissue and marrow are mimicked by two fluid layers of finite thickness. A Kelvin-Voigt model accounts for the absorption of all three biological domains. The simulated dispersion curves are validated by the results from the commercial software DISPERSE and published literature. Finally, the algorithm is applied to a viscoelastic trilayered TI bone model to interpret the guided modes of an ex-vivo experimental data set from a bone phantom. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Triboelectric-Nanogenerator-Based Soft Energy-Harvesting Skin Enabled by Toughly Bonded Elastomer/Hydrogel Hybrids.

    Science.gov (United States)

    Liu, Ting; Liu, Mengmeng; Dou, Su; Sun, Jiangman; Cong, Zifeng; Jiang, Chunyan; Du, Chunhua; Pu, Xiong; Hu, Weiguo; Wang, Zhong Lin

    2018-03-27

    A major challenge accompanying the booming next-generation soft electronics is providing correspondingly soft and sustainable power sources for driving such devices. Here, we report stretchable triboelectric nanogenerators (TENG) with dual working modes based on the soft hydrogel-elastomer hybrid as energy skins for harvesting biomechanical energies. The tough interfacial bonding between the hydrophilic hydrogel and hydrophobic elastomer, achieved by the interface modification, ensures the stable mechanical and electrical performances of the TENGs. Furthermore, the dehydration of this toughly bonded hydrogel-elastomer hybrid is significantly inhibited (the average dehydration decreases by over 73%). With PDMS as the electrification layer and hydrogel as the electrode, a stretchable, transparent (90% transmittance), and ultrathin (380 μm) single-electrode TENG was fabricated to conformally attach on human skin and deform as the body moves. The two-electrode mode TENG is capable of harvesting energy from arbitrary human motions (press, stretch, bend, and twist) to drive the self-powered electronics. This work provides a feasible technology to design soft power sources, which could potentially solve the energy issues of soft electronics.

  5. Computational alloy design of (Co1-xNix)88Zr7B4Cu1 nanocomposite soft magnets

    Science.gov (United States)

    Dong, B.; Healy, J.; Lan, S.; Daniil, M.; Willard, M. A.

    2018-05-01

    The dependence of coercivity on composition is an important factor for establishing optimized soft magnetic properties. In this study, we have used the random anisotropy and coherent rotation models to estimate the variation of coercivity with composition in (Co1-xNix)88Zr7B4Cu1 nanocomposite alloys. Our calculations that the magnetoelastic anisotropy contribution to coercivity dominates for Ni rich compositions (x > 0.5). A small range of compositions (0.65 < x < 0.75) is predicted to result in low values of coercivity (<10 A/m). To validate this prediction, (Co1-xNix)88Zr7B4Cu1 nanocomposites in this range were prepared by melt spinning followed by 3600 s isothermal annealing at the primary crystallization peak temperature (˜673 K). Hysteresis loops were measured using vibrating sample magnetometry at room temperature and saturation magnetostriction was measured using a strain gage based magnetostrictometer. Moderately small coercivities (30-40 A/m) and magnetostrictions (3-4 ppm) were measured at for samples with 0.685 < x < 0.725. Our measured coercivity had a minimum value of 32 A/m at x = 0.725, a shift in composition of about 5 at% in the direction of higher Ni content and without the anticipated low value of coercivity. Several reasons for the inaccuracy of this approach are described, including: ignored contributions from amorphous phase (especially in magnetoealstic anisotropy), composition segregation during crystallization leading to unpredictable compositional shifts in prediction, and the general observation that the predictability of minimum coercivity from minimal combined anisotropies has unexplained deviation even in far less complicated materials.

  6. Design and characterization of low-cost fabric-based flat pneumatic actuators for soft assistive glove application.

    Science.gov (United States)

    Yap, Hong Kai; Sebastian, Frederick; Wiedeman, Christopher; Yeow, Chen-Hua

    2017-07-01

    We present the design of low-cost fabric-based Hat pneumatic actuators for soft assistive glove application. The soft assistive glove is designed to assist hand impaired patients in performing activities of daily living and rehabilitation. The actuators consist of flexible materials such as fabric and latex bladder. Using zero volume actuation concept, the 2D configuration of the actuators simplifies the manufacturing process and allows the actuators to be more compact. The actuators achieve bi-directional flexion and extension motions. Compared to previously developed inflatable soft actuators, the actuators generate sufficient force and torque to assist in both finger flexion and extension at lower air pressure. Preliminary evaluation results show that the glove is able to provide both active finger flexion and extension assistance for activities of daily living and rehabilitative training.

  7. Monitoring the Microgravity Environment Quality On-board the International Space Station Using Soft Computing Techniques. Part 2; Preliminary System Performance Results

    Science.gov (United States)

    Jules, Kenol; Lin, Paul P.; Weiss, Daniel S.

    2002-01-01

    and unknown vibratory disturbance sources. Several soft computing techniques such as Kohonen's Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

  8. Confidential benchmarking based on multiparty computation

    DEFF Research Database (Denmark)

    Damgård, Ivan Bjerre; Damgård, Kasper Lyneborg; Nielsen, Kurt

    We report on the design and implementation of a system that uses multiparty computation to enable banks to benchmark their customers' confidential performance data against a large representative set of confidential performance data from a consultancy house. The system ensures that both the banks......' and the consultancy house's data stays confidential, the banks as clients learn nothing but the computed benchmarking score. In the concrete business application, the developed prototype help Danish banks to find the most efficient customers among a large and challenging group of agricultural customers with too much...... debt. We propose a model based on linear programming for doing the benchmarking and implement it using the SPDZ protocol by Damgård et al., which we modify using a new idea that allows clients to supply data and get output without having to participate in the preprocessing phase and without keeping...

  9. "Transit data"-based MST computation

    Directory of Open Access Journals (Sweden)

    Thodoris Karatasos

    2017-10-01

    Full Text Available In this work, we present an innovative image recognition technique which is based on the exploitation of transit-data in images or simple photographs of sites of interest. Our objective is to automatically transform real-world images to graphs and, then, compute Minimum Spanning Trees (MST in them.We apply this framework and present an application which automatically computes efficient construction plans (for escalator or low-emission hot spots for connecting all points of interest in cultural sites, i.e., archaeological sites, museums, galleries, etc, aiming to to facilitate global physical access to cultural heritage and artistic work and make it accessible to all groups of population.

  10. Evolutionary Based Solutions for Green Computing

    CERN Document Server

    Kołodziej, Joanna; Li, Juan; Zomaya, Albert

    2013-01-01

    Today’s highly parameterized large-scale distributed computing systems may be composed  of a large number of various components (computers, databases, etc) and must provide a wide range of services. The users of such systems, located at different (geographical or managerial) network cluster may have a limited access to the system’s services and resources, and different, often conflicting, expectations and requirements. Moreover, the information and data processed in such dynamic environments may be incomplete, imprecise, fragmentary, and overloading. All of the above mentioned issues require some intelligent scalable methodologies for the management of the whole complex structure, which unfortunately may increase the energy consumption of such systems.   This book in its eight chapters, addresses the fundamental issues related to the energy usage and the optimal low-cost system design in high performance ``green computing’’ systems. The recent evolutionary and general metaheuristic-based solutions ...

  11. Computational chemistry and metal-based radiopharmaceuticals

    International Nuclear Information System (INIS)

    Neves, M.; Fausto, R.

    1998-01-01

    Computer-assisted techniques have found extensive use in the design of organic pharmaceuticals but have not been widely applied on metal complexes, particularly on radiopharmaceuticals. Some examples of computer generated structures of complexes of In, Ga and Tc with N, S, O and P donor ligands are referred. Besides parameters directly related with molecular geometries, molecular properties of the predicted structures, as ionic charges or dipole moments, are considered to be related with biodistribution studies. The structure of a series of oxo neutral Tc-biguanide complexes are predicted by molecular mechanics calculations, and their interactions with water molecules or peptide chains correlated with experimental data of partition coefficients and percentage of human protein binding. The results stress the interest of using molecular modelling to predict molecular properties of metal-based radiopharmaceuticals, which can be successfully correlated with results of in vitro studies. (author)

  12. A Quatro-Based 65-nm Flip-Flop Circuit for Soft-Error Resilience

    Science.gov (United States)

    Li, Y.-Q.; Wang, H.-B.; Liu, R.; Chen, L.; Nofal, I.; Shi, S.-T.; He, A.-L.; Guo, G.; Baeg, S. H.; Wen, S.-J.; Wong, R.; Chen, M.; Wu, Q.

    2017-06-01

    A flip-flop circuit hardened against soft errors is presented in this paper. This design is an improved version of Quatro for further enhanced soft-error resilience by integrating the guard-gate technique. The proposed design, as well as reference Quatro and regular flip-flops, was implemented and manufactured in a 65-nm CMOS bulk technology. Experimental characterization results of their alpha and heavy ions soft-error rates verified the superior hardening performance of the proposed design over the other two circuits.

  13. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

    Directory of Open Access Journals (Sweden)

    Jiangyi Qin

    Full Text Available A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

  14. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

    Science.gov (United States)

    Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

    2015-01-01

    A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

  15. Soft-sensing Modeling Based on MLS-SVM Inversion for L-lysine Fermentation Processes

    Directory of Open Access Journals (Sweden)

    Bo Wang

    2015-06-01

    Full Text Available A modeling approach 63 based on multiple output variables least squares support vector machine (MLS-SVM inversion is presented by a combination of inverse system and support vector machine theory. Firstly, a dynamic system model is developed based on material balance relation of a fed-batch fermentation process, with which it is analyzed whether an inverse system exists or not, and into which characteristic information of a fermentation process is introduced to set up an extended inversion model. Secondly, an initial extended inversion model is developed off-line by the use of the fitting capacity of MLS-SVM; on-line correction is made by the use of a differential evolution (DE algorithm on the basis of deviation information. Finally, a combined pseudo-linear system is formed by means of a serial connection of a corrected extended inversion model behind the L-lysine fermentation processes; thereby crucial biochemical parameters of a fermentation process could be predicted on-line. The simulation experiment shows that this soft-sensing modeling method features very high prediction precision and can predict crucial biochemical parameters of L-lysine fermentation process very well.

  16. Fabrication of platinum nanopillars on peptide-based soft structures using a focused ion beam

    International Nuclear Information System (INIS)

    Joshi, K B; Singh, Prabhpreet; Verma, Sandeep

    2009-01-01

    An expedient entry into the construction of bionanocomposites by merging peptide self-assembly, focused ion beam milling, and electron beam-induced deposition is described. Hexapeptides 1 and 2 revealed spherical self-assembled structures which are confirmed by a scanning electron microscope (SEM), atomic force microscope (AFM), focused ion beam/high-resolution scanning electron microscope (FIB-HRSEM), and high-resolution transmission electron microscopy (HRTEM). The microspheres from 1 and 2 are milled with the help of an ion beam to create different shapes. Soft spherical peptide-based structures were also subjected to fabrication under a gallium ion beam, followed by deposition of platinum pillars through a direct write process. It is envisaged that such hybrid bionanocomposites could have applications ranging from Pt-based hydrogenation catalysts to bioelectronics. In addition, such a fabrication process might also be useful to electrically connect two biological systems in order to study an electrical signal or electron transport phenomenon and structural transformations

  17. The HEP Software and Computing Knowledge Base

    Science.gov (United States)

    Wenaus, T.

    2017-10-01

    HEP software today is a rich and diverse domain in itself and exists within the mushrooming world of open source software. As HEP software developers and users we can be more productive and effective if our work and our choices are informed by a good knowledge of what others in our community have created or found useful. The HEP Software and Computing Knowledge Base, hepsoftware.org, was created to facilitate this by serving as a collection point and information exchange on software projects and products, services, training, computing facilities, and relating them to the projects, experiments, organizations and science domains that offer them or use them. It was created as a contribution to the HEP Software Foundation, for which a HEP S&C knowledge base was a much requested early deliverable. This contribution will motivate and describe the system, what it offers, its content and contributions both existing and needed, and its implementation (node.js based web service and javascript client app) which has emphasized ease of use for both users and contributors.

  18. Computational steering of GEM based detector simulations

    Science.gov (United States)

    Sheharyar, Ali; Bouhali, Othmane

    2017-10-01

    Gas based detector R&D relies heavily on full simulation of detectors and their optimization before final prototypes can be built and tested. These simulations in particular those with complex scenarios such as those involving high detector voltages or gas with larger gains are computationally intensive may take several days or weeks to complete. These long-running simulations usually run on the high-performance computers in batch mode. If the results lead to unexpected behavior, then the simulation might be rerun with different parameters. However, the simulations (or jobs) may have to wait in a queue until they get a chance to run again because the supercomputer is a shared resource that maintains a queue of other user programs as well and executes them as time and priorities permit. It may result in inefficient resource utilization and increase in the turnaround time for the scientific experiment. To overcome this issue, the monitoring of the behavior of a simulation, while it is running (or live), is essential. In this work, we employ the computational steering technique by coupling the detector simulations with a visualization package named VisIt to enable the exploration of the live data as it is produced by the simulation.

  19. A computer-based purchase management system

    International Nuclear Information System (INIS)

    Kuriakose, K.K.; Subramani, M.G.

    1989-01-01

    The details of a computer-based purchase management system developed to meet the specific requirements of Madras Regional Purchase Unit (MRPU) is given. Howe ver it can be easily modified to meet the requirements of any other purchase department. It covers various operations of MRPU starting from indent processing to preparation of purchase orders and reminders. In order to enable timely management action and control facilities are provided to generate the necessary management information reports. The scope for further work is also discussed. The system is completely menu driven and user friendly. Appendix A and B contains the menu implemented and the sample outputs respectively. (author)

  20. Secure information transfer based on computing reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Szmoski, R.M.; Ferrari, F.A.S. [Department of Physics, Universidade Estadual de Ponta Grossa, 84030-900, Ponta Grossa (Brazil); Pinto, S.E. de S, E-mail: desouzapinto@pq.cnpq.br [Department of Physics, Universidade Estadual de Ponta Grossa, 84030-900, Ponta Grossa (Brazil); Baptista, M.S. [Institute for Complex Systems and Mathematical Biology, SUPA, University of Aberdeen, Aberdeen (United Kingdom); Viana, R.L. [Department of Physics, Universidade Federal do Parana, 81531-990, Curitiba, Parana (Brazil)

    2013-04-01

    There is a broad area of research to ensure that information is transmitted securely. Within this scope, chaos-based cryptography takes a prominent role due to its nonlinear properties. Using these properties, we propose a secure mechanism for transmitting data that relies on chaotic networks. We use a nonlinear on–off device to cipher the message, and the transfer entropy to retrieve it. We analyze the system capability for sending messages, and we obtain expressions for the operating time. We demonstrate the system efficiency for a wide range of parameters. We find similarities between our method and the reservoir computing.

  1. Computer Profiling Based Model for Investigation

    OpenAIRE

    Neeraj Choudhary; Nikhil Kumar Singh; Parmalik Singh

    2011-01-01

    Computer profiling is used for computer forensic analysis, and proposes and elaborates on a novel model for use in computer profiling, the computer profiling object model. The computer profiling object model is an information model which models a computer as objects with various attributes and inter-relationships. These together provide the information necessary for a human investigator or an automated reasoning engine to make judgments as to the probable usage and evidentiary value of a comp...

  2. GPU-based cone beam computed tomography.

    Science.gov (United States)

    Noël, Peter B; Walczak, Alan M; Xu, Jinhui; Corso, Jason J; Hoffmann, Kenneth R; Schafer, Sebastian

    2010-06-01

    The use of cone beam computed tomography (CBCT) is growing in the clinical arena due to its ability to provide 3D information during interventions, its high diagnostic quality (sub-millimeter resolution), and its short scanning times (60 s). In many situations, the short scanning time of CBCT is followed by a time-consuming 3D reconstruction. The standard reconstruction algorithm for CBCT data is the filtered backprojection, which for a volume of size 256(3) takes up to 25 min on a standard system. Recent developments in the area of Graphic Processing Units (GPUs) make it possible to have access to high-performance computing solutions at a low cost, allowing their use in many scientific problems. We have implemented an algorithm for 3D reconstruction of CBCT data using the Compute Unified Device Architecture (CUDA) provided by NVIDIA (NVIDIA Corporation, Santa Clara, California), which was executed on a NVIDIA GeForce GTX 280. Our implementation results in improved reconstruction times from minutes, and perhaps hours, to a matter of seconds, while also giving the clinician the ability to view 3D volumetric data at higher resolutions. We evaluated our implementation on ten clinical data sets and one phantom data set to observe if differences occur between CPU and GPU-based reconstructions. By using our approach, the computation time for 256(3) is reduced from 25 min on the CPU to 3.2 s on the GPU. The GPU reconstruction time for 512(3) volumes is 8.5 s. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

  3. Unified Research on Network-Based Hard/Soft Information Fusion

    Science.gov (United States)

    2016-02-02

    3.2.1 Hard +Soft Data Association Data gathered during various Counterinsurgency (or COIN) operations is in different formats . For example, the...characteristic, observation time, and related data. Figure 45: Sample snapshot frame from hard sensor data TML formats were developed and...160 Figure 54: Penn State components of overall hard and soft fusion process Summary of Year 1 Accomplishments • Team formation • Initial

  4. PERANGKAT PEMBELAJARAN PROBLEM BASED LEARNING BERORIENTASI GREEN CHEMISTRY MATERI HIDROLISIS GARAM UNTUK MENGEMBANGKAN SOFT SKILL KONSERVASI SISWA

    Directory of Open Access Journals (Sweden)

    A. Rosita

    2014-10-01

    Full Text Available Penelitian ini bertujuan untuk mengembangkan perangkat pembelajaran problem based learning berorientasi green chemistry pada materi hidrolisis garam untuk mengembangkan soft skill konservasi siswa SMA. Metode penelitian ini adalah research and development (R&D. Hasil penelitian menunjukkan LKS yang dikembangkan sangat layak untuk digunakan dalam pembelajaran kimia. Perangkat pembelajaran dapat meningkatkan pemahaman konsep siswa materi hidrolisis garam dengan N-gain sebesar 0,63 (sedang. Peningkatan soft skill konservasi siswa yang berkriteria tinggi sebanyak 35,48 % sedangkan yang berkriteria sedang 64,52 %. This research has aim to developt teaching and learning instrument application on problem based learning which oriented on green chemistry on salt hydrolisys for developing conservation soft skill for student. The method of this research is research and development (R&D. The results showed a very worthy worksheets developed for use in teaching chemistry. Teaching instrument can improve the understanding of student concept of salt hydrolysis matery can get N-gain 0,63 (medium. The improving soft skill of student conservation has high criteria 35,48%. For medium has 64,52%.

  5. Transforming bases to bytes: Molecular computing with DNA

    Indian Academy of Sciences (India)

    Despite the popular image of silicon-based computers for computation, an embryonic field of mole- cular computation is emerging, where molecules in solution perform computational ..... [4] Mao C, Sun W, Shen Z and Seeman N C 1999. A nanomechanical device based on the B-Z transition of DNA; Nature 397 144–146.

  6. An Overview of Computer-Based Natural Language Processing.

    Science.gov (United States)

    Gevarter, William B.

    Computer-based Natural Language Processing (NLP) is the key to enabling humans and their computer-based creations to interact with machines using natural languages (English, Japanese, German, etc.) rather than formal computer languages. NLP is a major research area in the fields of artificial intelligence and computational linguistics. Commercial…

  7. A novel method of freeform surface grinding with a soft wheel based on industrial robots

    Science.gov (United States)

    Sha, Sheng-chun; Guo, Xiao-ling

    2011-08-01

    In order to meet the growing demand for high-quality images, optical elements of freeform surface are more and more applied to imaging system. However the fabrication of freeform surface optical elements is much more difficult than that of traditional spherical ones. Recent research on freeform surface manufacture often deals with precision machine tools which have limitations on dimensions and are always expensive. Little has been researched on industrial robots. In this paper, a new method of freeform surface grinding based on industrial robots was found. This method could be applied to both whole surface grinding as well as partial surface grinding. The diameter of lenses to be ground would not be restricted to the machine tool's size. In this method a high-speed-rotating soft wheel was used. The relation between removing amount and grinding time which could be called removing function was established and measured. The machining precision was achieved by means of controlling the grinding time instead of the machine tool or industrial robot itself. There are two main factors affecting the removing function: i).rotating speed of the soft wheel; ii).pressure between the wheel and the work piece. In this paper, two groups of experiments have been conducted. One is the removing function tested at constant rotating speed while under different pressure. The other is that tested under a certain pressure with variable speed. Tables and curves which can show the effect of speed and pressure on the removing efficiency have been obtained. Cause for inaccuracy between experiment data and calculated result according to the theory and the non-linearity in the curves was analyzed. Through these analyses the removing function could be concluded under certain condition including rotating speed and pressure. Finally several experiments were performed to verify the appropriateness of the removing function. It could also be concluded that this method was more efficient in comparison

  8. Soft X-ray synchrotron radiation spectroscopy study of molecule-based nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Lee, E. S.; Kim, D. H.; Kang, J. S.; Kim, P. [The Catholic University of Korea, Bucheon (Korea, Republic of); Kim, K. H. [Korea University, Jochiwon (Korea, Republic of); Baik, J. Y.; Shin, H. J. [POSTECH, Pohang (Korea, Republic of)

    2014-11-15

    The electronic structures of molecule-based nanoparticles, such as biomineralized Helicobacter pylori ferritin (Hpf), Heme, and RbCo[Fe(CN){sub 6}]H{sub 2}O (RbCoFe) Prussian blue analogue, have been investigated by employing photoemission spectroscopy and soft X-ray absorption spectroscopy. Fe ions are found to be nearly trivalent in Hpf and Heme nanoparticles, which provides evidence that the amount of magnetite (Fe{sub 3}O{sub 4}) should be negligible in the Hpf core and that the biomineralization of Fe oxides in the high-Fe-bound-state Hpf core arises from a hematite-like formation. On the other hand, Fe ions are nearly divalent and Co ions are Co{sup 2+}-Co{sup 3+} mixed-valent in RbCoFe. Therefore this finding suggests that the mechanism of the photo-induced transition in RbCoFe Prussian blue analogue is not a simple spin-state transition of Fe{sup 2+}-Co{sup 3+} → Fe{sup 3+}-Co{sup 2+}. It is likely that Co{sup 2+} ions have the high-spin configuration while Fe{sup 2+} ions have the low-spin configuration.

  9. Soft object deformation monitoring and learning for model-based robotic hand manipulation.

    Science.gov (United States)

    Cretu, Ana-Maria; Payeur, Pierre; Petriu, Emil M

    2012-06-01

    This paper discusses the design and implementation of a framework that automatically extracts and monitors the shape deformations of soft objects from a video sequence and maps them with force measurements with the goal of providing the necessary information to the controller of a robotic hand to ensure safe model-based deformable object manipulation. Measurements corresponding to the interaction force at the level of the fingertips and to the position of the fingertips of a three-finger robotic hand are associated with the contours of a deformed object tracked in a series of images using neural-network approaches. The resulting model captures the behavior of the object and is able to predict its behavior for previously unseen interactions without any assumption on the object's material. The availability of such models can contribute to the improvement of a robotic hand controller, therefore allowing more accurate and stable grasp while providing more elaborate manipulation capabilities for deformable objects. Experiments performed for different objects, made of various materials, reveal that the method accurately captures and predicts the object's shape deformation while the object is submitted to external forces applied by the robot fingers. The proposed method is also fast and insensitive to severe contour deformations, as well as to smooth changes in lighting, contrast, and background.

  10. From Cellulosic Based Liquid Crystalline Sheared Solutions to 1D and 2D Soft Materials

    Directory of Open Access Journals (Sweden)

    Maria Helena Godinho

    2014-06-01

    Full Text Available Liquid crystalline cellulosic-based solutions described by distinctive properties are at the origin of different kinds of multifunctional materials with unique characteristics. These solutions can form chiral nematic phases at rest, with tuneable photonic behavior, and exhibit a complex behavior associated with the onset of a network of director field defects under shear. Techniques, such as Nuclear Magnetic Resonance (NMR, Rheology coupled with NMR (Rheo-NMR, rheology, optical methods, Magnetic Resonance Imaging (MRI, Wide Angle X-rays Scattering (WAXS, were extensively used to enlighten the liquid crystalline characteristics of these cellulosic solutions. Cellulosic films produced by shear casting and fibers by electrospinning, from these liquid crystalline solutions, have regained wider attention due to recognition of their innovative properties associated to their biocompatibility. Electrospun membranes composed by helical and spiral shape fibers allow the achievement of large surface areas, leading to the improvement of the performance of this kind of systems. The moisture response, light modulated, wettability and the capability of orienting protein and cellulose crystals, opened a wide range of new applications to the shear casted films. Characterization by NMR, X-rays, tensile tests, AFM, and optical methods allowed detailed characterization of those soft cellulosic materials. In this work, special attention will be given to recent developments, including, among others, a moisture driven cellulosic motor and electro-optical devices.

  11. Annealing effects on magnetic properties of silicone-coated iron-based soft magnetic composites

    International Nuclear Information System (INIS)

    Wu Shen; Sun Aizhi; Zhai Fuqiang; Wang Jin; Zhang Qian; Xu Wenhuan; Logan, Philip; Volinsky, Alex A.

    2012-01-01

    This paper focuses on novel iron-based soft magnetic composites synthesis utilizing high thermal stability silicone resin to coat iron powder. The effect of an annealing treatment on the magnetic properties of synthesized magnets was investigated. The coated silicone insulating layer was characterized by scanning electron microscopy and energy dispersive X-ray spectroscopy. Silicone uniformly coated the powder surface, resulting in a reduction of the imaginary part of the permeability, thereby increasing the electrical resistivity and the operating frequency of the synthesized magnets. The annealing treatment increased the initial permeability, the maximum permeability, and the magnetic induction, and decreased the coercivity. Annealing at 580 °C increased the maximum permeability by 72.5%. The result of annealing at 580 °C shows that the ferromagnetic resonance frequency increased from 2 kHz for conventional epoxy resin coated samples to 80 kHz for the silicone resin insulated composites. - Highlights: ► Silicone uniformly coated the powder, increased the operating frequency of SMCs. ► The annealing treatment increased the DC properties of SMCs. ► Annealing at 580 °C increased the maximum permeability by 72.5%. ► Compared with epoxy coated, the SMCs had higher resistivity annealing at 580 °C.

  12. Computer Animation Based on Particle Methods

    Directory of Open Access Journals (Sweden)

    Rafal Wcislo

    1999-01-01

    Full Text Available The paper presents the main issues of a computer animation of a set of elastic macroscopic objects based on the particle method. The main assumption of the generated animations is to achieve very realistic movements in a scene observed on the computer display. The objects (solid bodies interact mechanically with each other, The movements and deformations of solids are calculated using the particle method. Phenomena connected with the behaviour of solids in the gravitational field, their defomtations caused by collisions and interactions with the optional liquid medium are simulated. The simulation ofthe liquid is performed using the cellular automata method. The paper presents both simulation schemes (particle method and cellular automata rules an the method of combining them in the single animation program. ln order to speed up the execution of the program the parallel version based on the network of workstation was developed. The paper describes the methods of the parallelization and it considers problems of load-balancing, collision detection, process synchronization and distributed control of the animation.

  13. Hardware Implementation of A Non-RLL Soft-decoding Beacon-based Visible Light Communication Receiver

    OpenAIRE

    Nguyen, Duc-Phuc; Le, Dinh-Dung; Tran, Thi-Hong; Huynh, Huu-Thuan; Nakashima, Yasuhiko

    2018-01-01

    Visible light communication (VLC)-based beacon systems, which usually transmit identification (ID) information in small-size data frames are applied widely in indoor localization applications. There is one fact that flicker of LED light should be avoid in any VLC systems. Current flicker mitigation solutions based on run-length limited (RLL) codes suffer from reduced code rates, or are limited to hard-decoding forward error correction (FEC) decoders. Recently, soft-decoding techniques of RLL-...

  14. GPU-based acceleration of computations in nonlinear finite element deformation analysis.

    Science.gov (United States)

    Mafi, Ramin; Sirouspour, Shahin

    2014-03-01

    The physics of deformation for biological soft-tissue is best described by nonlinear continuum mechanics-based models, which then can be discretized by the FEM for a numerical solution. However, computational complexity of such models have limited their use in applications requiring real-time or fast response. In this work, we propose a graphic processing unit-based implementation of the FEM using implicit time integration for dynamic nonlinear deformation analysis. This is the most general formulation of the deformation analysis. It is valid for large deformations and strains and can account for material nonlinearities. The data-parallel nature and the intense arithmetic computations of nonlinear FEM equations make it particularly suitable for implementation on a parallel computing platform such as graphic processing unit. In this work, we present and compare two different designs based on the matrix-free and conventional preconditioned conjugate gradients algorithms for solving the FEM equations arising in deformation analysis. The speedup achieved with the proposed parallel implementations of the algorithms will be instrumental in the development of advanced surgical simulators and medical image registration methods involving soft-tissue deformation. Copyright © 2013 John Wiley & Sons, Ltd.

  15. Necrotizing Soft Tissue Infection

    Directory of Open Access Journals (Sweden)

    Sahil Aggarwal, BS

    2018-04-01

    Full Text Available History of present illness: A 71-year-old woman with a history of metastatic ovarian cancer presented with sudden onset, rapidly progressing painful rash in the genital region and lower abdominal wall. She was febrile to 103°F, heart rate was 114 beats per minute, and respiratory rate was 24 per minute. Her exam was notable for a toxic-appearing female with extensive areas of erythema, tenderness, and induration to her lower abdomen, intertriginous areas, and perineum with intermittent segments of crepitus without hemorrhagic bullae or skin breakdown. Significant findings: Computed tomography (CT of the abdominal and pelvis with intravenous (IV contrast revealed inflammatory changes, including gas and fluid collections within the ventral abdominal wall extending to the vulva, consistent with a necrotizing soft tissue infection. Discussion: Necrotizing fasciitis is a serious infection of the skin and soft tissues that requires an early diagnosis to reduce morbidity and mortality. Classified into several subtypes based on the type of microbial infection, necrotizing fasciitis can rapidly progress to septic shock or death if left untreated.1 Diagnosing necrotizing fasciitis requires a high index of suspicion based on patient risk factors, presentation, and exam findings. Definitive treatment involves prompt surgical exploration and debridement coupled with IV antibiotics.2,3 Clinical characteristics such as swelling, disproportionate pain, erythema, crepitus, and necrotic tissue should be a guide to further diagnostic tests.4 Unfortunately, lab values such as white blood cell count and lactate imaging studies have high sensitivity but low specificity, making the diagnosis of necrotizing fasciitis still largely a clinical one.4,5 CT is a reliable method to exclude the diagnosis of necrotizing soft tissue infections (sensitivity of 100%, but is only moderately reliable in correctly identifying such infections (specificity of 81%.5 Given the emergent

  16. A Smoothed Finite Element-Based Elasticity Model for Soft Bodies

    Directory of Open Access Journals (Sweden)

    Juan Zhang

    2017-01-01

    Full Text Available One of the major challenges in mesh-based deformation simulation in computer graphics is to deal with mesh distortion. In this paper, we present a novel mesh-insensitive and softer method for simulating deformable solid bodies under the assumptions of linear elastic mechanics. A face-based strain smoothing method is adopted to alleviate mesh distortion instead of the traditional spatial adaptive smoothing method. Then, we propose a way to combine the strain smoothing method and the corotational method. With this approach, the amplitude and frequency of transient displacements are slightly affected by the distorted mesh. Realistic simulation results are generated under large rotation using a linear elasticity model without adding significant complexity or computational cost to the standard corotational FEM. Meanwhile, softening effect is a by-product of our method.

  17. Construction of a multi-vender fieldbus system for PC-based control using soft PLC

    Energy Technology Data Exchange (ETDEWEB)

    Park, J. H.; Park, Y. J.; Choi, J. M.; Park, J. S. [Hankyong National Univ., Ansung (Korea)

    2000-12-01

    The relationship between the IEC 61131-3 programming language and the fieldbus application that became necessary as an outcome of the recent automation technology was described.An educational text for the field users on the integration of the Input/Output (I/O) modules and on the IEC 61131-3 programming language was prepared. An attempt was made to include description of the various kind of the fieldbuses and promote understanding of the CAN and the AS-I bus using a practical approach. The profibus is most widely used in the world, and thus is an important and a standardized tool in the area of the process control. A method of integrating the profibus with the most commonly used I/O modules in the field was suggested. The most essential characteristics of the IEC 61131-3 programming language was also described. A method for the construction of the multi-vender I/O modules by the Soft PLC 4C of the softings was suggested. Various technical steps are necessary for the integration of the I/O modules by the soft PLC. An additional software is needed for the more intelligent devises possessing complex technical functions, such as the control valve, the AC driver among others. The 4C control by the softing which is an important industrial solution for the soft PLC was specifically designed for the profibus. So, an OPC server is needed to exchange between the other fieldbuses while the optimum performance is only achieved by using the profibus card by softing. This implies that the business aspect has played a major role for developing the profibus by softing and the domestic users need to pay careful attention to this point additional software tools, such as the PDM or the comuwinn II, are necessary in the process control area to operate a complex and instruments using the DP/PA segment coupler. 13 refs., 46 figs., 12 tabs. (Author)

  18. A soft biomolecule actuator based on a highly functionalized bacterial cellulose nano-fiber network with carboxylic acid groups.

    Science.gov (United States)

    Wang, Fan; Jeon, Jin-Han; Park, Sukho; Kee, Chang-Doo; Kim, Seong-Jun; Oh, Il-Kwon

    2016-01-07

    Upcoming human-related applications such as soft wearable electronics, flexible haptic systems, and active bio-medical devices will require bio-friendly actuating materials. Here, we report a soft biomolecule actuator based on carboxylated bacterial cellulose (CBC), ionic liquid (IL), and poly (3,4-ethylenedioxythiophene)-poly(styrenesulfonate) ( PSS) electrodes. Soft and biocompatible polymer-IL composites were prepared via doping of CBC with ILs. The highly conductive PSS layers were deposited on both sides of the CBC-IL membranes by a dip-coating technique to yield a sandwiched actuator system. Ionic conductivity and ionic exchange capacity of the CBC membrane can be increased up to 22.8 times and 1.5 times compared with pristine bacterial cellulose (BC), respectively, resulting in 8 times large bending deformation than the pure BC actuators with metallic electrodes in an open air environment. The developed CBC-IL actuators show significant progress in the development of biocompatible and soft actuating materials with quick response, low operating voltage and comparatively large bending deformation.

  19. Soft tissue deformation for surgical simulation: a position-based dynamics approach.

    Science.gov (United States)

    Camara, Mafalda; Mayer, Erik; Darzi, Ara; Pratt, Philip

    2016-06-01

    To assist the rehearsal and planning of robot-assisted partial nephrectomy, a real-time simulation platform is presented that allows surgeons to visualise and interact with rapidly constructed patient-specific biomechanical models of the anatomical regions of interest. Coupled to a framework for volumetric deformation, the platform furthermore simulates intracorporeal 2D ultrasound image acquisition, using preoperative imaging as the data source. This not only facilitates the planning of optimal transducer trajectories and viewpoints, but can also act as a validation context for manually operated freehand 3D acquisitions and reconstructions. The simulation platform was implemented within the GPU-accelerated NVIDIA FleX position-based dynamics framework. In order to validate the model and determine material properties and other simulation parameter values, a porcine kidney with embedded fiducial beads was CT-scanned and segmented. Acquisitions for the rest position and three different levels of probe-induced deformation were collected. Optimal values of the cluster stiffness coefficients were determined for a range of different particle radii, where the objective function comprised the mean distance error between real and simulated fiducial positions over the sequence of deformations. The mean fiducial error at each deformation stage was found to be compatible with the level of ultrasound probe calibration error typically observed in clinical practice. Furthermore, the simulation exhibited unconditional stability on account of its use of clustered shape-matching constraints. A novel position-based dynamics implementation of soft tissue deformation has been shown to facilitate several desirable simulation characteristics: real-time performance, unconditional stability, rapid model construction enabling patient-specific behaviour and accuracy with respect to reference CT images.

  20. Methods to quantify soft-tissue based facial growth and treatment outcomes in children: a systematic review.

    Directory of Open Access Journals (Sweden)

    Sander Brons

    Full Text Available CONTEXT: Technological advancements have led craniofacial researchers and clinicians into the era of three-dimensional digital imaging for quantitative evaluation of craniofacial growth and treatment outcomes. OBJECTIVE: To give an overview of soft-tissue based methods for quantitative longitudinal assessment of facial dimensions in children until six years of age and to assess the reliability of these methods in studies with good methodological quality. DATA SOURCE: PubMed, EMBASE, Cochrane Library, Web of Science, Scopus and CINAHL were searched. A hand search was performed to check for additional relevant studies. STUDY SELECTION: Primary publications on facial growth and treatment outcomes in children younger than six years of age were included. DATA EXTRACTION: Independent data extraction by two observers. A quality assessment instrument was used to determine the methodological quality. Methods, used in studies with good methodological quality, were assessed for reliability expressed as the magnitude of the measurement error and the correlation coefficient between repeated measurements. RESULTS: In total, 47 studies were included describing 4 methods: 2D x-ray cephalometry; 2D photography; anthropometry; 3D imaging techniques (surface laser scanning, stereophotogrammetry and cone beam computed tomography. In general the measurement error was below 1 mm and 1° and correlation coefficients range from 0.65 to 1.0. CONCLUSION: Various methods have shown to be reliable. However, at present stereophotogrammetry seems to be the best 3D method for quantitative longitudinal assessment of facial dimensions in children until six years of age due to its millisecond fast image capture, archival capabilities, high resolution and no exposure to ionizing radiation.

  1. COMPUTER-BASED REASONING SYSTEMS: AN OVERVIEW

    Directory of Open Access Journals (Sweden)

    CIPRIAN CUCU

    2012-12-01

    Full Text Available Argumentation is nowadays seen both as skill that people use in various aspects of their lives, as well as an educational technique that can support the transfer or creation of knowledge thus aiding in the development of other skills (e.g. Communication, critical thinking or attitudes. However, teaching argumentation and teaching with argumentation is still a rare practice, mostly due to the lack of available resources such as time or expert human tutors that are specialized in argumentation. Intelligent Computer Systems (i.e. Systems that implement an inner representation of particular knowledge and try to emulate the behavior of humans could allow more people to understand the purpose, techniques and benefits of argumentation. The proposed paper investigates the state of the art concepts of computer-based argumentation used in education and tries to develop a conceptual map, showing benefits, limitation and relations between various concepts focusing on the duality “learning to argue – arguing to learn”.

  2. A soft sensor for bioprocess control based on sequential filtering of metabolic heat signals.

    Science.gov (United States)

    Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

    2014-09-26

    Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

  3. A Soft Sensor for Bioprocess Control Based on Sequential Filtering of Metabolic Heat Signals

    Directory of Open Access Journals (Sweden)

    Dan Paulsson

    2014-09-01

    Full Text Available Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

  4. Holiday fun with soft gluons

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Emissions of soft gluons from energetic particles play an important role in collider processes. While the basic physics of soft emissions is simple, it gives rise to a variety of interesting and intricate phenomena (non-global logs, Glauber phases, super-leading logs, factorization breaking). After an introduction, I will review progress in resummation methods such as Soft-Collinear Effective Theory driven by a better understanding of soft emissions. I will also show some new results for computations of soft-gluon effects in gap-between-jets and isolation-cone cross sections.

  5. DNA microsatellite region for a reliable quantification of soft wheat adulteration in durum wheat-based foodstuffs by real-time PCR.

    Science.gov (United States)

    Sonnante, Gabriella; Montemurro, Cinzia; Morgese, Anita; Sabetta, Wilma; Blanco, Antonio; Pasqualone, Antonella

    2009-11-11

    Italian industrial pasta and durum wheat typical breads must be prepared using exclusively durum wheat semolina. Previously, a microsatellite sequence specific of the wheat D-genome had been chosen for traceability of soft wheat in semolina and bread samples, using qualitative and quantitative Sybr green-based real-time experiments. In this work, we describe an improved method based on the same soft wheat genomic region by means of a quantitative real-time PCR using a dual-labeled probe. Standard curves based on dilutions of 100% soft wheat flour, pasta, or bread were constructed. Durum wheat semolina, pasta, and bread samples were prepared with increasing amounts of soft wheat to verify the accuracy of the method. Results show that reliable quantifications were obtained especially for the samples containing a lower amount of soft wheat DNA, fulfilling the need to verify labeling of pasta and typical durum wheat breads.

  6. Computer-based training at Sellafield

    International Nuclear Information System (INIS)

    Cartmell, A.; Evans, M.C.

    1986-01-01

    British Nuclear Fuel Limited (BNFL) operate the United Kingdom's spent-fuel receipt, storage, and reprocessing complex at Sellafield. Spent fuel from graphite-moderated CO 2 -cooled Magnox reactors has been reprocessed at Sellafield for 22 yr. Spent fuel from light water and advanced gas reactors is stored pending reprocessing in the Thermal Oxide Reprocessing Plant currently being constructed. The range of knowledge and skills needed for plant operation, construction, and commissioning represents a formidable training requirement. In addition, employees need to be acquainted with company practices and procedures. Computer-based training (CBT) is expected to play a significant role in this process. In this paper, current applications of CBT to the filed of nuclear criticality safety are described and plans for the immediate future are outlined

  7. Computer based training for oil spill management

    International Nuclear Information System (INIS)

    Goodman, R.

    1993-01-01

    Large oil spills are infrequent occurrences, which poses a particular problem for training oil spill response staff and for maintaining a high level of response readiness. Conventional training methods involve table-top simulations to develop tactical and strategic response skills and boom-deployment exercises to maintain operational readiness. Both forms of training are quite effective, but they are very time-consuming to organize, are expensive to conduct, and tend to become repetitious. To provide a variety of response experiences, a computer-based system of oil spill response training has been developed which can supplement a table-top training program. Using a graphic interface, a realistic and challenging computerized oil spill response simulation has been produced. Integral to the system is a program editing tool which allows the teacher to develop a custom training exercise for the area of interest to the student. 1 ref

  8. CVD diamond based soft X-ray detector with fast response

    International Nuclear Information System (INIS)

    Li Fang; Hou Lifei; Su Chunxiao; Yang Guohong; Liu Shenye

    2010-01-01

    A soft X-ray detector has been made with high quality chemical vapor deposited (CVD) diamond and the electrical structure of micro-strip. Through the measurement of response time on a laser with the pulse width of 10 ps, the full width at half maximum of the data got in the oscilloscope was 115 ps. The rise time of the CVD diamond detector was calculated to be 49 ps. In the experiment on the laser prototype facility, the signal got by the CVD diamond detector was compared with that got by a soft X-ray spectrometer. Both signals coincided well. The detector is proved to be a kind of reliable soft X-ray detector with fast response and high signal-to-noise ratio. (authors)

  9. A High Performance COTS Based Computer Architecture

    Science.gov (United States)

    Patte, Mathieu; Grimoldi, Raoul; Trautner, Roland

    2014-08-01

    Using Commercial Off The Shelf (COTS) electronic components for space applications is a long standing idea. Indeed the difference in processing performance and energy efficiency between radiation hardened components and COTS components is so important that COTS components are very attractive for use in mass and power constrained systems. However using COTS components in space is not straightforward as one must account with the effects of the space environment on the COTS components behavior. In the frame of the ESA funded activity called High Performance COTS Based Computer, Airbus Defense and Space and its subcontractor OHB CGS have developed and prototyped a versatile COTS based architecture for high performance processing. The rest of the paper is organized as follows: in a first section we will start by recapitulating the interests and constraints of using COTS components for space applications; then we will briefly describe existing fault mitigation architectures and present our solution for fault mitigation based on a component called the SmartIO; in the last part of the paper we will describe the prototyping activities executed during the HiP CBC project.

  10. Low-voltage, large-strain soft electrothermal actuators based on laser-reduced graphene oxide/Ag particle composites

    Science.gov (United States)

    Wang, Qian; Li, Yu-Tao; Zhang, Tian-Yu; Wang, Dan-Yang; Tian, Ye; Yan, Jun-Chao; Tian, He; Yang, Yi; Yang, Fan; Ren, Tian-Ling

    2018-03-01

    In this paper, low-voltage, large-strain flexible electrothermal actuators (ETAs) based on laser-reduced graphene oxide (LRGO)/Ag particle composites were fabricated in a simple and cost-efficient process. By adding Ag particles to the LRGO, the sheet resistance decreased effectively. Under a driving voltage of 28 V, the actuator obtained a bending angle of 192° within 6 s. Besides, the bending deformation could be precisely controlled by the driving voltage ranging from 10° to 192°. Finally, a gripper composed of two actuators was demonstrated to manipulate a piece of polydimethylsiloxane block. With the advantages of low-voltage, fast-response, and easy-to-manufacture, the graphene based ETAs have a promising application in soft robotics and soft machines.

  11. The Research about Embedded Soft PLC Running System Based on ARM

    Directory of Open Access Journals (Sweden)

    Fang Ding

    2014-09-01

    Full Text Available The paper discusses the overall construction and operational principle of soft PLC. Considering the real time request of the system, we use Linux+RTAI dual core system as software platform. In this platform, the implementation method of soft PLC operational system is introduced. Especially, the design of instruction analysis module is emphasized. On the basis of energy flow concept, the logic algorithm is established, aligning to the left bus. Finally, the system is tested to evaluate the desired control behavior.

  12. Determination of the electromagnetic character of soft dipole modes solely based on quasicontinuous γ spectroscopy

    International Nuclear Information System (INIS)

    Voinov, A.; Schiller, A.; Guttormsen, M.; Rekstad, J.; Siem, S.

    2003-01-01

    We show that the combined analysis of quasicontinuous γ spectra from the ( 3 He,α) and (n th ,2γ) reactions gives the possibility to measure the electromagnetic character of soft dipole resonances. Two-step γ-cascade spectra have been calculated, using level densities and radiative strength functions from the ( 3 He,αγ) reaction. The calculations show that the intensity of the two-step cascades depends on the electromagnetic character of the soft dipole resonance under study. The difference reaches 40-100% which can be measured experimentally

  13. Computer Networks as a New Data Base.

    Science.gov (United States)

    Beals, Diane E.

    1992-01-01

    Discusses the use of communication on computer networks as a data source for psychological, social, and linguistic research. Differences between computer-mediated communication and face-to-face communication are described, the Beginning Teacher Computer Network is discussed, and examples of network conversations are appended. (28 references) (LRW)

  14. Quantum computing based on semiconductor nanowires

    NARCIS (Netherlands)

    Frolov, S.M.; Plissard, S.R.; Nadj-Perge, S.; Kouwenhoven, L.P.; Bakkers, E.P.A.M.

    2013-01-01

    A quantum computer will have computational power beyond that of conventional computers, which can be exploited for solving important and complex problems, such as predicting the conformations of large biological molecules. Materials play a major role in this emerging technology, as they can enable

  15. CSNS computing environment Based on OpenStack

    Science.gov (United States)

    Li, Yakang; Qi, Fazhi; Chen, Gang; Wang, Yanming; Hong, Jianshu

    2017-10-01

    Cloud computing can allow for more flexible configuration of IT resources and optimized hardware utilization, it also can provide computing service according to the real need. We are applying this computing mode to the China Spallation Neutron Source(CSNS) computing environment. So, firstly, CSNS experiment and its computing scenarios and requirements are introduced in this paper. Secondly, the design and practice of cloud computing platform based on OpenStack are mainly demonstrated from the aspects of cloud computing system framework, network, storage and so on. Thirdly, some improvments to openstack we made are discussed further. Finally, current status of CSNS cloud computing environment are summarized in the ending of this paper.

  16. Hyaluronic acid based hydrogel system for soft tissue regeneration and drug delivery

    Science.gov (United States)

    Jha, Amit Kumar

    the gels. Human MSCs were undifferentiated during the early time points of culture, however differentiated into osteoblast phenotype after 28 days of culture. In summary, the HA-based hydrogel matrices are hierarchically structured, mechanically robust and enzymatically stable, capable of mediating cellular functions through the spatial and temporal presentation of defined biological cues. These hydrogel systems are promising candidates for soft tissue regeneration.

  17. Tumor type resulting in upgrade: An analysis based on 333 low grade soft tissue sarcoma

    Directory of Open Access Journals (Sweden)

    Langer, Stefan

    2014-11-01

    Full Text Available [english] Introduction: Soft tissue sarcomas (STS are rare tumors. Based on histopathological criteria, three grades are distinguished from low (G1 to intermediate (G2 and high grade (G3. After complete initial surgical resection, some G1 STS recur as lesions with an upgrade of a previous G1 STS to a recurrent G2 STS. This upgrade indicates higher malignancy of the STS. Our aim was to find possible risk factors for these upgrades including age, localization of tumor and tumor type. Methods: This retrospective case-control study evaluated 333 patients. Of these 333, 54.7% were male and 45.3% female. All patients underwent R0 resections and among these, 10% subsequently upgraded. The processed data include age, gender, tumor type, tumor localization, local recurrence and upgrade. Results: Patients with upgrades have a higher mean age of 5.5 years than our reference collective. The tumor type has a significant effect on upgrades. Patients with fibrosarcomas are at a threefold risk of an upgrade compared to patients with other G1 STS.Conclusion: Our results indicate that age and tumor type play a key role in upgrades in G1 STS. Patients, age 60 and above and diagnosed with G1 fibrosarcomas, are three times as likely to upgrade compared to patients younger than 60 with other G1 STS. We discuss the significance of these risk factors and whether aside from complete tumor resection, additional therapies (e.g. irradiation may be applied to improve therapeutic outcome.

  18. Gemcitabine treatment of rat soft tissue sarcoma with phosphatidyldiglycerol-based thermosensitive liposomes.

    Science.gov (United States)

    Limmer, Simone; Hahn, Jasmin; Schmidt, Rebecca; Wachholz, Kirsten; Zengerle, Anja; Lechner, Katharina; Eibl, Hansjörg; Issels, Rolf D; Hossann, Martin; Lindner, Lars H

    2014-09-01

    The pyrimidine analogue gemcitabine (dFdC) is frequently used in the treatment of patients with solid tumors. However, after i.v. application dFdC is rapidly inactivated by metabolization. Here, the potential of thermosensitive liposomes based on 1,2-dipalmitoyl-sn-glycero-3-phosphodiglycerol (DPPG2-TSL) were investigated as carrier and targeting system for delivery of dFdC in combination with local hyperthermia (HT). DPPG2-TSL were prepared by the lipid film hydration and extrusion method and characterized by dynamic light scattering, thin layer chromatography, phosphate assay and HPLC. In vivo experiments were performed in Brown Norway rats with a syngeneic soft tissue sarcoma. Local HT treatment was performed by light exposure. DPPG2-TSL were stable at 37°C in serum and showed a temperature dependent dFdC release >40°C. Plasma half-life of dFdC was strongly increased from 0.07 h (non-liposomal) to 0.53 h (liposomal, vesicle size 105 nm) or 2.59 h (liposomal, 129 nm). Therapy of BN175 tumors with dFdC encapsulated in DPPG2-TSL + HT showed significant improvement in tumor growth delay compared to non-liposomal dFdC without HT (p < 0.05), non-liposomal dFdC with HT (p < 0.01), and liposomal dFdC without HT (p < 0.05), respectively. Gemcitabine encapsulated in DPPG2-TSL in combination with local HT is a promising tool for the treatment of solid tumors. Therefore, these encouraging results ask for further investigation and evaluation.

  19. An Applet-based Anonymous Distributed Computing System.

    Science.gov (United States)

    Finkel, David; Wills, Craig E.; Ciaraldi, Michael J.; Amorin, Kevin; Covati, Adam; Lee, Michael

    2001-01-01

    Defines anonymous distributed computing systems and focuses on the specifics of a Java, applet-based approach for large-scale, anonymous, distributed computing on the Internet. Explains the possibility of a large number of computers participating in a single computation and describes a test of the functionality of the system. (Author/LRW)

  20. Outcome and Toxicity of an Ifosfamide-Based Soft Tissue Sarcoma Treatment Protocol in Children. The Importance of Local Therapy

    Directory of Open Access Journals (Sweden)

    S. Murray Yule

    1998-01-01

    Full Text Available Background. Although the survival of children with soft tissue sarcoma (STS has improved considerably, the outcome of patients with metastatic disease, and those with primary tumours of the extremities or parameningeal sites remains disappointing. We describe the clinical outcome of an ifosfamide-based regimen with local therapy directed only to children who failed to achieve a complete response to initial chemotherapy.

  1. The Enhancement of Junior High School Students' Abilities in Mathematical Problem Solving Using Soft Skill-based Metacognitive Learning

    OpenAIRE

    Murni, Atma; Sabandar, Jozua; S. Kusumah, Yaya; Kartasamita, Bana Goerbana

    2013-01-01

    The aim of this study is to know the differences of enhancement in mathematical problem solving ability (MPSA) between the students who received soft skill- based metacognitive learning (SSML) with the students who got conventional learning (CL). This research is a quasi experimental design with pretest-postest control group. The population in this study is the students of Junior High School in Pekanbaru city. The sample consist of 135 students, 68 of them are from the high-level...

  2. Novel computer-based endoscopic camera

    Science.gov (United States)

    Rabinovitz, R.; Hai, N.; Abraham, Martin D.; Adler, Doron; Nissani, M.; Fridental, Ron; Vitsnudel, Ilia

    1995-05-01

    We have introduced a computer-based endoscopic camera which includes (a) unique real-time digital image processing to optimize image visualization by reducing over exposed glared areas and brightening dark areas, and by accentuating sharpness and fine structures, and (b) patient data documentation and management. The image processing is based on i Sight's iSP1000TM digital video processor chip and Adaptive SensitivityTM patented scheme for capturing and displaying images with wide dynamic range of light, taking into account local neighborhood image conditions and global image statistics. It provides the medical user with the ability to view images under difficult lighting conditions, without losing details `in the dark' or in completely saturated areas. The patient data documentation and management allows storage of images (approximately 1 MB per image for a full 24 bit color image) to any storage device installed into the camera, or to an external host media via network. The patient data which is included with every image described essential information on the patient and procedure. The operator can assign custom data descriptors, and can search for the stored image/data by typing any image descriptor. The camera optics has extended zoom range of f equals 20 - 45 mm allowing control of the diameter of the field which is displayed on the monitor such that the complete field of view of the endoscope can be displayed on all the area of the screen. All these features provide versatile endoscopic camera with excellent image quality and documentation capabilities.

  3. Using a micro computer based test bank

    International Nuclear Information System (INIS)

    Hamel, R.T.

    1987-01-01

    Utilizing a micro computer based test bank offers a training department many advantages and can have a positive impact upon training procedures and examination standards. Prior to data entry, Training Department management must pre-review the examination questions and answers to ensure compliance with examination standards and to verify the validity of all questions. Management must adhere to the TSD format since all questions require an enabling objective numbering scheme. Each question is entered under the enabling objective upon which it is based. Then the question is selected via the enabling objective. This eliminates any instructor bias because a random number generator chooses the test question. However, the instructor may load specific questions to create an emphasis theme for any test. The examination, answer and cover sheets are produced and printed within minutes. The test bank eliminates the large amount of time that is normally required for an instructor to formulate an examination. The need for clerical support is reduced by the elimination of typing examinations and also by the software's ability to maintain and generate student/course lists, attendance sheets, and grades. Software security measures limit access to the test bank, and the impromptu method used to generate and print an examination enhance its security

  4. Microemulsion-Based Soft Bacteria-Driven Microswimmers for Active Cargo Delivery.

    Science.gov (United States)

    Singh, Ajay Vikram; Hosseinidoust, Zeinab; Park, Byung-Wook; Yasa, Oncay; Sitti, Metin

    2017-10-24

    Biohybrid cell-driven microsystems offer unparalleled possibilities for realization of soft microrobots at the micron scale. Here, we introduce a bacteria-driven microswimmer that combines the active locomotion and sensing capabilities of bacteria with the desirable encapsulation and viscoelastic properties of a soft double-micelle microemulsion for active transport and delivery of cargo (e.g., imaging agents, genes, and drugs) to living cells. Quasi-monodisperse double emulsions were synthesized with an aqueous core that encapsulated the fluorescence imaging agents, as a proof-of-concept cargo in this study, and an outer oil shell that was functionalized with streptavidin for specific and stable attachment of biotin-conjugated Escherichia coli. Motile bacteria effectively propelled the soft microswimmers across a Transwell membrane, actively delivering imaging agents (i.e., dyes) encapsulated inside of the micelles to a monolayer of cultured MCF7 breast cancer and J744A.1 macrophage cells, which enabled real-time, live-cell imaging of cell organelles, namely mitochondria, endoplasmic reticulum, and Golgi body. This in vitro model demonstrates the proof-of-concept feasibility of the proposed soft microswimmers and offers promise for potential biomedical applications in active and/or targeted transport and delivery of imaging agents, drugs, stem cells, siRNA, and therapeutic genes to live tissue in in vitro disease models (e.g., organ-on-a-chip devices) and stagnant or low-flow-velocity fluidic regions of the human body.

  5. Soft but Powerful Artificial Muscles Based on 3D Graphene-CNT-Ni Heteronanostructures.

    Science.gov (United States)

    Kim, Jaehwan; Bae, Seok-Hu; Kotal, Moumita; Stalbaum, Tyler; Kim, Kwang J; Oh, Il-Kwon

    2017-08-01

    Bioinspired soft ionic actuators, which exhibit large strain and high durability under low input voltages, are regarded as prospective candidates for future soft electronics. However, due to the intrinsic drawback of weak blocking force, the feasible applications of soft ionic actuators are limited until now. An electroactive artificial muscle electro-chemomechanically reinforced with 3D graphene-carbon nanotube-nickel heteronanostructures (G-CNT-Ni) to improve blocking force and bending deformation of the ionic actuators is demonstrated. The G-CNT-Ni heteronanostructure, which provides an electrically conductive 3D network and sufficient contact area with mobile ions in the polymer electrolyte, is embedded as a nanofiller in both ionic polymer and conductive electrodes of the ionic actuators. An ionic exchangeable composite membrane consisting of Nafion, G-CNT-Ni and ionic liquid (IL) shows improved tensile modulus and strength of up to 166% and 98%, respectively, and increased ionic conductivity of 0.254 S m -1 . The ionic actuator exhibits enhanced actuation performances including three times larger bending deformation, 2.37 times higher blocking force, and 4 h durability. The electroactive artificial muscle electro-chemomechanically reinforced with 3D G-CNT-Ni heteronanostructures offers improvements over current soft ionic actuator technologies and can advance the practical engineering applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. A bayesian nework based risk model for volume loss in soft soils in mechanized bored tunnels

    NARCIS (Netherlands)

    Chivatá Cárdenas, Ibsen; Al-Jibouri, Saad H.S.; Halman, Johannes I.M.

    2012-01-01

    Volume loss is one of the most important risks when boring a tunnel. This is particularly true when a tunnel is being constructed in soft soils. The risk of excessive volume loss, if materialised can lead to large consequences such as damage in buildings on the surface. This paper describes the

  7. Perception-Based Tactile Soft Keyboard for the Touchscreen of Tablets

    Directory of Open Access Journals (Sweden)

    Kwangtaek Kim

    2018-01-01

    Full Text Available Most mobile devices equipped with touchscreens provide on-screen soft keyboard as an input method. However, many users are experiencing discomfort due to lack of physical feedback that causes slow typing speed and error-prone typing, as compared to the physical keyboard. To solve the problem, a platform-independent haptic soft keyboard suitable for tablet-sized touchscreens was proposed and developed. The platform-independent haptic soft keyboard was verified on both Android and Windows. In addition, a psychophysical experiment has been conducted to find an optimal strength of key click feedback on touchscreens, and the perception result was applied for making uniform tactile forces on touchscreens. The developed haptic soft keyboard can be easily integrated with existing tablets by putting the least amount of effort. The evaluation results confirm platform independency, fast tactile key click feedback, and uniform tactile force distribution on touchscreen with using only two piezoelectric actuators. The proposed system was developed on a commercial tablet (Mu Pad that has dual platforms (Android and Windows.

  8. Electrokinetics of diffuse soft interfaces. 2. Analysis based on the nonlinear Poisson-Boltzmann equation

    NARCIS (Netherlands)

    Duval, J.F.L.

    2005-01-01

    In a previous study (Langmuir 2004, 20, 10324), the electrokinetic properties of diffuse soft layers were theoretically investigated within the framework of the Debye-H¿ckel approximation valid in the limit of sufficiently low values for the Donnan potential. In the current paper, the

  9. Structural Changes in Deformed Soft Magnetic Ni-Based Metallic Glass

    NARCIS (Netherlands)

    Jurikova, A.; Csach, K.; Miskuf, J.; Ocelik, V.

    The effects of intensive plastic deformation of the soft magnetic metallic glass Ni Si 13 on the structural relaxation were examined. The enthalpy changes studied by differential scanning calorimetry revealed that the intensive plastic deformation was associated with the partial structural

  10. Improving Students Soft Skills Using Thinking Process Profile Based on Personality Types

    Science.gov (United States)

    Sunarto, M. J. Dewiyani

    2015-01-01

    The challenge in education field these days rises as the cause of society's expectation for higher education. This increasingly complex expectation demands that higher education prepares the students to gain integrity. Higher education provides not only hard skills for the student, but also soft skills. By observing the hard skills side, in the…

  11. Evaluation of effectiveness of class-based nutrition intervention on changes in soft drink and milk consumption among young adults.

    Science.gov (United States)

    Ha, Eun-Jeong; Caine-Bish, Natalie; Holloman, Christopher; Lowry-Gordon, Karen

    2009-10-26

    During last few decades, soft drink consumption has steadily increased while milk intake has decreased. Excess consumption of soft drinks and low milk intake may pose risks of several diseases such as dental caries, obesity, and osteoporosis. Although beverage consumption habits form during young adulthood, which has a strong impact on beverage choices in later life, nutrition education programs on beverages are scarce in this population. The purpose of this investigation was 1) to assess soft drink and milk consumption and 2) to evaluate the effectiveness of 15-week class-based nutrition intervention in changing beverage choices among college students. A total of 80 college students aged 18 to 24 years who were enrolled in basic nutrition class participated in the study. Three-day dietary records were collected, verified, and analyzed before and after the intervention. Class lectures focused on healthful dietary choices related to prevention of chronic diseases and were combined with interactive hands on activities and dietary feedback. Class-based nutrition intervention combining traditional lecture and interactive activities was successful in decreasing soft drink consumption. Total milk consumption, specifically fat free milk, increased in females and male students changed milk choice favoring skim milk over low fat milk. (1% and 2%). Class-based nutrition education focusing on prevention of chronic diseases can be an effective strategy in improving both male and female college students' beverage choices. Using this type of intervention in a general nutrition course may be an effective approach to motivate changes in eating behaviors in a college setting.

  12. Evaluation of effectiveness of class-based nutrition intervention on changes in soft drink and milk consumption among young adults

    Directory of Open Access Journals (Sweden)

    Holloman Christopher

    2009-10-01

    Full Text Available Abstract Background During last few decades, soft drink consumption has steadily increased while milk intake has decreased. Excess consumption of soft drinks and low milk intake may pose risks of several diseases such as dental caries, obesity, and osteoporosis. Although beverage consumption habits form during young adulthood, which has a strong impact on beverage choices in later life, nutrition education programs on beverages are scarce in this population. The purpose of this investigation was 1 to assess soft drink and milk consumption and 2 to evaluate the effectiveness of 15-week class-based nutrition intervention in changing beverage choices among college students. Methods A total of 80 college students aged 18 to 24 years who were enrolled in basic nutrition class participated in the study. Three-day dietary records were collected, verified, and analyzed before and after the intervention. Class lectures focused on healthful dietary choices related to prevention of chronic diseases and were combined with interactive hands on activities and dietary feedback. Results Class-based nutrition intervention combining traditional lecture and interactive activities was successful in decreasing soft drink consumption. Total milk consumption, specifically fat free milk, increased in females and male students changed milk choice favoring skim milk over low fat milk. (1% and 2%. Conclusion Class-based nutrition education focusing on prevention of chronic diseases can be an effective strategy in improving both male and female college students' beverage choices. Using this type of intervention in a general nutrition course may be an effective approach to motivate changes in eating behaviors in a college setting.

  13. Pervasive Computing Support for Hospitals: An Overview of the Activity-Based Computing Project

    DEFF Research Database (Denmark)

    Christensen, Henrik Bærbak; Bardram, Jakob E

    2007-01-01

    The activity-based computing project researched pervasive computing support for clinical hospital work. Such technologies have potential for supporting the mobile, collaborative, and disruptive use of heterogeneous embedded devices in a hospital......The activity-based computing project researched pervasive computing support for clinical hospital work. Such technologies have potential for supporting the mobile, collaborative, and disruptive use of heterogeneous embedded devices in a hospital...

  14. Soft X-ray imaging of thick carbon-based materials using the normal incidence multilayer optics.

    Science.gov (United States)

    Artyukov, I A; Feschenko, R M; Vinogradov, A V; Bugayev, Ye A; Devizenko, O Y; Kondratenko, V V; Kasyanov, Yu S; Hatano, T; Yamamoto, M; Saveliev, S V

    2010-10-01

    The high transparency of carbon-containing materials in the spectral region of "carbon window" (lambda approximately 4.5-5nm) introduces new opportunities for various soft X-ray microscopy applications. The development of efficient multilayer coated X-ray optics operating at the wavelengths of about 4.5nm has stimulated a series of our imaging experiments to study thick biological and synthetic objects. Our experimental set-up consisted of a laser plasma X-ray source generated with the 2nd harmonics of Nd-glass laser, scandium-based thin-film filters, Co/C multilayer mirror and X-ray film UF-4. All soft X-ray images were produced with a single nanosecond exposure and demonstrated appropriate absorption contrast and detector-limited spatial resolution. A special attention was paid to the 3D imaging of thick low-density foam materials to be used in design of laser fusion targets.

  15. Soft leptogenesis

    International Nuclear Information System (INIS)

    D'Ambrosio, Giancarlo; Giudice, Gian F.; Raidal, Martti

    2003-01-01

    We study 'soft leptogenesis', a new mechanism of leptogenesis which does not require flavour mixing among the right-handed neutrinos. Supersymmetry soft-breaking terms give a small mass splitting between the CP-even and CP-odd right-handed sneutrino states of a single generation and provide a CP-violating phase sufficient to generate a lepton asymmetry. The mechanism is successful if the lepton-violating soft bilinear coupling is unconventionally (but not unnaturally) small. The values of the right-handed neutrino masses predicted by soft leptogenesis can be low enough to evade the cosmological gravitino problem

  16. Printing soft matter in three dimensions

    Science.gov (United States)

    Truby, Ryan L.; Lewis, Jennifer A.

    2016-12-01

    Light- and ink-based three-dimensional (3D) printing methods allow the rapid design and fabrication of materials without the need for expensive tooling, dies or lithographic masks. They have led to an era of manufacturing in which computers can control the fabrication of soft matter that has tunable mechanical, electrical and other functional properties. The expanding range of printable materials, coupled with the ability to programmably control their composition and architecture across various length scales, is driving innovation in myriad applications. This is illustrated by examples of biologically inspired composites, shape-morphing systems, soft sensors and robotics that only additive manufacturing can produce.

  17. Quantification and validation of soft tissue deformation

    DEFF Research Database (Denmark)

    Mosbech, Thomas Hammershaimb; Ersbøll, Bjarne Kjær; Christensen, Lars Bager

    2009-01-01

    We present a model for soft tissue deformation derived empirically from 10 pig carcases. The carcasses are subjected to deformation from a known single source of pressure located at the skin surface, and the deformation is quantified by means of steel markers injected into the tissue. The steel...... markers are easy to distinguish from the surrounding soft tissue in 3D computed tomography images. By tracking corresponding markers using methods from point-based registration, we are able to accurately quantify the magnitude and propagation of the induced deformation. The deformation is parameterised...

  18. Blind topological measurement-based quantum computation.

    Science.gov (United States)

    Morimae, Tomoyuki; Fujii, Keisuke

    2012-01-01

    Blind quantum computation is a novel secure quantum-computing protocol that enables Alice, who does not have sufficient quantum technology at her disposal, to delegate her quantum computation to Bob, who has a fully fledged quantum computer, in such a way that Bob cannot learn anything about Alice's input, output and algorithm. A recent proof-of-principle experiment demonstrating blind quantum computation in an optical system has raised new challenges regarding the scalability of blind quantum computation in realistic noisy conditions. Here we show that fault-tolerant blind quantum computation is possible in a topologically protected manner using the Raussendorf-Harrington-Goyal scheme. The error threshold of our scheme is 4.3 × 10(-3), which is comparable to that (7.5 × 10(-3)) of non-blind topological quantum computation. As the error per gate of the order 10(-3) was already achieved in some experimental systems, our result implies that secure cloud quantum computation is within reach.

  19. Computer-Based Cognitive Training in Aging.

    Science.gov (United States)

    Klimova, Blanka

    2016-01-01

    At present there is a rapid growth of aging population groups worldwide, which brings about serious economic and social problems. Thus, there is considerable effort to prolong the active life of these older people and keep them independent. The purpose of this mini review is to explore available clinical studies implementing computer-based cognitive training programs as intervention tools in the prevention and delay of cognitive decline in aging, with a special focus on their effectiveness. This was done by conducting a literature search in the databases Web of Science, Scopus, MEDLINE and Springer, and consequently by evaluating the findings of the relevant studies. The findings show that computerized cognitive training can lead to the improvement of cognitive functions such as working memory and reasoning skills in particular. However, this training should be performed over a longer time span since a short-term cognitive training mainly has an impact on short-term memory with temporary effects. In addition, the training must be intense to become effective. Furthermore, the results indicate that it is important to pay close attention to the methodological standards in future clinical studies.

  20. Computer Based Training Authors' and Designers' training

    Directory of Open Access Journals (Sweden)

    Frédéric GODET

    2016-03-01

    Full Text Available This communication, through couple of studies driven since 10 years, tries to show how important is the training of authors in Computer Based Training (CBT. We submit here an approach to prepare designers mastering Interactive Multimedia modules in this domain. Which institutions are really dedicating their efforts in training authors and designers in this area of CBTs? Television devices and broadcast organisations offered since year 60s' a first support for Distance Learning. New media, New Information and Communication Technologies (NICT allowed several public and private organisations to start Distance Learning projects. As usual some of them met their training objectives, other of them failed. Did their really failed? Currently, nobody has the right answer. Today, we do not have enough efficient tools allowing us to evaluate trainees' acquisition in a short term view. Training evaluation needs more than 10 to 20 years of elapsed time to bring reliable measures. Nevertheless, given the high investments already done in this area, we cannot wait until the final results of the pedagogical evaluation. A lot of analyses showed relevant issues which can be used as directions for CBTs authors and designers training. Warning - Our studies and the derived conclusions are mainly based on projects driven in the field. We additionally bring our several years experience in the training of movie film authors in the design of interactive multimedia products. Some of our examples are extracting from vocational training projects where we were involved in all development phases from the analysis of needs to the evaluation of the acquisition within the trainee's / employee job's. Obviously, we cannot bring and exhaustive approach in this domain where a lot of parameters are involved as frame for the CBT interactive multimedia modules authors' and designers' training.