Optimal design of a main driving mechanism for servo punch press based on performance atlases

NASA Astrophysics Data System (ADS)

Zhou, Yanhua; Xie, Fugui; Liu, Xinjun

2013-09-01

The servomotor drive turret punch press is attracting more attentions and being developed more intensively due to the advantages of high speed, high accuracy, high flexibility, high productivity, low noise, cleaning and energy saving. To effectively improve the performance and lower the cost, it is necessary to develop new mechanisms and establish corresponding optimal design method with uniform performance indices. A new patented main driving mechanism and a new optimal design method are proposed. In the optimal design, the performance indices, i.e., the local motion/force transmission indices ITI, OTI, good transmission workspace good transmission workspace(GTW) and the global transmission indices GTIs are defined. The non-dimensional normalization method is used to get all feasible solutions in dimensional synthesis. Thereafter, the performance atlases, which can present all possible design solutions, are depicted. As a result, the feasible solution of the mechanism with good motion/force transmission performance is obtained. And the solution can be flexibly adjusted by designer according to the practical design requirements. The proposed mechanism is original, and the presented design method provides a feasible solution to the optimal design of the main driving mechanism for servo punch press.

Extraction of memory colors for preferred color correction in digital TVs

NASA Astrophysics Data System (ADS)

Ryu, Byong Tae; Yeom, Jee Young; Kim, Choon-Woo; Ahn, Ji-Young; Kang, Dong-Woo; Shin, Hyun-Ho

2009-01-01

Subjective image quality is one of the most important performance indicators for digital TVs. In order to improve subjective image quality, preferred color correction is often employed. More specifically, areas of memory colors such as skin, grass, and sky are modified to generate pleasing impression to viewers. Before applying the preferred color correction, tendency of preference for memory colors should be identified. It is often accomplished by off-line human visual tests. Areas containing the memory colors should be extracted then color correction is applied to the extracted areas. These processes should be performed on-line. This paper presents a new method for area extraction of three types of memory colors. Performance of the proposed method is evaluated by calculating the correct and false detection ratios. Experimental results indicate that proposed method outperform previous methods proposed for the memory color extraction.

Using project performance to measure effectiveness of quality management system maintenance and practices in construction industry.

PubMed

Leong, Tiong Kung; Zakuan, Norhayati; Mat Saman, Muhamad Zameri; Ariff, Mohd Shoki Md; Tan, Choy Soon

2014-01-01

This paper proposed seven existing and new performance indicators to measure the effectiveness of quality management system (QMS) maintenance and practices in construction industry. This research is carried out with a questionnaire based on QMS variables which are extracted from literature review and project performance indicators which are established from project management's theory. Data collected was analyzed using correlation and regression analysis. The findings indicate that client satisfaction and time variance have positive and significant relationship with QMS while other project performance indicators do not show significant results. Further studies can use the same project performance indicators to study the effectiveness of QMS in different sampling area to improve the generalizability of the findings.

Using Project Performance to Measure Effectiveness of Quality Management System Maintenance and Practices in Construction Industry

PubMed Central

Leong, Tiong Kung; Ariff, Mohd. Shoki Md.

2014-01-01

This paper proposed seven existing and new performance indicators to measure the effectiveness of quality management system (QMS) maintenance and practices in construction industry. This research is carried out with a questionnaire based on QMS variables which are extracted from literature review and project performance indicators which are established from project management's theory. Data collected was analyzed using correlation and regression analysis. The findings indicate that client satisfaction and time variance have positive and significant relationship with QMS while other project performance indicators do not show significant results. Further studies can use the same project performance indicators to study the effectiveness of QMS in different sampling area to improve the generalizability of the findings. PMID:24701182

Use of social media in health promotion: purposes, key performance indicators, and evaluation metrics.

PubMed

Neiger, Brad L; Thackeray, Rosemary; Van Wagenen, Sarah A; Hanson, Carl L; West, Joshua H; Barnes, Michael D; Fagen, Michael C

2012-03-01

Despite the expanding use of social media, little has been published about its appropriate role in health promotion, and even less has been written about evaluation. The purpose of this article is threefold: (a) outline purposes for social media in health promotion, (b) identify potential key performance indicators associated with these purposes, and (c) propose evaluation metrics for social media related to the key performance indicators. Process evaluation is presented in this article as an overarching evaluation strategy for social media.

Similarity indices based on link weight assignment for link prediction of unweighted complex networks

NASA Astrophysics Data System (ADS)

Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

2017-01-01

Many link prediction methods have been proposed for predicting the likelihood that a link exists between two nodes in complex networks. Among these methods, similarity indices are receiving close attention. Most similarity-based methods assume that the contribution of links with different topological structures is the same in the similarity calculations. This paper proposes a local weighted method, which weights the strength of connection between each pair of nodes. Based on the local weighted method, six local weighted similarity indices extended from unweighted similarity indices (including Common Neighbor (CN), Adamic-Adar (AA), Resource Allocation (RA), Salton, Jaccard and Local Path (LP) index) are proposed. Empirical study has shown that the local weighted method can significantly improve the prediction accuracy of these unweighted similarity indices and that in sparse and weakly clustered networks, the indices perform even better.

Simulation modelling of central order processing system under resource sharing strategy in demand-driven garment supply chains

NASA Astrophysics Data System (ADS)

Ma, K.; Thomassey, S.; Zeng, X.

2017-10-01

In this paper we proposed a central order processing system under resource sharing strategy for demand-driven garment supply chains to increase supply chain performances. We examined this system by using simulation technology. Simulation results showed that significant improvement in various performance indicators was obtained in new collaborative model with proposed system.

A conceptual framework for evaluation of public health and primary care system performance in iran.

PubMed

Jahanmehr, Nader; Rashidian, Arash; Khosravi, Ardeshir; Farzadfar, Farshad; Shariati, Mohammad; Majdzadeh, Reza; Akbari Sari, Ali; Mesdaghinia, Alireza

2015-01-26

The main objective of this study was to design a conceptual framework, according to the policies and priorities of the ministry of health to evaluate provincial public health and primary care performance and to assess their share in the overall health impacts of the community. We used several tools and techniques, including system thinking, literature review to identify relevant attributes of health system performance framework and interview with the key stakeholders. The PubMed, Scopus, web of science, Google Scholar and two specialized databases of Persian language literature (IranMedex and SID) were searched using main terms and keywords. Following decision-making and collective agreement among the different stakeholders, 51 core indicators were chosen from among 602 obtained indicators in a four stage process, for monitoring and evaluation of Health Deputies. We proposed a conceptual framework by identifying the performance area for Health Deputies between other determinants of health, as well as introducing a chain of results, for performance, consisting of Input, Process, Output and Outcome indicators. We also proposed 5 dimensions for measuring the performance of Health Deputies, consisting of efficiency, effectiveness, equity, access and improvement of health status. The proposed Conceptual Framework illustrates clearly the Health Deputies success in achieving best results and consequences of health in the country. Having the relative commitment of the ministry of health and Health Deputies at the University of Medical Sciences is essential for full implementation of this framework and providing the annual performance report.

The Efficacy of Key Performance Indicators in Ontario Universities as Perceived by Key Informants

ERIC Educational Resources Information Center

Chan, Vivian

2015-01-01

The Ontario Ministry of Education and Training's Task Force on University Accountability first proposed key performance indicators (KPIs) for colleges and universities in Ontario in the early 1990s. The three main KPIs for Ontario universities are the rates of (1) graduation, (2) employment, and (3) Ontario Student Assistance Program loan default.…

Indicators in Perspective. The Use of Quality Indicators in Vocational Education and Training. CEDEFOP Document.

ERIC Educational Resources Information Center

Van den Berghe, Wouter

Indicators are used in quite different ways in vocational education and training, from control and accountability to performance and quality purposes. A classification model has been proposed in which many indicators can fit. It is based on two important dimensions of indicators: (1) the "message" relating to the information content,…

SELECTING INDICATORS OF BIODIVERSITY FOR CONSERVATION PLANNING: IDENTIFYING THE MECHANISMS BEHIND INDICATOR GROUP PERFORMANCE

EPA Science Inventory

Most conservation planning is constrained by time and funding. In particular, the selection of areas to protect biodiversity must often be completed with limited data on species distributions. Consequently, different groups of species have been proposed as indicators or surroga...

20 CFR 669.520 - What information is required in the NFJP grant plans?

Code of Federal Regulations, 2010 CFR

2010-04-01

..., DEPARTMENT OF LABOR NATIONAL FARMWORKER JOBS PROGRAM UNDER TITLE I OF THE WORKFORCE INVESTMENT ACT Performance Accountability, Planning and Waiver Provision § 669.520 What information is required in the NFJP... performance indicators and proposed levels of performance used to assess the performance of such entity...

Extended resource allocation index for link prediction of complex network

NASA Astrophysics Data System (ADS)

Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

2017-08-01

Recently, a number of similarity-based methods have been proposed to predict the missing links in complex network. Among these indices, the resource allocation index performs very well with lower time complexity. However, it ignores potential resources transferred by local paths between two endpoints. Motivated by the resource exchange taking places between endpoints, an extended resource allocation index is proposed. Empirical study on twelve real networks and three synthetic dynamic networks has shown that the index we proposed can achieve a good performance, compared with eight mainstream baselines.

A Conceptual Framework for Evaluation of Public Health and Primary Care System Performance in Iran

PubMed Central

Jahanmehr, Nader; Rashidian, Arash; Khosravi, Ardeshir; Farzadfar, Farshad; Shariati, Mohammad; Majdzadeh, Reza; Sari, Ali Akbari; Mesdaghinia, Alireza

2015-01-01

Introduction: The main objective of this study was to design a conceptual framework, according to the policies and priorities of the ministry of health to evaluate provincial public health and primary care performance and to assess their share in the overall health impacts of the community. Methods: We used several tools and techniques, including system thinking, literature review to identify relevant attributes of health system performance framework and interview with the key stakeholders. The PubMed, Scopus, web of science, Google Scholar and two specialized databases of Persian language literature (IranMedex and SID) were searched using main terms and keywords. Following decision-making and collective agreement among the different stakeholders, 51 core indicators were chosen from among 602 obtained indicators in a four stage process, for monitoring and evaluation of Health Deputies. Results: We proposed a conceptual framework by identifying the performance area for Health Deputies between other determinants of health, as well as introducing a chain of results, for performance, consisting of Input, Process, Output and Outcome indicators. We also proposed 5 dimensions for measuring the performance of Health Deputies, consisting of efficiency, effectiveness, equity, access and improvement of health status. Conclusion: The proposed Conceptual Framework illustrates clearly the Health Deputies success in achieving best results and consequences of health in the country. Having the relative commitment of the ministry of health and Health Deputies at the University of Medical Sciences is essential for full implementation of this framework and providing the annual performance report. PMID:25946937

ConceFT for Time-Varying Heart Rate Variability Analysis as a Measure of Noxious Stimulation During General Anesthesia.

PubMed

Lin, Yu-Ting; Wu, Hau-Tieng

2017-01-01

Heart rate variability (HRV) offers a noninvasive way to peek into the physiological status of the human body. When this physiological status is dynamic, traditional HRV indices calculated from power spectrum do not resolve the dynamic situation due to the issue of nonstationarity. Clinical anesthesia is a typically dynamic situation that calls for time-varying HRV analysis. Concentration of frequency and time (ConceFT) is a nonlinear time-frequency (TF) analysis generalizing the multitaper technique and the synchrosqueezing transform. The result is a sharp TF representation capturing the dynamics inside HRV. Companion indices of the commonly applied HRV indices, including time-varying low-frequency power (tvLF), time-varying high-frequency power, and time-varying low-high ratio, are considered as measures of noxious stimulation. To evaluate the feasibility of the proposed indices, we apply these indices to study two different types of noxious stimulation, the endotracheal intubation and surgical skin incision, under general anesthesia. The performance was compared with traditional HRV indices, the heart rate reading, and indices from electroencephalography. The results indicate that the tvLF index performs best and outperforms not only the traditional HRV index, but also the commonly used heart rate reading. With the help of ConceFT, the proposed HRV indices are potential to provide a better quantification of the dynamic change of the autonomic nerve system. Our proposed scheme of time-varying HRV analysis could contribute to the clinical assessment of analgesia under general anesthesia.

A robust probabilistic collaborative representation based classification for multimodal biometrics

NASA Astrophysics Data System (ADS)

Zhang, Jing; Liu, Huanxi; Ding, Derui; Xiao, Jianli

2018-04-01

Most of the traditional biometric recognition systems perform recognition with a single biometric indicator. These systems have suffered noisy data, interclass variations, unacceptable error rates, forged identity, and so on. Due to these inherent problems, it is not valid that many researchers attempt to enhance the performance of unimodal biometric systems with single features. Thus, multimodal biometrics is investigated to reduce some of these defects. This paper proposes a new multimodal biometric recognition approach by fused faces and fingerprints. For more recognizable features, the proposed method extracts block local binary pattern features for all modalities, and then combines them into a single framework. For better classification, it employs the robust probabilistic collaborative representation based classifier to recognize individuals. Experimental results indicate that the proposed method has improved the recognition accuracy compared to the unimodal biometrics.

The robust model predictive control based on mixed H2/H∞ approach with separated performance formulations and its ISpS analysis

NASA Astrophysics Data System (ADS)

Li, Dewei; Li, Jiwei; Xi, Yugeng; Gao, Furong

2017-12-01

In practical applications, systems are always influenced by parameter uncertainties and external disturbance. Both the H2 performance and the H∞ performance are important for the real applications. For a constrained system, the previous designs of mixed H2/H∞ robust model predictive control (RMPC) optimise one performance with the other performance requirement as a constraint. But the two performances cannot be optimised at the same time. In this paper, an improved design of mixed H2/H∞ RMPC for polytopic uncertain systems with external disturbances is proposed to optimise them simultaneously. In the proposed design, the original uncertain system is decomposed into two subsystems by the additive character of linear systems. Two different Lyapunov functions are used to separately formulate the two performance indices for the two subsystems. Then, the proposed RMPC is designed to optimise both the two performances by the weighting method with the satisfaction of the H∞ performance requirement. Meanwhile, to make the design more practical, a simplified design is also developed. The recursive feasible conditions of the proposed RMPC are discussed and the closed-loop input state practical stable is proven. The numerical examples reflect the enlarged feasible region and the improved performance of the proposed design.

Use of comparative performance indicators in rehabilitation.

PubMed

Zidarov, Diana; Poissant, Lise; Sicotte, Claude

The development of performance indicators that enable benchmarking between organizations is an important mechanism for accountability, organizational learning, and performance improvement. In the province of Quebec (Canada), 21 rehabilitation organizations developed a common set of performance indicators through interorganizational collaboration. The aims of this study were to describe the rehabilitation organizations' use of a common set of performance indicators and to identify the factors influencing such use. A qualitative survey was performed. Individual semistructured interviews were conducted with executives (n = 18) working at 16 rehabilitation organizations using a common set of performance indicators. A thematic analysis of the factors of use was performed according to the Consolidated Framework for Implementation Research. The use of performance indicators was categorized as purposeful, political, or passive. Our results showed that all organizations used the common set of performance indicators. Four factors were identified as important to all the rehabilitation organizations to explain their interest in comparative performance indicators: the need to develop their own performance indicators, the compatibility of performance information with organizational needs, complexity/simplicity of performance information, and the support offered by their common association. Sixty-three percent of rehabilitation organizations made purposeful or political use of performance indicators. Three main factors contributed to typify those organizations from the others: the perceived quality of the performance indicators, the leadership of decision makers, and the resources available. Our results showed that use of performance indicators can support the initiation of projects for improving the quality of care. Key recommendations are proposed to decision makers that may enhance performance indicators' use.

Review of Cuttability Indices and A New Rockmass Classification Approach for Selection of Surface Miners

NASA Astrophysics Data System (ADS)

Dey, Kaushik; Ghose, A. K.

2011-09-01

Rock excavation is carried out either by drilling and blasting or using rock-cutting machines like rippers, bucket wheel excavators, surface miners, road headers etc. Economics of mechanised rock excavation by rock-cutting machines largely depends on the achieved production rates. Thus, assessment of the performance (productivity) is important prior to deploying a rock-cutting machine. In doing so, several researchers have classified rockmass in different ways and have developed cuttability indices to correlate machine performance directly. However, most of these indices were developed to assess the performance of road headers/tunnel-boring machines apart from a few that were developed in the earlier days when the ripper was a popular excavating equipment. Presently, around 400 surface miners are in operation around the world amongst which, 105 are in India. Until now, no rockmass classification system is available to assess the performance of surface miners. Surface miners are being deployed largely on trial and error basis or based on the performance charts provided by the manufacturer. In this context, it is logical to establish a suitable cuttability index to predict the performance of surface miners. In this present paper, the existing cuttability indices are reviewed and a new cuttability indexes proposed. A new relationship is also developed to predict the output from surface miners using the proposed cuttability index.

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling.

PubMed

Sefuba, Maria; Walingo, Tom; Takawira, Fambirai

2015-09-18

This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols.

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling

PubMed Central

Sefuba, Maria; Walingo, Tom; Takawira, Fambirai

2015-01-01

This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols. PMID:26393608

Using key performance indicators as knowledge-management tools at a regional health-care authority level.

PubMed

Berler, Alexander; Pavlopoulos, Sotiris; Koutsouris, Dimitris

2005-06-01

The advantages of the introduction of information and communication technologies in the complex health-care sector are already well-known and well-stated in the past. It is, nevertheless, paradoxical that although the medical community has embraced with satisfaction most of the technological discoveries allowing the improvement in patient care, this has not happened when talking about health-care informatics. Taking the above issue of concern, our work proposes an information model for knowledge management (KM) based upon the use of key performance indicators (KPIs) in health-care systems. Based upon the use of the balanced scorecard (BSC) framework (Kaplan/Norton) and quality assurance techniques in health care (Donabedian), this paper is proposing a patient journey centered approach that drives information flow at all levels of the day-to-day process of delivering effective and managed care, toward information assessment and knowledge discovery. In order to persuade health-care decision-makers to assess the added value of KM tools, those should be used to propose new performance measurement and performance management techniques at all levels of a health-care system. The proposed KPIs are forming a complete set of metrics that enable the performance management of a regional health-care system. In addition, the performance framework established is technically applied by the use of state-of-the-art KM tools such as data warehouses and business intelligence information systems. In that sense, the proposed infrastructure is, technologically speaking, an important KM tool that enables knowledge sharing amongst various health-care stakeholders and between different health-care groups. The use of BSC is an enabling framework toward a KM strategy in health care.

Financial Time Series Prediction Using Elman Recurrent Random Neural Networks

PubMed Central

Wang, Jie; Wang, Jun; Fang, Wen; Niu, Hongli

2016-01-01

In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective function. By analyzing the proposed model with the linear regression, complexity invariant distance (CID), and multiscale CID (MCID) analysis methods and taking the model compared with different models such as the backpropagation neural network (BPNN), the stochastic time effective neural network (STNN), and the Elman recurrent neural network (ERNN), the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices. PMID:27293423

Financial Time Series Prediction Using Elman Recurrent Random Neural Networks.

PubMed

Wang, Jie; Wang, Jun; Fang, Wen; Niu, Hongli

2016-01-01

In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective function. By analyzing the proposed model with the linear regression, complexity invariant distance (CID), and multiscale CID (MCID) analysis methods and taking the model compared with different models such as the backpropagation neural network (BPNN), the stochastic time effective neural network (STNN), and the Elman recurrent neural network (ERNN), the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices.

Proposed design class of grazing incidence echelle spectrometers - Critical analysis and reevaluation

NASA Technical Reports Server (NTRS)

Hettrick, M. C.; Jelinsky, P.; Bowyer, S.; Malina, R. F.

1984-01-01

The class of miltibounce grazing spectrometers proposed by Cash (1982) and by McClintock and Cash (1982) is analyzed, and performance values significantly lower than asserted by these authors are found. Ray tracing calculations used to examine the design parameters given in the above papers are reported, as is the efficiency which results from use of accepted reflectance data. Several schemes which can improve some of the performance parameters are indicated.

Lean Information Management: Criteria For Selecting Key Performance Indicators At Shop Floor

NASA Astrophysics Data System (ADS)

Iuga, Maria Virginia; Kifor, Claudiu Vasile; Rosca, Liviu-Ion

2015-07-01

Most successful organizations worldwide use key performance indicators as an important part of their corporate strategy in order to forecast, measure and plan their businesses. Performance metrics vary in their purpose, definition and content. Therefore, the way organizations select what they think are the optimal indicators for their businesses varies from company to company, sometimes even from department to department. This study aims to answer the question of what is the most suitable way to define and select key performance indicators. More than that, it identifies the right criteria to select key performance indicators at shop floor level. This paper contributes to prior research by analysing and comparing previously researched selection criteria and proposes an original six-criteria-model, which caters towards choosing the most adequate KPIs. Furthermore, the authors take the research a step further by further steps to closed research gaps within this field of study.

LDPC-based iterative joint source-channel decoding for JPEG2000.

PubMed

Pu, Lingling; Wu, Zhenyu; Bilgin, Ali; Marcellin, Michael W; Vasic, Bane

2007-02-01

A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.

Data warehouse model for monitoring key performance indicators (KPIs) using goal oriented approach

NASA Astrophysics Data System (ADS)

Abdullah, Mohammed Thajeel; Ta'a, Azman; Bakar, Muhamad Shahbani Abu

2016-08-01

The growth and development of universities, just as other organizations, depend on their abilities to strategically plan and implement development blueprints which are in line with their vision and mission statements. The actualizations of these statements, which are often designed into goals and sub-goals and linked to their respective actors are better measured by defining key performance indicators (KPIs) of the university. The proposes ReGADaK, which is an extended the GRAnD approach highlights the facts, dimensions, attributes, measures and KPIs of the organization. The measures from the goal analysis of this unit serve as the basis of developing the related university's KPIs. The proposed data warehouse schema is evaluated through expert review, prototyping and usability evaluation. The findings from the evaluation processes suggest that the proposed data warehouse schema is suitable for monitoring the University's KPIs.

Organizational culture and organizational effectiveness: a meta-analytic investigation of the competing values framework's theoretical suppositions.

PubMed

Hartnell, Chad A; Ou, Amy Yi; Kinicki, Angelo

2011-07-01

We apply Quinn and Rohrbaugh's (1983) competing values framework (CVF) as an organizing taxonomy to meta-analytically test hypotheses about the relationship between 3 culture types and 3 major indices of organizational effectiveness (employee attitudes, operational performance [i.e., innovation and product and service quality], and financial performance). The paper also tests theoretical suppositions undergirding the CVF by investigating the framework's nomological validity and proposed internal structure (i.e., interrelationships among culture types). Results based on data from 84 empirical studies with 94 independent samples indicate that clan, adhocracy, and market cultures are differentially and positively associated with the effectiveness criteria, though not always as hypothesized. The findings provide mixed support for the CVF's nomological validity and fail to support aspects of the CVF's proposed internal structure. We propose an alternative theoretical approach to the CVF and delineate directions for future research.

Justification of Drug Product Dissolution Rate and Drug Substance Particle Size Specifications Based on Absorption PBPK Modeling for Lesinurad Immediate Release Tablets.

PubMed

Pepin, Xavier J H; Flanagan, Talia R; Holt, David J; Eidelman, Anna; Treacy, Don; Rowlings, Colin E

2016-09-06

In silico absorption modeling has been performed, to assess the impact of in vitro dissolution on in vivo performance for ZURAMPIC (lesinurad) tablets. The dissolution profiles of lesinurad tablets generated using the quality control method were used as an input to a GastroPlus model to estimate in vivo dissolution in the various parts of the GI tract and predict human exposure. A model was set up, which accounts for differences of dosage form transit, dissolution, local pH in the GI tract, and fluid volumes available for dissolution. The predictive ability of the model was demonstrated by confirming that it can reproduce the Cmax observed for independent clinical trial. The model also indicated that drug product batches that pass the proposed dissolution specification of Q = 80% in 30 min are anticipated to be bioequivalent to the clinical reference batch. To further explore the dissolution space, additional simulations were performed using a theoretical dissolution profile below the proposed specification. The GastroPlus modeling indicates that such a batch will also be bioequivalent to standard clinical batches despite having a dissolution profile, which would fail the proposed dissolution specification of Q = 80% in 30 min. This demonstrates that the proposed dissolution specification sits comfortably within a region of dissolution performance where bioequivalence is anticipated and is not near an edge of failure for dissolution, providing additional confidence to the proposed specifications. Finally, simulations were performed using a virtual drug substance batch with a particle size distribution at the limit of the proposed specification for particle size. Based on these simulations, such a batch is also anticipated to be bioequivalent to clinical reference, demonstrating that the proposed specification limits for particle size distribution would give products bioequivalent to the pivotal clinical batches.

Reviewers’ Ratings and Bibliometric Indicators: Hand in Hand When Assessing Over Research Proposals?

PubMed Central

Cabezas-Clavijo, Álvaro; Robinson-García, Nicolás; Escabias, Manuel; Jiménez-Contreras, Evaristo

2013-01-01

Background The peer review system has been traditionally challenged due to its many limitations especially for allocating funding. Bibliometric indicators may well present themselves as a complement. Objective We analyze the relationship between peers’ ratings and bibliometric indicators for Spanish researchers in the 2007 National R&D Plan for 23 research fields. Methods and Materials We analyze peers’ ratings for 2333 applications. We also gathered principal investigators’ research output and impact and studied the differences between accepted and rejected applications. We used the Web of Science database and focused on the 2002-2006 period. First, we analyzed the distribution of granted and rejected proposals considering a given set of bibliometric indicators to test if there are significant differences. Then, we applied a multiple logistic regression analysis to determine if bibliometric indicators can explain by themselves the concession of grant proposals. Results 63.4% of the applications were funded. Bibliometric indicators for accepted proposals showed a better previous performance than for those rejected; however the correlation between peer review and bibliometric indicators is very heterogeneous among most areas. The logistic regression analysis showed that the main bibliometric indicators that explain the granting of research proposals in most cases are the output (number of published articles) and the number of papers published in journals that belong to the first quartile ranking of the Journal Citations Report. Discussion Bibliometric indicators predict the concession of grant proposals at least as well as peer ratings. Social Sciences and Education are the only areas where no relation was found, although this may be due to the limitations of the Web of Science’s coverage. These findings encourage the use of bibliometric indicators as a complement to peer review in most of the analyzed areas. PMID:23840840

Measurement of sustainability index among paper manufacturing plants

NASA Astrophysics Data System (ADS)

Sharathkumar Reddy, V.; Jayakrishna, K.; Lal, Babu

2017-11-01

The paper manufacturing companies are facing challenges to implement sustainable manufacturing into their products and processes. Paper manufacturing has remarked as an intensive consumer of natural raw materials, energy and a major source of multiple pollutants. Thus, evaluating the sustainable manufacturing in these companies has become a necessity. This paper proposes a set of Performance Indicators (PIs) for evaluating the sustainable manufacturing appropriate to the paper manufacturing companies based on the triple bottom line of sustainability. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision analysis method is applied to prioritize the performance indicators by summarizing the opinions of stakeholders. It is hoped that the proposed PIs enables and assists the paper manufacturing companies to achieve the higher performance in sustainable manufacturing and so as to increase their competitiveness.

Bayesian SEM for Specification Search Problems in Testing Factorial Invariance.

PubMed

Shi, Dexin; Song, Hairong; Liao, Xiaolan; Terry, Robert; Snyder, Lori A

2017-01-01

Specification search problems refer to two important but under-addressed issues in testing for factorial invariance: how to select proper reference indicators and how to locate specific non-invariant parameters. In this study, we propose a two-step procedure to solve these issues. Step 1 is to identify a proper reference indicator using the Bayesian structural equation modeling approach. An item is selected if it is associated with the highest likelihood to be invariant across groups. Step 2 is to locate specific non-invariant parameters, given that a proper reference indicator has already been selected in Step 1. A series of simulation analyses show that the proposed method performs well under a variety of data conditions, and optimal performance is observed under conditions of large magnitude of non-invariance, low proportion of non-invariance, and large sample sizes. We also provide an empirical example to demonstrate the specific procedures to implement the proposed method in applied research. The importance and influences are discussed regarding the choices of informative priors with zero mean and small variances. Extensions and limitations are also pointed out.

Output-Based Structural Damage Detection by Using Correlation Analysis Together with Transmissibility

PubMed Central

Cao, Hongyou; Liu, Quanmin; Wahab, Magd Abdel

2017-01-01

Output-based structural damage detection is becoming increasingly appealing due to its potential in real engineering applications without any restriction regarding excitation measurements. A new transmissibility-based damage detection approach is presented in this study by combining transmissibility with correlation analysis in order to strengthen its performance in discriminating damaged from undamaged scenarios. From this perspective, damage detection strategies are hereafter established by constructing damage-sensitive indicators from a derived transmissibility. A cantilever beam is numerically analyzed to verify the feasibility of the proposed damage detection procedure, and an ASCE (American Society of Civil Engineers) benchmark is henceforth used in the validation for its application in engineering structures. The results of both studies reveal a good performance of the proposed methodology in identifying damaged states from intact states. The comparison between the proposed indicator and the existing indicator also affirms its applicability in damage detection, which might be adopted in further structural health monitoring systems as a discrimination criterion. This study contributed an alternative criterion for transmissibility-based damage detection in addition to the conventional ones. PMID:28773218

Development of an Integrated Performance Measurement (PM) Model for Pharmaceutical Industry

PubMed Central

Shabaninejad, Hosein; Mirsalehian, Mohammad Hossein; Mehralian, Gholamhossein

2014-01-01

With respect to special characteristics of pharmaceutical industry and lack of reported performance measure, this study tries to design an integrated PM model for pharmaceutical companies. For generating this model; we first identified the key performance indicators (KPIs) and the key result indicators (KRIs) of a typical pharmaceutical company. Then, based on experts᾽ opinions, the identified indicators were ranked with respect to their importance, and the most important of them were selected to be used in the proposed model; In this model, we identified 25 KPIs and 12 KRIs. Although, this model is mostly appropriate to measure the performances of pharmaceutical companies, it can be also used to measure the performances of other industries with some modifications. We strongly recommend pharmaceutical managers to link these indicators with their payment and reward system, which can dramatically affect the performance of employees, and consequently their organization`s success. PMID:24711848

Formalizing Evaluation Procedures for Marketing Faculty Research Performance.

ERIC Educational Resources Information Center

McDermott, Dennis R.; And Others

1994-01-01

Results of a national survey of marketing department heads (n=142) indicate that few marketing departments have formalized the development and communication of research performance standards to faculty. Guidelines and methods to accomplish those procedures most efficiently were proposed. (Author/JOW)

Measuring Value Added in Higher Education: A Proposed Methodology for Developing a Performance Indicator Based on the Economic Value Added to Graduates

ERIC Educational Resources Information Center

Rodgers, Timothy

2007-01-01

The 2003 UK higher education White Paper suggested that the sector needed to re-examine the potential of the value added concept. This paper describes a possible methodology for developing a performance indicator based on the economic value added to graduates. The paper examines how an entry-quality-adjusted measure of a graduate's…

Glycemic Control Indices and Their Aggregation in the Prediction of Nocturnal Hypoglycemia From Intermittent Blood Glucose Measurements.

PubMed

Sampath, Sivananthan; Tkachenko, Pavlo; Renard, Eric; Pereverzev, Sergei V

2016-11-01

Despite the risk associated with nocturnal hypoglycemia (NH) there are only a few methods aiming at the prediction of such events based on intermittent blood glucose monitoring data. One of the first methods that potentially can be used for NH prediction is based on the low blood glucose index (LBGI) and suggested, for example, in Accu-Chek® Connect as a hypoglycemia risk indicator. On the other hand, nowadays there are other glucose control indices (GCI), which could be used for NH prediction in the same spirit as LBGI. In the present study we propose a general approach of combining NH predictors constructed from different GCI. The approach is based on a recently developed strategy for aggregating ranking algorithms in machine learning. NH predictors have been calibrated and tested on data extracted from clinical trials, performed in EU FP7-funded project DIAdvisor. Then, to show a portability of the method we have tested it on another dataset that was received from EU Horizon 2020-funded project AMMODIT. We exemplify the proposed approach by aggregating NH predictors that have been constructed based on 4 GCI associated with hypoglycemia. Even though these predictors have been preliminary optimized to exhibit better performance on the considered dataset, our aggregation approach allows a further performance improvement. On the dataset, where a portability of the proposed approach has been demonstrated, the aggregating predictor has exhibited the following performance: sensitivity 77%, specificity 83.4%, positive predictive value 80.2%, negative predictive value 80.6%, which is higher than conventionally considered as acceptable. The proposed approach shows potential to be used in telemedicine systems for NH prediction. © 2016 Diabetes Technology Society.

Instrumental Landing Using Audio Indication

NASA Astrophysics Data System (ADS)

Burlak, E. A.; Nabatchikov, A. M.; Korsun, O. N.

2018-02-01

The paper proposes an audio indication method for presenting to a pilot the information regarding the relative positions of an aircraft in the tasks of precision piloting. The implementation of the method is presented, the use of such parameters of audio signal as loudness, frequency and modulation are discussed. To confirm the operability of the audio indication channel the experiments using modern aircraft simulation facility were carried out. The simulated performed the instrument landing using the proposed audio method to indicate the aircraft deviations in relation to the slide path. The results proved compatible with the simulated instrumental landings using the traditional glidescope pointers. It inspires to develop the method in order to solve other precision piloting tasks.

A new composite measure of colonoscopy: the Performance Indicator of Colonic Intubation (PICI).

PubMed

Valori, Roland M; Damery, Sarah; Gavin, Daniel R; Anderson, John T; Donnelly, Mark T; Williams, J Graham; Swarbrick, Edwin T

2018-01-01

 Cecal intubation rate (CIR) is an established performance indicator of colonoscopy. In some patients, cecal intubation with acceptable tolerance is only achieved with additional sedation. This study proposes a composite Performance Indicator of Colonic Intubation (PICI), which combines CIR, comfort, and sedation. METHODS : Data from 20 085 colonoscopies reported in the 2011 UK national audit were analyzed. PICI was defined as the percentage of procedures achieving cecal intubation with median dose (2 mg) of midazolam or less, and nurse-assessed comfort score of 1 - 3/5. Multivariate logistic regression analysis evaluated possible associations between PICI and patient, unit, colonoscopist, and diagnostic factors. RESULTS : PICI was achieved in 54.1 % of procedures. PICI identified factors affecting performance more frequently than single measures such as CIR and polyp detection, or CIR + comfort alone. Older age, male sex, adequate bowel preparation, and a positive fecal occult blood test as indication were associated with a higher PICI. Unit accreditation, the presence of magnetic imagers in the unit, greater annual volume, fewer years' experience, and higher training/trainer status were associated with higher PICI rates. Procedures in which PICI was achieved were associated with significantly higher polyp detection rates than when PICI was not achieved. CONCLUSIONS : PICI provides a simpler picture of performance of colonoscopic intubation than separate measures of CIR, comfort, and sedation. It is associated with more factors that are amenable to change that might improve performance and with higher likelihood of polyp detection. It is proposed that PICI becomes the key performance indicator for intubation of the colon in colonoscopy quality improvement initiatives. © Georg Thieme Verlag KG Stuttgart · New York.

Application of gain scheduling to the control of batch bioreactors

NASA Technical Reports Server (NTRS)

Cardello, Ralph; San, Ka-Yiu

1987-01-01

The implementation of control algorithms to batch bioreactors is often complicated by the inherent variations in process dynamics during the course of fermentation. Such a wide operating range may render the performance of fixed gain PID controllers unsatisfactory. In this work, a detailed study on the control of batch fermentation is performed. Furthermore, a simple batch controller design is proposed which incorporates the concept of gain-scheduling, a subclass of adaptive control, with oxygen uptake rate as an auxiliary variable. The control of oxygen tension in the biorector is used as a vehicle to convey the proposed idea, analysis and results. Simulation experiments indicate significant improvement in controller performance can be achieved by the proposed approach even in the presence of measurement noise.

Combined Vision and Wearable Sensors-based System for Movement Analysis in Rehabilitation.

PubMed

Spasojević, Sofija; Ilić, Tihomir V; Milanović, Slađan; Potkonjak, Veljko; Rodić, Aleksandar; Santos-Victor, José

2017-03-23

Traditional rehabilitation sessions are often a slow, tedious, disempowering and non-motivational process, supported by clinical assessment tools, i.e. evaluation scales that are prone to subjective rating and imprecise interpretation of patient's performance. Poor patient motivation and insufficient accuracy are thus critical factors that can be improved by new sensing / processing technologies. We aim to develop a portable and affordable system, suitable for home rehabilitation, which combines vision-based and wearable sensors. We introduce a novel approach for examining and characterizing the rehabilitation movements, using quantitative descriptors. We propose new Movement Performance Indicators (MPIs) that are extracted directly from sensor data and quantify the symmetry, velocity, and acceleration of the movement of different body/hand parts, and that can potentially be used by therapists for diagnosis and progress assessment. First, a set of rehabilitation exercises is defined, with the supervision of neurologists and therapists for the specific case of Parkinson's disease. It comprises full-body movements measured with a Kinect device and fine hand movements, acquired with a data glove. Then, the sensor data is used to compute 25 Movement Performance Indicators, to assist the diagnosis and progress monitoring (assessing the disease stage) in Parkinson's disease. A kinematic hand model is developed for data verification and as an additional resource for extracting supplementary movement information. Our results show that the proposed Movement Performance Indicators are relevant for the Parkinson's disease assessment. This is further confirmed by correlation of the proposed indicators with clinical tapping test and UPDRS clinical scale. Classification results showed the potential of these indicators to discriminate between the patients and controls, as well as between the stages that characterize the evolution of the disease. The proposed sensor system, along with the developed approach for rehabilitation movement analysis have a significant potential to support and advance traditional rehabilitation therapy. The main impact of our work is two-fold: (i) the proposition of an approach for supporting the therapists during the diagnosis and monitoring evaluations by reducing subjectivity and imprecision, and (ii) offering the possibility of the system to be used at home for rehabilitation exercises in between sessions with doctors and therapists.

Design Tools to Assess Hydro-Turbine Biological Performance: Priest Rapids Dam Turbine Replacement Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Richmond, Marshall C.; Rakowski, Cynthia L.; Serkowski, John A.

2013-06-25

Over the past two decades, there have been many studies describing injury mechanisms associated with turbine passage, the response of various fish species to these mechanisms, and the probability of survival through dams. Although developing tools to design turbines that improve passage survival has been difficult and slow, a more robust quantification of the turbine environment has emerged through integrating physical model data, fish survival data, and computational fluid dynamics (CFD) studies. Grant County Public Utility District (GCPUD) operates the Priest Rapids Dam (PRD), a hydroelectric facility on the Columbia River in Washington State. The dam contains 10 Kaplan-type turbinemore » units that are now almost 50 years old. The Utility District plans to refit all of these aging turbines with new turbines. The Columbia River at PRD is a migratory pathway for several species of juvenile and adult salmonids, so passage of fish through the dam is a major consideration when replacing the turbines. In this presentation, a method for turbine biological performance assessment (BioPA) is introduced. Using this method, a suite of biological performance indicators is computed based on simulated data from a CFD model of a proposed turbine design. Each performance indicator is a measure of the probability of exposure to a certain dose of an injury mechanism. Using known relationships between the dose of an injury mechanism and frequency of injury (dose–response) from laboratory or field studies, the likelihood of fish injury for a turbine design can be computed from the performance indicator. By comparing the values of the indicators from proposed designs, the engineer can identify the more-promising alternatives. We will present application of the BioPA method for baseline risk assessment calculations for the existing Kaplan turbines at PRD that will be used as the minimum biological performance that a proposed new design must achieve.« less

Evaluating Performance Measurement Systems in Nonprofit Agencies: The Program Accountability Quality Scale (PAQS).

ERIC Educational Resources Information Center

Poole, Dennis L.; Nelson, Joan; Carnahan, Sharon; Chepenik, Nancy G.; Tubiak, Christine

2000-01-01

Developed and field tested the Performance Accountability Quality Scale (PAQS) on 191 program performance measurement systems developed by nonprofit agencies in central Florida. Preliminary findings indicate that the PAQS provides a structure for obtaining expert opinions based on a theory-driven model about the quality of proposed measurement…

Techno-economic performance indicators of municipal solid waste collection strategies.

PubMed

Bertanza, G; Ziliani, E; Menoni, L

2018-04-01

Several indicators for the evaluation of the MSW collection systems have been proposed in the literature. These evaluation tools consider only some of the aspects that influence the operational efficiency of the collection service. The aim of this paper is to suggest a set of (easy to calculate) indicators that overcomes this limitation, taking into account both the characteristics of collected waste and the operational - economic performance. The main components of the collection system (labour, vehicles and containers) are separately considered so that it is possible to quantify and compare their role within the whole process. As an example of application, the proposed approach was used for comparing the MSW collection strategies adopted in four towns in Northern Italy. Results are discussed and a comparison with alternative assessment methods available in the scientific literature is reported. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Breast cancer screening process indicators in Mexico: a case study].

PubMed

Uscanga-Sánchez, Santos; Torres-Mejía, Gabriela; Ángeles-Llerenas, Angélica; Domínguez-Malpica, Raúl; Lazcano-Ponce, Eduardo

2014-01-01

To identify, measure and compare the performance indicators of productivity, effective access and quality service for the early detection breast cancer program in Mexico. By means of a study case based on the 2011 Women Cancer Information System (SICAM), the indicators were measured and compared with the Mexican official standard NOM-041-SSA2-2011 and international standards. The analysis showed insufficient installed capacity (37%), low coverage in screening (15%), diagnostic evaluation (16%), biopsy (44%) and treatment (57%), and very low effectiveness in confirmed cases by the total number of screening mammograms performed (0.04%). There was no information available, from SICAM, to estimate the rest of the indicators proposed. Efficient health information systems are required in order to monitor indicators and generate performance observatories of screening programs.

A computerized method for automated identification of erect posteroanterior and supine anteroposterior chest radiographs

NASA Astrophysics Data System (ADS)

Kao, E.-Fong; Lin, Wei-Chen; Hsu, Jui-Sheng; Chou, Ming-Chung; Jaw, Twei-Shiun; Liu, Gin-Chung

2011-12-01

A computerized scheme was developed for automated identification of erect posteroanterior (PA) and supine anteroposterior (AP) chest radiographs. The method was based on three features, the tilt angle of the scapula superior border, the tilt angle of the clavicle and the extent of radiolucence in lung fields, to identify the view of a chest radiograph. The three indices Ascapula, Aclavicle and Clung were determined from a chest image for the three features. Linear discriminant analysis was used to classify PA and AP chest images based on the three indices. The performance of the method was evaluated by receiver operating characteristic analysis. The proposed method was evaluated using a database of 600 PA and 600 AP chest radiographs. The discriminant performances Az of Ascapula, Aclavicle and Clung were 0.878 ± 0.010, 0.683 ± 0.015 and 0.962 ± 0.006, respectively. The combination of the three indices obtained an Az value of 0.979 ± 0.004. The results indicate that the combination of the three indices could yield high discriminant performance. The proposed method could provide radiologists with information about the view of chest radiographs for interpretation or could be used as a preprocessing step for analyzing chest images.

Environmental Assessment: Proposed Training Facilities, Hill Air Force Base, Utah

DTIC Science & Technology

2013-08-08

FA8201-09-D-0002 Facilities, Hill Air Force Base, Utah 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Klein, Randal 5d...PERFORMING ORGANIZATION REPORT NUMBER Streamline Consulting, LLC 1713 N. Sweetwater Lane Farmington, Utah 84025...proposes to construct new training facilities at Hill Air Force Base, Utah . The findings of this EA indicate that the proposed action would not have

Thermodynamic analysis of a new dual evaporator CO2 transcritical refrigeration cycle

NASA Astrophysics Data System (ADS)

Abdellaoui, Ezzaalouni Yathreb; Kairouani, Lakdar Kairouani

2017-03-01

In this work, a new dual-evaporator CO2 transcritical refrigeration cycle with two ejectors is proposed. In this new system, we proposed to recover the lost energy of condensation coming off the gas cooler and operate the refrigeration cycle ejector free and enhance the system performance and obtain dual-temperature refrigeration simultaneously. The effects of some key parameters on the thermodynamic performance of the modified cycle are theoretically investigated based on energetic and exergetic analysis. The simulation results for the modified cycle indicate more effective system performance improvement than the single ejector in the CO2 vapor compression cycle using ejector as an expander ranging up to 46%. The exergetic analysis for this system is made. The performance characteristics of the proposed cycle show its promise in dual-evaporator refrigeration system.

Environmental performance policy indicators for the public sector: the case of the defence sector.

PubMed

Ramos, Tomás B; Alves, Inês; Subtil, Rui; Joanaz de Melo, João

2007-03-01

The development of environmental performance policy indicators for public services, and in particular for the defence sector, is an emerging issue. Despite a number of recent initiatives there has been little work done in this area, since the other sectors usually focused on are agriculture, transport, industry, tourism and energy. This type of tool can be an important component for environmental performance evaluation at policy level, when integrated in the general performance assessment system of public missions and activities. The main objective of this research was to develop environmental performance policy indicators for the public sector, specifically applied to the defence sector. Previous research included an assessment of the environmental profile, through the evaluation of how environmental management practices have been adopted in this sector and an assessment of environmental aspects and impacts. This paper builds upon that previous research, developing an indicator framework--SEPI--supported by the selection and construction of environmental performance indicators. Another aim is to discuss how the current environmental indicator framework can be integrated into overall performance management. The Portuguese defence sector is presented and the usefulness of this methodology demonstrated. Feasibility and relevancy criteria are applied to evaluate the set of indicators proposed, allowing indicators to be scored and indicators for the policy level to be obtained.

78 FR 18865 - Defense Federal Acquisition Regulation Supplement: Proposal Adequacy Checklist (DFARS Case 2011...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-28

..., applicable CLIN, Work Breakdown Structure, rationale for estimate, applicable history, and time-phasing... price adjustments, not just those based on indices. Checklist item 45 (final rule item 35) is modified to read ``If the offeror is proposing Performance-Based Payments did the offeror comply with FAR...

Performance Evaluation Model for Application Layer Firewalls.

PubMed

Xuan, Shichang; Yang, Wu; Dong, Hui; Zhang, Jiangchuan

2016-01-01

Application layer firewalls protect the trusted area network against information security risks. However, firewall performance may affect user experience. Therefore, performance analysis plays a significant role in the evaluation of application layer firewalls. This paper presents an analytic model of the application layer firewall, based on a system analysis to evaluate the capability of the firewall. In order to enable users to improve the performance of the application layer firewall with limited resources, resource allocation was evaluated to obtain the optimal resource allocation scheme in terms of throughput, delay, and packet loss rate. The proposed model employs the Erlangian queuing model to analyze the performance parameters of the system with regard to the three layers (network, transport, and application layers). Then, the analysis results of all the layers are combined to obtain the overall system performance indicators. A discrete event simulation method was used to evaluate the proposed model. Finally, limited service desk resources were allocated to obtain the values of the performance indicators under different resource allocation scenarios in order to determine the optimal allocation scheme. Under limited resource allocation, this scheme enables users to maximize the performance of the application layer firewall.

Novel probabilistic neuroclassifier

NASA Astrophysics Data System (ADS)

Hong, Jiang; Serpen, Gursel

2003-09-01

A novel probabilistic potential function neural network classifier algorithm to deal with classes which are multi-modally distributed and formed from sets of disjoint pattern clusters is proposed in this paper. The proposed classifier has a number of desirable properties which distinguish it from other neural network classifiers. A complete description of the algorithm in terms of its architecture and the pseudocode is presented. Simulation analysis of the newly proposed neuro-classifier algorithm on a set of benchmark problems is presented. Benchmark problems tested include IRIS, Sonar, Vowel Recognition, Two-Spiral, Wisconsin Breast Cancer, Cleveland Heart Disease and Thyroid Gland Disease. Simulation results indicate that the proposed neuro-classifier performs consistently better for a subset of problems for which other neural classifiers perform relatively poorly.

PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast.

PubMed

Lai, Fu-Jou; Chang, Hong-Tsun; Wu, Wei-Sheng

2015-01-01

Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface. The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses. Allowing users to select eight existing performance indices and 15 existing algorithms for comparison, our web tool benefits researchers who are eager to comprehensively and objectively evaluate the performance of their newly developed algorithm. Thus, our tool greatly expedites the progress in the research of computational identification of cooperative TF pairs.

PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast

PubMed Central

2015-01-01

Background Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface. Results The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses. Conclusions Allowing users to select eight existing performance indices and 15 existing algorithms for comparison, our web tool benefits researchers who are eager to comprehensively and objectively evaluate the performance of their newly developed algorithm. Thus, our tool greatly expedites the progress in the research of computational identification of cooperative TF pairs. PMID:26677932

A Low-Complexity and High-Performance 2D Look-Up Table for LDPC Hardware Implementation

NASA Astrophysics Data System (ADS)

Chen, Jung-Chieh; Yang, Po-Hui; Lain, Jenn-Kaie; Chung, Tzu-Wen

In this paper, we propose a low-complexity, high-efficiency two-dimensional look-up table (2D LUT) for carrying out the sum-product algorithm in the decoding of low-density parity-check (LDPC) codes. Instead of employing adders for the core operation when updating check node messages, in the proposed scheme, the main term and correction factor of the core operation are successfully merged into a compact 2D LUT. Simulation results indicate that the proposed 2D LUT not only attains close-to-optimal bit error rate performance but also enjoys a low complexity advantage that is suitable for hardware implementation.

Collaboration Indices for Monitoring Potential Problems in Online Small Groups

ERIC Educational Resources Information Center

Jahng, Namsook

2013-01-01

The purpose of this study is to test the validity and reliability of three collaboration indices ("quantity", "equality", "and shareness") proposed by Jahng et al. (2010). The present study repeated the quantitative assessment of Jahng et al., and performed a further qualitative analysis to identify possible factors…

Online damage detection using recursive principal component analysis and recursive condition indicators

NASA Astrophysics Data System (ADS)

Krishnan, M.; Bhowmik, B.; Tiwari, A. K.; Hazra, B.

2017-08-01

In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using recursive principal component analysis (RPCA) in conjunction with online damage indicators is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal modes in online using the rank-one perturbation method, and subsequently utilized to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/nonlinear-states that indicate damage. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. An online condition indicator (CI) based on the L2 norm of the error between actual response and the response projected using recursive eigenvector matrix updates over successive iterations is proposed. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data. The proposed CI, named recursive residual error, is also adopted for simultaneous spatio-temporal damage detection. Numerical simulations performed on five-degree of freedom nonlinear system under white noise and El Centro excitations, with different levels of nonlinearity simulating the damage scenarios, demonstrate the robustness of the proposed algorithm. Successful results obtained from practical case studies involving experiments performed on a cantilever beam subjected to earthquake excitation, for full sensors and underdetermined cases; and data from recorded responses of the UCLA Factor building (full data and its subset) demonstrate the efficacy of the proposed methodology as an ideal candidate for real-time, reference free structural health monitoring.

Combining University Student Self-Regulated Learning Indicators and Engagement with Online Learning Events to Predict Academic Performance

ERIC Educational Resources Information Center

Pardo, Abelardo; Han, Feifei; Ellis, Robert A.

2017-01-01

Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…

Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse Recovery

PubMed Central

Kim, Daeun; Haldar, Justin P.

2016-01-01

This work proposes a family of greedy algorithms to jointly reconstruct a set of vectors that are (i) nonnegative and (ii) simultaneously sparse with a shared support set. The proposed algorithms generalize previous approaches that were designed to impose these constraints individually. Similar to previous greedy algorithms for sparse recovery, the proposed algorithms iteratively identify promising support indices. In contrast to previous approaches, the support index selection procedure has been adapted to prioritize indices that are consistent with both the nonnegativity and shared support constraints. Empirical results demonstrate for the first time that the combined use of simultaneous sparsity and nonnegativity constraints can substantially improve recovery performance relative to existing greedy algorithms that impose less signal structure. PMID:26973368

Metal radomes for reduced RCS performance

NASA Astrophysics Data System (ADS)

Wahid, M.; Morris, S. B.

A frequency selective surface (FSS) comprising a square grid and a hexagonal array of disks is proposed as a means of reducing the Radar Cross Section (RCS) of a radar bay over a wide (2 GHz to 14.6 GHz) frequency bandwidth. Results are presented in terms of transmission loss for an 'A'-type sandwich radome consisting of two FSS layers for normal and non-normal incidence. A single FSS layer on a GRP flat panel is also considered. Good agreement is found between the predicted and measured results. The proposed FSS shows good performance and is relatively insensitive to angle of incidence between 3.8 GHz and 10.1 GHz. Predicted Insertion Phase Delay (IPD) and cross-polar performances are also given. Parametric studies have indicated the versatility of the proposed structure.

Fundamental-mode MMF transmission enabled by mode conversion

NASA Astrophysics Data System (ADS)

Wu, Zhongying; Li, Juhao; Tian, Yu; Ge, Dawei; Zhu, Jinglong; Ren, Fang; Mo, Qi; Yu, Jinyi; Li, Zhengbin; Chen, Zhangyuan; He, Yongqi

2018-03-01

Modal dispersion in conventional multi-mode fiber (MMF) will cause serious signal degradation and an effective solution is to restrict the signal transmission in the fundamental mode of MMF. In this paper, unlike previous methods by filtering out higher-order modes, we propose to adopt low-modal-crosstalk mode converters to realize fundamental-mode MMF transmission. We design and fabricate all-fiber mode-selective couplers (MSC), which perform mode conversion between the fundamental mode in single-mode fiber (SMF) and fundamental mode in MMF. The proposed scheme is experimentally compared with center launching method under different MMF links and then its wavelength division multiplexing (WDM) transmission performance is investigated. Experimental results indicate that the proposed mode conversion scheme could achieve better transmission performance and works well for the whole C-band.

Performance evaluation of Olympic weightlifters.

PubMed

Garhammer, J

1979-01-01

The comparison of weights lifted by athletes in different bodyweight categories is a continuing problem for the sport of olympic weightlifting. An objective mechanical evaluation procedure was developed using basic ideas from a model proposed by Ranta in 1975. This procedure was based on more realistic assumptions than the original model and considered both vertical and horizontal bar movements. Utilization of data obtained from film of national caliber lifters indicated that the proposed method was workable, and that the evaluative indices ranked lifters in reasonable order relative to other comparative techniques.

A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method.

PubMed

Li, Wutao; Huang, Zhigang; Lang, Rongling; Qin, Honglei; Zhou, Kai; Cao, Yongbin

2016-03-04

Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS) receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM) is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM) algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms) level and the monitoring time is on microsecond (μs) level, which make the proposed approach usable in practical interference monitoring applications.

A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method

PubMed Central

Li, Wutao; Huang, Zhigang; Lang, Rongling; Qin, Honglei; Zhou, Kai; Cao, Yongbin

2016-01-01

Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS) receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM) is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM) algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms) level and the monitoring time is on microsecond (μs) level, which make the proposed approach usable in practical interference monitoring applications. PMID:26959020

Adaptive dynamic programming for finite-horizon optimal control of discrete-time nonlinear systems with ε-error bound.

PubMed

Wang, Fei-Yue; Jin, Ning; Liu, Derong; Wei, Qinglai

2011-01-01

In this paper, we study the finite-horizon optimal control problem for discrete-time nonlinear systems using the adaptive dynamic programming (ADP) approach. The idea is to use an iterative ADP algorithm to obtain the optimal control law which makes the performance index function close to the greatest lower bound of all performance indices within an ε-error bound. The optimal number of control steps can also be obtained by the proposed ADP algorithms. A convergence analysis of the proposed ADP algorithms in terms of performance index function and control policy is made. In order to facilitate the implementation of the iterative ADP algorithms, neural networks are used for approximating the performance index function, computing the optimal control policy, and modeling the nonlinear system. Finally, two simulation examples are employed to illustrate the applicability of the proposed method.

A recursive field-normalized bibliometric performance indicator: an application to the field of library and information science.

PubMed

Waltman, Ludo; Yan, Erjia; van Eck, Nees Jan

2011-10-01

Two commonly used ideas in the development of citation-based research performance indicators are the idea of normalizing citation counts based on a field classification scheme and the idea of recursive citation weighing (like in PageRank-inspired indicators). We combine these two ideas in a single indicator, referred to as the recursive mean normalized citation score indicator, and we study the validity of this indicator. Our empirical analysis shows that the proposed indicator is highly sensitive to the field classification scheme that is used. The indicator also has a strong tendency to reinforce biases caused by the classification scheme. Based on these observations, we advise against the use of indicators in which the idea of normalization based on a field classification scheme and the idea of recursive citation weighing are combined.

Analytic network process model for sustainable lean and green manufacturing performance indicator

NASA Astrophysics Data System (ADS)

Aminuddin, Adam Shariff Adli; Nawawi, Mohd Kamal Mohd; Mohamed, Nik Mohd Zuki Nik

2014-09-01

Sustainable manufacturing is regarded as the most complex manufacturing paradigm to date as it holds the widest scope of requirements. In addition, its three major pillars of economic, environment and society though distinct, have some overlapping among each of its elements. Even though the concept of sustainability is not new, the development of the performance indicator still needs a lot of improvement due to its multifaceted nature, which requires integrated approach to solve the problem. This paper proposed the best combination of criteria en route a robust sustainable manufacturing performance indicator formation via Analytic Network Process (ANP). The integrated lean, green and sustainable ANP model can be used to comprehend the complex decision system of the sustainability assessment. The finding shows that green manufacturing is more sustainable than lean manufacturing. It also illustrates that procurement practice is the most important criteria in the sustainable manufacturing performance indicator.

Joint image encryption and compression scheme based on IWT and SPIHT

NASA Astrophysics Data System (ADS)

Zhang, Miao; Tong, Xiaojun

2017-03-01

A joint lossless image encryption and compression scheme based on integer wavelet transform (IWT) and set partitioning in hierarchical trees (SPIHT) is proposed to achieve lossless image encryption and compression simultaneously. Making use of the properties of IWT and SPIHT, encryption and compression are combined. Moreover, the proposed secure set partitioning in hierarchical trees (SSPIHT) via the addition of encryption in the SPIHT coding process has no effect on compression performance. A hyper-chaotic system, nonlinear inverse operation, Secure Hash Algorithm-256(SHA-256), and plaintext-based keystream are all used to enhance the security. The test results indicate that the proposed methods have high security and good lossless compression performance.

Test Anxiety, Computer-Adaptive Testing and the Common Core

ERIC Educational Resources Information Center

Colwell, Nicole Makas

2013-01-01

This paper highlights the current findings and issues regarding the role of computer-adaptive testing in test anxiety. The computer-adaptive test (CAT) proposed by one of the Common Core consortia brings these issues to the forefront. Research has long indicated that test anxiety impairs student performance. More recent research indicates that…

Weather related continuity and completeness on Deep Space Ka-band links: statistics and forecasting

NASA Technical Reports Server (NTRS)

Shambayati, Shervin

2006-01-01

In this paper the concept of link 'stability' as means of measuring the continuity of the link is introduced and through it, along with the distributions of 'good' periods and 'bad' periods, the performance of the proposed Ka-band link design method using both forecasting and long-term statistics has been analyzed. The results indicate that the proposed link design method has relatively good continuity and completeness characteristics even when only long-term statistics are used and that the continuity performance further improves when forecasting is employed. .

Adaptive image coding based on cubic-spline interpolation

NASA Astrophysics Data System (ADS)

Jiang, Jian-Xing; Hong, Shao-Hua; Lin, Tsung-Ching; Wang, Lin; Truong, Trieu-Kien

2014-09-01

It has been investigated that at low bit rates, downsampling prior to coding and upsampling after decoding can achieve better compression performance than standard coding algorithms, e.g., JPEG and H. 264/AVC. However, at high bit rates, the sampling-based schemes generate more distortion. Additionally, the maximum bit rate for the sampling-based scheme to outperform the standard algorithm is image-dependent. In this paper, a practical adaptive image coding algorithm based on the cubic-spline interpolation (CSI) is proposed. This proposed algorithm adaptively selects the image coding method from CSI-based modified JPEG and standard JPEG under a given target bit rate utilizing the so called ρ-domain analysis. The experimental results indicate that compared with the standard JPEG, the proposed algorithm can show better performance at low bit rates and maintain the same performance at high bit rates.

A novel integrated approach for path following and directional stability control of road vehicles after a tire blow-out

NASA Astrophysics Data System (ADS)

Wang, Fei; Chen, Hong; Guo, Konghui; Cao, Dongpu

2017-09-01

The path following and directional stability are two crucial problems when a road vehicle experiences a tire blow-out or sudden tire failure. Considering the requirement of rapid road vehicle motion control during a tire blow-out, this article proposes a novel linearized decoupling control procedure with three design steps for a class of second order multi-input-multi-output non-affine system. The evaluating indicators for controller performance are presented and a performance related control parameter distribution map is obtained based on the stochastic algorithm which is an innovation for non-blind parameter adjustment in engineering implementation. The analysis on the robustness of the proposed integrated controller is also performed. The simulation studies for a range of driving conditions are conducted, to demonstrate the effectiveness of the proposed controller.

Performance evaluation methodology for historical document image binarization.

PubMed

Ntirogiannis, Konstantinos; Gatos, Basilis; Pratikakis, Ioannis

2013-02-01

Document image binarization is of great importance in the document image analysis and recognition pipeline since it affects further stages of the recognition process. The evaluation of a binarization method aids in studying its algorithmic behavior, as well as verifying its effectiveness, by providing qualitative and quantitative indication of its performance. This paper addresses a pixel-based binarization evaluation methodology for historical handwritten/machine-printed document images. In the proposed evaluation scheme, the recall and precision evaluation measures are properly modified using a weighting scheme that diminishes any potential evaluation bias. Additional performance metrics of the proposed evaluation scheme consist of the percentage rates of broken and missed text, false alarms, background noise, character enlargement, and merging. Several experiments conducted in comparison with other pixel-based evaluation measures demonstrate the validity of the proposed evaluation scheme.

Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

2015-01-01

Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

Resolving the challenges in the international comparison of health systems: the must do's and the trade-offs.

PubMed

Forde, Ian; Morgan, David; Klazinga, Niek S

2013-09-01

Countries are increasingly publishing health system performance statistics alongside those of their peers, to identify high performers and achieve a continuously improving health system. The aim of the paper is to identify, and discuss resolution of, some key methodological challenges, which arise when comparing health system performance. To illustrate the issues, we focus on two OECD flagship initiatives: the System of Health Accounts (SHA) and the Health Care Quality Indicators (HCQI) project and refer to two main actors: a coordinating agency, which proposes and collates performance data and second, data correspondents in constituent health systems, who submit data to the coordinating centre. Discussion is structured around two themes: a set of must-do's (legitimacy of the coordinating centre, validity of proposed indicators, feasibility of data collection and technical support for data correspondents) and a set of trade-offs (depth vs. breadth in the number of system elements compared, aggregation vs. granularity of data, flexibility vs. consistency of indicator definitions and inclusion criteria). Robust fulfillment of the must-do's and transparent resolution of the trade-offs both depend upon effective collaboration between the coordinating centre and data correspondents, and a close working relationship between a technical secretariat and a body of experts. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Basis for the development of sustainable optimisation indicators for activated sludge wastewater treatment plants in the Republic of Ireland.

PubMed

Gordon, G T; McCann, B P

2015-01-01

This paper describes the basis of a stakeholder-based sustainable optimisation indicator (SOI) system to be developed for small-to-medium sized activated sludge (AS) wastewater treatment plants (WwTPs) in the Republic of Ireland (ROI). Key technical publications relating to best practice plant operation, performance audits and optimisation, and indicator and benchmarking systems for wastewater services are identified. Optimisation studies were developed at a number of Irish AS WwTPs and key findings are presented. A national AS WwTP manager/operator survey was carried out to verify the applied operational findings and identify the key operator stakeholder requirements for this proposed SOI system. It was found that most plants require more consistent operational data-based decision-making, monitoring and communication structures to facilitate optimised, sustainable and continuous performance improvement. The applied optimisation and stakeholder consultation phases form the basis of the proposed stakeholder-based SOI system. This system will allow for continuous monitoring and rating of plant performance, facilitate optimised operation and encourage the prioritisation of performance improvement through tracking key operational metrics. Plant optimisation has become a major focus due to the transfer of all ROI water services to a national water utility from individual local authorities and the implementation of the EU Water Framework Directive.

Highly accurate adaptive TOF determination method for ultrasonic thickness measurement

NASA Astrophysics Data System (ADS)

Zhou, Lianjie; Liu, Haibo; Lian, Meng; Ying, Yangwei; Li, Te; Wang, Yongqing

2018-04-01

Determining the time of flight (TOF) is very critical for precise ultrasonic thickness measurement. However, the relatively low signal-to-noise ratio (SNR) of the received signals would induce significant TOF determination errors. In this paper, an adaptive time delay estimation method has been developed to improve the TOF determination’s accuracy. An improved variable step size adaptive algorithm with comprehensive step size control function is proposed. Meanwhile, a cubic spline fitting approach is also employed to alleviate the restriction of finite sampling interval. Simulation experiments under different SNR conditions were conducted for performance analysis. Simulation results manifested the performance advantage of proposed TOF determination method over existing TOF determination methods. When comparing with the conventional fixed step size, and Kwong and Aboulnasr algorithms, the steady state mean square deviation of the proposed algorithm was generally lower, which makes the proposed algorithm more suitable for TOF determination. Further, ultrasonic thickness measurement experiments were performed on aluminum alloy plates with various thicknesses. They indicated that the proposed TOF determination method was more robust even under low SNR conditions, and the ultrasonic thickness measurement accuracy could be significantly improved.

Significance of parametric spectral ratio methods in detection and recognition of whispered speech

NASA Astrophysics Data System (ADS)

Mathur, Arpit; Reddy, Shankar M.; Hegde, Rajesh M.

2012-12-01

In this article the significance of a new parametric spectral ratio method that can be used to detect whispered speech segments within normally phonated speech is described. Adaptation methods based on the maximum likelihood linear regression (MLLR) are then used to realize a mismatched train-test style speech recognition system. This proposed parametric spectral ratio method computes a ratio spectrum of the linear prediction (LP) and the minimum variance distortion-less response (MVDR) methods. The smoothed ratio spectrum is then used to detect whispered segments of speech within neutral speech segments effectively. The proposed LP-MVDR ratio method exhibits robustness at different SNRs as indicated by the whisper diarization experiments conducted on the CHAINS and the cell phone whispered speech corpus. The proposed method also performs reasonably better than the conventional methods for whisper detection. In order to integrate the proposed whisper detection method into a conventional speech recognition engine with minimal changes, adaptation methods based on the MLLR are used herein. The hidden Markov models corresponding to neutral mode speech are adapted to the whispered mode speech data in the whispered regions as detected by the proposed ratio method. The performance of this method is first evaluated on whispered speech data from the CHAINS corpus. The second set of experiments are conducted on the cell phone corpus of whispered speech. This corpus is collected using a set up that is used commercially for handling public transactions. The proposed whisper speech recognition system exhibits reasonably better performance when compared to several conventional methods. The results shown indicate the possibility of a whispered speech recognition system for cell phone based transactions.

Developing Urban Environment Indicators for Neighborhood Sustainability Assessment in Tripoli-Libya

NASA Astrophysics Data System (ADS)

Elgadi, Ahmed. A.; Hakim Ismail, Lokman; Abass, Fatma; Ali, Abdelmuniem

2016-11-01

Sustainability assessment frameworks are becoming increasingly important to assist in the transition towards a sustainable urban environment. The urban environment is an effective system and requires regular monitoring and evaluation through a set of relevant indicators. The indicator provides information about the state of the environment through the production value of quantity. The indicator creates sustainability assessment requests to be considered on all spatial scales to specify efficient information of urban environment sustainability in Tripoli-Libya. Detailed data is necessary to assess environmental modification in the urban environment on a local scale and ease the transfer of this information to national and global stages. This paper proposes a set of key indicators to monitor urban environmental sustainability developments of Libyan residential neighborhoods. The proposed environmental indicator framework measures the sustainability performance of an urban environment through 13 sub-categories consisting of 21 indicators. This paper also explains the theoretical foundations for the selection of all indicators with reference to previous studies.

Dehazed Image Quality Assessment by Haze-Line Theory

NASA Astrophysics Data System (ADS)

Song, Yingchao; Luo, Haibo; Lu, Rongrong; Ma, Junkai

2017-06-01

Images captured in bad weather suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. However, there is a lack of evaluation metrics to assess the performance of these algorithms or rate them. In this paper, an indicator of contrast enhancement is proposed basing on the newly proposed haze-line theory. The theory assumes that colors of a haze-free image are well approximated by a few hundred distinct colors, which form tight clusters in RGB space. The presence of haze makes each color cluster forms a line, which is named haze-line. By using these haze-lines, we assess performance of dehazing algorithms designed to enhance the contrast by measuring the inter-cluster deviations between different colors of dehazed image. Experimental results demonstrated that the proposed Color Contrast (CC) index correlates well with human judgments of image contrast taken in a subjective test on various scene of dehazed images and performs better than state-of-the-art metrics.

ASCCP Colposcopy Standards: Colposcopy Quality Improvement Recommendations for the United States.

PubMed

Mayeaux, Edward J; Novetsky, Akiva P; Chelmow, David; Garcia, Francisco; Choma, Kim; Liu, Angela H; Papasozomenos, Theognosia; Einstein, Mark H; Massad, L Stewart; Wentzensen, Nicolas; Waxman, Alan G; Conageski, Christine; Khan, Michelle J; Huh, Warner K

2017-10-01

The American Society for Colposcopy and Cervical Pathology (ASCCP) Colposcopy Standards recommendations address the role of and approach to colposcopy and biopsy for cervical cancer prevention in the United States. The recommendations were developed by an expert working group appointed by ASCCP's Board of Directors. The ASCCP Quality Improvement Working Group developed evidence-based guidelines to promote best practices and reduce errors in colposcopy and recommended indicators to measure colposcopy quality. The working group performed a systematic review of existing major society and national guidelines and quality indicators. An initial list of potential quality indicators was developed and refined through successive iterative discussions, and draft quality indicators were proposed. The draft recommendations were then reviewed and commented on by the entire Colposcopy Standards Committee, posted online for public comment, and presented at the International Federation for Cervical Pathology and Colposcopy 2017 World Congress for further comment. All comments were considered, additional adjustments made, and the final recommendations approved by the entire Task Force. Eleven quality indicators were selected spanning documentation, biopsy protocols, and time intervals between index screening tests and completion of diagnostic evaluation. The proposed quality indicators are intended to serve as a starting point for quality improvement in colposcopy at a time when colposcopy volume is decreasing and individual procedures are becoming technically more difficult to perform.

Research and application of a novel hybrid decomposition-ensemble learning paradigm with error correction for daily PM10 forecasting

NASA Astrophysics Data System (ADS)

Luo, Hongyuan; Wang, Deyun; Yue, Chenqiang; Liu, Yanling; Guo, Haixiang

2018-03-01

In this paper, a hybrid decomposition-ensemble learning paradigm combining error correction is proposed for improving the forecast accuracy of daily PM10 concentration. The proposed learning paradigm is consisted of the following two sub-models: (1) PM10 concentration forecasting model; (2) error correction model. In the proposed model, fast ensemble empirical mode decomposition (FEEMD) and variational mode decomposition (VMD) are applied to disassemble original PM10 concentration series and error sequence, respectively. The extreme learning machine (ELM) model optimized by cuckoo search (CS) algorithm is utilized to forecast the components generated by FEEMD and VMD. In order to prove the effectiveness and accuracy of the proposed model, two real-world PM10 concentration series respectively collected from Beijing and Harbin located in China are adopted to conduct the empirical study. The results show that the proposed model performs remarkably better than all other considered models without error correction, which indicates the superior performance of the proposed model.

A Skill Score of Trajectory Model Evaluation Using Reinitialized Series of Normalized Cumulative Lagrangian Separation

NASA Astrophysics Data System (ADS)

Liu, Y.; Weisberg, R. H.

2017-12-01

The Lagrangian separation distance between the endpoints of simulated and observed drifter trajectories is often used to assess the performance of numerical particle trajectory models. However, the separation distance fails to indicate relative model performance in weak and strong current regions, such as a continental shelf and its adjacent deep ocean. A skill score is proposed based on the cumulative Lagrangian separation distances normalized by the associated cumulative trajectory lengths. The new metrics correctly indicates the relative performance of the Global HYCOM in simulating the strong currents of the Gulf of Mexico Loop Current and the weaker currents of the West Florida Shelf in the eastern Gulf of Mexico. In contrast, the Lagrangian separation distance alone gives a misleading result. Also, the observed drifter position series can be used to reinitialize the trajectory model and evaluate its performance along the observed trajectory, not just at the drifter end position. The proposed dimensionless skill score is particularly useful when the number of drifter trajectories is limited and neither a conventional Eulerian-based velocity nor a Lagrangian-based probability density function may be estimated.

Performance measure that indicates geometry sufficiency of state highways : volume II -- clear zones and cross-section information extraction.

DOT National Transportation Integrated Search

2015-03-01

Evaluationmethod employedforthe proposed corridor projects by IndianaDepartment of Transportation(INDOT) considerroad : geometry improvements by a generalized categorization. A newmethod which consi...

Developing an Index to Measure Health System Performance: Measurement for Districts of Nepal.

PubMed

Kandel, N; Fric, A; Lamichhane, J

2014-01-01

Various frameworks for measuring health system performance have been proposed and discussed. The scope of using performance indicators are broad, ranging from examining national health system to individual patients at various levels of health system. Development of innovative and easy index is essential to measure multidimensionality of health systems. We used indicators, which also serve as proxy to the set of activities, whose primary goal is to maintain and improve health. We used eleven indicators of MDGs, which represent all dimensions of health to develop index. These indicators are computed with similar methodology that of human development index. We used published data of Nepal for computation of the index for districts of Nepal as an illustration. To validate our finding, we compared the indices of these districts with other development indices of Nepal. An index for each district has been computed from eleven indicators. Then indices are compared with that of human development index, socio-economic and infrastructure development indices and findings has shown the similarity on distribution of districts. Categories of low and high performing districts on health system performance are also having low and high human development, socio-economic, and infrastructure indices respectively. This methodology of computing index from various indicators could assist policy makers and program managers to prioritize activities based on their performance. Validation of the findings with that of other development indicators show that this can be one of the tools, which can assist on assessing health system performance for policy makers, program managers and others.

Research on the strategy of underwater united detection fusion and communication using multi-sensor

NASA Astrophysics Data System (ADS)

Xu, Zhenhua; Huang, Jianguo; Huang, Hai; Zhang, Qunfei

2011-09-01

In order to solve the distributed detection fusion problem of underwater target detection, when the signal to noise ratio (SNR) of the acoustic channel is low, a new strategy for united detection fusion and communication using multiple sensors was proposed. The performance of detection fusion was studied and compared based on the Neyman-Pearson principle when the binary phase shift keying (BPSK) and on-off keying (OOK) modes were used by the local sensors. The comparative simulation and analysis between the optimal likelihood ratio test and the proposed strategy was completed, and both the theoretical analysis and simulation indicate that using the proposed new strategy could improve the detection performance effectively. In theory, the proposed strategy of united detection fusion and communication is of great significance to the establishment of an underwater target detection system.

Joint image encryption and compression scheme based on a new hyperchaotic system and curvelet transform

NASA Astrophysics Data System (ADS)

Zhang, Miao; Tong, Xiaojun

2017-07-01

This paper proposes a joint image encryption and compression scheme based on a new hyperchaotic system and curvelet transform. A new five-dimensional hyperchaotic system based on the Rabinovich system is presented. By means of the proposed hyperchaotic system, a new pseudorandom key stream generator is constructed. The algorithm adopts diffusion and confusion structure to perform encryption, which is based on the key stream generator and the proposed hyperchaotic system. The key sequence used for image encryption is relation to plain text. By means of the second generation curvelet transform, run-length coding, and Huffman coding, the image data are compressed. The joint operation of compression and encryption in a single process is performed. The security test results indicate the proposed methods have high security and good compression effect.

SOLID PHASE EXTRACTION AND HIGH PERFORMANCE LIQUID CHROMATOGRAPHY WITH PHOTODIODE ARRAY DETECTION OF CHEMICAL INDICATORS OF HUMAN FECAL CONTAMINATION IN WATER

EPA Science Inventory

Faster and more sensitive analysis of water that is contaminated by human fecal matter is very important for health. The current microbiological methods to assess water quality do not meet this need. Alternate non-microbial human fecal indicators have been proposed by various r...

76 FR 10135 - Public Housing Evaluation and Oversight: Changes to the Public Housing Assessment System (PHAS...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-23

... PHA to four key areas of a PHA's operations: (1) The physical condition of the PHA's properties; (2... and to require PHAs to be scored on performance based on evaluation of four indicators: physical... changes proposed to each of the four current PHAS indicators are as follows: Physical. The physical...

An Evaluation of Proposed School Safety Indicators for Georgia.

ERIC Educational Resources Information Center

Todd, Knox H.; Kellermann, Arthur L.; Wald, Marlena; Lipscomb, Leslie; Fajman, Nancy

One of the tasks of the Council for School Performance is to implement measures of school safety to determine the impact of Georgia Lottery for Education expenditures. During the 1994-95 school year, the council pilot-tested several indicators of school safety. This document presents the results of an evaluation that examined the relevance,…

Mixed kernel function support vector regression for global sensitivity analysis

NASA Astrophysics Data System (ADS)

Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

2017-11-01

Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

Automatic detection method for mura defects on display film surface using modified Weber's law

NASA Astrophysics Data System (ADS)

Kim, Myung-Muk; Lee, Seung-Ho

2014-07-01

We propose a method that automatically detects mura defects on display film surfaces using a modified version of Weber's law. The proposed method detects mura defects regardless of their properties and shapes by identifying regions perceived by human vision as mura using the brightness of pixel and image distribution ratio of mura in an image histogram. The proposed detection method comprises five stages. In the first stage, the display film surface image is acquired and a gray-level shift performed. In the second and third stages, the image histogram is acquired and analyzed, respectively. In the fourth stage, the mura range is acquired. This is followed by postprocessing in the fifth stage. Evaluations of the proposed method conducted using 200 display film mura image samples indicate a maximum detection rate of ˜95.5%. Further, the results of application of the Semu index for luminance mura in flat panel display (FPD) image quality inspection indicate that the proposed method is more reliable than a popular conventional method.

Analysis of the Seismic Performance of Isolated Buildings according to Life-Cycle Cost

PubMed Central

Dang, Yu; Han, Jian-ping; Li, Yong-tao

2015-01-01

This paper proposes an indicator of seismic performance based on life-cycle cost of a building. It is expressed as a ratio of lifetime damage loss to life-cycle cost and determines the seismic performance of isolated buildings. Major factors are considered, including uncertainty in hazard demand and structural capacity, initial costs, and expected loss during earthquakes. Thus, a high indicator value indicates poor building seismic performance. Moreover, random vibration analysis is conducted to measure structural reliability and evaluate the expected loss and life-cycle cost of isolated buildings. The expected loss of an actual, seven-story isolated hospital building is only 37% of that of a fixed-base building. Furthermore, the indicator of the structural seismic performance of the isolated building is much lower in value than that of the structural seismic performance of the fixed-base building. Therefore, isolated buildings are safer and less risky than fixed-base buildings. The indicator based on life-cycle cost assists owners and engineers in making investment decisions in consideration of structural design, construction, and expected loss. It also helps optimize the balance between building reliability and building investment. PMID:25653677

Analysis of the seismic performance of isolated buildings according to life-cycle cost.

PubMed

Dang, Yu; Han, Jian-Ping; Li, Yong-Tao

2015-01-01

This paper proposes an indicator of seismic performance based on life-cycle cost of a building. It is expressed as a ratio of lifetime damage loss to life-cycle cost and determines the seismic performance of isolated buildings. Major factors are considered, including uncertainty in hazard demand and structural capacity, initial costs, and expected loss during earthquakes. Thus, a high indicator value indicates poor building seismic performance. Moreover, random vibration analysis is conducted to measure structural reliability and evaluate the expected loss and life-cycle cost of isolated buildings. The expected loss of an actual, seven-story isolated hospital building is only 37% of that of a fixed-base building. Furthermore, the indicator of the structural seismic performance of the isolated building is much lower in value than that of the structural seismic performance of the fixed-base building. Therefore, isolated buildings are safer and less risky than fixed-base buildings. The indicator based on life-cycle cost assists owners and engineers in making investment decisions in consideration of structural design, construction, and expected loss. It also helps optimize the balance between building reliability and building investment.

Rolling element bearing fault diagnosis based on Over-Complete rational dilation wavelet transform and auto-correlation of analytic energy operator

NASA Astrophysics Data System (ADS)

Singh, Jaskaran; Darpe, A. K.; Singh, S. P.

2018-02-01

Local damage in rolling element bearings usually generates periodic impulses in vibration signals. The severity, repetition frequency and the fault excited resonance zone by these impulses are the key indicators for diagnosing bearing faults. In this paper, a methodology based on over complete rational dilation wavelet transform (ORDWT) is proposed, as it enjoys a good shift invariance. ORDWT offers flexibility in partitioning the frequency spectrum to generate a number of subbands (filters) with diverse bandwidths. The selection of the optimal filter that perfectly overlaps with the bearing fault excited resonance zone is based on the maximization of a proposed impulse detection measure "Temporal energy operated auto correlated kurtosis". The proposed indicator is robust and consistent in evaluating the impulsiveness of fault signals in presence of interfering vibration such as heavy background noise or sporadic shocks unrelated to the fault or normal operation. The structure of the proposed indicator enables it to be sensitive to fault severity. For enhanced fault classification, an autocorrelation of the energy time series of the signal filtered through the optimal subband is proposed. The application of the proposed methodology is validated on simulated and experimental data. The study shows that the performance of the proposed technique is more robust and consistent in comparison to the original fast kurtogram and wavelet kurtogram.

[Consolidation of international guidelines for the management of canine populations in urban areas and proposal of performance indicators].

PubMed

Garcia, Rita de Cassia Maria; Calderón, Néstor; Ferreira, Fernando

2012-08-01

The objective of this study is to propose a generic program for the management of urban canine populations with suggestion of performance indicators. The following international guidelines on canine population management were revised and consolidated: World Health Organization, World Organisation for Animal Health, World Society for the Protection of Animals, International Companion Animal Management Coalition, and the Food and Agriculture Organization. Management programs should cover: situation diagnosis, including estimates of population size; social participation with involvement of various sectors in the planning and execution of strategies; educational actions to promote humane values, animal welfare, community health, and responsible ownership (through purchase or adoption); environmental and waste management to eliminate sources of food and shelter; registration and identification of animals; animal health care, reproductive control; prevention and control of zoonoses; control of animal commerce; management of animal behavior and adequate solutions for abandoned animals; and laws regulating responsible ownership, prevention of abandonment and zoonoses. To monitor these actions, four groups of indicators are suggested: animal population indicators, human/animal interaction indicators, public service indicators, and zoonosis indicators. The management of stray canine populations requires political, sanitary, ethologic, ecologic, and humanitarian strategies that are socially acceptable and environmentally sustainable. Such measures must also include the control of zoonoses such as rabies and leishmaniasis, considering the concept of "one health," which benefits both the animals and people in the community.

Robust tuning of robot control systems

NASA Technical Reports Server (NTRS)

Minis, I.; Uebel, M.

1992-01-01

The computed torque control problem is examined for a robot arm with flexible, geared, joint drive systems which are typical in many industrial robots. The standard computed torque algorithm is not directly applicable to this class of manipulators because of the dynamics introduced by the joint drive system. The proposed approach to computed torque control combines a computed torque algorithm with torque controller at each joint. Three such control schemes are proposed. The first scheme uses the joint torque control system currently implemented on the robot arm and a novel form of the computed torque algorithm. The other two use the standard computed torque algorithm and a novel model following torque control system based on model following techniques. Standard tasks and performance indices are used to evaluate the performance of the controllers. Both numerical simulations and experiments are used in evaluation. The study shows that all three proposed systems lead to improved tracking performance over a conventional PD controller.

GPS/DR Error Estimation for Autonomous Vehicle Localization.

PubMed

Lee, Byung-Hyun; Song, Jong-Hwa; Im, Jun-Hyuck; Im, Sung-Hyuck; Heo, Moon-Beom; Jee, Gyu-In

2015-08-21

Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.

GPS/DR Error Estimation for Autonomous Vehicle Localization

PubMed Central

Lee, Byung-Hyun; Song, Jong-Hwa; Im, Jun-Hyuck; Im, Sung-Hyuck; Heo, Moon-Beom; Jee, Gyu-In

2015-01-01

Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level. PMID:26307997

Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems.

PubMed

Ashtiani Haghighi, Donya; Mobayen, Saleh

2018-04-01

This paper proposes an adaptive super-twisting decoupled terminal sliding mode control technique for a class of fourth-order systems. The adaptive-tuning law eliminates the requirement of the knowledge about the upper bounds of external perturbations. Using the proposed control procedure, the state variables of cart-pole system are converged to decoupled terminal sliding surfaces and their equilibrium points in the finite time. Moreover, via the super-twisting algorithm, the chattering phenomenon is avoided without affecting the control performance. The numerical results demonstrate the high stabilization accuracy and lower performance indices values of the suggested method over the other ones. The simulation results on the cart-pole system as well as experimental validations demonstrate that the proposed control technique exhibits a reasonable performance in comparison with the other methods. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Performance evaluation of extension education centers in universities based on the balanced scorecard.

PubMed

Wu, Hung-Yi; Lin, Yi-Kuei; Chang, Chi-Hsiang

2011-02-01

This study aims at developing a set of appropriate performance evaluation indices mainly based on balanced scorecard (BSC) for extension education centers in universities by utilizing multiple criteria decision making (MCDM). Through literature reviews and experts who have real practical experiences in extension education, adequate performance evaluation indices have been selected and then utilizing the decision making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP), respectively, further establishes the causality between the four BSC perspectives as well as the relative weights between evaluation indices. According to this previous result, an empirical analysis of the performance evaluation of extension education centers of three universities at Taoyuan County in Taiwan is illustrated by applying VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). From the analysis results, it indicates that "Learning and growth" is the significant influential factor and it would affect the other three perspectives. In addition, it is discovered that "Internal process" perspective as well as "Financial" perspective play important roles in the performance evaluation of extension education centers. The top three key performance indices are "After-sales service", "Turnover volume", and "Net income". The proposed evaluation model could be considered as a reference for extension education centers in universities to prioritize their improvements on the key performance indices after performing VIKOR analyses. 2010 Elsevier Ltd. All rights reserved.

GPU-Based Point Cloud Superpositioning for Structural Comparisons of Protein Binding Sites.

PubMed

Leinweber, Matthias; Fober, Thomas; Freisleben, Bernd

2018-01-01

In this paper, we present a novel approach to solve the labeled point cloud superpositioning problem for performing structural comparisons of protein binding sites. The solution is based on a parallel evolution strategy that operates on large populations and runs on GPU hardware. The proposed evolution strategy reduces the likelihood of getting stuck in a local optimum of the multimodal real-valued optimization problem represented by labeled point cloud superpositioning. The performance of the GPU-based parallel evolution strategy is compared to a previously proposed CPU-based sequential approach for labeled point cloud superpositioning, indicating that the GPU-based parallel evolution strategy leads to qualitatively better results and significantly shorter runtimes, with speed improvements of up to a factor of 1,500 for large populations. Binary classification tests based on the ATP, NADH, and FAD protein subsets of CavBase, a database containing putative binding sites, show average classification rate improvements from about 92 percent (CPU) to 96 percent (GPU). Further experiments indicate that the proposed GPU-based labeled point cloud superpositioning approach can be superior to traditional protein comparison approaches based on sequence alignments.

Location verification algorithm of wearable sensors for wireless body area networks.

PubMed

Wang, Hua; Wen, Yingyou; Zhao, Dazhe

2018-01-01

Knowledge of the location of sensor devices is crucial for many medical applications of wireless body area networks, as wearable sensors are designed to monitor vital signs of a patient while the wearer still has the freedom of movement. However, clinicians or patients can misplace the wearable sensors, thereby causing a mismatch between their physical locations and their correct target positions. An error of more than a few centimeters raises the risk of mistreating patients. The present study aims to develop a scheme to calculate and detect the position of wearable sensors without beacon nodes. A new scheme was proposed to verify the location of wearable sensors mounted on the patient's body by inferring differences in atmospheric air pressure and received signal strength indication measurements from wearable sensors. Extensive two-sample t tests were performed to validate the proposed scheme. The proposed scheme could easily recognize a 30-cm horizontal body range and a 65-cm vertical body range to correctly perform sensor localization and limb identification. All experiments indicate that the scheme is suitable for identifying wearable sensor positions in an indoor environment.

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

PubMed Central

Huang, Yongfeng; Wu, Xian; Li, Xing

2015-01-01

With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods. PMID:26106409

Exploiting teleconnection indices for probabilistic forecasting of drought class transitions in Sicily region (Italy)

NASA Astrophysics Data System (ADS)

Bonaccorso, Brunella; Cancelliere, Antonino

2015-04-01

In the present study two probabilistic models for short-medium term drought forecasting able to include information provided by teleconnection indices are proposed and applied to Sicily region (Italy). Drought conditions are expressed in terms of the Standardized Precipitation-Evapotranspiration Index (SPEI) at different aggregation time scales. More specifically, a multivariate approach based on normal distribution is developed in order to estimate: 1) on the one hand transition probabilities to future SPEI drought classes and 2) on the other hand, SPEI forecasts at a generic time horizon M, as functions of past values of SPEI and the selected teleconnection index. To this end, SPEI series at 3, 4 and 6 aggregation time scales for Sicily region are extracted from the Global SPEI database, SPEIbase , available at Web repository of the Spanish National Research Council (http://sac.csic.es/spei/database.html), and averaged over the study area. In particular, SPEIbase v2.3 with spatial resolution of 0.5° lat/lon and temporal coverage between January 1901 and December 2013 is used. A preliminary correlation analysis is carried out to investigate the link between the drought index and different teleconnection patterns, namely: the North Atlantic Oscillation (NAO), the Scandinavian (SCA) and the East Atlantic-West Russia (EA-WR) patterns. Results of such analysis indicate a strongest influence of NAO on drought conditions in Sicily with respect to other teleconnection indices. Then, the proposed forecasting methodology is applied and the skill in forecasting of the proposed models is quantitatively assessed through the application of a simple score approach and of performance indices. Results indicate that inclusion of NAO index generally enhance model performance thus confirming the suitability of the models for short- medium term forecast of drought conditions.

Blood detection in wireless capsule endoscope images based on salient superpixels.

PubMed

Iakovidis, Dimitris K; Chatzis, Dimitris; Chrysanthopoulos, Panos; Koulaouzidis, Anastasios

2015-08-01

Wireless capsule endoscopy (WCE) enables screening of the gastrointestinal (GI) tract with a miniature, optical endoscope packed within a small swallowable capsule, wirelessly transmitting color images. In this paper we propose a novel method for automatic blood detection in contemporary WCE images. Blood is an alarming indication for the presence of pathologies requiring further treatment. The proposed method is based on a new definition of superpixel saliency. The saliency of superpixels is assessed upon their color, enabling the identification of image regions that are likely to contain blood. The blood patterns are recognized by their color features using a supervised learning machine. Experiments performed on a public dataset using automatically selected first-order statistical features from various color components indicate that the proposed method outperforms state-of-the-art methods.

An evaluation of indices that describe the impact of ozone on the yield of spring wheat ( Triticum aestivum L.)

NASA Astrophysics Data System (ADS)

Finnan, J. M.; Burke, J. I.; Jones, M. B.

A comparison of the performance of different ozone indices in exposure-response functions was made using crop yield and ozone monitoring data from spring wheat studies carried out within the framework of the European open-top chamber programme. Indices were calculated for a twelve-hour period (0900-2100 h, local time). An attempt was made to incorporate a measure of absorbed dose into current indices by weighting with simultaneous sunshine hour values. Both linear and Weibull models were fitted to the exposure-response data in order to evaluate index performance. Cumulative indices which employed continuous weighting functions (allometric or sigmoid) or which censored concentrations above threshold values performed best as they attributed increasing weight to higher concentrations. Indices which simply summed concentrations greater than or equal to a threshold value did not perform as well as equal weight was given to all concentrations greater than the threshold value. Model selection was found to be very important in determining the indices that best describe the relationship between exposure and response. In general weighting hourly ozone concentrations with the corresponding sunshine hour values in an attempt to incorporate this proposed measure of plant activity into current indices did not improve index performance. Ozone exposure indices accounted for a large proportion of the variability in data (91%) and it is suggested that a strong link exists between exposure and dose.

Performance Degradation Assessment of Rolling Element Bearings using Improved Fuzzy Entropy

NASA Astrophysics Data System (ADS)

Zhu, Keheng; Jiang, Xiaohui; Chen, Liang; Li, Haolin

2017-10-01

Rolling element bearings are an important unit in the rotating machines, and their performance degradation assessment is the basis of condition-based maintenance. Targeting the non-linear dynamic characteristics of faulty signals of rolling element bearings, a bearing performance degradation assessment approach based on improved fuzzy entropy (FuzzyEn) is proposed in this paper. FuzzyEn has less dependence on data length and achieves more freedom of parameter selection and more robustness to noise. However, it neglects the global trend of the signal when calculating similarity degree of two vectors, and thus cannot reflect the running state of the rolling element bearings accurately. Based on this consideration, the algorithm of FuzzyEn is improved in this paper and the improved FuzzyEn is utilized as an indicator for bearing performance degradation evaluation. The vibration data from run-to-failure test of rolling element bearings are used to validate the proposed method. The experimental results demonstrate that, compared with the traditional kurtosis and root mean square, the proposed method can detect the incipient fault in advance and can reflect the whole performance degradation process more clearly.

Investigating the optimal passive and active vibration controls of adjacent buildings based on performance indices using genetic algorithms

NASA Astrophysics Data System (ADS)

Hadi, Muhammad N. S.; Uz, Mehmet E.

2015-02-01

This study proposes the optimal passive and active damper parameters for achieving the best results in seismic response mitigation of coupled buildings connected to each other by dampers. The optimization to minimize the H2 and H∞ norms in the performance indices is carried out by genetic algorithms (GAs). The final passive and active damper parameters are checked for adjacent buildings connected to each other under El Centro NS 1940 and Kobe NS 1995 excitations. Using real coded GA in H∞ norm, the optimal controller gain is obtained by different combinations of the measurement as the feedback for designing the control force between the buildings. The proposed method is more effective than other metaheuristic methods and more feasible, although the control force increased. The results in the active control system show that the response of adjacent buildings is reduced in an efficient manner.

Ka-Band Wide-Bandgap Solid-State Power Amplifier: Hardware Validation

NASA Technical Reports Server (NTRS)

Epp, L.; Khan, P.; Silva, A.

2005-01-01

Motivated by recent advances in wide-bandgap (WBG) gallium nitride (GaN) semiconductor technology, there is considerable interest in developing efficient solid-state power amplifiers (SSPAs) as an alternative to the traveling-wave tube amplifier (TWTA) for space applications. This article documents proof-of-concept hardware used to validate power-combining technologies that may enable a 120-W, 40 percent power-added efficiency (PAE) SSPA. Results in previous articles [1-3] indicate that architectures based on at least three power combiner designs are likely to enable the target SSPA. Previous architecture performance analyses and estimates indicate that the proposed architectures can power combine 16 to 32 individual monolithic microwave integrated circuits (MMICs) with >80 percent combining efficiency. This combining efficiency would correspond to MMIC requirements of 5- to 10-W output power and >48 percent PAE. In order to validate the performance estimates of the three proposed architectures, measurements of proof-of-concept hardware are reported here.

A Novel Magnetic Actuation Scheme to Disaggregate Nanoparticles and Enhance Passage across the Blood–Brain Barrier

PubMed Central

Le, Tuan-Anh; Amin, Faiz Ul; Kim, Myeong Ok

2017-01-01

The blood–brain barrier (BBB) hinders drug delivery to the brain. Despite various efforts to develop preprogramed actuation schemes for magnetic drug delivery, the unmodeled aggregation phenomenon limits drug delivery performance. This paper proposes a novel scheme with an aggregation model for a feed-forward magnetic actuation design. A simulation platform for aggregated particle delivery is developed and an actuation scheme is proposed to deliver aggregated magnetic nanoparticles (MNPs) using a discontinuous asymmetrical magnetic actuation. The experimental results with a Y-shaped channel indicated the success of the proposed scheme in steering and disaggregation. The delivery performance of the developed scheme was examined using a realistic, three-dimensional (3D) vessel simulation. Furthermore, the proposed scheme enhanced the transport and uptake of MNPs across the BBB in mice. The scheme presented here facilitates the passage of particles across the BBB to the brain using an electromagnetic actuation scheme. PMID:29271927

Guided particle swarm optimization method to solve general nonlinear optimization problems

NASA Astrophysics Data System (ADS)

Abdelhalim, Alyaa; Nakata, Kazuhide; El-Alem, Mahmoud; Eltawil, Amr

2018-04-01

The development of hybrid algorithms is becoming an important topic in the global optimization research area. This article proposes a new technique in hybridizing the particle swarm optimization (PSO) algorithm and the Nelder-Mead (NM) simplex search algorithm to solve general nonlinear unconstrained optimization problems. Unlike traditional hybrid methods, the proposed method hybridizes the NM algorithm inside the PSO to improve the velocities and positions of the particles iteratively. The new hybridization considers the PSO algorithm and NM algorithm as one heuristic, not in a sequential or hierarchical manner. The NM algorithm is applied to improve the initial random solution of the PSO algorithm and iteratively in every step to improve the overall performance of the method. The performance of the proposed method was tested over 20 optimization test functions with varying dimensions. Comprehensive comparisons with other methods in the literature indicate that the proposed solution method is promising and competitive.

A Novel Magnetic Actuation Scheme to Disaggregate Nanoparticles and Enhance Passage across the Blood-Brain Barrier.

PubMed

Hoshiar, Ali Kafash; Le, Tuan-Anh; Amin, Faiz Ul; Kim, Myeong Ok; Yoon, Jungwon

2017-12-22

The blood-brain barrier (BBB) hinders drug delivery to the brain. Despite various efforts to develop preprogramed actuation schemes for magnetic drug delivery, the unmodeled aggregation phenomenon limits drug delivery performance. This paper proposes a novel scheme with an aggregation model for a feed-forward magnetic actuation design. A simulation platform for aggregated particle delivery is developed and an actuation scheme is proposed to deliver aggregated magnetic nanoparticles (MNPs) using a discontinuous asymmetrical magnetic actuation. The experimental results with a Y-shaped channel indicated the success of the proposed scheme in steering and disaggregation. The delivery performance of the developed scheme was examined using a realistic, three-dimensional (3D) vessel simulation. Furthermore, the proposed scheme enhanced the transport and uptake of MNPs across the BBB in mice. The scheme presented here facilitates the passage of particles across the BBB to the brain using an electromagnetic actuation scheme.

Performance indicators and indices of sludge management in urban wastewater treatment plants.

PubMed

Silva, C; Saldanha Matos, J; Rosa, M J

2016-12-15

Sludge (or biosolids) management is highly complex and has a significant cost associated with the biosolids disposal, as well as with the energy and flocculant consumption in the sludge processing units. The sludge management performance indicators (PIs) and indices (PXs) are thus core measures of the performance assessment system developed for urban wastewater treatment plants (WWTPs). The key PIs proposed cover the sludge unit production and dry solids concentration (DS), disposal/beneficial use, quality compliance for agricultural use and costs, whereas the complementary PIs assess the plant reliability and the chemical reagents' use. A key PI was also developed for assessing the phosphorus reclamation, namely through the beneficial use of the biosolids and the reclaimed water in agriculture. The results of a field study with 17 Portuguese urban WWTPs in a 5-year period were used to derive the PI reference values which are neither inherent to the PI formulation nor literature-based. Clusters by sludge type (primary, activated, trickling filter and mixed sludge) and by digestion and dewatering processes were analysed and the reference values for sludge production and dry solids were proposed for two clusters: activated sludge or biofilter WWTPs with primary sedimentation, sludge anaerobic digestion and centrifuge dewatering; activated sludge WWTPs without primary sedimentation and anaerobic digestion and with centrifuge dewatering. The key PXs are computed for the DS after each processing unit and the complementary PXs for the energy consumption and the operating conditions DS-determining. The PX reference values are treatment specific and literature based. The PI and PX system was applied to a WWTP and the results demonstrate that it diagnosis the situation and indicates opportunities and measures for improving the WWTP performance in sludge management. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using a new incentive mechanism to improve wastewater sector performance: the case study of Italy.

PubMed

De Gisi, Sabino; Petta, Luigi; Farina, Roberto; De Feo, Giovanni

2014-01-01

The system of "Service Objectives", introduced by the Italian National Strategic Framework 2007-2013, is an innovative results-oriented programme concerning 4 thematic areas (education, care for the elderly and children, management of municipal solid wastes and integrated water service) in which the Ministry of Economic Development and eight Southern Italy districts are involved. The system was initially associated to an incentive mechanism which provided subsidies for a total amount of EUR 3 billion from the national Underdeveloped Areas Fund, according to the achievement of specific targets set for 11 service indicators in 2013. The indicators used for the integrated water service refer to the efficiency in water supply service as well as the coverage of wastewater treatment service. The aim of the study is to describe the activities carried out in Italy by the ENEA Agency in order to define a new performance indicator for wastewater treatment service taking into account the appropriateness and efficiency of existing plants equipment and, consequently, evaluating economic incentives. The proposed procedure takes into account both wastewater treatment demand and quality of wastewater treatment service offered to citizens. Input data, provided by the National Institute of Statistics (ISTAT), were elaborated in order to define appropriate parameters, with a multi-criteria analysis being used to define the new performance indicator. The applicability of the proposed procedure was verified considering all the 8 Southern Italy and Island districts (Abruzzo, Molise, Campania, Apulia, Basilicata, Calabria, Sicily and Sardinia) involved in the programme. The obtained results show that the quality of municipal wastewater may influence the calculation of the incentive amount. The performance indicators defined in this work might be conveniently extended to other contexts similar to the assessed geographical area (Southern Italy and Islands). Copyright © 2013 Elsevier Ltd. All rights reserved.

Construction and application of an indicator system to assess the ergonomic performance of large and medium-sized construction companies.

PubMed

Bezerra, Isabela Xavier Barbalho; de Carvalho, Ricardo José Matos

2012-01-01

This article proposes a system of indicators to evaluate the performance of companies in ergonomics for buildings. The system was developed based primarily on studies related to the performance evaluation of the construction industry and on Brazilian standards of ergonomics and work safety and had also the contribution of national and international indicators related to ergonomics, work safety, quality, sustainability, quality of work life and to organizational behavior. The indicators were named, classified and their components were assigned to compose the theoretical model SIDECE--System of Performance Indicators in Ergonomics for Building Construction (as for the Portuguese acronym), serving the major goals of ergonomics: health, safety and workers' satisfaction and production efficiency. The SIDECE is being validated along with the building construction companies in the city of Natal, Brazil, whose practical results, deriving from the application of instruments to collect field data, are under process, to be presented on the occasion of the 18th World Congress on Ergonomics. It is intended that the SIDECE be used by building construction companies as a support tool for excellence management.

Achieving continuous improvement in laboratory organization through performance measurements: a seven-year experience.

PubMed

Salinas, Maria; López-Garrigós, Maite; Gutiérrez, Mercedes; Lugo, Javier; Sirvent, Jose Vicente; Uris, Joaquin

2010-01-01

Laboratory performance can be measured using a set of model key performance indicators (KPIs). The design and implementation of KPIs are important issues. KPI results from 7 years are reported and their implementation, monitoring, objectives, interventions, result reporting and delivery are analyzed. The KPIs of the entire laboratory process were obtained using Laboratory Information System (LIS) registers. These were collected automatically using a data warehouse application, spreadsheets and external quality program reports. Customer satisfaction was assessed using surveys. Nine model laboratory KPIs were proposed and measured. The results of some examples of KPIs used in our laboratory are reported. Their corrective measurements or the implementation of objectives led to improvement in the associated KPIs results. Measurement of laboratory performance using KPIs and a data warehouse application that continuously collects registers and calculates KPIs confirmed the reliability of indicators, indicator acceptability and usability for users, and continuous process improvement.

Interpretive Structural Model of Key Performance Indicators for Sustainable Maintenance Evaluatian in Rubber Industry

NASA Astrophysics Data System (ADS)

Amrina, E.; Yulianto, A.

2018-03-01

Sustainable maintenance is a new challenge for manufacturing companies to realize sustainable development. In this paper, an interpretive structural model is developed to evaluate sustainable maintenance in the rubber industry. The initial key performance indicators (KPIs) is identified and derived from literature and then validated by academic and industry experts. As a result, three factors of economic, social, and environmental dividing into a total of thirteen indicators are proposed as the KPIs for sustainable maintenance evaluation in rubber industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs consisting of three levels. The results show the economic factor is regarded as the basic factor, the social factor as the intermediate factor, while the environmental factor indicated to be the leading factor. Two indicators of social factor i.e. labor relationship, and training and education have both high driver and dependence power, thus categorized as the unstable indicators which need further attention. All the indicators of environmental factor and one indicator of social factor are indicated as the most influencing indicator. The interpretive structural model hoped can aid the rubber companies in evaluating sustainable maintenance performance.

Generation and evaluation of an indicator of the health system's performance in maternal and reproductive health in Colombia: An ecological study.

PubMed

Pinzón-Flórez, Carlos Eduardo; Fernandez-Niño, Julian Alfredo; Cardenas-Cardenas, Luz Mery; Díaz-Quijano, Diana Marcela; Ruiz-Rodriguez, Myriam; Reveiz, Ludovic; Arredondo-López, Armando

2017-01-01

To generate and evaluate an indicator of the health system's performance in the area of maternal and reproductive health in Colombia. An indicator was constructed based on variables related to the coverage and utilization of healthcare services for pregnant and reproductive-age women. A factor analysis was performed using a polychoric correlation matrix and the states were classified according to the indicator's score. A path analysis was used to evaluate the relationship between the indicator and social determinants, with the maternal mortality ratio as the response variable. The factor analysis indicates that only one principal factor exists, namely "coverage and utilization of maternal healthcare services" (eigenvalue 4.35). The indicator performed best in the states of Atlantic, Bogota, Boyaca, Cundinamarca, Huila, Risaralda and Santander (Q4). The poorest performance (Q1) occurred in Caqueta, Choco, La Guajira, Vichada, Guainia, Amazonas and Vaupes. The indicator's behavior was found to have an association with the unsatisfied basic needs index and women's education (β = -0.021; 95%CI -0031 to -0.01 and β 0.554; 95%CI 0.39 to 0.72, respectively). According to the path analysis, an inverse relationship exists between the proposed indicator and the behavior of the maternal mortality ratio (β = -49.34; 95%CI -77.7 to -20.9); performance was a mediating variable. The performance of the health system with respect to its management of access and coverage for maternal and reproductive health appears to function as a mediating variable between social determinants and maternal mortality in Colombia.

Structural and psychological empowerment climates, performance, and the moderating role of shared felt accountability: a managerial perspective.

PubMed

Wallace, J Craig; Johnson, Paul D; Mathe, Kimberly; Paul, Jeff

2011-07-01

The authors proposed and tested a model in which data were collected from managers (n = 539) at 116 corporate-owned quick service restaurants to assess the structural and psychological empowerment process as moderated by shared-felt accountability on indices of performance from a managerial perspective. The authors found that empowering leadership climate positively relates to psychological empowerment climate. In turn, psychological empowerment climate relates to performance only under conditions of high-felt accountability; it does not relate to performance under conditions of low-felt accountability. Overall, the present results indicate that the quick-service restaurant managers, who feel more empowered, operate restaurants that perform better than managers who feel less empowered, but only when those empowered managers also feel a high sense of accountability.

Identification and selection of Environmental Performance Indicators for sustainable port development.

PubMed

Puig, Martí; Wooldridge, Chris; Darbra, Rosa Mari

2014-04-15

In this paper an identification and selection of Environmental Performance Indicators (EPIs) in port areas has been conducted. A comprehensive inventory of existing EPIs in use in the seaport sector has been identified for monitoring performance of operational (e.g. dust, noise, dredging, and waste), managerial (e.g. certification, compliance, and complaints) and environmental condition (e.g. air, water, sediment and ecosystems). These indicators have been filtered against specific criteria and have been assessed and evaluated by port stakeholders in order to obtain a final set of indicators suitable to be implemented at EU level. A user friendly tool has been developed specifically to assist port authorities in calculating and reporting the proposed indicators. This study has drawn on major research projects to blend academic research with input from marine professionals in order to identify, select, evaluate and validate EPIs that are acceptable and feasible to the sector, and practicable in their application and implementation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Currency crisis indication by using ensembles of support vector machine classifiers

NASA Astrophysics Data System (ADS)

Ramli, Nor Azuana; Ismail, Mohd Tahir; Wooi, Hooy Chee

2014-07-01

There are many methods that had been experimented in the analysis of currency crisis. However, not all methods could provide accurate indications. This paper introduces an ensemble of classifiers by using Support Vector Machine that's never been applied in analyses involving currency crisis before with the aim of increasing the indication accuracy. The proposed ensemble classifiers' performances are measured using percentage of accuracy, root mean squared error (RMSE), area under the Receiver Operating Characteristics (ROC) curve and Type II error. The performances of an ensemble of Support Vector Machine classifiers are compared with the single Support Vector Machine classifier and both of classifiers are tested on the data set from 27 countries with 12 macroeconomic indicators for each country. From our analyses, the results show that the ensemble of Support Vector Machine classifiers outperforms single Support Vector Machine classifier on the problem involving indicating a currency crisis in terms of a range of standard measures for comparing the performance of classifiers.

Key performance indicators to benchmark hospital information systems - a delphi study.

PubMed

Hübner-Bloder, G; Ammenwerth, E

2009-01-01

To identify the key performance indicators for hospital information systems (HIS) that can be used for HIS benchmarking. A Delphi survey with one qualitative and two quantitative rounds. Forty-four HIS experts from health care IT practice and academia participated in all three rounds. Seventy-seven performance indicators were identified and organized into eight categories: technical quality, software quality, architecture and interface quality, IT vendor quality, IT support and IT department quality, workflow support quality, IT outcome quality, and IT costs. The highest ranked indicators are related to clinical workflow support and user satisfaction. Isolated technical indicators or cost indicators were not seen as useful. The experts favored an interdisciplinary group of all the stakeholders, led by hospital management, to conduct the HIS benchmarking. They proposed benchmarking activities both in regular (annual) intervals as well as at defined events (for example after IT introduction). Most of the experts stated that in their institutions no HIS benchmarking activities are being performed at the moment. In the context of IT governance, IT benchmarking is gaining importance in the healthcare area. The found indicators reflect the view of health care IT professionals and researchers. Research is needed to further validate and operationalize key performance indicators, to provide an IT benchmarking framework, and to provide open repositories for a comparison of the HIS benchmarks of different hospitals.

78 FR 52564 - Agency Information Collection Activities; Submission for OMB Review; Comment Request; Survey of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-23

... primary indicator of national progress in providing every working man and woman safe and healthful working...: Evaluate whether the proposed collection of information is necessary for the proper performance of the...

Evaluation of the power consumption of a high-speed parallel robot

NASA Astrophysics Data System (ADS)

Han, Gang; Xie, Fugui; Liu, Xin-Jun

2018-06-01

An inverse dynamic model of a high-speed parallel robot is established based on the virtual work principle. With this dynamic model, a new evaluation method is proposed to measure the power consumption of the robot during pick-and-place tasks. The power vector is extended in this method and used to represent the collinear velocity and acceleration of the moving platform. Afterward, several dynamic performance indices, which are homogenous and possess obvious physical meanings, are proposed. These indices can evaluate the power input and output transmissibility of the robot in a workspace. The distributions of the power input and output transmissibility of the high-speed parallel robot are derived with these indices and clearly illustrated in atlases. Furtherly, a low-power-consumption workspace is selected for the robot.

Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.

PubMed

Wang, Ping; Jiang, Jin-Yang; Li, Na; Luo, Han-Wu; Li, Fang; Cui, Shi-Gang

2017-07-01

It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.

Structural and Psychological Empowerment Climates, Performance, and the Moderating Role of Shared Felt Accountability: A Managerial Perspective

ERIC Educational Resources Information Center

Wallace, J. Craig; Johnson, Paul D.; Mathe, Kimberly; Paul, Jeff

2011-01-01

The authors proposed and tested a model in which data were collected from managers (n = 539) at 116 corporate-owned quick service restaurants to assess the structural and psychological empowerment process as moderated by shared-felt accountability on indices of performance from a managerial perspective. The authors found that empowering leadership…

Addressing social aspects associated with wastewater treatment facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Padilla-Rivera, Alejandro; Morgan-Sagastume, Juan Manuel; Noyola, Adalberto

In wastewater treatment facilities (WWTF), technical and financial aspects have been considered a priority, while other issues, such as social aspects, have not been evaluated seriously and there is not an accepted methodology for assessing it. In this work, a methodology focused on social concerns related to WWTF is presented. The methodology proposes the use of 25 indicators as a framework for measuring social performance to evaluate the progress in moving towards sustainability. The methodology was applied to test its applicability and effectiveness in two WWTF in Mexico (urban and rural). This evaluation helped define the key elements, stakeholders andmore » barriers in the facilities. In this context, the urban facility showed a better overall performance, a result that may be explained mainly by the better socioeconomic context of the urban municipality. Finally, the evaluation of social aspects using the semi-qualitative approach proposed in this work allows for a comparison between different facilities and for the identification of strengths and weakness, and it provides an alternative tool for achieving and improving wastewater management. - Highlights: • The methodology proposes 25 indicators as a framework for measuring social performance in wastewater treatment facilities. • The evaluation helped to define the key elements, stakeholders and barriers in the wastewater treatment facilities. • The evaluation of social aspects allows the identification of strengths and weakness for improving wastewater management. • It provides a social profile of the facility that highlights the best and worst performances.« less

Dynamic characteristics of oxygen consumption.

PubMed

Ye, Lin; Argha, Ahmadreza; Yu, Hairong; Celler, Branko G; Nguyen, Hung T; Su, Steven

2018-04-23

Previous studies have indicated that oxygen uptake ([Formula: see text]) is one of the most accurate indices for assessing the cardiorespiratory response to exercise. In most existing studies, the response of [Formula: see text] is often roughly modelled as a first-order system due to the inadequate stimulation and low signal to noise ratio. To overcome this difficulty, this paper proposes a novel nonparametric kernel-based method for the dynamic modelling of [Formula: see text] response to provide a more robust estimation. Twenty healthy non-athlete participants conducted treadmill exercises with monotonous stimulation (e.g., single step function as input). During the exercise, [Formula: see text] was measured and recorded by a popular portable gas analyser ([Formula: see text], COSMED). Based on the recorded data, a kernel-based estimation method was proposed to perform the nonparametric modelling of [Formula: see text]. For the proposed method, a properly selected kernel can represent the prior modelling information to reduce the dependence of comprehensive stimulations. Furthermore, due to the special elastic net formed by [Formula: see text] norm and kernelised [Formula: see text] norm, the estimations are smooth and concise. Additionally, the finite impulse response based nonparametric model which estimated by the proposed method can optimally select the order and fit better in terms of goodness-of-fit comparing to classical methods. Several kernels were introduced for the kernel-based [Formula: see text] modelling method. The results clearly indicated that the stable spline (SS) kernel has the best performance for [Formula: see text] modelling. Particularly, based on the experimental data from 20 participants, the estimated response from the proposed method with SS kernel was significantly better than the results from the benchmark method [i.e., prediction error method (PEM)] ([Formula: see text] vs [Formula: see text]). The proposed nonparametric modelling method is an effective method for the estimation of the impulse response of VO 2 -Speed system. Furthermore, the identified average nonparametric model method can dynamically predict [Formula: see text] response with acceptable accuracy during treadmill exercise.

A New Quantum Watermarking Based on Quantum Wavelet Transforms

NASA Astrophysics Data System (ADS)

Heidari, Shahrokh; Naseri, Mosayeb; Gheibi, Reza; Baghfalaki, Masoud; Rasoul Pourarian, Mohammad; Farouk, Ahmed

2017-06-01

Quantum watermarking is a technique to embed specific information, usually the owner’s identification, into quantum cover data such for copyright protection purposes. In this paper, a new scheme for quantum watermarking based on quantum wavelet transforms is proposed which includes scrambling, embedding and extracting procedures. The invisibility and robustness performances of the proposed watermarking method is confirmed by simulation technique. The invisibility of the scheme is examined by the peak-signal-to-noise ratio (PSNR) and the histogram calculation. Furthermore the robustness of the scheme is analyzed by the Bit Error Rate (BER) and the Correlation Two-Dimensional (Corr 2-D) calculation. The simulation results indicate that the proposed watermarking scheme indicate not only acceptable visual quality but also a good resistance against different types of attack. Supported by Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach.

PubMed

Varmazyar, Mohsen; Dehghanbaghi, Maryam; Afkhami, Mehdi

2016-10-01

Balanced Scorecard (BSC) is a strategic evaluation tool using both financial and non-financial indicators to determine the business performance of organizations or companies. In this paper, a new integrated approach based on the Balanced Scorecard (BSC) and multi-criteria decision making (MCDM) methods are proposed to evaluate the performance of research centers of research and technology organization (RTO) in Iran. Decision-Making Trial and Evaluation Laboratory (DEMATEL) are employed to reflect the interdependencies among BSC perspectives. Then, Analytic Network Process (ANP) is utilized to weight the indices influencing the considered problem. In the next step, we apply four MCDM methods including Additive Ratio Assessment (ARAS), Complex Proportional Assessment (COPRAS), Multi-Objective Optimization by Ratio Analysis (MOORA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking of alternatives. Finally, the utility interval technique is applied to combine the ranking results of MCDM methods. Weighted utility intervals are computed by constructing a correlation matrix between the ranking methods. A real case is presented to show the efficacy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Minimum detectable gas concentration performance evaluation method for gas leak infrared imaging detection systems.

PubMed

Zhang, Xu; Jin, Weiqi; Li, Jiakun; Wang, Xia; Li, Shuo

2017-04-01

Thermal imaging technology is an effective means of detecting hazardous gas leaks. Much attention has been paid to evaluation of the performance of gas leak infrared imaging detection systems due to several potential applications. The minimum resolvable temperature difference (MRTD) and the minimum detectable temperature difference (MDTD) are commonly used as the main indicators of thermal imaging system performance. This paper establishes a minimum detectable gas concentration (MDGC) performance evaluation model based on the definition and derivation of MDTD. We proposed the direct calculation and equivalent calculation method of MDGC based on the MDTD measurement system. We build an experimental MDGC measurement system, which indicates the MDGC model can describe the detection performance of a thermal imaging system to typical gases. The direct calculation, equivalent calculation, and direct measurement results are consistent. The MDGC and the minimum resolvable gas concentration (MRGC) model can effectively describe the performance of "detection" and "spatial detail resolution" of thermal imaging systems to gas leak, respectively, and constitute the main performance indicators of gas leak detection systems.

Parallel-vector unsymmetric Eigen-Solver on high performance computers

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.; Jiangning, Qin

1993-01-01

The popular QR algorithm for solving all eigenvalues of an unsymmetric matrix is reviewed. Among the basic components in the QR algorithm, it was concluded from this study, that the reduction of an unsymmetric matrix to a Hessenberg form (before applying the QR algorithm itself) can be done effectively by exploiting the vector speed and multiple processors offered by modern high-performance computers. Numerical examples of several test cases have indicated that the proposed parallel-vector algorithm for converting a given unsymmetric matrix to a Hessenberg form offers computational advantages over the existing algorithm. The time saving obtained by the proposed methods is increased as the problem size increased.

Simultaneous confidence bands for Cox regression from semiparametric random censorship.

PubMed

Mondal, Shoubhik; Subramanian, Sundarraman

2016-01-01

Cox regression is combined with semiparametric random censorship models to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined.

Indicators for Universal Health Coverage: can Kenya comply with the proposed post-2015 monitoring recommendations?

PubMed

Obare, Valerie; Brolan, Claire E; Hill, Peter S

2014-12-20

Universal Health Coverage (UHC), referring to access to healthcare without financial burden, has received renewed attention in global health spheres. UHC is a potential goal in the post-2015 development agenda. Monitoring of progress towards achieving UHC is thus critical at both country and global level, and a monitoring framework for UHC was proposed by a joint WHO/World Bank discussion paper in December 2013. The aim of this study was to determine the feasibility of the framework proposed by WHO/World Bank for global UHC monitoring framework in Kenya. The study utilised three documents--the joint WHO/World Bank UHC monitoring framework and its update, and the Bellagio meeting report sponsored by WHO and the Rockefeller Foundation--to conduct the research. These documents informed the list of potential indicators that were used to determine the feasibility of the framework. A purposive literature search was undertaken to identify key government policy documents and relevant scholarly articles. A desk review of the literature was undertaken to answer the research objectives of this study. Kenya has yet to establish an official policy on UHC that provides a clear mandate on the goals, targets and monitoring and evaluation of performance. However, a significant majority of Kenyans continue to have limited access to health services as well as limited financial risk protection. The country has the capacity to reasonably report on five out of the seven proposed UHC indicators. However, there was very limited capacity to report on the two service coverage indicators for the chronic condition and injuries (CCIs) interventions. Out of the potential tracer indicators (n = 27) for aggregate CCI-related measures, four tracer indicators were available. Moreover the country experiences some wider challenges that may impact on the implementation and feasibility of the WHO/World Bank framework. The proposed global framework for monitoring UHC will only be feasible in Kenya if systemic challenges are addressed. While the infrastructure for reporting the MDG related indicators is in place, Kenya will require continued international investment to extend its capacity to meet the data requirements of the proposed UHC monitoring framework, particularly for the CCI-related indicators.

A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability.

PubMed

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-03-20

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

PubMed Central

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-01-01

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments. PMID:23519351

Application of new type of distributed multimedia databases to networked electronic museum

NASA Astrophysics Data System (ADS)

Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

1999-01-01

Recently, various kinds of multimedia application systems have actively been developed based on the achievement of advanced high sped communication networks, computer processing technologies, and digital contents-handling technologies. Under this background, this paper proposed a new distributed multimedia database system which can effectively perform a new function of cooperative retrieval among distributed databases. The proposed system introduces a new concept of 'Retrieval manager' which functions as an intelligent controller so that the user can recognize a set of distributed databases as one logical database. The logical database dynamically generates and performs a preferred combination of retrieving parameters on the basis of both directory data and the system environment. Moreover, a concept of 'domain' is defined in the system as a managing unit of retrieval. The retrieval can effectively be performed by cooperation of processing among multiple domains. Communication language and protocols are also defined in the system. These are used in every action for communications in the system. A language interpreter in each machine translates a communication language into an internal language used in each machine. Using the language interpreter, internal processing, such internal modules as DBMS and user interface modules can freely be selected. A concept of 'content-set' is also introduced. A content-set is defined as a package of contents. Contents in the content-set are related to each other. The system handles a content-set as one object. The user terminal can effectively control the displaying of retrieved contents, referring to data indicating the relation of the contents in the content- set. In order to verify the function of the proposed system, a networked electronic museum was experimentally built. The results of this experiment indicate that the proposed system can effectively retrieve the objective contents under the control to a number of distributed domains. The result also indicate that the system can effectively work even if the system becomes large.

Fast and simultaneous determination of 12 polyphenols in apple peel and pulp by using chemometrics-assisted high-performance liquid chromatography with diode array detection.

PubMed

Wang, Tong; Wu, Hai-Long; Xie, Li-Xia; Zhu, Li; Liu, Zhi; Sun, Xiao-Dong; Xiao, Rong; Yu, Ru-Qin

2017-04-01

In this work, a smart chemometrics-enhanced strategy, high-performance liquid chromatography, and diode array detection coupled with second-order calibration method based on alternating trilinear decomposition algorithm was proposed to simultaneously quantify 12 polyphenols in different kinds of apple peel and pulp samples. The proposed strategy proved to be a powerful tool to solve the problems of coelution, unknown interferences, and chromatographic shifts in the process of high-performance liquid chromatography analysis, making it possible for the determination of 12 polyphenols in complex apple matrices within 10 min under simple conditions of elution. The average recoveries with standard deviations, and figures of merit including sensitivity, selectivity, limit of detection, and limit of quantitation were calculated to validate the accuracy of the proposed method. Compared to the quantitative analysis results from the classic high-performance liquid chromatography method, the statistical and graphical analysis showed that our proposed strategy obtained more reliable results. All results indicated that our proposed method used in the quantitative analysis of apple polyphenols was an accurate, fast, universal, simple, and green one, and it was expected to be developed as an attractive alternative method for simultaneous determination of multitargeted analytes in complex matrices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Load Index Metrics for an Optimized Management of Web Services: A Systematic Evaluation

PubMed Central

Souza, Paulo S. L.; Santana, Regina H. C.; Santana, Marcos J.; Zaluska, Ed; Faical, Bruno S.; Estrella, Julio C.

2013-01-01

The lack of precision to predict service performance through load indices may lead to wrong decisions regarding the use of web services, compromising service performance and raising platform cost unnecessarily. This paper presents experimental studies to qualify the behaviour of load indices in the web service context. The experiments consider three services that generate controlled and significant server demands, four levels of workload for each service and six distinct execution scenarios. The evaluation considers three relevant perspectives: the capability for representing recent workloads, the capability for predicting near-future performance and finally stability. Eight different load indices were analysed, including the JMX Average Time index (proposed in this paper) specifically designed to address the limitations of the other indices. A systematic approach is applied to evaluate the different load indices, considering a multiple linear regression model based on the stepwise-AIC method. The results show that the load indices studied represent the workload to some extent; however, in contrast to expectations, most of them do not exhibit a coherent correlation with service performance and this can result in stability problems. The JMX Average Time index is an exception, showing a stable behaviour which is tightly-coupled to the service runtime for all executions. Load indices are used to predict the service runtime and therefore their inappropriate use can lead to decisions that will impact negatively on both service performance and execution cost. PMID:23874776

Nonparametric estimation of median survival times with applications to multi-site or multi-center studies.

PubMed

Rahbar, Mohammad H; Choi, Sangbum; Hong, Chuan; Zhu, Liang; Jeon, Sangchoon; Gardiner, Joseph C

2018-01-01

We propose a nonparametric shrinkage estimator for the median survival times from several independent samples of right-censored data, which combines the samples and hypothesis information to improve the efficiency. We compare efficiency of the proposed shrinkage estimation procedure to unrestricted estimator and combined estimator through extensive simulation studies. Our results indicate that performance of these estimators depends on the strength of homogeneity of the medians. When homogeneity holds, the combined estimator is the most efficient estimator. However, it becomes inconsistent when homogeneity fails. On the other hand, the proposed shrinkage estimator remains efficient. Its efficiency decreases as the equality of the survival medians is deviated, but is expected to be as good as or equal to the unrestricted estimator. Our simulation studies also indicate that the proposed shrinkage estimator is robust to moderate levels of censoring. We demonstrate application of these methods to estimating median time for trauma patients to receive red blood cells in the Prospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study.

Nonparametric estimation of median survival times with applications to multi-site or multi-center studies

PubMed Central

Choi, Sangbum; Hong, Chuan; Zhu, Liang; Jeon, Sangchoon; Gardiner, Joseph C.

2018-01-01

We propose a nonparametric shrinkage estimator for the median survival times from several independent samples of right-censored data, which combines the samples and hypothesis information to improve the efficiency. We compare efficiency of the proposed shrinkage estimation procedure to unrestricted estimator and combined estimator through extensive simulation studies. Our results indicate that performance of these estimators depends on the strength of homogeneity of the medians. When homogeneity holds, the combined estimator is the most efficient estimator. However, it becomes inconsistent when homogeneity fails. On the other hand, the proposed shrinkage estimator remains efficient. Its efficiency decreases as the equality of the survival medians is deviated, but is expected to be as good as or equal to the unrestricted estimator. Our simulation studies also indicate that the proposed shrinkage estimator is robust to moderate levels of censoring. We demonstrate application of these methods to estimating median time for trauma patients to receive red blood cells in the Prospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study. PMID:29772007

Theoretical investigation of the upper and lower bounds of a generalized dimensionless bearing health indicator

NASA Astrophysics Data System (ADS)

Wang, Dong; Tsui, Kwok-Leung

2018-01-01

Bearing-supported shafts are widely used in various machines. Due to harsh working environments, bearing performance degrades over time. To prevent unexpected bearing failures and accidents, bearing performance degradation assessment becomes an emerging topic in recent years. Bearing performance degradation assessment aims to evaluate the current health condition of a bearing through a bearing health indicator. In the past years, many signal processing and data mining based methods were proposed to construct bearing health indicators. However, the upper and lower bounds of these bearing health indicators were not theoretically calculated and they strongly depended on historical bearing data including normal and failure data. Besides, most health indicators are dimensional, which connotes that these health indicators are prone to be affected by varying operating conditions, such as varying speeds and loads. In this paper, based on the principle of squared envelope analysis, we focus on theoretical investigation of bearing performance degradation assessment in the case of additive Gaussian noises, including distribution establishment of squared envelope, construction of a generalized dimensionless bearing health indicator, and mathematical calculation of the upper and lower bounds of the generalized dimensionless bearing health indicator. Then, analyses of simulated and real bearing run to failure data are used as two case studies to illustrate how the generalized dimensionless health indicator works and demonstrate its effectiveness in bearing performance degradation assessment. Results show that squared envelope follows a noncentral chi-square distribution and the upper and lower bounds of the generalized dimensionless health indicator can be mathematically established. Moreover, the generalized dimensionless health indicator is sensitive to an incipient bearing defect in the process of bearing performance degradation.

Solid waste management in primary healthcare centers: application of a facilitation tool 1

PubMed Central

Moreira, Ana Maria Maniero; Günther, Wanda Maria Risso

2016-01-01

Abstract Objectives: to propose a tool to facilitate diagnosis, formulation and evaluation of the Waste Management Plan in Primary Healthcare Centers and to present the results of the application in four selected units. Method: descriptive research, covering the stages of formulation /application of the proposed instrument and the evaluation of waste management performance at the units. Results: the tool consists in five forms; specific indicators of waste generation for outpatients healthcare units were proposed, and performance indicators that give scores for compliance with current legislation. In the studied units it is generated common waste (52-60%), infectious-sharps (31-42%) and recyclable (5-17%). The average rates of generation are: 0,09kg of total waste/outpatient assistance and 0,09kg of infectious-sharps waste/outpatient procedure. The compliance with regulations, initially 26-30%, then reached 30-38% a year later. Conclusion: the tool showed to be easy to use, bypassing the existence of a complex range of existing regulatory requirements, allowed to identify non-conformities, pointed out corrective measures and evaluated the performance of waste management. In this sense, it contributes to decision making and management practices relating to waste, tasks usually assigned to nurses. It is recommended that the tool be applied in similar healthcare units for comparative studies, and implementation of necessary adaptations for other medical services. PMID:27556874

An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System.

PubMed

Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

2017-02-20

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

The Analysis of the Strength, Distribution and Direction for the EEG Phase Synchronization by Musical Stimulus

NASA Astrophysics Data System (ADS)

Ogawa, Yutaro; Ikeda, Akira; Kotani, Kiyoshi; Jimbo, Yasuhiko

In this study, we propose the EEG phase synchronization analysis including not only the average strength of the synchronization but also the distribution and directions under the conditions that evoked emotion by musical stimuli. The experiment is performed with the two different musical stimuli that evoke happiness or sadness for 150 seconds. It is found that the average strength of synchronization indicates no difference between the right side and the left side of the frontal lobe during the happy stimulus, the distribution and directions indicate significant differences. Therefore, proposed analysis is useful for detecting emotional condition because it provides information that cannot be obtained only by the average strength of synchronization.

Compression of CCD raw images for digital still cameras

NASA Astrophysics Data System (ADS)

Sriram, Parthasarathy; Sudharsanan, Subramania

2005-03-01

Lossless compression of raw CCD images captured using color filter arrays has several benefits. The benefits include improved storage capacity, reduced memory bandwidth, and lower power consumption for digital still camera processors. The paper discusses the benefits in detail and proposes the use of a computationally efficient block adaptive scheme for lossless compression. Experimental results are provided that indicate that the scheme performs well for CCD raw images attaining compression factors of more than two. The block adaptive method also compares favorably with JPEG-LS. A discussion is provided indicating how the proposed lossless coding scheme can be incorporated into digital still camera processors enabling lower memory bandwidth and storage requirements.

A modeling of dynamic storage assignment for order picking in beverage warehousing with Drive-in Rack system

NASA Astrophysics Data System (ADS)

Hadi, M. Z.; Djatna, T.; Sugiarto

2018-04-01

This paper develops a dynamic storage assignment model to solve storage assignment problem (SAP) for beverages order picking in a drive-in rack warehousing system to determine the appropriate storage location and space for each beverage products dynamically so that the performance of the system can be improved. This study constructs a graph model to represent drive-in rack storage position then combine association rules mining, class-based storage policies and an arrangement rule algorithm to determine an appropriate storage location and arrangement of the product according to dynamic orders from customers. The performance of the proposed model is measured as rule adjacency accuracy, travel distance (for picking process) and probability a product become expiry using Last Come First Serve (LCFS) queue approach. Finally, the proposed model is implemented through computer simulation and compare the performance for different storage assignment methods as well. The result indicates that the proposed model outperforms other storage assignment methods.

A novel grounded to floating admittance converter with electronic control

NASA Astrophysics Data System (ADS)

Prasad, Dinesh; Ahmad, Javed; Srivastava, Mayank

2018-01-01

This article suggests a new grounded to floating admittance convertor employing only two voltage differencing transconductance amplifiers (VDTAs). The proposed circuit can convert any arbitrary grounded admittance into floating admittance with electronically controllable scaling factor. The presented converter enjoys the following beneficial: (1) no requirement of any additional passive element (2) scaling factor can be tuned electronically through bias currents of VDTAs (3) no matching constraint required (4) low values of active/passive sensitivity indexes and (5) excellent non ideal behavior that indicates no deviation in circuit behavior even under non ideal environment. Application of the proposed configuration in realization of floating resistor and floating capacitor has been presented and the workability of these floating elements has been confirmed by active filter design examples. SPICE simulations have been performed to demonstrate the performance of the proposed circuits.

Xenia Spacecraft Study

NASA Technical Reports Server (NTRS)

Hopkins, Randy

2009-01-01

This slide presentation reviews the proposed design for the Xenia mission spacecraft. The goal of this study is to perform a mission concept study for the mission. Included in this study are: the overall ground rules and assumptions (GR&A), a mission analysis, the configuration, the mass properties, the guidance, Navigation and control, the proposed avionics, the power system, the thermal protection system, the propulsion system, and the proposed structures. Conclusions from the study indicate that the observatory fits within the Falcon 9 mass and volume envelope for launching from Omelek, the pointing, slow slewing, and fast slewing requirements and the thermal requirements are met.

Executive Functions Do Not Mediate Prospective Relations between Indices of Physical Activity and Academic Performance: The Active Smarter Kids (ASK) Study.

PubMed

Aadland, Katrine N; Ommundsen, Yngvar; Aadland, Eivind; Brønnick, Kolbjørn S; Lervåg, Arne; Resaland, Geir K; Moe, Vegard F

2017-01-01

Changes in cognitive function induced by physical activity have been proposed as a mechanism for the link between physical activity and academic performance. The aim of this study was to investigate if executive function mediated the prospective relations between indices of physical activity and academic performance in a sample of 10-year-old Norwegian children. The study included 1,129 children participating in the Active Smarter Kids (ASK) trial, followed over 7 months. Structural equation modeling (SEM) with a latent variable of executive function (measuring inhibition, working memory, and cognitive flexibility) was used in the analyses. Predictors were objectively measured physical activity, time spent sedentary, aerobic fitness, and motor skills. Outcomes were performance on national tests of numeracy, reading, and English (as a second language). Generally, indices of physical activity did not predict executive function and academic performance. A modest mediation effect of executive function was observed for the relation between motor skills and academic performance. Trial registration: Clinicaltrials.gov registry, trial registration number: NCT02132494.

Executive Functions Do Not Mediate Prospective Relations between Indices of Physical Activity and Academic Performance: The Active Smarter Kids (ASK) Study

PubMed Central

Aadland, Katrine N.; Ommundsen, Yngvar; Aadland, Eivind; Brønnick, Kolbjørn S.; Lervåg, Arne; Resaland, Geir K.; Moe, Vegard F.

2017-01-01

Changes in cognitive function induced by physical activity have been proposed as a mechanism for the link between physical activity and academic performance. The aim of this study was to investigate if executive function mediated the prospective relations between indices of physical activity and academic performance in a sample of 10-year-old Norwegian children. The study included 1,129 children participating in the Active Smarter Kids (ASK) trial, followed over 7 months. Structural equation modeling (SEM) with a latent variable of executive function (measuring inhibition, working memory, and cognitive flexibility) was used in the analyses. Predictors were objectively measured physical activity, time spent sedentary, aerobic fitness, and motor skills. Outcomes were performance on national tests of numeracy, reading, and English (as a second language). Generally, indices of physical activity did not predict executive function and academic performance. A modest mediation effect of executive function was observed for the relation between motor skills and academic performance. Trial registration: Clinicaltrials.gov registry, trial registration number: NCT02132494. PMID:28706500

Test anxiety, perfectionism, goal orientation, and academic performance.

PubMed

Eum, KoUn; Rice, Kenneth G

2011-03-01

Dimensions of perfectionism and goal orientation have been reported to have differential relationships with test anxiety. However, the degree of inter-relationship between different dimensions of perfectionism, the 2 × 2 model of goal orientations proposed by Elliot and McGregor, cognitive test anxiety, and academic performance indicators is not known. Based on data from 134 university students, we conducted correlation and regression analyses to test associations between adaptive and maladaptive perfectionism, four types of goal orientations, cognitive test anxiety, and two indicators of academic performance: proximal cognitive performance on a word list recall test and distal academic performance in terms of grade point average. Cognitive test anxiety was inversely associated with both performance indicators, and positively associated with maladaptive perfectionism and avoidance goal orientations. Adaptive and maladaptive perfectionism accounted for significant variance in cognitive test anxiety after controlling for approach and avoidance goal orientations. Overall, nearly 50% of the variance in cognitive test anxiety could be attributed to gender, goal orientations, and perfectionism. Results suggested that students who are highly test anxious are likely to be women who endorse avoidance goal orientations and are maladaptively perfectionistic.

Multiscale multifractal DCCA and complexity behaviors of return intervals for Potts price model

NASA Astrophysics Data System (ADS)

Wang, Jie; Wang, Jun; Stanley, H. Eugene

2018-02-01

To investigate the characteristics of extreme events in financial markets and the corresponding return intervals among these events, we use a Potts dynamic system to construct a random financial time series model of the attitudes of market traders. We use multiscale multifractal detrended cross-correlation analysis (MM-DCCA) and Lempel-Ziv complexity (LZC) perform numerical research of the return intervals for two significant China's stock market indices and for the proposed model. The new MM-DCCA method is based on the Hurst surface and provides more interpretable cross-correlations of the dynamic mechanism between different return interval series. We scale the LZC method with different exponents to illustrate the complexity of return intervals in different scales. Empirical studies indicate that the proposed return intervals from the Potts system and the real stock market indices hold similar statistical properties.

A methodology for the evaluation of the human-bioclimatic performance of open spaces

NASA Astrophysics Data System (ADS)

Charalampopoulos, Ioannis; Tsiros, Ioannis; Chronopoulou-Sereli, Aik.; Matzarakis, Andreas

2017-05-01

The purpose of this paper is to present a simple methodology to improve the evaluation of the human-biometeorological benefits of open spaces. It is based on two groups of new indices using as basis the well-known PET index. This simple methodology along with the accompanying indices allows a qualitative and quantitative evaluation of the climatic behavior of the selected sites. The proposed methodology was applied in a human-biometeorology research in the city of Athens, Greece. The results of this study are in line with the results of other related studies indicating the considerable influence of the sky view factor (SVF), the existence of the vegetation and the building material on human-biometeorological conditions. The proposed methodology may provide new insights in the decision-making process related to urban open spaces' best configuration.

Simulation Modeling of Software Development Processes

NASA Technical Reports Server (NTRS)

Calavaro, G. F.; Basili, V. R.; Iazeolla, G.

1996-01-01

A simulation modeling approach is proposed for the prediction of software process productivity indices, such as cost and time-to-market, and the sensitivity analysis of such indices to changes in the organization parameters and user requirements. The approach uses a timed Petri Net and Object Oriented top-down model specification. Results demonstrate the model representativeness, and its usefulness in verifying process conformance to expectations, and in performing continuous process improvement and optimization.

Performance evaluation of MLP and RBF feed forward neural network for the recognition of off-line handwritten characters

NASA Astrophysics Data System (ADS)

Rishi, Rahul; Choudhary, Amit; Singh, Ravinder; Dhaka, Vijaypal Singh; Ahlawat, Savita; Rao, Mukta

2010-02-01

In this paper we propose a system for classification problem of handwritten text. The system is composed of preprocessing module, supervised learning module and recognition module on a very broad level. The preprocessing module digitizes the documents and extracts features (tangent values) for each character. The radial basis function network is used in the learning and recognition modules. The objective is to analyze and improve the performance of Multi Layer Perceptron (MLP) using RBF transfer functions over Logarithmic Sigmoid Function. The results of 35 experiments indicate that the Feed Forward MLP performs accurately and exhaustively with RBF. With the change in weight update mechanism and feature-drawn preprocessing module, the proposed system is competent with good recognition show.

An atlas-based multimodal registration method for 2D images with discrepancy structures.

PubMed

Lv, Wenchao; Chen, Houjin; Peng, Yahui; Li, Yanfeng; Li, Jupeng

2018-06-04

An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.

Analysis of navigation performance for the Earth Observing System (EOS) using the TDRSS Onboard Navigation System (TONS)

NASA Technical Reports Server (NTRS)

Elrod, B.; Kapoor, A.; Folta, David C.; Liu, K.

1991-01-01

Use of the Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) was proposed as an alternative to the Global Positioning System (GPS) for supporting the Earth Observing System (EOS) mission. The results are presented of EOS navigation performance evaluation with respect to TONS based orbit, time, and frequency determination (OD/TD/FD). Two TONS modes are considered: one uses scheduled TDRSS forward link service to derive one way Doppler tracking data for OD/FD support (TONS-I); the other uses an unscheduled navigation beacon service (proposed for Advanced TDRSS) to obtain pseudorange and Doppler data for OD/TD/FD support (TONS-II). Key objectives of the analysis were to evaluate nominal performance and potential sensitivities, such as suboptimal tracking geometry, tracking contact scheduling, and modeling parameter selection. OD/TD/FD performance predictions are presented based on covariance and simulation analyses. EOS navigation scenarios and the contributions of principal error sources impacting performance are also described. The results indicate that a TONS mode can be configured to meet current and proposed EOS position accuracy requirements of 100 and 50 m, respectively.

Evaluating transient performance of servo mechanisms by analysing stator current of PMSM

NASA Astrophysics Data System (ADS)

Zhang, Qing; Tan, Luyao; Xu, Guanghua

2018-02-01

Smooth running and rapid response are the desired performance goals for the transient motions of servo mechanisms. Because of the uncertain and unobservable transient behaviour of servo mechanisms, it is difficult to evaluate their transient performance. Under the effects of electromechanical coupling, the stator current signals of a permanent-magnet synchronous motor (PMSM) potentially contain the performance information regarding servo mechanisms in use. In this paper, a novel method based on analysing the stator current of the PMSM is proposed for quantifying the transient performance. First, a vector control model is constructed to simulate the stator current behaviour in the transient processes of consecutive speed changes, consecutive load changes, and intermittent start-stops. It is discovered that the amplitude and frequency of the stator current are modulated by the transient load torque and motor speed, respectively. The stator currents under different performance conditions are also simulated and compared. Then, the stator current is processed using a local means decomposition (LMD) algorithm to extract the instantaneous amplitude and instantaneous frequency. The sample entropy of the instantaneous amplitude, which reflects the complexity of the load torque variation, is calculated as a performance indicator of smooth running. The peak-to-peak value of the instantaneous frequency, which defines the range of the motor speed variation, is set as a performance indicator of rapid response. The proposed method is applied to both simulated data in an intermittent start-stops process and experimental data measured for a batch of servo turrets for turning lathes. The results show that the performance evaluations agree with the actual performance.

Developing micro-level urban ecosystem indicators for sustainability assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dizdaroglu, Didem, E-mail: dizdaroglu@bilkent.edu.tr

Sustainability assessment is increasingly being viewed as an important tool to aid in the shift towards sustainable urban ecosystems. An urban ecosystem is a dynamic system and requires regular monitoring and assessment through a set of relevant indicators. An indicator is a parameter which provides information about the state of the environment by producing a quantitative value. Indicator-based sustainability assessment needs to be considered on all spatial scales to provide efficient information of urban ecosystem sustainability. The detailed data is necessary to assess environmental change in urban ecosystems at local scale and easily transfer this information to the national andmore » global scales. This paper proposes a set of key micro-level urban ecosystem indicators for monitoring the sustainability of residential developments. The proposed indicator framework measures the sustainability performance of urban ecosystem in 3 main categories including: natural environment, built environment, and socio-economic environment which are made up of 9 sub-categories, consisting of 23 indicators. This paper also describes theoretical foundations for the selection of each indicator with reference to the literature [Turkish] Highlights: • As the impacts of environmental problems have multi-scale characteristics, sustainability assessment needs to be considered on all scales. • The detailed data is necessary to assess local environmental change in urban ecosystems to provide insights into the national and global scales. • This paper proposes a set of key micro-level urban ecosystem indicators for monitoring the sustainability of residential developments. • This paper also describes theoretical foundations for the selection of each indicator with reference to the literature.« less

Double-negative metamaterial for mobile phone application

NASA Astrophysics Data System (ADS)

Hossain, M. I.; Faruque, M. R. I.; Islam, M. T.

2017-01-01

In this paper, a new design and analysis of metamaterial and its applications to modern handset are presented. The proposed metamaterial unit-cell design consists of two connected square spiral structures, which leads to increase the effective media ratio. The finite instigation technique based on Computer Simulation Technology Microwave Studio is utilized in this investigation, and the measurement is taken in an anechoic chamber. A good agreement is observed among simulated and measured results. The results indicate that the proposed metamaterial can successfully cover cellular phone frequency bands. Moreover, the uses of proposed metamaterial in modern handset antennas are also analyzed. The results reveal that the proposed metamaterial attachment significantly reduces specific absorption rate values without reducing the antenna performances.

A non-iterative extension of the multivariate random effects meta-analysis.

PubMed

Makambi, Kepher H; Seung, Hyunuk

2015-01-01

Multivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative, have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.

Acquisition and production of skilled behavior in dynamic decision-making tasks. Semiannual Status Report M.S. Thesis - Georgia Inst. of Tech., Nov. 1992

NASA Technical Reports Server (NTRS)

Kirlik, Alex; Kossack, Merrick Frank

1993-01-01

This status report consists of a thesis entitled 'Ecological Task Analysis: A Method for Display Enhancements.' Previous use of various analysis processes for the purpose of display interface design or enhancement has run the risk of failing to improve user performance due to the analysis resulting in only a sequencial listing of user tasks. Adopting an ecological approach to performing the task analysis, however, may result in the necessary modeling of an unpredictable and variable task domain required to improve user performance. Kirlik has proposed an Ecological Task Analysis framework which is designed for this purpose. It is the purpose of this research to measure this framework's effectiveness at enhancing display interfaces in order to improve user performance. Following the proposed framework, an ecological task analysis of experienced users of a complex and dynamic laboratory task, Star Cruiser, was performed. Based on this analysis, display enhancements were proposed and implemented. An experiment was then conducted to compare this new version of Star Cruiser to the original. By measuring user performance at different tasks, it was determined that during early sessions, use of the enhanced display contributed to better user performance compared to that achieved using the original display. Furthermore, the results indicate that the enhancements proposed as a result of the ecological task analysis affected user performance differently depending on whether they are enhancements which aid in the selection of a possible action or in the performance of an action. Generalizations of these findings to larger, more complex systems were avoided since the analysis was only performed on this one particular system.

Urban local climate zone mapping and apply in urban environment study

NASA Astrophysics Data System (ADS)

He, Shan; Zhang, Yunwei; Zhang, Jili

2018-02-01

The city’s local climate zone (LCZ) was considered to be a powerful tool for urban climate mapping. But for cities in different countries and regions, the LCZ division methods and results were different, thus targeted researches should be performed. In the current work, a LCZ mapping method was proposed, which is convenient in operation and city planning oriented. In this proposed method, the local climate zoning types were adjusted firstly, according to the characteristics of Chinese city, that more tall buildings and high density. Then the classification method proposed by WUDAPT based on remote sensing data was performed on Xi’an city, as an example, for LCZ mapping. Combined with the city road network, a reasonable expression of the dividing results was provided, to adapt to the characteristics in city planning that land parcels are usually recognized as the basic unit. The proposed method was validated against the actual land use and construction data that surveyed in Xi’an, with results indicating the feasibility of the proposed method for urban LCZ mapping in China.

All-IP wireless sensor networks for real-time patient monitoring.

PubMed

Wang, Xiaonan; Le, Deguang; Cheng, Hongbin; Xie, Conghua

2014-12-01

This paper proposes the all-IP WSNs (wireless sensor networks) for real-time patient monitoring. In this paper, the all-IP WSN architecture based on gateway trees is proposed and the hierarchical address structure is presented. Based on this architecture, the all-IP WSN can perform routing without route discovery. Moreover, a mobile node is always identified by a home address and it does not need to be configured with a care-of address during the mobility process, so the communication disruption caused by the address change is avoided. Through the proposed scheme, a physician can monitor the vital signs of a patient at any time and at any places, and according to the IPv6 address he can also obtain the location information of the patient in order to perform effective and timely treatment. Finally, the proposed scheme is evaluated based on the simulation, and the simulation data indicate that the proposed scheme might effectively reduce the communication delay and control cost, and lower the packet loss rate. Copyright © 2014 Elsevier Inc. All rights reserved.

MIMO channel estimation and evaluation for airborne traffic surveillance in cellular networks

NASA Astrophysics Data System (ADS)

Vahidi, Vahid; Saberinia, Ebrahim

2018-01-01

A channel estimation (CE) procedure based on compressed sensing is proposed to estimate the multiple-input multiple-output sparse channel for traffic data transmission from drones to ground stations. The proposed procedure consists of an offline phase and a real-time phase. In the offline phase, a pilot arrangement method, which considers the interblock and block mutual coherence simultaneously, is proposed. The real-time phase contains three steps. At the first step, it obtains the priori estimate of the channel by block orthogonal matching pursuit; afterward, it utilizes that estimated channel to calculate the linear minimum mean square error of the received pilots. Finally, the block compressive sampling matching pursuit utilizes the enhanced received pilots to estimate the channel more accurately. The performance of the CE procedure is evaluated by simulating the transmission of traffic data through the communication channel and evaluating its fidelity for car detection after demodulation. Simulation results indicate that the proposed CE technique enhances the performance of the car detection in a traffic image considerably.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agalgaonkar, Yashodhan P.; Hammerstrom, Donald J.

The Pacific Northwest Smart Grid Demonstration (PNWSGD) was a smart grid technology performance evaluation project that included multiple U.S. states and cooperation from multiple electric utilities in the northwest region. One of the local objectives for the project was to achieve improved distribution system reliability. Toward this end, some PNWSGD utilities automated their distribution systems, including the application of fault detection, isolation, and restoration and advanced metering infrastructure. In light of this investment, a major challenge was to establish a correlation between implementation of these smart grid technologies and actual improvements of distribution system reliability. This paper proposes using Welch’smore » t-test to objectively determine and quantify whether distribution system reliability is improving over time. The proposed methodology is generic, and it can be implemented by any utility after calculation of the standard reliability indices. The effectiveness of the proposed hypothesis testing approach is demonstrated through comprehensive practical results. It is believed that wider adoption of the proposed approach can help utilities to evaluate a realistic long-term performance of smart grid technologies.« less

Verification of the Seismic Performance of a Rigidly Connected Modular System Depending on the Shape and Size of the Ceiling Bracket.

PubMed

Lee, Seungjae; Park, Jaeseong; Kwak, Euishin; Shon, Sudeok; Kang, Changhoon; Choi, Hosoon

2017-03-06

Modular systems have been mostly researched in relatively low-rise structures but, lately, their applications to mid- to high-rise structures began to be reviewed, and research interest in new modularization subjects has increased. The application of modular systems to mid- to high-rise structures requires the structural stability of the frame and connections that consist of units, and the evaluation of the stiffness of structures that are combined in units. However, the combination of general units causes loss of the cross-section of columns or beams, resulting in low seismic performance and hindering installation works in the field. In addition, the evaluation of a frame considering such a cross-sectional loss is not easy. Therefore, it is necessary to develop a joint that is stable and easy to install. In the study, a rigidly connected modular system was proposed as a moment-resisting frame for a unit modular system, and their joints were developed and their performances were compared. The proposed system changed the ceiling beam into a bracket type to fasten bolts. It can be merged with other seismic force-resisting systems. To verify the seismic performance of the proposed system, a cyclic loading test was conducted, and the rigidly connected joint performance and integrated behavior at the joint of modular units were investigated. From the experimental results, the maximum resisting force of the proposed connection exceeded the theoretical parameters, indicating that a rigid joint structural performance could be secured.

Proposal of an environmental performance index to assess solid waste treatment technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goulart Coelho, Hosmanny Mauro, E-mail: hosmanny@hotmail.com; Lange, Lisete Celina; Coelho, Lineker Max Goulart

2012-07-15

Highlights: Black-Right-Pointing-Pointer Proposal of a new concept in waste management: Cleaner Treatment. Black-Right-Pointing-Pointer Development of an index to assess quantitatively waste treatment technologies. Black-Right-Pointing-Pointer Delphi Method was carried out so as to define environmental indicators. Black-Right-Pointing-Pointer Environmental performance evaluation of waste-to-energy plants. - Abstract: Although the concern with sustainable development and environment protection has considerably grown in the last years it is noted that the majority of decision making models and tools are still either excessively tied to economic aspects or geared to the production process. Moreover, existing models focus on the priority steps of solid waste management, beyond wastemore » energy recovery and disposal. So, in order to help the lack of models and tools aiming at the waste treatment and final disposal, a new concept is proposed: the Cleaner Treatment, which is based on the Cleaner Production principles. This paper focuses on the development and validation of the Cleaner Treatment Index (CTI), to assess environmental performance of waste treatment technologies based on the Cleaner Treatment concept. The index is formed by aggregation (summation or product) of several indicators that consists in operational parameters. The weights of the indicator were established by Delphi Method and Brazilian Environmental Laws. In addition, sensitivity analyses were carried out comparing both aggregation methods. Finally, index validation was carried out by applying the CTI to 10 waste-to-energy plants data. From sensitivity analysis and validation results it is possible to infer that summation model is the most suitable aggregation method. For summation method, CTI results were superior to 0.5 (in a scale from 0 to 1) for most facilities evaluated. So, this study demonstrates that CTI is a simple and robust tool to assess and compare the environmental performance of different treatment plants being an excellent quantitative tool to support Cleaner Treatment implementation.« less

California Guide to Traffic Safety Education.

ERIC Educational Resources Information Center

California State Dept. of Education, Sacramento.

The guide proposes an elementary through high school program encompassing many aspects of traffic safety. Chapter 1 presents definitions, instructional goals, behavioral objectives, and K-6 traffic safety concepts coupled with student performance indicators. Various elements of program administration are covered in Chapter 2. Chapter 3 includes…

Education in the Scottish Parliament.

ERIC Educational Resources Information Center

Donn, Gari

2000-01-01

Reviews some educational issues arising during the first year of the new Scottish Parliament. Discusses facility problems and funding needs of small rural schools, debate over what constitutes standards and which performance indicators should be included in legislation, proposed accountability structures for local education authorities, and the…

Heredity Factors in Spatial Visualization.

ERIC Educational Resources Information Center

Vandenberg, S. G.

Spatial visualization is not yet clearly understood. Some researchers have concluded that two factors or abilities are involved, spatial orientation and spatial visualization. Different definitions and different tests have been proposed for these two abilities. Several studies indicate that women generally perform more poorly on spatial tests than…

Spatial Interpolation of Rain-field Dynamic Time-Space Evolution in Hong Kong

NASA Astrophysics Data System (ADS)

Liu, P.; Tung, Y. K.

2017-12-01

Accurate and reliable measurement and prediction of spatial and temporal distribution of rain-field over a wide range of scales are important topics in hydrologic investigations. In this study, geostatistical treatment of precipitation field is adopted. To estimate the rainfall intensity over a study domain with the sample values and the spatial structure from the radar data, the cumulative distribution functions (CDFs) at all unsampled locations were estimated. Indicator Kriging (IK) was used to estimate the exceedance probabilities for different pre-selected cutoff levels and a procedure was implemented for interpolating CDF values between the thresholds that were derived from the IK. Different interpolation schemes of the CDF were proposed and their influences on the performance were also investigated. The performance measures and visual comparison between the observed rain-field and the IK-based estimation suggested that the proposed method can provide fine results of estimation of indicator variables and is capable of producing realistic image.

Biclustering Learning of Trading Rules.

PubMed

Huang, Qinghua; Wang, Ting; Tao, Dacheng; Li, Xuelong

2015-10-01

Technical analysis with numerous indicators and patterns has been regarded as important evidence for making trading decisions in financial markets. However, it is extremely difficult for investors to find useful trading rules based on numerous technical indicators. This paper innovatively proposes the use of biclustering mining to discover effective technical trading patterns that contain a combination of indicators from historical financial data series. This is the first attempt to use biclustering algorithm on trading data. The mined patterns are regarded as trading rules and can be classified as three trading actions (i.e., the buy, the sell, and no-action signals) with respect to the maximum support. A modified K nearest neighborhood ( K -NN) method is applied to classification of trading days in the testing period. The proposed method [called biclustering algorithm and the K nearest neighbor (BIC- K -NN)] was implemented on four historical datasets and the average performance was compared with the conventional buy-and-hold strategy and three previously reported intelligent trading systems. Experimental results demonstrate that the proposed trading system outperforms its counterparts and will be useful for investment in various financial markets.

The role of institutional design and organizational practice for health financing performance and universal coverage.

PubMed

Mathauer, Inke; Carrin, Guy

2011-03-01

Many low- and middle income countries heavily rely on out-of-pocket health care expenditure. The challenge for these countries is how to modify their health financing system in order to achieve universal coverage. This paper proposes an analytical framework for undertaking a systematic review of a health financing system and its performance on the basis of which to identify adequate changes to enhance the move towards universal coverage. The distinctive characteristic of this framework is the focus on institutional design and organizational practice of health financing, on which health financing performance is contingent. Institutional design is understood as formal rules, namely legal and regulatory provisions relating to health financing; organizational practice refers to the way organizational actors implement and comply with these rules. Health financing performance is operationalized into nine generic health financing performance indicators. Inadequate performance can be caused by six types of bottlenecks in institutional design and organizational practice. Accordingly, six types of improvement measures are proposed to address these bottlenecks. The institutional design and organizational practice of a health financing system can be actively developed, modified or strengthened. By understanding the incentive environment within a health financing system, the potential impacts of the proposed changes can be anticipated. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Network coding multiuser scheme for indoor visible light communications

NASA Astrophysics Data System (ADS)

Zhang, Jiankun; Dang, Anhong

2017-12-01

Visible light communication (VLC) is a unique alternative for indoor data transfer and developing beyond point-to-point. However, for realizing high-capacity networks, VLC is facing challenges including the constrained bandwidth of the optical access point and random occlusion. A network coding scheme for VLC (NC-VLC) is proposed, with increased throughput and system robustness. Based on the Lambertian illumination model, theoretical decoding failure probability of the multiuser NC-VLC system is derived, and the impact of the system parameters on the performance is analyzed. Experiments demonstrate the proposed scheme successfully in the indoor multiuser scenario. These results indicate that the NC-VLC system shows a good performance under the link loss and random occlusion.

A Lifetime Maximization Relay Selection Scheme in Wireless Body Area Networks.

PubMed

Zhang, Yu; Zhang, Bing; Zhang, Shi

2017-06-02

Network Lifetime is one of the most important metrics in Wireless Body Area Networks (WBANs). In this paper, a relay selection scheme is proposed under the topology constrains specified in the IEEE 802.15.6 standard to maximize the lifetime of WBANs through formulating and solving an optimization problem where relay selection of each node acts as optimization variable. Considering the diversity of the sensor nodes in WBANs, the optimization problem takes not only energy consumption rate but also energy difference among sensor nodes into account to improve the network lifetime performance. Since it is Non-deterministic Polynomial-hard (NP-hard) and intractable, a heuristic solution is then designed to rapidly address the optimization. The simulation results indicate that the proposed relay selection scheme has better performance in network lifetime compared with existing algorithms and that the heuristic solution has low time complexity with only a negligible performance degradation gap from optimal value. Furthermore, we also conduct simulations based on a general WBAN model to comprehensively illustrate the advantages of the proposed algorithm. At the end of the evaluation, we validate the feasibility of our proposed scheme via an implementation discussion.

Wheelchair Propulsion Biomechanics in Junior Basketball Players: A Method for the Evaluation of the Efficacy of a Specific Training Program

PubMed Central

Bergamini, Elena; Morelli, Francesca; Marchetti, Flavia; Vannozzi, Giuseppe; Polidori, Lorenzo; Paradisi, Francesco; Traballesi, Marco; Cappozzo, Aurelio

2015-01-01

As participation in wheelchair sports increases, the need of quantitative assessment of biomechanical performance indicators and of sports- and population-specific training protocols has become central. The present study focuses on junior wheelchair basketball and aims at (i) proposing a method to identify biomechanical performance indicators of wheelchair propulsion using an instrumented in-field test and (ii) developing a training program specific for the considered population and assessing its efficacy using the proposed method. Twelve athletes (10 M, 2 F, age = 17.1 ± 2.7 years, years of practice = 4.5 ± 1.8) equipped with wheelchair- and wrist-mounted inertial sensors performed a 20-metre sprint test. Biomechanical parameters related to propulsion timing, progression force, and coordination were estimated from the measured accelerations and used in a regression model where the time to complete the test was set as dependent variable. Force- and coordination-related parameters accounted for 80% of the dependent variable variance. Based on these results, a training program was designed and administered for three months to six of the athletes (the others acting as control group). The biomechanical indicators proved to be effective in providing additional information about the wheelchair propulsion technique with respect to the final test outcome and demonstrated the efficacy of the developed program. PMID:26543852

Measuring performance in off-patent drug markets: a methodological framework and empirical evidence from twelve EU Member States.

PubMed

Kanavos, Panos

2014-11-01

This paper develops a methodological framework to help evaluate the performance of generic pharmaceutical policies post-patent expiry or after loss of exclusivity in non-tendering settings, comprising five indicators (generic availability, time delay to and speed of generic entry, number of generic competitors, price developments, and generic volume share evolution) and proposes a series of metrics to evaluate performance. The paper subsequently tests this framework across twelve EU Member States (MS) by using IMS data on 101 patent expired molecules over the 1998-2010 period. Results indicate that significant variation exists in generic market entry, price competition and generic penetration across the study countries. Size of a geographical market is not a predictor of generic market entry intensity or price decline. Regardless of geographic or product market size, many off patent molecules lack generic competitors two years after loss of exclusivity. The ranges in each of the five proposed indicators suggest, first, that there are numerous factors--including institutional ones--contributing to the success of generic entry, price decline and market penetration and, second, MS should seek a combination of supply and demand-side policies in order to maximise cost-savings from generics. Overall, there seems to be considerable potential for faster generic entry, uptake and greater generic competition, particularly for molecules at the lower end of the market. Copyright © 2014. Published by Elsevier Ireland Ltd.

Internal hydraulic loss in a seal-less centrifugal Gyro pump.

PubMed

Makinouchi, K; Ohara, Y; Sakuma, I; Damm, G; Mizuguchi, K; Jikuya, T; Takatani, S; Noon, G P; Nosé, Y

1994-01-01

A new index "loss factor Z" defined by Eq. 1 was introduced as the absolute expression of the mock loop resistance for testing a nonpulsatile pump. [formula: see text] where gamma is specific gravity of the fluid, g is the acceleration of gravity, delta P is total pressure head, and Q is flow. Z is expected to be constant, regardless of the pumping parameters. Z values obtained in the same mock loop but with different rotary blood pumps were almost identical and were defined as Z0. New methods of analysis of the flow-restrictive conditions of various rotary blood pumps are proposed in this paper: namely, differential loss factor delta Z, and loss factor sensitivity delta Z/delta A. The proposed Z-Q curves demonstrated better performance mapping than the conventional delta P-Q curves. Delta Z is the difference between the Z-Q curves of two different pumps. A is a design parameter of the pump; therefore delta Z/delta A is a quantitative expression of the effect of the design change on the hydraulic performance. These various indices were used to analyze the internal hydraulic loss of a centrifugal pump (Gyro pump). The relationship between its gap size (rotor casing) and hydraulic performance was assessed quantitatively by these indices. In this paper, the derivation processes and above-mentioned indices are described.

Pink shrimp as an indicator for restoration of everglades ecosystems

USGS Publications Warehouse

Browder, Joan A.; Robblee, M.B.

2009-01-01

The pink shrimp, Farfantepenaeus duorarum, familiar to most Floridians as either food or bait shrimp, is ubiquitous in South Florida coastal and offshore waters and is proposed as an indicator for assessing restoration of South Florida's southern estuaries: Florida Bay, Biscayne Bay, and the mangrove estuaries of the lower southwest coast. Relationships between pink shrimp and salinity have been determined in both field and laboratory studies. Salinity is directly relevant to restoration because the salinity regimes of South Florida estuaries, critical nursery habitat for the pink shrimp, will be altered by changes in the quantity, timing, and distribution of freshwater inflow planned as part of the Comprehensive Everglades Restoration Project (CERP). Here we suggest performance measures based on pink shrimp density (number per square meter) in the estuaries and propose a restoration assessment and scoring scheme using these performance measures that can readily be communicated to managers, policy makers, and the interested public. The pink shrimp is an appropriate restoration indicator because of its ecological as well as its economic importance and also because scientific interest in pink shrimp in South Florida has produced a wealth of information about the species and relatively long time series of data on both juveniles in estuarine nursery habitats and adults on the fishing grounds. We suggest research needs for improving the pink shrimp performance measure.

Noninvasive evaluation of mental stress using by a refined rough set technique based on biomedical signals.

PubMed

Liu, Tung-Kuan; Chen, Yeh-Peng; Hou, Zone-Yuan; Wang, Chao-Chih; Chou, Jyh-Horng

2014-06-01

Evaluating and treating of stress can substantially benefits to people with health problems. Currently, mental stress evaluated using medical questionnaires. However, the accuracy of this evaluation method is questionable because of variations caused by factors such as cultural differences and individual subjectivity. Measuring of biomedical signals is an effective method for estimating mental stress that enables this problem to be overcome. However, the relationship between the levels of mental stress and biomedical signals remain poorly understood. A refined rough set algorithm is proposed to determine the relationship between mental stress and biomedical signals, this algorithm combines rough set theory with a hybrid Taguchi-genetic algorithm, called RS-HTGA. Two parameters were used for evaluating the performance of the proposed RS-HTGA method. A dataset obtained from a practice clinic comprising 362 cases (196 male, 166 female) was adopted to evaluate the performance of the proposed approach. The empirical results indicate that the proposed method can achieve acceptable accuracy in medical practice. Furthermore, the proposed method was successfully used to identify the relationship between mental stress levels and bio-medical signals. In addition, the comparison between the RS-HTGA and a support vector machine (SVM) method indicated that both methods yield good results. The total averages for sensitivity, specificity, and precision were greater than 96%, the results indicated that both algorithms produced highly accurate results, but a substantial difference in discrimination existed among people with Phase 0 stress. The SVM algorithm shows 89% and the RS-HTGA shows 96%. Therefore, the RS-HTGA is superior to the SVM algorithm. The kappa test results for both algorithms were greater than 0.936, indicating high accuracy and consistency. The area under receiver operating characteristic curve for both the RS-HTGA and a SVM method were greater than 0.77, indicating a good discrimination capability. In this study, crucial attributes in stress evaluation were successfully recognized using biomedical signals, thereby enabling the conservation of medical resources and elucidating the mapping relationship between levels of mental stress and candidate attributes. In addition, we developed a prototype system for mental stress evaluation that can be used to provide benefits in medical practice. Copyright © 2014. Published by Elsevier B.V.

Test of a mediated performance-turnover relationship highlighting the moderating roles of visibility and reward contingency.

PubMed

Allen, D G; Griffeth, R W

2001-10-01

Despite the importance of understanding the conditions under which high performing employees are more likely or less likely to voluntarily leave an organization, the nature of the relationship between job performance and voluntary turnover has proven to be elusive. A model of the performance-turnover relationship that highlights important moderators and mediators is proposed and tested. Data consisted of organizational performance and turnover records and survey responses for 130 employees of a medical services organization. Results indicate that visibility and reward contingencies moderate performance relationships with alternatives and job satisfaction, respectively, and that performance may influence turnover through multiple mechanisms.

Measurement of signal use and vehicle turns as indication of driver cognition.

PubMed

Wallace, Bruce; Goubran, Rafik; Knoefel, Frank

2014-01-01

This paper uses data analytics to provide a method for the measurement of a key driving task, turn signal usage as a measure of an automatic over-learned cognitive function drivers. The paper augments previously reported more complex executive function cognition measures by proposing an algorithm that analyzes dashboard video to detect turn indicator use with 100% accuracy without any false positives. The paper proposes two algorithms that determine the actual turns made on a trip. The first through analysis of GPS location traces for the vehicle, locating 73% of the turns made with a very low false positive rate of 3%. A second algorithm uses GIS tools to retroactively create turn by turn directions. Fusion of GIS and GPS information raises performance to 77%. The paper presents the algorithm required to measure signal use for actual turns by realigning the 0.2Hz GPS data, 30fps video and GIS turn events. The result is a measure that can be tracked over time and changes in the driver's performance can result in alerts to the driver, caregivers or clinicians as indication of cognitive change. A lack of decline can also be shared as reassurance.

Study on coupled shock absorber system using four electromagnetic dampers

NASA Astrophysics Data System (ADS)

Fukumori, Y.; Hayashi, R.; Okano, H.; Suda, Y.; Nakano, K.

2016-09-01

Recently, the electromagnetic damper, which is composed of an electric motor, a ball screw, and a nut, was proposed. The electromagnetic damper has high responsiveness, controllability, and energy saving performance. It has been reported that it improved ride comfort and drivability. In addition, the authors have proposed a coupling method of two electromagnetic dampers. The method enables the characteristics of bouncing and rolling or pitching motion of a vehicle to be tuned independently. In this study, the authors increase the number of coupling of electromagnetic dampers from two to four, and propose a method to couple four electromagnetic dampers. The proposed method enables the characteristics of bouncing, rolling and pitching motion of a vehicle to be tuned independently. Basic experiments using proposed circuit and motors and numerical simulations of an automobile equipped with the proposed coupling electromagnetic damper are carried out. The results indicate the proposed method is effective.

Memetic computing through bio-inspired heuristics integration with sequential quadratic programming for nonlinear systems arising in different physical models.

PubMed

Raja, Muhammad Asif Zahoor; Kiani, Adiqa Kausar; Shehzad, Azam; Zameer, Aneela

2016-01-01

In this study, bio-inspired computing is exploited for solving system of nonlinear equations using variants of genetic algorithms (GAs) as a tool for global search method hybrid with sequential quadratic programming (SQP) for efficient local search. The fitness function is constructed by defining the error function for systems of nonlinear equations in mean square sense. The design parameters of mathematical models are trained by exploiting the competency of GAs and refinement are carried out by viable SQP algorithm. Twelve versions of the memetic approach GA-SQP are designed by taking a different set of reproduction routines in the optimization process. Performance of proposed variants is evaluated on six numerical problems comprising of system of nonlinear equations arising in the interval arithmetic benchmark model, kinematics, neurophysiology, combustion and chemical equilibrium. Comparative studies of the proposed results in terms of accuracy, convergence and complexity are performed with the help of statistical performance indices to establish the worth of the schemes. Accuracy and convergence of the memetic computing GA-SQP is found better in each case of the simulation study and effectiveness of the scheme is further established through results of statistics based on different performance indices for accuracy and complexity.

An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System

PubMed Central

Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

2017-01-01

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequency-domain and achieves computational complexity reduction. PMID:28230763

Modeling and comparative study of linear and nonlinear controllers for rotary inverted pendulum

NASA Astrophysics Data System (ADS)

Lima, Byron; Cajo, Ricardo; Huilcapi, Víctor; Agila, Wilton

2017-01-01

The rotary inverted pendulum (RIP) is a problem difficult to control, several studies have been conducted where different control techniques have been applied. Literature reports that, although problem is nonlinear, classical PID controllers presents appropriate performances when applied to the system. In this paper, a comparative study of the performances of linear and nonlinear PID structures is carried out. The control algorithms are evaluated in the RIP system, using indices of performance and power consumption, which allow the categorization of control strategies according to their performance. This article also presents the modeling system, which has been estimated some of the parameters involved in the RIP system, using computer-aided design tools (CAD) and experimental methods or techniques proposed by several authors attended. The results indicate a better performance of the nonlinear controller with an increase in the robustness and faster response than the linear controller.

On current contribution to Fronsdal equations

NASA Astrophysics Data System (ADS)

Misuna, N. G.

2018-03-01

We explore a local form of second-order Vasiliev equations proposed in [arxiv:arXiv:1706.03718] and obtain an explicit expression for quadratic corrections to bosonic Fronsdal equations, generated by gauge-invariant higher-spin currents. Our analysis is performed for general phase factor, and for the case of parity-invariant theory we find the agreement with expressions for cubic vertices available in the literature. This provides an additional indication that local frame proposed in [arxiv:arXiv:1706.03718] is the proper one.

Detecting representative data and generating synthetic samples to improve learning accuracy with imbalanced data sets.

PubMed

Li, Der-Chiang; Hu, Susan C; Lin, Liang-Sian; Yeh, Chun-Wu

2017-01-01

It is difficult for learning models to achieve high classification performances with imbalanced data sets, because with imbalanced data sets, when one of the classes is much larger than the others, most machine learning and data mining classifiers are overly influenced by the larger classes and ignore the smaller ones. As a result, the classification algorithms often have poor learning performances due to slow convergence in the smaller classes. To balance such data sets, this paper presents a strategy that involves reducing the sizes of the majority data and generating synthetic samples for the minority data. In the reducing operation, we use the box-and-whisker plot approach to exclude outliers and the Mega-Trend-Diffusion method to find representative data from the majority data. To generate the synthetic samples, we propose a counterintuitive hypothesis to find the distributed shape of the minority data, and then produce samples according to this distribution. Four real datasets were used to examine the performance of the proposed approach. We used paired t-tests to compare the Accuracy, G-mean, and F-measure scores of the proposed data pre-processing (PPDP) method merging in the D3C method (PPDP+D3C) with those of the one-sided selection (OSS), the well-known SMOTEBoost (SB) study, and the normal distribution-based oversampling (NDO) approach, and the proposed data pre-processing (PPDP) method. The results indicate that the classification performance of the proposed approach is better than that of above-mentioned methods.

Robust multiperson detection and tracking for mobile service and social robots.

PubMed

Li, Liyuan; Yan, Shuicheng; Yu, Xinguo; Tan, Yeow Kee; Li, Haizhou

2012-10-01

This paper proposes an efficient system which integrates multiple vision models for robust multiperson detection and tracking for mobile service and social robots in public environments. The core technique is a novel maximum likelihood (ML)-based algorithm which combines the multimodel detections in mean-shift tracking. First, a likelihood probability which integrates detections and similarity to local appearance is defined. Then, an expectation-maximization (EM)-like mean-shift algorithm is derived under the ML framework. In each iteration, the E-step estimates the associations to the detections, and the M-step locates the new position according to the ML criterion. To be robust to the complex crowded scenarios for multiperson tracking, an improved sequential strategy to perform the mean-shift tracking is proposed. Under this strategy, human objects are tracked sequentially according to their priority order. To balance the efficiency and robustness for real-time performance, at each stage, the first two objects from the list of the priority order are tested, and the one with the higher score is selected. The proposed method has been successfully implemented on real-world service and social robots. The vision system integrates stereo-based and histograms-of-oriented-gradients-based human detections, occlusion reasoning, and sequential mean-shift tracking. Various examples to show the advantages and robustness of the proposed system for multiperson tracking from mobile robots are presented. Quantitative evaluations on the performance of multiperson tracking are also performed. Experimental results indicate that significant improvements have been achieved by using the proposed method.

Assessment of school mathematics: Teachers' perceptions and practices

NASA Astrophysics Data System (ADS)

Pfannkuch, Maxine

2001-12-01

This is the first report of a proposed ten-year interval longitudinal study about teacher assessment practice in Auckland, New Zealand. Interviews with teachers of Year 3, 6, 8, 10, and 13 students are analysed. These interviews indicate that primary teachers are using a variety of assessment strategies in a mastery-based system. Their judgement of mathematical performance is dominated by the belief that all students must feel that they are achieving. The secondary teacher interviews indicate common use of alternative assessment strategies in non-examination classes. Judgement of student performance is benchmarked against national examinations. It is conjectured that an education system effect determines teachers' assessment practices.

Assessing the risk posed by natural hazards to infrastructures

NASA Astrophysics Data System (ADS)

Eidsvig, Unni Marie K.; Kristensen, Krister; Vidar Vangelsten, Bjørn

2017-03-01

This paper proposes a model for assessing the risk posed by natural hazards to infrastructures, with a focus on the indirect losses and loss of stability for the population relying on the infrastructure. The model prescribes a three-level analysis with increasing level of detail, moving from qualitative to quantitative analysis. The focus is on a methodology for semi-quantitative analyses to be performed at the second level. The purpose of this type of analysis is to perform a screening of the scenarios of natural hazards threatening the infrastructures, identifying the most critical scenarios and investigating the need for further analyses (third level). The proposed semi-quantitative methodology considers the frequency of the natural hazard, different aspects of vulnerability, including the physical vulnerability of the infrastructure itself, and the societal dependency on the infrastructure. An indicator-based approach is applied, ranking the indicators on a relative scale according to pre-defined ranking criteria. The proposed indicators, which characterise conditions that influence the probability of an infrastructure malfunctioning caused by a natural event, are defined as (1) robustness and buffer capacity, (2) level of protection, (3) quality/level of maintenance and renewal, (4) adaptability and quality of operational procedures and (5) transparency/complexity/degree of coupling. Further indicators describe conditions influencing the socio-economic consequences of the infrastructure malfunctioning, such as (1) redundancy and/or substitution, (2) cascading effects and dependencies, (3) preparedness and (4) early warning, emergency response and measures. The aggregated risk estimate is a combination of the semi-quantitative vulnerability indicators, as well as quantitative estimates of the frequency of the natural hazard, the potential duration of the infrastructure malfunctioning (e.g. depending on the required restoration effort) and the number of users of the infrastructure. Case studies for two Norwegian municipalities are presented for demonstration purposes, where risk posed by adverse weather and natural hazards to primary road, water supply and power networks is assessed. The application examples show that the proposed model provides a useful tool for screening of potential undesirable events, contributing to a targeted reduction of the risk.

Proposed biopsy performance benchmarks for MRI based on an audit of a large academic center.

PubMed

Sedora Román, Neda I; Mehta, Tejas S; Sharpe, Richard E; Slanetz, Priscilla J; Venkataraman, Shambhavi; Fein-Zachary, Valerie; Dialani, Vandana

2018-05-01

Performance benchmarks exist for mammography (MG); however, performance benchmarks for magnetic resonance imaging (MRI) are not yet fully developed. The purpose of our study was to perform an MRI audit based on established MG and screening MRI benchmarks and to review whether these benchmarks can be applied to an MRI practice. An IRB approved retrospective review of breast MRIs was performed at our center from 1/1/2011 through 12/31/13. For patients with biopsy recommendation, core biopsy and surgical pathology results were reviewed. The data were used to derive mean performance parameter values, including abnormal interpretation rate (AIR), positive predictive value (PPV), cancer detection rate (CDR), percentage of minimal cancers and axillary node negative cancers and compared with MG and screening MRI benchmarks. MRIs were also divided by screening and diagnostic indications to assess for differences in performance benchmarks amongst these two groups. Of the 2455 MRIs performed over 3-years, 1563 were performed for screening indications and 892 for diagnostic indications. With the exception of PPV2 for screening breast MRIs from 2011 to 2013, PPVs were met for our screening and diagnostic populations when compared to the MRI screening benchmarks established by the Breast Imaging Reporting and Data System (BI-RADS) 5 Atlas ® . AIR and CDR were lower for screening indications as compared to diagnostic indications. New MRI screening benchmarks can be used for screening MRI audits while the American College of Radiology (ACR) desirable goals for diagnostic MG can be used for diagnostic MRI audits. Our study corroborates established findings regarding differences in AIR and CDR amongst screening versus diagnostic indications. © 2017 Wiley Periodicals, Inc.

A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard.

PubMed

Azadmanjir, Zahra; Torabi, Mashallah; Safdari, Reza; Bayat, Maryam; Golmahi, Fatemeh

2015-08-01

management challenges of clinical laboratories are more complicated for educational hospital clinical laboratories. Managers can use tools of business intelligence (BI), such as information dashboards that provide the possibility of intelligent decision-making and problem solving about increasing income, reducing spending, utilization management and even improving quality. Critical phase of dashboard design is setting indicators and modeling causal relations between them. The paper describes the process of creating a map for laboratory dashboard. the study is one part of an action research that begins from 2012 by innovation initiative for implementing laboratory intelligent dashboard. Laboratories management problems were determined in educational hospitals by the brainstorming sessions. Then, with regard to the problems key performance indicators (KPIs) specified. the map of indicators designed in form of three layered. They have a causal relationship so that issues measured in the subsequent layers affect issues measured in the prime layers. the proposed indicator map can be the base of performance monitoring. However, these indicators can be modified to improve during iterations of dashboard designing process.

Similarity indices of meteo-climatic gauging stations: definition and comparison.

PubMed

Barca, Emanuele; Bruno, Delia Evelina; Passarella, Giuseppe

2016-07-01

Space-time dependencies among monitoring network stations have been investigated to detect and quantify similarity relationships among gauging stations. In this work, besides the well-known rank correlation index, two new similarity indices have been defined and applied to compute the similarity matrix related to the Apulian meteo-climatic monitoring network. The similarity matrices can be applied to address reliably the issue of missing data in space-time series. In order to establish the effectiveness of the similarity indices, a simulation test was then designed and performed with the aim of estimating missing monthly rainfall rates in a suitably selected gauging station. The results of the simulation allowed us to evaluate the effectiveness of the proposed similarity indices. Finally, the multiple imputation by chained equations method was used as a benchmark to have an absolute yardstick for comparing the outcomes of the test. In conclusion, the new proposed multiplicative similarity index resulted at least as reliable as the selected benchmark.

Proposing new indicators for glaucoma healthcare service.

PubMed

Liang, Yuan Bo; Zhang, Ye; Musch, David C; Congdon, Nathan

2017-01-01

Glaucoma is the first leading cause of irreversible blindness worldwide with increasing importance in public health. Indicators of glaucoma care quality as well as efficiency would benefit public health assessments, but are lacking. We propose three such indicators. First, the glaucoma coverage rate (GCR), which is the number of people known to have glaucoma divided by the total number of people with glaucoma as estimated from population-based studies multiplied by 100%. Second, the glaucoma detection rate (GDR), which is number of newly diagnosed glaucoma patients in one year divided by the population in a defined area in millions. Third, the glaucoma follow-up adherence rate (GFAR), calculated as the number of patients with glaucoma who visit eye care provider(s) at least once a year over the total number of patients with glaucoma in given eye care provider(s) in a specific period. Regularly tracking and reporting these three indicators may help to improve the healthcare system performance at national or regional levels.

Motor Skill Learning in Children.

ERIC Educational Resources Information Center

Gabbard, Carl P.

The purpose of this article is to briefly describe schema theory and indicate its relevance to early childhood development, with specific reference to children's acquisition of motor skills. Schema theory proposes an explanation of how individuals learn and perform a seemingly endless variety of movements. According to Schmidt (1975), goal…

A Multidimensional Analysis Tool for Visualizing Online Interactions

ERIC Educational Resources Information Center

Kim, Minjeong; Lee, Eunchul

2012-01-01

This study proposes and verifies the performance of an analysis tool for visualizing online interactions. A review of the most widely used methods for analyzing online interactions, including quantitative analysis, content analysis, and social network analysis methods, indicates these analysis methods have some limitations resulting from their…

77 FR 2510 - Proposed Information Collection; Comment Request; Quarterly Financial Report

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-18

... scope of collection. The current collection includes the Manufacturing, Mining, Wholesale Trade, Retail... economic indicator that also provides financial data essential to the estimation of key Government measures of national economic performance. The importance of this data collection is reflected by the granting...

Image segmentation on adaptive edge-preserving smoothing

NASA Astrophysics Data System (ADS)

He, Kun; Wang, Dan; Zheng, Xiuqing

2016-09-01

Nowadays, typical active contour models are widely applied in image segmentation. However, they perform badly on real images with inhomogeneous subregions. In order to overcome the drawback, this paper proposes an edge-preserving smoothing image segmentation algorithm. At first, this paper analyzes the edge-preserving smoothing conditions for image segmentation and constructs an edge-preserving smoothing model inspired by total variation. The proposed model has the ability to smooth inhomogeneous subregions and preserve edges. Then, a kind of clustering algorithm, which reasonably trades off edge-preserving and subregion-smoothing according to the local information, is employed to learn the edge-preserving parameter adaptively. At last, according to the confidence level of segmentation subregions, this paper constructs a smoothing convergence condition to avoid oversmoothing. Experiments indicate that the proposed algorithm has superior performance in precision, recall, and F-measure compared with other segmentation algorithms, and it is insensitive to noise and inhomogeneous-regions.

Cluster Correspondence Analysis.

PubMed

van de Velden, M; D'Enza, A Iodice; Palumbo, F

2017-03-01

A method is proposed that combines dimension reduction and cluster analysis for categorical data by simultaneously assigning individuals to clusters and optimal scaling values to categories in such a way that a single between variance maximization objective is achieved. In a unified framework, a brief review of alternative methods is provided and we show that the proposed method is equivalent to GROUPALS applied to categorical data. Performance of the methods is appraised by means of a simulation study. The results of the joint dimension reduction and clustering methods are compared with the so-called tandem approach, a sequential analysis of dimension reduction followed by cluster analysis. The tandem approach is conjectured to perform worse when variables are added that are unrelated to the cluster structure. Our simulation study confirms this conjecture. Moreover, the results of the simulation study indicate that the proposed method also consistently outperforms alternative joint dimension reduction and clustering methods.

Compressed learning and its applications to subcellular localization.

PubMed

Zheng, Zhong-Long; Guo, Li; Jia, Jiong; Xie, Chen-Mao; Zeng, Wen-Cai; Yang, Jie

2011-09-01

One of the main challenges faced by biological applications is to predict protein subcellular localization in automatic fashion accurately. To achieve this in these applications, a wide variety of machine learning methods have been proposed in recent years. Most of them focus on finding the optimal classification scheme and less of them take the simplifying the complexity of biological systems into account. Traditionally, such bio-data are analyzed by first performing a feature selection before classification. Motivated by CS (Compressed Sensing) theory, we propose the methodology which performs compressed learning with a sparseness criterion such that feature selection and dimension reduction are merged into one analysis. The proposed methodology decreases the complexity of biological system, while increases protein subcellular localization accuracy. Experimental results are quite encouraging, indicating that the aforementioned sparse methods are quite promising in dealing with complicated biological problems, such as predicting the subcellular localization of Gram-negative bacterial proteins.

A vertical handoff decision algorithm based on ARMA prediction model

NASA Astrophysics Data System (ADS)

Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan

2012-01-01

With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.

Compression of hyper-spectral images using an accelerated nonnegative tensor decomposition

NASA Astrophysics Data System (ADS)

Li, Jin; Liu, Zilong

2017-12-01

Nonnegative tensor Tucker decomposition (NTD) in a transform domain (e.g., 2D-DWT, etc) has been used in the compression of hyper-spectral images because it can remove redundancies between spectrum bands and also exploit spatial correlations of each band. However, the use of a NTD has a very high computational cost. In this paper, we propose a low complexity NTD-based compression method of hyper-spectral images. This method is based on a pair-wise multilevel grouping approach for the NTD to overcome its high computational cost. The proposed method has a low complexity under a slight decrease of the coding performance compared to conventional NTD. We experimentally confirm this method, which indicates that this method has the less processing time and keeps a better coding performance than the case that the NTD is not used. The proposed approach has a potential application in the loss compression of hyper-spectral or multi-spectral images

Interference Canceller Based on Cycle-and-Add Property for Single User Detection in DS-CDMA

NASA Astrophysics Data System (ADS)

Hettiarachchi, Ranga; Yokoyama, Mitsuo; Uehara, Hideyuki; Ohira, Takashi

In this paper, performance of a novel interference cancellation technique for the single user detection in a direct-sequence code-division multiple access (DS-CDMA) system has been investigated. This new algorithm is based on the Cycle-and-Add property of PN (Pseudorandom Noise) sequences and can be applied for both synchronous and asynchronous systems. The proposed strategy provides a simple method that can delete interference signals one by one in spite of the power levels of interferences. Therefore, it is possible to overcome the near-far problem (NFP) in a successive manner without using transmit power control (TPC) techniques. The validity of the proposed procedure is corroborated by computer simulations in additive white Gaussian noise (AWGN) and frequency-nonselective fading channels. Performance results indicate that the proposed receiver outperforms the conventional receiver and, in many cases, it does so with a considerable gain.

A High-Performance Genetic Algorithm: Using Traveling Salesman Problem as a Case

PubMed Central

Tsai, Chun-Wei; Tseng, Shih-Pang; Yang, Chu-Sing

2014-01-01

This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA. PMID:24892038

A high-performance genetic algorithm: using traveling salesman problem as a case.

PubMed

Tsai, Chun-Wei; Tseng, Shih-Pang; Chiang, Ming-Chao; Yang, Chu-Sing; Hong, Tzung-Pei

2014-01-01

This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA.

A near-optimal low complexity sensor fusion technique for accurate indoor localization based on ultrasound time of arrival measurements from low-quality sensors

NASA Astrophysics Data System (ADS)

Mitilineos, Stelios A.; Argyreas, Nick D.; Thomopoulos, Stelios C. A.

2009-05-01

A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance characteristics is established. A low-complexity but accurate sensor fusion and localization technique is then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and availability.

Constructing a strategy map for banking institutions with key performance indicators of the balanced scorecard.

PubMed

Wu, Hung-Yi

2012-08-01

This study presents a structural evaluation methodology to link key performance indicators (KPIs) into a strategy map of the balanced scorecard (BSC) for banking institutions. Corresponding with the four BSC perspectives (finance, customer, internal business process, and learning and growth), the most important evaluation indicators of banking performance are synthesized from the relevant literature and screened by a committee of experts. The Decision Making Trial and Evaluation Laboratory (DEMATEL) method, a multiple criteria analysis tool, is then employed to determine the causal relationships between the KPIs, to identify the critical central and influential factors, and to establish a visualized strategy map with logical links to improve banking performance. An empirical application is provided as an example. According to the expert evaluations, the three most essential KPIs for banking performance are customer satisfaction, sales performance, and customer retention rate. The DEMATEL results demonstrate a clear road map to assist management in prioritizing the performance indicators and in focusing attention on the strategy-related activities of the crucial indicators. According to the constructed strategy map, management could better invest limited resources in the areas that need improvement most. Although these strategy maps of the BSC are not universal, the research results show that the presented approach is an objective and feasible way to construct strategy maps more justifiably. The proposed framework can be applicable to institutions in other industries as well. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantitative performance targets by using balanced scorecard system: application to waste management and public administration.

PubMed

Mendes, Paula; Nunes, Luis Miguel; Teixeira, Margarida Ribau

2014-09-01

This article demonstrates how decision-makers can be guided in the process of defining performance target values in the balanced scorecard system. We apply a method based on sensitivity analysis with Monte Carlo simulation to the municipal solid waste management system in Loulé Municipality (Portugal). The method includes two steps: sensitivity analysis of performance indicators to identify those performance indicators with the highest impact on the balanced scorecard model outcomes; and sensitivity analysis of the target values for the previously identified performance indicators. Sensitivity analysis shows that four strategic objectives (IPP1: Comply with the national waste strategy; IPP4: Reduce nonrenewable resources and greenhouse gases; IPP5: Optimize the life-cycle of waste; and FP1: Meet and optimize the budget) alone contribute 99.7% of the variability in overall balanced scorecard value. Thus, these strategic objectives had a much stronger impact on the estimated balanced scorecard outcome than did others, with the IPP1 and the IPP4 accounting for over 55% and 22% of the variance in overall balanced scorecard value, respectively. The remaining performance indicators contribute only marginally. In addition, a change in the value of a single indicator's target value made the overall balanced scorecard value change by as much as 18%. This may lead to involuntarily biased decisions by organizations regarding performance target-setting, if not prevented with the help of methods such as that proposed and applied in this study. © The Author(s) 2014.

Deterministic and fuzzy-based methods to evaluate community resilience

NASA Astrophysics Data System (ADS)

Kammouh, Omar; Noori, Ali Zamani; Taurino, Veronica; Mahin, Stephen A.; Cimellaro, Gian Paolo

2018-04-01

Community resilience is becoming a growing concern for authorities and decision makers. This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework. PEOPLES is a multi-layered framework that defines community resilience using seven dimensions. Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator's performance. The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community. The second method exploits a knowledge-based fuzzy modeling for its implementation. This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis. The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community. The paper also introduces an open source online tool in which the first method is implemented. A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.

Performance analysis of hybrid vibrational energy harvesters with experimental verification

NASA Astrophysics Data System (ADS)

Sriramdas, Rammohan; Pratap, Rudra

2018-07-01

In the present work, performance indices for a hybrid energy harvester (HEH) that is composed of piezoelectric and electrodynamic or electromagnetic mechanisms of energy conversion are analyzed. Performance of a HEH is defined in terms of Q-normalized power factor and efficiency of conversion. They are observed to acutely depend on coupling strength or figures of merit in both piezoelectric and electrodynamic domains. The influence of figures of merit on the Q-normalized power factor, and the limits of conversion efficiency are explored. Based on the studies, a suitable range for figures of merit that would maximize both Q-normalized power factor and conversion efficiency in hybrid harvesters is proposed. The proposed idea is verified experimentally for the appropriate values of figures of merit and efficiencies by fabricating and testing four experimental models of the HEHs.

Physician performance assessment using a composite quality index.

PubMed

Liu, Kaibo; Jain, Shabnam; Shi, Jianjun

2013-07-10

Assessing physician performance is important for the purposes of measuring and improving quality of service and reducing healthcare delivery costs. In recent years, physician performance scorecards have been used to provide feedback on individual measures; however, one key challenge is how to develop a composite quality index that combines multiple measures for overall physician performance evaluation. A controversy arises over establishing appropriate weights to combine indicators in multiple dimensions, and cannot be easily resolved. In this study, we proposed a generic unsupervised learning approach to develop a single composite index for physician performance assessment by using non-negative principal component analysis. We developed a new algorithm named iterative quadratic programming to solve the numerical issue in the non-negative principal component analysis approach. We conducted real case studies to demonstrate the performance of the proposed method. We provided interpretations from both statistical and clinical perspectives to evaluate the developed composite ranking score in practice. In addition, we implemented the root cause assessment techniques to explain physician performance for improvement purposes. Copyright © 2012 John Wiley & Sons, Ltd.

A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

PubMed Central

Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Chen, Yiping; Zhuang, Zhaowen; Cheng, Yongqiang; Deng, Bin; Wang, Liandong; Zeng, Yonghu; Gao, Lei

2014-01-01

This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called “context-probability” estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good. PMID:24967605

Generation and evaluation of an indicator of the health system’s performance in maternal and reproductive health in Colombia: An ecological study

PubMed Central

Pinzón-Flórez, Carlos Eduardo; Fernandez-Niño, Julian Alfredo; Cardenas-Cardenas, Luz Mery; Díaz-Quijano, Diana Marcela; Ruiz-Rodriguez, Myriam; Reveiz, Ludovic; Arredondo-López, Armando

2017-01-01

Objective To generate and evaluate an indicator of the health system’s performance in the area of maternal and reproductive health in Colombia. Materials and methods An indicator was constructed based on variables related to the coverage and utilization of healthcare services for pregnant and reproductive-age women. A factor analysis was performed using a polychoric correlation matrix and the states were classified according to the indicator’s score. A path analysis was used to evaluate the relationship between the indicator and social determinants, with the maternal mortality ratio as the response variable. Results The factor analysis indicates that only one principal factor exists, namely "coverage and utilization of maternal healthcare services" (eigenvalue 4.35). The indicator performed best in the states of Atlantic, Bogota, Boyaca, Cundinamarca, Huila, Risaralda and Santander (Q4). The poorest performance (Q1) occurred in Caqueta, Choco, La Guajira, Vichada, Guainia, Amazonas and Vaupes. The indicator’s behavior was found to have an association with the unsatisfied basic needs index and women’s education (β = -0.021; 95%CI -0031 to -0.01 and β 0.554; 95%CI 0.39 to 0.72, respectively). According to the path analysis, an inverse relationship exists between the proposed indicator and the behavior of the maternal mortality ratio (β = -49.34; 95%CI -77.7 to -20.9); performance was a mediating variable. Discussion The performance of the health system with respect to its management of access and coverage for maternal and reproductive health appears to function as a mediating variable between social determinants and maternal mortality in Colombia. PMID:28854236

Automated Discrimination Method of Muscular and Subcutaneous Fat Layers Based on Tissue Elasticity

NASA Astrophysics Data System (ADS)

Inoue, Masahiro; Fukuda, Osamu; Tsubai, Masayoshi; Muraki, Satoshi; Okumura, Hiroshi; Arai, Kohei

Balance between human body composition, e.g. bones, muscles, and fat, is a major and basic indicator of personal health. Body composition analysis using ultrasound has been developed rapidly. However, interpretation of echo signal is conducted manually, and accuracy and confidence in interpretation requires experience. This paper proposes an automated discrimination method of tissue boundaries for measuring the thickness of subcutaneous fat and muscular layers. A portable one-dimensional ultrasound device was used in this study. The proposed method discriminated tissue boundaries based on tissue elasticity. Validity of the proposed method was evaluated in twenty-one subjects (twelve women, nine men; aged 20-70 yr) at three anatomical sites. Experimental results show that the proposed method can achieve considerably high discrimination performance.

Design of Planar Leaky Wave Antenna Fed by Substrate Integrated Waveguide Horn

NASA Astrophysics Data System (ADS)

Cai, Yang; Zhang, Yingsong; Qian, Zuping

2017-12-01

A metal strip grating leaky wave antenna (MSG-LWA) fed by substrate integrated waveguide (SIW) horn is proposed. The planar horn shares the same substrate with the MSG-LWA, which leads to a compact structure of the proposed antenna. Furthermore, through introducing phase-corrected structure by embedding metallized vias into the SIW horn, a nearly uniform phase distribution at the horn aperture is obtained, which effectively enhances the radiating performance of the MSG-LWA. Results indicate that the proposed antenna scans from -50° to -25° in the frequency band ranging from 15.3 GHz to 17.3 GHz. Besides, effectiveness of the proposed design is validated by comparing with a same MSG-LWA fed by an ideal rectangular waveguide.

Development of a method for the determination of iodine in spacecraft potable water

NASA Technical Reports Server (NTRS)

Whittle, G. P.

1972-01-01

A one-reagent indicator solution has been prepared for the analysis of iodine concentrations in the range of 0.5 to 12 mg/1 of I2 for use on the potable water proposed for the Skylab project. The indicator solution was formulated to contain the minimum concentrations of reagents for optimum analytical performance. Performance tests indicated that the reagent is stable for at least six months and is reliable for the determination of I2 under a variety of conditions of I(-) concentrations and sample temperatures. Visual estimations as low as 0.5 mg/1 were obtained without difficulty and the stability of the developed color allows visual determinations from 0.5 to 12 mg/1 of I2 with a relatively small error.

Vulvar intraepithelial neoplasia--the need for auditable measures of management.

PubMed

Athavale, Ram; Naik, R; Godfrey, K A; Cross, P; Hatem, M H; de Barros Lopes, A

2008-03-01

Surgical excision is currently the standard treatment for vulvar intraepithelial neoplasia (VIN). To date it has proved difficult to evaluate the management of VIN in reported series due to heterogeneity in datasets. The objective of this study was to justify standardised data presentation to permit comparison between series and facilitate determination of an optimal strategy for management of VIN. We propose auditable indicators of performance to benchmark management and outcomes. This may also enable definition of a surgical control arm for future novel therapy studies. Data from the Northern Gynaecological Oncology Centre (NGOC), UK on women with proven VIN diagnosed between 1989 and 2004 who attended the vulvar review clinic are presented and analysed alongside three large retrospective series by Jones et al. [Jones RW, Rowan DM, Stewart AW. Vulvar intraepithelial neoplasia: aspects of the natural history and outcome in 405 women. Obstet Gynecol 2005;106(6):1319-26], Herod et al. [Herod JJ, Shafi MI, Rollason TP, Jordan JA, Luesley DM. Vulvar intraepithelial neoplasia: long term follow up of treated and untreated women. Br J Obstet Gynaecol 1996;103(5):446-52], McNally et al. [McNally OM, Mulvany NJ, Pagano R, Quinn MA, Rome RM. VIN 3: a clinicopathologic review. Int J Gynecol Cancer 2002;12(5):490-5] against proposed performance indicators to illustrate the deficiencies in current data presentation. Demographics and indicators such as degree of pathological expertise, definition of early stromal invasion and use of International Society for the study of Vulvovaginal Disease (ISSVD) classification were usually well documented. The description of lesions including size and focality were not always documented, nor the proportion examined by co-specialists. Numbers of primary treatments were well described but the indications for treatment, completeness of excision and VIN subclassification were not. Subsequent surgical treatments were inconsistently reported including the pathological details and intervals between treatments. Symptomatology was not well reported. Information on follow-up intervals and duration of follow-up with an indication of patient compliance was inadequate. Outcome data on recurrence of VIN and progression to carcinoma (early stromal invasion or frankly invasive carcinoma) were included in all series. Consensus on the ideal management of VIN or evaluation of new strategies will prove impossible without standardised data presentation. We propose a number of performance indicators that will facilitate evaluation of future studies or series against the current benchmark of surgical treatment for VIN.

Integrating the acoustics of running speech into the pure tone audiogram: a step from audibility to intelligibility and disability.

PubMed

Corthals, Paul

2008-01-01

The aim of the present study is to construct a simple method for visualizing and quantifying the audibility of speech on the audiogram and to predict speech intelligibility. The proposed method involves a series of indices on the audiogram form reflecting the sound pressure level distribution of running speech. The indices that coincide with a patient's pure tone thresholds reflect speech audibility and give evidence of residual functional hearing capacity. Two validation studies were conducted among sensorineurally hearing-impaired participants (n = 56 and n = 37, respectively) to investigate the relation with speech recognition ability and hearing disability. The potential of the new audibility indices as predictors for speech reception thresholds is comparable to the predictive potential of the ANSI 1968 articulation index and the ANSI 1997 speech intelligibility index. The sum of indices or a weighted combination can explain considerable proportions of variance in speech reception results for sentences in quiet free field conditions. The proportions of variance that can be explained in questionnaire results on hearing disability are less, presumably because the threshold indices almost exclusively reflect message audibility and much less the psychosocial consequences of hearing deficits. The outcomes underpin the validity of the new audibility indexing system, even though the proposed method may be better suited for predicting relative performance across a set of conditions than for predicting absolute speech recognition performance. (c) 2007 S. Karger AG, Basel

An Alignment/Transfer Experiment with Low Socioeconomic Level Students.

ERIC Educational Resources Information Center

Elia, June Isaacs

1994-01-01

This study examined the amount of variance explained by alignment of testing to instruction among low socioeconomic level fourth graders, proposing two instructional alignment hypotheses. Results indicated that alignment had an unusually high effect. Low performing low socioeconomic level students achieved high success levels when conditions of…

48 CFR 52.222-46 - Evaluation of Compensation for Professional Employees.

Code of Federal Regulations, 2011 CFR

2011-10-01

... contract. The Government will evaluate the plan to assure that it reflects a sound management approach and... understanding of work to be performed and should indicate the capability of the proposed compensation structure... of sound management judgment and lack of understanding of the requirement. (c) The Government is...

75 FR 6641 - Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-10

...; subjective measures such as personality traits and values; and performance in a structured interview. All... individuals as judge advocates. A survey will allow the JAG Corps to assess whether certain traits and/or... surveys are the most accurate and cost-effective means for determining personality and value indicators of...

A Comparative Study of the Present and Ideal Roles of Communication Directors in Selected Business Organizations.

ERIC Educational Resources Information Center

Shatshat, Hussein M.

1980-01-01

Examines the role of communication directors involved in internal communication activities in business organizations. Indicates that directors perform a variety of roles ranging from journalistic to advisory/support work. Proposes a functional role involved in determining major policies for communications systems. (JMF)

A Proposed Roadmap for Inpatient Neurology Quality Indicators

PubMed Central

Douglas, Vanja C.; Josephson, S. Andrew

2011-01-01

Background/Purpose: In recent years, there has been increasing pressure to measure and report quality in health care. However, there has been little focus on quality measurement in the field of neurology for conditions other than stroke and transient ischemic attack. As the number of evidence-based treatments for neurological conditions grows, so will the demand to measure the quality of care delivered. The purpose of this study was to review essential components of hospital performance measures for neurological disease and propose potential quality indicators for commonly encountered inpatient neurological diagnoses. Methods: We determined the most common inpatient neurological diagnoses at a major tertiary care medical center by reviewing the billing database. We then searched PubMed and the National Guidelines Clearinghouse to identify treatment guidelines for these conditions. Guideline recommendations with class I/level A evidence were evaluated as possible quality indicators. Results: We found 94 guidelines for 14 inpatient neurological conditions other than stroke and transient ischemic attack. Of these, 36 guidelines contained at least 1 recommendation with class I evidence. Based on these, potential quality indicators for intracerebral hemorrhage, subarachnoid hemorrhage, pneumococcal meningitis, coma following cardiac arrest, encephalitis, Guillain-Barre syndrome, multiple sclerosis, and benign paroxysmal positional vertigo are proposed. Conclusions: There are several inpatient neurological conditions with treatments or diagnostic test routines supported by high levels of evidence that could be used in the future as quality indicators. PMID:23983832

Advanced general aviation engine/airframe integration study

NASA Technical Reports Server (NTRS)

Zmroczek, L. A.

1982-01-01

A comparison of the in-airframe performance and efficiency of the advanced engine concepts is presented. The results indicate that the proposed advanced engines can significantly improve the performance and economy of general aviation airplanes. The engine found to be most promising is the highly advanced version of a rotary combustion (Wankel) engine. The low weight and fuel consumption of this engine, as well as its small size, make it suited for aircraft use.

A new cooperative MIMO scheme based on SM for energy-efficiency improvement in wireless sensor network.

PubMed

Peng, Yuyang; Choi, Jaeho

2014-01-01

Improving the energy efficiency in wireless sensor networks (WSN) has attracted considerable attention nowadays. The multiple-input multiple-output (MIMO) technique has been proved as a good candidate for improving the energy efficiency, but it may not be feasible in WSN which is due to the size limitation of the sensor node. As a solution, the cooperative multiple-input multiple-output (CMIMO) technique overcomes this constraint and shows a dramatically good performance. In this paper, a new CMIMO scheme based on the spatial modulation (SM) technique named CMIMO-SM is proposed for energy-efficiency improvement. We first establish the system model of CMIMO-SM. Based on this model, the transmission approach is introduced graphically. In order to evaluate the performance of the proposed scheme, a detailed analysis in terms of energy consumption per bit of the proposed scheme compared with the conventional CMIMO is presented. Later, under the guide of this new scheme we extend our proposed CMIMO-SM to a multihop clustered WSN for further achieving energy efficiency by finding an optimal hop-length. Equidistant hop as the traditional scheme will be compared in this paper. Results from the simulations and numerical experiments indicate that by the use of the proposed scheme, significant savings in terms of total energy consumption can be achieved. Combining the proposed scheme with monitoring sensor node will provide a good performance in arbitrary deployed WSN such as forest fire detection system.

An approach to an acute emotional stress reference scale.

PubMed

Garzon-Rey, J M; Arza, A; de-la-Camara, C; Lobo, A; Armario, A; Aguilo, J

2017-06-16

The clinical diagnosis aims to identify the degree of affectation of the psycho-physical state of the patient as a guide to therapeutic intervention. In stress, the lack of a measurement tool based on a reference makes it difficult to quantitatively assess this degree of affectation. To define and perform a primary assessment of a standard reference in order to measure acute emotional stress from the markers identified as indicators of the degree. Psychometric tests and biochemical variables are, in general, the most accepted stress measurements by the scientific community. Each one of them probably responds to different and complementary processes related to the reaction to a stress stimulus. The reference that is proposed is a weighted mean of these indicators by assigning them relative weights in accordance with a principal components analysis. An experimental study was conducted on 40 healthy young people subjected to the psychosocial stress stimulus of the Trier Social Stress Test in order to perform a primary assessment and consistency check of the proposed reference. The proposed scale clearly differentiates between the induced relax and stress states. Accepting the subjectivity of the definition and the lack of a subsequent validation with new experimental data, the proposed standard differentiates between a relax state and an emotional stress state triggered by a moderate stress stimulus, as it is the Trier Social Stress Test. The scale is robust. Although the variations in the percentage composition slightly affect the score, but they do not affect the valid differentiation between states.

A psychometric assessment of Disturbances in Self-Organization symptom indicators for ICD-11 Complex PTSD using the International Trauma Questionnaire

PubMed Central

Shevlin, Mark; Hyland, Philip; Roberts, Neil P.; Bisson, Jonathan I.; Brewin, Chris R; Cloitre, Marylene

2018-01-01

ABSTRACT Background: Two ‘sibling disorders’ have been proposed for the 11th version of the International Classification of Diseases (ICD-11): Posttraumatic Stress Disorder (PTSD) and Complex PTSD (CPTSD). To date, no research has attempted to identify the optimal symptom indicators for the ‘Disturbances in Self-Organization’ (DSO) symptom cluster. Objective: The aim of the current study was to assess the psychometric performance of scores of 16 potential DSO symptom indicators from the International Trauma Questionnaire (ITQ). Criteria relating to score variability and their ability to discriminate were employed. Method: Participants (N = 1839) were a nationally representative household sample of non-institutionalized adults currently residing in the US. Item scores from the ITQ were examined in relation to basic criteria associated with interpretability, variability, homogeneity, and association with functional impairment. The performance of the DSO symptoms was also assessed using 1- and 2-parameter item response theory (IRT) models. Results: The distribution of responses for all DSO indicators met the criteria associated with interpretability, variability, homogeneity, and association with functional impairment. The 1-parameter graded response model was considered the best model and indicated that each set of indictors performed very similarly. Conclusions: The ITQ contains 16 DSO symptom indicators and they perform well in measuring their respective symptom cluster. There was no evidence that particular indicators were ‘better’ than others, and it was concluded that the indicators are essentially interchangeable. PMID:29372014

A psychometric assessment of Disturbances in Self-Organization symptom indicators for ICD-11 Complex PTSD using the International Trauma Questionnaire.

PubMed

Shevlin, Mark; Hyland, Philip; Roberts, Neil P; Bisson, Jonathan I; Brewin, Chris R; Cloitre, Marylene

2018-01-01

Background : Two 'sibling disorders' have been proposed for the 11 th version of the International Classification of Diseases (ICD-11): Posttraumatic Stress Disorder (PTSD) and Complex PTSD (CPTSD). To date, no research has attempted to identify the optimal symptom indicators for the 'Disturbances in Self-Organization' (DSO) symptom cluster. Objective : The aim of the current study was to assess the psychometric performance of scores of 16 potential DSO symptom indicators from the International Trauma Questionnaire (ITQ). Criteria relating to score variability and their ability to discriminate were employed. Method : Participants ( N  = 1839) were a nationally representative household sample of non-institutionalized adults currently residing in the US. Item scores from the ITQ were examined in relation to basic criteria associated with interpretability, variability, homogeneity, and association with functional impairment. The performance of the DSO symptoms was also assessed using 1- and 2-parameter item response theory (IRT) models. Results : The distribution of responses for all DSO indicators met the criteria associated with interpretability, variability, homogeneity, and association with functional impairment. The 1-parameter graded response model was considered the best model and indicated that each set of indictors performed very similarly. Conclusions : The ITQ contains 16 DSO symptom indicators and they perform well in measuring their respective symptom cluster. There was no evidence that particular indicators were 'better' than others, and it was concluded that the indicators are essentially interchangeable.

CD-Based Indices for Link Prediction in Complex Network.

PubMed

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks.

CD-Based Indices for Link Prediction in Complex Network

PubMed Central

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks. PMID:26752405

Verification of the Seismic Performance of a Rigidly Connected Modular System Depending on the Shape and Size of the Ceiling Bracket

PubMed Central

Lee, Seungjae; Park, Jaeseong; Kwak, Euishin; Shon, Sudeok; Kang, Changhoon; Choi, Hosoon

2017-01-01

Modular systems have been mostly researched in relatively low-rise structures but, lately, their applications to mid- to high-rise structures began to be reviewed, and research interest in new modularization subjects has increased. The application of modular systems to mid- to high-rise structures requires the structural stability of the frame and connections that consist of units, and the evaluation of the stiffness of structures that are combined in units. However, the combination of general units causes loss of the cross-section of columns or beams, resulting in low seismic performance and hindering installation works in the field. In addition, the evaluation of a frame considering such a cross-sectional loss is not easy. Therefore, it is necessary to develop a joint that is stable and easy to install. In the study, a rigidly connected modular system was proposed as a moment-resisting frame for a unit modular system, and their joints were developed and their performances were compared. The proposed system changed the ceiling beam into a bracket type to fasten bolts. It can be merged with other seismic force-resisting systems. To verify the seismic performance of the proposed system, a cyclic loading test was conducted, and the rigidly connected joint performance and integrated behavior at the joint of modular units were investigated. From the experimental results, the maximum resisting force of the proposed connection exceeded the theoretical parameters, indicating that a rigid joint structural performance could be secured. PMID:28772622

PET-CT image fusion using random forest and à-trous wavelet transform.

PubMed

Seal, Ayan; Bhattacharjee, Debotosh; Nasipuri, Mita; Rodríguez-Esparragón, Dionisio; Menasalvas, Ernestina; Gonzalo-Martin, Consuelo

2018-03-01

New image fusion rules for multimodal medical images are proposed in this work. Image fusion rules are defined by random forest learning algorithm and a translation-invariant à-trous wavelet transform (AWT). The proposed method is threefold. First, source images are decomposed into approximation and detail coefficients using AWT. Second, random forest is used to choose pixels from the approximation and detail coefficients for forming the approximation and detail coefficients of the fused image. Lastly, inverse AWT is applied to reconstruct fused image. All experiments have been performed on 198 slices of both computed tomography and positron emission tomography images of a patient. A traditional fusion method based on Mallat wavelet transform has also been implemented on these slices. A new image fusion performance measure along with 4 existing measures has been presented, which helps to compare the performance of 2 pixel level fusion methods. The experimental results clearly indicate that the proposed method outperforms the traditional method in terms of visual and quantitative qualities and the new measure is meaningful. Copyright © 2017 John Wiley & Sons, Ltd.

An Effective 3D Shape Descriptor for Object Recognition with RGB-D Sensors

PubMed Central

Liu, Zhong; Zhao, Changchen; Wu, Xingming; Chen, Weihai

2017-01-01

RGB-D sensors have been widely used in various areas of computer vision and graphics. A good descriptor will effectively improve the performance of operation. This article further analyzes the recognition performance of shape features extracted from multi-modality source data using RGB-D sensors. A hybrid shape descriptor is proposed as a representation of objects for recognition. We first extracted five 2D shape features from contour-based images and five 3D shape features over point cloud data to capture the global and local shape characteristics of an object. The recognition performance was tested for category recognition and instance recognition. Experimental results show that the proposed shape descriptor outperforms several common global-to-global shape descriptors and is comparable to some partial-to-global shape descriptors that achieved the best accuracies in category and instance recognition. Contribution of partial features and computational complexity were also analyzed. The results indicate that the proposed shape features are strong cues for object recognition and can be combined with other features to boost accuracy. PMID:28245553

An Adaptive Supervisory Sliding Fuzzy Cerebellar Model Articulation Controller for Sensorless Vector-Controlled Induction Motor Drive Systems

PubMed Central

Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang

2015-01-01

This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes. PMID:25815450

An adaptive supervisory sliding fuzzy cerebellar model articulation controller for sensorless vector-controlled induction motor drive systems.

PubMed

Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang

2015-03-25

This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes--the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC--were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.

Optimizing Input/Output Using Adaptive File System Policies

NASA Technical Reports Server (NTRS)

Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

1996-01-01

Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

Design of an unified chassis controller for rollover prevention, manoeuvrability and lateral stability

NASA Astrophysics Data System (ADS)

Yoon, Jangyeol; Yim, Seongjin; Cho, Wanki; Koo, Bongyeong; Yi, Kyongsu

2010-11-01

This paper describes a unified chassis control (UCC) strategy to prevent vehicle rollover and improve both manoeuvrability and lateral stability. Since previous researches on rollover prevention are only focused on the reduction of lateral acceleration, the manoeuvrability and lateral stability cannot be guaranteed. For this reason, it is necessary to design a UCC controller to prevent rollover and improve lateral stability by integrating electronic stability control, active front steering and continuous damping control. This integration is performed through switching among several control modes and a simulation is performed to validate the proposed method. Simulation results indicate that a significant improvement in rollover prevention, manoeuvrability and lateral stability can be expected from the proposed UCC system.

Optimum detection of tones transmitted by a spacecraft

NASA Technical Reports Server (NTRS)

Simon, M. K.; Shihabi, M. M.; Moon, T.

1995-01-01

The performance of a scheme proposed for automated routine monitoring of deep-space missions is presented. The scheme uses four different tones (sinusoids) transmitted from the spacecraft (S/C) to a ground station with the positive identification of each of them used to indicate different states of the S/C. Performance is measured in terms of detection probability versus false alarm probability with detection signal-to-noise ratio as a parameter. The cases where the phase of the received tone is unknown and where both the phase and frequency of the received tone are unknown are treated separately. The decision rules proposed for detecting the tones are formulated from average-likelihood ratio and maximum-likelihood ratio tests, the former resulting in optimum receiver structures.

Partial fingerprint identification algorithm based on the modified generalized Hough transform on mobile device

NASA Astrophysics Data System (ADS)

Qin, Jin; Tang, Siqi; Han, Congying; Guo, Tiande

2018-04-01

Partial fingerprint identification technology which is mainly used in device with small sensor area like cellphone, U disk and computer, has taken more attention in recent years with its unique advantages. However, owing to the lack of sufficient minutiae points, the conventional method do not perform well in the above situation. We propose a new fingerprint matching technique which utilizes ridges as features to deal with partial fingerprint images and combines the modified generalized Hough transform and scoring strategy based on machine learning. The algorithm can effectively meet the real-time and space-saving requirements of the resource constrained devices. Experiments on in-house database indicate that the proposed algorithm have an excellent performance.

A 7.4 ps FPGA-Based TDC with a 1024-Unit Measurement Matrix

PubMed Central

Zhang, Min; Wang, Hai; Liu, Yan

2017-01-01

In this paper, a high-resolution time-to-digital converter (TDC) based on a field programmable gate array (FPGA) device is proposed and tested. During the implementation, a new architecture of TDC is proposed which consists of a measurement matrix with 1024 units. The utilization of routing resources as the delay elements distinguishes the proposed design from other existing designs, which contributes most to the device insensitivity to variations of temperature and voltage. Experimental results suggest that the measurement resolution is 7.4 ps, and the INL (integral nonlinearity) and DNL (differential nonlinearity) are 11.6 ps and 5.5 ps, which indicates that the proposed TDC offers high performance among the available TDCs. Benefitting from the FPGA platform, the proposed TDC has superiorities in easy implementation, low cost, and short development time. PMID:28420121

A 7.4 ps FPGA-Based TDC with a 1024-Unit Measurement Matrix.

PubMed

Zhang, Min; Wang, Hai; Liu, Yan

2017-04-14

In this paper, a high-resolution time-to-digital converter (TDC) based on a field programmable gate array (FPGA) device is proposed and tested. During the implementation, a new architecture of TDC is proposed which consists of a measurement matrix with 1024 units. The utilization of routing resources as the delay elements distinguishes the proposed design from other existing designs, which contributes most to the device insensitivity to variations of temperature and voltage. Experimental results suggest that the measurement resolution is 7.4 ps, and the INL (integral nonlinearity) and DNL (differential nonlinearity) are 11.6 ps and 5.5 ps, which indicates that the proposed TDC offers high performance among the available TDCs. Benefitting from the FPGA platform, the proposed TDC has superiorities in easy implementation, low cost, and short development time.

Adaptive optics for confocal laser scanning microscopy with adjustable pinhole

NASA Astrophysics Data System (ADS)

Yoo, Han Woong; van Royen, Martin E.; van Cappellen, Wiggert A.; Houtsmuller, Adriaan B.; Verhaegen, Michel; Schitter, Georg

2016-04-01

The pinhole plays an important role in confocal laser scanning microscopy (CLSM) for adaptive optics (AO) as well as in imaging, where the size of the pinhole denotes a trade-off between out-of-focus rejection and wavefront distortion. This contribution proposes an AO system for a commercial CLSM with an adjustable square pinhole to cope with such a trade-off. The proposed adjustable pinhole enables to calibrate the AO system and to evaluate the imaging performance. Experimental results with fluorescence beads on the coverslip and at a depth of 40 μm in the human hepatocellular carcinoma cell spheroid demonstrate that the proposed AO system can improve the image quality by the proposed calibration method. The proposed pinhole intensity ratio also indicates the image improvement by the AO correction in intensity as well as resolution.

Utilizing Chinese Admission Records for MACE Prediction of Acute Coronary Syndrome

PubMed Central

Hu, Danqing; Huang, Zhengxing; Chan, Tak-Ming; Dong, Wei; Lu, Xudong; Duan, Huilong

2016-01-01

Background: Clinical major adverse cardiovascular event (MACE) prediction of acute coronary syndrome (ACS) is important for a number of applications including physician decision support, quality of care assessment, and efficient healthcare service delivery on ACS patients. Admission records, as typical media to contain clinical information of patients at the early stage of their hospitalizations, provide significant potential to be explored for MACE prediction in a proactive manner. Methods: We propose a hybrid approach for MACE prediction by utilizing a large volume of admission records. Firstly, both a rule-based medical language processing method and a machine learning method (i.e., Conditional Random Fields (CRFs)) are developed to extract essential patient features from unstructured admission records. After that, state-of-the-art supervised machine learning algorithms are applied to construct MACE prediction models from data. Results: We comparatively evaluate the performance of the proposed approach on a real clinical dataset consisting of 2930 ACS patient samples collected from a Chinese hospital. Our best model achieved 72% AUC in MACE prediction. In comparison of the performance between our models and two well-known ACS risk score tools, i.e., GRACE and TIMI, our learned models obtain better performances with a significant margin. Conclusions: Experimental results reveal that our approach can obtain competitive performance in MACE prediction. The comparison of classifiers indicates the proposed approach has a competitive generality with datasets extracted by different feature extraction methods. Furthermore, our MACE prediction model obtained a significant improvement by comparison with both GRACE and TIMI. It indicates that using admission records can effectively provide MACE prediction service for ACS patients at the early stage of their hospitalizations. PMID:27649220

Functioning: the third health indicator in the health system and the key indicator for rehabilitation.

PubMed

Stucki, Gerold; Bickenbach, Jerome

2017-02-01

In this methodological note on applying the ICF in rehabilitation, we introduce functioning as the third health indicator complementing the established indicators mortality and morbidity. Together, these three provide a complete set of indicators for monitoring the performance of health strategies in health systems. When applying functioning as the third health indicator across the five health strategies, it is fundamental to distinguish between biological health and lived health. For rehabilitation, functioning is the key indicator. Since we can now code mortality and morbidity data with the ICD, and functioning data with the ICF, and since given current plans to including functioning properties in the proposed ICD-11 revision, we should in the future be able to report on all three health indicators.

A Research on Performance Measurement Based on Economic Valued-Added Comprehensive Scorecard

NASA Astrophysics Data System (ADS)

Chen, Qin; Zhang, Xiaomei

With the development of economic, the traditional performance mainly rely on financial indicators could not satisfy the need of work. In order to make the performance measurement taking the best services for business goals, this paper proposed Economic Valued-Added Comprehensive Scorecard based on research of shortages and advantages of EVA and BSC .We used Analytic Hierarchy Process to build matrix to solve the weighting of EVA Comprehensive Scorecard. At last we could find the most influence factors for enterprise value forming the weighting.

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

Practical performance of real-time shot-noise measurement in continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Wang, Tao; Huang, Peng; Zhou, Yingming; Liu, Weiqi; Zeng, Guihua

2018-01-01

In a practical continuous-variable quantum key distribution (CVQKD) system, real-time shot-noise measurement (RTSNM) is an essential procedure for preventing the eavesdropper exploiting the practical security loopholes. However, the performance of this procedure itself is not analyzed under the real-world condition. Therefore, we indicate the RTSNM practical performance and investigate its effects on the CVQKD system. In particular, due to the finite-size effect, the shot-noise measurement at the receiver's side may decrease the precision of parameter estimation and consequently result in a tight security bound. To mitigate that, we optimize the block size for RTSNM under the ensemble size limitation to maximize the secure key rate. Moreover, the effect of finite dynamics of amplitude modulator in this scheme is studied and its mitigation method is also proposed. Our work indicates the practical performance of RTSNM and provides the real secret key rate under it.

Progress toward a performance based specification for diamond grinding wheels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taylor, J.S.; Piscotty, M.S.; Blaedel, K.L.

1996-11-12

This work sought to improve the communication between users and makers of fine diamond grinding wheels. A promising avenue for this is to formulate a voluntary product standard that comprises performance indicators that bridge the gap between specific user requirements and the details of wheel formulations. We propose a set of performance specifiers of figures-of-merit, that might be assessed by straightforward and traceable testing methods, but do not compromise proprietary information of the wheel user of wheel maker. One such performance indicator might be wheel hardness. In addition we consider technologies that might be required to realize the benefits ofmore » optimized grinding wheels. A non-contact wheel-to- workpiece proximity sensor may provide a means of monitoring wheel wear and thus wheel position, for wheels that exhibit high wear rates in exchange for improved surface finish.« less

Comparing the Performance of Improved Classify-Analyze Approaches For Distal Outcomes in Latent Profile Analysis

PubMed Central

Dziak, John J.; Bray, Bethany C.; Zhang, Jieting; Zhang, Minqiang; Lanza, Stephanie T.

2016-01-01

Several approaches are available for estimating the relationship of latent class membership to distal outcomes in latent profile analysis (LPA). A three-step approach is commonly used, but has problems with estimation bias and confidence interval coverage. Proposed improvements include the correction method of Bolck, Croon, and Hagenaars (BCH; 2004), Vermunt’s (2010) maximum likelihood (ML) approach, and the inclusive three-step approach of Bray, Lanza, & Tan (2015). These methods have been studied in the related case of latent class analysis (LCA) with categorical indicators, but not as well studied for LPA with continuous indicators. We investigated the performance of these approaches in LPA with normally distributed indicators, under different conditions of distal outcome distribution, class measurement quality, relative latent class size, and strength of association between latent class and the distal outcome. The modified BCH implemented in Latent GOLD had excellent performance. The maximum likelihood and inclusive approaches were not robust to violations of distributional assumptions. These findings broadly agree with and extend the results presented by Bakk and Vermunt (2016) in the context of LCA with categorical indicators. PMID:28630602

An improved non-uniformity correction algorithm and its GPU parallel implementation

NASA Astrophysics Data System (ADS)

Cheng, Kuanhong; Zhou, Huixin; Qin, Hanlin; Zhao, Dong; Qian, Kun; Rong, Shenghui

2018-05-01

The performance of SLP-THP based non-uniformity correction algorithm is seriously affected by the result of SLP filter, which always leads to image blurring and ghosting artifacts. To address this problem, an improved SLP-THP based non-uniformity correction method with curvature constraint was proposed. Here we put forward a new way to estimate spatial low frequency component. First, the details and contours of input image were obtained respectively by minimizing local Gaussian curvature and mean curvature of image surface. Then, the guided filter was utilized to combine these two parts together to get the estimate of spatial low frequency component. Finally, we brought this SLP component into SLP-THP method to achieve non-uniformity correction. The performance of proposed algorithm was verified by several real and simulated infrared image sequences. The experimental results indicated that the proposed algorithm can reduce the non-uniformity without detail losing. After that, a GPU based parallel implementation that runs 150 times faster than CPU was presented, which showed the proposed algorithm has great potential for real time application.

A fast fusion scheme for infrared and visible light images in NSCT domain

NASA Astrophysics Data System (ADS)

Zhao, Chunhui; Guo, Yunting; Wang, Yulei

2015-09-01

Fusion of infrared and visible light images is an effective way to obtain a simultaneous visualization of details of background provided by visible light image and hiding target information provided by infrared image, which is more suitable for browsing and further processing. Two crucial components for infrared and visual light image fusion are improving its fusion performance as well as reducing its computational burden. In this paper, a novel fusion algorithm named pixel information estimation is proposed, which determines the weights by evaluating the information of pixel and is well applied in visible light and infrared image fusion with better fusion quality and lower time-consumption. Besides, a fast realization of non-subsampled contourlet transform is also proposed in this paper to improve the computational efficiency. To verify the advantage of the proposed method, this paper compares it with several popular ones in six evaluation metrics over four different image groups. Experimental results show that the proposed algorithm gets a more effective result with much less time consuming and performs well in both subjective evaluation and objective indicators.

A mathematical programming method for formulating a fuzzy regression model based on distance criterion.

PubMed

Chen, Liang-Hsuan; Hsueh, Chan-Ching

2007-06-01

Fuzzy regression models are useful to investigate the relationship between explanatory and response variables with fuzzy observations. Different from previous studies, this correspondence proposes a mathematical programming method to construct a fuzzy regression model based on a distance criterion. The objective of the mathematical programming is to minimize the sum of distances between the estimated and observed responses on the X axis, such that the fuzzy regression model constructed has the minimal total estimation error in distance. Only several alpha-cuts of fuzzy observations are needed as inputs to the mathematical programming model; therefore, the applications are not restricted to triangular fuzzy numbers. Three examples, adopted in the previous studies, and a larger example, modified from the crisp case, are used to illustrate the performance of the proposed approach. The results indicate that the proposed model has better performance than those in the previous studies based on either distance criterion or Kim and Bishu's criterion. In addition, the efficiency and effectiveness for solving the larger example by the proposed model are also satisfactory.

Characterization of System Status Signals for Multivariate Time Series Discretization Based on Frequency and Amplitude Variation

PubMed Central

2018-01-01

Many fault detection methods have been proposed for monitoring the health of various industrial systems. Characterizing the monitored signals is a prerequisite for selecting an appropriate detection method. However, fault detection methods tend to be decided with user’s subjective knowledge or their familiarity with the method, rather than following a predefined selection rule. This study investigates the performance sensitivity of two detection methods, with respect to status signal characteristics of given systems: abrupt variance, characteristic indicator, discernable frequency, and discernable index. Relation between key characteristics indicators from four different real-world systems and the performance of two fault detection methods using pattern recognition are evaluated. PMID:29316731

Performance improvement of planar dielectric elastomer actuators by magnetic modulating mechanism

NASA Astrophysics Data System (ADS)

Zhao, Yun-Hua; Li, Wen-Bo; Zhang, Wen-Ming; Yan, Han; Peng, Zhi-Ke; Meng, Guang

2018-06-01

In this paper, a novel planar dielectric elastomer actuator (DEA) with magnetic modulating mechanism is proposed. This design can provide the availability of wider actuation range and larger output force, which are significant indicators to evaluate the performance of DEAs. The DEA tends to be a compact and simple design, and an analytical model is developed to characterize the mechanical behavior. The result shows that the output force induced by the DEA can be improved by 76.90% under a certain applied voltage and initial magnet distance. Moreover, experiments are carried out to reveal the performance of the proposed DEA and validate the theoretical model. It demonstrates that the DEA using magnetic modulating mechanism can enlarge the actuation range and has more remarkable effect with decreasing initial magnet distance within the stable range. It can be useful to promote the applications of DEAs to soft robots and haptic feedback.

[Municipalities Stratification for Health Performance Evaluation].

PubMed

Calvo, Maria Cristina Marino; Lacerda, Josimari Telino de; Colussi, Claudia Flemming; Schneider, Ione Jayce Ceola; Rocha, Thiago Augusto Hernandes

2016-01-01

to propose and present a stratification of Brazilian municipalities into homogeneous groups for evaluation studies of health management performance. this was a methodological study, with selected indicators which classify municipalities according to conditions that influence the health management and population size; data for the year 2010 were collected from demographic and health databases; correlation tests and factor analysis were used. seven strata were identified - Large-sized; Medium-sized with favorable, regular or unfavorable influences; and Small-sized with favorable, regular or unfavorable influences -; there was a concentration of municipalities with favorable influences in strata with better purchasing power and funding, as well as a concentration of municipalities with unfavorable influences in the North and Northeast regions. the proposed classification grouped similar municipalities regarding influential factors in health management, which allowed the identification of comparable groups of municipalities, setting up a consistent alternative to performance evaluation studies.

A scalable silicon photonic chip-scale optical switch for high performance computing systems.

PubMed

Yu, Runxiang; Cheung, Stanley; Li, Yuliang; Okamoto, Katsunari; Proietti, Roberto; Yin, Yawei; Yoo, S J B

2013-12-30

This paper discusses the architecture and provides performance studies of a silicon photonic chip-scale optical switch for scalable interconnect network in high performance computing systems. The proposed switch exploits optical wavelength parallelism and wavelength routing characteristics of an Arrayed Waveguide Grating Router (AWGR) to allow contention resolution in the wavelength domain. Simulation results from a cycle-accurate network simulator indicate that, even with only two transmitter/receiver pairs per node, the switch exhibits lower end-to-end latency and higher throughput at high (>90%) input loads compared with electronic switches. On the device integration level, we propose to integrate all the components (ring modulators, photodetectors and AWGR) on a CMOS-compatible silicon photonic platform to ensure a compact, energy efficient and cost-effective device. We successfully demonstrate proof-of-concept routing functions on an 8 × 8 prototype fabricated using foundry services provided by OpSIS-IME.

The Performance Analysis of a 3d Map Embedded Ins/gps Fusion Algorithm for Seamless Vehicular Navigation in Elevated Highway Environments

NASA Astrophysics Data System (ADS)

Lee, Y. H.; Chiang, K. W.

2012-07-01

In this study, a 3D Map Matching (3D MM) algorithm is embedded to current INS/GPS fusion algorithm for enhancing the sustainability and accuracy of INS/GPS integration systems, especially the height component. In addition, this study propose an effective solutions to the limitation of current commercial vehicular navigation systems where they fail to distinguish whether the vehicle is moving on the elevated highway or the road under it because those systems don't have sufficient height resolution. To validate the performance of proposed 3D MM embedded INS/GPS integration algorithms, in the test area, two scenarios were considered, paths under the freeways and streets between tall buildings, where the GPS signal is obstacle or interfered easily. The test platform was mounted on the top of a land vehicle and also systems in the vehicle. The IMUs applied includes SPAN-LCI (0.1 deg/hr gyro bias) from NovAtel, which was used as the reference system, and two MEMS IMUs with different specifications for verifying the performance of proposed algorithm. The preliminary results indicate the proposed algorithms are able to improve the accuracy of positional components in GPS denied environments significantly with the use of INS/GPS integrated systems in SPP mode.

High-bandwidth and flexible tracking control for precision motion with application to a piezo nanopositioner.

PubMed

Feng, Zhao; Ling, Jie; Ming, Min; Xiao, Xiao-Hui

2017-08-01

For precision motion, high-bandwidth and flexible tracking are the two important issues for significant performance improvement. Iterative learning control (ILC) is an effective feedforward control method only for systems that operate strictly repetitively. Although projection ILC can track varying references, the performance is still limited by the fixed-bandwidth Q-filter, especially for triangular waves tracking commonly used in a piezo nanopositioner. In this paper, a wavelet transform-based linear time-varying (LTV) Q-filter design for projection ILC is proposed to compensate high-frequency errors and improve the ability to tracking varying references simultaneously. The LVT Q-filter is designed based on the modulus maximum of wavelet detail coefficients calculated by wavelet transform to determine the high-frequency locations of each iteration with the advantages of avoiding cross-terms and segmenting manually. The proposed approach was verified on a piezo nanopositioner. Experimental results indicate that the proposed approach can locate the high-frequency regions accurately and achieve the best performance under varying references compared with traditional frequency-domain and projection ILC with a fixed-bandwidth Q-filter, which validates that through implementing the LTV filter on projection ILC, high-bandwidth and flexible tracking can be achieved simultaneously by the proposed approach.

Towards a Cloud Based Smart Traffic Management Framework

NASA Astrophysics Data System (ADS)

Rahimi, M. M.; Hakimpour, F.

2017-09-01

Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM) real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

MRI Volume Fusion Based on 3D Shearlet Decompositions.

PubMed

Duan, Chang; Wang, Shuai; Wang, Xue Gang; Huang, Qi Hong

2014-01-01

Nowadays many MRI scans can give 3D volume data with different contrasts, but the observers may want to view various contrasts in the same 3D volume. The conventional 2D medical fusion methods can only fuse the 3D volume data layer by layer, which may lead to the loss of interframe correlative information. In this paper, a novel 3D medical volume fusion method based on 3D band limited shearlet transform (3D BLST) is proposed. And this method is evaluated upon MRI T2* and quantitative susceptibility mapping data of 4 human brains. Both the perspective impression and the quality indices indicate that the proposed method has a better performance than conventional 2D wavelet, DT CWT, and 3D wavelet, DT CWT based fusion methods.

Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System.

PubMed

Turksoy, Kamuran; Samadi, Sediqeh; Feng, Jianyuan; Littlejohn, Elizabeth; Quinn, Laurie; Cinar, Ali

2016-01-01

A novel meal-detection algorithm is developed based on continuous glucose measurements. Bergman's minimal model is modified and used in an unscented Kalman filter for state estimations. The estimated rate of appearance of glucose is used for meal detection. Data from nine subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with high accuracy. The average change in glucose levels between the meals and the detection points is 16(±9.42) [mg/dl] for 61 successfully detected meals and snacks. The algorithm is developed as a new module of an integrated multivariable adaptive artificial pancreas control system. Meal detection with the proposed method is used to administer insulin boluses and prevent most of postprandial hyperglycemia without any manual meal announcements. A novel meal bolus calculation method is proposed and tested with the UVA/Padova simulator. The results indicate significant reduction in hyperglycemia.

Simulation and analysis of the absorption enhancement in p-i-n InGaN/GaN solar cell using photonic crystal light trapping structures

NASA Astrophysics Data System (ADS)

Gupta, Nikhil Deep; Janyani, Vijay

2016-10-01

The structure of p-i-n InGaN/GaN based solar cell having a photonic crystal (PhC)-based light trapping structure (LTS) at the top assisted by the planar metallic (aluminum) back reflector (BR) is proposed. We propose two different designs for efficiency enhancement: in one we keep the PhC structure etching depth extending from the top antireflective coating (ARC) of indium tin oxide (ITO) up to the p-GaN layer (which is beneath the ITO and above the active layer), whereas in the other design, the PhC LTS etching depth has been extended up to the InxGa1-xN absorbing layer, starting from the top ITO layer. The theoretical optical simulation studies and optimization of the required parameters of the structure, which help to investigate and demonstrate the effectiveness of the LTS in the efficiency enhancement of the structure, are presented. The work also demonstrates the Lambertian light trapping limits for the practical indium concentrations in a InxGa1-xN active layer cell. The paper also presents the comparison between the proposed designs and compares their results with that of a planar reference cell. The studies are carried out for various indium concentrations. The results indicate considerable enhancement in the efficiency due to the PhC LTS, mainly because of better coupling, low reflectance, and diffraction capability of the proposed LTS, although it is still under the Lambertian limits. The performance evaluation of the proposed structure with respect to the angle of incident light has also been done, indicating improved performance. The parameters have been optimized and calculated by means of rigorous coupled wave analysis (RCWA) method.

FIESTA ROC: A new finite element analysis program for solar cell simulation

NASA Technical Reports Server (NTRS)

Clark, Ralph O.

1991-01-01

The Finite Element Semiconductor Three-dimensional Analyzer by Ralph O. Clark (FIESTA ROC) is a computational tool for investigating in detail the performance of arbitrary solar cell structures. As its name indicates, it uses the finite element technique to solve the fundamental semiconductor equations in the cell. It may be used for predicting the performance (thereby dictating the design parameters) of a proposed cell or for investigating the limiting factors in an established design.

Assessing health system performance in developing countries: a review of the literature.

PubMed

Kruk, Margaret Elizabeth; Freedman, Lynn P

2008-03-01

With the setting of ambitious international health goals and an influx of additional development assistance for health, there is growing interest in assessing the performance of health systems in developing countries. This paper proposes a framework for the assessment of health system performance and reviews the literature on indicators currently in use to measure performance using online medical and public health databases. This was complemented by a review of relevant books and reports in the grey literature. The indicators were organized into three categories: effectiveness, equity, and efficiency. Measures of health system effectiveness were improvement in health status, access to and quality of care and, increasingly, patient satisfaction. Measures of equity included access and quality of care for disadvantaged groups together with fair financing, risk protection and accountability. Measures of efficiency were appropriate levels of funding, the cost-effectiveness of interventions, and effective administration. This framework and review of indicators may be helpful to health policy makers interested in assessing the effects of different policies, expenditures, and organizational structures on health outputs and outcomes in developing countries.

An ex ante control chart for project monitoring using earned duration management observations

NASA Astrophysics Data System (ADS)

Mortaji, Seyed Taha Hossein; Noori, Siamak; Noorossana, Rassoul; Bagherpour, Morteza

2017-12-01

In the past few years, there has been an increasing interest in developing project control systems. The primary purpose of such systems is to indicate whether the actual performance is consistent with the baseline and to produce a signal in the case of non-compliance. Recently, researchers have shown an increased interest in monitoring project's performance indicators, by plotting them on the Shewhart-type control charts over time. However, these control charts are fundamentally designed for processes and ignore project-specific dynamics, which can lead to weak results and misleading interpretations. By paying close attention to the project baseline schedule and using statistical foundations, this paper proposes a new ex ante control chart which discriminates between acceptable (as-planned) and non-acceptable (not-as-planned) variations of the project's schedule performance. Such control chart enables project managers to set more realistic thresholds leading to a better decision making for taking corrective and/or preventive actions. For the sake of clarity, an illustrative example has been presented to show how the ex ante control chart is constructed in practice. Furthermore, an experimental investigation has been set up to analyze the performance of the proposed control chart. As expected, the results confirm that, when a project starts to deflect significantly from the project's baseline schedule, the ex ante control chart shows a respectable ability to detect and report right signals while avoiding false alarms.

MATSurv: multisensor air traffic surveillance system

NASA Astrophysics Data System (ADS)

Yeddanapudi, Murali; Bar-Shalom, Yaakov; Pattipati, Krishna R.; Gassner, Richard R.

1995-09-01

This paper deals with the design and implementation of MATSurv 1--an experimental Multisensor Air Traffic Surveillance system. The proposed system consists of a Kalman filter based state estimator used in conjunction with a 2D sliding window assignment algorithm. Real data from two FAA radars is used to evaluate the performance of this algorithm. The results indicate that the proposed algorithm provides a superior classification of the measurements into tracks (i.e., the most likely aircraft trajectories) when compared to the aircraft trajectories obtained using the measurement IDs (squawk or IFF code).

Comparative Flow Path Analysis and Design Assessment of an Axisymmetric Hydrogen Fueled Scramjet Flight Test Engine at a Mach Number of 6.5

NASA Technical Reports Server (NTRS)

McClinton, C.; Rondakov, A.; Semenov, V.; Kopehenov, V.

1991-01-01

NASA has contracted with the Central Institute of Aviation Motors CIAM to perform a flight test and ground test and provide a scramjet engine for ground test in the United States. The objective of this contract is to obtain ground to flight correlation for a supersonic combustion ramjet (scramjet) engine operating point at a Mach number of 6.5. This paper presents results from a flow path performance and thermal evaluation performed on the design proposed by the CIAM. This study shows that the engine will perform in the scramjet mode for stoichiometric operation at a flight Mach number of 6.5. Thermal assessment of the structure indicates that the combustor cooling liner will provide adequate cooling for a Mach number of 6.5 test condition and that optional material proposed by CIAM for the cowl leading-edge design are required to allow operation with or without a type IV shock-shock interaction.

Optimization of planar self-collimating photonic crystals.

PubMed

Rumpf, Raymond C; Pazos, Javier J

2013-07-01

Self-collimation in photonic crystals has received a lot of attention in the literature, partly due to recent interest in silicon photonics, yet no performance metrics have been proposed. This paper proposes a figure of merit (FOM) for self-collimation and outlines a methodical approach for calculating it. Performance metrics include bandwidth, angular acceptance, strength, and an overall FOM. Two key contributions of this work include the performance metrics and identifying that the optimum frequency for self-collimation is not at the inflection point. The FOM is used to optimize a planar photonic crystal composed of a square array of cylinders. Conclusions are drawn about how the refractive indices and fill fraction of the lattice impact each of the performance metrics. The optimization is demonstrated by simulating two spatially variant self-collimating photonic crystals, where one has a high FOM and the other has a low FOM. This work gives optical designers tremendous insight into how to design and optimize robust self-collimating photonic crystals, which promises many applications in silicon photonics and integrated optics.

Baseline Design and Performance Analysis of Laser Altimeter for Korean Lunar Orbiter

NASA Astrophysics Data System (ADS)

Lim, Hyung-Chul; Neumann, Gregory A.; Choi, Myeong-Hwan; Yu, Sung-Yeol; Bang, Seong-Cheol; Ka, Neung-Hyun; Park, Jong-Uk; Choi, Man-Soo; Park, Eunseo

2016-09-01

Korea’s lunar exploration project includes the launching of an orbiter, a lander (including a rover), and an experimental orbiter (referred to as a lunar pathfinder). Laser altimeters have played an important scientific role in lunar, planetary, and asteroid exploration missions since their first use in 1971 onboard the Apollo 15 mission to the Moon. In this study, a laser altimeter was proposed as a scientific instrument for the Korean lunar orbiter, which will be launched by 2020, to study the global topography of the surface of the Moon and its gravitational field and to support other payloads such as a terrain mapping camera or spectral imager. This study presents the baseline design and performance model for the proposed laser altimeter. Additionally, the study discusses the expected performance based on numerical simulation results. The simulation results indicate that the design of system parameters satisfies performance requirements with respect to detection probability and range error even under unfavorable conditions.

Performance potential of an advanced technology Mach 3 turbojet engine installed on a conceptual high-speed civil transport

NASA Technical Reports Server (NTRS)

Morris, Shelby J., Jr.; Geiselhart, Karl A.; Coen, Peter G.

1989-01-01

The performance of an advanced technology conceptual turbojet optimized for a high-speed civil aircraft is presented. This information represents an estimate of performance of a Mach 3 Brayton (gas turbine) cycle engine optimized for minimum fuel burned at supersonic cruise. This conceptual engine had no noise or environmental constraints imposed upon it. The purpose of this data is to define an upper boundary on the propulsion performance for a conceptual commercial Mach 3 transport design. A comparison is presented demonstrating the impact of the technology proposed for this conceptual engine on the weight and other characteristics of a proposed high-speed civil transport. This comparison indicates that the advanced technology turbojet described could reduce the gross weight of a hypothetical Mach 3 high-speed civil transport design from about 714,000 pounds to about 545,000 pounds. The aircraft with the baseline engine and the aircraft with the advanced technology engine are described.

Application of capability indices and control charts in the analytical method control strategy.

PubMed

Oliva, Alexis; Llabres Martinez, Matías

2017-08-01

In this study, we assessed the usefulness of control charts in combination with the process capability indices, C pm and C pk , in the control strategy of an analytical method. The traditional X-chart and moving range chart were used to monitor the analytical method over a 2-year period. The results confirmed that the analytical method is in-control and stable. Different criteria were used to establish the specifications limits (i.e. analyst requirements) for fixed method performance (i.e. method requirements). If the specification limits and control limits are equal in breadth, the method can be considered "capable" (C pm  = 1), but it does not satisfy the minimum method capability requirements proposed by Pearn and Shu (2003). Similar results were obtained using the C pk index. The method capability was also assessed as a function of method performance for fixed analyst requirements. The results indicate that the method does not meet the requirements of the analytical target approach. A real-example data of a SEC with light-scattering detection method was used as a model whereas previously published data were used to illustrate the applicability of the proposed approach. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal scheme of star observation of missile-borne inertial navigation system/stellar refraction integrated navigation

NASA Astrophysics Data System (ADS)

Lu, Jiazhen; Yang, Lie

2018-05-01

To achieve accurate and completely autonomous navigation for spacecraft, inertial/celestial integrated navigation gets increasing attention. In this study, a missile-borne inertial/stellar refraction integrated navigation scheme is proposed. Position Dilution of Precision (PDOP) for stellar refraction is introduced and the corresponding equation is derived. Based on the condition when PDOP reaches the minimum value, an optimized observation scheme is proposed. To verify the feasibility of the proposed scheme, numerical simulation is conducted. The results of the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are compared and impact factors of navigation accuracy are studied in the simulation. The simulation results indicated that the proposed observation scheme has an accurate positioning performance, and the results of EKF and UKF are similar.

Optimal scheme of star observation of missile-borne inertial navigation system/stellar refraction integrated navigation.

PubMed

Lu, Jiazhen; Yang, Lie

2018-05-01

To achieve accurate and completely autonomous navigation for spacecraft, inertial/celestial integrated navigation gets increasing attention. In this study, a missile-borne inertial/stellar refraction integrated navigation scheme is proposed. Position Dilution of Precision (PDOP) for stellar refraction is introduced and the corresponding equation is derived. Based on the condition when PDOP reaches the minimum value, an optimized observation scheme is proposed. To verify the feasibility of the proposed scheme, numerical simulation is conducted. The results of the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are compared and impact factors of navigation accuracy are studied in the simulation. The simulation results indicated that the proposed observation scheme has an accurate positioning performance, and the results of EKF and UKF are similar.

Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking.

PubMed

Zhou, Ping; Guo, Dongwei; Wang, Hong; Chai, Tianyou

2017-09-29

Optimal operation of an industrial blast furnace (BF) ironmaking process largely depends on a reliable measurement of molten iron quality (MIQ) indices, which are not feasible using the conventional sensors. This paper proposes a novel data-driven robust modeling method for the online estimation and control of MIQ indices. First, a nonlinear autoregressive exogenous (NARX) model is constructed for the MIQ indices to completely capture the nonlinear dynamics of the BF process. Then, considering that the standard least-squares support vector regression (LS-SVR) cannot directly cope with the multioutput problem, a multitask transfer learning is proposed to design a novel multioutput LS-SVR (M-LS-SVR) for the learning of the NARX model. Furthermore, a novel M-estimator is proposed to reduce the interference of outliers and improve the robustness of the M-LS-SVR model. Since the weights of different outlier data are properly given by the weight function, their corresponding contributions on modeling can properly be distinguished, thus a robust modeling result can be achieved. Finally, a novel multiobjective evaluation index on the modeling performance is developed by comprehensively considering the root-mean-square error of modeling and the correlation coefficient on trend fitting, based on which the nondominated sorting genetic algorithm II is used to globally optimize the model parameters. Both experiments using industrial data and industrial applications illustrate that the proposed method can eliminate the adverse effect caused by the fluctuation of data in BF process efficiently. This indicates its stronger robustness and higher accuracy. Moreover, control testing shows that the developed model can be well applied to realize data-driven control of the BF process.

Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ping; Guo, Dongwei; Wang, Hong

Optimal operation of an industrial blast furnace (BF) ironmaking process largely depends on a reliable measurement of molten iron quality (MIQ) indices, which are not feasible using the conventional sensors. This paper proposes a novel data-driven robust modeling method for the online estimation and control of MIQ indices. First, a nonlinear autoregressive exogenous (NARX) model is constructed for the MIQ indices to completely capture the nonlinear dynamics of the BF process. Then, considering that the standard least-squares support vector regression (LS-SVR) cannot directly cope with the multioutput problem, a multitask transfer learning is proposed to design a novel multioutput LS-SVRmore » (M-LS-SVR) for the learning of the NARX model. Furthermore, a novel M-estimator is proposed to reduce the interference of outliers and improve the robustness of the M-LS-SVR model. Since the weights of different outlier data are properly given by the weight function, their corresponding contributions on modeling can properly be distinguished, thus a robust modeling result can be achieved. Finally, a novel multiobjective evaluation index on the modeling performance is developed by comprehensively considering the root-mean-square error of modeling and the correlation coefficient on trend fitting, based on which the nondominated sorting genetic algorithm II is used to globally optimize the model parameters. Both experiments using industrial data and industrial applications illustrate that the proposed method can eliminate the adverse effect caused by the fluctuation of data in BF process efficiently. In conclusion, this indicates its stronger robustness and higher accuracy. Moreover, control testing shows that the developed model can be well applied to realize data-driven control of the BF process.« less

Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

DOE PAGES

Zhou, Ping; Guo, Dongwei; Wang, Hong; ...

2017-09-29

Optimal operation of an industrial blast furnace (BF) ironmaking process largely depends on a reliable measurement of molten iron quality (MIQ) indices, which are not feasible using the conventional sensors. This paper proposes a novel data-driven robust modeling method for the online estimation and control of MIQ indices. First, a nonlinear autoregressive exogenous (NARX) model is constructed for the MIQ indices to completely capture the nonlinear dynamics of the BF process. Then, considering that the standard least-squares support vector regression (LS-SVR) cannot directly cope with the multioutput problem, a multitask transfer learning is proposed to design a novel multioutput LS-SVRmore » (M-LS-SVR) for the learning of the NARX model. Furthermore, a novel M-estimator is proposed to reduce the interference of outliers and improve the robustness of the M-LS-SVR model. Since the weights of different outlier data are properly given by the weight function, their corresponding contributions on modeling can properly be distinguished, thus a robust modeling result can be achieved. Finally, a novel multiobjective evaluation index on the modeling performance is developed by comprehensively considering the root-mean-square error of modeling and the correlation coefficient on trend fitting, based on which the nondominated sorting genetic algorithm II is used to globally optimize the model parameters. Both experiments using industrial data and industrial applications illustrate that the proposed method can eliminate the adverse effect caused by the fluctuation of data in BF process efficiently. In conclusion, this indicates its stronger robustness and higher accuracy. Moreover, control testing shows that the developed model can be well applied to realize data-driven control of the BF process.« less

A framework to support decision making in the selection of sustainable drainage system design alternatives.

PubMed

Wang, Mingming; Sweetapple, Chris; Fu, Guangtao; Farmani, Raziyeh; Butler, David

2017-10-01

This paper presents a new framework for decision making in sustainable drainage system (SuDS) scheme design. It integrates resilience, hydraulic performance, pollution control, rainwater usage, energy analysis, greenhouse gas (GHG) emissions and costs, and has 12 indicators. The multi-criteria analysis methods of entropy weight and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were selected to support SuDS scheme selection. The effectiveness of the framework is demonstrated with a SuDS case in China. Indicators used include flood volume, flood duration, a hydraulic performance indicator, cost and resilience. Resilience is an important design consideration, and it supports scheme selection in the case study. The proposed framework will help a decision maker to choose an appropriate design scheme for implementation without subjectivity. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Rapid Auto-Indexing Technology for Designing Readable E-Learning Content

ERIC Educational Resources Information Center

Yu, Pao-Ta; Liao, Yuan-Hsun; Su, Ming-Hsiang; Cheng, Po-Jen; Pai, Chun-Hsuan

2012-01-01

A rapid scene indexing method is proposed to improve retrieval performance for students accessing instructional videos. This indexing method is applied to anchor suitable indices to the instructional video so that students can obtain several small lesson units to gain learning mastery. The method also regulates online course progress. These…

Experimental Determination of Ultraviolet Radiation Protection of Common Materials

ERIC Educational Resources Information Center

Tavares, Susana C. A.; da Silva, Joaquim C. G. Esteves; Paiva, Joao

2007-01-01

Aiming at a better understanding of the problems associated with the depletion of the ozone layer, we propose several experiments to be performed by students of different levels: secondary and first-year undergraduate students. The oxidation of iodide induced by ultraviolet (UV) radiation, generated by a mercury lamp, is used as an indicator for…

76 FR 54507 - Proposed Generic Communication; Draft NRC Generic Letter 2011-XX: Seismic Risk Evaluations for...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-01

... design estimates. Analyses performed under the Generic Issue program (GIP) indicated the need to evaluate... Examination of External Events (IPEEE) for Severe Accident Vulnerabilities,'' (ADAMS Accession No. ML031150485) to request that each licensee identify and report to the NRC all plant- specific vulnerabilities to...

7 CFR 1487.5 - What is the process for submitting proposals?

Code of Federal Regulations, 2010 CFR

2010-01-01

... reimbursement will be sought; and (viii) Information indicating all financial and in-kind support to the... services. Although highly encouraged, financial support from the participant is not required. (3) Export... performance measure for the year prior to the year that the project would begin; and (iii) The viability of...

A Mindtool-Based Collaborative Learning Approach to Enhancing Students' Innovative Performance in Management Courses

ERIC Educational Resources Information Center

Wu, Chih-Hsiang; Hwang, Gwo-Jen; Kuo, Fan-Ray; Huang, Iwen

2013-01-01

Educators have indicated that creative teaching is the most important educational activity; nevertheless, most existing education systems fail to engage students in effective creative tasks. To address this issue, this study proposes a mind map based collaborative learning approach for supporting creative learning activities and enhancing…

Analysis of reaching movements of upper arm in robot assisted exercises. Kinematic assessment of robot assisted upper arm reaching single-joint movements.

PubMed

Iuppariello, Luigi; D'Addio, Giovanni; Romano, Maria; Bifulco, Paolo; Lanzillo, Bernardo; Pappone, Nicola; Cesarelli, Mario

2016-01-01

Robot-mediated therapy (RMT) has been a very dynamic area of research in recent years. Robotics devices are in fact capable to quantify the performances of a rehabilitation task in treatments of several disorders of the arm and the shoulder of various central and peripheral etiology. Different systems for robot-aided neuro-rehabilitation are available for upper limb rehabilitation but the biomechanical parameters proposed until today, to evaluate the quality of the movement, are related to the specific robot used and to the type of exercise performed. Besides, none study indicated a standardized quantitative evaluation of robot assisted upper arm reaching movements, so the RMT is still far to be considered a standardised tool. In this paper a quantitative kinematic assessment of robot assisted upper arm reaching movements, considering also the effect of gravity on the quality of the movements, is proposed. We studied a group of 10 healthy subjects and results indicate that our advised protocol can be useful for characterising normal pattern in reaching movements.

Social vulnerability indicators as a sustainable planning tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Yung-Jaan, E-mail: yungjaanlee@gmail.com

In the face of global warming and environmental change, the conventional strategy of resource centralization will not be able to cope with a future of increasingly extreme climate events and related disasters. It may even contribute to inter-regional disparities as a result of these events. To promote sustainable development, this study offers a case study of developmental planning in Chiayi, Taiwan and a review of the relevant literature to propose a framework of social vulnerability indicators at the township level. The proposed framework can not only be used to measure the social vulnerability of individual townships in Chiayi, but alsomore » be used to capture the spatial developmental of Chiayi. Seventeen social vulnerability indicators provide information in five dimensions. Owing to limited access to relevant data, the values of only 13 indicators were calculated. By simply summarizing indicators without using weightings and by using zero-mean normalization to standardize the indicators, this study calculates social vulnerability scores for each township. To make social vulnerability indicators more useful, this study performs an overlay analysis of social vulnerability and patterns of risk associated with national disasters. The social vulnerability analysis draws on secondary data for 2012 from Taiwan's National Geographic Information System. The second layer of analysis consists of the flood potential ratings of the Taiwan Water Resources Agency as an index of biophysical vulnerability. The third layer consists of township-level administrative boundaries. Analytical results reveal that four out of the 18 townships in Chiayi not only are vulnerable to large-scale flooding during serious flood events, but also have the highest degree of social vulnerability. Administrative boundaries, on which social vulnerability is based, do not correspond precisely to “cross-administrative boundaries,” which are characteristics of the natural environment. This study adopts an exploratory approach that provides Chiayi and other government agencies with a foundation for sustainable strategic planning for environmental change. The final section offers four suggestions concerning the implications of social vulnerability for local development planning. -- Highlights: • This study proposes a framework of social vulnerability indicators at the township level in Chiayi County, Taiwan. • Seventeen social vulnerability indicators are categorized into four dimensions. • This study performs a three-layer overlay analysis of social vulnerability and natural disaster risk patterns. • 4 out of the 18 townships not only have potential for large-scale flooding, but also high degree of social vulnerability. • This study provides a foundation for sustainable strategic planning to deal with environmental change. • Four suggestions are proposed regarding the implications of social vulnerability for local development planning.« less

A simple method for assessing occupational exposure via the one-way random effects model.

PubMed

Krishnamoorthy, K; Mathew, Thomas; Peng, Jie

2016-11-01

A one-way random effects model is postulated for the log-transformed shift-long personal exposure measurements, where the random effect in the model represents an effect due to the worker. Simple closed-form confidence intervals are proposed for the relevant parameters of interest using the method of variance estimates recovery (MOVER). The performance of the confidence bounds is evaluated and compared with those based on the generalized confidence interval approach. Comparison studies indicate that the proposed MOVER confidence bounds are better than the generalized confidence bounds for the overall mean exposure and an upper percentile of the exposure distribution. The proposed methods are illustrated using a few examples involving industrial hygiene data.

Next Day Price Forecasting in Deregulated Market by Combination of Artificial Neural Network and ARIMA Time Series Models

NASA Astrophysics Data System (ADS)

Areekul, Phatchakorn; Senjyu, Tomonobu; Urasaki, Naomitsu; Yona, Atsushi

Electricity price forecasting is becoming increasingly relevant to power producers and consumers in the new competitive electric power markets, when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper proposed a method to predict hourly electricity prices for next-day electricity markets by combination methodology of ARIMA and ANN models. The proposed method is examined on the Australian National Electricity Market (NEM), New South Wales regional in year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN and combination (ARIMA-ANN) models are presented. Empirical results indicate that an ARIMA-ANN model can improve the price forecasting accuracy.

Performance assessment of geospatial simulation models of land-use change--a landscape metric-based approach.

PubMed

Sakieh, Yousef; Salmanmahiny, Abdolrassoul

2016-03-01

Performance evaluation is a critical step when developing land-use and cover change (LUCC) models. The present study proposes a spatially explicit model performance evaluation method, adopting a landscape metric-based approach. To quantify GEOMOD model performance, a set of composition- and configuration-based landscape metrics including number of patches, edge density, mean Euclidean nearest neighbor distance, largest patch index, class area, landscape shape index, and splitting index were employed. The model takes advantage of three decision rules including neighborhood effect, persistence of change direction, and urbanization suitability values. According to the results, while class area, largest patch index, and splitting indices demonstrated insignificant differences between spatial pattern of ground truth and simulated layers, there was a considerable inconsistency between simulation results and real dataset in terms of the remaining metrics. Specifically, simulation outputs were simplistic and the model tended to underestimate number of developed patches by producing a more compact landscape. Landscape-metric-based performance evaluation produces more detailed information (compared to conventional indices such as the Kappa index and overall accuracy) on the model's behavior in replicating spatial heterogeneity features of a landscape such as frequency, fragmentation, isolation, and density. Finally, as the main characteristic of the proposed method, landscape metrics employ the maximum potential of observed and simulated layers for a performance evaluation procedure, provide a basis for more robust interpretation of a calibration process, and also deepen modeler insight into the main strengths and pitfalls of a specific land-use change model when simulating a spatiotemporal phenomenon.

Real-time spectrum estimation–based dual-channel speech-enhancement algorithm for cochlear implant

PubMed Central

2012-01-01

Background Improvement of the cochlear implant (CI) front-end signal acquisition is needed to increase speech recognition in noisy environments. To suppress the directional noise, we introduce a speech-enhancement algorithm based on microphone array beamforming and spectral estimation. The experimental results indicate that this method is robust to directional mobile noise and strongly enhances the desired speech, thereby improving the performance of CI devices in a noisy environment. Methods The spectrum estimation and the array beamforming methods were combined to suppress the ambient noise. The directivity coefficient was estimated in the noise-only intervals, and was updated to fit for the mobile noise. Results The proposed algorithm was realized in the CI speech strategy. For actual parameters, we use Maxflat filter to obtain fractional sampling points and cepstrum method to differentiate the desired speech frame and the noise frame. The broadband adjustment coefficients were added to compensate the energy loss in the low frequency band. Discussions The approximation of the directivity coefficient is tested and the errors are discussed. We also analyze the algorithm constraint for noise estimation and distortion in CI processing. The performance of the proposed algorithm is analyzed and further be compared with other prevalent methods. Conclusions The hardware platform was constructed for the experiments. The speech-enhancement results showed that our algorithm can suppresses the non-stationary noise with high SNR. Excellent performance of the proposed algorithm was obtained in the speech enhancement experiments and mobile testing. And signal distortion results indicate that this algorithm is robust with high SNR improvement and low speech distortion. PMID:23006896

A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard

PubMed Central

Azadmanjir, Zahra; Torabi, Mashallah; Safdari, Reza; Bayat, Maryam; Golmahi, Fatemeh

2015-01-01

Introduction: management challenges of clinical laboratories are more complicated for educational hospital clinical laboratories. Managers can use tools of business intelligence (BI), such as information dashboards that provide the possibility of intelligent decision-making and problem solving about increasing income, reducing spending, utilization management and even improving quality. Critical phase of dashboard design is setting indicators and modeling causal relations between them. The paper describes the process of creating a map for laboratory dashboard. Methods: the study is one part of an action research that begins from 2012 by innovation initiative for implementing laboratory intelligent dashboard. Laboratories management problems were determined in educational hospitals by the brainstorming sessions. Then, with regard to the problems key performance indicators (KPIs) specified. Results: the map of indicators designed in form of three layered. They have a causal relationship so that issues measured in the subsequent layers affect issues measured in the prime layers. Conclusion: the proposed indicator map can be the base of performance monitoring. However, these indicators can be modified to improve during iterations of dashboard designing process. PMID:26483593

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taylor, Valerie

Given the significant impact of computing on society, it is important that all cultures, especially underrepresented cultures, are fully engaged in the field of computing to ensure that everyone benefits from the advances in computing. This proposal is focused on the field of high performance computing. The lack of cultural diversity in computing, in particular high performance computing, is especially evident with respect to the following ethnic groups – African Americans, Hispanics, and Native Americans – as well as People with Disabilities. The goal of this proposal is to organize and coordinate a National Laboratory Career Development Workshop focused onmore » underrepresented cultures (ethnic cultures and disability cultures) in high performance computing. It is expected that the proposed workshop will increase the engagement of underrepresented cultures in HPC through increased exposure to the excellent work at the national laboratories. The National Laboratory Workshops are focused on the recruitment of senior graduate students and the retention of junior lab staff through the various panels and discussions at the workshop. Further, the workshop will include a community building component that extends beyond the workshop. The workshop was held was held at the Lawrence Livermore National Laboratory campus in Livermore, CA. from June 14 - 15, 2012. The grant provided funding for 25 participants from underrepresented groups. The workshop also included another 25 local participants in the summer programs at Lawrence Livermore National Laboratory. Below are some key results from the assessment of the workshops: 86% of the participants indicated strongly agree or agree to the statement "I am more likely to consider/continue a career at a national laboratory as a result of participating in this workshop." 77% indicated strongly agree or agree to the statement "I plan to pursue a summer internship at a national laboratory." 100% of the participants indicated strongly agree or agree to the statement "The CMD-IT NLPDEV workshop was a valuable experience."« less

VTOL shipboard letdown guidance system analysis

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Karmali, M. S.

1983-01-01

Alternative letdown guidance strategies are examined for landing of a VTOL aircraft onboard a small aviation ship under adverse environmental conditions. Off line computer simulation of shipboard landing task is utilized for assessing the relative merits of the proposed guidance schemes. The touchdown performance of a nominal constant rate of descent (CROD) letdown strategy serves as a benchmark for ranking the performance of the alternative letdown schemes. Analysis of ship motion time histories indicates the existence of an alternating sequence of quiescent and rough motions called lulls and swells. A real time algorithms lull/swell classification based upon ship motion pattern features is developed. The classification algorithm is used to command a go/no go signal to indicate the initiation and termination of an acceptable landing window. Simulation results show that such a go/no go pattern based letdown guidance strategy improves touchdown performance.

Stock price change rate prediction by utilizing social network activities.

PubMed

Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Stock Price Change Rate Prediction by Utilizing Social Network Activities

PubMed Central

Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

Performance analysis: a study using data envelopment analysis in 26 Brazilian hospitals.

PubMed

Guerra, Mariana; de Souza, Antônio Artur; Moreira, Douglas Rafael

2012-01-01

This article describes a proposal for analyzing the performance of public Brazilian hospitals using financial and non-financial rates (i.e., operational rates), and thereby highlights the effectiveness (or otherwise) of the financial management of organizations in this study. A total of 72 hospitals in the Brazilian Unified Health Care System (in Portuguese, Sistema Unico de Saúde-SUS), were selected for accessibility and completeness of their data. Twenty-six organizations were used for the study sample, consisting of entities that had publicly disclosed financial statements for the period from 2008 (in particular, via the Internet) and whose operational data could be found in the SUS database. Our proposal, based on models using the method of Data Envelopment Analysis (DEA), was the construction of six initial models that were later compiled into a standard model. The relations between the rates that comprised the models were based on the variables and the notes of: Schuhmann, McCue and Nayar, Barnum and Kutzin, Younis, Younies, and Okojie, Marinho, Moreno, and Cavalini, and Ersoy, Kavuncubasi, Ozcan, and Harris II. We put forward an enhanced grant proposal applicable to Brazil aiming to (i) confirm or refute the rates that show the effectiveness or ineffectiveness of financial management of national hospitals; and (ii) determine the best performances, which could be used as a reference for future studies. Obtained results: (i) for all financial indicators considered, only one showed no significance in all models; and (ii) for operational indicators, the results were not relevant when the number of occupied beds was considered. Though the analysis was related to only services provided by SUS, we conclude that our study has great potential for analyzing the financial management performance of Brazilian hospitals in general, for the following reasons: (i) it shows the relationship of financial and operational rates that can be used to analyze the performance of these organizations; and (ii) it introduces ranges of these values that can be used as standard for the analysis of Brazilian hospitals.

Does taking endurance into account improve the prediction of weaning outcome in mechanically ventilated children?

PubMed Central

Noizet, Odile; Leclerc, Francis; Sadik, Ahmed; Grandbastien, Bruno; Riou, Yvon; Dorkenoo, Aimée; Fourier, Catherine; Cremer, Robin; Leteurtre, Stephane

2005-01-01

Introduction We conducted the present study to determine whether a combination of the mechanical ventilation weaning predictors proposed by the collective Task Force of the American College of Chest Physicians (TF) and weaning endurance indices enhance prediction of weaning success. Method Conducted in a tertiary paediatric intensive care unit at a university hospital, this prospective study included 54 children receiving mechanical ventilation (≥6 hours) who underwent 57 episodes of weaning. We calculated the indices proposed by the TF (spontaneous respiratory rate, paediatric rapid shallow breathing, rapid shallow breathing occlusion pressure [ROP] and maximal inspiratory pressure during an occlusion test [Pimax]) and weaning endurance indices (pressure-time index, tension-time index obtained from P0.1 [TTI1] and from airway pressure [TTI2]) during spontaneous breathing. Performances of each TF index and combinations of them were calculated, and the best single index and combination were identified. Weaning endurance parameters (TTI1 and TTI2) were calculated and the best index was determined using a logistic regression model. Regression coefficients were estimated using the maximum likelihood ratio (LR) method. Hosmer–Lemeshow test was used to estimate goodness-of-fit of the model. An equation was constructed to predict weaning success. Finally, we calculated the performances of combinations of best TF indices and best endurance index. Results The best single TF index was ROP, the best TF combination was represented by the expression (0.66 × ROP) + (0.34 × Pimax), and the best endurance index was the TTI2, although their performance was poor. The best model resulting from the combination of these indices was defined by the following expression: (0.6 × ROP) – (0.1 × Pimax) + (0.5 × TTI2). This integrated index was a good weaning predictor (P < 0.01), with a LR+ of 6.4 and LR+/LR- ratio of 12.5. However, at a threshold value <1.3 it was only predictive of weaning success (LR- = 0.5). Conclusion The proposed combined index, incorporating endurance, was of modest value in predicting weaning outcome. This is the first report of the value of endurance parameters in predicting weaning success in children. Currently, clinical judgement associated with spontaneous breathing trials apparently remain superior. PMID:16356229

When daily planning improves employee performance: The importance of planning type, engagement, and interruptions.

PubMed

Parke, Michael R; Weinhardt, Justin M; Brodsky, Andrew; Tangirala, Subrahmaniam; DeVoe, Sanford E

2018-03-01

Does planning for a particular workday help employees perform better than on other days they fail to plan? We investigate this question by identifying 2 distinct types of daily work planning to explain why and when planning improves employees' daily performance. The first type is time management planning (TMP)-creating task lists, prioritizing tasks, and determining how and when to perform them. We propose that TMP enhances employees' performance by increasing their work engagement, but that these positive effects are weakened when employees face many interruptions in their day. The second type is contingent planning (CP) in which employees anticipate possible interruptions in their work and plan for them. We propose that CP helps employees stay engaged and perform well despite frequent interruptions. We investigate these hypotheses using a 2-week experience-sampling study. Our findings indicate that TMP's positive effects are conditioned upon the amount of interruptions, but CP has positive effects that are not influenced by the level of interruptions. Through this study, we help inform workers of the different planning methods they can use to increase their daily motivation and performance in dynamic work environments. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Management of antiplatelet therapy in patients undergoing elective invasive procedures. Proposals from the French Working Group on perioperative haemostasis (GIHP) and the French Study Group on thrombosis and haemostasis (GFHT). In collaboration with the French Society for Anaesthesia and Intensive Care Medicine (SFAR).

PubMed

Godier, Anne; Fontana, Pierre; Motte, Serge; Steib, Annick; Bonhomme, Fanny; Schlumberger, Sylvie; Lecompte, Thomas; Rosencher, Nadia; Susen, Sophie; Vincentelli, André; Gruel, Yves; Albaladejo, Pierre; Collet, Jean-Philippe

2018-01-05

The French Working Group on Perioperative Haemostasis (GIHP) and the French Study Group on Haemostasis and Thrombosis (GFHT) in collaboration with the French Society for Anaesthesia and Intensive Care Medicine (SFAR) drafted up-to-date proposals for the management of antiplatelet therapy in patients undergoing elective invasive procedures. The proposals were discussed and validated by a vote; all proposals but one could be assigned with a high strength. The management of antiplatelet therapy is based on their indication and the procedure. The risk of bleeding related to the procedure can be divided into high, moderate and low categories depending on the possibility of performing the procedure in patients receiving antiplatelet agents (none, monotherapy and dual antiplatelet therapy respectively). If discontinuation of antiplatelet therapy is indicated before the procedure, a last intake of aspirin, clopidogrel, ticagrelor and prasugrel 3, 5, 5 and 7 days before surgery respectively is proposed. The thrombotic risk associated with discontinuation should be assessed according to each specific indication of antiplatelet therapy and is higher for patients receiving dual therapy for coronary artery disease (with further refinements based on a few well-accepted items) than for those receiving monotherapy for cardiovascular prevention, for secondary stroke prevention or for lower extremity arterial disease. These proposals also address the issue of the potential role of platelet functional tests and consider management of antiplatelet therapy for regional anaesthesia, including central neuraxial anaesthesia and peripheral nerve blocks, and for coronary artery surgery. Copyright © 2018 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

An initial test of a normative Figure Of Merit for the quality of overall task performance

NASA Technical Reports Server (NTRS)

Lemay, Moira; Comstock, J. R., Jr.

1990-01-01

An overall indicator, or Figure Of Merit (FOM), of the quality of crew/vehicle system performance is needed to establish the effect of workload on efficiency and to identify overload conditions. A normative FOM is proposed in which performance is measured on a representative task and a normative data base obtained. FOMs for subsequent executions of the task are then reported in terms of weighted deviations from average task performance. Performance of discrete tasks is measured primarily in terms of subtask time and errors. Discrete task performance is then combined with a measure of continuous vehicle control. In order to test the normative FOM procedure, the technique was applied to an existing set of data from a simulated landing task in which standard communications with ATC was compared with a data link communications system. The results indicated that while mean task performance was not affected, task variability, as measured by the FOM, was significantly higher when data link communications were used. In order to establish the sensitivity of the normative FOM method, further testing of the measure is recommended.

A novel integrated assessment methodology of urban water reuse.

PubMed

Listowski, A; Ngo, H H; Guo, W S; Vigneswaran, S

2011-01-01

Wastewater is no longer considered a waste product and water reuse needs to play a stronger part in securing urban water supply. Although treatment technologies for water reclamation have significantly improved the question that deserves further analysis is, how selection of a particular wastewater treatment technology relates to performance and sustainability? The proposed assessment model integrates; (i) technology, characterised by selected quantity and quality performance parameters; (ii) productivity, efficiency and reliability criteria; (iii) quantitative performance indicators; (iv) development of evaluation model. The challenges related to hierarchy and selections of performance indicators have been resolved through the case study analysis. The goal of this study is to validate a new assessment methodology in relation to performance of the microfiltration (MF) technology, a key element of the treatment process. Specific performance data and measurements were obtained at specific Control and Data Acquisition Points (CP) to satisfy the input-output inventory in relation to water resources, products, material flows, energy requirements, chemicals use, etc. Performance assessment process contains analysis and necessary linking across important parametric functions leading to reliable outcomes and results.

Experimental Investigation of the Performance of Vertical Handover Algorithms between WiFi and UMTS Networks

NASA Astrophysics Data System (ADS)

Busanelli, Stefano; Martalò, Marco; Ferrari, Gianluigi; Spigoni, Giovanni; Iotti, Nicola

In this paper, we analyze the performance of vertical handover (VHO) algorithms for seamless mobility between WiFi and UMTS networks. We focus on a no-coupling scenario, characterized by the lack of any form of cooperation between the involved players (users and network operators). In this context, we first propose a low-complexity Received Signal Strength Indicator (RSSI)-based algorithm, and then an improved hybrid RSSI/goodput version. We present experimental results based on the implementation of a real testbed with commercial WiFi (Guglielmo) and UMTS (Telecom Italia) deployed networks. Despite the relatively long handover times experienced in our testbed, the proposed RSSI-based VHO algorithm guarantees an effective goodput increase at the MTs. Moreover, this algorithm mitigates the ping-pong phenomenon.

Sound reproduction in personal audio systems using the least-squares approach with acoustic contrast control constraint.

PubMed

Cai, Yefeng; Wu, Ming; Yang, Jun

2014-02-01

This paper describes a method for focusing the reproduced sound in the bright zone without disturbing other people in the dark zone in personal audio systems. The proposed method combines the least-squares and acoustic contrast criteria. A constrained parameter is introduced to tune the balance between two performance indices, namely, the acoustic contrast and the spatial average error. An efficient implementation of this method using convex optimization is presented. Offline simulations and real-time experiments using a linear loudspeaker array are conducted to evaluate the performance of the presented method. Results show that compared with the traditional acoustic contrast control method, the proposed method can improve the flatness of response in the bright zone by sacrificing the level of acoustic contrast.

Improving performance of DS-CDMA systems using chaotic complex Bernoulli spreading codes

NASA Astrophysics Data System (ADS)

Farzan Sabahi, Mohammad; Dehghanfard, Ali

2014-12-01

The most important goal of spreading spectrum communication system is to protect communication signals against interference and exploitation of information by unintended listeners. In fact, low probability of detection and low probability of intercept are two important parameters to increase the performance of the system. In Direct Sequence Code Division Multiple Access (DS-CDMA) systems, these properties are achieved by multiplying the data information in spreading sequences. Chaotic sequences, with their particular properties, have numerous applications in constructing spreading codes. Using one-dimensional Bernoulli chaotic sequence as spreading code is proposed in literature previously. The main feature of this sequence is its negative auto-correlation at lag of 1, which with proper design, leads to increase in efficiency of the communication system based on these codes. On the other hand, employing the complex chaotic sequences as spreading sequence also has been discussed in several papers. In this paper, use of two-dimensional Bernoulli chaotic sequences is proposed as spreading codes. The performance of a multi-user synchronous and asynchronous DS-CDMA system will be evaluated by applying these sequences under Additive White Gaussian Noise (AWGN) and fading channel. Simulation results indicate improvement of the performance in comparison with conventional spreading codes like Gold codes as well as similar complex chaotic spreading sequences. Similar to one-dimensional Bernoulli chaotic sequences, the proposed sequences also have negative auto-correlation. Besides, construction of complex sequences with lower average cross-correlation is possible with the proposed method.

Integrated guidance and control for microsatellite real-time automated proximity operations

NASA Astrophysics Data System (ADS)

Chen, Ying; He, Zhen; Zhou, Ding; Yu, Zhenhua; Li, Shunli

2018-07-01

This paper investigates the trajectory planning and control of autonomous spacecraft proximity operations with impulsive dynamics. A new integrated guidance and control scheme is developed to perform automated close-range rendezvous for underactuated microsatellites. To efficiently prevent collision, a modified RRT* trajectory planning algorithm is proposed under this context. Several engineering constraints such as collision avoidance, plume impingement, field of view and control feasibility are considered simultaneously. Then, the feedback controller that employs a turn-burn-turn strategy with a combined impulsive orbital control and finite-time attitude control is designed to ensure the implementation of planned trajectory. Finally, the performance of trajectory planner and controller are evaluated through numerical tests. Simulation results indicate the real-time implementability of the proposed integrated guidance and control scheme with position control error less than 0.5 m and velocity control error less than 0.05 m/s. Consequently, the proposed scheme offers the potential for wide applications, such as on-orbit maintenance, space surveillance and debris removal.

Train axle bearing fault detection using a feature selection scheme based multi-scale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin

2018-02-01

This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.

Predicting performance for ecological restoration: A case study using Spartina altemiflora

USGS Publications Warehouse

Travis, S.E.; Grace, J.B.

2010-01-01

The success of population-based ecological restoration relies on the growth and reproductive performance of selected donor materials, whether consisting of whole plants or seed. Accurately predicting performance requires an understanding of a variety of underlying processes, particularly gene flow and selection, which can be measured, at least in part, using surrogates such as neutral marker genetic distances and simple latitudinal effects. Here we apply a structural equation modeling approach to understanding and predicting performance in a widespread salt marsh grass, Spartina alterniflora, commonly used for ecological restoration throughout its native range in North America. We collected source materials from throughout this range, consisting of eight clones each from 23 populations, for transplantation to a common garden site in coastal Louisiana and monitored their performance. We modeled performance as a latent process described by multiple indicator variables (e.g., clone diameter, stem number) and estimated direct and indirect influences of geographic and genetic distances on performance. Genetic distances were determined by comparison of neutral molecular markers with those from a local population at the common garden site. Geographic distance metrics included dispersal distance (the minimum distance over water between donor and experimental sites) and latitude. Model results indicate direct effects of genetic distance and latitude on performance variation among the donor sites. Standardized effect strengths indicate that performance was roughly twice as sensitive to variation in genetic distance as to latitudinal variation. Dispersal distance had an indirect influence on performance through effects on genetic distance, indicating a typical pattern of genetic isolation by distance. Latitude also had an indirect effect on genetic distance through its linear relationship with dispersal distance. Three performance indicators had significant loadings on performance alone (mean clone diameter, mean number of stems, mean number of inflorescences), while the performance indicators mean stem height and mean stem width were also influenced by latitude. We suggest that dispersal distance and latitude should provide an adequate means of predicting performance in future S. alterniflora restorations and propose a maximum sampling distance of 300 km (holding latitude constant) to avoid the sampling of inappropriate ecotypes. ?? 2010 by the Ecological Society of America.

conindex: Estimation of concentration indices

PubMed Central

O'Donnell, Owen; O'Neill, Stephen; Van Ourti, Tom; Walsh, Brendan

2016-01-01

Concentration indices are frequently used to measure inequality in one variable over the distribution of another. Most commonly, they are applied to the measurement of socioeconomic-related inequality in health. We introduce a user-written Stata command conindex which provides point estimates and standard errors of a range of concentration indices. The command also graphs concentration curves (and Lorenz curves) and performs statistical inference for the comparison of inequality between groups. The article offers an accessible introduction to the various concentration indices that have been proposed to suit different measurement scales and ethical responses to inequality. The command’s capabilities and syntax are demonstrated through analysis of wealth-related inequality in health and healthcare in Cambodia. PMID:27053927

From Determinism and Probability to Chaos: Chaotic Evolution towards Philosophy and Methodology of Chaotic Optimization

PubMed Central

2015-01-01

We present and discuss philosophy and methodology of chaotic evolution that is theoretically supported by chaos theory. We introduce four chaotic systems, that is, logistic map, tent map, Gaussian map, and Hénon map, in a well-designed chaotic evolution algorithm framework to implement several chaotic evolution (CE) algorithms. By comparing our previous proposed CE algorithm with logistic map and two canonical differential evolution (DE) algorithms, we analyse and discuss optimization performance of CE algorithm. An investigation on the relationship between optimization capability of CE algorithm and distribution characteristic of chaotic system is conducted and analysed. From evaluation result, we find that distribution of chaotic system is an essential factor to influence optimization performance of CE algorithm. We propose a new interactive EC (IEC) algorithm, interactive chaotic evolution (ICE) that replaces fitness function with a real human in CE algorithm framework. There is a paired comparison-based mechanism behind CE search scheme in nature. A simulation experimental evaluation is conducted with a pseudo-IEC user to evaluate our proposed ICE algorithm. The evaluation result indicates that ICE algorithm can obtain a significant better performance than or the same performance as interactive DE. Some open topics on CE, ICE, fusion of these optimization techniques, algorithmic notation, and others are presented and discussed. PMID:25879067

A measure for provisional-and-urgent sanitary improvement in developing countries: septic-tank performance improvement.

PubMed

Harada, H; Dong, N T; Matsui, S

2008-01-01

Although many cities have planed to develop sewerages in developing countries, sewerage establishment still requires huge investment and engineering efforts. Improvement of existing sanitation facilities may contribute the betterment of urban sanitation before sewerage establishment. The purpose of this study is to propose a measure to improve urban sanitation in areas where a sewerage development plan is proposed but has not been yet established, based on a case study in Hanoi, Vietnam. We found that 90.5% of human excreta flowed into septic tanks. However, 89.6% of septic tanks have never been desludged in the past and their performance was observed to be at a low level. The study also showed that if they introduce regular desludging with a frequency of once a year, they can eliminate 72.8% of COD loads from septic tanks. It was indicated that the performance can be dramatically recovered by regular desludging, which could contribute urban sanitation improvement in Hanoi. In conclusion, the performance recovery of septic tanks by regular desludging was proposed as a provisional-and-urgent measure for urban sanitation improvement, together with the septage treatment in sewage sludge treatment facilities, which should be established earlier than other facilities of sewage treatment systems. IWA Publishing 2008.

From determinism and probability to chaos: chaotic evolution towards philosophy and methodology of chaotic optimization.

PubMed

Pei, Yan

2015-01-01

We present and discuss philosophy and methodology of chaotic evolution that is theoretically supported by chaos theory. We introduce four chaotic systems, that is, logistic map, tent map, Gaussian map, and Hénon map, in a well-designed chaotic evolution algorithm framework to implement several chaotic evolution (CE) algorithms. By comparing our previous proposed CE algorithm with logistic map and two canonical differential evolution (DE) algorithms, we analyse and discuss optimization performance of CE algorithm. An investigation on the relationship between optimization capability of CE algorithm and distribution characteristic of chaotic system is conducted and analysed. From evaluation result, we find that distribution of chaotic system is an essential factor to influence optimization performance of CE algorithm. We propose a new interactive EC (IEC) algorithm, interactive chaotic evolution (ICE) that replaces fitness function with a real human in CE algorithm framework. There is a paired comparison-based mechanism behind CE search scheme in nature. A simulation experimental evaluation is conducted with a pseudo-IEC user to evaluate our proposed ICE algorithm. The evaluation result indicates that ICE algorithm can obtain a significant better performance than or the same performance as interactive DE. Some open topics on CE, ICE, fusion of these optimization techniques, algorithmic notation, and others are presented and discussed.

A penalized quantitative structure-property relationship study on melting point of energetic carbocyclic nitroaromatic compounds using adaptive bridge penalty.

PubMed

Al-Fakih, A M; Algamal, Z Y; Lee, M H; Aziz, M

2018-05-01

A penalized quantitative structure-property relationship (QSPR) model with adaptive bridge penalty for predicting the melting points of 92 energetic carbocyclic nitroaromatic compounds is proposed. To ensure the consistency of the descriptor selection of the proposed penalized adaptive bridge (PBridge), we proposed a ridge estimator ([Formula: see text]) as an initial weight in the adaptive bridge penalty. The Bayesian information criterion was applied to ensure the accurate selection of the tuning parameter ([Formula: see text]). The PBridge based model was internally and externally validated based on [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], the Y-randomization test, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and the applicability domain. The validation results indicate that the model is robust and not due to chance correlation. The descriptor selection and prediction performance of PBridge for the training dataset outperforms the other methods used. PBridge shows the highest [Formula: see text] of 0.959, [Formula: see text] of 0.953, [Formula: see text] of 0.949 and [Formula: see text] of 0.959, and the lowest [Formula: see text] and [Formula: see text]. For the test dataset, PBridge shows a higher [Formula: see text] of 0.945 and [Formula: see text] of 0.948, and a lower [Formula: see text] and [Formula: see text], indicating its better prediction performance. The results clearly reveal that the proposed PBridge is useful for constructing reliable and robust QSPRs for predicting melting points prior to synthesizing new organic compounds.

A Novel Continuous Blood Pressure Estimation Approach Based on Data Mining Techniques.

PubMed

Miao, Fen; Fu, Nan; Zhang, Yuan-Ting; Ding, Xiao-Rong; Hong, Xi; He, Qingyun; Li, Ye

2017-11-01

Continuous blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for unobtrusive BP measurement. However, the accuracy of this approach must be improved for it to be viable for a wide range of applications. This study proposes a novel continuous BP estimation approach that combines data mining techniques with a traditional mechanism-driven model. First, 14 features derived from simultaneous electrocardiogram and photoplethysmogram signals were extracted for beat-to-beat BP estimation. A genetic algorithm-based feature selection method was then used to select BP indicators for each subject. Multivariate linear regression and support vector regression were employed to develop the BP model. The accuracy and robustness of the proposed approach were validated for static, dynamic, and follow-up performance. Experimental results based on 73 subjects showed that the proposed approach exhibited excellent accuracy in static BP estimation, with a correlation coefficient and mean error of 0.852 and -0.001 ± 3.102 mmHg for systolic BP, and 0.790 and -0.004 ± 2.199 mmHg for diastolic BP. Similar performance was observed for dynamic BP estimation. The robustness results indicated that the estimation accuracy was lower by a certain degree one day after model construction but was relatively stable from one day to six months after construction. The proposed approach is superior to the state-of-the-art PTT-based model for an approximately 2-mmHg reduction in the standard derivation at different time intervals, thus providing potentially novel insights for cuffless BP estimation.

Research on Method of Interactive Segmentation Based on Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yang, Y.; Li, H.; Han, Y.; Yu, F.

2017-09-01

In this paper, we aim to solve the object extraction problem in remote sensing images using interactive segmentation tools. Firstly, an overview of the interactive segmentation algorithm is proposed. Then, our detailed implementation of intelligent scissors and GrabCut for remote sensing images is described. Finally, several experiments on different typical features (water area, vegetation) in remote sensing images are performed respectively. Compared with the manual result, it indicates that our tools maintain good feature boundaries and show good performance.

Evaluating color deficiency simulation and daltonization methods through visual search and sample-to-match: SaMSEM and ViSDEM

NASA Astrophysics Data System (ADS)

Simon-Liedtke, Joschua T.; Farup, Ivar; Laeng, Bruno

2015-01-01

Color deficient people might be confronted with minor difficulties when navigating through daily life, for example when reading websites or media, navigating with maps, retrieving information from public transport schedules and others. Color deficiency simulation and daltonization methods have been proposed to better understand problems of color deficient individuals and to improve color displays for their use. However, it remains unclear whether these color prosthetic" methods really work and how well they improve the performance of color deficient individuals. We introduce here two methods to evaluate color deficiency simulation and daltonization methods based on behavioral experiments that are widely used in the field of psychology. Firstly, we propose a Sample-to-Match Simulation Evaluation Method (SaMSEM); secondly, we propose a Visual Search Daltonization Evaluation Method (ViSDEM). Both methods can be used to validate and allow the generalization of the simulation and daltonization methods related to color deficiency. We showed that both the response times (RT) and the accuracy of SaMSEM can be used as an indicator of the success of color deficiency simulation methods and that performance in the ViSDEM can be used as an indicator for the efficacy of color deficiency daltonization methods. In future work, we will include comparison and analysis of different color deficiency simulation and daltonization methods with the help of SaMSEM and ViSDEM.

A new post-phase rotation based dynamic receive beamforming architecture for smartphone-based wireless ultrasound imaging

NASA Astrophysics Data System (ADS)

Park, Minsuk; Kang, Jeeun; Lee, Gunho; Kim, Min; Song, Tai-Kyong

2016-04-01

Recently, a portable US imaging system using smart devices is highlighted for enhancing the portability of diagnosis. Especially, the system combination can enhance the user experience during whole US diagnostic procedures by employing the advanced wireless communication technology integrated in a smart device, e.g., WiFi, Bluetooth, etc. In this paper, an effective post-phase rotation-based dynamic receive beamforming (PRBF-POST) method is presented for wireless US imaging device integrating US probe system and commercial smart device. In conventional, the frame rate of conventional PRBF (PRBF-CON) method suffers from the large amount of calculations for the bifurcated processing paths of in-phase and quadrature signal components as the number of channel increase. Otherwise, the proposed PRBF-POST method can preserve the frame rate regardless of the number of channels by firstly aggregating the baseband IQ data along the channels whose phase quantization levels are identical ahead of phase rotation and summation procedures on a smart device. To evaluate the performance of the proposed PRBF-POST method, the pointspread functions of PRBF-CON and PRBF-POST methods were compared each other. Also, the frame rate of each PRBF method was measured 20-times to calculate the average frame rate and its standard deviation. As a result, the PRBFCON and PRBF-POST methods indicates identical beamforming performance in the Field-II simulation (correlation coefficient = 1). Also, the proposed PRBF-POST method indicates the consistent frame rate for varying number of channels (i.e., 44.25, 44.32, and 44.35 fps for 16, 64, and 128 channels, respectively), while the PRBF-CON method shows the decrease of frame rate as the number of channel increase (39.73, 13.19, and 3.8 fps). These results indicate that the proposed PRBF-POST method can be more advantageous for implementing the wireless US imaging system than the PRBF-CON method.

Structural Health Monitoring of a Composite Panel Based on PZT Sensors and a Transfer Impedance Framework.

PubMed

Dziendzikowski, Michal; Niedbala, Patryk; Kurnyta, Artur; Kowalczyk, Kamil; Dragan, Krzysztof

2018-05-11

One of the ideas for development of Structural Health Monitoring (SHM) systems is based on excitation of elastic waves by a network of PZT piezoelectric transducers integrated with the structure. In the paper, a variant of the so-called Transfer Impedance (TI) approach to SHM is followed. Signal characteristics, called the Damage Indices (DIs), were proposed for data presentation and analysis. The idea underlying the definition of DIs was to maintain most of the information carried by the voltage induced on PZT sensors by elastic waves. In particular, the DIs proposed in the paper should be sensitive to all types of damage which can influence the amplitude or the phase of the voltage induced on the sensor. Properties of the proposed DIs were investigated experimentally using a GFRP composite panel equipped with PZT networks attached to its surface and embedded into its internal structure. Repeatability and stability of DI indications under controlled conditions were verified in tests. Also, some performance indicators for surface-attached and structure-embedded sensors were obtained. The DIs' behavior was dependent mostly on the presence of a simulated damage in the structure. Anisotropy of mechanical properties of the specimen, geometrical properties of PZT network as well as, to some extent, the technology of sensor integration with the structure were irrelevant for damage indication. This property enables the method to be used for damage detection and classification.

Gait-Cycle-Driven Transmission Power Control Scheme for a Wireless Body Area Network.

PubMed

Zang, Weilin; Li, Ye

2018-05-01

In a wireless body area network (WBAN), walking movements can result in rapid channel fluctuations, which severely degrade the performance of transmission power control (TPC) schemes. On the other hand, these channel fluctuations are often periodic and are time-synchronized with the user's gait cycle, since they are all driven from the walking movements. In this paper, we propose a novel gait-cycle-driven transmission power control (G-TPC) for a WBAN. The proposed G-TPC scheme reinforces the existing TPC scheme by exploiting the periodic channel fluctuation in the walking scenario. In the proposed scheme, the user's gait cycle information acquired by an accelerometer is used as beacons for arranging the transmissions at the time points with the ideal channel state. The specific transmission power is then determined by using received signal strength indication (RSSI). An experiment was conducted to evaluate the energy efficiency and reliability of the proposed G-TPC based on a CC2420 platform. The results reveal that compared to the original RSSI/link-quality-indication-based TPC, G-TPC reduces energy consumption by 25% on the sensor node and reduce the packet loss rate by 65%.

Condition monitoring and fault diagnosis of motor bearings using undersampled vibration signals from a wireless sensor network

NASA Astrophysics Data System (ADS)

Lu, Siliang; Zhou, Peng; Wang, Xiaoxian; Liu, Yongbin; Liu, Fang; Zhao, Jiwen

2018-02-01

Wireless sensor networks (WSNs) which consist of miscellaneous sensors are used frequently in monitoring vital equipment. Benefiting from the development of data mining technologies, the massive data generated by sensors facilitate condition monitoring and fault diagnosis. However, too much data increase storage space, energy consumption, and computing resource, which can be considered fatal weaknesses for a WSN with limited resources. This study investigates a new method for motor bearings condition monitoring and fault diagnosis using the undersampled vibration signals acquired from a WSN. The proposed method, which is a fusion of the kurtogram, analog domain bandpass filtering, bandpass sampling, and demodulated resonance technique, can reduce the sampled data length while retaining the monitoring and diagnosis performance. A WSN prototype was designed, and simulations and experiments were conducted to evaluate the effectiveness and efficiency of the proposed method. Experimental results indicated that the sampled data length and transmission time of the proposed method result in a decrease of over 80% in comparison with that of the traditional method. Therefore, the proposed method indicates potential applications on condition monitoring and fault diagnosis of motor bearings installed in remote areas, such as wind farms and offshore platforms.

Parameter estimation in Cox models with missing failure indicators and the OPPERA study.

PubMed

Brownstein, Naomi C; Cai, Jianwen; Slade, Gary D; Bair, Eric

2015-12-30

In a prospective cohort study, examining all participants for incidence of the condition of interest may be prohibitively expensive. For example, the "gold standard" for diagnosing temporomandibular disorder (TMD) is a physical examination by a trained clinician. In large studies, examining all participants in this manner is infeasible. Instead, it is common to use questionnaires to screen for incidence of TMD and perform the "gold standard" examination only on participants who screen positively. Unfortunately, some participants may leave the study before receiving the "gold standard" examination. Within the framework of survival analysis, this results in missing failure indicators. Motivated by the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study, a large cohort study of TMD, we propose a method for parameter estimation in survival models with missing failure indicators. We estimate the probability of being an incident case for those lacking a "gold standard" examination using logistic regression. These estimated probabilities are used to generate multiple imputations of case status for each missing examination that are combined with observed data in appropriate regression models. The variance introduced by the procedure is estimated using multiple imputation. The method can be used to estimate both regression coefficients in Cox proportional hazard models as well as incidence rates using Poisson regression. We simulate data with missing failure indicators and show that our method performs as well as or better than competing methods. Finally, we apply the proposed method to data from the OPPERA study. Copyright © 2015 John Wiley & Sons, Ltd.

On the diffuse fraction of daily and monthly global radiation for the island of Cyprus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacovides, C.P.; Hadjioannou, L.; Pashiardis, S.

1996-06-01

Six years of hourly global and diffuse irradiation measurements on a horizontal surface performed at Athalassa, Cyprus, are used to establish a relationship between the daily diffuse fraction and the daily clearness index. Two types of correlations - yearly and seasonal - have been developed. These correlations, of first and third order in the clearness index are compared to the various correlations established by Collares-Pereira and Rabl (1979), Newland (1989), Erbs et al. (1982), Rao et al. (1984), Page (1961), Liu and Jordan (1960) and Lalas et al. (1987). The comparison has been performed in terms of the widely usedmore » statistical indicators (MBE) and (RMSE) errors; and additional statistical indicator, the t-statistic, combining the earlier indicators, is introduced. The results indicate that the proposed yearly correlation matches the earlier correlations quite closely and all correlations examined yield results that are statistically significant. For large K{sub t} > 0.60 values, most of the earlier correlations exhibit a slight tendency to systematically overestimate the diffuse fraction. This marginal disagreement between the earlier correlations and the proposed model is probably significantly affected by the clear sky conditions that prevail over Cyprus for most of the time as well as atmospheric humidity content. It is clear that the standard correlations examined in this analysis appear to be location-independent models for diffuse irradiation predictions, at least for the Cyprus case. 13 refs., 5 figs., 4 tabs.« less

A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals.

PubMed

Zarei, Roozbeh; He, Jing; Siuly, Siuly; Zhang, Yanchun

2017-07-01

Feature extraction of EEG signals plays a significant role in Brain-computer interface (BCI) as it can significantly affect the performance and the computational time of the system. The main aim of the current work is to introduce an innovative algorithm for acquiring reliable discriminating features from EEG signals to improve classification performances and to reduce the time complexity. This study develops a robust feature extraction method combining the principal component analysis (PCA) and the cross-covariance technique (CCOV) for the extraction of discriminatory information from the mental states based on EEG signals in BCI applications. We apply the correlation based variable selection method with the best first search on the extracted features to identify the best feature set for characterizing the distribution of mental state signals. To verify the robustness of the proposed feature extraction method, three machine learning techniques: multilayer perceptron neural networks (MLP), least square support vector machine (LS-SVM), and logistic regression (LR) are employed on the obtained features. The proposed methods are evaluated on two publicly available datasets. Furthermore, we evaluate the performance of the proposed methods by comparing it with some recently reported algorithms. The experimental results show that all three classifiers achieve high performance (above 99% overall classification accuracy) for the proposed feature set. Among these classifiers, the MLP and LS-SVM methods yield the best performance for the obtained feature. The average sensitivity, specificity and classification accuracy for these two classifiers are same, which are 99.32%, 100%, and 99.66%, respectively for the BCI competition dataset IVa and 100%, 100%, and 100%, for the BCI competition dataset IVb. The results also indicate the proposed methods outperform the most recently reported methods by at least 0.25% average accuracy improvement in dataset IVa. The execution time results show that the proposed method has less time complexity after feature selection. The proposed feature extraction method is very effective for getting representatives information from mental states EEG signals in BCI applications and reducing the computational complexity of classifiers by reducing the number of extracted features. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving benchmarking by using an explicit framework for the development of composite indicators: an example using pediatric quality of care

PubMed Central

2010-01-01

Background The measurement of healthcare provider performance is becoming more widespread. Physicians have been guarded about performance measurement, in part because the methodology for comparative measurement of care quality is underdeveloped. Comprehensive quality improvement will require comprehensive measurement, implying the aggregation of multiple quality metrics into composite indicators. Objective To present a conceptual framework to develop comprehensive, robust, and transparent composite indicators of pediatric care quality, and to highlight aspects specific to quality measurement in children. Methods We reviewed the scientific literature on composite indicator development, health systems, and quality measurement in the pediatric healthcare setting. Frameworks were selected for explicitness and applicability to a hospital-based measurement system. Results We synthesized various frameworks into a comprehensive model for the development of composite indicators of quality of care. Among its key premises, the model proposes identifying structural, process, and outcome metrics for each of the Institute of Medicine's six domains of quality (safety, effectiveness, efficiency, patient-centeredness, timeliness, and equity) and presents a step-by-step framework for embedding the quality of care measurement model into composite indicator development. Conclusions The framework presented offers researchers an explicit path to composite indicator development. Without a scientifically robust and comprehensive approach to measurement of the quality of healthcare, performance measurement will ultimately fail to achieve its quality improvement goals. PMID:20181129

Compressive Sensing of Foot Gait Signals and Its Application for the Estimation of Clinically Relevant Time Series.

PubMed

Pant, Jeevan K; Krishnan, Sridhar

2016-07-01

A new signal reconstruction algorithm for compressive sensing based on the minimization of a pseudonorm which promotes block-sparse structure on the first-order difference of the signal is proposed. Involved optimization is carried out by using a sequential version of Fletcher-Reeves' conjugate-gradient algorithm, and the line search is based on Banach's fixed-point theorem. The algorithm is suitable for the reconstruction of foot gait signals which admit block-sparse structure on the first-order difference. An additional algorithm for the estimation of stride-interval, swing-interval, and stance-interval time series from the reconstructed foot gait signals is also proposed. This algorithm is based on finding zero crossing indices of the foot gait signal and using the resulting indices for the computation of time series. Extensive simulation results demonstrate that the proposed signal reconstruction algorithm yields improved signal-to-noise ratio and requires significantly reduced computational effort relative to several competing algorithms over a wide range of compression ratio. For a compression ratio in the range from 88% to 94%, the proposed algorithm is found to offer improved accuracy for the estimation of clinically relevant time-series parameters, namely, the mean value, variance, and spectral index of stride-interval, stance-interval, and swing-interval time series, relative to its nearest competitor algorithm. The improvement in performance for compression ratio as high as 94% indicates that the proposed algorithms would be useful for designing compressive sensing-based systems for long-term telemonitoring of human gait signals.

A data-driven approach for denoising GNSS position time series

NASA Astrophysics Data System (ADS)

Li, Yanyan; Xu, Caijun; Yi, Lei; Fang, Rongxin

2017-12-01

Global navigation satellite system (GNSS) datasets suffer from common mode error (CME) and other unmodeled errors. To decrease the noise level in GNSS positioning, we propose a new data-driven adaptive multiscale denoising method in this paper. Both synthetic and real-world long-term GNSS datasets were employed to assess the performance of the proposed method, and its results were compared with those of stacking filtering, principal component analysis (PCA) and the recently developed multiscale multiway PCA. It is found that the proposed method can significantly eliminate the high-frequency white noise and remove the low-frequency CME. Furthermore, the proposed method is more precise for denoising GNSS signals than the other denoising methods. For example, in the real-world example, our method reduces the mean standard deviation of the north, east and vertical components from 1.54 to 0.26, 1.64 to 0.21 and 4.80 to 0.72 mm, respectively. Noise analysis indicates that for the original signals, a combination of power-law plus white noise model can be identified as the best noise model. For the filtered time series using our method, the generalized Gauss-Markov model is the best noise model with the spectral indices close to - 3, indicating that flicker walk noise can be identified. Moreover, the common mode error in the unfiltered time series is significantly reduced by the proposed method. After filtering with our method, a combination of power-law plus white noise model is the best noise model for the CMEs in the study region.

Advanced, Cost-Based Indices for Forecasting the Generation of Photovoltaic Power

NASA Astrophysics Data System (ADS)

Bracale, Antonio; Carpinelli, Guido; Di Fazio, Annarita; Khormali, Shahab

2014-01-01

Distribution systems are undergoing significant changes as they evolve toward the grids of the future, which are known as smart grids (SGs). The perspective of SGs is to facilitate large-scale penetration of distributed generation using renewable energy sources (RESs), encourage the efficient use of energy, reduce systems' losses, and improve the quality of power. Photovoltaic (PV) systems have become one of the most promising RESs due to the expected cost reduction and the increased efficiency of PV panels and interfacing converters. The ability to forecast power-production information accurately and reliably is of primary importance for the appropriate management of an SG and for making decisions relative to the energy market. Several forecasting methods have been proposed, and many indices have been used to quantify the accuracy of the forecasts of PV power production. Unfortunately, the indices that have been used have deficiencies and usually do not directly account for the economic consequences of forecasting errors in the framework of liberalized electricity markets. In this paper, advanced, more accurate indices are proposed that account directly for the economic consequences of forecasting errors. The proposed indices also were compared to the most frequently used indices in order to demonstrate their different, improved capability. The comparisons were based on the results obtained using a forecasting method based on an artificial neural network. This method was chosen because it was deemed to be one of the most promising methods available due to its capability for forecasting PV power. Numerical applications also are presented that considered an actual PV plant to provide evidence of the forecasting performances of all of the indices that were considered.

Multi-focus image fusion algorithm using NSCT and MPCNN

NASA Astrophysics Data System (ADS)

Liu, Kang; Wang, Lianli

2018-04-01

Based on nonsubsampled contourlet transform (NSCT) and modified pulse coupled neural network (MPCNN), the paper proposes an effective method of image fusion. Firstly, the paper decomposes the source image into the low-frequency components and high-frequency components using NSCT, and then processes the low-frequency components by regional statistical fusion rules. For high-frequency components, the paper calculates the spatial frequency (SF), which is input into MPCNN model to get relevant coefficients according to the fire-mapping image of MPCNN. At last, the paper restructures the final image by inverse transformation of low-frequency and high-frequency components. Compared with the wavelet transformation (WT) and the traditional NSCT algorithm, experimental results indicate that the method proposed in this paper achieves an improvement both in human visual perception and objective evaluation. It indicates that the method is effective, practical and good performance.

Continuing assessment of the 5 day sodium carbonate-ammonium nitrate extraction assay as an indicator test for silicon fertilizers

USDA-ARS?s Scientific Manuscript database

The five day sodium carbonate-ammonium nitrate extraction assay has been proposed by the AAFPCO as a standard test to identify fertilizers that provide plant-available Si. A single-lab validation test was previously performed; however, the analysis lacked any correlation to a grow-out study. To do...

The Performance of Local Dependence Measures with Psychological Data

ERIC Educational Resources Information Center

Houts, Carrie R.; Edwards, Michael C.

2013-01-01

The violation of the assumption of local independence when applying item response theory (IRT) models has been shown to have a negative impact on all estimates obtained from the given model. Numerous indices and statistics have been proposed to aid analysts in the detection of local dependence (LD). A Monte Carlo study was conducted to evaluate…

An Algorithm to Improve Test Answer Copying Detection Using the Omega Statistic

ERIC Educational Resources Information Center

Maeda, Hotaka; Zhang, Bo

2017-01-01

The omega (?) statistic is reputed to be one of the best indices for detecting answer copying on multiple choice tests, but its performance relies on the accurate estimation of copier ability, which is challenging because responses from the copiers may have been contaminated. We propose an algorithm that aims to identify and delete the suspected…

A comparison of four embedded validity indices for the RBANS in a memory disorders clinic.

PubMed

Paulson, Daniel; Horner, Michael David; Bachman, David

2015-05-01

This examination of four embedded validity indices for the Repeated Battery for the Assessment of Neuropsychological Status (RBANS) explores the potential utility of integrating cognitive and self-reported depressive measures. Examined indices include the proposed RBANS Performance Validity Index (RBANS PVI) and the Charleston Revised Index of Effort for the RBANS (CRIER). The CRIER represented the novel integration of cognitive test performance and depression self-report information. The sample included 234 patients without dementia who could be identified as having demonstrated either valid or invalid responding, based on standardized criteria. Sensitivity and specificity for invalid responding varied widely, with the CRIER emerging as the best all-around index (sensitivity = 0.84, specificity = 0.90, AUC = 0.94). Findings support the use of embedded response validity indices, and suggest that the integration of cognitive and self-report depression data may optimize detection of invalid responding among older Veterans. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

NASA Astrophysics Data System (ADS)

Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

2018-03-01

The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

A solution quality assessment method for swarm intelligence optimization algorithms.

PubMed

Zhang, Zhaojun; Wang, Gai-Ge; Zou, Kuansheng; Zhang, Jianhua

2014-01-01

Nowadays, swarm intelligence optimization has become an important optimization tool and wildly used in many fields of application. In contrast to many successful applications, the theoretical foundation is rather weak. Therefore, there are still many problems to be solved. One problem is how to quantify the performance of algorithm in finite time, that is, how to evaluate the solution quality got by algorithm for practical problems. It greatly limits the application in practical problems. A solution quality assessment method for intelligent optimization is proposed in this paper. It is an experimental analysis method based on the analysis of search space and characteristic of algorithm itself. Instead of "value performance," the "ordinal performance" is used as evaluation criteria in this method. The feasible solutions were clustered according to distance to divide solution samples into several parts. Then, solution space and "good enough" set can be decomposed based on the clustering results. Last, using relative knowledge of statistics, the evaluation result can be got. To validate the proposed method, some intelligent algorithms such as ant colony optimization (ACO), particle swarm optimization (PSO), and artificial fish swarm algorithm (AFS) were taken to solve traveling salesman problem. Computational results indicate the feasibility of proposed method.

Magnetic induction of hyperthermia by a modified self-learning fuzzy temperature controller

NASA Astrophysics Data System (ADS)

Wang, Wei-Cheng; Tai, Cheng-Chi

2017-07-01

The aim of this study involved developing a temperature controller for magnetic induction hyperthermia (MIH). A closed-loop controller was applied to track a reference model to guarantee a desired temperature response. The MIH system generated an alternating magnetic field to heat a high magnetic permeability material. This wireless induction heating had few side effects when it was extensively applied to cancer treatment. The effects of hyperthermia strongly depend on the precise control of temperature. However, during the treatment process, the control performance is degraded due to severe perturbations and parameter variations. In this study, a modified self-learning fuzzy logic controller (SLFLC) with a gain tuning mechanism was implemented to obtain high control performance in a wide range of treatment situations. This implementation was performed by appropriately altering the output scaling factor of a fuzzy inverse model to adjust the control rules. In this study, the proposed SLFLC was compared to the classical self-tuning fuzzy logic controller and fuzzy model reference learning control. Additionally, the proposed SLFLC was verified by conducting in vitro experiments with porcine liver. The experimental results indicated that the proposed controller showed greater robustness and excellent adaptability with respect to the temperature control of the MIH system.

A Novel Adjustment Method for Shearer Traction Speed through Integration of T-S Cloud Inference Network and Improved PSO

PubMed Central

Si, Lei; Wang, Zhongbin; Yang, Yinwei

2014-01-01

In order to efficiently and accurately adjust the shearer traction speed, a novel approach based on Takagi-Sugeno (T-S) cloud inference network (CIN) and improved particle swarm optimization (IPSO) is proposed. The T-S CIN is built through the combination of cloud model and T-S fuzzy neural network. Moreover, the IPSO algorithm employs parameter automation adjustment strategy and velocity resetting to significantly improve the performance of basic PSO algorithm in global search and fine-tuning of the solutions, and the flowchart of proposed approach is designed. Furthermore, some simulation examples are carried out and comparison results indicate that the proposed method is feasible, efficient, and is outperforming others. Finally, an industrial application example of coal mining face is demonstrated to specify the effect of proposed system. PMID:25506358

Study on Building Extraction from High-Resolution Images Using Mbi

NASA Astrophysics Data System (ADS)

Ding, Z.; Wang, X. Q.; Li, Y. L.; Zhang, S. S.

2018-04-01

Building extraction from high resolution remote sensing images is a hot research topic in the field of photogrammetry and remote sensing. However, the diversity and complexity of buildings make building extraction methods still face challenges in terms of accuracy, efficiency, and so on. In this study, a new building extraction framework based on MBI and combined with image segmentation techniques, spectral constraint, shadow constraint, and shape constraint is proposed. In order to verify the proposed method, worldview-2, GF-2, GF-1 remote sensing images covered Xiamen Software Park were used for building extraction experiments. Experimental results indicate that the proposed method improve the original MBI significantly, and the correct rate is over 86 %. Furthermore, the proposed framework reduces the false alarms by 42 % on average compared to the performance of the original MBI.

Low-reflection beam refractions by ultrathin Huygens metasurface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jia, Sheng Li; State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096; Synergetic Innovation Center of Wireless Communication Technology, Southeast University, Nanjing 210096

2015-06-15

We propose a Huygens source unit cell to develop an ultrathin low-reflection metasurface, which could provide extreme controls of phases of the transmitted waves. Both electric and magnetic currents are supported by the proposed unit cell, thus leading to highly efficient and full controls of phases. The coupling between electric and magnetic responses is negligible, which will significantly reduce the difficulty of design. Since the unit cell of metasurface is printed on two bonded boards, the fabrication process is simplified and the thickness of metasurface is reduced. Based on the proposed unit cell, a beam-refracting metasurface with low-reflection is designedmore » and manufactured. Both near-field and far-field characteristics of the beam-refracting metasurface are investigated by simulations and measurements, which indicate that the proposed Huygens metasurface performs well in controlling electromagnetic waves.« less

Building sustainability indicators in the health dimension for solid waste management 1

PubMed Central

Veiga, Tatiane Bonametti; Coutinho, Silvano da Silva; Andre, Silvia Carla Silva; Mendes, Adriana Aparecida; Takayanagui, Angela Maria Magosso

2016-01-01

ABSTRACT Objective: to prepare a list of sustainability indicators in the health dimension, for urban solid waste management. Methods: a descriptive and exploratory study performed jointly with 52 solid waste specialists, using a three-steps Delphi technique, and a scale measuring the degree of importance for agreement among the researchers in this area. Results: the subjects under study were 92,3% PhD's concentrated in the age group from 30 to 40 years old (32,7%) and 51% were men. At the end of the 3rd step of the Delphi process, the average and standard deviation of all the proposed indicators varied from 4,22 (±0,79) to 4,72 (±0,64), in a scale of scores for each indicator from 1 to 5 (from "dispensable" to "very important"). Results showed the level of correspondence among the participants ranging from 82% to 94% related to those indicators. Conclusion: the proposed indicators may be helpful not only for the identification of data that is updated in this area, but also to enlarge the field of debates of the environmental health policies, directed not only for urban solid waste but for the achievement of better health conditions for the Brazilian context. PMID:27508905

Analysis of the policymaking process in Burkina Faso's health sector: case studies of the creation of two health system support units.

PubMed

Zida, Andre; Lavis, John N; Sewankambo, Nelson K; Kouyate, Bocar; Moat, Kaelan; Shearer, Jessica

2017-02-13

Burkina Faso has made a number of health system policy decisions to improve performance on health indicators and strengthen responsiveness to health-related challenges. These included the creation of a General Directorate of Health Information and Statistics (DGISS) and a technical unit to coordinate performance-based financing (CT-FBR). We analysed the policymaking processes associated with the establishment of these units, and documented the factors that influenced this process. We used a multiple-case study design based on Kingdon's agenda-setting model to investigate the DGISS and CT-FBR policymaking processes. Data were collected from interviews with key informants (n = 28), published literature, policy documents (including two strategic and 230 action plans), and 55 legal/regulatory texts. Interviews were analysed using thematic qualitative analysis. Data from the documentary analysis were triangulated with the qualitative interview data. Key factors influencing the policymaking processes associated with the two units involved the 'problem' (problem identification), 'policy' (formation of policy proposals), and 'politics' (political climate/change) streams, which came together in a way that resulted in proposals being placed on the decision agenda. A number of problems with Burkina Faso's health information and financing systems were identified. Policy proposals for the DGISS and CT-FBR units were developed in response to these problems, emerging from several sources including development partners. Changes in political and public service administrations (specifically the 2008 appointment of a new Minister of Health and the establishment of a new budget allocation system), with corresponding changes in the actors and interests involved, appeared key in elevating the proposals to the decision agenda. Efforts to improve performance on health indicators and strengthen responsiveness to health-related challenges need focus on the need for a compelling problem, a viable policy, and conducive politics in order to make it to the decision agenda.

Tokyo Guidelines 2018: flowchart for the management of acute cholecystitis.

PubMed

Okamoto, Kohji; Suzuki, Kenji; Takada, Tadahiro; Strasberg, Steven M; Asbun, Horacio J; Endo, Itaru; Iwashita, Yukio; Hibi, Taizo; Pitt, Henry A; Umezawa, Akiko; Asai, Koji; Han, Ho-Seong; Hwang, Tsann-Long; Mori, Yasuhisa; Yoon, Yoo-Seok; Huang, Wayne Shih-Wei; Belli, Giulio; Dervenis, Christos; Yokoe, Masamichi; Kiriyama, Seiki; Itoi, Takao; Jagannath, Palepu; Garden, O James; Miura, Fumihiko; Nakamura, Masafumi; Horiguchi, Akihiko; Wakabayashi, Go; Cherqui, Daniel; de Santibañes, Eduardo; Shikata, Satoru; Noguchi, Yoshinori; Ukai, Tomohiko; Higuchi, Ryota; Wada, Keita; Honda, Goro; Supe, Avinash Nivritti; Yoshida, Masahiro; Mayumi, Toshihiko; Gouma, Dirk J; Deziel, Daniel J; Liau, Kui-Hin; Chen, Miin-Fu; Shibao, Kazunori; Liu, Keng-Hao; Su, Cheng-Hsi; Chan, Angus C W; Yoon, Dong-Sup; Choi, In-Seok; Jonas, Eduard; Chen, Xiao-Ping; Fan, Sheung Tat; Ker, Chen-Guo; Giménez, Mariano Eduardo; Kitano, Seigo; Inomata, Masafumi; Hirata, Koichi; Inui, Kazuo; Sumiyama, Yoshinobu; Yamamoto, Masakazu

2018-01-01

We propose a new flowchart for the treatment of acute cholecystitis (AC) in the Tokyo Guidelines 2018 (TG18). Grade III AC was not indicated for straightforward laparoscopic cholecystectomy (Lap-C). Following analysis of subsequent clinical investigations and drawing on Big Data in particular, TG18 proposes that some Grade III AC can be treated by Lap-C when performed at advanced centers with specialized surgeons experienced in this procedure and for patients that satisfy certain strict criteria. For Grade I, TG18 recommends early Lap-C if the patients meet the criteria of Charlson comorbidity index (CCI) ≤5 and American Society of Anesthesiologists physical status classification (ASA-PS) ≤2. For Grade II AC, if patients meet the criteria of CCI ≤5 and ASA-PS ≤2, TG18 recommends early Lap-C performed by experienced surgeons; and if not, after medical treatment and/or gallbladder drainage, Lap-C would be indicated. TG18 proposes that Lap-C is indicated in Grade III patients with strict criteria. These are that the patients have favorable organ system failure, and negative predictive factors, who meet the criteria of CCI ≤3 and ASA-PS ≤2 and who are being treated at an advanced center (where experienced surgeons practice). If the patient is not considered suitable for early surgery, TG18 recommends early/urgent biliary drainage followed by delayed Lap-C once the patient's overall condition has improved. Free full articles and mobile app of TG18 are available at: http://www.jshbps.jp/modules/en/index.php?content_id=47. Related clinical questions and references are also included. © 2017 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

An Improved Genetic Fuzzy Logic Control Method to Reduce the Enlargement of Coal Floor Deformation in Shearer Memory Cutting Process

PubMed Central

Tan, Chao; Xu, Rongxin; Wang, Zhongbin; Si, Lei; Liu, Xinhua

2016-01-01

In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement of coal floor deformation is analyzed and a model is built. Then, the framework of proposed approach is built. Moreover, the constituents of GA such as tangent function roulette wheel selection (Tan-RWS) selection, uniform crossover, and nonuniform mutation are employed to enhance the performance of GFLC. Finally, two simulation examples and an industrial application example are carried out and the results indicate that the proposed method is feasible and efficient. PMID:27217824

CHRONIC ZINC SCREENING WATER EFFECT RATIO FOR THE H-12 OUTFALL, SAVANNAH RIVER SITE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coughlin, D.; Looney, B.; Millings, M.

2009-01-13

In response to proposed Zn limits for the NPDES outfall H-12, a Zn screening Water Effects Ratio (WER) study was conducted to determine if a full site-specific WER is warranted. Using standard assumptions for relating the lab results to the stream, the screening WER data were consistent with the proposed Zn limit and suggest that a full WER would result in a similar limit. Addition of a humate amendment to the outfall water reduced Zn toxicity, but the toxicity reduction was relatively small and unlikely to impact proposed Zn limits. The screening WER data indicated that the time and expensemore » required to perform a full WER for Zn is not warranted.« less

A simultaneous all-optical half/full-subtraction strategy using cascaded highly nonlinear fibers

NASA Astrophysics Data System (ADS)

Singh, Karamdeep; Kaur, Gurmeet; Singh, Maninder Lal

2018-02-01

Using non-linear effects such as cross-gain modulation (XGM) and cross-phase modulation (XPM) inside two highly non-linear fibres (HNLF) arranged in cascaded configuration, a simultaneous half/full-subtracter is proposed. The proposed simultaneous half/full-subtracter design is attractive due to several features such as input data pattern independence and usage of minimal number of non-linear elements i.e. HNLFs. Proof of concept simulations have been conducted at 100 Gbps rate, indicating fine performance, as extinction ratio (dB) > 6.28 dB and eye opening factors (EO) > 77.1072% are recorded for each implemented output. The proposed simultaneous half/full-subtracter can be used as a key component in all-optical information processing circuits.

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

PubMed

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

2012-01-01

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

Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter.

PubMed

Fu, Xingang; Li, Shuhui; Fairbank, Michael; Wunsch, Donald C; Alonso, Eduardo

2015-09-01

This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an RNN using the LM algorithm, a new forward accumulation through time (FATT) algorithm is proposed to calculate the Jacobian matrix required by the LM algorithm. This paper explores how to incorporate FATT into the LM algorithm. The results show that the combination of the LM and FATT algorithms trains RNNs better than the conventional backpropagation through time algorithm. This paper presents an analytical study on the optimal control of GCCs, including theoretically ideal optimal and suboptimal controllers. To overcome the inapplicability of the optimal GCC controller under practical conditions, a new RNN controller with an improved input structure is proposed to approximate the ideal optimal controller. The performance of an ideal optimal controller and a well-trained RNN controller was compared in close to real-life power converter switching environments, demonstrating that the proposed RNN controller can achieve close to ideal optimal control performance even under low sampling rate conditions. The excellent performance of the proposed RNN controller under challenging and distorted system conditions further indicates the feasibility of using an RNN to approximate optimal control in practical applications.

EEG-based learning system for online motion sickness level estimation in a dynamic vehicle environment.

PubMed

Lin, Chin-Teng; Tsai, Shu-Fang; Ko, Li-Wei

2013-10-01

Motion sickness is a common experience for many people. Several previous researches indicated that motion sickness has a negative effect on driving performance and sometimes leads to serious traffic accidents because of a decline in a person's ability to maintain self-control. This safety issue has motivated us to find a way to prevent vehicle accidents. Our target was to determine a set of valid motion sickness indicators that would predict the occurrence of a person's motion sickness as soon as possible. A successful method for the early detection of motion sickness will help us to construct a cognitive monitoring system. Such a monitoring system can alert people before they become sick and prevent them from being distracted by various motion sickness symptoms while driving or riding in a car. In our past researches, we investigated the physiological changes that occur during the transition of a passenger's cognitive state using electroencephalography (EEG) power spectrum analysis, and we found that the EEG power responses in the left and right motors, parietal, lateral occipital, and occipital midline brain areas were more highly correlated to subjective sickness levels than other brain areas. In this paper, we propose the use of a self-organizing neural fuzzy inference network (SONFIN) to estimate a driver's/passenger's sickness level based on EEG features that have been extracted online from five motion sickness-related brain areas, while either in real or virtual vehicle environments. The results show that our proposed learning system is capable of extracting a set of valid motion sickness indicators that originated from EEG dynamics, and through SONFIN, a neuro-fuzzy prediction model, we successfully translated the set of motion sickness indicators into motion sickness levels. The overall performance of this proposed EEG-based learning system can achieve an average prediction accuracy of ~82%.

A Chaotic Ordered Hierarchies Consistency Analysis Performance Evaluation Model

NASA Astrophysics Data System (ADS)

Yeh, Wei-Chang

2013-02-01

The Hierarchies Consistency Analysis (HCA) is proposed by Guh in-cooperated along with some case study on a Resort to reinforce the weakness of Analytical Hierarchy Process (AHP). Although the results obtained enabled aid for the Decision Maker to make more reasonable and rational verdicts, the HCA itself is flawed. In this paper, our objective is to indicate the problems of HCA, and then propose a revised method called chaotic ordered HCA (COH in short) which can avoid problems. Since the COH is based upon Guh's method, the Decision Maker establishes decisions in a way similar to that of the original method.

Electrophysiological indices of anterior cingulate cortex function reveal changing levels of cognitive effort and reward valuation that sustain task performance.

PubMed

Umemoto, Akina; Inzlicht, Michael; Holroyd, Clay B

2018-06-21

Successful execution of goal-directed behaviors often requires the deployment of cognitive control, which is thought to require cognitive effort. Recent theories have proposed that anterior cingulate cortex (ACC) regulates control levels by weighing the reward-related benefits of control against its effort-related costs. However, given that the sensations of cognitive effort and reward valuation are available only to introspection, this hypothesis is difficult to investigate empirically. We have proposed that two electrophysiological indices of ACC function, frontal midline theta and the reward positivity (RewP), provide objective measures of these functions. To explore this issue, we recorded the electroencephalogram (EEG) from participants engaged in an extended, cognitively-demanding task. Participants performed a time estimation task for 2 h in which they received reward and error feedback according to their task performance. We observed that the amplitude of the RewP, a feedback-locked component of the event related brain potential associated with reward processing, decreased with time-on-task. Conversely, frontal midline theta power, which consists of 4-8 Hz EEG oscillations associated with cognitive effort, increased with time-on-task. We also explored how these phenomena changed over time by conducting within-participant multi-level modeling analyses. Our results suggest that extended execution of a cognitively-demanding task is characterized by an early phase in which high control levels foster rapid improvements in task performance, and a later phase in which high control levels were necessary to maintain stable task performance, perhaps counteracting waning reward valuation. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Revision of Quality Indicators for the Endoscopy Quality Improvement Program of the National Cancer Screening Program in Korea].

PubMed

Min, Jun Ki; Cha, Jae Myung; Cho, Yu Kyung; Kim, Jie Hyun; Yoon, Soon Man; Im, Jong Pil; Jung, Yunho; Moon, Jeong Seop; Kim, Jin Oh; Jeen, Yoon Tae

2018-05-25

Gastroscopy and colonoscopy are widely used for the early diagnosis of stomach and colorectal cancer. The present revision integrates recent data regarding previous quality indicators and novel indicators suggested for gastroscopy and colonoscopy procedures for the National Cancer Screening Program in Korea. The new indicators, developed by the Quality Improvement Committee of the Korean Society for Gastrointestinal Endoscopy, vary in the level of supporting evidence, and most are based solely on expert opinion. Updated indicators validated by clinical research were prioritized, but were chosen by expert consensus when such studies were absent. The resultant quality indicators were graded according to the levels of consensus and recommendations. The updated indicators will provide a relevant guideline for high-quality endoscopy. The future direction of quality indicator development should include relevant outcome measures and an evidence-based approach to support proposed performance targets.

The Proposal of Key Performance Indicators in Facility Management and Determination the Weights of Significance

NASA Astrophysics Data System (ADS)

Rimbalová, Jarmila; Vilčeková, Silvia

2013-11-01

The practice of facilities management is rapidly evolving with the increasing interest in the discourse of sustainable development. The industry and its market are forecasted to develop to include non-core functions, activities traditionally not associated with this profession, but which are increasingly being addressed by facilities managers. The scale of growth in the built environment and the consequential growth of the facility management sector is anticipated to be enormous. Key Performance Indicators (KPI) are measure that provides essential information about performance of facility services delivery. In selecting KPI, it is critical to limit them to those factors that are essential to the organization reaching its goals. It is also important to keep the number of KPI small just to keep everyone's attention focused on achieving the same KPIs. This paper deals with the determination of weights of KPI of FM in terms of the design and use of sustainable buildings.

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography.

PubMed

Prakash, Jaya; Yalavarthy, Phaneendra K

2013-03-01

Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time.

A Compact VLSI System for Bio-Inspired Visual Motion Estimation.

PubMed

Shi, Cong; Luo, Gang

2018-04-01

This paper proposes a bio-inspired visual motion estimation algorithm based on motion energy, along with its compact very-large-scale integration (VLSI) architecture using low-cost embedded systems. The algorithm mimics motion perception functions of retina, V1, and MT neurons in a primate visual system. It involves operations of ternary edge extraction, spatiotemporal filtering, motion energy extraction, and velocity integration. Moreover, we propose the concept of confidence map to indicate the reliability of estimation results on each probing location. Our algorithm involves only additions and multiplications during runtime, which is suitable for low-cost hardware implementation. The proposed VLSI architecture employs multiple (frame, pixel, and operation) levels of pipeline and massively parallel processing arrays to boost the system performance. The array unit circuits are optimized to minimize hardware resource consumption. We have prototyped the proposed architecture on a low-cost field-programmable gate array platform (Zynq 7020) running at 53-MHz clock frequency. It achieved 30-frame/s real-time performance for velocity estimation on 160 × 120 probing locations. A comprehensive evaluation experiment showed that the estimated velocity by our prototype has relatively small errors (average endpoint error < 0.5 pixel and angular error < 10°) for most motion cases.

Gaussian Elimination-Based Novel Canonical Correlation Analysis Method for EEG Motion Artifact Removal.

PubMed

Roy, Vandana; Shukla, Shailja; Shukla, Piyush Kumar; Rawat, Paresh

2017-01-01

The motion generated at the capturing time of electro-encephalography (EEG) signal leads to the artifacts, which may reduce the quality of obtained information. Existing artifact removal methods use canonical correlation analysis (CCA) for removing artifacts along with ensemble empirical mode decomposition (EEMD) and wavelet transform (WT). A new approach is proposed to further analyse and improve the filtering performance and reduce the filter computation time under highly noisy environment. This new approach of CCA is based on Gaussian elimination method which is used for calculating the correlation coefficients using backslash operation and is designed for EEG signal motion artifact removal. Gaussian elimination is used for solving linear equation to calculate Eigen values which reduces the computation cost of the CCA method. This novel proposed method is tested against currently available artifact removal techniques using EEMD-CCA and wavelet transform. The performance is tested on synthetic and real EEG signal data. The proposed artifact removal technique is evaluated using efficiency matrices such as del signal to noise ratio (DSNR), lambda ( λ ), root mean square error (RMSE), elapsed time, and ROC parameters. The results indicate suitablity of the proposed algorithm for use as a supplement to algorithms currently in use.

Comprehensive Detection of Gas Plumes from Multibeam Water Column Images with Minimisation of Noise Interferences

PubMed Central

Zhao, Jianhu; Zhang, Hongmei; Wang, Shiqi

2017-01-01

Multibeam echosounder systems (MBES) can record backscatter strengths of gas plumes in the water column (WC) images that may be an indicator of possible occurrence of gas at certain depths. Manual or automatic detection is generally adopted in finding gas plumes, but frequently results in low efficiency and high false detection rates because of WC images that are polluted by noise. To improve the efficiency and reliability of the detection, a comprehensive detection method is proposed in this paper. In the proposed method, the characteristics of WC background noise are first analyzed and given. Then, the mean standard deviation threshold segmentations are respectively used for the denoising of time-angle and depth-angle images, an intersection operation is performed for the two segmented images to further weaken noise in the WC data, and the gas plumes in the WC data are detected from the intersection image by the morphological constraint. The proposed method was tested by conducting shallow-water and deepwater experiments. In these experiments, the detections were conducted automatically and higher correct detection rates than the traditional methods were achieved. The performance of the proposed method is analyzed and discussed. PMID:29186014

Assessing the performance of regional landslide early warning models: the EDuMaP method

NASA Astrophysics Data System (ADS)

Calvello, M.; Piciullo, L.

2015-10-01

The paper proposes the evaluation of the technical performance of a regional landslide early warning system by means of an original approach, called EDuMaP method, comprising three successive steps: identification and analysis of the Events (E), i.e. landslide events and warning events derived from available landslides and warnings databases; definition and computation of a Duration Matrix (DuMa), whose elements report the time associated with the occurrence of landslide events in relation to the occurrence of warning events, in their respective classes; evaluation of the early warning model Performance (P) by means of performance criteria and indicators applied to the duration matrix. During the first step, the analyst takes into account the features of the warning model by means of ten input parameters, which are used to identify and classify landslide and warning events according to their spatial and temporal characteristics. In the second step, the analyst computes a time-based duration matrix having a number of rows and columns equal to the number of classes defined for the warning and landslide events, respectively. In the third step, the analyst computes a series of model performance indicators derived from a set of performance criteria, which need to be defined by considering, once again, the features of the warning model. The proposed method is based on a framework clearly distinguishing between local and regional landslide early warning systems as well as among correlation laws, warning models and warning systems. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warnings data from the municipal early warning system operating in Rio de Janeiro (Brazil).

Assessing the performance of regional landslide early warning models: the EDuMaP method

NASA Astrophysics Data System (ADS)

Calvello, M.; Piciullo, L.

2016-01-01

A schematic of the components of regional early warning systems for rainfall-induced landslides is herein proposed, based on a clear distinction between warning models and warning systems. According to this framework an early warning system comprises a warning model as well as a monitoring and warning strategy, a communication strategy and an emergency plan. The paper proposes the evaluation of regional landslide warning models by means of an original approach, called the "event, duration matrix, performance" (EDuMaP) method, comprising three successive steps: identification and analysis of the events, i.e., landslide events and warning events derived from available landslides and warnings databases; definition and computation of a duration matrix, whose elements report the time associated with the occurrence of landslide events in relation to the occurrence of warning events, in their respective classes; evaluation of the early warning model performance by means of performance criteria and indicators applied to the duration matrix. During the first step the analyst identifies and classifies the landslide and warning events, according to their spatial and temporal characteristics, by means of a number of model parameters. In the second step, the analyst computes a time-based duration matrix with a number of rows and columns equal to the number of classes defined for the warning and landslide events, respectively. In the third step, the analyst computes a series of model performance indicators derived from a set of performance criteria, which need to be defined by considering, once again, the features of the warning model. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warning data from the municipal early warning system operating in Rio de Janeiro (Brazil).

An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA)

PubMed Central

2011-01-01

Background Segmentation is the most crucial part in the computer-aided bone age assessment. A well-known type of segmentation performed in the system is adaptive segmentation. While providing better result than global thresholding method, the adaptive segmentation produces a lot of unwanted noise that could affect the latter process of epiphysis extraction. Methods A proposed method with anisotropic diffusion as pre-processing and a novel Bounded Area Elimination (BAE) post-processing algorithm to improve the algorithm of ossification site localization technique are designed with the intent of improving the adaptive segmentation result and the region-of interest (ROI) localization accuracy. Results The results are then evaluated by quantitative analysis and qualitative analysis using texture feature evaluation. The result indicates that the image homogeneity after anisotropic diffusion has improved averagely on each age group for 17.59%. Results of experiments showed that the smoothness has been improved averagely 35% after BAE algorithm and the improvement of ROI localization has improved for averagely 8.19%. The MSSIM has improved averagely 10.49% after performing the BAE algorithm on the adaptive segmented hand radiograph. Conclusions The result indicated that hand radiographs which have undergone anisotropic diffusion have greatly reduced the noise in the segmented image and the result as well indicated that the BAE algorithm proposed is capable of removing the artifacts generated in adaptive segmentation. PMID:21952080

Local-learning-based neuron selection for grasping gesture prediction in motor brain machine interfaces

NASA Astrophysics Data System (ADS)

Xu, Kai; Wang, Yiwen; Wang, Yueming; Wang, Fang; Hao, Yaoyao; Zhang, Shaomin; Zhang, Qiaosheng; Chen, Weidong; Zheng, Xiaoxiang

2013-04-01

Objective. The high-dimensional neural recordings bring computational challenges to movement decoding in motor brain machine interfaces (mBMI), especially for portable applications. However, not all recorded neural activities relate to the execution of a certain movement task. This paper proposes to use a local-learning-based method to perform neuron selection for the gesture prediction in a reaching and grasping task. Approach. Nonlinear neural activities are decomposed into a set of linear ones in a weighted feature space. A margin is defined to measure the distance between inter-class and intra-class neural patterns. The weights, reflecting the importance of neurons, are obtained by minimizing a margin-based exponential error function. To find the most dominant neurons in the task, 1-norm regularization is introduced to the objective function for sparse weights, where near-zero weights indicate irrelevant neurons. Main results. The signals of only 10 neurons out of 70 selected by the proposed method could achieve over 95% of the full recording's decoding accuracy of gesture predictions, no matter which different decoding methods are used (support vector machine and K-nearest neighbor). The temporal activities of the selected neurons show visually distinguishable patterns associated with various hand states. Compared with other algorithms, the proposed method can better eliminate the irrelevant neurons with near-zero weights and provides the important neuron subset with the best decoding performance in statistics. The weights of important neurons converge usually within 10-20 iterations. In addition, we study the temporal and spatial variation of neuron importance along a period of one and a half months in the same task. A high decoding performance can be maintained by updating the neuron subset. Significance. The proposed algorithm effectively ascertains the neuronal importance without assuming any coding model and provides a high performance with different decoding models. It shows better robustness of identifying the important neurons with noisy signals presented. The low demand of computational resources which, reflected by the fast convergence, indicates the feasibility of the method applied in portable BMI systems. The ascertainment of the important neurons helps to inspect neural patterns visually associated with the movement task. The elimination of irrelevant neurons greatly reduces the computational burden of mBMI systems and maintains the performance with better robustness.

Design, analysis, and testing of a flexure-based vibration-assisted polishing device

NASA Astrophysics Data System (ADS)

Gu, Yan; Zhou, Yan; Lin, Jieqiong; Lu, Mingming; Zhang, Chenglong; Chen, Xiuyuan

2018-05-01

A vibration-assisted polishing device (VAPD) composed of leaf-spring and right-circular flexure hinges is proposed with the aim of realizing vibration-assisted machining along elliptical trajectories. To design the structure, energy methods and the finite-element method are used to calculate the performance of the proposed VAPD. An improved bacterial foraging optimization algorithm is used to optimize the structural parameters. In addition, the performance of the VAPD is tested experimentally. The experimental results indicate that the maximum strokes of the two directional mechanisms operating along the Z1 and Z2 directions are 29.5 μm and 29.3 μm, respectively, and the maximum motion resolutions are 10.05 nm and 10.01 nm, respectively. The maximum working bandwidth is 1,879 Hz, and the device has a good step response.

Measuring the usefulness of hidden units in Boltzmann machines with mutual information.

PubMed

Berglund, Mathias; Raiko, Tapani; Cho, Kyunghyun

2015-04-01

Restricted Boltzmann machines (RBMs) and deep Boltzmann machines (DBMs) are important models in deep learning, but it is often difficult to measure their performance in general, or measure the importance of individual hidden units in specific. We propose to use mutual information to measure the usefulness of individual hidden units in Boltzmann machines. The measure is fast to compute, and serves as an upper bound for the information the neuron can pass on, enabling detection of a particular kind of poor training results. We confirm experimentally that the proposed measure indicates how much the performance of the model drops when some of the units of an RBM are pruned away. We demonstrate the usefulness of the measure for early detection of poor training in DBMs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reduced state feedback gain computation. [optimization and control theory for aircraft control

NASA Technical Reports Server (NTRS)

Kaufman, H.

1976-01-01

Because application of conventional optimal linear regulator theory to flight controller design requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. Therefore, a stochastic linear model that was developed is presented which accounts for aircraft parameter and initial uncertainty, measurement noise, turbulence, pilot command and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell. Results using a seventh order process show the proposed procedures to be very effective.

Computation of output feedback gains for linear stochastic systems using the Zangnill-Powell Method

NASA Technical Reports Server (NTRS)

Kaufman, H.

1975-01-01

Because conventional optimal linear regulator theory results in a controller which requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. To this effect a stochastic linear model has been developed that accounts for process parameter and initial uncertainty, measurement noise, and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was then performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell. Results using a seventh order process show the proposed procedures to be very effective.

Determination of LEDs degradation with entropy generation rate

NASA Astrophysics Data System (ADS)

Cuadras, Angel; Yao, Jiaqiang; Quilez, Marcos

2017-10-01

We propose a method to assess the degradation and aging of light emitting diodes (LEDs) based on irreversible entropy generation rate. We degraded several LEDs and monitored their entropy generation rate ( S ˙ ) in accelerated tests. We compared the thermoelectrical results with the optical light emission evolution during degradation. We find a good relationship between aging and S ˙ (t), because S ˙ is both related to device parameters and optical performance. We propose a threshold of S ˙ (t) as a reliable damage indicator of LED end-of-life that can avoid the need to perform optical measurements to assess optical aging. The method lays beyond the typical statistical laws for lifetime prediction provided by manufacturers. We tested different LED colors and electrical stresses to validate the electrical LED model and we analyzed the degradation mechanisms of the devices.

High-performance liquid chromatographic method for potency determination of amoxicillin in commercial preparations and for stability studies.

PubMed Central

Hsu, M C; Hsu, P W

1992-01-01

A reversed-phase column liquid chromatographic method was developed for the assay of amoxicillin and its preparations. The linear calibration range was 0.2 to 2.0 mg/ml (r = 0.9998), and recoveries were generally greater than 99%. The high-performance liquid chromatographic assay results were compared with those obtained from a microbiological assay of bulk drug substance and capsule, injection, and granule formulations containing amoxicillin and degraded amoxicillin. At the 99% confidence level, no significant intermethod differences were noted for the paired results. Commercial formulations were also analyzed, and the results obtained by the proposed method closely agreed with those found by the microbiological method. The results indicated that the proposed method is a suitable substitute for the microbiological method for assays and stability studies of amoxicillin preparations. PMID:1416827

A RSSI-based parameter tracking strategy for constrained position localization

NASA Astrophysics Data System (ADS)

Du, Jinze; Diouris, Jean-François; Wang, Yide

2017-12-01

In this paper, a received signal strength indicator (RSSI)-based parameter tracking strategy for constrained position localization is proposed. To estimate channel model parameters, least mean squares method (LMS) is associated with the trilateration method. In the context of applications where the positions are constrained on a grid, a novel tracking strategy is proposed to determine the real position and obtain the actual parameters in the monitored region. Based on practical data acquired from a real localization system, an experimental channel model is constructed to provide RSSI values and verify the proposed tracking strategy. Quantitative criteria are given to guarantee the efficiency of the proposed tracking strategy by providing a trade-off between the grid resolution and parameter variation. The simulation results show a good behavior of the proposed tracking strategy in the presence of space-time variation of the propagation channel. Compared with the existing RSSI-based algorithms, the proposed tracking strategy exhibits better localization accuracy but consumes more calculation time. In addition, a tracking test is performed to validate the effectiveness of the proposed tracking strategy.

Multiview face detection based on position estimation over multicamera surveillance system

NASA Astrophysics Data System (ADS)

Huang, Ching-chun; Chou, Jay; Shiu, Jia-Hou; Wang, Sheng-Jyh

2012-02-01

In this paper, we propose a multi-view face detection system that locates head positions and indicates the direction of each face in 3-D space over a multi-camera surveillance system. To locate 3-D head positions, conventional methods relied on face detection in 2-D images and projected the face regions back to 3-D space for correspondence. However, the inevitable false face detection and rejection usually degrades the system performance. Instead, our system searches for the heads and face directions over the 3-D space using a sliding cube. Each searched 3-D cube is projected onto the 2-D camera views to determine the existence and direction of human faces. Moreover, a pre-process to estimate the locations of candidate targets is illustrated to speed-up the searching process over the 3-D space. In summary, our proposed method can efficiently fuse multi-camera information and suppress the ambiguity caused by detection errors. Our evaluation shows that the proposed approach can efficiently indicate the head position and face direction on real video sequences even under serious occlusion.

A Novel Hybrid Classification Model of Genetic Algorithms, Modified k-Nearest Neighbor and Developed Backpropagation Neural Network

PubMed Central

Salari, Nader; Shohaimi, Shamarina; Najafi, Farid; Nallappan, Meenakshii; Karishnarajah, Isthrinayagy

2014-01-01

Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. The purpose is benefitting from the synergies obtained from combining these technologies for the development of classification models. Such a combination creates an opportunity to invest in the strength of each algorithm, and is an approach to make up for their deficiencies. To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. Furthermore, the statistical analysis was performed using the Friedman test followed by post-hoc tests. The experimental findings indicated that the novel proposed hybrid model resulted in significantly better classification performance compared with all 13 classification methods. Finally, the performance results of the proposed model was benchmarked against the best ones reported as the state-of-the-art classifiers in terms of classification accuracy for the same data sets. The substantial findings of the comprehensive comparative study revealed that performance of the proposed model in terms of classification accuracy is desirable, promising, and competitive to the existing state-of-the-art classification models. PMID:25419659

New indicators proposed to assess tuberculosis control and elimination in Cuba.

PubMed

González, Edilberto R; Armas, Luisa

2012-10-01

Following 48 years of successful operation of the National Tuberculosis Control Program, Cuban health authorities have placed tuberculosis elimination on the agenda. To this end some tuberculosis control processes and their indicators need redesigned and new ones introduced, related to: number and proportion of suspected tuberculosis cases among vulnerable population groups; tuberculosis suspects with sputum microscopy and culture results useful for diagnosis (interpretable); and number of identified contacts of reported tuberculosis cases who were fully investigated. Such new indicators have been validated and successfully implemented in all provinces (2011-12) and are in the approval pipeline for generalized use in the National Tuberculosis Control Program. These indicators complement existing criteria for quality of case detection and support more comprehensive program performance assessment.

Optimal platform design using non-dominated sorting genetic algorithm II and technique for order of preference by similarity to ideal solution; application to automotive suspension system

NASA Astrophysics Data System (ADS)

Shojaeefard, Mohammad Hassan; Khalkhali, Abolfazl; Faghihian, Hamed; Dahmardeh, Masoud

2018-03-01

Unlike conventional approaches where optimization is performed on a unique component of a specific product, optimum design of a set of components for employing in a product family can cause significant reduction in costs. Increasing commonality and performance of the product platform simultaneously is a multi-objective optimization problem (MOP). Several optimization methods are reported to solve these MOPs. However, what is less discussed is how to find the trade-off points among the obtained non-dominated optimum points. This article investigates the optimal design of a product family using non-dominated sorting genetic algorithm II (NSGA-II) and proposes the employment of technique for order of preference by similarity to ideal solution (TOPSIS) method to find the trade-off points among the obtained non-dominated results while compromising all objective functions together. A case study for a family of suspension systems is presented, considering performance and commonality. The results indicate the effectiveness of the proposed method to obtain the trade-off points with the best possible performance while maximizing the common parts.

Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

NASA Astrophysics Data System (ADS)

Zadeh, S. M.; Powers, D. M. W.; Sammut, K.; Yazdani, A. M.

2016-12-01

Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle's mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.

The evaluation and enhancement of quality, environmental protection and seaport safety by using FAHP

NASA Astrophysics Data System (ADS)

Tadic, Danijela; Aleksic, Aleksandar; Popovic, Pavle; Arsovski, Slavko; Castelli, Ana; Joksimovic, Danijela; Stefanovic, Miladin

2017-02-01

The evaluation and enhancement of business processes in any organization in an uncertain environment presents one of the main requirements of ISO 9000:2008 and has a key effect on competitive advantage and long-term sustainability. The aim of this paper can be defined as the identification and discussion of some of the most important business processes of seaports and the performances of business processes and their key performance indicators (KPIs). The complexity and importance of the treated problem call for analytic methods rather than intuitive decisions. The existing decision variables of the considered problem are described by linguistic expressions which are modelled by triangular fuzzy numbers (TFNs). In this paper, the modified fuzzy extended analytic hierarchy process (FAHP) is proposed. The assessment of the relative importance of each pair of performances and their key performance indicators are stated as a fuzzy group decision-making problem. By using the modified fuzzy extended analytic hierarchy process, the fuzzy rank of business processes of a seaport is obtained. The model is tested through an illustrative example with real-life data, where the obtained data suggest measures which should enhance business strategy and improve key performance indicators. The future improvement is based on benchmark and knowledge sharing.

Hardware Implementation of a MIMO Decoder Using Matrix Factorization Based Channel Estimation

NASA Astrophysics Data System (ADS)

Islam, Mohammad Tariqul; Numan, Mostafa Wasiuddin; Misran, Norbahiah; Ali, Mohd Alauddin Mohd; Singh, Mandeep

2011-05-01

This paper presents an efficient hardware realization of multiple-input multiple-output (MIMO) wireless communication decoder that utilizes the available resources by adopting the technique of parallelism. The hardware is designed and implemented on Xilinx Virtex™-4 XC4VLX60 field programmable gate arrays (FPGA) device in a modular approach which simplifies and eases hardware update, and facilitates testing of the various modules independently. The decoder involves a proficient channel estimation module that employs matrix factorization on least squares (LS) estimation to reduce a full rank matrix into a simpler form in order to eliminate matrix inversion. This results in performance improvement and complexity reduction of the MIMO system. Performance evaluation of the proposed method is validated through MATLAB simulations which indicate 2 dB improvement in terms of SNR compared to LS estimation. Moreover complexity comparison is performed in terms of mathematical operations, which shows that the proposed approach appreciably outperforms LS estimation at a lower complexity and represents a good solution for channel estimation technique.

Support vector machine firefly algorithm based optimization of lens system.

PubMed

Shamshirband, Shahaboddin; Petković, Dalibor; Pavlović, Nenad T; Ch, Sudheer; Altameem, Torki A; Gani, Abdullah

2015-01-01

Lens system design is an important factor in image quality. The main aspect of the lens system design methodology is the optimization procedure. Since optimization is a complex, nonlinear task, soft computing optimization algorithms can be used. There are many tools that can be employed to measure optical performance, but the spot diagram is the most useful. The spot diagram gives an indication of the image of a point object. In this paper, the spot size radius is considered an optimization criterion. Intelligent soft computing scheme support vector machines (SVMs) coupled with the firefly algorithm (FFA) are implemented. The performance of the proposed estimators is confirmed with the simulation results. The result of the proposed SVM-FFA model has been compared with support vector regression (SVR), artificial neural networks, and generic programming methods. The results show that the SVM-FFA model performs more accurately than the other methodologies. Therefore, SVM-FFA can be used as an efficient soft computing technique in the optimization of lens system designs.

A Study on Application of Fuzzy Adaptive Unscented Kalman Filter to Nonlinear Turbojet Engine Control

NASA Astrophysics Data System (ADS)

Han, Dongju

2018-05-01

Safe and efficient flight powered by an aircraft turbojet engine relies on the performance of the engine controller preventing compressor surge with robustness from noises or disturbances. This paper proposes the effective nonlinear controller associated with the nonlinear filter for the real turbojet engine with highly nonlinear dynamics. For the feasible controller study the nonlinearity of the engine dynamics was investigated by comparing the step responses from the linearized model with the original nonlinear dynamics. The fuzzy-based PID control logic is introduced to control the engine efficiently and FAUKF is applied for robustness from noises. The simulation results prove the effectiveness of FAUKF applied to the proposed controller such that the control performances are superior over the conventional controller and the filer performance using FAUKF indicates the satisfactory results such as clearing the defects by reducing the distortions without compressor surge, whereas the conventional UKF is not fully effective as occurring some distortions with compressor surge due to a process noise.

Statistical methods for convergence detection of multi-objective evolutionary algorithms.

PubMed

Trautmann, H; Wagner, T; Naujoks, B; Preuss, M; Mehnen, J

2009-01-01

In this paper, two approaches for estimating the generation in which a multi-objective evolutionary algorithm (MOEA) shows statistically significant signs of convergence are introduced. A set-based perspective is taken where convergence is measured by performance indicators. The proposed techniques fulfill the requirements of proper statistical assessment on the one hand and efficient optimisation for real-world problems on the other hand. The first approach accounts for the stochastic nature of the MOEA by repeating the optimisation runs for increasing generation numbers and analysing the performance indicators using statistical tools. This technique results in a very robust offline procedure. Moreover, an online convergence detection method is introduced as well. This method automatically stops the MOEA when either the variance of the performance indicators falls below a specified threshold or a stagnation of their overall trend is detected. Both methods are analysed and compared for two MOEA and on different classes of benchmark functions. It is shown that the methods successfully operate on all stated problems needing less function evaluations while preserving good approximation quality at the same time.

Analysis and methodology for aeronautical systems technology program planning

NASA Technical Reports Server (NTRS)

White, M. J.; Gershkoff, I.; Lamkin, S.

1983-01-01

A structured methodology was developed that allows the generation, analysis, and rank-ordering of system concepts by their benefits and costs, indicating the preferred order of implementation. The methodology is supported by a base of data on civil transport aircraft fleet growth projections and data on aircraft performance relating the contribution of each element of the aircraft to overall performance. The performance data are used to assess the benefits of proposed concepts. The methodology includes a computer program for performing the calculations needed to rank-order the concepts and compute their cumulative benefit-to-cost ratio. The use of the methodology and supporting data is illustrated through the analysis of actual system concepts from various sources.

Evaluation of Student Performance through a Multidimensional Finite Mixture IRT Model.

PubMed

Bacci, Silvia; Bartolucci, Francesco; Grilli, Leonardo; Rampichini, Carla

2017-01-01

In the Italian academic system, a student can enroll for an exam immediately after the end of the teaching period or can postpone it; in this second case the exam result is missing. We propose an approach for the evaluation of a student performance throughout the course of study, accounting also for nonattempted exams. The approach is based on an item response theory model that includes two discrete latent variables representing student performance and priority in selecting the exams to take. We explicitly account for nonignorable missing observations as the indicators of attempted exams also contribute to measure the performance (within-item multidimensionality). The model also allows for individual covariates in its structural part.

Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

NASA Astrophysics Data System (ADS)

Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

2012-04-01

Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

Methods for pore water extraction from unsaturated zone tuff, Yucca Mountain, Nevada

USGS Publications Warehouse

Scofield, K.M.

2006-01-01

Assessing the performance of the proposed high-level radioactive waste repository at Yucca Mountain, Nevada, requires an understanding of the chemistry of the water that moves through the host rock. The uniaxial compression method used to extract pore water from samples of tuffaceous borehole core was successful only for nonwelded tuff. An ultracentrifugation method was adopted to extract pore water from samples of the densely welded tuff of the proposed repository horizon. Tests were performed using both methods to determine the efficiency of pore water extraction and the potential effects on pore water chemistry. Test results indicate that uniaxial compression is most efficient for extracting pore water from nonwelded tuff, while ultracentrifugation is more successful in extracting pore water from densely welded tuff. Pore water splits collected from a single nonwelded tuff core during uniaxial compression tests have shown changes in pore water chemistry with increasing pressure for calcium, chloride, sulfate, and nitrate. Pore water samples collected from the intermediate pressure ranges should prevent the influence of re-dissolved, evaporative salts and the addition of ion-deficient water from clays and zeolites. Chemistry of pore water splits from welded and nonwelded tuffs using ultracentrifugation indicates that there is no substantial fractionation of solutes.

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks

PubMed Central

Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M.

2016-01-01

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover. PMID:27438600

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks.

PubMed

Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M

2016-01-01

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF-FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model's performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF-FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF-FFA model can be applied as an efficient technique for the accurate prediction of vertical handover.

Thermoregulatory models of safety-for-flight issues for space operations

NASA Astrophysics Data System (ADS)

Pisacane, V. L.; Kuznetz, L. H.; Logan, J. S.; Clark, J. B.; Wissler, E. H.

2006-10-01

This study investigates the use of a mathematical model for thermoregulation as a tool in safety-of-flight issues and proposed solutions for mission operations of the Space Shuttle and the International Space Station. Specifically, this study assesses the effects of elevated cabin temperature and metabolic loads on astronauts wearing the Advanced Crew Escape Suit (ACES) and the Liquid Cooled Ventilation Garment (LCVG). The 225-node Wissler model is validated by comparison with two ground-based human subject tests, firefighters, and surrogate astronauts under anomalous conditions that show good agreement. Subsequent simulations indicate that the performance of the ACES/LCVG is marginal. Increases in either workload or cabin temperature from the nominal will increase rectal temperature, stored heat load, heart rate, and sweating leading to possible deficits in the ability of the astronauts to perform cognitive and motor tasks that could affect the safety of the mission, especially the safe landing of the Shuttle. Specific relationships are given between cabin temperature and metabolic rate that define the threshold for decreased manual dexterity and loss of tracking skills. Model results indicate that the most effective mitigation strategy would be to decrease the LCVG inlet temperature. Methods of accomplishing this are also proposed.

Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network.

PubMed

Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Jiang, Yuan Yuan; Kim, Sung Min

2015-01-01

This paper focuses on the improvement of the diagnostic accuracy of focal liver lesions by quantifying the key features of cysts, hemangiomas, and malignant lesions on ultrasound images. The focal liver lesions were divided into 29 cysts, 37 hemangiomas, and 33 malignancies. A total of 42 hybrid textural features that composed of 5 first order statistics, 18 gray level co-occurrence matrices, 18 Law's, and echogenicity were extracted. A total of 29 key features that were selected by principal component analysis were used as a set of inputs for a feed-forward neural network. For each lesion, the performance of the diagnosis was evaluated by using the positive predictive value, negative predictive value, sensitivity, specificity, and accuracy. The results of the experiment indicate that the proposed method exhibits great performance, a high diagnosis accuracy of over 96% among all focal liver lesion groups (cyst vs. hemangioma, cyst vs. malignant, and hemangioma vs. malignant) on ultrasound images. The accuracy was slightly increased when echogenicity was included in the optimal feature set. These results indicate that it is possible for the proposed method to be applied clinically.

Indicators to assess the environmental performances of an innovative subway station : example of Noisy-Champs

NASA Astrophysics Data System (ADS)

Schertzer, D. J. M.; Charbonnier, L.; Versini, P. A.; Tchiguirinskaia, I.

2017-12-01

Noisy-Champs is a train station located in Noisy-le-Grand and Champs-sur-Marne, in the Paris urban area (France). Integrated into the Grand Paris Express project (huge development project to modernise the transport network around Paris), this station is going to be radically transformed and become a major hub. Designed by the architectural office Duthilleul, the new Noisy-Champs station aspires to be an example of an innovative and sustainable infrastructure. Its architectural precepts are indeed meant to improve its environmental performances, especially those related to storm water management, water consumption and users' thermal and hygrometric comfort. In order to assess and monitor these performances, objectives and associated indicators have been developed. They aim to be adapted for a specific infrastructure such as a public transport station. Analyses of pre-existing comfort simulations, blueprints and regulatory documents have led to identify the main issues for the Noisy-Champs station, focusing on its resilience to extreme events like droughts, heatwaves and heaxvy rainfalls. Both objectives and indicators have been proposed by studying the space-time variabilities of physical fluxes (heat, pollutants, radiation, wind and water) and passenger flows, and their interactions. Each indicator is linked to an environmental performance and has been determined after consultation of the different stakeholders involved in the rebuilding of the station. It results a monitoring program to assess the environmental performances of the station composed by both the indicators grid and their related objectives, and a measurement program detailing the nature and location of sensors, and the frequency of measurements.

Automatic Building Detection based on Supervised Classification using High Resolution Google Earth Images

NASA Astrophysics Data System (ADS)

Ghaffarian, S.; Ghaffarian, S.

2014-08-01

This paper presents a novel approach to detect the buildings by automization of the training area collecting stage for supervised classification. The method based on the fact that a 3d building structure should cast a shadow under suitable imaging conditions. Therefore, the methodology begins with the detection and masking out the shadow areas using luminance component of the LAB color space, which indicates the lightness of the image, and a novel double thresholding technique. Further, the training areas for supervised classification are selected by automatically determining a buffer zone on each building whose shadow is detected by using the shadow shape and the sun illumination direction. Thereafter, by calculating the statistic values of each buffer zone which is collected from the building areas the Improved Parallelepiped Supervised Classification is executed to detect the buildings. Standard deviation thresholding applied to the Parallelepiped classification method to improve its accuracy. Finally, simple morphological operations conducted for releasing the noises and increasing the accuracy of the results. The experiments were performed on set of high resolution Google Earth images. The performance of the proposed approach was assessed by comparing the results of the proposed approach with the reference data by using well-known quality measurements (Precision, Recall and F1-score) to evaluate the pixel-based and object-based performances of the proposed approach. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.4 % and 853 % overall pixel-based and object-based precision performances, respectively.

Evaluating Effectiveness of Modeling Motion System Feedback in the Enhanced Hess Structural Model of the Human Operator

NASA Technical Reports Server (NTRS)

Zaychik, Kirill; Cardullo, Frank; George, Gary; Kelly, Lon C.

2009-01-01

In order to use the Hess Structural Model to predict the need for certain cueing systems, George and Cardullo significantly expanded it by adding motion feedback to the model and incorporating models of the motion system dynamics, motion cueing algorithm and a vestibular system. This paper proposes a methodology to evaluate effectiveness of these innovations by performing a comparison analysis of the model performance with and without the expanded motion feedback. The proposed methodology is composed of two stages. The first stage involves fine-tuning parameters of the original Hess structural model in order to match the actual control behavior recorded during the experiments at NASA Visual Motion Simulator (VMS) facility. The parameter tuning procedure utilizes a new automated parameter identification technique, which was developed at the Man-Machine Systems Lab at SUNY Binghamton. In the second stage of the proposed methodology, an expanded motion feedback is added to the structural model. The resulting performance of the model is then compared to that of the original one. As proposed by Hess, metrics to evaluate the performance of the models include comparison against the crossover models standards imposed on the crossover frequency and phase margin of the overall man-machine system. Preliminary results indicate the advantage of having the model of the motion system and motion cueing incorporated into the model of the human operator. It is also demonstrated that the crossover frequency and the phase margin of the expanded model are well within the limits imposed by the crossover model.

Incorporation of the equilibrium temperature approach in a Soil and Water Assessment Tool hydroclimatological stream temperature model

NASA Astrophysics Data System (ADS)

Du, Xinzhong; Shrestha, Narayan Kumar; Ficklin, Darren L.; Wang, Junye

2018-04-01

Stream temperature is an important indicator for biodiversity and sustainability in aquatic ecosystems. The stream temperature model currently in the Soil and Water Assessment Tool (SWAT) only considers the impact of air temperature on stream temperature, while the hydroclimatological stream temperature model developed within the SWAT model considers hydrology and the impact of air temperature in simulating the water-air heat transfer process. In this study, we modified the hydroclimatological model by including the equilibrium temperature approach to model heat transfer processes at the water-air interface, which reflects the influences of air temperature, solar radiation, wind speed and streamflow conditions on the heat transfer process. The thermal capacity of the streamflow is modeled by the variation of the stream water depth. An advantage of this equilibrium temperature model is the simple parameterization, with only two parameters added to model the heat transfer processes. The equilibrium temperature model proposed in this study is applied and tested in the Athabasca River basin (ARB) in Alberta, Canada. The model is calibrated and validated at five stations throughout different parts of the ARB, where close to monthly samplings of stream temperatures are available. The results indicate that the equilibrium temperature model proposed in this study provided better and more consistent performances for the different regions of the ARB with the values of the Nash-Sutcliffe Efficiency coefficient (NSE) greater than those of the original SWAT model and the hydroclimatological model. To test the model performance for different hydrological and environmental conditions, the equilibrium temperature model was also applied to the North Fork Tolt River Watershed in Washington, United States. The results indicate a reasonable simulation of stream temperature using the model proposed in this study, with minimum relative error values compared to the other two models. However, the NSE values were lower than those of the hydroclimatological model, indicating that more model verification needs to be done. The equilibrium temperature model uses existing SWAT meteorological data as input, can be calibrated using fewer parameters and less effort and has an overall better performance in stream temperature simulation. Thus, it can be used as an effective tool for predicting the changes in stream temperature regimes under varying hydrological and meteorological conditions. In addition, the impact of the stream temperature simulations on chemical reaction rates and concentrations was tested. The results indicate that the improved performance of the stream temperature simulation could significantly affect chemical reaction rates and the simulated concentrations, and the equilibrium temperature model could be a potential tool to model stream temperature in water quality simulations.

Volume-based characterization of postocclusion surge.

PubMed

Zacharias, Jaime; Zacharias, Sergio

2005-10-01

To propose an alternative method to characterize postocclusion surge using a collapsible artificial anterior chamber to replace the currently used rigid anterior chamber model. Fundación Oftamológica Los Andes, Santiago, Chile. The distal end of a phacoemulsification handpiece was placed inside a compliant artificial anterior chamber. Digital recordings of chamber pressure, chamber volume, inflow, and outflow were performed during occlusion break of the phacoemulsification tip. The occlusion break profile of 2 different consoles was compared. Occlusion break while using a rigid anterior chamber model produced a simultaneous increase of chamber inflow and outflow. In the rigid chamber model, pressure decreased sharply, reaching negative pressure values. Alternatively, with the collapsible chamber model, a delay was observed in the inflow that occurs to compensate the outflow surge. Also, the chamber pressure drop was smaller in magnitude, never undershooting below atmospheric pressure into negative values. Using 500 mm Hg as vacuum limit, the Infiniti System (Alcon) performed better that the Legacy (Alcon), showing an 18% reduction in peak volume variation. The collapsible anterior chamber model provides a more realistic representation of the postocclusion surge events that occur in the real eye during cataract surgery. Peak volume fluctuation (mL), half volume recovery time(s), and volume fluctuation integral value (mL x s) are proposed as realistic indicators to characterize the postocclusion surge performance. These indicators show that the Infiniti System has a better postocclusion surge behavior than the Legacy System.

Application of Islanding Detection and Classification of Power Quality Disturbance in Hybrid Energy System

NASA Astrophysics Data System (ADS)

Sun, L. B.; Wu, Z. S.; Yang, K. K.

2018-04-01

Islanding and power quality (PQ) disturbances in hybrid energy system become more serious with the application of renewable energy sources. In this paper, a novel method based on wavelet transform (WT) and modified feed forward neural network (FNN) is proposed to detect islanding and classify PQ problems. First, the performance indices, i.e., the energy content and SD of the transformed signal are extracted from the negative sequence component of the voltage signal at PCC using WT. Afterward, WT indices are fed to train FNNs midfield by Particle Swarm Optimization (PSO) which is a novel heuristic optimization method. Then, the results of simulation based on WT-PSOFNN are discussed in MATLAB/SIMULINK. Simulations on the hybrid power system show that the accuracy can be significantly improved by the proposed method in detecting and classifying of different disturbances connected to multiple distributed generations.

Experimental and simulated study of a composite structure metamaterial absorber

NASA Astrophysics Data System (ADS)

Li, Shengyong; Ai, Xiaochuan; Wu, Ronghua; Chen, Jiajun

2017-11-01

In this paper, a high performance metamaterial absorber is designed and experimental studied. Measured results indicate that a perfect absorption band and a short-wavelength absorption peak are achieved in the near-infrared spectrum. Current strength distributions reveal that the absorption band is excited by the cavity resonance. And electric field distributions show that the short-wavelength absorption peak is excited by the horizontal coupled of localized surface plasmon (LSP) modes near hole edges. On the one hand, the absorption property of the measured metamaterial absorber can be enhanced through optimizing the structural parameters (a, w, and H). On the other hand, the absorption property is sensitive to the change of refractive index of environmental medias. A sensing scheme is proposed for refractive index detecting based on the figure of merit (FOM) value. Measured results indicate that the proposed sensing scheme can achieve high FOM value with different environmental medias (water, glucose solution).

Customization of biomedical terminologies.

PubMed

Homo, Julien; Dupuch, Laëtitia; Benbrahim, Allel; Grabar, Natalia; Dupuch, Marie

2012-01-01

Within the biomedical area over one hundred terminologies exist and are merged in the Unified Medical Language System Metathesaurus, which gives over 1 million concepts. When such huge terminological resources are available, the users must deal with them and specifically they must deal with irrelevant parts of these terminologies. We propose to exploit seed terms and semantic distance algorithms in order to customize the terminologies and to limit within them a semantically homogeneous space. An evaluation performed by a medical expert indicates that the proposed approach is relevant for the customization of terminologies and that the extracted terms are mostly relevant to the seeds. It also indicates that different algorithms provide with similar or identical results within a given terminology. The difference is due to the terminologies exploited. A special attention must be paid to the definition of optimal association between the semantic similarity algorithms and the thresholds specific to a given terminology.

Implication of Two-Coupled Differential Van der Pol Duffing Oscillator in Weak Signal Detection

NASA Astrophysics Data System (ADS)

Peng, Hang-hang; Xu, Xue-mei; Yang, Bing-chu; Yin, Lin-zi

2016-04-01

The principle of the Van der Pol Duffing oscillator for state transition and for determining critical value is described, which has been studied to indicate that the application of the Van der Pol Duffing oscillator in weak signal detection is feasible. On the basis of this principle, an improved two-coupled differential Van der Pol Duffing oscillator is proposed which can identify signals under any frequency and ameliorate signal-to-noise ratio (SNR). The analytical methods of the proposed model and the construction of the proposed oscillator are introduced in detail. Numerical experiments on the properties of the proposed oscillator compared with those of the Van der Pol Duffing oscillator are carried out. Our numerical simulations have confirmed the analytical treatment. The results demonstrate that this novel oscillator has better detection performance than the Van der Pol Duffing oscillator.

Earned Value Management Considering Technical Readiness Level and Its Application to New Space Launcher Program

NASA Astrophysics Data System (ADS)

Choi, Young-In; Ahn, Jaemyung

2018-04-01

Earned value management (EVM) is a methodology for monitoring and controlling the performance of a project based on a comparison between planned and actual cost/schedule. This study proposes a concept of hybrid earned value management (H-EVM) that integrates the traditional EVM metrics with information on the technology readiness level. The proposed concept can reflect the progress of a project in a sensitive way and provides short-term perspective complementary to the traditional EVM metrics. A two-dimensional visualization on the cost/schedule status of a project reflecting both of the traditional EVM (long-term perspective) and the proposed H-EVM (short-term perspective) indices is introduced. A case study on the management of a new space launch vehicle development program is conducted to demonstrate the effectiveness of the proposed H-EVM concept, associated metrics, and the visualization technique.

Automatic Detection of Frontal Face Midline by Chain-coded Merlin-Farber Hough Trasform

NASA Astrophysics Data System (ADS)

Okamoto, Daichi; Ohyama, Wataru; Wakabayashi, Tetsushi; Kimura, Fumitaka

We propose a novel approach for detection of the facial midline (facial symmetry axis) from a frontal face image. The facial midline has several applications, for instance reducing computational cost required for facial feature extraction (FFE) and postoperative assessment for cosmetic or dental surgery. The proposed method detects the facial midline of a frontal face from an edge image as the symmetry axis using the Merlin-Faber Hough transformation. And a new performance improvement scheme for midline detection by MFHT is present. The main concept of the proposed scheme is suppression of redundant vote on the Hough parameter space by introducing chain code representation for the binary edge image. Experimental results on the image dataset containing 2409 images from FERET database indicate that the proposed algorithm can improve the accuracy of midline detection from 89.9% to 95.1 % for face images with different scales and rotation.

A novel data hiding scheme for block truncation coding compressed images using dynamic programming strategy

NASA Astrophysics Data System (ADS)

Chang, Ching-Chun; Liu, Yanjun; Nguyen, Son T.

2015-03-01

Data hiding is a technique that embeds information into digital cover data. This technique has been concentrated on the spatial uncompressed domain, and it is considered more challenging to perform in the compressed domain, i.e., vector quantization, JPEG, and block truncation coding (BTC). In this paper, we propose a new data hiding scheme for BTC-compressed images. In the proposed scheme, a dynamic programming strategy was used to search for the optimal solution of the bijective mapping function for LSB substitution. Then, according to the optimal solution, each mean value embeds three secret bits to obtain high hiding capacity with low distortion. The experimental results indicated that the proposed scheme obtained both higher hiding capacity and hiding efficiency than the other four existing schemes, while ensuring good visual quality of the stego-image. In addition, the proposed scheme achieved a low bit rate as original BTC algorithm.

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

QSAR modelling using combined simple competitive learning networks and RBF neural networks.

PubMed

Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

2018-04-01

The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

An effective visualization technique for depth perception in augmented reality-based surgical navigation.

PubMed

Choi, Hyunseok; Cho, Byunghyun; Masamune, Ken; Hashizume, Makoto; Hong, Jaesung

2016-03-01

Depth perception is a major issue in augmented reality (AR)-based surgical navigation. We propose an AR and virtual reality (VR) switchable visualization system with distance information, and evaluate its performance in a surgical navigation set-up. To improve depth perception, seamless switching from AR to VR was implemented. In addition, the minimum distance between the tip of the surgical tool and the nearest organ was provided in real time. To evaluate the proposed techniques, five physicians and 20 non-medical volunteers participated in experiments. Targeting error, time taken, and numbers of collisions were measured in simulation experiments. There was a statistically significant difference between a simple AR technique and the proposed technique. We confirmed that depth perception in AR could be improved by the proposed seamless switching between AR and VR, and providing an indication of the minimum distance also facilitated the surgical tasks. Copyright © 2015 John Wiley & Sons, Ltd.

Validating the performance of one-time decomposition for fMRI analysis using ICA with automatic target generation process.

PubMed

Yao, Shengnan; Zeng, Weiming; Wang, Nizhuan; Chen, Lei

2013-07-01

Independent component analysis (ICA) has been proven to be effective for functional magnetic resonance imaging (fMRI) data analysis. However, ICA decomposition requires to optimize the unmixing matrix iteratively whose initial values are generated randomly. Thus the randomness of the initialization leads to different ICA decomposition results. Therefore, just one-time decomposition for fMRI data analysis is not usually reliable. Under this circumstance, several methods about repeated decompositions with ICA (RDICA) were proposed to reveal the stability of ICA decomposition. Although utilizing RDICA has achieved satisfying results in validating the performance of ICA decomposition, RDICA cost much computing time. To mitigate the problem, in this paper, we propose a method, named ATGP-ICA, to do the fMRI data analysis. This method generates fixed initial values with automatic target generation process (ATGP) instead of being produced randomly. We performed experimental tests on both hybrid data and fMRI data to indicate the effectiveness of the new method and made a performance comparison of the traditional one-time decomposition with ICA (ODICA), RDICA and ATGP-ICA. The proposed method demonstrated that it not only could eliminate the randomness of ICA decomposition, but also could save much computing time compared to RDICA. Furthermore, the ROC (Receiver Operating Characteristic) power analysis also denoted the better signal reconstruction performance of ATGP-ICA than that of RDICA. Copyright © 2013 Elsevier Inc. All rights reserved.

Integration of membrane distillation into traditional salt farming method: Process development and modelling

NASA Astrophysics Data System (ADS)

Hizam, S.; Bilad, M. R.; Putra, Z. A.

2017-10-01

Farmers still practice the traditional salt farming in many regions, particularly in Indonesia. This archaic method not only produces low yield and poor salt quality, it is also laborious. Furthermore, the farming locations typically have poor access to fresh water and are far away from electricity grid, which restrict upgrade to a more advanced technology for salt production. This paper proposes a new concept of salt harvesting method that improves the salt yield and at the same time facilitates recovery of fresh water from seawater. The new concept integrates solar powered membrane distillation (MD) and photovoltaic cells to drive the pumping. We performed basic solar still experiments to quantify the heat flux received by a pond. The data were used as insight for designing the proposed concept, particularly on operational strategy and the most effective way to integrate MD. After the conceptual design had been developed, we formulated mass and energy balance to estimate the performance of the proposed concept. Based on our data and design, it is expected that the system would improve the yield and quality of the salt production, maximizing fresh water harvesting, and eventually provides economical gain for salt farmers hence improving their quality of life. The key performance can only be measured via experiment using gain output ratio as performance indicator, which will be done in a future study.

Training for planning tumour resection: augmented reality and human factors.

PubMed

Abhari, Kamyar; Baxter, John S H; Chen, Elvis C S; Khan, Ali R; Peters, Terry M; de Ribaupierre, Sandrine; Eagleson, Roy

2015-06-01

Planning surgical interventions is a complex task, demanding a high degree of perceptual, cognitive, and sensorimotor skills to reduce intra- and post-operative complications. This process requires spatial reasoning to coordinate between the preoperatively acquired medical images and patient reference frames. In the case of neurosurgical interventions, traditional approaches to planning tend to focus on providing a means for visualizing medical images, but rarely support transformation between different spatial reference frames. Thus, surgeons often rely on their previous experience and intuition as their sole guide is to perform mental transformation. In case of junior residents, this may lead to longer operation times or increased chance of error under additional cognitive demands. In this paper, we introduce a mixed augmented-/virtual-reality system to facilitate training for planning a common neurosurgical procedure, brain tumour resection. The proposed system is designed and evaluated with human factors explicitly in mind, alleviating the difficulty of mental transformation. Our results indicate that, compared to conventional planning environments, the proposed system greatly improves the nonclinicians' performance, independent of the sensorimotor tasks performed ( ). Furthermore, the use of the proposed system by clinicians resulted in a significant reduction in time to perform clinically relevant tasks ( ). These results demonstrate the role of mixed-reality systems in assisting residents to develop necessary spatial reasoning skills needed for planning brain tumour resection, improving patient outcomes.

Vocational Interests and Performance: A Quantitative Summary of Over 60 Years of Research.

PubMed

Nye, Christopher D; Su, Rong; Rounds, James; Drasgow, Fritz

2012-07-01

Despite early claims that vocational interests could be used to distinguish successful workers and superior students from their peers, interest measures are generally ignored in the employee selection literature. Nevertheless, theoretical descriptions of vocational interests from vocational and educational psychology have proposed that interest constructs should be related to performance and persistence in work and academic settings. Moreover, on the basis of Holland's (1959, 1997) theoretical predictions, congruence indices, which quantify the degree of similarity or person-environment fit between individuals and their occupations, should be more strongly related to performance than interest scores alone. Using a comprehensive review of the interest literature that spans more than 60 years of research, a meta-analysis was conducted to examine the veracity of these claims. A literature search identified 60 studies and approximately 568 correlations that addressed the relationship between interests and performance. Results showed that interests are indeed related to performance and persistence in work and academic contexts. In addition, the correlations between congruence indices and performance were stronger than for interest scores alone. Thus, consistent with interest theory, the fit between individuals and their environment was more predictive of performance than interest alone. © The Author(s) 2012.

On the error statistics of Viterbi decoding and the performance of concatenated codes

NASA Technical Reports Server (NTRS)

Miller, R. L.; Deutsch, L. J.; Butman, S. A.

1981-01-01

Computer simulation results are presented on the performance of convolutional codes of constraint lengths 7 and 10 concatenated with the (255, 223) Reed-Solomon code (a proposed NASA standard). These results indicate that as much as 0.8 dB can be gained by concatenating this Reed-Solomon code with a (10, 1/3) convolutional code, instead of the (7, 1/2) code currently used by the DSN. A mathematical model of Viterbi decoder burst-error statistics is developed and is validated through additional computer simulations.

The analysis on nonlinear control of the aircraft arresting system

NASA Astrophysics Data System (ADS)

Song, Jinchun; Du, Tianrong

2005-12-01

The aircraft arresting system is a complicated nonlinear system. This paper analyzes the mechanical-hydraulic structure of aircraft arresting system composed of electro hydraulic valve and establishes the dynamic equation of the aircraft arresting system. Based on the state-feedback linearization of nonlinear system, a PD-based controller is synthesized. Simulation studies indicate, while arresting the different type aircraft, the proposed controller has fast response, good tracking performance and strong robustness. By tuning the parameters of the PD controller, a satisfactory control performance can be guaranteed.

Plasmonic cloak using graphene at infrared frequencies

NASA Astrophysics Data System (ADS)

Li, Yan Xiu; Kong, Fan Min; Li, Kang; Zhuang, Hua Wei

2015-11-01

A carpet cloak based on graphene is designed and realized by making an approximate hemisphere surface which behaves as a flat surface, and the performances of the cloak are simulated by finite element method. The cloak performs perfectly through tuning conductivity of the graphene. The incident wave can propagate on the curved surface without being disturbed, and an object under the curved surface will be cloaked. It is indicated that graphene can be a platform for "on-atom-thick" cloaks, and the proposed methods can be applied in the practical design.

Annoyance from industrial noise: indicators for a wide variety of industrial sources.

PubMed

Alayrac, M; Marquis-Favre, C; Viollon, S; Morel, J; Le Nost, G

2010-09-01

In the study of noises generated by industrial sources, one issue is the variety of industrial noise sources and consequently the complexity of noises generated. Therefore, characterizing the environmental impact of an industrial plant requires better understanding of the noise annoyance caused by industrial noise sources. To deal with the variety of industrial sources, the proposed approach is set up by type of spectral features and based on a perceptive typology of steady and permanent industrial noises comprising six categories. For each perceptive category, listening tests based on acoustical factors are performed on noise annoyance. Various indicators are necessary to predict noise annoyance due to various industrial noise sources. Depending on the spectral features of the industrial noise sources, noise annoyance indicators are thus assessed. In case of industrial noise sources without main spectral features such as broadband noise, noise annoyance is predicted by the A-weighted sound pressure level L(Aeq) or the loudness level L(N). For industrial noises with spectral components such as low-frequency noises with a main component at 100 Hz or noises with spectral components in middle frequencies, indicators are proposed here that allow good prediction of noise annoyance by taking into account spectral features.

Inland waterway ports nodal attraction indices relevant in development strategies on regional level

NASA Astrophysics Data System (ADS)

Dinu, O.; Burciu, Ş.; Oprea, C.; Ilie, A.; Rosca, M.

2016-08-01

Present paper aims to propose a set of ranking indices and related criteria, concerning mainly spatial analysis, for the inland waterway port, with special view on inland ports of Danube. Commonly, the attraction potential of a certain transport node is assessed by its spatial accessibility indices considering both spatial features of the location provided by the networks that connect into that node and its economic potential defining the level of traffic flows depending on the economic centers of its hinterland. Paper starts with a overview of the critical needs that are required for potential sites to become inland waterway ports and presents nodal functions that coexist at different levels, leading to a port hierarchy from the points of view of: capacity, connection to hinterland, traffic structure and volume. After a brief review of the key inland waterway port ranking criterion, a selection of nodal attraction measures is made. Particular considerations for the Danube inland port case follows proposed methodology concerning indices of performance for network scale and centrality. As expected, the shorter the distance from an inland port to the nearest access point the greater accessibility. Major differences in ranking, dependent on selected criterion, were registered.

Diagnostic indicators for integrated assessment models of climate policy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kriegler, Elmar; Petermann, Nils; Krey, Volker

2015-01-01

Integrated assessments of how climate policy interacts with energy-economic systems can be performed by a variety of models with different functional structures. This article proposes a diagnostic scheme that can be applied to a wide range of integrated assessment models to classify differences among models based on their carbon price responses. Model diagnostics can uncover patterns and provide insights into why, under a given scenario, certain types of models behave in observed ways. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnosticmore » indicators to characterize model responses to carbon price signals and test these in a diagnostic study with 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to more easily explain variations among policy-relevant model results.« less

In itinere strategic environmental assessment of an integrated provincial waste system.

PubMed

Federico, Giovanna; Rizzo, Gianfranco; Traverso, Marzia

2009-06-01

In the paper, the practical problem of analysing in an integrated way the performance of provincial waste systems is approached, in the framework of the Strategic Environmental Assessment (SEA). In particular, the in itinere phase of SEA is analysed herein. After separating out a proper group of ambits, to which the waste system is supposed to determine relevant impacts, pertinent sets of single indicators are proposed. Through the adoption of such indicators the time trend of the system is investigated, and the suitability of each indicator is critically revised. The structure of the evaluation scheme, which is essentially based on the use of ambit issues and analytical indicators, calls for the application of the method of the Dashboard of Sustainability for the integrated evaluation of the whole system. The suitability of this method is shown through the paper, together with the possibility of a comparative analysis of different scenarios of interventions. Of course, the reliability of the proposed method strongly relies on the availability of a detailed set of territorial data. The method appears to represent a useful tool for public administration in the process of optimizing the policy actions aimed at minimizing the increasing problem represented by waste production in urban areas.

Structural Health Monitoring of a Composite Panel Based on PZT Sensors and a Transfer Impedance Framework

PubMed Central

Dziendzikowski, Michal; Niedbala, Patryk; Kurnyta, Artur; Kowalczyk, Kamil; Dragan, Krzysztof

2018-01-01

One of the ideas for development of Structural Health Monitoring (SHM) systems is based on excitation of elastic waves by a network of PZT piezoelectric transducers integrated with the structure. In the paper, a variant of the so-called Transfer Impedance (TI) approach to SHM is followed. Signal characteristics, called the Damage Indices (DIs), were proposed for data presentation and analysis. The idea underlying the definition of DIs was to maintain most of the information carried by the voltage induced on PZT sensors by elastic waves. In particular, the DIs proposed in the paper should be sensitive to all types of damage which can influence the amplitude or the phase of the voltage induced on the sensor. Properties of the proposed DIs were investigated experimentally using a GFRP composite panel equipped with PZT networks attached to its surface and embedded into its internal structure. Repeatability and stability of DI indications under controlled conditions were verified in tests. Also, some performance indicators for surface-attached and structure-embedded sensors were obtained. The DIs’ behavior was dependent mostly on the presence of a simulated damage in the structure. Anisotropy of mechanical properties of the specimen, geometrical properties of PZT network as well as, to some extent, the technology of sensor integration with the structure were irrelevant for damage indication. This property enables the method to be used for damage detection and classification. PMID:29751664

A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images

PubMed Central

Tang, Yunwei; Jing, Linhai; Ding, Haifeng

2017-01-01

The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA). Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods. PMID:29064416

Association between shift work history and performance on the trail making test in middle-aged and elderly humans: the EpiHealth study.

PubMed

Titova, Olga E; Lindberg, Eva; Elmståhl, Sölve; Lind, Lars; Schiöth, Helgi B; Benedict, Christian

2016-09-01

Shift work has been proposed to promote cognitive disturbances in humans; however, conflicting evidence is also present. By using data from 7143 middle-aged and elderly humans (45-75 years) who participated in the Swedish EpiHealth cohort study, the present analysis sought to investigate whether self-reported shift work history would be associated with performance on the trail making test (TMT). The TMT has been proposed to be a useful neuropsychological tool to evaluate humans' executive cognitive function, which is known to decrease with age. After adjustment for potential confounders (e.g., age, education, and sleep duration), it was observed that current and recent former shift workers (worked shifts during the past 5 years) performed worse on the TMT than nonshift workers. In contrast, performance on the TMT did not differ between past shift workers (off from shift work for more than 5 years) and nonshift workers. Collectively, our results indicate that shift work history is linked to poorer performance on the TMT in a cohort of middle-aged and elderly humans. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Statistical fusion of continuous labels: identification of cardiac landmarks

NASA Astrophysics Data System (ADS)

Xing, Fangxu; Soleimanifard, Sahar; Prince, Jerry L.; Landman, Bennett A.

2011-03-01

Image labeling is an essential task for evaluating and analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms. However, both approaches for labeling suffer from inevitable error due to noise and artifact in the acquired data. The Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm was developed to combine multiple rater decisions and simultaneously estimate unobserved true labels as well as each rater's level of performance (i.e., reliability). A generalization of STAPLE for the case of continuous-valued labels has also been proposed. In this paper, we first show that with the proposed Gaussian distribution assumption, this continuous STAPLE formulation yields equivalent likelihoods for the bias parameter, meaning that the bias parameter-one of the key performance indices-is actually indeterminate. We resolve this ambiguity by augmenting the STAPLE expectation maximization formulation to include a priori probabilities on the performance level parameters, which enables simultaneous, meaningful estimation of both the rater bias and variance performance measures. We evaluate and demonstrate the efficacy of this approach in simulations and also through a human rater experiment involving the identification the intersection points of the right ventricle to the left ventricle in CINE cardiac data.

Applying the Balanced Scorecard approach in teaching hospitals: a literature review and conceptual framework.

PubMed

Trotta, Annarita; Cardamone, Emma; Cavallaro, Giusy; Mauro, Marianna

2013-01-01

Teaching hospitals (THs) simultaneously serve three different roles: offering medical treatment, teaching future doctors and promoting research. The international literature recognises such organisations as 'peaks of excellence' and highlights their economic function in the health system. In addition, the literature describes the urgent need to manage the complex dynamics and inefficiency issues that threaten the survival of teaching hospitals worldwide. In this context, traditional performance measurement systems that focus only on accounting and financial measures appear to be inadequate. Given that THs are highly specific and complex, a multidimensional system of performance measurement, such as the Balanced Scorecard (BSC), may be more appropriate because of the multitude of stakeholders, each of whom seek a specific type of accountability. The aim of the paper was twofold: (i) to review the literature on the BSC and its applications in teaching hospitals and (ii) to propose a scorecard framework that is suitable for assessing the performance of THs and serving as a guide for scholars and practitioners. In addition, this research will contribute to the ongoing debate on performance evaluation systems by suggesting a revised BSC framework and proposing specific performance indicators for THs. Copyright © 2012 John Wiley & Sons, Ltd.

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

Statistical Fusion of Continuous Labels: Identification of Cardiac Landmarks.

PubMed

Xing, Fangxu; Soleimanifard, Sahar; Prince, Jerry L; Landman, Bennett A

2011-01-01

Image labeling is an essential task for evaluating and analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms. However, both approaches for labeling suffer from inevitable error due to noise and artifact in the acquired data. The Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm was developed to combine multiple rater decisions and simultaneously estimate unobserved true labels as well as each rater's level of performance (i.e., reliability). A generalization of STAPLE for the case of continuous-valued labels has also been proposed. In this paper, we first show that with the proposed Gaussian distribution assumption, this continuous STAPLE formulation yields equivalent likelihoods for the bias parameter, meaning that the bias parameter-one of the key performance indices-is actually indeterminate. We resolve this ambiguity by augmenting the STAPLE expectation maximization formulation to include a priori probabilities on the performance level parameters, which enables simultaneous, meaningful estimation of both the rater bias and variance performance measures. We evaluate and demonstrate the efficacy of this approach in simulations and also through a human rater experiment involving the identification the intersection points of the right ventricle to the left ventricle in CINE cardiac data.

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE PAGES

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

2016-07-26

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

IT Solution concept development for tracking and analyzing the labor effectiveness of employees

NASA Astrophysics Data System (ADS)

Ilin, Igor; Shirokova, Svetlana; Lepekhin, Aleksandr

2018-03-01

Labor efficiency and productivity of employees is an important aspect for the environment within any type of organization. This is particularly crucial factor for the companies, if which operations are associated with physical labor, such as construction companies. Productivity and efficiency are both very complicated concepts and a huge variety of methods and approaches to its analysis can be implemented within the organization. Despite that, it is important to choose the methods, which not only analyze the key performance indicators of employee, but take into account personal indicators, which might affect performance even more than professional skills. For this complicated analysis task it is important to build IT solution for tracking and analyzing of the labor effectiveness. The concept for designing this IT solution is proposed in the current research.

Improving Explicit Congestion Notification with the Mark-Front Strategy

NASA Technical Reports Server (NTRS)

Liu, Chunlei; Jain, Raj

2001-01-01

Delivering congestion signals is essential to the performance of networks. Current TCP/IP networks use packet losses to signal congestion. Packet losses not only reduces TCP performance, but also adds large delay. Explicit Congestion Notification (ECN) delivers a faster indication of congestion and has better performance. However, current ECN implementations mark the packet from the tail of the queue. In this paper, we propose the mark-front strategy to send an even faster congestion signal. We show that mark-front strategy reduces buffer size requirement, improves link efficiency and provides better fairness among users. Simulation results that verify our analysis are also presented.

Cooperative Learning for Distributed In-Network Traffic Classification

NASA Astrophysics Data System (ADS)

Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.

2017-04-01

Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.

Modification of a melanoma discrimination index derived from hyperspectral data: a clinical trial conducted in 2 centers between March 2011 and December 2013.

PubMed

Nagaoka, T; Kiyohara, Y; Koga, H; Nakamura, A; Saida, T; Sota, T

2015-08-01

The morphology of pigmented skin lesions (PSLs) is predominantly a result of varying concentrations and distributions of pigmented molecules such as melanin and hemoglobin. Based on these differences and the fact that their information is contained in cutaneous spectra, a hyperspectral imager (HSI) for pigmented melanoma and a single discrimination index derived from the resultant hyperspectral data are proposed. To develop and evaluate a new discrimination index for melanomas, compared to the previous index. A HSI, which is convenient for both patients and clinicians, was newly developed and used in a clinical trial conducted in 2 centers with 80 patients with primary lesions and 17 volunteers between March 2011 and December 2013. There were 24 melanomas and 110 other PSLs. A previously proposed discrimination index was used without modifications. A new index, which emphasized the essential features of melanoma, was proposed, and its performance was examined. For each index, a threshold value was set to minimize the average value of the false positive and false negative fractions. The performances of both indices were compared. The sensitivity and specificity of the old index were 75% and 97%, respectively, while those of the new index were 96% and 87%. The new index had a higher sensitivity and adequate specificity, indicating that it is more useful than the old index. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multiple sound source localization using gammatone auditory filtering and direct sound componence detection

NASA Astrophysics Data System (ADS)

Chen, Huaiyu; Cao, Li

2017-06-01

In order to research multiple sound source localization with room reverberation and background noise, we analyze the shortcomings of traditional broadband MUSIC and ordinary auditory filtering based broadband MUSIC method, then a new broadband MUSIC algorithm with gammatone auditory filtering of frequency component selection control and detection of ascending segment of direct sound componence is proposed. The proposed algorithm controls frequency component within the interested frequency band in multichannel bandpass filter stage. Detecting the direct sound componence of the sound source for suppressing room reverberation interference is also proposed, whose merits are fast calculation and avoiding using more complex de-reverberation processing algorithm. Besides, the pseudo-spectrum of different frequency channels is weighted by their maximum amplitude for every speech frame. Through the simulation and real room reverberation environment experiments, the proposed method has good performance. Dynamic multiple sound source localization experimental results indicate that the average absolute error of azimuth estimated by the proposed algorithm is less and the histogram result has higher angle resolution.

An Efficient Audio Watermarking Algorithm in Frequency Domain for Copyright Protection

NASA Astrophysics Data System (ADS)

Dhar, Pranab Kumar; Khan, Mohammad Ibrahim; Kim, Cheol-Hong; Kim, Jong-Myon

Digital Watermarking plays an important role for copyright protection of multimedia data. This paper proposes a new watermarking system in frequency domain for copyright protection of digital audio. In our proposed watermarking system, the original audio is segmented into non-overlapping frames. Watermarks are then embedded into the selected prominent peaks in the magnitude spectrum of each frame. Watermarks are extracted by performing the inverse operation of watermark embedding process. Simulation results indicate that the proposed watermarking system is highly robust against various kinds of attacks such as noise addition, cropping, re-sampling, re-quantization, MP3 compression, and low-pass filtering. Our proposed watermarking system outperforms Cox's method in terms of imperceptibility, while keeping comparable robustness with the Cox's method. Our proposed system achieves SNR (signal-to-noise ratio) values ranging from 20 dB to 28 dB, in contrast to Cox's method which achieves SNR values ranging from only 14 dB to 23 dB.

Development of neural network techniques for finger-vein pattern classification

NASA Astrophysics Data System (ADS)

Wu, Jian-Da; Liu, Chiung-Tsiung; Tsai, Yi-Jang; Liu, Jun-Ching; Chang, Ya-Wen

2010-02-01

A personal identification system using finger-vein patterns and neural network techniques is proposed in the present study. In the proposed system, the finger-vein patterns are captured by a device that can transmit near infrared through the finger and record the patterns for signal analysis and classification. The biometric system for verification consists of a combination of feature extraction using principal component analysis and pattern classification using both back-propagation network and adaptive neuro-fuzzy inference systems. Finger-vein features are first extracted by principal component analysis method to reduce the computational burden and removes noise residing in the discarded dimensions. The features are then used in pattern classification and identification. To verify the effect of the proposed adaptive neuro-fuzzy inference system in the pattern classification, the back-propagation network is compared with the proposed system. The experimental results indicated the proposed system using adaptive neuro-fuzzy inference system demonstrated a better performance than the back-propagation network for personal identification using the finger-vein patterns.

Assessing the risk posed by natural hazards to infrastructures

NASA Astrophysics Data System (ADS)

Eidsvig, Unni; Kristensen, Krister; Vidar Vangelsten, Bjørn

2015-04-01

The modern society is increasingly dependent on infrastructures to maintain its function, and disruption in one of the infrastructure systems may have severe consequences. The Norwegian municipalities have, according to legislation, a duty to carry out a risk and vulnerability analysis and plan and prepare for emergencies in a short- and long term perspective. Vulnerability analysis of the infrastructures and their interdependencies is an important part of this analysis. This paper proposes a model for assessing the risk posed by natural hazards to infrastructures. The model prescribes a three level analysis with increasing level of detail, moving from qualitative to quantitative analysis. This paper focuses on the second level, which consists of a semi-quantitative analysis. The purpose of this analysis is to perform a screening of the scenarios of natural hazards threatening the infrastructures identified in the level 1 analysis and investigate the need for further analyses, i.e. level 3 quantitative analyses. The proposed level 2 analysis considers the frequency of the natural hazard, different aspects of vulnerability including the physical vulnerability of the infrastructure itself and the societal dependency on the infrastructure. An indicator-based approach is applied, ranking the indicators on a relative scale. The proposed indicators characterize the robustness of the infrastructure, the importance of the infrastructure as well as interdependencies between society and infrastructure affecting the potential for cascading effects. Each indicator is ranked on a 1-5 scale based on pre-defined ranking criteria. The aggregated risk estimate is a combination of the semi-quantitative vulnerability indicators, as well as quantitative estimates of the frequency of the natural hazard and the number of users of the infrastructure. Case studies for two Norwegian municipalities are presented, where risk to primary road, water supply and power network threatened by storm and landslide is assessed. The application examples show that the proposed model provides a useful tool for screening of undesirable events, with the ultimate goal to reduce the societal vulnerability.

Use of Balanced Indicators as a Management Tool in Nursing.

PubMed

Fugaça, Neidamar Pedrini Arias; Cubas, Marcia Regina; Carvalho, Deborah Ribeiro

2015-01-01

To develop a proposal for a nursing panel of indicators based on the guiding principles of Balanced Scorecard. A single case study that ranked 200 medical records of patients, management reports and protocols, which are capable of generating indicators. We identified 163 variables that resulted in 72 indicators; of these, 32 nursing-related: two financial indicators (patient's average revenue per day and patient's revenue per day by product used); two client indicators (overall satisfaction rate of patient with nursing care and adherence rate to the patient satisfaction survey); 23 process indicators, and five learning and growth indicators (average total hours of training, total of approved nursing professionals in the internal selection process, absenteeism rate, turnover rate and index of performance evaluation). Although there is a limit related to the amount of data generated, the methodology of Balanced Scorecard has proved to be flexible and adaptable to incorporate nursing services. It was possible to identify indicators with adherence to more than one area. Internal processes was the area with the higher number of indicators.

EFPI sensor utilizing optical spectrum analyzer with tunable laser: detection of baseline oscillations faster than spectrum acquisition rate

NASA Astrophysics Data System (ADS)

Ushakov, Nikolai; Liokumovich, Leonid

2014-05-01

A novel approach for extrinsic Fabry-Perot interferometer baseline measurement has been developed. The principles of frequency-scanning interferometry are utilized for registration of the interferometer spectral function, from which the baseline is demodulated. The proposed approach enables one to capture the absolute baseline variations at frequencies much higher than the spectral acquisition rate. Despite the conventional approaches, associating a single baseline indication to the registered spectrum, in the proposed method a modified frequency detection procedure is applied to the spectrum. This provides an ability to capture the baseline variations which took place during the spectrum acquisition. The limitations on the parameters of the possibly registered baseline variations are formulated. The experimental verification of the proposed approach for different perturbations has been performed.

Robust Speech Enhancement Using Two-Stage Filtered Minima Controlled Recursive Averaging

NASA Astrophysics Data System (ADS)

Ghourchian, Negar; Selouani, Sid-Ahmed; O'Shaughnessy, Douglas

In this paper we propose an algorithm for estimating noise in highly non-stationary noisy environments, which is a challenging problem in speech enhancement. This method is based on minima-controlled recursive averaging (MCRA) whereby an accurate, robust and efficient noise power spectrum estimation is demonstrated. We propose a two-stage technique to prevent the appearance of musical noise after enhancement. This algorithm filters the noisy speech to achieve a robust signal with minimum distortion in the first stage. Subsequently, it estimates the residual noise using MCRA and removes it with spectral subtraction. The proposed Filtered MCRA (FMCRA) performance is evaluated using objective tests on the Aurora database under various noisy environments. These measures indicate the higher output SNR and lower output residual noise and distortion.

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Determination of phthalate esters from environmental water samples by micro-solid-phase extraction using TiO2 nanotube arrays before high-performance liquid chromatography.

PubMed

Zhou, Qingxiang; Fang, Zhi; Liao, Xiangkun

2015-07-01

We describe a highly sensitive micro-solid-phase extraction method for the pre-concentration of six phthalate esters utilizing a TiO2 nanotube array coupled to high-performance liquid chromatography with a variable-wavelength ultraviolet visible detector. The selected phthalate esters included dimethyl phthalate, diethyl phthalate, dibutyl phthalate, butyl benzyl phthalate, bis(2-ethylhexyl)phthalate and dioctyl phthalate. The factors that would affect the enrichment, such as desorption solvent, sample pH, salting-out effect, extraction time and desorption time, were optimized. Under the optimum conditions, the linear range of the proposed method was 0.3-200 μg/L. The limits of detection were 0.04-0.2 μg/L (S/N = 3). The proposed method was successfully applied to the determination of six phthalate esters in water samples and satisfied spiked recoveries were achieved. These results indicated that the proposed method was appropriate for the determination of trace phthalate esters in environmental water samples. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model parameter estimation approach based on incremental analysis for lithium-ion batteries without using open circuit voltage

NASA Astrophysics Data System (ADS)

Wu, Hongjie; Yuan, Shifei; Zhang, Xi; Yin, Chengliang; Ma, Xuerui

2015-08-01

To improve the suitability of lithium-ion battery model under varying scenarios, such as fluctuating temperature and SoC variation, dynamic model with parameters updated realtime should be developed. In this paper, an incremental analysis-based auto regressive exogenous (I-ARX) modeling method is proposed to eliminate the modeling error caused by the OCV effect and improve the accuracy of parameter estimation. Then, its numerical stability, modeling error, and parametric sensitivity are analyzed at different sampling rates (0.02, 0.1, 0.5 and 1 s). To identify the model parameters recursively, a bias-correction recursive least squares (CRLS) algorithm is applied. Finally, the pseudo random binary sequence (PRBS) and urban dynamic driving sequences (UDDSs) profiles are performed to verify the realtime performance and robustness of the newly proposed model and algorithm. Different sampling rates (1 Hz and 10 Hz) and multiple temperature points (5, 25, and 45 °C) are covered in our experiments. The experimental and simulation results indicate that the proposed I-ARX model can present high accuracy and suitability for parameter identification without using open circuit voltage.

Comparison of proposed countermeasures for dilemma zone at signalized intersections based on cellular automata simulations.

PubMed

Wu, Yina; Abdel-Aty, Mohamed; Ding, Yaoxian; Jia, Bin; Shi, Qi; Yan, Xuedong

2018-07-01

The Type II dilemma zone describes the road segment to a signalized intersection where drivers have difficulties to decide either stop or go at the onset of yellow signal. Such phenomenon can result in an increased crash risk at signalized intersections. Different types of warning systems have been proposed to help drivers make decisions. Although the warning systems help to improve drivers' behavior, they also have several disadvantages such as increasing rear-end crashes or red-light running (RLR) violations. In this study, a new warning system called pavement marking with auxiliary countermeasure (PMAIC) is proposed to reduce the dilemma zone and enhance the traffic safety at signalized intersections. The proposed warning system integrates the pavement marking and flashing yellow system which can provide drivers with better suggestions about stop/go decisions based on their arriving time and speed. In order to evaluate the performance of the proposed warning system, this paper presents a cellular automata (CA) simulation study. The CA simulations are conducted for four different scenarios in total, including the typical intersection without warning system, the intersection with flashing green countermeasure, the intersection with pavement marking, and the intersection with the PMAIC warning system. Before the specific CA simulation analysis, a logistic regression model is calibrated based on field video data to predict drivers' general stop/go decisions. Also, the rules of vehicle movements in the CA models under the influence by different warning systems are proposed. The proxy indicators of rear-end crash and potential RLR violations were estimated and used to evaluate safety levels for the different scenarios. The simulation results showed that the PMAIC countermeasure consistently offered best performance to reduce rear-end crash and RLR violation. Meanwhile, the results indicate that the flashing-green countermeasure could not effectively reduce either rear-end crash risk or RLR violations. Also, it is found that the pavement-marking countermeasure has positive effects on reducing the rear-end risk while it may increase the probability of RLR violation. Lastly, the implementation of the proposed warning system is discussed with the consideration of connected-vehicle technology. It is expected that the dilemma zone issues can be efficiently addressed if the proposed countermeasure can be employed within connected vehicle technology. Copyright © 2017 Elsevier Ltd. All rights reserved.

A robust indicator based on singular value decomposition for flaw feature detection from noisy ultrasonic signals

NASA Astrophysics Data System (ADS)

Cui, Ximing; Wang, Zhe; Kang, Yihua; Pu, Haiming; Deng, Zhiyang

2018-05-01

Singular value decomposition (SVD) has been proven to be an effective de-noising tool for flaw echo signal feature detection in ultrasonic non-destructive evaluation (NDE). However, the uncertainty in the arbitrary manner of the selection of an effective singular value weakens the robustness of this technique. Improper selection of effective singular values will lead to bad performance of SVD de-noising. What is more, the computational complexity of SVD is too large for it to be applied in real-time applications. In this paper, to eliminate the uncertainty in SVD de-noising, a novel flaw indicator, named the maximum singular value indicator (MSI), based on short-time SVD (STSVD), is proposed for flaw feature detection from a measured signal in ultrasonic NDE. In this technique, the measured signal is first truncated into overlapping short-time data segments to put feature information of a transient flaw echo signal in local field, and then the MSI can be obtained from the SVD of each short-time data segment. Research shows that this indicator can clearly indicate the location of ultrasonic flaw signals, and the computational complexity of this STSVD-based indicator is significantly reduced with the algorithm proposed in this paper. Both simulation and experiments show that this technique is very efficient for real-time application in flaw detection from noisy data.

An improved input shaping design for an efficient sway control of a nonlinear 3D overhead crane with friction

NASA Astrophysics Data System (ADS)

Maghsoudi, Mohammad Javad; Mohamed, Z.; Sudin, S.; Buyamin, S.; Jaafar, H. I.; Ahmad, S. M.

2017-08-01

This paper proposes an improved input shaping scheme for an efficient sway control of a nonlinear three dimensional (3D) overhead crane with friction using the particle swarm optimization (PSO) algorithm. Using this approach, a higher payload sway reduction is obtained as the input shaper is designed based on a complete nonlinear model, as compared to the analytical-based input shaping scheme derived using a linear second order model. Zero Vibration (ZV) and Distributed Zero Vibration (DZV) shapers are designed using both analytical and PSO approaches for sway control of rail and trolley movements. To test the effectiveness of the proposed approach, MATLAB simulations and experiments on a laboratory 3D overhead crane are performed under various conditions involving different cable lengths and sway frequencies. Their performances are studied based on a maximum residual of payload sway and Integrated Absolute Error (IAE) values which indicate total payload sway of the crane. With experiments, the superiority of the proposed approach over the analytical-based is shown by 30-50% reductions of the IAE values for rail and trolley movements, for both ZV and DZV shapers. In addition, simulations results show higher sway reductions with the proposed approach. It is revealed that the proposed PSO-based input shaping design provides higher payload sway reductions of a 3D overhead crane with friction as compared to the commonly designed input shapers.

Area and power efficient DCT architecture for image compression

NASA Astrophysics Data System (ADS)

Dhandapani, Vaithiyanathan; Ramachandran, Seshasayanan

2014-12-01

The discrete cosine transform (DCT) is one of the major components in image and video compression systems. The final output of these systems is interpreted by the human visual system (HVS), which is not perfect. The limited perception of human visualization allows the algorithm to be numerically approximate rather than exact. In this paper, we propose a new matrix for discrete cosine transform. The proposed 8 × 8 transformation matrix contains only zeros and ones which requires only adders, thus avoiding the need for multiplication and shift operations. The new class of transform requires only 12 additions, which highly reduces the computational complexity and achieves a performance in image compression that is comparable to that of the existing approximated DCT. Another important aspect of the proposed transform is that it provides an efficient area and power optimization while implementing in hardware. To ensure the versatility of the proposal and to further evaluate the performance and correctness of the structure in terms of speed, area, and power consumption, the model is implemented on Xilinx Virtex 7 field programmable gate array (FPGA) device and synthesized with Cadence® RTL Compiler® using UMC 90 nm standard cell library. The analysis obtained from the implementation indicates that the proposed structure is superior to the existing approximation techniques with a 30% reduction in power and 12% reduction in area.

Extra-analytical quality indicators and laboratory performances.

PubMed

Sciacovelli, Laura; Aita, Ada; Plebani, Mario

2017-07-01

In the last few years much progress has been made in raising the awareness of laboratory medicine professionals about the effectiveness of quality indicators (QIs) in monitoring, and improving upon, performances in the extra-analytical phases of the Total Testing Process (TTP). An effective system for management of QIs includes the implementation of an internal assessment system and participation in inter-laboratory comparison. A well-designed internal assessment system allows the identification of critical activities and their systematic monitoring. Active participation in inter-laboratory comparison provides information on the performance level of one laboratory with respect to that of other participating laboratories. In order to guarantee the use of appropriate QIs and facilitate their implementation, many laboratories have adopted the Model of Quality Indicators (MQI) proposed by Working Group "Laboratory Errors and Patient Safety" (WG-LEPS) of IFCC, since 2008, which is the result of international consensus and continuous experimentation, and updating to meet new, constantly emerging needs. Data from participating laboratories are collected monthly and reports describing the statistical results and evaluating laboratory data, utilizing the Six Sigma metric, issued regularly. Although the results demonstrate that the processes need to be improved upon, overall the comparison with data collected in 2014 shows a general stability of quality levels and that an improvement has been achieved over time for some activities. The continuous monitoring of QI data allows identification all possible improvements, thus highlighting the value of participation in the inter-laboratory program proposed by WG-LEPS. The active participation of numerous laboratories will guarantee an ever more significant State-of-the-Art, promote the reduction of errors and improve quality of the TTP, thus guaranteeing patient safety. Copyright © 2017. Published by Elsevier Inc.

Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments.

PubMed

Baldominos, Alejandro; Saez, Yago; Isasi, Pedro

2018-04-23

Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures.

Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments

PubMed Central

2018-01-01

Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures. PMID:29690587

Retrieval of canopy water content of different crop types with two new hyperspectral indices: Water Absorption Area Index and Depth Water Index

NASA Astrophysics Data System (ADS)

Pasqualotto, Nieves; Delegido, Jesús; Van Wittenberghe, Shari; Verrelst, Jochem; Rivera, Juan Pablo; Moreno, José

2018-05-01

Crop canopy water content (CWC) is an essential indicator of the crop's physiological state. While a diverse range of vegetation indices have earlier been developed for the remote estimation of CWC, most of them are defined for specific crop types and areas, making them less universally applicable. We propose two new water content indices applicable to a wide variety of crop types, allowing to derive CWC maps at a large spatial scale. These indices were developed based on PROSAIL simulations and then optimized with an experimental dataset (SPARC03; Barrax, Spain). This dataset consists of water content and other biophysical variables for five common crop types (lucerne, corn, potato, sugar beet and onion) and corresponding top-of-canopy (TOC) reflectance spectra acquired by the hyperspectral HyMap airborne sensor. First, commonly used water content index formulations were analysed and validated for the variety of crops, overall resulting in a R2 lower than 0.6. In an attempt to move towards more generically applicable indices, the two new CWC indices exploit the principal water absorption features in the near-infrared by using multiple bands sensitive to water content. We propose the Water Absorption Area Index (WAAI) as the difference between the area under the null water content of TOC reflectance (reference line) simulated with PROSAIL and the area under measured TOC reflectance between 911 and 1271 nm. We also propose the Depth Water Index (DWI), a simplified four-band index based on the spectral depths produced by the water absorption at 970 and 1200 nm and two reference bands. Both the WAAI and DWI outperform established indices in predicting CWC when applied to heterogeneous croplands, with a R2 of 0.8 and 0.7, respectively, using an exponential fit. However, these indices did not perform well for species with a low fractional vegetation cover (<30%). HyMap CWC maps calculated with both indices are shown for the Barrax region. The results confirmed the potential of using generically applicable indices for calculating CWC over a great variety of crops.

On local search for bi-objective knapsack problems.

PubMed

Liefooghe, Arnaud; Paquete, Luís; Figueira, José Rui

2013-01-01

In this article, a local search approach is proposed for three variants of the bi-objective binary knapsack problem, with the aim of maximizing the total profit and minimizing the total weight. First, an experimental study on a given structural property of connectedness of the efficient set is conducted. Based on this property, a local search algorithm is proposed and its performance is compared to exact algorithms in terms of runtime and quality metrics. The experimental results indicate that this simple local search algorithm is able to find a representative set of optimal solutions in most of the cases, and in much less time than exact algorithms.

Hiding message into DNA sequence through DNA coding and chaotic maps.

PubMed

Liu, Guoyan; Liu, Hongjun; Kadir, Abdurahman

2014-09-01

The paper proposes an improved reversible substitution method to hide data into deoxyribonucleic acid (DNA) sequence, and four measures have been taken to enhance the robustness and enlarge the hiding capacity, such as encode the secret message by DNA coding, encrypt it by pseudo-random sequence, generate the relative hiding locations by piecewise linear chaotic map, and embed the encoded and encrypted message into a randomly selected DNA sequence using the complementary rule. The key space and the hiding capacity are analyzed. Experimental results indicate that the proposed method has a better performance compared with the competing methods with respect to robustness and capacity.

An almost-parameter-free harmony search algorithm for groundwater pollution source identification.

PubMed

Jiang, Simin; Zhang, Yali; Wang, Pei; Zheng, Maohui

2013-01-01

The spatiotemporal characterization of unknown sources of groundwater pollution is frequently encountered in environmental problems. This study adopts a simulation-optimization approach that combines a contaminant transport simulation model with a heuristic harmony search algorithm to identify unknown pollution sources. In the proposed methodology, an almost-parameter-free harmony search algorithm is developed. The performance of this methodology is evaluated on an illustrative groundwater pollution source identification problem, and the identified results indicate that the proposed almost-parameter-free harmony search algorithm-based optimization model can give satisfactory estimations, even when the irregular geometry, erroneous monitoring data, and prior information shortage of potential locations are considered.

Flow Friction or Spontaneous Ignition?

NASA Technical Reports Server (NTRS)

Stoltzfus, Joel M.; Gallus, Timothy D.; Sparks, Kyle

2012-01-01

"Flow friction," a proposed ignition mechanism in oxygen systems, has proved elusive in attempts at experimental verification. In this paper, the literature regarding flow friction is reviewed and the experimental verification attempts are briefly discussed. Another ignition mechanism, a form of spontaneous combustion, is proposed as an explanation for at least some of the fire events that have been attributed to flow friction in the literature. In addition, the results of a failure analysis performed at NASA Johnson Space Center White Sands Test Facility are presented, and the observations indicate that spontaneous combustion was the most likely cause of the fire in this 2000 psig (14 MPa) oxygen-enriched system.

A reliable facility location design model with site-dependent disruption in the imperfect information context

PubMed Central

Yun, Lifen; Wang, Xifu; Fan, Hongqiang; Li, Xiaopeng

2017-01-01

This paper proposes a reliable facility location design model under imperfect information with site-dependent disruptions; i.e., each facility is subject to a unique disruption probability that varies across the space. In the imperfect information contexts, customers adopt a realistic “trial-and-error” strategy to visit facilities; i.e., they visit a number of pre-assigned facilities sequentially until they arrive at the first operational facility or give up looking for the service. This proposed model aims to balance initial facility investment and expected long-term operational cost by finding the optimal facility locations. A nonlinear integer programming model is proposed to describe this problem. We apply a linearization technique to reduce the difficulty of solving the proposed model. A number of problem instances are studied to illustrate the performance of the proposed model. The results indicate that our proposed model can reveal a number of interesting insights into the facility location design with site-dependent disruptions, including the benefit of backup facilities and system robustness against variation of the loss-of-service penalty. PMID:28486564

A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems.

PubMed

Ayvaz, M Tamer

2010-09-20

This study proposes a linked simulation-optimization model for solving the unknown groundwater pollution source identification problems. In the proposed model, MODFLOW and MT3DMS packages are used to simulate the flow and transport processes in the groundwater system. These models are then integrated with an optimization model which is based on the heuristic harmony search (HS) algorithm. In the proposed simulation-optimization model, the locations and release histories of the pollution sources are treated as the explicit decision variables and determined through the optimization model. Also, an implicit solution procedure is proposed to determine the optimum number of pollution sources which is an advantage of this model. The performance of the proposed model is evaluated on two hypothetical examples for simple and complex aquifer geometries, measurement error conditions, and different HS solution parameter sets. Identified results indicated that the proposed simulation-optimization model is an effective way and may be used to solve the inverse pollution source identification problems. Copyright (c) 2010 Elsevier B.V. All rights reserved.

A family of interaction-adjusted indices of community similarity.

PubMed

Schmidt, Thomas Sebastian Benedikt; Matias Rodrigues, João Frederico; von Mering, Christian

2017-03-01

Interactions between taxa are essential drivers of ecological community structure and dynamics, but they are not taken into account by traditional indices of β diversity. In this study, we propose a novel family of indices that quantify community similarity in the context of taxa interaction networks. Using publicly available datasets, we assessed the performance of two specific indices that are Taxa INteraction-Adjusted (TINA, based on taxa co-occurrence networks), and Phylogenetic INteraction-Adjusted (PINA, based on phylogenetic similarities). TINA and PINA outperformed traditional indices when partitioning human-associated microbial communities according to habitat, even for extremely downsampled datasets, and when organising ocean micro-eukaryotic plankton diversity according to geographical and physicochemical gradients. We argue that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity.

A family of interaction-adjusted indices of community similarity

PubMed Central

Schmidt, Thomas Sebastian Benedikt; Matias Rodrigues, João Frederico; von Mering, Christian

2017-01-01

Interactions between taxa are essential drivers of ecological community structure and dynamics, but they are not taken into account by traditional indices of β diversity. In this study, we propose a novel family of indices that quantify community similarity in the context of taxa interaction networks. Using publicly available datasets, we assessed the performance of two specific indices that are Taxa INteraction-Adjusted (TINA, based on taxa co-occurrence networks), and Phylogenetic INteraction-Adjusted (PINA, based on phylogenetic similarities). TINA and PINA outperformed traditional indices when partitioning human-associated microbial communities according to habitat, even for extremely downsampled datasets, and when organising ocean micro-eukaryotic plankton diversity according to geographical and physicochemical gradients. We argue that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity. PMID:27935587

Small drinking water systems under spatiotemporal water quality variability: a risk-based performance benchmarking framework.

PubMed

Bereskie, Ty; Haider, Husnain; Rodriguez, Manuel J; Sadiq, Rehan

2017-08-23

Traditional approaches for benchmarking drinking water systems are binary, based solely on the compliance and/or non-compliance of one or more water quality performance indicators against defined regulatory guidelines/standards. The consequence of water quality failure is dependent on location within a water supply system as well as time of the year (i.e., season) with varying levels of water consumption. Conventional approaches used for water quality comparison purposes fail to incorporate spatiotemporal variability and degrees of compliance and/or non-compliance. This can lead to misleading or inaccurate performance assessment data used in the performance benchmarking process. In this research, a hierarchical risk-based water quality performance benchmarking framework is proposed to evaluate small drinking water systems (SDWSs) through cross-comparison amongst similar systems. The proposed framework (R WQI framework) is designed to quantify consequence associated with seasonal and location-specific water quality issues in a given drinking water supply system to facilitate more efficient decision-making for SDWSs striving for continuous performance improvement. Fuzzy rule-based modelling is used to address imprecision associated with measuring performance based on singular water quality guidelines/standards and the uncertainties present in SDWS operations and monitoring. This proposed R WQI framework has been demonstrated using data collected from 16 SDWSs in Newfoundland and Labrador and Quebec, Canada, and compared to the Canadian Council of Ministers of the Environment WQI, a traditional, guidelines/standard-based approach. The study found that the R WQI framework provides an in-depth state of water quality and benchmarks SDWSs more rationally based on the frequency of occurrence and consequence of failure events.

Quantum Computation Using Optically Coupled Quantum Dot Arrays

NASA Technical Reports Server (NTRS)

Pradhan, Prabhakar; Anantram, M. P.; Wang, K. L.; Roychowhury, V. P.; Saini, Subhash (Technical Monitor)

1998-01-01

A solid state model for quantum computation has potential advantages in terms of the ease of fabrication, characterization, and integration. The fundamental requirements for a quantum computer involve the realization of basic processing units (qubits), and a scheme for controlled switching and coupling among the qubits, which enables one to perform controlled operations on qubits. We propose a model for quantum computation based on optically coupled quantum dot arrays, which is computationally similar to the atomic model proposed by Cirac and Zoller. In this model, individual qubits are comprised of two coupled quantum dots, and an array of these basic units is placed in an optical cavity. Switching among the states of the individual units is done by controlled laser pulses via near field interaction using the NSOM technology. Controlled rotations involving two or more qubits are performed via common cavity mode photon. We have calculated critical times, including the spontaneous emission and switching times, and show that they are comparable to the best times projected for other proposed models of quantum computation. We have also shown the feasibility of accessing individual quantum dots using the NSOM technology by calculating the photon density at the tip, and estimating the power necessary to perform the basic controlled operations. We are currently in the process of estimating the decoherence times for this system; however, we have formulated initial arguments which seem to indicate that the decoherence times will be comparable, if not longer, than many other proposed models.

Evolvable rough-block-based neural network and its biomedical application to hypoglycemia detection system.

PubMed

San, Phyo Phyo; Ling, Sai Ho; Nuryani; Nguyen, Hung

2014-08-01

This paper focuses on the hybridization technology using rough sets concepts and neural computing for decision and classification purposes. Based on the rough set properties, the lower region and boundary region are defined to partition the input signal to a consistent (predictable) part and an inconsistent (random) part. In this way, the neural network is designed to deal only with the boundary region, which mainly consists of an inconsistent part of applied input signal causing inaccurate modeling of the data set. Owing to different characteristics of neural network (NN) applications, the same structure of conventional NN might not give the optimal solution. Based on the knowledge of application in this paper, a block-based neural network (BBNN) is selected as a suitable classifier due to its ability to evolve internal structures and adaptability in dynamic environments. This architecture will systematically incorporate the characteristics of application to the structure of hybrid rough-block-based neural network (R-BBNN). A global training algorithm, hybrid particle swarm optimization with wavelet mutation is introduced for parameter optimization of proposed R-BBNN. The performance of the proposed R-BBNN algorithm was evaluated by an application to the field of medical diagnosis using real hypoglycemia episodes in patients with Type 1 diabetes mellitus. The performance of the proposed hybrid system has been compared with some of the existing neural networks. The comparison results indicated that the proposed method has improved classification performance and results in early convergence of the network.

Highly sensitive selectively coated photonic crystal fiber-based plasmonic sensor.

PubMed

Rifat, Ahmmed A; Haider, Firoz; Ahmed, Rajib; Mahdiraji, Ghafour Amouzad; Mahamd Adikan, F R; Miroshnichenko, Andrey E

2018-02-15

Highly sensitive and miniaturized sensors are highly desirable for real-time analyte/sample detection. In this Letter, we propose a highly sensitive plasmonic sensing scheme with the miniaturized photonic crystal fiber (PCF) attributes. A large cavity is introduced in the first ring of the PCFs for the efficient field excitation of the surface plasmon polariton mode and proficient infiltration of the sensing elements. Due to the irregular air-hole diameter in the first ring, the cavity exhibits the birefringence behavior which enhances the sensing performance. The novel plasmonic material gold has been used considering the chemical stability in an aqueous environment. The guiding properties and the effects of the sensing performance with different parameters have been investigated by the finite element method, and the proposed PCFs have been fabricated using the stack-and-draw fiber drawing method. The proposed sensor performance was investigated based on the wavelength and amplitude sensing techniques and shows the maximum sensitivities of 11,000 nm/RIU and 1,420  RIU -1 , respectively. It also shows the maximum sensor resolutions of 9.1×10 -6 and 7×10 -6   RIU for the wavelength and amplitude sensing schemes, respectively, and the maximum figure of merits of 407. Furthermore, the proposed sensor is able to detect the analyte refractive indices in the range of 1.33-1.42; as a result, it will find the possible applications in the medical diagnostics, biomolecules, organic chemical, and chemical analyte detection.

Dissociating the Components of Switch Cost Using Two-to-Two Cue-Task Mapping

ERIC Educational Resources Information Center

Hydock, Chris; Sohn, Myeong-Ho

2011-01-01

In the task switch paradigm, a switch of task is typically accompanied by a change in task cue. It has been proposed that the performance deficit usually observed when switching tasks is actually the result of changing cues. To test this possibility, we used a 2:2 cue-task mapping in which each cue indicated 2 different tasks. With advance…

An enhanced DWBA algorithm in hybrid WDM/TDM EPON networks with heterogeneous propagation delays

NASA Astrophysics Data System (ADS)

Li, Chengjun; Guo, Wei; Jin, Yaohui; Sun, Weiqiang; Hu, Weisheng

2011-12-01

An enhanced dynamic wavelength and bandwidth allocation (DWBA) algorithm in hybrid WDM/TDM PON is proposed and experimentally demonstrated. In addition to the fairness of bandwidth allocation, this algorithm also considers the varying propagation delays between ONUs and OLT. The simulation based on MATLAB indicates that the improved algorithm has a better performance compared with some other algorithms.

Novel Three-Dimensional Vertical Interconnect Technology for Microwave and RF Applications

NASA Technical Reports Server (NTRS)

Goverdhanam, Kavita; Simons, Rainee N.; Katehi, Linda P. B.

1999-01-01

In this paper, novel 3D interconnects suitable for applications in microwave and RF integrated circuit technology have been presented. The interconnect fabrication process and design details are presented. In addition, measured and numerically modeled results of the performance of the interconnects have been shown. The results indicate that the proposed technology has tremendous potential applications in integrated circuit technology. C,

A joint precoding scheme for indoor downlink multi-user MIMO VLC systems

NASA Astrophysics Data System (ADS)

Zhao, Qiong; Fan, Yangyu; Kang, Bochao

2017-11-01

In this study, we aim to improve the system performance and reduce the implementation complexity of precoding scheme for visible light communication (VLC) systems. By incorporating the power-method algorithm and the block diagonalization (BD) algorithm, we propose a joint precoding scheme for indoor downlink multi-user multi-input-multi-output (MU-MIMO) VLC systems. In this scheme, we apply the BD algorithm to eliminate the co-channel interference (CCI) among users firstly. Secondly, the power-method algorithm is used to search the precoding weight for each user based on the optimal criterion of signal to interference plus noise ratio (SINR) maximization. Finally, the optical power restrictions of VLC systems are taken into account to constrain the precoding weight matrix. Comprehensive computer simulations in two scenarios indicate that the proposed scheme always has better bit error rate (BER) performance and lower computation complexity than that of the traditional scheme.

On Per-Phase Topology Control and Switching in Emerging Distribution Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Fei; Mousavi, Mirrasoul J.

This paper presents a new concept and approach for topology control and switching in distribution systems by extending the traditional circuit switching to laterals and single-phase loads. Voltage unbalance and other key performance indicators including voltage magnitudes, line loading, and energy losses are used to characterize and demonstrate the technical value of optimizing system topology on a per-phase basis in response to feeder conditions. The near-optimal per-phase topology control is defined as a series of hierarchical optimization problems. The proposed approach is respectively applied to IEEE 13-bus and 123-bus test systems for demonstration, which included the impact of integrating electricmore » vehicles (EVs) in the test circuit. It is concluded that the proposed approach can be effectively leveraged to improve voltage profiles with electric vehicles, the extent of which depends upon the performance of the base case without EVs.« less

Weber-aware weighted mutual information evaluation for infrared-visible image fusion

NASA Astrophysics Data System (ADS)

Luo, Xiaoyan; Wang, Shining; Yuan, Ding

2016-10-01

A performance metric for infrared and visible image fusion is proposed based on Weber's law. To indicate the stimulus of source images, two Weber components are provided. One is differential excitation to reflect the spectral signal of visible and infrared images, and the other is orientation to capture the scene structure feature. By comparing the corresponding Weber component in infrared and visible images, the source pixels can be marked with different dominant properties in intensity or structure. If the pixels have the same dominant property label, the pixels are grouped to calculate the mutual information (MI) on the corresponding Weber components between dominant source and fused images. Then, the final fusion metric is obtained via weighting the group-wise MI values according to the number of pixels in different groups. Experimental results demonstrate that the proposed metric performs well on popular image fusion cases and outperforms other image fusion metrics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruzic, David

The Thermoelectric-Driven Liquid-Metal Plasma-Facing Structures (TELS) project was able to establish the experimental conditions necessary for flowing liquid metal surfaces in order to be utilized as surfaces facing fusion relevant energetic plasma flux. The work has also addressed additional developments along with progressing along the timeline detailed in the proposal. A no-cost extension was requested to conduct other relevant experiment- specifically regarding the characterization droplet ejection during energetic plasma flux impact. A specially designed trench module, which could accommodate trenches with different aspect ratios was fabricated and installed in the TELS setup and plasma gun experiments were performed. Droplet ejectionmore » was characterized using high speed image acquisition and also surface mounted probes were used to characterize the plasma. The Gantt chart below had been provided with the original proposal, indicating the tasks to be performed in the third year of funding. These tasks are listed above in the progress report outline, and their progress status is detailed below.« less

A Noise-Filtered Under-Sampling Scheme for Imbalanced Classification.

PubMed

Kang, Qi; Chen, XiaoShuang; Li, SiSi; Zhou, MengChu

2017-12-01

Under-sampling is a popular data preprocessing method in dealing with class imbalance problems, with the purposes of balancing datasets to achieve a high classification rate and avoiding the bias toward majority class examples. It always uses full minority data in a training dataset. However, some noisy minority examples may reduce the performance of classifiers. In this paper, a new under-sampling scheme is proposed by incorporating a noise filter before executing resampling. In order to verify the efficiency, this scheme is implemented based on four popular under-sampling methods, i.e., Undersampling + Adaboost, RUSBoost, UnderBagging, and EasyEnsemble through benchmarks and significance analysis. Furthermore, this paper also summarizes the relationship between algorithm performance and imbalanced ratio. Experimental results indicate that the proposed scheme can improve the original undersampling-based methods with significance in terms of three popular metrics for imbalanced classification, i.e., the area under the curve, -measure, and -mean.

Bias correction of nutritional status estimates when reported age is used for calculating WHO indicators in children under five years of age.

PubMed

Quezada, Amado D; García-Guerra, Armando; Escobar, Leticia

2016-06-01

To assess the performance of a simple correction method for nutritional status estimates in children under five years of age when exact age is not available from the data. The proposed method was based on the assumption of symmetry of age distributions within a given month of age and validated in a large population-based survey sample of Mexican preschool children. The main distributional assumption was consistent with the data. All prevalence estimates derived from the correction method showed no statistically significant bias. In contrast, failing to correct attained age resulted in an underestimation of stunting in general and an overestimation of overweight or obesity among the youngest. The proposed method performed remarkably well in terms of bias correction of estimates and could be easily applied in situations in which either birth or interview dates are not available from the data.

Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting

PubMed Central

Ming-jun, Deng; Shi-ru, Qu

2015-01-01

Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting but is deficient in the expression of time hysteretically. This paper proposed an approach that combining fuzzy state transform and KF forecasting model. In considering the advantage of the two models, a weight combination model is proposed. The minimum of the sum forecasting error squared is regarded as a goal in optimizing the combined weight dynamically. Real detection data are used to test the efficiency. Results indicate that the method has a good performance in terms of short-term traffic forecasting. PMID:26779258

Semikinematic mount for spatially constrained high aspect ratio spacecraft fold mirrors

NASA Astrophysics Data System (ADS)

Sahu, Rupali; Arora, Hemant; Munjal, Bhawdeep Singh

2017-12-01

An attempt has been made to propose a passive flexure-based semikinematic optimized mounting design for mirror fixing devices (MFDs) to mount spacecraft mirrors made of brittle materials, especially for high aspect ratio mirrors with low available space for mounting in satellites. The traditionally used tangent cantilever spiders occupy a lot of space and are suitable only for small mirrors. Similarly, the efficiency of flexural bipods is lost if not placed 120 deg apart, which is not possible in high aspect ratio mirrors. Two mounting configurations, one with collinear MFDs and the other with staggered MFDs, have been studied. An optimization problem is set up with dimensions of the proposed design as design variables and constraints imposed on structural performance of the mirror assembly. Investigations indicate that both configurations have potential applications in spacecrafts as they have provided feasible results and have satisfactory optical performance as well.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

PubMed

Bao, Wei; Yue, Jun; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

Single-channel EEG-based mental fatigue detection based on deep belief network.

PubMed

Pinyi Li; Wenhui Jiang; Fei Su

2016-08-01

Mental fatigue has a pernicious influence on road and work place safety as well as a negative symptom of many acute and chronic illnesses, since the ability of concentrating, responding and judging quickly decreases during the fatigue or drowsiness stage. Electroencephalography (EEG) has been proven to be a robust physiological indicator of human cognitive state over the last few decades. But most existing EEG-based fatigue detection methods have poor performance in accuracy. This paper proposed a single-channel EEG-based mental fatigue detection method based on Deep Belief Network (DBN). The fused nonliear features from specified sub-bands and dynamic analysis, a total of 21 features are extracted as the input of the DBN to discriminate three classes of mental state including alert, slight fatigue and severe fatigue. Experimental results show the good performance of the proposed model comparing with those state-of-art methods.

Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting.

PubMed

Deng, Ming-jun; Qu, Shi-ru

2015-01-01

Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting but is deficient in the expression of time hysteretically. This paper proposed an approach that combining fuzzy state transform and KF forecasting model. In considering the advantage of the two models, a weight combination model is proposed. The minimum of the sum forecasting error squared is regarded as a goal in optimizing the combined weight dynamically. Real detection data are used to test the efficiency. Results indicate that the method has a good performance in terms of short-term traffic forecasting.

Assessing agro-environmental performance of dairy farms in northwest Italy based on aggregated results from indicators.

PubMed

Gaudino, Stefano; Goia, Irene; Grignani, Carlo; Monaco, Stefano; Sacco, Dario

2014-07-01

Dairy farms control an important share of the agricultural area of Northern Italy. Zero grazing, large maize-cropped areas, high stocking densities, and high milk production make them intensive and prone to impact the environment. Currently, few published studies have proposed indicator sets able to describe the entire dairy farm system and their internal components. This work had four aims: i) to propose a list of agro-environmental indicators to assess dairy farms; ii) to understand which indicators classify farms best; iii) to evaluate the dairy farms based on the proposed indicator list; iv) to link farmer decisions to the consequent environmental pressures. Forty agro-environmental indicators selected for this study are described. Northern Italy dairy systems were analysed considering both farmer decision indicators (farm management) and the resulting pressure indicators that demonstrate environmental stress on the entire farming system, and its components: cropping system, livestock system, and milk production. The correlations among single indicators identified redundant indicators. Principal Components Analysis distinguished which indicators provided meaningful information about each pressure indicator group. Analysis of the communalities and the correlations among indicators identified those that best represented farm variability: Farm Gate N Balance, Greenhouse Gas Emission, and Net Energy of the farm system; Net Energy and Gross P Balance of the cropping system component; Energy Use Efficiency and Purchased Feed N Input of the livestock system component; N Eco-Efficiency of the milk production component. Farm evaluation, based on the complete list of selected indicators demonstrated organic farming resulted in uniformly high values, while farms with low milk-producing herds resulted in uniformly low values. Yet on other farms, the environmental quality varied greatly when different groups of pressure indicators were considered, which highlighted the importance of expanding environmental analysis to effects within the farm. Statistical analysis demonstrated positive correlations between all farmer decision and pressure group indicators. Consumption of mineral fertiliser and pesticide negatively influenced the cropping system. Furthermore, stocking rate was found to correlate positively with the milk production component and negatively with the farm system. This study provides baseline references for ex ante policy evaluation, and monitoring tools for analysis both in itinere and ex post environment policy implementation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of Two Variants Of a Kata Technique (Unsu): The Neuromechanical Point of View

PubMed Central

Camomilla, Valentina; Sbriccoli, Paola; Mario, Alberto Di; Arpante, Alessandro; Felici, Francesco

2009-01-01

The objective of this work was to characterize from a neuromechanical point of view a jump performed within the sequence of Kata Unsu in International top level karateka. A modified jumping technique was proposed to improve the already acquired technique. The neuromechanical evaluation, paralleled by a refereeing judgment, was then used to compare modified and classic technique to test if the modification could lead to a better performance capacity, e.g. a higher score during an official competition. To this purpose, four high ranked karateka were recruited and instructed to perform the two jumps. Surface electromyographic signals were recorded in a bipolar mode from the vastus lateralis, rectus femoris, biceps femoris, gluteus maximus, and gastrocnemious muscles of both lower limbs. Mechanical data were collected by means of a stereophotogrammetric system and force platforms. Performance was associated to parameters characterizing the initial conditions of the aerial phase and to the CoM maximal height. The most critical elements having a negative influence on the arbitral evaluation were associated to quantitative error indicators. 3D reconstruction of the movement and videos were used to obtain the referee scores. The Unsu jump was divided into five phases (preparation, take off, ascending flight, descending flight, and landing) and the critical elements were highlighted. When comparing the techniques, no difference was found in the pattern of sEMG activation of the throwing leg muscles, while the push leg showed an earlier activation of RF and GA muscles at the beginning of the modified technique. The only significant improvement associated with the modified technique was evidenced at the beginning of the aerial phase, while there was no significant improvement of the referee score. Nevertheless, the proposed neuromechanical analysis, finalized to correlate technique features with the core performance indicators, is new in the field and is a promising tool to perform further analyses. Key Points A quantitative phase analysis, highlighting the critical features of the technique, was provided for the jump executed during the Kata Unsu. Kinematics and neuromuscular activity can be assessed during the Kata Unsu jump performed by top level karateka. Neuromechanical parameters change during different Kata Unsu jump techniques. Appropriate performance capacity indicators based on the neuromechanical evaluation can describe changes due to a modification of the technique. PMID:24474884

Autonomy to health care professionals as a vehicle for value-based health care? Results of a quasi-experiment in hospital governance.

PubMed

Larsen, Kristian Nørgaard; Kristensen, Søren Rud; Søgaard, Rikke

2018-01-01

Health care systems increasingly aim to create value for money by simultaneous incentivizing of quality along with classical goals such as activity increase and cost containment. It has recently been suggested that letting health care professionals choose the performance metrics on which they are evaluated may improve value of care by facilitating greater employee initiative, especially in the quality domain. There is a risk that this strategy leads to loss of performance as measured by the classical goals, if these goals are not prioritized by health care professionals. In this study we investigate the performance of eight hospital departments in the second largest region of Denmark that were delegated the authority to choose their own performance focus during a three-year test period from 2013 to 2016. The usual activity-based remuneration was suspended and departments were instructed to keep their global budgets and maintain activity levels, while managing according to their newly chosen performance focuses. Our analysis is based on monthly observations from two years before to three years after delegation. We collected data for 32 new performance indicators chosen by hospital department managements; 11 new performance indicators chosen by a centre management under which 5 of the departments were organised; and 3 classical indicators of priority to the central administration (activity, productivity, and cost containment). Interrupted time series analysis is used to estimate the effect of delegation on these indicators. We find no evidence that this particular proposal for giving health care professionals greater autonomy leads to consistent quality improvements but, on the other hand, also no consistent evidence of harm to the classical goals. Future studies could consider alternative possibilities to create greater autonomy for hospital departments. Copyright © 2017 Elsevier Ltd. All rights reserved.

How to achieve more accurate comparisons in organ donation activity: time to effectiveness indicators.

PubMed

Deulofeu, R; Bodí, M A; Twose, J; López, P

2010-06-01

We are used to comparisons of activity using donation or transplantation population (pmp) rates between regions or countries, without a further evaluation of the process. But crude pmp rates do not clearly reflect real transplantation capacity, because organ procurement does not finish with the donation step; it is also necessary to know the utilization of the obtained organs. The objective of this study was to present methods and indicators deemed necessary to evaluate the effectiveness of the process. We have proposed the use of simple definitions and indicators to more accurately measure and compare the effectiveness of the total organ procurement process. To illustrate the use and performance of these indicators, we have presented the donation and transplantation activity in Catalonia from 2002 to 2007.

Effective Solar Indices for Ionospheric Modeling: A Review and a Proposal for a Real-Time Regional IRI

NASA Astrophysics Data System (ADS)

Pignalberi, A.; Pezzopane, M.; Rizzi, R.; Galkin, I.

2018-01-01

The first part of this paper reviews methods using effective solar indices to update a background ionospheric model focusing on those employing the Kriging method to perform the spatial interpolation. Then, it proposes a method to update the International Reference Ionosphere (IRI) model through the assimilation of data collected by a European ionosonde network. The method, called International Reference Ionosphere UPdate (IRI UP), that can potentially operate in real time, is mathematically described and validated for the period 9-25 March 2015 (a time window including the well-known St. Patrick storm occurred on 17 March), using IRI and IRI Real Time Assimilative Model (IRTAM) models as the reference. It relies on foF2 and M(3000)F2 ionospheric characteristics, recorded routinely by a network of 12 European ionosonde stations, which are used to calculate for each station effective values of IRI indices IG_{12} and R_{12} (identified as IG_{{12{eff}}} and R_{{12{eff}}}); then, starting from this discrete dataset of values, two-dimensional (2D) maps of IG_{{12{eff}}} and R_{{12{eff}}} are generated through the universal Kriging method. Five variogram models are proposed and tested statistically to select the best performer for each effective index. Then, computed maps of IG_{{12{eff}}} and R_{{12{eff}}} are used in the IRI model to synthesize updated values of foF2 and hmF2. To evaluate the ability of the proposed method to reproduce rapid local changes that are common under disturbed conditions, quality metrics are calculated for two test stations whose measurements were not assimilated in IRI UP, Fairford (51.7°N, 1.5°W) and San Vito (40.6°N, 17.8°E), for IRI, IRI UP, and IRTAM models. The proposed method turns out to be very effective under highly disturbed conditions, with significant improvements of the foF2 representation and noticeable improvements of the hmF2 one. Important improvements have been verified also for quiet and moderately disturbed conditions. A visual analysis of foF2 and hmF2 maps highlights the ability of the IRI UP method to catch small-scale changes occurring under disturbed conditions which are not seen by IRI.

A Simple Ensemble Simulation Technique for Assessment of Future Variations in Specific High-Impact Weather Events

NASA Astrophysics Data System (ADS)

Taniguchi, Kenji

2018-04-01

To investigate future variations in high-impact weather events, numerous samples are required. For the detailed assessment in a specific region, a high spatial resolution is also required. A simple ensemble simulation technique is proposed in this paper. In the proposed technique, new ensemble members were generated from one basic state vector and two perturbation vectors, which were obtained by lagged average forecasting simulations. Sensitivity experiments with different numbers of ensemble members, different simulation lengths, and different perturbation magnitudes were performed. Experimental application to a global warming study was also implemented for a typhoon event. Ensemble-mean results and ensemble spreads of total precipitation, atmospheric conditions showed similar characteristics across the sensitivity experiments. The frequencies of the maximum total and hourly precipitation also showed similar distributions. These results indicate the robustness of the proposed technique. On the other hand, considerable ensemble spread was found in each ensemble experiment. In addition, the results of the application to a global warming study showed possible variations in the future. These results indicate that the proposed technique is useful for investigating various meteorological phenomena and the impacts of global warming. The results of the ensemble simulations also enable the stochastic evaluation of differences in high-impact weather events. In addition, the impacts of a spectral nudging technique were also examined. The tracks of a typhoon were quite different between cases with and without spectral nudging; however, the ranges of the tracks among ensemble members were comparable. It indicates that spectral nudging does not necessarily suppress ensemble spread.

A temperature and vegetation adjusted NTL urban index for urban area mapping and analysis

NASA Astrophysics Data System (ADS)

Zhang, Xiya; Li, Peijun

2018-01-01

Accurate and timely information regarding the extent and spatial distribution of urban areas on regional and global scales is crucially important for both scientific and policy-making communities. Stable nighttime light (NTL) data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) provides a unique proxy of human settlement and activity, which has been used in the mapping and analysis of urban areas and urbanization dynamics. However, blooming and saturation effects of DMSP/OLS NTL data are two unresolved problems in regional urban area mapping and analysis. This study proposed a new urban index termed the Temperature and Vegetation Adjusted NTL Urban Index (TVANUI). It is intended to reduce blooming and saturation effects and to enhance urban features by combining DMSP/OLS NTL data with Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer onboard the Terra satellite. The proposed index was evaluated in two study areas by comparison with established urban indices. The results demonstrated the proposed TVANUI was effective in enhancing the variation of DMSP/OLS light in urban areas and in reducing blooming and saturation effects, showing better performance than three established urban indices. The TVANUI also significantly outperformed the established urban indices in urban area mapping using both the global-fixed threshold and the local-optimal threshold methods. Thus, the proposed TVANUI provides a useful variable for urban area mapping and analysis on regional scale, as well as for urbanization dynamics using time-series DMSP/OLS and related satellite data.

Habitability and performance issues for long duration space flights.

PubMed

Whitmore, M; McQuilkin, M L; Woolford, B J

1998-09-01

Advancing technology, coupled with the desire to explore space has resulted in increasingly longer manned space missions. Although the Long Duration Space Flights (LDSF) have provided a considerable amount of scientific research on human ability to function in extreme environments, findings indicate long duration missions take a toll on the individual, both physiologically and psychologically. These physiological and psychological issues manifest themselves in performance decrements; and could lead to serious errors endangering the mission, spacecraft and crew. The purpose of this paper is threefold: 1) to document existing knowledge of the effects of LDSF on performance, habitability, and workload, 2) to identify and assess potential tools designed to address these decrements, and 3) to propose an implementation plan to address these habitability, performance and workload issues.

Habitability and Performance Issues for Long Duration Space Flights

NASA Technical Reports Server (NTRS)

Whitmore, Mihriban; McQuilkin, Meredith L.; Woolford, Barbara J.

1997-01-01

Advancing technology, coupled with the desire to explore space has resulted in increasingly longer manned space missions. Although the Long Duration Space Flights (LDSF) have provided a considerable amount of scientific research on human ability to function in extreme environments, findings indicate long duration missions take a toll on the individual, both physiologically and psychologically. These physiological and psychological issues manifest themselves in performance decrements; and could lead to serious errors endangering the mission, spacecraft and crew. The purpose of this paper is to document existing knowledge of the effects of LDSF on performance, habitability, and workload and to identify and assess potential tools designed to address these decrements as well as propose an implementation plan to address the habitability, performance and workload issues.

Empirical performance of interpolation techniques in risk-neutral density (RND) estimation

NASA Astrophysics Data System (ADS)

Bahaludin, H.; Abdullah, M. H.

2017-03-01

The objective of this study is to evaluate the empirical performance of interpolation techniques in risk-neutral density (RND) estimation. Firstly, the empirical performance is evaluated by using statistical analysis based on the implied mean and the implied variance of RND. Secondly, the interpolation performance is measured based on pricing error. We propose using the leave-one-out cross-validation (LOOCV) pricing error for interpolation selection purposes. The statistical analyses indicate that there are statistical differences between the interpolation techniques:second-order polynomial, fourth-order polynomial and smoothing spline. The results of LOOCV pricing error shows that interpolation by using fourth-order polynomial provides the best fitting to option prices in which it has the lowest value error.

Human joint motion estimation for electromyography (EMG)-based dynamic motion control.

PubMed

Zhang, Qin; Hosoda, Ryo; Venture, Gentiane

2013-01-01

This study aims to investigate a joint motion estimation method from Electromyography (EMG) signals during dynamic movement. In most EMG-based humanoid or prosthetics control systems, EMG features were directly or indirectly used to trigger intended motions. However, both physiological and nonphysiological factors can influence EMG characteristics during dynamic movements, resulting in subject-specific, non-stationary and crosstalk problems. Particularly, when motion velocity and/or joint torque are not constrained, joint motion estimation from EMG signals are more challenging. In this paper, we propose a joint motion estimation method based on muscle activation recorded from a pair of agonist and antagonist muscles of the joint. A linear state-space model with multi input single output is proposed to map the muscle activity to joint motion. An adaptive estimation method is proposed to train the model. The estimation performance is evaluated in performing a single elbow flexion-extension movement in two subjects. All the results in two subjects at two load levels indicate the feasibility and suitability of the proposed method in joint motion estimation. The estimation root-mean-square error is within 8.3% ∼ 10.6%, which is lower than that being reported in several previous studies. Moreover, this method is able to overcome subject-specific problem and compensate non-stationary EMG properties.

BagMOOV: A novel ensemble for heart disease prediction bootstrap aggregation with multi-objective optimized voting.

PubMed

Bashir, Saba; Qamar, Usman; Khan, Farhan Hassan

2015-06-01

Conventional clinical decision support systems are based on individual classifiers or simple combination of these classifiers which tend to show moderate performance. This research paper presents a novel classifier ensemble framework based on enhanced bagging approach with multi-objective weighted voting scheme for prediction and analysis of heart disease. The proposed model overcomes the limitations of conventional performance by utilizing an ensemble of five heterogeneous classifiers: Naïve Bayes, linear regression, quadratic discriminant analysis, instance based learner and support vector machines. Five different datasets are used for experimentation, evaluation and validation. The datasets are obtained from publicly available data repositories. Effectiveness of the proposed ensemble is investigated by comparison of results with several classifiers. Prediction results of the proposed ensemble model are assessed by ten fold cross validation and ANOVA statistics. The experimental evaluation shows that the proposed framework deals with all type of attributes and achieved high diagnosis accuracy of 84.16 %, 93.29 % sensitivity, 96.70 % specificity, and 82.15 % f-measure. The f-ratio higher than f-critical and p value less than 0.05 for 95 % confidence interval indicate that the results are extremely statistically significant for most of the datasets.