Radiation protection in medicine. Actual regulations and the new EU BSS; Strahlenschutz in der Medizin. Aktuelle Regelungen und die neuen EU-BSS

Energy Technology Data Exchange (ETDEWEB)

Loose, R. [Klinikum Nuernberg-Nord, Nuernberg (Germany). Inst. fuer Diagnostische und Interventionelle Radiologie; Wucherer, M. [Klinikum Nuernberg, Nuernberg (Germany). Inst. fuer Medizinische Physik

2013-07-01

Medical radiation protection is based on the principles of justification, optimisation and dose limitation. Depending on the application, medical staff and patients are affected. The implementation of new basic safety standards (BSS) of the European Commission (EC) brings changes, which must be implemented into national law. They have varying effects depending on the type of application (radiology, nuclear medicine, radiation therapy) for all three principles of radiation protection. (orig.)

Influence of the initial guess spectrum in the unfolding of Bss data obtained inside a bunker of a PET cyclotron

Energy Technology Data Exchange (ETDEWEB)

Benavente C, J. A.; Lacerda, M. A. S.; Guimaraes, A. M.; Da Silva, T. A. [Universidade Federal de Minas Gerais, Departamento de Engenharia Nuclear, Programa de Pos-graduacao em Ciencias e Tecnicas Nucleares, Pte. Antonio Carlos 6627, Belo Horizonte 31270-901, Minas Gerais (Brazil); Vega C, H. R. [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98060 Zacatecas, Zac. (Mexico)

2015-10-15

In a cyclotron facility is strongly advised the use of spectrometry techniques to support workplace neutron dosimetry. Bonner sphere spectrometer (Bss) is the most used for radiation protection applications. Bss data must be unfolded to determine the spectral particle fluence. Some computer codes have been utilized for this purpose. These codes allow unfolding the spectrum from the Bss count rates through different algorithms. Some iterative routines need an initial guess spectrum to start the unfolding. The adequate choice of this initial spectrum is a critical part of the process and can affect the final solution. In this work, we evaluate the influence of the initial guess spectrum in the unfolding of Bss data obtained in four points inside the bunker of a PET cyclotron. The measurements were done utilizing a modified Bss system with thermoluminescent detectors (TLDs). Codes BUNKIUT and NSDUAZ were utilized to unfold the Bss data. For the NSDUAZ the starting spectrum is automatically obtained from a library initial guess spectra. For the BUNKIUT code were utilized two different initial guess spectra: (a) a Maxwellian spectrum with temperature of 1.4 MeV and shape factor of 0.1, created with the MAXIET algorithm and; (b) the spectra obtained through simulation with the MCNPX code version 2.7. Spectra obtained with both unfold codes and with the different initial guess spectra presented epithermal and thermal neutrons due to room-return effects. However, the contribution of the fast neutron to the total fluence were quite different for the different cases studied. These differences highlight the importance of an appropriate choice of an initial guess spectra for the quality of the results. (Author)

Influence of the initial guess spectrum in the unfolding of Bss data obtained inside a bunker of a PET cyclotron

International Nuclear Information System (INIS)

Benavente C, J. A.; Lacerda, M. A. S.; Guimaraes, A. M.; Da Silva, T. A.; Vega C, H. R.

2015-10-01

In a cyclotron facility is strongly advised the use of spectrometry techniques to support workplace neutron dosimetry. Bonner sphere spectrometer (Bss) is the most used for radiation protection applications. Bss data must be unfolded to determine the spectral particle fluence. Some computer codes have been utilized for this purpose. These codes allow unfolding the spectrum from the Bss count rates through different algorithms. Some iterative routines need an initial guess spectrum to start the unfolding. The adequate choice of this initial spectrum is a critical part of the process and can affect the final solution. In this work, we evaluate the influence of the initial guess spectrum in the unfolding of Bss data obtained in four points inside the bunker of a PET cyclotron. The measurements were done utilizing a modified Bss system with thermoluminescent detectors (TLDs). Codes BUNKIUT and NSDUAZ were utilized to unfold the Bss data. For the NSDUAZ the starting spectrum is automatically obtained from a library initial guess spectra. For the BUNKIUT code were utilized two different initial guess spectra: (a) a Maxwellian spectrum with temperature of 1.4 MeV and shape factor of 0.1, created with the MAXIET algorithm and; (b) the spectra obtained through simulation with the MCNPX code version 2.7. Spectra obtained with both unfold codes and with the different initial guess spectra presented epithermal and thermal neutrons due to room-return effects. However, the contribution of the fast neutron to the total fluence were quite different for the different cases studied. These differences highlight the importance of an appropriate choice of an initial guess spectra for the quality of the results. (Author)

Meeting the new BSS regulations: what are our strategies?

International Nuclear Information System (INIS)

Mohd Yusof Mohd Ali

2003-01-01

Industrial radiography is a widely known technique of non-destructive testing making use of penetrating ionizing radiation as a means of unfolding information of the subject being tested. It is an accepted practice recognized by industries worldwide. While taking advantage of penetrating nature of the radiation, it is a fact that the radiation can also be harmful to a radiographer and public if a radiation source used is not handled in a proper way and good working practice (GWP) is not observed. Such anticipated hazardous nature of the practice is confirmed by occupational exposure records of industrial radiographers kept by MINT SSDL for the last 15 years, which consistently show high annual dose received by these workers (2 to 43 times higher) as compared to workers involved in other practices. This is not a healthy trend especially in the light of new requirements of Basic Safety Standards (BSS) regulations recommended by IAEA and soon to be adopted by AELB, which allow for much stricter dose limits than before and introduction of new concepts and aspects of radiation protection. This paper highlights the situation of occupational exposure of industrial radiographers in Malaysia and a comparison is made with the experience of some of its counterparts in other countries. It also presents some pertinent points of the new BSS regulations that may cause serious implications to the industrial radiographic practices and some points to be considered as strategies to meet these new requirements. (Author)

Radiation protection in medicine. Actual regulations and the new EU BSS

International Nuclear Information System (INIS)

Loose, R.; Wucherer, M.

2013-01-01

Medical radiation protection is based on the principles of justification, optimisation and dose limitation. Depending on the application, medical staff and patients are affected. The implementation of new basic safety standards (BSS) of the European Commission (EC) brings changes, which must be implemented into national law. They have varying effects depending on the type of application (radiology, nuclear medicine, radiation therapy) for all three principles of radiation protection. (orig.)

Fast underdetermined BSS architecture design methodology for real time applications.

Science.gov (United States)

Mopuri, Suresh; Reddy, P Sreenivasa; Acharyya, Amit; Naik, Ganesh R

2015-01-01

In this paper, we propose a high speed architecture design methodology for the Under-determined Blind Source Separation (UBSS) algorithm using our recently proposed high speed Discrete Hilbert Transform (DHT) targeting real time applications. In UBSS algorithm, unlike the typical BSS, the number of sensors are less than the number of the sources, which is of more interest in the real time applications. The DHT architecture has been implemented based on sub matrix multiplication method to compute M point DHT, which uses N point architecture recursively and where M is an integer multiples of N. The DHT architecture and state of the art architecture are coded in VHDL for 16 bit word length and ASIC implementation is carried out using UMC 90 - nm technology @V DD = 1V and @ 1MHZ clock frequency. The proposed architecture implementation and experimental comparison results show that the DHT design is two times faster than state of the art architecture.

Design of Smart Ion-Selective Electrode Arrays Based on Source Separation through Nonlinear Independent Component Analysis

Directory of Open Access Journals (Sweden)

Duarte L.T.

2014-03-01

Full Text Available The development of chemical sensor arrays based on Blind Source Separation (BSS provides a promising solution to overcome the interference problem associated with Ion-Selective Electrodes (ISE. The main motivation behind this new approach is to ease the time-demanding calibration stage. While the first works on this problem only considered the case in which the ions under analysis have equal valences, the present work aims at developing a BSS technique that works when the ions have different charges. In this situation, the resulting mixing model belongs to a particular class of nonlinear systems that have never been studied in the BSS literature. In order to tackle this sort of mixing process, we adopted a recurrent network as separating system. Moreover, concerning the BSS learning strategy, we develop a mutual information minimization approach based on the notion of the differential of the mutual information. The method works requires a batch operation, and, thus, can be used to perform off-line analysis. The validity of our approach is supported by experiments where the mixing model parameters were extracted from actual data.

Practices in norm industries. Some remarks and questions on the implementation of the EU-BSS; Taetigkeiten in Norm-Industrien. Anmerkungen und Fragestellungen zur Umsetzung der EU-BSS

Energy Technology Data Exchange (ETDEWEB)

Flesch, K. [Saechsisches Landesamt fuer Umwelt, Landwirtschaft und Geologie, Dresden (Germany); Deutsch-Schweizerischer Fachverband fuer Strahlenschutz e.V., Juelich (Germany). Arbeitskreis ' ' Natuerliche Radioaktivitaet' ' (AKNAT)

2015-07-01

The expert group ''Natural radioactivity'' (AKNAT) of the ''German-Swiss Fachverband fuer Strahlenschutz e.V.'' (FS) has assessed the practicability of individual facts of provisions in the EU BSS (Council Directive 2013/59/Euratom) for protection against natural radiation sources with regard to its implementation into the laws and administrative provisions. Therefore the topics concerning NORM industries, radon, contaminated sites and commodities with NORM were identified to that the AKNAT commented from the technical point of view in preparation for implementing to a German radiation protection law. This presentation focuses on the topic of NORM industries. The AKNAT can provide its expert knowledge in practical radiation protection in terms of objections or suggestions for the implementation of the EU BSS into German radiation protection legislation. This relates to terminologies that are established or will be introduced, to the integration on the protection against natural radiation sources in the new concept of exposure situations and to the application on the principle of justification. This is as well connected to the modified methodology with the new concept of a 'graded approach' for NORM industries. Furthermore, some aspects will be discussed in connection with the new list of NORM industries, with the dose limits of occupational exposure as well as the dose limits for public exposure from all authorised practices.

Effect of Normothermic and Cold Eye Irrigation Solution (BSS and Viscoelastic Gel on the Consumption of Sedative Drugs in Phacoemulsification Cataract Surgery

Directory of Open Access Journals (Sweden)

Mojtaba Rahimi Varposhti

2017-11-01

Full Text Available Abstract Background: This study aimed to compare the effect of cold eye irrigation solution (BSS and viscoelastic gel with their combination in room temperature on the dosage of sedative drugs which we use in Phacoemulsification cataract surgery. Material and Methods: 190 patients scheduled for cataract surgery under sedation were randomly divided into two equal groups. During surgery, we used cold (4ºc and warm (room temperature BSS and viscoelastic gel in the first and second group respectively. For all patients, we started sedation with Midazolam and Fentanyl and in case that we needed additional drug, we used Sodium Thiopental till we reached desired sedation level. Ramsay sedation scores (before, during and after surgery and total sedative drug consumption were evaluated and compared between two groups and at the end of the surgery, we checked and recorded the satisfaction score of patients and surgeon about the quality of sedation. Results: The average dosage of Midazolam wasn’t significantly different between two groups, while the average dosage of Sodium Thiopental was significantly lower in cold group. Also, the average time on which we reached desired Ramsay sedation score and the level of Ramsay score were significantly different between two groups. Conclusion: Using cold BSS and viscoelastic gel in cataract surgery in comparison of their combination in room temperature will reduce the dosage of sedative drugs which we use during surgery and help us getting a more effective sedation and higher patient and surgeon satisfaction.

A Study of Learners PerceptIon and AttItude towards BA/BSS Program of SSHL of Bangladesh Open UnIversity

Directory of Open Access Journals (Sweden)

Sabiha SULTANA

2011-07-01

Full Text Available In the present day open and distance education has become a significant way of the development of higher education. Bangladesh Open University (BOU, the only public institution in Bangladesh offers several formal and non-formal programs from secondary to post graduate level through distance mode. The main objectives of BOU’s program is to provide flexible and need based education particularly to the rural and disadvantaged groups like woman, agricultural workers, unemployed youths, uneducated adults, on-the-job people etc. The School of Social Science, Humanities and Language (SSHL at the BOU offers Bachelor of Arts/Bachelor of Social Science (BA/BSS to create efficient and skilled manpower in the country. The focuses of this paper is to find out learners’ views and attitude towards BA/BSS program at BOU. In this study, 187 respondents were randomly selected from 15 tutorial centers of 2 Regional Resource centers (RRCs of BOU. The study showed that 62% learners were male and the mean age of the learners was 34.05 years (minimum 22; maximum 54. More than 50% learners were married and nearly half (47.6% of them were private employees and 86.6% were Muslims. Amongst them, 72.2% were come from urban areas and residing around 23.08 km from the tutorial centers. Most (72% of the learners of BA/BSS program stated that the program was as usual but 24.1% expressed that it was difficult to understand but 97.7% learners responded that text materials were up to the mark. Regarding the media programs, 61% of the learners gave their opinion that TV programs were at the level best but they wanted to watch these at the evening or night schedule. It was surprising that 26.2% of the learners had bitter experience with the services of RRCs. Finally, some measures have been proposed to offer effective and more popular educational program through BOU.

47 CFR 25.262 - Licensing and domestic coordination requirements for 17/24 GHz BSS space stations.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Licensing and domestic coordination requirements for 17/24 GHz BSS space stations. 25.262 Section 25.262 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Standards § 25.262...

47 CFR 25.224 - Protection of receive-only earth stations in the 17/24 GHz BSS.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Protection of receive-only earth stations in the 17/24 GHz BSS. 25.224 Section 25.224 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Standards § 25.224 Protection of...

Online Artifact Removal for Brain-Computer Interfaces Using Support Vector Machines and Blind Source Separation

Directory of Open Access Journals (Sweden)

Sebastian Halder

2007-01-01

that are designed for online usage. In order to select a suitable BSS/ICA method, three ICA algorithms (JADE, Infomax, and FastICA and one BSS algorithm (AMUSE are evaluated to determine their ability to isolate electromyographic (EMG and electrooculographic (EOG artifacts into individual components. An implementation of the selected BSS/ICA method with SVMs trained to classify EMG and EOG artifacts, which enables the usage of the method as a filter in measurements with online feedback, is described. This filter is evaluated on three BCI datasets as a proof-of-concept of the method.

Online artifact removal for brain-computer interfaces using support vector machines and blind source separation.

Science.gov (United States)

Halder, Sebastian; Bensch, Michael; Mellinger, Jürgen; Bogdan, Martin; Kübler, Andrea; Birbaumer, Niels; Rosenstiel, Wolfgang

2007-01-01

We propose a combination of blind source separation (BSS) and independent component analysis (ICA) (signal decomposition into artifacts and nonartifacts) with support vector machines (SVMs) (automatic classification) that are designed for online usage. In order to select a suitable BSS/ICA method, three ICA algorithms (JADE, Infomax, and FastICA) and one BSS algorithm (AMUSE) are evaluated to determine their ability to isolate electromyographic (EMG) and electrooculographic (EOG) artifacts into individual components. An implementation of the selected BSS/ICA method with SVMs trained to classify EMG and EOG artifacts, which enables the usage of the method as a filter in measurements with online feedback, is described. This filter is evaluated on three BCI datasets as a proof-of-concept of the method.

Feature Selection and Blind Source Separation in an EEG-Based Brain-Computer Interface

Directory of Open Access Journals (Sweden)

Michael H. Thaut

2005-11-01

Full Text Available Most EEG-based BCI systems make use of well-studied patterns of brain activity. However, those systems involve tasks that indirectly map to simple binary commands such as “yes” or “no” or require many weeks of biofeedback training. We hypothesized that signal processing and machine learning methods can be used to discriminate EEG in a direct “yes”/“no” BCI from a single session. Blind source separation (BSS and spectral transformations of the EEG produced a 180-dimensional feature space. We used a modified genetic algorithm (GA wrapped around a support vector machine (SVM classifier to search the space of feature subsets. The GA-based search found feature subsets that outperform full feature sets and random feature subsets. Also, BSS transformations of the EEG outperformed the original time series, particularly in conjunction with a subset search of both spaces. The results suggest that BSS and feature selection can be used to improve the performance of even a “direct,” single-session BCI.

47 CFR 25.223 - Off-axis EIRP spectral density limits for feeder link earth stations in the 17/24 GHz BSS.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Off-axis EIRP spectral density limits for feeder link earth stations in the 17/24 GHz BSS. 25.223 Section 25.223 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS Technical Standards § 25...

Online Artifact Removal for Brain-Computer Interfaces Using Support Vector Machines and Blind Source Separation

OpenAIRE

Halder, Sebastian; Bensch, Michael; Mellinger, Jürgen; Bogdan, Martin; Kübler, Andrea; Birbaumer, Niels; Rosenstiel, Wolfgang

2007-01-01

We propose a combination of blind source separation (BSS) and independent component analysis (ICA) (signal decomposition into artifacts and nonartifacts) with support vector machines (SVMs) (automatic classification) that are designed for online usage. In order to select a suitable BSS/ICA method, three ICA algorithms (JADE, Infomax, and FastICA) and one BSS algorithm (AMUSE) are evaluated to determine their ability to isolate electromyographic (EMG) and electrooculographic...

The effect of different physical agents in the behaviour of bss-13 Lettuce variety

International Nuclear Information System (INIS)

Perez, C.; Calderon, S.; Mendoza, M.; Perez, M.; Perez, G.; Labrada, A.

1999-01-01

The objective of this study was to evaluate and compare the effect of two physical agents in their physiological answer the BSS-13 lettuce variety. Rays gamma Co 60 and rays laser (He-Ne) were the physiological agents utilised. A group of seed were irradiated with gamma in a dose of 10 and 100Grey, and the other group with a time of exposure of 15 sec and 15 min., and power density of 0,4mW/cm2, the rest was no irradiated and was considered like witness. The seed were planted in the protected cultural where remained until of transplantation in field conditions. In the harvest was measured the height, diameter and weight of lettuce. The results show that both agents were presented with an outstanding stimulating with laser with a good efficiency respect to control

ENETRAP III WP7. European guidance on the implementation of the requirements of the EURATOM BSS; ENETRAP III WP7. Europaeische Leitlinien zur Umsetzung der Aus- und Weiterbildungs-Anforderungen der EURATOM-Grundnormen im Strahlenschutz

Energy Technology Data Exchange (ETDEWEB)

Paynter, R. [EUTERP (Netherlands); Stewart, J. [PHE (United Kingdom); Schmitt-Hannig, A. [BfS (Germany); Coeck, M. [SCK-CEN (Belgium); Falcao, A. [IST (Portugal)

2016-07-01

The Euratom BSS lays down specific requirements for the Radiation Protection Expert (RPE) and for the Radiation Protection Officer (RPO) and education and training requirements associated with these roles. A guidance document has been developed within the framework of ENETRAP III WP7 ''Guidance to support the implementation of E and T requirements for RPE and RPO as defined in the Euratom BSS''. The objective of WP7 activities is to facilitate the implementation of the new requirements for RPE and RPO in Member States and to help ensuring a consistent approach throughout the European Union.

Double peak-induced distance error in short-time-Fourier-transform-Brillouin optical time domain reflectometers event detection and the recovery method.

Science.gov (United States)

Yu, Yifei; Luo, Linqing; Li, Bo; Guo, Linfeng; Yan, Jize; Soga, Kenichi

2015-10-01

The measured distance error caused by double peaks in the BOTDRs (Brillouin optical time domain reflectometers) system is a kind of Brillouin scattering spectrum (BSS) deformation, discussed and simulated for the first time in the paper, to the best of the authors' knowledge. Double peak, as a kind of Brillouin spectrum deformation, is important in the enhancement of spatial resolution, measurement accuracy, and crack detection. Due to the variances of the peak powers of the BSS along the fiber, the measured starting point of a step-shape frequency transition region is shifted and results in distance errors. Zero-padded short-time-Fourier-transform (STFT) can restore the transition-induced double peaks in the asymmetric and deformed BSS, thus offering more accurate and quicker measurements than the conventional Lorentz-fitting method. The recovering method based on the double-peak detection and corresponding BSS deformation can be applied to calculate the real starting point, which can improve the distance accuracy of the STFT-based BOTDR system.

Blind Separation of Nonstationary Sources Based on Spatial Time-Frequency Distributions

Directory of Open Access Journals (Sweden)

Zhang Yimin

2006-01-01

Full Text Available Blind source separation (BSS based on spatial time-frequency distributions (STFDs provides improved performance over blind source separation methods based on second-order statistics, when dealing with signals that are localized in the time-frequency (t-f domain. In this paper, we propose the use of STFD matrices for both whitening and recovery of the mixing matrix, which are two stages commonly required in many BSS methods, to provide robust BSS performance to noise. In addition, a simple method is proposed to select the auto- and cross-term regions of time-frequency distribution (TFD. To further improve the BSS performance, t-f grouping techniques are introduced to reduce the number of signals under consideration, and to allow the receiver array to separate more sources than the number of array sensors, provided that the sources have disjoint t-f signatures. With the use of one or more techniques proposed in this paper, improved performance of blind separation of nonstationary signals can be achieved.

Utilization of BSS-Safety Series 115 in facilities for mining ore with uranium and thorium associated to it

International Nuclear Information System (INIS)

Matta, Luiz Ernesto S. de C.; Ferreira, Paulo R. Rocha; Mouco, Charles D. do C.L.

1999-01-01

During the year of 1995, the Brazilian Nuclear Energy Commission, started a investigation program called Mining Project. The main objective of this program was to create a integrated study of environmental and occupational conditions of mining ores with uranium and thorium associated to it. Several technical visits were done at four different types of mines: coal, phosphate, niobium and gold. This work presents the area monitoring results obtained by the occupational radiation protection group. The data found in these inspections were compared to limits established by national rules. A special assessment of the data obtained was done for a future adoption of the BSS-Safety Series 115 recommendations. (author)

Joint High Speed Sealift (JHSS) Baseline Shaft & Strut (BSS) Model 5653-3: Series 2, Propeller Disk LDV Wake Survey; and Series 3, Stock Propeller Powering and Stern Flap Evaluation Experiments

National Research Council Canada - National Science Library

Cusanelli, Dominic S; Chesnakas, Christopher J

2007-01-01

...) and Stock Propeller Powering and Stern Flap Evaluation tests (Series 3. In order to assist in the design of a propeller for the BSS hull, the nominal wakes in the inboard and outboard starboard propeller planes were measured using LDV...

Selective-imaging camera

Science.gov (United States)

Szu, Harold; Hsu, Charles; Landa, Joseph; Cha, Jae H.; Krapels, Keith A.

2015-05-01

How can we design cameras that image selectively in Full Electro-Magnetic (FEM) spectra? Without selective imaging, we cannot use, for example, ordinary tourist cameras to see through fire, smoke, or other obscurants contributing to creating a Visually Degraded Environment (VDE). This paper addresses a possible new design of selective-imaging cameras at firmware level. The design is consistent with physics of the irreversible thermodynamics of Boltzmann's molecular entropy. It enables imaging in appropriate FEM spectra for sensing through the VDE, and displaying in color spectra for Human Visual System (HVS). We sense within the spectra the largest entropy value of obscurants such as fire, smoke, etc. Then we apply a smart firmware implementation of Blind Sources Separation (BSS) to separate all entropy sources associated with specific Kelvin temperatures. Finally, we recompose the scene using specific RGB colors constrained by the HVS, by up/down shifting Planck spectra at each pixel and time.

A new method for quantifying the performance of EEG blind source separation algorithms by referencing a simultaneously recorded ECoG signal.

Science.gov (United States)

Oosugi, Naoya; Kitajo, Keiichi; Hasegawa, Naomi; Nagasaka, Yasuo; Okanoya, Kazuo; Fujii, Naotaka

2017-09-01

Blind source separation (BSS) algorithms extract neural signals from electroencephalography (EEG) data. However, it is difficult to quantify source separation performance because there is no criterion to dissociate neural signals and noise in EEG signals. This study develops a method for evaluating BSS performance. The idea is neural signals in EEG can be estimated by comparison with simultaneously measured electrocorticography (ECoG). Because the ECoG electrodes cover the majority of the lateral cortical surface and should capture most of the original neural sources in the EEG signals. We measured real EEG and ECoG data and developed an algorithm for evaluating BSS performance. First, EEG signals are separated into EEG components using the BSS algorithm. Second, the EEG components are ranked using the correlation coefficients of the ECoG regression and the components are grouped into subsets based on their ranks. Third, canonical correlation analysis estimates how much information is shared between the subsets of the EEG components and the ECoG signals. We used our algorithm to compare the performance of BSS algorithms (PCA, AMUSE, SOBI, JADE, fastICA) via the EEG and ECoG data of anesthetized nonhuman primates. The results (Best case >JADE = fastICA >AMUSE = SOBI ≥ PCA >random separation) were common to the two subjects. To encourage the further development of better BSS algorithms, our EEG and ECoG data are available on our Web site (http://neurotycho.org/) as a common testing platform. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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

CERN Document Server

Mukherjee, B

2002-01-01

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

Fluid temperature at the corneal endothelium during phacoemulsification: comparison of an ophthalmic viscosurgical device and balanced salt solution using the finite element method.

Science.gov (United States)

Reepolmaha, Somporn; Limtrakarn, Wiroj; Uthaisang-Tanechpongtamb, Wanlaya; Dechaumphai, Pramote

2010-01-01

The purpose of this study was to estimate and compare the temperatures of two different anterior chamber solutions at the corneal endothelial level during phacoemulsification. An ophthalmic viscosurgical device (OVD) and balanced salt solution (BSS) were compared using the finite element method (FEM). The thermal properties of an OVD (IAL-F) and BSS were studied in an experimental setting. A computer-aided design model of ocular anatomy was created in two dimensions. The phaco needle was considered to be the only source of heat generation. Then, the FEM was used to demonstrate the transient temperature distribution in the two ocular models at 10, 20, 30, 40, 50 and 60 s. In these models, the anterior chamber was filled with IAL-F (IAL-F model) or BSS (BSS model). The heat generation rate of the phaco needle was 0.0004 cal/s/mm(2). The maximum corneal endothelial temperatures for the two models at 60 s were 52.67 and 41.57 degrees C, respectively. The experimental IAL-F model showed fewer changes in temperature for any given time and location. At larger distances from the heat source, less temperature variation was detected. Phacoemulsification is a potential heat-generating procedure performed between the delicate anterior chamber structures. During this procedure, IAL-F protects the endothelium against heat better than BSS. Copyright 2009 S. Karger AG, Basel.

Mining method selection by integrated AHP and PROMETHEE method.

Science.gov (United States)

Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana

2012-03-01

Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.

PWC-ICA: A Method for Stationary Ordered Blind Source Separation with Application to EEG

Science.gov (United States)

Bigdely-Shamlo, Nima; Mullen, Tim; Robbins, Kay

2016-01-01

Independent component analysis (ICA) is a class of algorithms widely applied to separate sources in EEG data. Most ICA approaches use optimization criteria derived from temporal statistical independence and are invariant with respect to the actual ordering of individual observations. We propose a method of mapping real signals into a complex vector space that takes into account the temporal order of signals and enforces certain mixing stationarity constraints. The resulting procedure, which we call Pairwise Complex Independent Component Analysis (PWC-ICA), performs the ICA in a complex setting and then reinterprets the results in the original observation space. We examine the performance of our candidate approach relative to several existing ICA algorithms for the blind source separation (BSS) problem on both real and simulated EEG data. On simulated data, PWC-ICA is often capable of achieving a better solution to the BSS problem than AMICA, Extended Infomax, or FastICA. On real data, the dipole interpretations of the BSS solutions discovered by PWC-ICA are physically plausible, are competitive with existing ICA approaches, and may represent sources undiscovered by other ICA methods. In conjunction with this paper, the authors have released a MATLAB toolbox that performs PWC-ICA on real, vector-valued signals. PMID:27340397

PWC-ICA: A Method for Stationary Ordered Blind Source Separation with Application to EEG.

Science.gov (United States)

Ball, Kenneth; Bigdely-Shamlo, Nima; Mullen, Tim; Robbins, Kay

2016-01-01

Independent component analysis (ICA) is a class of algorithms widely applied to separate sources in EEG data. Most ICA approaches use optimization criteria derived from temporal statistical independence and are invariant with respect to the actual ordering of individual observations. We propose a method of mapping real signals into a complex vector space that takes into account the temporal order of signals and enforces certain mixing stationarity constraints. The resulting procedure, which we call Pairwise Complex Independent Component Analysis (PWC-ICA), performs the ICA in a complex setting and then reinterprets the results in the original observation space. We examine the performance of our candidate approach relative to several existing ICA algorithms for the blind source separation (BSS) problem on both real and simulated EEG data. On simulated data, PWC-ICA is often capable of achieving a better solution to the BSS problem than AMICA, Extended Infomax, or FastICA. On real data, the dipole interpretations of the BSS solutions discovered by PWC-ICA are physically plausible, are competitive with existing ICA approaches, and may represent sources undiscovered by other ICA methods. In conjunction with this paper, the authors have released a MATLAB toolbox that performs PWC-ICA on real, vector-valued signals.

A Selection Method for COTS Systems

DEFF Research Database (Denmark)

Hedman, Jonas

new skills and methods supporting the process of evaluating and selecting information systems. This paper presents a method for selecting COTS systems. The method includes the following phases: problem framing, requirements and appraisal, and selection of systems. The idea and distinguishing feature...... behind the method is that improved understanding of organizational' ends' or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends' (e.g. improved organizational effectiveness) and ‘means' (e.g. implementing COTS systems). This way of approaching...

Blind Source Separation For Ion Mobility Spectra

International Nuclear Information System (INIS)

Marco, S.; Pomareda, V.; Pardo, A.; Kessler, M.; Goebel, J.; Mueller, G.

2009-01-01

Miniaturization is a powerful trend for smart chemical instrumentation in a diversity of applications. It is know that miniaturization in IMS leads to a degradation of the system characteristics. For the present work, we are interested in signal processing solutions to mitigate limitations introduced by limited drift tube length that basically involve a loss of chemical selectivity. While blind source separation techniques (BSS) are popular in other domains, their application for smart chemical instrumentation is limited. However, in some conditions, basically linearity, BSS may fully recover the concentration time evolution and the pure spectra with few underlying hypothesis. This is extremely helpful in conditions where non-expected chemical interferents may appear, or unwanted perturbations may pollute the spectra. SIMPLISMA has been advocated by Harrington et al. in several papers. However, more modern methods of BSS for bilinear decomposition with the restriction of positiveness have appeared in the last decade. In order to explore and compare the performances of those methods a series of experiments were performed.

A review of output-only structural mode identification literature employing blind source separation methods

Science.gov (United States)

Sadhu, A.; Narasimhan, S.; Antoni, J.

2017-09-01

Output-only modal identification has seen significant activity in recent years, especially in large-scale structures where controlled input force generation is often difficult to achieve. This has led to the development of new system identification methods which do not require controlled input. They often work satisfactorily if they satisfy some general assumptions - not overly restrictive - regarding the stochasticity of the input. Hundreds of papers covering a wide range of applications appear every year related to the extraction of modal properties from output measurement data in more than two dozen mechanical, aerospace and civil engineering journals. In little more than a decade, concepts of blind source separation (BSS) from the field of acoustic signal processing have been adopted by several researchers and shown that they can be attractive tools to undertake output-only modal identification. Originally intended to separate distinct audio sources from a mixture of recordings, mathematical equivalence to problems in linear structural dynamics have since been firmly established. This has enabled many of the developments in the field of BSS to be modified and applied to output-only modal identification problems. This paper reviews over hundred articles related to the application of BSS and their variants to output-only modal identification. The main contribution of the paper is to present a literature review of the papers which have appeared on the subject. While a brief treatment of the basic ideas are presented where relevant, a comprehensive and critical explanation of their contents is not attempted. Specific issues related to output-only modal identification and the relative advantages and limitations of BSS methods both from theoretical and application standpoints are discussed. Gap areas requiring additional work are also summarized and the paper concludes with possible future trends in this area.

A new nonlinear blind source separation method with chaos indicators for decoupling diagnosis of hybrid failures: A marine propulsion gearbox case with a large speed variation

International Nuclear Information System (INIS)

Li, Zhixiong; Peng, Z

2016-01-01

The normal operation of propulsion gearboxes ensures the ship safety. Chaos indicators could efficiently indicate the state change of the gearboxes. However, accurate detection of gearbox hybrid faults using Chaos indicators is a challenging task and the detection under speed variation conditions is attracting considerable attentions. Literature review suggests that the gearbox vibration is a kind of nonlinear mixture of variant vibration sources and the blind source separation (BSS) is reported to be a promising technique for fault vibration analysis, but very limited work has addressed the nonlinear BSS approach for hybrid faults decoupling diagnosis. Aiming to enhance the fault detection performance of Chaos indicators, this work presents a new nonlinear BSS algorithm for gearbox hybrid faults detection under a speed variation condition. This new method appropriately introduces the kernel spectral regression (KSR) framework into the morphological component analysis (MCA). The original vibration data are projected into the reproducing kernel Hilbert space (RKHS) where the instinct nonlinear structure in the original data can be linearized by KSR. Thus the MCA is able to deal with nonlinear BSS in the KSR space. Reliable hybrid faults decoupling is then achieved by this new nonlinear MCA (NMCA). Subsequently, by calculating the Chaos indicators of the decoupled fault components and comparing them with benchmarks, the hybrid faults can be precisely identified. Two specially designed case studies were implemented to evaluate the proposed NMCA-Chaos method on hybrid gear faults decoupling diagnosis. The performance of the NMCA-Chaos was compared with state of art techniques. The analysis results show high performance of the proposed method on hybrid faults detection in a marine propulsion gearbox with large speed variations.

EEG feature selection method based on decision tree.

Science.gov (United States)

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Impact of Base Station Cooperation on Cell Planning

Directory of Open Access Journals (Sweden)

Ian Dexter Garcia

2010-01-01

Full Text Available Base station cooperation (BSC has been identified as a key radio access technology for next-generation cellular networks such as LTE-Advanced. BSC impacts cell planning, which is the methodical selection of base station (BS sites, and BS equipment configuration for cost-effective cellular networks. In this paper, the impact of BSC on cell plan parameters (coverage, traffic, handover, and cost, as well as additional cell planning steps required for BSC are discussed. Results show that BSC maximizes its gains over noncooperation (NC in a network wherein interference from cooperating BSs is the main limitation. Locations exist where NC may produce higher throughputs, therefore dynamic or semistatic switching between BSC and NC, called fractional BSC, is recommended. Because of interference from noncooperating BSs, the gains of BSC over NC are upper bounded, and diminishes at greater intersite distances because of noise. This encourages smaller cell sizes, higher transmit powers, and dynamic clustering of cooperative BSs.

AMES: Towards an Agile Method for ERP Selection

OpenAIRE

Juell-Skielse, Gustaf; Nilsson, Anders G.; Nordqvist, Andreas; Westergren, Mattias

2012-01-01

Conventional on-premise installations of ERP are now rapidly being replaced by ERP as service. Although ERP becomes more accessible and no longer requires local infrastructure, current selection methods do not take full advantage of the provided agility. In this paper we present AMES (Agile Method for ERP Selection), a novel method for ERP selection which better utilizes the strengths of service oriented ERP. AMES is designed to shorten lead time for selection, support identification of essen...

Tailoring nutritional and process variables for hyperproduction of catalase from a novel isolated bacterium Geobacillus sp. BSS-7.

Science.gov (United States)

Kauldhar, Baljinder Singh; Sooch, Balwinder Singh

2016-01-14

Catalase (EC 1.11.1.6) is one of the important industrial enzyme employed in diagnostic and analytical methods in the form of biomarkers and biosensors in addition to their enormous applications in textile, paper, food and pharmaceutical sectors. The present study demonstrates the utility of a newly isolated and adapted strain of genus Geobacillus possessing unique combination of several industrially important extremophilic properties for the hyper production of catalase. The bacterium can grow over a wide range of pH (3-12) and temperature (10-90 °C) with extraordinary capability to produce catalase. A novel extremophilic strain belonging to genus Geobacillus was exploited for the production of catalase by tailoring its nutritional requirements and process variables. One variable at a time traditional approach followed by computational designing was applied to customize the fermentation process. A simple fermentation media containing only three components namely sucrose (0.55 %, w/v), yeast extract (1.0 %, w/v) and BaCl2 (0.08 %, w/v) was designed for the hyperproduction of catalase. A controlled and optimum air supply caused a tremendous increase in the enzyme production on moving the bioprocess from the flask to bioreactor level. The present paper reports high quantum of catalase production (105,000 IU/mg of cells) in a short fermentation time of 12 h. To the best of our knowledge, there is no report in the literature that matches the performance of the developed protocol for the catalase production. This is the first serious study covering intracellular catalase production from thermophilic genus Geobacillus. An increase in intracellular catalase production by 214.72 % was achieved in the optimized medium when transferred from the shake flask to the fermenter level. The extraordinary high production of catalase from Geobacillus sp. BSS-7 makes the isolated strain a prospective candidate for bulk catalase production on an industrial scale.

Alternative microbial methods: An overview and selection criteria.

Science.gov (United States)

Jasson, Vicky; Jacxsens, Liesbeth; Luning, Pieternel; Rajkovic, Andreja; Uyttendaele, Mieke

2010-09-01

This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant bibliography. Perspectives on future development and the potential of the rapid method for routine application in food diagnostics are discussed. As various alternative "rapid" methods in different formats are available on the market, it can be very difficult for a food business operator or for a control authority to select the most appropriate method which fits its purpose. Validation of a method by a third party, according to international accepted protocol based upon ISO 16140, may increase the confidence in the performance of a method. A list of at the moment validated methods for enumeration of both utility indicators (aerobic plate count) and hygiene indicators (Enterobacteriaceae, Escherichia coli, coagulase positive Staphylococcus) as well as for detection of the four major pathogens (Salmonella spp., Listeria monocytogenes, E. coli O157 and Campylobacter spp.) is included with reference to relevant websites to check for updates. In a second part of this study, selection criteria are introduced to underpin the choice of the appropriate method(s) for a defined application. The selection criteria link the definition of the context in which the user of the method functions - and thus the prospective use of the microbial test results - with the technical information on the method and its operational requirements and sustainability. The selection criteria can help the end user of the method to obtain a systematic insight into all relevant factors to be taken into account for selection of a method for microbial analysis. Copyright 2010 Elsevier Ltd. All rights reserved.

Inventory of LCIA selection methods for assessing toxic releases. Methods and typology report part B

DEFF Research Database (Denmark)

Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

method(s) in Work package 8 (WP8) of the OMNIITOX project. The selection methods and the other CRS methods are described in detail, a set of evaluation criteria are developed and the methods are evaluated against these criteria. This report (Deliverable 11B (D11B)) gives the results from task 7.1d, 7.1e......This report describes an inventory of Life Cycle Impact Assessment (LCIA) selection methods for assessing toxic releases. It consists of an inventory of current selection methods and other Chemical Ranking and Scoring (CRS) methods assessed to be relevant for the development of (a) new selection...... and 7.1f of WP 7 for selection methods. The other part of D11 (D11A) is reported in another report and deals with characterisation methods. A selection method is a method for prioritising chemical emissions to be included in an LCIA characterisation of toxic releases, i.e. calculating indicator scores...

Inspection methods and their selection

International Nuclear Information System (INIS)

Maier, H.J.

1980-01-01

First those nondestructive testing methods, which are used in quality assurance, are to be treated, e.g. - ultrasonics - radiography - magnetic particle testing - dye penetrant testing - eddy currents, and their capabilities and limitations are shown. Second the selection of optimal testing methods under the aspect of defect recognition in different materials and components are shown. (orig./RW)

Development of an Assessment Method for Building Materials Under Euratom Scope.

Science.gov (United States)

de With, Govert

2017-11-01

In 2013, the European Commission published its basic safety standards for protection against the dangers arising from exposure to ionizing radiation (Council Directive 2013/59/Euratom)-also known as EU-BSS. As a result, the use of raw materials with potentially elevated activity concentrations such as fly ash, phosphogypsum, and slags will now fall under EU-BSS scope when applied in building materials. In light of this new policy, a variety of tools are available to assess compliance with the 1-mSv y reference level for building materials. At the heart of these tools is a gamma-spectrometric determination of the naturally occurring radionuclides Ra, Th, and K in the material of concern. As a large number of construction products contain a certain amount of the raw material that falls under the scope of the EU regulation, this policy will lead to substantial measurement of building materials that pose little radiation risk. For this reason, a method is developed to enable assessment against the 1-mSv value not on the basis of gamma-spectrometric analysis but rather based on the product's material composition. The proposed method prescribes a maximum permitted content of raw materials with potentially elevated activity concentrations in terms of a weight percentage of the end product, where the raw materials of concern are defined as those listed in Annex XIII of the EU-BSS. The permitted content is a function of the product's surface density. Therefore, a product with a low surface density of up to 25 kg m can consist of nearly 100% raw materials with potentially elevated activity concentrations, and this percentage drops to around 15% for products with a surface density of around 500 kg m. Building materials that comply with these requirements on product composition are exempt from testing, while products that do not comply must perform regular gamma-spectrometric analysis. A full validation and testing of the method is provided. In addition, the paper discusses

Using MACBETH method for supplier selection in manufacturing environment

Directory of Open Access Journals (Sweden)

Prasad Karande

2013-04-01

Full Text Available Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches.

Blind Source Separation of Event-Related EEG/MEG.

Science.gov (United States)

Metsomaa, Johanna; Sarvas, Jukka; Ilmoniemi, Risto Juhani

2017-09-01

Blind source separation (BSS) can be used to decompose complex electroencephalography (EEG) or magnetoencephalography data into simpler components based on statistical assumptions without using a physical model. Applications include brain-computer interfaces, artifact removal, and identifying parallel neural processes. We wish to address the issue of applying BSS to event-related responses, which is challenging because of nonstationary data. We introduce a new BSS approach called momentary-uncorrelated component analysis (MUCA), which is tailored for event-related multitrial data. The method is based on approximate joint diagonalization of multiple covariance matrices estimated from the data at separate latencies. We further show how to extend the methodology for autocovariance matrices and how to apply BSS methods suitable for piecewise stationary data to event-related responses. We compared several BSS approaches by using simulated EEG as well as measured somatosensory and transcranial magnetic stimulation (TMS) evoked EEG. Among the compared methods, MUCA was the most tolerant one to noise, TMS artifacts, and other challenges in the data. With measured somatosensory data, over half of the estimated components were found to be similar by MUCA and independent component analysis. MUCA was also stable when tested with several input datasets. MUCA is based on simple assumptions, and the results suggest that MUCA is robust with nonideal data. Event-related responses and BSS are valuable and popular tools in neuroscience. Correctly designed BSS is an efficient way of identifying artifactual and neural processes from nonstationary event-related data.

Analytical modeling of mode selection and power control for underlay D2D communication in cellular networks

KAUST Repository

Elsawy, Hesham

2014-11-01

Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D communication can improve spatial frequency reuse and energy efficiency in cellular networks. This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control. The developed framework is used to analyze and understand how the underlaying D2D communication affects the cellular network performance. Through comprehensive numerical analysis, we investigate the expected performance gains and provide guidelines for selecting the network parameters.

Revisiting the Basic Symptom Concept: Towards Translating Risk Symptoms for Psychosis into Neurobiological Targets

Directory of Open Access Journals (Sweden)

Frauke eSchultze-Lutter

2016-01-01

Full Text Available In its initial formulation, the concept of basic symptoms (BSs integrated findings on the early symptomatic course of schizophrenia and first in vivo evidence of accompanying brain aberrations. It argued that the subtle subclinical disturbances in mental processes described as BSs were the most direct self-experienced expression of the underlying neurobiological aberrations of the disease. Other characteristic symptoms of psychosis (e.g., delusions, hallucinations were conceptualized as secondary phenomena, resulting from dysfunctional beliefs and suboptimal coping styles with emerging BSs and/or concomitant stressors. While BSs can occur in many mental disorders, in particular affective disorders, a subset of perceptive and cognitive BSs appear to be specific to psychosis and are currently employed in two alternative risk criteria. However, despite their clinical recognition in the early detection of psychosis, neurobiological research on the aetiopathology of psychosis with neuroimaging methods has only just begun to consider the neural correlate of BSs. This perspective paper reviews the emerging evidence of an association between BSs and aberrant brain activation, connectivity patterns, and metabolism, and outlines promising routes for the use of BSs in aetiopathological research on psychosis.

Variable selection by lasso-type methods

Directory of Open Access Journals (Sweden)

Sohail Chand

2011-09-01

Full Text Available Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adaptive lasso to satisfy the necessary and almost sufcient condition for consistent variable selection. We suggest a novel algorithm and give an important result that for the adaptive lasso if predictors are normalised after the introduction of adaptive weights, it makes the adaptive lasso performance identical to the lasso.

Personnel Selection Based on Fuzzy Methods

Directory of Open Access Journals (Sweden)

Lourdes Cañós

2011-03-01

Full Text Available The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate. Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.

The use of portable equipment for the activity concentration index determination of building materials: method validation and survey of building materials on the Belgian market

International Nuclear Information System (INIS)

Stals, M.; Verhoeven, S.; Bruggeman, M.; Pellens, V.; Schroeyers, W.; Schreurs, S.

2014-01-01

The Euratom BSS requires that in the near future (2015) the building materials for application in dwellings or buildings such as offices or workshops are screened for NORM nuclides. The screening tool is the activity concentration index (ACI). Therefore it is expected that a large number of building materials will be screened for NORM and thus require ACI determination. Nowadays, the proposed standard for determination of building material ACI is a laboratory analyses technique with high purity germanium spectrometry and 21 days equilibrium delay. In this paper, the B-NORM method for determination of building material ACI is assessed as a faster method that can be performed on-site, alternative to the aforementioned standard method. The B-NORM method utilizes a LaBr 3 (Ce) scintillation probe to obtain the spectral data. Commercially available software was applied to comprehensively take into account the factors determining the counting efficiency. The ACI was determined by interpreting the gamma spectrum from 226 Ra and its progeny; 232 Th progeny and 40 K. In order to assess the accuracy of the B-NORM method, a large selection of samples was analyzed by a certified laboratory and the results were compared with the B-NORM results. The results obtained with the B-NORM method were in good correlation with the results obtained by the certified laboratory, indicating that the B-NORM method is an appropriate screening method to assess building material ACI. The B-NORM method was applied to analyze more than 120 building materials on the Belgian market. No building materials that exceed the proposed reference level of 1 mSv/year were encountered. -- Highlights: • Many building materials will have to be tested for NORM activity concentrations. • An on-site NORM analysis method has been developed and validated. • Over 120 building materials on the Belgian market have been analyzed with this method. • The Euratom BSS reference level of 1 mSv/year excess dose will

Methods for model selection in applied science and engineering.

Energy Technology Data Exchange (ETDEWEB)

Field, Richard V., Jr.

2004-10-01

Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

SELECTION OF NON-CONVENTIONAL MACHINING PROCESSES USING THE OCRA METHOD

Directory of Open Access Journals (Sweden)

Miloš Madić

2015-04-01

Full Text Available Selection of the most suitable nonconventional machining process (NCMP for a given machining application can be viewed as multi-criteria decision making (MCDM problem with many conflicting and diverse criteria. To aid these selection processes, different MCDM methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. operational competitiveness ratings analysis (OCRA method for solving the NCMP selection problems. Applicability, suitability and computational procedure of OCRA method have been demonstrated while solving three case studies dealing with selection of the most suitable NCMP. In each case study the obtained rankings were compared with those derived by the past researchers using different MCDM methods. The results obtained using the OCRA method have good correlation with those derived by the past researchers which validate the usefulness of this method while solving complex NCMP selection problems.

Selection of industrial robots using the Polygons area method

Directory of Open Access Journals (Sweden)

Mortaza Honarmande Azimi

2014-08-01

Full Text Available Selection of robots from the several proposed alternatives is a very important and tedious task. Decision makers are not limited to one method and several methods have been proposed for solving this problem. This study presents Polygons Area Method (PAM as a multi attribute decision making method for robot selection problem. In this method, the maximum polygons area obtained from the attributes of an alternative robot on the radar chart is introduced as a decision-making criterion. The results of this method are compared with other typical multiple attribute decision-making methods (SAW, WPM, TOPSIS, and VIKOR by giving two examples. To find similarity in ranking given by different methods, Spearman’s rank correlation coefficients are obtained for different pairs of MADM methods. It was observed that the introduced method is in good agreement with other well-known MADM methods in the robot selection problem.

Equipment Selection by using Fuzzy TOPSIS Method

Science.gov (United States)

Yavuz, Mahmut

2016-10-01

In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

Optimization methods for activities selection problems

Science.gov (United States)

Mahad, Nor Faradilah; Alias, Suriana; Yaakop, Siti Zulaika; Arshad, Norul Amanina Mohd; Mazni, Elis Sofia

2017-08-01

Co-curriculum activities must be joined by every student in Malaysia and these activities bring a lot of benefits to the students. By joining these activities, the students can learn about the time management and they can developing many useful skills. This project focuses on the selection of co-curriculum activities in secondary school using the optimization methods which are the Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP). A secondary school in Negeri Sembilan, Malaysia was chosen as a case study. A set of questionnaires were distributed randomly to calculate the weighted for each activity based on the 3 chosen criteria which are soft skills, interesting activities and performances. The weighted was calculated by using AHP and the results showed that the most important criteria is soft skills. Then, the ZOGP model will be analyzed by using LINGO Software version 15.0. There are two priorities to be considered. The first priority which is to minimize the budget for the activities is achieved since the total budget can be reduced by RM233.00. Therefore, the total budget to implement the selected activities is RM11,195.00. The second priority which is to select the co-curriculum activities is also achieved. The results showed that 9 out of 15 activities were selected. Thus, it can concluded that AHP and ZOGP approach can be used as the optimization methods for activities selection problem.

Relationship of Source Selection Methods to Contract Outcomes: an Analysis of Air Force Source Selection

Science.gov (United States)

2015-12-01

some occasions, performance is terminated early; this can occur due to either mutual agreement or a breach of contract by one of the parties (Garrett...Relationship of Source Selection Methods to Contract Outcomes: an Analysis of Air Force Source Selection December 2015 Capt Jacques Lamoureux, USAF...on the contract management process, with special emphasis on the source selection methods of tradeoff and lowest price technically acceptable (LPTA

Selection Method for COTS Systems

DEFF Research Database (Denmark)

Hedman, Jonas; Andersson, Bo

2014-01-01

feature behind the method is that improved understanding of organizational ‘ends’ or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends’ (e.g. improved organizational effectiveness) and ‘means’ (e.g. implementing COTS systems). This way...

An improved selective sampling method

International Nuclear Information System (INIS)

Miyahara, Hiroshi; Iida, Nobuyuki; Watanabe, Tamaki

1986-01-01

The coincidence methods which are currently used for the accurate activity standardisation of radio-nuclides, require dead time and resolving time corrections which tend to become increasingly uncertain as countrates exceed about 10 K. To reduce the dependence on such corrections, Muller, in 1981, proposed the selective sampling method using a fast multichannel analyser (50 ns ch -1 ) for measuring the countrates. It is, in many ways, more convenient and possibly potentially more reliable to replace the MCA with scalers and a circuit is described employing five scalers; two of them serving to measure the background correction. Results of comparisons using our new method and the coincidence method for measuring the activity of 60 Co sources yielded agree-ment within statistical uncertainties. (author)

An Identification Key for Selecting Methods for Sustainability Assessments

Directory of Open Access Journals (Sweden)

Michiel C. Zijp

2015-03-01

Full Text Available Sustainability assessments can play an important role in decision making. This role starts with selecting appropriate methods for a given situation. We observed that scientists, consultants, and decision-makers often do not systematically perform a problem analyses that guides the choice of the method, partly related to a lack of systematic, though sufficiently versatile approaches to do so. Therefore, we developed and propose a new step towards method selection on the basis of question articulation: the Sustainability Assessment Identification Key. The identification key was designed to lead its user through all important choices needed for comprehensive question articulation. Subsequently, methods that fit the resulting specific questions are suggested by the key. The key consists of five domains, of which three determine method selection and two the design or use of the method. Each domain consists of four or more criteria that need specification. For example in the domain “system boundaries”, amongst others, the spatial and temporal scales are specified. The key was tested (retrospectively on a set of thirty case studies. Using the key appeared to contribute to improved: (i transparency in the link between the question and method selection; (ii consistency between questions asked and answers provided; and (iii internal consistency in methodological design. There is latitude to develop the current initial key further, not only for selecting methods pertinent to a problem definition, but also as a principle for associated opportunities such as stakeholder identification.

A Selection Method That Succeeds!

Science.gov (United States)

Weitman, Catheryn J.

Provided a structural selection method is carried out, it is possible to find quality early childhood personnel. The hiring process involves five definite steps, each of which establishes a base for the next. A needs assessment formulating basic minimal qualifications is the first step. The second step involves review of current job descriptions…

Supplier selection based on multi-criterial AHP method

Directory of Open Access Journals (Sweden)

Jana Pócsová

2010-03-01

Full Text Available This paper describes a case-study of supplier selection based on multi-criterial Analytic Hierarchy Process (AHP method.It is demonstrated that using adequate mathematical method can bring us “unprejudiced” conclusion, even if the alternatives (suppliercompanies are very similar in given selection-criteria. The result is the best possible supplier company from the viewpoint of chosen criteriaand the price of the product.

Methods for producing thin film charge selective transport layers

Science.gov (United States)

Hammond, Scott Ryan; Olson, Dana C.; van Hest, Marinus Franciscus Antonius Maria

2018-01-02

Methods for producing thin film charge selective transport layers are provided. In one embodiment, a method for forming a thin film charge selective transport layer comprises: providing a precursor solution comprising a metal containing reactive precursor material dissolved into a complexing solvent; depositing the precursor solution onto a surface of a substrate to form a film; and forming a charge selective transport layer on the substrate by annealing the film.

Reference satellite selection method for GNSS high-precision relative positioning

Directory of Open Access Journals (Sweden)

Xiao Gao

2017-03-01

Full Text Available Selecting the optimal reference satellite is an important component of high-precision relative positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision (PDOP value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.

Multiple somatic symptoms in primary care

DEFF Research Database (Denmark)

Goldberg, D. P.; Reed, G. M.; Robles, R.

2016-01-01

Objective A World Health Organization (WHO) field study conducted in five countries assessed proposals for Bodily Stress Syndrome (BSS) and Health Anxiety (HA) for the Primary Health Care Version of ICD-11. BSS requires multiple somatic symptoms not caused by known physical pathology and associated...... with distress or dysfunction. HA involves persistent, intrusive fears of having an illness or intense preoccupation with and misinterpretation of bodily sensations. This study examined how the proposed descriptions for BSS and HA corresponded to what was observed by working primary care physicians (PCPs......) in participating countries, and the relationship of BSS and HA to depressive and anxiety disorders and to disability. Method PCPs referred patients judged to have BSS or HA, who were then interviewed using a standardized psychiatric interview and a standardized measure of disability. Results Of 587 patients...

Underground Mining Method Selection Using WPM and PROMETHEE

Science.gov (United States)

Balusa, Bhanu Chander; Singam, Jayanthu

2018-04-01

The aim of this paper is to represent the solution to the problem of selecting suitable underground mining method for the mining industry. It is achieved by using two multi-attribute decision making techniques. These two techniques are weighted product method (WPM) and preference ranking organization method for enrichment evaluation (PROMETHEE). In this paper, analytic hierarchy process is used for weight's calculation of the attributes (i.e. parameters which are used in this paper). Mining method selection depends on physical parameters, mechanical parameters, economical parameters and technical parameters. WPM and PROMETHEE techniques have the ability to consider the relationship between the parameters and mining methods. The proposed techniques give higher accuracy and faster computation capability when compared with other decision making techniques. The proposed techniques are presented to determine the effective mining method for bauxite mine. The results of these techniques are compared with methods used in the earlier research works. The results show, conventional cut and fill method is the most suitable mining method.

Development of modelling method selection tool for health services management: from problem structuring methods to modelling and simulation methods.

Science.gov (United States)

Jun, Gyuchan T; Morris, Zoe; Eldabi, Tillal; Harper, Paul; Naseer, Aisha; Patel, Brijesh; Clarkson, John P

2011-05-19

There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.

A Quantitative Risk Assessment Model Involving Frequency and Threat Degree under Line-of-Business Services for Infrastructure of Emerging Sensor Networks.

Science.gov (United States)

Jing, Xu; Hu, Hanwen; Yang, Huijun; Au, Man Ho; Li, Shuqin; Xiong, Naixue; Imran, Muhammad; Vasilakos, Athanasios V

2017-03-21

The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider's server contains a lot of valuable resources. LoBSs' users are very diverse as they may come from a wide range of locations with vastly different characteristics. Cost of joining could be low and in many cases, intruders are eligible users conducting malicious actions. As a result, user access should be adjusted dynamically. Assessing LoBSs' risk dynamically based on both frequency and threat degree of malicious operations is therefore necessary. In this paper, we proposed a Quantitative Risk Assessment Model (QRAM) involving frequency and threat degree based on value at risk. To quantify the threat degree as an elementary intrusion effort, we amend the influence coefficient of risk indexes in the network security situation assessment model. To quantify threat frequency as intrusion trace effort, we make use of multiple behavior information fusion. Under the influence of intrusion trace, we adapt the historical simulation method of value at risk to dynamically access LoBSs' risk. Simulation based on existing data is used to select appropriate parameters for QRAM. Our simulation results show that the duration influence on elementary intrusion effort is reasonable when the normalized parameter is 1000. Likewise, the time window of intrusion trace and the weight between objective risk and subjective risk can be set to 10 s and 0.5, respectively. While our focus is to develop QRAM for assessing the risk of LoBSs for infrastructure of ESNs dynamically involving frequency and threat degree, we believe it is also appropriate for other scenarios in cloud computing.

FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

Directory of Open Access Journals (Sweden)

Ratri Enggar Pawening

2016-06-01

Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.

Supplier Selection Using Weighted Utility Additive Method

Science.gov (United States)

Karande, Prasad; Chakraborty, Shankar

2015-10-01

Supplier selection is a multi-criteria decision-making (MCDM) problem which mainly involves evaluating a number of available suppliers according to a set of common criteria for choosing the best one to meet the organizational needs. For any manufacturing or service organization, selecting the right upstream suppliers is a key success factor that will significantly reduce purchasing cost, increase downstream customer satisfaction and improve competitive ability. The past researchers have attempted to solve the supplier selection problem employing different MCDM techniques which involve active participation of the decision makers in the decision-making process. This paper deals with the application of weighted utility additive (WUTA) method for solving supplier selection problems. The WUTA method, an extension of utility additive approach, is based on ordinal regression and consists of building a piece-wise linear additive decision model from a preference structure using linear programming (LP). It adopts preference disaggregation principle and addresses the decision-making activities through operational models which need implicit preferences in the form of a preorder of reference alternatives or a subset of these alternatives present in the process. The preferential preorder provided by the decision maker is used as a restriction of a LP problem, which has its own objective function, minimization of the sum of the errors associated with the ranking of each alternative. Based on a given reference ranking of alternatives, one or more additive utility functions are derived. Using these utility functions, the weighted utilities for individual criterion values are combined into an overall weighted utility for a given alternative. It is observed that WUTA method, having a sound mathematical background, can provide accurate ranking to the candidate suppliers and choose the best one to fulfill the organizational requirements. Two real time examples are illustrated to prove

Evaluation of blind signal separation methods

NARCIS (Netherlands)

Schobben, D.W.E.; Torkkola, K.; Smaragdis, P.

1999-01-01

Recently many new Blind Signal Separation BSS algorithms have been introduced Authors evaluate the performance of their algorithms in various ways Among these are speech recognition rates plots of separated signals plots of cascaded mixingunmixing impulse responses and signal to noise ratios Clearly

Alternative microbial methods: An overview and selection criteria.

NARCIS (Netherlands)

Jasson, V.; Jacxsens, L.; Luning, P.A.; Rajkovic, A.; Uyttendaele, M.

2010-01-01

This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant

Methods for selective functionalization and separation of carbon nanotubes

Science.gov (United States)

Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H (Inventor); Smalley, Richard E. (Inventor); Marek, legal representative, Irene Marie (Inventor)

2011-01-01

The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

Advanced display object selection methods for enhancing user-computer productivity

Science.gov (United States)

Osga, Glenn A.

1993-01-01

The User-Interface Technology Branch at NCCOSC RDT&E Division has been conducting a series of studies to address the suitability of commercial off-the-shelf (COTS) graphic user-interface (GUI) methods for efficiency and performance in critical naval combat systems. This paper presents an advanced selection algorithm and method developed to increase user performance when making selections on tactical displays. The method has also been applied with considerable success to a variety of cursor and pointing tasks. Typical GUI's allow user selection by: (1) moving a cursor with a pointing device such as a mouse, trackball, joystick, touchscreen; and (2) placing the cursor on the object. Examples of GUI objects are the buttons, icons, folders, scroll bars, etc. used in many personal computer and workstation applications. This paper presents an improved method of selection and the theoretical basis for the significant performance gains achieved with various input devices tested. The method is applicable to all GUI styles and display sizes, and is particularly useful for selections on small screens such as notebook computers. Considering the amount of work-hours spent pointing and clicking across all styles of available graphic user-interfaces, the cost/benefit in applying this method to graphic user-interfaces is substantial, with the potential for increasing productivity across thousands of users and applications.

A fuzzy logic based PROMETHEE method for material selection problems

Directory of Open Access Journals (Sweden)

Muhammet Gul

2018-03-01

Full Text Available Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

Factors of Selection of the Stock Allocation Method

Directory of Open Access Journals (Sweden)

Rohov Heorhii K.

2014-03-01

Full Text Available The article describes results of the author’s study of factors of making strategic decisions on selection of methods of stock allocation by public joint stock companies in Ukraine. The author used the Random forest mathematical apparatus of classification trees building and also informal methods. The article analyses the reasons that restrain public allocation of stock. It shows significant influence upon selection of a method of stock allocation of such factors as capital concentration, balance rate of corporate rights, sector of economy and significant participation of the institutes of common investment or the state in the authorised capital. The built hierarchical model of classification of factors of the issuing policy of joint stock companies finds logical justification in specific features of the institutional environment, however, it does not fit into the framework of the classical concept of the market economy. The model could be used both for formation of goals of corporate financial strategies and in the process of improvement of state regulation of activity of securities issuers. The prospect of further studies in this direction is identification of transformation of factors of selection of the stock allocation method under conditions of revival of the stock market.

Proactive AP Selection Method Considering the Radio Interference Environment

Science.gov (United States)

Taenaka, Yuzo; Kashihara, Shigeru; Tsukamoto, Kazuya; Yamaguchi, Suguru; Oie, Yuji

In the near future, wireless local area networks (WLANs) will overlap to provide continuous coverage over a wide area. In such ubiquitous WLANs, a mobile node (MN) moving freely between multiple access points (APs) requires not only permanent access to the Internet but also continuous communication quality during handover. In order to satisfy these requirements, an MN needs to (1) select an AP with better performance and (2) execute a handover seamlessly. To satisfy requirement (2), we proposed a seamless handover method in a previous study. Moreover, in order to achieve (1), the Received Signal Strength Indicator (RSSI) is usually employed to measure wireless link quality in a WLAN system. However, in a real environment, especially if APs are densely situated, it is difficult to always select an AP with better performance based on only the RSSI. This is because the RSSI alone cannot detect the degradation of communication quality due to radio interference. Moreover, it is important that AP selection is completed only on an MN, because we can assume that, in ubiquitous WLANs, various organizations or operators will manage APs. Hence, we cannot modify the APs for AP selection. To overcome these difficulties, in the present paper, we propose and implement a proactive AP selection method considering wireless link condition based on the number of frame retransmissions in addition to the RSSI. In the evaluation, we show that the proposed AP selection method can appropriately select an AP with good wireless link quality, i.e., high RSSI and low radio interference.

Blind source separation advances in theory, algorithms and applications

CERN Document Server

Wang, Wenwu

2014-01-01

Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications. Furthermore, the research results previously scattered in many journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms, and applications of BSS. Dr. Ganesh R. Naik works at University of Technology, Sydney, Australia; Dr. Wenwu Wang works at University of Surrey, UK.

Selection method of terrain matching area for TERCOM algorithm

Science.gov (United States)

Zhang, Qieqie; Zhao, Long

2017-10-01

The performance of terrain aided navigation is closely related to the selection of terrain matching area. The different matching algorithms have different adaptability to terrain. This paper mainly studies the adaptability to terrain of TERCOM algorithm, analyze the relation between terrain feature and terrain characteristic parameters by qualitative and quantitative methods, and then research the relation between matching probability and terrain characteristic parameters by the Monte Carlo method. After that, we propose a selection method of terrain matching area for TERCOM algorithm, and verify the method correctness with real terrain data by simulation experiment. Experimental results show that the matching area obtained by the method in this paper has the good navigation performance and the matching probability of TERCOM algorithm is great than 90%

Dynamic surface tension measurement for the screening of biosurfactants produced by Lactobacillus plantarum subsp. plantarum PTCC 1896.

Science.gov (United States)

Bakhshi, Nafiseh; Soleimanian-Zad, Sabihe; Sheikh-Zeinoddin, Mahmoud

2017-06-01

Currently, screening of microbial biosurfactants (BSs) is based on their equilibrium surface tension values obtained using static surface tension measurement. However, a good surfactant should not only have a low equilibrium surface tension, but its dynamic surface tension (DST) should also decrease rapidly with time. In this study, screening of BSs produced by Lactobacillus plantarum subsp. plantarum PTCC 1896 (probiotic) was performed based on their DST values measured by Wilhelmy plate tensiometry. The relationship between DST and structural and functional properties (anti-adhesive activity) of the BSs was investigated. The results showed that the changes in the yield, productivity and structure of the BSs were growth medium and incubation time dependent (p<0.05). Structurally different BSs produced exhibited identical equilibrium surface tension values. However, differences among the structure/yield of the BSs were observed through the measurement of their DST. The considerable dependence of DST on the concentration and composition of the BS proteins was observed (p<0.05). Moreover, the anti-adhesive activity of the BS was found to be positively correlated with its DST. The results suggest that the DST measurement could serve as an efficient method for the clever screening of BSs producer/production condition, and consequently, for the investigation of probiotic features of bacteria, since the anti-adhesive activity is an important criterion of probiotics. Copyright © 2017 Elsevier Inc. All rights reserved.

A probabilistic method for testing and estimating selection differences between populations.

Science.gov (United States)

He, Yungang; Wang, Minxian; Huang, Xin; Li, Ran; Xu, Hongyang; Xu, Shuhua; Jin, Li

2015-12-01

Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection. © 2015 He et al.; Published by Cold Spring Harbor Laboratory Press.

Biologically Inspired Intercellular Slot Synchronization

Directory of Open Access Journals (Sweden)

Alexander Tyrrell

2009-01-01

Full Text Available The present article develops a decentralized interbase station slot synchronization algorithm suitable for cellular mobile communication systems. The proposed cellular firefly synchronization (CelFSync algorithm is derived from the theory of pulse-coupled oscillators, common to describe synchronization phenomena in biological systems, such as the spontaneous synchronization of fireflies. In order to maintain synchronization among base stations (BSs, even when there is no direct link between adjacent BSs, some selected user terminals (UTs participate in the network synchronization process. Synchronization emerges by exchanging two distinct synchronization words, one transmitted by BSs and the other by active UTs, without any a priori assumption on the initial timing misalignments of BSs and UTs. In large-scale networks with inter-BS site distances up to a few kilometers, propagation delays severely affect the attainable timing accuracy of CelFSync. We show that by an appropriate combination of CelFSync with the timing advance procedure, which aligns uplink transmission of UTs to arrive simultaneously at the BS, a timing accuracy within a fraction of the inter-BS propagation delay is retained.

Profiling and analysis of multiple constituents in Baizhu Shaoyao San before and after processing by stir-frying using UHPLC/Q-TOF-MS/MS coupled with multivariate statistical analysis.

Science.gov (United States)

Xu, Yangyang; Cai, Hao; Cao, Gang; Duan, Yu; Pei, Ke; Tu, Sicong; Zhou, Jia; Xie, Li; Sun, Dongdong; Zhao, Jiayu; Liu, Jing; Wang, Xiaoqi; Shen, Lin

2018-04-15

Baizhu Shaoyao San (BSS) is a famous traditional Chinese medicinal formula widely used for the treatment of painful diarrhea, intestinal inflammation, and diarrhea-predominant irritable bowel syndrome. According to clinical medication, three medicinal herbs (Atractylodis Macrocephalae Rhizoma, Paeoniae Radix Alba, and Citri Reticulatae Pericarpium) included in BSS must be processed using some specific methods of stir-frying. On the basis of the classical theories of traditional Chinese medicine, the therapeutic effects of BSS would be significantly enhanced after processing. Generally, the changes of curative effects mainly result from the variations of inside chemical basis caused by the processing procedure. To find out the corresponding changes of chemical compositions in BSS after processing and to elucidate the material basis of the changed curative effects, an optimized ultra-high-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry in positive and negative ion modes coupled with multivariate statistical analyses were developed. As a result, a total of 186 compounds were ultimately identified in crude and processed BSS, in which 62 marker compounds with significant differences between crude and processed BSS were found by principal component analysis and t-test. Compared with crude BSS, the contents of 23 compounds were remarkably decreased and the contents of 39 compounds showed notable increase in processed BSS. The transformation mechanisms of some changed compounds were appropriately inferred from the results. Furthermore, compounds with extremely significant differences might strengthen the effects of the whole herbal formula. Copyright © 2018 Elsevier B.V. All rights reserved.

The experiments and analysis of several selective video encryption methods

Science.gov (United States)

Zhang, Yue; Yang, Cheng; Wang, Lei

2013-07-01

This paper presents four methods for selective video encryption based on the MPEG-2 video compression,including the slices, the I-frames, the motion vectors, and the DCT coefficients. We use the AES encryption method for simulation experiment for the four methods on VS2010 Platform, and compare the video effects and the processing speed of each frame after the video encrypted. The encryption depth can be arbitrarily selected, and design the encryption depth by using the double limit counting method, so the accuracy can be increased.

Quantitative Methods for Software Selection and Evaluation

National Research Council Canada - National Science Library

Bandor, Michael S

2006-01-01

... (the ability of the product to meet the need) and the cost. The method used for the analysis and selection activities can range from the use of basic intuition to counting the number of requirements fulfilled, or something...

PROBING THE ROLE OF DYNAMICAL FRICTION IN SHAPING THE BSS RADIAL DISTRIBUTION. I. SEMI-ANALYTICAL MODELS AND PRELIMINARY N-BODY SIMULATIONS

Energy Technology Data Exchange (ETDEWEB)

Miocchi, P.; Lanzoni, B.; Ferraro, F. R.; Dalessandro, E.; Alessandrini, E. [Dipartimento di Fisica e Astronomia, Università di Bologna, Viale Berti Pichat 6/2, I-40127 Bologna (Italy); Pasquato, M.; Lee, Y.-W. [Department of Astronomy and Center for Galaxy Evolution Research, Yonsei University, Seoul 120-749 (Korea, Republic of); Vesperini, E. [Department of Astronomy, Indiana University, Bloomington, IN 47405 (United States)

2015-01-20

We present semi-analytical models and simplified N-body simulations with 10{sup 4} particles aimed at probing the role of dynamical friction (DF) in determining the radial distribution of blue straggler stars (BSSs) in globular clusters. The semi-analytical models show that DF (which is the only evolutionary mechanism at work) is responsible for the formation of a bimodal distribution with a dip progressively moving toward the external regions of the cluster. However, these models fail to reproduce the formation of the long-lived central peak observed in all dynamically evolved clusters. The results of N-body simulations confirm the formation of a sharp central peak, which remains as a stable feature over time regardless of the initial concentration of the system. In spite of noisy behavior, a bimodal distribution forms in many cases, with the size of the dip increasing as a function of time. In the most advanced stages, the distribution becomes monotonic. These results are in agreement with the observations. Also, the shape of the peak and the location of the minimum (which, in most of cases, is within 10 core radii) turn out to be consistent with observational results. For a more detailed and close comparison with observations, including a proper calibration of the timescales of the dynamical processes driving the evolution of the BSS spatial distribution, more realistic simulations will be necessary.

A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

KAUST Repository

Abusamra, Heba

2013-01-01

Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

Determination of Selection Method in Genetic Algorithm for Land Suitability

Directory of Open Access Journals (Sweden)

Irfianti Asti Dwi

2016-01-01

Full Text Available Genetic Algoirthm is one alternative solution in the field of modeling optimization, automatic programming and machine learning. The purpose of the study was to compare some type of selection methods in Genetic Algorithm for land suitability. Contribution of this research applies the best method to develop region based horticultural commodities. This testing is done by comparing the three methods on the method of selection, the Roulette Wheel, Tournament Selection and Stochastic Universal Sampling. Parameters of the locations used in the test scenarios include Temperature = 27°C, Rainfall = 1200 mm, hummidity = 30%, Cluster fruit = 4, Crossover Probabiitiy (Pc = 0.6, Mutation Probabilty (Pm = 0.2 and Epoch = 10. The second test epoch incluides location parameters consist of Temperature = 30°C, Rainfall = 2000 mm, Humidity = 35%, Cluster fruit = 5, Crossover Probability (Pc = 0.7, Mutation Probability (Pm = 0.3 and Epoch 10. The conclusion of this study shows that the Roulette Wheel is the best method because it produces more stable and fitness value than the other two methods.

Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.

Science.gov (United States)

Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

2016-01-01

Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago.

Directory of Open Access Journals (Sweden)

Xiaolu Zhou

Full Text Available The growing number of bike sharing systems (BSS in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago.

Science.gov (United States)

Zhou, Xiaolu

2015-01-01

The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.

Research on filter’s parameter selection based on PROMETHEE method

Science.gov (United States)

Zhu, Hui-min; Wang, Hang-yu; Sun, Shi-yan

2018-03-01

The selection of filter’s parameters in target recognition was studied in this paper. The PROMETHEE method was applied to the optimization problem of Gabor filter parameters decision, the correspondence model of the elemental relation between two methods was established. The author took the identification of military target as an example, problem about the filter’s parameter decision was simulated and calculated by PROMETHEE. The result showed that using PROMETHEE method for the selection of filter’s parameters was more scientific. The human disturbance caused by the experts method and empirical method could be avoided by this way. The method can provide reference for the parameter configuration scheme decision of the filter.

Combining AHP and DEA Methods for Selecting a Project Manager

Directory of Open Access Journals (Sweden)

Baruch Keren

2014-07-01

Full Text Available A project manager has a major influence on the success or failure of the project. A good project manager can match between the strategy and objectives of the organization and the goals of the project. Therefore, the selection of the appropriate project manager is a key factor for the success of the project. A potential project manager is judged by his or her proven performance and personal qualifications. This paper proposes a method to calculate the weighted scores and the full rank of candidates for managing a project, and to select the best of those candidates. The proposed method combines specific methodologies: the Data Envelopment Analysis (DEA and the Analytical Hierarchical Process (AHP and uses DEA Ranking Methods to enhance selection.

Indicators for Monitoring Water, Sanitation, and Hygiene: A Systematic Review of Indicator Selection Methods

Directory of Open Access Journals (Sweden)

Stefanie Schwemlein

2016-03-01

Full Text Available Monitoring water, sanitation, and hygiene (WaSH is important to track progress, improve accountability, and demonstrate impacts of efforts to improve conditions and services, especially in low- and middle-income countries. Indicator selection methods enable robust monitoring of WaSH projects and conditions. However, selection methods are not always used and there are no commonly-used methods for selecting WaSH indicators. To address this gap, we conducted a systematic review of indicator selection methods used in WaSH-related fields. We present a summary of indicator selection methods for environment, international development, and water. We identified six methodological stages for selecting indicators for WaSH: define the purpose and scope; select a conceptual framework; search for candidate indicators; determine selection criteria; score indicators against criteria; and select a final suite of indicators. This summary of indicator selection methods provides a foundation for the critical assessment of existing methods. It can be used to inform future efforts to construct indicator sets in WaSH and related fields.

An Optimal Joint User Association and Power Allocation Algorithm for Secrecy Information Transmission in Heterogeneous Networks

Directory of Open Access Journals (Sweden)

Rong Chai

2017-01-01

Full Text Available In recent years, heterogeneous radio access technologies have experienced rapid development and gradually achieved effective coordination and integration, resulting in heterogeneous networks (HetNets. In this paper, we consider the downlink secure transmission of HetNets where the information transmission from base stations (BSs to legitimate users is subject to the interception of eavesdroppers. In particular, we stress the problem of joint user association and power allocation of the BSs. To achieve data transmission in a secure and energy efficient manner, we introduce the concept of secrecy energy efficiency which is defined as the ratio of the secrecy transmission rate and power consumption of the BSs and formulate the problem of joint user association and power allocation as an optimization problem which maximizes the joint secrecy energy efficiency of all the BSs under the power constraint of the BSs and the minimum data rate constraint of user equipment (UE. By equivalently transforming the optimization problem into two subproblems, that is, power allocation subproblem and user association subproblem of the BSs, and applying iterative method and Kuhn-Munkres (K-M algorithm to solve the two subproblems, respectively, the optimal user association and power allocation strategies can be obtained. Numerical results demonstrate that the proposed algorithm outperforms previously proposed algorithms.

Overall Bike Effectiveness as a Sustainability Metric for Bike Sharing Systems

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Bernardo Nugroho Yahya

2017-11-01

Full Text Available Bike sharing systems (BSS have been widely accepted as an urban transport scheme in many cities around the world. The concept is recently expanded and followed by many cities to offer citizen a “green” and flexible transportation scheme in urban areas. Many works focus on the issues of bike availability while the bike performance, i.e., life cycle issues and its sustainability, for better management has been abandoned. As a consequence, mismanagement of BSS would lead to cost inefficiency and, the worst case, end with operation termination. This study proposes a design science approach by developing an Overall Bike Effectiveness (OBE framework. By incorporating the concept of overall equipment analysis (OEE, the proposed framework is used to measure the bike utilization. Accordingly, the OBE is extended into Theoretical OBE to measure the sustainability of the early-stage of BSS. The framework has been verified and evaluated using a real dataset of BSS. The proposed method provides valuable results for benchmarking, life cycle analysis, system expansion and strategy planning toward sustainability. The paper concludes with a discussion to show the impact of the proposed approach into the real practices of BSS including an outlook toward sustainability of BSS.

Selective Integration in the Material-Point Method

DEFF Research Database (Denmark)

Andersen, Lars; Andersen, Søren; Damkilde, Lars

2009-01-01

The paper deals with stress integration in the material-point method. In order to avoid parasitic shear in bending, a formulation is proposed, based on selective integration in the background grid that is used to solve the governing equations. The suggested integration scheme is compared...... to a traditional material-point-method computation in which the stresses are evaluated at the material points. The deformation of a cantilever beam is analysed, assuming elastic or elastoplastic material behaviour....

Maintenance of the selected infant feeding methods amongst ...

African Journals Online (AJOL)

The focus of this study was to explore and describe influences on decision making related to infant feeding methods in the context of HIV and AIDS. Study objectives were: (1) to explore and describe the influences on decision making related to infant feeding methods selected by the mother during the antenatal period and ...

Supplier Portfolio Selection and Optimum Volume Allocation: A Knowledge Based Method

NARCIS (Netherlands)

Aziz, Romana; Aziz, R.; van Hillegersberg, Jos; Kersten, W.; Blecker, T.; Luthje, C.

2010-01-01

Selection of suppliers and allocation of optimum volumes to suppliers is a strategic business decision. This paper presents a decision support method for supplier selection and the optimal allocation of volumes in a supplier portfolio. The requirements for the method were gathered during a case

A review of methods supporting supplier selection

NARCIS (Netherlands)

de Boer, L.; Labro, Eva; Morlacchi, Pierangela

2001-01-01

this paper we present a review of decision methods reported in the literature for supporting the supplier selection process. The review is based on an extensive search in the academic literature. We position the contributions in a framework that takes the diversity of procurement situations in terms

Another non-segregated Blue Straggler population in a globular cluster: the case of NGC 2419.

Science.gov (United States)

Dalessandro, E.; Lanzoni, B.; Ferraro, F. R.; Vespe, F.; Bellazzini, M.; Rood, R. T.

We have used a combination of ACS-HST high-resolution and wide-field SUBARU data in order to study the Blue Straggler Star (BSS) population over the entire extension of the remote Galactic globular cluster NGC 2419. The radial distribution of the selected BSS is the same as that of the other cluster stars. In this sense the BSS radial distribution is like that of omega Centauri and unlike that of all Galactic globular clusters studied to date, which have highly centrally segregated distributions and in most cases a pronounced upturn in the external regions. As in the case of omega Centauri, this evidence indicates that NGC 2419 is not yet relaxed even in the central regions. This observational fact is in agreement with estimated half-mass relaxation time, which is of the order of the cluster age.

Evaluation of selection methods for toxicological impacts in LCA. Recommendations for OMNIITOX

DEFF Research Database (Denmark)

Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

2004-01-01

selection methods. Conclusion and Recommendations. For the development of SMs it is recommended that the general principles for CRS systems as applied to SMs are taken into account. Furthermore, special attention should be paid to some specific issues, i.e. the emitted amount should be included, data......Goal, Scope and Background. The aim of this study has been to come up with recommendations on how to develop a selection method (SM) within the method development research of the OMNIITOX project. An SM is a method for prioritization of chemical emissions to be included in a Life Cycle Impact...... categories, and when they do there are typically many gaps. This study covers the only existing methods explicitly designed as SMs (EDIP-selection, Priofactor and CPM-selection), the dominating Chemical Ranking and Scoring (CRS) method in Europe (EURAM) and in USA (WMPT) that can be adapted for this purpose...

Selected Tools and Methods from Quality Management Field

Directory of Open Access Journals (Sweden)

Kateřina BRODECKÁ

2009-06-01

Full Text Available Following paper describes selected tools and methods from Quality management field and their practical applications on defined examples. Solved examples were elaborated in the form of electronic support. This in detail elaborated electronic support provides students opportunity to thoroughly practice specific issues, help them to prepare for exams and consequently will lead to education improvement. Especially students of combined study form will appreciate this support. The paper specifies project objectives, subjects that will be covered by mentioned support, target groups, structure and the way of elaboration of electronic exercise book in view. The emphasis is not only on manual solution of selected examples that may help students to understand the principles and relationships, but also on solving and results interpreting of selected examples using software support. Statistic software Statgraphics Plus v 5.0 is used while working support, because it is free to use for all students of the faculty. Exemplary example from the subject Basic Statistical Methods of Quality Management is also part of this paper.

A survey of variable selection methods in two Chinese epidemiology journals

Directory of Open Access Journals (Sweden)

Lynn Henry S

2010-09-01

Full Text Available Abstract Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163 via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44% used stepwise procedures, 89 (41% tested individual regression coefficients, but 33 (15% did not mention how variables were selected. Sixty percent (58/97 of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals.

The Preparation and Selection of Budget Methods for Promotion in Kosovo

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MSc. Halit Karaxha

2017-06-01

Full Text Available Selecting the adequate method for promotion has a huge importance in increasing business’s performance. Selecting the method of the budget depends from a number of factors. The formulation of budget is known as the most critical period which requires special analysis from marketing’s managers. The expenses for promotion are usually high, and every investment made in the field of promotion directly influences in the business situation. Thus, the selection and adequate formulation of budget methods for promotion influences the growth of profit. The allocated amount for promotion depends from a number of factors, such as: the size of the firm, the sector in which it operates, competition etc. After planning the budget, we have to do the budget allocation to select the promotional form which is considered to be successful by the firms in promoting the products and services and that will help the company to connect with its clients. In this paper, I have elaborated the role and importance of the preparation and selection of budget methods for promotion in the theoretical aspect and the practical one as well.

The Choice Method of Selected Material has influence single evaporation flash method

International Nuclear Information System (INIS)

Sunaryo, Geni Rina; Sumijanto; Nurul L, Siti

2000-01-01

The final objective of this research is to design the mini scale of desalination installation. It has been started from 1997/1998 and has been doing for this 3 years. Where the study on the assessment of various desalination system has been done in the first year and thermodynamic in the second year. In this third year, literatully study on material resistance from outside pressure has been done. The number of pressure for single evaporator flashing method is mainly depend on the temperature that applied in that system. In this paper, the configuration stage, the choice method of selecting material for main evaporator vessel, tube, tube plates, water boxes, pipework, and valves for multistage flash distillation will be described. The choice of selecting material for MSF is base on economical consideration, cheap, high resistance and easy to be maintained

Personnel Selection Method Based on Personnel-Job Matching

OpenAIRE

Li Wang; Xilin Hou; Lili Zhang

2013-01-01

The existing personnel selection decisions in practice are based on the evaluation of job seeker's human capital, and it may be difficult to make personnel-job matching and make each party satisfy. Therefore, this paper puts forward a new personnel selection method by consideration of bilateral matching. Starting from the employment thoughts of ¡°satisfy¡±, the satisfaction evaluation indicator system of each party are constructed. The multi-objective optimization model is given according to ...

Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method

Directory of Open Access Journals (Sweden)

Mohammad Panahi Borujeni

2017-01-01

Full Text Available The increasing complexity surrounding decision-making situations has made it inevitable for practitioners to apply ideas from a group of experts or decision makers (DMs instead of individuals. In a large proportion of recent studies, not enough attention has been paid to considering uncertainty in practical ways. In this paper, a hesitant fuzzy preference selection index (HFPSI method is proposed based on a new soft computing approach with risk preferences of DMs to deal with imprecise multi-criteria decision-making problems. Meanwhile, qualitative assessing criteria are considered in the process of the proposed method to help the DMs by providing suitable expressions of membership degrees for an element under a set. Moreover, the best alternative is selected based on considering the concepts of preference relation and hesitant fuzzy sets, simultaneously. Therefore, DMs' weights are determined according to the proposed hesitant fuzzy compromise solution technique to prevent judgment errors. Moreover, the proposed method has been extended based on the last aggregation method by aggregating the DMs' opinions during the last stage to avoid data loss. In this respect, a real case study about the mining contractor selection problem is provided to represent the effectiveness and efficiency of the proposed HFPSI method in practice. Then, a comparative analysis is performed to show the feasibility of the presented approach. Finally, sensitivity analysis is carried out to show the effect of considering the DMs' weights and last aggregation approach in a dispersion of the alternatives’ ranking values.

GREY STATISTICS METHOD OF TECHNOLOGY SELECTION FOR ADVANCED PUBLIC TRANSPORTATION SYSTEMS

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Chien Hung WEI

2003-01-01

Full Text Available Taiwan is involved in intelligent transportation systems planning, and is now selecting its prior focus areas for investment and development. The high social and economic impact associated with which intelligent transportation systems technology are chosen explains the efforts of various electronics and transportation corporations for developing intelligent transportation systems technology to expand their business opportunities. However, there has been no detailed research conducted with regard to selecting technology for advanced public transportation systems in Taiwan. Thus, the present paper demonstrates a grey statistics method integrated with a scenario method for solving the problem of selecting advanced public transportation systems technology for Taiwan. A comprehensive questionnaire survey was conducted to demonstrate the effectiveness of the grey statistics method. The proposed approach indicated that contactless smart card technology is the appropriate technology for Taiwan to develop in the near future. The significance of our research results implies that the grey statistics method is an effective method for selecting advanced public transportation systems technologies. We feel our information will be beneficial to the private sector for developing an appropriate intelligent transportation systems technology strategy.

Toward optimal feature selection using ranking methods and classification algorithms

Directory of Open Access Journals (Sweden)

Novaković Jasmina

2011-01-01

Full Text Available We presented a comparison between several feature ranking methods used on two real datasets. We considered six ranking methods that can be divided into two broad categories: statistical and entropy-based. Four supervised learning algorithms are adopted to build models, namely, IB1, Naive Bayes, C4.5 decision tree and the RBF network. We showed that the selection of ranking methods could be important for classification accuracy. In our experiments, ranking methods with different supervised learning algorithms give quite different results for balanced accuracy. Our cases confirm that, in order to be sure that a subset of features giving the highest accuracy has been selected, the use of many different indices is recommended.

METHOD FOR SELECTION OF PROJECT MANAGEMENT APPROACH BASED ON FUZZY CONCEPTS

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Igor V. KONONENKO

2017-03-01

Full Text Available Literature analysis of works that devoted to research of the selection a project management approach and development of effective methods for this problem solution is given. Mathematical model and method for selection of project management approach with fuzzy concepts of applicability of existing approaches are proposed. The selection is made of such approaches as the PMBOK Guide, the ISO21500 standard, the PRINCE2 methodology, the SWEBOK Guide, agile methodologies Scrum, XP, and Kanban. The number of project parameters which have a great impact on the result of the selection and measure of their impact is determined. Project parameters relate to information about the project, team, communication, critical project risks. They include the number of people involved in the project, the customer's experience with this project team, the project team's experience in this field, the project team's understanding of requirements, adapting ability, initiative, and others. The suggested method is considered on the example of its application for selection a project management approach to software development project.

Traditional and robust vector selection methods for use with similarity based models

International Nuclear Information System (INIS)

Hines, J. W.; Garvey, D. R.

2006-01-01

Vector selection, or instance selection as it is often called in the data mining literature, performs a critical task in the development of nonparametric, similarity based models. Nonparametric, similarity based modeling (SBM) is a form of 'lazy learning' which constructs a local model 'on the fly' by comparing a query vector to historical, training vectors. For large training sets the creation of local models may become cumbersome, since each training vector must be compared to the query vector. To alleviate this computational burden, varying forms of training vector sampling may be employed with the goal of selecting a subset of the training data such that the samples are representative of the underlying process. This paper describes one such SBM, namely auto-associative kernel regression (AAKR), and presents five traditional vector selection methods and one robust vector selection method that may be used to select prototype vectors from a larger data set in model training. The five traditional vector selection methods considered are min-max, vector ordering, combination min-max and vector ordering, fuzzy c-means clustering, and Adeli-Hung clustering. Each method is described in detail and compared using artificially generated data and data collected from the steam system of an operating nuclear power plant. (authors)

Selective saturation method for EPR dosimetry with tooth enamel

International Nuclear Information System (INIS)

Ignatiev, E.A.; Romanyukha, A.A.; Koshta, A.A.; Wieser, A.

1996-01-01

The method of selective saturation is based on the difference in the microwave (mw) power dependence of the background and radiation induced EPR components of the tooth enamel spectrum. The subtraction of the EPR spectrum recorded at low mw power from that recorded at higher mw power provides a considerable reduction of the background component in the spectrum. The resolution of the EPR spectrum could be improved 10-fold, however simultaneously the signal-to-noise ratio was found to be reduced twice. A detailed comparative study of reference samples with known absorbed doses was performed to demonstrate the advantage of the method. The application of the selective saturation method for EPR dosimetry with tooth enamel reduced the lower limit of EPR dosimetry to about 100 mGy. (author)

A new DEA-GAHP method for supplier selection problem

Directory of Open Access Journals (Sweden)

Behrooz Ahadian

2012-10-01

Full Text Available Supplier selection is one of the most important decisions made in supply chain management. Supplier evaluation problem has been in the center of supply chain researcher’s attention in these years. Managers regard some of these studies and methods inappropriate due to simple, weight scoring methods that generally are based on subjective opinions and judgments of decision maker units involved in the supplier evaluation process yielding imprecise and even unreliable results. This paper seeks to propose a methodology to integrate data envelopment analysis (DEA and group analytical hierarchy process (GAHP for evaluating and selecting the most efficient supplier. We develop a methodology, which consists of 6 steps, one by one has been introduced in lecture and finally applicability of proposed method is indicated by assessing 12 suppliers in a numerical example.

An iterative method for selecting degenerate multiplex PCR primers.

Science.gov (United States)

Souvenir, Richard; Buhler, Jeremy; Stormo, Gary; Zhang, Weixiong

2007-01-01

Single-nucleotide polymorphism (SNP) genotyping is an important molecular genetics process, which can produce results that will be useful in the medical field. Because of inherent complexities in DNA manipulation and analysis, many different methods have been proposed for a standard assay. One of the proposed techniques for performing SNP genotyping requires amplifying regions of DNA surrounding a large number of SNP loci. To automate a portion of this particular method, it is necessary to select a set of primers for the experiment. Selecting these primers can be formulated as the Multiple Degenerate Primer Design (MDPD) problem. The Multiple, Iterative Primer Selector (MIPS) is an iterative beam-search algorithm for MDPD. Theoretical and experimental analyses show that this algorithm performs well compared with the limits of degenerate primer design. Furthermore, MIPS outperforms an existing algorithm that was designed for a related degenerate primer selection problem.

Rate of Post-traumatic Endophthalmitis with or without Injection of Balanced Salt Solution

Directory of Open Access Journals (Sweden)

Nasrin Rafati

2013-01-01

Full Text Available Purpose: In a study complementing a previous multicenter randomized clinical trial on prophylactic injection of intraocular antibiotics during primary repair of penetrating eye injuries (PEIs, we sought to determine whether needle entrance and injection of balanced salt solution (BSS, per se, could increase the rate of acute post-traumatic bacterial endophthalmitis (APBE. Methods: Patients randomized to the BSS injection arm (n=167 of the Traumatic Endophthalmitis Trial, and eligible patients who had refused enrollment and received no intraocular injections during primary repair (n=111 were compared for the development of APBE. Results: APBE occurred in 8 of 167 (4.8% eyes in the BSS group and in 5 of 111 (4.5% eyes in the non-injection group (P=0.91. Retained intraocular foreign bodies were present in 46 eyes including 25 (15% eyes in the BSS injection group and 21 (18.9% eyes in the non-injection group (P=0.38. Logistic regression analysis showed no significant difference between BSS injected and non-injected eyes in terms of APBE (P=0.69. However, the presence of intraocular foreign bodies was strongly associated with the risk of endophthalmitis (P<0.001, OR=14.1, 95% CI: 4.1-48.5. Conclusion: Needle entrance and intraocular injection of BSS during primary repair of PEIs does not increase the risk of APBE.

Evaluation of the small intestinal submucosa covered stent in preventing restenosis after percutaneous transluminal angioplasty in the swine

International Nuclear Information System (INIS)

Wang Xiaobai; Li Jinglei; Zhang Hong; Zhang Yan

2012-01-01

Objective: To compare the performance of small intestinal submucosa (SIS)-covered endografts (SCEs) to bare nitinol stents (BSs) in injured swine iliac arteries. Materials and methods: Twenty-eight nitinol stents were used: 14 externally SCEs and 14 BSs. Devices were implanted in each side of balloon-injured external iliac arteries of 14 swine via carotid approach. Arteriograms were obtained before and after implantation and before animal sacrifice at 4, 8, and 12 weeks. Histopathological and electron microscopy studies of explanted specimens were performed. Results: Implantation of all SCEs and BSs was technically successful, but one SCE and one BS were obstructed at 8 weeks after implantation. At sacrifice, the other 26 stents were patent, with angiogram showing no significant different luminal narrowing between SCEs and BSs. Proliferating cell nuclear antigen (PCNA) immunohistochemistry examination revealed that the percentage of PCNA(+) cells were lower in SCEs (p < 0.05). Additionally, histomorphological analysis indicated that the neointima area and percentage of narrowing area were greater in SCEs, but there was no statistical significance. Greater endothelial cell count in SCEs than in BSs per visual field at 4000 times magnification by scanning electron microscope (p < 0.05). Conclusion: Compared to BSs, no definite decrease of neointima and restenosis was found in SCEs in the present study. However, it is effective in promoting endothelial regeneration and strengthening endothelial function.

Selective adsorption-desorption method for the enrichment of krypton

International Nuclear Information System (INIS)

Yuasa, Y.; Ohta, M.; Watanabe, A.; Tani, A.; Takashima, N.

1975-01-01

Selective adsorption-desorption method has been developed as an effective means of enriching krypton and xenon gases. A seriesof laboratory-scale tests were performed to provide some basic data of the method when applied to off-gas streams of nuclear power plants. For the first step of the enrichment process of the experiments, krypton was adsorbed on solid adsorbents from dilute mixtures with air at temperatures ranging from -50 0 C to -170 0 C. After the complete breakthrough was obtained, the adsorption bed was evacuated at low temperature by a vacuum pump. By combining these two steps krypton was highly enriched on the adsorbents, and the enrichment factor for krypton was calculated as the product of individual enrichment factors of each step. Two types of adsorbents, coconut charcoal and molecular sieves 5A, were used. Experimental results showed that the present method gave the greater enrichment factor than the conventional method which used selective adsorption step only. (U.S.)

Personnel selection using group fuzzy AHP and SAW methods

Directory of Open Access Journals (Sweden)

Ali Reza Afshari

2017-01-01

Full Text Available Personnel evaluation and selection is a very important activity for the enterprises. Different job needs different ability and the requirement of criteria which can measure ability is different. It needs a suitable and flexible method to evaluate the performance of each candidate according to different requirements of different jobs in relation to each criterion. Analytic Hierarchy Process (AHP is one of Multi Criteria decision making methods derived from paired comparisons. Simple Additive Weighting (SAW is most frequently used multi attribute decision technique. The method is based on the weighted average. It successfully models the ambiguity and imprecision associated with the pair wise comparison process and reduces the personal biasness. This study tries to analyze the Analytic Hierarchy Process in order to make the recruitment process more reasonable, based on the fuzzy multiple criteria decision making model to achieve the goal of personnel selection. Finally, an example is implemented to demonstrate the practicability of the proposed method.

Blind Source Separation Algorithms Using Hyperbolic and Givens Rotations for High-Order QAM Constellations

KAUST Repository

Shah, Syed Awais Wahab

2017-11-24

This paper addresses the problem of blind demixing of instantaneous mixtures in a multiple-input multiple-output communication system. The main objective is to present efficient blind source separation (BSS) algorithms dedicated to moderate or high-order QAM constellations. Four new iterative batch BSS algorithms are presented dealing with the multimodulus (MM) and alphabet matched (AM) criteria. For the optimization of these cost functions, iterative methods of Givens and hyperbolic rotations are used. A pre-whitening operation is also utilized to reduce the complexity of design problem. It is noticed that the designed algorithms using Givens rotations gives satisfactory performance only for large number of samples. However, for small number of samples, the algorithms designed by combining both Givens and hyperbolic rotations compensate for the ill-whitening that occurs in this case and thus improves the performance. Two algorithms dealing with the MM criterion are presented for moderate order QAM signals such as 16-QAM. The other two dealing with the AM criterion are presented for high-order QAM signals. These methods are finally compared with the state of art batch BSS algorithms in terms of signal-to-interference and noise ratio, symbol error rate and convergence rate. Simulation results show that the proposed methods outperform the contemporary batch BSS algorithms.

Blind Source Separation Algorithms Using Hyperbolic and Givens Rotations for High-Order QAM Constellations

KAUST Repository

Shah, Syed Awais Wahab; Abed-Meraim, Karim; Al-Naffouri, Tareq Y.

2017-01-01

This paper addresses the problem of blind demixing of instantaneous mixtures in a multiple-input multiple-output communication system. The main objective is to present efficient blind source separation (BSS) algorithms dedicated to moderate or high-order QAM constellations. Four new iterative batch BSS algorithms are presented dealing with the multimodulus (MM) and alphabet matched (AM) criteria. For the optimization of these cost functions, iterative methods of Givens and hyperbolic rotations are used. A pre-whitening operation is also utilized to reduce the complexity of design problem. It is noticed that the designed algorithms using Givens rotations gives satisfactory performance only for large number of samples. However, for small number of samples, the algorithms designed by combining both Givens and hyperbolic rotations compensate for the ill-whitening that occurs in this case and thus improves the performance. Two algorithms dealing with the MM criterion are presented for moderate order QAM signals such as 16-QAM. The other two dealing with the AM criterion are presented for high-order QAM signals. These methods are finally compared with the state of art batch BSS algorithms in terms of signal-to-interference and noise ratio, symbol error rate and convergence rate. Simulation results show that the proposed methods outperform the contemporary batch BSS algorithms.

ALIS-FLP: Amplified ligation selected fragment-length polymorphism method for microbial genotyping

DEFF Research Database (Denmark)

Brillowska-Dabrowska, A.; Wianecka, M.; Dabrowski, Slawomir

2008-01-01

A DNA fingerprinting method known as ALIS-FLP (amplified ligation selected fragment-length polymorphism) has been developed for selective and specific amplification of restriction fragments from TspRI restriction endonuclease digested genomic DNA. The method is similar to AFLP, but differs...

Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

Directory of Open Access Journals (Sweden)

Rasim M. Alguliyev

2015-01-01

Full Text Available Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method.

Anomalous Cepheids and population II blue stragglers

Science.gov (United States)

Nemec, James M.

Recent studies of anomalous Cepheids (ACs) and population II blue stragglers (BSs), including photometrically variable BSs (VBSs), are reviewed. The VBSs represent about 25 percent of the BSs, the majority of which are SX Phe short-period variables in the Cepheid instability strip. Mass estimates derived using various techniques suggest that both ACs and BSs are relatively massive (about 1.0-1.6 solar mass). The recent discovery that two BSs in the globular cluster NGC 5466 are contact binaries, and the earlier discovery that one of the BSs in Omega Cen is an eclipsing binary, provide direct evidence that at least some BSs are binary systems.

A Fast Adaptive Receive Antenna Selection Method in MIMO System

Directory of Open Access Journals (Sweden)

Chaowei Wang

2013-01-01

Full Text Available Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

Analytical modeling of mode selection and power control for underlay D2D communication in cellular networks

KAUST Repository

Elsawy, Hesham; Hossain, Ekram; Alouini, Mohamed-Slim

2014-01-01

Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D

A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

KAUST Repository

Abusamra, Heba

2013-05-01

Microarray technology has enriched the study of gene expression in such a way that scientists are now able to measure the expression levels of thousands of genes in a single experiment. Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification, interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This thesis aims on a comparative study of state-of-the-art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k- nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t- statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used for this study. Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in

Development, effectiveness and cost-effectiveness of a new out-patient Breathlessness Support Service: study protocol of a phase III fast-track randomised controlled trial

Directory of Open Access Journals (Sweden)

Bausewein Claudia

2012-09-01

Full Text Available Abstract Background Breathlessness is a common and distressing symptom affecting many patients with advanced disease both from malignant and non-malignant origin. A combination of pharmacological and non-pharmacological measures is necessary to treat this symptom successfully. Breathlessness services in various compositions aim to provide comprehensive care for patients and their carers by a multiprofessional team but their effectiveness and cost-effectiveness have not yet been proven. The Breathlessness Support Service (BSS is a newly created multiprofessional and interdisciplinary outpatient service at a large university hospital in South East London. The aim of this study is to develop and evaluate the effectiveness and cost effectiveness of this multidisciplinary out–patient BSS for the palliation of breathlessness, in advanced malignant and non-malignant disease. Methods The BSS was modelled based on the results of qualitative and quantitative studies, and systematic literature reviews. A randomised controlled fast track trial (RCT comprising two groups: 1 intervention (immediate access to BSS in addition to standard care; 2 control group (standard best practice and access to BSS after a waiting time of six weeks. Patients are included if suffering from breathlessness on exertion or at rest due to advanced disease such as cancer, chronic obstructive pulmonary disease (COPD, chronic heart failure (CHF, interstitial lung disease (ILD or motor neurone disease (MND that is refractory to maximal optimised medical management. Both quantitative and qualitative outcomes are assessed in face to-face interviews at baseline, after 6 and 12 weeks. The primary outcome is patients' improvement of mastery of breathlessness after six weeks assessed on the Chronic Respiratory Disease Questionnaire (CRQ. Secondary outcomes for patients include breathlessness severity, symptom burden, palliative care needs, service use, and respiratory measures (spirometry

Some selected quantitative methods of thermal image analysis in Matlab.

Science.gov (United States)

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data

Directory of Open Access Journals (Sweden)

Lijun Wang

2013-01-01

Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.

Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking

Directory of Open Access Journals (Sweden)

Hiekata Takashi

2006-01-01

Full Text Available A new two-stage blind source separation (BSS method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO-model-based independent component analysis (ICA and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.

Validation of Passive Sampling Devices for Monitoring of Munitions Constituents in Underwater Environments

Science.gov (United States)

2017-09-01

TNT TOC TSS Low Order Detonation Munitions constituents Munitions Debris Method Detection Limit Munitions and explosives of concern Mean low...Total organic carbon ( TOC ) and grain size distribution from stations A1, T10, T11, and T12 at BSS...16 syringes/stn) TNT, ADNTs, DNTs, RDX 4 locations in BSS based on positive POCIS results Sediment 5 TOC , grain size 4, co-located with sediment

FORMATION AND EVOLUTION OF BLUE STRAGGLERS IN 47 TUCANAE

Energy Technology Data Exchange (ETDEWEB)

Parada, Javiera; Richer, Harvey; Heyl, Jeremy; Goldsbury, Ryan [Department of Physics and Astronomy, University of British Columbia, Vancouver, BC V6T 1Z1 (Canada); Kalirai, Jason, E-mail: jparada@phas.ubc.ca, E-mail: heyl@phas.ubc.ca, E-mail: richer@astro.ubc.ca, E-mail: jkalirai@stsci.edu [Space Telescope Science Institute, Baltimore, MD 21218 (United States)

2016-10-20

Blue stragglers (BSS) are stars whose position in the color–magnitude diagram (CMD) places them above the main sequence (MS) turn-off (TO) point of a star cluster. Using data from the core of 47 Tuc in the ultraviolet (UV), we have identified various stellar populations in the CMD, and used their radial distributions to study the evolution and origin of BSS, and obtain a dynamical estimate of the mass of BSS systems. When we separate the BSS into two samples by their magnitude, we find that the bright BSS show a much more centrally concentrated radial distribution and thus higher mass estimate (over twice the TO mass for these BSS systems), suggesting an origin involving triple or multiple stellar systems. In contrast, the faint BSS are less concentrated, with a radial distribution similar to the MS binaries, pointing to the MS binaries as the likely progenitors of these BSS. Putting our data together with available photometric data in the visible and using MESA evolutionary models, we calculate the expected number of stars in each evolutionary stage for the normal evolution of stars and the number of stars coming from the evolution of BSS. The results indicate that BSS have a post-MS evolution comparable to that of a normal star of the same mass and a MS BSS lifetime of about 200–300 Myr. We also find that the excess population of asymptotic giant branch stars in 47 Tuc is due to evolved BSS.

Quantitative sacroiliac scintigraphy. The effect of method of selection of region of interest

International Nuclear Information System (INIS)

Davis, M.C.; Turner, D.A.; Charters, J.R.; Golden, H.E.; Ali, A.; Fordham, E.W.

1984-01-01

Various authors have advocated quantitative methods of evaluating bone scintigrams to detect sacroiliitis, while others have not found them useful. Many explanations for this disagreement have been offered, including differences in the method of case selection, ethnicity, gender, and previous drug therapy. It would appear that one of the most important impediments to consistent results is the variability of selecting sacroiliac joint and reference regions of interest (ROIs). The effect of ROI selection would seem particularly important because of the normal variability of radioactivity within the reference regions that have been used (sacrum, spine, iliac wing) and the inhomogeneity of activity in the SI joints. We have investigated the effect of ROI selection, using five different methods representative of, though not necessarily identical to, those found in the literature. Each method produced unique mean indices that were different for patients with ankylosing spondylitis (AS) and controls. The method of Ayres (19) proved superior (largest mean difference, smallest variance), but none worked well as a diagnostic tool because of substantial overlap of the distributions of indices of patient and control groups. We conclude that ROI selection is important in determining results, and quantitative scintigraphic methods in general are not effective tools for diagnosing AS. Among the possible factors limiting success, difficulty in selecting a stable reference area seems of particular importance

Selecting device for processing method of radioactive gaseous wastes

International Nuclear Information System (INIS)

Sasaki, Ryoichi; Komoda, Norihisa.

1976-01-01

Object: To extend the period of replacement of a filter for adsorbing radioactive material by discharging waste gas containing radioactive material produced from an atomic power equipment after treating it by a method selected on the basis of the results of measurement of wind direction. Structure: Exhaust gas containing radioactive material produced from atomic power equipment is discharged after it is treated by a method selected on the basis of the results of wind direction measurement. For Instance, in case of sea wind the waste gas passes through a route selected for this case and is discharged through the waste gas outlet. When the sea wind disappears (that is, when a land wind or calm sets in), the exhaust gas is switched to a route for the case other than that of the sea wind, so that it passes through a filter consisting of active carbon where the radioactive material is removed through adsorption. The waste gas now free from the radioactive material is discharged through the waste gas outlet. (Moriyama, K.)

Method for Selection of Solvents for Promotion of Organic Reactions

DEFF Research Database (Denmark)

Gani, Rafiqul; Jiménez-González, Concepción; Constable, David J.C.

2005-01-01

is to produce, for a given reaction, a short list of chemicals that could be considered as potential solvents, to evaluate their performance in the reacting system, and, based on this, to rank them according to a scoring system. Several examples of application are given to illustrate the main features and steps......A method to select appropriate green solvents for the promotion of a class of organic reactions has been developed. The method combines knowledge from industrial practice and physical insights with computer-aided property estimation tools for selection/design of solvents. In particular, it employs...... estimates of thermodynamic properties to generate a knowledge base of reaction, solvent and environment related properties that directly or indirectly influence the rate and/or conversion of a given reaction. Solvents are selected using a rules-based procedure where the estimated reaction-solvent properties...

Integral planning of new components and production methods for BSS installations

OpenAIRE

Bárcena, C.; Sánchez Labrador, R.; Segarra Martinez, M.J.; Smith, M.; Martin, D.; Gimenez, A.; Balaguer, C.; Kessoudis, K.; Schimpf, Sven

2009-01-01

In today's manufacturing world, there are many challenges to face such as globalisation, reduced lead times, reduced costs, environmental demands etc. These trends currently being applied or studied in production are being assessed to be developed in the construction industry. The I3CON project has the vision of an "integrated, intelligent and industrialised system", with very ambitious aims. This is a real challenge for construction manufacturers, who should profit from principles adopted in...

Method for hydrometallurgical recovery of selected metals

International Nuclear Information System (INIS)

Lorenz, G.; Schaefer, B.; Balzat, W.

1988-01-01

The method for hydrometallurgical recovery of selected metals refers to ore dressing by means of milling and alkaline leaching of metals, preferably uranium. By adding CaO during wet milling, Na + or K + ions of clayey ores are replaced by Ca 2+ ions. Due to the ion exchange processes, the uranium bonded with clays becomes more accessible to the leaching solution. The uranium yield increases and the consumption of reagents decreases

Bismuth subsalicylate nanoparticles with anaerobic antibacterial activity for dental applications

Science.gov (United States)

Vega-Jiménez, A. L.; Almaguer-Flores, A.; Flores-Castañeda, M.; Camps, E.; Uribe-Ramírez, M.; Aztatzi-Aguilar, O. G.; De Vizcaya-Ruiz, A.

2017-10-01

In recent years, nanomaterials have been used in the medical-dental field as new alternative antimicrobial agents. Bismuth subsalicylate (BSS) has been used as an antimicrobial agent, but the effect of BSS in the form of nanoparticles (BSS-nano) as a potential antimicrobial agent has not been tested, in specific against bacteria responsible for periodontal disease. The aim of this study was to evaluate the antibacterial effect of BSS-nano against oral anaerobic bacteria and to assess the safety of BSS-nano by evaluating their cytotoxicity in human gingival fibroblast (HGF-1) cells. BSS-nano were synthesized by laser ablation and were previously physico-chemically characterized using in vitro assays. The antibacterial activity was measured using the tetrazolium-based XTT assay, and cytotoxicity was determined using lactate dehydrogenase (LDH) and MTS assays in HGF-1 cells. Transmission electron microscopy of HGF-1 exposed to BSS-nano was also performed. BSS-nano was shown to have a primary size of 4-22 nm and a polygonal shape. Among the tested bacterial strains, those with a greater sensitivity to BSS-nano (highest concentration of 21.7 μg ml-1) were A. actinomycetemcomitans, C. gingivalis, and P. gingivalis. BSS-nano at a concentration of 60 μg ml-1 showed low cytotoxicity (6%) in HFG-1 cells and was mainly localized intracellularly in acidic vesicles. Our results indicate that the concentration of BSS-nano used as an effective antibacterial agent does not induce cytotoxicity in mammalian cells; thus, BSS-nano can be applied as an antibacterial agent in dental materials or antiseptic solutions.

Experiences gained from implementing mandatory buffer strips in Denmark: how can we enhance their ecosystem services?

Science.gov (United States)

Kronvang, Brian; Hoffmann, Carl Christian; Baattrup-Pedersen, Annette; Hille, Sandra; Rubæk, Gitte; Heckrath, Goswin; Gertz, Flemming; Jensen, Henning; Feuerback, Peter; Strand, John; Stutter, Marc

2015-04-01

along watercourses from ca. 50,000 ha to ca. 25,000 ha and at the same time they reduced the width of the mandatory BSs from 10 m to 9 m. The aim of this presentation is to share the experience gained in Denmark on establishing mandatory BSs. Furthermore, we will show some preliminary results from two newly initiated research projects (BUFFERTECH and BALTICSEA2020) that studies how to enhance the ecosystem services provided by buffer strips. We will show how intelligently to guide managers when establishing BSs along watercourses at catchment scale utilizing a combined P-index model for soil erosion and a statistical model for P retention in BSs as well as results obtained from new 'Engineered' or 'Constructed' BSs that delays tile drainage flow from field to streams thereby increasing nutrient retention. Acknowledgement The work is supported by the Strategic Research Foundation/Innovation Fund Denmark project 'BUFFERTECH - Optimization of Ecosystem Services Provided by Buffer Strips Using Novel Technological Methods' (Grant No. 1305-00017B) and the BalticSea2020 project 'Integrerade skyddszoner (IBZ)'.

Analysis of the Decoupled Access for Downlink and Uplink in Wireless Heterogeneous Networks

DEFF Research Database (Denmark)

Smiljkovikj, K.; Popovski, Petar; Gavrilovska, L.

2015-01-01

Wireless cellular networks evolve towards a heterogeneous infrastructure, featuring multiple types of Base Stations (BSs), such as Femto BSs (FBSs) and Macro BSs (MBSs). A wireless device observes multiple points (BSs) through which it can access the infrastructure and it may choose to receive th...

Preparation of Iron Nanoparticles by Selective Leaching Method

Czech Academy of Sciences Publication Activity Database

Michalcová, A.; Vojtěch, D.; Kubatík, Tomáš František; Stehlíková, K.; Brabec, F.; Marek, I.

2015-01-01

Roč. 128, č. 4 (2015), s. 640-642 ISSN 0587-4246. [International Symposium on Physics of Materials (ISPMA) /13./. Prague, 31.08.2014-04.09.2014] Institutional support: RVO:61389021 Keywords : Iron nanoparticles * selective leaching method Subject RIV: JK - Corrosion ; Surface Treatment of Materials Impact factor: 0.525, year: 2015

Selecting and Using Mathematics Methods Texts: Nontrivial Tasks

Science.gov (United States)

Harkness, Shelly Sheats; Brass, Amy

2017-01-01

Mathematics methods textbooks/texts are important components of many courses for preservice teachers. Researchers should explore how these texts are selected and used. Within this paper we report the findings of a survey administered electronically to 132 members of the Association of Mathematics Teacher Educators (AMTE) in order to answer the…

Enhanced individual selection for selecting fast growing fish: the "PROSPER" method, with application on brown trout (Salmo trutta fario

Directory of Open Access Journals (Sweden)

Vandeputte Marc

2004-11-01

Full Text Available Abstract Growth rate is the main breeding goal of fish breeders, but individual selection has often shown poor responses in fish species. The PROSPER method was developed to overcome possible factors that may contribute to this low success, using (1 a variable base population and high number of breeders (Ne > 100, (2 selection within groups with low non-genetic effects and (3 repeated growth challenges. Using calculations, we show that individual selection within groups, with appropriate management of maternal effects, can be superior to mass selection as soon as the maternal effect ratio exceeds 0.15, when heritability is 0.25. Practically, brown trout were selected on length at the age of one year with the PROSPER method. The genetic gain was evaluated against an unselected control line. After four generations, the mean response per generation in length at one year was 6.2% of the control mean, while the mean correlated response in weight was 21.5% of the control mean per generation. At the 4th generation, selected fish also appeared to be leaner than control fish when compared at the same size, and the response on weight was maximal (≈130% of the control mean between 386 and 470 days post fertilisation. This high response is promising, however, the key points of the method have to be investigated in more detail.

A comparison of statistical methods for genomic selection in a mice population

Directory of Open Access Journals (Sweden)

Neves Haroldo HR

2012-11-01

Full Text Available Abstract Background The availability of high-density panels of SNP markers has opened new perspectives for marker-assisted selection strategies, such that genotypes for these markers are used to predict the genetic merit of selection candidates. Because the number of markers is often much larger than the number of phenotypes, marker effect estimation is not a trivial task. The objective of this research was to compare the predictive performance of ten different statistical methods employed in genomic selection, by analyzing data from a heterogeneous stock mice population. Results For the five traits analyzed (W6W: weight at six weeks, WGS: growth slope, BL: body length, %CD8+: percentage of CD8+ cells, CD4+/ CD8+: ratio between CD4+ and CD8+ cells, within-family predictions were more accurate than across-family predictions, although this superiority in accuracy varied markedly across traits. For within-family prediction, two kernel methods, Reproducing Kernel Hilbert Spaces Regression (RKHS and Support Vector Regression (SVR, were the most accurate for W6W, while a polygenic model also had comparable performance. A form of ridge regression assuming that all markers contribute to the additive variance (RR_GBLUP figured among the most accurate for WGS and BL, while two variable selection methods ( LASSO and Random Forest, RF had the greatest predictive abilities for %CD8+ and CD4+/ CD8+. RF, RKHS, SVR and RR_GBLUP outperformed the remainder methods in terms of bias and inflation of predictions. Conclusions Methods with large conceptual differences reached very similar predictive abilities and a clear re-ranking of methods was observed in function of the trait analyzed. Variable selection methods were more accurate than the remainder in the case of %CD8+ and CD4+/CD8+ and these traits are likely to be influenced by a smaller number of QTL than the remainder. Judged by their overall performance across traits and computational requirements, RR

Blind source separation based on time-frequency morphological characteristics for rigid acoustic scattering by underwater objects

Science.gov (United States)

Yang, Yang; Li, Xiukun

2016-06-01

Separation of the components of rigid acoustic scattering by underwater objects is essential in obtaining the structural characteristics of such objects. To overcome the problem of rigid structures appearing to have the same spectral structure in the time domain, time-frequency Blind Source Separation (BSS) can be used in combination with image morphology to separate the rigid scattering components of different objects. Based on a highlight model, the separation of the rigid scattering structure of objects with time-frequency distribution is deduced. Using a morphological filter, different characteristics in a Wigner-Ville Distribution (WVD) observed for single auto term and cross terms can be simplified to remove any cross-term interference. By selecting time and frequency points of the auto terms signal, the accuracy of BSS can be improved. An experimental simulation has been used, with changes in the pulse width of the transmitted signal, the relative amplitude and the time delay parameter, in order to analyzing the feasibility of this new method. Simulation results show that the new method is not only able to separate rigid scattering components, but can also separate the components when elastic scattering and rigid scattering exist at the same time. Experimental results confirm that the new method can be used in separating the rigid scattering structure of underwater objects.

A Comparison of Multidimensional Item Selection Methods in Simple and Complex Test Designs

Directory of Open Access Journals (Sweden)

Eren Halil ÖZBERK

2017-03-01

Full Text Available In contrast with the previous studies, this study employed various test designs (simple and complex which allow the evaluation of the overall ability score estimations across multiple real test conditions. In this study, four factors were manipulated, namely the test design, number of items per dimension, correlation between dimensions and item selection methods. Using the generated item and ability parameters, dichotomous item responses were generated in by using M3PL compensatory multidimensional IRT model with specified correlations. MCAT composite ability score accuracy was evaluated using absolute bias (ABSBIAS, correlation and the root mean square error (RMSE between true and estimated ability scores. The results suggest that the multidimensional test structure, number of item per dimension and correlation between dimensions had significant effect on item selection methods for the overall score estimations. For simple structure test design it was found that V1 item selection has the lowest absolute bias estimations for both long and short tests while estimating overall scores. As the model gets complex KL item selection method performed better than other two item selection method.

A new screening method for selection of desired recombinant ...

African Journals Online (AJOL)

A new screening method for selection of desired recombinant plasmids in molecular cloning. ... African Journal of Biotechnology ... Regarding the facts of this study, after digestion process, the products directly were subjected to ligation. Due to ...

The Hull Method for Selecting the Number of Common Factors

Science.gov (United States)

Lorenzo-Seva, Urbano; Timmerman, Marieke E.; Kiers, Henk A. L.

2011-01-01

A common problem in exploratory factor analysis is how many factors need to be extracted from a particular data set. We propose a new method for selecting the number of major common factors: the Hull method, which aims to find a model with an optimal balance between model fit and number of parameters. We examine the performance of the method in an…

Orthogonal feature selection method. [For preprocessing of man spectral data

Energy Technology Data Exchange (ETDEWEB)

Kowalski, B R [Univ. of Washington, Seattle; Bender, C F

1976-01-01

A new method of preprocessing spectral data for extraction of molecular structural information is desired. This SELECT method generates orthogonal features that are important for classification purposes and that also retain their identity to the original measurements. A brief introduction to chemical pattern recognition is presented. A brief description of the method and an application to mass spectral data analysis follow. (BLM)

TEHRAN AIR POLLUTANTS PREDICTION BASED ON RANDOM FOREST FEATURE SELECTION METHOD

Directory of Open Access Journals (Sweden)

A. Shamsoddini

2017-09-01

Full Text Available Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

Tehran Air Pollutants Prediction Based on Random Forest Feature Selection Method

Science.gov (United States)

Shamsoddini, A.; Aboodi, M. R.; Karami, J.

2017-09-01

Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

New Hybrid Features Selection Method: A Case Study on Websites Phishing

Directory of Open Access Journals (Sweden)

Khairan D. Rajab

2017-01-01

Full Text Available Phishing is one of the serious web threats that involves mimicking authenticated websites to deceive users in order to obtain their financial information. Phishing has caused financial damage to the different online stakeholders. It is massive in the magnitude of hundreds of millions; hence it is essential to minimize this risk. Classifying websites into “phishy” and legitimate types is a primary task in data mining that security experts and decision makers are hoping to improve particularly with respect to the detection rate and reliability of the results. One way to ensure the reliability of the results and to enhance performance is to identify a set of related features early on so the data dimensionality reduces and irrelevant features are discarded. To increase reliability of preprocessing, this article proposes a new feature selection method that combines the scores of multiple known methods to minimize discrepancies in feature selection results. The proposed method has been applied to the problem of website phishing classification to show its pros and cons in identifying relevant features. Results against a security dataset reveal that the proposed preprocessing method was able to derive new features datasets which when mined generate high competitive classifiers with reference to detection rate when compared to results obtained from other features selection methods.

A Feature Subset Selection Method Based On High-Dimensional Mutual Information

Directory of Open Access Journals (Sweden)

Chee Keong Kwoh

2011-04-01

Full Text Available Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if the mutual information between a feature set X and the class attribute Y equals to the entropy of Y , then X is a Markov Blanket of Y . We show that in some cases, it is infeasible to approximate the high-dimensional mutual information with algebraic combinations of pairwise mutual information in any forms. In addition, the exhaustive searches of all combinations of features are prerequisite for finding the optimal feature subsets for classifying these kinds of data sets. We show that our approach outperforms existing filter feature subset selection methods for most of the 24 selected benchmark data sets.

A fractured rock geophysical toolbox method selection tool

Science.gov (United States)

Day-Lewis, F. D.; Johnson, C.D.; Slater, L.D.; Robinson, J.L.; Williams, J.H.; Boyden, C.L.; Werkema, D.D.; Lane, J.W.

2016-01-01

Geophysical technologies have the potential to improve site characterization and monitoring in fractured rock, but the appropriate and effective application of geophysics at a particular site strongly depends on project goals (e.g., identifying discrete fractures) and site characteristics (e.g., lithology). No method works at every site or for every goal. New approaches are needed to identify a set of geophysical methods appropriate to specific project goals and site conditions while considering budget constraints. To this end, we present the Excel-based Fractured-Rock Geophysical Toolbox Method Selection Tool (FRGT-MST). We envision the FRGT-MST (1) equipping remediation professionals with a tool to understand what is likely to be realistic and cost-effective when contracting geophysical services, and (2) reducing applications of geophysics with unrealistic objectives or where methods are likely to fail.

Investigation of the paired-gear method in selectivity studies

DEFF Research Database (Denmark)

Sistiaga, Manu; Herrmann, Bent; Larsen, R.B.

2009-01-01

was repeated throughout the eight cases in this investigation. When using the paired-gear method, the distribution of the estimated L50 and SR is wider; the distribution of the estimated split parameter has a higher variability than the true split; the estimated mean L50 and SR can be biased; the estimated...... recommend that the methodology used to obtain selectivity estimates using the paired-gear method be reviewed....

Method selection for sustainability assessments: The case of recovery of resources from waste water.

Science.gov (United States)

Zijp, M C; Waaijers-van der Loop, S L; Heijungs, R; Broeren, M L M; Peeters, R; Van Nieuwenhuijzen, A; Shen, L; Heugens, E H W; Posthuma, L

2017-07-15

Sustainability assessments provide scientific support in decision procedures towards sustainable solutions. However, in order to contribute in identifying and choosing sustainable solutions, the sustainability assessment has to fit the decision context. Two complicating factors exist. First, different stakeholders tend to have different views on what a sustainability assessment should encompass. Second, a plethora of sustainability assessment methods exist, due to the multi-dimensional characteristic of the concept. Different methods provide other representations of sustainability. Based on a literature review, we present a protocol to facilitate method selection together with stakeholders. The protocol guides the exploration of i) the decision context, ii) the different views of stakeholders and iii) the selection of pertinent assessment methods. In addition, we present an online tool for method selection. This tool identifies assessment methods that meet the specifications obtained with the protocol, and currently contains characteristics of 30 sustainability assessment methods. The utility of the protocol and the tool are tested in a case study on the recovery of resources from domestic waste water. In several iterations, a combination of methods was selected, followed by execution of the selected sustainability assessment methods. The assessment results can be used in the first phase of the decision procedure that leads to a strategic choice for sustainable resource recovery from waste water in the Netherlands. Copyright © 2017 Elsevier Ltd. All rights reserved.

Direct methods for measuring radionuclides in the human body

International Nuclear Information System (INIS)

1996-01-01

Occupational exposure leading to intakes of internally incorporated radionuclides can occur as a result of various activities. This includes work associated with the different stages of the nuclear fuel cycle, the use of radioactive sources in medicine, scientific research, agriculture and industry, and occupations which involve exposure to enhanced levels of naturally occurring radionuclides. In 1987 the IAEA published a Safety Guide on basic principles for occupational radiation monitoring which set forth principles and objectives of a strategy for monitoring exposures of workers. Since drafting of the present Safety Practice commenced, the International Basic Safety Standards for Protection against Ionizing Radiation and for the Safety of Radiation Sources (BSS) have been issued. On the basis of the principles laid down in the BSS, the 1987 Safety Guide is also being revised, and recommendations on the assessment of the occupational intake of radioactive materials are to be added. The present Safety Practice, which deals with direct measurement of radionuclides in the human body, is the first to be published in this area. Refs, figs, tabs

A Feature Selection Method for Large-Scale Network Traffic Classification Based on Spark

Directory of Open Access Journals (Sweden)

Yong Wang

2016-02-01

Full Text Available Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce framework have been proposed, the execution time was still unsatisfactory with numeral iterative computations during the processing. To address this issue, an efficient feature selection method for network traffic based on a new parallel computing framework called Spark is proposed in this paper. In our approach, the complete feature set is firstly preprocessed based on Fisher score, and a sequential forward search strategy is employed for subsets. The optimal feature subset is then selected using the continuous iterations of the Spark computing framework. The implementation demonstrates that, on the precondition of keeping the classification accuracy, our method reduces the time cost of modeling and classification, and improves the execution efficiency of feature selection significantly.

AN APPLICATION OF FUZZY PROMETHEE METHOD FOR SELECTING OPTIMAL CAR PROBLEM

Directory of Open Access Journals (Sweden)

SERKAN BALLI

2013-06-01

Full Text Available Most of the economical, industrial, financial or political decision problems are multi-criteria. In these multi criteria problems, optimal selection of alternatives is hard and complex process. Recently, some kinds of methods are improved to solve these problems. Promethee is one of most efficient and easiest method and solves problems that consist quantitative criteria.  However, in daily life, there are criteria which are explained as linguistic and cannot modeled numerical. Hence, Promethee method is incomplete for linguistic criteria which are imprecise. To satisfy this deficiency, fuzzy set approximation can be used. Promethee method, which is extended with using fuzzy inputs, is applied to car selection for seven different cars in same class by using criteria: price, fuel, performance and security. The obtained results are appropriate and consistent.

Sensor Selection method for IoT systems – focusing on embedded system requirements

Directory of Open Access Journals (Sweden)

Hirayama Masayuki

2016-01-01

Full Text Available Recently, various types of sensors have been developed. Using these sensors, IoT systems have become hot topics in embedded system domain. However, sensor selections for embedded systems are not well discussed up to now. This paper focuses on embedded system’s features and architecture, and proposes a sensor selection method which is composed seven steps. In addition, we applied the proposed method to a simple example – a sensor selection for computer scored answer sheet reader unit. From this case study, an idea to use FTA in sensor selection is also discussed.

Pyrochemical and Dry Processing Methods Program. A selected bibliography

Energy Technology Data Exchange (ETDEWEB)

McDuffie, H.F.; Smith, D.H.; Owen, P.T.

1979-03-01

This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles.

Pyrochemical and Dry Processing Methods Program. A selected bibliography

International Nuclear Information System (INIS)

McDuffie, H.F.; Smith, D.H.; Owen, P.T.

1979-03-01

This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles

LCIA selection methods for assessing toxic releases

DEFF Research Database (Denmark)

Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

2002-01-01

the inventory that contribute significantly to the impact categories on ecotoxicity and human toxicity to focus the characterisation work. The reason why the selection methods are more important for the chemical-related impact categories than for other impact categories is the extremely high number......Characterization of toxic emissions in life cycle impact assessment (LCIA) is in many cases severely limited by the lack of characterization factors for the emissions mapped in the inventory. The number of substances assigned characterization factors for (eco)toxicity included in the dominating LCA....... The methods are evaluated against a set of pre-defined criteria (comprising consistency with characterization and data requirement) and applied to case studies and a test set of chemicals. The reported work is part of the EU-project OMNIITOX....

A Fourier transform method for the selection of a smoothing interval

International Nuclear Information System (INIS)

Kekre, H.B.; Madan, V.K.; Bairi, B.R.

1989-01-01

A novel method for the selection of a smoothing interval for the widely used Savitzky and Golay's smoothing filter is proposed. Complementary bandwidths for the nuclear spectral data and the smoothing filter are defined. The criterion for the selection of smoothing interval is based on matching the bandwidths of the spectral data to the filter. Using the above method five real observed spectral peaks of different full width at half maximum, viz. 23.5, 19.5, 17, 8.5 and 6.5 channels, were smoothed and the results are presented. (orig.)

Effect of cooking methods on the micronutrient profile of selected ...

African Journals Online (AJOL)

Effect of cooking methods on the micronutrient profile of selected vegetables: okra fruit ( Abelmoshcus esculentus ), fluted pumpkin ( Telfairia occidentalis ), African spinach ( Amarantus viridis ), and scent leaf ( Ocumum gratissimum.

On a selection method of imaging condition in scintigraphy

International Nuclear Information System (INIS)

Ikeda, Hozumi; Kishimoto, Kenji; Shimonishi, Yoshihiro; Ohmura, Masahiro; Kosakai, Kazuhisa; Ochi, Hironobu

1992-01-01

Selection of imaging condition in scintigraphy was evaluated using analytic hierarchy process. First, a method of the selection was led by determining at the points of image quantity and imaging time. Influence of image quality was thought to depend on changes of system resolution, count density, image size, and image density. Also influence of imaging time was thought to depend on changes of system sensitivity and data acquisition time. Phantom study was done for paired comparison of these selection factors, and relations of sample data and the factors, that is Rollo phantom images were taken by changing count density, image size, and image density. Image quality was shown by calculating the score of visual evaluation that done by comparing of a pair of images in clearer cold lesion on the scintigrams. Imaging time was shown by relative values for changes of count density. However, system resolution and system sensitivity were constant in this study. Next, using these values analytic hierarchy process was adapted for this selection of imaging conditions. We conclude that this selection of imaging conditions can be analyzed quantitatively using analytic hierarchy process and this analysis develops theoretical consideration of imaging technique. (author)

The analysis of dynamic characteristics and wind-induced displacement response of space Beam String Structure

Directory of Open Access Journals (Sweden)

Chen Yong Jian

2018-01-01

Full Text Available The Beam String Structure structural system, also called BSS, has the advantages of lighter dead weight and greater flexibility. The wind load is the main design control factor. The dynamic characteristics and wind-induced displacement response of BSS are studied by the finite element method. The roof structure of the stadium roof of the Fuzhou Olympic Sports Center is the engineering background. 1The numerical model was built by ANSYS, by shape finding, determine the initial stress state of structural members such as external cables; 2From the analysis of dynamic characteristics, the main mode of vibration is the vibration of cables; 3The wind speed spectrum of MATLAB generation structure is obtained by AR method, the structural response of the structure under static wind load and fluctuating wind load is calculated. From the analysis result, considering the equivalent static wind load of BSS , the design of adverse wind is not safe, and the fluctuating wind load should be taken into account.

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

Science.gov (United States)

White, David J.; Congedo, Marco; Ciorciari, Joseph

2014-01-01

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation (BSS) of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using BSS may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes where individual brain sources may be targeted by source-based EEG neurofeedback. PMID

Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration

Directory of Open Access Journals (Sweden)

Haitao Chang

2016-06-01

Full Text Available One of the essential factors influencing the prediction accuracy of multivariate calibration models is the quality of the calibration data. A local regression strategy, together with a wavelength selection approach, is proposed to build the multivariate calibration models based on partial least squares regression. The local algorithm is applied to create a calibration set of spectra similar to the spectrum of an unknown sample; the synthetic degree of grey relation coefficient is used to evaluate the similarity. A wavelength selection method based on simple-to-use interactive self-modeling mixture analysis minimizes the influence of noisy variables, and the most informative variables of the most similar samples are selected to build the multivariate calibration model based on partial least squares regression. To validate the performance of the proposed method, ultraviolet-visible absorbance spectra of mixed solutions of food coloring analytes in a concentration range of 20–200 µg/mL is measured. Experimental results show that the proposed method can not only enhance the prediction accuracy of the calibration model, but also greatly reduce its complexity.

Variable selection in near-infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data

International Nuclear Information System (INIS)

Balabin, Roman M.; Smirnov, Sergey V.

2011-01-01

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm -1 ) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic

Evolutionary dynamics on graphs: Efficient method for weak selection

Science.gov (United States)

Fu, Feng; Wang, Long; Nowak, Martin A.; Hauert, Christoph

2009-04-01

Investigating the evolutionary dynamics of game theoretical interactions in populations where individuals are arranged on a graph can be challenging in terms of computation time. Here, we propose an efficient method to study any type of game on arbitrary graph structures for weak selection. In this limit, evolutionary game dynamics represents a first-order correction to neutral evolution. Spatial correlations can be empirically determined under neutral evolution and provide the basis for formulating the game dynamics as a discrete Markov process by incorporating a detailed description of the microscopic dynamics based on the neutral correlations. This framework is then applied to one of the most intriguing questions in evolutionary biology: the evolution of cooperation. We demonstrate that the degree heterogeneity of a graph impedes cooperation and that the success of tit for tat depends not only on the number of rounds but also on the degree of the graph. Moreover, considering the mutation-selection equilibrium shows that the symmetry of the stationary distribution of states under weak selection is skewed in favor of defectors for larger selection strengths. In particular, degree heterogeneity—a prominent feature of scale-free networks—generally results in a more pronounced increase in the critical benefit-to-cost ratio required for evolution to favor cooperation as compared to regular graphs. This conclusion is corroborated by an analysis of the effects of population structures on the fixation probabilities of strategies in general 2×2 games for different types of graphs. Computer simulations confirm the predictive power of our method and illustrate the improved accuracy as compared to previous studies.

Multi criteria decision making methods for location selection of distribution centers

Directory of Open Access Journals (Sweden)

Romita Chakraborty

2013-10-01

Full Text Available In recent years, major challenges such as, increase in inflexible consumer demands and to improve the competitive advantage, it has become necessary for various industrial organizations all over the world to focus on strategies that will help them achieve cost reduction, continual quality improvement, increased customer satisfaction and on time delivery performance. As a result, selection of the most suitable and optimal facility location for a new organization or expansion of an existing location is one of the most important strategic issues, required to fulfill all of these above mentioned objectives. In order to sustain in the global competitive market of 21st century, many industrial organizations have begun to concentrate on the proper selection of the plant site or best facility location. The best location is that which results in higher economic benefits through increased productivity and good distribution network. When a choice is to be made from among several alternative facility locations, it is necessary to compare their performance characteristics in a decisive way. As the facility location selection problem involves multiple conflicting criteria and a finite set of potential candidate alternatives, different multi-criteria decision-making (MCDM methods can be effectively applied to solve such type of problem. In this paper, four well known MCDM methods have been applied on a facility location selection problem and their relative ranking performances are compared. Because of disagreement in the ranks obtained by the four different MCDM methods a final ranking method based on REGIME has been proposed by the authors to facilitate the decision making process.

Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

KAUST Repository

Xu, Zhiqiang

2017-02-16

Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

KAUST Repository

Xu, Zhiqiang; Cheng, James; Xiao, Xiaokui; Fujimaki, Ryohei; Muraoka, Yusuke

2017-01-01

Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

Fuzzy decision-making: a new method in model selection via various validity criteria

International Nuclear Information System (INIS)

Shakouri Ganjavi, H.; Nikravesh, K.

2001-01-01

Modeling is considered as the first step in scientific investigations. Several alternative models may be candida ted to express a phenomenon. Scientists use various criteria to select one model between the competing models. Based on the solution of a Fuzzy Decision-Making problem, this paper proposes a new method in model selection. The method enables the scientist to apply all desired validity criteria, systematically by defining a proper Possibility Distribution Function due to each criterion. Finally, minimization of a utility function composed of the Possibility Distribution Functions will determine the best selection. The method is illustrated through a modeling example for the A verage Daily Time Duration of Electrical Energy Consumption in Iran

Sustainable Supplier Performance Evaluation and Selection with Neofuzzy TOPSIS Method.

Science.gov (United States)

Chaharsooghi, S K; Ashrafi, Mehdi

2014-01-01

Supplier selection plays an important role in the supply chain management and traditional criteria such as price, quality, and flexibility are considered for supplier performance evaluation in researches. In recent years sustainability has received more attention in the supply chain management literature with triple bottom line (TBL) describing the sustainability in supply chain management with social, environmental, and economic initiatives. This paper explores sustainability in supply chain management and examines the problem of identifying a new model for supplier selection based on extended model of TBL approach in supply chain by presenting fuzzy multicriteria method. Linguistic values of experts' subjective preferences are expressed with fuzzy numbers and Neofuzzy TOPSIS is proposed for finding the best solution of supplier selection problem. Numerical results show that the proposed model is efficient for integrating sustainability in supplier selection problem. The importance of using complimentary aspects of sustainability and Neofuzzy TOPSIS concept in sustainable supplier selection process is shown with sensitivity analysis.

Logging costs and production rates for the group selection cutting method

Science.gov (United States)

Philip M. McDonald

1965-01-01

Young-growth, mixed-conifer stands were logged by a group-selection method designed to create openings 30, 60, and 90 feet in diameter. Total costs for felling, limbing, bucking, and skidding on these openings ranged from $7.04 to $7.99 per thousand board feet. Cost differences between openings were not statistically significant. Logging costs for group selection...

The birth satisfaction scale: Turkish adaptation, validation and reliability study

Science.gov (United States)

Cetin, Fatma Cosar; Sezer, Ayse; Merih, Yeliz Dogan

2015-01-01

OBJECTIVE: The objective of this study is to investigate the validity and the reliability of Birth Satisfaction Scale (BSS) and to adapt it into the Turkish language. This scale is used for measuring maternal satisfaction with birth in order to evaluate women’s birth perceptions. METHODS: In this study there were 150 women who attended to inpatient postpartum clinic. The participants filled in an information form and the BSS questionnaire forms. The properties of the scale were tested by conducting reliability and validation analyses. RESULTS: BSS entails 30 Likert-type questions. It was developed by Hollins Martin and Fleming. Total scale scores ranged between 30–150 points. Higher scores from the scale mean increases in birth satisfaction. Three overarching themes were identified in Scale: service provision (home assessment, birth environment, support, relationships with health care professionals); personal attributes (ability to cope during labour, feeling in control, childbirth preparation, relationship with baby); and stress experienced during labour (distress, obstetric injuries, receiving sufficient medical care, obstetric intervention, pain, prolonged labour and baby’s health). Cronbach’s alfa coefficient was 0.62. CONCLUSION: According to the present study, BSS entails 30 Likert-type questions and evaluates women’s birth perceptions. The Turkish version of BSS has been proven to be a valid and a reliable scale. PMID:28058355

An active learning representative subset selection method using net analyte signal

Science.gov (United States)

He, Zhonghai; Ma, Zhenhe; Luan, Jingmin; Cai, Xi

2018-05-01

To guarantee accurate predictions, representative samples are needed when building a calibration model for spectroscopic measurements. However, in general, it is not known whether a sample is representative prior to measuring its concentration, which is both time-consuming and expensive. In this paper, a method to determine whether a sample should be selected into a calibration set is presented. The selection is based on the difference of Euclidean norm of net analyte signal (NAS) vector between the candidate and existing samples. First, the concentrations and spectra of a group of samples are used to compute the projection matrix, NAS vector, and scalar values. Next, the NAS vectors of candidate samples are computed by multiplying projection matrix with spectra of samples. Scalar value of NAS is obtained by norm computation. The distance between the candidate set and the selected set is computed, and samples with the largest distance are added to selected set sequentially. Last, the concentration of the analyte is measured such that the sample can be used as a calibration sample. Using a validation test, it is shown that the presented method is more efficient than random selection. As a result, the amount of time and money spent on reference measurements is greatly reduced.

Optical wavelength selection for portable hemoglobin determination by near-infrared spectroscopy method

Science.gov (United States)

Tian, Han; Li, Ming; Wang, Yue; Sheng, Dinggao; Liu, Jun; Zhang, Linna

2017-11-01

Hemoglobin concentration is commonly used in clinical medicine to diagnose anemia, identify bleeding, and manage red blood cell transfusions. The golden standard method for determining hemoglobin concentration in blood requires reagent. Spectral methods were advantageous at fast and non-reagent measurement. However, model calibration with full spectrum is time-consuming. Moreover, it is necessary to use a few variables considering size and cost of instrumentation, especially for a portable biomedical instrument. This study presents different wavelength selection methods for optical wavelengths for total hemoglobin concentration determination in whole blood. The results showed that modelling using only two wavelengths combination (1143 nm, 1298 nm) can keep on the fine predictability with full spectrum. It appears that the proper selection of optical wavelengths can be more effective than using the whole spectra for determination hemoglobin in whole blood. We also discussed the influence of water absorptivity on the wavelength selection. This research provides valuable references for designing portable NIR instruments determining hemoglobin concentration, and may provide some experience for noninvasive hemoglobin measurement by NIR methods.

Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

International Nuclear Information System (INIS)

Wang Xiaojia; Mao Qirong; Zhan Yongzhao

2008-01-01

There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions. The experiments show that this method can improve the recognition rate and the time of feature extraction

A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

KAUST Repository

Abusamra, Heba

2013-11-01

Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

KAUST Repository

Abusamra, Heba

2013-01-01

Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

A Robust Service Selection Method Based on Uncertain QoS

Directory of Open Access Journals (Sweden)

Yanping Chen

2016-01-01

Full Text Available Nowadays, the number of Web services on the Internet is quickly increasing. Meanwhile, different service providers offer numerous services with the similar functions. Quality of Service (QoS has become an important factor used to select the most appropriate service for users. The most prominent QoS-based service selection models only take the certain attributes into account, which is an ideal assumption. In the real world, there are a large number of uncertain factors. In particular, at the runtime, QoS may become very poor or unacceptable. In order to solve the problem, a global service selection model based on uncertain QoS was proposed, including the corresponding normalization and aggregation functions, and then a robust optimization model adopted to transform the model. Experiment results show that the proposed method can effectively select services with high robustness and optimality.

Objective Versus Subjective Military Pilot Selection Methods in the United States of America

Science.gov (United States)

2015-12-14

a computerized test designed to assess pilot skills by measuring spatial orientation and psychomotor skills and multitasking . The second is the...AFRL-SA-WP-SR-2015-0028 Objective Versus Subjective Military Pilot Selection Methods in the United States of America Joe...September 2014 4. TITLE AND SUBTITLE Objective Versus Subjective Military Pilot Selection Methods in the United States of America 5a. CONTRACT

An Integrated DEMATEL-VIKOR Method-Based Approach for Cotton Fibre Selection and Evaluation

Science.gov (United States)

Chakraborty, Shankar; Chatterjee, Prasenjit; Prasad, Kanika

2018-01-01

Selection of the most appropriate cotton fibre type for yarn manufacturing is often treated as a multi-criteria decision-making (MCDM) problem as the optimal selection decision needs to be taken in presence of several conflicting fibre properties. In this paper, two popular MCDM methods in the form of decision making trial and evaluation laboratory (DEMATEL) and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR) are integrated to aid the cotton fibre selection decision. DEMATEL method addresses the interrelationships between various physical properties of cotton fibres while segregating them into cause and effect groups, whereas, VIKOR method helps in ranking all the considered 17 cotton fibres from the best to the worst. The derived ranking of cotton fibre alternatives closely matches with that obtained by the past researchers. This model can assist the spinning industry personnel in the blending process while making accurate fibre selection decision when cotton fibre properties are numerous and interrelated.

Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System.

Science.gov (United States)

Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

2015-01-01

The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

[Analysis on the accuracy of simple selection method of Fengshi (GB 31)].

Science.gov (United States)

Li, Zhixing; Zhang, Haihua; Li, Suhe

2015-12-01

To explore the accuracy of simple selection method of Fengshi (GB 31). Through the study of the ancient and modern data,the analysis and integration of the acupuncture books,the comparison of the locations of Fengshi (GB 31) by doctors from all dynasties and the integration of modern anatomia, the modern simple selection method of Fengshi (GB 31) is definite, which is the same as the traditional way. It is believed that the simple selec tion method is in accord with the human-oriented thought of TCM. Treatment by acupoints should be based on the emerging nature and the individual difference of patients. Also, it is proposed that Fengshi (GB 31) should be located through the integration between the simple method and body surface anatomical mark.

Validity of a structured method of selecting abstracts for a plastic surgical scientific meeting

NARCIS (Netherlands)

van der Steen, LPE; Hage, JJ; Kon, M; Monstrey, SJ

In 1999, the European Association of Plastic Surgeons accepted a structured method to assess and select the abstracts that are submitted for its yearly scientific meeting. The two criteria used to evaluate whether such a selection method is accurate were reliability and validity. The authors

A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy

Directory of Open Access Journals (Sweden)

Ge Jianjun

2017-12-01

Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.

Selection method and characterization of neutron monochromator natural crystals

International Nuclear Information System (INIS)

Stasiulevicius, R.; Kastner, G.F.

2000-01-01

Thermal neutrons are important analytical tools for microscopic material probe. These neutrons can be selected by diffraction technique using monocrystal, usually artificial. A crystal selection process was implemented and the characteristics of natural specimens were studied by activation analysis-k 0 method. The representative 120 samples, of which 21 best types, were irradiated in IPR-R1 and measured with a neutron diffractometer at IEA-R1m Brazilian reactors. These results are useful for database build up and ease the choice of appropriate natural crystal, with some advantage options: highest intensity diffracted, enlarging the energy operational interval and optimal performance in special applications. (author)

Contextual control over selective attention: evidence from a two-target method.

Science.gov (United States)

MacLellan, Ellen; Shore, David I; Milliken, Bruce

2015-07-01

Selective attention is generally studied with conflict tasks, using response time as the dependent measure. Here, we study the impact of selective attention to a first target, T1, presented simultaneously with a distractor, on the accuracy of subsequent encoding of a second target item, T2. This procedure produces an "attentional blink" (AB) effect much like that reported in other studies, and allowed us to study the influence of context on cognitive control with a novel method. In particular, we examined whether preparation to attend selectively to T1 had an impact on the selective encoding of T1 that would translate to report of T2. Preparation to attend selectively was manipulated by varying whether difficult selective attention T1 trials were presented in the context of other difficult selective attention T1 trials. The results revealed strong context effects of this nature, with smaller AB effects when difficult selective attention T1 trials were embedded in a context with many, rather than few, other difficult selective attention T1 trials. Further, the results suggest that both the trial-to-trial local context and the block-wide global context modulate performance in this task.

Manual of selected physico-chemical analytical methods. IV

International Nuclear Information System (INIS)

Beran, M.; Klosova, E.; Krtil, J.; Sus, F.; Kuvik, V.; Vrbova, L.; Hamplova, M.; Lengyel, J.; Kelnar, L.; Zakouril, K.

1990-11-01

The Central Testing Laboratory of the Nuclear Research Institute at Rez has for a decade been participating in the development of analytical procedures and has been providing analyses of samples of different types and origin. The analytical procedures developed have been published in special journals and a number of them in the Manuals of analytical methods, in three parts. The 4th part of the Manual contains selected physico-chemical methods developed or modified by the Laboratory in the years 1986-1990 within the project ''Development of physico-chemical analytical methods''. In most cases, techniques are involved for non-nuclear applications. Some can find wider applications, especially in analyses of environmental samples. Others have been developed for specific cases of sample analyses or require special instrumentation (mass spectrometer), which partly restricts their applicability by other institutions. (author)

The MCDM Model for Personnel Selection Based on SWARA and ARAS Methods

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Darjan Karabasevic

2015-05-01

Full Text Available Competent employees are the key resource in an organization for achieving success and, therefore, competitiveness on the market. The aim of the recruitment and selection process is to acquire personnel with certain competencies required for a particular position, i.e.,a position within the company. Bearing in mind the fact that in the process of decision making decision-makers have underused the methods of making decisions, this paper aims to establish an MCDM model for the evaluation and selection of candidates in the process of the recruitment and selection of personnel based on the SWARA and the ARAS methods. Apart from providing an MCDM model, the paper will additionally provide a set of evaluation criteria for the position of a sales manager (the middle management in the telecommunication industry which will also be used in the numerical example. On the basis of a numerical example, in the process of employment, theproposed MCDMmodel can be successfully usedin selecting candidates.

IV international conference on computational methods in marine engineering : selected papers

CERN Document Server

Oñate, Eugenio; García-Espinosa, Julio; Kvamsdal, Trond; Bergan, Pål; MARINE 2011

2013-01-01

This book contains selected papers from the Fourth International Conference on Computational Methods in Marine Engineering, held at Instituto Superior Técnico, Technical University of Lisbon, Portugal in September 2011.  Nowadays, computational methods are an essential tool of engineering, which includes a major field of interest in marine applications, such as the maritime and offshore industries and engineering challenges related to the marine environment and renewable energies. The 2011 Conference included 8 invited plenary lectures and 86 presentations distributed through 10 thematic sessions that covered many of the most relevant topics of marine engineering today. This book contains 16 selected papers from the Conference that cover “CFD for Offshore Applications”, “Fluid-Structure Interaction”, “Isogeometric Methods for Marine Engineering”, “Marine/Offshore Renewable Energy”, “Maneuvering and Seakeeping”, “Propulsion and Cavitation” and “Ship Hydrodynamics”.  The papers we...

Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

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Pavol Partila

2015-01-01

Full Text Available The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

Radio Frequency EMF Exposure due to Gsm Mobile Phones Base ...

African Journals Online (AJOL)

BSs). In Nigerian some people believed that exposure to radiation from BSs for long period could cause different diseases like cancer, destroys reproductive organs, congenital anomalies, epilepsy and persistent headache and some of the BSs ...

Selection of boron based tribological hard coatings using multi-criteria decision making methods

International Nuclear Information System (INIS)

Çalışkan, Halil

2013-01-01

Highlights: • Boron based coating selection problem for cutting tools was solved. • EXPROM2, TOPSIS and VIKOR methods were used for ranking the alternative materials. • The best coatings for cutting tool were selected as TiBN and TiSiBN. • The ranking results are in good agreement with cutting test results in literature. - Abstract: Mechanical and tribological properties of hard coatings can be enhanced using boron as alloying element. Therefore, multicomponent nanostructured boron based hard coatings are deposited on cutting tools by different methods at different parameters. Different mechanical and tribological properties are obtained after deposition, and it is a difficult task to select the best coating material. In this paper, therefore, a systematic evaluation model was proposed to tackle the difficulty of the material selection with specific properties among a set of available alternatives. The alternatives consist of multicomponent nanostructured TiBN, TiCrBN, TiSiBN and TiAlSiBN coatings deposited by magnetron sputtering and ion implantation assisted magnetron sputtering at different parameters. The alternative coating materials were ranked by using three multi-criteria decision-making (MCDM) methods, i.e. EXPROM2 (preference ranking organization method for enrichment evaluation), TOPSIS (technique for order performance by similarity to ideal solution) and VIKOR (VIšekriterijumsko KOmpromisno Rangiranje), in order to determine the best coating material for cutting tools. Hardness (H), Young’s modulus (E), elastic recovery, friction coefficient, critical load, H/E and H 3 /E 2 ratios were considered as material selection criteria. In order to determine the importance weights of the evaluation criteria, a compromised weighting method, which composes of the analytic hierarchy process and Entropy methods, were used. The ranking results showed that TiBN and TiSiBN coatings deposited at given parameters are the best coatings for cutting tools

Postcataract endophthalmitis prophylaxis using irrigation, incision hydration, and eye pressurization with vancomycin

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Schelonka LP

2015-07-01

Full Text Available Lee P Schelonka,1 Margaret A SaBell2 1Department of Opthalmology, Kaiser Permanente Lone Tree Medical Offices, Lone Tree, 2Department of Infection Control, Kaiser Permanente Lone Tree Medical Offices, Lone Tree, Denver, CO, USA Purpose: This study aimed to determine whether switching from balanced salt solution (BSS to vancomycin 20 g/mL BSS for incision hydration and eye pressurization reduces the rate of postcataract endophthalmitis.Methods: This was a patient safety/quality improvement project, including all patients undergoing cataract surgery at the Kaiser Permanente Colorado Ophthalmology Department from January 2002 to December 2014. Throughout the study, patients received vancomycin 20 µg/mL in the irrigating solution. During the baseline period from 2002 to 2005, surgeons pressurized eyes and hydrated incisions with plain BSS. During the intervention period from 2006 through 2014, surgeons switched from BSS to the vancomycin/BSS irrigating solution for eye pressurization and incision hydration.Results: A total of 57,263 cataract operations were performed by 24 surgeons at seven surgical centers: 12,400 in the baseline period and 44,863 in the intervention period. The rate of postcataract endophthalmitis declined significantly from 5/12,400 (rate: 0.4/1,000 in the baseline period to 1/44,863 (rate: 0.022/1,000 during the intervention period (odds ratio [OR]: 18.1, 95% confidence interval [CI]: 2.11–154.9; χ2=13.5, P=0.00024. Accounting for an estimated 2.05-fold risk reduction due to confounding variables, the risk reduction attributed to the intervention remained significant: (adjusted OR: 8.78, 95% CI: 1.73–44.5; χ2=10.06, P=0.0015. Since 2009, we have not experienced any cases of postcataract endophthalmitis after 32,753 operations.Conclusion: We experienced a significant reduction in postcataract endophthalmitis when we switched from BSS to the vancomycin/BSS irrigating solution for incision hydration and eye pressurization

A multi-fidelity analysis selection method using a constrained discrete optimization formulation

Science.gov (United States)

Stults, Ian C.

The purpose of this research is to develop a method for selecting the fidelity of contributing analyses in computer simulations. Model uncertainty is a significant component of result validity, yet it is neglected in most conceptual design studies. When it is considered, it is done so in only a limited fashion, and therefore brings the validity of selections made based on these results into question. Neglecting model uncertainty can potentially cause costly redesigns of concepts later in the design process or can even cause program cancellation. Rather than neglecting it, if one were to instead not only realize the model uncertainty in tools being used but also use this information to select the tools for a contributing analysis, studies could be conducted more efficiently and trust in results could be quantified. Methods for performing this are generally not rigorous or traceable, and in many cases the improvement and additional time spent performing enhanced calculations are washed out by less accurate calculations performed downstream. The intent of this research is to resolve this issue by providing a method which will minimize the amount of time spent conducting computer simulations while meeting accuracy and concept resolution requirements for results. In many conceptual design programs, only limited data is available for quantifying model uncertainty. Because of this data sparsity, traditional probabilistic means for quantifying uncertainty should be reconsidered. This research proposes to instead quantify model uncertainty using an evidence theory formulation (also referred to as Dempster-Shafer theory) in lieu of the traditional probabilistic approach. Specific weaknesses in using evidence theory for quantifying model uncertainty are identified and addressed for the purposes of the Fidelity Selection Problem. A series of experiments was conducted to address these weaknesses using n-dimensional optimization test functions. These experiments found that model

APPLICATION OF THE PERFORMANCE SELECTION INDEX METHOD FOR SOLVING MACHINING MCDM PROBLEMS

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Dušan Petković

2017-04-01

Full Text Available Complex nature of machining processes requires the use of different methods and techniques for process optimization. Over the past few years a number of different optimization methods have been proposed for solving continuous machining optimization problems. In manufacturing environment, engineers are also facing a number of discrete machining optimization problems. In order to help decision makers in solving this type of optimization problems a number of multi criteria decision making (MCDM methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. performance selection index (PSI method for solving machining MCDM problems. The main motivation for using the PSI method is that it is not necessary to determine criteria weights as in other MCDM methods. Applicability and effectiveness of the PSI method have been demonstrated while solving two case studies dealing with machinability of materials and selection of the most suitable cutting fluid for the given machining application. The obtained rankings have good correlation with those derived by the past researchers using other MCDM methods which validate the usefulness of this method for solving machining MCDM problems.

Method for selective immobilization of macromolecules on self assembled monolayer surfaces

Science.gov (United States)

Laskin, Julia [Richland, WA; Wang, Peng [Billerica, MA

2011-11-29

Disclosed is a method for selective chemical binding and immobilization of macromolecules on solid supports in conjunction with self-assembled monolayer (SAM) surfaces. Immobilization involves selective binding of peptides and other macromolecules to SAM surfaces using reactive landing (RL) of mass-selected, gas phase ions. SAM surfaces provide a simple and convenient platform for tailoring chemical properties of a variety of substrates. The invention finds applications in biochemistry ranging from characterization of molecular recognition events at the amino acid level and identification of biologically active motifs in proteins, to development of novel biosensors and substrates for stimulated protein and cell adhesion.

Selection and evaluation of gamma decay standards for detector calibration using coincidence method

International Nuclear Information System (INIS)

Hlavac, S.

2000-01-01

Coincidence method for calibration of gamma detectors using suitable calibration standards with two cascading gamma rays is analyzed. From the list of recommended gamma ray standards currently under reevaluation by the CRP, 14 radionuclides were selected as the potential source candidates for the coincidence method. The following sources were selected 24 Na, 46 Sc, 60 Co, 66 Ga, 75 Se, 88 Y, Nb 94 , 111 In, 123m Te, 133 Ba, 134 Cs, 152 Eu, 154 Eu and 207 Bi. Reaction 11 B (p,γ) 12 C* was also selected as a source of high energy gamma rays. Experimental data on angular correlation coefficients for selected sources were collected from the literature and evaluated according to the recommended procedure. Theoretical angular correlation coefficients were calculated and compared to the evaluated data. (author)

Feature selection for splice site prediction: A new method using EDA-based feature ranking

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Rouzé Pierre

2004-05-01

Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

Primitive polynomials selection method for pseudo-random number generator

Science.gov (United States)

Anikin, I. V.; Alnajjar, Kh

2018-01-01

In this paper we suggested the method for primitive polynomials selection of special type. This kind of polynomials can be efficiently used as a characteristic polynomials for linear feedback shift registers in pseudo-random number generators. The proposed method consists of two basic steps: finding minimum-cost irreducible polynomials of the desired degree and applying primitivity tests to get the primitive ones. Finally two primitive polynomials, which was found by the proposed method, used in pseudorandom number generator based on fuzzy logic (FRNG) which had been suggested before by the authors. The sequences generated by new version of FRNG have low correlation magnitude, high linear complexity, less power consumption, is more balanced and have better statistical properties.

Supplier selection for a tire company with AHP and PROMETHEE methods

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Atakan ALKAN

2017-04-01

Full Text Available Supplier selection is very important for a company to be successful in a globalized competitive environment. The aims at choosing the optimal supplier; to increase customer satisfaction, improve the competitive ability and continue to exist at minimal cost. This study was intended to choose the most suitable raw material supplier in a company engaged in the production of agricultural tires. In the study Analytical Hierarchy Process (AHP and Promethee I-II methods were applied in order to select the most optimal supplier to a company. In conclusion, AHP and Promethee I-II methods used by the company to determine the suppliers with the optimal supplier and brought several recommendations.

Application of mathematical methods of analysis in selection of competing information technologies

Science.gov (United States)

Semenov, V. L.; Kadyshev, E. N.; Zakharova, A. N.; Patianova, A. O.; Dulina, G. S.

2018-05-01

The article discusses the use of qualimetry methods using the apparatus of mathematical analysis in the formation of the integral index that allows one to select the best option among competing information technology. The authors propose the use of affine space in the evaluation and selection of competing information technologies.

An input feature selection method applied to fuzzy neural networks for signal esitmation

International Nuclear Information System (INIS)

Na, Man Gyun; Sim, Young Rok

2001-01-01

It is well known that the performance of a fuzzy neural networks strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output. As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural networks and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PAC), genetic algorithms (GA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods

Relationship between Blood Stasis Syndrome Score and Cardioankle Vascular Index in Stroke Patients

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Ki-Ho Cho

2012-01-01

Full Text Available Blood stasis syndrome (BSS in traditional Asian medicine has been considered to correlate with the extent of atherosclerosis, which can be estimated using the cardioankle vascular index (CAVI. Here, the diagnostic utility of CAVI in predicting BSS was examined. The BSS scores and CAVI were measured in 140 stroke patients and evaluated with respect to stroke risk factors. Receiver operating characteristic (ROC curve analysis was used to determine the diagnostic accuracy of CAVI for the diagnosis of BSS. The BSS scores correlated significantly with CAVI, age, and systolic blood pressure (SBP. Multiple logistic regression analysis showed that CAVI was a significant associate factor for BSS (OR 1.55, P=0.032 after adjusting for the age and SBP. The ROC curve showed that CAVI and age provided moderate diagnostic accuracy for BSS (area under the ROC curve (AUC for CAVI, 0.703, P<0.001; AUC for age, 0.692, P=0.001. The AUC of the “CAVI+Age,” which was calculated by combining CAVI with age, showed better accuracy (0.759, P<0.0001 than those of CAVI or age. The present study suggests that the CAVI combined with age can clinically serve as an objective tool to diagnose BSS in stroke patients.

Selection criteria for oxidation method in total organic carbon measurement.

Science.gov (United States)

Yoon, GeunSeok; Park, Sang-Min; Yang, Heuiwon; Tsang, Daniel C W; Alessi, Daniel S; Baek, Kitae

2018-05-01

During the measurement of total organic carbon (TOC), dissolved organic carbon is converted into CO 2 by using high temperature combustion (HTC) or wet chemical oxidation (WCO). However, the criteria for selecting the oxidation methods are not clear. In this study, the chemical structures of organic material were considered as a key factor to select the oxidation method used. Most non-degradable organic compounds showed a similar oxidation efficiency in both methods, including natural organic compounds, dyes, and pharmaceuticals, and thus both methods are appropriate to measure TOC in waters containing these compounds. However, only a fraction of the carbon in the halogenated compounds (perfluorooctanoic acid and trifluoroacetic acid) were oxidized using WCO, resulting in measured TOC values that are considerably lower than those determined by HTC. This result is likely due to the electronegativity of halogen elements which inhibits the approach of electron-rich sulfate radicals in the WCO, and the higher bond strength of carbon-halogen pairs as compared to carbon-hydrogen bonds, which results in a lower degree of oxidation of the compounds. Our results indicate that WCO could be used to oxidize most organic compounds, but may not be appropriate to quantify TOC in organic carbon pools that contain certain halogenated compounds. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluating the Use of Synthetic Replicas for SEM Identification of Bloodstains (with Emphasis on Archaeological and Ethnographic Artifacts).

Science.gov (United States)

Hortolà, Policarp

2015-12-01

Some archaeological or ethnographic specimens are unavailable for direct examination using a scanning electron microscope (SEM) due to methodological obstacles or legal issues. In order to assess the feasibility of using SEM synthetic replicas for the identification of bloodstains (BSs) via morphology of red blood cells (RBCs), three fragments of different natural raw material (inorganic, stone; plant, wood; animal, shell) were smeared with peripheral human blood. Afterwards, molds and casts of the bloodstained areas were made using vinyl polysiloxane (VPS) silicone impression and polyurethane (PU) resin casting material, respectively. Then, the original samples and the resulting casts were coated with gold and examined in secondary-electron mode using a high-vacuum SEM. Results suggest that PU resin casts obtained from VPS silicone molds can preserve RBC morphology in BSs, and consequently that synthetic replicas are feasible for SEM identification of BSs on cultural heritage specimens made of natural raw materials. Although the focus of this study was on BSs, the method reported in this paper may be applicable to organic residues other than blood, as well as to the surface of other specimens when, for any reason, the original is unavailable for an SEM.

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

Science.gov (United States)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

Evaluation of Maryland abutment scour equation through selected threshold velocity methods

Science.gov (United States)

Benedict, S.T.

2010-01-01

The U.S. Geological Survey, in cooperation with the Maryland State Highway Administration, used field measurements of scour to evaluate the sensitivity of the Maryland abutment scour equation to the critical (or threshold) velocity variable. Four selected methods for estimating threshold velocity were applied to the Maryland abutment scour equation, and the predicted scour to the field measurements were compared. Results indicated that performance of the Maryland abutment scour equation was sensitive to the threshold velocity with some threshold velocity methods producing better estimates of predicted scour than did others. In addition, results indicated that regional stream characteristics can affect the performance of the Maryland abutment scour equation with moderate-gradient streams performing differently from low-gradient streams. On the basis of the findings of the investigation, guidance for selecting threshold velocity methods for application to the Maryland abutment scour equation are provided, and limitations are noted.

Evaluation and selection of decision-making methods to assess landfill mining projects.

Science.gov (United States)

Hermann, Robert; Baumgartner, Rupert J; Vorbach, Stefan; Ragossnig, Arne; Pomberger, Roland

2015-09-01

For the first time in Austria, fundamental technological and economic studies on recovering secondary raw materials from large landfills have been carried out, based on the 'LAMIS - Landfill Mining Austria' pilot project. A main focus of the research - and the subject of this article - was to develop an assessment or decision-making procedure that allows landfill owners to thoroughly examine the feasibility of a landfill mining project in advance. Currently there are no standard procedures that would sufficiently cover all the multiple-criteria requirements. The basic structure of the multiple attribute decision making process was used to narrow down on selection, conceptual design and assessment of suitable procedures. Along with a breakdown into preliminary and main assessment, the entire foundation required was created, such as definitions of requirements to an assessment method, selection and accurate description of the various assessment criteria and classification of the target system for the present 'landfill mining' vs. 'retaining the landfill in after-care' decision-making problem. Based on these studies, cost-utility analysis and the analytical-hierarchy process were selected from the range of multiple attribute decision-making procedures and examined in detail. Overall, both methods have their pros and cons with regard to their use for assessing landfill mining projects. Merging these methods or connecting them with single-criteria decision-making methods (like the net present value method) may turn out to be reasonable and constitute an appropriate assessment method. © The Author(s) 2015.

Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

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Abdel Samee Nagwan M

2012-08-01

Full Text Available Abstract Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC. The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy. A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when

A Parameter Selection Method for Wind Turbine Health Management through SCADA Data

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Mian Du

2017-02-01

Full Text Available Wind turbine anomaly or failure detection using machine learning techniques through supervisory control and data acquisition (SCADA system is drawing wide attention from academic and industry While parameter selection is important for modelling a wind turbine’s condition, only a few papers have been published focusing on this issue and in those papers interconnections among sub-components in a wind turbine are used to address this problem. However, merely the interconnections for decision making sometimes is too general to provide a parameter list considering the differences of each SCADA dataset. In this paper, a method is proposed to provide more detailed suggestions on parameter selection based on mutual information. First, the copula is proven to be capable of simplifying the estimation of mutual information. Then an empirical copulabased mutual information estimation method (ECMI is introduced for application. After that, a real SCADA dataset is adopted to test the method, and the results show the effectiveness of the ECMI in providing parameter selection suggestions when physical knowledge is not accurate enough.

Application of PROMETHEE-GAIA method for non-traditional machining processes selection

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Prasad Karande

2012-10-01

Full Text Available With ever increasing demand for manufactured products of hard alloys and metals with high surface finish and complex shape geometry, more interest is now being paid to non-traditional machining (NTM processes, where energy in its direct form is used to remove material from workpiece surface. Compared to conventional machining processes, NTM processes possess almost unlimited capabilities and there is a strong believe that use of NTM processes would go on increasing in diverse range of applications. Presence of a large number of NTM processes along with complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Past researchers have already attempted to solve NTM process selection problems using various complex mathematical approaches which often require a profound knowledge in mathematics/artificial intelligence from the part of process engineers. In this paper, four NTM process selection problems are solved using an integrated PROMETHEE (preference ranking organization method for enrichment evaluation and GAIA (geometrical analysis for interactive aid method which would act as a visual decision aid to the process engineers. The observed results are quite satisfactory and exactly match with the expected solutions.

Analysis of Criteria Influencing Contractor Selection Using TOPSIS Method

Science.gov (United States)

Alptekin, Orkun; Alptekin, Nesrin

2017-10-01

Selection of the most suitable contractor is an important process in public construction projects. This process is a major decision which may influence the progress and success of a construction project. Improper selection of contractors may lead to problems such as bad quality of work and delay in project duration. Especially in the construction projects of public buildings, the proper choice of contractor is beneficial to the public institution. Public procurement processes have different characteristics in respect to dissimilarities in political, social and economic features of every country. In Turkey, Turkish Public Procurement Law PPL 4734 is the main regulatory law for the procurement of the public buildings. According to the PPL 4734, public construction administrators have to contract with the lowest bidder who has the minimum requirements according to the criteria in prequalification process. Public administrators are not sufficient for selection of the proper contractor because of the restrictive provisions of the PPL 4734. The lowest bid method does not enable public construction administrators to select the most qualified contractor and they have realised the fact that the selection of a contractor based on lowest bid alone is inadequate and may lead to the failure of the project in terms of time delay Eand poor quality standards. In order to evaluate the overall efficiency of a project, it is necessary to identify selection criteria. This study aims to focus on identify importance of other criteria besides lowest bid criterion in contractor selection process of PPL 4734. In this study, a survey was conducted to staff of Department of Construction Works of Eskisehir Osmangazi University. According to TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) for analysis results, termination of construction work in previous tenders is the most important criterion of 12 determined criteria. The lowest bid criterion is ranked in rank 5.

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

Science.gov (United States)

Zhang, Jianhai; Chen, Ming; Zhao, Shaokai; Hu, Sanqing; Shi, Zhiguo; Cao, Yu

2016-09-22

Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP). Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation). Furthermore, support vector machine (SVM) was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels' weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels). In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a contribution to the

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition

Directory of Open Access Journals (Sweden)

Jianhai Zhang

2016-09-01

Full Text Available Electroencephalogram (EEG signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP. Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation. Furthermore, support vector machine (SVM was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels’ weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels. In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a

Fringe-period selection for a multifrequency fringe-projection phase unwrapping method

International Nuclear Information System (INIS)

Zhang, Chunwei; Zhao, Hong; Jiang, Kejian

2016-01-01

The multi-frequency fringe-projection phase unwrapping method (MFPPUM) is a typical phase unwrapping algorithm for fringe projection profilometry. It has the advantage of being capable of correctly accomplishing phase unwrapping even in the presence of surface discontinuities. If the fringe frequency ratio of the MFPPUM is too large, fringe order error (FOE) may be triggered. FOE will result in phase unwrapping error. It is preferable for the phase unwrapping to be kept correct while the fewest sets of lower frequency fringe patterns are used. To achieve this goal, in this paper a parameter called fringe order inaccuracy (FOI) is defined, dominant factors which may induce FOE are theoretically analyzed, a method to optimally select the fringe periods for the MFPPUM is proposed with the aid of FOI, and experiments are conducted to research the impact of the dominant factors in phase unwrapping and demonstrate the validity of the proposed method. Some novel phenomena are revealed by these experiments. The proposed method helps to optimally select the fringe periods and detect the phase unwrapping error for the MFPPUM. (paper)

Improved time series prediction with a new method for selection of model parameters

International Nuclear Information System (INIS)

Jade, A M; Jayaraman, V K; Kulkarni, B D

2006-01-01

A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hoelder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. (letter to the editor)

A novel selection method of seismic attributes based on gray relational degree and support vector machine.

Directory of Open Access Journals (Sweden)

Yaping Huang

Full Text Available The selection of seismic attributes is a key process in reservoir prediction because the prediction accuracy relies on the reliability and credibility of the seismic attributes. However, effective selection method for useful seismic attributes is still a challenge. This paper presents a novel selection method of seismic attributes for reservoir prediction based on the gray relational degree (GRD and support vector machine (SVM. The proposed method has a two-hierarchical structure. In the first hierarchy, the primary selection of seismic attributes is achieved by calculating the GRD between seismic attributes and reservoir parameters, and the GRD between the seismic attributes. The principle of the primary selection is that these seismic attributes with higher GRD to the reservoir parameters will have smaller GRD between themselves as compared to those with lower GRD to the reservoir parameters. Then the SVM is employed in the second hierarchy to perform an interactive error verification using training samples for the purpose of determining the final seismic attributes. A real-world case study was conducted to evaluate the proposed GRD-SVM method. Reliable seismic attributes were selected to predict the coalbed methane (CBM content in southern Qinshui basin, China. In the analysis, the instantaneous amplitude, instantaneous bandwidth, instantaneous frequency, and minimum negative curvature were selected, and the predicted CBM content was fundamentally consistent with the measured CBM content. This real-world case study demonstrates that the proposed method is able to effectively select seismic attributes, and improve the prediction accuracy. Thus, the proposed GRD-SVM method can be used for the selection of seismic attributes in practice.

A novel heterogeneous training sample selection method on space-time adaptive processing

Science.gov (United States)

Wang, Qiang; Zhang, Yongshun; Guo, Yiduo

2018-04-01

The performance of ground target detection about space-time adaptive processing (STAP) decreases when non-homogeneity of clutter power is caused because of training samples contaminated by target-like signals. In order to solve this problem, a novel nonhomogeneous training sample selection method based on sample similarity is proposed, which converts the training sample selection into a convex optimization problem. Firstly, the existing deficiencies on the sample selection using generalized inner product (GIP) are analyzed. Secondly, the similarities of different training samples are obtained by calculating mean-hausdorff distance so as to reject the contaminated training samples. Thirdly, cell under test (CUT) and the residual training samples are projected into the orthogonal subspace of the target in the CUT, and mean-hausdorff distances between the projected CUT and training samples are calculated. Fourthly, the distances are sorted in order of value and the training samples which have the bigger value are selective preference to realize the reduced-dimension. Finally, simulation results with Mountain-Top data verify the effectiveness of the proposed method.

The selective dynamical downscaling method for extreme-wind atlases

DEFF Research Database (Denmark)

Larsén, Xiaoli Guo; Badger, Jake; Hahmann, Andrea N.

2012-01-01

A selective dynamical downscaling method is developed to obtain extreme-wind atlases for large areas. The method is general, efficient and flexible. The method consists of three steps: (i) identifying storm episodes for a particular area, (ii) downscaling of the storms using mesoscale modelling...... and (iii) post-processing. The post-processing generalizes the winds from the mesoscale modelling to standard conditions, i.e. 10-m height over a homogeneous surface with roughness length of 5 cm. The generalized winds are then used to calculate the 50-year wind using the annual maximum method for each...... mesoscale grid point. The generalization of the mesoscale winds through the post-processing provides a framework for data validation and for applying further the mesoscale extreme winds at specific places using microscale modelling. The results are compared with measurements from two areas with different...

A novel peak-hopping stepwise feature selection method with application to Raman spectroscopy

International Nuclear Information System (INIS)

McShane, M.J.; Cameron, B.D.; Cote, G.L.; Motamedi, M.; Spiegelman, C.H.

1999-01-01

A new stepwise approach to variable selection for spectroscopy that includes chemical information and attempts to test several spectral regions producing high ranking coefficients has been developed to improve on currently available methods. Existing selection techniques can, in general, be placed into two groups: the first, time-consuming optimization approaches that ignore available information about sample chemistry and require considerable expertise to arrive at appropriate solutions (e.g. genetic algorithms), and the second, stepwise procedures that tend to select many variables in the same area containing redundant information. The algorithm described here is a fast stepwise procedure that uses multiple ranking chains to identify several spectral regions correlated with known sample properties. The multiple-chain approach allows the generation of a final ranking vector that moves quickly away from the initial selection point, testing several areas exhibiting correlation between spectra and composition early in the stepping procedure. Quantitative evidence of the success of this approach as applied to Raman spectroscopy is given in terms of processing speed, number of selected variables, and prediction error in comparison with other selection methods. In this respect, the procedure described here may be considered as a significant evolutionary step in variable selection algorithms. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

A Ranking Method for Neutral Pion and Eta Selection in Hadronic Events

International Nuclear Information System (INIS)

Bingoel, A.

2004-01-01

The selection of neutral pions and etas with a high purity while maintaining also a high efficiency can be important in the formation of statistically significant mass spectra in the reconstruction of short-lived particles such as the omega meson (ω→π + + π - + π 0 ). In this study a Ranking method has been optimized for data from the ALEPH Experiment, CERN. The results show that the Ranking method, when applied to high multiplicity events, yields significant improvements in the purity of selected pion candidates and facilitates the relaxation of standard cuts thereby avoiding some systematic uncertainties

20 CFR 617.23 - Selection of training methods and programs.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Selection of training methods and programs. 617.23 Section 617.23 Employees' Benefits EMPLOYMENT AND TRAINING ADMINISTRATION, DEPARTMENT OF LABOR... for which training is undertaken shall not preclude the development of an individual retraining...

Standard methods for rearing and selection of Apis mellifera queens

DEFF Research Database (Denmark)

Büchler, Ralph; Andonov, Sreten; Bienefeld, Kaspar

2013-01-01

Here we cover a wide range of methods currently in use and recommended in modern queen rearing, selection and breeding. The recommendations are meant to equally serve as standards for both scientific and practical beekeeping purposes. The basic conditions and different management techniques for q...

Sampling point selection for energy estimation in the quasicontinuum method

NARCIS (Netherlands)

Beex, L.A.A.; Peerlings, R.H.J.; Geers, M.G.D.

2010-01-01

The quasicontinuum (QC) method reduces computational costs of atomistic calculations by using interpolation between a small number of so-called repatoms to represent the displacements of the complete lattice and by selecting a small number of sampling atoms to estimate the total potential energy of

Selection of candidate plus phenotypes of Jatropha curcas L. using method of paired comparisons

Energy Technology Data Exchange (ETDEWEB)

Mishra, D.K. [Silviculture Division, Arid Forest Research Institute, P.O. Krishi Mandi, New Pali Road, Jodhpur 342005, Rajasthan (India)

2009-03-15

Jatropha curcas L. (Euphorbiaceae) is an oil bearing species with multiple uses and considerable potential as a biodiesel crop. The present communication deals with the method of selecting plus phenotypes of J. curcas for exploiting genetic variability for further improvement. Candidate plus tree selection is the first and most important stage in any tree improvement programme. The selection of candidate plus plants (CPPs) is based upon various important attributes associated with the species and their relative ranking. Relative preference between various traits and scoring for each trait has been worked out by using the method of paired comparisons for the selection of CPP in J. curcas L. The most important ones are seed and oil yields. (author)

Testing the biocompatibility of a glutathione-containing intra-ocular irrigation solution by using an isolated perfused bovine retina organ culture model - an alternative to animal testing.

Science.gov (United States)

Januschowski, Kai; Zhour, Ahmad; Lee, Albert; Maddani, Ramin; Mueller, Sebastien; Spitzer, Martin S; Schnichels, Sven; Schultheiss, Maximilian; Doycheva, Deshka; Bartz-Schmidt, Karl-Ulrich; Szurman, Peter

2012-03-01

The effects of a glutathione-containing intra-ocular irrigation solution, BSS Plus©, on retinal function and on the survival of ganglion cells in whole-mount retinal explants were studied. Evidence is provided that the perfused ex vivo bovine retina can serve as an alternative to in vivo animal testing. Isolated bovine retinas were prepared and perfused with an oxygen-saturated standard irrigation solution, and an electroretinogram was recorded to assess retinal function. After stable b-waves were detected, the isolated retinas were perfused with BSS Plus for 45 minutes. To investigate the effects of BSS Plus on photoreceptor function, 1mM aspartate was added to the irrigation solution in order to obtain a-waves, and the ERG trace was monitored for 75 minutes. For histological analysis, isolated whole retinal mounts were stored for 24 hours at 4°C, in the dark. The percentages of cell death in the retinal ganglion cell layer and in the outer and inner nuclear layers were estimated by using an ethidium homodimer-1 stain and the TUNEL assay. General swelling of the retina was examined with high-resolution optical coherence tomography. During perfusion with BSS Plus, no significant changes in a-wave and b-wave amplitudes were recorded. Retinas stored for 24 hours in BSS Plus showed a statistically significant smaller percentage (52.6%, standard deviation [SD] = 16.1%) of cell death in the retinal ganglion cell layer compared to the control group (69.6%, SD = 3.9, p = 0.0031). BSS Plus did not seem to affect short-term retinal function, and had a beneficial effect on the survival of retinal ganglion cells. This method for analysing the isolated perfused retina represents a valuable alternative for testing substances for their retinal biocompatibility and toxicity. 2012 FRAME.

New evaluation methods for conceptual design selection using computational intelligence techniques

Energy Technology Data Exchange (ETDEWEB)

Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai [University of Electronic Science and Technology of China, Chengdu (China); Xue, Lihua [Higher Education Press, Beijing (China)

2013-03-15

The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

New evaluation methods for conceptual design selection using computational intelligence techniques

International Nuclear Information System (INIS)

Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai; Xue, Lihua

2013-01-01

The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

Revision of the Euratom basic safety standards directive-current status

International Nuclear Information System (INIS)

Mundig, S.

2011-01-01

The European Commission is currently developing a revised Euratom Basic Safety Standards (BSS) Directive covering two major objectives: the consolidation of existing Euratom Radiation Protection legislation and the revision of the Euratom BSS. The consolidation will merge the following five Directives into one single Directive: the BSS Directive, the Medical Exposures Directive, the Public Information Directive, the Outside Workers Directive and the Directive on the Control of high-activity sealed radioactive sources and orphan sources. The revision of the Euratom BSS will take account of the latest recommendations by the International Commission on Radiological Protection and shall improve clarity of the requirements where appropriate. It is planned to introduce more binding requirements on natural radiation sources, on criteria for exemption and clearance, and on the cooperation between Member States for emergency planning and response. The provisions for regulatory control of planned exposure situations foresee a graded approach commensurate to the magnitude and likelihood of exposures from a practice. Finally, the new BSS shall take account of recent scientific developments. One additional goal is to achieve greater harmonisation between the Euratom BSS and the international BSS. While the requirements on the protection of workers, apprentices and students remain nearly unchanged, the revised BSS will clarify the roles and responsibilities of services and experts involved in technical and practical aspects of radiation protection, such as the occupational health services, the dosimetry services, the radiation protection expert and the medical physics expert. The requirements in the BSS on individual monitoring of category A workers remain unchanged, but the existing guidance on individual monitoring was revised and updated-the technical recommendations for monitoring individuals occupationally exposed to external radiation are published by the European

A QSAR Study of Environmental Estrogens Based on a Novel Variable Selection Method

Directory of Open Access Journals (Sweden)

Aiqian Zhang

2012-05-01

Full Text Available A large number of descriptors were employed to characterize the molecular structure of 53 natural, synthetic, and environmental chemicals which are suspected of disrupting endocrine functions by mimicking or antagonizing natural hormones and may thus pose a serious threat to the health of humans and wildlife. In this work, a robust quantitative structure-activity relationship (QSAR model with a novel variable selection method has been proposed for the effective estrogens. The variable selection method is based on variable interaction (VSMVI with leave-multiple-out cross validation (LMOCV to select the best subset. During variable selection, model construction and assessment, the Organization for Economic Co-operation and Development (OECD principles for regulation of QSAR acceptability were fully considered, such as using an unambiguous multiple-linear regression (MLR algorithm to build the model, using several validation methods to assessment the performance of the model, giving the define of applicability domain and analyzing the outliers with the results of molecular docking. The performance of the QSAR model indicates that the VSMVI is an effective, feasible and practical tool for rapid screening of the best subset from large molecular descriptors.

Independent EEG sources are dipolar.

Directory of Open Access Journals (Sweden)

Arnaud Delorme

Full Text Available Independent component analysis (ICA and blind source separation (BSS methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA; best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison.

Feature Selection Methods for Zero-Shot Learning of Neural Activity

Directory of Open Access Journals (Sweden)

Carlos A. Caceres

2017-06-01

Full Text Available Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

Comparison of multimedia system and conventional method in patients’ selecting prosthetic treatment

Directory of Open Access Journals (Sweden)

Baghai R

2010-12-01

Full Text Available "nBackground and Aims: Selecting an appropriate treatment plan is one of the most critical aspects of dental treatments. The purpose of this study was to compare multimedia system and conventional method in patients' selecting prosthetic treatment and the time consumed."nMaterials and Methods: Ninety patients were randomly divided into three groups. Patients in group A, once were instructed using the conventional method of dental office and once multimedia system and time was measured in seconds from the beginning of the instruction till the patient had came to decision. The patients were asked about the satisfaction of the method used for them. In group B, patients were only instructed using the conventional method, whereas they were only exposed to soft ware in group C. The data were analyzed with Paired-T-test"n(in group A and T-test and Mann-Whitney test (in groups B and C."nResult: There was a significant difference between multimedia system and conventional method in group A and also between groups B and C (P<0.001. In group A and between groups B and C, patient's satisfaction about multimedia system was better. However, in comparison between groups B and C, multimedia system did not have a significant effect in treatment selection score (P=0.08."nConclusion: Using multimedia system is recommended due to its high ability in giving answers to a large number of patient's questions as well as in terms of marketing.

A method for selection of spent nuclear fuel (SNF) transportation route considering socioeconomic cost based on contingent valuation method (CVM)

International Nuclear Information System (INIS)

Kim, Young Sik

2008-02-01

A transportation of SNF may cause an additional radiation exposure to human beings. It means that the radiological risk should be estimated and managed quantitatively for the public who live near the shipments route. Before the SNF transportation is performed, the route selection is concluded based on the radiological risk estimated with RADTRAN code in existing method generally. It means the existing method for route selection is based only on the radiological health risk but there are not only the impacts related to the radiological health risk but also the socioeconomic impacts related to the cost. In this study, a new method and its numerical formula for route selection on transporting SNF is proposed based on cost estimation because there are several costs in transporting SNF. The total cost consists of radiological health cost, transportation cost, and socioeconomic cost. Each cost is defined properly to the characteristics of SNF transportation and many coefficients and variables describing the meaning of each cost are obtained or estimated through many surveys. Especially to get the socioeconomic cost, contingent valuation method (CVM) is used with a questionnaire. The socioeconomic cost estimation is the most important part of the total cost originated from transporting SNF because it is a very dominant cost in the total cost. The route selection regarding SNF transportation can be supported with the proposed method reasonably and unnecessary or exhausting controversies about the shipments could be avoided

Location of airports - selected quantitative methods

Directory of Open Access Journals (Sweden)

Agnieszka Merkisz-Guranowska

2016-09-01

Full Text Available Background: The role of air transport in  the economic development of a country and its regions cannot be overestimated. The decision concerning an airport's location must be in line with the expectations of all the stakeholders involved. This article deals with the issues related to the choice of  sites where airports should be located. Methods: Two main quantitative approaches related to the issue of airport location are presented in this article, i.e. the question of optimizing such a choice and the issue of selecting the location from a predefined set. The former involves mathematical programming and formulating the problem as an optimization task, the latter, however, involves ranking the possible variations. Due to various methodological backgrounds, the authors present the advantages and disadvantages of both approaches and point to the one which currently has its own practical application. Results: Based on real-life examples, the authors present a multi-stage procedure, which renders it possible to solve the problem of airport location. Conclusions: Based on the overview of literature of the subject, the authors point to three types of approach to the issue of airport location which could enable further development of currently applied methods.

Systematic differences in the response of genetic variation to pedigree and genome-based selection methods.

Science.gov (United States)

Heidaritabar, M; Vereijken, A; Muir, W M; Meuwissen, T; Cheng, H; Megens, H-J; Groenen, M A M; Bastiaansen, J W M

2014-12-01

Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60 K SNP chip with markers spaced throughout the entire chicken genome, we compared the impact of GS and traditional BLUP (best linear unbiased prediction) selection methods applied side-by-side in three different lines of egg-laying chickens. Differences were demonstrated between methods, both at the level and genomic distribution of allele frequency changes. In all three lines, the average allele frequency changes were larger with GS, 0.056 0.064 and 0.066, compared with BLUP, 0.044, 0.045 and 0.036 for lines B1, B2 and W1, respectively. With BLUP, 35 selected regions (empirical P selected regions were identified. Empirical thresholds for local allele frequency changes were determined from gene dropping, and differed considerably between GS (0.167-0.198) and BLUP (0.105-0.126). Between lines, the genomic regions with large changes in allele frequencies showed limited overlap. Our results show that GS applies selection pressure much more locally than BLUP, resulting in larger allele frequency changes. With these results, novel insights into the nature of selection on quantitative traits have been gained and important questions regarding the long-term impact of GS are raised. The rapid changes to a part of the genetic architecture, while another part may not be selected, at least in the short term, require careful consideration, especially when selection occurs before phenotypes are observed.

extrap: Software to assist the selection of extrapolation methods for moving-boat ADCP streamflow measurements

Science.gov (United States)

Mueller, David S.

2013-04-01

Selection of the appropriate extrapolation methods for computing the discharge in the unmeasured top and bottom parts of a moving-boat acoustic Doppler current profiler (ADCP) streamflow measurement is critical to the total discharge computation. The software tool, extrap, combines normalized velocity profiles from the entire cross section and multiple transects to determine a mean profile for the measurement. The use of an exponent derived from normalized data from the entire cross section is shown to be valid for application of the power velocity distribution law in the computation of the unmeasured discharge in a cross section. Selected statistics are combined with empirically derived criteria to automatically select the appropriate extrapolation methods. A graphical user interface (GUI) provides the user tools to visually evaluate the automatically selected extrapolation methods and manually change them, as necessary. The sensitivity of the total discharge to available extrapolation methods is presented in the GUI. Use of extrap by field hydrographers has demonstrated that extrap is a more accurate and efficient method of determining the appropriate extrapolation methods compared with tools currently (2012) provided in the ADCP manufacturers' software.

Computational Experiment Study on Selection Mechanism of Project Delivery Method Based on Complex Factors

Directory of Open Access Journals (Sweden)

Xiang Ding

2014-01-01

Full Text Available Project delivery planning is a key stage used by the project owner (or project investor for organizing design, construction, and other operations in a construction project. The main task in this stage is to select an appropriate project delivery method. In order to analyze different factors affecting the PDM selection, this paper establishes a multiagent model mainly to show how project complexity, governance strength, and market environment affect the project owner’s decision on PDM. Experiment results show that project owner usually choose Design-Build method when the project is very complex within a certain range. Besides, this paper points out that Design-Build method will be the prior choice when the potential contractors develop quickly. This paper provides the owners with methods and suggestions in terms of showing how the factors affect PDM selection, and it may improve the project performance.

Systematic differences in the response of genetic variation to pedigree and genome-based selection methods

NARCIS (Netherlands)

Heidaritabar, M.; Vereijken, A.; Muir, W.M.; Meuwissen, T.H.E.; Cheng, H.; Megens, H.J.W.C.; Groenen, M.; Bastiaansen, J.W.M.

2014-01-01

Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60¿K SNP chip with markers spaced throughout the

System and method for programmable bank selection for banked memory subsystems

Energy Technology Data Exchange (ETDEWEB)

Blumrich, Matthias A. (Ridgefield, CT); Chen, Dong (Croton on Hudson, NY); Gara, Alan G. (Mount Kisco, NY); Giampapa, Mark E. (Irvington, NY); Hoenicke, Dirk (Seebruck-Seeon, DE); Ohmacht, Martin (Yorktown Heights, NY); Salapura, Valentina (Chappaqua, NY); Sugavanam, Krishnan (Mahopac, NY)

2010-09-07

A programmable memory system and method for enabling one or more processor devices access to shared memory in a computing environment, the shared memory including one or more memory storage structures having addressable locations for storing data. The system comprises: one or more first logic devices associated with a respective one or more processor devices, each first logic device for receiving physical memory address signals and programmable for generating a respective memory storage structure select signal upon receipt of pre-determined address bit values at selected physical memory address bit locations; and, a second logic device responsive to each of the respective select signal for generating an address signal used for selecting a memory storage structure for processor access. The system thus enables each processor device of a computing environment memory storage access distributed across the one or more memory storage structures.

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

Science.gov (United States)

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

Flexible Design for α-Duplex Communications in Multi-Tier Cellular Networks

KAUST Repository

AlAmmouri, Ahmad

2016-06-13

Backward compatibility is an essential ingredient for the success of new technologies. In the context of inband full-duplex (FD) communication, FD base stations (BSs) should support half-duplex (HD) users’ equipment (UEs) without sacrificing the foreseen FD gains. This paper presents flexible and tractable modeling framework for multi-tier cellular networks with FD BSs and FD/HD UEs. The presented model is based on stochastic geometry and accounts for the intrinsic vulnerability of uplink transmissions. The results show that FD UEs are not necessarily required to harvest rate gains from FD BSs. In particular, the results show that adding FD UEs to FD BSs offers a maximum of 5% rate gain over FD BSs and HD UEs case if multi-user diversity is exploited, which is a marginal gain compared to the burden required to implement FD transceivers at the UEs’ side. To this end, we shed light on practical scenarios where HD UEs operation with FD BSs outperforms the operation when both the BSs and UEs are FD and we find a closed form expression for the critical value of the self-interference attenuation power required for the FD UEs to outperform HD UEs.

A kernel-based multivariate feature selection method for microarray data classification.

Directory of Open Access Journals (Sweden)

Shiquan Sun

Full Text Available High dimensionality and small sample sizes, and their inherent risk of overfitting, pose great challenges for constructing efficient classifiers in microarray data classification. Therefore a feature selection technique should be conducted prior to data classification to enhance prediction performance. In general, filter methods can be considered as principal or auxiliary selection mechanism because of their simplicity, scalability, and low computational complexity. However, a series of trivial examples show that filter methods result in less accurate performance because they ignore the dependencies of features. Although few publications have devoted their attention to reveal the relationship of features by multivariate-based methods, these methods describe relationships among features only by linear methods. While simple linear combination relationship restrict the improvement in performance. In this paper, we used kernel method to discover inherent nonlinear correlations among features as well as between feature and target. Moreover, the number of orthogonal components was determined by kernel Fishers linear discriminant analysis (FLDA in a self-adaptive manner rather than by manual parameter settings. In order to reveal the effectiveness of our method we performed several experiments and compared the results between our method and other competitive multivariate-based features selectors. In our comparison, we used two classifiers (support vector machine, [Formula: see text]-nearest neighbor on two group datasets, namely two-class and multi-class datasets. Experimental results demonstrate that the performance of our method is better than others, especially on three hard-classify datasets, namely Wang's Breast Cancer, Gordon's Lung Adenocarcinoma and Pomeroy's Medulloblastoma.

Energy Sustainable Mobile Networks via Energy Routing, Learning and Foresighted Optimization

OpenAIRE

Gambin, Angel Fernandez; Scalabrin, Maria; Rossi, Michele

2018-01-01

The design of self-sustainable base station (BS) deployments is addressed in this paper: BSs have energy harvesting and storage capabilities, they can use ambient energy to serve the local traffic or store it for later use. A dedicated power packet grid allows energy transfer across BSs, compensating for imbalance in the harvested energy or in the traffic load. Some BSs are offgrid, i.e., they can only use the locally harvested energy and that transferred from other BSs, whereas others are on...

Variable selection methods in PLS regression - a comparison study on metabolomics data

DEFF Research Database (Denmark)

Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach

. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using LC-MS based metabolomic approach. References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse PLS for Variable Selection when...... integrated approach. Due to the high number of variables in data sets (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need to be related. Variable selection (or removal of irrelevant...... different strategies for variable selection on PLSR method were considered and compared with respect to selected subset of variables and the possibility for biological validation. Sparse PLSR [1] as well as PLSR with Jack-knifing [2] was applied to data in order to achieve variable selection prior...

Evaluation of an Improved Branch-Site Likelihood Method for Detecting Positive Selection at the Molecular Level

DEFF Research Database (Denmark)

Zhang, Jianzhi; Nielsen, Rasmus; Yang, Ziheng

2005-01-01

of interest, while test 2 had acceptable false-positive rates and appeared robust against violations of model assumptions. As test 2 is a direct test of positive selection on the lineages of interest, it is referred to as the branch-site test of positive selection and is recommended for use in real data......Detecting positive Darwinian selection at the DNA sequence level has been a subject of considerable interest. However, positive selection is difficult to detect because it often operates episodically on a few amino acid sites, and the signal may be masked by negative selection. Several methods have...... been developed to test positive selection that acts on given branches (branch methods) or on a subset of sites (site methods). Recently, Yang, Z., and R. Nielsen (2002. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol. Biol. Evol. 19...

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

Science.gov (United States)

Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

A target recognition method for maritime surveillance radars based on hybrid ensemble selection

Science.gov (United States)

Fan, Xueman; Hu, Shengliang; He, Jingbo

2017-11-01

In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

Locating disease genes using Bayesian variable selection with the Haseman-Elston method

Directory of Open Access Journals (Sweden)

He Qimei

2003-12-01

Full Text Available Abstract Background We applied stochastic search variable selection (SSVS, a Bayesian model selection method, to the simulated data of Genetic Analysis Workshop 13. We used SSVS with the revisited Haseman-Elston method to find the markers linked to the loci determining change in cholesterol over time. To study gene-gene interaction (epistasis and gene-environment interaction, we adopted prior structures, which incorporate the relationship among the predictors. This allows SSVS to search in the model space more efficiently and avoid the less likely models. Results In applying SSVS, instead of looking at the posterior distribution of each of the candidate models, which is sensitive to the setting of the prior, we ranked the candidate variables (markers according to their marginal posterior probability, which was shown to be more robust to the prior. Compared with traditional methods that consider one marker at a time, our method considers all markers simultaneously and obtains more favorable results. Conclusions We showed that SSVS is a powerful method for identifying linked markers using the Haseman-Elston method, even for weak effects. SSVS is very effective because it does a smart search over the entire model space.

Optimized green operation of LTE networks in the presence of multiple electricity providers

KAUST Repository

Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim; Abu-Dayya, Adnan A.

2012-01-01

Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.

Optimized green operation of LTE networks in the presence of multiple electricity providers

KAUST Repository

Ghazzai, Hakim

2012-12-01

Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.

Explicit Content Caching at Mobile Edge Networks with Cross-Layer Sensing

Science.gov (United States)

Chen, Lingyu; Su, Youxing; Luo, Wenbin; Hong, Xuemin; Shi, Jianghong

2018-01-01

The deployment density and computational power of small base stations (BSs) are expected to increase significantly in the next generation mobile communication networks. These BSs form the mobile edge network, which is a pervasive and distributed infrastructure that can empower a variety of edge/fog computing applications. This paper proposes a novel edge-computing application called explicit caching, which stores selective contents at BSs and exposes such contents to local users for interactive browsing and download. We formulate the explicit caching problem as a joint content recommendation, caching, and delivery problem, which aims to maximize the expected user quality-of-experience (QoE) with varying degrees of cross-layer sensing capability. Optimal and effective heuristic algorithms are presented to solve the problem. The theoretical performance bounds of the explicit caching system are derived in simplified scenarios. The impacts of cache storage space, BS backhaul capacity, cross-layer information, and user mobility on the system performance are simulated and discussed in realistic scenarios. Results suggest that, compared with conventional implicit caching schemes, explicit caching can better exploit the mobile edge network infrastructure for personalized content dissemination. PMID:29565313

Explicit Content Caching at Mobile Edge Networks with Cross-Layer Sensing.

Science.gov (United States)

Chen, Lingyu; Su, Youxing; Luo, Wenbin; Hong, Xuemin; Shi, Jianghong

2018-03-22

The deployment density and computational power of small base stations (BSs) are expected to increase significantly in the next generation mobile communication networks. These BSs form the mobile edge network, which is a pervasive and distributed infrastructure that can empower a variety of edge/fog computing applications. This paper proposes a novel edge-computing application called explicit caching, which stores selective contents at BSs and exposes such contents to local users for interactive browsing and download. We formulate the explicit caching problem as a joint content recommendation, caching, and delivery problem, which aims to maximize the expected user quality-of-experience (QoE) with varying degrees of cross-layer sensing capability. Optimal and effective heuristic algorithms are presented to solve the problem. The theoretical performance bounds of the explicit caching system are derived in simplified scenarios. The impacts of cache storage space, BS backhaul capacity, cross-layer information, and user mobility on the system performance are simulated and discussed in realistic scenarios. Results suggest that, compared with conventional implicit caching schemes, explicit caching can better exploit the mobile edge network infrastructure for personalized content dissemination.

Robust gene selection methods using weighting schemes for microarray data analysis.

Science.gov (United States)

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

NON-CONVENTIONAL MACHINING PROCESSES SELECTION USING MULTI-OBJECTIVE OPTIMIZATION ON THE BASIS OF RATIO ANALYSIS METHOD

Directory of Open Access Journals (Sweden)

MILOŠ MADIĆ

2015-11-01

Full Text Available The role of non-conventional machining processes (NCMPs in today’s manufacturing environment has been well acknowledged. For effective utilization of the capabilities and advantages of different NCMPs, selection of the most appropriate NCMP for a given machining application requires consideration of different conflicting criteria. The right choice of the NCMP is critical to the success and competitiveness of the company. As the NCMP selection problem involves consideration of different conflicting criteria, of different relative importance, the multi-criteria decision making (MCDM methods are very useful in systematical selection of the most appropriate NCMP. This paper presents the application of a recent MCDM method, i.e., the multi-objective optimization on the basis of ratio analysis (MOORA method to solve NCMP selection which has been defined considering different performance criteria of four most widely used NCMPs. In order to determine the relative significance of considered quality criteria a pair-wise comparison matrix of the analytic hierarchy process was used. The results obtained using the MOORA method showed perfect correlation with those obtained by the technique for order preference by similarity to ideal solution (TOPSIS method which proves the applicability and potentiality of this MCDM method for solving complex NCMP selection problems.

Study on the partner selecting method of strategic alliance in high and new technology enterprises

Institute of Scientific and Technical Information of China (English)

王宏起; 唐宇; 迟运领

2004-01-01

A successful and effective strategic alliance involves many factors, of which selecting a proper partner is the most important factor to achieve the success of the alliance. In view of the characteristics of strategic alliance in high and new technology enterprises and according to the analysis on the standards of partner selecting and the factors of the success of alliance, this paper does some deeper research on the partner selecting and the alliance evaluation process from the perspective of different strategic levels by using a fuzzy comprehensive evaluating method, thus providing a method to select the alliance partner for high and new technology enterprises in China.

Method of generating intense nuclear polarized beams by selective photodetachment of negative ions

International Nuclear Information System (INIS)

Hershcovitch, A.

1986-01-01

A novel method for production of nuclear polarized negative hydrogen ions by selective neutralization with a laser of negative hydrogen ions in a magnetic field is described. This selectivity is possible since a final state of the neutralized atom, and hence the neutralization energy, depends on its nuclear polarization. The main advantages of this scheme are the availability of multi-ampere negative ion sources and the possibility of neutralizing negative ions with very high efficiency. An assessment of the required laser power indicates that this method is in principle feasible with today's technology

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

Directory of Open Access Journals (Sweden)

Jun-He Yang

2017-01-01

Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem

Science.gov (United States)

Aytaç Adalı, Esra; Tuş Işık, Ayşegül

2017-06-01

A decision making process requires the values of conflicting objectives for alternatives and the selection of the best alternative according to the needs of decision makers. Multi-objective optimization methods may provide solution for this selection. In this paper it is aimed to present the laptop selection problem based on MOORA plus full multiplicative form (MULTIMOORA) and multi-objective optimization on the basis of simple ratio analysis (MOOSRA) which are relatively new multi-objective optimization methods. The novelty of this paper is solving this problem with the MULTIMOORA and MOOSRA methods for the first time.

Proposed Project Selection Method for Human Support Research and Technology Development (HSR&TD)

Science.gov (United States)

Jones, Harry

2005-01-01

The purpose of HSR&TD is to deliver human support technologies to the Exploration Systems Mission Directorate (ESMD) that will be selected for future missions. This requires identifying promising candidate technologies and advancing them in technology readiness until they are acceptable. HSR&TD must select an may of technology development projects, guide them, and either terminate or continue them, so as to maximize the resulting number of usable advanced human support technologies. This paper proposes an effective project scoring methodology to support managing the HSR&TD project portfolio. Researchers strongly disagree as to what are the best technology project selection methods, or even if there are any proven ones. Technology development is risky and outstanding achievements are rare and unpredictable. There is no simple formula for success. Organizations that are satisfied with their project selection approach typically use a mix of financial, strategic, and scoring methods in an open, established, explicit, formal process. This approach helps to build consensus and develop management insight. It encourages better project proposals by clarifying the desired project attributes. We propose a project scoring technique based on a method previously used in a federal laboratory and supported by recent research. Projects are ranked by their perceived relevance, risk, and return - a new 3 R's. Relevance is the degree to which the project objective supports the HSR&TD goal of developing usable advanced human support technologies. Risk is the estimated probability that the project will achieve its specific objective. Return is the reduction in mission life cycle cost obtained if the project is successful. If the project objective technology performs a new function with no current cost, its return is the estimated cash value of performing the new function. The proposed project selection scoring method includes definitions of the criteria, a project evaluation

Research on Big Data Attribute Selection Method in Submarine Optical Fiber Network Fault Diagnosis Database

Directory of Open Access Journals (Sweden)

Chen Ganlang

2017-11-01

Full Text Available At present, in the fault diagnosis database of submarine optical fiber network, the attribute selection of large data is completed by detecting the attributes of the data, the accuracy of large data attribute selection cannot be guaranteed. In this paper, a large data attribute selection method based on support vector machines (SVM for fault diagnosis database of submarine optical fiber network is proposed. Mining large data in the database of optical fiber network fault diagnosis, and calculate its attribute weight, attribute classification is completed according to attribute weight, so as to complete attribute selection of large data. Experimental results prove that ,the proposed method can improve the accuracy of large data attribute selection in fault diagnosis database of submarine optical fiber network, and has high use value.

Systematic Methods in School Planning and Design. A Selected and Annotated Bibliography.

Science.gov (United States)

Murtha, D. Michael

A selection of technical reports, journal articles and books on various aspects of systematic methods for school planning and design, are presented in this bibliography. The subject areas include the design process in terms of--(1) practice, (2) theory, (3) methods, (4) decision systems, and (5) computer applications. Criteria for design with…

Simulation-based investigation of the paired-gear method in cod-end selectivity studies

DEFF Research Database (Denmark)

Herrmann, Bent; Frandsen, Rikke; Holst, René

2007-01-01

In this paper, the paired-gear and covered cod-end methods for estimating the selectivity of trawl cod-ends are compared. A modified version of the cod-end selectivity simulator PRESEMO is used to simulate the data that would be collected from a paired-gear experiment where the test cod-end also ...

Achieving energy efficiency in LTE with joint D2D communications and green networking techniques

KAUST Repository

Yaacoub, Elias E.

2013-07-01

In this paper, the joint operation of cooperative device-to-device (D2D) communications and green cellular communications is investigated. An efficient approach for grouping mobile terminals (MTs) into cooperative clusters is described. In each cluster, MTs cooperate via D2D communications to share content of common interest. Furthermore, an energy-efficient technique for putting BSs in sleep mode in an LTE cellular network is presented. Finally, both methods are combined in order to ensure green communications for both the users\\' MTs and the operator\\'s BSs. The studied methods are investigated in the framework of OFDMA-based state-of-the-art LTE cellular networks, while taking into account intercell interference and resource allocation. © 2013 IEEE.

A Method to Select Software Test Cases in Consideration of Past Input Sequence

International Nuclear Information System (INIS)

Kim, Hee Eun; Kim, Bo Gyung; Kang, Hyun Gook

2015-01-01

In the Korea Nuclear I and C Systems (KNICS) project, the software for the fully-digitalized reactor protection system (RPS) was developed under a strict procedure. Even though the behavior of the software is deterministic, the randomness of input sequence produces probabilistic behavior of software. A software failure occurs when some inputs to the software occur and interact with the internal state of the digital system to trigger a fault that was introduced into the software during the software lifecycle. In this paper, the method to select test set for software failure probability estimation is suggested. This test set reflects past input sequence of software, which covers all possible cases. In this study, the method to select test cases for software failure probability quantification was suggested. To obtain profile of paired state variables, relationships of the variables need to be considered. The effect of input from human operator also have to be considered. As an example, test set of PZR-PR-Lo-Trip logic was examined. This method provides framework for selecting test cases of safety-critical software

A New Manufacturing Service Selection and Composition Method Using Improved Flower Pollination Algorithm

Directory of Open Access Journals (Sweden)

Wenyu Zhang

2016-01-01

Full Text Available With an increasing number of manufacturing services, the means by which to select and compose these manufacturing services have become a challenging problem. It can be regarded as a multiobjective optimization problem that involves a variety of conflicting quality of service (QoS attributes. In this study, a multiobjective optimization model of manufacturing service composition is presented that is based on QoS and an environmental index. Next, the skyline operator is applied to reduce the solution space. And then a new method called improved Flower Pollination Algorithm (FPA is proposed for solving the problem of manufacturing service selection and composition. The improved FPA enhances the performance of basic FPA by combining the latter with crossover and mutation operators of the Differential Evolution (DE algorithm. Finally, a case study is conducted to compare the proposed method with other evolutionary algorithms, including the Genetic Algorithm, DE, basic FPA, and extended FPA. The experimental results reveal that the proposed method performs best at solving the problem of manufacturing service selection and composition.

Method for selecting FBR development strategies in the presence of uncertainty

International Nuclear Information System (INIS)

Fraley, D.W.; Burnham, J.B.

1981-12-01

This report describes the methods used to probabilistically analyze data related to the uranium supply the FBR's competitive dates, development strategies' time and costs, and economic benefits. It also describes the econometric methods used to calculate the economic risks of mistiming the development. Seven strategies for developing the FBR are analyzed. The various measures of a strategy's performance - timing, costs, benefits, and risks - are combined into several criteria which are used to evaluate the seven strategies. Methods are described for selecting a strategy based on a number of alternative criteria

Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.

Science.gov (United States)

Sahran, Shahnorbanun; Albashish, Dheeb; Abdullah, Azizi; Shukor, Nordashima Abd; Hayati Md Pauzi, Suria

2018-04-18

Feature selection (FS) methods are widely used in grading and diagnosing prostate histopathological images. In this context, FS is based on the texture features obtained from the lumen, nuclei, cytoplasm and stroma, all of which are important tissue components. However, it is difficult to represent the high-dimensional textures of these tissue components. To solve this problem, we propose a new FS method that enables the selection of features with minimal redundancy in the tissue components. We categorise tissue images based on the texture of individual tissue components via the construction of a single classifier and also construct an ensemble learning model by merging the values obtained by each classifier. Another issue that arises is overfitting due to the high-dimensional texture of individual tissue components. We propose a new FS method, SVM-RFE(AC), that integrates a Support Vector Machine-Recursive Feature Elimination (SVM-RFE) embedded procedure with an absolute cosine (AC) filter method to prevent redundancy in the selected features of the SV-RFE and an unoptimised classifier in the AC. We conducted experiments on H&E histopathological prostate and colon cancer images with respect to three prostate classifications, namely benign vs. grade 3, benign vs. grade 4 and grade 3 vs. grade 4. The colon benchmark dataset requires a distinction between grades 1 and 2, which are the most difficult cases to distinguish in the colon domain. The results obtained by both the single and ensemble classification models (which uses the product rule as its merging method) confirm that the proposed SVM-RFE(AC) is superior to the other SVM and SVM-RFE-based methods. We developed an FS method based on SVM-RFE and AC and successfully showed that its use enabled the identification of the most crucial texture feature of each tissue component. Thus, it makes possible the distinction between multiple Gleason grades (e.g. grade 3 vs. grade 4) and its performance is far superior to

METHODS OF SELECTING THE EFFECTIVE MODELS OF BUILDINGS REPROFILING PROJECTS

Directory of Open Access Journals (Sweden)

Александр Иванович МЕНЕЙЛЮК

2016-02-01

Full Text Available The article highlights the important task of project management in reprofiling of buildings. It is expedient to pay attention to selecting effective engineering solutions to reduce the duration and cost reduction at the project management in the construction industry. This article presents a methodology for the selection of efficient organizational and technical solutions for the reconstruction of buildings reprofiling. The method is based on a compilation of project variants in the program Microsoft Project and experimental statistical analysis using the program COMPEX. The introduction of this technique in the realigning of buildings allows choosing efficient models of projects, depending on the given constraints. Also, this technique can be used for various construction projects.

Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures.

Science.gov (United States)

Bastiaansen, John W M; Coster, Albart; Calus, Mario P L; van Arendonk, Johan A M; Bovenhuis, Henk

2012-01-24

Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects. Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations. Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure. The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

Science.gov (United States)

Tučník, Petr; Bureš, Vladimír

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

Entropy Based Test Point Evaluation and Selection Method for Analog Circuit Fault Diagnosis

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Yuan Gao

2014-01-01

Full Text Available By simplifying tolerance problem and treating faulty voltages on different test points as independent variables, integer-coded table technique is proposed to simplify the test point selection process. Usually, simplifying tolerance problem may induce a wrong solution while the independence assumption will result in over conservative result. To address these problems, the tolerance problem is thoroughly considered in this paper, and dependency relationship between different test points is considered at the same time. A heuristic graph search method is proposed to facilitate the test point selection process. First, the information theoretic concept of entropy is used to evaluate the optimality of test point. The entropy is calculated by using the ambiguous sets and faulty voltage distribution, determined by component tolerance. Second, the selected optimal test point is used to expand current graph node by using dependence relationship between the test point and graph node. Simulated results indicate that the proposed method more accurately finds the optimal set of test points than other methods; therefore, it is a good solution to minimize the size of the test point set. To simplify and clarify the proposed method, only catastrophic and some specific parametric faults are discussed in this paper.

Using and reporting the Delphi method for selecting healthcare quality indicators: a systematic review.

Science.gov (United States)

Boulkedid, Rym; Abdoul, Hendy; Loustau, Marine; Sibony, Olivier; Alberti, Corinne

2011-01-01

Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi method to develop quality indicators, 2) to discuss specific methodological skills for quality indicators selection 3) to give guidance about this practice. Three electronic data bases were searched over a 30 years period (1978-2009). All articles that used the Delphi method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. The use and reporting of the Delphi method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the method in future surveys.

Using and reporting the Delphi method for selecting healthcare quality indicators: a systematic review.

Directory of Open Access Journals (Sweden)

Rym Boulkedid

Full Text Available OBJECTIVE: Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1 to describe reporting of the Delphi method to develop quality indicators, 2 to discuss specific methodological skills for quality indicators selection 3 to give guidance about this practice. METHODOLOGY AND MAIN FINDING: Three electronic data bases were searched over a 30 years period (1978-2009. All articles that used the Delphi method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used. Reporting of methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80 of studies reported response rates for all rounds, 60% (48/80 that feedback was given between rounds, 77% (62/80 the method used to achieve consensus and 57% (48/80 listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63% with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31. In 40/70 (57% studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40 of cases. Among 75 studies describing criteria to select quality indicators, 28 (37% used validity and 17(23% feasibility. CONCLUSION: The use and reporting of the Delphi method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the method in future surveys.

Analysis of a wavelength selectable cascaded DFB laser based on the transfer matrix method

International Nuclear Information System (INIS)

Xie Hongyun; Chen Liang; Shen Pei; Sun Botao; Wang Renqing; Xiao Ying; You Yunxia; Zhang Wanrong

2010-01-01

A novel cascaded DFB laser, which consists of two serial gratings to provide selectable wavelengths, is presented and analyzed by the transfer matrix method. In this method, efficient facet reflectivity is derived from the transfer matrix built for each serial section and is then used to simulate the performance of the novel cascaded DFB laser through self-consistently solving the gain equation, the coupled wave equation and the current continuity equations. The simulations prove the feasibility of this kind of wavelength selectable laser and a corresponding designed device with two selectable wavelengths of 1.51 μm and 1.53 μm is realized by experiments on InP-based multiple quantum well structure. (semiconductor devices)

Methods of selecting factors in the analysis of the real estates market

OpenAIRE

Jasińska, Elżbieta; Preweda, Edward

2006-01-01

In the paper the problem of selecting the method of choosing factors in factorial analysis is presented. For the database of 61 real estates the process of singling out the factors was carried out with the use of all the methods proposed in the STATISTICA 6.0 pack. A particular attention was paid on the number of differentiated factors and the efficiency of subsequent methods for the analysis of the real estates market. Edward Preweda

SORIOS – A method for evaluating and selecting environmental certificates and labels

DEFF Research Database (Denmark)

Kikkenborg Pedersen, Dennis; Dukovska-Popovska, Iskra; Ola Strandhagen, Jan

2012-01-01

This paper presents a general method for evaluating and selecting environmental certificates and labels for companies to use on products and services. The method is developed based on a case study using a Grounded Theory approach. The result is a generalized six-step method that features an initial...... searching strategy and an evaluation model that weighs the prerequisites, rewards and the organization of certificate or label against the strategic needs of a company....

Aplication of AHP method in partner's selection process for supply chain development

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Barac Nada

2012-06-01

Full Text Available The process of developing a supply chain is long and complex. with many restrictions and obstacles that accompany it. In this paper the authors focus on the first stage in developing the supply chain and the selection process and selection of partners. This phase of the development significantly affect the competitive position of the supply chain and create value for the consumer. Selected partners or 'links' of the supply chain influence the future performance of the chain which points to the necessity of full commitment to this process. The process of selection and choice of partner is conditioned by the key criteria that are used on that occasion. The use of inadequate criteria may endanger the whole process of building a supply chain partner selection through inadequate future supply chain needs. This paper is an analysis of partner selection based on key criteria used by managers in Serbia. For this purpose we used the AHP method. the results show that these are the top ranked criteria in terms of managers.

Implantation of a new Beta Secondary Standard system at Centro de Desenvolvimento da Tecnologia Nuclear

International Nuclear Information System (INIS)

Reynaldo, Sibele Reis

2005-01-01

The crescent use of beta radiation sources in medical, industrial and research applications has increased the need for higher accuracy in beta dosimetry. As the first Beta Secondary Standard system (BSS1) was developed about 20 years ago, a new BSS2 system was made commercially available to fulfill new metrological demands and to follow the technological development. The BSS2 has a new positioning set-up, high activity and long half-life beta radiation sources and a special safety system. The Centro de Desenvolvimento da Tecnologia Nuclear is the first laboratory in Latin America that has got a BSS2. This work describes the BSS2 and it compares its advantages in relation to BSS1; results of the beam uniformity tests of the radiation fields from 90 Sr/ 90 Y, 85 Kr and 147 Pm sources, that were measured with an ionization chamber and with thermoluminescent detectors, are also shown. Results show that the beta radiation fields are considered to be uniform for diameters between 8 and 20 cm according to the chosen source. (author)

A DYNAMIC FEATURE SELECTION METHOD FOR DOCUMENT RANKING WITH RELEVANCE FEEDBACK APPROACH

Directory of Open Access Journals (Sweden)

K. Latha

2010-07-01

Full Text Available Ranking search results is essential for information retrieval and Web search. Search engines need to not only return highly relevant results, but also be fast to satisfy users. As a result, not all available features can be used for ranking, and in fact only a small percentage of these features can be used. Thus, it is crucial to have a feature selection mechanism that can find a subset of features that both meets latency requirements and achieves high relevance. In this paper we describe a 0/1 knapsack procedure for automatically selecting features to use within Generalization model for Document Ranking. We propose an approach for Relevance Feedback using Expectation Maximization method and evaluate the algorithm on the TREC Collection for describing classes of feedback textual information retrieval features. Experimental results, evaluated on standard TREC-9 part of the OHSUMED collections, show that our feature selection algorithm produces models that are either significantly more effective than, or equally effective as, models such as Markov Random Field model, Correlation Co-efficient and Count Difference method

A general method for selection of riboflavin-overproducing food grade micro-organisms

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Rutten Ger

2006-07-01

Full Text Available Abstract Background This study describes a strategy to select and isolate spontaneous riboflavin-overproducing strains of Lactobacillus (Lb. plantarum, Leuconostoc (Lc. mesenteroides and Propionibacterium (P. freudenreichii. Results The toxic riboflavin analogue roseoflavin was used to isolate natural riboflavin-overproducing variants of the food grade micro-organisms Lb. plantarum, Lc. mesenteroides and P. freudenreichii strains. The method was successfully employed for strains of all three species. The mutation(s responsible for the observed overproduction of riboflavin were identified for isolates of two species. Conclusion Selection for spontaneous roseoflavin-resistant mutants was found to be a reliable method to obtain natural riboflavin-overproducing strains of a number of species commonly used in the food industry. This study presents a convenient method for deriving riboflavin-overproducing strains of bacterial starter cultures, which are currently used in the food industry, by a non-recombinant methodology. Use of such starter strains can be exploited to increase the vitamin content in certain food products.

Method for selection of optimal road safety composite index with examples from DEA and TOPSIS method.

Science.gov (United States)

Rosić, Miroslav; Pešić, Dalibor; Kukić, Dragoslav; Antić, Boris; Božović, Milan

2017-01-01

Concept of composite road safety index is a popular and relatively new concept among road safety experts around the world. As there is a constant need for comparison among different units (countries, municipalities, roads, etc.) there is need to choose an adequate method which will make comparison fair to all compared units. Usually comparisons using one specific indicator (parameter which describes safety or unsafety) can end up with totally different ranking of compared units which is quite complicated for decision maker to determine "real best performers". Need for composite road safety index is becoming dominant since road safety presents a complex system where more and more indicators are constantly being developed to describe it. Among wide variety of models and developed composite indexes, a decision maker can come to even bigger dilemma than choosing one adequate risk measure. As DEA and TOPSIS are well-known mathematical models and have recently been increasingly used for risk evaluation in road safety, we used efficiencies (composite indexes) obtained by different models, based on DEA and TOPSIS, to present PROMETHEE-RS model for selection of optimal method for composite index. Method for selection of optimal composite index is based on three parameters (average correlation, average rank variation and average cluster variation) inserted into a PROMETHEE MCDM method in order to choose the optimal one. The model is tested by comparing 27 police departments in Serbia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimized smart grid energy procurement for LTE networks using evolutionary algorithms

KAUST Repository

Ghazzai, Hakim

2014-11-01

Energy efficiency aspects in cellular networks can contribute significantly to reducing worldwide greenhouse gas emissions. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Moreover, introducing renewable energy as an alternative power source has become a real challenge among network operators. In this paper, we formulate an optimization problem that aims to maximize the profit of Long-Term Evolution (LTE) cellular operators and to simultaneously minimize the CO2 emissions in green wireless cellular networks without affecting the desired quality of service (QoS). The BS sleeping strategy lends itself to an interesting implementation using several heuristic approaches, such as the genetic (GA) and particle swarm optimization (PSO) algorithms. In this paper, we propose GA-based and PSO-based methods that reduce the energy consumption of BSs by not only shutting down underutilized BSs but by optimizing the amounts of energy procured from different retailers (renewable energy and electricity retailers), as well. A comparison with another previously proposed algorithm is also carried out to evaluate the performance and the computational complexity of the employed methods.

A new and fast image feature selection method for developing an optimal mammographic mass detection scheme.

Science.gov (United States)

Tan, Maxine; Pu, Jiantao; Zheng, Bin

2014-08-01

Selecting optimal features from a large image feature pool remains a major challenge in developing computer-aided detection (CAD) schemes of medical images. The objective of this study is to investigate a new approach to significantly improve efficacy of image feature selection and classifier optimization in developing a CAD scheme of mammographic masses. An image dataset including 1600 regions of interest (ROIs) in which 800 are positive (depicting malignant masses) and 800 are negative (depicting CAD-generated false positive regions) was used in this study. After segmentation of each suspicious lesion by a multilayer topographic region growth algorithm, 271 features were computed in different feature categories including shape, texture, contrast, isodensity, spiculation, local topological features, as well as the features related to the presence and location of fat and calcifications. Besides computing features from the original images, the authors also computed new texture features from the dilated lesion segments. In order to select optimal features from this initial feature pool and build a highly performing classifier, the authors examined and compared four feature selection methods to optimize an artificial neural network (ANN) based classifier, namely: (1) Phased Searching with NEAT in a Time-Scaled Framework, (2) A sequential floating forward selection (SFFS) method, (3) A genetic algorithm (GA), and (4) A sequential forward selection (SFS) method. Performances of the four approaches were assessed using a tenfold cross validation method. Among these four methods, SFFS has highest efficacy, which takes 3%-5% of computational time as compared to GA approach, and yields the highest performance level with the area under a receiver operating characteristic curve (AUC) = 0.864 ± 0.034. The results also demonstrated that except using GA, including the new texture features computed from the dilated mass segments improved the AUC results of the ANNs optimized

Selection of the Bank Investment Strategy on the Basis of the Hierarchy Analysis Method

Directory of Open Access Journals (Sweden)

Zhytar Maksym O.

2014-02-01

Full Text Available The goal of the article lies in identification of a methodical approach to selection of the investment strategy of banks on the basis of factors of its formation with the use of the hierarchy analysis method. Factors of formation of the bank’s investment strategy were identified in the result of the study. The article demonstrates that selection of the investment strategy of the bank could be efficiently realised on the basis of the hierarchy analysis method, which is the most popular under conditions of a multi-criteria assessment of the search for optimal solution of the set task. The article offers a hierarchical structure of decision making, which could be a basis of selection of the bank’s investment strategy with consideration of the institutional flexibility. The prospect of further study in this direction is development of an optimisation model of the bank’s investment portfolio with consideration of not only institutional, but also market flexibility of decision making.

A systematic and practical method for selecting systems engineering tools

DEFF Research Database (Denmark)

Munck, Allan; Madsen, Jan

2017-01-01

analyses of the actual needs and the available tools. Grouping needs into categories, allow us to obtain a comprehensive set of requirements for the tools. The entire model-based systems engineering discipline was categorized for a modeling tool case to enable development of a tool specification...... in successful operation since 2013 at GN Hearing. We further utilized the method to select a set of tools that we used on pilot cases at GN Hearing for modeling, simulating and formally verifying embedded systems.......The complexity of many types of systems has grown considerably over the last decades. Using appropriate systems engineering tools therefore becomes increasingly important. Starting the tool selection process can be intimidating because organizations often only have a vague idea about what they need...

Application of Bayesian methods to habitat selection modeling of the northern spotted owl in California: new statistical methods for wildlife research

Science.gov (United States)

Howard B. Stauffer; Cynthia J. Zabel; Jeffrey R. Dunk

2005-01-01

We compared a set of competing logistic regression habitat selection models for Northern Spotted Owls (Strix occidentalis caurina) in California. The habitat selection models were estimated, compared, evaluated, and tested using multiple sample datasets collected on federal forestlands in northern California. We used Bayesian methods in interpreting...

Research on Methods for Discovering and Selecting Cloud Infrastructure Services Based on Feature Modeling

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Huamin Zhu

2016-01-01

Full Text Available Nowadays more and more cloud infrastructure service providers are providing large numbers of service instances which are a combination of diversified resources, such as computing, storage, and network. However, for cloud infrastructure services, the lack of a description standard and the inadequate research of systematic discovery and selection methods have exposed difficulties in discovering and choosing services for users. First, considering the highly configurable properties of a cloud infrastructure service, the feature model method is used to describe such a service. Second, based on the description of the cloud infrastructure service, a systematic discovery and selection method for cloud infrastructure services are proposed. The automatic analysis techniques of the feature model are introduced to verify the model’s validity and to perform the matching of the service and demand models. Finally, we determine the critical decision metrics and their corresponding measurement methods for cloud infrastructure services, where the subjective and objective weighting results are combined to determine the weights of the decision metrics. The best matching instances from various providers are then ranked by their comprehensive evaluations. Experimental results show that the proposed methods can effectively improve the accuracy and efficiency of cloud infrastructure service discovery and selection.

Generation of induced pluripotent stem cells (iPSCs from a Bernard–Soulier syndrome patient carrying a W71R mutation in the GPIX gene

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Lourdes Lopez-Onieva

2016-05-01

Full Text Available We generated an induced pluripotent stem cell (iPSC line from a Bernard–Soulier Syndrome (BSS patient carrying the mutation p.Trp71Arg in the GPIX locus (BSS1-PBMC-iPS4F4. Peripheral blood mononuclear cells (PBMCs were reprogrammed using heat sensitive non-integrative Sendai viruses containing the reprogramming factors Oct3/4, SOX2, KLF4 and c-MYC. Successful silencing of the exogenous reprogramming factors was checked by RT-PCR. Characterization of BSS1-PBMC-iPS4F4 included mutation analysis of GPIX locus, Short Tandem Repeats (STR profiling, alkaline phosphatase enzymatic activity, analysis of conventional pluripotency-associated factors at mRNA and protein level and in vivo differentiation studies. BSS1-PBMC-iPS4F4 will provide a powerful tool to study BSS.

Using the AHP Method to Select an ERP System for an SME Manufacturing Company

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Kłos Sławomir

2014-09-01

Full Text Available This paper proposes the application of the Analytic Hierarchy Process method to support decision making regarding the selection of an Enterprise Resource Planning system in a manufacturing company. The main assumption of the work is that the management of the selection of an ERP system should consider that the most important selection criteria are concerned with the functionality of the ERP system. Besides this, the aspects of total cost of ownership, technical support and implementation time or vendor experience are taken into consideration to guarantee a successful ERP implementation. The proposed procedure of an ERP system selection is dedicated for small and medium manufacturing enterprises. A structure of attributes for the AHP method is proposed on the basis of an analysis and identification of critical success factors. Different kinds of production (make-to-stock, make-to-order and engineer-to-order are taken into consideration. Illustrative examples are also given.

The measurement of acetanilide in plasma by spectrophotometric and selected ion monitoring methods.

Science.gov (United States)

Baty, J D; Playfer, J; Evans, D A; Lamb, J

1977-08-01

Plasma samples from volunteers who had received an oral dose of acetanilide have been analysed by gas chromatography mass spectrometry and ultraviolet absorption techniques. The gas chromatography mass spectrometry method involved extraction of the plasma and analysis of the acetanilide using selected ion monitoring with a deuterated internal standard. In the ultraviolet method the plasma was hydrolysed with acid to convert the acetanilide to aniline, and this compound was diazotized and coupled with N-1-naphthylethylene-diamine. The absorbance of the resulting complex was read at 550 nm. Acetanilide levels in plasma determined by the selected ion monitoring method were significantly lower than those measured by spectrophotometry. Pharmacokinetic data calculated from the results obtained using these two assays are very different and illustrate the need for an accurate and specific method of analysis. The major metabolites of acetanilide are shown not to interfere with these assays and the results suggest the possible presence of a new metabolite of acetanilide.

A comparison of two methods for prediction of response and rates of inbreeding in selected populations with the results obtained in two selection experiments

Directory of Open Access Journals (Sweden)

Verrier Etienne

2005-05-01

Full Text Available Abstract Selection programmes are mainly concerned with increasing genetic gain. However, short-term progress should not be obtained at the expense of the within-population genetic variability. Different prediction models for the evolution within a small population of the genetic mean of a selected trait, its genetic variance and its inbreeding have been developed but have mainly been validated through Monte Carlo simulation studies. The purpose of this study was to compare theoretical predictions to experimental results. Two deterministic methods were considered, both grounded on a polygenic additive model. Differences between theoretical predictions and experimental results arise from differences between the true and the assumed genetic model, and from mathematical simplifications applied in the prediction methods. Two sets of experimental lines of chickens were used in this study: the Dutch lines undergoing true truncation mass selection, the other lines (French undergoing mass selection with a restriction on the representation of the different families. This study confirmed, on an experimental basis, that modelling is an efficient approach to make useful predictions of the evolution of selected populations although the basic assumptions considered in the models (polygenic additive model, normality of the distribution, base population at the equilibrium, etc. are not met in reality. The two deterministic methods compared yielded results that were close to those observed in real data, especially when the selection scheme followed the rules of strict mass selection: for instance, both predictions overestimated the genetic gain in the French experiment, whereas both predictions were close to the observed values in the Dutch experiment.

Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes

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Lotz Meredith J

2008-01-01

Full Text Available Abstract Background Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures × time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. Results We found that the optimal imputation algorithms (LSA, LLS, and BPCA are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Conclusion Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA

Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes.

Science.gov (United States)

Brock, Guy N; Shaffer, John R; Blakesley, Richard E; Lotz, Meredith J; Tseng, George C

2008-01-10

Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures x time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. We found that the optimal imputation algorithms (LSA, LLS, and BPCA) are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS) scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS) scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA) are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA) performed better on mcroarray data with lower complexity

Selection of variables for neural network analysis. Comparisons of several methods with high energy physics data

International Nuclear Information System (INIS)

Proriol, J.

1994-01-01

Five different methods are compared for selecting the most important variables with a view to classifying high energy physics events with neural networks. The different methods are: the F-test, Principal Component Analysis (PCA), a decision tree method: CART, weight evaluation, and Optimal Cell Damage (OCD). The neural networks use the variables selected with the different methods. We compare the percentages of events properly classified by each neural network. The learning set and the test set are the same for all the neural networks. (author)

Selection of polychlorinated plastics in plastic waste by X-ray fluorescence method

International Nuclear Information System (INIS)

Kumasaki, H.; Shinozaki, Y.

1979-01-01

The X-ray fluorescence method using a small source of 55 Fe was examined and found to be applicable for the selection of polychlorinated plastics from plastic waste in model areas in Tokyo designated for investigating their content in the waste. The weight ratios of soft and hard polychlorinated plastics to the total plastic waste estimated by this method were found to be 15.6% and 0.29% respectively. These values agree well with the results obtained with the Beilstein method. (author)

An Ensemble Method with Integration of Feature Selection and Classifier Selection to Detect the Landslides

Science.gov (United States)

Zhongqin, G.; Chen, Y.

2017-12-01

Abstract Quickly identify the spatial distribution of landslides automatically is essential for the prevention, mitigation and assessment of the landslide hazard. It's still a challenging job owing to the complicated characteristics and vague boundary of the landslide areas on the image. The high resolution remote sensing image has multi-scales, complex spatial distribution and abundant features, the object-oriented image classification methods can make full use of the above information and thus effectively detect the landslides after the hazard happened. In this research we present a new semi-supervised workflow, taking advantages of recent object-oriented image analysis and machine learning algorithms to quick locate the different origins of landslides of some areas on the southwest part of China. Besides a sequence of image segmentation, feature selection, object classification and error test, this workflow ensemble the feature selection and classifier selection. The feature this study utilized were normalized difference vegetation index (NDVI) change, textural feature derived from the gray level co-occurrence matrices (GLCM), spectral feature and etc. The improvement of this study shows this algorithm significantly removes some redundant feature and the classifiers get fully used. All these improvements lead to a higher accuracy on the determination of the shape of landslides on the high resolution remote sensing image, in particular the flexibility aimed at different kinds of landslides.

A method for the deliberate and deliberative selection of policy instrument mixes for climate change adaptation

Directory of Open Access Journals (Sweden)

Heleen L. P. Mees

2014-06-01

Full Text Available Policy instruments can help put climate adaptation plans into action. Here, we propose a method for the systematic assessment and selection of policy instruments for stimulating adaptation action. The multi-disciplinary set of six assessment criteria is derived from economics, policy, and legal studies. These criteria are specified for the purpose of climate adaptation by taking into account four challenges to the governance of climate adaptation: uncertainty, spatial diversity, controversy, and social complexity. The six criteria and four challenges are integrated into a step-wise method that enables the selection of instruments starting from a generic assessment and ending with a specific assessment of policy instrument mixes for the stimulation of a specific adaptation measure. We then apply the method to three examples of adaptation measures. The method's merits lie in enabling deliberate choices through a holistic and comprehensive set of adaptation specific criteria, as well as deliberative choices by offering a stepwise method that structures an informed dialog on instrument selection. Although the method was created and applied by scientific experts, policy-makers can also use the method.

Evaluation and selection of energy technologies using an integrated graph theory and analytic hierarchy process methods

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P. B. Lanjewar

2016-06-01

Full Text Available The evaluation and selection of energy technologies involve a large number of attributes whose selection and weighting is decided in accordance with the social, environmental, technical and economic framework. In the present work an integrated multiple attribute decision making methodology is developed by combining graph theory and analytic hierarchy process methods to deal with the evaluation and selection of energy technologies. The energy technology selection attributes digraph enables a quick visual appraisal of the energy technology selection attributes and their interrelationships. The preference index provides a total objective score for comparison of energy technologies alternatives. Application of matrix permanent offers a better appreciation of the considered attributes and helps to analyze the different alternatives from combinatorial viewpoint. The AHP is used to assign relative weights to the attributes. Four examples of evaluation and selection of energy technologies are considered in order to demonstrate and validate the proposed method.

Evaluation of Stress Loaded Steel Samples Using Selected Electromagnetic Methods

International Nuclear Information System (INIS)

Chady, T.

2004-01-01

In this paper the magnetic leakage flux and eddy current method were used to evaluate changes of materials' properties caused by stress. Seven samples made of ferromagnetic material with different level of applied stress were prepared. First, the leakage magnetic fields were measured by scanning the surface of the specimens with GMR gradiometer. Next, the same samples were evaluated using an eddy current sensor. A comparison between results obtained from both methods was carried out. Finally, selected parameters of the measured signal were calculated and utilized to evaluate level of the applied stress. A strong coincidence between amount of the applied stress and the maximum amplitude of the derivative was confirmed

A passive Bonner sphere spectrometer for in-flight neutron spectrometry

International Nuclear Information System (INIS)

Hajek, M.; Berger, T.; Vana, N.

2003-01-01

The neutron energy spectrum was measured onboard a series of four return flights between Cologne (Germany) and Washington, DC (USA) during the solar minimum conditions of June/July 1996. This experiment was world-wide the first determination of the neutron spectrum by passive spectrometry methods onboard an aircraft. The project was conducted with the support of the German Airforce which reserved two seat rows in the front of an Airbus A 310-304 for the passive BSS. The count rates were computed according to the Pair Method and unfolded with MAXED. Obtained spectrum shows two relative maxima around 1 and 100 MeV, the second of which cannot be completely assessed by the applied BSS. The agreement between measurement and calculation proved to be excellent

Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

Science.gov (United States)

Abe, Sumiyoshi

2014-11-01

The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

Will genomic selection be a practical method for plant breeding?

Science.gov (United States)

Nakaya, Akihiro; Isobe, Sachiko N

2012-11-01

Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

Progress in assisted natural remediation of an arsenic contaminated agricultural soil

International Nuclear Information System (INIS)

Mench, Michel; Vangronsveld, Jaco; Beckx, Caroline; Ruttens, Ann

2006-01-01

A contaminated soil was collected in a field adjacent to a derelict As (III) smelter in Reppel (Bocholt, Belgium). A single soil treatment (% by soil weight) based on either iron grit (SS, 1%), beringite (B, 5%), or iron grit (1%) + beringite (5%) (BSS) was applied. Untreated and treated Reppel soils and a control soil were placed in lysimeters inside a greenhouse and cropped annually. The efficiency of soil treatments in decreasing As and metals in exposure sources and restoring soil functions was assessed 6 years after the treatments commenced. Decreases in extractable Cd, Mn, Zn and As occurred in the BSS soil. Only BSS treatment reduced both As and metal concentrations in leachates. BSS treatment produced best growth of lettuce and cabbage, the highest shoot and pod yields for dwarf bean, the lowest As, Cd and Zn concentrations in plant tissues, and partly restored Rhizobium nodulation on bean roots. The epigeic earthworm (Dendrobaena octaedra) could only survive in the BSS soil. Depurated living worms from the BSS soil had Cd concentration similar to those in control worms, but higher As, Ca, Fe, and Zn concentrations. Based on physiologically based extraction test (PBET), As bioaccessibility was reduced from 12% (untreated soil) to 7.4% (BSS) and 3% (SS), but only the SS treatment decreased the bioaccessibility of Cd (-30%) and Pb (-35%). The range of chemical and biological indicators suggested that BSS amendment was the most effective treatment for restoration of normal soil functions 6 years after initial treatment of the Reppel soil. - Restoration occurred in a contaminated soil six years after the combined application of iron grit and beringite

Exploring selection and recruitment processes for newly qualified nurses: a sequential-explanatory mixed-method study.

Science.gov (United States)

Newton, Paul; Chandler, Val; Morris-Thomson, Trish; Sayer, Jane; Burke, Linda

2015-01-01

To map current selection and recruitment processes for newly qualified nurses and to explore the advantages and limitations of current selection and recruitment processes. The need to improve current selection and recruitment practices for newly qualified nurses is highlighted in health policy internationally. A cross-sectional, sequential-explanatory mixed-method design with 4 components: (1) Literature review of selection and recruitment of newly qualified nurses; and (2) Literature review of a public sector professions' selection and recruitment processes; (3) Survey mapping existing selection and recruitment processes for newly qualified nurses; and (4) Qualitative study about recruiters' selection and recruitment processes. Literature searches on the selection and recruitment of newly qualified candidates in teaching and nursing (2005-2013) were conducted. Cross-sectional, mixed-method data were collected from thirty-one (n = 31) individuals in health providers in London who had responsibility for the selection and recruitment of newly qualified nurses using a survey instrument. Of these providers who took part, six (n = 6) purposively selected to be interviewed qualitatively. Issues of supply and demand in the workforce, rather than selection and recruitment tools, predominated in the literature reviews. Examples of tools to measure values, attitudes and skills were found in the nursing literature. The mapping exercise found that providers used many selection and recruitment tools, some providers combined tools to streamline process and assure quality of candidates. Most providers had processes which addressed the issue of quality in the selection and recruitment of newly qualified nurses. The 'assessment centre model', which providers were adopting, allowed for multiple levels of assessment and streamlined recruitment. There is a need to validate the efficacy of the selection tools. © 2014 John Wiley & Sons Ltd.

Effective enzymatic in situ saccharification of bamboo shoot shell pretreated by dilute alkalic salts sodium hypochlorite/sodium sulfide pretreatment under the autoclave system.

Science.gov (United States)

Chong, Gang-Gang; He, Yu-Cai; Liu, Qiu-Xiang; Kou, Xiao-Qin; Huang, Xiao-Jun; Di, Jun-Hua; Ma, Cui-Luan

2017-10-01

In this study, dilute alkali salts (0.6% NaClO, 0.067% Na 2 S) pretreatment at 10% sulfidity under the autoclave system at 120°C for 40min was used for pretreating bamboo shoot shell (BSS). Furthermore, FT-IR, XRD and SEM were employed to characterize the changes in the cellulose structural characteristics (porosity, morphology, and crystallinity) of the pretreated BSS solid residue. After 72h, the reducing sugars and glucose from the enzymatic in situ hydrolysis of 50g/L pretreated BSS in dilute NaClO/Na 2 S media could be obtained at 31.11 and 20.32g/L, respectively. Finally, the obtained BSS-hydrolysates containing alkalic salt NaClO/Na 2 S resulted in slightly negative effects on the ethanol production. Glucose in BSS-hydrolysates was fermented from 20.0 to 0.17g/L within 48h, and an ethanol yield of 0.41g/g glucose, which represents 80.1% of the theoretical yield, was obtained. This study provided an effective strategy for potential utilization of BSS. Copyright © 2017 Elsevier Ltd. All rights reserved.

Normalization method for metabolomics data using optimal selection of multiple internal standards

Directory of Open Access Journals (Sweden)

Yetukuri Laxman

2007-03-01

Full Text Available Abstract Background Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task. Results With the aim to remove unwanted systematic variation, we present an approach that utilizes variability information from multiple internal standard compounds to find optimal normalization factor for each individual molecular species detected by metabolomics approach (NOMIS. We demonstrate the method on mouse liver lipidomic profiles using Ultra Performance Liquid Chromatography coupled to high resolution mass spectrometry, and compare its performance to two commonly utilized normalization methods: normalization by l2 norm and by retention time region specific standard compound profiles. The NOMIS method proved superior in its ability to reduce the effect of systematic error across the full spectrum of metabolite peaks. We also demonstrate that the method can be used to select best combinations of standard compounds for normalization. Conclusion Depending on experiment design and biological matrix, the NOMIS method is applicable either as a one-step normalization method or as a two-step method where the normalization parameters, influenced by variabilities of internal standard compounds and their correlation to metabolites, are first calculated from a study conducted in repeatability conditions. The method can also be used in analytical development of metabolomics methods by helping to select best combinations of standard compounds for a particular biological matrix and analytical platform.

Base Station Activation and Linear Transceiver Design for Optimal Resource Management in Heterogeneous Networks

Science.gov (United States)

Liao, Wei-Cheng; Hong, Mingyi; Liu, Ya-Feng; Luo, Zhi-Quan

2014-08-01

In a densely deployed heterogeneous network (HetNet), the number of pico/micro base stations (BS) can be comparable with the number of the users. To reduce the operational overhead of the HetNet, proper identification of the set of serving BSs becomes an important design issue. In this work, we show that by jointly optimizing the transceivers and determining the active set of BSs, high system resource utilization can be achieved with only a small number of BSs. In particular, we provide formulations and efficient algorithms for such joint optimization problem, under the following two common design criteria: i) minimization of the total power consumption at the BSs, and ii) maximization of the system spectrum efficiency. In both cases, we introduce a nonsmooth regularizer to facilitate the activation of the most appropriate BSs. We illustrate the efficiency and the efficacy of the proposed algorithms via extensive numerical simulations.

r2VIM: A new variable selection method for random forests in genome-wide association studies.

Science.gov (United States)

Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E

2016-01-01

Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.

Method for routine determination of fluoride in urine by selective ion- electrode

International Nuclear Information System (INIS)

Pires, M.A.F.; Bellintani, S.A.

1985-01-01

A simple, fast and sensitive method is outlined for determining fluoride in urine of workers who handle fluoride compounds. The determination is based on the measurement of fluoride by ion selective electrode. Cationic interferents like Ca ++ , Mg ++ , Fe +++ and Al +++ are complexed by EDTA and citric acid. Common anions present in urine, such as Cl - , PO --- 4 and SO -- 4 do not interfere in the method. (Author) [pt

Comparison of selection methods to deduce natural background levels for groundwater units

NARCIS (Netherlands)

Griffioen, J.; Passier, H.F.; Klein, J.

2008-01-01

Establishment of natural background levels (NBL) for groundwater is commonly performed to serve as reference when assessing the contamination status of groundwater units. We compare various selection methods to establish NBLs using groundwater quality data forfour hydrogeologically different areas

An Imaging and Histological Study on Intrahepatic Microvascular Passage of Contrast Materials in Rat Liver

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Qian Xia

2017-01-01

Full Text Available Background. Lipiodol has been applied for decades in transarterial chemoembolization to treat liver malignancies, but its intrahepatic pathway through arterioportal shunt (APS in the liver has not been histologically revealed. This rodent experiment was conducted to provide evidence for the pathway of Lipiodol delivered through the hepatic artery (HA but found in the portal vein (PV and to elucidate the observed unidirectional APS. Methods. Thirty rats were divided into 5 groups receiving systemic or local arterial infusion of red-stained iodized oil (RIO or its hydrosoluble substitute barium sulfate suspension (BSS, or infusion of BSS via the PV, monitored by real-time digital radiography. Histomorphology of serial frozen and paraffin sections was performed and quantified. Results. After HA infusion, RIO and BSS appeared extensively in PV lumens with peribiliary vascular plexus (PVP identified as the responsible anastomotic channel. After PV infusion, BSS appeared predominantly in the PV and surrounding sinusoids and to a much lesser extent in the PVP and HA (P<0.001. Fluid mechanics well explains the one-way-valve phenomenon of APS. Conclusions. Intravascularly injected rat livers provide histomorphologic evidences: (1 the PVP exists in between the HA and PV, which is responsible to the APS of Lipiodol; and (2 the intrahepatic vascular inflow appears HA-PVP-PV unidirectional without a physical one-way valve, which can be postulated by the fluid mechanics.

Hybrid Multicriteria Group Decision Making Method for Information System Project Selection Based on Intuitionistic Fuzzy Theory

Directory of Open Access Journals (Sweden)

Jian Guo

2013-01-01

Full Text Available Information system (IS project selection is of critical importance to every organization in dynamic competing environment. The aim of this paper is to develop a hybrid multicriteria group decision making approach based on intuitionistic fuzzy theory for IS project selection. The decision makers’ assessment information can be expressed in the form of real numbers, interval-valued numbers, linguistic variables, and intuitionistic fuzzy numbers (IFNs. All these evaluation pieces of information can be transformed to the form of IFNs. Intuitionistic fuzzy weighted averaging (IFWA operator is utilized to aggregate individual opinions of decision makers into a group opinion. Intuitionistic fuzzy entropy is used to obtain the entropy weights of the criteria. TOPSIS method combined with intuitionistic fuzzy set is proposed to select appropriate IS project in group decision making environment. Finally, a numerical example for information system projects selection is given to illustrate application of hybrid multi-criteria group decision making (MCGDM method based on intuitionistic fuzzy theory and TOPSIS method.

Asymptotic theory for Brownian semi-stationary processes with application to turbulence

DEFF Research Database (Denmark)

Corcuera, José Manuel; Hedevang, Emil; Pakkanen, Mikko S.

2013-01-01

This paper presents some asymptotic results for statistics of Brownian semi-stationary (BSS) processes. More precisely, we consider power variations of BSS processes, which are based on high frequency (possibly higher order) differences of the BSS model. We review the limit theory discussed......, which allow to obtain a valid central limit theorem for the critical region. Finally, we apply our statistical theory to turbulence data....

A simple negative selection method to identify adenovirus recombinants using colony PCR

Directory of Open Access Journals (Sweden)

Yongliang Zhao

2014-01-01

Conclusions: The negative selection method to identify AdEasy adenovirus recombinants by colony PCR can identify the recombined colony within a short time-period, and maximally avoid damage to the recombinant plasmid by limiting recombination time, resulting in improved adenovirus packaging.

Highly selective coulometric method and equipment for the automated determination of plutonium

International Nuclear Information System (INIS)

Jackson, D.D.; Hollen, R.M.; Roensch, F.R.; Rein, J.E.

1977-01-01

A highly selective, controlled-potential coulometric method has been developed for the determination of plutonium. An automated instrument, consisting of commercial electronic components under control of a programmable calculator, is being constructed. Half-cell potentials and interfering anions are listed

A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification

Science.gov (United States)

Wang, Suge; Li, Deyu; Wei, Yingjie; Li, Hongxia

With the rapid growth of e-commerce, product reviews on the Web have become an important information source for customers' decision making when they intend to buy some product. As the reviews are often too many for customers to go through, how to automatically classify them into different sentiment orientation categories (i.e. positive/negative) has become a research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for product review text sentiment classification. In order to validate the validity of the proposed method, we compared it with other methods respectively based on information gain and mutual information while support vector machine is adopted as the classifier. In this paper, 6 subexperiments are conducted by combining different feature selection methods with 2 kinds of candidate feature sets. Under 1006 review documents of cars, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance with F value 83.3% while the candidate features are the words which appear in both positive and negative texts.

Selected physico-mechanical characteristics of cryogenic and ambient ground turmeric

Science.gov (United States)

Barnwal, Pradyuman; Mohite, Ashish M.; Singh, Krishna K.; Kumar, Pankaj

2014-03-01

In this communication, selected physicomechanical characteristics of ground turmeric (cv. Prabha) were investigated for cryogenic and ambient grinding conditions of turmeric at different moisture contents (4, 6, 8 and 10% w.b.). A cryogenic grinder (Model: 100 UPZ, Hosokawa Alpine, Germany) and a micro pulverizer (hammer mill) were used for cryogenic and ambient grinding, respectively. The ground turmeric was graded in three grades viz. Gr-I, Gr-II and Gr-III with a sieve shaker using BSS Nos. 40, 85 and pan, respectively. Tap densities for cryogenic and ambient ground turmeric decreased from 678.7 (Gr-I) to 546.7 kgm-3 (Gr-III) and from 642.3 (Gr-I) to 468.6 kgm-3 (Gr-III), respectively, with the moisture increase. The angle of repose for cryogenic and ambient ground turmeric increased linearly from 26.85 (Gr-I) to 34.0° (Gr-III) and from 23.10 (Gr-I) to 28.06° (Gr-III), respectively with the increase in moisture content. The static coefficient of friction was the highest on plywood surface followed by mild steel sheet and galvanized iron sheet. The cryoground samples were found better in colour. Thermal conductivity of cryo-ground samples was higher than that of ambient ground samples. These physico-mechanical characteristics of cryogenic and ambient ground turmeric will be helpful for packaging, handling, and storage.

PERFLUOROCARBON LIQUIDS' ABILITY TO PROTECT THE MACULA FROM INTRAOCULAR DROPPING OF METALLIC FOREIGN BODIES: A Model Eye Study.

Science.gov (United States)

Shah, Chirag M; Gentile, Ronald C; Mehta, Mitul C

2016-07-01

To examine the utility of perfluoro-n-octane (PFO) in balanced salt solution (BSS) to shield the macula from the impact of dropped metallic intraocular foreign bodies (IOFBs) by modeling scenarios in which they may fall during surgical removal. Model eyes were filled with various fluid mixtures (Group 1: 10% PFO/90% BSS; Group 2: 100% BSS; Group 3: 100% PFO; Group 4: 10% PFO/90% air; Group 5: 10% BSS/90% air). In Groups 1, 4, and 5, the 10% fluid volume covered the theoretical macula. For each fluid mixture, up to 30 IOFB drop scenarios were performed for each of the 5 sample IOFBs from 3 locations. Trajectories were recorded using a camera attached to a Zeiss operating microscope (Carl Zeiss, Jena, Germany). The percentages of IOFBs impacting the macula were calculated and Fisher exact test was used to assess differences. In Group 1, 93% (417/450) of the dropped IOFBs were deflected by the PFO-BSS interface compared with 0% (0/500) in Groups 2, 3, 4, and 5 (P macula in 30% of tests when dropped from the superior posterior segment (P < 0.01), all other IOFBs (2.8-13.4 mg) were deflected by the PFO-BSS interface in 100% of Group 1 drops (P < 0.01). As demonstrated by these simulations, the PFO-BSS interface can deflect IOFBs dropped during surgery in a wide range of scenarios, especially when the IOFB is of lower mass.

Essay on Methods in Futures Studies and a Selective Bibliography

DEFF Research Database (Denmark)

Poulsen, Claus

2005-01-01

Futures studies is often conflated with science fiction or pop-futurism. Consequently there is a need for demarcation of what is futures studies and what is not. From the same reason the essay stresses the need for quality control to focus on futures research and its methods: Publications in futu...... programme are (only) partly reduced by applying Causal Layered Analysis as an internal quality control. The following selective bibliography is focussed on these methodological issues...

Tree regeneration response to the group selection method in southern Indiana

Science.gov (United States)

Dale R. Weigel; George R. Parker

1997-01-01

Tree regeneration response following the use of the group selection method was studied within 36 group openings on the Naval Surface Warfare Center, Crane Division in south central Indiana. Two different aspects and three time periods since cutting were examined. The objectives were to determine whether aspect, age, species group, location within the opening, or their...

Effects of temperature variations on guided waves propagating in composite structures

Science.gov (United States)

Shoja, Siavash; Berbyuk, Viktor; Boström, Anders

2016-04-01

Effects of temperature on guided waves propagating in composite materials is a well-known problem which has been investigated in many studies. The majority of the studies is focused on effects of high temperature. Understanding the effects of low temperature has major importance in composite structures and components which are operating in cold climate conditions such as e.g. wind turbines operating in cold climate regions. In this study first the effects of temperature variations on guided waves propagating in a composite plate is investigated experimentally in a cold climate chamber. The material is a common material used to manufacture rotor blades of wind turbines. The temperature range is 25°C to -25°C and effects of temperature variations on amplitude and phase shift of the received signal are investigated. In order to apply the effects of lowering the temperature on the received signal, the Baseline Signal Stretch (BSS) method is modified and used. The modification is based on decomposing the signal into symmetric and asymmetric modes and applying two different stretch factors on each of them. Finally the results obtained based on the new method is compared with the results of application of BSS with one stretch factor and experimental measurements. Comparisons show that an improvement is obtained using the BSS with the mode decomposition method at temperature variations of more than 25°C.

Using the Delphi Method for Selecting Effective Rehabilitation Practices for Case Study Research: Methods, Challenges, and Solutions and Implications for Future Research

Science.gov (United States)

Fleming, Allison R.; Boeltzig-Brown, Heike; Foley, Susan M.

2015-01-01

Purpose: We describe a modified Delphi method used to select effective state vocational rehabilitation agency practices to prioritize rehabilitation services for individuals with most significant disabilities within the context of Order of Selection, an area where there is little known and published. Specifically, we describe how we applied the…

Automatic method for selective enhancement of different tissue densities at digital chest radiography

International Nuclear Information System (INIS)

McNitt-Gray, M.F.; Taira, R.K.; Eldredge, S.L.; Razavi, M.

1991-01-01

This paper reports that digital chest radiographs often are too bright and/or lack contrast when viewed on a video display. The authors have developed a method that can automatically provide a series of look-up tables that selectively enhance the radiographically soft or dense tissues on a digital chest radiograph. This reduces viewer interaction and improves displayed image quality. On the basis of a histogram analysis, gray-level ranges are approximated for the patient background, radiographically soft tissues, and radiographically dense tissues. A series of look-up tables is automatically created by varying the contrast in each range to achieve a level of enhancement for a selected tissue range. This is repeated for differing amounts of enhancement and for each tissue range. This allows the viewer to interactively select a tissue density range and degree of enhancement at the time of display via precalculated look-up tables. Preclinical trials in pediatric radiology using computed radiography images show that this method reduces viewer interaction and improves or maintains the displayed image quality

TU-AB-202-10: How Effective Are Current Atlas Selection Methods for Atlas-Based Auto-Contouring in Radiotherapy Planning?

Energy Technology Data Exchange (ETDEWEB)

Peressutti, D; Schipaanboord, B; Kadir, T; Gooding, M [Mirada Medical Limited, Science and Medical Technology, Oxford (United Kingdom); Soest, J van; Lustberg, T; Elmpt, W van; Dekker, A [Maastricht University Medical Centre, Department of Radiation Oncology MAASTRO - GROW School for Oncology Developmental Biology, Maastricht (Netherlands)

2016-06-15

Purpose: To investigate the effectiveness of atlas selection methods for improving atlas-based auto-contouring in radiotherapy planning. Methods: 275 H&N clinically delineated cases were employed as an atlas database from which atlases would be selected. A further 40 previously contoured cases were used as test patients against which atlas selection could be performed and evaluated. 26 variations of selection methods proposed in the literature and used in commercial systems were investigated. Atlas selection methods comprised either global or local image similarity measures, computed after rigid or deformable registration, combined with direct atlas search or with an intermediate template image. Workflow Box (Mirada-Medical, Oxford, UK) was used for all auto-contouring. Results on brain, brainstem, parotids and spinal cord were compared to random selection, a fixed set of 10 “good” atlases, and optimal selection by an “oracle” with knowledge of the ground truth. The Dice score and the average ranking with respect to the “oracle” were employed to assess the performance of the top 10 atlases selected by each method. Results: The fixed set of “good” atlases outperformed all of the atlas-patient image similarity-based selection methods (mean Dice 0.715 c.f. 0.603 to 0.677). In general, methods based on exhaustive comparison of local similarity measures showed better average Dice scores (0.658 to 0.677) compared to the use of either template image (0.655 to 0.672) or global similarity measures (0.603 to 0.666). The performance of image-based selection methods was found to be only slightly better than a random (0.645). Dice scores given relate to the left parotid, but similar results patterns were observed for all organs. Conclusion: Intuitively, atlas selection based on the patient CT is expected to improve auto-contouring performance. However, it was found that published approaches performed marginally better than random and use of a fixed set of

SX Phoenicis stars

International Nuclear Information System (INIS)

Nemec, J.; Mateo, M.

1990-01-01

The purpose of this paper is to review the basic observational information concerning SX Phe stars, including recent findings such as the discovery of about 40 low-luminosity variable stars in the Carina dwarf galaxy and identification of at least one SX Phe star in the metal-rich globular cluster M71. Direct evidence supporting the hypothesis that at least some BSs are binary systems comes from the discovery of two contact binaries and a semidetached binary among the 50 BSs in the globular cluster NGC 5466. Since these systems will coalesce on a time scale 500 Myr, it stands to reason that many (if not most) BSs are coalesced binaries. The merger hypothesis also explains the relatively-large masses (1.0-1.2 solar masses) that have been derived for SX Phe stars and halo BSs, and may also account for the nonvariable BSs in the 'SX Phe instability strip'. 132 refs

Comparison of the effects of intraocular irrigating solutions on the corneal endothelium in intraocular lens implantation.

Science.gov (United States)

Matsuda, M; Kinoshita, S; Ohashi, Y; Shimomura, Y; Ohguro, N; Okamoto, H; Omoto, T; Hosotani, H; Yoshida, H

1991-01-01

We conducted a randomised prospective controlled study to determine the effects of a glucose glutathione bicarbonate solution (BSS Plus) and a citrate acetate bicarbonate solution (S-MA2) on the corneal endothelium in patients undergoing extracapsular cataract extraction with posterior chamber lens implantation. One eye of each patient was randomly assigned to receive BSS Plus, and the other eye to receive S-MA2. BSS Plus caused significantly less corneal swelling on the first postoperative day than did S-MA2. There was no difference between the two solutions in their effect on corneal thickness one week and one month postoperatively. Computer assisted morphometric analysis of wide-field specular microscopic photographs demonstrated minimal changes in endothelial morphological characteristics in the eyes irrigated with BSS Plus. By comparison S-MA2, caused a significant loss of endothelial cells and a marked reduction in the figure coefficient. These results indicated that BSS Plus has a clinical advantage over S-MA2 with respect to the corneal endothelium. PMID:1873266

Base Station Ordering for Emergency Call Localization in Ultra-dense Cellular Networks

KAUST Repository

Elsawy, Hesham

2017-10-04

This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.

Two-Stage Multi-Objective Collaborative Scheduling for Wind Farm and Battery Switch Station

Directory of Open Access Journals (Sweden)

Zhe Jiang

2016-10-01

Full Text Available In order to deal with the uncertainties of wind power, wind farm and electric vehicle (EV battery switch station (BSS were proposed to work together as an integrated system. In this paper, the collaborative scheduling problems of such a system were studied. Considering the features of the integrated system, three indices, which include battery swapping demand curtailment of BSS, wind curtailment of wind farm, and generation schedule tracking of the integrated system are proposed. In addition, a two-stage multi-objective collaborative scheduling model was designed. In the first stage, a day-ahead model was built based on the theory of dependent chance programming. With the aim of maximizing the realization probabilities of these three operating indices, random fluctuations of wind power and battery switch demand were taken into account simultaneously. In order to explore the capability of BSS as reserve, the readjustment process of the BSS within each hour was considered in this stage. In addition, the stored energy rather than the charging/discharging power of BSS during each period was optimized, which will provide basis for hour-ahead further correction of BSS. In the second stage, an hour-ahead model was established. In order to cope with the randomness of wind power and battery swapping demand, the proposed hour-ahead model utilized ultra-short term prediction of the wind power and the battery switch demand to schedule the charging/discharging power of BSS in a rolling manner. Finally, the effectiveness of the proposed models was validated by case studies. The simulation results indicated that the proposed model could realize complement between wind farm and BSS, reduce the dependence on power grid, and facilitate the accommodation of wind power.

Thermodynamic measurement after cooling the cornea with intact epithelium and lid manipulation.

Science.gov (United States)

de Ortueta, Diego; Magnago, Thomas; Arba-Mosquera, Samuel

2015-01-01

To characterize the rate of change of ocular surface temperature (OST) under lid manipulation after cooling the intact cornea with balanced salt solution (BSS). In a patient for refractive surgery, prior to the ablation, the temperature of the cornea was continuously recorded with a high speed infrared (350Hz) camera. Two millilitre of chilled BSS with a temperature of 8.6°Celsius (°C) was instilled for about 3s. Using exponential functions, the three contributions have been determined, subjacent corneal layers, environment, and chilled BSS. The mean temperature of the cornea preoperatively was 34.5°C. After applying the chilled BSS the temperature decreased about 14°C down to an OST of 20°C and the time needed afterwards to get the normal (OST) temperature of about 30°C was 40s. Due to the inserted speculum and missing blink, OST did not reach the original OST of 34.5°C and faded at about 32.5°C. According to our best fitted model, absolute value of each contributing component was 31.4°C (subjacent corneal layers), 26.8°C (environment) and 8.6°C (BSS). Applying chilled BSS to the cornea quickly reduces the temperature of the cornea with a thermal relaxation time of 3s and a amplitude decrease of 8.6°C. This together with a relaxation time of 7s for subjacent corneal layers, and 184s for environment after instillation of BSS combined with a well-controlled environment provides a period of 40s of corneal temperature below baseline, which may be of clinical benefit when applying chilled BSS immediately before or immediately after ablation. Copyright © 2014 Spanish General Council of Optometry. Published by Elsevier Espana. All rights reserved.

Base Station Ordering for Emergency Call Localization in Ultra-dense Cellular Networks

KAUST Repository

Elsawy, Hesham; Dai, Wenhan; Alouini, Mohamed-Slim; Win, Moe Z.

2017-01-01

This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.

SELECTING A MANAGEMENT SYSTEM HOSPITAL BY A METHOD MULTICRITERIA

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Vitorino, Sidney L.

2016-12-01

Full Text Available The objective of this report is to assess how the multi-criteria method Analytic Hierarchy Process [HP] can help a hospital complex to choose a more suitable management system, known as Enterprise Resource Planning (ERP. The choice coated is very complex due to the novelty of the process of choosing and conflicts generated between areas that did not have a single view of organizational needs, generating a lot of pressure in the department responsible for implementing systems. To assist in this process, he was hired an expert consultant in decision-making and AHP, which in its role of facilitator, contributed to the criteria for system selection were defined, and the choice to occur within a consensual process. We used the study of a single case, based on two indepth interviews with the consultant and the project manager, and documents generated by the advisory and the tool that supported the method. The results of this analysis showed that the method could effectively collaborate in the system acquisition process, but knowledge of the problems of employees and senior management support, it was not used in new decisions of the organization. We conclude that this method contributed to the consensus in the procurement process, team commitment and engagement of those involved.

Roka Listeria detection method using transcription mediated amplification to detect Listeria species in select foods and surfaces. Performance Tested Method(SM) 011201.

Science.gov (United States)

Hua, Yang; Kaplan, Shannon; Reshatoff, Michael; Hu, Ernie; Zukowski, Alexis; Schweis, Franz; Gin, Cristal; Maroni, Brett; Becker, Michael; Wisniewski, Michele

2012-01-01

The Roka Listeria Detection Assay was compared to the reference culture methods for nine select foods and three select surfaces. The Roka method used Half-Fraser Broth for enrichment at 35 +/- 2 degrees C for 24-28 h. Comparison of Roka's method to reference methods requires an unpaired approach. Each method had a total of 545 samples inoculated with a Listeria strain. Each food and surface was inoculated with a different strain of Listeria at two different levels per method. For the dairy products (Brie cheese, whole milk, and ice cream), our method was compared to AOAC Official Method(SM) 993.12. For the ready-to-eat meats (deli chicken, cured ham, chicken salad, and hot dogs) and environmental surfaces (sealed concrete, stainless steel, and plastic), these samples were compared to the U.S. Department of Agriculture/Food Safety and Inspection Service-Microbiology Laboratory Guidebook (USDA/FSIS-MLG) method MLG 8.07. Cold-smoked salmon and romaine lettuce were compared to the U.S. Food and Drug Administration/Bacteriological Analytical Manual, Chapter 10 (FDA/BAM) method. Roka's method had 358 positives out of 545 total inoculated samples compared to 332 positive for the reference methods. Overall the probability of detection analysis of the results showed better or equivalent performance compared to the reference methods.

Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

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Ueki Masao

2012-05-01

Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

Analysis of Multi-Criteria Evaluation Method of Landfill Site Selection for Municipal Solid Waste Management

Science.gov (United States)

Mohammed, Habiba Ibrahim; Majid, Zulkepli; Yusof, Norhakim Bin; Bello Yamusa, Yamusa

2018-03-01

Landfilling remains the most common systematic technique of solid waste disposal in most of the developed and developing countries. Finding a suitable site for landfill is a very challenging task. Landfill site selection process aims to provide suitable areas that will protect the environment and public health from pollution and hazards. Therefore, various factors such as environmental, physical, socio-economic, and geological criteria must be considered before siting any landfill. This makes the site selection process vigorous and tedious because it involves the processing of large amount of spatial data, rules and regulations from different agencies and also policy from decision makers. This allows the incorporation of conflicting objectives and decision maker preferences into spatial decision models. This paper particularly analyzes the multi-criteria evaluation (MCE) method of landfill site selection for solid waste management by means of literature reviews and surveys. The study will help the decision makers and waste management authorities to choose the most effective method when considering landfill site selection.

Analysis of Multi-Criteria Evaluation Method of Landfill Site Selection for Municipal Solid Waste Management

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Ibrahim Mohammed Habiba

2018-01-01

Full Text Available Landfilling remains the most common systematic technique of solid waste disposal in most of the developed and developing countries. Finding a suitable site for landfill is a very challenging task. Landfill site selection process aims to provide suitable areas that will protect the environment and public health from pollution and hazards. Therefore, various factors such as environmental, physical, socio-economic, and geological criteria must be considered before siting any landfill. This makes the site selection process vigorous and tedious because it involves the processing of large amount of spatial data, rules and regulations from different agencies and also policy from decision makers. This allows the incorporation of conflicting objectives and decision maker preferences into spatial decision models. This paper particularly analyzes the multi-criteria evaluation (MCE method of landfill site selection for solid waste management by means of literature reviews and surveys. The study will help the decision makers and waste management authorities to choose the most effective method when considering landfill site selection.

A genetic algorithm solution for the operation of green LTE networks with energy and environment considerations

KAUST Repository

Ghazzai, Hakim

2012-01-01

The Base Station (BS) sleeping strategy has become a well-known technique to achieve energy savings in cellular networks by switching off redundant BSs mainly for lightly loaded networks. Besides, the exploitation of renewable energies, as additional power sources in smart grids, becomes a real challenge to network operators to reduce power costs. In this paper, we propose a method based on genetic algorithms that decreases the energy consumption of a Long-Term Evolution (LTE) cellular network by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from the smart grid without affecting the desired Quality of Service. © 2012 Springer-Verlag.

Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

KAUST Repository

Abusamra, Heba

2016-07-20

The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

[The assessment of biological maturation for talent selection - which method can be used?].

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Müller, L; Müller, E; Hildebrandt, C; Kapelari, K; Raschner, C

2015-03-01

The biological maturity status plays an important role in sports, since it influences the performance level and the talent selection in various types of sport. More mature athletes are favorably selected for regional and national squads. Therefore, the biological maturity status should be considered during the talent selection process. In this context, the relative age effect (RAE), which exists when the relative age quarter distribution of selected sports groups shows a biased distribution with an over-representation of athletes born in the first months after the specific cut-off-date for the competition categories, represents another problem in the talent development. From an ethical point of view, discrimination of young talented kids does exist: the relatively younger athletes have little to no chance of reaching the elite level, despite their talents and efforts. The causal mechanisms behind the RAE are still unclear and have to be assessed. In this context, the biological maturation seems to be a possible influential factor for the existence of a RAE in sport, which has to be examined. Several methods for estimating the biological maturity status exist; however, they are often expensive and not practicable. Consequently, the aim of the present study was to assess the concordance of a simple, yet accurate method of estimating biological maturation (prediction equation of age at peak height velocity, APHV) of Mirwald and co-workers, and the gold standard method of estimating skeletal age (SA, the x-ray of the left wrist). In total, 75 Austrian students (40♂, 35♀) aged 10 - 13 years, were examined. Thirty of the participants (17♂, 13♀) were students of a well-known Austrian ski boarding school, and 45 (23♂, 22♀) of a non-sportive secondary modern school of the same region. The participants included in the study had not experienced a rupture of the carpal bones of the left wrist. Parents and participants were informed of the study aims

A method for selecting cis-acting regulatory sequences that respond to small molecule effectors

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Allas Ülar

2010-08-01

Full Text Available Abstract Background Several cis-acting regulatory sequences functioning at the level of mRNA or nascent peptide and specifically influencing transcription or translation have been described. These regulatory elements often respond to specific chemicals. Results We have developed a method that allows us to select cis-acting regulatory sequences that respond to diverse chemicals. The method is based on the β-lactamase gene containing a random sequence inserted into the beginning of the ORF. Several rounds of selection are used to isolate sequences that suppress β-lactamase expression in response to the compound under study. We have isolated sequences that respond to erythromycin, troleandomycin, chloramphenicol, meta-toluate and homoserine lactone. By introducing synonymous and non-synonymous mutations we have shown that at least in the case of erythromycin the sequences act at the peptide level. We have also tested the cross-activities of the constructs and found that in most cases the sequences respond most strongly to the compound on which they were isolated. Conclusions Several selected peptides showed ligand-specific changes in amino acid frequencies, but no consensus motif could be identified. This is consistent with previous observations on natural cis-acting peptides, showing that it is often impossible to demonstrate a consensus. Applying the currently developed method on a larger scale, by selecting and comparing an extended set of sequences, might allow the sequence rules underlying the activity of cis-acting regulatory peptides to be identified.

Development of an optimal velocity selection method with velocity obstacle

Energy Technology Data Exchange (ETDEWEB)

Kim, Min Geuk; Oh, Jun Ho [KAIST, Daejeon (Korea, Republic of)

2015-08-15

The Velocity obstacle (VO) method is one of the most well-known methods for local path planning, allowing consideration of dynamic obstacles and unexpected obstacles. Typical VO methods separate a velocity map into a collision area and a collision-free area. A robot can avoid collisions by selecting its velocity from within the collision-free area. However, if there are numerous obstacles near a robot, the robot will have very few velocity candidates. In this paper, a method for choosing optimal velocity components using the concept of pass-time and vertical clearance is proposed for the efficient movement of a robot. The pass-time is the time required for a robot to pass by an obstacle. By generating a latticized available velocity map for a robot, each velocity component can be evaluated using a cost function that considers the pass-time and other aspects. From the output of the cost function, even a velocity component that will cause a collision in the future can be chosen as a final velocity if the pass-time is sufficiently long enough.

Antibacterial effect of bismuth subsalicylate nanoparticles synthesized by laser ablation

Science.gov (United States)

Flores-Castañeda, Mariela; Vega-Jiménez, Alejandro L.; Almaguer-Flores, Argelia; Camps, Enrique; Pérez, Mario; Silva-Bermudez, Phaedra; Berea, Edgardo; Rodil, Sandra E.

2015-11-01

The antimicrobial properties of bismuth subsalicylate (BSS) nanoparticles against four opportunistic pathogens; E. coli, P. aeruginosa, S. aureus, and S. epidermidis were determined. BSS nanoparticles were synthesized by pulse laser ablation of a solid target in distilled water under different conditions. The nanoparticles were characterized using high-resolution transmission electron microscopy and absorption spectra and small angle X-ray scattering. The analysis shows that the colloids maintained the BSS structure and presented average particle size between 20 and 60 nm, while the concentration ranges from 95 to 195 mg/L. The antibacterial effect was reported as the inhibition ratio of the bacterial growth after 24 h and the cell viability was measured using the XTT assay. The results showed that the inhibition ratio of E. coli and S. epidermidis was dependant on the NPs size and/or concentration, meanwhile P. aeruginosa and S. aureus were more sensitive to the BSS nanoparticles independently of both the size and the concentration. In general, the BSS colloids with average particle size of 20 nm were the most effective, attaining inhibition ratios >80 %, similar or larger than those obtained with the antibiotic used as control. The results suggest that the BSS colloids could be used as effective antibacterial agents with potential applications in the medical area.

a Method for the Seamlines Network Automatic Selection Based on Building Vector

Science.gov (United States)

Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

2018-04-01

In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

Selection of a method to produce activated charcoal using four forest species

International Nuclear Information System (INIS)

Herrera Builes, Jhon Fredy; Morales Yepes, Wilmar Alexander; Perez Schile, Juan David

2004-01-01

This investigation was conducted in the coal and of forest products laboratory of the Universidad Nacional de Colombia, sede Medellin. It was oriented towards the selection of a method to obtain activated carbon form the following forest species; pino patula (Pinus patula), chingale Jacaranda copaia) pino tecunumani (pinus tecunumani) and roble (Quercus humboldti). The wood of each was characterized determining their physical properties of density and contraction. Seven different methods were tested; chemical activation chemical-physical activation with CO 2 chemical-physical activation with CO 2 and water vapor; chemical-physical activation with water vapor; physical activation with CO 2 ; physical activation with water vapor and physical activation with CO 2 and water vapor. The variables studied were residence time and temperature. Taking as a parameter the Iodine index, the chemical-physical activation with water vapor was selected, obtaining an Iodine index of over 800 for all the species studied with the exception of roble that only attained 764 which is still acceptable for water treatment

A New Decision-Making Method for Stock Portfolio Selection Based on Computing with Linguistic Assessment

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Chen-Tung Chen

2009-01-01

Full Text Available The purpose of stock portfolio selection is how to allocate the capital to a large number of stocks in order to bring a most profitable return for investors. In most of past literatures, experts considered the portfolio of selection problem only based on past crisp or quantitative data. However, many qualitative and quantitative factors will influence the stock portfolio selection in real investment situation. It is very important for experts or decision-makers to use their experience or knowledge to predict the performance of each stock and make a stock portfolio. Because of the knowledge, experience, and background of each expert are different and vague, different types of 2-tuple linguistic variable are suitable used to express experts' opinions for the performance evaluation of each stock with respect to criteria. According to the linguistic evaluations of experts, the linguistic TOPSIS and linguistic ELECTRE methods are combined to present a new decision-making method for dealing with stock selection problems in this paper. Once the investment set has been determined, the risk preferences of investor are considered to calculate the investment ratio of each stock in the investment set. Finally, an example is implemented to demonstrate the practicability of the proposed method.

Method selection for mercury removal from hard coal

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Dziok Tadeusz

2017-01-01

Full Text Available Mercury is commonly found in coal and the coal utilization processes constitute one of the main sources of mercury emission to the environment. This issue is particularly important for Poland, because the Polish energy production sector is based on brown and hard coal. The forecasts show that this trend in energy production will continue in the coming years. At the time of the emission limits introduction, methods of reducing the mercury emission will have to be implemented in Poland. Mercury emission can be reduced as a result of using coal with a relatively low mercury content. In the case of the absence of such coals, the methods of mercury removal from coal can be implemented. The currently used and developing methods include the coal cleaning process (both the coal washing and the dry deshaling as well as the thermal pretreatment of coal (mild pyrolysis. The effectiveness of these methods various for different coals, which is caused by the diversity of coal origin, various characteristics of coal and, especially, by the various modes of mercury occurrence in coal. It should be mentioned that the coal cleaning process allows for the removal of mercury occurring in mineral matter, mainly in pyrite. The thermal pretreatment of coal allows for the removal of mercury occurring in organic matter as well as in the inorganic constituents characterized by a low temperature of mercury release. In this paper, the guidelines for the selection of mercury removal method from hard coal were presented. The guidelines were developed taking into consideration: the effectiveness of mercury removal from coal in the process of coal cleaning and thermal pretreatment, the synergy effect resulting from the combination of these processes, the direction of coal utilization as well as the influence of these processes on coal properties.

A Novel Fault Line Selection Method Based on Improved Oscillator System of Power Distribution Network

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Xiaowei Wang

2014-01-01

Full Text Available A novel method of fault line selection based on IOS is presented. Firstly, the IOS is established by using math model, which adopted TZSC signal to replace built-in signal of duffing chaotic oscillator by selecting appropriate parameters. Then, each line’s TZSC decomposed by db10 wavelet packet to get CFB with the maximum energy principle, and CFB was solved by IOS. Finally, maximum chaotic distance and average chaotic distance on the phase trajectory are used to judge fault line. Simulation results show that the proposed method can accurately judge fault line and healthy line in strong noisy background. Besides, the nondetection zones of proposed method are elaborated.

Dynamic spectrum management in green cognitive radio cellular networks

KAUST Repository

Sboui, Lokman

2018-02-15

In this paper, we propose a new cellular network operation scheme fulfilling the 5G requirements related to spectrum management and green communications. We focus on cognitive radio cellular networks in which both the primary network (PN) and the secondary network (SN) are maximizing their operational profits. The PN and the SN are required to respect a CO emissions threshold by switching off one or more lightly loaded base stations (BSs). In addition, the PN accepts to cooperate with the SN by leasing its spectrum in the cells where the PN is turned off. In return, the corresponding SN BSs host the PN users and impose extra roaming fees to the PN. We propose a low-complexity algorithm that maximizes the profit per CO emissions metric while switching on/off the BSs. In the simulations, we show that our proposed algorithm achieves performances close to the exhaustive search method. In addition, we find that the roaming price is a key parameter that affects both PN and SN profits.

An Entropy-based gene selection method for cancer classification using microarray data

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Krishnan Arun

2005-03-01

Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

Linear feature selection in texture analysis - A PLS based method

DEFF Research Database (Denmark)

Marques, Joselene; Igel, Christian; Lillholm, Martin

2013-01-01

We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....

Effect of contouring on bending structural stiffness and bending strength of the 3.5 titanium SOP implant.

Science.gov (United States)

Rutherford, Scott; Ness, Malcolm G

2012-11-01

To compare the bending structural stiffness (BSS) and bending strength (BS) of the 3.5 titanium (Ti) string of pearls (SOP) plate and the 3.5 316LVM stainless steel SOP plate; and the effect of contouring on the BSS and BS of the 3.5 Ti SOP plate. In vitro experimental static 4-point bending materials testing. Twenty-five 3.5 mm Ti and five 3.5 mm 316LVM stainless steel SOP locking bone plates. Each plate was tested in 4-point bending until 10 mm of displacement was achieved. BSS and BS were then calculated for each plate. A 2-sample t-test was used to compare the mean BSS and BS of the different groups. The 3.5 Ti SOP plate had lower mean BSS (0.00263 Nm(2) ) but similar mean BS (12.8 Nm) when compared to the 3.5 316LVM SOP (0.00402 Nm(2) , 13.0 Nm). Prebending the 3.5 Ti SOP diminished its mean BSS (0.00224 Nm(2) ) and mean BS (9.4 Nm) when compared to the Ti control. Pretwisting the 3.5 Ti SOP increased its mean BSS (0.00273 Nm(2) ) but decreased its mean BS (12.4 Nm) when compared to the Ti control. The 3.5 Ti SOP is less stiff but of similar strength to the 3.5 316LVM stainless steel SOP. Prebending the Ti SOP significantly lowers its stiffness and strength. Pretwisting the SOP actually increases its stiffness but slightly lowers its strength. © Copyright 2012 by The American College of Veterinary Surgeons.

Band selection method based on spectrum difference in targets of interest in hyperspectral imagery

Science.gov (United States)

Zhang, Xiaohan; Yang, Guang; Yang, Yongbo; Huang, Junhua

2016-10-01

While hyperspectral data shares rich spectrum information, it has numbers of bands with high correlation coefficients, causing great data redundancy. A reasonable band selection is important for subsequent processing. Bands with large amount of information and low correlation should be selected. On this basis, according to the needs of target detection applications, the spectral characteristics of the objects of interest are taken into consideration in this paper, and a new method based on spectrum difference is proposed. Firstly, according to the spectrum differences of targets of interest, a difference matrix which represents the different spectral reflectance of different targets in different bands is structured. By setting a threshold, the bands satisfying the conditions would be left, constituting a subset of bands. Then, the correlation coefficients between bands are calculated and correlation matrix is given. According to the size of the correlation coefficient, the bands can be set into several groups. At last, the conception of normalized variance is used on behalf of the information content of each band. The bands are sorted by the value of its normalized variance. Set needing number of bands, and the optimum band combination solution can be get by these three steps. This method retains the greatest degree of difference between the target of interest and is easy to achieve by computer automatically. Besides, false color image synthesis experiment is carried out using the bands selected by this method as well as other 3 methods to show the performance of method in this paper.

Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method

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Yunna Wu

2016-03-01

Full Text Available The task of site selection for electric vehicle charging stations (EVCS is hugely important from the perspective of harmonious and sustainable development. However, flaws and inadequacies in the currently used multi-criteria decision making methods could result in inaccurate and irrational decision results. First of all, the uncertainty of the information cannot be described integrally in the evaluation of the EVCS site selection. Secondly, rigorous consideration of the mutual influence between the various criteria is lacking, which is mainly evidenced in two aspects: one is ignoring the correlation, and the other is the unconscionable measurements. Last but not least, the ranking method adopted in previous studies is not very appropriate for evaluating the EVCS site selection problem. As a result of the above analysis, a Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE method-based decision system combined with the cloud model is proposed in this paper for EVCS site selection. Firstly, the use of the PROMETHEE method can bolster the confidence and visibility for decision makers. Secondly, the cloud model is recommended to describe the fuzziness and randomness of linguistic terms integrally and accurately. Finally, the Analytical Network Process (ANP method is adopted to measure the correlation of the indicators with a greatly simplified calculation of the parameters and the steps required.

A comparison of U.S. and European methods for accident scenario, identificaton, selection and quantification

International Nuclear Information System (INIS)

Cadwallader, L.C.; Djerassi, H.; Lampin, I.

1989-10-01

This paper presents a comparison of the varying methods used to identify and select accident-initiating events for safety analysis and probabilistic risk assessment (PRA). Initiating events are important in that they define the extent of a given safety analysis or PRA. Comprehensiveness in identification and selection of initiating events is necessary to ensure that a thorough analysis is being performed. While total completeness cannot ever be realized, inclusion of all safety significant events can be attained. The European approach to initiating event identification and selection arises from within a newly developed Safety Analysis methodology framework. This is a functional approach, with accident initiators based on events that will cause a system or facility loss of function. The US method divides accident initiators into two groups, internal accident initiators into two groups, internal and external events. Since traditional US PRA techniques are applied to fusion facilities, the recommended PRA-based approach is a review of historical safety documents coupled with a facility-level Master Logic Diagram. The US and European methods are described, and both are applied to a proposed International Thermonuclear Experiment Reactor (ITER) Magnet System in a sample problem. Contrasts in the US and European methods are discussed. Within their respective frameworks, each method can provide the comprehensiveness of safety-significant events needed for a thorough analysis. 4 refs., 8 figs., 11 tabs

Dichotomous versus semi-quantitative scoring of ultrasound joint inflammation in rheumatoid arthritis using novel individualized joint selection methods.

Science.gov (United States)

Tan, York Kiat; Allen, John C; Lye, Weng Kit; Conaghan, Philip G; Chew, Li-Ching; Thumboo, Julian

2017-05-01

The aim of the study is to compare the responsiveness of two joint inflammation scoring systems (dichotomous scoring (DS) versus semi-quantitative scoring (SQS)) using novel individualized ultrasound joint selection methods and existing ultrasound joint selection methods. Responsiveness measured by the standardized response means (SRMs) using the DS and the SQS system (for both the novel and existing ultrasound joint selection methods) was derived using the baseline and the 3-month total inflammatory scores from 20 rheumatoid arthritis patients. The relative SRM gain ratios (SRM-Gains) for both scoring system (DS and SQS) comparing the novel to the existing methods were computed. Both scoring systems (DS and SQS) demonstrated substantial SRM-Gains (ranged from 3.31 to 5.67 for the DS system and ranged from 1.82 to 3.26 for the SQS system). The SRMs using the novel methods ranged from 0.94 to 1.36 for the DS system and ranged from 0.89 to 1.11 for the SQS system. The SRMs using the existing methods ranged from 0.24 to 0.32 for the DS system and ranged from 0.34 to 0.49 for the SQS system. The DS system appears to achieve high responsiveness comparable to SQS for the novel individualized ultrasound joint selection methods.

Selection of analytical methods for mixed waste analysis at the Hanford Site

International Nuclear Information System (INIS)

Morant, P.M.

1994-09-01

This document describes the process that the US Department of Energy (DOE), Richland Operations Office (RL) and contractor laboratories use to select appropriate or develop new or modified analytical methods. These methods are needed to provide reliable mixed waste characterization data that meet project-specific quality assurance (QA) requirements while also meeting health and safety standards for handling radioactive materials. This process will provide the technical basis for DOE's analysis of mixed waste and support requests for regulatory approval of these new methods when they are used to satisfy the regulatory requirements of the Hanford Federal Facility Agreement and Consent Order (Tri-party Agreement) (Ecology et al. 1992)

Selection of Investment Projects by Monte Carlo Method in Risk Condition

Directory of Open Access Journals (Sweden)

M. E.

2017-12-01

Full Text Available The Monte Carlo method (also known as the Monte Carlo simulation was proposed by Nicholas Metropolis, S. Ulam and Jhon Von Neiman in 50-th years of the past century. The method can be widely applied to analysis of investment projects due to the advantages recognized both by practitioners and the academic community. The balance model of a project with discounted financial flows has been implemented for Microsoft Excel and Google Docs spread-sheet solutions. The Monte Carlo method for project with low and high correlated net present value (NPV parameters in the environment of the electronic tables of MS Excel/Google Docs. A distinct graduation of risk was identified. A necessity of account of correlation effects and the use of multivariate imitation during the project selection has been demonstrated.

A Novel Extension Decision-Making Method for Selecting Solar Power Systems

Directory of Open Access Journals (Sweden)

Meng-Hui Wang

2013-01-01

Full Text Available Due to the complex parameters of a solar power system, the designer not only must think about the load demand but also needs to consider the price, weight, and annual power generating capacity (APGC and maximum power of the solar system. It is an important task to find the optimal solar power system with many parameters. Therefore, this paper presents a novel decision-making method based on the extension theory; we call it extension decision-making method (EDMM. Using the EDMM can make it quick to select the optimal solar power system. The paper proposed this method not only to provide a useful estimated tool for the solar system engineers but also to supply the important reference with the installation of solar systems to the consumer.

Selecting minimum dataset soil variables using PLSR as a regressive multivariate method

Science.gov (United States)

Stellacci, Anna Maria; Armenise, Elena; Castellini, Mirko; Rossi, Roberta; Vitti, Carolina; Leogrande, Rita; De Benedetto, Daniela; Ferrara, Rossana M.; Vivaldi, Gaetano A.

2017-04-01

Long-term field experiments and science-based tools that characterize soil status (namely the soil quality indices, SQIs) assume a strategic role in assessing the effect of agronomic techniques and thus in improving soil management especially in marginal environments. Selecting key soil variables able to best represent soil status is a critical step for the calculation of SQIs. Current studies show the effectiveness of statistical methods for variable selection to extract relevant information deriving from multivariate datasets. Principal component analysis (PCA) has been mainly used, however supervised multivariate methods and regressive techniques are progressively being evaluated (Armenise et al., 2013; de Paul Obade et al., 2016; Pulido Moncada et al., 2014). The present study explores the effectiveness of partial least square regression (PLSR) in selecting critical soil variables, using a dataset comparing conventional tillage and sod-seeding on durum wheat. The results were compared to those obtained using PCA and stepwise discriminant analysis (SDA). The soil data derived from a long-term field experiment in Southern Italy. On samples collected in April 2015, the following set of variables was quantified: (i) chemical: total organic carbon and nitrogen (TOC and TN), alkali-extractable C (TEC and humic substances - HA-FA), water extractable N and organic C (WEN and WEOC), Olsen extractable P, exchangeable cations, pH and EC; (ii) physical: texture, dry bulk density (BD), macroporosity (Pmac), air capacity (AC), and relative field capacity (RFC); (iii) biological: carbon of the microbial biomass quantified with the fumigation-extraction method. PCA and SDA were previously applied to the multivariate dataset (Stellacci et al., 2016). PLSR was carried out on mean centered and variance scaled data of predictors (soil variables) and response (wheat yield) variables using the PLS procedure of SAS/STAT. In addition, variable importance for projection (VIP

The Analysis Of Accuracy Of Selected Methods Of Measuring The Thermal Resistance Of IGBTs

Directory of Open Access Journals (Sweden)

Górecki Krzysztof

2015-09-01

Full Text Available In the paper selected methods of measuring the thermal resistance of an IGBT (Insulated Gate Bipolar Transistor are presented and the accuracy of these methods is analysed. The analysis of the measurement error is performed and operating conditions of the considered device, at which each measurement method assures the least measuring error, are pointed out. Theoretical considerations are illustrated with some results of measurements and calculations.

New visible and selective DNA staining method in gels with tetrazolium salts.

Science.gov (United States)

Paredes, Aaron J; Naranjo-Palma, Tatiana; Alfaro-Valdés, Hilda M; Barriga, Andrés; Babul, Jorge; Wilson, Christian A M

2017-01-15

DNA staining in gels has historically been carried out using silver staining and fluorescent dyes like ethidium bromide and SYBR Green I (SGI). Using fluorescent dyes allows recovery of the analyte, but requires instruments such as a transilluminator or fluorimeter to visualize the DNA. Here we described a new and simple method that allows DNA visualization to the naked eye by generating a colored precipitate. It works by soaking the acrylamide or agarose DNA gel in SGI and nitro blue tetrazolium (NBT) solution that, when exposed to sunlight, produces a purple insoluble formazan precipitate that remains in the gel after exposure to light. A calibration curve made with a DNA standard established a detection limit of approximately 180 pg/band at 500 bp. Selectivity of this assay was determined using different biomolecules, demonstrating a high selectivity for DNA. Integrity and functionality of the DNA recovered from gels was determined by enzymatic cutting with a restriction enzyme and by transforming competent cells after the different staining methods, respectively. Our method showed the best performance among the dyes employed. Based on its specificity, low cost and its adequacy for field work, this new methodology has enormous potential benefits to research and industry. Copyright © 2016 Elsevier Inc. All rights reserved.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

Science.gov (United States)

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

Analysis of Various Frequency Selective Shielding Glass by FDTD method

OpenAIRE

笠嶋, 善憲; Kasashima, Yoshinori

2012-01-01

A frequency Selective shielding (FSS) glass is a print of many same size antennas on a sheet of glass, and it has high shielding properties for one specific frequency. This time, the author analyzed characteristics of various FSSs whose antenna types are different by FDTD method. The antenna types are cross dipole, circular loop, square loop, circular patch, and square patch. As the result, the FSSs can be composed of the various types of the antennas, and the FSSs have broad-band shielding c...

The CHOICE study: effect of counselling on the selection of combined hormonal contraceptive methods in 11 countries.

Science.gov (United States)

Bitzer, Johannes; Gemzell-Danielsson, Kristina; Roumen, Frans; Marintcheva-Petrova, Maya; van Bakel, Bas; Oddens, Björn J

2012-02-01

To encourage healthcare professionals to counsel women seeking combined hormonal contraceptives (CHCs) about alternative CHCs and to study the influence of counselling on women's selection of CHCs. Women (15-40 years old) in 11 countries who consulted HCPs about CHCs were counselled about the pill, transdermal patch, and vaginal ring. Both the HCPs and the women completed questionnaires. Of women who were counselled (n = 18,787), 47% selected another CHC method than originally planned. One in four who intended to use the pill chose another method (16% chose the patch; 65% chose the ring). In total, patch use increased from 5% -8% (difference = 3.7% [97.5% CI: 3.3-4.2]; p use nearly quadrupled from 8% -30% (difference = 21.7% [97.5% CI: 21.0-22.5]; p women who were undecided prior to counselling selected a method after counselling. Selection of the pill increased most in Russia (+ 11%) and Sweden (+ 5%); patch selection was greatest in Russia (+ 7%) and Israel (+ 6%); ring use increased most in Ukraine and in the Czech Republic and Slovakia (+ 36%). Counselling increases use of alternative CHCs, such as the patch and the ring. Considerable differences between countries were noted.

A simple method for finding explicit analytic transition densities of diffusion processes with general diploid selection.

Science.gov (United States)

Song, Yun S; Steinrücken, Matthias

2012-03-01

The transition density function of the Wright-Fisher diffusion describes the evolution of population-wide allele frequencies over time. This function has important practical applications in population genetics, but finding an explicit formula under a general diploid selection model has remained a difficult open problem. In this article, we develop a new computational method to tackle this classic problem. Specifically, our method explicitly finds the eigenvalues and eigenfunctions of the diffusion generator associated with the Wright-Fisher diffusion with recurrent mutation and arbitrary diploid selection, thus allowing one to obtain an accurate spectral representation of the transition density function. Simplicity is one of the appealing features of our approach. Although our derivation involves somewhat advanced mathematical concepts, the resulting algorithm is quite simple and efficient, only involving standard linear algebra. Furthermore, unlike previous approaches based on perturbation, which is applicable only when the population-scaled selection coefficient is small, our method is nonperturbative and is valid for a broad range of parameter values. As a by-product of our work, we obtain the rate of convergence to the stationary distribution under mutation-selection balance.

Selection of heat disposal methods for a Hanford Nuclear Energy Center

International Nuclear Information System (INIS)

Young, J.R.; Kannberg, L.D.; Ramsdell, J.V.; Rickard, W.H.; Watson, D.G.

1976-06-01

Selection of the best method for disposal of the waste heat from a large power generation center requires a comprehensive comparison of the costs and environmental effects. The objective is to identify the heat dissipation method with the minimum total economic and environmental cost. A 20 reactor HNEC will dissipate about 50,000 MWt of waste heat; a 40 reactor HNEC would release about 100,000 MWt. This is a much larger discharge of heat than has occurred from other concentrated industrial facilities and consequently a special analysis is required to determine the permissibility of such a large heat disposal and the best methods of disposal. It is possible that some methods of disposal will not be permissible because of excessive environmental effects or that the optimum disposal method may include a combination of several methods. A preliminary analysis is presented of the Hanford Nuclear Energy Center heat disposal problem to determine the best methods for disposal and any obvious limitations on the amount of heat that can be released. The analysis is based, in part, on information from an interim conceptual study, a heat sink management analysis, and a meteorological analysis

Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data.

Science.gov (United States)

Song, Sutao; Zhan, Zhichao; Long, Zhiying; Zhang, Jiacai; Yao, Li

2011-02-16

Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

Science.gov (United States)

Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

2017-07-01

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

Analysis of multicriteria models application for selection of an optimal artificial lift method in oil production

Directory of Open Access Journals (Sweden)

Crnogorac Miroslav P.

2016-01-01

Full Text Available In the world today for the exploitation of oil reservoirs by artificial lift methods are applied different types of deep pumps (piston, centrifugal, screw, hydraulic, water jet pumps and gas lift (continuous, intermittent and plunger. Maximum values of oil production achieved by these exploitation methods are significantly different. In order to select the optimal exploitation method of oil well, the multicriteria analysis models are used. In this paper is presented an analysis of the multicriteria model's application known as VIKOR, TOPSIS, ELECTRE, AHP and PROMETHEE for selection of optimal exploitation method for typical oil well at Serbian exploration area. Ranking results of applicability of the deep piston pumps, hydraulic pumps, screw pumps, gas lift method and electric submersible centrifugal pumps, indicated that in the all above multicriteria models except in PROMETHEE, the optimal method of exploitation are deep piston pumps and gas lift.

Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods

International Nuclear Information System (INIS)

Çalışkan, Halil; Kurşuncu, Bilal; Kurbanoğlu, Cahit; Güven, Şevki Yılmaz

2013-01-01

Highlights: ► The material selection problem for tool holders used in hard milling was solved. ► EXPROM2, TOPSIS and VIKOR methods were used for ranking the alternative materials. ► The weighting of criteria was performed by compromised weighting method. ► The best material for the tool holder was selected as Fe–5Cr–Mo–V aircraft steel. -- Abstract: Nowadays machining of materials in their hardened state, also called hard machining, is a challenge in production of tools and molds. It has some advantages such as lower process time and lower manufacturing cost when compared to conventional machining. In machining of hard workpiece materials, however, very high stresses act on the tool holder through the cutting tool. These stresses necessitate the tool holder to have some specific properties. Especially in hard milling, the tool holder should have high stiffness and should be able to dissipate the energy generated during interrupted cutting. Material cost of the tool holder is also important since lower costs provide a competitive advantage for manufacturers. The material selection for the tool holder should be conducted considering aforementioned requirements. To tackle the difficulty of the material selection with specific properties from a large number of alternatives, multi-criteria decision-making (MCDM) methods have been used. In this paper a decision model including extended PROMETHEE II (EXPROM2) (preference ranking organization method for enrichment evaluation), TOPSIS (technique for order performance by similarity to ideal solution) and VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) methods were used for the selection of the best material for the tool holder used in hard milling. The criteria weighting was performed by compromised weighting method composed of AHP (analytic hierarchy process) and Entropy methods. The candidate materials were ranked by using these methods and the results obtained by each method were compared. It was confirmed

Selection of materials using multi-criteria decision-making methods with minimum data

Directory of Open Access Journals (Sweden)

Shankar Chakraborty

2013-07-01

Full Text Available Selection of material for a specific engineering component, which plays a significant role in its design and proper functioning, is often treated as a multi-criteria decision-making (MCDM problem where the most suitable material is to be chosen based on a given set of conflicting criteria. For solving these MCDM problems, the designers do not generally know what should be the optimal number of criteria required for arriving at the best decisive action. Those criteria should be independent to each other and their number should usually limit to seven plus or minus two. In this paper, five material selection problems are solved using three common MCDM techniques to demonstrate the effect of number of criteria on the final rankings of the material alternatives. It is interesting to observe that the choices of the best suited materials solely depend on the criterion having the maximum priority value. It is also found that among the three MCDM methods, the ranking performance of VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje method is the best.

Statistical approach for selection of regression model during validation of bioanalytical method

Directory of Open Access Journals (Sweden)

Natalija Nakov

2014-06-01

Full Text Available The selection of an adequate regression model is the basis for obtaining accurate and reproducible results during the bionalytical method validation. Given the wide concentration range, frequently present in bioanalytical assays, heteroscedasticity of the data may be expected. Several weighted linear and quadratic regression models were evaluated during the selection of the adequate curve fit using nonparametric statistical tests: One sample rank test and Wilcoxon signed rank test for two independent groups of samples. The results obtained with One sample rank test could not give statistical justification for the selection of linear vs. quadratic regression models because slight differences between the error (presented through the relative residuals were obtained. Estimation of the significance of the differences in the RR was achieved using Wilcoxon signed rank test, where linear and quadratic regression models were treated as two independent groups. The application of this simple non-parametric statistical test provides statistical confirmation of the choice of an adequate regression model.

Antibacterial effect of bismuth subsalicylate nanoparticles synthesized by laser ablation

International Nuclear Information System (INIS)

Flores-Castañeda, Mariela; Vega-Jiménez, Alejandro L.; Almaguer-Flores, Argelia; Camps, Enrique; Pérez, Mario; Silva-Bermudez, Phaedra; Berea, Edgardo; Rodil, Sandra E.

2015-01-01

The antimicrobial properties of bismuth subsalicylate (BSS) nanoparticles against four opportunistic pathogens; E. coli, P. aeruginosa, S. aureus, and S. epidermidis were determined. BSS nanoparticles were synthesized by pulse laser ablation of a solid target in distilled water under different conditions. The nanoparticles were characterized using high-resolution transmission electron microscopy and absorption spectra and small angle X-ray scattering. The analysis shows that the colloids maintained the BSS structure and presented average particle size between 20 and 60 nm, while the concentration ranges from 95 to 195 mg/L. The antibacterial effect was reported as the inhibition ratio of the bacterial growth after 24 h and the cell viability was measured using the XTT assay. The results showed that the inhibition ratio of E. coli and S. epidermidis was dependant on the NPs size and/or concentration, meanwhile P. aeruginosa and S. aureus were more sensitive to the BSS nanoparticles independently of both the size and the concentration. In general, the BSS colloids with average particle size of 20 nm were the most effective, attaining inhibition ratios >80 %, similar or larger than those obtained with the antibiotic used as control. The results suggest that the BSS colloids could be used as effective antibacterial agents with potential applications in the medical area

Antibacterial effect of bismuth subsalicylate nanoparticles synthesized by laser ablation

Energy Technology Data Exchange (ETDEWEB)

Flores-Castañeda, Mariela [Instituto Nacional de Investigaciones Nucleares (Mexico); Vega-Jiménez, Alejandro L., E-mail: argelia.almaguer@mac.com; Almaguer-Flores, Argelia [Universidad Nacional Autónoma de México, Facultad de Odontología, DEPeI, I (Mexico); Camps, Enrique; Pérez, Mario [Instituto Nacional de Investigaciones Nucleares (Mexico); Silva-Bermudez, Phaedra [Instituto Nacional de Rehabilitación, Unidad de Ingeniería de Tejidos, Terapia Celular y Medicina Regenerativa (Mexico); Berea, Edgardo [FarmaQuimia SA de CV. (Mexico); Rodil, Sandra E. [Universidad Nacional Autónoma de México, Instituto de Investigaciones en Materiales (Mexico)

2015-11-15

The antimicrobial properties of bismuth subsalicylate (BSS) nanoparticles against four opportunistic pathogens; E. coli, P. aeruginosa, S. aureus, and S. epidermidis were determined. BSS nanoparticles were synthesized by pulse laser ablation of a solid target in distilled water under different conditions. The nanoparticles were characterized using high-resolution transmission electron microscopy and absorption spectra and small angle X-ray scattering. The analysis shows that the colloids maintained the BSS structure and presented average particle size between 20 and 60 nm, while the concentration ranges from 95 to 195 mg/L. The antibacterial effect was reported as the inhibition ratio of the bacterial growth after 24 h and the cell viability was measured using the XTT assay. The results showed that the inhibition ratio of E. coli and S. epidermidis was dependant on the NPs size and/or concentration, meanwhile P. aeruginosa and S. aureus were more sensitive to the BSS nanoparticles independently of both the size and the concentration. In general, the BSS colloids with average particle size of 20 nm were the most effective, attaining inhibition ratios >80 %, similar or larger than those obtained with the antibiotic used as control. The results suggest that the BSS colloids could be used as effective antibacterial agents with potential applications in the medical area.

An objective method for High Dynamic Range source content selection

DEFF Research Database (Denmark)

Narwaria, Manish; Mantel, Claire; Da Silva, Matthieu Perreira

2014-01-01

With the aim of improving the immersive experience of the end user, High Dynamic Range (HDR) imaging has been gaining popularity. Therefore, proper validation and performance benchmarking of HDR processing algorithms is a key step towards standardization and commercial deployment. A crucial...... component of such validation studies is the selection of a challenging and balanced set of source (reference) HDR content. In order to facilitate this, we present an objective method based on the premise that a more challenging HDR scene encapsulates higher contrast, and as a result will show up more...

An Efficient Adaptive Window Size Selection Method for Improving Spectrogram Visualization

Directory of Open Access Journals (Sweden)

Shibli Nisar

2016-01-01

Full Text Available Short Time Fourier Transform (STFT is an important technique for the time-frequency analysis of a time varying signal. The basic approach behind it involves the application of a Fast Fourier Transform (FFT to a signal multiplied with an appropriate window function with fixed resolution. The selection of an appropriate window size is difficult when no background information about the input signal is known. In this paper, a novel empirical model is proposed that adaptively adjusts the window size for a narrow band-signal using spectrum sensing technique. For wide-band signals, where a fixed time-frequency resolution is undesirable, the approach adapts the constant Q transform (CQT. Unlike the STFT, the CQT provides a varying time-frequency resolution. This results in a high spectral resolution at low frequencies and high temporal resolution at high frequencies. In this paper, a simple but effective switching framework is provided between both STFT and CQT. The proposed method also allows for the dynamic construction of a filter bank according to user-defined parameters. This helps in reducing redundant entries in the filter bank. Results obtained from the proposed method not only improve the spectrogram visualization but also reduce the computation cost and achieves 87.71% of the appropriate window length selection.

A comparison of methods to separate treatment from self-selection effects in an online banking setting

NARCIS (Netherlands)

Gensler, S.; Leeflang, P.S.H.; Skiera, B.

The literature discusses several methods to control for self-selection effects but provides little guidance on which method to use in a setting with a limited number of variables. The authors theoretically compare and empirically assess the performance of different matching methods and instrumental

[Targeted pharmacist-led medication order review in hospital: Assessment of a selection method for drug prescriptions].

Science.gov (United States)

Jarre, C; Bouchet, J; Hellot-Guersing, M; Leromain, A-S; Derharoutunian, C; Gadot, A; Roubille, R

2017-11-01

The aim of this study was to assess a selection method for drug prescriptions developed at the hospital level that allows to target pharmacist-led medication order review for at-risk patients and drugs. A one-month study has been conducted on all targeted medication orders in 19 care units. Selection criteria have been identified: biological criteria, alert medications and drug interactions. Pharmacists' interventions proposed during medication order review were listed and the possible links to the selection criteria were determined. A total of 1612 prescriptions were analysed and 236 pharmacists' interventions were performed (14.6 interventions per 100 prescriptions). Physicians' acceptance rate was 60.6%. The percentage of pharmacists' interventions linked to the selection criteria was 35.6%. The relevance of the biological criteria was identified, particularly the one identifying patients with creatinine clearance below 30ml/min. Six alert medications were also relevant selection criteria: dabigatran, morphine, gentamicin, methotrexate, potassium chloride and trimethoprim sulfamethoxazole. Drug interactions criteria was irrelevant. This study allowed a first assessment of the selection criteria used. A largest study seems necessary to continue the analysis of this selection method for prescriptions, especially the assessment of the alert medications list, in order to refine the prescriptions targeting. Copyright © 2017 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

New Method of Selecting Efficient Project Portfolios in the Presence of Hybrid Uncertainty

Directory of Open Access Journals (Sweden)

Bogdan Rębiasz

2016-01-01

Full Text Available A new methods of selecting efficient project portfolios in the presence of hybrid uncertainty has been presented. Pareto optimal solutions have been defined by an algorithm for generating project portfolios. The method presented allows us to select efficient project portfolios taking into account statistical and economic dependencies between projects when some of the parameters used in the calculation of effectiveness can be expressed in the form of an interactive possibility distribution and some in the form of a probability distribution. The procedure for processing such hybrid data combines stochastic simulation with nonlinear programming. The interaction between data are modeled by correlation matrices and the interval regression. Economic dependences are taken into account by the equations balancing the production capacity of the company. The practical example presented indicates that an interaction between projects has a significant impact on the results of calculations. (original abstract

Obstetric and gynecological intervention in women with Bernard-Soulier syndrome: Report of two cases

Directory of Open Access Journals (Sweden)

Mitrović Mirjana

2014-01-01

Full Text Available Introduction. Bernard-Soulier syndrome (BSS is a rare inherited bleeding disorder characterized by giant platelets thrombocytopenia e prolonged bleeding timee frequent hemorrhages with considerable morbidity. Data on the outcome of pregnancy and gynecological intervention in BSS are rare and there are no general therapeutic recommendations. Cases Outline. We report two cases of BSS. In the first case a 29-year-old patient with BSS was admitted in 8 weeks of gestation. The diagnosis of BSS was made on the basis of prolonged bleeding time, giant-platelets thrombocytopenia, and absent ristocetin-induced platelet aggregation. In 38 week of gestation Cesarean section, with platelets transfusion preparation, was performed. Obstetric intervention passed without complication. Postoperative course was complicated with a three-week vaginal bleeding resistant to platelet transfusion. Neonate platelet count was normal. Our second case was a 28-year-old patient with BSS, hospitalized for ovarial tumor surgery. The patient was prepared for the intervention with platelets transfusion. The surgery was uncomplicated, but on the second postoperative day a massive vaginal bleeding, resistant to the platelet transfusion, developed. Bleeding control was achieved with activated recombinant factor VII. Twelve hours the patient developed later hypertensive crisis with epileptic seizure due to subarachnoid hemorrhage. Therapy was continued with platelet transfusion, antihypertensive and antiedema drugs. PH examination of tumor tissue showed hemorrhagic ovarial cyst. Conclusion. Obstretic and gynecological intervention in women with BSS may be associated with a life-threatening bleeding thus requiring a multidisciplinary approach with adequate preparation. Because of the limited data in the literature, it is not possible to provide firm management recommendations and each case should be managed individually.

An improved culture method for selective isolation of Campylobacter jejuni from wastewater

Directory of Open Access Journals (Sweden)

Jinyong Kim

2016-08-01

Full Text Available Campylobacter jejuni is one of the leading foodborne pathogens worldwide. C. jejuni is isolated from a wide range of foods, domestic animals, wildlife, and environmental sources. The currently-available culture-based isolation methods are not highly effective for wastewater samples due to the low number of C. jejuni in the midst of competing bacteria. To detect and isolate C. jejuni from wastewater samples, in this study, we evaluated a few different enrichment conditions using five different antibiotics (i.e., cefoperazone, vancomycin, trimethoprim, polymyxin B, and rifampicin, to which C. jejuni is intrinsically resistant. The selectivity of each enrichment condition was measured with Ct value using quantitative real-time PCR (qRT-PCR, and multiplex PCR to determine Campylobacter species. In addition, the efficacy of Campylobacter isolation on different culture media after selective enrichment was examined by growing on Bolton and Preston agar plates. The addition of polymyxin B, rifampicin, or both to the Bolton selective supplements enhanced the selective isolation of C. jejuni. In particular, rifampicin supplementation and an increased culture temperature (i.e., 42°C had a decisive effect on the selective enrichment of C. jejuni from wastewater. The results of 16S rDNA sequencing also revealed that Enterococcus spp. and Pseudomonas aeruginosa are major competing bacteria in the enrichment conditions. Although it is known to be difficult to isolate Campylobacter from samples with heavy contamination, this study well exhibited that the manipulation of antibiotic selective pressure improves the isolation efficiency of fastidious Campylobacter from wastewater.

A stereo remote sensing feature selection method based on artificial bee colony algorithm

Science.gov (United States)

Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

2014-05-01

To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

Selective methods for polyphenols and sulphur dioxide determination in wines.

Science.gov (United States)

García-Guzmán, Juan J; Hernández-Artiga, María P; Palacios-Ponce de León, Lourdes; Bellido-Milla, Dolores

2015-09-01

A critical review to the methods recommended by international bodies and widely used in the winery industry and research studies was performed. A Laccase biosensor was applied to the selective determination of polyphenols in wines. The biosensor response was characterised and it responds mainly to o-diphenols which are the principal polyphenols responsible for the stability and sensory qualities of wines. The spectrophotometric method to determine free and total sulphur dioxide recommended for beers was applied directly to wines. A sampling of 14 red and white wines was performed and they were analysed for biosensor polyphenol index (IBP) and sulphur dioxide concentration (SO2). The antioxidant capacity by the ABTS(+) spectrophotometric method was also determined. A correlation study was performed to elucidate the influence of the polyphenols and SO2 on the wines stability. High correlations were found between IBP and antioxidant capacity and low correlation between SO2 and antioxidant capacity. To evaluate the benefits of wine drinking a new parameter (IBP/SO2) is proposed. Copyright © 2015 Elsevier Ltd. All rights reserved.

FCNN-MR: A Parallel Instance Selection Method Based on Fast Condensed Nearest Neighbor Rule

OpenAIRE

Lu Si; Jie Yu; Shasha Li; Jun Ma; Lei Luo; Qingbo Wu; Yongqi Ma; Zhengji Liu

2017-01-01

Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rul...

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

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Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

2015-06-01

Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Wavelength selection method with standard deviation: application to pulse oximetry.

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Vazquez-Jaccaud, Camille; Paez, Gonzalo; Strojnik, Marija

2011-07-01

Near-infrared spectroscopy provides useful biological information after the radiation has penetrated through the tissue, within the therapeutic window. One of the significant shortcomings of the current applications of spectroscopic techniques to a live subject is that the subject may be uncooperative and the sample undergoes significant temporal variations, due to his health status that, from radiometric point of view, introduce measurement noise. We describe a novel wavelength selection method for monitoring, based on a standard deviation map, that allows low-noise sensitivity. It may be used with spectral transillumination, transmission, or reflection signals, including those corrupted by noise and unavoidable temporal effects. We apply it to the selection of two wavelengths for the case of pulse oximetry. Using spectroscopic data, we generate a map of standard deviation that we propose as a figure-of-merit in the presence of the noise introduced by the living subject. Even in the presence of diverse sources of noise, we identify four wavelength domains with standard deviation, minimally sensitive to temporal noise, and two wavelengths domains with low sensitivity to temporal noise.

Developing TOPSIS method using statistical normalization for selecting knowledge management strategies

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Amin Zadeh Sarraf

2013-09-01

Full Text Available Purpose: Numerous companies are expecting their knowledge management (KM to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. Design/methodology/approach: An extension of TOPSIS, a multi-attribute decision making (MADM technique, to a group decision environment is investigated. TOPSIS is a practical and useful technique for ranking and selection of a number of externally determined alternatives through distance measures. The entropy method is often used for assessing weights in the TOPSIS method. Entropy in information theory is a criterion uses for measuring the amount of disorder represented by a discrete probability distribution. According to decrease resistance degree of employees opposite of implementing a new strategy, it seems necessary to spot all managers’ opinion. The normal distribution considered the most prominent probability distribution in statistics is used to normalize gathered data. Findings: The results of this study show that by considering 6 criteria for alternatives Evaluation, the most appropriate KM strategy to implement  in our company was ‘‘Personalization’’. Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the approach such as normal distribution of sample and community. These assumptions can be changed in future work. Originality/value: This paper proposes an effective solution based on combined entropy and TOPSIS approach to help companies that need to evaluate and select KM strategies. In represented solution, opinions of all managers is gathered and normalized by using standard normal distribution and central limit theorem. Keywords: Knowledge management; strategy; TOPSIS; Normal distribution; entropy

Selective aerobic alcohol oxidation method for conversion of lignin into simple aromatic compounds

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Stahl, Shannon S; Rahimi, Alireza

2015-03-03

Described is a method to oxidize lignin or lignin sub-units. The method includes oxidation of secondary benzylic alcohol in the lignin or lignin sub-unit to a corresponding ketone in the presence of unprotected primarily aliphatic alcohol in the lignin or lignin sub-unit. The optimal catalyst system consists of HNO.sub.3 in combination with another Bronsted acid, in the absence of a metal-containing catalyst, thereby yielding a selectively oxidized lignin or lignin sub-unit. The method may be carried out in the presence or absence of additional reagents including TEMPO and TEMPO derivatives.

Duration and speed of speech events: A selection of methods

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Gibbon Dafydd

2015-07-01

Full Text Available The study of speech timing, i.e. the duration and speed or tempo of speech events, has increased in importance over the past twenty years, in particular in connection with increased demands for accuracy, intelligibility and naturalness in speech technology, with applications in language teaching and testing, and with the study of speech timing patterns in language typology. H owever, the methods used in such studies are very diverse, and so far there is no accessible overview of these methods. Since the field is too broad for us to provide an exhaustive account, we have made two choices: first, to provide a framework of paradigmatic (classificatory, syntagmatic (compositional and functional (discourse-oriented dimensions for duration analysis; and second, to provide worked examples of a selection of methods associated primarily with these three dimensions. Some of the methods which are covered are established state-of-the-art approaches (e.g. the paradigmatic Classification and Regression Trees, CART , analysis, others are discussed in a critical light (e.g. so-called ‘rhythm metrics’. A set of syntagmatic approaches applies to the tokenisation and tree parsing of duration hierarchies, based on speech annotations, and a functional approach describes duration distributions with sociolinguistic variables. Several of the methods are supported by a new web-based software tool for analysing annotated speech data, the Time Group Analyser.

Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

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Jaesung Lee

2016-11-01

Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

Rapid one-step selection method for generating nucleic acid aptamers: development of a DNA aptamer against α-bungarotoxin.

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Lasse H Lauridsen

Full Text Available BACKGROUND: Nucleic acids based therapeutic approaches have gained significant interest in recent years towards the development of therapeutics against many diseases. Recently, research on aptamers led to the marketing of Macugen®, an inhibitor of vascular endothelial growth factor (VEGF for the treatment of age related macular degeneration (AMD. Aptamer technology may prove useful as a therapeutic alternative against an array of human maladies. Considering the increased interest in aptamer technology globally that rival antibody mediated therapeutic approaches, a simplified selection, possibly in one-step, technique is required for developing aptamers in limited time period. PRINCIPAL FINDINGS: Herein, we present a simple one-step selection of DNA aptamers against α-bungarotoxin. A toxin immobilized glass coverslip was subjected to nucleic acid pool binding and extensive washing followed by PCR enrichment of the selected aptamers. One round of selection successfully identified a DNA aptamer sequence with a binding affinity of 7.58 µM. CONCLUSION: We have demonstrated a one-step method for rapid production of nucleic acid aptamers. Although the reported binding affinity is in the low micromolar range, we believe that this could be further improved by using larger targets, increasing the stringency of selection and also by combining a capillary electrophoresis separation prior to the one-step selection. Furthermore, the method presented here is a user-friendly, cheap and an easy way of deriving an aptamer unlike the time consuming conventional SELEX-based approach. The most important application of this method is that chemically-modified nucleic acid libraries can also be used for aptamer selection as it requires only one enzymatic step. This method could equally be suitable for developing RNA aptamers.

Optimal Selection Method of Process Patents for Technology Transfer Using Fuzzy Linguistic Computing

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Gangfeng Wang

2014-01-01

Full Text Available Under the open innovation paradigm, technology transfer of process patents is one of the most important mechanisms for manufacturing companies to implement process innovation and enhance the competitive edge. To achieve promising technology transfers, we need to evaluate the feasibility of process patents and optimally select the most appropriate patent according to the actual manufacturing situation. Hence, this paper proposes an optimal selection method of process patents using multiple criteria decision-making and 2-tuple fuzzy linguistic computing to avoid information loss during the processes of evaluation integration. An evaluation index system for technology transfer feasibility of process patents is designed initially. Then, fuzzy linguistic computing approach is applied to aggregate the evaluations of criteria weights for each criterion and corresponding subcriteria. Furthermore, performance ratings for subcriteria and fuzzy aggregated ratings of criteria are calculated. Thus, we obtain the overall technology transfer feasibility of patent alternatives. Finally, a case study of aeroengine turbine manufacturing is presented to demonstrate the applicability of the proposed method.

Using multi-criteria decision methods for selecting a language school

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Mileine Henriques Elias Velasco

2014-11-01

Full Text Available Nowadays, the interest of organizations by professionals who have deep knowledge concerning more than one language has been increasing. In this scenario, the choice of a language school has been one of the most common decision problems, which has been often made on the basis of word-of-mouth, marketing activities of schools and trials without criteria. In order to contribute to this problem, this paper presents a study in which two multi-criteria decision aid methods (AHP and Weighted Average were used to select a language school. Thus, the degree of importance of criteria relating to the problem and the degree of satisfaction of undergraduate and postgraduate students in relation to language schools they study were taken into account. The best ranked language school was the same for both MCDA methods, although some schools have obtained different positions. It was found that the analysis with AHP is richer and more elaborate than with the Weighted Average method. However, the large number of pairwise comparisons which were required to the study demanded significant attention and cognitive effort from the decision maker, and more time to perform the analysis - aspects that may contribute to the preference for the Weighted Average method in similar studies.

Rapid determination method of radiocesium in sea water by cesium-selective resin

International Nuclear Information System (INIS)

Nakaoka, A.; Yokoyama, H.; Fukushima, M.; Takagi, S.

1980-01-01

A rapid and precise method of determining radiocesium corresponding to 5 mrem/y (the Japan AEC's guideline) was proposed. The development and practical performance of cesium-selective resin and the determination method are described in this paper. The resin was prepared by the formation of ammonium molybdophosphate in the structure of Amberlite XAD-7 resin. It took only 3 hours to carry out all the procedures the authors proposed. This value represents 1/10 to 1/2 of the time of the conventional method. The concentration of 137 Cs and 134 Cs in sea water was determined to be 0.13 to 0.16 pCi/l and less than 7.1x10 -2 pCi/l, respectively. (author)

Comparison of selected methods of prediction of wine exports and imports

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Radka Šperková

2008-01-01

Full Text Available For prediction of future events, there exist a number of methods usable in managerial practice. Decision on which of them should be used in a particular situation depends not only on the amount and quality of input information, but also on a subjective managerial judgement. Paper performs a practical application and consequent comparison of results of two selected methods, which are statistical method and deductive method. Both methods were used for predicting wine exports and imports in (from the Czech Republic. Prediction was done in 2003 and it related to the economic years 2003/2004, 2004/2005, 2005/2006, and 2006/2007, within which it was compared with the real values of the given indicators.Within the deductive methods there were characterized the most important factors of external environment including the most important influence according to authors’ opinion, which was the integration of the Czech Republic into the EU from 1st May, 2004. On the contrary, the statistical method of time-series analysis did not regard the integration, which is comes out of its principle. Statistics only calculates based on data from the past, and cannot incorporate the influence of irregular future conditions, just as the EU integration. Because of this the prediction based on deductive method was more optimistic and more precise in terms of its difference from real development in the given field.

THIRD PARTY LOGISTIC SERVICE PROVIDER SELECTION USING FUZZY AHP AND TOPSIS METHOD