Structure coefficients and strategy selection in multiplayer games.

Science.gov (United States)

McAvoy, Alex; Hauert, Christoph

2016-01-01

Evolutionary processes based on two-player games such as the Prisoner's Dilemma or Snowdrift Game are abundant in evolutionary game theory. These processes, including those based on games with more than two strategies, have been studied extensively under the assumption that selection is weak. However, games involving more than two players have not received the same level of attention. To address this issue, and to relate two-player games to multiplayer games, we introduce a notion of reducibility for multiplayer games that captures what it means to break down a multiplayer game into a sequence of interactions with fewer players. We discuss the role of reducibility in structured populations, and we give examples of games that are irreducible in any population structure. Since the known conditions for strategy selection, otherwise known as [Formula: see text]-rules, have been established only for two-player games with multiple strategies and for multiplayer games with two strategies, we extend these rules to multiplayer games with many strategies to account for irreducible games that cannot be reduced to those simpler types of games. In particular, we show that the number of structure coefficients required for a symmetric game with [Formula: see text]-player interactions and [Formula: see text] strategies grows in [Formula: see text] like [Formula: see text]. Our results also cover a type of ecologically asymmetric game based on payoff values that are derived not only from the strategies of the players, but also from their spatial positions within the population.

Fine mapping quantitative trait loci under selective phenotyping strategies based on linkage and linkage disequilibrium criteria

DEFF Research Database (Denmark)

Ansari-Mahyari, S; Berg, P; Lund, M S

2009-01-01

disequilibrium-based sampling criteria (LDC) for selecting individuals to phenotype are compared to random phenotyping in a quantitative trait loci (QTL) verification experiment using stochastic simulation. Several strategies based on LAC and LDC for selecting the most informative 30%, 40% or 50% of individuals...... for phenotyping to extract maximum power and precision in a QTL fine mapping experiment were developed and assessed. Linkage analyses for the mapping was performed for individuals sampled on LAC within families and combined linkage disequilibrium and linkage analyses was performed for individuals sampled across...... the whole population based on LDC. The results showed that selecting individuals with similar haplotypes to the paternal haplotypes (minimum recombination criterion) using LAC compared to random phenotyping gave at least the same power to detect a QTL but decreased the accuracy of the QTL position. However...

Selective hedging strategies for oil stockpiling

International Nuclear Information System (INIS)

Yun, Won-Cheol

2006-01-01

As a feasible option for improving the economics and operational efficiency of stockpiling by public agency, this study suggests simple selective hedging strategies using forward contracts. The main advantage of these selective hedging strategies over the previous ones is not to predict future spot prices, but to utilize the sign and magnitude of basis easily available to the public. Using the weekly spot and forward prices of West Texas Intermediate for the period of October 1997-August 2002, this study adopts an ex ante out-of-sample analysis to examine selective hedging performances compared to no-hedge and minimum-variance routine hedging strategies. To some extent, selective hedging strategies dominate the traditional routine hedging strategy, but do not improve upon the expected returns of no-hedge case, which is mainly due to the data characteristics of out-of-sample period used in this analysis

The Effect of Using a Proposed Teaching Strategy Based on the Selective Thinking on Students' Acquisition Concepts in Mathematics

Science.gov (United States)

Qudah, Ahmad Hassan

2016-01-01

This study aimed at identify the effect of using a proposed teaching strategy based on the selective thinking in acquire mathematical concepts by Classroom Teacher Students at Al- al- Bayt University, The sample of the study consisted of (74) students, equally distributed into a control group and an experimental group. The selective thinking…

Selection of intellectual capital management strategies

OpenAIRE

Shcherbachenko Viktoriia Oleksiivna

2016-01-01

This article deals with the selection of intellectual capital management strategy. The attention is paid to the structure of intellectual capital, which consists of human capital, customer capital, process capital, intellectual property, intangible assets. The algorithm of selection of intellectual capital management strategy was created by author.

Waste Management Strategy in The Netherlands. Part 3. Strategy Selection

International Nuclear Information System (INIS)

Haverkate, B.R.W.

2003-01-01

This report reflects the Dutch input prepared in the framework of work package 3 of the EU thematic network COMPAS, which dealt with the evaluation and comparison of waste management strategies in EU member states and their applicant countries. Based on three generic decision trees the current strategy as well as the reason(s) for the selected options regarding radioactive waste management in The Netherlands is extensively described in this report. The trees are represented in terms of (numbered) decision nodes. Each node is discussed in the context of the Dutch situation, with relevant potential outcomes being highlighted where possible. After a short introduction (chapter 1) followed by a brief waste management policy overview (chapter 2), this approach is considered, in chapter 3, for: spent nuclear fuel and high level waste; low and intermediate level waste; disposal strategy

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Directory of Open Access Journals (Sweden)

Guisan Antoine

2009-04-01

Full Text Available Abstract Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a real absences b pseudo-absences selected randomly from the background and c two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97, and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have

Strategy selection as rational metareasoning.

Science.gov (United States)

Lieder, Falk; Griffiths, Thomas L

2017-11-01

Many contemporary accounts of human reasoning assume that the mind is equipped with multiple heuristics that could be deployed to perform a given task. This raises the question of how the mind determines when to use which heuristic. To answer this question, we developed a rational model of strategy selection, based on the theory of rational metareasoning developed in the artificial intelligence literature. According to our model people learn to efficiently choose the strategy with the best cost-benefit tradeoff by learning a predictive model of each strategy's performance. We found that our model can provide a unifying explanation for classic findings from domains ranging from decision-making to arithmetic by capturing the variability of people's strategy choices, their dependence on task and context, and their development over time. Systematic model comparisons supported our theory, and 4 new experiments confirmed its distinctive predictions. Our findings suggest that people gradually learn to make increasingly more rational use of fallible heuristics. This perspective reconciles the 2 poles of the debate about human rationality by integrating heuristics and biases with learning and rationality. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A belief-based evolutionarily stable strategy.

Science.gov (United States)

Deng, Xinyang; Wang, Zhen; Liu, Qi; Deng, Yong; Mahadevan, Sankaran

2014-11-21

As an equilibrium refinement of the Nash equilibrium, evolutionarily stable strategy (ESS) is a key concept in evolutionary game theory and has attracted growing interest. An ESS can be either a pure strategy or a mixed strategy. Even though the randomness is allowed in mixed strategy, the selection probability of pure strategy in a mixed strategy may fluctuate due to the impact of many factors. The fluctuation can lead to more uncertainty. In this paper, such uncertainty involved in mixed strategy has been further taken into consideration: a belief strategy is proposed in terms of Dempster-Shafer evidence theory. Furthermore, based on the proposed belief strategy, a belief-based ESS has been developed. The belief strategy and belief-based ESS can reduce to the mixed strategy and mixed ESS, which provide more realistic and powerful tools to describe interactions among agents. Copyright © 2014 Elsevier Ltd. All rights reserved.

Selection of intellectual capital management strategies

Directory of Open Access Journals (Sweden)

Shcherbachenko Viktoriia Oleksiivna

2016-02-01

Full Text Available This article deals with the selection of intellectual capital management strategy. The attention is paid to the structure of intellectual capital, which consists of human capital, customer capital, process capital, intellectual property, intangible assets. The algorithm of selection of intellectual capital management strategy was created by author.

An automatic fuzzy-based multi-temporal brain digital subtraction angiography image fusion algorithm using curvelet transform and content selection strategy.

Science.gov (United States)

Momeni, Saba; Pourghassem, Hossein

2014-08-01

Recently image fusion has prominent role in medical image processing and is useful to diagnose and treat many diseases. Digital subtraction angiography is one of the most applicable imaging to diagnose brain vascular diseases and radiosurgery of brain. This paper proposes an automatic fuzzy-based multi-temporal fusion algorithm for 2-D digital subtraction angiography images. In this algorithm, for blood vessel map extraction, the valuable frames of brain angiography video are automatically determined to form the digital subtraction angiography images based on a novel definition of vessel dispersion generated by injected contrast material. Our proposed fusion scheme contains different fusion methods for high and low frequency contents based on the coefficient characteristic of wrapping second generation of curvelet transform and a novel content selection strategy. Our proposed content selection strategy is defined based on sample correlation of the curvelet transform coefficients. In our proposed fuzzy-based fusion scheme, the selection of curvelet coefficients are optimized by applying weighted averaging and maximum selection rules for the high frequency coefficients. For low frequency coefficients, the maximum selection rule based on local energy criterion is applied to better visual perception. Our proposed fusion algorithm is evaluated on a perfect brain angiography image dataset consisting of one hundred 2-D internal carotid rotational angiography videos. The obtained results demonstrate the effectiveness and efficiency of our proposed fusion algorithm in comparison with common and basic fusion algorithms.

Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy.

Directory of Open Access Journals (Sweden)

Lina Zhang

Full Text Available Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information, PSSM (Position Specific Scoring Matrix, RSA (Relative Solvent Accessibility, and CTD (Composition, Transition, Distribution. The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest, SMO (Sequential Minimal Optimization, NNA (Nearest Neighbor Algorithm, and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew's Correlation Coefficient of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

Science.gov (United States)

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model

Science.gov (United States)

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals. PMID:27877103

Neural underpinnings of decision strategy selection: a review and a theoretical model

Directory of Open Access Journals (Sweden)

Szymon Wichary

2016-11-01

Full Text Available In multi-attribute choice, decision makers use various decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a unifying neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g. affect, stress on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models explaining this process. We also present the neurocognitive Bottom-Up Model of Strategy Selection (BUMSS. The model assumes that the use of the rational, normative Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: 1 cue weight computation, 2 gain modulation, and 3 weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neurophysiological indices.

Influence of Strategy Selection of Dairy Enterprises on Performance

Institute of Scientific and Technical Information of China (English)

Chaoqun REN; Yucheng HE; Lisha HU

2016-01-01

Dairy enterprises have to cope with intense market pressure and survival pressure.In such complex and competitive market environment,it is of great realistic significance for studying the influence of strategy selection of dairy enterprises on their performance.Through selecting 115 dairy enterprises,empirical analysis was made,and multiple linear regression model and structural equation model were established with the aid of SPSS and Amos software.Comparative analysis was carried out for performance of different strategy selection.Results indicate that dairy enterprises selecting vertical strategies obtain the best performance,followed by horizontal strategy,and the worst is multiple strategy,and the strategy selection exerts positive and direct influence on performance of dairy enterprises.

System for selecting a postponement strategy portfolio for supply chains

Directory of Open Access Journals (Sweden)

Luiz Eduardo Simão

2015-03-01

Full Text Available The stagnation of the economy has increased competition and uncertainty in the industrial sector. Trends such as the increase in the proliferation of the variety of products and the requirement for customization of products has contributed to difficulties in forecasting demand, due to increased uncertainty of demand for final products. In this new competitive environment, it is no longer possible to use the traditional “one size fits all” supply chain process, with unique policies for all products because this practice can lead to significant profitability losses due to the increase in stock levels and lost sales. However, research on supply chains has given relatively little attention to the need to use different, segmented supply chain strategies as well as to develop and manage these multiple supply chains strategies simultaneously. Thus, this paper aims to present an approach for selecting a portfolio of postponement strategies based on segmentation of supply chain, based on analysis of the demand profile (volume-variety analysis and a tool to assist in the selection of postponement strategies driven by the customer-product sector and their respective propositions of value.

SUPPLIER SELECTION STRATEGY AND MANUFACTURING FLEXIBILITY: IMPACT OF QUALITY AND TECHNOLOGY ROADMAPS

Directory of Open Access Journals (Sweden)

Muhamad Jantan

2006-01-01

Full Text Available The study evaluates the relationship between technology, quality, cost and delivery performance-based, supplier selection strategies, and manufacturing flexibilities namely, product flexibility, launch flexibility, and volume flexibility. Moreover, the moderating impact of supplier management strategies, namely quality roadmap and technology roadmap on the above relationships were also explored. The data for the study was drawn from a sample of companies listed in the factory directory published by the Penang Development Corporation (PDC. A postal survey of 120 manufacturers provided a return of 92 usable responses. The results reveal that the selection of suppliers based on technological and quality performance positively affects all the three dimensions of manufacturing flexibility, with complementary effects of good technology and quality roadmaps. Technology and quality roadmaps act as predictors for product and volume flexibilities. However, when launch flexibility is the focus, both technology and quality roadmaps moderate the impact of supplier selection strategies. Details of the findings, theoretical and practical implications, and the research limitation are discussed.

Selection Strategies for Social Influence in the Threshold Model

Science.gov (United States)

Karampourniotis, Panagiotis; Szymanski, Boleslaw; Korniss, Gyorgy

The ubiquity of online social networks makes the study of social influence extremely significant for its applications to marketing, politics and security. Maximizing the spread of influence by strategically selecting nodes as initiators of a new opinion or trend is a challenging problem. We study the performance of various strategies for selection of large fractions of initiators on a classical social influence model, the Threshold model (TM). Under the TM, a node adopts a new opinion only when the fraction of its first neighbors possessing that opinion exceeds a pre-assigned threshold. The strategies we study are of two kinds: strategies based solely on the initial network structure (Degree-rank, Dominating Sets, PageRank etc.) and strategies that take into account the change of the states of the nodes during the evolution of the cascade, e.g. the greedy algorithm. We find that the performance of these strategies depends largely on both the network structure properties, e.g. the assortativity, and the distribution of the thresholds assigned to the nodes. We conclude that the optimal strategy needs to combine the network specifics and the model specific parameters to identify the most influential spreaders. Supported in part by ARL NS-CTA, ARO, and ONR.

Method for selecting FBR development strategies in the presence of uncertainty

International Nuclear Information System (INIS)

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

1981-12-01

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

The Success Of Stock Selection Strategies In Emerging Markets: Is It Risk Or Behavioral Bias?

NARCIS (Netherlands)

J. van der Hart; G.J. de Zwart (Gerben); D.J.C. van Dijk (Dick)

2005-01-01

textabstractWe examine competing explanations, based on risk and behavioral models, for the profitability of stock selection strategies in emerging markets. We document that both emerging market risk and global risk factors cannot account for the significant excess returns of selection strategies

Processes in arithmetic strategy selection: A fMRI study.

Directory of Open Access Journals (Sweden)

Julien eTaillan

2015-02-01

Full Text Available This neuroimaging (fMRI study investigated neural correlates of strategy selection. Young adults performed an arithmetic task in two different conditions. In both conditions, participants had to provide estimates of two-digit multiplication problems like 54 x 78. In the choice condition, participants had to select the better of two available rounding strategies, rounding-up strategy (RU (i.e., doing 60x80 = 4,800 or rounding-down strategy (RD (i.e., doing 50x70=3,500 to estimate product of 54x78. In the no-choice condition, participants did not have to select strategy on each problem but were told which strategy to use; they executed RU and RD strategies each on a series of problems. Participants also had a control task (i.e., providing correct products of multiplication problems like 40x50. Brain activations and performance were analyzed as a function of these conditions. Participants were able to frequently choose the better strategy in the choice condition; they were also slower when they executed the difficult RU than the easier RD. Neuroimaging data showed greater brain activations in right anterior cingulate cortex (ACC, dorso-lateral prefrontal cortex (DLPFC, and angular gyrus (ANG, when selecting (relative to executing the better strategy on each problem. Moreover, RU was associated with more parietal cortex activation than RD. These results suggest an important role of fronto-parietal network in strategy selection and have important implications for our further understanding and modelling cognitive processes underlying strategy selection.

Processes in arithmetic strategy selection: a fMRI study.

Science.gov (United States)

Taillan, Julien; Ardiale, Eléonore; Anton, Jean-Luc; Nazarian, Bruno; Félician, Olivier; Lemaire, Patrick

2015-01-01

This neuroimaging (functional magnetic resonance imaging) study investigated neural correlates of strategy selection. Young adults performed an arithmetic task in two different conditions. In both conditions, participants had to provide estimates of two-digit multiplication problems like 54 × 78. In the choice condition, participants had to select the better of two available rounding strategies, rounding-up (RU) strategy (i.e., doing 60 × 80 = 4,800) or rounding-down (RD) strategy (i.e., doing 50 × 70 = 3,500 to estimate product of 54 × 78). In the no-choice condition, participants did not have to select strategy on each problem but were told which strategy to use; they executed RU and RD strategies each on a series of problems. Participants also had a control task (i.e., providing correct products of multiplication problems like 40 × 50). Brain activations and performance were analyzed as a function of these conditions. Participants were able to frequently choose the better strategy in the choice condition; they were also slower when they executed the difficult RU than the easier RD. Neuroimaging data showed greater brain activations in right anterior cingulate cortex (ACC), dorso-lateral prefrontal cortex (DLPFC), and angular gyrus (ANG), when selecting (relative to executing) the better strategy on each problem. Moreover, RU was associated with more parietal cortex activation than RD. These results suggest an important role of fronto-parietal network in strategy selection and have important implications for our further understanding and modeling cognitive processes underlying strategy selection.

Evaluation of genomic selection for replacement strategies using selection index theory.

Science.gov (United States)

Calus, M P L; Bijma, P; Veerkamp, R F

2015-09-01

Our objective was to investigate the economic effect of prioritizing heifers for replacement at the herd level based on genomic estimated breeding values, and to compute break-even genotyping costs across a wide range of scenarios. Specifically, we aimed to determine the optimal proportion of preselection based on parent average information for all scenarios considered. Considered replacement strategies include a range of different selection intensities by considering different numbers of heifers available for replacement (15-45 in a herd with 100 dairy cows) as well as different replacement rates (15-40%). Use of conventional versus sexed semen was considered, where the latter resulted in having twice as many heifers available for replacement. The baseline scenario relies on prioritization of replacement heifers based on parent average. The first alternative scenario involved genomic selection of heifers, considering that all heifers were genotyped. The benefits of genomic selection in this scenario were computed using a simple formula that only requires the number of lactating animals, the difference in accuracy between parent average and genomic selection (GS), and the selection intensity as input. When all heifers were genotyped, using GS for replacement of heifers was beneficial in most scenarios for current genotyping prices, provided some room exists for selection, in the sense that at least 2 more heifers are available than needed for replacement. In those scenarios, minimum break-even genotyping costs were equal to half the economic value of a standard deviation of the breeding goal. The second alternative scenario involved a preselection based on parent average, followed by GS among all the preselected heifers. It was in almost all cases beneficial to genotype all heifers when conventional semen was used (i.e., to do no preselection). The optimal proportion of preselection based on parent average was at least 0.63 when sexed semen was used. Use of sexed

Therapists' causal attributions of clients' problems and selection of intervention strategies.

Science.gov (United States)

Royce, W S; Muehlke, C V

1991-04-01

Therapists' choices of intervention strategies are influenced by many factors, including judgments about the bases of clients' problems. To assess the relationships between such causal attributions and the selection of intervention strategies, 196 counselors, psychologists, and social workers responded to the written transcript of a client's interview by answering two questionnaires, a 1982 scale (Causal Dimension Scale by Russell) which measured causal attribution of the client's problem, and another which measured preference for emotional, rational, and active intervention strategies in dealing with the client, based on the 1979 E-R-A taxonomy of Frey and Raming. A significant relationship was found between the two sets of variables, with internal attributions linked to rational intervention strategies and stable attributions linked to active strategies. The results support Halleck's 1978 hypothesis that theories of psychotherapy tie interventions to etiological considerations.

A modified strategy for sequence specific assignment of protein NMR spectra based on amino acid type selective experiments

International Nuclear Information System (INIS)

Schubert, Mario; Labudde, Dirk; Leitner, Dietmar; Oschkinat, Hartmut; Schmieder, Peter

2005-01-01

The determination of the three-dimensional structure of a protein or the study of protein-ligand interactions requires the assignment of all relevant nuclei as an initial step. This is nowadays almost exclusively performed using triple-resonance experiments. The conventional strategy utilizes one or more pairs of three dimensional spectra to obtain redundant information and thus reliable assignments. Here, a modified strategy for obtaining sequence specific assignments based on two dimensional amino acid type selective triple-resonance experiments is proposed. These experiments can be recorded with good resolution in a relatively short time. They provide very specific and redundant information, in particular on sequential connectivities, that drastically increases the ease and reliability of the assignment procedure, done either manually or in an automated fashion. The new strategy is demonstrated with the protein domain PB1 from yeast CDC24p

Affect-Aware Adaptive Tutoring Based on Human-Automation Etiquette Strategies.

Science.gov (United States)

Yang, Euijung; Dorneich, Michael C

2018-06-01

We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human-automation etiquette strategies. Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students' motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration. Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors (motivation, confidence, satisfaction, and performance) under two different levels of user frustration. We explored whether etiquette strategy selection based on this rule set (systematic) or random changes in etiquette strategy for a given level of frustration affected the four learning factors. Participants solved mathematics problems under different frustration conditions with feedback that adapted dynamic changes in etiquette strategies either systematically or randomly. The results demonstrated that feedback with etiquette strategies chosen systematically via the rule set could selectively target and improve motivation, confidence, satisfaction, and performance more than changing etiquette strategies randomly. The systematic adaptation was effective no matter the level of frustration for the participant. If computer tutors can vary the interaction style to effectively mitigate negative emotions, then ITS designers would have one more mechanism in which to design affect-aware adaptations that provide the proper responses in situations where human emotions affect the ability to learn.

Effect of "owners" selection strategies on autumn weight in reindeer (Rangifer t. tarandus calves

Directory of Open Access Journals (Sweden)

Robert B. Weladji

2002-03-01

Full Text Available Many northern indigenous peoples, including the Sami are dependent on reindeer herding for their livelihood. In view of the socio-cultural and economical importance of reindeer herding, emphasis should be put on appropriate herd structure and selection strategies that maximise marketable products, such as meat (the primary marketable product nowadays. Empirical observations reveal that within a herd, some owners seem to have better productivity in term of carcass autumn weight of calves, than others. We hypothesized that there may be an "owner" effect in reindeer herding, i.e. some owners may be applying particular selection strategies that might be beneficial. We investigated this in three reindeer grazing districts in South Norway, using mixed linear models. We found that autumn carcass weight of calves varied significantly with year and "owner" within herd in all three districts. Consistently some particular owners within a herd had higher average autumn carcass weight of their calves than others. We attributed this difference to "individual selection strategies", meaning that some owners may follow more accurately the sex, age and weight-based recommended strategy and in addition, they may make superior choices when selecting animals for slaughtering. We conclude that individual owners have the capability, through appropriate selection decisions to improve the average annual autumn weight of their reindeer calves. This might be an important aspect of "Traditional Ecological Knowledge", in addition to the recommended modern sex, age and weight-based selection criteria.

Missing Data Bias on a Selective Hedging Strategy

Directory of Open Access Journals (Sweden)

Kiss Gábor Dávid

2017-03-01

Full Text Available Foreign exchange rates affect corporate profitability both on the macro and cash-flow level. The current study analyses the bias of missing data on a selective hedging strategy, where currency options are applied in case of Value at Risk (1% signs. However, there can be special occasions when one or some data is missing due to lack of a trading activity. This paper focuses on the impact of different missing data handling methods on GARCH and Value at Risk model parameters, because of selective hedging and option pricing based on them. The main added value of the current paper is the comparison of the impact of different methods, such as listwise deletion, mean substitution, and maximum likelihood based Expectation Maximization, on risk management because this subject has insufficient literature. The current study tested daily closing data of floating currencies from Kenya (KES, Ghana (GHS, South Africa (ZAR, Tanzania (TZS, Uganda (UGX, Gambia (GMD, Madagascar (MGA and Mozambique (MZN in USD denomination against EUR/USD rate between March 8, 2000 and March 6, 2015 acquired from the Bloomberg database. Our results suggested the biases of missingness on Value at Risk and volatility models, presenting significant differences among the number of extreme fluctuations or model parameters. A selective hedging strategy can have different expenditures due to the choice of method. This paper suggests the usage of mean substitution or listwise deletion for daily financial time series due to their tendency to have a close to zero first momentum

A strategy for selective detection based on interferent depleting and redox cycling using the plane-recessed microdisk array electrodes

International Nuclear Information System (INIS)

Zhu Feng; Yan Jiawei; Lu Miao; Zhou Yongliang; Yang Yang; Mao Bingwei

2011-01-01

Highlights: → A novel strategy based on a combination of interferent depleting and redox cycling is proposed for the plane-recessed microdisk array electrodes. → The strategy break up the restriction of selectively detecting a species that exhibits reversible reaction in a mixture with one that exhibits an irreversible reaction. → The electrodes enhance the current signal by redox cycling. → The electrodes can work regardless of the reversibility of interfering species. - Abstract: The fabrication, characterization and application of the plane-recessed microdisk array electrodes for selective detection are demonstrated. The electrodes, fabricated by lithographic microfabrication technology, are composed of a planar film electrode and a 32 x 32 recessed microdisk array electrode. Different from commonly used redox cycling operating mode for array configurations such as interdigitated array electrodes, a novel strategy based on a combination of interferent depleting and redox cycling is proposed for the electrodes with an appropriate configuration. The planar film electrode (the plane electrode) is used to deplete the interferent in the diffusion layer. The recessed microdisk array electrode (the microdisk array), locating within the diffusion layer of the plane electrode, works for detecting the target analyte in the interferent-depleted diffusion layer. In addition, the microdisk array overcomes the disadvantage of low current signal for a single microelectrode. Moreover, the current signal of the target analyte that undergoes reversible electron transfer can be enhanced due to the redox cycling between the plane electrode and the microdisk array. Based on the above working principle, the plane-recessed microdisk array electrodes break up the restriction of selectively detecting a species that exhibits reversible reaction in a mixture with one that exhibits an irreversible reaction, which is a limitation of single redox cycling operating mode. The

Hybrid collaborative optimization based on selection strategy of initial point and adaptive relaxation

Energy Technology Data Exchange (ETDEWEB)

Ji, Aimin; Yin, Xu; Yuan, Minghai [Hohai University, Changzhou (China)

2015-09-15

There are two problems in Collaborative optimization (CO): (1) the local optima arising from the selection of an inappropriate initial point; (2) the low efficiency and accuracy root in inappropriate relaxation factors. To solve these problems, we first develop the Latin hypercube design (LHD) to determine an initial point of optimization, and then use the non-linear programming by quadratic Lagrangian (NLPQL) to search for the global solution. The effectiveness of the initial point selection strategy is verified by three benchmark functions with some dimensions and different complexities. Then we propose the Adaptive relaxation collaborative optimization (ARCO) algorithm to solve the inconsistency between the system level and the disciplines level, and in this method, the relaxation factors are determined according to the three separated stages of CO respectively. The performance of the ARCO algorithm is compared with the standard collaborative algorithm and the constant relaxation collaborative algorithm with a typical numerical example, which indicates that the ARCO algorithm is more efficient and accurate. Finally, we propose a Hybrid collaborative optimization (HCO) approach, which integrates the selection strategy of initial point with the ARCO algorithm. The results show that HCO can achieve the global optimal solution without the initial value and it also has advantages in convergence, accuracy and robustness. Therefore, the proposed HCO approach can solve the CO problems with applications in the spindle and the speed reducer.

Hybrid collaborative optimization based on selection strategy of initial point and adaptive relaxation

International Nuclear Information System (INIS)

Ji, Aimin; Yin, Xu; Yuan, Minghai

2015-01-01

There are two problems in Collaborative optimization (CO): (1) the local optima arising from the selection of an inappropriate initial point; (2) the low efficiency and accuracy root in inappropriate relaxation factors. To solve these problems, we first develop the Latin hypercube design (LHD) to determine an initial point of optimization, and then use the non-linear programming by quadratic Lagrangian (NLPQL) to search for the global solution. The effectiveness of the initial point selection strategy is verified by three benchmark functions with some dimensions and different complexities. Then we propose the Adaptive relaxation collaborative optimization (ARCO) algorithm to solve the inconsistency between the system level and the disciplines level, and in this method, the relaxation factors are determined according to the three separated stages of CO respectively. The performance of the ARCO algorithm is compared with the standard collaborative algorithm and the constant relaxation collaborative algorithm with a typical numerical example, which indicates that the ARCO algorithm is more efficient and accurate. Finally, we propose a Hybrid collaborative optimization (HCO) approach, which integrates the selection strategy of initial point with the ARCO algorithm. The results show that HCO can achieve the global optimal solution without the initial value and it also has advantages in convergence, accuracy and robustness. Therefore, the proposed HCO approach can solve the CO problems with applications in the spindle and the speed reducer

Selecting decision strategies: the differential role of affect.

Science.gov (United States)

Scheibehenne, Benjamin; von Helversen, Bettina

2015-01-01

Many theories on cognition assume that people adapt their decision strategies depending on the situation they face. To test if and how affect guides the selection of decision strategies, we conducted an online study (N = 166), where different mood states were induced through video clips. Results indicate that mood influenced the use of decision strategies. Negative mood, in particular anger, facilitated the use of non-compensatory strategies, whereas positive mood promoted compensatory decision rules. These results are in line with the idea that positive mood broadens the focus of attention and thus increases the use of compensatory decision strategies that take many pieces of information into account, whereas negative mood narrows the focus of attention and thus fosters non-compensatory strategies that rely on a selective use of information. The results further indicate that gaining a deeper theoretical understanding of the cognitive mechanisms that govern decision processes requires taking emotions into account.

An evaluation of oligonucleotide-based therapeutic strategies for polyQ diseases

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Fiszer Agnieszka

2012-03-01

Full Text Available Abstract Background RNA interference (RNAi and antisense strategies provide experimental therapeutic agents for numerous diseases, including polyglutamine (polyQ disorders caused by CAG repeat expansion. We compared the potential of different oligonucleotide-based strategies for silencing the genes responsible for several polyQ diseases, including Huntington's disease and two spinocerebellar ataxias, type 1 and type 3. The strategies included nonallele-selective gene silencing, gene replacement, allele-selective SNP targeting and CAG repeat targeting. Results Using the patient-derived cell culture models of polyQ diseases, we tested various siRNAs, and antisense reagents and assessed their silencing efficiency and allele selectivity. We showed considerable allele discrimination by several SNP targeting siRNAs based on a weak G-G or G-U pairing with normal allele and strong G-C pairing with mutant allele at the site of RISC-induced cleavage. Among the CAG repeat targeting reagents the strongest allele discrimination is achieved by miRNA-like functioning reagents that bind to their targets and inhibit their translation without substantial target cleavage. Also, morpholino analog performs well in mutant and normal allele discrimination but its efficient delivery to cells at low effective concentration still remains a challenge. Conclusions Using three cellular models of polyQ diseases and the same experimental setup we directly compared the performance of different oligonucleotide-based treatment strategies that are currently under development. Based on the results obtained by us and others we discussed the advantages and drawbacks of these strategies considering them from several different perspectives. The strategy aimed at nonallele-selective inhibiting of causative gene expression by targeting specific sequence of the implicated gene is the easiest to implement but relevant benefits are still uncertain. The gene replacement strategy that

Coevolution of Cooperation and Layer Selection Strategy in Multiplex Networks

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Katsuki Hayashi

2016-11-01

Full Text Available Recently, the emergent dynamics in multiplex networks, composed of layers of multiple networks, has been discussed extensively in network sciences. However, little is still known about whether and how the evolution of strategy for selecting a layer to participate in can contribute to the emergence of cooperative behaviors in multiplex networks of social interactions. To investigate these issues, we constructed a coevolutionary model of cooperation and layer selection strategies in which each an individual selects one layer from multiple layers of social networks and plays the Prisoner’s Dilemma with neighbors in the selected layer. We found that the proportion of cooperative strategies increased with increasing the number of layers regardless of the degree of dilemma, and this increase occurred due to a cyclic coevolution process of game strategies and layer selection strategies. We also showed that the heterogeneity of links among layers is a key factor for multiplex networks to facilitate the evolution of cooperation, and such positive effects on cooperation were observed regardless of the difference in the stochastic properties of network topologies.

Containment severe accident management - selected strategies

International Nuclear Information System (INIS)

Duco, J.; Royen, J.; Rohde, J.; Frid, W.; De Boeck, B.

1994-01-01

The OECD Nuclear Energy Agency (NEA) organized in June 1994, in collaboration with the Swedish Nuclear Power Inspectorate (SKI), a Specialist Meeting on Selected Containment Severe Accident Management Strategies, to discuss their feasibility, effectiveness, benefits and drawbacks, and long-term impact. The meeting focused on water reactors, mainly on existing systems. The technical content covered topics such as general aspects of accident management strategies in OECD Member countries, hydrogen management techniques and other containment accident management strategies, surveillance and protection of the containment function. The main conclusions of the meeting are summarized in the paper. (author)

Designing a fuzzy expert system for selecting knowledge management strategy

OpenAIRE

Ameneh Khadivar; Shohreh Nasri Nasr Abadi; Elham Fallah

2014-01-01

knowledge management strategy is mentioned as one of the most important success factors for implementing knowledge management. The KM strategy selection is a complex decision that requires consideration of several factors. For evaluation and selection of an appropriate knowledge management strategy in organizations, many factors must be considered. The identified factors and their impact on knowledge management strategy are inherently ambiguous. In this study, an overview of theoretical found...

Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

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Jaesung Lee

2016-11-01

Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

A strategy for position-selective epoxidation of polyprenols.

Science.gov (United States)

Gnanadesikan, Vijay; Corey, E J

2008-06-25

An effective strategy has been developed for the efficient site-selective epoxidation of poylolefinic isoprenoid alcohols, based on the use of an internal control element for intramolecular reaction. The approach is illustrated by application to a series of polyisoprenoid alcohols (polyprenols) at substrate concentration of 0.5 mM. With polyprenol substrates having the hydroxyl function at one terminus, the internal epoxidation can be directed at the double bond of the polyprenol, which is either four or five away from the terminal hydroxyprenyl subunit.

Feature Extraction and Selection Strategies for Automated Target Recognition

Science.gov (United States)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Bet hedging based cooperation can limit kin selection and form a basis for mutualism.

Science.gov (United States)

Uitdehaag, Joost C M

2011-07-07

Mutualism is a mechanism of cooperation in which partners that differ help each other. As such, mutualism opposes mechanisms of kin selection and tag-based selection (for example the green beard mechanism), which are based on giving exclusive help to partners that are related or carry the same tag. In contrast to kin selection, which is a basis for parochialism and intergroup warfare, mutualism can therefore be regarded as a mechanism that drives peaceful coexistence between different groups and individuals. Here the competition between mutualism and kin (tag) selection is studied. In a model where kin selection and tag-based selection are dominant, mutualism is promoted by introducing environmental fluctuations. These fluctuations cause reduction in reproductive success by the mechanism of variance discount. The best strategy to counter variance discount is to share with agents who experience the most anticorrelated fluctuations, a strategy called bet hedging. In this way, bet hedging stimulates cooperation with the most unrelated partners, which is a basis for mutualism. Analytic results and simulations reveal that, if this effect is large enough, mutualistic strategies can dominate kin selective strategies. In addition, mutants of these mutualistic strategies that experience fluctuations that are more anticorrelated to their partner, can outcompete wild type, which can lead to the evolution of specialization. In this way, the evolutionary success of mutualistic strategies can be explained by bet hedging-based cooperation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Innovative Strategies for Selective Inhibition of Histone Deacetylases

DEFF Research Database (Denmark)

Maolanon, Alex Ramalak; Madsen, Andreas Stahl; Olsen, Christian Adam

2016-01-01

Histone deacetylases (HDAC) are a family of closely related enzymes involved in epigenetic and posttranscriptional regulation of numerous genes and proteins. Their deregulation is associated with a number of diseases, and a handful of HDAC inhibitors have been approved for cancer treatment. None......, functionally important, features. Based on this analysis, we suggest alternative strategies to achieve selective HDAC inhibition that does not rely on chelation of the zinc ion in the active site but rather on disruption of protein-protein interactions important for HDAC activity. We believe that, although...

Priority Selection Within National Innovation Strategy in Global Context

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Prokopenko Olha

2017-08-01

Full Text Available The article deals with global experience in analysing the priorities based on their importance for country development and on national and international criteria using algorithm for the selection process. The main aspects of the process of development and implementation of international technology strategies were considered. The authors prove that through the analysis of innovation systems at macro level decision about the priorities in optimization with the aim to improve regulations in science, technology and innovation is provided. The main techniques and decisions were considered based on foresight-studies. Authors propose to create informative and analytical system for the foresight aims.

Mature Epitope Density - A strategy for target selection based on immunoinformatics and exported prokaryotic proteins

DEFF Research Database (Denmark)

Santos, Anderson R; Pereira, Vanessa Bastos; Barbosa, Eudes

2013-01-01

. However, currently available tools do not account for the concentration of epitope products in the mature protein product and its relation to the reliability of target selection. RESULTS: We developed a computational strategy based on measuring the epitope's concentration in the mature protein, called...... Mature Epitope Density (MED). Our method, though simple, is capable of identifying promising vaccine targets. Our online software implementation provides a computationally light and reliable analysis of bacterial exoproteins and their potential for vaccines or diagnosis projects against pathogenic...... proteins were confirmed as related. There was no experimental evidence of antigenic or pathogenic contributions for three of the highest MED-scored Mtb proteins. Hence, these three proteins could represent novel putative vaccine and drug targets for Mtb. A web version of MED is publicly available online...

Building Cell Selectivity into CPP-Mediated Strategies

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Irene Martín

2010-05-01

Full Text Available There is a pressing need for more effective and selective therapies for cancer and other diseases. Consequently, much effort is being devoted to the development of alternative experimental approaches based on selective systems, which are designed to be specifically directed against target cells. In addition, a large number of highly potent therapeutic molecules are being discovered. However, they do not reach clinical trials because of their low delivery, poor specificity or their incapacity to bypass the plasma membrane. Cell-penetrating peptides (CPPs are an open door for cell-impermeable compounds to reach intracellular targets. Putting all these together, research is sailing in the direction of the design of systems with the capacity to transport new drugs into a target cell. Some CPPs show cell type specificity while others require modifications or form part of more sophisticated drug delivery systems. In this review article we summarize several strategies for directed drug delivery involving CPPs that have been reported in the literature.

Strategies for Fostering the Efficacy of School-Based Management ...

African Journals Online (AJOL)

The study examined community participation in the School-Based Management Committees (SBMC), the challenges hindering participation, and strategies for fostering efficacy of the School Based Management Committee. The number 340 schools were selected from the population of 2543 public primary schools in ...

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

Science.gov (United States)

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

2016-09-22

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

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition

Directory of Open Access Journals (Sweden)

Jianhai Zhang

2016-09-01

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

Quick Link Selection Method by Using Pricing Strategy Based on User Equilibrium for Implementing an Effective Urban Travel Demand Management

Directory of Open Access Journals (Sweden)

Shahriar Afandizadeh Zargari

2016-12-01

Full Text Available This paper presents a two-stage model of optimization as a quick method to choose the best potential links for implementing urban travel demand management (UTDM strategy like road pricing. The model is optimized by minimizing the hidden cost of congestion based on user equilibrium (MHCCUE. It forecasts the exact amount of flows and tolls for links in user equilibrium condition to determine the hidden cost for each link to optimize the link selection based on the network congestion priority. The results show that not only the amount of total cost is decreased, but also the number of selected links for pricing is reduced as compared with the previous toll minimization methods. Moreover, as this model just uses the traffic assignment data for calculation, it could be considered as a quick and optimum solution for choosing the potential links.

Research on regularized mean-variance portfolio selection strategy with modified Roy safety-first principle.

Science.gov (United States)

Atta Mills, Ebenezer Fiifi Emire; Yan, Dawen; Yu, Bo; Wei, Xinyuan

2016-01-01

We propose a consolidated risk measure based on variance and the safety-first principle in a mean-risk portfolio optimization framework. The safety-first principle to financial portfolio selection strategy is modified and improved. Our proposed models are subjected to norm regularization to seek near-optimal stable and sparse portfolios. We compare the cumulative wealth of our preferred proposed model to a benchmark, S&P 500 index for the same period. Our proposed portfolio strategies have better out-of-sample performance than the selected alternative portfolio rules in literature and control the downside risk of the portfolio returns.

Pricing Strategy Selection Using Fuzzy Linear Programming

OpenAIRE

Elif Alaybeyoğlu; Y. Esra Albayrak

2013-01-01

Marketing establishes a communication network between producers and consumers. Nowadays, marketing approach is customer-focused and products are directly oriented to meet customer needs. Marketing, which is a long process, needs organization and management. Therefore strategic marketing planning becomes more and more important in today’s competitive conditions. Main focus of this paper is to evaluate pricing strategies and select the best pricing strategy solution while considering internal a...

Analysis of Contract Source Selection Strategy

Science.gov (United States)

2015-07-07

accomplish this milestone due to his unconditional love. I would like to thank my mom, Saraswati, and my dad , Khilendra, for their support and patience...FOR FURTHER RESEARCH The task of understanding the impact of a source selection strategy on resultant contract outcomes is a topic rich for further

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

Science.gov (United States)

Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

Directory of Open Access Journals (Sweden)

Ying Chen

2014-01-01

Full Text Available In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region’s weights and then weighted different subregions’ matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1, demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity.

Efficient iris recognition based on optimal subfeature selection and weighted subregion fusion.

Science.gov (United States)

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; He, Fei; Wang, Hongye; Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, and MMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity.

Statistical power of model selection strategies for genome-wide association studies.

Directory of Open Access Journals (Sweden)

Zheyang Wu

2009-07-01

Full Text Available Genome-wide association studies (GWAS aim to identify genetic variants related to diseases by examining the associations between phenotypes and hundreds of thousands of genotyped markers. Because many genes are potentially involved in common diseases and a large number of markers are analyzed, it is crucial to devise an effective strategy to identify truly associated variants that have individual and/or interactive effects, while controlling false positives at the desired level. Although a number of model selection methods have been proposed in the literature, including marginal search, exhaustive search, and forward search, their relative performance has only been evaluated through limited simulations due to the lack of an analytical approach to calculating the power of these methods. This article develops a novel statistical approach for power calculation, derives accurate formulas for the power of different model selection strategies, and then uses the formulas to evaluate and compare these strategies in genetic model spaces. In contrast to previous studies, our theoretical framework allows for random genotypes, correlations among test statistics, and a false-positive control based on GWAS practice. After the accuracy of our analytical results is validated through simulations, they are utilized to systematically evaluate and compare the performance of these strategies in a wide class of genetic models. For a specific genetic model, our results clearly reveal how different factors, such as effect size, allele frequency, and interaction, jointly affect the statistical power of each strategy. An example is provided for the application of our approach to empirical research. The statistical approach used in our derivations is general and can be employed to address the model selection problems in other random predictor settings. We have developed an R package markerSearchPower to implement our formulas, which can be downloaded from the

Developing TOPSIS method using statistical normalization for selecting knowledge management strategies

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Amin Zadeh Sarraf

2013-09-01

Full Text Available Purpose: Numerous companies are expecting their knowledge management (KM to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. Design/methodology/approach: An extension of TOPSIS, a multi-attribute decision making (MADM technique, to a group decision environment is investigated. TOPSIS is a practical and useful technique for ranking and selection of a number of externally determined alternatives through distance measures. The entropy method is often used for assessing weights in the TOPSIS method. Entropy in information theory is a criterion uses for measuring the amount of disorder represented by a discrete probability distribution. According to decrease resistance degree of employees opposite of implementing a new strategy, it seems necessary to spot all managers’ opinion. The normal distribution considered the most prominent probability distribution in statistics is used to normalize gathered data. Findings: The results of this study show that by considering 6 criteria for alternatives Evaluation, the most appropriate KM strategy to implement  in our company was ‘‘Personalization’’. Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the approach such as normal distribution of sample and community. These assumptions can be changed in future work. Originality/value: This paper proposes an effective solution based on combined entropy and TOPSIS approach to help companies that need to evaluate and select KM strategies. In represented solution, opinions of all managers is gathered and normalized by using standard normal distribution and central limit theorem. Keywords: Knowledge management; strategy; TOPSIS; Normal distribution; entropy

Neural Substrates of Similarity and Rule-based Strategies in Judgment

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Bettina eVon Helversen

2014-10-01

Full Text Available Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI, we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved.

Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration

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Haitao Chang

2016-06-01

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

Situation selection is a particularly effective emotion regulation strategy for people who need help regulating their emotions.

Science.gov (United States)

Webb, Thomas L; Lindquist, Kristen A; Jones, Katelyn; Avishai, Aya; Sheeran, Paschal

2018-03-01

Situation selection involves choosing situations based on their likely emotional impact and may be less cognitively taxing or challenging to implement compared to other strategies for regulating emotion, which require people to regulate their emotions "in the moment"; we thus predicted that individuals who chronically experience intense emotions or who are not particularly competent at employing other emotion regulation strategies would be especially likely to benefit from situation selection. Consistent with this idea, we found that the use of situation selection interacted with individual differences in emotional reactivity and competence at emotion regulation to predict emotional outcomes in both a correlational (Study 1; N = 301) and an experimental field study (Study 2; N = 125). Taken together, the findings suggest that situation selection is an effective strategy for regulating emotions, especially for individuals who otherwise struggle to do so.

Domain-based Teaching Strategy for Intelligent Tutoring System Based on Generic Rules

Science.gov (United States)

Kseibat, Dawod; Mansour, Ali; Adjei, Osei; Phillips, Paul

In this paper we present a framework for selecting the proper instructional strategy for a given teaching material based on its attributes. The new approach is based on a flexible design by means of generic rules. The framework was adapted in an Intelligent Tutoring System to teach Modern Standard Arabic language to adult English-speaking learners with no pre-knowledge of Arabic language is required.

Health information technology vendor selection strategies and total factor productivity.

Science.gov (United States)

Ford, Eric W; Huerta, Timothy R; Menachemi, Nir; Thompson, Mark A; Yu, Feliciano

2013-01-01

The aim of this study was to compare health information technology (HIT) adoption strategies' relative performance on hospital-level productivity measures. The American Hospital Association's Annual Survey and Healthcare Information and Management Systems Society Analytics for fiscal years 2002 through 2007 were used for this study. A two-stage approach is employed. First, a Malmquist model is specified to calculate hospital-level productivity measures. A logistic regression model is then estimated to compare the three HIT adoption strategies' relative performance on the newly constructed productivity measures. The HIT vendor selection strategy impacts the amount of technological change required of an organization but does not appear to have either a positive or adverse impact on technical efficiency or total factor productivity. The higher levels in technological change experienced by hospitals using the best of breed and best of suite HIT vendor selection strategies may have a more direct impact on the organization early on in the process. However, these gains did not appear to translate into either increased technical efficiency or total factor productivity during the period studied. Over a longer period, one HIT vendor selection strategy may yet prove to be more effective at improving efficiency and productivity.

Gender, Strategy Selection, and Discussion Satisfaction in Interpersonal Conflict.

Science.gov (United States)

Papa, Michael J.; Natalle, Elizabeth J.

1989-01-01

Examines gender-related similarities and differences regarding conflict strategies and satisfaction with conflict interaction in a corporate setting. Reports that gender significantly affected the selection of influence strategies: male-male dyads used assertiveness and reason consistently, while female-female dyads shifted from high levels of…

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum.

Directory of Open Access Journals (Sweden)

Makoto Ito

2015-11-01

Full Text Available Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the "win-stay, lose-switch" strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS, the dorsomedial striatum (DMS, and the ventral striatum (VS identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum.

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum.

Science.gov (United States)

Ito, Makoto; Doya, Kenji

2015-11-01

Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the "win-stay, lose-switch" strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum.

Selection of a management strategy for depleted uranium

International Nuclear Information System (INIS)

Patton, S.; Hanrahan, E.; Bradley, C. Jnr.

1995-01-01

A consequence of the uranium enrichment process is the accumulation of a significant amount of depleted uranium hexafluoride (UF 6 ). Currently, in the United States approximately 560 000 tonnes of the material are stored at three different sites. The US Department of Energy (DOE) has recently initiated a programme to consider alternative strategies for the cost-effective and environmentally safe long-term management of this inventory of depleted UF 6 . The programme involves a technology and engineering assessment of proposed management options (which are: use/reuse, conversion, storage, or disposal) and an analysis of the potential environmental impacts and life-cycle costs of alternative management strategies. The information obtained from the studies will be used by the DOE to select a preferred long-term management strategy. Because of its provisions for considering a wide range of relevant issues and involving the public, this programme has become a model for future DOE materials disposition programmes. This paper presents an overview of the Depleted Uranium Hexafluoride Management Programme. Technical findings of the programme to date are presented, and major issues involved in selecting and implementing a management strategy are discussed. (author)

Reducing residual stresses and deformations in selective laser melting through multi-level multi-scale optimization of cellular scanning strategy

DEFF Research Database (Denmark)

Mohanty, Sankhya; Hattel, Jesper Henri

2016-01-01

. A multilevel optimization strategy is adopted using a customized genetic algorithm developed for optimizing cellular scanning strategy for selective laser melting, with an objective of reducing residual stresses and deformations. The resulting thermo-mechanically optimized cellular scanning strategies......, a calibrated, fast, multiscale thermal model coupled with a 3D finite element mechanical model is used to simulate residual stress formation and deformations during selective laser melting. The resulting reduction in thermal model computation time allows evolutionary algorithm-based optimization of the process...

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

Science.gov (United States)

Sowers, T. Shane; Kopasakis, George; Simon, Donald L.

2008-01-01

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Marketing strategy of the selected company

OpenAIRE

Vodstrčilová, Kateřina

2010-01-01

This bachelor thesis deals with the marketing strategy of the company Náš grunt, s.r.o., the operator of the farm food concept Náš grunt. The aim of the thesis is to analyse the marketing strategy of the company and to suggest possible improvements. The theoretical part of the thesis is focused on the marketing, the marketing process, the marketing strategy, the marketing mix and SWOT analysis. The practical part is based on the situation analysis and the marketing strategy of the company Náš...

Metacognition for strategy selection during arithmetic problem-solving in young and older adults.

Science.gov (United States)

Geurten, Marie; Lemaire, Patrick

2018-04-19

We examined participants' strategy choices and metacognitive judgments during arithmetic problem-solving. Metacognitive judgments were collected either prospectively or retrospectively. We tested whether metacognitive judgments are related to strategy choices on the current problems and on the immediately following problems, and age-related differences in relations between metacognition and strategy choices. Data showed that both young and older adults were able to make accurate retrospective, but not prospective, judgments. Moreover, the accuracy of retrospective judgments was comparable in young and older adults when participants had to select and execute the better strategy. Metacognitive accuracy was even higher in older adults when participants had to only select the better strategy. Finally, low-confidence judgments on current items were more frequently followed by better strategy selection on immediately succeeding items than high-confidence judgments in both young and older adults. Implications of these findings to further our understanding of age-related differences and similarities in adults' metacognitive monitoring and metacognitive regulation for strategy selection in the context of arithmetic problem solving are discussed.

Selection of a management strategy for depleted uranium hexafluoride

International Nuclear Information System (INIS)

Patton, S.E.; Hanrahan, E.J.; Bradley, C.E.

1995-01-01

A consequence of the uranium enrichment process used in the United States (US) is the accumulation of a significant amount of depleted uranium hexafluoride (UF 6 ). Currently, approximately 560,000 metric tons of the material are stored at three different sites. The US Department of Energy (DOE) has recently initiated a program to consider alternative strategies for the cost-effective and environmentally safe long-term management of this inventory of depleted UF 6 . The program involves a technology and engineering assessment of proposed management options (use/reuse, conversion, storage, or disposal) and an analysis of the potential environmental impacts and life-cycle costs of alternative management strategies. The information obtained from the studies will be used by the DOE to select a preferred long-term management strategy. The selection and implementation of a management strategy will involve consideration of a number of important issues such as environmental, health, and safety effects; the balancing of risks versus costs in a context of reduced government spending; socioeconomic implications, including effects on the domestic and international uranium industry; the technical status of proposed uses or technologies; and public involvement in the decision making process. Because of its provisions for considering a wide range of relevant issues and involving the public, this program has become a model for future DOE materials disposition programs. This paper presents an overview of the Depleted Uranium Hexafluoride Management Program. Technical findings of the program to date are presented, and major issues involved in selecting and implementing a management strategy are discussed

LPTA versus Tradeoff: Analysis of Contract Source Selection Strategies and Performance Outcomes

Science.gov (United States)

2016-06-15

7 - Naval Postgraduate School source selection strategies to be made on a best value basis and not the lowest price ” (Office of...cost is an evaluation factor in all procurements, regardless of the source selection strategy chosen. In evaluating cost or price , FAR...contract performance is minimal, cost or price may play a dominant role in source selection. The less definitive the requirement, the more

Impact of selection strategies on representation of underserved populations and intention to practise: international findings.

Science.gov (United States)

Larkins, Sarah; Michielsen, Kristien; Iputo, Jehu; Elsanousi, Salwa; Mammen, Marykutty; Graves, Lisa; Willems, Sara; Cristobal, Fortunato L; Samson, Rex; Ellaway, Rachel; Ross, Simone; Johnston, Karen; Derese, Anselme; Neusy, André-Jacques

2015-01-01

Socially accountable medical schools aim to reduce health inequalities by training workforces responsive to the priority health needs of underserved communities. One key strategy involves recruiting students from underserved and unequally represented communities on the basis that they may be more likely to return and address local health priorities. This study describes the impacts of different selection strategies of medical schools that aspire to social accountability on the presence of students from underserved communities in their medical education programmes and on student practice intentions. A cross-sectional questionnaire was administered to students starting medical education in five institutions with a social accountability mandate in five different countries. The questionnaire assessed students' background characteristics, rurality of background, and practice intentions (location, discipline of practice and population to be served). The results were compared with the characteristics of students entering medical education in schools with standard selection procedures, and with publicly available socio-economic data. The selection processes of all five schools included strategies that extended beyond the assessment of academic achievement. Four distinct strategies were identified: the quota system; selection based on personal attributes; community involvement, and school marketing strategies. Questionnaire data from 944 students showed that students at the five schools were more likely to be of non-urban origin, of lower socio-economic status and to come from underserved groups. A total of 407 of 810 (50.2%) students indicated an intention to practise in a non-urban area after graduation and the likelihood of this increased with increasing rurality of primary schooling (p = 0.000). Those of rural origin were statistically less likely to express an intention to work abroad (p = 0.003). Selection strategies to ensure that members of underserved communities

The Effect of Vocabulary Self-Selection Strategy and Input Enhancement Strategy on the Vocabulary Knowledge of Iranian EFL Learners

Science.gov (United States)

Masoudi, Golfam

2017-01-01

The present study was designed to investigate empirically the effect of Vocabulary Self-Selection strategy and Input Enhancement strategy on the vocabulary knowledge of Iranian EFL Learners. After taking a diagnostic pretest, both experimental groups enrolled in two classes. Learners who practiced Vocabulary Self-Selection were allowed to…

Task-selective memory effects for successfully implemented encoding strategies.

Science.gov (United States)

Leshikar, Eric D; Duarte, Audrey; Hertzog, Christopher

2012-01-01

Previous behavioral evidence suggests that instructed strategy use benefits associative memory formation in paired associate tasks. Two such effective encoding strategies--visual imagery and sentence generation--facilitate memory through the production of different types of mediators (e.g., mental images and sentences). Neuroimaging evidence suggests that regions of the brain support memory reflecting the mental operations engaged at the time of study. That work, however, has not taken into account self-reported encoding task success (i.e., whether participants successfully generated a mediator). It is unknown, therefore, whether task-selective memory effects specific to each strategy might be found when encoding strategies are successfully implemented. In this experiment, participants studied pairs of abstract nouns under either visual imagery or sentence generation encoding instructions. At the time of study, participants reported their success at generating a mediator. Outside of the scanner, participants further reported the quality of the generated mediator (e.g., images, sentences) for each word pair. We observed task-selective memory effects for visual imagery in the left middle occipital gyrus, the left precuneus, and the lingual gyrus. No such task-selective effects were observed for sentence generation. Intriguingly, activity at the time of study in the left precuneus was modulated by the self-reported quality (vividness) of the generated mental images with greater activity for trials given higher ratings of quality. These data suggest that regions of the brain support memory in accord with the encoding operations engaged at the time of study.

A belief-based evolutionarily stable strategy

OpenAIRE

Deng, Xinyang; Wang, Zhen; Liu, Qi; Deng, Yong; Mahadevan, Sankaran

2014-01-01

As an equilibrium refinement of the Nash equilibrium, evolutionarily stable strategy (ESS) is a key concept in evolutionary game theory and has attracted growing interest. An ESS can be either a pure strategy or a mixed strategy. Even though the randomness is allowed in mixed strategy, the selection probability of pure strategy in a mixed strategy may fluctuate due to the impact of many factors. The fluctuation can lead to more uncertainty. In this paper, such uncertainty involved in mixed st...

An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications.

Science.gov (United States)

Ye, Fei; Lou, Xin Yuan; Sun, Lin Fu

2017-01-01

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find the food source. However, the proposed mutation strategy uses two distinct generative mechanisms for new food sources at the osphresis phase, allowing the algorithm procedure to search for the optimal solution in both the whole solution space and within the local solution space containing the fruit fly swarm location. In an evaluation based on a group of ten benchmark problems, the proposed algorithm's performance is compared with that of other well-known algorithms, and the results support the superiority of the proposed algorithm. Moreover, this algorithm is successfully applied in a SVM to perform both parameter setting turning for the SVM and feature selection to solve real-world classification problems. This method is called chaotic fruit fly optimization algorithm (CIFOA)-SVM and has been shown to be a more robust and effective optimization method than other well-known methods, particularly in terms of solving the medical diagnosis problem and the credit card problem.

Secure relay selection based on learning with negative externality in wireless networks

Science.gov (United States)

Zhao, Caidan; Xiao, Liang; Kang, Shan; Chen, Guiquan; Li, Yunzhou; Huang, Lianfen

2013-12-01

In this paper, we formulate relay selection into a Chinese restaurant game. A secure relay selection strategy is proposed for a wireless network, where multiple source nodes send messages to their destination nodes via several relay nodes, which have different processing and transmission capabilities as well as security properties. The relay selection utilizes a learning-based algorithm for the source nodes to reach their best responses in the Chinese restaurant game. In particular, the relay selection takes into account the negative externality of relay sharing among the source nodes, which learn the capabilities and security properties of relay nodes according to the current signals and the signal history. Simulation results show that this strategy improves the user utility and the overall security performance in wireless networks. In addition, the relay strategy is robust against the signal errors and deviations of some user from the desired actions.

The Process of Marketing Segmentation Strategy Selection

OpenAIRE

Ionel Dumitru

2007-01-01

The process of marketing segmentation strategy selection represents the essence of strategical marketing. We present hereinafter the main forms of the marketing statategy segmentation: undifferentiated marketing, differentiated marketing, concentrated marketing and personalized marketing. In practice, the companies use a mix of these marketing segmentation methods in order to maximize the proffit and to satisfy the consumers’ needs.

Regional MLEM reconstruction strategy for PET-based treatment verification in ion beam radiotherapy

International Nuclear Information System (INIS)

Gianoli, Chiara; Riboldi, Marco; Fattori, Giovanni; Baselli, Giuseppe; Baroni, Guido; Bauer, Julia; Debus, Jürgen; Parodi, Katia; De Bernardi, Elisabetta

2014-01-01

In ion beam radiotherapy, PET-based treatment verification provides a consistency check of the delivered treatment with respect to a simulation based on the treatment planning. In this work the region-based MLEM reconstruction algorithm is proposed as a new evaluation strategy in PET-based treatment verification. The comparative evaluation is based on reconstructed PET images in selected regions, which are automatically identified on the expected PET images according to homogeneity in activity values. The strategy was tested on numerical and physical phantoms, simulating mismatches between the planned and measured β + activity distributions. The region-based MLEM reconstruction was demonstrated to be robust against noise and the sensitivity of the strategy results were comparable to three voxel units, corresponding to 6 mm in numerical phantoms. The robustness of the region-based MLEM evaluation outperformed the voxel-based strategies. The potential of the proposed strategy was also retrospectively assessed on patient data and further clinical validation is envisioned. (paper)

Selective catalyst reduction light-off strategy

Science.gov (United States)

Gonze, Eugene V [Pinckney, MI

2011-10-18

An emissions control system includes a temperature determination module and an emissions control module. The temperature determination module determines a first temperature of a heater element of a diesel particulate filter (DPF) assembly in an exhaust system and determines a second temperature of a catalyst of the DPF assembly. The emissions control module selectively activates the heater element, selectively initiates a predefined combustion process in an engine based upon the first temperature, and selectively starts a reductant injection process based upon the second temperature.

Task-selective memory effects for successfully implemented encoding strategies.

Directory of Open Access Journals (Sweden)

Eric D Leshikar

Full Text Available Previous behavioral evidence suggests that instructed strategy use benefits associative memory formation in paired associate tasks. Two such effective encoding strategies--visual imagery and sentence generation--facilitate memory through the production of different types of mediators (e.g., mental images and sentences. Neuroimaging evidence suggests that regions of the brain support memory reflecting the mental operations engaged at the time of study. That work, however, has not taken into account self-reported encoding task success (i.e., whether participants successfully generated a mediator. It is unknown, therefore, whether task-selective memory effects specific to each strategy might be found when encoding strategies are successfully implemented. In this experiment, participants studied pairs of abstract nouns under either visual imagery or sentence generation encoding instructions. At the time of study, participants reported their success at generating a mediator. Outside of the scanner, participants further reported the quality of the generated mediator (e.g., images, sentences for each word pair. We observed task-selective memory effects for visual imagery in the left middle occipital gyrus, the left precuneus, and the lingual gyrus. No such task-selective effects were observed for sentence generation. Intriguingly, activity at the time of study in the left precuneus was modulated by the self-reported quality (vividness of the generated mental images with greater activity for trials given higher ratings of quality. These data suggest that regions of the brain support memory in accord with the encoding operations engaged at the time of study.

Competitive seeds-selection in complex networks

Science.gov (United States)

Zhao, Jiuhua; Liu, Qipeng; Wang, Lin; Wang, Xiaofan

2017-02-01

This paper investigates a competitive diffusion model where two competitors simultaneously select a set of nodes (seeds) in the network to influence. We focus on the problem of how to select these seeds such that, when the diffusion process terminates, a competitor can obtain more supports than its opponent. Instead of studying this problem in the game-theoretic framework as in the existing work, in this paper we design several heuristic seed-selection strategies inspired by commonly used centrality measures-Betweenness Centrality (BC), Closeness Centrality (CC), Degree Centrality (DC), Eigenvector Centrality (EC), and K-shell Centrality (KS). We mainly compare three centrality-based strategies, which have better performances in competing with the random selection strategy, through simulations on both real and artificial networks. Even though network structure varies across different networks, we find certain common trend appearing in all of these networks. Roughly speaking, BC-based strategy and DC-based strategy are better than CC-based strategy. Moreover, if a competitor adopts CC-based strategy, then BC-based strategy is a better strategy than DC-based strategy for his opponent, and the superiority of BC-based strategy decreases as the heterogeneity of the network decreases.

Marketing strategy and product performance: a study of selected ...

African Journals Online (AJOL)

Marketing strategy and product performance: a study of selected firms in Nigeria. ... Ethiopian Journal of Environmental Studies and Management ... This paper therefore recommends that business organisations should accord necessary ...

An Optimization Model For Strategy Decision Support to Select Kind of CPO’s Ship

Science.gov (United States)

Suaibah Nst, Siti; Nababan, Esther; Mawengkang, Herman

2018-01-01

The selection of marine transport for the distribution of crude palm oil (CPO) is one of strategy that can be considered in reducing cost of transport. The cost of CPO’s transport from one area to CPO’s factory located at the port of destination may affect the level of CPO’s prices and the number of demands. In order to maintain the availability of CPO a strategy is required to minimize the cost of transporting. In this study, the strategy used to select kind of charter ships as barge or chemical tanker. This study aims to determine an optimization model for strategy decision support in selecting kind of CPO’s ship by minimizing costs of transport. The select of ship was done randomly, so that two-stage stochastic programming model was used to select the kind of ship. Model can help decision makers to select either barge or chemical tanker to distribute CPO.

How to select the correct education strategy: when not to go online.

Science.gov (United States)

Klingbeil, Carol G; Johnson, Norah L; Totka, Joan P; Doyle, Lynn

2009-01-01

Screening for intimate partner violence is an important injury prevention strategy. Nurses who develop staff education, to promote screening, need to select a method that is sensitive to learners. Online learning, although convenient, is not well suited to sensitive topics such as screening for intimate partner violence. The purpose of this article is to describe a curriculum for intimate partner violence screening based on self-efficacy theory, which includes a hospital-produced video, a role play, and a discussion.

Image-Based Method for Determining Better Walking Strategies for Hexapods

Directory of Open Access Journals (Sweden)

Kazi Mostafa

2015-05-01

Full Text Available An intelligent walking strategy is vital for multi-legged robots possessing no a priori information of an environment when traversing across discontinuous terrain. Six-legged robots outperform other multi-legged robots in static and dynamic stability. However, hexapods require careful planning to traverse across discontinuous terrain. A hexapod walking strategy can be accomplished using a vision-based navigation system to identify the surrounding environment. This paper presents an image-based technique to achieve better walking strategies for a hexapod walking on a special terrain containing irregular, restricted regions. The properties of the restricted regions were acquired beforehand by using reliable surveillance means. Moreover, simplified forward gaits, better rotational gaits, and adaptive gait selection strategies for walking on discontinuous terrain were proposed. The hexapod can effectively switch the gait sequences and types according to the environment involved. The boundary of standing zones can be successfully labelled by applying the greyscale erosion comprising a structuring element similar in shape and size to the foot tip of the hexapod. The experimental results demonstrated that the proposed image-based technique significantly improved the walking strategies of hexapods traversing on discontinuous terrain.

An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications

Science.gov (United States)

Lou, Xin Yuan; Sun, Lin Fu

2017-01-01

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find the food source. However, the proposed mutation strategy uses two distinct generative mechanisms for new food sources at the osphresis phase, allowing the algorithm procedure to search for the optimal solution in both the whole solution space and within the local solution space containing the fruit fly swarm location. In an evaluation based on a group of ten benchmark problems, the proposed algorithm’s performance is compared with that of other well-known algorithms, and the results support the superiority of the proposed algorithm. Moreover, this algorithm is successfully applied in a SVM to perform both parameter setting turning for the SVM and feature selection to solve real-world classification problems. This method is called chaotic fruit fly optimization algorithm (CIFOA)-SVM and has been shown to be a more robust and effective optimization method than other well-known methods, particularly in terms of solving the medical diagnosis problem and the credit card problem. PMID:28369096

The Effect of Exit Strategy on Optimal Portfolio Selection with Birandom Returns

Directory of Open Access Journals (Sweden)

Guohua Cao

2013-01-01

Full Text Available The aims of this paper are to use a birandom variable to denote the stock return selected by some recurring technical patterns and to study the effect of exit strategy on optimal portfolio selection with birandom returns. Firstly, we propose a new method to estimate the stock return and use birandom distribution to denote the final stock return which can reflect the features of technical patterns and investors' heterogeneity simultaneously; secondly, we build a birandom safety-first model and design a hybrid intelligent algorithm to help investors make decisions; finally, we innovatively study the effect of exit strategy on the given birandom safety-first model. The results indicate that (1 the exit strategy affects the proportion of portfolio, (2 the performance of taking the exit strategy is better than when the exit strategy is not taken, if the stop-loss point and the stop-profit point are appropriately set, and (3 the investor using the exit strategy become conservative.

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System.

Science.gov (United States)

Xiong, Lian; Yang, Liu; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-14

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay.

Model For Marketing Strategy Decision Based On Multicriteria Decicion Making: A Case Study In Batik Madura Industry

Science.gov (United States)

Anna, I. D.; Cahyadi, I.; Yakin, A.

2018-01-01

Selection of marketing strategy is a prominent competitive advantage for small and medium enterprises business development. The selection process is is a multiple criteria decision-making problem, which includes evaluation of various attributes or criteria in a process of strategy formulation. The objective of this paper is to develop a model for the selection of a marketing strategy in Batik Madura industry. The current study proposes an integrated approach based on analytic network process (ANP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine the best strategy for Batik Madura marketing problems. Based on the results of group decision-making technique, this study selected fourteen criteria, including consistency, cost, trend following, customer loyalty, business volume, uniqueness manpower, customer numbers, promotion, branding, bussiness network, outlet location, credibility and the inovation as Batik Madura marketing strategy evaluation criteria. A survey questionnaire developed from literature review was distributed to a sample frame of Batik Madura SMEs in Pamekasan. In the decision procedure step, expert evaluators were asked to establish the decision matrix by comparing the marketing strategy alternatives under each of the individual criteria. Then, considerations obtained from ANP and TOPSIS methods were applied to build the specific criteria constraints and range of the launch strategy in the model. The model in this study demonstrates that, under current business situation, Straight-focus marketing strategy is the best marketing strategy for Batik Madura SMEs in Pamekasan.

An efficient strategy based on an individualized selection of registration methods. Application to the coregistration of MR and SPECT images in neuro-oncology

International Nuclear Information System (INIS)

Tacchella, Jean-Marc; Lefort, Muriel; Habert, Marie-Odile; Yeni, Nathanaëlle; Kas, Aurélie; Frouin, Frédérique; Roullot, Elodie; Cohen, Mike-Ely; Guillevin, Rémy; Petrirena, Grégorio; Delattre, Jean-Yves

2014-01-01

An efficient registration strategy is described that aims to help solve delicate medical imaging registration problems. It consists of running several registration methods for each dataset and selecting the best one for each specific dataset, according to an evaluation criterion. Finally, the quality of the registration results, obtained with the best method, is visually scored by an expert as excellent, correct or poor. The strategy was applied to coregister Technetium-99m Sestamibi SPECT and MRI data in the framework of a follow-up protocol in patients with high grade gliomas receiving antiangiogenic therapy. To adapt the strategy to this clinical context, a robust semi-automatic evaluation criterion based on the physiological uptake of the Sestamibi tracer was defined. A panel of eighteen multimodal registration algorithms issued from BrainVisa, SPM or AIR software environments was systematically applied to the clinical database composed of sixty-two datasets. According to the expert visual validation, this new strategy provides 85% excellent registrations, 12% correct ones and only 3% poor ones. These results compare favorably to the ones obtained by the globally most efficient registration method over the whole database, for which only 61% of excellent registration results have been reported. Thus the registration strategy in its current implementation proves to be suitable for clinical application. (paper)

Effects of selected coping strategies on impediment oriented ...

African Journals Online (AJOL)

The study was carried out to determine the effects of selected coping strategies on the impediment oriented academic stress of the visually impaired pupils in Oji- River School for the Blind, Enugu State. The study is a quasi-Experimental design involving two treatment groups and one control group. Twenty visually impaired ...

Strategy of Cooling Parameters Selection in the Continuous Casting of Steel

Directory of Open Access Journals (Sweden)

Falkus J.

2016-03-01

Full Text Available This paper presents a strategy of the cooling parameters selection in the process of continuous steel casting. Industrial tests were performed at a slab casting machine at the Arcelor Mittal Poland Unit in Krakow. The tests covered 55 heats for 7 various steel grades. Based on the existing casting technology a numerical model of the continuous steel casting process was formulated. The numerical calculations were performed for three casting speeds - 0.6, 0.8 and 1 m min-1. An algorithm was presented that allows us to compute the values of the heat transfer coefficients for the secondary cooling zone. The correctness of the cooling parameter strategy was evaluated by inspecting the shell thickness, the length of the liquid core and the strand surface temperature. The ProCAST software package was used to construct the numerical model of continuous casting of steel.

A novel strategy for selection of allosteric ribozymes yields RiboReporter™ sensors for caffeine and aspartame

Science.gov (United States)

Ferguson, Alicia; Boomer, Ryan M.; Kurz, Markus; Keene, Sara C.; Diener, John L.; Keefe, Anthony D.; Wilson, Charles; Cload, Sharon T.

2004-01-01

We have utilized in vitro selection technology to develop allosteric ribozyme sensors that are specific for the small molecule analytes caffeine or aspartame. Caffeine- or aspartame-responsive ribozymes were converted into fluorescence-based RiboReporter™ sensor systems that were able to detect caffeine or aspartame in solution over a concentration range from 0.5 to 5 mM. With read-times as short as 5 min, these caffeine- or aspartame-dependent ribozymes function as highly specific and facile molecular sensors. Interestingly, successful isolation of allosteric ribozymes for the analytes described here was enabled by a novel selection strategy that incorporated elements of both modular design and activity-based selection methods typically used for generation of catalytic nucleic acids. PMID:15026535

Comparison of Coping Strategies of Student Teachers Based on Their Subject of Specialisation

Science.gov (United States)

P. M., Majitha; Sajan, K. S.

2015-01-01

The purpose of the study was to find out the difference in the mean scores of coping strategies of student teachers based on their subject of specialisation. A total of 558 student teachers were selected for the study. Results indicate that there exists a significant difference in the mean scores of Coping Strategies of student teachers of Arts…

Proceedings of the specialist meeting on selected containment severe accident management strategies

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-07-15

Twenty papers were presented at the first specialist meeting on Selected Containment Severe Accident management Strategies, held in Stockholm, Sweden, in 1994, half of them dealing with accident management strategies implementation status, half of them with research aspects. The four sessions were: general aspects of containment accident management strategies, hydrogen management techniques, other containment accident management strategies (spray cooling, core catcher...), surveillance and protection of containment function

Proceedings of the specialist meeting on selected containment severe accident management strategies

International Nuclear Information System (INIS)

1995-07-01

Twenty papers were presented at the first specialist meeting on Selected Containment Severe Accident management Strategies, held in Stockholm, Sweden, in 1994, half of them dealing with accident management strategies implementation status, half of them with research aspects. The four sessions were: general aspects of containment accident management strategies, hydrogen management techniques, other containment accident management strategies (spray cooling, core catcher...), surveillance and protection of containment function

Strategies to address participant misrepresentation for eligibility in Web-based research.

Science.gov (United States)

Kramer, Jessica; Rubin, Amy; Coster, Wendy; Helmuth, Eric; Hermos, John; Rosenbloom, David; Moed, Rich; Dooley, Meghan; Kao, Ying-Chia; Liljenquist, Kendra; Brief, Deborah; Enggasser, Justin; Keane, Terence; Roy, Monica; Lachowicz, Mark

2014-03-01

Emerging methodological research suggests that the World Wide Web ("Web") is an appropriate venue for survey data collection, and a promising area for delivering behavioral intervention. However, the use of the Web for research raises concerns regarding sample validity, particularly when the Web is used for recruitment and enrollment. The purpose of this paper is to describe the challenges experienced in two different Web-based studies in which participant misrepresentation threatened sample validity: a survey study and an online intervention study. The lessons learned from these experiences generated three types of strategies researchers can use to reduce the likelihood of participant misrepresentation for eligibility in Web-based research. Examples of procedural/design strategies, technical/software strategies and data analytic strategies are provided along with the methodological strengths and limitations of specific strategies. The discussion includes a series of considerations to guide researchers in the selection of strategies that may be most appropriate given the aims, resources and target population of their studies. Copyright © 2014 John Wiley & Sons, Ltd.

Construction and applications of exon-trapping gene-targeting vectors with a novel strategy for negative selection.

Science.gov (United States)

Saito, Shinta; Ura, Kiyoe; Kodama, Miho; Adachi, Noritaka

2015-06-30

Targeted gene modification by homologous recombination provides a powerful tool for studying gene function in cells and animals. In higher eukaryotes, non-homologous integration of targeting vectors occurs several orders of magnitude more frequently than does targeted integration, making the gene-targeting technology highly inefficient. For this reason, negative-selection strategies have been employed to reduce the number of drug-resistant clones associated with non-homologous vector integration, particularly when artificial nucleases to introduce a DNA break at the target site are unavailable or undesirable. As such, an exon-trap strategy using a promoterless drug-resistance marker gene provides an effective way to counterselect non-homologous integrants. However, constructing exon-trapping targeting vectors has been a time-consuming and complicated process. By virtue of highly efficient att-mediated recombination, we successfully developed a simple and rapid method to construct plasmid-based vectors that allow for exon-trapping gene targeting. These exon-trap vectors were useful in obtaining correctly targeted clones in mouse embryonic stem cells and human HT1080 cells. Most importantly, with the use of a conditionally cytotoxic gene, we further developed a novel strategy for negative selection, thereby enhancing the efficiency of counterselection for non-homologous integration of exon-trap vectors. Our methods will greatly facilitate exon-trapping gene-targeting technologies in mammalian cells, particularly when combined with the novel negative selection strategy.

Selection of examples in case-based computer-aided decision systems

International Nuclear Information System (INIS)

Mazurowski, Maciej A; Zurada, Jacek M; Tourassi, Georgia D

2008-01-01

Case-based computer-aided decision (CB-CAD) systems rely on a database of previously stored, known examples when classifying new, incoming queries. Such systems can be particularly useful since they do not need retraining every time a new example is deposited in the case base. The adaptive nature of case-based systems is well suited to the current trend of continuously expanding digital databases in the medical domain. To maintain efficiency, however, such systems need sophisticated strategies to effectively manage the available evidence database. In this paper, we discuss the general problem of building an evidence database by selecting the most useful examples to store while satisfying existing storage requirements. We evaluate three intelligent techniques for this purpose: genetic algorithm-based selection, greedy selection and random mutation hill climbing. These techniques are compared to a random selection strategy used as the baseline. The study is performed with a previously presented CB-CAD system applied for false positive reduction in screening mammograms. The experimental evaluation shows that when the development goal is to maximize the system's diagnostic performance, the intelligent techniques are able to reduce the size of the evidence database to 37% of the original database by eliminating superfluous and/or detrimental examples while at the same time significantly improving the CAD system's performance. Furthermore, if the case-base size is a main concern, the total number of examples stored in the system can be reduced to only 2-4% of the original database without a decrease in the diagnostic performance. Comparison of the techniques shows that random mutation hill climbing provides the best balance between the diagnostic performance and computational efficiency when building the evidence database of the CB-CAD system.

Cow genotyping strategies for genomic selection in a small dairy cattle population.

Science.gov (United States)

Jenko, J; Wiggans, G R; Cooper, T A; Eaglen, S A E; Luff, W G de L; Bichard, M; Pong-Wong, R; Woolliams, J A

2017-01-01

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds. Copyright © 2017 American Dairy Science Association. Published by

Strategies to intervene on causal systems are adaptively selected.

Science.gov (United States)

Coenen, Anna; Rehder, Bob; Gureckis, Todd M

2015-06-01

How do people choose interventions to learn about causal systems? Here, we considered two possibilities. First, we test an information sampling model, information gain, which values interventions that can discriminate between a learner's hypotheses (i.e. possible causal structures). We compare this discriminatory model to a positive testing strategy that instead aims to confirm individual hypotheses. Experiment 1 shows that individual behavior is described best by a mixture of these two alternatives. In Experiment 2 we find that people are able to adaptively alter their behavior and adopt the discriminatory model more often after experiencing that the confirmatory strategy leads to a subjective performance decrement. In Experiment 3, time pressure leads to the opposite effect of inducing a change towards the simpler positive testing strategy. These findings suggest that there is no single strategy that describes how intervention decisions are made. Instead, people select strategies in an adaptive fashion that trades off their expected performance and cognitive effort. Copyright © 2015 Elsevier Inc. All rights reserved.

Conceptual framework in creating and selecting the performance measurement system for marketing strategy control

Directory of Open Access Journals (Sweden)

Krstić Bojan

2011-01-01

Full Text Available Performance measurement in modern conditions is one of the most important business requirements since enterprises face the need to exhibit returns for stockholders and investors, but also contribution of management to those returns, as well as contribution of certain business units, functional departments and activities within them. Hence, it is particularly important to assess marketing successfulness as a business function according to return on investment in marketing activities, but also according to the set of indicators from following performance groups - marketing effectiveness and marketing efficiency. Core issue is which measures to select and use in the marketing performance measurement system of certain enterprise so that it could be able to assess how effective and efficient its marketing is. In other words, adequate performance measurement system ought to contain performance measures that will be used to monitor effects and marketing strategy implementation process (controlling while implementing, and performance measures that can be applied to overall effect monitoring after the strategy implementation period. Otherwise, creating the marketing performance measurement system is a complex task for marketing managers. Therefore, the aim of this paper is to explore key principles and develop conceptual framework for creating and selecting performance measurement system for marketing strategy control which is based on characteristics and key success factors of marketing strategy, that is activities and actions for its operationalizing and effective implementing.

Recurrent selection as breeding strategy for heat tolerance in wheat

OpenAIRE

Juarez Campolina Machado; Moacil Alves de Souza; Davi Melo de Oliveira; Adeliano Cargnin; Aderico Júnior Badaró Pimentel; Josiane Cristina de Assis

2010-01-01

The development of heat-tolerant varieties is an important goal of wheat breeding programs, requiringefficient selection methods. In the present study the use of recurrent selection was evaluated as a strategy to improve heatstress tolerance in wheat. Two cycles of recurrent selection were performed in experiments conducted in research areas of theUniversidade Federal de Viçosa, located in Coimbra-MG and Viçosa-MG, in 2004 and 2007, in two growing seasons (summerand winter). The genetic gain ...

Recurrent selection as breeding strategy for heat tolerance in wheat

Directory of Open Access Journals (Sweden)

Juarez Campolina Machado

2010-01-01

Full Text Available The development of heat-tolerant varieties is an important goal of wheat breeding programs, requiringefficient selection methods. In the present study the use of recurrent selection was evaluated as a strategy to improve heatstress tolerance in wheat. Two cycles of recurrent selection were performed in experiments conducted in research areas of theUniversidade Federal de Viçosa, located in Coimbra-MG and Viçosa-MG, in 2004 and 2007, in two growing seasons (summerand winter. The genetic gain and the existence of variability show the possibility of successful recurrent selection for heattolerancein wheat.

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

Science.gov (United States)

Xiong, Lian; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-01

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay. PMID:29342897

The Prediction of Coping Strategies Based on Personality Traits in Irritants Affiliates

Directory of Open Access Journals (Sweden)

Ali Masoud Rostami

2013-07-01

Full Text Available Objective: This study aimed to predict coping strategies based on the characteristics of the stimulants-dependent people. Method: The research method was correlational. The population consisted of all stimulant-dependent individuals (n=402 that consecutively admitted to addiction centers of Tehran over the last year and had a drug dependence diagnosis. By systematic sampling, 201 subjects were selected of this population. The NEO personality inventory (NEO-FFI short form and Lazarus-Folkman’s coping strategies (WCQ-short form questionnaires administered among selected sample. Results: The results showed that there is a positive correlation between the personality dimension of neuroticism and coping strategies of avoidance, disengagement, and a negative one with continence. There is a positive correlation between the personality dimension of extroversion and avoidance, seeking social support and a negative one with (assuming responsibility. Also there is a positive correlation between the personality dimension of compatibility with restraint coping strategies and seeking social support. Conscientiousness personality dimension did not predict any coping strategies in stimulus-dependent patients. Conclusion: Personality traits can predict coping strategies in stimulus-dependent individuals. For the treatment of addicted patients paying attention to evaluation of the patients’ characteristics is suggested.

SELECTION OF BUSINESS STRATEGIES FOR QUALITY IMPROVEMENT USING FUZZY ANALYTICAL HIERARCHY PROCESS

Directory of Open Access Journals (Sweden)

Prasun Das

2010-12-01

Full Text Available Fuzzy linguistic concepts are often used to enhance the traditional analytic hierarchy process (AHP in capturing the fuzziness and subjectiveness of decision makers' judgments. In this paper, fuzzy AHP methodology is adopted for selection of the strategies for business improvement in an Indian industry as a decision making problem. Due to simplicity and effectiveness, triangular fuzzy numbers are adopted as a reference to indicate the influence strength of each element in the hierarchy structure. The confidence level and the optimistic levels of multiple decision makers are captured by using ? -cut based fuzzy number methods. This fuzzy set theory based multi-attribute decision making method is found to be quite useful and effective in industrial environment.

Optimal Channel Selection Based on Online Decision and Offline Learning in Multichannel Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Mu Qiao

2017-01-01

Full Text Available We propose a channel selection strategy with hybrid architecture, which combines the centralized method and the distributed method to alleviate the overhead of access point and at the same time provide more flexibility in network deployment. By this architecture, we make use of game theory and reinforcement learning to fulfill the optimal channel selection under different communication scenarios. Particularly, when the network can satisfy the requirements of energy and computational costs, the online decision algorithm based on noncooperative game can help each individual sensor node immediately select the optimal channel. Alternatively, when the network cannot satisfy the requirements of energy and computational costs, the offline learning algorithm based on reinforcement learning can help each individual sensor node to learn from its experience and iteratively adjust its behavior toward the expected target. Extensive simulation results validate the effectiveness of our proposal and also prove that higher system throughput can be achieved by our channel selection strategy over the conventional off-policy channel selection approaches.

Development strategy and conceptual design of China Lead-based Research Reactor

International Nuclear Information System (INIS)

Wu, Yican; Bai, Yunqing; Song, Yong; Huang, Qunying; Zhao, Zhumin; Hu, Liqin

2016-01-01

Highlights: • China LEAd-based Reactor (CLEAR) proposed by Institute of Nuclear Energy Safety Technology (INEST) is selected as the ADS reference reactor. • The Chinese ADS development program consists of three stages, and during the first stage, a 10 MW th lead-based research reactor named CLEAR-I will be built with subcritical and critical dual-mode operation capability for validation of ADS transmutation system and lead cooled fast reactor technology. • Major design principles of CLEAR-I are oriented at technology feasibility, safety reliability, experiment flexibility and technology continuity. Followed by the development strategy and design principles, CLEAR-I design options and conceptual design scenarios are presented. - Abstract: Chinese Academy of Sciences (CAS) launched an engineering project to develop an Accelerator Driven System (ADS) for nuclear waste transmutation since 2011, and China LEAd-based Reactor (CLEAR) proposed by Institute of Nuclear Energy Safety Technology (INEST) is selected as the ADS reference reactor. In this paper, the development strategy and conceptual design of China Lead-based Research Reactor are proposed. The Chinese ADS development program consists of three stages, and during the first stage, a 10 MW th lead-based research reactor named CLEAR-I will be built with subcritical and critical dual-mode operation capability for validation of ADS transmutation system and lead cooled fast reactor technology. Major design principles of CLEAR-I are oriented at technology feasibility, safety reliability, experiment flexibility and technology continuity. Followed by the development strategy and design principles, CLEAR-I design options and conceptual design scenarios are presented.

Strategies, limitations and opportunities for marker-assisted selection in livestock

International Nuclear Information System (INIS)

Dekkers, J.C.M.; Werf, H.J. van der

2007-01-01

This chapter reviews the principles, opportunities and limitations for detection of quantitative trait loci (QTL) in livestock and for their use in genetic improvement programmes. Alternate strategies for QTL detection are discussed, as are methods for inclusion of marker and QTL information in genetic evaluation. Practical issues regarding implementation of marker-assisted selection (MAS) for selection in breed crosses and for selection within breeds are described, along with likely routes towards achieving that goal. Opportunities and challenges are also discussed for the use of molecular information for genetic improvement of livestock in developing countries. (author)

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

Science.gov (United States)

Bian, Yuemin; Xie, Xiang-Qun Sean

2018-04-09

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

Competitive Strategies and Improved Performance of Selected Nigeria Telecommunication Companies

Directory of Open Access Journals (Sweden)

Waidi Adeniyi Akingbad

2014-01-01

Full Text Available Abstract The influence of globalization in telecommunication companies has greatly increased the level of competition in the industry and they are forced to be competitive to survive. Different types of strategies are put in place in order to be profitable and competitive. All these strategies are directed to attract, retain and maintain customers for continuous profitability. However, majority of them hardly measure the impact of their strategic innovation on their customers. The paper seeks to explore the influence of competitive strategies embarked upon by selected telecommunication companies in Nigeria on their performance. The paper also examines how competitive strategies could be implemented for improved customer satisfaction, retention and loyalty. Three null hypotheses were postulated to test the relationship between lower prices and customer satisfaction, uninterrupted trunk services and customer loyalty, and customer complaint handling and retention. Only customers using telephone service were selected as respondents from Lagos State. The state was stratified in to 20 local government council area and questionnaires were distributed to 125 respondents in each of them. The completion rate of the questionnaire in each of them is between 103 and 110. Survey research design was adopted to carry out the study. A structured questionnaire was designed and validated through the construct validity and tested for confirmation using the KMO measure of sampling adequacy. It was also made reliable using Cronbach’s Alpha test. From the study, findings revealed relationship between competitive strategies and customer satisfaction, retention and loyalty. The findings revealed that there is a relationship between competitive strategies, its constituents and performance of telecommunication companies. It is recommended that universal mobile telecommunication services (UMTS operators should adopt the culture of competitive strategies since it can

Strategy selection for the decommissioning of nuclear facilities

International Nuclear Information System (INIS)

2004-01-01

As modern nuclear power programmes mature and large, commercial nuclear power plants and fuel cycle facilities approach the end of their useful life by reason of age, economics or change of policy on the use of nuclear power, new challenges associated with decommissioning and dismantling come to the fore. Politicians and the public may expect there to be a 'right answer' to the choice of strategy for a particular type of facility, or even all facilities. Both this seminar and wider experience show that this is not the case. Local factors and national political positions have a significant input and often result in widely differing strategy approaches to broadly similar decommissioning projects. All facility owners represented at the seminar were able to demonstrate a rational process for strategy selection and compelling arguments for the choices made. In addition to the papers that were presented, these proceedings include a summary of the discussions that took place. (author)

Strategies for a Professional Development Programme: Empowering Teachers for Context-Based Chemistry Education

Science.gov (United States)

Stolk, Machiel J.; Bulte, Astrid M. W.; de Jong, Onno; Pilot, Albert

2009-01-01

The aim of this study is to understand the design of professional development programmes in teacher-based and context-based chemistry curriculum innovations. Firstly, the goals of these programmes are discussed and related to the concept of empowerment. Next, in a selection of empirical studies, four general strategies for professional development…

The Effects of Relationship Type, Partner Intent, and Gender on the Selection of Relationship Maintenance Strategies.

Science.gov (United States)

Shea, B. Christine; Pearson, Judy C.

1986-01-01

Indicates that relationship type did not affect the maintenance strategies that partners chose; however, the partners' relationship intent and the sex-composition of the dyad had a significant impact on the selection of directness strategies. Suggests that individuals are not necessarily more likely to select directness strategies than balance or…

Contract Source Selection: An Analysis of Lowest Price Technically Acceptable and Tradeoff Strategies

Science.gov (United States)

2016-06-01

it can start moderately, and as it progresses to the right, price is seen to be less important than the advantage (non-cost factor) gained. 3... advantages compared to the LPTA source selection strategy. These include “learning,” “ business judgment,” “flexibility,” and “customer satisfaction...2014, p. 5). The next advantage is the use of business judgment. The tradeoff source selection strategy is highly subjective and this allows the source

Integrative review of implementation strategies for translation of research-based evidence by nurses.

Science.gov (United States)

Wuchner, Staci S

2014-01-01

The purpose of this review was to synthesize and critique experimental and/or quasi-experimental research that has evaluated implementation strategies for translation of research-based evidence into nursing practice. Successfully implementing evidence-based research can improve patient outcomes. Identifying successful implementation strategies is imperative to move research-based evidence into practice. As implementation science gains popularity, it is imperative to understand the strategies that most effectively translate research-based evidence into practice. The review used the CINAHL and MEDLINE (Ovid) databases. Articles were included if they were experimental and/or quasi-experimental research designs, were written in English, and measured nursing compliance to translation of research-based evidence. An independent review was performed to select and critique the included articles. A wide array of interventions were completed, including visual cues, audit and feedback, educational meetings and materials, reminders, outreach, and leadership involvement. Because of the complex multimodal nature of the interventions and the variety of research topics, comparison across interventions was difficult. Many difficulties exist in determining what implementation strategies are most effective for translation of research-based evidence into practice by nurses. With these limited findings, further research is warranted to determine which implementation strategies most successfully translate research-based evidence into practice.

Goal selection versus process control in a brain-computer interface based on sensorimotor rhythms.

Science.gov (United States)

Royer, Audrey S; He, Bin

2009-02-01

In a brain-computer interface (BCI) utilizing a process control strategy, the signal from the cortex is used to control the fine motor details normally handled by other parts of the brain. In a BCI utilizing a goal selection strategy, the signal from the cortex is used to determine the overall end goal of the user, and the BCI controls the fine motor details. A BCI based on goal selection may be an easier and more natural system than one based on process control. Although goal selection in theory may surpass process control, the two have never been directly compared, as we are reporting here. Eight young healthy human subjects participated in the present study, three trained and five naïve in BCI usage. Scalp-recorded electroencephalograms (EEG) were used to control a computer cursor during five different paradigms. The paradigms were similar in their underlying signal processing and used the same control signal. However, three were based on goal selection, and two on process control. For both the trained and naïve populations, goal selection had more hits per run, was faster, more accurate (for seven out of eight subjects) and had a higher information transfer rate than process control. Goal selection outperformed process control in every measure studied in the present investigation.

Strategies for Selecting Routes through Real-World Environments: Relative Topography, Initial Route Straightness, and Cardinal Direction.

Directory of Open Access Journals (Sweden)

Tad T Brunyé

Full Text Available Previous research has demonstrated that route planners use several reliable strategies for selecting between alternate routes. Strategies include selecting straight rather than winding routes leaving an origin, selecting generally south- rather than north-going routes, and selecting routes that avoid traversal of complex topography. The contribution of this paper is characterizing the relative influence and potential interactions of these strategies. We also examine whether individual differences would predict any strategy reliance. Results showed evidence for independent and additive influences of all three strategies, with a strong influence of topography and initial segment straightness, and relatively weak influence of cardinal direction. Additively, routes were also disproportionately selected when they traversed relatively flat regions, had relatively straight initial segments, and went generally south rather than north. Two individual differences, extraversion and sense of direction, predicted the extent of some effects. Under real-world conditions navigators indeed consider a route's initial straightness, cardinal direction, and topography, but these cues differ in relative influence and vary in their application across individuals.

Reading strategies used by Grade 9 English Second Language learners in a selected school

Directory of Open Access Journals (Sweden)

Madoda Cekiso

2014-09-01

Full Text Available Knowledge of the reading strategies used by English Second Language learners can help teachers to plan appropriate lessons and apply relevant methods of teaching reading in order to enhance learners’ reading comprehension. The main objective of this study was to investigate the reading strategies used by Grade 9 English Second Language (ESL learners and also to establish if there was any significant difference between perceived strategy use and gender. The respondents (192 were all ESL learners in Grade 9 in 2011 in a selected school. The study employed a quantitative research method. The study used convenience sampling on a group of 192 Grade 9 learners. The data collected through questionnaires was analysed by means of the Statistical Package for Social Sciences (SPSS software. The findings revealed that the learners did not employ a wide range of reading strategies. The results further indicated that there was no significant difference between boys and girls in terms of strategy use. Based on the above findings several suggestions were made to help teachers improve their teaching and help learners improve their reading comprehension and also about possible areas for future research.

Strategy for selecting disposable bags for cell culture media applications based on a root-cause investigation.

Science.gov (United States)

Wood, Joseph; Mahajan, Ekta; Shiratori, Masaru

2013-01-01

The use of disposable bags for cell culture media storage has grown significantly in the past decade. Some of the key advantages of using disposable bags relative to non-disposable containers include increased product throughput, decreased cleaning validation costs, reduced risk of cross contamination and lower facility costs. As the scope of use of disposable bags for cell culture applications increases, problematic bags and scenarios should be identified and addressed to continue improving disposables technologies and meet the biotech industry's needs. In this article, we examine a cell culture application wherein media stored in disposable bags is warmed at 37°C before use for cell culture operations. A problematic bag film was identified through a prospective and retrospective cell culture investigation. The investigation provided information on the scope and variation of the issue with respect to different Chinese hamster ovary (CHO) cell lines, cell culture media, and application-specific parameters. It also led to the development of application-specific test methods and enabled a strategy for disposable bag film testing. The strategy was implemented for qualifying an alternative bag film for use in our processes. In this test strategy, multiple lots of 13 bag film types, encompassing eight vendors were evaluated using a three round, cell culture-based test strategy. The test strategy resulted in the determination of four viable bag film options based on the technical data. The results of this evaluation were used to conclude that a volatile or air-quenched compound, likely generated by gamma irradiation of the problematic bag film, negatively impacted cell culture performance. © 2013 American Institute of Chemical Engineers.

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

Directory of Open Access Journals (Sweden)

Zhytar Maksym O.

2014-02-01

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

Agent Based Simulation of Group Emotions Evolution and Strategy Intervention in Extreme Events

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Bo Li

2014-01-01

Full Text Available Agent based simulation method has become a prominent approach in computational modeling and analysis of public emergency management in social science research. The group emotions evolution, information diffusion, and collective behavior selection make extreme incidents studies a complex system problem, which requires new methods for incidents management and strategy evaluation. This paper studies the group emotion evolution and intervention strategy effectiveness using agent based simulation method. By employing a computational experimentation methodology, we construct the group emotion evolution as a complex system and test the effects of three strategies. In addition, the events-chain model is proposed to model the accumulation influence of the temporal successive events. Each strategy is examined through three simulation experiments, including two make-up scenarios and a real case study. We show how various strategies could impact the group emotion evolution in terms of the complex emergence and emotion accumulation influence in extreme events. This paper also provides an effective method of how to use agent-based simulation for the study of complex collective behavior evolution problem in extreme incidents, emergency, and security study domains.

Coordinated control strategy for hybrid wind farms with DFIG-based and PMSG-based wind farms during network unbalance

DEFF Research Database (Denmark)

Yao, Jun; Liu, Ruikuo; Zhou, Te

2017-01-01

This paper investigates the coordinated control strategy for a hybrid wind farm with doubly fed induction generator (DFIG)-based and direct-driven permanent-magnet synchronous generator (PMSG)-based wind farms during network unbalance. The negative-sequence current output capabilities of DFIG...... to the controllable operating regions, a targets selection scheme for each control unit is proposed to improve the stability of the hybrid wind farms containing both DFIG-based and PMSG-based wind farms during network unbalance, especially to avoid DFIG-based wind farm tripping from connected power grid under severe...... grid voltage unbalance conditions. Finally, the proposed coordinated control strategy is validated by the simulation results of a 30-MW-DFIG-based wind farm and a 30-MW-PMSG-based wind farm under different operation conditions and experimental results on a laboratory-scale experimental rig under severe...

Variable selection in multivariate calibration based on clustering of variable concept.

Science.gov (United States)

Farrokhnia, Maryam; Karimi, Sadegh

2016-01-01

Recently we have proposed a new variable selection algorithm, based on clustering of variable concept (CLoVA) in classification problem. With the same idea, this new concept has been applied to a regression problem and then the obtained results have been compared with conventional variable selection strategies for PLS. The basic idea behind the clustering of variable is that, the instrument channels are clustered into different clusters via clustering algorithms. Then, the spectral data of each cluster are subjected to PLS regression. Different real data sets (Cargill corn, Biscuit dough, ACE QSAR, Soy, and Tablet) have been used to evaluate the influence of the clustering of variables on the prediction performances of PLS. Almost in the all cases, the statistical parameter especially in prediction error shows the superiority of CLoVA-PLS respect to other variable selection strategies. Finally the synergy clustering of variable (sCLoVA-PLS), which is used the combination of cluster, has been proposed as an efficient and modification of CLoVA algorithm. The obtained statistical parameter indicates that variable clustering can split useful part from redundant ones, and then based on informative cluster; stable model can be reached. Copyright © 2015 Elsevier B.V. All rights reserved.

Public Speaking Apprehension, Decision-Making Errors in the Selection of Speech Introduction Strategies and Adherence to Strategy.

Science.gov (United States)

Beatty, Michael J.

1988-01-01

Examines the choice-making processes of students engaged in the selection of speech introduction strategies. Finds that the frequency of students making decision-making errors was a positive function of public speaking apprehension. (MS)

Could non-grade based selection improve medical student socio-demographic diversity?

DEFF Research Database (Denmark)

O'Neill, Lotte Dyhrberg

2013-01-01

selected with a non-grade-based or ’non-cognitive’ admission program. The two admission groups were compared on seven social indices (doctor parent, ethnic origin, father’s education, mother’s education, parenthood, parents live together, parent on benefit). Result: Selection strategy made no difference...... to the social diversity of admitted medical students. The non-cognitive admission program studied was not a useful initiative for improving medical student diversity nor did it further disadvantaged educationally vulnerable population groups in these cohorts. Discussion: The social heritage and general...

QoE-based transmission strategies for multi-user wireless information and power transfer

Directory of Open Access Journals (Sweden)

Taehun Jung

2015-12-01

Full Text Available One solution to the problem of supplying energy to wireless networks is wireless power transfer. One such technology–electromagnetic radiation enabled wireless power transfer–will change traditional wireless networks. In this paper, we investigate a transmission strategy for multi-user wireless information and power transfer. We consider a multi-user multiple-input multiple-output (MIMO channel that includes one base station (BS and two user terminals (UT consisting of one energy harvesting (EH receiver and one information decoding (ID receiver. Our system provides transmission strategies that can be executed and implemented in practical scenarios. The paper then analyzes the rate–energy (R–E pair of our strategies and compares them to those of the theoretical optimal strategy. We furthermore propose a QoE-based mode selection algorithm by mapping the R–E pair to the utility functions.

Decision method for optimal selection of warehouse material handling strategies by production companies

Science.gov (United States)

Dobos, P.; Tamás, P.; Illés, B.

2016-11-01

Adequate establishment and operation of warehouse logistics determines the companies’ competitiveness significantly because it effects greatly the quality and the selling price of the goods that the production companies produce. In order to implement and manage an adequate warehouse system, adequate warehouse position, stock management model, warehouse technology, motivated work force committed to process improvement and material handling strategy are necessary. In practical life, companies have paid small attantion to select the warehouse strategy properly. Although it has a major influence on the production in the case of material warehouse and on smooth costumer service in the case of finished goods warehouse because this can happen with a huge loss in material handling. Due to the dynamically changing production structure, frequent reorganization of warehouse activities is needed, on what the majority of the companies react basically with no reactions. This work presents a simulation test system frames for eligible warehouse material handling strategy selection and also the decision method for selection.

Time-Consistent Strategies for a Multiperiod Mean-Variance Portfolio Selection Problem

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Huiling Wu

2013-01-01

Full Text Available It remained prevalent in the past years to obtain the precommitment strategies for Markowitz's mean-variance portfolio optimization problems, but not much is known about their time-consistent strategies. This paper takes a step to investigate the time-consistent Nash equilibrium strategies for a multiperiod mean-variance portfolio selection problem. Under the assumption that the risk aversion is, respectively, a constant and a function of current wealth level, we obtain the explicit expressions for the time-consistent Nash equilibrium strategy and the equilibrium value function. Many interesting properties of the time-consistent results are identified through numerical sensitivity analysis and by comparing them with the classical pre-commitment solutions.

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

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Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

Stress, Time Pressure, Strategy Selection and Math Anxiety in Mathematics: A Review of the Literature.

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Caviola, Sara; Carey, Emma; Mammarella, Irene C; Szucs, Denes

2017-01-01

We review how stress induction, time pressure manipulations and math anxiety can interfere with or modulate selection of problem-solving strategies (henceforth "strategy selection") in arithmetical tasks. Nineteen relevant articles were identified, which contain references to strategy selection and time limit (or time manipulations), with some also discussing emotional aspects in mathematical outcomes. Few of these take cognitive processes such as working memory or executive functions into consideration. We conclude that due to the sparsity of available literature our questions can only be partially answered and currently there is not much evidence of clear associations. We identify major gaps in knowledge and raise a series of open questions to guide further research.

Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study

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Arslan, Burcu; Taatgen, Niels A.; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback “Wrong,” they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children’s failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy. PMID:28293206

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

Science.gov (United States)

Arslan, Burcu; Taatgen, Niels A; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

Multi-objective optimization of cellular scanning strategy in selective laser melting

DEFF Research Database (Denmark)

Ahrari, Ali; Deb, Kalyanmoy; Mohanty, Sankhya

2017-01-01

The scanning strategy for selective laser melting - an additive manufacturing process - determines the temperature fields during the manufacturing process, which in turn affects residual stresses and distortions, two of the main sources of process-induced defects. The goal of this study is to dev......The scanning strategy for selective laser melting - an additive manufacturing process - determines the temperature fields during the manufacturing process, which in turn affects residual stresses and distortions, two of the main sources of process-induced defects. The goal of this study......, the problem is a combination of combinatorial and choice optimization, which makes the problem difficult to solve. On a process simulation domain consisting of 32 cells, our multi-objective evolutionary method is able to find a set of trade-off solutions for the defined conflicting objectives, which cannot...

Comparison of genome-wide selection strategies to identify furfural tolerance genes in Escherichia coli.

Science.gov (United States)

Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T

2015-01-01

Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural. © 2014 Wiley Periodicals, Inc.

A Reinforcement Learning Approach to Improve the Argument Selection Effectiveness in Argumentation-based Negotiation

OpenAIRE

Amandi, Analia Adriana; Monteserin, Ariel José

2016-01-01

Argument selection is considered the essence of the strategy in argumentation-based negotiation. An agent, which is arguing during a negotiation, must decide what arguments are the best to persuade the opponent. In fact, in each negotiation step, the agent must select an argument from a set of candidate arguments by applying some selection policy. Following this policy, the agent observes some factors of the negotiation context, for instance: trust in the opponent and expected utility of the...

Selection and Penalty Strategies for Genetic Algorithms Designed to Solve Spatial Forest Planning Problems

International Nuclear Information System (INIS)

Thompson, M.P.; Sessions, J.; Hamann, J.D.

2009-01-01

Genetic algorithms (GAs) have demonstrated success in solving spatial forest planning problems. We present an adaptive GA that incorporates population-level statistics to dynamically update penalty functions, a process analogous to strategic oscillation from the tabu search literature. We also explore performance of various selection strategies. The GA identified feasible solutions within 96%, 98%, and 93% of a non spatial relaxed upper bound calculated for landscapes of 100, 500, and 1000 units, respectively. The problem solved includes forest structure constraints limiting harvest opening sizes and requiring minimally sized patches of mature forest. Results suggest that the dynamic penalty strategy is superior to the more standard static penalty implementation. Results also suggest that tournament selection can be superior to the more standard implementation of proportional selection for smaller problems, but becomes susceptible to premature convergence as problem size increases. It is therefore important to balance selection pressure with appropriate disruption. We conclude that integrating intelligent search strategies into the context of genetic algorithms can yield improvements and should be investigated for future use in spatial planning with ecological goals.

Burnout and job performance: the moderating role of selection, optimization, and compensation strategies.

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Demerouti, Evangelia; Bakker, Arnold B; Leiter, Michael

2014-01-01

The present study aims to explain why research thus far has found only low to moderate associations between burnout and performance. We argue that employees use adaptive strategies that help them to maintain their performance (i.e., task performance, adaptivity to change) at acceptable levels despite experiencing burnout (i.e., exhaustion, disengagement). We focus on the strategies included in the selective optimization with compensation model. Using a sample of 294 employees and their supervisors, we found that compensation is the most successful strategy in buffering the negative associations of disengagement with supervisor-rated task performance and both disengagement and exhaustion with supervisor-rated adaptivity to change. In contrast, selection exacerbates the negative relationship of exhaustion with supervisor-rated adaptivity to change. In total, 42% of the hypothesized interactions proved to be significant. Our study uncovers successful and unsuccessful strategies that people use to deal with their burnout symptoms in order to achieve satisfactory job performance. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Portable, universal, and visual ion sensing platform based on the light emitting diode-based self-referencing-ion selective field-effect transistor.

Science.gov (United States)

Zhang, Xiaowei; Han, Yanchao; Li, Jing; Zhang, Libing; Jia, Xiaofang; Wang, Erkang

2014-02-04

In this work, a novel and universal ion sensing platform was presented, which enables the visual detection of various ions with high sensitivity and selectivity. Coaxial potential signals (millivolt-scale) of the sample from the self-referencing (SR) ion selective chip can be transferred into the ad620-based amplifier with an output of volt-scale potentials. The amplified voltage is high enough to drive a light emitting diode (LED), which can be used as an amplifier and indicator to report the sample information. With this double amplification device (light emitting diode-based self-referencing-ion selective field-effect transistor, LED-SR-ISFET), a tiny change of the sample concentration can be observed with a distinguishable variation of LED brightness by visual inspection. This LED-based luminescent platform provided a facile, low-cost, and rapid sensing strategy without the need of additional expensive chemiluminescence reagent and instruments. Moreover, the SR mode also endows this device excellent stability and reliability. With this innovative design, sensitive determination of K(+), H(+), and Cl(-) by the naked eye was achieved. It should also be noticed that this sensing strategy can easily be extended to other ions (or molecules) by simply integrating the corresponding ion (or molecule) selective electrode.

Contract Source Selection: An Analysis of Lowest Price Technically Acceptable and Tradeoff Strategies

Science.gov (United States)

2016-06-15

using- spss - statistics.php Lamoureux, J., Murrow, M., & Walls, C. (2015). Relationship of source selection methods to contract outcomes: an analysis ...Contract Source Selection: an Analysis of Lowest Price Technically Acceptable and Tradeoff Strategies 15 June 2016 LCDR Jamal M. Osman, USN...ACQUISITION RESEARCH PROGRAM SPONSORED REPORT SERIES Contract Source Selection: an Analysis of Lowest Price Technically Acceptable and Tradeoff

DEA-BASED INVESTMENT STRATEGY AND ITS APPLICATION IN THE CROATIAN STOCK MARKET

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Margareta Gardijan

2012-12-01

Full Text Available This paper describes the DEA-based investment strategy for constructing of a stock portfolio in the Croatian stock market. The relative efficiency of the DMUs, which are in this case the selected stocks from Zagreb Stock Exchange, is obtained from the output oriented CCR and BCC models. The set of inputs consists of risk measures, namely return variance, Value at Risk (VaR and beta coefficient $(\\beta$, while monthly return represents an output. Following the „efficiency scores“, obtained from the models, we construct a portfolio of DEA-efficient stocks (DEA-portfolio. This portfolio can be modified over time according to changes of the DMU's efficiency scores. By comparing the returns of the EA-portfolio and the market return during the given time period, the applicability of the investment strategy based on a DEA methodology, as a strategy for achieving superior returns, is estimated.

Comparison of Different Strategies for Selection/Adaptation of Mixed Microbial Cultures Able to Ferment Crude Glycerol Derived from Second-Generation Biodiesel

DEFF Research Database (Denmark)

Varrone, Cristiano; Heggeset, T. M. B.; Le, S. B.

2015-01-01

Objective of this study was the selection and adaptation of mixed microbial cultures (MMCs), able to ferment crude glycerol generated from animal fat-based biodiesel and produce building-blocks and green chemicals. Various adaptation strategies have been investigated for the enrichment of suitable...... Control. The adaptation of activated sludge inoculum was performed successfully and continued unhindered for several months. The best results showed a substrate degradation efficiency of almost 100% (about 10 g/L glycerol in 21 h) and different dominant metabolic products were obtained, depending...... on the selection strategy (mainly 1,3-propanediol, ethanol, or butyrate). On the other hand, anaerobic sludge exhibited inactivation after a few transfers. To circumvent this problem, fed-batch mode was used as an alternative adaptation strategy, which led to effective substrate degradation and high 1...

Microbiome selection could spur next-generation plant breeding strategies

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Murali Gopal

2016-12-01

Full Text Available Plants, though sessile, have developed a unique strategy to counter biotic and abiotic stresses by symbiotically co-evolving with microorganisms and tapping into their genome for this purpose. Soil is the bank of microbial diversity from which a plant selectively sources its microbiome to suit its needs. Besides soil, seeds, which carry the genetic blueprint of plants during trans-generational propagation, are home to diverse microbiota that acts as the principal source of microbial inoculum in crop cultivation. Overall, a plant is ensconced both on the outside and inside with a diverse assemblage of microbiota. Together, the plant genome and the genes of the microbiota that the plant harbours in different plant tissues i.e the ‘plant microbiome’, form the holobiome which is now considered as unit of selection: ‘the holobiont’. The ‘plant microbiome’ not only helps plants to remain fit but also offers critical genetic variability, hitherto, not employed in the breeding strategy by plant breeders, who traditionally have exploited the genetic variability of the host for developing high yielding or disease tolerant or drought resistant varieties. This fresh knowledge of the microbiome, particularly of the rhizosphere, offering genetic variability to plants, opens up new horizons for breeding that could usher in cultivation of next-generation crops depending less on inorganic inputs, resistant to insect pest and diseases and resilient to climatic perturbations. We surmise, from ever increasing evidences, that plants and their microbial symbionts need to be co-propagated as life-long partners in future strategies for plant breeding.

Strategies for efficiently selecting PHA producing mixed microbial cultures using complex feedstocks: Feast and famine regime and uncoupled carbon and nitrogen availabilities.

Science.gov (United States)

Oliveira, Catarina S S; Silva, Carlos E; Carvalho, Gilda; Reis, Maria A

2017-07-25

Production of polyhydroxyalkanoates (PHAs) by open mixed microbial cultures (MMCs) has been attracting increasing interest as an alternative technology to PHA production by pure cultures, due to the potential for lower costs associated with the use of open systems (eliminating the requirement for sterile conditions) and the utilisation of cheap feedstock (industrial and agricultural wastes). Such technology relies on the efficient selection of an MMC enriched in PHA-accumulating organisms. Fermented cheese whey, a protein-rich complex feedstock, has been used previously to produce PHA using the feast and famine regime for selection of PHA accumulating cultures. While this selection strategy was found efficient when operated at relatively low organic loading rate (OLR, 2g-CODL -1 d -1 ), great instability and low selection efficiency of PHA accumulating organisms were observed when higher OLR (ca. 6g-CODL -1 d -1 ) was applied. High organic loading is desirable as a means to enhance PHA productivity. In the present study, a new selection strategy was tested with the aim of improving selection for high OLR. It was based on uncoupling carbon and nitrogen supply and was implemented and compared with the conventional feast and famine strategy. For this, two selection reactors were fed with fermented cheese whey applying an OLR of ca. 8.5g-CODL -1 (with 3.8g-CODL -1 resulting from organic acids and ethanol), and operated in parallel under similar conditions, except for the timing of nitrogen supplementation. Whereas in the conventional strategy nitrogen and carbon substrates were added simultaneously at the beginning of the cycle, in the uncoupled substrates strategy, nitrogen addition was delayed to the end of the feast phase (i.e. after exogenous carbon was exhausted). The two different strategies selected different PHA-storing microbial communities, dominated by Corynebacterium and a Xantomonadaceae, respectively with the conventional and the new approaches. The new

A Capture-SELEX Strategy for Multiplexed Selection of RNA Aptamers Against Small Molecules

DEFF Research Database (Denmark)

Lauridsen, Lasse Holm; Doessing, Holger B.; Long, Katherine S.

2018-01-01

-SELEX, a selection strategy that uses an RNA library to yield ligand-responsive RNA aptamers targeting small organic molecules in solution. To demonstrate the power of this method we selected several aptamers with specificity towards either the natural sweetener rebaudioside A or the food-coloring agent carminic...

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors

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Stefania Russo

2017-08-01

Full Text Available Electrical Impedance Tomography (EIT is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR and Boundary Voltage Changes (BVC, and study image quality with Size Error (SE, Position Error (PE and Ringing (RNG parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively.

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors.

Science.gov (United States)

Russo, Stefania; Nefti-Meziani, Samia; Carbonaro, Nicola; Tognetti, Alessandro

2017-08-31

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively.

Selective and Sensitive Detection of Cyanide Based on the Displacement Strategy Using a Water-Soluble Fluorescent Probe

Science.gov (United States)

La, Ming; Hao, Yuanqiang; Wang, Zhaoyang; Han, Guo-Cheng; Qu, Lingbo

2016-01-01

A water-soluble fluorescent probe (C-GGH) was used for the highly sensitive and selective detection of cyanide (CN−) in aqueous media based on the displacement strategy. Due to the presence of the recognition unit GGH (Gly-Gly-His), the probe C-GGH can coordinate with Cu2+ and consequently display ON-OFF type fluorescence response. Furthermore, the in situ formed nonfluorescent C-GGH-Cu2+ complex can act as an effective OFF-ON type fluorescent probe for sensing CN− anion. Due to the strong binding affinity of CN− to Cu2+, CN− can extract Cu2+ from C-GGH-Cu2+ complex, leading to the release of C-GGH and the recovery of fluorescent emission of the system. The probe C-GGH-Cu2+ allowed detection of CN− in aqueous solution with a LOD (limit of detection) of 0.017 μmol/L which is much lower than the maximum contaminant level (1.9 μmol/L) for CN− in drinking water set by the WHO (World Health Organization). The probe also displayed excellent specificity for CN− towards other anions, including F−, Cl−, Br−, I−, SCN−, PO4 3−, N3 −, NO3 −, AcO−, SO4 2−, and CO3 2−. PMID:26881185

Selective and Sensitive Detection of Cyanide Based on the Displacement Strategy Using a Water-Soluble Fluorescent Probe

Directory of Open Access Journals (Sweden)

Ming La

2016-01-01

Full Text Available A water-soluble fluorescent probe (C-GGH was used for the highly sensitive and selective detection of cyanide (CN− in aqueous media based on the displacement strategy. Due to the presence of the recognition unit GGH (Gly-Gly-His, the probe C-GGH can coordinate with Cu2+ and consequently display ON-OFF type fluorescence response. Furthermore, the in situ formed nonfluorescent C-GGH-Cu2+ complex can act as an effective OFF-ON type fluorescent probe for sensing CN− anion. Due to the strong binding affinity of CN− to Cu2+, CN− can extract Cu2+ from C-GGH-Cu2+ complex, leading to the release of C-GGH and the recovery of fluorescent emission of the system. The probe C-GGH-Cu2+ allowed detection of CN− in aqueous solution with a LOD (limit of detection of 0.017 μmol/L which is much lower than the maximum contaminant level (1.9 μmol/L for CN− in drinking water set by the WHO (World Health Organization. The probe also displayed excellent specificity for CN− towards other anions, including F−, Cl−, Br−, I−, SCN−, PO43-, N3-, NO3-, AcO−, SO42-, and CO32-.

Cost-effectiveness and harm-benefit analyses of risk-based screening strategies for breast cancer.

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Ester Vilaprinyo

Full Text Available The one-size-fits-all paradigm in organized screening of breast cancer is shifting towards a personalized approach. The present study has two objectives: 1 To perform an economic evaluation and to assess the harm-benefit ratios of screening strategies that vary in their intensity and interval ages based on breast cancer risk; and 2 To estimate the gain in terms of cost and harm reductions using risk-based screening with respect to the usual practice. We used a probabilistic model and input data from Spanish population registries and screening programs, as well as from clinical studies, to estimate the benefit, harm, and costs over time of 2,624 screening strategies, uniform or risk-based. We defined four risk groups, low, moderate-low, moderate-high and high, based on breast density, family history of breast cancer and personal history of breast biopsy. The risk-based strategies were obtained combining the exam periodicity (annual, biennial, triennial and quinquennial, the starting ages (40, 45 and 50 years and the ending ages (69 and 74 years in the four risk groups. Incremental cost-effectiveness and harm-benefit ratios were used to select the optimal strategies. Compared to risk-based strategies, the uniform ones result in a much lower benefit for a specific cost. Reductions close to 10% in costs and higher than 20% in false-positive results and overdiagnosed cases were obtained for risk-based strategies. Optimal screening is characterized by quinquennial or triennial periodicities for the low or moderate risk-groups and annual periodicity for the high-risk group. Risk-based strategies can reduce harm and costs. It is necessary to develop accurate measures of individual risk and to work on how to implement risk-based screening strategies.

Unsupervised Performance Evaluation Strategy for Bridge Superstructure Based on Fuzzy Clustering and Field Data

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Yubo Jiao

2013-01-01

Full Text Available Performance evaluation of a bridge is critical for determining the optimal maintenance strategy. An unsupervised bridge superstructure state assessment method is proposed in this paper based on fuzzy clustering and bridge field measured data. Firstly, the evaluation index system of bridge is constructed. Secondly, a certain number of bridge health monitoring data are selected as clustering samples to obtain the fuzzy similarity matrix and fuzzy equivalent matrix. Finally, different thresholds are selected to form dynamic clustering maps and determine the best classification based on statistic analysis. The clustering result is regarded as a sample base, and the bridge state can be evaluated by calculating the fuzzy nearness between the unknown bridge state data and the sample base. Nanping Bridge in Jilin Province is selected as the engineering project to verify the effectiveness of the proposed method.

In silico tools used for compound selection during target-based drug discovery and development.

Science.gov (United States)

Caldwell, Gary W

2015-01-01

The target-based drug discovery process, including target selection, screening, hit-to-lead (H2L) and lead optimization stage gates, is the most common approach used in drug development. The full integration of in vitro and/or in vivo data with in silico tools across the entire process would be beneficial to R&D productivity by developing effective selection criteria and drug-design optimization strategies. This review focuses on understanding the impact and extent in the past 5 years of in silico tools on the various stage gates of the target-based drug discovery approach. There are a large number of in silico tools available for establishing selection criteria and drug-design optimization strategies in the target-based approach. However, the inconsistent use of in vitro and/or in vivo data integrated with predictive in silico multiparameter models throughout the process is contributing to R&D productivity issues. In particular, the lack of reliable in silico tools at the H2L stage gate is contributing to the suboptimal selection of viable lead compounds. It is suggested that further development of in silico multiparameter models and organizing biologists, medicinal and computational chemists into one team with a single accountable objective to expand the utilization of in silico tools in all phases of drug discovery would improve R&D productivity.

Genotype-by-environment interactions leads to variable selection on life-history strategy in Common Evening Primrose (Oenothera biennis).

Science.gov (United States)

Johnson, M T J

2007-01-01

Monocarpic plant species, where reproduction is fatal, frequently exhibit variation in the length of their prereproductive period prior to flowering. If this life-history variation in flowering strategy has a genetic basis, genotype-by-environment interactions (G x E) may maintain phenotypic diversity in flowering strategy. The native monocarpic plant Common Evening Primrose (Oenothera biennis L., Onagraceae) exhibits phenotypic variation for annual vs. biennial flowering strategies. I tested whether there was a genetic basis to variation in flowering strategy in O. biennis, and whether environmental variation causes G x E that imposes variable selection on flowering strategy. In a field experiment, I randomized more than 900 plants from 14 clonal families (genotypes) into five distinct habitats that represented a natural productivity gradient. G x E strongly affected the lifetime fruit production of O. biennis, with the rank-order in relative fitness of genotypes changing substantially between habitats. I detected genetic variation in annual vs. biennial strategies in most habitats, as well as a G x E effect on flowering strategy. This variation in flowering strategy was correlated with genetic variation in relative fitness, and phenotypic and genotypic selection analyses revealed that environmental variation resulted in variable directional selection on annual vs. biennial strategies. Specifically, a biennial strategy was favoured in moderately productive environments, whereas an annual strategy was favoured in low-productivity environments. These results highlight the importance of variable selection for the maintenance of genetic variation in the life-history strategy of a monocarpic plant.

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Science.gov (United States)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Threshold-selecting strategy for best possible ground state detection with genetic algorithms

Science.gov (United States)

Lässig, Jörg; Hoffmann, Karl Heinz

2009-04-01

Genetic algorithms are a standard heuristic to find states of low energy in complex state spaces as given by physical systems such as spin glasses but also in combinatorial optimization. The paper considers the problem of selecting individuals in the current population in genetic algorithms for crossover. Many schemes have been considered in literature as possible crossover selection strategies. We show for a large class of quality measures that the best possible probability distribution for selecting individuals in each generation of the algorithm execution is a rectangular distribution over the individuals sorted by their energy values. This means uniform probabilities have to be assigned to a group of the individuals with lowest energy in the population but probabilities equal to zero to individuals which are corresponding to energy values higher than a fixed cutoff, which is equal to a certain rank in the vector sorted by the energy of the states in the current population. The considered strategy is dubbed threshold selecting. The proof applies basic arguments of Markov chains and linear optimization and makes only a few assumptions on the underlying principles and hence applies to a large class of algorithms.

Cellular scanning strategy for selective laser melting: Evolution of optimal grid-based scanning path & parametric approach to thermal homogeneity

DEFF Research Database (Denmark)

Mohanty, Sankhya; Tutum, Cem Celal; Hattel, Jesper Henri

2013-01-01

Selective laser melting, as a rapid manufacturing technology, is uniquely poised to enforce a paradigm shift in the manufacturing industry by eliminating the gap between job- and batch-production techniques. Products from this process, however, tend to show an increased amount of defects such as ...... strategy has been developed for processing the standard sample, one unit cell at a time, using genetic algorithms, with an objective of reducing thermal asymmetries. © 2013 SPIE....

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

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Yong Wang

2016-02-01

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

An Optical Biosensing Strategy Based on Selective Light Absorption and Wavelength Filtering from Chromogenic Reaction

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Hyeong Jin Chun

2018-03-01

Full Text Available To overcome the time and space constraints in disease diagnosis via the biosensing approach, we developed a new signal-transducing strategy that can be applied to colorimetric optical biosensors. Our study is focused on implementation of a signal transduction technology that can directly translate the color intensity signals—that require complicated optical equipment for the analysis—into signals that can be easily counted with the naked eye. Based on the selective light absorption and wavelength-filtering principles, our new optical signaling transducer was built from a common computer monitor and a smartphone. In this signal transducer, the liquid crystal display (LCD panel of the computer monitor served as a light source and a signal guide generator. In addition, the smartphone was used as an optical receiver and signal display. As a biorecognition layer, a transparent and soft material-based biosensing channel was employed generating blue output via a target-specific bienzymatic chromogenic reaction. Using graphics editor software, we displayed the optical signal guide patterns containing multiple polygons (a triangle, circle, pentagon, heptagon, and 3/4 circle, each associated with a specified color ratio on the LCD monitor panel. During observation of signal guide patterns displayed on the LCD monitor panel using a smartphone camera via the target analyte-loaded biosensing channel as a color-filtering layer, the number of observed polygons changed according to the concentration of the target analyte via the spectral correlation between absorbance changes in a solution of the biosensing channel and color emission properties of each type of polygon. By simple counting of the changes in the number of polygons registered by the smartphone camera, we could efficiently measure the concentration of a target analyte in a sample without complicated and expensive optical instruments. In a demonstration test on glucose as a model analyte, we

An Optical Biosensing Strategy Based on Selective Light Absorption and Wavelength Filtering from Chromogenic Reaction.

Science.gov (United States)

Chun, Hyeong Jin; Han, Yong Duk; Park, Yoo Min; Kim, Ka Ram; Lee, Seok Jae; Yoon, Hyun C

2018-03-06

To overcome the time and space constraints in disease diagnosis via the biosensing approach, we developed a new signal-transducing strategy that can be applied to colorimetric optical biosensors. Our study is focused on implementation of a signal transduction technology that can directly translate the color intensity signals-that require complicated optical equipment for the analysis-into signals that can be easily counted with the naked eye. Based on the selective light absorption and wavelength-filtering principles, our new optical signaling transducer was built from a common computer monitor and a smartphone. In this signal transducer, the liquid crystal display (LCD) panel of the computer monitor served as a light source and a signal guide generator. In addition, the smartphone was used as an optical receiver and signal display. As a biorecognition layer, a transparent and soft material-based biosensing channel was employed generating blue output via a target-specific bienzymatic chromogenic reaction. Using graphics editor software, we displayed the optical signal guide patterns containing multiple polygons (a triangle, circle, pentagon, heptagon, and 3/4 circle, each associated with a specified color ratio) on the LCD monitor panel. During observation of signal guide patterns displayed on the LCD monitor panel using a smartphone camera via the target analyte-loaded biosensing channel as a color-filtering layer, the number of observed polygons changed according to the concentration of the target analyte via the spectral correlation between absorbance changes in a solution of the biosensing channel and color emission properties of each type of polygon. By simple counting of the changes in the number of polygons registered by the smartphone camera, we could efficiently measure the concentration of a target analyte in a sample without complicated and expensive optical instruments. In a demonstration test on glucose as a model analyte, we could easily measure the

Influence of Pre-question and genre-based instructional strategies on reading

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Titi J. Fola-Adebayo

2014-12-01

Full Text Available This study investigated the influence of Pre-question and genre-based instructional strategies on science undergraduates’ achievement in, and attitude to, reading. Using purposive sampling,two specialised universities in Nigeria were selected and stratified sampling was employed in assigning students to research groups based on gender and performance in a verbal ability test. Two hundred and eighty-five students participated in the study. Pre-post randomised block experimental design was used with three experimental groups and one control group. The experimental procedure involving Pre-question, genre-based instruction and a combination of Pre-question and genre-based instructional strategies were used for the experimental groups for four weeks whilst the control group received normal teacher input. Data were collected through a Reading Comprehension Achievement Test and Students’ Attitude Questionnaire. Qualitative data, obtained from videotapes of classroom interactions, were subjected to conversation and interaction analyses and quantitative data were analysed with Analysis of Covariance (ANCOVA. The results indicate that although there was no significant main effect of instructional strategy on students’ achievement in reading comprehension, there was significant main effect of instructional strategy on students’ attitude to reading (F(3,231 = 30.9;p <.05. Findings from the qualitative enquiry revealed that female students were more voluble and assertive in their responses probably because of the need to resist male domination whilst male students used discourse strategies to affirm their authority. The study indicated that the combination of pre-question and genre-based approach was the most effective in enhancing the students’ attitude to reading. Reading is one of the most useful of the Language Arts skills which learners need for academic reasons and for lifelong learning. The globalised world demands that the second language

FiGS: a filter-based gene selection workbench for microarray data

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Yun Taegyun

2010-01-01

Full Text Available Abstract Background The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset. Results FiGS is a web-based workbench that automatically compares various gene selection procedures and provides the optimal gene selection result for an input microarray dataset. FiGS builds up diverse gene selection procedures by aligning different feature selection techniques and classifiers. In addition to the highly reputed techniques, FiGS diversifies the gene selection procedures by incorporating gene clustering options in the feature selection step and different data pre-processing options in classifier training step. All candidate gene selection procedures are evaluated by the .632+ bootstrap errors and listed with their classification accuracies and selected gene sets. FiGS runs on parallelized computing nodes that capacitate heavy computations. FiGS is freely accessible at http://gexp.kaist.ac.kr/figs. Conclusion FiGS is an web-based application that automates an extensive search for the optimized gene selection analysis for a microarray dataset in a parallel computing environment. FiGS will provide both an efficient and comprehensive means of acquiring optimal gene sets that discriminate disease states from microarray datasets.

Selection of decommissioning strategies: Issues and factors. Report by an expert group

International Nuclear Information System (INIS)

2005-11-01

A comprehensive assessment of possible strategies is the key step in a decommissioning process. It should be initiated at an early stage in a facility's lifecycle and include a number of factors. The IAEA has provided extensive guidance on decommissioning strategy selection, but there are a number of cases - particularly in countries with limited resources, but not limited to them - where the selection is forced and constrained by prevailing factors and conditions. In its role of an international expert committee assisting the IAEA, the Technical Group on Decommissioning (TEGDE) debates and draws conclusions on topics omitted from general guidance. TEGDE members met in Vienna in 2003, 2004 and 2005 to develop the basis for this publication. The views expressed here reflect those of TEGDE and not necessarily those of the IAEA

End-to-End Joint Antenna Selection Strategy and Distributed Compress and Forward Strategy for Relay Channels

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Rahul Vaze

2009-01-01

Full Text Available Multihop relay channels use multiple relay stages, each with multiple relay nodes, to facilitate communication between a source and destination. Previously, distributed space-time codes were proposed to maximize the achievable diversity-multiplexing tradeoff; however, they fail to achieve all the points of the optimal diversity-multiplexing tradeoff. In the presence of a low-rate feedback link from the destination to each relay stage and the source, this paper proposes an end-to-end antenna selection (EEAS strategy as an alternative to distributed space-time codes. The EEAS strategy uses a subset of antennas of each relay stage for transmission of the source signal to the destination with amplifying and forwarding at each relay stage. The subsets are chosen such that they maximize the end-to-end mutual information at the destination. The EEAS strategy achieves the corner points of the optimal diversity-multiplexing tradeoff (corresponding to maximum diversity gain and maximum multiplexing gain and achieves better diversity gain at intermediate values of multiplexing gain, versus the best-known distributed space-time coding strategies. A distributed compress and forward (CF strategy is also proposed to achieve all points of the optimal diversity-multiplexing tradeoff for a two-hop relay channel with multiple relay nodes.

A Distributed Dynamic Super Peer Selection Method Based on Evolutionary Game for Heterogeneous P2P Streaming Systems

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Jing Chen

2013-01-01

Full Text Available Due to high efficiency and good scalability, hierarchical hybrid P2P architecture has drawn more and more attention in P2P streaming research and application fields recently. The problem about super peer selection, which is the key problem in hybrid heterogeneous P2P architecture, is becoming highly challenging because super peers must be selected from a huge and dynamically changing network. A distributed super peer selection (SPS algorithm for hybrid heterogeneous P2P streaming system based on evolutionary game is proposed in this paper. The super peer selection procedure is modeled based on evolutionary game framework firstly, and its evolutionarily stable strategies are analyzed. Then a distributed Q-learning algorithm (ESS-SPS according to the mixed strategies by analysis is proposed for the peers to converge to the ESSs based on its own payoff history. Compared to the traditional randomly super peer selection scheme, experiments results show that the proposed ESS-SPS algorithm achieves better performance in terms of social welfare and average upload rate of super peers and keeps the upload capacity of the P2P streaming system increasing steadily with the number of peers increasing.

Efficient generation of long-distance conditional alleles using recombineering and a dual selection strategy in replicate plates

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Liang Hong-Erh

2009-07-01

Full Text Available Abstract Background Conditional knockout mice are a useful tool to study the function of gene products in a tissue-specific or inducible manner. Classical approaches to generate targeting vectors for conditional alleles are often limited by the availability of suitable restriction sites. Furthermore, plasmid-based targeting vectors can only cover a few kB of DNA which precludes the generation of targeting vectors where the two loxP sites are placed far apart. These limitations have been overcome in the recent past by using homologous recombination of bacterial artificial chromosomes (BACs in Escherichia coli to produce large targeting vector containing two different loxP-flanked selection cassettes so that a single targeting event is sufficient to introduce loxP-sites a great distances into the mouse genome. However, the final targeted allele should be free of selection cassettes and screening for correct removal of selection cassettes can be a laborious task. Therefore, we developed a new strategy to rapidly identify ES cells containing the desired allele. Results Using BAC recombineering we generated a single targeting vector which contained two different selection cassettes that were flanked by loxP-loxP sites or by FRT-FRT/loxP sites so that they could be deleted sequentially by Cre- and FLPe-recombinases, respectively. Transfected ES cells were first selected in the presence of both antibiotics in vitro before correctly targeted clones were identified by Southern blot. After transfection of a Cre recombinase expression plasmid ES cell clones were selected on replicate plates to identify those clones which maintained the FRT-FRT/loxP flanked cassette and lost the loxP-loxP flanked cassette. Using this strategy facilitated the identification of ES cell clones containing the desired allele before blastocyst injection. Conclusion The strategy of ES cell cultures in replicate plates proved to be very efficient in identifying ES cells that had

Microbiome Selection Could Spur Next-Generation Plant Breeding Strategies.

Science.gov (United States)

Gopal, Murali; Gupta, Alka

2016-01-01

" No plant is an island too …" Plants, though sessile, have developed a unique strategy to counter biotic and abiotic stresses by symbiotically co-evolving with microorganisms and tapping into their genome for this purpose. Soil is the bank of microbial diversity from which a plant selectively sources its microbiome to suit its needs. Besides soil, seeds, which carry the genetic blueprint of plants during trans-generational propagation, are home to diverse microbiota that acts as the principal source of microbial inoculum in crop cultivation. Overall, a plant is ensconced both on the outside and inside with a diverse assemblage of microbiota. Together, the plant genome and the genes of the microbiota that the plant harbors in different plant tissues, i.e., the 'plant microbiome,' form the holobiome which is now considered as unit of selection: 'the holobiont.' The 'plant microbiome' not only helps plants to remain fit but also offers critical genetic variability, hitherto, not employed in the breeding strategy by plant breeders, who traditionally have exploited the genetic variability of the host for developing high yielding or disease tolerant or drought resistant varieties. This fresh knowledge of the microbiome, particularly of the rhizosphere, offering genetic variability to plants, opens up new horizons for breeding that could usher in cultivation of next-generation crops depending less on inorganic inputs, resistant to insect pest and diseases and resilient to climatic perturbations. We surmise, from ever increasing evidences, that plants and their microbial symbionts need to be co-propagated as life-long partners in future strategies for plant breeding. In this perspective, we propose bottom-up approach to co-propagate the co-evolved, the plant along with the target microbiome, through - (i) reciprocal soil transplantation method, or (ii) artificial ecosystem selection method of synthetic microbiome inocula, or (iii) by exploration of microRNA transfer

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

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Kursat Zuhtuogullari

2013-01-01

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

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

Science.gov (United States)

Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

2013-01-01

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

Assessing Reading Strategy Training based on CALLA model in EFL and ESL Context

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Alireza Karbalaei

2011-04-01

Full Text Available Reading strategies instruction is currently gaining much attention as an effective means of enhancing reading comprehension. In this research, we examined the effect of Underlining Strategy Intervention, based on the CALLA model in EFL and ESL contexts. A group of 189 college students were randomly selected from different universities in Iran and India. Based on a proficiency test, students were grouped into high, moderate, and low level. Then, the underlining strategy was taught during the treatment sessions. The results suggest that intervention or explicit instruction was effective in increasing the reading comprehension of both Iranian and Indian students although Indian ESL students were able to perform better in comparison to their Iranian EFL counterparts. There was no significant difference between proficiency level and students' performance in reading comprehension in EFL and ESL contexts. In addition, there was no significant difference between males and females in both contexts.

Strategy scenario selection in the competition of mobile ecosystems

OpenAIRE

Lee, Hyun Joo; Kim, Jin Ki

2013-01-01

Competition in the mobile market is centered on platforms, or operating systems, for smartphones. The current competition and market structure of the global mobile market has shifted to a competition among ecosystems that utilize the same mobile operating systems of the platform operators. This paper aims to answer those questions. The direction of competition in the smartphone industry is traced. This study tries to list the selectable strategy options for each major ecosystem. Then the stra...

System-based strategies for p53 recovery.

Science.gov (United States)

Azam, Muhammad Rizwan; Fazal, Sahar; Ullah, Mukhtar; Bhatti, Aamer I

2018-06-01

The authors have proposed a systems theory-based novel drug design approach for the p53 pathway. The pathway is taken as a dynamic system represented by ordinary differential equations-based mathematical model. Using control engineering practices, the system analysis and subsequent controller design is performed for the re-activation of wild-type p53. p53 revival is discussed for both modes of operation, i.e. the sustained and oscillatory. To define the problem in control system paradigm, modification in the existing mathematical model is performed to incorporate the effect of Nutlin. Attractor point analysis is carried out to select the suitable domain of attraction. A two-loop negative feedback control strategy is devised to drag the system trajectories to the attractor point and to regulate cellular concentration of Nutlin, respectively. An integrated framework is constituted to incorporate the pharmacokinetic effects of Nutlin in the cancerous cells. Bifurcation analysis is also performed on the p53 model to see the conditions for p53 oscillation.

Implications of structural genomics target selection strategies: Pfam5000, whole genome, and random approaches

Energy Technology Data Exchange (ETDEWEB)

Chandonia, John-Marc; Brenner, Steven E.

2004-07-14

The structural genomics project is an international effort to determine the three-dimensional shapes of all important biological macromolecules, with a primary focus on proteins. Target proteins should be selected according to a strategy which is medically and biologically relevant, of good value, and tractable. As an option to consider, we present the Pfam5000 strategy, which involves selecting the 5000 most important families from the Pfam database as sources for targets. We compare the Pfam5000 strategy to several other proposed strategies that would require similar numbers of targets. These include including complete solution of several small to moderately sized bacterial proteomes, partial coverage of the human proteome, and random selection of approximately 5000 targets from sequenced genomes. We measure the impact that successful implementation of these strategies would have upon structural interpretation of the proteins in Swiss-Prot, TrEMBL, and 131 complete proteomes (including 10 of eukaryotes) from the Proteome Analysis database at EBI. Solving the structures of proteins from the 5000 largest Pfam families would allow accurate fold assignment for approximately 68 percent of all prokaryotic proteins (covering 59 percent of residues) and 61 percent of eukaryotic proteins (40 percent of residues). More fine-grained coverage which would allow accurate modeling of these proteins would require an order of magnitude more targets. The Pfam5000 strategy may be modified in several ways, for example to focus on larger families, bacterial sequences, or eukaryotic sequences; as long as secondary consideration is given to large families within Pfam, coverage results vary only slightly. In contrast, focusing structural genomics on a single tractable genome would have only a limited impact in structural knowledge of other proteomes: a significant fraction (about 30-40 percent of the proteins, and 40-60 percent of the residues) of each proteome is classified in small

Stress, Time Pressure, Strategy Selection and Math Anxiety in Mathematics: A Review of the Literature

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Sara Caviola

2017-09-01

Full Text Available We review how stress induction, time pressure manipulations and math anxiety can interfere with or modulate selection of problem-solving strategies (henceforth “strategy selection” in arithmetical tasks. Nineteen relevant articles were identified, which contain references to strategy selection and time limit (or time manipulations, with some also discussing emotional aspects in mathematical outcomes. Few of these take cognitive processes such as working memory or executive functions into consideration. We conclude that due to the sparsity of available literature our questions can only be partially answered and currently there is not much evidence of clear associations. We identify major gaps in knowledge and raise a series of open questions to guide further research.

The Relationship between Preschoolers' Selective Attention and Memory for Location Strategies

Science.gov (United States)

Blumberg, F.C.; Torenberg, M.; Randall, J.D.

2005-01-01

Late and early preschoolers' attention and spatial strategies were examined in response to instructions to recall relevant objects [Blumberg, F. C. & Torenberg, M. (2003). The impact of spatial cues on preschoolers' selective attention. Journal of Genetic Psychology, 164, 42-53] and irrelevant objects [Blumberg, F. C. & Torenberg, M. (in press).…

A Holistic Quality Evaluation, Selection and Improvement Approach driven by Multilevel Goals and Strategies

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Belen Rivera

2016-12-01

Full Text Available Organizations should establish business goals and check for their achievement in a systematic and disciplined way. In order to know if a business goal is achieved, it should be necessary to consider information need goals that also can require satisfying measurement and evaluation goals at operational level. Furthermore, if measurement and evaluation goals are not aligned with top-level business goals such as tactical or strategic level goals, the organization could waste its effort and resources. Usually, the different goals established in an organization are operationalized through projects. For a given project, strategies should be used in order to help in the goal achievement. A strategy defines a set of activities and methods to be followed for a specific goal purpose. Ultimately, to engineering all these issues in a systematic way, organizations should adopt a holistic evaluation approach supported by a set of integrated strategies. By means of a systematic literature review as research method, we have observed that very few approaches support integrated strategies and multilevel goals. To bridge this gap, we have developed a holistic quality multilevel and multipurpose evaluation approach that ties together multilevel goals, projects and integrated strategies. As contributions, this paper discusses an enhanced conceptual base (specified by ontologies for linking business and information need goal concepts with project, strategy and nonfunctional requirements concepts. Then, it defines the step by step of our holistic quality evaluation approach, by listing the necessary activities to establish goals and projects at different organizational levels. Lastly, it specifies and illustrates evaluation scenarios for business/information need goal purposes such as understanding, improving, monitoring and controlling, comparing and selecting entities, which are supported by strategies and strategy patterns.

Do biological-based strategies hold promise to biofouling control in MBRs?

KAUST Repository

Malaeb, Lilian

2013-10-01

Biofouling in membrane bioreactors (MBRs) remains a primary challenge for their wider application, despite the growing acceptance of MBRs worldwide. Research studies on membrane fouling are extensive in the literature, with more than 200 publications on MBR fouling in the last 3 years; yet, improvements in practice on biofouling control and management have been remarkably slow. Commonly applied cleaning methods are only partially effective and membrane replacement often becomes frequent. The reason for the slow advancement in successful control of biofouling is largely attributed to the complex interactions of involved biological compounds and the lack of representative-for-practice experimental approaches to evaluate potential effective control strategies. Biofouling is driven by microorganisms and their associated extra-cellular polymeric substances (EPS) and microbial products. Microorganisms and their products convene together to form matrices that are commonly treated as a black box in conventional control approaches. Biological-based antifouling strategies seem to be a promising constituent of an effective integrated control approach since they target the essence of biofouling problems. However, biological-based strategies are in their developmental phase and several questions should be addressed to set a roadmap for translating existing and new information into sustainable and effective control techniques. This paper investigates membrane biofouling in MBRs from the microbiological perspective to evaluate the potential of biological-based strategies in offering viable control alternatives. Limitations of available control methods highlight the importance of an integrated anti-fouling approach including biological strategies. Successful development of these strategies requires detailed characterization of microorganisms and EPS through the proper selection of analytical tools and assembly of results. Existing microbiological/EPS studies reveal a number of

Hyperspectral band selection based on consistency-measure of neighborhood rough set theory

International Nuclear Information System (INIS)

Liu, Yao; Xie, Hong; Wang, Liguo; Tan, Kezhu; Chen, Yuehua; Xu, Zhen

2016-01-01

Band selection is a well-known approach for reducing dimensionality in hyperspectral imaging. In this paper, a band selection method based on consistency-measure of neighborhood rough set theory (CMNRS) was proposed to select informative bands from hyperspectral images. A decision-making information system was established by the reflection spectrum of soybeans’ hyperspectral data between 400 nm and 1000 nm wavelengths. The neighborhood consistency-measure, which reflects not only the size of the decision positive region, but also the sample distribution in the boundary region, was used as the evaluation function of band significance. The optimal band subset was selected by a forward greedy search algorithm. A post-pruning strategy was employed to overcome the over-fitting problem and find the minimum subset. To assess the effectiveness of the proposed band selection technique, two classification models (extreme learning machine (ELM) and random forests (RF)) were built. The experimental results showed that the proposed algorithm can effectively select key bands and obtain satisfactory classification accuracy. (paper)

Phylogenetic systematics and biogeography of hummingbirds: Bayesian and maximum likelihood analyses of partitioned data and selection of an appropriate partitioning strategy.

Science.gov (United States)

McGuire, Jimmy A; Witt, Christopher C; Altshuler, Douglas L; Remsen, J V

2007-10-01

Hummingbirds are an important model system in avian biology, but to date the group has been the subject of remarkably few phylogenetic investigations. Here we present partitioned Bayesian and maximum likelihood phylogenetic analyses for 151 of approximately 330 species of hummingbirds and 12 outgroup taxa based on two protein-coding mitochondrial genes (ND2 and ND4), flanking tRNAs, and two nuclear introns (AK1 and BFib). We analyzed these data under several partitioning strategies ranging between unpartitioned and a maximum of nine partitions. In order to select a statistically justified partitioning strategy following partitioned Bayesian analysis, we considered four alternative criteria including Bayes factors, modified versions of the Akaike information criterion for small sample sizes (AIC(c)), Bayesian information criterion (BIC), and a decision-theoretic methodology (DT). Following partitioned maximum likelihood analyses, we selected a best-fitting strategy using hierarchical likelihood ratio tests (hLRTS), the conventional AICc, BIC, and DT, concluding that the most stringent criterion, the performance-based DT, was the most appropriate methodology for selecting amongst partitioning strategies. In the context of our well-resolved and well-supported phylogenetic estimate, we consider the historical biogeography of hummingbirds using ancestral state reconstructions of (1) primary geographic region of occurrence (i.e., South America, Central America, North America, Greater Antilles, Lesser Antilles), (2) Andean or non-Andean geographic distribution, and (3) minimum elevational occurrence. These analyses indicate that the basal hummingbird assemblages originated in the lowlands of South America, that most of the principle clades of hummingbirds (all but Mountain Gems and possibly Bees) originated on this continent, and that there have been many (at least 30) independent invasions of other primary landmasses, especially Central America.

The Effect of Exit Strategy on Optimal Portfolio Selection with Birandom Returns

OpenAIRE

Cao, Guohua; Shan, Dan

2013-01-01

The aims of this paper are to use a birandom variable to denote the stock return selected by some recurring technical patterns and to study the effect of exit strategy on optimal portfolio selection with birandom returns. Firstly, we propose a new method to estimate the stock return and use birandom distribution to denote the final stock return which can reflect the features of technical patterns and investors' heterogeneity simultaneously; secondly, we build a birandom safety-first model and...

The design strategy of selective PTP1B inhibitors over TCPTP.

Science.gov (United States)

Li, XiangQian; Wang, LiJun; Shi, DaYong

2016-08-15

Protein tyrosine phosphatase 1B (PTP1B) has already been well studied as a highly validated therapeutic target for diabetes and obesity. However, the lack of selectivity limited further studies and clinical applications of PTP1B inhibitors, especially over T-cell protein tyrosine phosphatase (TCPTP). In this review, we enumerate the published specific inhibitors of PTP1B, discuss the structure-activity relationships by analysis of their X-ray structures or docking results, and summarize the characteristic of selectivity related residues and groups. Furthermore, the design strategy of selective PTP1B inhibitors over TCPTP is also proposed. We hope our work could provide an effective way to gain specific PTP1B inhibitors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Strategy for Developing Expert-System-Based Internet Protocols (TCP/IP)

Science.gov (United States)

Ivancic, William D.

1997-01-01

The Satellite Networks and Architectures Branch of NASA's Lewis Research is addressing the issue of seamless interoperability of satellite networks with terrestrial networks. One of the major issues is improving reliable transmission protocols such as TCP over long latency and error-prone links. Many tuning parameters are available to enhance the performance of TCP including segment size, timers and window sizes. There are also numerous congestion avoidance algorithms such as slow start, selective retransmission and selective acknowledgment that are utilized to improve performance. This paper provides a strategy to characterize the performance of TCP relative to various parameter settings in a variety of network environments (i.e. LAN, WAN, wireless, satellite, and IP over ATM). This information can then be utilized to develop expert-system-based Internet protocols.

Evaluation of delivered dose for a clinical daily adaptive plan selection strategy for bladder cancer radiotherapy

International Nuclear Information System (INIS)

Lutkenhaus, Lotte J.; Visser, Jorrit; Jong, Rianne de; Hulshof, Maarten C.C.M.; Bel, Arjan

2015-01-01

Purpose: To account for variable bladder size during bladder cancer radiotherapy, a daily plan selection strategy was implemented. The aim of this study was to calculate the actually delivered dose using an adaptive strategy, compared to a non-adaptive approach. Material and methods: Ten patients were treated to the bladder and lymph nodes with an adaptive full bladder strategy. Interpolated delineations of bladder and tumor on a full and empty bladder CT scan resulted in five PTVs for which VMAT plans were created. Daily cone beam CT (CBCT) scans were used for plan selection. Bowel, rectum and target volumes were delineated on these CBCTs, and delivered dose for these was calculated using both the adaptive plan, and a non-adaptive plan. Results: Target coverage for lymph nodes improved using an adaptive strategy. The full bladder strategy spared the healthy part of the bladder from a high dose. Average bowel cavity V30Gy and V40Gy significantly reduced with 60 and 69 ml, respectively (p < 0.01). Other parameters for bowel and rectum remained unchanged. Conclusions: Daily plan selection compared to a non-adaptive strategy yielded similar bladder coverage and improved coverage for lymph nodes, with a significant reduction in bowel cavity V30Gy and V40Gy only, while other sparing was limited

How Metastrategic Considerations Influence the Selection of Frequency Estimation Strategies

Science.gov (United States)

Brown, Norman R.

2008-01-01

Prior research indicates that enumeration-based frequency estimation strategies become increasingly common as memory for relevant event instances improves and that moderate levels of context memory are associated with moderate rates of enumeration [Brown, N. R. (1995). Estimation strategies and the judgment of event frequency. Journal of…

Optimum Performance Enhancing Strategies of the Gas Turbine Based on the Effective Temperatures

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Ibrahim Thamir K.

2016-01-01

Full Text Available Gas turbines (GT have come to play a significant role in distributed energy systems due to its multi-fuel capability, compact size and low environmental impact and reduced cost. Nevertheless, the low electrical efficiency, typically about 30% (LHV, is an important obstruction to the development of the GT plants. New strategies are designed for the GT plant, to increase the overall performance based on the operational modeling and optimization of GT power plants. The enhancing strategies effect on the GT power plant’s performance (with intercooler, two-shaft, reheat and regenerative based on the real power plant of GT. An analysis based on thermodynamics has been carried out on the modifications of the cycle configurations’ enhancements. Then, the results showed the effect of the ambient and turbine inlet temperatures on the performance of the GT plants to select an optimum strategy for the GT. The performance model code to compare the strategies of the GT plants were developed utilizing the MATLAB software. The results show that, the best thermal efficiency occurs in the intercooler-regenerative-reheated GT strategy (IRHGT; it decreased from 51.5 to 48%, when the ambient temperature increased (from 273 to 327K. Furthermore, the thermal efficiency of the GT for the strategies without the regenerative increased (about 3.3%, while thermal efficiency for the strategies with regenerative increased (about 22% with increased of the turbine inlet temperature. The lower thermal efficiency occurs in the IHGT strategy, while the higher thermal efficiency occurs in the IRHGT strategy. However, the power output variation is more significant at a higher value of the turbine inlet temperature. The simulation model gives a consistent result compared with Baiji GT plant. The extensive modeling performed in this study reveals that; the ambient temperature and turbine inlet temperature are strongly influenced on the performance of GT plant.

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

Science.gov (United States)

Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

2017-07-01

Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

Strategies in Development and Delivery of Nanotechnology Based Cosmetic Products.

Science.gov (United States)

Ahmad, Usama; Ahmad, Zeeshan; Khan, Ahmed Abdullah; Akhtar, Juber; Singh, Satya Prakash; Ahmad, Farhan Jalees

2018-03-26

The science of formulation involving cosmetic ingredients has always been a challenge since the release of active components greatly depends upon the carrier system involved and the selectivity of skin barrier. The principle obstacle of the skin resides in the epidermis and it's hard for many active components to cross it. The formulation related factors like size of particles, viscosity and lipophilicity of the components also play an important role in permeation of the dermal composition. Though widely used; conventional creams and gels still struggle in terms of success. This work focuses on nano based formulation strategies for successful delivery of cosmetic agents. Novel strategies like nanoemulsion, nanogels, liposomes, aquasomes, niosomes, dendrimers and fullerenes have paved way for successful delivery of dermal formulations to desire depths in the skin. © Georg Thieme Verlag KG Stuttgart · New York.

Selection indices for yield and quality traits in sweet corn

International Nuclear Information System (INIS)

Asghar, M.J.; Mehdi, S.S.

2010-01-01

The efficiency of three selection indices, viz., Smith-Hazel index (SHI), Desired gain index (DGI) and Base Index (BI) was compared for the improvement of an open pollinated sweet corn (Zea mays L. Saccharata) population. The data of genetic studies on various yield and quality traits among S1 families were used to construct these selection indices. Smith-Hazel index was found to be the most efficient in improving the aggregate genotype of yield traits for most of the selection strategies. Base index proved to be more efficient as compared to Smith-Hazel index in the improvement of aggregate genotype for five out of six selection strategies of quality traits. Both smith-hazel and Base indices were found useful for the improvement of sweetness and sweet flavour for all the selection strategies. When selection was confined to eight yield and four quality traits simultaneously, Base index proved to be more efficient as compared to Smith-Hazel index and desired gain index in improving the aggregate genotype for almost all the selection strategies. (author)

Cell-Based Strategies for Meniscus Tissue Engineering

Science.gov (United States)

Niu, Wei; Guo, Weimin; Han, Shufeng; Zhu, Yun; Liu, Shuyun; Guo, Quanyi

2016-01-01

Meniscus injuries remain a significant challenge due to the poor healing potential of the inner avascular zone. Following a series of studies and clinical trials, tissue engineering is considered a promising prospect for meniscus repair and regeneration. As one of the key factors in tissue engineering, cells are believed to be highly beneficial in generating bionic meniscus structures to replace injured ones in patients. Therefore, cell-based strategies for meniscus tissue engineering play a fundamental role in meniscal regeneration. According to current studies, the main cell-based strategies for meniscus tissue engineering are single cell type strategies; cell coculture strategies also were applied to meniscus tissue engineering. Likewise, on the one side, the zonal recapitulation strategies based on mimicking meniscal differing cells and internal architectures have received wide attentions. On the other side, cell self-assembling strategies without any scaffolds may be a better way to build a bionic meniscus. In this review, we primarily discuss cell seeds for meniscus tissue engineering and their application strategies. We also discuss recent advances and achievements in meniscus repair experiments that further improve our understanding of meniscus tissue engineering. PMID:27274735

A NEURAL NETWORK BASED TRAFFIC-AWARE FORWARDING STRATEGY IN NAMED DATA NETWORKING

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Parisa Bazmi

2016-11-01

Full Text Available Named Data Networking (NDN is a new Internet architecture which has been proposed to eliminate TCP/IP Internet architecture restrictions. This architecture is abstracting away the notion of host and working based on naming datagrams. However, one of the major challenges of NDN is supporting QoS-aware forwarding strategy so as to forward Interest packets intelligently over multiple paths based on the current network condition. In this paper, Neural Network (NN Based Traffic-aware Forwarding strategy (NNTF is introduced in order to determine an optimal path for Interest forwarding. NN is embedded in NDN routers to select next hop dynamically based on the path overload probability achieved from the NN. This solution is characterized by load balancing and QoS-awareness via monitoring the available path and forwarding data on the traffic-aware shortest path. The performance of NNTF is evaluated using ndnSIM which shows the efficiency of this scheme in terms of network QoS improvementof17.5% and 72% reduction in network delay and packet drop respectively.

Specialist meeting on selected containment severe accident management strategies. Summary and conclusions

International Nuclear Information System (INIS)

1994-01-01

The CSNI Specialist Meeting on Selected Containment Severe Accident Management Strategies held in Stockholm, Sweden in June 1994 was organised by the Task Group on Containment Aspects of Severe Accident Management (CAM) of CSNI's Principal Working Group on the Confinement of Accidental Radioactive Releases (PWG4) in collaboration with the Swedish Nuclear Power Inspectorate (SKI). Conclusions and recommendations are given for each of the sessions of the workshops: Containment accident management strategies (general aspects); hydrogen management techniques and other containment accident management techniques; surveillance and protection of containment function

Credit Rating via Dynamic Slack-Based Measure And It´s Optimal Investment Strategy

Directory of Open Access Journals (Sweden)

A. Delavarkhalafi

2015-01-01

Full Text Available In this paper we check the credit rating of firms applied for a loan. In this regard we introduce a model, named Dynamic Slack-Based Measure (DSBM for measuring credit rating of applicant companies. Selection of financial ratios that represent the financial state of a company -in the best possible way- is one of the most challenging parts of any credit rating analysis. At first, ranking needs to identify the appropriate variables. Therefore we introduce five financial variables to provide a ranking. As noted above, we assess the performance of these firms. Then we introduce the dynamic model of SBM and theorems, also we discuss the overall structure of DSBM. Then we will present the implementation and the simulation model. After that, we propose a stochastic controlled dynamic system model to express the optimal strategy. Banks expect companies selected with DSBM model, act in accordance with this strategy. This stochastic dynamic system is originated from the balance sheets of firms applying for a loan. Finally we evaluate the performance of the system and strategy problem.

Dynamic Portfolio Strategy Using Clustering Approach.

Science.gov (United States)

Ren, Fei; Lu, Ya-Nan; Li, Sai-Ping; Jiang, Xiong-Fei; Zhong, Li-Xin; Qiu, Tian

2017-01-01

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

Dynamic Portfolio Strategy Using Clustering Approach.

Directory of Open Access Journals (Sweden)

Fei Ren

Full Text Available The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

Risk-averse portfolio selection of renewable electricity generator investments in Brazil: An optimised multi-market commercialisation strategy

International Nuclear Information System (INIS)

Maier, Sebastian; Street, Alexandre; McKinnon, Ken

2016-01-01

Investment decisions in renewable energy sources such as small hydro, wind power, biomass and solar are frequently made in the context of enormous uncertainty surrounding both intermittent generation and the highly volatile electricity spot prices that are used for clearing of trades. This paper presents a new portfolio-based approach for selecting long-term investments in small-scale renewable energy projects and matching contracts for the sale of the resulting electricity. Using this approach, we have formulated a stochastic optimisation model that maximises a holding company's risk-averse measure of value. Using an illustrative example representative of investment decisions within the Brazilian electricity system, we investigate the sensitivity of the optimised portfolio composition and commercialisation strategy to contract prices in the free contracting environment and to the decision maker's attitude towards risk. The numerical results demonstrate it is possible to reduce significantly financial risks, such as the price-quantity risk, not only by exploiting the complementarity of the considered renewable sources generation profiles, but also by selecting the optimal mix of commercialisation contracts from different markets. We find that the multi-market strategy generally results in appreciably higher optimal value than single-market strategies and can be applied to a wide range of renewable generators and contracts. - Highlights: • Gives a portfolio-based multi-market, multi-asset approach to renewable investment. • Details how to model currently used contract types in each of the Brazilian markets. • Presents a test case using realistic contract and real renewable data from Brazil. • Shows that the approach controls financial risks and boosts optimal values. • Explains how relative contract prices and attitude to risk affect optimal decisions.

The key role of extinction learning in anxiety disorders: behavioral strategies to enhance exposure-based treatments.

Science.gov (United States)

Pittig, Andre; van den Berg, Linda; Vervliet, Bram

2016-01-01

Extinction learning is a major mechanism for fear reduction by means of exposure. Current research targets innovative strategies to enhance fear extinction and thereby optimize exposure-based treatments for anxiety disorders. This selective review updates novel behavioral strategies that may provide cutting-edge clinical implications. Recent studies provide further support for two types of enhancement strategies. Procedural enhancement strategies implemented during extinction training translate to how exposure exercises may be conducted to optimize fear extinction. These strategies mostly focus on a maximized violation of dysfunctional threat expectancies and on reducing context and stimulus specificity of extinction learning. Flanking enhancement strategies target periods before and after extinction training and inform optimal preparation and post-processing of exposure exercises. These flanking strategies focus on the enhancement of learning in general, memory (re-)consolidation, and memory retrieval. Behavioral strategies to enhance fear extinction may provide powerful clinical applications to further maximize the efficacy of exposure-based interventions. However, future replications, mechanistic examinations, and translational studies are warranted to verify long-term effects and naturalistic utility. Future directions also comprise the interplay of optimized fear extinction with (avoidance) behavior and motivational antecedents of exposure.

Genetic gain and economic values of selection strategies including semen traits in three- and four-way crossbreeding systems for swine production.

Science.gov (United States)

González-Peña, D; Knox, R V; MacNeil, M D; Rodriguez-Zas, S L

2015-03-01

Four semen traits: volume (VOL), concentration (CON), progressive motility of spermatozoa (MOT), and abnormal spermatozoa (ABN) provide complementary information on boar fertility. Assessment of the impact of selection for semen traits is hindered by limited information on economic parameters. Objectives of this study were to estimate economic values for semen traits and to evaluate the genetic gain when these traits are incorporated into traditional selection strategies in a 3-tier system of swine production. Three-way (maternal nucleus lines A and B and paternal nucleus line C) and 4-way (additional paternal nucleus line D) crossbreeding schemes were compared. A novel population structure that accommodated selection for semen traits was developed. Three selection strategies were simulated. Selection Strategy I (baseline) encompassed selection for maternal traits: number of pigs born alive (NBA), litter birth weight (LBW), adjusted 21-d litter weight (A21), and number of pigs at 21 d (N21); and paternal traits: number of days to 113.5 kg (D113), backfat (BF), ADG, feed efficiency (FE), and carcass lean % (LEAN). Selection Strategy II included Strategy I and the number of usable semen doses per collection (DOSES), a function of the 4 semen traits. Selection Strategy III included Strategy I and the 4 semen traits individually. The estimated economic values of VOL, CON, MOT, ABN, and DOSES for 7 to 1 collections/wk ranged from $0.21 to $1.44/mL, $0.12 to $0.83/10 spermatozoa/mm, $0.61 to $12.66/%, -$0.53 to -$10.88/%, and $2.01 to $41.43/%, respectively. The decrease in the relative economic values of semen traits and DOSES with higher number of collections per wk was sharper between 1 and 2.33 collections/wk than between 2.33 and 7 collections/wk. The higher economic value of MOT and ABN relative to VOL and CON could be linked to the genetic variances and covariances of these traits. Average genetic gains for the maternal traits were comparable across strategies

Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms

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Fernando A. Auat Cheein

2013-01-01

Full Text Available Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitrary measurement selection criterion for Gaussian-based algorithms is proposed. The measurement selection criterion is based on the determination of the most significant measurement from both an estimation convergence perspective and the covariance matrix associated with the measurement. The selection criterion is independent from the nature of the measured variable. This criterion is used in conjunction with three Gaussian-based algorithms: the EIF (Extended Information Filter, the EKF (Extended Kalman Filter and the UKF (Unscented Kalman Filter. Nevertheless, the measurement selection criterion shown herein can also be applied to other Gaussian-based algorithms. Although this work is focused on environment modeling, the results shown herein can be applied to other Gaussian-based algorithm implementations. Mathematical descriptions and implementation results that validate the proposal are also included in this work.

An Integrated Approach with Group Decision-Making for Strategy Selection in SWOT Analysis

OpenAIRE

İhsan Yüksel

2012-01-01

The main aim of this study was to improve the analytical dimension of SWOT (strengths, weaknesses, opportunities and threats) analysis with group decision-making, which underlines the analysis of internal and external environments that in turn, will improve the definition of corporate strategy within the strategic planning process. The main issue of the study was how to select the most appropriate strategy by taking into consideration different effects of each factor of SWOT analysis on strat...

Strategies for implementing genomic selection in family-based aquaculture breeding schemes: double haploid sib test populations

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Nirea Kahsay G

2012-10-01

Full Text Available Abstract Background Simulation studies have shown that accuracy and genetic gain are increased in genomic selection schemes compared to traditional aquaculture sib-based schemes. In genomic selection, accuracy of selection can be maximized by increasing the precision of the estimation of SNP effects and by maximizing the relationships between test sibs and candidate sibs. Another means of increasing the accuracy of the estimation of SNP effects is to create individuals in the test population with extreme genotypes. The latter approach was studied here with creation of double haploids and use of non-random mating designs. Methods Six alternative breeding schemes were simulated in which the design of the test population was varied: test sibs inherited maternal (Mat, paternal (Pat or a mixture of maternal and paternal (MatPat double haploid genomes or test sibs were obtained by maximum coancestry mating (MaxC, minimum coancestry mating (MinC, or random (RAND mating. Three thousand test sibs and 3000 candidate sibs were genotyped. The test sibs were recorded for a trait that could not be measured on the candidates and were used to estimate SNP effects. Selection was done by truncation on genome-wide estimated breeding values and 100 individuals were selected as parents each generation, equally divided between both sexes. Results Results showed a 7 to 19% increase in selection accuracy and a 6 to 22% increase in genetic gain in the MatPat scheme compared to the RAND scheme. These increases were greater with lower heritabilities. Among all other scenarios, i.e. Mat, Pat, MaxC, and MinC, no substantial differences in selection accuracy and genetic gain were observed. Conclusions In conclusion, a test population designed with a mixture of paternal and maternal double haploids, i.e. the MatPat scheme, increases substantially the accuracy of selection and genetic gain. This will be particularly interesting for traits that cannot be recorded on the

Implementation strategies and tools for condition based monitoring at nuclear power plants

International Nuclear Information System (INIS)

2007-05-01

There is now an acute need to optimize maintenance to improve both reliability and competitiveness of nuclear power plant operation. There is an increasing tendency to move from the preventive (time based) maintenance concept to one dependent on plant and component conditions. In this context, various on-line and off-line condition monitoring and diagnostics, nondestructive inspection techniques and surveillance are used. Component selection for condition based maintenance, parameter selection for monitoring condition, evaluation of condition monitoring results are issues influencing the effectiveness of condition based maintenance. All these selections of components and parameters to be monitored, monitoring and diagnostics techniques to be used, acceptance criteria and trending for condition evaluation, and the economic aspect of predictive maintenance and condition monitoring should be incorporated into an integrated, effective condition based maintenance programme, which is part of the plant's overall maintenance optimization programme. This publication collects and analyses proven condition based maintenance strategies and techniques (engineering and organizational) in Member States. It includes selected papers on maintenance optimization presented during its preparation. This report was prepared under IAEA project on integrated NPP life cycle management including decommissioning. The main objective of an integrated life cycle management programme is to enable NPP's to compete, without compromising safety, successfully in the changing energy markets throughout their service life and to facilitate life extension and eventual decommissioning through improved engineering, technological, economic and managerial actions. The technical working group on NPP life management and other advisory groups nominated by the Member States provide recommendations on high priority needs of Member States in this area

Selecting the most appropriate maintenance strategies using fuzzy Analytic Network Process: A case study of Saipa vehicle industry

Directory of Open Access Journals (Sweden)

Mina Rahimi

2014-04-01

Full Text Available It is necessary for companies and industries to select the most appropriate maintenance strategy to increase the reliability and safety level with reasonable cost. The primary objective of this paper is to assess different maintenance strategies and to select the best and the most appropriate alternatives for Saipa vehicle industry in Tehran, Iran. For this purpose, we simultaneously consider numerous conflicting objectives and constraints. In this study to counter with this conflicting and to consider the dependency among the qualitative and quantitative criteria and sub-criteria, an integration of Analytic Network Process (ANP and fuzzy set theory are considered. Therefore, factors playing important role in selecting the best maintenance strategy are determined by reviewing the research literature and interviewing with the experts by Delphi technique. Considering the relations among different factors, a network with 4 criteria and 28 sub-criteria are proposed. In the next step, ANP technique is applied for ranking effective factors in evolution of appropriate maintenance strategy. Results reveal that the best maintenance strategy for fixture body of pride (setter is corrective maintenance.

Early Invasive Versus Selective Strategy for Non-ST-Segment Elevation Acute Coronary Syndrome: The ICTUS Trial

NARCIS (Netherlands)

Hoedemaker, N.P.G.; Damman, P.; Woudstra, P.; Hirsch, A.; Windhausen, F.; Tijssen, J.G.; Winter, R.J. de; Verheugt, F.W.A.; et al.,

2017-01-01

BACKGROUND: The ICTUS (Invasive Versus Conservative Treatment in Unstable Coronary Syndromes) trial compared early invasive strategy with a selective invasive strategy in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and an elevated cardiac troponin T. No long-term

Computer-based theory of strategies

Energy Technology Data Exchange (ETDEWEB)

Findler, N V

1983-01-01

Some of the objectives and working tools of a new area of study, tentatively called theory of strategies, are described. It is based on the methodology of artificial intelligence, decision theory, operations research and digital gaming. The latter refers to computing activity that incorporates model building, simulation and learning programs in conflict situations. Three long-term projects which aim at automatically analyzing and synthesizing strategies are discussed. 27 references.

Quantitative learning strategies based on word networks

Science.gov (United States)

Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

2018-02-01

Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

Metasurface-based angle-selective multichannel acoustic refractor

Science.gov (United States)

Liu, Bingyi; Jiang, Yongyuan

2018-05-01

We theoretically study the angle-selective refractions of an impedance-matched acoustic gradient-index metasurface, which is integrated with a rigid bar array of a deep subwavelength period. An interesting refraction order appears under the all-angle incidence despite the existence of a critical angle, and notably, the odevity of the phase-discretization level apparently selects the transmitted diffraction orders. We utilize the strategy of multilayered media design to realize a three-channel acoustic refractor, which shows good promise for constructing multifunctional diffractive acoustic elements for acoustic communication.

Early Invasive Versus Selective Strategy for Non-ST-Segment Elevation Acute Coronary Syndrome: The ICTUS Trial

NARCIS (Netherlands)

Hoedemaker, Niels P. G.; Damman, Peter; Woudstra, Pier; Hirsch, Alexander; Windhausen, Fons; Tijssen, Jan G. P.; de Winter, Robbert J.; Peters, R. J. G.; Dunselman, P. H. J. M.; Verheugt, F. W. A.; Janus, C. L.; Umans, V.; Bendermacher, P. E. F.; Michels, H. R.; Sadé e, A.; Hertzberger, D.; de Miliano, P. A. R. M.; Liem, A. H.; Tjon Joe Gin, R.; van der Linde, M.; Lok, D.; Hoedemaker, G.; Pieterse, M.; van den Merkhof, L.; Danië ls, M.; van Hessen, M.; Hermans, W.; Schotborgh, C. E.; de Zwaan, C.; Bredero, A.; de Jaegere, P.; Janssen, M.; Louwerenburg, J.; Veerhoek, M.; Schalij, M.; de Porto, A.; Zijlstra, F.; Winter, J.; de Feyter, P.; Robles de Medina, R.; Withagen, P.; Sedney, M.; Thijssen, H.; van Rees, C.; van den Bergh, P.; de Cock, C.; van 't Hof, A.; Suttorp, M. J.; Windhausen, F.; Cornel, J. H.

2017-01-01

The ICTUS (Invasive Versus Conservative Treatment in Unstable Coronary Syndromes) trial compared early invasive strategy with a selective invasive strategy in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and an elevated cardiac troponin T. No long-term benefit of an

Radiological protection and the selection of management strategies for intermediate level wastes

International Nuclear Information System (INIS)

Hill, M.D.; Webb, G.A.M.

1982-01-01

This paper describes the steps involved in selecting management systems and an overall management strategy for intermediate level solid radioactive wastes. The radiological protection inputs to intermediate level waste management decisions are discussed, together with the results of preliminary radiological assessments of disposal options. Areas where further work is required are identified. (author)

Strategy-based listening and pragmatic comprehension

Directory of Open Access Journals (Sweden)

Corsetti, Cristiane Ruzicki

2014-01-01

Full Text Available This article addresses the role of strategy-based listening as an alternative methodological approach to develop pragmatic comprehension in L2 contexts. Pragmatic comprehension refers to the understanding of speech acts and conversational implicatures. Listening comprehension comprises both bottom-up and top-down processes. Strategy-based listening encompasses the activation of pragmatic knowledge through pre-listening activities and the development of specific listening micro-skills. An empirical project which included a classroom project carried out with a group of eight learners preparing for the IELTS examination in 2009 corroborated the following assumptions: in order to achieve listening proficiency, learners need practice in making inferences as semantic and pragmatic inferences are embedded in verbal communication; semantic and pragmatic aspects affecting the meaning of utterances can be highlighted via comprehension activities focusing on specific listening subskills. The results of the classroom project suggested that strategy-based listening is potentially capable of directly enhancing pragmatic comprehension but were inconclusive with regards to pragmatic production

Model building strategy for logistic regression: purposeful selection.

Science.gov (United States)

Zhang, Zhongheng

2016-03-01

Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

DEA-BASED INVESTMENT STRATEGY AND ITS APPLICATION IN THE CROATIAN STOCK MARKET

OpenAIRE

Margareta Gardijan; Vedran Kojić

2012-01-01

This paper describes the DEA-based investment strategy for constructing of a stock portfolio in the Croatian stock market. The relative efficiency of the DMUs, which are in this case the selected stocks from Zagreb Stock Exchange, is obtained from the output oriented CCR and BCC models. The set of inputs consists of risk measures, namely return variance, Value at Risk (VaR) and beta coefficient $(\\beta)$, while monthly return represents an output. Following the „efficiency scores“, obtained f...

Knowledge Governance Strategies in Project-based Organizations

DEFF Research Database (Denmark)

Pemsel, Sofia; Müller, Ralf; Söderlund, Jonas

2016-01-01

Knowledge governance (KG) aims at strategically influencing knowledge processes by implementing governance mechanisms. Little is known about whether, how, or why such strategies differ among firms. We utilize a large-scale empirical study of 20 organizations to develop a typology of KG strategies...... in project-based organizations; we then explore how these strategies emerge and affect organizational knowledge processes. Six strategies are identified: Protector, Deliverer, Polisher, Explorer, Supporter, and Analyzer. This paper posits a multi-level categorization model to facilitate comparisons among KG...... strategies. We uncover three main drivers of organizations' chosen knowledge governance strategies-namely, attitudes about humans, knowledge, and knowledge control....

Optimizing complement-activating antibody-based cancer immunotherapy: a feasible strategy?

Directory of Open Access Journals (Sweden)

Maio Michele

2004-06-01

Full Text Available Abstract Passive immunotherapy with monoclonal antibodies (mAb targeted to specific tumor-associated antigens is amongst the most rapidly expanding approaches to biological therapy of cancer. However, until now a limited number of therapeutic mAb has demonstrated clinical efficacy in selected neoplasia. Results emerging from basic research point to a deeper characterization of specific biological features of neoplastic cells as crucial to optimize the clinical potential of therapeutic mAb, and to identify cancer patients who represent the best candidates to antibody-based immunotherapy. Focus on the tissue distribution and on the functional role of membrane complement-regulatory proteins such as Protectin (CD59, which under physiologic conditions protects tissues from Complement (C-damage, might help to optimize the efficacy of immunotherapeutic strategies based on C-activating mAb.

INNOVATION IN ORGANIC CHEMISTRY PRACTICAL WORKS, USING PROBLEM-BASED LEARNING AS TEACHING STRATEGY

OpenAIRE

Miriam G. Acuña; Nora M. Sosa; Eusebia C. Valdez

2011-01-01

This paper presents the teaching strategy known as problem-based learning as an innovation implemented in the practical experiences of the Organic Chemistry course (Bachelor of Genetics), Faculty of Exact, Chemical and Natural Sciences (Universidad Nacional de Misiones, Argentina). It reviews the results of the experience implemented with students, in groups of 7 selected according to their preferences. A problem that required skills in planning, decision making process, thinking, using of ap...

Selective harmonic elimination strategy in eleven level inverter for PV system with unbalanced DC sources

Science.gov (United States)

Ghoudelbourk, Sihem.; Dib, D.; Meghni, B.; Zouli, M.

2017-02-01

The paper deals with the multilevel converters control strategy for photovoltaic system integrated in distribution grids. The objective of the proposed work is to design multilevel inverters for solar energy applications so as to reduce the Total Harmonic Distortion (THD) and to improve the power quality. The multilevel inverter power structure plays a vital role in every aspect of the power system. It is easier to produce a high-power, high-voltage inverter with the multilevel structure. The topologies of multilevel inverter have several advantages such as high output voltage, lower total harmonic distortion (THD) and reduction of voltage ratings of the power semiconductor switching devices. The proposed control strategy ensures an implementation of selective harmonic elimination (SHE) modulation for eleven levels. SHE is a very important and efficient strategy of eliminating selected harmonics by judicious selection of the firing angles of the inverter. Harmonics elimination technique eliminates the need of the expensive low pass filters in the system. Previous research considered that constant and equal DC sources with invariant behavior; however, this research extends earlier work to include variant DC sources, which are typical of lead-acid batteries when used in system PV. This Study also investigates methods to minimize the total harmonic distortion of the synthesized multilevel waveform and to help balance the battery voltage. The harmonic elimination method was used to eliminate selected lower dominant harmonics resulting from the inverter switching action.

The Inertia Weight Updating Strategies in Particle Swarm Optimisation Based on the Beta Distribution

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Petr Maca

2015-01-01

Full Text Available The presented paper deals with the comparison of selected random updating strategies of inertia weight in particle swarm optimisation. Six versions of particle swarm optimization were analysed on 28 benchmark functions, prepared for the Special Session on Real-Parameter Single Objective Optimisation at CEC2013. The random components of tested inertia weight were generated from Beta distribution with different values of shape parameters. The best analysed PSO version is the multiswarm PSO, which combines two strategies of updating the inertia weight. The first is driven by the temporally varying shape parameters, while the second is based on random control of shape parameters of Beta distribution.

Ecological dynamics of age selective harvesting of fish population: Maximum sustainable yield and its control strategy

International Nuclear Information System (INIS)

Jana, Debaldev; Agrawal, Rashmi; Upadhyay, Ranjit Kumar; Samanta, G.P.

2016-01-01

Highlights: • Age-selective harvesting of prey and predator are considered by multi-delayed prey-predator system. • System experiences stable coexistence to oscillatory mode and vice versa via Hopf-bifurcation depending upon the parametric restrictions. • MSY, bionomic equilibrium and optimal harvesting policy are also depending upon the age-selection of prey and predator. • All the analytic results are delay dependent. • Numerical examples support the analytical findings. - Abstract: Life history of ecological resource management and empirical studies are increasingly documenting the impact of selective harvesting process on the evolutionary stable strategy of both aquatic and terrestrial ecosystems. In the present study, the interaction between population and their independent and combined selective harvesting are framed by a multi-delayed prey-predator system. Depending upon the age selection strategy, system experiences stable coexistence to oscillatory mode and vice versa via Hopf-bifurcation. Economic evolution of the system which is mainly featured by maximum sustainable yield (MSY), bionomic equilibrium and optimal harvesting vary largely with the commensurate age selections of both population because equilibrium population abundance becomes age-selection dependent. Our study indicates that balance between harvesting delays and harvesting intensities should be maintained for better ecosystem management. Numerical examples support the analytical findings.

Catch the Best: Novel Screening Strategy to Select Stress Protecting Agents for Crop Plants

Directory of Open Access Journals (Sweden)

Christin Zachow

2013-11-01

Full Text Available Climate change increases stress levels for crops and affects the economic and environmental aspects of agricultural management systems. The application of stress tolerance-mediating microorganisms is an auspicious strategy for improving crop protection, and as such, we developed a direct selection strategy to obtain cultivable microorganisms from promising bioresources using the bait plants, maize, oilseed rape, sorghum and sugar beet. Alpine mosses, lichens and primrose were selected as bioresources, as each is adapted to adverse environmental conditions. A 10% crop-specific selection was found for bait plant rhizosphere communities using cultivation-independent fingerprints, and their potential role as stress protecting agents (SPA was evaluated following the cultivation of captured bacteria. In addition to assays identifying phytopathogen antagonism and plant growth promotion capacities, our evaluation included those that test the ability to allocate nutrients. Moreover, we developed new assays to measure tolerance in diverse stress conditions. A score scheme was applied to select SPAs with desired properties, and three Pseudomonas species with pronounced antagonistic activity that showed elevated tolerance to desiccation and an improved seed germination rate were subsequently chosen. Screening for environmentally-conditioned and host-adapted microorganisms provides a novel tool for target-oriented exploitation of microbial bioresources for the management of ecofriendly crops facing biotic and abiotic stresses.

Influence of learning strategy on response time during complex value-based learning and choice.

Directory of Open Access Journals (Sweden)

Shiva Farashahi

Full Text Available Measurements of response time (RT have long been used to infer neural processes underlying various cognitive functions such as working memory, attention, and decision making. However, it is currently unknown if RT is also informative about various stages of value-based choice, particularly how reward values are constructed. To investigate these questions, we analyzed the pattern of RT during a set of multi-dimensional learning and decision-making tasks that can prompt subjects to adopt different learning strategies. In our experiments, subjects could use reward feedback to directly learn reward values associated with possible choice options (object-based learning. Alternatively, they could learn reward values of options' features (e.g. color, shape and combine these values to estimate reward values for individual options (feature-based learning. We found that RT was slower when the difference between subjects' estimates of reward probabilities for the two alternative objects on a given trial was smaller. Moreover, RT was overall faster when the preceding trial was rewarded or when the previously selected object was present. These effects, however, were mediated by an interaction between these factors such that subjects were faster when the previously selected object was present rather than absent but only after unrewarded trials. Finally, RT reflected the learning strategy (i.e. object-based or feature-based approach adopted by the subject on a trial-by-trial basis, indicating an overall faster construction of reward value and/or value comparison during object-based learning. Altogether, these results demonstrate that the pattern of RT can be informative about how reward values are learned and constructed during complex value-based learning and decision making.

Patch-based visual tracking with online representative sample selection

Science.gov (United States)

Ou, Weihua; Yuan, Di; Li, Donghao; Liu, Bin; Xia, Daoxun; Zeng, Wu

2017-05-01

Occlusion is one of the most challenging problems in visual object tracking. Recently, a lot of discriminative methods have been proposed to deal with this problem. For the discriminative methods, it is difficult to select the representative samples for the target template updating. In general, the holistic bounding boxes that contain tracked results are selected as the positive samples. However, when the objects are occluded, this simple strategy easily introduces the noises into the training data set and the target template and then leads the tracker to drift away from the target seriously. To address this problem, we propose a robust patch-based visual tracker with online representative sample selection. Different from previous works, we divide the object and the candidates into several patches uniformly and propose a score function to calculate the score of each patch independently. Then, the average score is adopted to determine the optimal candidate. Finally, we utilize the non-negative least square method to find the representative samples, which are used to update the target template. The experimental results on the object tracking benchmark 2013 and on the 13 challenging sequences show that the proposed method is robust to the occlusion and achieves promising results.

RNA interference-based therapeutics: new strategies to fight infectious disease.

Science.gov (United States)

López-Fraga, M; Wright, N; Jiménez, A

2008-12-01

For many years, there has been an ongoing search for new compounds that can selectively alter gene expression as a new way to treat human disease by addressing targets that are otherwise "undruggable" with traditional pharmaceutical approaches involving small molecules or proteins. RNA interference (RNAi) strategies have raised a lot of attention and several compounds are currently being tested in clinical trials. Viruses are the obvious target for RNAi-therapy, as most are difficult to treat with conventional drugs, they become rapidly resistant to drug treatment and their genes differ substantially from human genes, minimizing side effects. Antisense strategy offers very high target specificity, i.e., any viral sequence could potentially be targeted using the complementary oligonucleotide sequence. Consequently, new antisense-based therapeutics have the potential to lead a revolution in the anti-infective drug development field. Additionally, the relatively short turnaround for efficacy testing of potential RNAi molecules and that any pathogen is theoretically amenable to rapid targeting, make them invaluable tools for treating a wide range of diseases. This review will focus on some of the current efforts to treat infectious disease with RNAi-based therapies and some of the obstacles that have appeared on the road to successful clinical intervention.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

Science.gov (United States)

Xiang, Lin

incomplete and many relationships among the model ideas had not been well established by the end of the study. Most of them did not treat the natural selection model as a whole but only focused on some ideas within the model. Very few of them could scientifically apply the natural selection model to interpret other evolutionary phenomena. The findings about participating students' programming processes revealed these processes were composed of consecutive programming cycles. The cycle typically included posing a task, constructing and running program codes, and examining the resulting simulation. Students held multiple ideas and applied various programming strategies in these cycles. Students were involved in MBI at each step of a cycle. Three types of ideas, six programming strategies and ten MBI actions were identified out of the processes. The relationships among these ideas, strategies and actions were also identified and described. Findings suggested that ABPM activities could support MBI by (1) exposing students' personal models and understandings, (2) provoking and supporting a series of model-based inquiry activities, such as elaborating target phenomena, abstracting patterns, and revising conceptual models, and (3) provoking and supporting tangible and productive conversations among students, as well as between the instructor and students. Findings also revealed three programming behaviors that appeared to impede productive MBI, including (1) solely phenomenon-orientated programming, (2) transplanting program codes, and (3) blindly running procedures. Based on the findings, I propose a general modeling process in ABPM activities, summarize the ways in which MBI can be supported in ABPM activities and constrained by multiple factors, and suggest the implications of this study in the future ABPM-assisted science instructional design and research.

Theoretical Aspects of Enterprise Business Strategy Formation

OpenAIRE

Valentinavičius, Stasys

2009-01-01

The paper presents interpretations of business strategy concept and analyses strategy planning and formation, models. The concept of business strategy is revised and formulated considering various authors approaches. Analysis of business strategy formation process – steps of development and management, selection of strategy type – is based on presented strategy planning models. The aspects of enterprise business and investment strategy formation, coordination and valuation are analysed. The s...

Investigating the Effectiveness of Teaching Methods Based on a Four-Step Constructivist Strategy

Science.gov (United States)

Çalik, Muammer; Ayas, Alipaşa; Coll, Richard K.

2010-02-01

This paper reports on an investigation of the effectiveness an intervention using several different methods for teaching solution chemistry. The teaching strategy comprised a four-step approach derived from a constructivist view of learning. A sample consisting of 44 students (18 boys and 26 girls) was selected purposively from two different Grade 9 classes in the city of Trabzon, Turkey. Data collection employed a purpose-designed `solution chemistry concept test', consisting of 17 items, with the quantitative data from the survey supported by qualitative interview data. The findings suggest that using different methods embedded within the four-step constructivist-based teaching strategy enables students to refute some alternative conceptions, but does not completely eliminate student alternative conceptions for solution chemistry.

Activity-based in vitro selection of T4 DNA ligase

International Nuclear Information System (INIS)

Takahashi, Fumio; Funabashi, Hisakage; Mie, Masayasu; Endo, Yaeta; Sawasaki, Tatsuya; Aizawa, Masuo; Kobatake, Eiry

2005-01-01

Recent in vitro methodologies for selection and directed evolution of proteins have concentrated not only on proteins with affinity such as single-chain antibody but also on enzymes. We developed a display technology for selection of T4 DNA ligase on ribosome because an in vitro selection method for DNA ligase had never been developed. The 3' end of mRNA encoding the gene of active or inactive T4 DNA ligase-spacer peptide fusion protein was hybridized to dsDNA fragments with cohesive ends, the substrate of T4 DNA ligase. After in vitro translation of the mRNA-dsDNA complex in a rabbit reticulocyte system, a mRNA-dsDNA-ribosome-ligase complex was produced. T4 DNA ligase enzyme displayed on a ribosome, through addition of a spacer peptide, is able to react with dsDNA in the complex. The complex expressing active ligase was biotinylated by ligation with another biotinylated dsDNA probe and selected with streptavidin-coated magnetic beads. We effectively selected active T4 DNA ligase from a small amount of protein. The gene of the active T4 DNA ligase was enriched 40 times from a mixture of active and inactive genes using this selection strategy. This ribosomal display strategy may have high potential to be useful for selection of other enzymes associated with DNA

Strategy-aligned fuzzy approach for market segment evaluation and selection: a modular decision support system by dynamic network process (DNP)

Science.gov (United States)

Mohammadi Nasrabadi, Ali; Hosseinpour, Mohammad Hossein; Ebrahimnejad, Sadoullah

2013-05-01

In competitive markets, market segmentation is a critical point of business, and it can be used as a generic strategy. In each segment, strategies lead companies to their targets; thus, segment selection and the application of the appropriate strategies over time are very important to achieve successful business. This paper aims to model a strategy-aligned fuzzy approach to market segment evaluation and selection. A modular decision support system (DSS) is developed to select an optimum segment with its appropriate strategies. The suggested DSS has two main modules. The first one is SPACE matrix which indicates the risk of each segment. Also, it determines the long-term strategies. The second module finds the most preferred segment-strategies over time. Dynamic network process is applied to prioritize segment-strategies according to five competitive force factors. There is vagueness in pairwise comparisons, and this vagueness has been modeled using fuzzy concepts. To clarify, an example is illustrated by a case study in Iran's coffee market. The results show that success possibility of segments could be different, and choosing the best ones could help companies to be sure in developing their business. Moreover, changing the priority of strategies over time indicates the importance of long-term planning. This fact has been supported by a case study on strategic priority difference in short- and long-term consideration.

Individual-based and group-based occupational exposure assessment: some equations to evaluate different strategies.

NARCIS (Netherlands)

Tielemans, E.; Kupper, L.L.; Kromhout, H.; Heederik, D.; Houba, R.

1998-01-01

Basically, two strategies can be considered for the analysis of hazardous pollutants in the work environment: group-based and individual-based strategies. This paper provides existing and recently derived equations for both strategies describing the influence of several factors on attenuation and on

Stable isotope labeling strategy based on coding theory

Energy Technology Data Exchange (ETDEWEB)

Kasai, Takuma; Koshiba, Seizo; Yokoyama, Jun; Kigawa, Takanori, E-mail: kigawa@riken.jp [RIKEN Quantitative Biology Center (QBiC), Laboratory for Biomolecular Structure and Dynamics (Japan)

2015-10-15

We describe a strategy for stable isotope-aided protein nuclear magnetic resonance (NMR) analysis, called stable isotope encoding. The basic idea of this strategy is that amino-acid selective labeling can be considered as “encoding and decoding” processes, in which the information of amino acid type is encoded by the stable isotope labeling ratio of the corresponding residue and it is decoded by analyzing NMR spectra. According to the idea, the strategy can diminish the required number of labelled samples by increasing information content per sample, enabling discrimination of 19 kinds of non-proline amino acids with only three labeled samples. The idea also enables this strategy to combine with information technologies, such as error detection by check digit, to improve the robustness of analyses with low quality data. Stable isotope encoding will facilitate NMR analyses of proteins under non-ideal conditions, such as those in large complex systems, with low-solubility, and in living cells.

Stable isotope labeling strategy based on coding theory

International Nuclear Information System (INIS)

Kasai, Takuma; Koshiba, Seizo; Yokoyama, Jun; Kigawa, Takanori

2015-01-01

We describe a strategy for stable isotope-aided protein nuclear magnetic resonance (NMR) analysis, called stable isotope encoding. The basic idea of this strategy is that amino-acid selective labeling can be considered as “encoding and decoding” processes, in which the information of amino acid type is encoded by the stable isotope labeling ratio of the corresponding residue and it is decoded by analyzing NMR spectra. According to the idea, the strategy can diminish the required number of labelled samples by increasing information content per sample, enabling discrimination of 19 kinds of non-proline amino acids with only three labeled samples. The idea also enables this strategy to combine with information technologies, such as error detection by check digit, to improve the robustness of analyses with low quality data. Stable isotope encoding will facilitate NMR analyses of proteins under non-ideal conditions, such as those in large complex systems, with low-solubility, and in living cells

Optimization‐based framework for resin selection strategies in biopharmaceutical purification process development

Science.gov (United States)

Liu, Songsong; Gerontas, Spyridon; Gruber, David; Turner, Richard; Titchener‐Hooker, Nigel J.

2017-01-01

This work addresses rapid resin selection for integrated chromatographic separations when conducted as part of a high‐throughput screening exercise during the early stages of purification process development. An optimization‐based decision support framework is proposed to process the data generated from microscale experiments to identify the best resins to maximize key performance metrics for a biopharmaceutical manufacturing process, such as yield and purity. A multiobjective mixed integer nonlinear programming model is developed and solved using the ε‐constraint method. Dinkelbach's algorithm is used to solve the resulting mixed integer linear fractional programming model. The proposed framework is successfully applied to an industrial case study of a process to purify recombinant Fc Fusion protein from low molecular weight and high molecular weight product related impurities, involving two chromatographic steps with eight and three candidate resins for each step, respectively. The computational results show the advantage of the proposed framework in terms of computational efficiency and flexibility. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1116–1126, 2017 PMID:28393478

Hybrid Multiple Soft-Sensor Models of Grinding Granularity Based on Cuckoo Searching Algorithm and Hysteresis Switching Strategy

Directory of Open Access Journals (Sweden)

Jie-Sheng Wang

2015-01-01

Full Text Available According to the characteristics of grinding process and accuracy requirements of technical indicators, a hybrid multiple soft-sensor modeling method of grinding granularity is proposed based on cuckoo searching (CS algorithm and hysteresis switching (HS strategy. Firstly, a mechanism soft-sensor model of grinding granularity is deduced based on the technique characteristics and a lot of experimental data of grinding process. Meanwhile, the BP neural network soft-sensor model and wavelet neural network (WNN soft-sensor model are set up. Then, the hybrid multiple soft-sensor model based on the hysteresis switching strategy is realized. That is to say, the optimum model is selected as the current predictive model according to the switching performance index at each sampling instant. Finally the cuckoo searching algorithm is adopted to optimize the performance parameters of hysteresis switching strategy. Simulation results show that the proposed model has better generalization results and prediction precision, which can satisfy the real-time control requirements of grinding classification process.

Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

Science.gov (United States)

Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

2016-05-01

In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Modelling the consequences of targeted selective treatment strategies on performance and emergence of anthelmintic resistance amongst grazing calves

Directory of Open Access Journals (Sweden)

Zoe Berk

2016-12-01

Full Text Available The development of anthelmintic resistance by helminths can be slowed by maintaining refugia on pasture or in untreated hosts. Targeted selective treatments (TST may achieve this through the treatment only of individuals that would benefit most from anthelmintic, according to certain criteria. However TST consequences on cattle are uncertain, mainly due to difficulties of comparison between alternative strategies. We developed a mathematical model to compare: 1 the most ‘beneficial’ indicator for treatment selection and 2 the method of selection of calves exposed to Ostertagia ostertagi, i.e. treating a fixed percentage of the population with the lowest (or highest indicator values versus treating individuals who exceed (or are below a given indicator threshold. The indicators evaluated were average daily gain (ADG, faecal egg counts (FEC, plasma pepsinogen, combined FEC and plasma pepsinogen, versus random selection of individuals. Treatment success was assessed in terms of benefit per R (BPR, the ratio of average benefit in weight gain to change in frequency of resistance alleles R (relative to an untreated population. The optimal indicator in terms of BPR for fixed percentages of calves treated was plasma pepsinogen and the worst ADG; in the latter case treatment was applied to some individuals who were not in need of treatment. The reverse was found when calves were treated according to threshold criteria, with ADG being the best target indicator for treatment. This was also the most beneficial strategy overall, with a significantly higher BPR value than any other strategy, but its degree of success depended on the chosen threshold of the indicator. The study shows strong support for TST, with all strategies showing improvements on calves treated selectively, compared with whole-herd treatment at 3, 8, 13 weeks post-turnout. The developed model appeared capable of assessing the consequences of other TST strategies on calf populations.

Tissue-engineering-based Strategies for Regenerative Endodontics

Science.gov (United States)

Albuquerque, M.T.P.; Valera, M.C.; Nakashima, M.; Nör, J.E.; Bottino, M.C.

2014-01-01

Stemming from in vitro and in vivo pre-clinical and human models, tissue-engineering-based strategies continue to demonstrate great potential for the regeneration of the pulp-dentin complex, particularly in necrotic, immature permanent teeth. Nanofibrous scaffolds, which closely resemble the native extracellular matrix, have been successfully synthesized by various techniques, including but not limited to electrospinning. A common goal in scaffold synthesis has been the notion of promoting cell guidance through the careful design and use of a collection of biochemical and physical cues capable of governing and stimulating specific events at the cellular and tissue levels. The latest advances in processing technologies allow for the fabrication of scaffolds where selected bioactive molecules can be delivered locally, thus increasing the possibilities for clinical success. Though electrospun scaffolds have not yet been tested in vivo in either human or animal pulpless models in immature permanent teeth, recent studies have highlighted their regenerative potential both from an in vitro and in vivo (i.e., subcutaneous model) standpoint. Possible applications for these bioactive scaffolds continue to evolve, with significant prospects related to the regeneration of both dentin and pulp tissue and, more recently, to root canal disinfection. Nonetheless, no single implantable scaffold can consistently guide the coordinated growth and development of the multiple tissue types involved in the functional regeneration of the pulp-dentin complex. The purpose of this review is to provide a comprehensive perspective on the latest discoveries related to the use of scaffolds and/or stem cells in regenerative endodontics. The authors focused this review on bioactive nanofibrous scaffolds, injectable scaffolds and stem cells, and pre-clinical findings using stem-cell-based strategies. These topics are discussed in detail in an attempt to provide future direction and to shed light on

Activity-Based Information Integrating the operations strategy

Directory of Open Access Journals (Sweden)

José Augusto da Rocha de Araujo

2005-12-01

Full Text Available In the globalized world, companies seek for new operations strategies to ensure world corporate success. This article analyzes how the cost management models – both traditional and activity-based, aid the planning and management of corporate globalized operations. The efficacy of the models application depends on their alignment with the competitive strategy. Companies must evaluate the nature of the competition and its competitive priorities; they should then define the necessary and sufficient dependence level on costs information. In this article, three dependence levels are presented: operational, decision support and strategic control. The result of the research shows the importance of alignment between the cost management model and the competitive strategy for corporate success, and confirms the adequacy of the activity-based costing model as a supporting tool for decision taking in a global strategy. Case studies in world class companies in Brazil are presented.

The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation

International Nuclear Information System (INIS)

Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

2015-01-01

The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy

Application of a collaborative modelling and strategic fuzzy decision support system for selecting appropriate resilience strategies for seaport operations

Directory of Open Access Journals (Sweden)

Andrew John

2014-06-01

Full Text Available The selection of an appropriate resilience investment strategy to optimize the operational efficiency of a seaport is a challenging task given that many criteria need to be considered and modelled under an uncertain environment. The design of such a complex decision system consists of many subjective and imprecise parameters contained in different quantitative and qualitative forms. This paper proposes a fuzzy multi-attribute decision making methodology for the selection of an appropriate resilience investment strategy in a succinct and straightforward manner. The decision support model allows for a collaborative modelling of the system by multiple analysts in a group decision making process. Fuzzy analytical hierarchy process (FAHP was utilized to analyse the complex structure of the system to obtain the weights of all the criteria while fuzzy technique for order of preference by similarity to ideal solution (TOPSIS was employed to facilitate the ranking process of the resilience strategies. Given that it is often financially difficult to invest in all the resilience strategies, it is envisaged that the proposed approach could provide decision makers with a flexible and transparent tool for selecting appropriate resilience strategies aimed at increasing the resilience of seaport operations.

Efficient community-based control strategies in adaptive networks

International Nuclear Information System (INIS)

Yang Hui; Tang Ming; Zhang Haifeng

2012-01-01

Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible–infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible–infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans. (paper)

Strategy for selection of soybean genotypes tolerant to drought during germination.

Science.gov (United States)

Dantas, S A G; Silva, F C S; Silva, L J; Silva, F L

2017-05-10

Water deficit is the main reason for instability in the context of soybean culture. The development of strategies for the selection of more tolerant genotypes is necessary. These strategies include the use of polyethylene glycol 6000 solutions (PEG-6000) for conducting the germination test under conditions of water restriction. Thus, the objective of this study was to determine the osmotic potential and the main characteristics that promote the discrimination of soybean genotypes with regard to water stress tolerance during germination and the vigor test. Thirteen soybean cultivars were used. The seeds were allowed to germinate on sheets of germitest paper moistened in solution with PEG-6000, simulating different levels of water availability, which is expressed as osmotic potential (0.0, -0.2, -0.4, and -0.6 MPa). We assessed germination, length, and dry mass for seedlings and seeds, as well as reserve dynamics. Germination and variables related to the dynamics of reservation have great influence on the expression of variability in environments under stress. Among the different osmotic potentials, the -0.2 MPa was the most efficient for the expression of genetic variability among the cultivars. Conducting the germination test with PEG-6000 solution to -0.2 MPa was efficient for selecting soybean cultivars tolerant to water stress. This was accomplished by evaluating the percentage of germination, along with variables related to the dynamics of reservation.

Sustaining the edge: factors influencing strategy selection in academic health centers.

Science.gov (United States)

Walsh, Anne M; Szabat, Kathryn

2002-01-01

Competition within the acute care sector as well as increased penetration by managed care organizations has influenced the structure and role of academic health centers during the past decade. The market factors confronting academic health centers are not dissimilar from conditions that confront other organizations competing in mature industries characterized by declining profitability and intense rivalry for market share. When confronted with intense competition or adverse external events, organizations in other industries have responded to potential threats by forming alliances, developing joint ventures, or merging with another firm to maintain their competitive advantage. Although mergers and acquisitions dominated the strategic landscape in the healthcare industry during the past decade, recent evidence suggests that other types of strategic ventures may offer similar economic and contracting benefits to member organizations. Academic health centers have traditionally been involved in network relationships with multiple partners via their shared technology, collaborative research, and joint educational endeavors. These quasi-organizational relationships appear to have provided a framework for strategic decisions and allowed executives of academic health centers to select strategies that were competitive yet closely aligned with their organizational mission. The analysis of factors that influenced strategy selection by executives of academic health centers suggests a deliberate and methodical approach to achieving market share objectives, expanding managed care contracts, and developing physician networks.

Trophic strategies of unicellular plankton

DEFF Research Database (Denmark)

Chakraborty, Subhendu; Nielsen, Lasse Tor; Andersen, Ken Haste

2017-01-01

. To this end, we develop and calibrate a trait-based model for unicellular planktonic organisms characterized by four traits: cell size and investments in phototrophy, nutrient uptake, and phagotrophy. We use the model to predict how optimal trophic strategies depend on cell size under various environmental...... unicellulars are colimited by organic carbon and nutrients, and only large photoautotrophs and smaller mixotrophs are nutrient limited; (2) trophic strategy is bottom-up selected by the environment, while optimal size is top-down selected by predation. The focus on cell size and trophic strategies facilitates......Unicellular plankton employ trophic strategies ranging from pure photoautotrophs over mixotrophy to obligate heterotrophs (phagotrophs), with cell sizes from 10-8 to 1 μg C. A full understanding of how trophic strategy and cell size depend on resource environment and predation is lacking...

EEG feature selection method based on decision tree.

Science.gov (United States)

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

2015-01-01

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

Glucose Injections into the Dorsal Hippocampus or Dorsolateral Striatum of Rats Prior to T-Maze Training: Modulation of Learning Rates and Strategy Selection

Science.gov (United States)

Canal, Clinton E.; Stutz, Sonja J.; Gold, Paul E.

2005-01-01

The present experiments examined the effects of injecting glucose into the dorsal hippocampus or dorsolateral striatum on learning rates and on strategy selection in rats trained on a T-maze that can be solved by using either a hippocampus-sensitive place or striatum-sensitive response strategy. Percentage strategy selection on a probe trial…

The selection and adaptation of staff as the basis of the successful implementation of HR strategy

Directory of Open Access Journals (Sweden)

Vanicheva A.G.

2016-11-01

Full Text Available the article deals with questions of effective strategies of HR policy in the field of selection and adaptation of staff in the company. The text gives an information about effective methods of selection and adaptation, also it draws our attention to development of communication between employees. This paper can help to pay managers’ attention to effective selection and adaptation taking into consideration that introduction of a new employee to a position is responsible enough. Probably, first days in a new company are crucial for the system of motivation of HR policy in the development of HR strategy. Much attention is given to stages of adaptation for employee or chief executive.

Strategies of molecular imprinting-based fluorescence sensors for chemical and biological analysis.

Science.gov (United States)

Yang, Qian; Li, Jinhua; Wang, Xiaoyan; Peng, Hailong; Xiong, Hua; Chen, Lingxin

2018-07-30

One pressing concern today is to construct sensors that can withstand various disturbances for highly selective and sensitive detecting trace analytes in complicated samples. Molecularly imprinted polymers (MIPs) with tailor-made binding sites are preferred to be recognition elements in sensors for effective targets detection, and fluorescence measurement assists in highly sensitive detection and user-friendly control. Accordingly, molecular imprinting-based fluorescence sensors (MI-FL sensors) have attracted great research interest in many fields such as chemical and biological analysis. Herein, we comprehensively review the recent advances in MI-FL sensors construction and applications, giving insights on sensing principles and signal transduction mechanisms, focusing on general construction strategies for intrinsically fluorescent or nonfluorescent analytes and improvement strategies in sensing performance, particularly in sensitivity. Construction strategies are well overviewed, mainly including the traditional indirect methods of competitive binding against pre-bound fluorescent indicators, employment of fluorescent functional monomers and embedding of fluorescence substances, and novel rational designs of hierarchical architecture (core-shell/hollow and mesoporous structures), post-imprinting modification, and ratiometric fluorescence detection. Furthermore, MI-FL sensor based microdevices are discussed, involving micromotors, test strips and microfluidics, which are more portable for rapid point-of-care detection and in-field diagnosing. Finally, the current challenges and future perspectives of MI-FL sensors are proposed. Copyright © 2018 Elsevier B.V. All rights reserved.

Range Sensor-Based Efficient Obstacle Avoidance through Selective Decision-Making.

Science.gov (United States)

Shim, Youngbo; Kim, Gon-Woo

2018-03-29

In this paper, we address a collision avoidance method for mobile robots. Many conventional obstacle avoidance methods have been focused solely on avoiding obstacles. However, this can cause instability when passing through a narrow passage, and can also generate zig-zag motions. We define two strategies for obstacle avoidance, known as Entry mode and Bypass mode. Entry mode is a pattern for passing through the gap between obstacles, while Bypass mode is a pattern for making a detour around obstacles safely. With these two modes, we propose an efficient obstacle avoidance method based on the Expanded Guide Circle (EGC) method with selective decision-making. The simulation and experiment results show the validity of the proposed method.

Range Sensor-Based Efficient Obstacle Avoidance through Selective Decision-Making

Directory of Open Access Journals (Sweden)

Youngbo Shim

2018-03-01

Full Text Available In this paper, we address a collision avoidance method for mobile robots. Many conventional obstacle avoidance methods have been focused solely on avoiding obstacles. However, this can cause instability when passing through a narrow passage, and can also generate zig-zag motions. We define two strategies for obstacle avoidance, known as Entry mode and Bypass mode. Entry mode is a pattern for passing through the gap between obstacles, while Bypass mode is a pattern for making a detour around obstacles safely. With these two modes, we propose an efficient obstacle avoidance method based on the Expanded Guide Circle (EGC method with selective decision-making. The simulation and experiment results show the validity of the proposed method.

Instruction of Research-Based Comprehension Strategies in Basal Reading Programs

Science.gov (United States)

Pilonieta, Paola

2010-01-01

Research supports using research-based comprehension strategies; however, comprehension strategy instruction is not highly visible in basal reading programs or classroom instruction, resulting in many students who struggle with comprehension. A content analysis examined which research-based comprehension strategies were presented in five…

Comparison between Exclusive and Selective Drug-Eluting Stent Strategies in Treating Patients with Multivessel Coronary Artery Disease.

Science.gov (United States)

Tung, Ying-Chang; Hsiao, Ping-Gune; Hsu, Lung-An; Kuo, Chi-Tai; Chang, Chi-Jen

2014-05-01

The expanded usage of drug-eluting stents (DES) in treating patients with multivessel coronary artery disease (CAD) may sometimes be limited in real-world practice due to cost concerns. We compared the clinical outcomes of exclusive and selective DES use in treating patients with multivessel CAD. From November 2004 to December 2011, 110 patients with multivessel CAD who received four or more stents were enrolled into this study, and divided into two groups according to the DES strategy employed: exclusive DES (n = 52), or selective DES (n = 58). In the selective DES group, DES was reserved for complex lesions only, such that the incidence and predictors of clinical events were assessed. At a mean follow-up of 41.4 ± 26.5 months, there were no significant differences between the two strategies in terms of baseline characteristics, all-cause mortality (exclusive vs. selective: 1.9% vs. 6.9%, p = 0.21), cardiac death (1.9% vs. 1.7%, p = 0.94) and nonfatal myocardial infarction (3.8% vs. 5.2%, p = 0.74). Despite the presence of more ostial lesions in the exclusive DES group, there was a trend such that major adverse cardiac events (MACE) and target lesion revascularization (TLR) rates were higher in the selective DES group (MACE: 17.3% vs. 31%, p = 0.16; TLR: 11.5% vs. 24.1%, p = 0.08). The higher MACE rate in the selective DES group was mainly driven by a higher target vessel revascularization (TVR) rate (15.4% vs. 29.3%, p = 0.08). In the exclusive DES group, SYNTAX score was an independent predictor of MACE [Haxard ratio (HR): 1.09, 95% confidence internal (CI): 1.02-1.16, p = 0.01] and TVR (HR 1.08, 95% CI 1.01-1.15, p = 0.04). Compared to the exclusive DES strategy, the selective DES strategy with reservation of DES for complex lesions is associated with numerically higher, but not statistically significant, rates of MACE and all-cause mortality in this small group of patients with multivessel CAD receiving four or more stents. Bare metal stent; Drug

Manufacturing strategies for time based competitive advantages

OpenAIRE

Lin, Yong; Ma, Shihua; Zhou, Li

2012-01-01

Purpose – The main purpose of this paper is to investigate the current manufacturing strategies and practices of bus manufacturers in China, and to propose a framework of manufacturing strategies for time-based competitive advantages.\\ud Design/methodology/approach – The conceptual research framework is devised from a review of the literature, and case studies are used to investigate the manufacturing strategies and practices in place in the case companies. Data is collected through semi-stru...

Anionic chromogenic chemosensors highly selective for fluoride or cyanide based on 4-(4-Nitrobenzylideneamine)phenol

Energy Technology Data Exchange (ETDEWEB)

Nicoleti, Celso R; Marini, Vanderleia G; Zimmermann, Lizandra M; Machado, Vanderlei G., E-mail: vanderlei.machado@ufsc.br [Departamento de Quimica, Universidade Federal de Santa Catarina (UFSC), Florianopolis, SC (Brazil)

2012-08-15

4-(4-Nitrobenzylideneamine)phenol was used in two strategies allowing the highly selective detection of F{sup -} and CN{sup -}. Firstly, the compound in acetonitrile acts as a chromogenic chemosensor based on the idea that more basic anions cause its deprotonation (colorless solution), generating a colored solution containing phenolate. The discrimination of CN{sup -} over F{sup -} was obtained by adding 1.4% water to acetonitrile: water preferentially solvates F{sup -}, leaving the CN{sup -} free to deprotonate the compound. Another strategy involved an assay comprised of the competition between phenolate dye and the analyte for calyx[4]pyrrole in acetonitrile, a receptor highly selective for F{sup -}. Phenolate and calyx[4]pyrrole form a hydrogen-bonded complex, which changes the color of the medium. On the addition of various anions, only F{sup -} was able to restore the original color corresponding to phenolate in solution due to the fact that the anion dislodges phenolate from the complexation site. (author)

Anionic chromogenic chemosensors highly selective for fluoride or cyanide based on 4-(4-Nitrobenzylideneamine)phenol

International Nuclear Information System (INIS)

Nicoleti, Celso R.; Marini, Vanderleia G.; Zimmermann, Lizandra M.; Machado, Vanderlei G.

2012-01-01

4-(4-Nitrobenzylideneamine)phenol was used in two strategies allowing the highly selective detection of F - and CN - . Firstly, the compound in acetonitrile acts as a chromogenic chemosensor based on the idea that more basic anions cause its deprotonation (colorless solution), generating a colored solution containing phenolate. The discrimination of CN - over F - was obtained by adding 1.4% water to acetonitrile: water preferentially solvates F - , leaving the CN - free to deprotonate the compound. Another strategy involved an assay comprised of the competition between phenolate dye and the analyte for calyx[4]pyrrole in acetonitrile, a receptor highly selective for F - . Phenolate and calyx[4]pyrrole form a hydrogen-bonded complex, which changes the color of the medium. On the addition of various anions, only F - was able to restore the original color corresponding to phenolate in solution due to the fact that the anion dislodges phenolate from the complexation site. (author)

A semiparametric graphical modelling approach for large-scale equity selection.

Science.gov (United States)

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

Science.gov (United States)

Guthier, Christian V; Damato, Antonio L; Hesser, Juergen W; Viswanathan, Akila N; Cormack, Robert A

2017-12-01

Interstitial high-dose rate (HDR) brachytherapy is an important therapeutic strategy for the treatment of locally advanced gynecologic (GYN) cancers. The outcome of this therapy is determined by the quality of dose distribution achieved. This paper focuses on a novel yet simple heuristic for catheter selection for GYN HDR brachytherapy and their comparison against state of the art optimization strategies. The proposed technique is intended to act as a decision-supporting tool to select a favorable needle configuration. The presented heuristic for catheter optimization is based on a shrinkage-type algorithm (SACO). It is compared against state of the art planning in a retrospective study of 20 patients who previously received image-guided interstitial HDR brachytherapy using a Syed Neblett template. From those plans, template orientation and position are estimated via a rigid registration of the template with the actual catheter trajectories. All potential straight trajectories intersecting the contoured clinical target volume (CTV) are considered for catheter optimization. Retrospectively generated plans and clinical plans are compared with respect to dosimetric performance and optimization time. All plans were generated with one single run of the optimizer lasting 0.6-97.4 s. Compared to manual optimization, SACO yields a statistically significant (P ≤ 0.05) improved target coverage while at the same time fulfilling all dosimetric constraints for organs at risk (OARs). Comparing inverse planning strategies, dosimetric evaluation for SACO and "hybrid inverse planning and optimization" (HIPO), as gold standard, shows no statistically significant difference (P > 0.05). However, SACO provides the potential to reduce the number of used catheters without compromising plan quality. The proposed heuristic for needle selection provides fast catheter selection with optimization times suited for intraoperative treatment planning. Compared to manual optimization, the

Comparison of Different Strategies for Selection/Adaptation of Mixed Microbial Cultures Able to Ferment Crude Glycerol Derived from Second-Generation Biodiesel

Directory of Open Access Journals (Sweden)

C. Varrone

2015-01-01

Full Text Available Objective of this study was the selection and adaptation of mixed microbial cultures (MMCs, able to ferment crude glycerol generated from animal fat-based biodiesel and produce building-blocks and green chemicals. Various adaptation strategies have been investigated for the enrichment of suitable and stable MMC, trying to overcome inhibition problems and enhance substrate degradation efficiency, as well as generation of soluble fermentation products. Repeated transfers in small batches and fed-batch conditions have been applied, comparing the use of different inoculum, growth media, and Kinetic Control. The adaptation of activated sludge inoculum was performed successfully and continued unhindered for several months. The best results showed a substrate degradation efficiency of almost 100% (about 10 g/L glycerol in 21 h and different dominant metabolic products were obtained, depending on the selection strategy (mainly 1,3-propanediol, ethanol, or butyrate. On the other hand, anaerobic sludge exhibited inactivation after a few transfers. To circumvent this problem, fed-batch mode was used as an alternative adaptation strategy, which led to effective substrate degradation and high 1,3-propanediol and butyrate production. Changes in microbial composition were monitored by means of Next Generation Sequencing, revealing a dominance of glycerol consuming species, such as Clostridium, Klebsiella, and Escherichia.

Comparison of Different Strategies for Selection/Adaptation of Mixed Microbial Cultures Able to Ferment Crude Glycerol Derived from Second-Generation Biodiesel.

Science.gov (United States)

Varrone, C; Heggeset, T M B; Le, S B; Haugen, T; Markussen, S; Skiadas, I V; Gavala, H N

2015-01-01

Objective of this study was the selection and adaptation of mixed microbial cultures (MMCs), able to ferment crude glycerol generated from animal fat-based biodiesel and produce building-blocks and green chemicals. Various adaptation strategies have been investigated for the enrichment of suitable and stable MMC, trying to overcome inhibition problems and enhance substrate degradation efficiency, as well as generation of soluble fermentation products. Repeated transfers in small batches and fed-batch conditions have been applied, comparing the use of different inoculum, growth media, and Kinetic Control. The adaptation of activated sludge inoculum was performed successfully and continued unhindered for several months. The best results showed a substrate degradation efficiency of almost 100% (about 10 g/L glycerol in 21 h) and different dominant metabolic products were obtained, depending on the selection strategy (mainly 1,3-propanediol, ethanol, or butyrate). On the other hand, anaerobic sludge exhibited inactivation after a few transfers. To circumvent this problem, fed-batch mode was used as an alternative adaptation strategy, which led to effective substrate degradation and high 1,3-propanediol and butyrate production. Changes in microbial composition were monitored by means of Next Generation Sequencing, revealing a dominance of glycerol consuming species, such as Clostridium, Klebsiella, and Escherichia.

A strategy for clone selection under different production conditions.

Science.gov (United States)

Legmann, Rachel; Benoit, Brian; Fedechko, Ronald W; Deppeler, Cynthia L; Srinivasan, Sriram; Robins, Russell H; McCormick, Ellen L; Ferrick, David A; Rodgers, Seth T; Russo, A Peter

2011-01-01

Top performing clones have failed at the manufacturing scale while the true best performer may have been rejected early in the screening process. Therefore, the ability to screen multiple clones in complex fed-batch processes using multiple process variations can be used to assess robustness and to identify critical factors. This dynamic ranking of clones' strategy requires the execution of many parallel experiments than traditional approaches. Therefore, this approach is best suited for micro-bioreactor models which can perform hundreds of experiments quickly and efficiently. In this study, a fully monitored and controlled small scale platform was used to screen eight CHO clones producing a recombinant monoclonal antibody across several process variations, including different feeding strategies, temperature shifts and pH control profiles. The first screen utilized 240 micro-bioreactors were run for two weeks for this assessment of the scale-down model as a high-throughput tool for clone evaluation. The richness of the outcome data enable to clearly identify the best and worst clone as well as process in term of maximum monoclonal antibody titer. The follow-up comparison study utilized 180 micro-bioreactors in a full factorial design and a subset of 12 clone/process combinations was selected to be run parallel in duplicate shake flasks. Good correlation between the micro-bioreactor predictions and those made in shake flasks with a Pearson correlation value of 0.94. The results also demonstrate that this micro-scale system can perform clone screening and process optimization for gaining significant titer improvements simultaneously. This dynamic ranking strategy can support better choices of production clones. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

Two-dimensional solid-phase extraction strategy for the selective enrichment of aminoglycosides in milk.

Science.gov (United States)

Shen, Aijin; Wei, Jie; Yan, Jingyu; Jin, Gaowa; Ding, Junjie; Yang, Bingcheng; Guo, Zhimou; Zhang, Feifang; Liang, Xinmiao

2017-03-01

An orthogonal two-dimensional solid-phase extraction strategy was established for the selective enrichment of three aminoglycosides including spectinomycin, streptomycin, and dihydrostreptomycin in milk. A reversed-phase liquid chromatography material (C 18 ) and a weak cation-exchange material (TGA) were integrated in a single solid-phase extraction cartridge. The feasibility of two-dimensional clean-up procedure that experienced two-step adsorption, two-step rinsing, and two-step elution was systematically investigated. Based on the orthogonality of reversed-phase and weak cation-exchange procedures, the two-dimensional solid-phase extraction strategy could minimize the interference from the hydrophobic matrix existing in traditional reversed-phase solid-phase extraction. In addition, high ionic strength in the extracts could be effectively removed before the second dimension of weak cation-exchange solid-phase extraction. Combined with liquid chromatography and tandem mass spectrometry, the optimized procedure was validated according to the European Union Commission directive 2002/657/EC. A good performance was achieved in terms of linearity, recovery, precision, decision limit, and detection capability in milk. Finally, the optimized two-dimensional clean-up procedure incorporated with liquid chromatography and tandem mass spectrometry was successfully applied to the rapid monitoring of aminoglycoside residues in milk. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-Regulatory Strategies in Daily Life: Selection, Optimization, and Compensation and Everyday Memory Problems

Science.gov (United States)

Robinson, Stephanie A.; Rickenbach, Elizabeth H.; Lachman, Margie E.

2016-01-01

The effective use of self-regulatory strategies, such as selection, optimization, and compensation (SOC) requires resources. However, it is theorized that SOC use is most advantageous for those experiencing losses and diminishing resources. The present study explored this seeming paradox within the context of limitations or constraints due to…

Selection for Surgical Training: An Evidence-Based Review.

Science.gov (United States)

Schaverien, Mark V

2016-01-01

The predictive relationship between candidate selection criteria for surgical training programs and future performance during and at the completion of training has been investigated for several surgical specialties, however there is no interspecialty agreement regarding which selection criteria should be used. Better understanding the predictive reliability between factors at selection and future performance may help to optimize the process and lead to greater standardization of the surgical selection process. PubMed and Ovid MEDLINE databases were searched. Over 560 potentially relevant publications were identified using the search strategy and screened using the Cochrane Collaboration Data Extraction and Assessment Template. 57 studies met the inclusion criteria. Several selection criteria used in the traditional selection demonstrated inconsistent correlation with subsequent performance during and at the end of surgical training. The following selection criteria, however, demonstrated good predictive relationships with subsequent resident performance: USMLE examination scores, Letters of Recommendation (LOR) including the Medical Student Performance Evaluation (MSPE), academic performance during clinical clerkships, the interview process, displaying excellence in extracurricular activities, and the use of unadjusted rank lists. This systematic review supports that the current selection process needs to be further evaluated and improved. Multicenter studies using standardized outcome measures of success are now required to improve the reliability of the selection process to select the best trainees. Published by Elsevier Inc.

Ethnopharmacological survey: a selection strategy to identify medicinal plants for a local phytotherapy program

Directory of Open Access Journals (Sweden)

Flávia Liparini Pereira

2012-06-01

Full Text Available Ethnopharmacological studies are important for documenting and protecting cultural and traditional knowledge associated with the medical use of biodiversity. In this paper, we present a survey on medicinal plants used by locals in a community of Nova Viçosa, Viçosa, MG, Brazil, as a strategy to select medicinal plants for a phytotherapy-based local healthcare program. Eleven knowledgeable local informants were chosen by snowball sampling and interviewed about the use of medicinal plants. Plant samples were collected, herborised and then identified using traditional techniques and specialised literature. We sampled 107 medicinal plant species belonging to 86 genera and 39 families, predominantly Asteraceae with 16 species. Costus spicatus (Jacq. Sw, M. pulegium L., Rosmarinus officinalis L. and Ruta graveolens L. were found to have Consensus of Main Use corrected (CMUc values above 50%, which were in agreement with the traditional uses described by the informants. However, species with CMUc values equal to or above 20%, combined with the scientific information survey, were also used to select medicinal plants for the phytotherapy-based local healthcare program. The selection of medicinal plants based on the CMUc index from this particular community, in combination with the scientific survey, appears to be an effective strategy for the implementation of phytotherapy programs.Estudos etnofarmacológicos são importantes no registro e na preservação de conhecimentos de uma cultura tradicional associada ao uso medicinal da biodiversidade. No presente trabalho, foi realizado o levantamento das plantas medicinais utilizadas por conhecedores populares na comunidade de Nova Viçosa, Viçosa, Minas Gerais, Brasil, como ferramenta para auxiliar na seleção de espécies vegetais visando à implantação de um programa de fitoterapia local na comunidade estudada. Participaram 11 conhecedores escolhidos por amostragem Bola de Neve e submetidos a

A risk based model supporting long term maintenance and reinvestment strategy decision making

Energy Technology Data Exchange (ETDEWEB)

Sand, Kjell; Montard, Julien; Tremoen, Tord H.

2010-02-15

This Technical Report is a product from the project Risk-Based Distribution System Asset Management (short: RISK DSAM) - Work Package 3 Risk exposure on company/strategic level. In the report a concept for portfolio distribution system asset management is presented. The approach comprises four main steps: 1. Decide the asset base. 2. Divide the asset base into relevant archetypes. 3. Develop or select relevant maintenance and reinvestment strategies for the different archetypes. 4. Estimate risks and costs for each archetype for the relevant strategies. For the different steps guidelines are given and a proposal for implementation of the concept is given in terms of a proposed IT system architecture.To evaluate the feasibility of such a concept, a prototype was developed in by using Visual Basic macros in Excel using real technical data from a small DSO. The experience from using the prototype shows that the concept is realistic. All assets are included and depending of the ambition of the risk analysis both simple simulation models and more advanced might be embedded. Presentations of the concept for a utility engineers have receive positive feedback indicating that the concept is regarded as a practical way to develop risk based asset management strategies for the asset fleet. It should be noted that the concept should be applied on a company strategic level and is thus not designed to be applied for a specific project or asset decisions. For this, more detailed models with area specific information, topology etc. are needed. (Author)

Preferential selection based on degree difference in the spatial prisoner's dilemma games

Science.gov (United States)

Huang, Changwei; Dai, Qionglin; Cheng, Hongyan; Li, Haihong

2017-10-01

Strategy evolution in spatial evolutionary games is generally implemented through imitation processes between individuals. In most previous studies, it is assumed that individuals pick up one of their neighbors randomly to learn from. However, by considering the heterogeneity of individuals' influence in the real society, preferential selection is more realistic. Here, we introduce a preferential selection mechanism based on degree difference into spatial prisoner's dilemma games on Erdös-Rényi networks and Barabási-Albert scale-free networks and investigate the effects of the preferential selection on cooperation. The results show that, when the individuals prefer to choose the neighbors who have small degree difference with themselves to imitate, cooperation is hurt by the preferential selection. In contrast, when the individuals prefer to choose those large degree difference neighbors to learn from, there exists optimal preference strength resulting in the maximal cooperation level no matter what the network structure is. In addition, we investigate the robustness of the results against variations of the noise, the average degree and the size of network in the model, and find that the qualitative features of the results are unchanged.

New detection systems of bacteria using highly selective media designed by SMART: selective medium-design algorithm restricted by two constraints.

Directory of Open Access Journals (Sweden)

Takeshi Kawanishi

Full Text Available Culturing is an indispensable technique in microbiological research, and culturing with selective media has played a crucial role in the detection of pathogenic microorganisms and the isolation of commercially useful microorganisms from environmental samples. Although numerous selective media have been developed in empirical studies, unintended microorganisms often grow on such media probably due to the enormous numbers of microorganisms in the environment. Here, we present a novel strategy for designing highly selective media based on two selective agents, a carbon source and antimicrobials. We named our strategy SMART for highly Selective Medium-design Algorithm Restricted by Two constraints. To test whether the SMART method is applicable to a wide range of microorganisms, we developed selective media for Burkholderia glumae, Acidovorax avenae, Pectobacterium carotovorum, Ralstonia solanacearum, and Xanthomonas campestris. The series of media developed by SMART specifically allowed growth of the targeted bacteria. Because these selective media exhibited high specificity for growth of the target bacteria compared to established selective media, we applied three notable detection technologies: paper-based, flow cytometry-based, and color change-based detection systems for target bacteria species. SMART facilitates not only the development of novel techniques for detecting specific bacteria, but also our understanding of the ecology and epidemiology of the targeted bacteria.

Economics of place-based monitoring under the safe drinking water act, part II: design and development of place-based monitoring strategies.

Science.gov (United States)

Brands, Edwin; Rajagopal, R

2008-08-01

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the United States. In this three part series, spatial and temporal patterns in water quality data are utilized to develop, compare, and evaluate the economic performance of alternative place-based monitoring approaches to current monitoring practice. Part II: Several factors affect the performance of monitoring strategies, including: measurable objectives, required precision in estimates, acceptable confidence levels of such estimates, available budget for sampling. In this paper, we develop place-based monitoring strategies based on extensive analysis of available historical water quality data (1960-1994) of 19 Iowa community water systems. These systems supply potable water to over 350,000 people. In the context of drinking water, the objective is to protect public health by utilizing monitoring resources to characterize contaminants that are detectable, and are close to exceeding health standards. A place-based monitoring strategy was developed in which contaminants were selected based on their historical occurrence, rather than their appearance on the SDWA contaminant list. In a subset of the water systems, the temporal frequency of monitoring for one ubiquitous contaminant, nitrate, was tailored to patterns in its historical occurrence and concentration. Three sampling allocation models (linear, quadratic, and cubic) based on historic patterns in peak occurrence were developed and

An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments

Directory of Open Access Journals (Sweden)

Xiaohong Li

2018-03-01

Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.

Content-based image retrieval: Color-selection exploited

NARCIS (Netherlands)

Broek, E.L. van den; Vuurpijl, L.G.; Kisters, P. M. F.; Schmid, J.C.M. von; Moens, M.F.; Busser, R. de; Hiemstra, D.; Kraaij, W.

2002-01-01

This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

Content-Based Image Retrieval: Color-selection exploited

NARCIS (Netherlands)

Moens, Marie-Francine; van den Broek, Egon; Vuurpijl, L.G.; de Brusser, Rik; Kisters, P.M.F.; Hiemstra, Djoerd; Kraaij, Wessel; von Schmid, J.C.M.

2002-01-01

This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

Reliable Portfolio Selection Problem in Fuzzy Environment: An mλ Measure Based Approach

Directory of Open Access Journals (Sweden)

Yuan Feng

2017-04-01

Full Text Available This paper investigates a fuzzy portfolio selection problem with guaranteed reliability, in which the fuzzy variables are used to capture the uncertain returns of different securities. To effectively handle the fuzziness in a mathematical way, a new expected value operator and variance of fuzzy variables are defined based on the m λ measure that is a linear combination of the possibility measure and necessity measure to balance the pessimism and optimism in the decision-making process. To formulate the reliable portfolio selection problem, we particularly adopt the expected total return and standard variance of the total return to evaluate the reliability of the investment strategies, producing three risk-guaranteed reliable portfolio selection models. To solve the proposed models, an effective genetic algorithm is designed to generate the approximate optimal solution to the considered problem. Finally, the numerical examples are given to show the performance of the proposed models and algorithm.

Implementation of Technology-based Patient Engagement Strategies within Practice-based Research Networks.

Science.gov (United States)

Careyva, Beth; Shaak, Kyle; Mills, Geoffrey; Johnson, Melanie; Goodrich, Samantha; Stello, Brian; Wallace, Lorraine S

2016-01-01

Technology-based patient engagement strategies (such as patient portals) are increasingly available, yet little is known about current use and barriers within practice-based research networks (PBRNs). PBRN directors have unique opportunities to inform the implementation of patient-facing technology and to translate these findings into practice. PBRN directors were queried regarding technology-based patient engagement strategies as part of the 2015 CAFM Educational Research Alliance (CERA) survey of PBRN directors. A total of 102 PBRN directors were identified via the Agency for Healthcare Research and Quality's registry; 54 of 96 eligible PBRN directors completed the survey, for a response rate of 56%. Use of technology-based patient engagement strategies within PBRNs was limited, with less than half of respondents reporting experience with the most frequently named tools (risk assessments/decision aids). Information technology (IT) support was the top barrier, followed by low rates of portal enrollment. For engaging participant practices, workload and practice leadership were cited as most important, with fewer respondents noting concerns about patient privacy. Given limited use of patient-facing technologies, PBRNs have an opportunity to clarify the optimal use of these strategies. Providing IT support and addressing clinician concerns regarding workload may facilitate the inclusion of innovative technologies in PBRNs. © Copyright 2016 by the American Board of Family Medicine.

How to investigate the information processing strategies of students in competence-based pre-vocational secondary education: selection of the right instrument

NARCIS (Netherlands)

Koopman, M.; Teune, P.J.; Beijaard, D.

2012-01-01

In the Netherlands, many Pre-Vocational Secondary Education schools are implementing elements of competence-based education. These learning environments are expected to elicit the use of deep information processing strategies and to positively influence learning outcomes. While questionnaires are

Tailoring the texture of IN738LC processed by selective laser melting (SLM) by specific scanning strategies

Energy Technology Data Exchange (ETDEWEB)

Geiger, Fabian [General Electric Switzerland GmbH – GE Power, CH-5401 Baden (Switzerland); Kunze, Karsten, E-mail: karsten.kunze@scopem.ethz.ch [ETH Zurich, Scientific Center of Optical and Electron Microscopy (ScopeM), CH-8093 Zürich (Switzerland); Etter, Thomas [General Electric Switzerland GmbH – GE Power, CH-5401 Baden (Switzerland)

2016-04-20

Selective laser melting (SLM) is an emerging technology of additive manufacturing, which is used to directly produce metallic parts from thin powder layers. This study aims at correlating laser scanning strategies with the resulting textures and corresponding anisotropy of the elastic behavior of bulk materials. Tensile test specimens made of the γ’-containing Ni-base superalloy IN738LC were built with the loading direction oriented either parallel (z-specimens) or perpendicular to the build-up direction (xy-specimens). Their bulk mechanical properties were determined at room temperature and at 850 °C. Specimens were investigated in the ‘as-built’ condition and after recrystallization heat treatment. SEM-based electron backscatter diffraction (EBSD) was applied to measure their crystallographic preferred orientations (texture) and to correlate the anisotropy of Young's modulus with the texture of the material. It is shown that the applied laser scanning strategies allow to tailor the crystallographic texture locally. The possibility to switch from transverse anisotropic to transverse isotropic properties and reverse is demonstrated for triple layered tensile samples. A recrystallization heat treatment reduces the degree of crystallographic texture and thus the elastic anisotropy by abundant annealing twinning. Predictions of Young's modulus calculated from the measured textures compare well with the data from tensile tests.

Mean value-based power allocation and ratio selection for MIMO cognitive radio systems

KAUST Repository

Tourki, Kamel; Qaraqe, Khalid A.; Alouini, Mohamed-Slim

2013-01-01

In this paper, we consider a spectrum sharing cognitive radio system with ratio selection using a mean value-based power allocation strategy. We first provide the exact statistics in terms of probability density function and cumulative density function of the secondary channel gain as well as of the interference channel gain. These statistics are then used to derive exact closed form expression of the secondary outage probability. Furthermore, asymptotical analysis is derived and generalized diversity gain is deduced. We validate our analysis with simulation results in a Rayleigh fading environment. © 2013 IEEE.

Mean value-based power allocation and ratio selection for MIMO cognitive radio systems

KAUST Repository

Tourki, Kamel

2013-06-01

In this paper, we consider a spectrum sharing cognitive radio system with ratio selection using a mean value-based power allocation strategy. We first provide the exact statistics in terms of probability density function and cumulative density function of the secondary channel gain as well as of the interference channel gain. These statistics are then used to derive exact closed form expression of the secondary outage probability. Furthermore, asymptotical analysis is derived and generalized diversity gain is deduced. We validate our analysis with simulation results in a Rayleigh fading environment. © 2013 IEEE.

A TOTAL MANUFACTURING SOLUTIONS TECHNIQUE TO SELECT APPROPRIATE IMPROVEMENT STRATEGY: CASE STUDY OF A FOOTWEAR FACTORY

Directory of Open Access Journals (Sweden)

Gezahegn Tesfaye

2014-09-01

Full Text Available The Government of Ethiopia is promoting the manufacturing sector to join the global market in a large scale. Due to its comparative advantages, the Ethiopian leather and leather products industry have been given due attention. To fully utilize such advantages, the country shifted its export items from hides/skins to footwear products. Nevertheless, the performance of the leather sector in general and footwear sub-sector in particular is far below the desired standards. The improvement strategies applied hitherto were mainly to tackle a small portion of their total problems. If the Ethiopian footwear companies have to become globally competitive, their entire business spectrum has to be assessed and appropriate improvement strategies must be selected. In this research, we used a Total manufacturing solutions (TMS technique to identify areas of improvement and improvement strategy of one of Ethiopian footwear companies. For this purpose, we conducted two surveys using structured questionnaire. The first survey was to test the TMS technique against the context of footwear industry. The result proved that the original TMS model can be used to measure the performance of footwear companies. The second survey was done to identify company's total problems, map its current position and select appropriate improvement strategy. The result revealed that the company has company-wide problems and its current position is a plodder. For plodders which have company-wide problems, the improvement strategy must include aggressive application of BPR; and the implementation of best practices to develop workers skills that encourages networking and promotion, a market-led manufacturing strategy, employee involvement and team work cultures. According to the findings of this research, we suggested that a BPR technique followed by a continuous improvement programme could be an appropriate improvement strategy for this company. The company requires long-term improvement

Anionic chromogenic chemosensors highly selective for fluoride or cyanide based on 4-(4-Nitrobenzylideneamine)phenol

OpenAIRE

Nicoleti,Celso R.; Marini,Vanderléia G.; Zimmermann,Lizandra M.; Machado,Vanderlei G.

2012-01-01

4-(4-Nitrobenzylideneamine)phenol was used in two strategies allowing the highly selective detection of F- and CN-. Firstly, the compound in acetonitrile acts as a chromogenic chemosensor based on the idea that more basic anions cause its deprotonation (colorless solution), generating a colored solution containing phenolate. The discrimination of CN- over F- was obtained by adding 1.4% water to acetonitrile: water preferentially solvates F-, leaving the CN- free to deprotonate the compound. A...

Repair of Ischemic Injury by Pluripotent Stem Cell Based Cell Therapy without Teratoma through Selective Photosensitivity

Directory of Open Access Journals (Sweden)

Seung-Ju Cho

2015-12-01

Full Text Available Stem-toxic small molecules have been developed to induce selective cell death of pluripotent stem cells (PSCs to lower the risk of teratoma formation. However, despite their high efficacies, chemical-based approaches may carry unexpected toxicities on specific differentiated cell types. Herein, we took advantage of KillerRed (KR as a suicide gene, to selectively induce phototoxicity using visible light via the production of reactive oxygen species. PSCs in an undifferentiated state that exclusively expressed KR (KR-PSCs were eliminated by a single exposure to visible light. This highly selective cell death in KR-PSCs was exploited to successfully inhibit teratoma formation. In particular, endothelial cells from KR-mPSCs remained fully functional in vitro and sufficient to repair ischemic injury in vivo regardless of light exposure, suggesting that a genetic approach in which KR is expressed in a tightly controlled manner would be a viable strategy to inhibit teratoma formation for future safe PSC-based therapies.

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

Energy Technology Data Exchange (ETDEWEB)

Choudhury, Sutanay; Holder, Larry; Chin, George; Agarwal, Khushbu; Feo, John T.

2015-05-27

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving networks spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with prominent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphs in a continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a ``Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named ``Relative Selectivity" that is used to select between different query processing strategies. Our experiments performed on real online news, network traffic stream and a synthetic social network benchmark demonstrate 10-100x speedups over non-incremental, selectivity agnostic approaches.

A universal mini-vector and an annealing of PCR products (APP)-based cloning strategy for convenient molecular biological manipulations.

Science.gov (United States)

Liu, Xia; Li, Tuoping; Hart, Darren J; Gao, Song; Wang, Hongling; Gao, Herui; Xu, Shumin; Zhang, Yifeng; Liu, Yifei; An, Yingfeng

2018-03-18

Currently, the most widely used strategies for molecular cloning are sticky-end ligation-based cloning, TA cloning, blunt-end ligation-based cloning and ligase-independent cloning. In this study we have developed a novel mini-vector pANY1 which can simultaneously meet the requirements of all these cloning strategies. In addition, the selection of appropriate restriction digestion sites is difficult in some cases because of the presence of internal sites. In this study, an annealing of PCR products (APP)-based sticky-end cloning strategy was introduced to avoid this issue. Additionally, false positives occur during molecular cloning, which increases the workload of isolating positive clones. The plasmid pANY1 contains a ccdB cassette between multiple cloning sites, which efficiently avoids these false positives. Therefore, this mini-vector should serve as a useful tool with wide applications in biosciences, agriculture, food technologies, etc. Copyright © 2018 Elsevier Inc. All rights reserved.

A RSSI-based parameter tracking strategy for constrained position localization

Science.gov (United States)

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.

Determining the appropriate strategies for emergency planning through AHP-SWOT.

Science.gov (United States)

Kalatpour, Omid

2017-01-01

During an unexpected incident, companies should demonstrate appropriate behaviour based on predetermined and rehearsed emergency strategies. This paper describes how to select the proper strategies for emergency situations via means of the AHP-SWOT tool, where the initial SWOT analysis is conducted for the emergency management system, and the final strategies are selected via the analytic hierarchy process (AHP). Alternative response strategies comprise internal, shared and external responses. Most of the scenarios investigated for this study demanded a shared response. These findings highlight the importance of mutual aid agreements, cooperative exercises and the improvement of communication systems. Organisations can take advantage of integrated approaches to select the best strategies and tactics for normal situations in general and emergency situations in particular.

Pareto Optimal Solutions for Network Defense Strategy Selection Simulator in Multi-Objective Reinforcement Learning

Directory of Open Access Journals (Sweden)

Yang Sun

2018-01-01

Full Text Available Using Pareto optimization in Multi-Objective Reinforcement Learning (MORL leads to better learning results for network defense games. This is particularly useful for network security agents, who must often balance several goals when choosing what action to take in defense of a network. If the defender knows his preferred reward distribution, the advantages of Pareto optimization can be retained by using a scalarization algorithm prior to the implementation of the MORL. In this paper, we simulate a network defense scenario by creating a multi-objective zero-sum game and using Pareto optimization and MORL to determine optimal solutions and compare those solutions to different scalarization approaches. We build a Pareto Defense Strategy Selection Simulator (PDSSS system for assisting network administrators on decision-making, specifically, on defense strategy selection, and the experiment results show that the Satisficing Trade-Off Method (STOM scalarization approach performs better than linear scalarization or GUESS method. The results of this paper can aid network security agents attempting to find an optimal defense policy for network security games.

Reviewing Clinical Effectiveness of Active Training Strategies of Platform-Based Ankle Rehabilitation Robots

Directory of Open Access Journals (Sweden)

Xiangfeng Zeng

2018-01-01

Full Text Available Objective. This review aims to provide a systematical investigation of clinical effectiveness of active training strategies applied in platform-based ankle robots. Method. English-language studies published from Jan 1980 to Aug 2017 were searched from four databases using key words of “Ankle∗” AND “Robot∗” AND “Effect∗ OR Improv∗ OR Increas∗.” Following an initial screening, three rounds of discrimination were successively conducted based on the title, the abstract, and the full paper. Result. A total of 21 studies were selected with 311 patients involved; of them, 13 studies applied a single group while another eight studies used different groups for comparison to verify the therapeutic effect. Virtual-reality (VR game training was applied in 19 studies, while two studies used proprioceptive neuromuscular facilitation (PNF training. Conclusion. Active training techniques delivered by platform ankle rehabilitation robots have been demonstrated with great potential for clinical applications. Training strategies are mostly combined with one another by considering rehabilitation schemes and motion ability of ankle joints. VR game environment has been commonly used with active ankle training. Bioelectrical signals integrated with VR game training can implement intelligent identification of movement intention and assessment. These further provide the foundation for advanced interactive training strategies that can lead to enhanced training safety and confidence for patients and better treatment efficacy.

ENHANCED DOE HIGH LEVEL WASTE MELTER THROUGHPUT STUDIES: SRNL GLASS SELECTION STRATEGY

Energy Technology Data Exchange (ETDEWEB)

Raszewski, F; Tommy Edwards, T; David Peeler, D

2008-01-23

The Department of Energy has authorized a team of glass formulation and processing experts at the Savannah River National Laboratory (SRNL), the Pacific Northwest National Laboratory (PNNL), and the Vitreous State Laboratory (VSL) at Catholic University of America to develop a systematic approach to increase high level waste melter throughput (by increasing waste loading with minimal or positive impacts on melt rate). This task is aimed at proof-of-principle testing and the development of tools to improve waste loading and melt rate, which will lead to higher waste throughput. Four specific tasks have been proposed to meet these objectives (for details, see WSRC-STI-2007-00483): (1) Integration and Oversight, (2) Crystal Accumulation Modeling (led by PNNL)/Higher Waste Loading Glasses (led by SRNL), (3) Melt Rate Evaluation and Modeling, and (4) Melter Scale Demonstrations. Task 2, Crystal Accumulation Modeling/Higher Waste Loading Glasses is the focus of this report. The objective of this study is to provide supplemental data to support the possible use of alternative melter technologies and/or implementation of alternative process control models or strategies to target higher waste loadings (WLs) for the Defense Waste Processing Facility (DWPF)--ultimately leading to higher waste throughputs and a reduced mission life. The glass selection strategy discussed in this report was developed to gain insight into specific technical issues that could limit or compromise the ability of glass formulation efforts to target higher WLs for future sludge batches at the Savannah River Site (SRS). These technical issues include Al-dissolution, higher TiO{sub 2} limits and homogeneity issues for coupled-operations, Al{sub 2}O{sub 3} solubility, and nepheline formation. To address these technical issues, a test matrix of 28 glass compositions has been developed based on 5 different sludge projections for future processing. The glasses will be fabricated and characterized based on

Supplier selection an MCDA-based approach

CERN Document Server

Mukherjee, Krishnendu

2017-01-01

The purpose of this book is to present a comprehensive review of the latest research and development trends at the international level for modeling and optimization of the supplier selection process for different industrial sectors. It is targeted to serve two audiences: the MBA and PhD student interested in procurement, and the practitioner who wishes to gain a deeper understanding of procurement analysis with multi-criteria based decision tools to avoid upstream risks to get better supply chain visibility. The book is expected to serve as a ready reference for supplier selection criteria and various multi-criteria based supplier’s evaluation methods for forward, reverse and mass customized supply chain. This book encompasses several criteria, methods for supplier selection in a systematic way based on extensive literature review from 1998 to 2012. It provides several case studies and some useful links which can serve as a starting point for interested researchers. In the appendix several computer code wri...

Effect Of Constructivist-Based Teaching Strategy On Academic ...

African Journals Online (AJOL)

Research reports indicate that this negative attitude was caused, majorly, by teachers' conventional (lecture) method of teaching integrated science. Research reports on the effectiveness of constructivist-based teaching strategy revealed that the strategy enhanced students' academic performance. In view of this, this study ...

A high efficiency gene disruption strategy using a positive-negative split selection marker and electroporation for Fusarium oxysporum.

Science.gov (United States)

Liang, Liqin; Li, Jianqiang; Cheng, Lin; Ling, Jian; Luo, Zhongqin; Bai, Miao; Xie, Bingyan

2014-11-01

The Fusarium oxysporum species complex consists of fungal pathogens that cause serial vascular wilt disease on more than 100 cultivated species throughout the world. Gene function analysis is rapidly becoming more and more important as the whole-genome sequences of various F. oxysporum strains are being completed. Gene-disruption techniques are a common molecular tool for studying gene function, yet are often a limiting step in gene function identification. In this study we have developed a F. oxysporum high-efficiency gene-disruption strategy based on split-marker homologous recombination cassettes with dual selection and electroporation transformation. The method was efficiently used to delete three RNA-dependent RNA polymerase (RdRP) genes. The gene-disruption cassettes of three genes can be constructed simultaneously within a short time using this technique. The optimal condition for electroporation is 10μF capacitance, 300Ω resistance, 4kV/cm field strength, with 1μg of DNA (gene-disruption cassettes). Under these optimal conditions, we were able to obtain 95 transformants per μg DNA. And after positive-negative selection, the transformants were efficiently screened by PCR, screening efficiency averaged 85%: 90% (RdRP1), 85% (RdRP2) and 77% (RdRP3). This gene-disruption strategy should pave the way for high throughout genetic analysis in F. oxysporum. Copyright © 2014 Elsevier GmbH. All rights reserved.

Age differences in everyday problem-solving effectiveness: older adults select more effective strategies for interpersonal problems.

Science.gov (United States)

Blanchard-Fields, Fredda; Mienaltowski, Andrew; Seay, Renee Baldi

2007-01-01

Using the Everyday Problem Solving Inventory of Cornelius and Caspi, we examined differences in problem-solving strategy endorsement and effectiveness in two domains of everyday functioning (instrumental or interpersonal, and a mixture of the two domains) and for four strategies (avoidance-denial, passive dependence, planful problem solving, and cognitive analysis). Consistent with past research, our research showed that older adults were more problem focused than young adults in their approach to solving instrumental problems, whereas older adults selected more avoidant-denial strategies than young adults when solving interpersonal problems. Overall, older adults were also more effective than young adults when solving everyday problems, in particular for interpersonal problems.

Strategy community development based on local resources

Science.gov (United States)

Meirinawati; Prabawati, I.; Pradana, G. W.

2018-01-01

The problem of progressing regions is not far from economic problems and is often caused by the inability of the regions in response to changes in economic conditions that occur, so the need for community development programs implemented to solve various problems. Improved community effort required with the real conditions and needs of each region. Community development based on local resources process is very important, because it is an increase in human resource capability in the optimal utilization of local resource potential. In this case a strategy is needed in community development based on local resources. The community development strategy are as follows:(1) “Eight Line Equalization Plus” which explains the urgency of rural industrialization, (2) the construction of the village will be more successful when combining strategies are tailored to regional conditions, (3) the escort are positioning themselves as the Planner, supervisor, information giver, motivator, facilitator, connecting at once evaluators.

Molecularly imprinted fluorescent probe based on FRET for selective and sensitive detection of doxorubicin

Energy Technology Data Exchange (ETDEWEB)

Xu, Zhifeng, E-mail: 897061147@qq.com [College of Chemistry and Materials Science, Hengyang Normal University, Key Laboratory of Functional Organometallic Materials of Hunan Province University, Hengyang 421008 (China); Deng, Peihong; Li, Junhua [College of Chemistry and Materials Science, Hengyang Normal University, Key Laboratory of Functional Organometallic Materials of Hunan Province University, Hengyang 421008 (China); Xu, Li [Department of Applied Chemistry, College of Materials and Energy, South China Agricultural University, Guangzhou 510642 (China); Tang, Siping [College of Chemistry and Materials Science, Hengyang Normal University, Key Laboratory of Functional Organometallic Materials of Hunan Province University, Hengyang 421008 (China)

2017-04-15

Highlights: • FRET-based molecularly imprinted probe for detection of doxorubicin was prepared. • The detection limit of the probe was 13.8 nM for doxorubicin. • The FRET-based probe had a higher selectivity for the template than ordinary MIMs. - Abstract: In this work, a new type of fluorescent probe for detection of doxorubicin has been constructed by the combined use of fluorescence resonance energy transfer (FRET) technology and molecular imprinting technique (MIT). Using doxorubicin as the template, the molecularly imprinted polymer thin layer was fabricated on the surfaces of carbon dot (CD) modified silica by sol-gel polymerization. The excitation energy of the fluorescent donor (CDs) could be transferred to the fluorescent acceptor (doxorubicin). The FRET based fluorescent probe demonstrated high sensitivity and selectivity for doxorubicin. The detection limit was 13.8 nM. The fluorescent probe was successfully applied for detecting doxorubicin in doxorubicin-spiked plasmas with a recovery of 96.8–103.8%, a relative standard deviation (RSD) of 1.3–2.8%. The strategy for construction of FRET-based molecularly imprinted materials developed in this work is very promising for analytical applications.

Efficient selection against categorically scored hip dysplasia in dogs is possible using best linear unbiased prediction and optimum contribution selection: a simulation study

DEFF Research Database (Denmark)

Malm, S; Sørensen, Anders Christian; Fikse, W F

2013-01-01

Breeding to reduce the prevalence of categorically scored hip dysplasia (HD), based on phenotypic assessment of radiographic hip status, has had limited success. The aim of this study was to evaluate two selection strategies for improved hip status: truncation selection based on phenotypic record...

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

Science.gov (United States)

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

Evaluation of a selective management strategy of patients with primary cystic neoplasms of the pancreas

NARCIS (Netherlands)

de Castro, S. M. M.; Houwert, J. T.; van der Gaag, N. A.; Busch, O. R. C.; van Gulik, T. M.; Gouma, D. J.

2011-01-01

Recent studies have shown that a selective group of patients with primary cystic neoplasms of the pancreas can be managed conservatively by radiological follow-up. The aim of this study was to analyze if such a strategy is efficient and safe. A retrospective analyses was performed of patients who

DWFS: A Wrapper Feature Selection Tool Based on a Parallel Genetic Algorithm

KAUST Repository

Soufan, Othman

2015-02-26

Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification models requires identification of suitable combinations of features. The smaller number of features reduces the problem\\'s dimensionality and may result in higher classification performance. We developed DWFS, a web-based tool that allows for efficient selection of features for a variety of problems. DWFS follows the wrapper paradigm and applies a search strategy based on Genetic Algorithms (GAs). A parallel GA implementation examines and evaluates simultaneously large number of candidate collections of features. DWFS also integrates various filteringmethods thatmay be applied as a pre-processing step in the feature selection process. Furthermore, weights and parameters in the fitness function of GA can be adjusted according to the application requirements. Experiments using heterogeneous datasets from different biomedical applications demonstrate that DWFS is fast and leads to a significant reduction of the number of features without sacrificing performance as compared to several widely used existing methods. DWFS can be accessed online at www.cbrc.kaust.edu.sa/dwfs.

DWFS: A Wrapper Feature Selection Tool Based on a Parallel Genetic Algorithm

KAUST Repository

Soufan, Othman; Kleftogiannis, Dimitrios A.; Kalnis, Panos; Bajic, Vladimir B.

2015-01-01

Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification models requires identification of suitable combinations of features. The smaller number of features reduces the problem's dimensionality and may result in higher classification performance. We developed DWFS, a web-based tool that allows for efficient selection of features for a variety of problems. DWFS follows the wrapper paradigm and applies a search strategy based on Genetic Algorithms (GAs). A parallel GA implementation examines and evaluates simultaneously large number of candidate collections of features. DWFS also integrates various filteringmethods thatmay be applied as a pre-processing step in the feature selection process. Furthermore, weights and parameters in the fitness function of GA can be adjusted according to the application requirements. Experiments using heterogeneous datasets from different biomedical applications demonstrate that DWFS is fast and leads to a significant reduction of the number of features without sacrificing performance as compared to several widely used existing methods. DWFS can be accessed online at www.cbrc.kaust.edu.sa/dwfs.

λ-Selection Strategy in C+L Band 1-Pbit/s (448 WDM/19-Core/128 Gbit/s/channel) Flex-Grid Space Division Multiplexed Transmission

DEFF Research Database (Denmark)

Asif, Rameez; Ye, Feihong; Morioka, Toshio

2015-01-01

In this paper, an inter-core crosstalk based wavelength selection scheme has been proposed for flex-grid superchannels in space division multiplexed transmission. The two λ-selection strategies are categorized as: (a) aligned wavelength super-channels (Aλ-SCs), where all super-channels are placed...... at same λ in all the cores and (b) interleaved wavelength super-channels (Iλ-SCs), where all super-channels are placed at different λ in all the neighboring cores. It is depicted that system performance is improved for DP-16QAM channels in 1-Pbit/s (448 WDM/19 Core/128 Gbit/s/channel) 60 km fiber link...

Control Strategies for the DAB Based PV Interface System.

Directory of Open Access Journals (Sweden)

Hadi M El-Helw

Full Text Available This paper presents an interface system based on the Dual Active Bridge (DAB converter for Photovoltaic (PV arrays. Two control strategies are proposed for the DAB converter to harvest the maximum power from the PV array. The first strategy is based on a simple PI controller to regulate the terminal PV voltage through the phase shift angle of the DAB converter. The Perturb and Observe (P&O Maximum Power Point Tracking (MPPT technique is utilized to set the reference of the PV terminal voltage. The second strategy presented in this paper employs the Artificial Neural Network (ANN to directly set the phase shift angle of the DAB converter that results in harvesting maximum power. This feed-forward strategy overcomes the stability issues of the feedback strategy. The proposed PV interface systems are modeled and simulated using MATLAB/SIMULINK and the EMTDC/PSCAD software packages. The simulation results reveal accurate and fast response of the proposed systems. The dynamic performance of the proposed feed-forward strategy outdoes that of the feedback strategy in terms of accuracy and response time. Moreover, an experimental prototype is built to test and validate the proposed PV interface system.

Improving the satellite communication efficiency of the accumulative acknowledgement strategies

Science.gov (United States)

Duarte, Otto Carlos M. B.; de Lima, Heliomar Medeiros

The performances of two finite buffer error recovery strategies are analyzed. In both strategies the retransmission request decision between selective repeat and continuous retransmission is based on an imminent buffer overflow condition. These are accumulative acknowledgment schemes, but in the second strategy the selective-repeat control frame is uniquely an individual negative acknowledgment. The two strategies take advantage of the availability of a greater buffer capacity, making the most of the selective repeat, postponing the sending of a continuous retransmission request. Numerical results show a better performance very close to the ideal, but it does not integrally conform to the high-level data link control (HDLC) procedures. It is shown that these strategies are well suited for high-speed data transfer in the high-error-rate satellite environment.

Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming

Science.gov (United States)

Vercher, Enriqueta

2008-08-01

This paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.

A novel safety assessment strategy applied to non-selective extracts.

Science.gov (United States)

Koster, Sander; Leeman, Winfried; Verheij, Elwin; Dutman, Ellen; van Stee, Leo; Nielsen, Lene Munch; Ronsmans, Stefan; Noteborn, Hub; Krul, Lisette

2015-06-01

A main challenge in food safety research is to demonstrate that processing of foodstuffs does not lead to the formation of substances for which the safety upon consumption might be questioned. This is especially so since food is a complex matrix in which the analytical detection of substances, and consequent risk assessment thereof, is difficult to determine. Here, a pragmatic novel safety assessment strategy is applied to the production of non-selective extracts (NSEs), used for different purposes in food such as for colouring purposes, which are complex food mixtures prepared from reference juices. The Complex Mixture Safety Assessment Strategy (CoMSAS) is an exposure driven approach enabling to efficiently assess the safety of the NSE by focussing on newly formed substances or substances that may increase in exposure during the processing of the NSE. CoMSAS enables to distinguish toxicologically relevant from toxicologically less relevant substances, when related to their respective levels of exposure. This will reduce the amount of work needed for identification, characterisation and safety assessment of unknown substances detected at low concentration, without the need for toxicity testing using animal studies. In this paper, the CoMSAS approach has been applied for elderberry and pumpkin NSEs used for food colouring purposes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bourdieu's Distinction between Rules and Strategies and Secondary Principal Practice: A Review of Selected Literature

Science.gov (United States)

Anderson, Karen

2016-01-01

This paper reviews a selection of literature on secondary principal practice from which to propose an approach for further research. The review demonstrates that applications of Bourdieu's theory of practice have contributed to understandings about secondary principal practice, and that the distinction he made between rules and strategies has the…

A genetic replacement system for selection-based engineering of essential proteins

Science.gov (United States)

2012-01-01

Background Essential genes represent the core of biological functions required for viability. Molecular understanding of essentiality as well as design of synthetic cellular systems includes the engineering of essential proteins. An impediment to this effort is the lack of growth-based selection systems suitable for directed evolution approaches. Results We established a simple strategy for genetic replacement of an essential gene by a (library of) variant(s) during a transformation. The system was validated using three different essential genes and plasmid combinations and it reproducibly shows transformation efficiencies on the order of 107 transformants per microgram of DNA without any identifiable false positives. This allowed for reliable recovery of functional variants out of at least a 105-fold excess of non-functional variants. This outperformed selection in conventional bleach-out strains by at least two orders of magnitude, where recombination between functional and non-functional variants interfered with reliable recovery even in recA negative strains. Conclusions We propose that this selection system is extremely suitable for evaluating large libraries of engineered essential proteins resulting in the reliable isolation of functional variants in a clean strain background which can readily be used for in vivo applications as well as expression and purification for use in in vitro studies. PMID:22898007

Oligonucleotide-based pharmaceuticals: Non-clinical and clinical safety signals and non-clinical testing strategies.

Science.gov (United States)

Mustonen, Enni-Kaisa; Palomäki, Tiina; Pasanen, Markku

2017-11-01

Antisense oligonucleotides, short interfering RNAs (siRNAs) and aptamers are oligonucleotide-based pharmaceuticals with a promising role in targeted therapies. Currently, five oligonucleotide-based pharmaceuticals have achieved marketing authorization in Europe or USA and many more are undergoing clinical testing. However, several safety concerns have been raised in non-clinical and clinical studies. Oligonucleotides share properties with both chemical and biological pharmaceuticals and therefore they pose challenges also from the regulatory point of view. We have analyzed the safety data of oligonucleotides and evaluated the applicability of current non-clinical toxicological guidelines for assessing the safety of oligonucleotide-based pharmaceuticals. Oligonucleotide-based pharmaceuticals display a similar toxicological profile, exerting adverse effects on liver and kidney, evoking hematological alterations, as well as causing immunostimulation and prolonging the coagulation time. It is possible to extrapolate some of these effects from non-clinical studies to humans. However, evaluation strategies for genotoxicity testing of "non-natural" oligonucleotides should be revised. Additionally, the selective use of surrogates and prediction of clinical endpoints for non-clinically observed immunostimulation is complicated by its multiple potential manifestations, demanding improvements in the testing strategies. Utilizing more relevant and mechanistic-based approaches and taking better account of species differences, could possibly improve the prediction of relevant immunological/proinflammatory effects in humans. Copyright © 2017 Elsevier Inc. All rights reserved.

Selecting a risk-based tool to aid in decision making

Energy Technology Data Exchange (ETDEWEB)

Bendure, A.O.

1995-03-01

Selecting a risk-based tool to aid in decision making is as much of a challenge as properly using the tool once it has been selected. Failure to consider customer and stakeholder requirements and the technical bases and differences in risk-based decision making tools will produce confounding and/or politically unacceptable results when the tool is used. Selecting a risk-based decisionmaking tool must therefore be undertaken with the same, if not greater, rigor than the use of the tool once it is selected. This paper presents a process for selecting a risk-based tool appropriate to a set of prioritization or resource allocation tasks, discusses the results of applying the process to four risk-based decision-making tools, and identifies the ``musts`` for successful selection and implementation of a risk-based tool to aid in decision making.

Distributed User Selection in Network MIMO Systems with Limited Feedback

KAUST Repository

Elkhalil, Khalil; Eltayeb, Mohammed E.; Dahrouj, Hayssam; Al-Naffouri, Tareq Y.

2015-01-01

We propose a distributed user selection strategy in a network MIMO setting with M base stations serving K users. Each base station is equipped with L antennas, where LM ≪ K. The conventional selection strategy is based on a well known technique called semi-orthogonal user selection when the zero-forcing beamforming (ZFBF) is adopted. Such technique, however, requires perfect channel state information at the transmitter (CSIT), which might not be available or need large feedback overhead. This paper proposes an alternative distributed user selection technique where each user sets a timer that is inversely proportional to his channel quality indicator (CQI), as a means to reduce the feedback overhead. The proposed strategy allows only the user with the highest CQI to respond with a feedback. Such technique, however, remains collision free only if the transmission time is shorter than the difference between the strongest user timer and the second strongest user timer. To overcome the situation of longer transmission times, the paper proposes another feedback strategy that is based on the theory of compressive sensing, where collision is allowed and all users encode their feedback information and send it back to the base-stations simultaneously. The paper shows that the problem can be formulated as a block sparse recovery problem which is agnostic on the transmission time, which makes it a good alternative to the timer approach when collision is dominant.

Distributed User Selection in Network MIMO Systems with Limited Feedback

KAUST Repository

Elkhalil, Khalil

2015-09-06

We propose a distributed user selection strategy in a network MIMO setting with M base stations serving K users. Each base station is equipped with L antennas, where LM ≪ K. The conventional selection strategy is based on a well known technique called semi-orthogonal user selection when the zero-forcing beamforming (ZFBF) is adopted. Such technique, however, requires perfect channel state information at the transmitter (CSIT), which might not be available or need large feedback overhead. This paper proposes an alternative distributed user selection technique where each user sets a timer that is inversely proportional to his channel quality indicator (CQI), as a means to reduce the feedback overhead. The proposed strategy allows only the user with the highest CQI to respond with a feedback. Such technique, however, remains collision free only if the transmission time is shorter than the difference between the strongest user timer and the second strongest user timer. To overcome the situation of longer transmission times, the paper proposes another feedback strategy that is based on the theory of compressive sensing, where collision is allowed and all users encode their feedback information and send it back to the base-stations simultaneously. The paper shows that the problem can be formulated as a block sparse recovery problem which is agnostic on the transmission time, which makes it a good alternative to the timer approach when collision is dominant.

IPTV program recommendation based on combination strategies

Directory of Open Access Journals (Sweden)

Li Hao

2018-01-01

Full Text Available As a new interactive service technology, IPTV has been extensively studying in the field of TV pro-gram recommendation, but the sparse of the user-program rating matrix and the cold-start problem is a bottleneck that the program recommended accurately. In this paper, a flexible combination of two recommendation strategies proposed, which explored the sparse and cold-start problem as well as the issue of user interest change over time. This paper achieved content-based filtering section and collaborative filtering section according to the two combination strategies, which effectively solved the cold-start program and over the sparse problem and the problem of users interest change over time. The experimental results showed that this combinational recommendation system in optimal parameters compared by using any one of two combination strategies or not using any combination strategy at all, and the reducing range of MAE is [2.7%,3%].The increasing range of precision and recall is [13.8%95.5%] and [0,97.8%], respectively. The experiment showed better results when using combinational recommendation system in optimal parameters than using each combination strategies individually or not using any combination strategy.

Control strategies for VSC-based HVDC transmission system

DEFF Research Database (Denmark)

Stan, Ana-Irina; Stroe, Daniel Ioan; Silva, Rodrigo Da

2011-01-01

Throughout this paper the modeling and control of the VSC-based HVDC systems are investigated and described. Two different control methods capable of controlling such systems are proposed. Both developed control strategies are implemented in the dq synchronous reference frame. In order to analyze...... the behavior of the developed VSC-based HVDC transmission system two study cases are carried out using MATLAB/Simulink. The results obtained from simulations show acceptable performances, of the proposed strategies, when changes in the reference parameters are considered. The active power flow between...

Confirming preferences or collecting data? Information search strategies and romantic partner selection.

Science.gov (United States)

Hennessy, Michael H; Fishbein, Marty; Curtis, Brenda; Barrett, Daniel

2008-03-01

This article investigates two kinds of information search strategies in the context of selecting romantic partners. Confirmatory searching occurs when people ask for more information about a romantic partner in order to validate or confirm their assessment. Balanced searches are characterized by a search for risk information for partners rated as attractive and for attractiveness information about partners rated as risky in order to attain a more complete evaluation. A factorial survey computer program randomly constructed five types of partner descriptions and college-age respondents evaluated nine descriptions in terms of both health risk and romantic attractiveness outcomes. The results show little evidence of balanced search strategies: for all vignette types the respondents searched for attractiveness information. Regression analysis of the search outcomes showed no difference between males and females in the desire for attractiveness or risk information, the amount of additional information desired, or the proportion of descriptions for which more information was desired. However, an attractive physical appearance did increase the amount of additional information desired and the proportion of vignettes for which more information was desired. The results were generally inconsistent with a balanced search hypothesis; a better characterization of the respondents' strategy might be "confirmatory bias."

Distance based control system for machine vision-based selective spraying

NARCIS (Netherlands)

Steward, B.L.; Tian, L.F.; Tang, L.

2002-01-01

For effective operation of a selective sprayer with real-time local weed sensing, herbicides must be delivered, accurately to weed targets in the field. With a machine vision-based selective spraying system, acquiring sequential images and switching nozzles on and off at the correct locations are

Information access in a dual-task context: testing a model of optimal strategy selection

Science.gov (United States)

Wickens, C. D.; Seidler, K. S.

1997-01-01

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

Breaking the color barrier - a multi-selective antibody reporter offers innovative strategies of fluorescence detection.

Science.gov (United States)

Gallo, Eugenio; Jarvik, Jonathan W

2017-08-01

A novel bi-partite fluorescence platform exploits the high affinity and selectivity of antibody scaffolds to capture and activate small-molecule fluorogens. In this report, we investigated the property of multi-selectivity activation by a single antibody against diverse cyanine family fluorogens. Our fluorescence screen identified three cell-impermeant fluorogens, each with unique emission spectra (blue, green and red) and nanomolar affinities. Most importantly, as a protein fusion tag to G-protein-coupled receptors, the antibody biosensor retained full activity - displaying bright fluorogen signals with minimal background on live cells. Because fluorogen-activating antibodies interact with their target ligands via non-covalent interactions, we were able to perform advanced multi-color detection strategies on live cells, previously difficult or impossible with conventional reporters. We found that by fine-tuning the concentrations of the different color fluorogen molecules in solution, a user may interchange the fluorescence signal (onset versus offset), execute real-time signal exchange via fluorogen competition, measure multi-channel fluorescence via co-labeling, and assess real-time cell surface receptor traffic via pulse-chase experiments. Thus, here we inform of an innovative reporter technology based on tri-color signal that allows user-defined fluorescence tuning in live-cell applications. © 2017. Published by The Company of Biologists Ltd.

Genome-based nutrition: An intervention strategy for the prevention and treatment of obesity and nonalcoholic steatohepatitis

Science.gov (United States)

Roman, Sonia; Ojeda-Granados, Claudia; Ramos-Lopez, Omar; Panduro, Arturo

2015-01-01

Obesity and nonalcoholic steatohepatitis are increasing in westernized countries, regardless of their geographic location. In Latin America, most countries, including Mexico, have a heterogeneous admixture genome with Amerindian, European and African ancestries. However, certain high allelic frequencies of several nutrient-related polymorphisms may have been achieved by past gene-nutrient interactions. Such interactions may have promoted the positive selection of variants adapted to regional food sources. At present, the unbalanced diet composition of the Mexicans has led the country to a 70% prevalence rate of overweightness and obesity due to substantial changes in food habits, among other factors. International guidelines and intervention strategies may not be adequate for all populations worldwide because they do not consider disparities in genetic and environmental factors, and thus there is a need for differential prevention and management strategies. Here, we provide the rationale for an intervention strategy for the prevention and management of obesity-related diseases such as non-alcoholic steatohepatitis based on a regionalized genome-based diet. The components required to design such a diet should focus on the specific ancestry of each population around the world and the convenience of consuming traditional ethnic food. PMID:25834309

Selection of nursing teaching strategies in mainland China: A questionnaire survey.

Science.gov (United States)

Zhou, HouXiu; Liu, MengJie; Zeng, Jing; Zhu, JingCi

2016-04-01

In nursing education, the traditional lecture and direct demonstration teaching method cannot cultivate the various skills that nursing students need. How to choose a more scientific and rational teaching method is a common concern for nursing educators worldwide. To investigate the basis for selecting teaching methods among nursing teachers in mainland China, the factors affecting the selection of different teaching methods, and the application of different teaching methods in theoretical and skill-based nursing courses. Questionnaire survey. Seventy one nursing colleges from 28 provincial-level administrative regions in mainland China. Following the principle of voluntary informed consent, 262 nursing teachers were randomly selected through a nursing education network platform and a conference platform. The questionnaire contents included the basis for and the factors influencing the selection of nursing teaching methods, the participants' common teaching methods, and the teaching experience of the surveyed nursing teachers. The questionnaires were distributed through the network or conference platform, and the data were analyzed by SPSS 17.0 software. The surveyed nursing teachers selected teaching methods mainly based on the characteristics of the teaching content, the characteristics of the students, and their previous teaching experiences. The factors affecting the selection of teaching methods mainly included large class sizes, limited class time, and limited examination formats. The surveyed nursing teachers primarily used lectures to teach theory courses and the direct demonstration method to teach skills courses, and the application frequencies of these two teaching methods were significantly higher than those of other teaching methods (P=0.000). More attention should be paid to the selection of nursing teaching methods. Every teacher should strategically choose teaching methods before each lesson, and nursing education training focused on selecting

Development of an operation strategy for hydrogen production using solar PV energy based on fluid dynamic aspects

Directory of Open Access Journals (Sweden)

Amores Ernesto

2017-06-01

Full Text Available Alkaline water electrolysis powered by renewable energy sources is one of the most promising strategies for environmentally friendly hydrogen production. However, wind and solar energy sources are highly dependent on weather conditions. As a result, power fluctuations affect the electrolyzer and cause several negative effects. Considering these limiting effects which reduce the water electrolysis efficiency, a novel operation strategy is proposed in this study. It is based on pumping the electrolyte according to the current density supplied by a solar PV module, in order to achieve the suitable fluid dynamics conditions in an electrolysis cell. To this aim, a mathematical model including the influence of electrode-membrane distance, temperature and electrolyte flow rate has been developed and used as optimization tool. The obtained results confirm the convenience of the selected strategy, especially when the electrolyzer is powered by renewable energies.

Design Strategies for Aptamer-Based Biosensors

Science.gov (United States)

Han, Kun; Liang, Zhiqiang; Zhou, Nandi

2010-01-01

Aptamers have been widely used as recognition elements for biosensor construction, especially in the detection of proteins or small molecule targets, and regarded as promising alternatives for antibodies in bioassay areas. In this review, we present an overview of reported design strategies for the fabrication of biosensors and classify them into four basic modes: target-induced structure switching mode, sandwich or sandwich-like mode, target-induced dissociation/displacement mode and competitive replacement mode. In view of the unprecedented advantages brought about by aptamers and smart design strategies, aptamer-based biosensors are expected to be one of the most promising devices in bioassay related applications. PMID:22399891

Impact of selective genotyping in the training population on accuracy and bias of genomic selection.

Science.gov (United States)

Zhao, Yusheng; Gowda, Manje; Longin, Friedrich H; Würschum, Tobias; Ranc, Nicolas; Reif, Jochen C

2012-08-01

Estimating marker effects based on routinely generated phenotypic data of breeding programs is a cost-effective strategy to implement genomic selection. Truncation selection in breeding populations, however, could have a strong impact on the accuracy to predict genomic breeding values. The main objective of our study was to investigate the influence of phenotypic selection on the accuracy and bias of genomic selection. We used experimental data of 788 testcross progenies from an elite maize breeding program. The testcross progenies were evaluated in unreplicated field trials in ten environments and fingerprinted with 857 SNP markers. Random regression best linear unbiased prediction method was used in combination with fivefold cross-validation based on genotypic sampling. We observed a substantial loss in the accuracy to predict genomic breeding values in unidirectional selected populations. In contrast, estimating marker effects based on bidirectional selected populations led to only a marginal decrease in the prediction accuracy of genomic breeding values. We concluded that bidirectional selection is a valuable approach to efficiently implement genomic selection in applied plant breeding programs.

New Market Business Strategies : a comparative study of selected Norwegian entrepreneurial companies

OpenAIRE

Tiltnes, Anders Arnesen

2012-01-01

This thesis is based on two assumptions: that disruptive technology changes the conditions of how new businesses are created, and that effective management methods and the adaption of internet facilitate an increasingly more rapid change in most markets. This thesis argues that any company doing business in a segmented or a new market (i.e. an entrepreneurial company) could consider using a new market business strategy. This thesis introduces the term New Market Business Strategy as a ge...

Strategy2D: Turn-based Strategy Video Game Engine for Mobile Devices

OpenAIRE

Calvo Villazón, Javier

2014-01-01

Multi-platform video game engine for the development of turn-based strategy games for mobile devices. Developed in C++ within the Cocos2d-x framework, It provides a scalable and configurable tool for the creation of this type of games.

Application of Q-learning with temperature variation for bidding strategies in market based power systems

International Nuclear Information System (INIS)

Naghibi-Sistani, M.B.; Akbarzadeh-Tootoonchi, M.R.; Javidi-Dashte Bayaz, M.H.; Rajabi-Mashhadi, H.

2006-01-01

The electric power industry is confronted with restructuring in which the operation scheduling is going to be decided based on a competitive market. In this new arrangement, bidding strategy has become a major issue. Participants in this deregulated energy market place may be able to compete better by choosing a suitable bidding strategy for trading electricity. Different classical methods for decision making in the uncertain environment of the market can be applied to select a suitable strategy. Most of these methods, such as game theory, that insure reaching the best solution for all market participants, require a lot of information about the other market players and the market. However, in the real market place only a little information, such as the spot price, is available for all participants. In this paper, a modified reinforcement learning based on temperature variation has been first proposed and then applied to determine the optimal strategy for a power supplier in the electricity market. A Pool-Co model has been considered here, and the simulation results are shown to be the same as those of standard game theory. Adaptation of the method in the presence of parameter variation has been verified as well. The main advantage of the proposed method is that no information about other participants is required. Furthermore, our investigation shows that even if all participants use this method, they will stay in Nash equilibrium. (author)

Personnel Selection Based on Fuzzy Methods

Directory of Open Access Journals (Sweden)

Lourdes Cañós

2011-03-01

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

NetProt: Complex-based Feature Selection.

Science.gov (United States)

Goh, Wilson Wen Bin; Wong, Limsoon

2017-08-04

Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

Strategy selection in the minority game

Science.gov (United States)

D'hulst, R.; Rodgers, G. J.

2000-04-01

We investigate the dynamics of the choice of an active strategy in the minority game. A history distribution is introduced as an analytical tool to study the asymmetry between the two choices offered to the agents. Its properties are studied numerically. It allows us to show that the departure from uniformity in the initial attribution of strategies to the agents is important even in the efficient market. Also, an approximate expression for the variance of the number of agents at one side in the efficient phase is proposed. All the analytical propositions are supported by numerical simulations of the system.

A high-throughput screening strategy for nitrile-hydrolyzing enzymes based on ferric hydroxamate spectrophotometry.

Science.gov (United States)

He, Yu-Cai; Ma, Cui-Luan; Xu, Jian-He; Zhou, Li

2011-02-01

Nitrile-hydrolyzing enzymes (nitrilase or nitrile hydratase/amidase) have been widely used in the pharmaceutical industry for the production of carboxylic acids and their derivatives, and it is important to build a method for screening for nitrile-hydrolyzing enzymes. In this paper, a simple, rapid, and high-throughput screening method based on the ferric hydroxamate spectrophotometry has been proposed. To validate the accuracy of this screening strategy, the nitrilases from Rhodococcus erythropolis CGMCC 1.2362 and Alcaligenes sp. ECU0401 were used for evaluating the method. As a result, the accuracy for assaying aliphatic and aromatic carboxylic acids was as high as the HPLC-based method. Therefore, the method may be potentially used in the selection of microorganisms or engineered proteins with nitrile-hydrolyzing enzymes.

Development of a qPCR strategy to select bean genes involved in plant defence response and regulated by the Trichoderma velutinum - Rhizoctonia solani interaction

Directory of Open Access Journals (Sweden)

Sara Mayo

2016-08-01

Full Text Available Bean production is affected by a wide diversity of fungal pathogens, among them Rhizoctonia solani is one of the most important. A strategy to control bean infectious diseases, mainly those caused by fungi, is based on the use of biocontrol agents that can reduce the negative effects of plant pathogens and also can promote positive responses in the plant. Trichoderma is a fungal genus that is able to induce the expression of genes involved in plant defence response and also to promote plant growth, root development and nutrient uptake. In this article, a strategy that combines in silico analysis and real time PCR to detect additional bean defence-related genes, regulated by the presence of Trichoderma velutinum and/or R. solani has been applied. Based in this strategy, from From the 48 bean genes initially analysed, 14 were selected, and only WRKY33, CH5b and hGS showed an up-regulatory response in the presence of T. velutinum. The other genes were or not affected (OSM34 or down-regulated by the presence of this fungus. R. solani infection resulted in a down-regulation of most of the genes analyzed, except PR1, OSM34 and CNGC2 that were not affected, and the presence of both, T. velutinum and R. solani, up-regulates hGS and down-regulates all the other genes analyzed, except CH5b which was not significantly affected.As conclusion, the strategy described in the present work has been shown to be effective to detect genes involved in plant defence, which respond to the presence of a biocontrol agent or to a pathogen and also to the presence of both. The selected genes show significant homology with previously described plant defence genes and they are expressed in bean leaves of plants treated with T. velutinum and/or infected with R. solani.

Modelling the impacts of pasture contamination and stocking rate for the development of targeted selective treatment strategies for Ostertagia ostertagi infection in calves

OpenAIRE

Berk, Zoe; Laurenson, Yan C.S.M.; Forbes, Andrew B.; Kyriazakis, Ilias

2017-01-01

A simulation study was carried out to assess whether variation in pasture contamination or stocking rate impact upon the optimal design of targeted selective treatment (TST) strategies. Two methods of TST implementation were considered: 1) treatment of a fixed percentage of a herd according to a given phenotypic trait, or 2) treatment of individuals that exceeded a threshold value for a given phenotypic trait. Four phenotypic traits, on which to base treatment were considered: 1) average dail...

Rule-based energy management strategies for hybrid vehicles

NARCIS (Netherlands)

Hofman, T.; Druten, van R.M.; Serrarens, A.F.A.; Steinbuch, M.

2007-01-01

Int. J. of Electric and Hybrid Vehicles (IJEHV), The highest control layer of a (hybrid) vehicular drive train is termed the Energy Management Strategy (EMS). In this paper an overview of different control methods is given and a new rule-based EMS is introduced based on the combination of Rule-Based

Identifying and ranking implicit leadership strategies to promote evidence-based practice implementation in addiction health services.

Science.gov (United States)

Guerrero, Erick G; Padwa, Howard; Fenwick, Karissa; Harris, Lesley M; Aarons, Gregory A

2016-05-14

Despite a solid research base supporting evidence-based practices (EBPs) for addiction treatment such as contingency management and medication-assisted treatment, these services are rarely implemented and delivered in community-based addiction treatment programs in the USA. As a result, many clients do not benefit from the most current and efficacious treatments, resulting in reduced quality of care and compromised treatment outcomes. Previous research indicates that addiction program leaders play a key role in supporting EBP adoption and use. The present study expanded on this previous work to identify strategies that addiction treatment program leaders report using to implement new practices. We relied on a staged and iterative mixed-methods approach to achieve the following four goals: (a) collect data using focus groups and semistructured interviews and conduct analyses to identify implicit managerial strategies for implementation, (b) use surveys to quantitatively rank strategy effectiveness, (c) determine how strategies fit with existing theories of organizational management and change, and (d) use a consensus group to corroborate and expand on the results of the previous three stages. Each goal corresponded to a methodological phase, which included data collection and analytic approaches to identify and evaluate leadership interventions that facilitate EBP implementation in community-based addiction treatment programs. Findings show that the top-ranked strategies involved the recruitment and selection of staff members receptive to change, offering support and requesting feedback during the implementation process, and offering in vivo and hands-on training. Most strategies corresponded to emergent implementation leadership approaches that also utilize principles of transformational and transactional leadership styles. Leadership behaviors represented orientations such as being proactive to respond to implementation needs, supportive to assist staff members

A novel microfluidic origami photoelectrochemical sensor based on CdTe quantum dots modified molecularly imprinted polymer and its highly selective detection of S-fenvalerate

International Nuclear Information System (INIS)

Wang, Yanhu; Zang, Dejin; Ge, Shenguang; Ge, Lei; Yu, Jinghua; Yan, Mei

2013-01-01

Driven by the urgent demand of high-selectively point-of-care testing device for pesticide, molecular imprinting-photoelectrochemistry (MI-PEC) was introduced into microfluidic paper-based analytical strategy to design a novel paper-based photoelectrochemical (paper-based PEC) protocol. The MI-PEC strategy was constructed based on CdTe quantum dots dotted molecular imprinted polymers (CdTe QDs@MIPs), and triggered by a common ultraviolet lamp (∼365 nm, 50$). The paper-based PEC sensor was fabricated by immobilizing CdTe QDs@MIPs on paper-based screen-printed working electrodes (WEs) via gold nanoparticles (Au NPs), which was electrodeposited on the surface of WE to improve the electron transfer efficiency for high sensitivity. Using S-fenvalerate as model analyte, the produced photocurrent from the proposed paper-based MI-PEC sensor upon ultraviolet radiation decreased with the increasing concentrations of S-fenvalerate solution, and the quenched paper-based MI-PEC showed a low detection limit of 3.2 × 10 −9 mol L −1 . This study has made a successful attempt in the development of highly selective and sensitive photoelectrochemical sensor for S-fenvalerate monitoring

Multidisciplinary perspectives for Alzheimer's and Parkinson's diseases: hydrogels for protein delivery and cell-based drug delivery as therapeutic strategies.

Science.gov (United States)

Giordano, Carmen; Albani, Diego; Gloria, Antonio; Tunesi, Marta; Batelli, Sara; Russo, Teresa; Forloni, Gianluigi; Ambrosio, Luigi; Cigada, Alberto

2009-12-01

This review presents two intriguing multidisciplinary strategies that might make the difference in the treatment of neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. The first proposed strategy is based on the controlled delivery of recombinant proteins known to play a key role in these neurodegenerative disorders that are released in situ by optimized polymer-based systems. The second strategy is the use of engineered cells, encapsulated and delivered in situ by suitable polymer-based systems, that act as drug reservoirs and allow the delivery of selected molecules to be used in the treatment of Alzheimer's and Parkinson's diseases. In both these scenarios, the design and development of optimized polymer-based drug delivery and cell housing systems for central nervous system applications represent a key requirement. Materials science provides suitable hydrogel-based tools to be optimized together with suitably designed recombinant proteins or drug delivering-cells that, once in situ, can provide an effective treatment for these neurodegenerative disorders. In this scenario, only interdisciplinary research that fully integrates biology, biochemistry, medicine and materials science can provide a springboard for the development of suitable therapeutic tools, not only for the treatment of Alzheimer's and Parkinson's diseases but also, prospectively, for a wide range of severe neurodegenerative disorders.

Quantifying Selective Pressures Driving Bacterial Evolution Using Lineage Analysis

Science.gov (United States)

Lambert, Guillaume; Kussell, Edo

2015-01-01

Organisms use a variety of strategies to adapt to their environments and maximize long-term growth potential, but quantitative characterization of the benefits conferred by the use of such strategies, as well as their impact on the whole population's rate of growth, remains challenging. Here, we use a path-integral framework that describes how selection acts on lineages—i.e., the life histories of individuals and their ancestors—to demonstrate that lineage-based measurements can be used to quantify the selective pressures acting on a population. We apply this analysis to Escherichia coli bacteria exposed to cyclical treatments of carbenicillin, an antibiotic that interferes with cell-wall synthesis and affects cells in an age-dependent manner. While the extensive characterization of the life history of thousands of cells is necessary to accurately extract the age-dependent selective pressures caused by carbenicillin, the same measurement can be recapitulated using lineage-based statistics of a single surviving cell. Population-wide evolutionary pressures can be extracted from the properties of the surviving lineages within a population, providing an alternative and efficient procedure to quantify the evolutionary forces acting on a population. Importantly, this approach is not limited to age-dependent selection, and the framework can be generalized to detect signatures of other trait-specific selection using lineage-based measurements. Our results establish a powerful way to study the evolutionary dynamics of life under selection and may be broadly useful in elucidating selective pressures driving the emergence of antibiotic resistance and the evolution of survival strategies in biological systems.

Structure-Based Design of Potent and Selective 3-Phosphoinositide-Dependent Kinase-1 (PDK1) Inhibitors

Energy Technology Data Exchange (ETDEWEB)

Medina, Jesus R.; Becker, Christopher J.; Blackledge, Charles W.; Duquenne, Celine; Feng, Yanhong; Grant, Seth W.; Heerding, Dirk; Li, William H.; Miller, William H.; Romeril, Stuart P.; Scherzer, Daryl; Shu, Arthur; Bobko, Mark A.; Chadderton, Antony R.; Dumble, Melissa; Gardiner, Christine M.; Gilbert, Seth; Liu, Qi; Rabindran, Sridhar K.; Sudakin, Valery; Xiang, Hong; Brady, Pat G.; Campobasso, Nino; Ward, Paris; Axten, Jeffrey M. (GSKPA)

2014-10-02

Phosphoinositide-dependent protein kinase-1(PDK1) is a master regulator of the AGC family of kinases and an integral component of the PI3K/AKT/mTOR pathway. As this pathway is among the most commonly deregulated across all cancers, a selective inhibitor of PDK1 might have utility as an anticancer agent. Herein we describe our lead optimization of compound 1 toward highly potent and selective PDK1 inhibitors via a structure-based design strategy. The most potent and selective inhibitors demonstrated submicromolar activity as measured by inhibition of phosphorylation of PDK1 substrates as well as antiproliferative activity against a subset of AML cell lines. In addition, reduction of phosphorylation of PDK1 substrates was demonstrated in vivo in mice bearing OCl-AML2 xenografts. These observations demonstrate the utility of these molecules as tools to further delineate the biology of PDK1 and the potential pharmacological uses of a PDK1 inhibitor.

Study of selected phenotype switching strategies in time varying environment

Energy Technology Data Exchange (ETDEWEB)

Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)

2016-03-22

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Study of selected phenotype switching strategies in time varying environment

International Nuclear Information System (INIS)

Horvath, Denis; Brutovsky, Branislav

2016-01-01

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Outage Probability versus Fairness Trade-off in Opportunistic Relay Selection with Outdated CSI

Directory of Open Access Journals (Sweden)

Vicario JoseLopez

2009-01-01

Full Text Available We analyze the existing trade-offs in terms of system performance versus fairness of a cooperative system based on opportunistic relay selection (ORS and with outdated channel state information (CSI. In particular, system performance is analytically evaluated in terms of outage probability, and the fairness behavior is assessed based on the power consumption at the different relays. In order to improve the fairness behavior of ORS while keeping the selection diversity gain, we propose a relay selection mechanism where the relay with the highest normalized signal-to-noise ratio (SNR is selected for relaying the source's information. The proposed strategy is compared with existing relay selection strategies by adopting a novel graphical representation inspired by expected profit versus risk plots used in modern portfolio theory. As shown in the paper, this strategy allows operating the system in more favorable points of the outage versus fairness region.

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach.

Science.gov (United States)

Nasir, Muhammad; Attique Khan, Muhammad; Sharif, Muhammad; Lali, Ikram Ullah; Saba, Tanzila; Iqbal, Tassawar

2018-02-21

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F-score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods. © 2018 Wiley Periodicals, Inc.

Multi-criteria Group Decision Making based on Linguistic Refined Neutrosophic Strategy

OpenAIRE

Kalyan Mondal; Surapati Pramanik; Bibhas C. Giri

2018-01-01

Multi-criteria group decision making (MCGDM) strategy, which consists of a group of experts acting collectively for best selection among all possible alternatives with respect to some criteria, is focused on in this study. To develop the paper, we define linguistic neutrosophic refine set.

Entropy-based gene ranking without selection bias for the predictive classification of microarray data

Directory of Open Access Journals (Sweden)

Serafini Maria

2003-11-01

Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

Strategies for Improving the Performance of Sensors Based on Organic Field-Effect Transistors.

Science.gov (United States)

Wu, Xiaohan; Mao, Shun; Chen, Junhong; Huang, Jia

2018-04-01

Organic semiconductors (OSCs) have been extensively studied as sensing channel materials in field-effect transistors due to their unique charge transport properties. Stimulation caused by its environmental conditions can readily change the charge-carrier density and mobility of OSCs. Organic field-effect transistors (OFETs) can act as both signal transducers and signal amplifiers, which greatly simplifies the device structure. Over the past decades, various sensors based on OFETs have been developed, including physical sensors, chemical sensors, biosensors, and integrated sensor arrays with advanced functionalities. However, the performance of OFET-based sensors still needs to be improved to meet the requirements from various practical applications, such as high sensitivity, high selectivity, and rapid response speed. Tailoring molecular structures and micro/nanofilm structures of OSCs is a vital strategy for achieving better sensing performance. Modification of the dielectric layer and the semiconductor/dielectric interface is another approach for improving the sensor performance. Moreover, advanced sensory functionalities have been achieved by developing integrated device arrays. Here, a brief review of strategies used for improving the performance of OFET sensors is presented, which is expected to inspire and provide guidance for the design of future OFET sensors for various specific and practical applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Selective Distance-Based K+ Quantification on Paper-Based Microfluidics.

Science.gov (United States)

Gerold, Chase T; Bakker, Eric; Henry, Charles S

2018-04-03

In this study, paper-based microfluidic devices (μPADs) capable of K + quantification in aqueous samples, as well as in human serum, using both colorimetric and distance-based methods are described. A lipophilic phase containing potassium ionophore I (valinomycin) was utilized to achieve highly selective quantification of K + in the presence of Na + , Li + , and Mg 2+ ions. Successful addition of a suspended lipophilic phase to a wax printed paper-based device is described and offers a solution to current approaches that rely on organic solvents, which damage wax barriers. The approach provides an avenue for future alkali/alkaline quantification utilizing μPADs. Colorimetric spot tests allowed for K + quantification from 0.1-5.0 mM using only 3.00 μL of sample solution. Selective distance-based quantification required small sample volumes (6.00 μL) and gave responses sensitive enough to distinguish between 1.0 and 2.5 mM of sample K + . μPADs using distance-based methods were also capable of differentiating between 4.3 and 6.9 mM K + in human serum samples. Distance-based methods required no digital analysis, electronic hardware, or pumps; any steps required for quantification could be carried out using the naked eye.

Use of expert judgment in the development and evaluation of risk-based inservice testing strategies for pumps and valves

International Nuclear Information System (INIS)

McAllister, W.J.; Perdue, R.K.; Balkey, K.R.; Closky, N.B.

1996-01-01

This paper describes a rigorous approach for quantitatively evaluating inservice testing effectiveness that evolved from two pilot plant studies. These studies prototyped methodologies for designing and selecting inservice testing (IST) strategies in a manner structured to insure that the targeted components will perform their required safety functions while minimizing life cycle inservice testing costs. The paper concentrates on the use of expert judgment in developing test effectiveness measures that move risk-based methods beyond ranking to optimization of plant IST programs. Selected results for check valves and pumps are shown to illustrate the practical significance of the approach

Use of expert judgment in the development and evaluation of risk-based inservice testing strategies for pumps and valves

Energy Technology Data Exchange (ETDEWEB)

McAllister, W.J.; Perdue, R.K.; Balkey, K.R.; Closky, N.B. [and others

1996-12-01

This paper describes a rigorous approach for quantitatively evaluating inservice testing effectiveness that evolved from two pilot plant studies. These studies prototyped methodologies for designing and selecting inservice testing (IST) strategies in a manner structured to insure that the targeted components will perform their required safety functions while minimizing life cycle inservice testing costs. The paper concentrates on the use of expert judgment in developing test effectiveness measures that move risk-based methods beyond ranking to optimization of plant IST programs. Selected results for check valves and pumps are shown to illustrate the practical significance of the approach.

Chronic Periprosthetic Hip Joint Infection. A Retrospective, Observational Study on the Treatment Strategy and Prognosis in 130 Non-Selected Patients

DEFF Research Database (Denmark)

Lange, Jeppe; Troelsen, Anders; Søballe, Kjeld

2016-01-01

INTRODUCTION: Limited information is available regarding the treatment strategy and prognosis of non-selected patients treated for chronic periprosthetic hip joint infection. Such information is important as no head-to-head studies on treatment strategies are available. The purpose of this study...... is to report on the treatment strategy and prognosis of a non-selected, consecutive patient population. METHODS: We identified 130 patients in the National Patient Registry, consecutively treated for a chronic periprosthetic hip joint infection between 2003-2008 at 11 departments of orthopaedic surgery. We...... extracted information regarding patient demographics, treatment and outcome. 82 patients were re-implanted in a two-stage revision (national standard), the remaining 48 were not re-implanted in a two-stage revision. We were able to collect up-to-date information on all patients to date of death or medical...

PERFORMANCE OF SELECTED PRE-HARVEST AND POST-HARVEST CORN AND SOYBEAN MARKETING STRATEGIES VS. ALTERNATIVE MARKET BENCHMARKS

OpenAIRE

Blue, E. Neal; Wisner, Robert N.; Baldwin, E. Dean

2004-01-01

This study was undertaken to update earlier work by the authors that analyzed selected preharvest pricing strategies utilizing options markets to establish a price floor for part of the crop in the spring, with additional pricing done by use of short hedges in early summer. The timing of implementing these strategies was moved back to late February if the previous year's U.S. crop was a weather-induced short crop. A weather-induced short crop as opposed to a government program induced short c...

Strategie stosowane w marketingu dóbr przemysłowych

OpenAIRE

Golik-Górecka, Grażyna

2003-01-01

The paper tries to define the difference between a marketing strategy and a tactic in industrial marketing. The tactics are part of a coherent strategy. The problems are connected with (methods of grouping or classifying strategies, generally) three approaches to classifying strategies in thery and into practice. The first way: matrix of Ansoff, second way to classify strategies is based on the distinction between primary and selective demand and third one sets Porter’s three generic strategi...

Selection of Highly Expressed Gene Variants in Escherichia coli Using Translationally Coupled Antibiotic Selection Markers

DEFF Research Database (Denmark)

Rennig, Maja; Daley, Daniel O.; Nørholm, Morten H. H.

2018-01-01

Strategies to select highly expressed variants of a protein coding sequence are usually based on trial-and-error approaches, which are time-consuming and expensive. We address this problem using translationally coupled antibiotic resistance markers. The system requires that the target gene can...

Toward a Common Understanding of Research-Based Instructional Strategies

Science.gov (United States)

Goodwin, Deborah; Webb, Mary Ann

2014-01-01

A review of available books, articles and on-line resources which deal with "Research-Based Instructional Strategies" will produce a plethora of materials which promote the effectiveness of these strategies on student achievement. Also, a perusal of classroom instruction and teacher evaluation instruments will reveal that many of the…

Label fusion based brain MR image segmentation via a latent selective model

Science.gov (United States)

Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

2018-04-01

Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

Healthy Aging Promotion through Neuroscientific Information-Based Strategies.

Science.gov (United States)

Seinfeld, Sofia; Sanchez-Vives, Maria V

2015-09-28

To ensure the well-being of a rapidly growing elderly population, it is fundamental to find strategies to foster healthy brain aging. With this intention, we designed a program of scientific-based lectures aimed at dissemination by established neuroscientists about brain function, brain plasticity and how lifestyle influences the brain. We also carried out a pilot study on the impact of the lectures on attendees. The objective was to provide information to elderly people in order to encourage them to identify unhealthy and healthy daily habits, and more importantly, to promote behavioral changes towards healthy brain aging. Here we report on our experience. In order to determine the impact of the lectures in the daily routine of the attendees, we asked them to fill out questionnaires. Preliminary results indicate that neuroscientific information-based strategies can be a useful method to have a positive impact on the lives of elderly, increase their awareness on how to improve brain function and promote positive lifestyle modifications. Furthermore, based on self-reported data, we also found that through this strategy it is possible to promote behavioral changes related to nutrition, sleep, and realization of physical and cognitively stimulating activities. Finally, based on the results obtained, the importance of promoting self-efficacy and the empowerment of the older populations is highlighted.

Healthy Aging Promotion through Neuroscientific Information-Based Strategies

Directory of Open Access Journals (Sweden)

Sofia Seinfeld

2015-09-01

Full Text Available To ensure the well-being of a rapidly growing elderly population, it is fundamental to find strategies to foster healthy brain aging. With this intention, we designed a program of scientific-based lectures aimed at dissemination by established neuroscientists about brain function, brain plasticity and how lifestyle influences the brain. We also carried out a pilot study on the impact of the lectures on attendees. The objective was to provide information to elderly people in order to encourage them to identify unhealthy and healthy daily habits, and more importantly, to promote behavioral changes towards healthy brain aging. Here we report on our experience. In order to determine the impact of the lectures in the daily routine of the attendees, we asked them to fill out questionnaires. Preliminary results indicate that neuroscientific information-based strategies can be a useful method to have a positive impact on the lives of elderly, increase their awareness on how to improve brain function and promote positive lifestyle modifications. Furthermore, based on self-reported data, we also found that through this strategy it is possible to promote behavioral changes related to nutrition, sleep, and realization of physical and cognitively stimulating activities. Finally, based on the results obtained, the importance of promoting self-efficacy and the empowerment of the older populations is highlighted.

Strategies for reward-based crowdfunding campaigns

Directory of Open Access Journals (Sweden)

Sascha Kraus

2016-01-01

Full Text Available Crowdfunding represents an alternative way of funding entrepreneurial ventures – and is attracting a high amount of interest in research as well as practice. Against this background, this paper analyzes reward-based crowdfunding campaign strategies and their communication tools. To do this, 446 crowdfunding projects were gathered and empirically analyzed. Three different paths of successful crowdfunding projects could be identified and are described in detail. Practical implications of crowdfunding strategies are derived, and are dependent on the required sales effort and the project added value. The terms communicator, networker and self-runner are created for this crowdfunding strategy and filled with practical examples. This paper contributes to the literature in different ways: first, it sheds more light on the developing concept of crowdfunding, with an overview of current academic discussions on crowdfunding. Furthermore, the analysis of success factors for crowdfunding initiatives adds to an emerging area of research and allows entrepreneurs to extract best practice examples for increasing the probability of successful crowdfunding projects under consideration of the key influencing factors of communication.

PMU Measurement-Based Intelligent Strategy for Power System Controlled Islanding

Directory of Open Access Journals (Sweden)

Yi Tang

2018-01-01

Full Text Available Controlled islanding is an effective remedy to prevent large-area blackouts in a power system under a critically unstable condition. When and where to separate the power system are the essential issues facing controlled islanding. In this paper, both tasks are studied to ensure higher time efficiency and a better post-splitting restoration effect. A transient stability assessment model based on extreme learning machine (ELM and trajectory fitting (TF is constructed to determine the start-up criterion for controlled islanding. This model works through prompt stability status judgment with ELM and selective result amendment with TF to ensure that the assessment is both efficient and accurate. Moreover, a splitting surface searching algorithm, subject to minimal power disruption, is proposed for determination of the controlled islanding implementing locations. A highlight of this algorithm is a proposed modified electrical distance concept defined by active power magnitude and reactance on transmission lines that realize a computational burden reduction without feasible solution loss. Finally, the simulation results and comparison analysis based on the New England 39-bus test system validates the implementation effects of the proposed controlled islanding strategy.

A dynamic replication management strategy in distributed GIS

Science.gov (United States)

Pan, Shaoming; Xiong, Lian; Xu, Zhengquan; Chong, Yanwen; Meng, Qingxiang

2018-03-01

Replication strategy is one of effective solutions to meet the requirement of service response time by preparing data in advance to avoid the delay of reading data from disks. This paper presents a brand-new method to create copies considering the selection of replicas set, the number of copies for each replica and the placement strategy of all copies. First, the popularities of all data are computed considering both the historical access records and the timeliness of the records. Then, replica set can be selected based on their recent popularities. Also, an enhanced Q-value scheme is proposed to assign the number of copies for each replica. Finally, a reasonable copies placement strategy is designed to meet the requirement of load balance. In addition, we present several experiments that compare the proposed method with techniques that use other replication management strategies. The results show that the proposed model has better performance than other algorithms in all respects. Moreover, the experiments based on different parameters also demonstrated the effectiveness and adaptability of the proposed algorithm.

A survey on OFDM channel estimation techniques based on denoising strategies

Directory of Open Access Journals (Sweden)

Pallaviram Sure

2017-04-01

Full Text Available Channel estimation forms the heart of any orthogonal frequency division multiplexing (OFDM based wireless communication receiver. Frequency domain pilot aided channel estimation techniques are either least squares (LS based or minimum mean square error (MMSE based. LS based techniques are computationally less complex. Unlike MMSE ones, they do not require a priori knowledge of channel statistics (KCS. However, the mean square error (MSE performance of the channel estimator incorporating MMSE based techniques is better compared to that obtained with the incorporation of LS based techniques. To enhance the MSE performance using LS based techniques, a variety of denoising strategies have been developed in the literature, which are applied on the LS estimated channel impulse response (CIR. The advantage of denoising threshold based LS techniques is that, they do not require KCS but still render near optimal MMSE performance similar to MMSE based techniques. In this paper, a detailed survey on various existing denoising strategies, with a comparative discussion of these strategies is presented.

Cermet based solar selective absorbers : further selectivity improvement and developing new fabrication technique

OpenAIRE

Nejati, Mohammadreza

2008-01-01

Spectral selectivity of cermet based selective absorbers were increased by inducing surface roughness on the surface of the cermet layer using a roughening technique (deposition on hot substrates) or by micro-structuring the metallic substrates before deposition of the absorber coating using laser and imprint structuring techniques. Cu-Al2O3 cermet absorbers with very rough surfaces and excellent selectivity were obtained by employing a roughness template layer under the infrared reflective l...

Positive versus Negative Communication Strategies in Task-Based Learning

Science.gov (United States)

Rohani, Siti

2013-01-01

This study aimed at describing how the implementation of Task-Based Learning (TBL) would shape or change students' use of oral communication strategies. Students' problems and strategies to solve the problems during the implementation of TBL were also explored. The study was a mixed method, employing both quantitative and qualitative analysis…

Performance-Based Technology Selection Filter description report

International Nuclear Information System (INIS)

O'Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

1992-05-01

A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL)

Discriminative Projection Selection Based Face Image Hashing

Science.gov (United States)

Karabat, Cagatay; Erdogan, Hakan

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

Performance-Based Technology Selection Filter description report

Energy Technology Data Exchange (ETDEWEB)

O' Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

1992-05-01

A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL).

Switch in Site of Inhibition: A Strategy for Structure-Based Discovery of Human Topoisomerase IIα Catalytic Inhibitors

Science.gov (United States)

2015-01-01

A study of structure-based modulation of known ligands of hTopoIIα, an important enzyme involved in DNA processes, coupled with synthesis and in vitro assays led to the establishment of a strategy of rational switch in mode of inhibition of the enzyme’s catalytic cycle. 6-Arylated derivatives of known imidazopyridine ligands were found to be selective inhibitors of hTopoIIα, while not showing TopoI inhibition and DNA binding. Interestingly, while the parent imidazopyridines acted as ATP-competitive inhibitors, arylated derivatives inhibited DNA cleavage similar to merbarone, indicating a switch in mode of inhibition from ATP-hydrolysis to the DNA-cleavage stage of catalytic cycle of the enzyme. The 6-aryl-imidazopyridines were relatively more cytotoxic than etoposide in cancer cells and less toxic to normal cells. Such unprecedented strategy will encourage research on “choice-based change” in target-specific mode of action for rapid drug discovery. PMID:25941559

[Progress in the spectral library based protein identification strategy].

Science.gov (United States)

Yu, Derui; Ma, Jie; Xie, Zengyan; Bai, Mingze; Zhu, Yunping; Shu, Kunxian

2018-04-25

Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

Infrastructure Analysis of Sazeh Gostar Saipa Outsourcing Company to Select Knowledge Management Strategy: Qualitative Approach

Directory of Open Access Journals (Sweden)

hossein Khanifar

2017-09-01

Full Text Available In today's turbulent business environment, organizations have to make changes in their structure such as outsourcing. This change that is a requirement to provide for the needs of that organization and for competitive advantage can be considered as a new trouble for that organization as well. Because of such changes, an organization may lose the workers' (employee knowledge that is the most important element of the competitive advantage. Thus, the organizations are required to use the most effective knowledge management strategy that is proposed according to the analysis of the key aspects of those organizations. This study examines Sazeh Gostar, the most important suppliers of spare parts for Saipa Automobile Company. At first, the two coding and personalization strategies were applied provided that they were reviewed in the literature. The influential factors were then classified according to McKenzie 7S model. Then, the data were obtained using snowball and targeted sampling from interviews with 9 experts, and through reviewing the company documents. Current status of the company was identified using Theme Analysis. Finally, comparing the influential factors on the company's knowledge management strategy, the appropriate coding strategy was selected.

What Successful Science Teachers Do: 75 Research-Based Strategies

Science.gov (United States)

Glasgow, Neal A.; Cheyne, Michele; Yerrick, Randy K.

2010-01-01

The experience and science expertise of these award-winning authors makes this easy-to-use guide a teacher's treasure trove. This latest edition to the popular What Successful Teachers Do series describes 75 research-based strategies and outlines best practices for inquiry-oriented science. Each strategy includes a brief description of the…

Age differences in strategy shift: retrieval avoidance or general shift reluctance?

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Frank, David J; Touron, Dayna R; Hertzog, Christopher

2013-09-01

Previous studies of metacognitive age differences in skill acquisition strategies have relied exclusively on tasks with a processing shift from an algorithm to retrieval strategy. Older adults' demonstrated reluctance to shift strategies in such tasks could reflect either a specific aversion to a memory retrieval strategy or a general, inertial resistance to strategy change. Haider and Frensch's (1999) alphabet verification task (AVT) affords a non-retrieval-based strategy shift. Participants verify the continuation of alphabet strings such as D E F G [4] L, with the bracketed digit indicating a number of letters to be skipped. When all deviations are restricted to the letter-digit-letter portion, participants can speed their responses by selectively attending to only that part of the stimulus. We adapted the AVT to include conditions that promoted shift to a retrieval strategy, a selective attention strategy, or both strategies. Item-level strategy reports were validated by eye movement data. Older adults shifted more slowly to the retrieval strategy but more quickly to the selective attention strategy than young adults, indicating a retrieval-strategy avoidance. Strategy confidence and perceived strategy difficulty correlated with shift to the two strategies in both age groups. Perceived speed of responses with each strategy specifically correlated with older adults' strategy choices, suggesting that some older adults avoid retrieval because they do not appreciate its efficiency benefits.

Age Differences in Strategy Shift: Retrieval Avoidance or General Shift Reluctance?

Science.gov (United States)

Frank, David J.; Touron, Dayna R.; Hertzog, Christopher

2013-01-01

Previous studies of metacognitive age differences in skill acquisition strategies have relied exclusively on tasks with a processing shift from an algorithm to retrieval strategy. Older adults’ demonstrated reluctance to shift strategies in such tasks could reflect either a specific aversion to a memory retrieval strategy or a general, inertial resistance to strategy change. Haider and Frensch’s (1999) alphabet verification task (AVT) affords a non-retrieval-based strategy shift. Participants verify the continuation of alphabet strings such as D E F G [4] L, with the bracketed digit indicating a number of letters to be skipped. When all deviations are restricted to the letter-digit-letter portion, participants can speed their responses by selectively attend only to that part of the stimulus. We adapted the AVT to include conditions which promoted shift to a retrieval strategy, a selective attention strategy, or both strategies. Item-level strategy reports were validated by eye movement data. Older adults shifted more slowly to the retrieval strategy but more quickly to the selective attention strategy than young adults, indicating a retrieval-strategy avoidance. Strategy confidence and perceived strategy difficulty correlated with shift to the two strategies in both age groups. Perceived speed of responses with each strategy specifically correlated with older adults’ strategy choices, suggesting that some older adults avoid retrieval because they do not appreciate its efficiency benefits. PMID:23088195

Influence of scan strategy and molten pool configuration on microstructures and tensile properties of selective laser melting additive manufactured aluminum based parts

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Dai, Donghua; Gu, Dongdong; Zhang, Han; Xiong, Jiapeng; Ma, Chenglong; Hong, Chen; Poprawe, Reinhart

2018-02-01

Selective laser melting additive manufacturing of the AlSi12 material parts through the re-melting of the previously solidified layer using the continuous two layers 90° rotate scan strategy was conducted. The influence of the re-melting behavior and scan strategy on the formation of the ;track-track; and ;layer-layer; molten pool boundaries (MPBs), dimensional accuracy, microstructure feature, tensile properties, microscopic sliding behavior and the fracture mechanism as loaded a tensile force has been studied. It showed that the defects, such as the part distortion, delamination and cracks, were significantly eliminated with the deformation rate less than 1%. The microstructure of a homogeneous distribution of the Si phase, no apparent grain orientation on both sides of the MPBs, was produced in the as-fabricated part, promoting the efficient transition of the load stress. Cracks preferentially initiate at the ;track-track; MPBs when the tensile stress increases to a certain value, resulting in the formation of the cleavage steps along the tensile loading direction. The cracks propagate along the ;layer-layer; MPBs, generating the fine dimples. The mechanical behavior of the SLM-processed AlSi12 parts can be significantly enhanced with the ultimate tensile strength, yield strength and elongation of 476.3 MPa, 315.5 MPa and 6.7%, respectively.

Innovation Marketing Strategy of Selected Sporting Events

OpenAIRE

Zezula, Vojtěch

2015-01-01

Cílem bakalářské práce je návrh modernizace marketingové strategie, která je tvořena za pomocí dat získaných z předešlého ročníku Moravské ligy Taekwon-Do ITF. Úvodní část práce obsahuje teoretická východiska, která jsou nezbytná ke zpracování praktické části. Objasňuje terminologii marketingu, marketingové strategie. Praktická část je následně tvořena analýzou předchozího ročníku, přičemž výsledky slouží jako podklady pro samotnou inovaci marketingové strategie. The aim of this thesis is ...

Transfer of analytical procedures: a panel of strategies selected for risk management, with emphasis on an integrated equivalence-based comparative testing approach.

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Agut, C; Caron, A; Giordano, C; Hoffman, D; Ségalini, A

2011-09-10

In 2001, a multidisciplinary team made of analytical scientists and statisticians at Sanofi-aventis has published a methodology which has governed, from that time, the transfers from R&D sites to Manufacturing sites of the release monographs. This article provides an overview of the recent adaptations brought to this original methodology taking advantage of our experience and the new regulatory framework, and, in particular, the risk management perspective introduced by ICH Q9. Although some alternate strategies have been introduced in our practices, the comparative testing one, based equivalence testing as statistical approach, remains the standard for assays lying on very critical quality attributes. This is conducted with the concern to control the most important consumer's risk involved at two levels in analytical decisions in the frame of transfer studies: risk, for the receiving laboratory, to take poor release decisions with the analytical method and risk, for the sending laboratory, to accredit such a receiving laboratory on account of its insufficient performances with the method. Among the enhancements to the comparative studies, the manuscript presents the process settled within our company for a better integration of the transfer study into the method life-cycle, just as proposals of generic acceptance criteria and designs for assay and related substances methods. While maintaining rigor and selectivity of the original approach, these improvements tend towards an increased efficiency in the transfer operations. Copyright © 2011 Elsevier B.V. All rights reserved.

Advances in stable isotope assisted labeling strategies with information science.

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Kigawa, Takanori

2017-08-15

Stable-isotope (SI) labeling of proteins is an essential technique to investigate their structures, interactions or dynamics by nuclear magnetic resonance (NMR) spectroscopy. The assignment of the main-chain signals, which is the fundamental first step in these analyses, is usually achieved by a sequential assignment method based on triple resonance experiments. Independently of the triple resonance experiment-based sequential assignment, amino acid-selective SI labeling is beneficial for discriminating the amino acid type of each signal; therefore, it is especially useful for the signal assignment of difficult targets. Various combinatorial selective labeling schemes have been developed as more sophisticated labeling strategies. In these strategies, amino acids are represented by combinations of SI labeled samples, rather than simply assigning one amino acid to one SI labeled sample as in the case of conventional amino acid-selective labeling. These strategies have proven to be useful for NMR analyses of difficult proteins, such as those in large complex systems, in living cells, attached or integrated into membranes, or with poor solubility. In this review, recent advances in stable isotope assisted labeling strategies will be discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

The Learning Environment Counts: Longitudinal Qualitative Analysis of Study Strategies Adopted by First-Year Medical Students in a Competency-Based Educational Program.

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Bierer, S Beth; Dannefer, Elaine F

2016-11-01

The move toward competency-based education will require medical schools and postgraduate training programs to restructure learning environments to motivate trainees to take personal ownership for learning. This qualitative study explores how medical students select and implement study strategies while enrolled in a unique, nontraditional program that emphasizes reflection on performance and competence rather than relying on high-stakes examinations or grades to motivate students to learn and excel. Fourteen first-year medical students volunteered to participate in three, 45-minute interviews (42 overall) scheduled three months apart during 2013-2014. Two medical educators used structured interview guides to solicit students' previous assessment experiences, preferred learning strategies, and performance monitoring processes. Interviews were digitally recorded and transcribed verbatim. Participants confirmed accuracy of transcripts. Researchers independently read transcripts and met regularly to discuss transcripts and judge when themes achieved saturation. Medical students can adopt an assessment for learning mind-set with faculty guidance and implement appropriate study strategies for mastery-learning demands. Though students developed new strategies at different rates during the year, they all eventually identified study and performance monitoring strategies to meet learning needs. Students who had diverse learning experiences in college embraced mastery-based study strategies sooner than peers after recognizing that the learning environment did not reward performance-based strategies. Medical students can take ownership for their learning and implement specific strategies to regulate behavior when learning environments contain building blocks emphasized in self-determination theory. Findings should generalize to educational programs seeking strategies to design learning environments that promote self-regulated learning.

Selection of the open pit mining cut-off grade strategy under price uncertainty using a risk based multi-criteria ranking system / Wybór strategii określania warunku opłacalności wydobycia w kopalniach odkrywkowych w warunkach niepewności cen w oparciu o wielokryterialny system rankingowy z uwzględnieniem czynników ryzyka

Science.gov (United States)

Azimi, Yousue; Osanloo, Montza; Esfahanipour, Akbar

2012-12-01

Cut-off Grade Strategy (COGS) is a concept that directly influences the financial, technical, economic, environmental, and legal issues in relation to exploitation of a mineral resource. A decision making system is proposed to select the best technically feasible COGS under price uncertainty. In the proposed system both the conventional discounted cash flow and modern simulation based real option valuations are used to evaluate the alternative strategies. Then the conventional expected value criterion and a multiple criteria ranking system were used to rank the strategies based on the two valuation methods. In the multiple criteria ranking system besides the expected value other stochastic orders expressing abilities of strategies in producing extra profits, minimizing losses and achieving the predefined goals of the exploitation strategy are considered. Finally, the best strategy is selected based on the overall average rank of strategies through all ranking systems. The proposed system was examined using the data of Sungun Copper Mine. To assess the merits of the alternatives better, ranking process was done at both high (prevailing economic condition) and low price conditions. Ranking results revealed that at different price conditions and valuation methods, different results would be obtained. It is concluded that these differences are due to the different behavior of the embedded option to close the mine early, which is more likely to be exercised under low price condition rather than high price condition. The proposed system would enhance the quality of decision making process by providing a more informative and certain platform for project evaluation.

Strategies of marine dinoflagellate survival and some rules of assembly

Science.gov (United States)

Smayda, Theodore J.; Reynolds, Colin S.

2003-03-01

Dinoflagellate ecology is based on multiple adaptive strategies and species having diverse habitat preferences. Nine types of mixing-irradiance-nutrient habitats selecting for specific marine dinoflagellate life-form types are recognised, with five rules of assembly proposed to govern bloom-species selection and community organisation within these habitats. Assembly is moulded around an abiotic template of light energy, nutrient supply and physical mixing in permutative combinations. Species selected will have one of three basic ( C-, S-, R-) strategies: colonist species ( C-) which predominate in chemically disturbed habitats; nutrient stress tolerant species ( S-), and species ( R-) tolerant of shear/stress forces in physically disturbed water masses. This organisational plan of three major habitat variables and three major adaptive strategies is termed the 3-3 plan. The bloom behaviour and habitat specialisation of dinoflagellates and diatoms are compared. Dinoflagellates behave as annual species, bloom soloists, are ecophysiologically diverse, and habitat specialists whose blooms tend to be monospecific. Diatoms behave as perennial species, guild members, are habitat cosmopolites, have a relatively uniform bloom strategy based on species-rich pools and exhibit limited habitat specialisation. Dinoflagellate bloom-species selection follows a taxonomic hierarchical pathway which progresses from phylogenetic to generic to species selection, and in that sequence. Each hierarchical taxonomic level has its own adaptive requirements subject to rules of assembly. Dinoflagellates would appear to be well suited to exploit marine habitats and to be competitive with other phylogenetic groups, yet fail to do so.

A Hydrazone-Based exo-Directing-Group Strategy for β C-H Oxidation of Aliphatic Amines.

Science.gov (United States)

Huang, Zhongxing; Wang, Chengpeng; Dong, Guangbin

2016-04-18

Described is a new hydrazone-based exo-directing group (DG) strategy developed for the functionalization of unactivated primary β C-H bonds of aliphatic amines. Conveniently synthesized from protected primary amines, the hydrazone DGs are shown to site-selectively promote the β-acetoxylation and tosyloxylation via five-membered exo-palladacycles. Amines with a wide scope of skeletons and functional groups are tolerated. Moreover, the hydrazone DG can be readily removed, and a one-pot C-H acetoxylation/DG removal protocol was also discovered. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.