A VLSI Implementation of Rank-Order Searching Circuit Employing a Time-Domain Technique

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Trong-Tu Bui

2013-01-01

Full Text Available We present a compact and low-power rank-order searching (ROS circuit that can be used for building associative memories and rank-order filters (ROFs by employing time-domain computation and floating-gate MOS techniques. The architecture inherits the accuracy and programmability of digital implementations as well as the compactness and low-power consumption of analog ones. We aim to implement identification function as the first priority objective. Filtering function would be implemented once the location identification function has been carried out. The prototype circuit was designed and fabricated in a 0.18 μm CMOS technology. It consumes only 132.3 μW for an eight-input demonstration case.

Effects of prosthetic foot forefoot flexibility on oxygen cost and subjective preference rankings of unilateral transtibial prosthesis users.

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Klodd, Elizabeth; Hansen, Andrew; Fatone, Stefania; Edwards, Mark

2010-01-01

The investigators conducted a double-blind randomized crossover study to determine the effects of prosthetic foot forefoot flexibility on oxygen cost and subjective preference rankings of 13 unilateral transtibial prosthesis users. Five experimental feet were fabricated for use in the study: F1, F2, F3, F4, and F5. F1 was most flexible, F5 was least flexible, and F3 was designed to conform to a biomimetic ankle-foot roll-over shape. The experimental feet were modeled after the Shape&Roll prosthetic foot (originally produced by Northwestern University, Chicago, Illinois; now in public domain) but had different numbers of saw cuts within the forefoot members, allowing more or less flexibility during walking. Participants walked at the same comfortable, freely selected speed on the treadmill for 7 min with each foot while energy expenditure was measured. No significant difference was found in oxygen cost (mL O(2)/kg/m) between the different feet (p = 0.17), and the order of use was also not significant (p = 0.94). However, the preference ranking was significantly affected by the flexibility of the feet (p = 0.002), with the most flexible foot (F1) ranking significantly poorer than feet F3 (p = 0.003) and F4 (p = 0.004). Users may prefer prosthetic feet that match the flexibility of an intact ankle-foot system, even though we did not detect an energetic benefit at freely selected speeds.

Learning User Preferences for Sets of Objects

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desJardins, Marie; Eaton, Eric; Wagstaff, Kiri L.

2006-01-01

Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of items. Our learning method takes as input a collection of positive examples--that is, one or more sets that have been identified by a user as desirable. Kernel density estimation is used to estimate the value function for individual items, and the desired set diversity is estimated from the average set diversity observed in the collection. Since this is a new learning problem, we introduce a new evaluation methodology and evaluate the learning method on two data collections: synthetic blocks-world data and a new real-world music data collection that we have gathered.

SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

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Shams, Bita; Haratizadeh, Saman

2016-09-01

Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

Multi-objective engineering design using preferences

Science.gov (United States)

Sanchis, J.; Martinez, M.; Blasco, X.

2008-03-01

System design is a complex task when design parameters have to satisy a number of specifications and objectives which often conflict with those of others. This challenging problem is called multi-objective optimization (MOO). The most common approximation consists in optimizing a single cost index with a weighted sum of objectives. However, once weights are chosen the solution does not guarantee the best compromise among specifications, because there is an infinite number of solutions. A new approach can be stated, based on the designer's experience regarding the required specifications and the associated problems. This valuable information can be translated into preferences for design objectives, and will lead the search process to the best solution in terms of these preferences. This article presents a new method, which enumerates these a priori objective preferences. As a result, a single objective is built automatically and no weight selection need be performed. Problems occuring because of the multimodal nature of the generated single cost index are managed with genetic algorithms (GAs).

An R package for analyzing and modeling ranking data.

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Lee, Paul H; Yu, Philip L H

2013-05-14

In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis. Examples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians' preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as "internal/external"), and the second dimension can be interpreted as their overall variance of (labeled as "push/pull factors"). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman's footrule distance. In this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought

Multi-criteria ranking of energy generation scenarios with Monte Carlo simulation

International Nuclear Information System (INIS)

Baležentis, Tomas; Streimikiene, Dalia

2017-01-01

Highlights: • Two advanced optimization models were applied for EU energy policy scenarios development. • Several advanced MCDA were applied for energy policy scenarios ranking: WASPAS, ARAS, TOPSIS. • A Monte Carlo simulation was applied for sensitivity analysis of scenarios ranking. • New policy insights in terms of energy scenarios forecasting were provided based on research conducted. - Abstract: Integrated Assessment Models (IAMs) are omnipresent in energy policy analysis. Even though IAMs can successfully handle uncertainty pertinent to energy planning problems, they render multiple variables as outputs of the modelling. Therefore, policy makers are faced with multiple energy development scenarios and goals. Specifically, technical, environmental, and economic aspects are represented by multiple criteria, which, in turn, are related to conflicting objectives. Preferences of decision makers need to be taken into account in order to facilitate effective energy planning. Multi-criteria decision making (MCDM) tools are relevant in aggregating diverse information and thus comparing alternative energy planning options. The paper aims at ranking European Union (EU) energy development scenarios based on several IAMs with respect to multiple criteria. By doing so, we account for uncertainty surrounding policy priorities outside the IAM. In order to follow a sustainable approach, the ranking of policy options is based on EU energy policy priorities: energy efficiency improvements, increased use of renewables, reduction in and low mitigations costs of GHG emission. The ranking of scenarios is based on the estimates rendered by the two advanced IAMs relying on different approaches, namely TIAM and WITCH. The data are fed into the three MCDM techniques: the method of weighted aggregated sum/product assessment (WASPAS), the Additive Ratio Assessment (ARAS) method, and technique for order preference by similarity to ideal solution (TOPSIS). As MCDM techniques allow

Fusion of multiagent preference orderings with information on agent's importance being incomplete certain

Institute of Scientific and Technical Information of China (English)

Wang Jianqiang

2007-01-01

The problem of fusing multiagent preference orderings, with information on agent's importance being incomplete certain with respect to a set of possible courses of action, is described. The approach is developed for dealing with the fusion problem described in the following sections and requires that each agent provides a preference ordering over the different alternatives completely independent of the other agents, and the information on agent's importance is incomplete certain. In this approach, the ternary comparison matrix of the alternatives is constructed, the eigenvector associated with the maximum eigenvalue of the ternary comparison matrix is attained so as to normalize priority vector of the alternatives. The interval number of the alternatives is then obtained by solving two sorts of linear programming problems. By comparing the interval numbers of the alternatives, the ranking of alternatives can be generated. Finally, some examples are given to show the feasibility and effectiveness of the method.

An integrated multicriteria decision-making approach for evaluating nuclear fuel cycle systems for long-term sustainability on the basis of an equilibrium model: Technique for order of preference by similarity to ideal solution, preference ranking organization method for enrichment evaluation, and multiattribute utility theory combined with analytic hierarchy process

Energy Technology Data Exchange (ETDEWEB)

Yoon, Sae Rom [Dept of Quantum Energy Chemical Engineering, Korea University of Science and Technology (KUST), Daejeon (Korea, Republic of); Choi, Sung Yeol [Ulsan National Institute of Science and Technology, Ulju (Korea, Republic of); Ko, Wonil [Nonproliferation System Development Division, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2017-02-15

The focus on the issues surrounding spent nuclear fuel and lifetime extension of old nuclear power plants continues to grow nowadays. A transparent decision-making process to identify the best suitable nuclear fuel cycle (NFC) is considered to be the key task in the current situation. Through this study, an attempt is made to develop an equilibrium model for the NFC to calculate the material flows based on 1 TWh of electricity production, and to perform integrated multicriteria decision-making method analyses via the analytic hierarchy process technique for order of preference by similarity to ideal solution, preference ranking organization method for enrichment evaluation, and multiattribute utility theory methods. This comparative study is aimed at screening and ranking the three selected NFC options against five aspects: sustainability, environmental friendliness, economics, proliferation resistance, and technical feasibility. The selected fuel cycle options include pressurized water reactor (PWR) once-through cycle, PWR mixed oxide cycle, or pyroprocessing sodium-cooled fast reactor cycle. A sensitivity analysis was performed to prove the robustness of the results and explore the influence of criteria on the obtained ranking. As a result of the comparative analysis, the pyroprocessing sodium-cooled fast reactor cycle is determined to be the most competitive option among the NFC scenarios.

An integrated multicriteria decision-making approach for evaluating nuclear fuel cycle systems for long-term sustainability on the basis of an equilibrium model: Technique for order of preference by similarity to ideal solution, preference ranking organization method for enrichment evaluation, and multiattribute utility theory combined with analytic hierarchy process

International Nuclear Information System (INIS)

Yoon, Sae Rom; Choi, Sung Yeol; Ko, Wonil

2017-01-01

The focus on the issues surrounding spent nuclear fuel and lifetime extension of old nuclear power plants continues to grow nowadays. A transparent decision-making process to identify the best suitable nuclear fuel cycle (NFC) is considered to be the key task in the current situation. Through this study, an attempt is made to develop an equilibrium model for the NFC to calculate the material flows based on 1 TWh of electricity production, and to perform integrated multicriteria decision-making method analyses via the analytic hierarchy process technique for order of preference by similarity to ideal solution, preference ranking organization method for enrichment evaluation, and multiattribute utility theory methods. This comparative study is aimed at screening and ranking the three selected NFC options against five aspects: sustainability, environmental friendliness, economics, proliferation resistance, and technical feasibility. The selected fuel cycle options include pressurized water reactor (PWR) once-through cycle, PWR mixed oxide cycle, or pyroprocessing sodium-cooled fast reactor cycle. A sensitivity analysis was performed to prove the robustness of the results and explore the influence of criteria on the obtained ranking. As a result of the comparative analysis, the pyroprocessing sodium-cooled fast reactor cycle is determined to be the most competitive option among the NFC scenarios

An Integrated Multicriteria Decision-Making Approach for Evaluating Nuclear Fuel Cycle Systems for Long-term Sustainability on the Basis of an Equilibrium Model: Technique for Order of Preference by Similarity to Ideal Solution, Preference Ranking Organization Method for Enrichment Evaluation, and Multiattribute Utility Theory Combined with Analytic Hierarchy Process

Directory of Open Access Journals (Sweden)

Saerom Yoon

2017-02-01

Full Text Available The focus on the issues surrounding spent nuclear fuel and lifetime extension of old nuclear power plants continues to grow nowadays. A transparent decision-making process to identify the best suitable nuclear fuel cycle (NFC is considered to be the key task in the current situation. Through this study, an attempt is made to develop an equilibrium model for the NFC to calculate the material flows based on 1 TWh of electricity production, and to perform integrated multicriteria decision-making method analyses via the analytic hierarchy process technique for order of preference by similarity to ideal solution, preference ranking organization method for enrichment evaluation, and multiattribute utility theory methods. This comparative study is aimed at screening and ranking the three selected NFC options against five aspects: sustainability, environmental friendliness, economics, proliferation resistance, and technical feasibility. The selected fuel cycle options include pressurized water reactor (PWR once-through cycle, PWR mixed oxide cycle, or pyroprocessing sodium-cooled fast reactor cycle. A sensitivity analysis was performed to prove the robustness of the results and explore the influence of criteria on the obtained ranking. As a result of the comparative analysis, the pyroprocessing sodium-cooled fast reactor cycle is determined to be the most competitive option among the NFC scenarios.

Rank-ordered multifractal analysis for intermittent fluctuations with global crossover behavior

International Nuclear Information System (INIS)

Tam, Sunny W. Y.; Chang, Tom; Kintner, Paul M.; Klatt, Eric M.

2010-01-01

The rank-ordered multifractal analysis (ROMA), a recently developed technique that combines the ideas of parametric rank ordering and one-parameter scaling of monofractals, has the capabilities of deciphering the multifractal characteristics of intermittent fluctuations. The method allows one to understand the multifractal properties through rank-ordered scaling or nonscaling parametric variables. The idea of the ROMA technique is applied to analyze the multifractal characteristics of the auroral zone electric-field fluctuations observed by the SIERRA sounding rocket. The observed fluctuations span across contiguous multiple regimes of scales with different multifractal characteristics. We extend the ROMA technique such that it can take into account the crossover behavior - with the possibility of collapsing probability distribution functions - over these contiguous regimes.

Man-Made Object Extraction from Remote Sensing Imagery by Graph-Based Manifold Ranking

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He, Y.; Wang, X.; Hu, X. Y.; Liu, S. H.

2018-04-01

The automatic extraction of man-made objects from remote sensing imagery is useful in many applications. This paper proposes an algorithm for extracting man-made objects automatically by integrating a graph model with the manifold ranking algorithm. Initially, we estimate a priori value of the man-made objects with the use of symmetric and contrast features. The graph model is established to represent the spatial relationships among pre-segmented superpixels, which are used as the graph nodes. Multiple characteristics, namely colour, texture and main direction, are used to compute the weights of the adjacent nodes. Manifold ranking effectively explores the relationships among all the nodes in the feature space as well as initial query assignment; thus, it is applied to generate a ranking map, which indicates the scores of the man-made objects. The man-made objects are then segmented on the basis of the ranking map. Two typical segmentation algorithms are compared with the proposed algorithm. Experimental results show that the proposed algorithm can extract man-made objects with high recognition rate and low omission rate.

Model of Decision Making through Consensus in Ranking Case

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Tarigan, Gim; Darnius, Open

2018-01-01

The basic problem to determine ranking consensus is a problem to combine some rankings those are decided by two or more Decision Maker (DM) into ranking consensus. DM is frequently asked to present their preferences over a group of objects in terms of ranks, for example to determine a new project, new product, a candidate in a election, and so on. The problem in ranking can be classified into two major categories; namely, cardinal and ordinal rankings. The objective of the study is to obtin the ranking consensus by appying some algorithms and methods. The algorithms and methods used in this study were partial algorithm, optimal ranking consensus, BAK (Borde-Kendal)Model. A method proposed as an alternative in ranking conssensus is a Weighted Distance Forward-Backward (WDFB) method, which gave a little difference i ranking consensus result compare to the result oethe example solved by Cook, et.al (2005).

Many-Objective Optimization Using Adaptive Differential Evolution with a New Ranking Method

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Xiaoguang He

2014-01-01

Full Text Available Pareto dominance is an important concept and is usually used in multiobjective evolutionary algorithms (MOEAs to determine the nondominated solutions. However, for many-objective problems, using Pareto dominance to rank the solutions even in the early generation, most obtained solutions are often the nondominated solutions, which results in a little selection pressure of MOEAs toward the optimal solutions. In this paper, a new ranking method is proposed for many-objective optimization problems to verify a relatively smaller number of representative nondominated solutions with a uniform and wide distribution and improve the selection pressure of MOEAs. After that, a many-objective differential evolution with the new ranking method (MODER for handling many-objective optimization problems is designed. At last, the experiments are conducted and the proposed algorithm is compared with several well-known algorithms. The experimental results show that the proposed algorithm can guide the search to converge to the true PF and maintain the diversity of solutions for many-objective problems.

Production objectives, trait and breed preferences of farmers keeping N'Dama, Fulani Zebu and crossbred cattle and implications for breeding programs.

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Traoré, S A; Markemann, A; Reiber, C; Piepho, H P; Valle Zárate, A

2017-04-01

Many local livestock breeds in developing countries are being replaced by exotic breeds, leading to a loss of genetic resources. In southern Mali, for the past two decades, a trend towards increasing crossbreeding between the trypanotolerant N'Dama cattle and the trypano-susceptible Fulani Zebu cattle has been taking place. A survey with 160 farmers owning a cattle herd was carried out in southern Mali to investigate their production objectives, as well as trait and breed preferences and correlated socio-economic determinants in order to understand farmers' breeding decisions and to identify comparative advantages of three breed groups (N'Dama, Fulani Zebu and crossbreds) raised in the study area. Data were analyzed using an exploded logit model. The reasons for raising cattle, as well as trait and breed preferences reflected the multiple objectives of the farmers. Draught power and savings were the most important production objectives. Productive traits were ranked highest; farmers reported large body size as the most preferred trait, followed by fertility, draught ability and milk yield. Crossbreds were the favored breed group. Breed preferences were mainly explained by 'resistance to disease' for N'Dama cattle and 'high market price' for Fulani Zebu and crossbred cattle. Production objectives, trait and breed preferences were mainly influenced by farmer group (local farmers and settled transhumants). Local farmers put comparatively more emphasis on livestock functions linked to crop production such as draught power. They had a higher preference for traction ability as a selection trait and preferred N'Dama over Fulani Zebu cattle. Settled transhumants emphasized milk yield as a selection trait and preferred Fulani Zebu over N'Dama. The results indicate that the trend towards more crossbreeding will continue putting the N'Dama breed under high risk of genetic dilution in southern Mali. The N'Dama cattle remain a valuable breed due to their adaptive traits such as

Algorithms for Learning Preferences for Sets of Objects

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Wagstaff, Kiri L.; desJardins, Marie; Eaton, Eric

2010-01-01

A method is being developed that provides for an artificial-intelligence system to learn a user's preferences for sets of objects and to thereafter automatically select subsets of objects according to those preferences. The method was originally intended to enable automated selection, from among large sets of images acquired by instruments aboard spacecraft, of image subsets considered to be scientifically valuable enough to justify use of limited communication resources for transmission to Earth. The method is also applicable to other sets of objects: examples of sets of objects considered in the development of the method include food menus, radio-station music playlists, and assortments of colored blocks for creating mosaics. The method does not require the user to perform the often-difficult task of quantitatively specifying preferences; instead, the user provides examples of preferred sets of objects. This method goes beyond related prior artificial-intelligence methods for learning which individual items are preferred by the user: this method supports a concept of setbased preferences, which include not only preferences for individual items but also preferences regarding types and degrees of diversity of items in a set. Consideration of diversity in this method involves recognition that members of a set may interact with each other in the sense that when considered together, they may be regarded as being complementary, redundant, or incompatible to various degrees. The effects of such interactions are loosely summarized in the term portfolio effect. The learning method relies on a preference representation language, denoted DD-PREF, to express set-based preferences. In DD-PREF, a preference is represented by a tuple that includes quality (depth) functions to estimate how desired a specific value is, weights for each feature preference, the desired diversity of feature values, and the relative importance of diversity versus depth. The system applies statistical

Societal objectives as drivers in the search for criteria weights when ranking energy efficiency measures

International Nuclear Information System (INIS)

Sousa, José L.; Martins, António G.; Jorge, Humberto M.

2012-01-01

In this paper we address a ranking problem from a tender mechanism established by the Portuguese energy regulator to promote energy efficiency measures in electricity consumption. Measures candidates to this tender are subjected to previously known assessment rules, and weighted criteria. Our proposal has explicitly taken avoided consumption and cost of saved kWh as decision variables for defining two societal objectives. In order to define ranges for the weights of the criteria and reference performance values, the search for the most suitable sets of weights is done by an evolutionary algorithm. Measures were used that applied for funding in previous tender calls. The results demonstrate that in face of different sets of measures, the range of weights for each criterion may vary significantly. The proposal, besides helping to obtain a more suitable set of criteria weights, can also assist in the very process of formulating the criteria, in view of the regulator’s societal objectives, since it was found that some of the used criteria actually lack the ability to discriminate between candidate measures. After a post-processing analysis, the DM is presented with a set of criteria weights from which he can select the one that better reflects his preferences. - Highlights: ► We address a Portuguese energy efficiency fostering tender mechanism. ► We used a genetic algorithm to search for sets of criteria weights. ► We used societal objectives to guide the selection of energy efficiency measures. ► Flexibility in the weights can help finding the best possible use of public money.

Examination Malpractice in Nigeria: Rank-ordering the Types ...

African Journals Online (AJOL)

Although 'giraffing' and carrying of prepared materials into the examination hall were the most common forms of examination malpractice, bribery (ranked 4.5) was the anchor. Students, peer group and parents were the worst malpractitioners in a decreasing order of culpability. Overvaluing of certificates and teachers' ...

PageRank tracker: from ranking to tracking.

Science.gov (United States)

Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

2014-06-01

Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

Experimental congruence of interval scale production from paired comparisons and ranking for image evaluation

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Handley, John C.; Babcock, Jason S.; Pelz, Jeff B.

2003-12-01

Image evaluation tasks are often conducted using paired comparisons or ranking. To elicit interval scales, both methods rely on Thurstone's Law of Comparative Judgment in which objects closer in psychological space are more often confused in preference comparisons by a putative discriminal random process. It is often debated whether paired comparisons and ranking yield the same interval scales. An experiment was conducted to assess scale production using paired comparisons and ranking. For this experiment a Pioneer Plasma Display and Apple Cinema Display were used for stimulus presentation. Observers performed rank order and paired comparisons tasks on both displays. For each of five scenes, six images were created by manipulating attributes such as lightness, chroma, and hue using six different settings. The intention was to simulate the variability from a set of digital cameras or scanners. Nineteen subjects, (5 females, 14 males) ranging from 19-51 years of age participated in this experiment. Using a paired comparison model and a ranking model, scales were estimated for each display and image combination yielding ten scale pairs, ostensibly measuring the same psychological scale. The Bradley-Terry model was used for the paired comparisons data and the Bradley-Terry-Mallows model was used for the ranking data. Each model was fit using maximum likelihood estimation and assessed using likelihood ratio tests. Approximate 95% confidence intervals were also constructed using likelihood ratios. Model fits for paired comparisons were satisfactory for all scales except those from two image/display pairs; the ranking model fit uniformly well on all data sets. Arguing from overlapping confidence intervals, we conclude that paired comparisons and ranking produce no conflicting decisions regarding ultimate ordering of treatment preferences, but paired comparisons yield greater precision at the expense of lack-of-fit.

Frames for exact inversion of the rank order coder.

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Masmoudi, Khaled; Antonini, Marc; Kornprobst, Pierre

2012-02-01

Our goal is to revisit rank order coding by proposing an original exact decoding procedure for it. Rank order coding was proposed by Thorpe et al. who stated that the order in which the retina cells are activated encodes for the visual stimulus. Based on this idea, the authors proposed in [1] a rank order coder/decoder associated to a retinal model. Though, it appeared that the decoding procedure employed yields reconstruction errors that limit the model bit-cost/quality performances when used as an image codec. The attempts made in the literature to overcome this issue are time consuming and alter the coding procedure, or are lacking mathematical support and feasibility for standard size images. Here we solve this problem in an original fashion by using the frames theory, where a frame of a vector space designates an extension for the notion of basis. Our contribution is twofold. First, we prove that the analyzing filter bank considered is a frame, and then we define the corresponding dual frame that is necessary for the exact image reconstruction. Second, to deal with the problem of memory overhead, we design a recursive out-of-core blockwise algorithm for the computation of this dual frame. Our work provides a mathematical formalism for the retinal model under study and defines a simple and exact reverse transform for it with over than 265 dB of increase in the peak signal-to-noise ratio quality compared to [1]. Furthermore, the framework presented here can be extended to several models of the visual cortical areas using redundant representations.

Discrepancies between multicriteria decision analysis-based ranking and intuitive ranking for pharmaceutical benefit-risk profiles in a hypothetical setting.

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Hoshikawa, K; Ono, S

2017-02-01

Multicriteria decision analysis (MCDA) has been generally considered a promising decision-making methodology for the assessment of drug benefit-risk profiles. There have been many discussions in both public and private sectors on its feasibility and applicability, but it has not been employed in official decision-makings. For the purpose of examining to what extent MCDA would reflect the first-hand, intuitive preference of evaluators in practical pharmaceutical assessments, we conducted a questionnaire survey involving the participation of employees of pharmaceutical companies. Showing profiles of the efficacy and safety of four hypothetical drugs, each respondent was asked to rank them following the standard MCDA process and then to rank them intuitively (i.e. without applying any analytical framework). These two approaches resulted in substantially different ranking patterns from the same individuals, and the concordance rate was surprisingly low (17%). Although many respondents intuitively showed a preference for mild, balanced risk-benefit profiles over profiles with a conspicuous advantage in either risk or benefit, the ranking orders based on MCDA scores did not reflect the intuitive preference. Observed discrepancies between the rankings seemed to be primarily attributed to the structural characteristics of MCDA, which assumes that evaluation on each benefit and risk component should have monotonic impact on final scores. It would be difficult for MCDA to reflect commonly observed non-monotonic preferences for risk and benefit profiles. Possible drawbacks of MCDA should be further investigated prior to the real-world application of its benefit-risk assessment. © 2016 John Wiley & Sons Ltd.

Color preferences change after experience with liked/disliked colored objects.

Science.gov (United States)

Strauss, Eli D; Schloss, Karen B; Palmer, Stephen E

2013-10-01

How are color preferences formed, and can they be changed by affective experiences with correspondingly colored objects? We examined these questions by testing whether affectively polarized experiences with images of colored objects would cause changes in color preferences. Such changes are implied by the ecological valence theory (EVT), which posits that color preferences are determined by people's average affective responses to correspondingly colored objects (Palmer & Schloss, Proceedings of the National Academy of Sciences, 107, 8877-8882, 2010). Seeing images of strongly liked (and disliked) red and green objects, therefore, should lead to increased (and decreased) preferences for correspondingly colored red and green color patches. Experiment 1 showed that this crossover interaction did occur, but only if participants were required to evaluate their preferences for the colored objects when they saw them. Experiment 2 showed that these overall changes decreased substantially over a 24-h delay, but the degree to which the effect lasted for individuals covaried with the magnitude of the effects immediately after object exposure. Experiment 3 demonstrated a similar, but weaker, effect of affectively biased changes in color preferences when participants did not see, but only imagined, the colored objects. The overall pattern of results indicated that color preferences are not fixed, but rather are shaped by affective experiences with colored objects. Possible explanations for the observed changes in color preferences were considered in terms of associative learning through evaluative conditioning and/or priming of prior knowledge in memory.

The Consistent Preferences Approach to Deductive Reasoning in Games

CERN Document Server

Asheim, Geir B

2006-01-01

"The Consistent Preferences Approach to Deductive Reasoning in Games" presents, applies, and synthesizes what my co-authors and I have called the 'consistent preferences' approach to deductive reasoning in games. Briefly described, this means that the object of the analysis is the ranking by each player of his own strategies, rather than his choice. The ranking can be required to be consistent (in different senses) with his beliefs about the opponent's ranking of her strategies. This can be contrasted to the usual 'rational choice' approach where a player's strategy choice is (in dif

Ranking Schools' Academic Performance Using a Fuzzy VIKOR

Science.gov (United States)

Musani, Suhaina; Aziz Jemain, Abdul

2015-06-01

Determination rank is structuring alternatives in order of priority. It is based on the criteria determined for each alternative involved. Evaluation criteria are performed and then a composite index composed of each alternative for the purpose of arranging in order of preference alternatives. This practice is known as multiple criteria decision making (MCDM). There are several common approaches to MCDM, one of the practice is known as VIKOR (Multi-criteria Optimization and Compromise Solution). The objective of this study is to develop a rational method for school ranking based on linguistic information of a criterion. The school represents an alternative, while the results for a number of subjects as the criterion. The results of the examination for a course, is given according to the student percentage of each grade. Five grades of excellence, honours, average, pass and fail is used to indicate a level of achievement in linguistics. Linguistic variables are transformed to fuzzy numbers to form a composite index of school performance. Results showed that fuzzy set theory can solve the limitations of using MCDM when there is uncertainty problems exist in the data.

Birth Order and Vocational Preference.

Science.gov (United States)

Lynch, Robert M.; Lynch, Janet

1980-01-01

The relationship between vocational preferences of adolescents and their birth order was examined. Firstborns were found to be overrepresented in the conventional and enterprising areas; later borns were found to be overrepresented in the social and investigative areas. (Author/GK)

Patients' self-interested preferences: empirical evidence from a priority setting experiment.

Science.gov (United States)

Alvarez, Begoña; Rodríguez-Míguez, Eva

2011-04-01

This paper explores whether patients act according to self-interest in priority setting experiments. The analysis is based on a ranking experiment, conducted in Galicia (Spain), to elicit preferences regarding the prioritization of patients on a waiting list for an elective surgical intervention (prostatectomy for benign prostatic hyperplasia). Participants were patients awaiting a similar intervention and members of the general populations. All of them were asked to rank hypothetical patients on a waiting list. A rank-ordered logit was then applied to their responses in order to obtain a prioritization scoring system. Using these estimations, we first test for differences in preferences between patients and general population. Second, we implement a procedure based on the similarity between respondents (true patients) and the hypothetical scenarios they evaluate (hypothetical patients) to analyze whether patients provide self-interested rankings. Our results show that patient preferences differ significantly from general population preferences. The findings also indicate that, when patients rank the hypothetical scenarios on the waiting list, they consider not only the explicit attributes but also the similarity of each scenario to their own. In particular, they assign a higher priority to scenarios that more closely match their own states. We also find that such a preference structure increases their likelihood of reporting "irrational" answers. Copyright © 2011 Elsevier Ltd. All rights reserved.

Rank-Ordered Multifractal Analysis (ROMA of probability distributions in fluid turbulence

Directory of Open Access Journals (Sweden)

C. C. Wu

2011-04-01

Full Text Available Rank-Ordered Multifractal Analysis (ROMA was introduced by Chang and Wu (2008 to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF simultaneously is introduced.

Mutual Fund Tournament: Risk Taking Incentives Induced by Ranking Objectives

OpenAIRE

Goriaev, A.P.; Palomino, F.A.; Prat, A.

2000-01-01

There is now extensive empirical evidence showing that fund managers have relative performance objectives and adapt their investment strategy in the last part of the calendar year to their performance in the early part of the year. However, emphasis was put on returns in excess of some exogenous benchmark return.In this paper, we investigate whether fund managers have ranking objectives (as in a tournament).First, in a two-period model, we analyze the game played by two risk-neutral fund mana...

Young Children's Color Preferences in the Interior Environment

Science.gov (United States)

Read, Marilyn A.; Upington, Deborah

2009-01-01

This study focuses on children's color preferences in the interior environment. Previous studies highlight young children's preferences for the colors red and blue. The methods of this study used a rank ordering technique and a semi-structured interview process with 3-, 4-, and 5-year-old children. Findings reveal that children prefer the color…

Ranking of lignocellulosic biomass pellets through multicriteria modeling

Energy Technology Data Exchange (ETDEWEB)

Sultana, A.; Kumar, A. [Alberta Univ., Edmonton, AB (Canada). Dept. of Mechanical Engineering

2009-07-01

A study was conducted in which pellets from different lignocellulosic biomass sources were ranked using a multicriteria assessment model. Five different pellet alternatives were compared based on 10 criteria. The pair-wise comparison was done in order to develop preference indices for various alternatives. The methodology used in this study was the Preference Ranking Organization Method for Enrichment and Evaluation (PROMETHEE). The biomass included wood pellets, straw pellets, switchgrass pellets, alfalfa pellets and poultry pellets. The study considered both quantitative and qualitative criteria such as energy consumption to produce the pellets, production cost, bulk density, NOx emissions, SOx emissions, deposit formation, net calorific value, moisture content, maturity of technology, and quality of material. A sensitivity analysis was performed by changing weights of criteria and threshold values of the criteria. Different scenarios were developed for ranking cost and environmental impacts. According to preliminary results, the wood pellet is the best energy source, followed by switchgrass pellets, straw pellets, alfalfa pellets and poultry pellets.

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

Science.gov (United States)

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

Low rank approach to computing first and higher order derivatives using automatic differentiation

International Nuclear Information System (INIS)

Reed, J. A.; Abdel-Khalik, H. S.; Utke, J.

2012-01-01

This manuscript outlines a new approach for increasing the efficiency of applying automatic differentiation (AD) to large scale computational models. By using the principles of the Efficient Subspace Method (ESM), low rank approximations of the derivatives for first and higher orders can be calculated using minimized computational resources. The output obtained from nuclear reactor calculations typically has a much smaller numerical rank compared to the number of inputs and outputs. This rank deficiency can be exploited to reduce the number of derivatives that need to be calculated using AD. The effective rank can be determined according to ESM by computing derivatives with AD at random inputs. Reduced or pseudo variables are then defined and new derivatives are calculated with respect to the pseudo variables. Two different AD packages are used: OpenAD and Rapsodia. OpenAD is used to determine the effective rank and the subspace that contains the derivatives. Rapsodia is then used to calculate derivatives with respect to the pseudo variables for the desired order. The overall approach is applied to two simple problems and to MATWS, a safety code for sodium cooled reactors. (authors)

Change in ranking order of prescribing patterns by age and sex standardization of the practice population--audit may be misleading

DEFF Research Database (Denmark)

Olesen, Frede; Vedsted, Peter; Nielsen, Jørgen Nørskov

1996-01-01

on the age, sex, and numbers of patients per practice was also obtained. The direct standardization method was used to adjust practice populations for age and sex. SETTING: The town of Randers, Aarhus County, Denmark. SUBJECTS: 35 practices, 41 GPs. MAIN OUTCOME MEASURES: Ranking of the 35 practices......OBJECTIVE: To demonstrate whether standardization of practice populations by age and sex changes the internal prescription ranking order of a group of practices. DESIGN: Data on the prescribing of cardiovascular drugs in a group of practices were obtained from a county-based database. Information...

Change in ranking order of prescribing patterns by age and sex standardization of the practice population--audit may be misleading

DEFF Research Database (Denmark)

Olesen, Frede; Vedsted, Peter; Nielsen, Jørgen Nørskov

1996-01-01

OBJECTIVE: To demonstrate whether standardization of practice populations by age and sex changes the internal prescription ranking order of a group of practices. DESIGN: Data on the prescribing of cardiovascular drugs in a group of practices were obtained from a county-based database. Information...... on the age, sex, and numbers of patients per practice was also obtained. The direct standardization method was used to adjust practice populations for age and sex. SETTING: The town of Randers, Aarhus County, Denmark. SUBJECTS: 35 practices, 41 GPs. MAIN OUTCOME MEASURES: Ranking of the 35 practices...... of the practices. Only four practices did not change ranking position, while four moved more than ten places. The slope between highest and lowest ranked practice did not diminish after standardization. CONCLUSION: Care should be taken when comparing peer prescribing patterns from crude utilization data, and we...

Preference Construction Processes for Renewable Energies: Assessing the Influence of Sustainability Information and Decision Support Methods

Directory of Open Access Journals (Sweden)

Kiyotada Hayashi

2016-11-01

Full Text Available Sustainability information and decision support can be two important driving forces for making sustainable transitions in society. However, not enough knowledge is available on the effectiveness of these two factors. Here, we conducted an experimental study to support the hypotheses that acquisition of sustainability information and use of decision support methods consistently construct preferences for renewable power generation technologies that use solar power, wind power, small-scale hydroelectric power, geothermal power, wood biomass, or biogas as energy sources. The sustainability information was prepared using a renewable energy-focused input-output model of Japan and contained life cycle greenhouse gas emissions, electricity generation costs, and job creation. We measured rank-ordered preferences in the following four steps in experimental workshops conducted for municipal officials: provision of (1 energy-source names; (2 sustainability information; (3 additional explanation of public value; and (4 knowledge and techniques about multi-attribute value functions. The degree of changes in preference orders was evaluated using Spearman’s rank correlation coefficient. The consistency of rank-ordered preferences among participants was determined by using the maximum eigenvalue for the coefficient matrix. The results show: (1 the individual preferences evolved drastically in response to the sustainability information and the decision support method; and (2 the rank-ordered preferences were more consistent during the preference construction processes. These results indicate that provision of sustainability information, coupled with decision support methods, is effective for decision making regarding renewable energies.

Lexical preferences in Dutch verbal cluster ordering

NARCIS (Netherlands)

Bloem, J.; Bellamy, K.; Karvovskaya, E.; Kohlberger, M.; Saad, G.

2016-01-01

This study discusses lexical preferences as a factor affecting the word order variation in Dutch verbal clusters. There are two grammatical word orders for Dutch two-verb clusters, with no clear meaning difference. Using the method of collostructional analysis, I find significant associations

On the ranking of chemicals based on their PBT characteristics: comparison of different ranking methodologies using selected POPs as an illustrative example.

Science.gov (United States)

Sailaukhanuly, Yerbolat; Zhakupbekova, Arai; Amutova, Farida; Carlsen, Lars

2013-01-01

Knowledge of the environmental behavior of chemicals is a fundamental part of the risk assessment process. The present paper discusses various methods of ranking of a series of persistent organic pollutants (POPs) according to the persistence, bioaccumulation and toxicity (PBT) characteristics. Traditionally ranking has been done as an absolute (total) ranking applying various multicriteria data analysis methods like simple additive ranking (SAR) or various utility functions (UFs) based rankings. An attractive alternative to these ranking methodologies appears to be partial order ranking (POR). The present paper compares different ranking methods like SAR, UF and POR. Significant discrepancies between the rankings are noted and it is concluded that partial order ranking, as a method without any pre-assumptions concerning possible relation between the single parameters, appears as the most attractive ranking methodology. In addition to the initial ranking partial order methodology offers a wide variety of analytical tools to elucidate the interplay between the objects to be ranked and the ranking parameters. In the present study is included an analysis of the relative importance of the single P, B and T parameters. Copyright © 2012 Elsevier Ltd. All rights reserved.

Evaluation of image reconstruction methods for 123I-MIBG-SPECT. A rank-order study

International Nuclear Information System (INIS)

Soederberg, Marcus; Mattsson, Soeren; Oddstig, Jenny; Uusijaervi-Lizana, Helena; Leide-Svegborn, Sigrid; Valind, Sven; Thorsson, Ola; Garpered, Sabine; Prautzsch, Tilmann; Tischenko, Oleg

2012-01-01

Background: There is an opportunity to improve the image quality and lesion detectability in single photon emission computed tomography (SPECT) by choosing an appropriate reconstruction method and optimal parameters for the reconstruction. Purpose: To optimize the use of the Flash 3D reconstruction algorithm in terms of equivalent iteration (EI) number (number of subsets times the number of iterations) and to compare with two recently developed reconstruction algorithms ReSPECT and orthogonal polynomial expansion on disc (OPED) for application on 123 I-metaiodobenzylguanidine (MIBG)-SPECT. Material and Methods: Eleven adult patients underwent SPECT 4 h and 14 patients 24 h after injection of approximately 200 MBq 123 I-MIBG using a Siemens Symbia T6 SPECT/CT. Images were reconstructed from raw data using the Flash 3D algorithm at eight different EI numbers. The images were ranked by three experienced nuclear medicine physicians according to their overall impression of the image quality. The obtained optimal images were then compared in one further visual comparison with images reconstructed using the ReSPECT and OPED algorithms. Results: The optimal EI number for Flash 3D was determined to be 32 for acquisition 4 h and 24 h after injection. The average rank order (best first) for the different reconstructions for acquisition after 4 h was: Flash 3D 32 > ReSPECT > Flash 3D 64 > OPED, and after 24 h: Flash 3D 16 > ReSPECT > Flash 3D 32 > OPED. A fair level of inter-observer agreement concerning optimal EI number and reconstruction algorithm was obtained, which may be explained by the different individual preferences of what is appropriate image quality. Conclusion: Using Siemens Symbia T6 SPECT/CT and specified acquisition parameters, Flash 3D 32 (4 h) and Flash 3D 16 (24 h), followed by ReSPECT, were assessed to be the preferable reconstruction algorithms in visual assessment of 123 I-MIBG images

Higher-order risk preferences in social settings.

Science.gov (United States)

Heinrich, Timo; Mayrhofer, Thomas

2018-01-01

We study prudence and temperance (next to risk aversion) in social settings. Previous experimental studies have shown that these higher-order risk preferences affect the choices of individuals deciding privately on lotteries that only affect their own payoff. Yet, many risky and financially relevant decisions are made in the social settings of households or organizations. We elicit higher-order risk preferences of individuals and systematically vary how an individual's decision is made (alone or while communicating with a partner) and who is affected by the decision (only the individual or the partner as well). In doing so, we can isolate the effects of other-regarding concerns and communication on choices. Our results reveal that the majority of choices are risk averse, prudent, and temperate across social settings. We also observe that individuals are influenced significantly by the preferences of a partner when they are able to communicate and choices are payoff-relevant for both of them.

Ranked retrieval of segmented nuclei for objective assessment of cancer gene repositioning

Directory of Open Access Journals (Sweden)

Cukierski William J

2012-09-01

Full Text Available Abstract Background Correct segmentation is critical to many applications within automated microscopy image analysis. Despite the availability of advanced segmentation algorithms, variations in cell morphology, sample preparation, and acquisition settings often lead to segmentation errors. This manuscript introduces a ranked-retrieval approach using logistic regression to automate selection of accurately segmented nuclei from a set of candidate segmentations. The methodology is validated on an application of spatial gene repositioning in breast cancer cell nuclei. Gene repositioning is analyzed in patient tissue sections by labeling sequences with fluorescence in situ hybridization (FISH, followed by measurement of the relative position of each gene from the nuclear center to the nuclear periphery. This technique requires hundreds of well-segmented nuclei per sample to achieve statistical significance. Although the tissue samples in this study contain a surplus of available nuclei, automatic identification of the well-segmented subset remains a challenging task. Results Logistic regression was applied to features extracted from candidate segmented nuclei, including nuclear shape, texture, context, and gene copy number, in order to rank objects according to the likelihood of being an accurately segmented nucleus. The method was demonstrated on a tissue microarray dataset of 43 breast cancer patients, comprising approximately 40,000 imaged nuclei in which the HES5 and FRA2 genes were labeled with FISH probes. Three trained reviewers independently classified nuclei into three classes of segmentation accuracy. In man vs. machine studies, the automated method outperformed the inter-observer agreement between reviewers, as measured by area under the receiver operating characteristic (ROC curve. Robustness of gene position measurements to boundary inaccuracies was demonstrated by comparing 1086 manually and automatically segmented nuclei. Pearson

Knowledge extraction from evolving spiking neural networks with rank order population coding.

Science.gov (United States)

Soltic, Snjezana; Kasabov, Nikola

2010-12-01

This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

14 CFR 1214.1105 - Final ranking.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Final ranking. 1214.1105 Section 1214.1105... Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of... preference will be included in this final ranking in accordance with applicable regulations. ...

Assessing Women's Preferences and Preference Modeling for Breast Reconstruction Decision-Making.

Science.gov (United States)

Sun, Clement S; Cantor, Scott B; Reece, Gregory P; Crosby, Melissa A; Fingeret, Michelle C; Markey, Mia K

2014-03-01

Women considering breast reconstruction must make challenging trade-offs amongst issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using nine different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual wellbeing as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants' rankings. The median amount of time required to assess preferences was 34 minutes. Agreement among the nine preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best performing risk averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the seven attributes. We recommend the risk averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study.

A combined QSAR and partial order ranking approach to risk assessment.

Science.gov (United States)

Carlsen, L

2006-04-01

QSAR generated data appear as an attractive alternative to experimental data as foreseen in the proposed new chemicals legislation REACH. A preliminary risk assessment for the aquatic environment can be based on few factors, i.e. the octanol-water partition coefficient (Kow), the vapour pressure (VP) and the potential biodegradability of the compound in combination with the predicted no-effect concentration (PNEC) and the actual tonnage in which the substance is produced. Application of partial order ranking, allowing simultaneous inclusion of several parameters leads to a mutual prioritisation of the investigated substances, the prioritisation possibly being further analysed through the concept of linear extensions and average ranks. The ranking uses endpoint values (log Kow and log VP) derived from strictly linear 'noise-deficient' QSAR models as input parameters. Biodegradation estimates were adopted from the BioWin module of the EPI Suite. The population growth impairment of Tetrahymena pyriformis was used as a surrogate for fish lethality.

Evaluation of image reconstruction methods for {sup 123}I-MIBG-SPECT. A rank-order study

Energy Technology Data Exchange (ETDEWEB)

Soederberg, Marcus; Mattsson, Soeren; Oddstig, Jenny; Uusijaervi-Lizana, Helena; Leide-Svegborn, Sigrid [Medical Radiation Physics, Dept. of Clinical Sciences Malmoe, Lund Univ., Skaane Univ. Hospital, Malmoe (Sweden)], e-mail: marcus.soderberg@med.lu.se; Valind, Sven; Thorsson, Ola; Garpered, Sabine [Dept. of Clinical Physiology, Skaane Univ. Hospital, Malmoe (Sweden); Prautzsch, Tilmann [Scivis wissenschaftlice Bildverarbeitung GmbH, Goettingen (Germany); Tischenko, Oleg [Research Unit Medical Radiation Physics and Diagnostics (AMSD), Helmholtz Zentrum Muenchen (Germany); German Research Center for Environmental Health, Neuherberg (Germany)

2012-09-15

Background: There is an opportunity to improve the image quality and lesion detectability in single photon emission computed tomography (SPECT) by choosing an appropriate reconstruction method and optimal parameters for the reconstruction. Purpose: To optimize the use of the Flash 3D reconstruction algorithm in terms of equivalent iteration (EI) number (number of subsets times the number of iterations) and to compare with two recently developed reconstruction algorithms ReSPECT and orthogonal polynomial expansion on disc (OPED) for application on {sup 123}I-metaiodobenzylguanidine (MIBG)-SPECT. Material and Methods: Eleven adult patients underwent SPECT 4 h and 14 patients 24 h after injection of approximately 200 MBq {sup 123}I-MIBG using a Siemens Symbia T6 SPECT/CT. Images were reconstructed from raw data using the Flash 3D algorithm at eight different EI numbers. The images were ranked by three experienced nuclear medicine physicians according to their overall impression of the image quality. The obtained optimal images were then compared in one further visual comparison with images reconstructed using the ReSPECT and OPED algorithms. Results: The optimal EI number for Flash 3D was determined to be 32 for acquisition 4 h and 24 h after injection. The average rank order (best first) for the different reconstructions for acquisition after 4 h was: Flash 3D{sub 32} > ReSPECT > Flash 3D{sub 64} > OPED, and after 24 h: Flash 3D{sub 16} > ReSPECT > Flash 3D{sub 32} > OPED. A fair level of inter-observer agreement concerning optimal EI number and reconstruction algorithm was obtained, which may be explained by the different individual preferences of what is appropriate image quality. Conclusion: Using Siemens Symbia T6 SPECT/CT and specified acquisition parameters, Flash 3D{sub 32} (4 h) and Flash 3D{sub 16} (24 h), followed by ReSPECT, were assessed to be the preferable reconstruction algorithms in visual assessment of {sup 123}I-MIBG images.

Comparing individual preferences for four meditation techniques: Zen, Vipassana (Mindfulness), Qigong, and Mantra.

Science.gov (United States)

Burke, Adam

2012-01-01

A significant number of studies have been published examining the mind-body effects of meditation and its clinical efficacy. There are very few studies, however, which directly compare different meditation methods with each other to explore potentially distinct mechanisms and effects, and no studies comparing individual preferences for different methods. As preference is seen as an important factor in consumer healthcare decision making, greater understanding of this aspect is needed as meditation becomes a more widely used therapeutic modality. For this reason a pilot study was conducted to compare four meditation techniques for personal preference. A within-subjects comparison design was employed. A convenience sample of 247 undergraduate university students participated in the study. Participants learned two open observing meditation techniques-Vipassana (Mindfulness) and Zen, and two focused attention techniques-Mantra and Qigong Visualization, practicing one method per week. At the end of a six-week training period participants ranked the four meditation methods in order of personal preference. Ranking of subjective preference of meditations practiced. A within subjects comparison revealed that significantly more participants chose Vipassana or Mantra meditation as their preferred techniques compared with Qigong Visualization and Zen. This study provides information on differences in preference for type of meditation. As the benefits of meditation accrue over time, selecting a method that motivates sustained practice is a critical objective if therapeutic effects are to be achieved. Copyright © 2012 Elsevier Inc. All rights reserved.

Bayesian framework for managing preferences in decision-making

International Nuclear Information System (INIS)

Maes, Marc A.; Faber, Michael H.

2006-01-01

A rational decision-making process does not exclude the possibility of decision makers expressing different preferences and disagreeing regarding the effects of consequences and optimal course of actions. This point of view is explored in depth in this paper. A framework is developed that includes several decision makers (instead of just one) and allows for the variability of preferences among these decision makers. The information provided by the varying opinions of decision makers can be used to optimize our own decision-making. To achieve this, likelihood functions are developed for stated preferences among both discrete and continuous alternatives, and stated preference rankings of alternatives. Two applications are pursued: the optimization of the lifecycle utility of a structural system subject to consequences of failure proportional to the intensity of hazards exceeding a variable threshold, and to follow-up consequences. Also, the problem of tight decisions or close calls is investigated in order to explore the efficiency of a Bayesian approach using stated preferences and stated rankings

A quantitative experimental paradigm to optimize construction of rank order lists in the National Resident Matching Program: the ROSS-MOORE approach.

Science.gov (United States)

Ross, David A; Moore, Edward Z

2013-09-01

As part of the National Resident Matching Program, programs must submit a rank order list of desired applicants. Despite the importance of this process and the numerous manifest limitations with traditional approaches, minimal research has been conducted to examine the accuracy of different ranking strategies. The authors developed the Moore Optimized Ordinal Rank Estimator (MOORE), a novel algorithm for ranking applicants that is based on college sports ranking systems. Because it is not possible to study the Match in vivo, the authors then designed the Recruitment Outcomes Simulation System (ROSS). This program was used to simulate a series of interview seasons and to compare MOORE and traditional approaches under different conditions. The accuracy of traditional ranking and the MOORE approach are equally and adversely affected with higher levels of intrarater variability. However, compared with traditional ranking methods, MOORE produces a more accurate rank order list as interrater variability increases. The present data demonstrate three key findings. First, they provide proof of concept that it is possible to scientifically test the accuracy of different rank methods used in the Match. Second, they show that small amounts of variability can have a significant adverse impact on the accuracy of rank order lists. Finally, they demonstrate that an ordinal approach may lead to a more accurate rank order list in the presence of interviewer bias. The ROSS-MOORE approach offers programs a novel way to optimize the recruitment process and, potentially, to construct a more accurate rank order list.

Multi-attribute risk assessment for risk ranking of natural gas pipelines

International Nuclear Information System (INIS)

Brito, A.J.; Almeida, A.T. de

2009-01-01

The paper presents a decision model for risk assessment and for risk ranking of sections of natural gas pipelines based on multi-attribute utility theory. Pipeline hazard scenarios are surveyed and the reasons for a risk assessment model based on a multi-attribute approach are presented. Three dimensions of impact and the need to translate decision-makers' preferences into risk management decisions are highlighted. The model approaches these factors by using a multi-attribute utility function, in order to produce multi-dimensional risk measurements. By using decision analysis concepts, this model quantitatively incorporates the decision-maker's preferences and behavior regarding risk within clear and consistent risk measurements. In order to support the prioritizing of critical sections of pipeline in natural gas companies, this multi-attribute model also allows sections of pipeline to be ranked into a risk hierarchy. A numerical application based on a real case study was undertaken so that the effectiveness of the decision model could be verified

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan

2014-04-17

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

Centrally-administered oxytocin promotes preference for familiar objects at a short delay in ovariectomized female rats.

Science.gov (United States)

Madularu, Dan; Athanassiou, Maria; Yee, Jason R; Mumby, Dave G

2014-11-01

Oxytocin has been previously associated with social attachment behaviors in various species, however, most studies focused on partner preference in the socially-monogamous prairie vole. In these, oxytocin treatment was shown to promote partner preference, such that females receiving either central or pulsatile peripheral administration would spend more time with a familiar male. This behavioral outcome was blocked by oxytocin receptor antagonist treatment. The aim of the current study was to further explore the preference-inducing properties of oxytocin by examining its effects on object preference on ovariectomized female rats. In other words, we assessed whether these effects would apply to objects and if they would be persistent across species. Eight rats were infused with oxytocin into the left ventricle and object preference was assessed at two delays: 30min and 4h. At the 30min delay, oxytocin-treated animals showed preference for the familiar object, whereas saline-treated controls exhibited preference for the novel object. At the 4h delay, both groups showed novel-object preference. Our findings show that oxytocin modulates object preference in the female rat at a shorter delay, similar to the findings from partner-preference studies in the prairie vole, suggesting that the mechanisms driving object preference might be in part similar to those responsible for partner preference. Copyright © 2014 Elsevier B.V. All rights reserved.

Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach

International Nuclear Information System (INIS)

Wang, Endong

2015-01-01

Highlights: • A TOPSIS based multi-criteria whole-building energy benchmarking is developed. • A selective objective-weighting procedure is used for a cost-accuracy tradeoff. • Results from a real case validated the benefits of the presented approach. - Abstract: This paper develops a robust multi-criteria Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based building energy efficiency benchmarking approach. The approach is explicitly selective to address multicollinearity trap due to the subjectivity in selecting energy variables by considering cost-accuracy trade-off. It objectively weights the relative importance of individual pertinent efficiency measuring criteria using either multiple linear regression or principal component analysis contingent on meta data quality. Through this approach, building energy performance is comprehensively evaluated and optimized. Simultaneously, the significant challenges associated with conventional single-criterion benchmarking models can be avoided. Together with a clustering algorithm on a three-year panel dataset, the benchmarking case of 324 single-family dwellings demonstrated an improved robustness of the presented multi-criteria benchmarking approach over the conventional single-criterion ones

Extraction and Preference Ordering of Multireservoir Water Supply Rules in Dry Years

Directory of Open Access Journals (Sweden)

Ling Kang

2016-01-01

Full Text Available This paper presents a new methodology of combined use of the nondominated sorting genetic algorithm II (NSGA-II and the approach of successive elimination of alternatives based on order and degree of efficiency (SEABODE in identifying the most preferred multireservoir water supply rules in dry years. First, the suggested operation rules consists of a two-point type time-varying hedging policy for a single reservoir and a simple proportional allocation policy of common water demand between two parallel reservoirs. Then, the NSGA-II is employed to derive enough noninferior operation rules (design alternatives in terms of two conflicting objectives (1 minimizing the total deficit ratio (TDR of all demands of the entire system in operation horizon, and (2 minimizing the maximum deficit ratio (MDR of water supply in a single period. Next, the SEABODE, a multicriteria decision making (MCDM procedure, is applied to further eliminate alternatives based on the concept of efficiency of order k with degree p. In SEABODE, the reservoir performance indices and water shortage indices are selected as evaluation criteria for preference ordering among the design alternatives obtained by NSGA-II. The proposed methodology was tested on a regional water supply system with three reservoirs located in the Jialing River, China, where the results demonstrate its applicability and merits.

Algorithm of resonance orders for the objects

Science.gov (United States)

Zhang, YongGang; Zhang, JianXue

2018-03-01

In mechanical engineering, the object resonance phenomena often occur when the external incident wave frequency is close to object of the natural frequency. Object resonance phenomena get the maximum value when the external incident frequency is equal to object the natural frequency. Experiments found that resonance intension of the object is changed, different objects resonance phenomena present different characteristics of ladders. Based on object orders resonance characteristics, the calculation method of object orders resonance is put forward in the paper, and the application for the light and sound waves on the seven order resonance characteristics by people feel, the result error is less than 1%.Visible in this paper, the method has high accuracy and usability. The calculation method reveals that some object resonance occur present order characteristic only four types, namely the first-orders resonance characteristics, third-orders characteristics, five orders characteristic, and seven orders characteristic.

Young children's preference for unique owned objects.

Science.gov (United States)

Gelman, Susan A; Davidson, Natalie S

2016-10-01

An important aspect of human thought is the value we place on unique individuals. Adults place higher value on authentic works of art than exact replicas, and young children at times value their original possessions over exact duplicates. What is the scope of this preference in early childhood, and when do children understand its subjective nature? On a series of trials, we asked three-year-olds (N=36) to choose between two toys for either themselves or the researcher: an old (visibly used) toy vs. a new (more attractive) toy matched in type and appearance (e.g., old vs. brand-new blanket). Focal pairs contrasted the child's own toy with a matched new object; Control pairs contrasted toys the child had never seen before. Children preferred the old toys for Focal pairs only, and treated their own preferences as not shared by the researcher. By 3years of age, young children place special value on unique individuals, and understand the subjective nature of that value. Copyright © 2016 Elsevier B.V. All rights reserved.

EVALUATION AND RANKING OF ARTIFICIAL HIP PROSTHESIS SUPPLIERS BY USING A FUZZY TOPSIS METHODOLOGY

Directory of Open Access Journals (Sweden)

Marija Zahar Djordjevic

2014-06-01

Full Text Available The aim of this study is to propose a fuzzy multi-criteria decision-making approach (MCDM to evaluate the artificial hip prosthesis suppliers with respect to numerous criteria, simultaneously, taking into account the type of each criteria and its relative importance. The fuzzy of the Technique for Order Preference by Similarity to Ideal Solution (FTOSISis applied in order to rank the artificial hip prosthesis suppliers. The rank is obtained using the process of fuzzy number comparison. Software solution based on suggested method is also presented. A real-life example with real data is presented to clarify the proposed method.

Wikipedia ranking of world universities

Science.gov (United States)

Lages, José; Patt, Antoine; Shepelyansky, Dima L.

2016-03-01

We use the directed networks between articles of 24 Wikipedia language editions for producing the wikipedia ranking of world Universities (WRWU) using PageRank, 2DRank and CheiRank algorithms. This approach allows to incorporate various cultural views on world universities using the mathematical statistical analysis independent of cultural preferences. The Wikipedia ranking of top 100 universities provides about 60% overlap with the Shanghai university ranking demonstrating the reliable features of this approach. At the same time WRWU incorporates all knowledge accumulated at 24 Wikipedia editions giving stronger highlights for historically important universities leading to a different estimation of efficiency of world countries in university education. The historical development of university ranking is analyzed during ten centuries of their history.

Do patient and practice characteristics confound age-group differences in preferences for general practice care? A quantitative study

Science.gov (United States)

2013-01-01

Background Previous research showed inconsistent results regarding the relationship between the age of patients and preference statements regarding GP care. This study investigates whether elderly patients have different preference scores and ranking orders concerning 58 preference statements for GP care than younger patients. Moreover, this study examines whether patient characteristics and practice location may confound the relationship between age and the categorisation of a preference score as very important. Methods Data of the Consumer Quality Index GP Care were used, which were collected in 32 general practices in the Netherlands. The rank order and preference score were calculated for 58 preference statements for four age groups (0–30, 31–50, 51–74, 75 years and older). Using chi-square tests and logistic regression analyses, it was investigated whether a significant relationship between age and preference score was confounded by patient characteristics and practice location. Results Elderly patients did not have a significant different ranking order for the preference statements than the other three age groups (r = 0.0193; p = 0.41). However, in 53% of the statements significant differences were found in preference score between the four age groups. Elderly patients categorized significantly less preference statements as ‘very important’. In most cases, the significant relationships were not confounded by gender, education, perceived health, the number of GP contacts and location of the GP practice. Conclusion The preferences of elderly patients for GP care concern the same items as younger patients. However, their preferences are less strong, which cannot be ascribed to gender, education, perceived health, the number of GP contacts and practice location. PMID:23800156

Perturbation theory for nematic liquid crystals of axially symmetric molecules: Evaluation of fourth rank orientational order parameter

International Nuclear Information System (INIS)

Singh, K.

1993-11-01

Using a statistical mechanical perturbation theory for isotropic-nematic transition we report a calculation of second and fourth rank orientation order parameters and thermodynamic properties for a model system of prolate ellipsoids of revolution parameterized by its length-to-width ratio. The influence of attractive potential represented by dispersion interaction on a variety of thermodynamic properties is analysed. Inclusion of fourth rank orientational order parameter in calculation slightly changes the transition parameter. (author). 7 refs, 1 tab

Processing subject-object ambiguities in Dutch

NARCIS (Netherlands)

Kaan, Edith

1997-01-01

Various clause types in Dutch and German are at least temporarily ambiguous with respect to the order of subject and object. A number of previous studies regarding the processing of such subject-object ambiguities have reported a preference for a subject-object interpretation. This order preference

Inequality of the Russian population in terms of quality of life and social preference order

Directory of Open Access Journals (Sweden)

Yu. P. Averin

2014-01-01

Full Text Available It is considered in this article a methodology way for research of people’s inequality in relation to quality life, and a mechanism influence it upon attitude towards contemporary social order in society and state, upon preference of the different communities in relation to it changes in dependence on condition of their quality life. It is showed the possibilities of the synergetic way to give an explanation this influence upon. Based on the results of sociological research of the objective and subjective variables is done the analysis of a inequality in relation to quality life among the residents of different types of Russian settlements - administrative and region towns, village community. It is exposed the preference dispositions of the residents in relation to democratic socialism, liberal democracy and “middle” order in comparison with them in dependence on condition of their quality life. It is done a conclusion about what a structure of the material and spiritual variables of quality life have an influence upon choice the residents the types of given order at present.

Visual Field Preferences of Object Analysis for Grasping with One Hand

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Ada eLe

2014-10-01

Full Text Available When we grasp an object using one hand, the opposite hemisphere predominantly guides the motor control of grasp movements (Davare et al. 2007; Rice et al. 2007. However, it is unclear whether visual object analysis for grasp control relies more on inputs (a from the contralateral than the ipsilateral visual field, (b from one dominant visual field regardless of the grasping hand, or (c from both visual fields equally. For bimanual grasping of a single object we have recently demonstrated a visual field preference for the left visual field (Le and Niemeier 2013a, 2013b, consistent with a general right-hemisphere dominance for sensorimotor control of bimanual grasps (Le et al., 2013. But visual field differences have never been tested for unimanual grasping. Therefore, here we asked right-handed participants to fixate to the left or right of an object and then grasp the object either with their right or left hand using a precision grip. We found that participants grasping with their right hand performed better with objects in the right visual field: maximum grip apertures (MGAs were more closely matched to the object width and were smaller than for objects in the left visual field. In contrast, when people grasped with their left hand, preferences switched to the left visual field. What is more, MGA scaling showed greater visual field differences compared to right-hand grasping. Our data suggest that, visual object analysis for unimanual grasping shows a preference for visual information from the ipsilateral visual field, and that the left hemisphere is better equipped to control grasps in both visual fields.

Something Old, Something New: A Developmental Transition from Familiarity to Novelty Preferences with Hidden Objects

Science.gov (United States)

Shinskey, Jeanne L.; Munakata, Yuko

2010-01-01

Novelty seeking is viewed as adaptive, and novelty preferences in infancy predict cognitive performance into adulthood. Yet 7-month-olds prefer familiar stimuli to novel ones when searching for hidden objects, in contrast to their strong novelty preferences with visible objects (Shinskey & Munakata, 2005). According to a graded representations…

Ranking Adverse Drug Reactions With Crowdsourcing

KAUST Repository

Gottlieb, Assaf

2015-03-23

Background: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. Objective: The intent of the study was to rank ADRs according to severity. Methods: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. Results: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. Conclusions: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

Interactive Preference Learning of Utility Functions for Multi-Objective Optimization

OpenAIRE

Dewancker, Ian; McCourt, Michael; Ainsworth, Samuel

2016-01-01

Real-world engineering systems are typically compared and contrasted using multiple metrics. For practical machine learning systems, performance tuning is often more nuanced than minimizing a single expected loss objective, and it may be more realistically discussed as a multi-objective optimization problem. We propose a novel generative model for scalar-valued utility functions to capture human preferences in a multi-objective optimization setting. We also outline an interactive active learn...

Customer love: Research on the ranking of food and beverage locations

Directory of Open Access Journals (Sweden)

Bahar Türk

2015-09-01

Full Text Available Intense competition in today’s markets has meant that customer loyalty is no longer as strong as it used to be. In this context, many researchers have aimed to add new values to the concept of loyalty, particularly focusing on the concept of “love”. This study explores customers’ feelings towards location in order to identify their preferred - or “most loved” - food and beverage locations. A questionnaire was administered to 395 adult customers living in the city centre of Erzurum, Turkey. The fuzzy Shannon’s entropy method is used to identify the weights of each criterion of love, while the fuzzy VIKOR method is used to rank alternative locations. As a result of the analyses, the most prominent expression was found as “I love this location!”, and customers’ most loved places were identified as those serving regional dishes in Erzurum Province, Turkey. The study uses fuzzy numbers to rank alternatives according to the criteria of love. In addition, the ranking is based on degrees of fuzziness by changing the α-cut levels of the fuzzy numbers. The study examines how customers’ preferences between alternatives alter via this change

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

Science.gov (United States)

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

A Reformulation of Normative Economics for Models with Endogenous Preferences

OpenAIRE

Vipul Bhatt; Masao Ogaki; Yuichi Yaguchi

2014-01-01

This paper proposes a framework to balance considerations of welfarism and virtue ethics in the normative analysis of economic models with endogenous preferences. We introduce the moral evaluation function (MEF), which ranks alternatives based purely on virtue ethics, and define the social objective function (SOF), which combines the Social Welfare Function (SWF) and the MEF. In a model of intergenerational altruism with endogenous time preference, using numerical simulations we show that max...

Survey of hospital clinicians' preferences regarding the format of radiology reports

International Nuclear Information System (INIS)

Plumb, A.A.O.; Grieve, F.M.; Khan, S.H.

2009-01-01

Aim: To determine hospital consultants' preferences for the format and content of radiology reports. Materials and methods: Ninety-nine questionnaires were sent to consultant staff with responsibility for requesting ultrasound examinations. The participants were invited to rank a variety of hypothetical reports in order of preference. They were also asked whether they felt other commonly included features of a radiology report were of value. Rank data were analysed by the Friedman statistic, Fisher's multiple comparisons least significant difference test, and the Kemeny-Young method. Results: Forty-nine responses were received. There was a preference for more detailed reports that included a clinical comment by the radiologist, for both normal and abnormal results (p < 0.05). Reports presented in tables were preferred. The combination of a detailed tabular report with a radiologist's comment was the most popular single structure, preferred by 43% of respondents for normal reports and 51% for abnormal reports. Conclusion: Detailed reports with a radiologists' comment are preferred to briefer reports, even for normal examinations. Tabular reports are preferred to prose, with the combination of a detailed report presented in a tabular format accompanied by a radiologist's comment being the most preferred style

Effects of Implied Motion and Facing Direction on Positional Preferences in Single-Object Pictures.

Science.gov (United States)

Palmer, Stephen E; Langlois, Thomas A

2017-07-01

Palmer, Gardner, and Wickens studied aesthetic preferences for pictures of single objects and found a strong inward bias: Right-facing objects were preferred left-of-center and left-facing objects right-of-center. They found no effect of object motion (people and cars showed the same inward bias as chairs and teapots), but the objects were not depicted as moving. Here we measured analogous inward biases with objects depicted as moving with an implied direction and speed by having participants drag-and-drop target objects into the most aesthetically pleasing position. In Experiment 1, human figures were shown diving or falling while moving forward or backward. Aesthetic biases were evident for both inward-facing and inward-moving figures, but the motion-based bias dominated so strongly that backward divers or fallers were preferred moving inward but facing outward. Experiment 2 investigated implied speed effects using images of humans, horses, and cars moving at different speeds (e.g., standing, walking, trotting, and galloping horses). Inward motion or facing biases were again present, and differences in their magnitude due to speed were evident. Unexpectedly, faster moving objects were generally preferred closer to frame center than slower moving objects. These results are discussed in terms of the combined effects of prospective, future-oriented biases, and retrospective, past-oriented biases.

Effects of prosthetic foot forefoot flexibility on oxygen cost and subjective preference rankings of unilateral transtibial prosthesis users

OpenAIRE

Mark Edwards, MHPE, CP; Stefania Fatone, PhD; Andrew Hansen, PhD; Elizabeth Klodd, MS

2010-01-01

The investigators conducted a double-blind randomized crossover study to determine the effects of prosthetic foot forefoot flexibility on oxygen cost and subjective preference rankings of 13 unilateral transtibial prosthesis users. Five experimental feet were fabricated for use in the study: F1, F2, F3, F4, and F5. F1 was most flexible, F5 was least flexible, and F3 was designed to conform to a biomimetic ankle-foot roll-over shape. The experimental feet were modeled after the Shape&Roll pros...

Ship detection in satellite imagery using rank-order greyscale hit-or-miss transforms

Energy Technology Data Exchange (ETDEWEB)

Harvey, Neal R [Los Alamos National Laboratory; Porter, Reid B [Los Alamos National Laboratory; Theiler, James [Los Alamos National Laboratory

2010-01-01

Ship detection from satellite imagery is something that has great utility in various communities. Knowing where ships are and their types provides useful intelligence information. However, detecting and recognizing ships is a difficult problem. Existing techniques suffer from too many false-alarms. We describe approaches we have taken in trying to build ship detection algorithms that have reduced false alarms. Our approach uses a version of the grayscale morphological Hit-or-Miss transform. While this is well known and used in its standard form, we use a version in which we use a rank-order selection for the dilation and erosion parts of the transform, instead of the standard maximum and minimum operators. This provides some slack in the fitting that the algorithm employs and provides a method for tuning the algorithm's performance for particular detection problems. We describe our algorithms, show the effect of the rank-order parameter on the algorithm's performance and illustrate the use of this approach for real ship detection problems with panchromatic satellite imagery.

The ranking of negative-cost emissions reduction measures

International Nuclear Information System (INIS)

Taylor, Simon

2012-01-01

A flaw has been identified in the calculation of the cost-effectiveness in marginal abatement cost curves (MACCs). The problem affects “negative-cost” emissions reduction measures—those that produce a return on investment. The resulting ranking sometimes favours measures that produce low emissions savings and is therefore unreliable. The issue is important because incorrect ranking means a potential failure to achieve the best-value outcome. A simple mathematical analysis shows that not only is the standard cost-effectiveness calculation inadequate for ranking negative-cost measures, but there is no possible replacement that satisfies reasonable requirements. Furthermore, the concept of negative cost-effectiveness is found to be unsound and its use should be avoided. Among other things, this means that MACCs are unsuitable for ranking negative-cost measures. As a result, MACCs produced by a range of organizations including UK government departments may need to be revised. An alternative partial ranking method has been devised by making use of Pareto optimization. The outcome can be presented as a stacked bar chart that indicates both the preferred ordering and the total emissions saving available for each measure without specifying a cost-effectiveness. - Highlights: ► Marginal abatement cost curves (MACCs) are used to rank emission reduction measures. ► There is a flaw in the standard ranking method for negative-cost measures. ► Negative values of cost-effectiveness (in £/tC or equivalent) are invalid. ► There may be errors in published MACCs. ► A method based on Pareto principles provides an alternative ranking method.

A multi-attribute preference model for optimal irrigated crop planning under water scarcity conditions

Energy Technology Data Exchange (ETDEWEB)

Montazar, A.; Snyder, R. L.

2012-11-01

Water resources sustainability has a key role in the existence and durability of irrigated farming systems and strongly depends on the crop planning. The decision process is complex due to a number of constraints and the desire to secure crop diversification and the involvement of affected various parameters. The objective of the present study was to develop a comprehensive multi-criteria model for selecting adequate cropping pattern in an irrigation district under water scarcity condition. Eleven and nine attribute decisions were considered in ranking the type of crop and determination of the percentage of crop cultivation area as an optimal irrigated crop planning system, respectively. The results indicate that the proposed multi-attribute preference approach can synthesize various sets of criteria in the preference elicitation of the crop type and cultivated area. The predictive validity analysis shows that the preferences acquired by the proposed model are evidently in reasonable accordance with those of the conjunctive water use model. Consequently, the model may be used to aggregate preferences in order to obtain a group decision, improve understanding of the choice problem, accommodate multiple objectives and increase transparency and credibility in decision making by actively involving relevant criteria in the crop planning. (Author) 27 refs.

Fuzzy preference based interactive fuzzy physical programming and its application in multi-objective optimization

International Nuclear Information System (INIS)

Zhang, Xu; Huang, Hong Zhong; Yu, Lanfeng

2006-01-01

Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer

Universality of rank-ordering distributions in the arts and sciences.

Directory of Open Access Journals (Sweden)

Gustavo Martínez-Mekler

Full Text Available Searching for generic behaviors has been one of the driving forces leading to a deep understanding and classification of diverse phenomena. Usually a starting point is the development of a phenomenology based on observations. Such is the case for power law distributions encountered in a wealth of situations coming from physics, geophysics, biology, lexicography as well as social and financial networks. This finding is however restricted to a range of values outside of which finite size corrections are often invoked. Here we uncover a universal behavior of the way in which elements of a system are distributed according to their rank with respect to a given property, valid for the full range of values, regardless of whether or not a power law has previously been suggested. We propose a two parameter functional form for these rank-ordered distributions that gives excellent fits to an impressive amount of very diverse phenomena, coming from the arts, social and natural sciences. It is a discrete version of a generalized beta distribution, given by f(r = A(N+1-r(b/r(a, where r is the rank, N its maximum value, A the normalization constant and (a, b two fitting exponents. Prompted by our genetic sequence observations we present a growth probabilistic model incorporating mutation-duplication features that generates data complying with this distribution. The competition between permanence and change appears to be a relevant, though not necessary feature. Additionally, our observations mainly of social phenomena suggest that a multifactorial quality resulting from the convergence of several heterogeneous underlying processes is an important feature. We also explore the significance of the distribution parameters and their classifying potential. The ubiquity of our findings suggests that there must be a fundamental underlying explanation, most probably of a statistical nature, such as an appropriate central limit theorem formulation.

Most and Least Preferred Colours Differ According to Object Context: New Insights from an Unrestricted Colour Range.

Science.gov (United States)

Jonauskaite, Domicele; Mohr, Christine; Antonietti, Jean-Philippe; Spiers, Peter M; Althaus, Betty; Anil, Selin; Dael, Nele

2016-01-01

Humans like some colours and dislike others, but which particular colours and why remains to be understood. Empirical studies on colour preferences generally targeted most preferred colours, but rarely least preferred (disliked) colours. In addition, findings are often based on general colour preferences leaving open the question whether results generalise to specific objects. Here, 88 participants selected the colours they preferred most and least for three context conditions (general, interior walls, t-shirt) using a high-precision colour picker. Participants also indicated whether they associated their colour choice to a valenced object or concept. The chosen colours varied widely between individuals and contexts and so did the reasons for their choices. Consistent patterns also emerged, as most preferred colours in general were more chromatic, while for walls they were lighter and for t-shirts they were darker and less chromatic compared to least preferred colours. This meant that general colour preferences could not explain object specific colour preferences. Measures of the selection process further revealed that, compared to most preferred colours, least preferred colours were chosen more quickly and were less often linked to valenced objects or concepts. The high intra- and inter-individual variability in this and previous reports furthers our understanding that colour preferences are determined by subjective experiences and that most and least preferred colours are not processed equally.

Most and Least Preferred Colours Differ According to Object Context: New Insights from an Unrestricted Colour Range.

Directory of Open Access Journals (Sweden)

Domicele Jonauskaite

Full Text Available Humans like some colours and dislike others, but which particular colours and why remains to be understood. Empirical studies on colour preferences generally targeted most preferred colours, but rarely least preferred (disliked colours. In addition, findings are often based on general colour preferences leaving open the question whether results generalise to specific objects. Here, 88 participants selected the colours they preferred most and least for three context conditions (general, interior walls, t-shirt using a high-precision colour picker. Participants also indicated whether they associated their colour choice to a valenced object or concept. The chosen colours varied widely between individuals and contexts and so did the reasons for their choices. Consistent patterns also emerged, as most preferred colours in general were more chromatic, while for walls they were lighter and for t-shirts they were darker and less chromatic compared to least preferred colours. This meant that general colour preferences could not explain object specific colour preferences. Measures of the selection process further revealed that, compared to most preferred colours, least preferred colours were chosen more quickly and were less often linked to valenced objects or concepts. The high intra- and inter-individual variability in this and previous reports furthers our understanding that colour preferences are determined by subjective experiences and that most and least preferred colours are not processed equally.

Most and Least Preferred Colours Differ According to Object Context: New Insights from an Unrestricted Colour Range

Science.gov (United States)

Jonauskaite, Domicele; Mohr, Christine; Antonietti, Jean-Philippe; Spiers, Peter M.; Althaus, Betty; Anil, Selin; Dael, Nele

2016-01-01

Humans like some colours and dislike others, but which particular colours and why remains to be understood. Empirical studies on colour preferences generally targeted most preferred colours, but rarely least preferred (disliked) colours. In addition, findings are often based on general colour preferences leaving open the question whether results generalise to specific objects. Here, 88 participants selected the colours they preferred most and least for three context conditions (general, interior walls, t-shirt) using a high-precision colour picker. Participants also indicated whether they associated their colour choice to a valenced object or concept. The chosen colours varied widely between individuals and contexts and so did the reasons for their choices. Consistent patterns also emerged, as most preferred colours in general were more chromatic, while for walls they were lighter and for t-shirts they were darker and less chromatic compared to least preferred colours. This meant that general colour preferences could not explain object specific colour preferences. Measures of the selection process further revealed that, compared to most preferred colours, least preferred colours were chosen more quickly and were less often linked to valenced objects or concepts. The high intra- and inter-individual variability in this and previous reports furthers our understanding that colour preferences are determined by subjective experiences and that most and least preferred colours are not processed equally. PMID:27022909

Optimal power system generation scheduling by multi-objective genetic algorithms with preferences

International Nuclear Information System (INIS)

Zio, E.; Baraldi, P.; Pedroni, N.

2009-01-01

Power system generation scheduling is an important issue both from the economical and environmental safety viewpoints. The scheduling involves decisions with regards to the units start-up and shut-down times and to the assignment of the load demands to the committed generating units for minimizing the system operation costs and the emission of atmospheric pollutants. As many other real-world engineering problems, power system generation scheduling involves multiple, conflicting optimization criteria for which there exists no single best solution with respect to all criteria considered. Multi-objective optimization algorithms, based on the principle of Pareto optimality, can then be designed to search for the set of nondominated scheduling solutions from which the decision-maker (DM) must a posteriori choose the preferred alternative. On the other hand, often, information is available a priori regarding the preference values of the DM with respect to the objectives. When possible, it is important to exploit this information during the search so as to focus it on the region of preference of the Pareto-optimal set. In this paper, ways are explored to use this preference information for driving a multi-objective genetic algorithm towards the preferential region of the Pareto-optimal front. Two methods are considered: the first one extends the concept of Pareto dominance by biasing the chromosome replacement step of the algorithm by means of numerical weights that express the DM' s preferences; the second one drives the search algorithm by changing the shape of the dominance region according to linear trade-off functions specified by the DM. The effectiveness of the proposed approaches is first compared on a case study of literature. Then, a nonlinear, constrained, two-objective power generation scheduling problem is effectively tackled

[Patient-related color preference and color design in the hospital].

Science.gov (United States)

Schuschke, G; Christiansen, H

1994-06-01

Colour-physiological studies involving volunteers and colour-psychological interviewing of patients with varied diagnoses revealed that, currently, no compelling scientific reasons can be given for coloration in the hospital. Interviewing 68 patients from a number of clinics on the coloration of sick-rooms yielded the following preferred colours, irrespective of the patients' classing into groups by various criteria: Light colours were consistently preferred for all objects such as ceiling, walls, floor, curtains, furniture, and bed linen. It should be emphasized that even white was a desirable colour for ceilings and bed linen. Beige was found to rank first for walls, floors, curtains, and furniture, whereas the colours of wood and grey shared the second rank for floors and furniture. Green and pink ranked second for bed linen. White and green ranked second for walls and curtains, respectively. In view of the heterogeneity, the findings may not be converted into an absolute just as the recommendations by other workers. Still, the patients' wish should be given priority over decreed recommendations by experts when basic considerations of illumination (reflectance!) are allowed for in the particular overall colour design project.

Data envelopment analysis of randomized ranks

Directory of Open Access Journals (Sweden)

Sant'Anna Annibal P.

2002-01-01

Full Text Available Probabilities and odds, derived from vectors of ranks, are here compared as measures of efficiency of decision-making units (DMUs. These measures are computed with the goal of providing preliminary information before starting a Data Envelopment Analysis (DEA or the application of any other evaluation or composition of preferences methodology. Preferences, quality and productivity evaluations are usually measured with errors or subject to influence of other random disturbances. Reducing evaluations to ranks and treating the ranks as estimates of location parameters of random variables, we are able to compute the probability of each DMU being classified as the best according to the consumption of each input and the production of each output. Employing the probabilities of being the best as efficiency measures, we stretch distances between the most efficient units. We combine these partial probabilities in a global efficiency score determined in terms of proximity to the efficiency frontier.

Ranking of biomass pellets by integration of economic, environmental and technical factors

International Nuclear Information System (INIS)

Sultana, Arifa; Kumar, Amit

2012-01-01

Interest in biomass as a renewable energy source has increased recently in response to a need to reduce greenhouse gas (GHG) emissions. The objective of this study is to develop a multi-criteria assessment model and rank different biomass feedstock-based pellets, in terms of their suitability for use in large heat and power generation plants and show the importance of environmental, economical and technical factors in making decision about different pellets. Five pellet alternatives, each produced from a different sustainable biomass feedstock i.e., wood, straw, switchgrass, alfalfa and poultry litter, are ranked according to eleven criteria, using the Preference Ranking Organization Method for Enrichment and Evaluation (PROMETHEE). Both quantitative and qualitative criteria are considered, including environmental, technical and economic factors. Three scenarios, namely base case, environmental and economic, are developed by changing the weight assigned to different criteria. In the base case scenario, equal weights are assigned to each criterion. In the economic and environmental scenarios, more weight is given to the economic and environmental factors, respectively. Based on the PROMETHEE rankings, wood pellets are the best source of energy for all scenarios followed by switchgrass, straw, poultry litter and alfalfa pellets except economic scenario, where straw pellets held higher position than switchgrass pellets. Sensitivity analysis on weights, threshold values, preference function and production cost indicate that the ranking was stable. The ranking in all scenarios remained same when qualitative criteria were omitted from the model; this indicates the stronger influence of quantitative criteria. -- Highlights: ► This study ranks the pellets produced from different biomass feedstocks. ► The ranking of the pellets is based on technical, economical and environmental factors. ► This study uses PROMETHEE method for ranking pellets based on a range of

Keypress-Based Musical Preference Is Both Individual and Lawful

Science.gov (United States)

Livengood, Sherri L.; Sheppard, John P.; Kim, Byoung W.; Malthouse, Edward C.; Bourne, Janet E.; Barlow, Anne E.; Lee, Myung J.; Marin, Veronica; O'Connor, Kailyn P.; Csernansky, John G.; Block, Martin P.; Blood, Anne J.; Breiter, Hans C.

2017-01-01

Musical preference is highly individualized and is an area of active study to develop methods for its quantification. Recently, preference-based behavior, associated with activity in brain reward circuitry, has been shown to follow lawful, quantifiable patterns, despite broad variation across individuals. These patterns, observed using a keypress paradigm with visual stimuli, form the basis for relative preference theory (RPT). Here, we sought to determine if such patterns extend to non-visual domains (i.e., audition) and dynamic stimuli, potentially providing a method to supplement psychometric, physiological, and neuroimaging approaches to preference quantification. For this study, we adapted our keypress paradigm to two sets of stimuli consisting of seventeenth to twenty-first century western art music (Classical) and twentieth to twenty-first century jazz and popular music (Popular). We studied a pilot sample and then a separate primary experimental sample with this paradigm, and used iterative mathematical modeling to determine if RPT relationships were observed with high R2 fits. We further assessed the extent of heterogeneity in the rank ordering of keypress-based responses across subjects. As expected, individual rank orderings of preferences were quite heterogeneous, yet we observed mathematical patterns fitting these data similar to those observed previously with visual stimuli. These patterns in music preference were recurrent across two cohorts and two stimulus sets, and scaled between individual and group data, adhering to the requirements for lawfulness. Our findings suggest a general neuroscience framework that predicts human approach/avoidance behavior, while also allowing for individual differences and the broad diversity of human choices; the resulting framework may offer novel approaches to advancing music neuroscience, or its applications to medicine and recommendation systems. PMID:28512395

Keypress-Based Musical Preference Is Both Individual and Lawful

Directory of Open Access Journals (Sweden)

Sherri L. Livengood

2017-05-01

Full Text Available Musical preference is highly individualized and is an area of active study to develop methods for its quantification. Recently, preference-based behavior, associated with activity in brain reward circuitry, has been shown to follow lawful, quantifiable patterns, despite broad variation across individuals. These patterns, observed using a keypress paradigm with visual stimuli, form the basis for relative preference theory (RPT. Here, we sought to determine if such patterns extend to non-visual domains (i.e., audition and dynamic stimuli, potentially providing a method to supplement psychometric, physiological, and neuroimaging approaches to preference quantification. For this study, we adapted our keypress paradigm to two sets of stimuli consisting of seventeenth to twenty-first century western art music (Classical and twentieth to twenty-first century jazz and popular music (Popular. We studied a pilot sample and then a separate primary experimental sample with this paradigm, and used iterative mathematical modeling to determine if RPT relationships were observed with high R2 fits. We further assessed the extent of heterogeneity in the rank ordering of keypress-based responses across subjects. As expected, individual rank orderings of preferences were quite heterogeneous, yet we observed mathematical patterns fitting these data similar to those observed previously with visual stimuli. These patterns in music preference were recurrent across two cohorts and two stimulus sets, and scaled between individual and group data, adhering to the requirements for lawfulness. Our findings suggest a general neuroscience framework that predicts human approach/avoidance behavior, while also allowing for individual differences and the broad diversity of human choices; the resulting framework may offer novel approaches to advancing music neuroscience, or its applications to medicine and recommendation systems.

Statistical Optimality in Multipartite Ranking and Ordinal Regression.

Science.gov (United States)

Uematsu, Kazuki; Lee, Yoonkyung

2015-05-01

Statistical optimality in multipartite ranking is investigated as an extension of bipartite ranking. We consider the optimality of ranking algorithms through minimization of the theoretical risk which combines pairwise ranking errors of ordinal categories with differential ranking costs. The extension shows that for a certain class of convex loss functions including exponential loss, the optimal ranking function can be represented as a ratio of weighted conditional probability of upper categories to lower categories, where the weights are given by the misranking costs. This result also bridges traditional ranking methods such as proportional odds model in statistics with various ranking algorithms in machine learning. Further, the analysis of multipartite ranking with different costs provides a new perspective on non-smooth list-wise ranking measures such as the discounted cumulative gain and preference learning. We illustrate our findings with simulation study and real data analysis.

Bilevel formulation of a policy design problem considering multiple objectives and incomplete preferences

Science.gov (United States)

Hawthorne, Bryant; Panchal, Jitesh H.

2014-07-01

A bilevel optimization formulation of policy design problems considering multiple objectives and incomplete preferences of the stakeholders is presented. The formulation is presented for Feed-in-Tariff (FIT) policy design for decentralized energy infrastructure. The upper-level problem is the policy designer's problem and the lower-level problem is a Nash equilibrium problem resulting from market interactions. The policy designer has two objectives: maximizing the quantity of energy generated and minimizing policy cost. The stakeholders decide on quantities while maximizing net present value and minimizing capital investment. The Nash equilibrium problem in the presence of incomplete preferences is formulated as a stochastic linear complementarity problem and solved using expected value formulation, expected residual minimization formulation, and the Monte Carlo technique. The primary contributions in this article are the mathematical formulation of the FIT policy, the extension of computational policy design problems to multiple objectives, and the consideration of incomplete preferences of stakeholders for policy design problems.

Estimating US federal wildland fire managers' preferences toward competing strategic suppression objectives

Science.gov (United States)

David E. Calkin; Tyron Venn; Matthew Wibbenmeyer; Matthew P. Thompson

2012-01-01

Wildfire management involves significant complexity and uncertainty, requiring simultaneous consideration of multiple, non-commensurate objectives. This paper investigates the tradeoffs fire managers are willing to make among these objectives using a choice experiment methodology that provides three key advancements relative to previous stated-preference studies...

A DEA-TOPSIS approach for ranking credit institutions

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Mohammad Ehsani

2014-09-01

Full Text Available Measuring the relative efficiency of financial units plays essential role for making strategic decisions such as business development, downsizing, etc. This paper presents an empirical investigation to rank different branches of a credit institution named Samen in city of Semnan, Iran. The proposed study uses data envelopment analysis (DEA for measuring the relative efficiency of 17 units. The results indicate that five units were efficient and using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS, the efficient units are ranked based on some inputs/outputs. The results of this study indicate that most branches of this financial unit performed poorly and a restructure in their businesses is necessary. In addition, the study has provided some evidences that considering employee wage, bank deposit and administration expenses as inputs for DEA implementation seems to provide better results than using total assets and equities.

Dietary preference in dairy calves for feed ingredients high in energy and protein.

Science.gov (United States)

Miller-Cushon, E K; Montoro, C; Ipharraguerre, I R; Bach, A

2014-03-01

In 3 experiments, we assessed preference of recently weaned dairy calves for (1) 8 high-energy feed types [barley meal, corn meal, corn gluten feed (CGF), oat meal, rice meal, sorghum meal, wheat meal, and wheat middlings meal]; (2) 6 high-protein feed types [corn gluten meal (CGM), wheat distillers dried grains, rapeseed meal, soybean meal (SBM), sunflower meal, and pea meal]; and (3) 4 mixtures (50:50) of the highest- and lowest-ranked high-energy and high-protein feeds, to assess whether calves maintain preference for feed ingredients that are included in a mixture. In all experiments, pairwise preference tests were conducted between all feed types (28 different pairwise preference tests in experiment 1, 15 tests in experiment 2, and 6 tests in experiment 3). Each pairwise preference test was conducted by offering ad libitum access to both feed types for 6h. All tests were repeated with 20 Holstein calves. Before this study, calves were offered milk replacer at a rate of 4 L/d and a pelleted starter feed ad libitum. After weaning at 62 d of age, each calf was involved in a pairwise preference test at 3 and 5d postweaning. A preference ratio was calculated for each calf in each test as (intake of feed type A)/(intake of feed type A + intake of feed type B). Preference for feed types was ranked across tests in each experiment using pairwise comparison charts. In experiment 1, the highest-ranked high-energy feed type was wheat meal and the lowest ranked were rice meal and CGF. In experiment 2, the highest-ranked high-protein feed type was SBM and the lowest ranked was CGM. According to the preference rankings from experiments 1 and 2, experiment 3 evaluated (50:50) mixtures of SBM + wheat meal, SBM + CGF, CGM + wheat meal, and CGM + CGF. The mixture of SBM + wheat meal was highest ranked, CGM + CGF was lowest ranked, and the mixtures containing one high-ranked and one low-ranked feed ingredient (SBM + CGF and CGM + wheat meal) were ranked equally. The results of

Stochastic dominance for law invariant preferences: The happy story of elliptical distributions

OpenAIRE

Matteo Del Vigna

2012-01-01

We study the connections between stochastic dominance and law invariant preferences. Whenever the functional that represents preferences depends only on the law of the random variable, we shall look for conditions that imply a ranking of distributions. In analogy with the Expected Utility paradigm, we prove that functional dominance leads to first order stochastic dominance. We analyze in details the case of Dual Theory of Choice and Cumulative Prospect Theory, including all its distinctive f...

Learning style preferences of surgical residency applicants.

Science.gov (United States)

Kim, Roger H; Gilbert, Timothy

2015-09-01

The learning style preferences of general surgery residents have been previously reported; there is evidence that residents who prefer read/write learning styles perform better on the American Board of Surgery In-Training Examination (ABSITE). However, little is known regarding the learning style preferences of applicants to general surgery residency and their impact on educational outcomes. In this study, the preferred learning styles of surgical residency applicants were determined. We hypothesized that applicant rank data are associated with specific learning style preferences. The Fleming VARK learning styles inventory was offered to all general surgery residency applicants that were interviewed at a university hospital-based program. The VARK model categorizes learners as visual (V), aural (A), read/write (R), kinesthetic (K), or multimodal (MM). Responses on the inventory were scored to determine the preferred learning style for each applicant. Applicant data, including United States Medical Licensing Examination (USMLE) scores, class rank, interview score, and overall final applicant ranking, were examined for association with preferred learning styles. Sixty-seven applicants were interviewed. Five applicants were excluded due to not completing the VARK inventory or having incomplete applicant data. The remaining 62 applicants (92%) were included for analysis. Most applicants (57%) had a multimodal preference. Sixty-nine percent of all applicants had some degree of preference for kinesthetic learning. There were statistically significant differences between applicants of different learning styles in terms of USMLE step 1 scores (P = 0.001) and USMLE step 2 clinical knowledge scores (P = 0.01), but not for class ranks (P = 0.27), interview scores (P = 0.20), or final ranks (P = 0.14). Multiple comparison analysis demonstrated that applicants with aural preferences had higher USMLE 1 scores (233.2) than those with kinesthetic (211.8, P = 0.005) or multimodal

Order-disorder transition in conflicting dynamics leading to rank-frequency generalized beta distributions

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Alvarez-Martinez, R.; Martinez-Mekler, G.; Cocho, G.

2011-01-01

The behavior of rank-ordered distributions of phenomena present in a variety of fields such as biology, sociology, linguistics, finance and geophysics has been a matter of intense research. Often power laws have been encountered; however, their validity tends to hold mainly for an intermediate range of rank values. In a recent publication (Martínez-Mekler et al., 2009 [7]), a generalization of the functional form of the beta distribution has been shown to give excellent fits for many systems of very diverse nature, valid for the whole range of rank values, regardless of whether or not a power law behavior has been previously suggested. Here we give some insight on the significance of the two free parameters which appear as exponents in the functional form, by looking into discrete probabilistic branching processes with conflicting dynamics. We analyze a variety of realizations of these so-called expansion-modification models first introduced by Wentian Li (1989) [10]. We focus our attention on an order-disorder transition we encounter as we vary the modification probability p. We characterize this transition by means of the fitting parameters. Our numerical studies show that one of the fitting exponents is related to the presence of long-range correlations exhibited by power spectrum scale invariance, while the other registers the effect of disordering elements leading to a breakdown of these properties. In the absence of long-range correlations, this parameter is sensitive to the occurrence of unlikely events. We also introduce an approximate calculation scheme that relates this dynamics to multinomial multiplicative processes. A better understanding through these models of the meaning of the generalized beta-fitting exponents may contribute to their potential for identifying and characterizing universality classes.

Learning to Recommend Point-of-Interest with the Weighted Bayesian Personalized Ranking Method in LBSNs

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Lei Guo

2017-02-01

Full Text Available Point-of-interest (POI recommendation has been well studied in recent years. However, most of the existing methods focus on the recommendation scenarios where users can provide explicit feedback. In most cases, however, the feedback is not explicit, but implicit. For example, we can only get a user’s check-in behaviors from the history of what POIs she/he has visited, but never know how much she/he likes and why she/he does not like them. Recently, some researchers have noticed this problem and began to learn the user preferences from the partial order of POIs. However, these works give equal weight to each POI pair and cannot distinguish the contributions from different POI pairs. Intuitively, for the two POIs in a POI pair, the larger the frequency difference of being visited and the farther the geographical distance between them, the higher the contribution of this POI pair to the ranking function. Based on the above observations, we propose a weighted ranking method for POI recommendation. Specifically, we first introduce a Bayesian personalized ranking criterion designed for implicit feedback to POI recommendation. To fully utilize the partial order of POIs, we then treat the cost function in a weighted way, that is give each POI pair a different weight according to their frequency of being visited and the geographical distance between them. Data analysis and experimental results on two real-world datasets demonstrate the existence of user preference on different POI pairs and the effectiveness of our weighted ranking method.

Conditioned Object Preference: An Alternative Approach to Measuring Reward Learning in Rats

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Kennedy, Bruce C.; Kohli, Maulika; Maertens, Jamie J.; Marell, Paulina S.; Gewirtz, Jonathan C.

2016-01-01

Pavlovian conditioned approach behavior can be directed as much toward discrete cues as it is toward the environmental contexts in which those cues are encountered. The current experiments characterized a tendency of rats to approach object cues whose prior exposure had been paired with reward (conditioned object preference, COP). To demonstrate…

Social Feedback and the Emergence of Rank in Animal Society.

Science.gov (United States)

Hobson, Elizabeth A; DeDeo, Simon

2015-09-01

Dominance hierarchies are group-level properties that emerge from the aggression of individuals. Although individuals can gain critical benefits from their position in a hierarchy, we do not understand how real-world hierarchies form. Nor do we understand what signals and decision-rules individuals use to construct and maintain hierarchies in the absence of simple cues such as size or spatial location. A study of conflict in two groups of captive monk parakeets (Myiopsitta monachus) found that a transition to large-scale order in aggression occurred in newly-formed groups after one week, with individuals thereafter preferring to direct aggression more frequently against those nearby in rank. We consider two cognitive mechanisms underlying the emergence of this order: inference based on overall levels of aggression, or on subsets of the aggression network. Both mechanisms were predictive of individual decisions to aggress, but observed patterns were better explained by rank inference through subsets of the aggression network. Based on these results, we present a new theory, of a feedback loop between knowledge of rank and consequent behavior. This loop explains the transition to strategic aggression and the formation and persistence of dominance hierarchies in groups capable of both social memory and inference.

"I can do perfectly well without a car!": An exploration of stated preferences for middle-distance travel

OpenAIRE

Exel, Job; Graaf, G.; Rietveld, Piet

2011-01-01

textabstractThis article presents the results of a study exploring travellers' preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative travel modes. By-person factor analysis revealed four distinct preference segments for middle-distance travel: (1) choice travellers with a preference for public transport, (2) deliberate-choice travel...

Primary-Care Weight-Management Strategies: Parental Priorities and Preferences.

Science.gov (United States)

Turer, Christy Boling; Upperman, Carla; Merchant, Zahra; Montaño, Sergio; Flores, Glenn

2016-04-01

To examine parental perspectives/rankings of the most important weight-management clinical practices and to determine whether preferences/rankings differ when parents disagree that their child is overweight. We performed mixed-methods analysis of a 32-question survey of parents of 2- to 18-year-old overweight children assessing parental agreement that their child is overweight, the single most important thing providers can do to improve weight status, ranking American Academy of Pediatrics-recommended clinical practices, and preferred follow-up interval. Four independent reviewers analyzed open-response data to identify qualitative themes/subthemes. Multivariable analyses examined parental rankings, preferred follow-up interval, and differences by agreement with their child's overweight assessment. Thirty-six percent of 219 children were overweight, 42% obese, and 22% severely obese; 16% of parents disagreed with their child's overweight assessment. Qualitative analysis of the most important practice to help overweight children yielded 10 themes; unique to parents disagreeing with their children's overweight assessments was "change weight-status assessments." After adjustment, the 3 highest-ranked clinical practices included, "check for weight-related problems," "review growth chart," and "recommend general dietary changes" (all P parents disagreeing with their children's overweight assessments ranked "review growth chart" as less important and ranked "reducing screen time" and "general activity changes" as more important. The mean preferred weight-management follow-up interval (10-12 weeks) did not differ by agreement with children's overweight assessments. Parents prefer weight-management strategies that prioritize evaluating weight-related problems, growth-chart review, and regular follow-up. Parents who disagree that their child is overweight want changes in how overweight is assessed. Using parent-preferred weight-management strategies may prove useful in

RankProdIt: A web-interactive Rank Products analysis tool

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Laing Emma

2010-08-01

Full Text Available Abstract Background The first objective of a DNA microarray experiment is typically to generate a list of genes or probes that are found to be differentially expressed or represented (in the case of comparative genomic hybridizations and/or copy number variation between two conditions or strains. Rank Products analysis comprises a robust algorithm for deriving such lists from microarray experiments that comprise small numbers of replicates, for example, less than the number required for the commonly used t-test. Currently, users wishing to apply Rank Products analysis to their own microarray data sets have been restricted to the use of command line-based software which can limit its usage within the biological community. Findings Here we have developed a web interface to existing Rank Products analysis tools allowing users to quickly process their data in an intuitive and step-wise manner to obtain the respective Rank Product or Rank Sum, probability of false prediction and p-values in a downloadable file. Conclusions The online interactive Rank Products analysis tool RankProdIt, for analysis of any data set containing measurements for multiple replicated conditions, is available at: http://strep-microarray.sbs.surrey.ac.uk/RankProducts

Identifying patient preferences for communicating risk estimates: A descriptive pilot study

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O'Connor Annette M

2001-08-01

Full Text Available Abstract Background Patients increasingly seek more active involvement in health care decisions, but little is known about how to communicate complex risk information to patients. The objective of this study was to elicit patient preferences for the presentation and framing of complex risk information. Method To accomplish this, eight focus group discussions and 15 one-on-one interviews were conducted, where women were presented with risk data in a variety of different graphical formats, metrics, and time horizons. Risk data were based on a hypothetical woman's risk for coronary heart disease, hip fracture, and breast cancer, with and without hormone replacement therapy. Participants' preferences were assessed using likert scales, ranking, and abstractions of focus group discussions. Results Forty peri- and postmenopausal women were recruited through hospital fliers (n = 25 and a community health fair (n = 15. Mean age was 51 years, 50% were non-Caucasian, and all had completed high school. Bar graphs were preferred by 83% of participants over line graphs, thermometer graphs, 100 representative faces, and survival curves. Lifetime risk estimates were preferred over 10 or 20-year horizons, and absolute risks were preferred over relative risks and number needed to treat. Conclusion Although there are many different formats for presenting and framing risk information, simple bar charts depicting absolute lifetime risk were rated and ranked highest overall for patient preferences for format.

Modelling object typicality in description logics - [Workshop on Description Logics

CSIR Research Space (South Africa)

Britz, K

2009-07-01

Full Text Available than those not in C. This is a technical construction which allows us to order the entire domain, instead of only the members of C. This leads us to take as starting point a finite set of preference orders f j : j 2 J g on objects in the application... domain, with index set J . If j prefers any object in C to any object outside of C, we call j a C-order. To ensure that the subsumption relations eventually generated are rational [4, 14], we assume the preference orders to be a modular partial...

Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

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LI Lan-yin

2017-04-01

Full Text Available The traditional PageRank algorithm can not efficiently perform large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank，which is based on PageRank on the MapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order to identify top k nodes，topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamically construct subgraphs，and iteratively estimates lower/upper bounds of PageRank scores through subgraphs. Theoretical analysis shows that this method guarantees result exactness. Experiments show that topK-Rank algorithm can find k nodes much faster than the existing approaches.

NONLINEAR ASSIGNMENT-BASED METHODS FOR INTERVAL-VALUED INTUITIONISTIC FUZZY MULTI-CRITERIA DECISION ANALYSIS WITH INCOMPLETE PREFERENCE INFORMATION

OpenAIRE

TING-YU CHEN

2012-01-01

In the context of interval-valued intuitionistic fuzzy sets, this paper develops nonlinear assignment-based methods to manage imprecise and uncertain subjective ratings under incomplete preference structures and thereby determines the optimal ranking order of the alternatives for multiple criteria decision analysis. By comparing each interval-valued intuitionistic fuzzy number's score function, accuracy function, membership uncertainty index, and hesitation uncertainty index, a ranking proced...

Ten year rank-order stability of personality traits and disorders in a clinical sample

Science.gov (United States)

Hopwood, Christopher J.; Morey, Leslie C.; Donnellan, M. Brent; Samuel, Douglas B.; Grilo, Carlos M.; McGlashan, Thomas H.; Shea, M. Tracie; Zanarini, Mary C.; Gunderson, John G.; Skodol, Andrew E.

2012-01-01

Objective To compare the 10-year retest stability of normal traits, pathological traits, and personality disorder dimensions in a clinical sample. Method Ten-year rank order stability estimates for the Revised NEO Personality Inventory, Schedule for Nonadaptive and Adaptive Personality, and Diagnostic Interview for DSM-IV Personality Disorders were evaluated before and after correcting for test-retest dependability and internal consistency in a clinical sample (N = 266). Results Dependability corrected stability estimates were generally in the range of .60–.90 for traits and .25–.65 for personality disorders. Conclusions The relatively lower stability of personality disorder symptoms may indicate important differences between pathological behaviors and relatively more stable self-attributed traits and imply that a full understanding of personality and personality pathology needs to take both traits and symptoms into account. The Five-Factor Theory distinction between basic tendencies and characteristic adaptations provides a theoretical framework for the separation of traits and disorders in terms of stability in which traits reflect basic tendencies that are stable and pervasive across situations, whereas personality disorder symptoms reflect characteristic maladaptations that are a function of both basic tendencies and environmental dynamics. PMID:22812532

A Multiobjective Programming Method for Ranking All Units Based on Compensatory DEA Model

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Haifang Cheng

2014-01-01

Full Text Available In order to rank all decision making units (DMUs on the same basis, this paper proposes a multiobjective programming (MOP model based on a compensatory data envelopment analysis (DEA model to derive a common set of weights that can be used for the full ranking of all DMUs. We first revisit a compensatory DEA model for ranking all units, point out the existing problem for solving the model, and present an improved algorithm for which an approximate global optimal solution of the model can be obtained by solving a sequence of linear programming. Then, we applied the key idea of the compensatory DEA model to develop the MOP model in which the objectives are to simultaneously maximize all common weights under constraints that the sum of efficiency values of all DMUs is equal to unity and the sum of all common weights is also equal to unity. In order to solve the MOP model, we transform it into a single objective programming (SOP model using a fuzzy programming method and solve the SOP model using the proposed approximation algorithm. To illustrate the ranking method using the proposed method, two numerical examples are solved.

Automatic figure ranking and user interfacing for intelligent figure search.

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Hong Yu

2010-10-01

Full Text Available Figures are important experimental results that are typically reported in full-text bioscience articles. Bioscience researchers need to access figures to validate research facts and to formulate or to test novel research hypotheses. On the other hand, the sheer volume of bioscience literature has made it difficult to access figures. Therefore, we are developing an intelligent figure search engine (http://figuresearch.askhermes.org. Existing research in figure search treats each figure equally, but we introduce a novel concept of "figure ranking": figures appearing in a full-text biomedical article can be ranked by their contribution to the knowledge discovery.We empirically validated the hypothesis of figure ranking with over 100 bioscience researchers, and then developed unsupervised natural language processing (NLP approaches to automatically rank figures. Evaluating on a collection of 202 full-text articles in which authors have ranked the figures based on importance, our best system achieved a weighted error rate of 0.2, which is significantly better than several other baseline systems we explored. We further explored a user interfacing application in which we built novel user interfaces (UIs incorporating figure ranking, allowing bioscience researchers to efficiently access important figures. Our evaluation results show that 92% of the bioscience researchers prefer as the top two choices the user interfaces in which the most important figures are enlarged. With our automatic figure ranking NLP system, bioscience researchers preferred the UIs in which the most important figures were predicted by our NLP system than the UIs in which the most important figures were randomly assigned. In addition, our results show that there was no statistical difference in bioscience researchers' preference in the UIs generated by automatic figure ranking and UIs by human ranking annotation.The evaluation results conclude that automatic figure ranking and user

Adaptive Game Level Creation through Rank-based Interactive Evolution

DEFF Research Database (Denmark)

Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

2013-01-01

as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...

24 CFR 599.401 - Ranking of applications.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 3 2010-04-01 2010-04-01 false Ranking of applications. 599.401... Communities § 599.401 Ranking of applications. (a) Ranking order. Rural and urban applications will be ranked... applications ranked first. (b) Separate ranking categories. After initial ranking, both rural and urban...

Public preferences for government spending in Canada

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Ramji Sabrina

2012-10-01

Full Text Available Abstract This study considers three questions: 1. What are the Canadian public’s prioritization preferences for new government spending on a range of public health-related goods outside the scope of the country’s national system of health insurance? 2. How homogenous or heterogeneous is the Canadian public in terms of these preferences? 3. What factors are predictive of the Canadian public’s preferences for new government spending? Data were collected in 2008 from a national random sample of Canadian adults through a telephone interview survey (n =1,005. Respondents were asked to rank five spending priorities in terms of their preference for new government spending. Bivariate and multivariable logistic regression analyses were conducted. As a first priority, Canadian adults prefer spending on child care (26.2%, followed by pharmacare (23.1%, dental care (20.8%, home care (17.2%, and vision care (12.7%. Sociodemographic characteristics predict spending preferences, based on the social position and needs of respondents. Policy leaders need to give fair consideration to public preferences in priority setting approaches in order to ensure that public health-related goods are distributed in a manner that best suits population needs.

Leveraging Multiactions to Improve Medical Personalized Ranking for Collaborative Filtering

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Shan Gao

2017-01-01

Full Text Available Nowadays, providing high-quality recommendation services to users is an essential component in web applications, including shopping, making friends, and healthcare. This can be regarded either as a problem of estimating users’ preference by exploiting explicit feedbacks (numerical ratings, or as a problem of collaborative ranking with implicit feedback (e.g., purchases, views, and clicks. Previous works for solving this issue include pointwise regression methods and pairwise ranking methods. The emerging healthcare websites and online medical databases impose a new challenge for medical service recommendation. In this paper, we develop a model, MBPR (Medical Bayesian Personalized Ranking over multiple users’ actions, based on the simple observation that users tend to assign higher ranks to some kind of healthcare services that are meanwhile preferred in users’ other actions. Experimental results on the real-world datasets demonstrate that MBPR achieves more accurate recommendations than several state-of-the-art methods and shows its generality and scalability via experiments on the datasets from one mobile shopping app.

Leveraging Multiactions to Improve Medical Personalized Ranking for Collaborative Filtering.

Science.gov (United States)

Gao, Shan; Guo, Guibing; Li, Runzhi; Wang, Zongmin

2017-01-01

Nowadays, providing high-quality recommendation services to users is an essential component in web applications, including shopping, making friends, and healthcare. This can be regarded either as a problem of estimating users' preference by exploiting explicit feedbacks (numerical ratings), or as a problem of collaborative ranking with implicit feedback (e.g., purchases, views, and clicks). Previous works for solving this issue include pointwise regression methods and pairwise ranking methods. The emerging healthcare websites and online medical databases impose a new challenge for medical service recommendation. In this paper, we develop a model, MBPR (Medical Bayesian Personalized Ranking over multiple users' actions), based on the simple observation that users tend to assign higher ranks to some kind of healthcare services that are meanwhile preferred in users' other actions. Experimental results on the real-world datasets demonstrate that MBPR achieves more accurate recommendations than several state-of-the-art methods and shows its generality and scalability via experiments on the datasets from one mobile shopping app.

Sex Differences in Food Preferences of Hadza Hunter-Gatherers

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Julia Colette Berbesque

2009-10-01

Full Text Available Food preferences are important for understanding foraging choices. In studying human foragers rather than other animals, we have the advantage of being able to ask them which foods they prefer. Yet surprisingly, no studies of systematically collected data exist on human forager food preferences. The Hadza of Tanzania are full-time foragers in an area where the hominin record extends back to 3-4 million years ago, so their diet is very relevant for understanding the paleo-diet. Here, we report on their food preferences, elicited with photographs of species within the five major food categories in their diet: honey, meat, berries, baobab, and tubers. There were sex differences in the ranks of two food categories: meat and berries. While male and female ranks agreed on the other three food categories, females ranked berries second and meat fourth, whereas males ranked meat second and berries fourth. Theses similarities and differences are interesting in light of the fact that the sexes target different foods. We discuss the implications of Hadza food preferences for the origin of the uniquely human sexual division of foraging labor.

Simultaneous grouping and ranking with combination of SOM and TOPSIS for selection of preferable analytical procedure for furan determination in food.

Science.gov (United States)

Jędrkiewicz, Renata; Tsakovski, Stefan; Lavenu, Aurore; Namieśnik, Jacek; Tobiszewski, Marek

2018-02-01

Novel methodology for grouping and ranking with application of self-organizing maps and multicriteria decision analysis is presented. The dataset consists of 22 objects that are analytical procedures applied to furan determination in food samples. They are described by 10 variables, referred to their analytical performance, environmental and economic aspects. Multivariate statistics analysis allows to limit the amount of input data for ranking analysis. Assessment results show that the most beneficial procedures are based on microextraction techniques with GC-MS final determination. It is presented how the information obtained from both tools complement each other. The applicability of combination of grouping and ranking is also discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Patients' preferences for doctors' attire in Japan.

Science.gov (United States)

Yamada, Yasuhiro; Takahashi, Osamu; Ohde, Sachiko; Deshpande, Gautam A; Fukui, Tsuguya

2010-01-01

Physicians' attire is one important factor to enhance the physician-patient relationship. However, there are few studies that examine patients' preferences for physicians' attire in Japan. We sought to assess patients' preference regarding doctors' attire and to assess the influence of doctors' attire on patients' confidence in their physician. Furthermore, we examined whether patients' preferences would change among various clinical situations. Employing a cross-sectional design, Japanese outpatients chosen over one week in October 2008 from waiting rooms in various outpatient departments at St. Luke's International Hospital, Tokyo, were given a 10-item questionnaire. A 5-point Likert scale was used to estimate patient preference for four types of attire in both male and female physicians, including semi-formal attire, white coat, surgical scrubs, and casual wear. In addition, a 4-point Likert Scale was used to measure the influence of doctors' attire on patient confidence. Japanese outpatients consecutively chosen from waiting rooms at St. Luke's International Hospital in Tokyo for one week in October 2008. Of 2,272 outpatients enrolled, 1483 (67.1%) of respondents were women. Mean age of subjects was 53.8 years (SD 16.2 years). Respondents most preferred the white coat (mean rank: 4.18, SD: 0.75) and preferred casual attire the least (mean rank: 2.32, SD: 0.81). For female physicians, 1.4% of respondents ranked the white coat little/least preferred while 64.7% of respondents ranked casual wear little/least preferred. Among respondents who most preferred the white coat for physician attire, perceived hygiene (62.7%) and inspiring confidence (59.3%) were important factors for doctor's attire. Around 70% of all respondents reported that physicians' attire has an influence on their confidence in their physician. This study confirms that Japanese outpatients prefer a white coat. Furthermore, this study strongly suggests that wearing a white coat could favorably

Children’s preferences for gender-typed objects and colours: a commentary from gender research in Spain

Directory of Open Access Journals (Sweden)

Raúl Navarro

2014-12-01

Full Text Available The main aim of this review was to examine international research on children’s preferences regarding gender-typed objects and colours. Firstly, we provide the theoretical background on gender development to elucidate the ways in which individuals can learn gender stereotypes and develop gender-related preferences. Secondly, we review international research on gender-related preferences. Thirdly, we analyse empirical studies on gender stereotypes in children conducted in Spain and Latin American countries, and show that although gender is a priority research area in these countries, studies on gender development in childhood are lacking. Thus, our aim was to identify a set of issues that provide insights into the development of gender-typed preferences, and that also suggest new directions for researchers in Spanish-speaking countries who are interested in clarifying the relationship between gender and children’s preferences for objects and colours.

I can do perfectly well without a car! An exploration of stated preferences for middle-distance travel using Q-methodology

OpenAIRE

Exel, N.J.A.; de Graaf, G.; Rietveld, P.

2011-01-01

This article presents the results of a study exploring travellers' preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative travel modes. By-person factor analysis revealed four distinct preference segments for middle-distance travel: (1) choice travellers with a preference for public transport, (2) deliberate-choice travellers, (3) ch...

Public engagement in setting healthcare priorities: a ranking exercise in Cyprus.

Science.gov (United States)

Farmakas, Antonis; Theodorou, Mamas; Galanis, Petros; Karayiannis, Georgios; Ghobrial, Stefanos; Polyzos, Nikos; Papastavrou, Evridiki; Agapidaki, Eirini; Souliotis, Kyriakos

2017-01-01

In countries such as Cyprus the financial crisis and the recession have severely affected the funding and priority setting of the health care system. There is evidence highlighting the importance of population' preferences in designing priorities for health care settings. Although public preferences have been thorough analysed in many countries, there is a research gap in terms of simultaneously investigating the relative importance and the weight of differing and competing criteria for determining healthcare priority settings. The main objective of the study was tο investigate public preferences for the relative utility and weight of differing and competing criteria for health care priority setting in Cyprus. The 'conjoint analysis' technique was applied to develop a ranking exercise. The aim of the study was to identify the preferences of the participants for alternative options. Participants were asked to grade in a priority order 16 hypothetical case scenarios of patients with different disease and of diverse socio-economic characteristics awaiting treatment. The sample was purposive and consisted of 100 Cypriots, selected from public locations all over the country. It was revealed that the "severity of the disease" and the " age of the patient" were the key prioritization criteria. Participants assigned the smallest relative value to the criterion " healthy lifestyle" . More precisely, participants older than 35 years old assigned higher relative importance to " age" , while younger participants to the " severity of the disease". The " healthy lifestyle" criterion was assigned to the lowest relative importance to by all participants. In Cyprus, public participation in health care priority setting is almost inexistent. Nonetheless, it seems that the public's participation in this process could lead to a wider acceptance of the healthcare system especially as a result of the financial crisis and the upcoming reforms implemented such as the establishment of the

Human preferences for colorful birds: Vivid colors or pattern?

Science.gov (United States)

Lišková, Silvie; Landová, Eva; Frynta, Daniel

2015-04-29

In a previous study, we found that the shape of a bird, rather than its color, plays a major role in the determination of human preferences. Thus, in the present study, we asked whether the preferences of human respondents towards uniformly shaped, colorful birds are determined by pattern rather than color. The experimental stimuli were pictures of small passerine birds of the family Pittidae possessing uniform shape but vivid coloration. We asked 200 participants to rank 43 colored and 43 identical, but grayscaled, pictures of birds. To find the traits determining human preferences, we performed GLM analysis in which we tried to explain the mean preference ranks and PC axes by the following explanatory variables: the overall lightness and saturation, edges (pattern), and the portion of each of the basic color hues. The results showed that the mean preference ranks of the grayscale set is explained mostly by the birds' pattern, whereas the colored set ranking is mostly determined by the overall lightness. The effect of colors was weaker, but still significant, and revealed that people liked blue and green birds. We found no significant role of the color red, the perception of which was acquired relatively recently in evolution.

Human Preferences for Colorful Birds: Vivid Colors or Pattern?

Directory of Open Access Journals (Sweden)

Silvie Lišková

2015-04-01

Full Text Available In a previous study, we found that the shape of a bird, rather than its color, plays a major role in the determination of human preferences. Thus, in the present study, we asked whether the preferences of human respondents towards uniformly shaped, colorful birds are determined by pattern rather than color. The experimental stimuli were pictures of small passerine birds of the family Pittidae possessing uniform shape but vivid coloration. We asked 200 participants to rank 43 colored and 43 identical, but grayscaled, pictures of birds. To find the traits determining human preferences, we performed GLM analysis in which we tried to explain the mean preference ranks and PC axes by the following explanatory variables: the overall lightness and saturation, edges (pattern, and the portion of each of the basic color hues. The results showed that the mean preference ranks of the grayscale set is explained mostly by the birds' pattern, whereas the colored set ranking is mostly determined by the overall lightness. The effect of colors was weaker, but still significant, and revealed that people liked blue and green birds. We found no significant role of the color red, the perception of which was acquired relatively recently in evolution.

Bayesian Plackett-Luce Mixture Models for Partially Ranked Data.

Science.gov (United States)

Mollica, Cristina; Tardella, Luca

2017-06-01

The elicitation of an ordinal judgment on multiple alternatives is often required in many psychological and behavioral experiments to investigate preference/choice orientation of a specific population. The Plackett-Luce model is one of the most popular and frequently applied parametric distributions to analyze rankings of a finite set of items. The present work introduces a Bayesian finite mixture of Plackett-Luce models to account for unobserved sample heterogeneity of partially ranked data. We describe an efficient way to incorporate the latent group structure in the data augmentation approach and the derivation of existing maximum likelihood procedures as special instances of the proposed Bayesian method. Inference can be conducted with the combination of the Expectation-Maximization algorithm for maximum a posteriori estimation and the Gibbs sampling iterative procedure. We additionally investigate several Bayesian criteria for selecting the optimal mixture configuration and describe diagnostic tools for assessing the fitness of ranking distributions conditionally and unconditionally on the number of ranked items. The utility of the novel Bayesian parametric Plackett-Luce mixture for characterizing sample heterogeneity is illustrated with several applications to simulated and real preference ranked data. We compare our method with the frequentist approach and a Bayesian nonparametric mixture model both assuming the Plackett-Luce model as a mixture component. Our analysis on real datasets reveals the importance of an accurate diagnostic check for an appropriate in-depth understanding of the heterogenous nature of the partial ranking data.

"I can do perfectly well without a car!": An exploration of stated preferences for middle-distance travel

NARCIS (Netherlands)

N.J.A. van Exel (Job); G. de Graaf; P. Rietveld (Piet)

2011-01-01

textabstractThis article presents the results of a study exploring travellers' preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative

A multi-supplier sourcing problem with a preference ordering of suppliers

NARCIS (Netherlands)

Honhon, D.B.L.P.; Gaur, V.; Seshadri, S.

2012-01-01

We study a sourcing problem faced by a firm that seeks to procure a product or a component from a pool of alternative suppliers. The firm has a preference ordering of the suppliers based on factors such as their past performance, quality, service, geographical location, and financial strength, which

Coming close to the ideal alternative: The concordant-ranks strategy

Directory of Open Access Journals (Sweden)

Neda Kerimi

2011-04-01

Full Text Available We present the Concordant-Ranks (CR strategy that decision makers use to quickly find an alternative that is proximate to an ideal alternative in a multi-attribute decision space. CR implies that decision makers prefer alternatives that exhibit concordant ranks between attribute values and attribute weights. We show that, in situations where the alternatives are equal in multi-attribute utility (MAU, minimization of the weighted Euclidean distance (WED to an ideal alternative implies the choice of a CR alternative. In two experiments, participants chose among, as well as evaluated, alternatives that were constructed to be equal in MAU. In Experiment 1, four alternatives were designed in such a way that the choice of each alternative would be consistent with one particular choice strategy, one of which was the CR strategy. In Experiment 2, participants were presented with a CR alternative and a number of arbitrary alternatives. In both experiments, participants tended to choose the CR alternative. The CR alternative was on average evaluated as more attractive than other alternatives. In addition, measures of WED, between given alternatives and the ideal alternative, by and large agreed with the preference order for choices and attractiveness evaluations of the different types of alternatives. These findings indicate that both choices and attractiveness evaluations are guided by proximity of alternatives to an ideal alternative.

MAGDM linear-programming models with distinct uncertain preference structures.

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Xu, Zeshui S; Chen, Jian

2008-10-01

Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.

A Preference Model for Supplier Selection Based on Hesitant Fuzzy Sets

Directory of Open Access Journals (Sweden)

Zhexuan Zhou

2018-03-01

Full Text Available The supplier selection problem is a widespread concern in the modern commercial economy. Ranking suppliers involves many factors and poses significant difficulties for decision makers. Supplier selection is a multi-criteria and multi-objective problem, which leads to decision makers forming their own preferences. In addition, there are both quantifiable and non-quantifiable attributes related to their preferences. To solve this problem, this paper presents a preference model based on hesitant fuzzy sets (HFS to select suppliers. The cost and service quality of suppliers are the main considerations in the proposed model. HFS with interactive and multi-criteria decision making are used to evaluate the non-quantifiable attributes of service quality, which include competitive display, qualification ability, suitability and competitiveness of solutions, and relational fitness and dynamics. Finally, a numerical example of supplier selection for a high-end equipment manufacturer is provided to illustrate the applicability of the proposed model. The preferences of a decision maker are then analyzed by altering preference parameters.

Ranking of microRNA target prediction scores by Pareto front analysis.

Science.gov (United States)

Sahoo, Sudhakar; Albrecht, Andreas A

2010-12-01

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts. Copyright © 2010 Elsevier Ltd. All rights reserved.

Learning strategy preferences, verbal-visual cognitive styles, and multimedia preferences for continuing engineering education instructional design

Science.gov (United States)

Baukal, Charles Edward, Jr.

A literature search revealed very little information on how to teach working engineers, which became the motivation for this research. Effective training is important for many reasons such as preventing accidents, maximizing fuel efficiency, minimizing pollution emissions, and reducing equipment downtime. The conceptual framework for this study included the development of a new instructional design framework called the Multimedia Cone of Abstraction (MCoA). This was developed by combining Dale's Cone of Experience and Mayer's Cognitive Theory of Multimedia Learning. An anonymous survey of 118 engineers from a single Midwestern manufacturer was conducted to determine their demographics, learning strategy preferences, verbal-visual cognitive styles, and multimedia preferences. The learning strategy preference profile and verbal-visual cognitive styles of the sample were statistically significantly different than the general population. The working engineers included more Problem Solvers and were much more visually-oriented than the general population. To study multimedia preferences, five of the seven levels in the MCoA were used. Eight types of multimedia were compared in four categories (types in parantheses): text (text and narration), static graphics (drawing and photograph), non-interactive dynamic graphics (animation and video), and interactive dynamic graphics (simulated virtual reality and real virtual reality). The first phase of the study examined multimedia preferences within a category. Participants compared multimedia types in pairs on dual screens using relative preference, rating, and ranking. Surprisingly, the more abstract multimedia (text, drawing, animation, and simulated virtual reality) were preferred in every category to the more concrete multimedia (narration, photograph, video, and real virtual reality), despite the fact that most participants had relatively little prior subject knowledge. However, the more abstract graphics were only slightly

Social class rank, essentialism, and punitive judgment.

Science.gov (United States)

Kraus, Michael W; Keltner, Dacher

2013-08-01

Recent evidence suggests that perceptions of social class rank influence a variety of social cognitive tendencies, from patterns of causal attribution to moral judgment. In the present studies we tested the hypotheses that upper-class rank individuals would be more likely to endorse essentialist lay theories of social class categories (i.e., that social class is founded in genetically based, biological differences) than would lower-class rank individuals and that these beliefs would decrease support for restorative justice--which seeks to rehabilitate offenders, rather than punish unlawful action. Across studies, higher social class rank was associated with increased essentialism of social class categories (Studies 1, 2, and 4) and decreased support for restorative justice (Study 4). Moreover, manipulated essentialist beliefs decreased preferences for restorative justice (Study 3), and the association between social class rank and class-based essentialist theories was explained by the tendency to endorse beliefs in a just world (Study 2). Implications for how class-based essentialist beliefs potentially constrain social opportunity and mobility are discussed.

Inferring Groups of Objects, Preferred Routes, and Facility Locations from Trajectories

DEFF Research Database (Denmark)

Ceikute, Vaida

(i) infer groups of objects traveling together, (ii) determine routes preferred by local drivers, and (iii) identify attractive facility locations. First, we present framework that efficiently supports online discovery of groups of moving objects that travel together. We adopt a sampling......-independent approach that makes no assumptions about when object positions are sampled and that supports the use of approximate trajectories. The framework’s algorithms exploit density-based clustering to identify groups. Such identified groups are scored based on cardinality and duration. With the use of domination...... and similarity notions, groups of low interest are pruned, and a variety of different, interesting groups are returned. Results from empirical studies with real and synthetic data offer insight into the effectiveness and efficiency of the proposed framework. Next, we view GPS trajectories as trips that represent...

OutRank

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Steinhausen, Uwe

2008-01-01

Outlier detection is an important data mining task for consistency checks, fraud detection, etc. Binary decision making on whether or not an object is an outlier is not appropriate in many applications and moreover hard to parametrize. Thus, recently, methods for outlier ranking have been proposed...

A multi-criteria decision analysis approach for importance identification and ranking of network components

International Nuclear Information System (INIS)

Almoghathawi, Yasser; Barker, Kash; Rocco, Claudio M.; Nicholson, Charles D.

2017-01-01

Analyzing network vulnerability is a key element of network planning in order to be prepared for any disruptive event that might impact the performance of the network. Hence, many importance measures have been proposed to identify the important components in a network with respect to vulnerability and rank them accordingly based on individual importance measure. However, in this paper, we propose a new approach to identify the most important network components based on multiple importance measures using a multi criteria decision making (MCDM) method, namely the technique for order performance by similarity to ideal solution (TOPSIS), able to take into account the preferences of decision-makers. We consider multiple edge-specific flow-based importance measures provided as the multiple criteria of a network where the alternatives are the edges. Accordingly, TOPSIS is used to rank the edges of the network based on their importance considering multiple different importance measures. The proposed approach is illustrated through different networks with different densities along with the effects of weighs. - Highlights: • We integrate several perspectives on network vulnerability to generate a component importance ranking. • We apply these measures to determine the importance of edges after disruptions. • Networks of varying size and density are explored.

Temporal (In)Stability of Employee Preferences for Rewards

Science.gov (United States)

Wine, Byron; Gilroy, Shawn; Hantula, Donald A.

2012-01-01

This study examined the temporal stability of employee preferences for rewards over seven monthly evaluations. Participants completed a ranking stimulus preference assessment monthly, and the latter six monthly assessments were compared to the initial assessment. Correlations of preferences from month to month ranged from r = -0.89 to 0.99.…

TopKube: A Rank-Aware Data Cube for Real-Time Exploration of Spatiotemporal Data.

Science.gov (United States)

Miranda, Fabio; Lins, Lauro; Klosowski, James; Silva, Claudio

2017-02-17

From economics to sports to entertainment and social media, ranking objects according to some notion of importance is a fundamental tool we humans use all the time to better understand our world. With the ever-increasing amount of user-generated content found online, "what's trending" is now a commonplace phrase that tries to capture the zeitgeist of the world by ranking the most popular microblogging hashtags in a given region and time. However, before we can understand what these rankings tell us about the world, we need to be able to more easily create and explore them, given the significant scale of today's data. In this paper, we describe the computational challenges in building a real-time visual exploratory tool for finding top-ranked objects; build on the recent work involving in-memory and rank-aware data cubes to propose TOPKUBE: a data structure that answers top-k queries up to one order of magnitude faster than the previous state of the art; demonstrate the usefulness of our methods using a set of real-world, publicly available datasets; and provide a new set of benchmarks for other researchers to validate their methods and compare to our own.

PageRank of integers

International Nuclear Information System (INIS)

Frahm, K M; Shepelyansky, D L; Chepelianskii, A D

2012-01-01

We up a directed network tracing links from a given integer to its divisors and analyze the properties of the Google matrix of this network. The PageRank vector of this matrix is computed numerically and it is shown that its probability is approximately inversely proportional to the PageRank index thus being similar to the Zipf law and the dependence established for the World Wide Web. The spectrum of the Google matrix of integers is characterized by a large gap and a relatively small number of nonzero eigenvalues. A simple semi-analytical expression for the PageRank of integers is derived that allows us to find this vector for matrices of billion size. This network provides a new PageRank order of integers. (paper)

I can do perfectly well without a car! An exploration of stated preferences for middle-distance travel using Q-methodology

NARCIS (Netherlands)

Exel, N.J.A.; de Graaf, G.; Rietveld, P.

2011-01-01

This article presents the results of a study exploring travellers' preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative travel modes.

Subjective and objective knowledge and decisional role preferences in cerebrovascular patients compared to controls

Directory of Open Access Journals (Sweden)

Riechel C

2016-08-01

Full Text Available Christina Riechel,1,* Anna Christina Alegiani,1,* Sascha Köpke,2 Jürgen Kasper,3,4 Michael Rosenkranz,1,5 Götz Thomalla,1 Christoph Heesen1,4 1Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 2Nursing Research Unit, Institute of Social Medicine and Epidemiology, University of Lübeck, Lübeck, Germany; 3Department of Health and Caring Sciences, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway; 4Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 5Department of Neurology, Albertinen-Krankenhaus, Hamburg, Germany *These authors contributed equally to this work Background: Risk knowledge and active role preferences are important for patient involvement in treatment decision-making and adherence. Although knowledge about stroke warning signs and risk factors has received considerable attention, objective knowledge on secondary prevention and further self-esteem subjective knowledge have rarely been studied. The aim of our study was to investigate knowledge and treatment decisional role preferences in cerebrovascular patients compared to controls. Methods: We performed a survey on subjective and objective stroke risk knowledge and autonomy preferences in cerebrovascular patients from our stroke outpatient clinic (n=262 and from pedestrians on the street taken as controls during a “World Stroke Day” (n=274. The questionnaire includes measures for knowledge and decisional role preferences from previously published questionnaires and newly developed measures, for example, subjective knowledge, revealed on a visual analog scale. Results: The overall stroke knowledge was low to moderate, with no differences between patients and controls. Knowledge about secondary prevention was particularly low. Only 10%–15% of participants correctly estimated the stroke absolute risk reduction potential of aspirin. The medical data

Measuring higher order ambiguity preferences

NARCIS (Netherlands)

A. Baillon (Aurélien); Schlesinger, H. (Harris); G. van de Kuilen (Gijs)

2017-01-01

textabstractWe report the results from an experiment designed to measure attitudes towards ambiguity beyond ambiguity aversion. In particular, we implement recently-proposed model-free preference conditions of ambiguity prudence and ambiguity temperance. Ambiguity prudence has been shown to play an

Selecting the best bank that offered Islamic personal loan package by using consistent fuzzy preference relations (CFPR)

Science.gov (United States)

Kadir, Norhidayah A.; Sarudin, Ezzah Suraya; Hamid, Fairus; Shamsuddin, Nor Diyana Ahmad

2014-10-01

There are various thoughts and opinions when it comes to how people think of their selected banks. Therefore, to choose the best bank with a good personal loan package can be a bit tricky especially for first time customer. This research offers a guide in choosing the right bank for applying personal loan package by highlighting the important criteria that applicants should take into consideration. In order to cater the problem above, we used Consistent Fuzzy Preference Relations (CFPR). Based on expert and public opinions, the important criteria in selecting an Islamic personal loan package are interest rate, tenure of loan, processing period and security of the loan. We developed questionnaire with the criteria mention earlier and distributed it among academic staffs and non academic staffs at Faculty of Computer and Mathematical Sciences (FSKM), UiTM Shah Alam. Based on the questionnaire, we found that four banks have been selected for multiple reasons. Before we could determine the best bank, calculations are divided into 2 phases which are criteria weights determination and ranking of alternatives. We implemented these phases to get the aggregation result and to obtain the ranking in descending order. As a result, our objectives have been achieved. As a conclusion, CFPR can help others in the decision making process.

Multiple graph regularized protein domain ranking.

Science.gov (United States)

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Women's preference of cosmetic results after gynecologic surgery.

Science.gov (United States)

Goebel, Kathryn; Goldberg, Jeffrey M

2014-01-01

To determine the cosmetic appeal of different incision types used in gynecologic surgery. One hundred women between the ages of 20 and 40 years were shown 4 color photographs of a female abdomen with incision sites marked for Pfannenstiel, minilaparotomy, traditional laparoscopy, and robotic-assisted laparoscopy. The women were asked to rank the photographs on cosmetic appeal alone. An additional photograph depicting single-port laparoscopy was then added, and patients were asked to again rank the photographs. Participants were also asked basic demographic information and prior surgical history. Office practice. One hundred women between the ages of 20 and 40. Participants. Minilaparotomy was ranked as the most appealing incision among the first set of photographs by 74% of the participants, and the remaining 26% preferred traditional laparoscopy. Robotic-assisted laparoscopy was ranked as the least appealing scar type by 42%, and no patient selected it as their first choice. Sixty-four percent preferred the appearance of a single-port laparoscopic scar when that option was added. The only demographic variable that reached statistical significance was the presence of prior abdominal surgery. Patients without prior surgery ranked minilaparotomy as more cosmetically appealing. When several minimally invasive surgical approaches are possible, the patient should be counseled regarding the cosmetic results of each. Patients in this study strongly preferred the appearance of minilaparotomy and single-port incisions over full Pfannenstiel or robotic incisions. Copyright © 2014 AAGL. Published by Elsevier Inc. All rights reserved.

Distance-Ranked Fault Identification of Reconfigurable Hardware Bitstreams via Functional Input

Directory of Open Access Journals (Sweden)

Naveed Imran

2014-01-01

Full Text Available Distance-Ranked Fault Identification (DRFI is a dynamic reconfiguration technique which employs runtime inputs to conduct online functional testing of fielded FPGA logic and interconnect resources without test vectors. At design time, a diverse set of functionally identical bitstream configurations are created which utilize alternate hardware resources in the FPGA fabric. An ordering is imposed on the configuration pool as updated by the PageRank indexing precedence. The configurations which utilize permanently damaged resources and hence manifest discrepant outputs, receive lower rank are thus less preferred for instantiation on the FPGA. Results indicate accurate identification of fault-free configurations in a pool of pregenerated bitstreams with a low number of reconfigurations and input evaluations. For MCNC benchmark circuits, the observed reduction in input evaluations is up to 75% when comparing the DRFI technique to unguided evaluation. The DRFI diagnosis method is seen to isolate all 14 healthy configurations from a pool of 100 pregenerated configurations, and thereby offering a 100% isolation accuracy provided the fault-free configurations exist in the design pool. When a complete recovery is not feasible, graceful degradation may be realized which is demonstrated by the PSNR improvement of images processed in a video encoder case study.

How to Rank Journals.

Science.gov (United States)

Bradshaw, Corey J A; Brook, Barry W

2016-01-01

There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

Effect of the social influence on topological properties of user-object bipartite networks

Science.gov (United States)

Liu, Jian-Guo; Hu, Zhaolong; Guo, Qiang

2013-11-01

Social influence plays an important role in analyzing online users' collective behaviors [Salganik et al., Science 311, 854 (2006)]. However, the effect of the social influence from the viewpoint of theoretical model is missing. In this paper, by taking into account the social influence and users' preferences, we develop a theoretical model to analyze the topological properties of user-object bipartite networks, including the degree distribution, average nearest neighbor degree and the bipartite clustering coefficient, as well as topological properties of the original user-object networks and their unipartite projections. According to the users' preferences and the global ranking effect, we analyze the theoretical results for two benchmark data sets, Amazon and Bookcrossing, which are approximately consistent with the empirical results. This work suggests that this model is feasible to analyze topological properties of bipartite networks in terms of the social influence and the users' preferences.

Sparse Contextual Activation for Efficient Visual Re-Ranking.

Science.gov (United States)

Bai, Song; Bai, Xiang

2016-03-01

In this paper, we propose an extremely efficient algorithm for visual re-ranking. By considering the original pairwise distance in the contextual space, we develop a feature vector called sparse contextual activation (SCA) that encodes the local distribution of an image. Hence, re-ranking task can be simply accomplished by vector comparison under the generalized Jaccard metric, which has its theoretical meaning in the fuzzy set theory. In order to improve the time efficiency of re-ranking procedure, inverted index is successfully introduced to speed up the computation of generalized Jaccard metric. As a result, the average time cost of re-ranking for a certain query can be controlled within 1 ms. Furthermore, inspired by query expansion, we also develop an additional method called local consistency enhancement on the proposed SCA to improve the retrieval performance in an unsupervised manner. On the other hand, the retrieval performance using a single feature may not be satisfactory enough, which inspires us to fuse multiple complementary features for accurate retrieval. Based on SCA, a robust feature fusion algorithm is exploited that also preserves the characteristic of high time efficiency. We assess our proposed method in various visual re-ranking tasks. Experimental results on Princeton shape benchmark (3D object), WM-SRHEC07 (3D competition), YAEL data set B (face), MPEG-7 data set (shape), and Ukbench data set (image) manifest the effectiveness and efficiency of SCA.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan

2012-11-19

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-01-01

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

Directory of Open Access Journals (Sweden)

Wang Jim

2012-11-01

Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Evaluation of the osteoclastogenic process associated with RANK / RANK-L / OPG in odontogenic myxomas

Science.gov (United States)

González-Galván, María del Carmen; Mosqueda-Taylor, Adalberto; Bologna-Molina, Ronell; Setien-Olarra, Amaia; Marichalar-Mendia, Xabier; Aguirre-Urizar, José-Manuel

2018-01-01

Background Odontogenic myxoma (OM) is a benign intraosseous neoplasm that exhibits local aggressiveness and high recurrence rates. Osteoclastogenesis is an important phenomenon in the tumor growth of maxillary neoplasms. RANK (Receptor Activator of Nuclear Factor κappa B) is the signaling receptor of RANK-L (Receptor activator of nuclear factor kappa-Β ligand) that activates the osteoclasts. OPG (osteoprotegerin) is a decoy receptor for RANK-L that inhibits pro-osteoclastogenesis. The RANK / RANKL / OPG system participates in the regulation of osteolytic activity under normal conditions, and its alteration has been associated with greater bone destruction, and also with tumor growth. Objectives To analyze the immunohistochemical expression of OPG, RANK and RANK-L proteins in odontogenic myxomas (OMs) and their relationship with the tumor size. Material and Methods Eighteen OMs, 4 small ( 3cm) and 18 dental follicles (DF) that were included as control were studied by means of standard immunohistochemical procedure with RANK, RANKL and OPG antibodies. For the evaluation, 5 fields (40x) of representative areas of OM and DF were selected where the expression of each antibody was determined. Descriptive and comparative statistical analyses were performed with the obtained data. Results There are significant differences in the expression of RANK in OM samples as compared to DF (p = 0.022) and among the OMSs and OMLs (p = 0.032). Also a strong association is recognized in the expression of RANK-L and OPG in OM samples. Conclusions Activation of the RANK / RANK-L / OPG triad seems to be involved in the mechanisms of bone balance and destruction, as well as associated with tumor growth in odontogenic myxomas. Key words:Odontogenic myxoma, dental follicle, RANK, RANK-L, OPG, osteoclastogenesis. PMID:29680857

Preference-based serial decision dynamics: your first sushi reveals your eating order at the sushi table.

Directory of Open Access Journals (Sweden)

Jaeseung Jeong

Full Text Available In everyday life, we regularly choose among multiple items serially such as playing music in a playlist or determining priorities in a to-do list. However, our behavioral strategy to determine the order of choice is poorly understood. Here we defined 'the sushi problem' as how we serially choose multiple items of different degrees of preference when multiple sequences are possible, and no particular order is necessarily better than another, given that all items will eventually be chosen. In the current study, participants selected seven sushi pieces sequentially at the lunch table, and we examined the relationship between eating order and preference. We found two dominant selection strategies, with one group selecting in order from most to least preferred, and the other doing the opposite, which were significantly different from patterns generated from a random strategy. Interestingly, we found that more females tended to employ the favorite-first rather than favorite-last strategy. These two choice sequences appear to reflect two opposing behavioral strategies that might provide selective advantages in their own right, while also helping to provide solutions to otherwise unconstrained problems.

Ranking factors affecting the packing of saffron from the perspective of consumers

Directory of Open Access Journals (Sweden)

Arash Dorandish

2017-06-01

Full Text Available Packaging is a tool for recognition and differentiation of product and it plays a crucial role in consumers' purchasing decisions, and it can be used to create competitive advantages. Saffron is one of the most important agricultural crops in Iran and its packaging in accordance with consumer demand increases sales and satisfaction of the consumers. Therefore, the main objective of this study is to rank the factors affecting the packaging from the perspective of consumers of saffron in Mashhad. Data was collected in the form of 99 questionnaires that have been answered by the consumers of saffron in Mashhad in 2015. Analytic hierarchy process (AHP was used to rank these factors. The results showed that labeling information about internal and international standards and saffron nutrients on the package have the greatest impact on consumer preferences. Also, the results of the ranking alternatives indicated that attention to the brand labelled on the packing is the most important issue from the perspective of the consumers. Hence, labelling information elements on the package can be a good way for brand differentiation and increasing its value. According to the results, it is recommended that producers and suppliers of saffron pay more attention to features and information elements in package design.

Ranking Support Vector Machine with Kernel Approximation.

Science.gov (United States)

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Ranking Support Vector Machine with Kernel Approximation

Directory of Open Access Journals (Sweden)

Kai Chen

2017-01-01

Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Generalized Reduced Rank Tests using the Singular Value Decomposition

NARCIS (Netherlands)

F.R. Kleibergen (Frank); R. Paap (Richard)

2003-01-01

textabstractWe propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables

Assessing preferences about the DNR order: does it depend on how you ask?

Science.gov (United States)

Percy, M E; Llewellyn-Thomas, H

1995-01-01

Despite increasing emphasis on advance directives, there has been little methodologic work to assess preferences about the "do not resuscitate" (DNR) order. This developmental work assessed, in a non-patient group, the performance of a probability-trade-off task designed to assess DNR attitudes, in terms of framing effects and stability of preferences. 105 female nursing students each completed one of two versions of the task. In version I (n = 58), the trade-off moved to increasingly negative descriptions of the outcomes of resuscitation (decreasing chance of survival and increasing risk of brain death), whereas in version II (n = 47), the trade-off moved to increasingly positive descriptions. One week later, repeat assessments were obtained for versions I (n = 35) and II (n = 28). The DNR preference scores were lower and more stable when the task moved to increasingly positive descriptions; perhaps this version of the task tends to weaken risk aversion. These results imply that care should be used in applying a probability trade-off task to the assessment of DNR preferences, since artefactual effects could be induced.

Generalized reduced rank tests using the singular value decomposition

NARCIS (Netherlands)

Kleibergen, F.R.; Paap, R.

2002-01-01

We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables for the LDU

A novel approach based on preference-based index for interval bilevel linear programming problem.

Science.gov (United States)

Ren, Aihong; Wang, Yuping; Xue, Xingsi

2017-01-01

This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation [Formula: see text]. Furthermore, the concept of a preference δ -optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.

A novel approach based on preference-based index for interval bilevel linear programming problem

Directory of Open Access Journals (Sweden)

Aihong Ren

2017-05-01

Full Text Available Abstract This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation ⪯ m w $\\preceq_{mw}$ . Furthermore, the concept of a preference δ-optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.

When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

KAUST Repository

Wang, Jim Jing-Yan

2017-06-28

Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been considered separately, assuming that data coding and ranking are two independent and irrelevant problems. However, is there any internal relationship between sparse coding and ranking score learning? If yes, how to explore and make use of this internal relationship? In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm. To explore the local distribution in the sparse code space, and also to bridge coding and ranking problems, we assume that in the neighborhood of each data point, the ranking scores can be approximated from the corresponding sparse codes by a local linear function. By considering the local approximation error of ranking scores, the reconstruction error and sparsity of sparse coding, and the query information provided by the user, we construct a unified objective function for learning of sparse codes, the dictionary and ranking scores. We further develop an iterative algorithm to solve this optimization problem.

A model-based approach to operational event groups ranking

Energy Technology Data Exchange (ETDEWEB)

Simic, Zdenko [European Commission Joint Research Centre, Petten (Netherlands). Inst. for Energy and Transport; Maqua, Michael [Gesellschaft fuer Anlagen- und Reaktorsicherheit mbH (GRS), Koeln (Germany); Wattrelos, Didier [Institut de Radioprotection et de Surete Nucleaire (IRSN), Fontenay-aux-Roses (France)

2014-04-15

The operational experience (OE) feedback provides improvements in all industrial activities. Identification of the most important and valuable groups of events within accumulated experience is important in order to focus on a detailed investigation of events. The paper describes the new ranking method and compares it with three others. Methods have been described and applied to OE events utilised by nuclear power plants in France and Germany for twenty years. The results show that different ranking methods only roughly agree on which of the event groups are the most important ones. In the new ranking method the analytical hierarchy process is applied in order to assure consistent and comprehensive weighting determination for ranking indexes. The proposed method allows a transparent and flexible event groups ranking and identification of the most important OE for further more detailed investigation in order to complete the feedback. (orig.)

Intrasubject Predictions of Vocational Preference: Convergent Validation via the Decision Theoretic Paradigm.

Science.gov (United States)

Monahan, Carlyn J.; Muchinsky, Paul M.

1985-01-01

The degree of convergent validity among four methods of identifying vocational preferences is assessed via the decision theoretic paradigm. Vocational preferences identified by Holland's Vocational Preference Inventory (VPI), a rating procedure, and ranking were compared with preferences identified from a policy-capturing model developed from an…

A Case-Based Reasoning Method with Rank Aggregation

Science.gov (United States)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

Organic and Conventional Dairy Farmers Prefer Different Improvements in Breeding Goal Traits

DEFF Research Database (Denmark)

Slagboom, Margot; Kargo, Morten; Edwards, David

software 1000Minds. These pairwise rankings were based on equal economic worth of trait improvements. The survey was filled in by 106 organic and 290 conventional farmers. The most preferred trait improvement for both production systems was in cow fertility, and the least preferred improvement......In dairy cattle breeding, breeding goals (BG) are developed and subsequently a selection index that farmers want to use. Therefore it is important to take their preferences for BG traits into account. Two production systems that are expected to influence farmer preferences for BG traits are organic...... and conventional systems. The aim of this study was to characterize preferences of organic and conventional Danish dairy farmers for improvements in BG traits for Holstein cattle. A survey was established to characterize preferences for improvements in ten traits, by means of pairwise rankings using the online...

Pharmacy Students’ Preference for Using Mobile Devices in a Clinical Setting for Practice-Related Tasks

Science.gov (United States)

Hastings, Justine F.; Bryant, Jennifer E.

2015-01-01

Objective. To examine pharmacy students’ ownership of, use of, and preference for using a mobile device in a practice setting. Methods. Eighty-one pharmacy students were recruited and completed a pretest that collected information about their demographics and mobile devices and also had them rank the iPhone, iPad mini, and iPad for preferred use in a pharmacy practice setting. Students used the 3 devices to perform pharmacy practice-related tasks and then completed a posttest to again rank the devices for preferred use in a pharmacy practice setting. Results. The iPhone was the most commonly owned mobile device (59.3% of students), and the iPad mini was the least commonly owned (18.5%). About 70% of the students used their mobile devices at least once a week in a pharmacy practice setting. The iPhone was the most commonly used device in a practice setting (46.9% of students), and the iPod Touch was the least commonly used device (1.2%). The iPad mini was the most preferred device for use in a pharmacy practice setting prior to performing pharmacy practice-related tasks (49.4% of students), and was preferred by significantly more students after performing the tasks (70.4%). Conclusion. Pharmacy students commonly use their mobile devices in pharmacy practice settings and most selected the iPad mini as the preferred device for use in a practice setting even though it was the device owned by the fewest students. PMID:25861103

The comparison of usage and availability measurements for evaluating resource preference

Science.gov (United States)

Johnson, Douglas H.

1980-01-01

Modern ecological research often involves the comparison of the usage of habitat types or food items to the availability of those resources to the animal. Widely used methods of determining preference from measurements of usage and availability depend critically on the array of components that the researcher, often with a degree of arbitrariness, deems available to the animal. This paper proposes a new method, based on ranks of components by usage and by availability. A virtue of the rank procedure is that it provides comparable results whether a questionable component is included or excluded from consideration. Statistical tests of significance are given for the method. The paper also offers a hierarchical ordering of selection processes. This hierarchy resolves certain inconsistencies among studies of selection and is compatible with the analytic technique offered in this paper.

RUSSIAN UNIVERSITIES IN THE LOOP OF THE WORLD EDUCATION RANKINGS

Directory of Open Access Journals (Sweden)

Inozemtseva Ekaterina Sergeevna

2013-02-01

Full Text Available Purpose: a research on different sociological and economic aspects of world education rankings (THE, ARWU, QS, evaluation of their role and impact on the world education market’s main consumers (i.e. students and academic staff as a subject to discussion in terms of the customers’ preferences and choice motivators. Methodology: general scientific research tools were applied throughout the research: analysis, synthesis, deduction. Results: world ranking approach and methodology was assessed, defined and systemized, a unique general ranking of the countries was developed and performed (based on the researched body – the US ranked #1, Russia #30, expert recommendations for Russian universities have been developed and concluded. Practical implications: the main statements could be used within learning courses on the internationalization of higher education and applied in sociological and economic research dedicated to macroeconomic problems and issues analysis.

Ranking economic history journals

DEFF Research Database (Denmark)

Di Vaio, Gianfranco; Weisdorf, Jacob Louis

2010-01-01

This study ranks-for the first time-12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We also...... compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential for economic...... history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

Ranking Economic History Journals

DEFF Research Database (Denmark)

Di Vaio, Gianfranco; Weisdorf, Jacob Louis

This study ranks - for the first time - 12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We...... also compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential...... for economic history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

Grooming Up the Hierarchy: The Exchange of Grooming and Rank-Related Benefits in a New World Primate

OpenAIRE

Tiddi, Barbara; Aureli, Filippo; Schino, Gabriele

2012-01-01

Seyfarth’s model assumes that female primates derive rank-related benefits from higher-ranking females in exchange for grooming. As a consequence, the model predicts females prefer high-ranking females as grooming partners and compete for the opportunity to groom them. Therefore, allogrooming is expected to be directed up the dominance hierarchy and to occur more often between females with adjacent ranks. Although data from Old World primates generally support the model, studies o...

Digital image comparison by subtracting contextual transformations—percentile rank order differentiation

Science.gov (United States)

Wehde, M. E.

1995-01-01

The common method of digital image comparison by subtraction imposes various constraints on the image contents. Precise registration of images is required to assure proper evaluation of surface locations. The attribute being measured and the calibration and scaling of the sensor are also important to the validity and interpretability of the subtraction result. Influences of sensor gains and offsets complicate the subtraction process. The presence of any uniform systematic transformation component in one of two images to be compared distorts the subtraction results and requires analyst intervention to interpret or remove it. A new technique has been developed to overcome these constraints. Images to be compared are first transformed using the cumulative relative frequency as a transfer function. The transformed images represent the contextual relationship of each surface location with respect to all others within the image. The process of differentiating between the transformed images results in a percentile rank ordered difference. This process produces consistent terrain-change information even when the above requirements necessary for subtraction are relaxed. This technique may be valuable to an appropriately designed hierarchical terrain-monitoring methodology because it does not require human participation in the process.

Subtracting a best rank-1 approximation may increase tensor rank

NARCIS (Netherlands)

Stegeman, Alwin; Comon, Pierre

2010-01-01

It has been shown that a best rank-R approximation of an order-k tensor may not exist when R >= 2 and k >= 3. This poses a serious problem to data analysts using tensor decompositions it has been observed numerically that, generally, this issue cannot be solved by consecutively computing and

An Objective Approach to Determining the Weight Ranges of Prey Preferred by and Accessible to the Five Large African Carnivores

OpenAIRE

Clements, Hayley S.; Tambling, Craig J.; Hayward, Matt W.; Kerley, Graham I. H.

2014-01-01

Broad-scale models describing predator prey preferences serve as useful departure points for understanding predator-prey interactions at finer scales. Previous analyses used a subjective approach to identify prey weight preferences of the five large African carnivores, hence their accuracy is questionable. This study uses a segmented model of prey weight versus prey preference to objectively quantify the prey weight preferences of the five large African carnivores. Based on simulations of kno...

Using Likert-type and ipsative/forced choice items in sequence to generate a preference.

Science.gov (United States)

Ried, L Douglas

2014-01-01

Collaboration and implementation of a minimum, standardized set of core global educational and professional competencies seems appropriate given the expanding international evolution of pharmacy practice. However, winnowing down hundreds of competencies from a plethora of local, national and international competency frameworks to select the most highly preferred to be included in the core set is a daunting task. The objective of this paper is to describe a combination of strategies used to ascertain the most highly preferred items among a large number of disparate items. In this case, the items were >100 educational and professional competencies that might be incorporated as the core components of new and existing competency frameworks. Panelists (n = 30) from the European Union (EU) and United States (USA) were chosen to reflect a variety of practice settings. Each panelist completed two electronic surveys. The first survey presented competencies in a Likert-type format and the second survey presented many of the same competencies in an ipsative/forced choice format. Item mean scores were calculated for each competency, the competencies were ranked, and non-parametric statistical tests were used to ascertain the consistency in the rankings achieved by the two strategies. This exploratory study presented over 100 competencies to the panelists in the beginning. The two methods provided similar results, as indicated by the significant correlation between the rankings (Spearman's rho = 0.30, P < 0.09). A two-step strategy using Likert-type and ipsative/forced choice formats in sequence, appears to be useful in a situation where a clear preference is required from among a large number of choices. The ipsative/forced choice format resulted in some differences in the competency preferences because the panelists could not rate them equally by design. While this strategy was used for the selection of professional educational competencies in this exploratory study, it is

Universal scaling in sports ranking

International Nuclear Information System (INIS)

Deng Weibing; Li Wei; Cai Xu; Bulou, Alain; Wang Qiuping A

2012-01-01

Ranking is a ubiquitous phenomenon in human society. On the web pages of Forbes, one may find all kinds of rankings, such as the world's most powerful people, the world's richest people, the highest-earning tennis players, and so on and so forth. Herewith, we study a specific kind—sports ranking systems in which players' scores and/or prize money are accrued based on their performances in different matches. By investigating 40 data samples which span 12 different sports, we find that the distributions of scores and/or prize money follow universal power laws, with exponents nearly identical for most sports. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player tops the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different matches. The simulations yield results consistent with the empirical findings. Extensive simulation studies indicate that the model is quite robust with respect to the modifications of some parameters. (paper)

Ranking online quality and reputation via the user activity

Science.gov (United States)

Liu, Xiao-Lu; Guo, Qiang; Hou, Lei; Cheng, Can; Liu, Jian-Guo

2015-10-01

How to design an accurate algorithm for ranking the object quality and user reputation is of importance for online rating systems. In this paper we present an improved iterative algorithm for online ranking object quality and user reputation in terms of the user degree (IRUA), where the user's reputation is measured by his/her rating vector, the corresponding objects' quality vector and the user degree. The experimental results for the empirical networks show that the AUC values of the IRUA algorithm can reach 0.9065 and 0.8705 in Movielens and Netflix data sets, respectively, which is better than the results generated by the traditional iterative ranking methods. Meanwhile, the results for the synthetic networks indicate that user degree should be considered in real rating systems due to users' rating behaviors. Moreover, we find that enhancing or reducing the influences of the large-degree users could produce more accurate reputation ranking lists.

Stakeholder preferences towards the sustainable development of CDM projects: Lessons from biomass (rice husk) CDM project in Thailand

International Nuclear Information System (INIS)

Parnphumeesup, Piya; Kerr, Sandy A.

2011-01-01

This research applies both quantitative and qualitative methods to investigate stakeholder preferences towards sustainable development (SD) priorities in Clean Development Mechanism (CDM) projects. The CDM's contribution to SD is explored in the context of a biomass (rice husk) case study conducted in Thailand. Quantitative analysis ranks increasing the usage of renewable energy as the highest priority, followed by employment and technology transfer. Air pollution (dust) is ranked as the most important problem. Preference weights expressed by experts and local resident are statistically different in the cases of: employment generation; emission reductions; dust; waste disposal; and noise. Qualitative results, suggest that rice husk CDM projects contribute significantly to SD in terms of employment generation, an increase in usage of renewable energy, and transfer of knowledge. However, rice husk biomass projects create a potential negative impact on air quality. In order to ensure the environmental sustainability of CDM projects, stakeholders suggest that Thailand should cancel an Environmental Impact Assessment (EIA) exemption for CDM projects with an installed capacity below 10 MW and apply it to all CDM projects. - Highlights: → Stakeholders rank increasing the usage of renewable energy as the highest priority. → Biomass (rice husk) CDM projects create a potential negative impact on air quality. → Rice husk CDM projects cannot give an extra income to farmers. → Preference weights expressed by experts and local residents are statistically different.

Freudenthal ranks: GHZ versus W

International Nuclear Information System (INIS)

Borsten, L

2013-01-01

The Hilbert space of three-qubit pure states may be identified with a Freudenthal triple system. Every state has an unique Freudenthal rank ranging from 1 to 4, which is determined by a set of automorphism group covariants. It is shown here that the optimal success rates for winning a three-player non-local game, varying over all local strategies, are strictly ordered by the Freudenthal rank of the shared three-qubit resource. (paper)

Differential invariants for higher-rank tensors. A progress report

International Nuclear Information System (INIS)

Tapial, V.

2004-07-01

We outline the construction of differential invariants for higher-rank tensors. In section 2 we outline the general method for the construction of differential invariants. A first result is that the simplest tensor differential invariant contains derivatives of the same order as the rank of the tensor. In section 3 we review the construction for the first-rank tensors (vectors) and second-rank tensors (metrics). In section 4 we outline the same construction for higher-rank tensors. (author)

Ranking accounting, banking and finance journals: A note

OpenAIRE

Halkos, George; Tzeremes, Nickolaos

2012-01-01

This paper by applying Data Envelopment Analysis (DEA) ranks Economics journals in the field of Accounting, Banking and Finance. By using one composite input and one composite output the paper ranks 57 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with the highest rankings in the field are Journal of Fi...

Ranking health between countries in international comparisons

DEFF Research Database (Denmark)

Brønnum-Hansen, Henrik

2014-01-01

Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions and docum......Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions...

Relative Performance Information, Rank Ordering and Employee Performance: A Research Note

NARCIS (Netherlands)

Kramer, S.; Maas, V.S.; van Rinsum, M.

2016-01-01

We conduct a laboratory experiment to examine whether the provision of detailed relative performance information (i.e., information about the specific performance levels of peers) affects employee performance. We also investigate how – if at all – explicit ranking of performance levels affects how

RUSSIAN UNIVERSITIES IN THE LOOP OF THE WORLD EDUCATION RANKINGS

Directory of Open Access Journals (Sweden)

Екатерина Сергеевна Иноземцева

2013-04-01

Full Text Available Purpose: a research on different sociological and economic aspects of world education rankings (THE, ARWU, QS, evaluation of their role and impact on the world education market’s main consumers (i.e. students and academic staff as a subject to discussion in terms of the customers’ preferences and choice motivators.  Methodology: general scientific research tools were applied throughout the research: analysis, synthesis, deduction.Results: world ranking approach and methodology was assessed, defined and systemized, a unique general ranking of the countries was developed and performed (based on the researched body – the US ranked #1, Russia #30, expert recommendations for Russian universities have been developed and concluded.Practical implications: the main statements could be used within learning courses on the internationalization of higher education and applied in sociological and economic research dedicated to macroeconomic problems and issues analysis.DOI: http://dx.doi.org/10.12731/2218-7405-2013-2-18

Ranking adverse drug reactions with crowdsourcing.

Science.gov (United States)

Gottlieb, Assaf; Hoehndorf, Robert; Dumontier, Michel; Altman, Russ B

2015-03-23

There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. The intent of the study was to rank ADRs according to severity. We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

Self-esteem, interpersonal risk, and preference for e-mail to face-to-face communication.

Science.gov (United States)

Joinson, Adam N

2004-08-01

The media choices made by high and low self-esteem Internet users were studied using web-based methodology (n = 265). Participants were asked to rank four media (face-to-face, e-mail, letter, and telephone) in order of preference across four different communication scenarios designed to pose an interpersonal risk. The level of interpersonal risk posed by two of the scenarios (asking for a pay rise and asking for a date) were also experimentally manipulated by randomly allocating participants to a 25%, 50%, or 75% chance of rejection. Low self-esteem users (LSE) showed a significant preference toward e-mail communication compared to high self-esteem users (HSE). This pattern was reversed for face-to-face preferences. Similarly, a greater chance of rejection in a scenario led to e-mail being preferred to face-to-face communication. The results are discussed in light of both the strategic use of different media and the motivated Internet user.

Compensatory versus noncompensatory models for predicting consumer preferences

Directory of Open Access Journals (Sweden)

Anja Dieckmann

2009-04-01

Full Text Available Standard preference models in consumer research assume that people weigh and add all attributes of the available options to derive a decision, while there is growing evidence for the use of simplifying heuristics. Recently, a greedoid algorithm has been developed (Yee, Dahan, Hauser and Orlin, 2007; Kohli and Jedidi, 2007 to model lexicographic heuristics from preference data. We compare predictive accuracies of the greedoid approach and standard conjoint analysis in an online study with a rating and a ranking task. The lexicographic model derived from the greedoid algorithm was better at predicting ranking compared to rating data, but overall, it achieved lower predictive accuracy for hold-out data than the compensatory model estimated by conjoint analysis. However, a considerable minority of participants was better predicted by lexicographic strategies. We conclude that the new algorithm will not replace standard tools for analyzing preferences, but can boost the study of situational and individual differences in preferential choice processes.

A multi-objective decision-making approach to the journal submission problem.

Directory of Open Access Journals (Sweden)

Tony E Wong

Full Text Available When researchers complete a manuscript, they need to choose a journal to which they will submit the study. This decision requires to navigate trade-offs between multiple objectives. One objective is to share the new knowledge as widely as possible. Citation counts can serve as a proxy to quantify this objective. A second objective is to minimize the time commitment put into sharing the research, which may be estimated by the total time from initial submission to final decision. A third objective is to minimize the number of rejections and resubmissions. Thus, researchers often consider the trade-offs between the objectives of (i maximizing citations, (ii minimizing time-to-decision, and (iii minimizing the number of resubmissions. To complicate matters further, this is a decision with multiple, potentially conflicting, decision-maker rationalities. Co-authors might have different preferences, for example about publishing fast versus maximizing citations. These diverging preferences can lead to conflicting trade-offs between objectives. Here, we apply a multi-objective decision analytical framework to identify the Pareto-front between these objectives and determine the set of journal submission pathways that balance these objectives for three stages of a researcher's career. We find multiple strategies that researchers might pursue, depending on how they value minimizing risk and effort relative to maximizing citations. The sequences that maximize expected citations within each strategy are generally similar, regardless of time horizon. We find that the "conditional impact factor"-impact factor times acceptance rate-is a suitable heuristic method for ranking journals, to strike a balance between minimizing effort objectives and maximizing citation count. Finally, we examine potential co-author tension resulting from differing rationalities by mapping out each researcher's preferred Pareto front and identifying compromise submission strategies

关于序区间偏好信息的群决策方法研究%Study on the method of ranking in group decision making based on ordinal interval preference information

Institute of Scientific and Technical Information of China (English)

陈侠; 陈岩

2011-01-01

It is a new important research topic to discuss the problem of ranking in group decision making based on ordinal interval preference information. In this paper, an analytic method is proposed to solve the problem of ranking based on the ordinal interval preference information in decision making. Firstly, some concepts and characters of the ordinal interval preference information are introduced. Then, based on introducing the concepts of possibility and possibility matrix, the conclusion is obtained that the matrices of possibility of all experts are fuzzy reciprocal matrices and they are weak consistent. Furthermore, an optimization model of group consensus is constructed to calculate the optimization weigh vector, and an analysis method of ranking in group decision making based on the ordinal interval preference information is proposed. Finally, a numerical example is given to illustrate the use of the proposed analysis method.%在群决策分析中,基于序区间偏好信息的排序方法的研究是一个新的重要研究课题.针对决策分析中基于序区间偏好信息的群决策方法问题,提出了一种新的分析方法.首先,提出了序区间的有关定义及性质；其次,通过定义序区间的可能度及可能度矩阵的概念,得出了每个专家的可能度矩阵均具有满意一致性的互补判断矩阵结论.进而构建了基于群体一致性的最优化模型,依据计算的最优权重向量给出了一种关于序区间偏好信息的群决策方案排序方法.最后,通过一个算例说明了提出的分析方法.

Social class & risk preferences and behavior.

Science.gov (United States)

Kish-Gephart, Jennifer J

2017-12-01

This paper reviews recent work regarding the link between one's societal ranking (or social class), and risk preferences and behavior. While the topic of social class and its relationship to risk has been studied only tentatively in psychology, preliminary evidence suggests that experiences with rank, access to resources, and movement between classes have a meaningful impact on people's risk preferences and behaviors. Yet, a clear pattern of results remains elusive. Some studies suggest that lower social class standing is related to risk aversion, while others suggest it is related to risk taking. These mixed results highlight the need for future research that examines when and why lower social class standing is related to more or less risky decisions. By shedding light on this important phenomenon, the hope is to offer intervention opportunities that influence policies and mitigate inequality. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ranking periodic ordering models on the basis of minimizing total inventory cost

Directory of Open Access Journals (Sweden)

Mohammadali Keramati

2015-06-01

Full Text Available This paper aims to provide proper policies for inventory under uncertain conditions by comparing different inventory policies. To review the efficiency of these algorithms it is necessary to specify the area in which each of them is applied. Therefore, each of the models has been reviewed under different forms of retailing and they are ranked in terms of their expenses. According to the high values of inventories and their impacts on the costs of the companies, the ranking of various models using the simulation annealing algorithm are presented, which indicates that the proposed model of this paper could perform better than other alternative ones. The results also indicate that the suggested algorithm could save from 4 to 29 percent on costs of inventories.

Co-integration Rank Testing under Conditional Heteroskedasticity

DEFF Research Database (Denmark)

Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert

null distributions of the rank statistics coincide with those derived by previous authors who assume either i.i.d. or (strict and covariance) stationary martingale difference innovations. We then propose wild bootstrap implementations of the co-integrating rank tests and demonstrate that the associated...... bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show the same is also true of the corresponding rank tests based on the i.i.d. bootstrap of Swensen (2006). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap......, it preserves in the re-sampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence sug- gests that, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples un...

Support vector regression scoring of receptor-ligand complexes for rank-ordering and virtual screening of chemical libraries.

Science.gov (United States)

Li, Liwei; Wang, Bo; Meroueh, Samy O

2011-09-26

The community structure-activity resource (CSAR) data sets are used to develop and test a support vector machine-based scoring function in regression mode (SVR). Two scoring functions (SVR-KB and SVR-EP) are derived with the objective of reproducing the trend of the experimental binding affinities provided within the two CSAR data sets. The features used to train SVR-KB are knowledge-based pairwise potentials, while SVR-EP is based on physicochemical properties. SVR-KB and SVR-EP were compared to seven other widely used scoring functions, including Glide, X-score, GoldScore, ChemScore, Vina, Dock, and PMF. Results showed that SVR-KB trained with features obtained from three-dimensional complexes of the PDBbind data set outperformed all other scoring functions, including best performing X-score, by nearly 0.1 using three correlation coefficients, namely Pearson, Spearman, and Kendall. It was interesting that higher performance in rank ordering did not translate into greater enrichment in virtual screening assessed using the 40 targets of the Directory of Useful Decoys (DUD). To remedy this situation, a variant of SVR-KB (SVR-KBD) was developed by following a target-specific tailoring strategy that we had previously employed to derive SVM-SP. SVR-KBD showed a much higher enrichment, outperforming all other scoring functions tested, and was comparable in performance to our previously derived scoring function SVM-SP.

Task 27 -- Alaskan low-rank coal-water fuel demonstration project

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-10-01

Development of coal-water-fuel (CWF) technology has to-date been predicated on the use of high-rank bituminous coal only, and until now the high inherent moisture content of low-rank coal has precluded its use for CWF production. The unique feature of the Alaskan project is the integration of hot-water-drying (HWD) into CWF technology as a beneficiation process. Hot-water-drying is an EERC developed technology unavailable to the competition that allows the range of CWF feedstock to be extended to low-rank coals. The primary objective of the Alaskan Project, is to promote interest in the CWF marketplace by demonstrating the commercial viability of low-rank coal-water-fuel (LRCWF). While commercialization plans cannot be finalized until the implementation and results of the Alaskan LRCWF Project are known and evaluated, this report has been prepared to specifically address issues concerning business objectives for the project, and outline a market development plan for meeting those objectives.

Measuring higher order ambiguity preferences.

Science.gov (United States)

Baillon, Aurélien; Schlesinger, Harris; van de Kuilen, Gijs

2018-01-01

We report the results from an experiment designed to measure attitudes towards ambiguity beyond ambiguity aversion. In particular, we implement recently-proposed model-free preference conditions of ambiguity prudence and ambiguity temperance. Ambiguity prudence has been shown to play an important role in precautionary behavior and the mere presence of ambiguity averse agents in markets. We observe that the majority of individuals' decisions are consistent with ambiguity aversion, ambiguity prudence and ambiguity temperance. This finding confirms the prediction of many popular (specifications of) ambiguity models and has important implications for models of prevention behavior.

[Differences in dietary habits and food preferences of adults depending on the age].

Science.gov (United States)

Adamska, Edyta; Ostrowska, Lucyna; Adamska, Ewelina; Maliszewska, Katarzyna; Citko, Anna; Waszczeniuk, Magdalena; Przystupa, Wojciech; Majewski, Radosław; Wasilewska, Anna; Milewski, Robert; Krytowski, Adam; Górska, Maria

2012-01-01

Changes in the structure and functioning of the body occur with age. Also nutrition is continually modified. Eating habits may affect favorably or unfavorably on the process of aging and the functioning of various tissues, organs and the whole body. The purpose of the study was to evaluate dietary habits and food preferences of patients in different age groups. In the studied groups also body mass index (BMI) and body fat content were analyzed. 237 people (133 women and 104 men, age 18-79 years) were examined. The participants completed questionnaires of the frequency of food consumption and food preferences. The height, weight, body mass index (BMI), the percentage of body fat (BIA) were also measured. For statistical analysis the assessment of correlation Spearman's rank order and nonparametric ANOVA rank Kruskal-Wallis were used. With age, the frequency of milk (p habits vary depending on age and may be one of the elements affecting the increase in BMI, body fat content, bone mass loss and increased risk of metabolic disorders. The observed changes in dietary habits can contribute to the development of dyslipidemia, glucose dysmetabolism and arterial hypertension, especially in the presence of overweight and obesity.

A Ranking Method for Evaluating Constructed Responses

Science.gov (United States)

Attali, Yigal

2014-01-01

This article presents a comparative judgment approach for holistically scored constructed response tasks. In this approach, the grader rank orders (rather than rate) the quality of a small set of responses. A prior automated evaluation of responses guides both set formation and scaling of rankings. Sets are formed to have similar prior scores and…

PageRank, HITS and a unified framework for link analysis

Energy Technology Data Exchange (ETDEWEB)

Ding, Chris; He, Xiaofeng; Husbands, Parry; Zha, Hongyuan; Simon, Horst

2001-10-01

Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement between authority and hub webpages, while PageRank emphasizes hyperlink weight normalization and web surfing based on random walk models. We systematically generalize/combine these concepts into a unified framework. The ranking framework contains a large algorithm space; HITS and PageRank are two extreme ends in this space. We study several normalized ranking algorithms which are intermediate between HITS and PageRank, and obtain closed-form solutions. We show that, to first order approximation, all ranking algorithms in this framework, including PageRank and HITS, lead to same ranking which is highly correlated with ranking by indegree. These results support the notion that in web resource ranking indegree and outdegree are of fundamental importance. Rankings of webgraphs of different sizes and queries are presented to illustrate our analysis.

Ranking Performance Measures in Multi-Task Agencies

DEFF Research Database (Denmark)

Christensen, Peter Ove; Sabac, Florin; Tian, Joyce

2010-01-01

We derive sufficient conditions for ranking performance evaluation systems in multi-task agency models (using both optimal and linear contracts) in terms of a second-order stochastic dominance (SSD) condition on the likelihood ratios. The SSD condition can be replaced by a variance-covariance mat......We derive sufficient conditions for ranking performance evaluation systems in multi-task agency models (using both optimal and linear contracts) in terms of a second-order stochastic dominance (SSD) condition on the likelihood ratios. The SSD condition can be replaced by a variance...

Measuring Prefered Services from Cloud Computing Providers ...

African Journals Online (AJOL)

pc

2018, 10(5S), 207-212. 207. Measuring Prefered Services from ... Published online: 22 March 2018 .... and then introduces a general service selection and ranking model with QoS ..... To facilitate add, remove, and prioritize services in election.

Reduced Rank Adaptive Filtering in Impulsive Noise Environments

KAUST Repository

Soury, Hamza

2014-01-06

An impulsive noise environment is used in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction. The minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each algorithm is discussed.

Reduced Rank Adaptive Filtering in Impulsive Noise Environments

KAUST Repository

Soury, Hamza; Abed-Meraim, Karim; Alouini, Mohamed-Slim

2014-01-01

An impulsive noise environment is used in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction. The minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each algorithm is discussed.

A Ranking Approach to Genomic Selection.

Science.gov (United States)

Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

2015-01-01

Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

Why Are Indian Children So Short? The Role of Birth Order and Son Preference.

Science.gov (United States)

Jayachandran, Seema; Pandi, Rohini

2017-09-01

Child stunting in India exceeds that in poorer regions like sub-Saharan Africa. Data on over 168,000 children show that, relative to Africa, India's height disadvantage increases sharply with birth order. We posit that India’s steep birth order gradient is due to favoritism toward eldest sons, which affects parents' fertility decisions and resource allocation across children. We show that, within India, the gradient is steeper for high-son-preference regions and religions. The gradient also varies with sibling gender as predicted. A back-of-the-envelope calculation suggests that India's steeper birth order gradient can explain over one-half of the India-Africa gap in average child height.

Rank Dynamics

Science.gov (United States)

Gershenson, Carlos

Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

Verifying object-oriented programs with higher-order separation logic in Coq

DEFF Research Database (Denmark)

Bengtson, Jesper; Jensen, Jonas Braband; Sieczkowski, Filip

2011-01-01

We present a shallow Coq embedding of a higher-order separation logic with nested triples for an object-oriented programming language. Moreover, we develop novel specification and proof patterns for reasoning in higher-order separation logic with nested triples about programs that use interfaces...... and interface inheritance. In particular, we show how to use the higher-order features of the Coq formalisation to specify and reason modularly about programs that (1) depend on some unknown code satisfying a specification or that (2) return objects conforming to a certain specification. All of our results have...

Is It that Difficult to Find a Good Preference Order for the Incremental Algorithm?

Science.gov (United States)

Krahmer, Emiel; Koolen, Ruud; Theune, Mariet

2012-01-01

In a recent article published in this journal (van Deemter, Gatt, van der Sluis, & Power, 2012), the authors criticize the Incremental Algorithm (a well-known algorithm for the generation of referring expressions due to Dale & Reiter, 1995, also in this journal) because of its strong reliance on a pre-determined, domain-dependent Preference Order.…

Statistically derived factors of varied importance to audiologists when making a hearing aid brand preference decision.

Science.gov (United States)

Johnson, Earl E; Mueller, H Gustav; Ricketts, Todd A

2009-01-01

To determine the amount of importance audiologists place on various items related to their selection of a preferred hearing aid brand manufacturer. Three hundred forty-three hearing aid-dispensing audiologists rated a total of 32 randomized items by survey methodology. Principle component analysis identified seven orthogonal statistical factors of importance. In rank order, these factors were Aptitude of the Brand, Image, Cost, Sales and Speed of Delivery, Exposure, Colleague Recommendations, and Contracts and Incentives. While it was hypothesized that differences among audiologists in the importance ratings of these factors would dictate their preference for a given brand, that was not our finding. Specifically, mean ratings for the six most important factors did not differ among audiologists preferring different brands. A statistically significant difference among audiologists preferring different brands was present, however, for one factor: Contracts and Incentives. Its assigned importance, though, was always lower than that for the other six factors. Although most audiologists have a preferred hearing aid brand, differences in the perceived importance of common factors attributed to brands do not largely determine preference for a particular brand.

Retirement Age: Preferences of Employees Representing Various Age Groups

Directory of Open Access Journals (Sweden)

Iwona Mendryk

2017-12-01

Full Text Available Prolonging professional activity constitutes one of the possible solutions for alleviating negative consequences of demographic changes/population ageing. Devising effective tools motivating employees to remain professionally active must take into account preferences associated with retirement age. The following constitute the objectives of the present paper: 1 identification of preferences in the retirement age for various age groups; 2 indication of potential consequences behind particular preferences; 3 formulation of guidelines for human resources management in organizations. In order to achieve these objectives, the results of the study encompassing 2076 respondents, specialists employed in various departments of Polish innovative companies, were analysed. On average, for each evaluated age group, the preferred retirement age was much lower than the statutory retirement age in Poland (65 years . In case of women in 45+ age groups, the average retirement age was observed to be higher than 60 years (the new statutory threshold.

Solving the Fully Fuzzy Bilevel Linear Programming Problem through Deviation Degree Measures and a Ranking Function Method

Directory of Open Access Journals (Sweden)

Aihong Ren

2016-01-01

Full Text Available This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solution of the problem, we apply deviation degree measures to deal with the fuzzy constraints and use a ranking function method of fuzzy numbers to rank the upper and lower level fuzzy objective functions. Then the fully fuzzy bilevel linear programming problem can be transformed into a deterministic bilevel programming problem. Considering the overall balance between improving objective function values and decreasing allowed deviation degrees, the computational procedure for finding a fuzzy optimal solution is proposed. Finally, a numerical example is provided to illustrate the proposed approach. The results indicate that the proposed approach gives a better optimal solution in comparison with the existing method.

Ranking oil sands bitumen recovery techniques

Energy Technology Data Exchange (ETDEWEB)

Lam, A.; Nobes, D.S.; Lipsett, M.G. [Alberta Univ., Edmonton, AB (Canada). Dept. of Mechanical Engineering

2009-07-01

The preference ranking organization method (PROMETHEE) was used to assess and rank 3 techniques for in situ bitumen recovery: (1) steam assisted gravity drainage; (2) vapour extraction (VAPEX); and (3) toe-to-heel air injection (THAI). The study used a business scenario where management-type indicators included potential production rates; estimated overall operating costs; energy consumption; facilities requirement; recovery efficiency; and energy loss. Amounts of carbon dioxide (CO{sub 2}) emissions were also considered, as well as the production depth, formation thickness, and API gravity of the produced bitumen. The study showed that THAI recovery methods had the most beneficial criteria weighting of the 3 processes, while SAGD was the least favourable choice. However, SAGD processes are the most widely used of the 3 processes, while THAI has only been demonstrated on a limited scale. It was concluded that the maturity of a technology should be weighted more heavily when using the PROMETHEE method. 8 refs., 2 tabs.

Flow shop scheduling decisions through Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS

Directory of Open Access Journals (Sweden)

Arun Gupta

2016-07-01

Full Text Available The flow-shop scheduling problem (FSP has been widely studied in the literature and having a very active research area. Over the last few decades, a number of heuristic/meta-heuristic solution techniques have been developed. Some of these techniques offer excellent effectiveness and efficiency at the expense of substantial implementation efforts and being extremely complicated. This paper brings out the application of a Multi-Criteria Decision Making (MCDM method known as techniques for order preference by similarity to an ideal solution (TOPSIS using different weighting schemes in flow-shop environment. The objective function is identification of a job sequence which in turn would have minimum makespan (total job completion time. The application of the proposed method to flow shop scheduling is presented and explained with a numerical example. The results of the proposed TOPSIS based technique of FSP are also compared on the basis of some benchmark problems and found compatible with the results obtained from other standard procedures.

Reduced rank adaptive filtering in impulsive noise environments

KAUST Repository

Soury, Hamza

2014-11-01

An impulsive noise environment is considered in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction, while the minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each method is discussed. © 2014 IEEE.

An approach to decision-making with triangular fuzzy reciprocal preference relations and its application

Science.gov (United States)

Meng, Fanyong

2018-02-01

Triangular fuzzy reciprocal preference relations (TFRPRs) are powerful tools to denoting decision-makers' fuzzy judgments, which permit the decision-makers to apply triangular fuzzy ratio rather than real numbers to express their judgements. Consistency analysis is one of the most crucial issues in preference relations that can guarantee the reasonable ranking order. However, all previous consistency concepts cannot well address this type of preference relations. Based on the operational laws on triangular fuzzy numbers, this paper introduces an additive consistency concept for TFRPRs by using quasi TFRPRs, which can be seen as a natural extension of the crisp case. Using this consistency concept, models to judging the additive consistency of TFRPRs and to estimating missing values in complete TFRPRs are constructed. Then, an algorithm to decision-making with TFRPRs is developed. Finally, two numerical examples are offered to illustrate the application of the proposed procedure, and comparison analysis is performed.

PROP taster status, food preferences and consumption of high-calorie snacks and sweet beverages among 6-year-old ethnically diverse children.

Science.gov (United States)

Wijtzes, Anne I; Jansen, Wilma; Bouthoorn, Selma H; Kiefte-de Jong, Jessica C; Jansen, Pauline W; Franco, Oscar H; Jaddoe, Vincent W V; Hofman, Albert; Raat, Hein

2017-04-01

A healthy diet is important for optimal growth and development in children. Food preferences are a main determinant of children's intake. The aim of this study was to examine the associations of 6-n-propylthiouracil (PROP) taster status (taste sensitivity to PROP) with children's food preferences and consumption of high-calorie snacks and sweet beverages among ethnically diverse children. We analysed data from 5585 6-year-old children enrolled in the Generation R Study, a birth cohort study in Rotterdam, the Netherlands. PROP taster status was evaluated using a suprathreshold screening solution. Food preferences of the children were assessed by a two-stage protocol using photographs of eight food items (candy, chocolate, mayonnaise, whipped cream, soup, potato chips, carrot and bread), yielding both hedonic ratings (1-3) and rank order scores (1-8). Univariate and multivariable linear and logistic regression analyses were performed, using tasters as the reference group. Non-tasters had a slightly higher preference for carrots (β: -0.07; 95% CI: -0.13, -0.02 and β: -0.15; 95% CI: -0.27, -0.02 for hedonic ratings and rank order scores, respectively) and bread (hedonic ratings; β: -0.06; 95% CI: -0.11, -0.01) compared with tasters. No differences were found in children's preference for sweet, fat or salty food items. Furthermore, there were no associations of PROP taster status with the consumption of high-calorie snacks ≥ 2 times/day (aOR: 1.06; 95% CI: 0.91,1.24) or sweet beverages ≥ 3 glasses/day (aOR: 1.06; 95% CI: 0.92,1.23). Other factors relating to the family food environment may be more important for young children's food preferences and consumption of high-calorie snacks and sweet beverages than their innate taste sensitivity. © 2016 John Wiley & Sons Ltd.

Reasons of Tourists’ Preferences of All-Inclusive System

Directory of Open Access Journals (Sweden)

Ali YAYLI

2012-03-01

Full Text Available The study is aimed to identify the reasons of tourists’ preferences of all inclusive system. Scale that has developed by Wong and Kwong (2004 has been used in this study. Population of study has been consisted of tourists that have come to Antalya by purchasing all inclusive system package tours. In the study which carried out by participated 387 tourists, statements of “guaranty of tour”, “price of travel” and “items included in the tour price” that are the most important criteria of tourists while they prefer all inclusive system were ranked among first three. Moreover, according to the results of factor analysis, ten factors were determined and was seen that factors of “innovations”, “price” and “specifications of travel” were ranked among first three.

Image quality preferences among radiographers and radiologists. A conjoint analysis

International Nuclear Information System (INIS)

Ween, Borgny; Kristoffersen, Doris Tove; Hamilton, Glenys A.; Olsen, Dag Rune

2005-01-01

Purpose: The aim of this study was to investigate the image quality preferences among radiographers and radiologists. The radiographers' preferences are mainly related to technical parameters, whereas radiologists assess image quality based on diagnostic value. Methods: A conjoint analysis was undertaken to survey image quality preferences; the study included 37 respondents: 19 radiographers and 18 radiologists. Digital urograms were post-processed into 8 images with different properties of image quality for 3 different patients. The respondents were asked to rank the images according to their personally perceived subjective image quality. Results: Nearly half of the radiographers and radiologists were consistent in their ranking of the image characterised as 'very best image quality'. The analysis showed, moreover, that chosen filtration level and image intensity were responsible for 72% and 28% of the preferences, respectively. The corresponding figures for each of the two professions were 76% and 24% for the radiographers, and 68% and 32% for the radiologists. In addition, there were larger variations in image preferences among the radiologists, as compared to the radiographers. Conclusions: Radiographers revealed a more consistent preference than the radiologists with respect to image quality. There is a potential for image quality improvement by developing sets of image property criteria

Personality traits in old age: measurement and rank-order stability and some mean-level change.

Science.gov (United States)

Mõttus, René; Johnson, Wendy; Deary, Ian J

2012-03-01

Lothian Birth Cohorts, 1936 and 1921 were used to study the longitudinal comparability of Five-Factor Model (McCrae & John, 1992) personality traits from ages 69 to 72 years and from ages 81 to 87 years, and cross-cohort comparability between ages 69 and 81 years. Personality was measured using the 50-item International Personality Item Pool (Goldberg, 1999). Satisfactory measurement invariance was established across time and cohorts. High rank-order stability was observed in both cohorts. Almost no mean-level change was observed in the younger cohort, whereas Extraversion, Agreeableness, Conscientiousness, and Intellect declined significantly in the older cohort. The older cohort scored higher on Agreeableness and Conscientiousness. In these cohorts, individual differences in personality traits continued to be stable even in very old age, mean-level changes accelerated.

Individual recognition of social rank and social memory performance depends on a functional circadian system.

Science.gov (United States)

Müller, L; Weinert, D

2016-11-01

In a natural environment, social abilities of an animal are important for its survival. Particularly, it must recognize its own social rank and the social rank of a conspecific and have a good social memory. While the role of the circadian system for object and spatial recognition and memory is well known, the impact of the social rank and circadian disruptions on social recognition and memory were not investigated so far. In the present study, individual recognition of social rank and social memory performance of Djungarian hamsters revealing different circadian phenotypes were investigated. Wild type (WT) animals show a clear and well-synchronized daily activity rhythm, whereas in arrhythmic (AR) hamsters, the suprachiasmatic nuclei (SCN) do not generate a circadian signal. The aim of the study was to investigate putative consequences of these deteriorations in the circadian system for animalś cognitive abilities. Hamsters were bred and kept under standardized housing conditions with food and water ad libitum and a 14l/10 D lighting regimen. Experimental animals were assigned to different groups (WT and AR) according to their activity pattern obtained by means of infrared motion sensors. Before the experiments, the animals were given to develop a dominant-subordinate relationship in a dyadic encounter. Experiment 1 dealt with individual recognition of social rank. Subordinate and dominant hamsters were tested in an open arena for their behavioral responses towards a familiar (known from the agonistic encounters) or an unfamiliar hamster (from another agonistic encounter) which had the same or an opposite social rank. The investigation time depended on the social rank of the WT subject hamster and its familiarity with the stimulus animal. Both subordinate and dominant WT hamsters preferred an unfamiliar subordinate stimulus animal. In contrast, neither subordinate nor dominant AR hamsters preferred any of the stimulus animals. Thus, disruptions in circadian

Like, Comment, Retweet: Understanding Student Social Media Preferences

OpenAIRE

Dee Winn; Michael Groenendyk; Melissa Rivosecchi

2016-01-01

The majority of academic libraries currently use one or more social media websites in their efforts to communicate and engage with students. Some of the most widely used sites are Facebook, Twitter, YouTube and Instagram. Education students at the University of British Columbia were surveyed and asked to rank whether they preferred receiving Library communications from Facebook, Twitter or WordPress (blogs). The results indicate that students ranked Facebook first, WordPress second and Twitte...

Block models and personalized PageRank.

Science.gov (United States)

Kloumann, Isabel M; Ugander, Johan; Kleinberg, Jon

2017-01-03

Methods for ranking the importance of nodes in a network have a rich history in machine learning and across domains that analyze structured data. Recent work has evaluated these methods through the "seed set expansion problem": given a subset [Formula: see text] of nodes from a community of interest in an underlying graph, can we reliably identify the rest of the community? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate in the space of "landing probabilities" of a random walk rooted at the seed set, ranking nodes according to weighted sums of landing probabilities of different length walks. Both schemes, however, lack an a priori relationship to the seed set objective. In this work, we develop a principled framework for evaluating ranking methods by studying seed set expansion applied to the stochastic block model. We derive the optimal gradient for separating the landing probabilities of two classes in a stochastic block model and find, surprisingly, that under reasonable assumptions the gradient is asymptotically equivalent to personalized PageRank for a specific choice of the PageRank parameter [Formula: see text] that depends on the block model parameters. This connection provides a formal motivation for the success of personalized PageRank in seed set expansion and node ranking generally. We use this connection to propose more advanced techniques incorporating higher moments of landing probabilities; our advanced methods exhibit greatly improved performance, despite being simple linear classification rules, and are even competitive with belief propagation.

IMPACT OF FOOD PREFERENCES ON THE DEVELOPMENT OF PATHOLOGICAL CHANGES IN THE MASTICATORY APPARATUS IN YOUNG PATIENTS

Directory of Open Access Journals (Sweden)

Desislava Konstantinova

2016-07-01

Full Text Available Food can have a mighty biological, therapeutic and preventive effect, yet its breakdown can provide the perfect setting for tooth decay and its implications, diseases of the periodontium and the oral mucosa. Due to the high incidence of periodontal and hard dental tissues pathologies among adolescents they have been ranked as socially significant diseases. A damaged dental-jaw apparatus may lead to forming unhealthy eating habits, more sensitive food preferences and nutritional deficiency. The objective was to explore the prevalence of those diseases and the dental hygiene among final year high school students as well as to seek any correlation with their eating habits and preferences. Materials and Methods: The study involved 121 students who underwent extraoral and intraoral examination in order to establish the state of the masticatory apparatus whereas the state of oral hygiene was measured as per Silness-Löe plaque index. A questionnaire filled out by the students provided data on the individual characteristics of the masticatory process, eating habits and frequency of consumption of certain cariogenic and anticariogenic foods and beverages. Results: The findings revealed unhealthy food preferences in the target group. The unsatisfactory oral hygiene habits and food preferences account for the high percentage of dental caries. Conclusion: Oral health of children and adolescents is problematic worldwide and can be resolved with the benefits of a balanced diet as well as personal and professional oral hygiene, etc. Teaching children the importance of proper oral care before reaching adolescence can build anticariogenic habits in them for a lifetime.

The proof is in the pudding: children prefer lower fat but higher sugar than do mothers.

Science.gov (United States)

Mennella, J A; Finkbeiner, S; Reed, D R

2012-10-01

Although there are established age-related differences in sweet preferences, it remains unknown whether children differ from mothers in their preference for and perception of fat (creaminess). We examined whether individual differences in sucrose and fat preferences and perception are related to age, genotype and lifestyle. Children 5-10 years-old (n=84) and their mothers (n=67) chose the concentration of sucrose and fat most preferred in pudding and sucrose most preferred in water using identical, two-alternative, forced-choice procedures, and ranked pudding samples for intensity of sweetness and creaminess. Subjects were also weighed and measured for height, as well as genotyped for a sweet-receptor gene (TAS1R3). Children preferred higher concentrations of sucrose in water (P=0.03) and in pudding (P=0.05) and lower concentrations of fat in pudding (PChildren and mothers were equally able to rank the intensity of different concentrations of fat (P=0.12) but not sucrose in pudding (P=0.01). Obese and lean children and mothers did not differ in preferences, but obese mothers were less able to correctly rank the concentration of fat in pudding than were lean mothers (P=0.03). Mothers who smoked preferred a higher concentration of sucrose than did those who never smoked (Pchildren (P=0.04). Irrespective of genotype, children prefer higher concentrations of sugar but lower concentrations of fat in puddings than do their mothers. Thus, reduced-fat foods may be better accepted by children than adults.

Effects of Context and Relative Rank on Mate Choice and Affiliation Ratings

Directory of Open Access Journals (Sweden)

P. Lynne Honey

2009-07-01

Full Text Available Female dominance has not often been studied as a factor in mate choice and other social interactions. When it has been examined, there have been a number of conflicting findings. The present study was designed to clarify interpretations of a study conducted by Brown and Lewis (2004 that found that men prefer subordinate women in a workplace context. We presented participants with information about the relative rank of physically attractive targets, in two very different contexts (work-related and recreational. We found that the context in which rank cues are presented has an impact on affiliation ratings, but that cues of rank do not affect mate choice ratings. Future studies of effects of dominance must take into account the context in which they are presented, and recognize that rank may not be a sufficient indicator of dominance for the purpose of mate choice by both men and women.

A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

Directory of Open Access Journals (Sweden)

Yubao Sun

2015-01-01

Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.

Decomposition of the Google PageRank and Optimal Linking Strategy

NARCIS (Netherlands)

Avrachenkov, Konstatin; Litvak, Nelli

We provide the analysis of the Google PageRank from the perspective of the Markov Chain Theory. First we study the Google PageRank for a Web that can be decomposed into several connected components which do not have any links to each other. We show that in order to determine the Google PageRank for

Ecological influences on individual differences in color preference.

Science.gov (United States)

Schloss, Karen B; Hawthorne-Madell, Daniel; Palmer, Stephen E

2015-11-01

How can the large, systematic differences that exist between individuals' color preferences be explained? The ecological valence theory (Palmer & Schloss, Proceedings of the National Academy of Sciences 107:8877-8882, 2010) posits that an individual's preference for each particular color is determined largely by his or her preferences for all correspondingly colored objects. Therefore, individuals should differ in their color preferences to the extent that they have different preferences for the same color-associated objects or that they experience different objects. Supporting this prediction, we found that individuals' color preferences were predicted better by their own preferences for correspondingly colored objects than by other peoples' preferences for the same objects. Moreover, the fit between color preferences and affect toward the colored objects was reliably improved when people's own idiosyncratic color-object associations were included in addition to a standard set of color-object associations. These and related results provide evidence that individual differences in color preferences are reliably influenced by people's personal experiences with colored objects in their environment.

Cross-cultural differences in processing of architectural ranking: evidence from an event-related potential study.

Science.gov (United States)

Mecklinger, Axel; Kriukova, Olga; Mühlmann, Heiner; Grunwald, Thomas

2014-01-01

Visual object identification is modulated by perceptual experience. In a cross-cultural ERP study we investigated whether cultural expertise determines how buildings that vary in their ranking between high and low according to the Western architectural decorum are perceived. Two groups of German and Chinese participants performed an object classification task in which high- and low-ranking Western buildings had to be discriminated from everyday life objects. ERP results indicate that an early stage of visual object identification (i.e., object model selection) is facilitated for high-ranking buildings for the German participants, only. At a later stage of object identification, in which object knowledge is complemented by information from semantic and episodic long-term memory, no ERP evidence for cultural differences was obtained. These results suggest that the identification of architectural ranking is modulated by culturally specific expertise with Western-style architecture already at an early processing stage.

A risk-based multi-objective model for optimal placement of sensors in water distribution system

Science.gov (United States)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value

Help Preferences Among Employees Who Wish to Change Health Behaviors.

Science.gov (United States)

Persson, Roger; Cleal, Bryan; Jakobsen, Mette Øllgaard; Villadsen, Ebbe; Andersen, Lars L

2014-08-01

To examine the help preferences of employees in the Danish police who had acknowledged that they wished to change health behaviors. In addition, we explored whether preferences varied with age, gender, chronic health concerns, positive expectations of good health, and past experiences of in-house health promotion services (i.e., wellness service). Respondents to an electronic questionnaire who acknowledged wishing to change health behaviors in relation to smoking (n = 845), alcohol (n = 684), eating (n = 4,431), and physical activity (n = 5,179) were asked to choose up to three help alternatives on a predefined list. In descending order, smokers preferred help from nicotine gum, no help, and help and support from family and friends. Alcohol consumers preferred no help or help and support from family and friends or "other" forms. Employees who wanted to change eating habits preferred a free fruit bowl, free nutritional guidance, and healthy food at work. Employees who wanted to change physical activity patterns preferred exercise at work, offers of free exercise, and exercise in a social/collegial context. Wishing to change health behaviors is not always accompanied by perceiving a need for assistance. The no-help option was selected fairly frequently and mostly in relation to alcohol and smoking. A fruit bowl was the most preferred option for help, followed by exercise at work and free exercise. Help from traditional health services was ranked low, possibly reflecting that they are primarily viewed as a solution for stopping disease rather than promoting health. © 2013 Society for Public Health Education.

Preference learning with evolutionary Multivariate Adaptive Regression Spline model

DEFF Research Database (Denmark)

Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

2015-01-01

This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

An Empirical Study on the Preference of Supermarkets with Analytic Hierarchy Process Model

Science.gov (United States)

Weng Siew, Lam; Singh, Ranjeet; Singh, Bishan; Weng Hoe, Lam; Kah Fai, Liew

2018-04-01

Large-scale retailers are very important to the consumers in this fast-paced world. Selection of desirable market to purchase products and services becomes major concern among consumers in their daily life due to vast choices available. Therefore, the objective of this paper is to determine the most preferred supermarket among AEON, Jaya Grocer, Tesco, Giant and Econsave by the undergraduate students in Malaysia with Analytic Hierarchy Process (AHP) model. Besides that, this study also aims to determine the priority of decision criteria in the selection of supermarkets among the undergraduatestudents with AHP model. The decision criteria employed in this study are product quality, competitive price, cleanliness, product variety, location, good price labelling, fast checkout and employee courtesy. The results of this study show that AEON is the most preferred supermarket followed by Jaya Grocer, Tesco, Econsave and Giant among the students based on AHP model. Product quality, cleanliness and competitive price are ranked as the top three influential factors in this study. This study is significant because it helps to determine the most preferred supermarket as well as the most influential decision criteria in the preference of supermarkets among the undergraduate students with AHP model.

Scalable Faceted Ranking in Tagging Systems

Science.gov (United States)

Orlicki, José I.; Alvarez-Hamelin, J. Ignacio; Fierens, Pablo I.

Nowadays, web collaborative tagging systems which allow users to upload, comment on and recommend contents, are growing. Such systems can be represented as graphs where nodes correspond to users and tagged-links to recommendations. In this paper we analyze the problem of computing a ranking of users with respect to a facet described as a set of tags. A straightforward solution is to compute a PageRank-like algorithm on a facet-related graph, but it is not feasible for online computation. We propose an alternative: (i) a ranking for each tag is computed offline on the basis of tag-related subgraphs; (ii) a faceted order is generated online by merging rankings corresponding to all the tags in the facet. Based on the graph analysis of YouTube and Flickr, we show that step (i) is scalable. We also present efficient algorithms for step (ii), which are evaluated by comparing their results with two gold standards.

Multi-criteria Ranking Under Pareto Inclusive Criterion of Preference: An Application in Ranking Some Fungi Species with Respect to Their Toxicity

Directory of Open Access Journals (Sweden)

Gniadek Agnieszka

2014-12-01

Full Text Available This study aims at demonstrating the usefulness of the Pareto in- clusive criterion methodology for comparative analyses of fungi toxicity. The toxicity of fungi is usually measured using a scale of several ranks. In practice, the ranks of toxicity are routinely grouped into only four conventional classes of toxicity: from a class of no toxicity, low toxicity, and moderate toxicity, to a class of high toxicity. The illustrative material included the N = 61 fungi samples obtained from three species: A. ochraceus, A. niger and A. flavus. In accordance with the Pareto approach, four partial criterions of the worst toxi- city were defined, a single criterion used for each conventional class of toxicity. Finally, the odds ratios (OR were calculated separately for each partial cri- terion, and the significance of the hypotheses OR = 1 was estimated. It was stated that A. ochraceus fungi are distinctly more toxic than the two remaining ones with respect to the all considered four partial criterions, with significance equal to p = 0.04, p = 0.04, p = 0.007 and p = 0.005, respectively. Thus, the suggested method illustrated its utility in the case under study.

Influences on Malaysian Pharmacy Students' Career Preferences

Science.gov (United States)

Kwai Chong, David Weng; Ahmadi, Keivan; Se, Wong Pei; Hassali, Mohammed Azmi; Hata, Ernieda Mohammed; Hadi, Muhammed Abdul; Sridhar, Sathvik Belagodu; Ahmed, Syed Imran; Yean, Low Bee; Efendie, Benny

2010-01-01

Objectives To identify and evaluate factors affecting the career preferences of fourth-year bachelor of pharmacy (BPharm) students in Malaysia in the presence of a 4-year period of mandatory government service. Methods A validated self-administered questionnaire was used in this cross-sectional study to collect data from final-year BPharm students enrolled at 3 government-funded universities and 1 private university in Malaysia. Both descriptive and inferential statistics were used for data analysis. Results Three hundred fourteen students responded (213 from public universities and 101 from the private university). Approximately 32% of public university students and 37% of private university students ranked their own interest in pharmacy as the reason for undertaking pharmacy degree studies; 40.4% of public and 19.8% of private university respondents stated that they would enter a nonpharmacy-related career upon graduation if given the choice. Public university students ranked hospital pharmacy as their choice of first career setting (4.39, p = 0.001), while private students ranked community pharmacy first (4.1, p = 0.002). On a scale of 1 to 5, salary received the highest mean score (3.9 and 4.0, p = 0.854) as the extrinsic factor most influencing their career choice. Conclusions Final-year students at Malaysian public universities were most interested in hospital pharmacy practice as their first career step upon graduation, while private university students were most interested in community pharmacy. The top 3 extrinsic factors rated as significant in selecting a career destination were salary, benefits, and geographical location. PMID:21301600

Consumer Preferences for Coconut Shell Charcoal in Suburban Indonesia

Directory of Open Access Journals (Sweden)

Pitri Yandri

2013-08-01

Full Text Available Suburbs in Indonesia are not only characterized by the presence of residential areas, but also trading activities. These activities exist in order to support the needs of residents for goods and/or services. The complicated process that involves pull and push factors causes the suburbs to be well-known as economically potential areas, especially for micro, small, medium and large enterprises. One example of the trading subsectors is restaurants, both micro enterprises with traditional management and franchises patterns with professional management. Most of these restaurants provide barbequed menus which consume shell coconut charcoal. Then the question arises, is the quality of those commodity is the only reason for the restaurants in using it? This paper presents the elaboration of the research on consumer preferences in a suburban area of the consumption of coconut shell charcoal. By using the Fishbein Model, it is concluded that the aspect of belief and price attribute are in the first rank, which shows that those commodity is an expensive fuel, while the second rank is quality. The rest are models and after-sales service, respectively. From the aspect of evaluation, the respondents believe that quality is in the first rank that should be improved in the future. The second is price and the rest are after-sales service, packaging and models, respectively.

Consumer Preferences for Coconut Shell Charcoal in Suburban Indonesia

Directory of Open Access Journals (Sweden)

Pitri Yandri

2013-08-01

Full Text Available Suburbs in Indonesia are not only characterized by the presence of residential areas, but also trading activities. These activities exist in order to support the needs of residents for goods and/or services. The complicated process that involves pull and push factors causes the su-burbs to be well-known as economically potential areas, especially for micro, small, medium and large enterprises. One example of the trading subsectors is restaurants, both micro enterprises with traditional management and franchises patterns with professional management. Most of these restaurants provide barbequed menus which consume shell coconut charcoal. Then the question arises, is the quality of those commodity is the only reason for the restaurants in using it? This paper presents the elaboration of the research on consumer preferences in a suburban area of the consumption of coconut shell charcoal. By using the Fishbein Model, it is concluded that the aspect of belief and price attribute are in the first rank, which shows that those commodity is an expensive fuel, while the second rank is quality. The rest are models and after-sales service, respectively. From the aspect of evaluation, the respondents believe that quality is in the first rank that should be improved in the future. The second is price and the rest are after-sales service, packaging and models, respectively.

Periodic self-rostering in shift work: correspondence between objective work hours, work hour preferences (personal fit), and work schedule satisfaction

NARCIS (Netherlands)

Ingre, M.; Äkerstedt, T.; Ekstedt, M.; Kecklund, L.G.

2012-01-01

Objectives The main objective of the present study was to investigate relative personal fit as the association between rated needs and preferences for work hours, on the one hand, and actual work hours, on the other hand, in three groups (hospital, call-center, and police) working with periodic

PageRank and rank-reversal dependence on the damping factor

Science.gov (United States)

Son, S.-W.; Christensen, C.; Grassberger, P.; Paczuski, M.

2012-12-01

PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d0=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d0.

PageRank and rank-reversal dependence on the damping factor.

Science.gov (United States)

Son, S-W; Christensen, C; Grassberger, P; Paczuski, M

2012-12-01

PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d_{0}=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d_{0}.

Kriging accelerated by orders of magnitude: combining low-rank with FFT techniques

KAUST Repository

Litvinenko, Alexander; Nowak, Wolfgang

2014-01-01

Kriging algorithms based on FFT, the separability of certain covariance functions and low-rank representations of covariance functions have been investigated. The current study combines these ideas, and so combines the individual speedup factors of all ideas. The reduced computational complexity is O(dLlogL), where L := max ini, i = 1

Kriging accelerated by orders of magnitude: combining low-rank with FFT techniques

KAUST Repository

Litvinenko, Alexander

2014-05-04

Kriging algorithms based on FFT, the separability of certain covariance functions and low-rank representations of covariance functions have been investigated. The current study combines these ideas, and so combines the individual speedup factors of all ideas. The reduced computational complexity is O(dLlogL), where L := max ini, i = 1

The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

Science.gov (United States)

Jaini, Nor I.; Utyuzhnikov, Sergei V.

2017-08-01

Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

Model assessment using a multi-metric ranking technique

Science.gov (United States)

Fitzpatrick, P. J.; Lau, Y.; Alaka, G.; Marks, F.

2017-12-01

Validation comparisons of multiple models presents challenges when skill levels are similar, especially in regimes dominated by the climatological mean. Assessing skill separation will require advanced validation metrics and identifying adeptness in extreme events, but maintain simplicity for management decisions. Flexibility for operations is also an asset. This work postulates a weighted tally and consolidation technique which ranks results by multiple types of metrics. Variables include absolute error, bias, acceptable absolute error percentages, outlier metrics, model efficiency, Pearson correlation, Kendall's Tau, reliability Index, multiplicative gross error, and root mean squared differences. Other metrics, such as root mean square difference and rank correlation were also explored, but removed when the information was discovered to be generally duplicative to other metrics. While equal weights are applied, weights could be altered depending for preferred metrics. Two examples are shown comparing ocean models' currents and tropical cyclone products, including experimental products. The importance of using magnitude and direction for tropical cyclone track forecasts instead of distance, along-track, and cross-track are discussed. Tropical cyclone intensity and structure prediction are also assessed. Vector correlations are not included in the ranking process, but found useful in an independent context, and will be briefly reported.

A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model

Directory of Open Access Journals (Sweden)

Madjid Tavana

2007-01-01

Full Text Available Ordinal consensus ranking problems have received much attention in the management science literature. A problem arises in situations where a group of k decision makers (DMs is asked to rank order n alternatives. The question is how to combine the DM rankings into one consensus ranking. Several different approaches have been suggested to aggregate DM responses into a compromise or consensus ranking; however, the similarity of consensus rankings generated by the different algorithms is largely unknown. In this paper, we propose a new hybrid distance-based ideal-seeking consensus ranking model (DCM. The proposed hybrid model combines parts of the two commonly used consensus ranking techniques of Beck and Lin (1983 and Cook and Kress (1985 into an intuitive and computationally simple model. We illustrate our method and then run a Monte Carlo simulation across a range of k and n to compare the similarity of the consensus rankings generated by our method with the best-known method of Borda and Kendall (Kendall 1962 and the two methods proposed by Beck and Lin (1983 and Cook and Kress (1985. DCM and Beck and Lin's method yielded the most similar consensus rankings, whereas the Cook-Kress method and the Borda-Kendall method yielded the least similar consensus rankings.

Robustness of Multiple Objective Decision Analysis Preference Functions

National Research Council Canada - National Science Library

Klimack, William

2002-01-01

.... The impact of these differences was examined to improve implementation efficiency. The robustness of the decision model was examined with respect to the preference functions to reduce the time burden imposed on the decision maker...

A new measure of output ranking performance in automatic document retrieval systems

International Nuclear Information System (INIS)

Ebinuma, Yukio

1987-01-01

A new measure of output ranking performance is proposed on the basis of recall-precision pairs corresponding to ranks of relevant documents when documents are arranged in decreasing order of their scores given by a ranking function. This measure is constructed to take a single value in starting from the area under a recall-precision graph for a ranked output and to distinguish meaningful ranking with a positive value between 0 and 1 from meaningless ranking with a negative value. It is clarified too that the measure must be useful in practice to evaluate the ranking performance made by various ranking function models and to choose the best ranking models among them. (author)

Power-law and exponential rank distributions: A panoramic Gibbsian perspective

International Nuclear Information System (INIS)

Eliazar, Iddo

2015-01-01

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation between ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars

Power-law and exponential rank distributions: A panoramic Gibbsian perspective

Energy Technology Data Exchange (ETDEWEB)

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

2015-04-15

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation between ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars.

Ranking structures and rank-rank correlations of countries: The FIFA and UEFA cases

Science.gov (United States)

Ausloos, Marcel; Cloots, Rudi; Gadomski, Adam; Vitanov, Nikolay K.

2014-04-01

Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European countries ranked by UEFA and FIFA from different soccer competitions. The first question to be answered is whether an empirical and simple law is obtained for such (self-) organizations of complex sociological systems with such different measuring schemes. It is found that the power law form is not the best description contrary to many modern expectations. The stretched exponential is much more adequate. Moreover, it is found that the measuring rules lead to some inner structures in both cases.

LogDet Rank Minimization with Application to Subspace Clustering

Directory of Open Access Journals (Sweden)

Zhao Kang

2015-01-01

Full Text Available Low-rank matrix is desired in many machine learning and computer vision problems. Most of the recent studies use the nuclear norm as a convex surrogate of the rank operator. However, all singular values are simply added together by the nuclear norm, and thus the rank may not be well approximated in practical problems. In this paper, we propose using a log-determinant (LogDet function as a smooth and closer, though nonconvex, approximation to rank for obtaining a low-rank representation in subspace clustering. Augmented Lagrange multipliers strategy is applied to iteratively optimize the LogDet-based nonconvex objective function on potentially large-scale data. By making use of the angular information of principal directions of the resultant low-rank representation, an affinity graph matrix is constructed for spectral clustering. Experimental results on motion segmentation and face clustering data demonstrate that the proposed method often outperforms state-of-the-art subspace clustering algorithms.

Order effect in a study on US voters’ preferences: quantum framework representation of the observables

International Nuclear Information System (INIS)

Khrennikova, Polina

2014-01-01

The US political system in the recent years has been mainly formed by a Divided Government, which is regarded as a consequence of ‘non-separability’ of voters’ preferences. The non- separability phenomenon emerges as a result of strong correlations that the voters establish between their preferences for the Congress and the White House contests. We investigate with help of the empirical data from the Smith et al (1999 J. Polit. Sci. 43 737–764) study what implications the upcoming information (encoded in the observables- questions) has on the non- separability emergence. We show that the informational context of the questions alters the preference frequencies that cannot be captured in a classical probabilistic framework. We attribute the changes to the incompatibility of observables C and P, which correspond to questions being asked. We embed our data in a quantum framework and model the voters’ mental state evolution as it is impacted by the operators, to show the non-commutativity of the transition probabilities as a result of the question order effect. (paper)

Diversity rankings among bacterial lineages in soil.

Science.gov (United States)

Youssef, Noha H; Elshahed, Mostafa S

2009-03-01

We used rarefaction curve analysis and diversity ordering-based approaches to rank the 11 most frequently encountered bacterial lineages in soil according to diversity in 5 previously reported 16S rRNA gene clone libraries derived from agricultural, undisturbed tall grass prairie and forest soils (n=26,140, 28 328, 31 818, 13 001 and 53 533). The Planctomycetes, Firmicutes and the delta-Proteobacteria were consistently ranked among the most diverse lineages in all data sets, whereas the Verrucomicrobia, Gemmatimonadetes and beta-Proteobacteria were consistently ranked among the least diverse. On the other hand, the rankings of alpha-Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes and Chloroflexi varied widely in different soil clone libraries. In general, lineages exhibiting largest differences in diversity rankings also exhibited the largest difference in relative abundance in the data sets examined. Within these lineages, a positive correlation between relative abundance and diversity was observed within the Acidobacteria, Actinobacteria and Chloroflexi, and a negative diversity-abundance correlation was observed within the Bacteroidetes. The ecological and evolutionary implications of these results are discussed.

Rank-dependent grooming patterns and cortisol alleviation in Barbary macaques.

Science.gov (United States)

Sonnweber, Ruth S; Ravignani, Andrea; Stobbe, Nina; Schiestl, Gisela; Wallner, Bernard; Fitch, W Tecumseh

2015-06-01

Flexibly adapting social behavior to social and environmental challenges helps to alleviate glucocorticoid (GC) levels, which may have positive fitness implications for an individual. For primates, the predominant social behavior is grooming. Giving grooming to others is particularly efficient in terms of GC mitigation. However, grooming is confined by certain limitations such as time constraints or restricted access to other group members. For instance, dominance hierarchies may impact grooming partner availability in primate societies. Consequently specific grooming patterns emerge. In despotic species focusing grooming activity on preferred social partners significantly ameliorates GC levels in females of all ranks. In this study we investigated grooming patterns and GC management in Barbary macaques, a comparably relaxed species. We monitored changes in grooming behavior and cortisol (C) for females of different ranks. Our results show that the C-amelioration associated with different grooming patterns had a gradual connection with dominance hierarchy: while higher-ranking individuals showed lowest urinary C measures when they focused their grooming on selected partners within their social network, lower-ranking individuals expressed lowest C levels when dispersing their grooming activity evenly across their social partners. We argue that the relatively relaxed social style of Barbary macaque societies allows individuals to flexibly adapt grooming patterns, which is associated with rank-specific GC management. © 2015 Wiley Periodicals, Inc.

GeoSearcher: Location-Based Ranking of Search Engine Results.

Science.gov (United States)

Watters, Carolyn; Amoudi, Ghada

2003-01-01

Discussion of Web queries with geospatial dimensions focuses on an algorithm that assigns location coordinates dynamically to Web sites based on the URL. Describes a prototype search system that uses the algorithm to re-rank search engine results for queries with a geospatial dimension, thus providing an alternative ranking order for search engine…

Ranking benchmarks of top 100 players in men's professional tennis.

Science.gov (United States)

Reid, Machar; Morris, Craig

2013-01-01

In men's professional tennis, players aspire to hold the top ranking position. On the way to the top spot, reaching the top 100 can be seen as a significant career milestone. National Federations undertake extensive efforts to assist their players to reach the top 100. However, objective data considering reasonable ranking yardsticks for top 100 success in men's professional tennis are lacking. Therefore, it is difficult for National Federations and those involved in player development to give empirical programming advice to young players. By taking a closer look at the ranking history of professional male tennis players, this article tries to provide those involved in player development a more objective basis for decision-making. The 100 names, countries, birthdates and ranking histories of the top 100 players listed in the Association of Tennis Professionals (ATP) at 31 December 2009 were recorded from websites in the public domain. Descriptive statistics were reported for the ranking milestones of interest. Results confirmed the merits of the International Tennis Federation's junior tour with 91% of the top 100 professionals earning a junior ranking, the mean peak of which was 94.1, s=148.9. On average, top 100 professionals achieved their best junior rankings and earned their first ATP point at similar ages, suggesting that players compete on both the junior and professional tours during their transition. Once professionally ranked, players took an average 4.5, s=2.1 years to reach the ATP top 100 at the mean age of 21.5, s=2.6 years, which contrasts with the mean current age of the top 100 of 26.8, s=3.2. The best professional rankings of players born in 1982 or earlier were positively related to the ages at which players earned their first ATP point and then entered the top 100, suggesting that the ages associated with these ranking milestones may have some forecasting potential. Future work should focus on the change in top 100 demographics over time as well

Treatment plan ranking using physical and biological indices

International Nuclear Information System (INIS)

Ebert, M. A.; University of Western Asutralia, WA

2001-01-01

Full text: The ranking of dose distributions is of importance in several areas such as i) comparing rival treatment plans, ii) comparing iterations in an optimisation routine, and iii) dose-assessment of clinical trial data. This study aimed to investigate the influence of choice of objective function in ranking tumour dose distributions. A series of physical (mean, maximum, minimum, standard deviation of dose) dose-volume histogram (DVH) reduction indices and biologically-based (tumour-control probability - TCP; equivalent uniform dose -EUD) indices were used to rank a series of hypothetical DVHs, as well as DVHs obtained from a series of 18 prostate patients. The distribution in ranking and change in distribution with change in indice parameters were investigated. It is found that not only is the ranking of DVHs dependent on the actual model used to perform the DVH reduction, it is also found to depend on the inherent characteristics of each model (i.e., selected parameters). The adjacent figure shows an example where the 18 prostate patients are ranked (grey-scale from black to white) by EUD when an α value of 0.8 Gy -1 is used in the model. The change of ranking as α varies is evident. Conclusion: This study has shown that the characteristics of the model selected in plan optimisation or DVH ranking will have an impact on the ranking obtained. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

Human preference for individual colors

Science.gov (United States)

Palmer, Stephen E.; Schloss, Karen B.

2010-02-01

Color preference is an important aspect of human behavior, but little is known about why people like some colors more than others. Recent results from the Berkeley Color Project (BCP) provide detailed measurements of preferences among 32 chromatic colors as well as other relevant aspects of color perception. We describe the fit of several color preference models, including ones based on cone outputs, color-emotion associations, and Palmer and Schloss's ecological valence theory. The ecological valence theory postulates that color serves an adaptive "steering' function, analogous to taste preferences, biasing organisms to approach advantageous objects and avoid disadvantageous ones. It predicts that people will tend to like colors to the extent that they like the objects that are characteristically that color, averaged over all such objects. The ecological valence theory predicts 80% of the variance in average color preference ratings from the Weighted Affective Valence Estimates (WAVEs) of correspondingly colored objects, much more variance than any of the other models. We also describe how hue preferences for single colors differ as a function of gender, expertise, culture, social institutions, and perceptual experience.

Population based ranking of frameless CT-MRI registration methods

Energy Technology Data Exchange (ETDEWEB)

Opposits, Gabor; Kis, Sandor A.; Tron, Lajos; Emri, Miklos [Debrecen Univ. (Hungary). Dept. of Nuclear Medicine; Berenyi, Ervin [Debrecen Univ. (Hungary). Dept. of Biomedical Laboratory and Imaging Science; Takacs, Endre [Rotating Gamma Ltd., Debrecen (Hungary); Dobai, Jozsef G.; Bognar, Laszlo [Debrecen Univ., Medical Center (Hungary). Dept. of Neurosurgery; Szuecs, Bernadett [ScanoMed Ltd., Debrecen (Hungary)

2015-07-01

Clinical practice often requires simultaneous information obtained by two different imaging modalities. Registration algorithms are commonly used for this purpose. Automated procedures are very helpful in cases when the same kind of registration has to be performed on images of a high number of subjects. Radiotherapists would prefer to use the best automated method to assist therapy planning, however there are not accepted procedures for ranking the different registration algorithms. We were interested in developing a method to measure the population level performance of CT-MRI registration algorithms by a parameter of values in the [0,1] interval. Pairs of CT and MRI images were collected from 1051 subjects. Results of an automated registration were corrected manually until a radiologist and a neurosurgeon expert both accepted the result as good. This way 1051 registered MRI images were produced by the same pair of experts to be used as gold standards for the evaluation of the performance of other registration algorithms. Pearson correlation coefficient, mutual information, normalized mutual information, Kullback-Leibler divergence, L{sub 1} norm and square L{sub 2} norm (dis)similarity measures were tested for sensitivity to indicate the extent of (dis)similarity of a pair of individual mismatched images. The square Hellinger distance proved suitable to grade the performance of registration algorithms at population level providing the developers with a valuable tool to rank algorithms. The developed procedure provides an objective method to find the registration algorithm performing the best on the population level out of newly constructed or available preselected ones.

Reliability-based decision making for selection of ready-mix concrete supply using stochastic superiority and inferiority ranking method

International Nuclear Information System (INIS)

Chou, Jui-Sheng; Ongkowijoyo, Citra Satria

2015-01-01

Corporate competitiveness is heavily influenced by the information acquired, processed, utilized and transferred by professional staff involved in the supply chain. This paper develops a decision aid for selecting on-site ready-mix concrete (RMC) unloading type in decision making situations involving multiple stakeholders and evaluation criteria. The uncertainty of criteria weights set by expert judgment can be transformed in random ways based on the probabilistic virtual-scale method within a prioritization matrix. The ranking is performed by grey relational grade systems considering stochastic criteria weight based on individual preference. Application of the decision aiding model in actual RMC case confirms that the method provides a robust and effective tool for facilitating decision making under uncertainty. - Highlights: • This study models decision aiding method to assess ready-mix concrete unloading type. • Applying Monte Carlo simulation to virtual-scale method achieves a reliable process. • Individual preference ranking method enhances the quality of global decision making. • Robust stochastic superiority and inferiority ranking obtains reasonable results

On Rank Driven Dynamical Systems

Science.gov (United States)

Veerman, J. J. P.; Prieto, F. J.

2014-08-01

We investigate a class of models related to the Bak-Sneppen (BS) model, initially proposed to study evolution. The BS model is extremely simple and yet captures some forms of "complex behavior" such as self-organized criticality that is often observed in physical and biological systems. In this model, random fitnesses in are associated to agents located at the vertices of a graph . Their fitnesses are ranked from worst (0) to best (1). At every time-step the agent with the worst fitness and some others with a priori given rank probabilities are replaced by new agents with random fitnesses. We consider two cases: The exogenous case where the new fitnesses are taken from an a priori fixed distribution, and the endogenous case where the new fitnesses are taken from the current distribution as it evolves. We approximate the dynamics by making a simplifying independence assumption. We use Order Statistics and Dynamical Systems to define a rank-driven dynamical system that approximates the evolution of the distribution of the fitnesses in these rank-driven models, as well as in the BS model. For this simplified model we can find the limiting marginal distribution as a function of the initial conditions. Agreement with experimental results of the BS model is excellent.

Output ordering and prioritisation system (OOPS): ranking biosynthetic gene clusters to enhance bioactive metabolite discovery.

Science.gov (United States)

Peña, Alejandro; Del Carratore, Francesco; Cummings, Matthew; Takano, Eriko; Breitling, Rainer

2017-12-18

The rapid increase of publicly available microbial genome sequences has highlighted the presence of hundreds of thousands of biosynthetic gene clusters (BGCs) encoding valuable secondary metabolites. The experimental characterization of new BGCs is extremely laborious and struggles to keep pace with the in silico identification of potential BGCs. Therefore, the prioritisation of promising candidates among computationally predicted BGCs represents a pressing need. Here, we propose an output ordering and prioritisation system (OOPS) which helps sorting identified BGCs by a wide variety of custom-weighted biological and biochemical criteria in a flexible and user-friendly interface. OOPS facilitates a judicious prioritisation of BGCs using G+C content, coding sequence length, gene number, cluster self-similarity and codon bias parameters, as well as enabling the user to rank BGCs based upon BGC type, novelty, and taxonomic distribution. Effective prioritisation of BGCs will help to reduce experimental attrition rates and improve the breadth of bioactive metabolites characterized.

[Lack of interest in general practice during the National Ranking Examination in 2005].

Science.gov (United States)

Lanson, Yves

2006-03-01

The second national ranking test took place in 2005 in the same conditions as the year before. Analysis of the results permits us to assess whether the objectives of this reform have been met so far. Data crossing of the results provided by the national testing center allowed us to rank: 1) the appeal of specializations for each geographic subdivision, 2) the candidates by medical school, and 3) the appeal of each subdivision by candidate rank. 66% of the students were classified high enough to be able to choose any specialization. Trends observed from the first examination, in 2004, were confirmed, with the clear desirability of medical specializations and a certain lack of interest in occupational medicine and public health. All the surgery posts were filled, even though the number of posts had increased enormously since the first examination. After adjustment for the number of posts available, the specializations in decreasing order of popularity were: medical, surgical, pediatrics, anesthesiology, gynecology-obstetrics, general medicine, psychiatry, and biology. Approximately 1000 posts in general medicine were not filled. The medical schools whose students ranked highest were Paris Pitié, Paris V, Paris West, Lyon North, Grenoble, and Aix-Marseille. Some medical schools did less well than previously: Marseille very slightly and Angers substantially. Strasbourg, Nancy Amiens and Bobigny were at the bottom of the list. The cities most desired for internships were Paris, Toulouse, Lyon, and Aix-Marseille, while Brest, Nancy, Limoges and the West Indies were ranked lowest, although each was chosen by highly ranked candidate. Two thirds of the students were ranked high enough to allow them a free choice of specializations. All the specializations except public health and occupational medicine had very highly ranked students. Medical specializations are the most desired, but surgery remains highly demanded, despite a substantial increase in the number of posts. All

MARKETING OBJECTIVES AMONG RURAL FOOD RETAILERS

OpenAIRE

Stegelin, Forrest E.

1996-01-01

Food retailers representing four retailer types (family operated grocery stores, produce markets, meat/egg/dairy markets, and convenience stores) in rural Georgia communities were surveyed as to their marketing objectives. Qualitative marketing objectives were ranked by the marketers as to marketing intentions, and by customers as to marketing expectations. More definitive and quantitative marketing objectives were also ranked by the food retailers as to the priority of implementation in thei...

Inverted rank distributions: Macroscopic statistics, universality classes, and critical exponents

Science.gov (United States)

Eliazar, Iddo; Cohen, Morrel H.

2014-01-01

An inverted rank distribution is an infinite sequence of positive sizes ordered in a monotone increasing fashion. Interlacing together Lorenzian and oligarchic asymptotic analyses, we establish a macroscopic classification of inverted rank distributions into five “socioeconomic” universality classes: communism, socialism, criticality, feudalism, and absolute monarchy. We further establish that: (i) communism and socialism are analogous to a “disordered phase”, feudalism and absolute monarchy are analogous to an “ordered phase”, and criticality is the “phase transition” between order and disorder; (ii) the universality classes are characterized by two critical exponents, one governing the ordered phase, and the other governing the disordered phase; (iii) communism, criticality, and absolute monarchy are characterized by sharp exponent values, and are inherently deterministic; (iv) socialism is characterized by a continuous exponent range, is inherently stochastic, and is universally governed by continuous power-law statistics; (v) feudalism is characterized by a continuous exponent range, is inherently stochastic, and is universally governed by discrete exponential statistics. The results presented in this paper yield a universal macroscopic socioeconophysical perspective of inverted rank distributions.

A welfare ranking of multilateral reductions in real and tariff trade barriers when firms are heterogenous

DEFF Research Database (Denmark)

Schröder, Philipp; Sørensen, Allan

2014-01-01

heterogeneous-firms-trade model with Pareto distributed productivities. We derive analytical welfare rankings of all four liberalization channels for an equal effect on two openness measures, for any trade cost level and while all four barriers are simultaneously present, i.e. for any initial equilibrium. We...... to the most preferred mode of liberalization. Among the other three barriers we etablished a universal welfare ranking for any strictly positive level of revenue redistribution and for either measure of openness....

Ranking nodes in growing networks: When PageRank fails.

Science.gov (United States)

Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

2015-11-10

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

Analysis model for forecasting extreme temperature using refined rank set pair

Directory of Open Access Journals (Sweden)

Qiao Ling-Xia

2013-01-01

Full Text Available In order to improve the precision of forecasting extreme temperature time series, a refined rank set pair analysis model with a refined rank transformation function is proposed to improve precision of its prediction. The measured values of the annual highest temperature of two China’s cities, Taiyuan and Shijiazhuang, in July are taken to examine the performance of a refined rank set pair model.

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

Comparing group deliberation to other forms of preference aggregation in valuing ecosystem services

Directory of Open Access Journals (Sweden)

Mackenzie B. Murphy

2017-12-01

Full Text Available Deliberative methods for valuing ecosystem services are hypothesized to yield group preferences that differ systematically from those that would be obtained through calculative aggregation of the preferences of participating individuals. We tested this hypothesis by comparing the group consensus results of structured deliberations against a variety of aggregation methods applied to individual participant preferences that were elicited both before and after the deliberations. Participants were also asked about their perceptions of the deliberative process, which we used to assess their ability to detect preference changes and identify the causes of any changes. For five of the seven groups tested, the group consensus results could not have been predicted from individual predeliberation preferences using any of the aggregation rules. However, individual postdeliberation preferences could be used to reconstruct the group preferences using consensual and rank-based aggregation rules. These results imply that the preferences of participants changed over the course of the deliberation and that the group preferences reflected a broad consensus on overall rankings rather than simply the pairwise preferences of the majority. Changes in individual preferences seem to have gone largely unnoticed by participants, as most stated that they did not believe their preferences had substantially changed. Most participants were satisfied with the outcome of the deliberation, and their degree of satisfaction was correlated with the feeling that their opinion was heard and that they had an influence on the outcome. Based on our results, group deliberation shows promise as a means of generating ecosystem service valuations that reflect a consensus opinion rather than simply a collection of personal preferences.

Optimization of the test intervals of a nuclear safety system by genetic algorithms, solution clustering and fuzzy preference assignment

International Nuclear Information System (INIS)

Zio, E.; Bazzo, R.

2010-01-01

In this paper, a procedure is developed for identifying a number of representative solutions manageable for decision-making in a multiobjective optimization problem concerning the test intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are identified by a genetic algorithm and then clustered by subtractive clustering into 'families'. On the basis of the decision maker's preferences, each family is then synthetically represented by a 'head of the family' solution. This is done by introducing a scoring system that ranks the solutions with respect to the different objectives: a fuzzy preference assignment is employed to this purpose. Level Diagrams are then used to represent, analyze and interpret the Pareto Fronts reduced to the head-of-the-family solutions

Ranking beta sheet topologies of proteins

DEFF Research Database (Denmark)

Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

2010-01-01

One of the challenges of protein structure prediction is to identify long-range interactions between amino acids. To reliably predict such interactions, we enumerate, score and rank all beta-topologies (partitions of beta-strands into sheets, orderings of strands within sheets and orientations...... of paired strands) of a given protein. We show that the beta-topology corresponding to the native structure is, with high probability, among the top-ranked. Since full enumeration is very time-consuming, we also suggest a method to deal with proteins with many beta-strands. The results reported...... in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. The top-ranked beta-topologies can be used to find initial conformations from which conformational searches can be started. They can also be used to filter decoys by removing those with poorly...

RankExplorer: Visualization of Ranking Changes in Large Time Series Data.

Science.gov (United States)

Shi, Conglei; Cui, Weiwei; Liu, Shixia; Xu, Panpan; Chen, Wei; Qu, Huamin

2012-12-01

For many applications involving time series data, people are often interested in the changes of item values over time as well as their ranking changes. For example, people search many words via search engines like Google and Bing every day. Analysts are interested in both the absolute searching number for each word as well as their relative rankings. Both sets of statistics may change over time. For very large time series data with thousands of items, how to visually present ranking changes is an interesting challenge. In this paper, we propose RankExplorer, a novel visualization method based on ThemeRiver to reveal the ranking changes. Our method consists of four major components: 1) a segmentation method which partitions a large set of time series curves into a manageable number of ranking categories; 2) an extended ThemeRiver view with embedded color bars and changing glyphs to show the evolution of aggregation values related to each ranking category over time as well as the content changes in each ranking category; 3) a trend curve to show the degree of ranking changes over time; 4) rich user interactions to support interactive exploration of ranking changes. We have applied our method to some real time series data and the case studies demonstrate that our method can reveal the underlying patterns related to ranking changes which might otherwise be obscured in traditional visualizations.

Designing pharmacy services based on grocery store patron preferences.

Science.gov (United States)

Lindstrom, Nicolette S Raya; Casper, Kristin A; Green, Tara R; Pedersen, Craig A

2007-01-01

To assess preferences of grocery store patrons concerning pharmacy services and identify study participant characteristics that may predict the success of pharmacy services in the community setting. Self-administered survey. Central Ohio from December 16, 2005, to January 12, 2006. 163 grocery store patrons. Eight grocery store survey events. Responses to survey items about (1) perceived importance of 28 pharmacy services, (2) identification of the 3 most important services, (3) frequency of grocery store and pharmacy use, (4) preferred methods of advertising pharmacy services, and (5) socioeconomic demographics. Preferred services delineated by various demographics also were analyzed. A total of 163 surveys were returned from study participants. Nine services appeared in both the top 12 overall preferred services and the 12 highest-ranked services. Statistically significant differences were observed among services ranked as important or very important by age, race, employment, income, caregiver status, and prescription drug coverage status. The three advertising tools selected most frequently included: weekly grocery store ads (68.6%), in-store signs (51.0%), and flyers attached to prescription bags (36.0%). Grocery store patrons would like a wide range of nontraditional pharmacy services that could be implemented into community pharmacies. Pharmacies in grocery stores need to provide both traditional and expanded pharmacy services to meet the desires and expectations of current and potential patients, and expanded marketing methods should be considered.

The Role of Presented Objects in Deriving Color Preference Criteria from Psychophysical Studies

Energy Technology Data Exchange (ETDEWEB)

Royer, Michael P.; Wei, Minchen

2016-12-08

Of the many “components” of a color rendering measure, one is perhaps the most important: the set of color samples (spectral reflectance functions) that are employed as a standardized means of evaluating and rating a light source. At the same time, a standardized set of color samples can never apply perfectly to a real space or a real set of observed objects, meaning there will always be some level of mismatch between the predicted and observed color shifts. This mismatch is important for lighting specifiers to consider, but even more critical for experiments that seek to evaluate the relationship between color rendering measures and human perception. This article explores how the color distortions of three possible experimental object sets compare to the color distortions predicted using the color evaluation samples of IES TM-30-15 (TM-30). The experimental object sets include those from Royer and colleagues [2016], a set of produce (10 fruits and vegetables), and the X-rite Color Checker Classic. The differences are traced back to properties of the samples sets, such as the coverage of color space, average chroma level, and specific spectral features. The consequence of the differences, that the visual evaluation is based on color distortions that are substantially different from what is predicted, can lead to inaccurate criteria or models of a given perception, such as preference. To minimize the error in using criteria or models when specifying color rendering attributes for a given application, the criteria or models should be developed using a set of experimental objects that matches the typical objects of the application as closely as possible. Alternatively, if typical objects of an application cannot be reasonably determined, an object set that matches the distortions predicted by TM-30 as close as possible is likely to provide the most meaningful results.

Ranking agricultural, environmental and natural resource economics journals: A note

OpenAIRE

Halkos, George; Tzeremes, Nickolaos

2012-01-01

This paper by applying Data Envelopment Analysis (DEA) ranks for the first time Economics journals in the field of Agricultural, Environmental and Natural Resource. Specifically, by using one composite input and one composite output the paper ranks 32 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with t...

National Automated Highway System Consortium: Modeling Stakeholder Preferences Project

OpenAIRE

Lathrop, John; Chen, Kan

1997-01-01

This document is the final report of the Modeling Stakeholder Preferences Project. The results of the project consist of three results: 1) evaluation framework; 2) focus group non-quantitative findings/ recommendations; and, 3) performance/impact measures, their endpoints, rankings and weights, for each stakeholder group.

Resolution of ranking hierarchies in directed networks

Science.gov (United States)

Barucca, Paolo; Lillo, Fabrizio

2018-01-01

Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit. PMID:29394278

Preferences of the Central Reserve Bank of Peru and optimal monetary rules in the inflation targeting regime

Directory of Open Access Journals (Sweden)

Nilda Mercedes Cabrera Pasca

2012-03-01

Full Text Available This study aims to identify the preferences of the monetary authority in the Peruvian regime of inflation targeting through the derivation of optimal monetary rules. To achieve that, we used a calibration strategy based on the choice of values of the parameters of preferences that minimize the square deviation between the true interest rate and interest rate optimal simulation. The results showed that the monetary authority has applied a system of flexible inflation targeting, prioritizing the stabilization of inflation, but without disregarding gradualism in interest rates. On the other hand, concern over output stabilization has been minimal, revealing that the output gap has been important because it contains information about future inflation and not because it is considered a variable goal in itself. Finally, when the smoothing of the nominal exchange rate is considered in the loss function of the monetary authority, the rank order of preferences has been maintained and the smoothing of the exchange rate proved insignificant.

Alignment of learning objectives and assessments in therapeutics courses to foster higher-order thinking.

Science.gov (United States)

FitzPatrick, Beverly; Hawboldt, John; Doyle, Daniel; Genge, Terri

2015-02-17

To determine whether national educational outcomes, course objectives, and classroom assessments for 2 therapeutics courses were aligned for curricular content and cognitive processes, and if they included higher-order thinking. Document analysis and student focus groups were used. Outcomes, objectives, and assessment tasks were matched for specific therapeutics content and cognitive processes. Anderson and Krathwohl's Taxonomy was used to define higher-order thinking. Students discussed whether assessments tested objectives and described their thinking when responding to assessments. There were 7 outcomes, 31 objectives, and 412 assessment tasks. The alignment for content and cognitive processes was not satisfactory. Twelve students participated in the focus groups. Students thought more short-answer questions than multiple choice questions matched the objectives for content and required higher-order thinking. The alignment analysis provided data that could be used to reveal and strengthen the enacted curriculum and improve student learning.

Technical note: An approach to derive breeding goals from the preferences of decision makers.

Science.gov (United States)

Alfonso, L

2016-11-01

This paper deals with the use of the Choquet integral to identify breeding objectives and construct an aggregate genotype. The Choquet integral can be interpreted as an extension of the aggregate genotype based on profit equations, substituting the vector of economic weights by a monotone function, called capacity, which allows the aggregation of traits based, for instance, on the preferences of decision makers. It allows the aggregation of traits with or without economic value, taking into account not only the importance of the breeding value of each trait but also the interaction among them. Two examples have been worked out for pig and dairy cattle breeding scenarios to illustrate its application. It is shown that the expression of stakeholders' or decision makers' preferences, as a single ranking of animals or groups of animals, could be sufficient to extract information to derive breeding objectives. It is also shown that coalitions among traits can be identified to evaluate whether a linear additive function, equivalent of the Hazel aggregate genotype where economic values are replaced by Shapley values, could be adequate to define the net merit of breeding animals.

Social Rank, Stress, Fitness, and Life Expectancy in Wild Rabbits

Science.gov (United States)

von Holst, Dietrich; Hutzelmeyer, Hans; Kaetzke, Paul; Khaschei, Martin; Schönheiter, Ronald

Wild rabbits of the two sexes have separate linear rank orders, which are established and maintained by intensive fights. The social rank of individuals strongly influence their fitness: males and females that gain a high social rank, at least at the outset of their second breeding season, have a much higher lifetime fitness than subordinate individuals. This is because of two separate factors: a much higher fecundity and annual reproductive success and a 50% longer reproductive life span. These results are in contrast to the view in evolutionary biology that current reproduction can be increased only at the expense of future survival and/or fecundity. These concepts entail higher physiological costs in high-ranking mammals, which is not supported by our data: In wild rabbits the physiological costs of social positions are caused predominantly by differential psychosocial stress responses that are much lower in high-ranking than in low-ranking individuals.

PageRank as a method to rank biomedical literature by importance.

Science.gov (United States)

Yates, Elliot J; Dixon, Louise C

2015-01-01

Optimal ranking of literature importance is vital in overcoming article overload. Existing ranking methods are typically based on raw citation counts, giving a sum of 'inbound' links with no consideration of citation importance. PageRank, an algorithm originally developed for ranking webpages at the search engine, Google, could potentially be adapted to bibliometrics to quantify the relative importance weightings of a citation network. This article seeks to validate such an approach on the freely available, PubMed Central open access subset (PMC-OAS) of biomedical literature. On-demand cloud computing infrastructure was used to extract a citation network from over 600,000 full-text PMC-OAS articles. PageRanks and citation counts were calculated for each node in this network. PageRank is highly correlated with citation count (R = 0.905, P PageRank can be trivially computed on commodity cluster hardware and is linearly correlated with citation count. Given its putative benefits in quantifying relative importance, we suggest it may enrich the citation network, thereby overcoming the existing inadequacy of citation counts alone. We thus suggest PageRank as a feasible supplement to, or replacement of, existing bibliometric ranking methods.

Water Resource Vulnerability Characteristics by District’s Population Size in a Changing Climate Using Subjective and Objective Weights

Directory of Open Access Journals (Sweden)

Eun-Sung Chung

2014-09-01

Full Text Available The goal of this study is to derive water resource vulnerability characteristics for South Korea according to individual district populations in a changing climate. The definition of water resource vulnerability in this study consists of potential flood damage and potential water scarcity. To quantify these vulnerabilities, key factors, or indicators affecting vulnerability, are integrated with a technique for order of preference by similarity to ideal solution (TOPSIS, which is a multi-criteria decision-making approach to determine the optimal alternative by considering both the best and worst solutions. The weight for each indicator is determined based on both the Delphi technique and Shannon’s entropy, which are employed to reduce the uncertainty in the process of determining the weights. The Delphi technique reflects expert opinions, and Shannon’s entropy reflects the uncertainty of the performance data. Under A1B climate change scenarios, medium-sized districts (200,000–300,000 inhabitants are the most vulnerable regarding potential flood damage; the largest districts (exceeding 500,000 inhabitants are found to be the most vulnerable with respect to potential water scarcity. This result indicates that the local governments of cities or districts with more than 200,000 inhabitants should implement better preventative measures for water resources. In addition, the Delphi and entropy methods show the same rankings for flood vulnerability; however, these approaches produce slightly different rankings regarding water scarcity vulnerability. Therefore, it is suggested that rankings from not only subjective but also objective weights should be considered in making a final decision to implement specific adaptive measures to climate change.

An Automatic Web Service Composition Framework Using QoS-Based Web Service Ranking Algorithm.

Science.gov (United States)

Mallayya, Deivamani; Ramachandran, Baskaran; Viswanathan, Suganya

2015-01-01

Web service has become the technology of choice for service oriented computing to meet the interoperability demands in web applications. In the Internet era, the exponential addition of web services nominates the "quality of service" as essential parameter in discriminating the web services. In this paper, a user preference based web service ranking (UPWSR) algorithm is proposed to rank web services based on user preferences and QoS aspect of the web service. When the user's request cannot be fulfilled by a single atomic service, several existing services should be composed and delivered as a composition. The proposed framework allows the user to specify the local and global constraints for composite web services which improves flexibility. UPWSR algorithm identifies best fit services for each task in the user request and, by choosing the number of candidate services for each task, reduces the time to generate the composition plans. To tackle the problem of web service composition, QoS aware automatic web service composition (QAWSC) algorithm proposed in this paper is based on the QoS aspects of the web services and user preferences. The proposed framework allows user to provide feedback about the composite service which improves the reputation of the services.

Preference for different relaxation techniques by COPD patients: comparison between six techniques

Directory of Open Access Journals (Sweden)

Hyl

2016-09-01

Full Text Available Michael E Hyland,1 David MG Halpin,2 Sue Blake,3 Clare Seamark,3 Margaret Pinnuck,3 David Ward,3 Ben Whalley,1 Colin J Greaves,4 Adam L Hawkins,5 Dave Seamark3 1School of Psychology, University of Plymouth, Plymouth, 2Department of Respiratory Medicine, Royal Devon and Exeter Hospital, Exeter, 3Honiton Group Practice, Honiton, 4University of Exeter Medical School, Exeter, 5GSK House, Brentford, UK Background: A review of the effectiveness of relaxation techniques for chronic obstructive pulmonary disease patients has shown inconsistent results, but studies have varied in terms of technique and outcome measures. Aim: To determine patient preference for different relaxation techniques. Methods: Chronic obstructive pulmonary disease patients were presented with six techniques via a DVD and asked to rate the techniques in terms of effectiveness, rank in order of likely use, and comment. Results: Patients differed in the technique preferred and reason for that preference, but the most commonly preferred technique both for effectiveness and ease of use was “thinking of a nice place” followed by progressive relaxation and counting. Familiarity and ease of activity were commonly given reasons for preference. Conclusion: Rather than providing patients with a single technique that they might find difficult to implement, these results suggest that it would be better to give a choice. “Thinking of a nice place” is a popular but under-investigated technique. Keywords: COPD exacerbation, anxiety, relaxation techniques

Automated characterization of perceptual quality of clinical chest radiographs: Validation and calibration to observer preference

International Nuclear Information System (INIS)

Samei, Ehsan; Lin, Yuan; Choudhury, Kingshuk R.; Page McAdams, H.

2014-01-01

Purpose: The authors previously proposed an image-based technique [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] to assess the perceptual quality of clinical chest radiographs. In this study, an observer study was designed and conducted to validate the output of the program against rankings by expert radiologists and to establish the ranges of the output values that reflect the acceptable image appearance so the program output can be used for image quality optimization and tracking. Methods: Using an IRB-approved protocol, 2500 clinical chest radiographs (PA/AP) were collected from our clinical operation. The images were processed through our perceptual quality assessment program to measure their appearance in terms of ten metrics of perceptual image quality: lung gray level, lung detail, lung noise, rib–lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm–lung contrast, and subdiaphragm area. From the results, for each targeted appearance attribute/metric, 18 images were selected such that the images presented a relatively constant appearance with respect to all metrics except the targeted one. The images were then incorporated into a graphical user interface, which displayed them into three panels of six in a random order. Using a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions, each of five participating attending chest radiologists was tasked to spatially order the images based only on the targeted appearance attribute regardless of the other qualities. Once ordered, the observer also indicated the range of image appearances that he/she considered clinically acceptable. The observer data were analyzed in terms of the correlations between the observer and algorithmic rankings and interobserver variability. An observer-averaged acceptable image appearance was also statistically derived for each quality attribute based on the collected individual acceptable ranges

Automated characterization of perceptual quality of clinical chest radiographs: Validation and calibration to observer preference

Energy Technology Data Exchange (ETDEWEB)

Samei, Ehsan, E-mail: samei@duke.edu [Carl E. Ravin Advanced Imaging Laboratories, Departments of Radiology, Physics, Biomedical Engineering, Electrical and Computer Engineering, Medical Physics Graduate Program, Duke Clinical Imaging Physics Group, Duke University, Durham, North Carolina 27710 (United States); Lin, Yuan [Carl E. Ravin Advanced Imaging Laboratories, Departments of Radiology and Physics, Duke University, Durham, North Carolina 27710 (United States); Choudhury, Kingshuk R. [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology and Biostatistics and Bioinformatics, Duke University, Durham, North Carolina 27710 (United States); Page McAdams, H. [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University, Durham, North Carolina 27710 (United States)

2014-11-01

Purpose: The authors previously proposed an image-based technique [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] to assess the perceptual quality of clinical chest radiographs. In this study, an observer study was designed and conducted to validate the output of the program against rankings by expert radiologists and to establish the ranges of the output values that reflect the acceptable image appearance so the program output can be used for image quality optimization and tracking. Methods: Using an IRB-approved protocol, 2500 clinical chest radiographs (PA/AP) were collected from our clinical operation. The images were processed through our perceptual quality assessment program to measure their appearance in terms of ten metrics of perceptual image quality: lung gray level, lung detail, lung noise, rib–lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm–lung contrast, and subdiaphragm area. From the results, for each targeted appearance attribute/metric, 18 images were selected such that the images presented a relatively constant appearance with respect to all metrics except the targeted one. The images were then incorporated into a graphical user interface, which displayed them into three panels of six in a random order. Using a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions, each of five participating attending chest radiologists was tasked to spatially order the images based only on the targeted appearance attribute regardless of the other qualities. Once ordered, the observer also indicated the range of image appearances that he/she considered clinically acceptable. The observer data were analyzed in terms of the correlations between the observer and algorithmic rankings and interobserver variability. An observer-averaged acceptable image appearance was also statistically derived for each quality attribute based on the collected individual acceptable ranges

Critical review of methods for risk ranking of food related hazards, based on risks for human health

DEFF Research Database (Denmark)

van der Fels-Klerx, H. J.; van Asselt, E. D.; Raley, M.

2018-01-01

This study aimed to critically review methods for ranking risks related to food safety and dietary hazards on the basis of their anticipated human health impacts. A literature review was performed to identify and characterize methods for risk ranking from the fields of food, environmental science......, and the risk ranking method characterized. The methods were then clustered - based on their characteristics - into eleven method categories. These categories included: risk assessment, comparative risk assessment, risk ratio method, scoring method, cost of illness, health adjusted life years, multi......-criteria decision analysis, risk matrix, flow charts/decision trees, stated preference techniques and expert synthesis. Method categories were described by their characteristics, weaknesses and strengths, data resources, and fields of applications. It was concluded there is no single best method for risk ranking...

Herd characteristics influence farmers’ preferences for trait improvements in Danish Red and Danish Jersey cows

DEFF Research Database (Denmark)

Slagboom, Margot; Kargo, Morten; Edwards, David

2016-01-01

The aim of this study was to characterize preferences of farmers for breeding goal traits with Danish Red (DR) or Danish Jersey (DJ) cows. A breed-specific survey was established to characterize farmers’ preferences for improvements in 10 traits, by means of pairwise rankings using the online sof...

Toward optimal feature selection using ranking methods and classification algorithms

Directory of Open Access Journals (Sweden)

Novaković Jasmina

2011-01-01

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

Drug-target interaction prediction: A Bayesian ranking approach.

Science.gov (United States)

Peska, Ladislav; Buza, Krisztian; Koller, Júlia

2017-12-01

In silico prediction of drug-target interactions (DTI) could provide valuable information and speed-up the process of drug repositioning - finding novel usage for existing drugs. In our work, we focus on machine learning algorithms supporting drug-centric repositioning approach, which aims to find novel usage for existing or abandoned drugs. We aim at proposing a per-drug ranking-based method, which reflects the needs of drug-centric repositioning research better than conventional drug-target prediction approaches. We propose Bayesian Ranking Prediction of Drug-Target Interactions (BRDTI). The method is based on Bayesian Personalized Ranking matrix factorization (BPR) which has been shown to be an excellent approach for various preference learning tasks, however, it has not been used for DTI prediction previously. In order to successfully deal with DTI challenges, we extended BPR by proposing: (i) the incorporation of target bias, (ii) a technique to handle new drugs and (iii) content alignment to take structural similarities of drugs and targets into account. Evaluation on five benchmark datasets shows that BRDTI outperforms several state-of-the-art approaches in terms of per-drug nDCG and AUC. BRDTI results w.r.t. nDCG are 0.929, 0.953, 0.948, 0.897 and 0.690 for G-Protein Coupled Receptors (GPCR), Ion Channels (IC), Nuclear Receptors (NR), Enzymes (E) and Kinase (K) datasets respectively. Additionally, BRDTI significantly outperformed other methods (BLM-NII, WNN-GIP, NetLapRLS and CMF) w.r.t. nDCG in 17 out of 20 cases. Furthermore, BRDTI was also shown to be able to predict novel drug-target interactions not contained in the original datasets. The average recall at top-10 predicted targets for each drug was 0.762, 0.560, 1.000 and 0.404 for GPCR, IC, NR, and E datasets respectively. Based on the evaluation, we can conclude that BRDTI is an appropriate choice for researchers looking for an in silico DTI prediction technique to be used in drug

Prioritizing sewer rehabilitation projects using AHP-PROMETHEE II ranking method.

Science.gov (United States)

Kessili, Abdelhak; Benmamar, Saadia

2016-01-01

The aim of this paper is to develop a methodology for the prioritization of sewer rehabilitation projects for Algiers (Algeria) sewer networks to support the National Sanitation Office in its challenge to make decisions on prioritization of sewer rehabilitation projects. The methodology applies multiple-criteria decision making. The study includes 47 projects (collectors) and 12 criteria to evaluate them. These criteria represent the different issues considered in the prioritization of the projects, which are structural, hydraulic, environmental, financial, social and technical. The analytic hierarchy process (AHP) is used to determine weights of the criteria and the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II) method is used to obtain the final ranking of the projects. The model was verified using the sewer data of Algiers. The results have shown that the method can be used for prioritizing sewer rehabilitation projects.

RANK and RANK ligand expression in primary human osteosarcoma

Directory of Open Access Journals (Sweden)

Daniel Branstetter

2015-09-01

Our results demonstrate RANKL expression was observed in the tumor element in 68% of human OS using IHC. However, the staining intensity was relatively low and only 37% (29/79 of samples exhibited≥10% RANKL positive tumor cells. RANK expression was not observed in OS tumor cells. In contrast, RANK expression was clearly observed in other cells within OS samples, including the myeloid osteoclast precursor compartment, osteoclasts and in giant osteoclast cells. The intensity and frequency of RANKL and RANK staining in OS samples were substantially less than that observed in GCTB samples. The observation that RANKL is expressed in OS cells themselves suggests that these tumors may mediate an osteoclastic response, and anti-RANKL therapy may potentially be protective against bone pathologies in OS. However, the absence of RANK expression in primary human OS cells suggests that any autocrine RANKL/RANK signaling in human OS tumor cells is not operative, and anti-RANKL therapy would not directly affect the tumor.

Ranking nodes in growing networks: When PageRank fails

Science.gov (United States)

Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

2015-11-01

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

Preferred Tone of Nutrition Text Messages for Young Adults: Focus Group Testing

Science.gov (United States)

2016-01-01

Background Young adults are a particularly hard to reach group using conventional health promotion practices as they do not see nutrition messages as personally relevant to them. Text messaging (short message service, SMS) offers an innovative approach to reaching young adults to support and promote dietary behavior change. Objective The aim of this study was to develop and test tonal preferences for nutrition text messages among young adults using focus groups. Methods A total of 39 young adults aged 18-30 years residing in Perth, Western Australia participated in four focus groups. Participants briefly discussed their perception of healthy eating and their responses to messages about increasing fruit and vegetables, and reducing “junk food” and alcohol intake. They ranked their preference for 15 nutrition messages across 3 dietary behaviors (fruit and vegetables, junk food, and alcohol) with 5 different message tones (authoritative, empathetic, generation Y, solutions, and substitutions) and identified the messages most likely to persuade young adults to change their diet. A 5-point ranking of the nutrition messages was from the most likely to least likely to persuade (1-5). The focus groups were conducted by a trained facilitator and observer and were recorded. Data driven content analysis was used to explore themes. Tonal preferences and potential motivators were collated and frequencies presented. Results Participants ranked offering substitutes (29%, 11/39) and using empathy (22%, 9/39) as the most persuasive message techniques in improving diets of young adults, with low responses for Generation Y (17%, 7/39), solutions (17%, 7/39), and authoritative (15%, 6/39) tones. Females were more likely to consider substitution messages persuasive (35%, 7/20) compared with males (22%, 4/19). A greater proportion of males compared with females considered authoritative messages persuasive: (22%, 4/19) compared with (7%, 1/20). There is a strong preference for a

Light colour preference of growing rabbits

Directory of Open Access Journals (Sweden)

Zsolt Szendrő

2010-01-01

Full Text Available The objective of the experiment was to evaluate the light colour preference of growing rabbits placed in a free-choice cage. The experiment was carried out on 128 Pannon White growing rabbits weaned at the age of 5 weeks and placed into blocks (2m2 of four cages. The rabbits could move freely among the four cages (0.5m2 each through swing doors. The cages differed only in the colour of the light applied (white, yellow, green or blue. The lighting schedule was 16L: 8D. From 6 until 10 weeks of age, infrared video recording was performed once a week (24 hours. The number of rabbits in each cage was counted every 15 minutes. Feed consumption was measured weekly. Between 6 and 10 weeks of age the rabbits significantly preferred white light (28.0%. The preference order was the following: yellow (26.3%, blue (23.4% and green (22.3% (P<0.001. No significant differences were recorded in the feed consumption among the cages. In conclusion, the cage preference of the rabbits was slightly affected by the light colour.

RANK/RANK-Ligand/OPG: Ein neuer Therapieansatz in der Osteoporosebehandlung

Directory of Open Access Journals (Sweden)

Preisinger E

2007-01-01

Full Text Available Die Erforschung der Kopplungsmechanismen zur Osteoklastogenese, Knochenresorption und Remodellierung eröffnete neue mögliche Therapieansätze in der Behandlung der Osteoporose. Eine Schlüsselrolle beim Knochenabbau spielt der RANK- ("receptor activator of nuclear factor (NF- κB"- Ligand (RANKL. Durch die Bindung von RANKL an den Rezeptor RANK wird die Knochenresorption eingeleitet. OPG (Osteoprotegerin sowie der für den klinischen Gebrauch entwickelte humane monoklonale Antikörper (IgG2 Denosumab blockieren die Bindung von RANK-Ligand an RANK und verhindern den Knochenabbau.

Poisson statistics of PageRank probabilities of Twitter and Wikipedia networks

Science.gov (United States)

Frahm, Klaus M.; Shepelyansky, Dima L.

2014-04-01

We use the methods of quantum chaos and Random Matrix Theory for analysis of statistical fluctuations of PageRank probabilities in directed networks. In this approach the effective energy levels are given by a logarithm of PageRank probability at a given node. After the standard energy level unfolding procedure we establish that the nearest spacing distribution of PageRank probabilities is described by the Poisson law typical for integrable quantum systems. Our studies are done for the Twitter network and three networks of Wikipedia editions in English, French and German. We argue that due to absence of level repulsion the PageRank order of nearby nodes can be easily interchanged. The obtained Poisson law implies that the nearby PageRank probabilities fluctuate as random independent variables.

Kriging accelerated by orders of magnitude: combining low-rank with FFT techniques

KAUST Repository

Litvinenko, Alexander; Nowak, Wolfgang

2014-01-01

Kriging algorithms based on FFT, the separability of certain covariance functions and low-rank representations of covariance functions have been investigated. The current study combines these ideas, and so combines the individual speedup factors of all ideas. For separable covariance functions, the results are exact, and non-separable covariance functions can be approximated through sums of separable components. Speedup factor is 1e+8, problem sizes 1.5e+13 and 2e+15 estimation points for Kriging and spatial design.

Kriging accelerated by orders of magnitude: combining low-rank with FFT techniques

KAUST Repository

Litvinenko, Alexander

2014-01-08

Kriging algorithms based on FFT, the separability of certain covariance functions and low-rank representations of covariance functions have been investigated. The current study combines these ideas, and so combines the individual speedup factors of all ideas. For separable covariance functions, the results are exact, and non-separable covariance functions can be approximated through sums of separable components. Speedup factor is 1e+8, problem sizes 1.5e+13 and 2e+15 estimation points for Kriging and spatial design.

1991 Acceptance priority ranking

International Nuclear Information System (INIS)

1991-12-01

The Standard Contract for Disposal of Spent Nuclear Fuel and/or High- Level Radioactive Waste (10 CFR Part 961) that the Department of Energy (DOE) has executed with the owners and generators of civilian spent nuclear fuel requires annual publication of the Acceptance Priority Ranking (APR). The 1991 APR details the order in which DOE will allocate Federal waste acceptance capacity. As required by the Standard Contract, the ranking is based on the age of permanently discharged spent nuclear fuel (SNF), with the owners of the oldest SNF, on an industry-wide basis, given the highest priority. the 1991 APR will be the basis for the annual allocation of waste acceptance capacity to the Purchasers in the 1991 Annual Capacity Report (ACR), to be issued later this year. This document is based on SNF discharges as of December 31, 1990, and reflects Purchaser comments and corrections, as appropriate, to the draft APR issued on May 15, 1991

Consumer preferences for food labels on tomatoes in Germany - A comparison of a quasi-experiment and two stated preference approaches.

Science.gov (United States)

Meyerding, Stephan G H

2016-08-01

In many studies, consumer preferences are determined by using direct surveys. For this method social desirability is problematic. This leads to the effect that participants answer in a way that they perceive as desired by society. This leads to the stated importance of certain features in these studies not being reflected in real purchasing decisions. Therefore, the aim of the study is to compare consumer preferences measured by a quasi-experiment to those quantified by direct questions. Another objective is to quantify the part-worth utilities of product characteristics such as origin, price and food labels. Part-worth utilities are estimated on an interval scale with an arbitrary origin and are a measure for preferences. The real purchasing situation was simulated in a quasi-experiment using a choice-based conjoint analysis. The part-worth utilities were then compared with the results of a conventional preference assessment (Likert scale). For this purpose, 645 consumers from all over Germany were surveyed in 2014. The participants were on average 44 years old and 63% were women. The results of the conjoint analysis report the highest part-worth utility (2.853) for the lowest price (1.49€), followed by the characteristic "grown locally" (2.157). For the labels, the German organic label shows the highest part-worth utility (0.785) followed by Fairtrade/"A heart for the producer" (0.200). It is noticeable that the carbon footprint labels have negative part-worth utilities compared to tomatoes without a label (-0.130 with CO2 indication, -0.186 without CO2 indication). The price is ranked 12th in the importance of the characteristics of purchasing tomatoes in the survey with a Likert scale, whereas it is first in the evaluation of the quasi-experiment (conjoint analysis), which supports the assumption of a social desirability bias. Copyright © 2016 Elsevier Ltd. All rights reserved.

Zipf rank approach and cross-country convergence of incomes

Science.gov (United States)

Shao, Jia; Ivanov, Plamen Ch.; Urošević, Branko; Stanley, H. Eugene; Podobnik, Boris

2011-05-01

We employ a concept popular in physics —the Zipf rank approach— in order to estimate the number of years that EU members would need in order to achieve "convergence" of their per capita incomes. Assuming that trends in the past twenty years continue to hold in the future, we find that after t≈30 years both developing and developed EU countries indexed by i will have comparable values of their per capita gross domestic product {\\cal G}_{i,t} . Besides the traditional Zipf rank approach we also propose a weighted Zipf rank method. In contrast to the EU block, on the world level the Zipf rank approach shows that, between 1960 and 2009, cross-country income differences increased over time. For a brief period during the 2007-2008 global economic crisis, at world level the {\\cal G}_{i,t} of richer countries declined more rapidly than the {\\cal G}_{i,t} of poorer countries, in contrast to EU where the {\\cal G}_{i,t} of developing EU countries declined faster than the {\\cal G}_{i,t} of developed EU countries, indicating that the recession interrupted the convergence between EU members. We propose a simple model of GDP evolution that accounts for the scaling we observe in the data.

Variability in Women Faculty’s Preferences Regarding Mentor Similarity: A Multi-Institution Study in Academic Medicine

Science.gov (United States)

Carapinha, René; Ortiz-Walters, Rowena; McCracken, Caitlin M.; Hill, Emorcia V.; Reede, Joan Y.

2016-01-01

Purpose To investigate which mentor similarity characteristics women faculty in academic medicine rate most important and to determine whether the importance of similarity differs among women faculty based on current and prior mentoring, demographic and personal factors, and career factors. Method Cross-sectional survey data from 3,100 women faculty at 13 purposively sampled U.S. medical schools were collected in 2012. The preferences of participants regarding the importance of mentor similarity in terms of race/ethnicity, gender, personal and career interests, and department and institution were studied. Analysis entailed chi square tests and multivariable ordered logistic models. Results Overall, respondents ranked having a mentor in the same department and institution as most important. Same department and institution were less important for those without a current mentor and for senior faculty, and were more important for Asian faculty. Same career and personal interests were less important for older faculty and more important for those with a doctorate only. Same gender was more important for Black faculty, faculty at the rank of instructor, and those without current mentoring. Overall, same race/ethnicity was rated least important; however, it was more important for racial/ethnic minorities, foreign-born faculty, and those who had never had a mentor. Conclusions Mentor preferences, as indicated by level of importance assigned to types of mentor similarity, varied among women faculty. To advance effective mentoring, characterized by high degree of mentor-mentee fit, the authors provide recommendations on matching strategies to be used in academic medicine when considering the diverse mentor preferences of women faculty. PMID:27332871

Focus Groups in Elderly Ophthalmologic Patients: Setting the Stage for Quantitative Preference Elicitation.

Science.gov (United States)

Danner, Marion; Vennedey, Vera; Hiligsmann, Mickaël; Fauser, Sascha; Stock, Stephanie

2016-02-01

Patients suffering from age-related macular degeneration (AMD) are rarely actively involved in decision-making, despite facing preference-sensitive treatment decisions. This paper presents a qualitative study to prepare quantitative preference elicitation in AMD patients. The aims of this study were (1) to gain familiarity with and learn about the special requirements of the AMD patient population for quantitative data collection; and (2) to select/refine patient-relevant treatment attributes and levels, and gain insights into preference structures. Semi-structured focus group interviews were performed. An interview guide including preselected categories in the form of seven potentially patient-relevant treatment attributes was followed. To identify the most patient-relevant treatment attributes, a ranking exercise was performed. Deductive content analyses were done by two independent reviewers for each attribute to derive subcategories (potential levels of attributes) and depict preference trends. The focus group interviews included 21 patients. The interviews revealed that quantitative preference surveys in this population will have to be interviewer assisted to make the survey feasible for patients. The five most patient-relevant attributes were the effect on visual function [ranking score (RS): 139], injection frequency (RS: 101), approval status (RS: 83), side effects (RS: 79), and monitoring frequency (RS: 76). Attribute and level refinement was based on patients' statements. Preference trends and dependencies between attributes informed the quantitative instrument design. This study suggests that qualitative research is a very helpful step to prepare the design and administration of quantitative preference elicitation instruments. It especially facilitated familiarization with the target population and its preferences, and it supported attribute/level refinement.

Impact of Consumer Preferences on Food Chain Choice: An empirical study of consumers in Bratislava

Directory of Open Access Journals (Sweden)

Pavol Kita

2017-01-01

Full Text Available The objective of this paper is to highlight the use of multiple criteria evaluation methods as a tool for the rating and selection of retail chains from the customers and suppliers perspective. We provide an assessment on the attractiveness of active retail chains on the Slovak market through multiple criteria methods used for the analysis of customer preferences. An analysis was conducted on a sample of consumers in Bratislava involving 11 389 respondents interviewed. The multi-attribute decision-making methods PROMETHEE II and V were used to assess the variants. In the first part of analysis the collected data uncover customers’ preferences in the selection of retail chains. Findings suggest a ranking of evaluated retail chains and thus of customer preferences. Based on the obtained evaluation, in the second part of analysis, a set of retail chains was chosen under constraints concerning the effectiveness of advertising, market share of sales and the maximum number of chosen retail chains and a binary linear programming model was formulated as an outcome. Proposed procedure aims to assist the decision maker in selecting which retail chain to choose for distribution of supplier’s products, and thus maximize benefits, which will result from consumer preferences and service satisfaction level in retail chain.

Convex hull ranking algorithm for multi-objective evolutionary algorithms

NARCIS (Netherlands)

Davoodi Monfrared, M.; Mohades, A.; Rezaei, J.

2012-01-01

Due to many applications of multi-objective evolutionary algorithms in real world optimization problems, several studies have been done to improve these algorithms in recent years. Since most multi-objective evolutionary algorithms are based on the non-dominated principle, and their complexity

Feature selection model based on clustering and ranking in pipeline for microarray data

Directory of Open Access Journals (Sweden)

Barnali Sahu

2017-01-01

Full Text Available Most of the available feature selection techniques in the literature are classifier bound. It means a group of features tied to the performance of a specific classifier as applied in wrapper and hybrid approach. Our objective in this study is to select a set of generic features not tied to any classifier based on the proposed framework. This framework uses attribute clustering and feature ranking techniques in pipeline in order to remove redundant features. On each uncovered cluster, signal-to-noise ratio, t-statistics and significance analysis of microarray are independently applied to select the top ranked features. Both filter and evolutionary wrapper approaches have been considered for feature selection and the data set with selected features are given to ensemble of predefined statistically different classifiers. The class labels of the test data are determined using majority voting technique. Moreover, with the aforesaid objectives, this paper focuses on obtaining a stable result out of various classification models. Further, a comparative analysis has been performed to study the classification accuracy and computational time of the current approach and evolutionary wrapper techniques. It gives a better insight into the features and further enhancing the classification accuracy with less computational time.

Parenting and later substance use among Mexican-origin youth: Moderation by preference for a common language.

Science.gov (United States)

Schofield, Thomas J; Toro, Rosa I; Parke, Ross D; Cookston, Jeffrey T; Fabricius, William V; Coltrane, Scott

2017-04-01

The primary goal of the current study was to test whether parent and adolescent preference for a common language moderates the association between parenting and rank-order change over time in offspring substance use. A sample of Mexican-origin 7th-grade adolescents (Mage = 12.5 years, N = 194, 52% female) was measured longitudinally on use of tobacco, alcohol, and marijuana. Mothers, fathers, and adolescents all reported on consistent discipline and monitoring of adolescents. Both consistent discipline and monitoring predicted relative decreases in substance use into early adulthood but only among parent-offspring dyads who expressed preference for the same language (either English or Spanish). This moderation held after controlling for parent substance use, family structure, having completed schooling in Mexico, years lived in the United States, family income, and cultural values. An unintended consequence of the immigration process may be the loss of parenting effectiveness that is normally present when parents and adolescents prefer to communicate in a common language. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

NON-EXPECTED UTILITY THEORIES: WEIGHTED EXPECTED, RANK DEPENDENT, AND CUMULATIVE PROSPECT THEORY UTILITY

OpenAIRE

Tuthill, Jonathan W.; Frechette, Darren L.

2002-01-01

This paper discusses some of the failings of expected utility including the Allais paradox and expected utility's inadequate one dimensional characterization of risk. Three alternatives to expected utility are discussed at length; weighted expected utility, rank dependent utility, and cumulative prospect theory. Each alternative is capable of explaining Allais paradox type problems and permits more sophisticated multi dimensional risk preferences.

About the use of rank transformation in sensitivity analysis of model output

International Nuclear Information System (INIS)

Saltelli, Andrea; Sobol', Ilya M

1995-01-01

Rank transformations are frequently employed in numerical experiments involving a computational model, especially in the context of sensitivity and uncertainty analyses. Response surface replacement and parameter screening are tasks which may benefit from a rank transformation. Ranks can cope with nonlinear (albeit monotonic) input-output distributions, allowing the use of linear regression techniques. Rank transformed statistics are more robust, and provide a useful solution in the presence of long tailed input and output distributions. As is known to practitioners, care must be employed when interpreting the results of such analyses, as any conclusion drawn using ranks does not translate easily to the original model. In the present note an heuristic approach is taken, to explore, by way of practical examples, the effect of a rank transformation on the outcome of a sensitivity analysis. An attempt is made to identify trends, and to correlate these effects to a model taxonomy. Employing sensitivity indices, whereby the total variance of the model output is decomposed into a sum of terms of increasing dimensionality, we show that the main effect of the rank transformation is to increase the relative weight of the first order terms (the 'main effects'), at the expense of the 'interactions' and 'higher order interactions'. As a result the influence of those parameters which influence the output mostly by way of interactions may be overlooked in an analysis based on the ranks. This difficulty increases with the dimensionality of the problem, and may lead to the failure of a rank based sensitivity analysis. We suggest that the models can be ranked, with respect to the complexity of their input-output relationship, by mean of an 'Association' index I y . I y may complement the usual model coefficient of determination R y 2 as a measure of model complexity for the purpose of uncertainty and sensitivity analysis

Gravitationally compact objects as nucleation sites for first-order vacuum phase transitions

International Nuclear Information System (INIS)

Samuel, D.A.; Hiscock, W.A.

1992-01-01

A characteristic of first-order phase transitions is their ability to be initiated by nucleation sites. In this paper we consider the role that gravitationally compact objects may play as nucleation sites for first-order phase transitions within quantum fields. As the presence of nucleation sites may prevent the onset of supercooling, the existence of nucleation sites for phase transitions within quantum fields may play an important role in some inflationary models of the Universe, in which the Universe is required to exist in a supercooled state for a period of time. In this paper we calculate the Euclidean action for an O(3) bubble nucleating about a gravitationally compact object, taken to be a boson star for simplicity. The gravitational field of the boson star is taken to be a small perturbation on flat space, and the O(3) action is calculated to linear order as a perturbation on the O(4) action. The Euclidean bubble profile is found by solving the (Higgs) scalar field equation numerically; the thin-wall approximation is not used. The gravitationally compact objects are found to have the effect of reducing the Euclidean action of the nucleating bubble, as compared to the Euclidean action for the bubble in flat spacetime. The effect is strongest when the size of the gravitationally compact object is comparable to the size of the nucleating bubble. Further, the size of the decrease in action increases as the nucleating ''star'' is made more gravitationally compact. Thus, gravitationally compact objects may play the role of nucleation sites. However, their importance to the process of false-vacuum decay is strongly dependent upon their number density within the Universe

SRS: Site ranking system for hazardous chemical and radioactive waste

International Nuclear Information System (INIS)

Rechard, R.P.; Chu, M.S.Y.; Brown, S.L.

1988-05-01

This report describes the rationale and presents instructions for a site ranking system (SRS). SRS ranks hazardous chemical and radioactive waste sites by scoring important and readily available factors that influence risk to human health. Using SRS, sites can be ranked for purposes of detailed site investigations. SRS evaluates the relative risk as a combination of potentially exposed population, chemical toxicity, and potential exposure of release from a waste site; hence, SRS uses the same concepts found in a detailed assessment of health risk. Basing SRS on the concepts of risk assessment tends to reduce the distortion of results found in other ranking schemes. More importantly, a clear logic helps ensure the successful application of the ranking procedure and increases its versatility when modifications are necessary for unique situations. Although one can rank sites using a detailed risk assessment, it is potentially costly because of data and resources required. SRS is an efficient approach to provide an order-of-magnitude ranking, requiring only readily available data (often only descriptive) and hand calculations. Worksheets are included to make the system easier to understand and use. 88 refs., 19 figs., 58 tabs

Predicting disease risk using bootstrap ranking and classification algorithms.

Directory of Open Access Journals (Sweden)

Ohad Manor

Full Text Available Genome-wide association studies (GWAS are widely used to search for genetic loci that underlie human disease. Another goal is to predict disease risk for different individuals given their genetic sequence. Such predictions could either be used as a "black box" in order to promote changes in life-style and screening for early diagnosis, or as a model that can be studied to better understand the mechanism of the disease. Current methods for risk prediction typically rank single nucleotide polymorphisms (SNPs by the p-value of their association with the disease, and use the top-associated SNPs as input to a classification algorithm. However, the predictive power of such methods is relatively poor. To improve the predictive power, we devised BootRank, which uses bootstrapping in order to obtain a robust prioritization of SNPs for use in predictive models. We show that BootRank improves the ability to predict disease risk of unseen individuals in the Wellcome Trust Case Control Consortium (WTCCC data and results in a more robust set of SNPs and a larger number of enriched pathways being associated with the different diseases. Finally, we show that combining BootRank with seven different classification algorithms improves performance compared to previous studies that used the WTCCC data. Notably, diseases for which BootRank results in the largest improvements were recently shown to have more heritability than previously thought, likely due to contributions from variants with low minimum allele frequency (MAF, suggesting that BootRank can be beneficial in cases where SNPs affecting the disease are poorly tagged or have low MAF. Overall, our results show that improving disease risk prediction from genotypic information may be a tangible goal, with potential implications for personalized disease screening and treatment.

Object recognition memory in zebrafish.

Science.gov (United States)

May, Zacnicte; Morrill, Adam; Holcombe, Adam; Johnston, Travis; Gallup, Joshua; Fouad, Karim; Schalomon, Melike; Hamilton, Trevor James

2016-01-01

The novel object recognition, or novel-object preference (NOP) test is employed to assess recognition memory in a variety of organisms. The subject is exposed to two identical objects, then after a delay, it is placed back in the original environment containing one of the original objects and a novel object. If the subject spends more time exploring one object, this can be interpreted as memory retention. To date, this test has not been fully explored in zebrafish (Danio rerio). Zebrafish possess recognition memory for simple 2- and 3-dimensional geometrical shapes, yet it is unknown if this translates to complex 3-dimensional objects. In this study we evaluated recognition memory in zebrafish using complex objects of different sizes. Contrary to rodents, zebrafish preferentially explored familiar over novel objects. Familiarity preference disappeared after delays of 5 mins. Leopard danios, another strain of D. rerio, also preferred the familiar object after a 1 min delay. Object preference could be re-established in zebra danios by administration of nicotine tartrate salt (50mg/L) prior to stimuli presentation, suggesting a memory-enhancing effect of nicotine. Additionally, exploration biases were present only when the objects were of intermediate size (2 × 5 cm). Our results demonstrate zebra and leopard danios have recognition memory, and that low nicotine doses can improve this memory type in zebra danios. However, exploration biases, from which memory is inferred, depend on object size. These findings suggest zebrafish ecology might influence object preference, as zebrafish neophobia could reflect natural anti-predatory behaviour. Copyright © 2015 Elsevier B.V. All rights reserved.

Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

Science.gov (United States)

Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

2016-03-10

Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of Buried Dielectric Objects Using Higher-Order MoM for Volume Integral Equations

DEFF Research Database (Denmark)

Kim, Oleksiy S.; Meincke, Peter; Breinbjerg, Olav

2004-01-01

A higher-order method of moments (MoM) is applied to solve a volume integral equation for dielectric objects in layered media. In comparison to low-order methods, the higher-order MoM, which is based on higher-order hierarchical Legendre vector basis functions and curvilinear hexahedral elements,...

Ranking Performance Measures in Multi-Task Agencies

DEFF Research Database (Denmark)

Christensen, Peter Ove; Sabac, Florin; Tian, Joyce

We derive sufficient conditions for ranking performance evaluation systems in multi-task agency models using both optimal and linear contracts in terms of a second-order stochastic dominance (SSD) condition on the likelihood ratios. The SSD condition can be replaced by a variance-covariance matrix...

Some spacetimes with higher rank Killing-Staeckel tensors

International Nuclear Information System (INIS)

Gibbons, G.W.; Houri, T.; Kubiznak, D.; Warnick, C.M.

2011-01-01

By applying the lightlike Eisenhart lift to several known examples of low-dimensional integrable systems admitting integrals of motion of higher-order in momenta, we obtain four- and higher-dimensional Lorentzian spacetimes with irreducible higher-rank Killing tensors. Such metrics, we believe, are first examples of spacetimes admitting higher-rank Killing tensors. Included in our examples is a four-dimensional supersymmetric pp-wave spacetime, whose geodesic flow is superintegrable. The Killing tensors satisfy a non-trivial Poisson-Schouten-Nijenhuis algebra. We discuss the extension to the quantum regime.

Kriging accelerated by orders of magnitude: combining low-rank with FFT techniques

KAUST Repository

Litvinenko, Alexander; Nowak, Wolfgang

2014-01-01

Kriging algorithms based on FFT, the separability of certain covariance functions and low-rank representations of covariance functions have been investigated. The current study combines these ideas, and so combines the individual speedup factors of all ideas. The reduced computational complexity is O(dLlogL), where L := max ini, i = 1..d. For separable covariance functions, the results are exact, and non-separable covariance functions can be approximated through sums of separable components. Speedup factor is 10 8, problem sizes 15e + 12 and 2e + 15 estimation points for Kriging and spatial design.

Kriging accelerated by orders of magnitude: combining low-rank with FFT techniques

KAUST Repository

Litvinenko, Alexander

2014-01-06

Kriging algorithms based on FFT, the separability of certain covariance functions and low-rank representations of covariance functions have been investigated. The current study combines these ideas, and so combines the individual speedup factors of all ideas. The reduced computational complexity is O(dLlogL), where L := max ini, i = 1..d. For separable covariance functions, the results are exact, and non-separable covariance functions can be approximated through sums of separable components. Speedup factor is 10 8, problem sizes 15e + 12 and 2e + 15 estimation points for Kriging and spatial design.

The Interplay between QSAR/QSPR Studiesand Partial Order Ranking and Formal Concept Analyses

Directory of Open Access Journals (Sweden)

Lars Carlsen

2009-04-01

Full Text Available The often observed scarcity of physical-chemical and well as toxicological data hampers the assessment of potentially hazardous chemicals released to the environment. In such cases Quantitative Structure-Activity Relationships/Quantitative Structure-Property Relationships (QSAR/QSPR constitute an obvious alternative for rapidly, effectively and inexpensively generatng missing experimental values. However, typically further treatment of the data appears necessary, e.g., to elucidate the possible relations between the single compounds as well as implications and associations between the various parameters used for the combined characterization of the compounds under investigation. In the present paper the application of QSAR/QSPR in combination with Partial Order Ranking (POR methodologies will be reviewed and new aspects using Formal Concept Analysis (FCA will be introduced. Where POR constitutes an attractive method for, e.g., prioritizing a series of chemical substances based on a simultaneous inclusion of a range of parameters, FCA gives important information on the implications associations between the parameters. The combined approach thus constitutes an attractive method to a preliminary assessment of the impact on environmental and human health by primary pollutants or possibly by a primary pollutant well as a possible suite of transformation subsequent products that may be both persistent in and bioaccumulating and toxic.The present review focus on the environmental – and human health impact by residuals of the rocket fuel 1,1-dimethyl- hydrazine (heptyl and its transformation products as an illustrative example.

A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

Science.gov (United States)

Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

2009-11-01

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation

Directory of Open Access Journals (Sweden)

Pandiarajan K.

2014-09-01

Full Text Available This paper presents an effective method of network overload management in power systems. The three competing objectives 1 generation cost 2 transmission line overload and 3 real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO and Differential evolution (DE. Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem

Solving the Fully Fuzzy Bilevel Linear Programming Problem through Deviation Degree Measures and a Ranking Function Method

OpenAIRE

Aihong Ren

2016-01-01

This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solut...

Exploiting Higher Order and Multi-modal Features for 3D Object Detection

DEFF Research Database (Denmark)

Kiforenko, Lilita

that describe object visual appearance such as shape, colour, texture etc. This thesis focuses on robust object detection and pose estimation of rigid objects using 3D information. The thesis main contributions are novel feature descriptors together with object detection and pose estimation algorithms....... The initial work introduces a feature descriptor that uses edge categorisation in combination with a local multi-modal histogram descriptor in order to detect objects with little or no texture or surface variation. The comparison is performed with a state-of-the-art method, which is outperformed...... of the methods work well for one type of objects in a specific scenario, in another scenario or with different objects they might fail, therefore more robust solutions are required. The typical problem solution is the design of robust feature descriptors, where feature descriptors contain information...

Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

Science.gov (United States)

Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

2017-08-18

Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

CONCEPTUAL PRINCIPLES OF ATLAS GEOENVIRONMENTAL MAPPING OF GEOSPATIAL OBJECTS AND SYSTEMS OF DIFFERENT RANKS

Directory of Open Access Journals (Sweden)

Kovalchuk I.

2017-08-01

Full Text Available The article discusses contemporary issues of digital atlas thematic mapping, which has been gaining momentum in recent decades. It shows that the atlas geoenvironmental mapping allows to perform high quality visualization of various spatial and temporal information in dynamic and static states, reflects the geoenvironmental state of objects that vary by rank, trends in its changes, and evaluates the influence of natural and anthropogenic factors on it. Solution to this problem is possible with the correct choice of cartographic service, which can serve as the basis for creating a wide range of interactive digital atlases. Using the ArcGIS Online service allows you to use a larger range of cartographic imagery, which attracts users. At the same time, there are few examples of the creation of atlases of geoenvironmental issues both in paper and in digital form, so the article discusses actual problems in this area. The views of various scientists on the nature of geoenvironmental atlas are characterized. It is shown that atlases of geoenvironmental content should have in their structure basic maps of such subjects: physical geography (hypsometric, geological, tectonic, hydrogeological, geomorphological, soil, hydrological, meteorological, biogeographical, etc.; Socio-economic (demographic, labor resource potential, health, industry, agrogeography, forestry, water management, mining, recreation and tourism, etc.; Ecological (ecology-geomorphological, ecology-geological, hydroecological, soil-ecological, bioecological, landscape-ecological, air pollution, medical-ecological, sanitary-epidemiological, etc.; Applied maps (recommendations aimed at solving geoenvironmental problems, optimizing the use of natural resources and improving living conditions of the population and biota. The article considers the options of atlases classifications and thematic maps that are part of their composition, offered by domestic and foreign authors. The range of

An objective approach to determining the weight ranges of prey preferred by and accessible to the five large African carnivores.

Directory of Open Access Journals (Sweden)

Hayley S Clements

Full Text Available Broad-scale models describing predator prey preferences serve as useful departure points for understanding predator-prey interactions at finer scales. Previous analyses used a subjective approach to identify prey weight preferences of the five large African carnivores, hence their accuracy is questionable. This study uses a segmented model of prey weight versus prey preference to objectively quantify the prey weight preferences of the five large African carnivores. Based on simulations of known predator prey preference, for prey species sample sizes above 32 the segmented model approach detects up to four known changes in prey weight preference (represented by model break-points with high rates of detection (75% to 100% of simulations, depending on number of break-points and accuracy (within 1.3±4.0 to 2.7±4.4 of known break-point. When applied to the five large African carnivores, using carnivore diet information from across Africa, the model detected weight ranges of prey that are preferred, killed relative to their abundance, and avoided by each carnivore. Prey in the weight ranges preferred and killed relative to their abundance are together termed "accessible prey". Accessible prey weight ranges were found to be 14-135 kg for cheetah Acinonyx jubatus, 1-45 kg for leopard Panthera pardus, 32-632 kg for lion Panthera leo, 15-1600 kg for spotted hyaena Crocuta crocuta and 10-289 kg for wild dog Lycaon pictus. An assessment of carnivore diets throughout Africa found these accessible prey weight ranges include 88±2% (cheetah, 82±3% (leopard, 81±2% (lion, 97±2% (spotted hyaena and 96±2% (wild dog of kills. These descriptions of prey weight preferences therefore contribute to our understanding of the diet spectrum of the five large African carnivores. Where datasets meet the minimum sample size requirements, the segmented model approach provides a means of determining, and comparing, the prey weight range preferences of any carnivore

An objective approach to determining the weight ranges of prey preferred by and accessible to the five large African carnivores.

Science.gov (United States)

Clements, Hayley S; Tambling, Craig J; Hayward, Matt W; Kerley, Graham I H

2014-01-01

Broad-scale models describing predator prey preferences serve as useful departure points for understanding predator-prey interactions at finer scales. Previous analyses used a subjective approach to identify prey weight preferences of the five large African carnivores, hence their accuracy is questionable. This study uses a segmented model of prey weight versus prey preference to objectively quantify the prey weight preferences of the five large African carnivores. Based on simulations of known predator prey preference, for prey species sample sizes above 32 the segmented model approach detects up to four known changes in prey weight preference (represented by model break-points) with high rates of detection (75% to 100% of simulations, depending on number of break-points) and accuracy (within 1.3±4.0 to 2.7±4.4 of known break-point). When applied to the five large African carnivores, using carnivore diet information from across Africa, the model detected weight ranges of prey that are preferred, killed relative to their abundance, and avoided by each carnivore. Prey in the weight ranges preferred and killed relative to their abundance are together termed "accessible prey". Accessible prey weight ranges were found to be 14-135 kg for cheetah Acinonyx jubatus, 1-45 kg for leopard Panthera pardus, 32-632 kg for lion Panthera leo, 15-1600 kg for spotted hyaena Crocuta crocuta and 10-289 kg for wild dog Lycaon pictus. An assessment of carnivore diets throughout Africa found these accessible prey weight ranges include 88±2% (cheetah), 82±3% (leopard), 81±2% (lion), 97±2% (spotted hyaena) and 96±2% (wild dog) of kills. These descriptions of prey weight preferences therefore contribute to our understanding of the diet spectrum of the five large African carnivores. Where datasets meet the minimum sample size requirements, the segmented model approach provides a means of determining, and comparing, the prey weight range preferences of any carnivore species.

Wanting, liking, and preference construction.

Science.gov (United States)

Dai, Xianchi; Brendl, C Miguel; Ariely, Dan

2010-06-01

According to theories on preference construction, multiple preferences result from multiple contexts (e.g., loss vs. gain frames). This implies that people can have different representations of a preference in different contexts. Drawing on Berridge's (1999) distinction between unconscious liking and wanting, we hypothesize that people may have multiple representations of a preference toward an object even within a single context. Specifically, we propose that people can have different representations of an object's motivational value, or incentive value, versus its emotional value, or likability, even when the object is placed in the same context. Study 1 establishes a divergence between incentive value and likability of faces using behavioral measures. Studies 2A and 2B, using self-report measures, provide support for our main hypothesis that people are perfectly aware of these distinct representations and are able to access them concurrently at will. We also discuss implications of our findings for the truism that people seek pleasure and for expectancy-value theories.

Fourth-rank gravity and cosmology

International Nuclear Information System (INIS)

Marrakchi, A.L.; Tapia, V.

1992-07-01

We consider the consequences of describing the metric properties of space-time through a quartic line element. The associated ''metric'' is a fourth-rank tensor G μυλπ . In order to recover a Riemannian behaviour of the geometry it is necessary to have G μυλπ = g (μυ g λπ) . We construct a theory for the gravitational field based on the fourth-rank metric G μυλπ . In the absence of matter the fourth-rank metric becomes separable and the theory coincides with General Relativity. In the presence of matter we can maintain Riemmanianicity, but now gravitation couples, as compared to General Relativity, in a different way to matter. We develop a simple cosmological model based on a FRW metric with matter described by a perfect fluid. For the present time the field equations are compatible with k OBS = O and Ω OBS t CLAS approx. 10 20 t PLANCK approx. 10 -23 s. Our final and most important result is the fact that the entropy is an increasing function of time. When interpreted at the light of General Relativity the treatment is shown to be almost equivalent to that of the standard model of cosmology combined with the inflationary scenario. (author). 16 refs, 1 fig

Natural preference of zebrafish (Danio rerio for a dark environment

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Serra E.L.

1999-01-01

Full Text Available The zebrafish (Danio rerio has been used as a model in neuroscience but knowledge about its behavior is limited. The aim of this study was to determine the preference of this fish species for a dark or light environment. Initially we used a place preference test and in a second experiment we applied an exit latency test. A two-chamber aquarium was used for the preference test. The aquarium consisted of a black chamber and a white chamber. In the first experiment the animal was placed in the aquarium and the time spent in the two compartments was recorded for 10 min. More time was spent in the black compartment (Wilcoxon matched-pairs signed-rank test, T = 7, N1 = N2 = 18, P = 0.0001. In the second experiment the animal was placed in the black or white compartment and the time it took to go from the initial compartment to the opposite one was recorded. The test lasted a maximum of 10 min. The results showed that the animal spent more time to go from the black to the white compartment (Mann-Whitney rank sum test, T = 48, N1 = 9, N2 = 8, P<0.0230. These data suggest that this fish species has a natural preference for a dark environment and this characteristic can be very useful for the development of new behavioral paradigms for fish.

A study on subjective preference to daylit residential indoor environment using conjoint analysis

Energy Technology Data Exchange (ETDEWEB)

Cheung, H.D.; Chung, T.M. [Department of Building Services Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (China)

2008-12-15

This paper reports a study of the subjective preference to daylit indoor environment of a residential room using conjoint analysis, which is a highly reputable method used to analyze the mutual relationships among different attributes. Seven influential attributes were selected in the view of daylight performance assessment. They include 'general brightness', 'desktop brightness', 'perceived glare', 'sunlight penetration', 'quality of view', 'user friendliness of shading control' and 'impact on energy'. Each of them has two levels. A total of eight combinations (profiles) of attributes with various levels were established by adopting fractional factorial design. Subjects were asked to rank-order the eight profiles according to their preference in terms of daylit environment of a residential room. The study aims at finding out the relative impact of the seven selected attributes to the overall daylight performance and seeking an organized assessment method for a residential daylit environment. Conjoint analysis found that the seven attributes have importance level in the order of 'quality of view', 'general brightness', 'impact on energy', 'user friendliness of shading control', 'perceived glare', 'desktop brightness' and 'sunlight penetration'. (author)

VaRank: a simple and powerful tool for ranking genetic variants

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Véronique Geoffroy

2015-03-01

Full Text Available Background. Most genetic disorders are caused by single nucleotide variations (SNVs or small insertion/deletions (indels. High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians.Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients.Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

Strong orientational coordinates and orientational order parameters for symmetric objects

International Nuclear Information System (INIS)

Haji-Akbari, Amir; Glotzer, Sharon C

2015-01-01

Recent advancements in the synthesis of anisotropic macromolecules and nanoparticles have spurred an immense interest in theoretical and computational studies of self-assembly. The cornerstone of such studies is the role of shape in self-assembly and in inducing complex order. The problem of identifying different types of order that can emerge in such systems can, however, be challenging. Here, we revisit the problem of quantifying orientational order in systems of building blocks with non-trivial rotational symmetries. We first propose a systematic way of constructing orientational coordinates for such symmetric building blocks. We call the arising tensorial coordinates strong orientational coordinates (SOCs) as they fully and exclusively specify the orientation of a symmetric object. We then use SOCs to describe and quantify local and global orientational order, and spatiotemporal orientational correlations in systems of symmetric building blocks. The SOCs and the orientational order parameters developed in this work are not only useful in performing and analyzing computer simulations of symmetric molecules or particles, but can also be utilized for the efficient storage of rotational information in long trajectories of evolving many-body systems. (paper)

Firmness Perception Influences Women’s Preferences for Vaginal Suppositories

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Toral Zaveri

2014-09-01

Full Text Available Microbicides are being actively researched and developed as woman-initiated means to prevent HIV transmission during unprotected coitus. Along with safety and efficacy, assessing and improving compliance is a major area of research in microbicide development. We have developed carrageenan-based semisoft vaginal suppositories and have previously evaluated how physical properties such as firmness, size and shape influence women’s willingness to try them. Firmness has previously been quantified in terms of small-strain storage modulus, G’, however large-strain properties of the gels may also play a role in the firmness perception. In the current study we prepared two sets of suppositories with the same G’ but different elongation properties at four different G’ values (250, 2500, 12,500, 25,000 Pa: For convenience we refer to these as “brittle” and “elastic”, although these terms were never provided to study participants. In the first of two tests conducted to assess preference, women compared pairs of brittle and elastic suppositories and indicated their preference. We observed an interaction, as women preferred brittle suppositories at lower G’ (250, 2500 Pa and elastic ones at a higher G’ (25,000 Pa. In the second test, women evaluated samples across different G’, rated the ease-of-insertion and willingness-to-try and ranked the samples in order of preference. Brittle suppositories at G’ of 12,500 Pa were most preferred. In vitro studies were also conducted to measure the softening of the suppositories in contact with vaginal simulant fluid (VSF. Release of antiretroviral drug tenofovir in VSF was quantified for the brittle and elastic suppositories at G’ of 12,500 Pa to determine the effect of suppository type on release. The initial rate of release was 20% slower with elastic suppositories as compared to brittle suppositories. Understanding how different physical properties simultaneously affect women’s preferences

Low-rank coal research

Energy Technology Data Exchange (ETDEWEB)

Weber, G. F.; Laudal, D. L.

1989-01-01

This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

Higher-order neural network software for distortion invariant object recognition

Science.gov (United States)

Reid, Max B.; Spirkovska, Lilly

1991-01-01

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Analysis of Scattering by Inhomogeneous Dielectric Objects Using Higher-Order Hierarchical MoM

DEFF Research Database (Denmark)

Kim, Oleksiy S.; Jørgensen, Erik; Meincke, Peter

2003-01-01

An efficient technique for the analysis of electromagnetic scattering by arbitrary shaped inhomogeneous dielectric objects is presented. The technique is based on a higher-order method of moments (MoM) solution of the volume integral equation. This higher-order MoM solution comprises recently...... that the condition number of the resulting MoM matrix is reduced by several orders of magnitude in comparison to existing higher-order hierarchical basis functions and, consequently, an iterative solver can be applied even for high expansion orders. Numerical results demonstrate excellent agreement...

Irrational decision-making in an amoeboid organism: transitivity and context-dependent preferences.

Science.gov (United States)

Latty, Tanya; Beekman, Madeleine

2011-01-22

Most models of animal foraging and consumer choice assume that individuals make choices based on the absolute value of items and are therefore 'economically rational'. However, frequent violations of rationality by animals, including humans, suggest that animals use comparative valuation rules. Are comparative valuation strategies a consequence of the way brains process information, or are they an intrinsic feature of biological decision-making? Here, we examine the principles of rationality in an organism with radically different information-processing mechanisms: the brainless, unicellular, slime mould Physarum polycephalum. We offered P. polycephalum amoebas a choice between food options that varied in food quality and light exposure (P. polycephalum is photophobic). The use of an absolute valuation rule will lead to two properties: transitivity and independence of irrelevant alternatives (IIA). Transitivity is satisfied if preferences have a consistent, linear ordering, while IIA states that a decision maker's preference for an item should not change if the choice set is expanded. A violation of either of these principles suggests the use of comparative rather than absolute valuation rules. Physarum polycephalum satisfied transitivity by having linear preference rankings. However, P. polycephalum's preference for a focal alternative increased when a third, inferior quality option was added to the choice set, thus violating IIA and suggesting the use of a comparative valuation process. The discovery of comparative valuation rules in a unicellular organism suggests that comparative valuation rules are ubiquitous, if not universal, among biological decision makers.

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

International Nuclear Information System (INIS)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A.

2009-01-01

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

Energy Technology Data Exchange (ETDEWEB)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A. [Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta (Canada)

2009-01-15

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle. (author)

Wine consumers’ preferences in Spain: an analysis using the best-worst scaling approach

Directory of Open Access Journals (Sweden)

Tiziana de-Magistris

2014-06-01

Full Text Available Research on wine consumers’ preferences has largely been explored in the academic literature and the importance of wine attributes has been measured by rating or ranking scales. However, the most recent literature on wine preferences has applied the best-worst scaling approach to avoid the biased outcomes derived from using rating or ranking scales in surveys. This study investigates premium red wine consumers’ preferences in Spain by applying best-worst alternatives. To achieve this goal, a random parameter logit model is applied to assess the impacts of wine attributes on the probability of choosing premium quality red wine by using data from an ad-hoc survey conducted in a medium-sized Spanish city. The results suggest that some wine attributes related to past experience (i.e. it matches food followed by some related to personal knowledge (i.e. the designation of origin are valued as the most important, whereas other attributes related to the image of the New World (i.e. label or brand name are perceived as the least important or indifferent.

HONTIOR - HIGHER-ORDER NEURAL NETWORK FOR TRANSFORMATION INVARIANT OBJECT RECOGNITION

Science.gov (United States)

Spirkovska, L.

1994-01-01

Neural networks have been applied in numerous fields, including transformation invariant object recognition, wherein an object is recognized despite changes in the object's position in the input field, size, or rotation. One of the more successful neural network methods used in invariant object recognition is the higher-order neural network (HONN) method. With a HONN, known relationships are exploited and the desired invariances are built directly into the architecture of the network, eliminating the need for the network to learn invariance to transformations. This results in a significant reduction in the training time required, since the network needs to be trained on only one view of each object, not on numerous transformed views. Moreover, one hundred percent accuracy is guaranteed for images characterized by the built-in distortions, providing noise is not introduced through pixelation. The program HONTIOR implements a third-order neural network having invariance to translation, scale, and in-plane rotation built directly into the architecture, Thus, for 2-D transformation invariance, the network needs only to be trained on just one view of each object. HONTIOR can also be used for 3-D transformation invariant object recognition by training the network only on a set of out-of-plane rotated views. Historically, the major drawback of HONNs has been that the size of the input field was limited to the memory required for the large number of interconnections in a fully connected network. HONTIOR solves this problem by coarse coding the input images (coding an image as a set of overlapping but offset coarser images). Using this scheme, large input fields (4096 x 4096 pixels) can easily be represented using very little virtual memory (30Mb). The HONTIOR distribution consists of three main programs. The first program contains the training and testing routines for a third-order neural network. The second program contains the same training and testing procedures as the

Incorporating the surfing behavior of web users into PageRank

OpenAIRE

Ashyralyyev, Shatlyk

2013-01-01

Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013. Thesis (Master's) -- Bilkent University, 2013. Includes bibliographical references leaves 68-73 One of the most crucial factors that determines the effectiveness of a large-scale commercial web search engine is the ranking (i.e., order) in which web search results are presented to the end user. In modern web search engines, the skeleton for the rank...

The Possible Role of TASK Channels in Rank-Ordered Recruitment of Motoneurons in the Dorsolateral Part of the Trigeminal Motor Nucleus.

Science.gov (United States)

Okamoto, Keiko; Emura, Norihito; Sato, Hajime; Fukatsu, Yuki; Saito, Mitsuru; Tanaka, Chie; Morita, Yukako; Nishimura, Kayo; Kuramoto, Eriko; Xu Yin, Dong; Furutani, Kazuharu; Okazawa, Makoto; Kurachi, Yoshihisa; Kaneko, Takeshi; Maeda, Yoshinobu; Yamashiro, Takashi; Takada, Kenji; Toyoda, Hiroki; Kang, Youngnam

2016-01-01

Because a rank-ordered recruitment of motor units occurs during isometric contraction of jaw-closing muscles, jaw-closing motoneurons (MNs) may be recruited in a manner dependent on their soma sizes or input resistances (IRs). In the dorsolateral part of the trigeminal motor nucleus (dl-TMN) in rats, MNs abundantly express TWIK (two-pore domain weak inwardly rectifying K channel)-related acid-sensitive-K(+) channel (TASK)-1 and TASK3 channels, which determine the IR and resting membrane potential. Here we examined how TASK channels are involved in IR-dependent activation/recruitment of MNs in the rat dl-TMN by using multiple methods. The real-time PCR study revealed that single large MNs (>35 μm) expressed TASK1 and TASK3 mRNAs more abundantly compared with single small MNs (15-20 μm). The immunohistochemistry revealed that TASK1 and TASK3 channels were complementarily distributed in somata and dendrites of MNs, respectively. The density of TASK1 channels seemed to increase with a decrease in soma diameter while there were inverse relationships between the soma size of MNs and IR, resting membrane potential, or spike threshold. Dual whole-cell recordings obtained from smaller and larger MNs revealed that the recruitment of MNs depends on their IRs in response to repetitive stimulation of the presumed Ia afferents. 8-Bromoguanosine-cGMP decreased IRs in small MNs, while it hardly changed those in large MNs, and subsequently decreased the difference in spike-onset latency between the smaller and larger MNs, causing a synchronous activation of MNs. These results suggest that TASK channels play critical roles in rank-ordered recruitment of MNs in the dl-TMN.

Informed public preferences for electricity portfolios with CCS and other low-carbon technologies.

Science.gov (United States)

Fleishman, Lauren A; De Bruin, Wändi Bruine; Morgan, M Granger

2010-09-01

Public perceptions of carbon capture and sequestration (CCS) and other low-carbon electricity-generating technologies may affect the feasibility of their widespread deployment. We asked a diverse sample of 60 participants recruited from community groups in Pittsburgh, Pennsylvania to rank 10 technologies (e.g., coal with CCS, natural gas, nuclear, various renewables, and energy efficiency), and seven realistic low-carbon portfolios composed of these technologies, after receiving comprehensive and carefully balanced materials that explained the costs and benefits of each technology. Rankings were obtained in small group settings as well as individually before and after the group discussions. The ranking exercise asked participants to assume that the U.S. Congress had mandated a reduction in carbon dioxide emissions from power plants to be built in the future. Overall, rankings suggest that participants favored energy efficiency, followed by nuclear power, integrated gasification combined-cycle coal with CCS and wind. The most preferred portfolio also included these technologies. We find that these informed members of the general public preferred diverse portfolios that contained CCS and nuclear over alternatives once they fully understood the benefits, cost, and limitations of each. The materials and approach developed for this study may also have value in educating members of the general public about the challenges of achieving a low-carbon energy future. © 2010 Society for Risk Analysis.

Don’t Always Prefer My Chosen Objects: Low Level of Trait Autonomy and Autonomy Deprivation Decreases Mere Choice Effect

Science.gov (United States)

Shang, Zhe; Tao, Tuoxin; Wang, Lei

2016-01-01

Choice effect is a robust phenomenon in which even “mere choice” that does not include actual choosing actions could result in more preference for the self-chosen objects over other-chosen objects. In the current research, we proposed that autonomy would impact the mere choice effect. We conducted two studies to examine the hypothesis. The results showed that the mere choice effect measured by Implicit Association Test (IAT) significantly decreased for participants with lower levels of trait autonomy (Study 1) and when participants were primed to experience autonomy deprivation (Study 2). The theoretical and practical implications are discussed. PMID:27148132

Salient Object Detection via Structured Matrix Decomposition.

Science.gov (United States)

Peng, Houwen; Li, Bing; Ling, Haibin; Hu, Weiming; Xiong, Weihua; Maybank, Stephen J

2016-05-04

Low-rank recovery models have shown potential for salient object detection, where a matrix is decomposed into a low-rank matrix representing image background and a sparse matrix identifying salient objects. Two deficiencies, however, still exist. First, previous work typically assumes the elements in the sparse matrix are mutually independent, ignoring the spatial and pattern relations of image regions. Second, when the low-rank and sparse matrices are relatively coherent, e.g., when there are similarities between the salient objects and background or when the background is complicated, it is difficult for previous models to disentangle them. To address these problems, we propose a novel structured matrix decomposition model with two structural regularizations: (1) a tree-structured sparsity-inducing regularization that captures the image structure and enforces patches from the same object to have similar saliency values, and (2) a Laplacian regularization that enlarges the gaps between salient objects and the background in feature space. Furthermore, high-level priors are integrated to guide the matrix decomposition and boost the detection. We evaluate our model for salient object detection on five challenging datasets including single object, multiple objects and complex scene images, and show competitive results as compared with 24 state-of-the-art methods in terms of seven performance metrics.

The Cantor-Bendixson Rank of Certain Bridgeland-Smith Stability Conditions

Science.gov (United States)

Aulicino, David

2018-01-01

We provide a novel proof that the set of directions that admit a saddle connection on a meromorphic quadratic differential with at least one pole of order at least two is closed, which generalizes a result of Bridgeland and Smith, and Gaiotto, Moore, and Neitzke. Secondly, we show that this set has finite Cantor-Bendixson rank and give a tight bound. Finally, we present a family of surfaces realizing all possible Cantor-Bendixson ranks. The techniques in the proof of this result exclusively concern Abelian differentials on Riemann surfaces, also known as translation surfaces. The concept of a "slit translation surface" is introduced as the primary tool for studying meromorphic quadratic differentials with higher order poles.

Identifying online user reputation in terms of user preference

Science.gov (United States)

Dai, Lu; Guo, Qiang; Liu, Xiao-Lu; Liu, Jian-Guo; Zhang, Yi-Cheng

2018-03-01

Identifying online user reputation is significant for online social systems. In this paper, taking into account the preference physics of online user collective behaviors, we present an improved group-based rating method for ranking online user reputation based on the user preference (PGR). All the ratings given by each specific user are mapped to the same rating criteria. By grouping users according to their mapped ratings, the online user reputation is calculated based on the corresponding group sizes. Results for MovieLens and Netflix data sets show that the AUC values of the PGR method can reach 0.9842 (0.9493) and 0.9995 (0.9987) for malicious (random) spammers, respectively, outperforming the results generated by the traditional group-based method, which indicates that the online preference plays an important role for measuring user reputation.

A C++11 implementation of arbitrary-rank tensors for high-performance computing

Science.gov (United States)

Aragón, Alejandro M.

2014-11-01

This article discusses an efficient implementation of tensors of arbitrary rank by using some of the idioms introduced by the recently published C++ ISO Standard (C++11). With the aims at providing a basic building block for high-performance computing, a single Array class template is carefully crafted, from which vectors, matrices, and even higher-order tensors can be created. An expression template facility is also built around the array class template to provide convenient mathematical syntax. As a result, by using templates, an extra high-level layer is added to the C++ language when dealing with algebraic objects and their operations, without compromising performance. The implementation is tested running on both CPU and GPU.

Social variables affecting mate preferences, copulation and reproductive outcome in a pack of free-ranging dogs.

Directory of Open Access Journals (Sweden)

Simona Cafazzo

Full Text Available Mating and reproductive outcome is often determined by the simultaneous operation of different mechanisms like intra-sexual competition, mating preferences and sexual coercion. The present study investigated how social variables affected mating outcome in a pack of free-ranging dogs, a species supposed to have lost most features of the social system of wolves during domestication. We found that, although the pack comprised multiple breeding individuals, both male copulation success and female reproductive success were positively influenced by a linear combination of dominance rank, age and leadership. Our results also suggest that mate preferences affect mating outcome by reinforcing the success of most dominant individuals. In particular, during their oestrous period bitches clearly searched for the proximity of high-ranking males who displayed affiliative behaviour towards them, while they were more likely to reject the males who intimidated them. At the same time, male courting effort and male-male competition for receptive females appeared to be stronger in the presence of higher-ranking females, suggesting a male preference for dominant females. To our knowledge, these results provide the first clear evidence of social regulation of reproductive activities in domestic dogs, and suggest that some common organizing mechanisms may contribute to shape the social organization of both dogs and wolves.

Grooming up the hierarchy: the exchange of grooming and rank-related benefits in a new world primate.

Directory of Open Access Journals (Sweden)

Barbara Tiddi

Full Text Available Seyfarth's model assumes that female primates derive rank-related benefits from higher-ranking females in exchange for grooming. As a consequence, the model predicts females prefer high-ranking females as grooming partners and compete for the opportunity to groom them. Therefore, allogrooming is expected to be directed up the dominance hierarchy and to occur more often between females with adjacent ranks. Although data from Old World primates generally support the model, studies on the relation between grooming and dominance rank in the New World genus Cebus have found conflicting results, showing considerable variability across groups and species. In this study, we investigated the pattern of grooming in wild tufted capuchin females (Cebus apella nigritus in Iguazú National Park, Argentina by testing both the assumption (i.e., that females gain rank-related return benefits from grooming and predictions (i.e., that females direct grooming up the dominance hierarchy and the majority of grooming occurs between females with adjacent ranks of Seyfarth's model. Study subjects were 9 adult females belonging to a single group. Results showed that grooming was given in return for tolerance during naturally occurring feeding, a benefit that higher-ranking females can more easily grant. Female grooming was directed up the hierarchy and was given more often to partners with similar rank. These findings provide supporting evidence for both the assumption and predictions of Seyfarth's model and represent, more generally, the first evidence of reciprocal behavioural interchanges driven by rank-related benefits in New World female primates.

Grooming up the hierarchy: the exchange of grooming and rank-related benefits in a new world primate.

Science.gov (United States)

Tiddi, Barbara; Aureli, Filippo; Schino, Gabriele

2012-01-01

Seyfarth's model assumes that female primates derive rank-related benefits from higher-ranking females in exchange for grooming. As a consequence, the model predicts females prefer high-ranking females as grooming partners and compete for the opportunity to groom them. Therefore, allogrooming is expected to be directed up the dominance hierarchy and to occur more often between females with adjacent ranks. Although data from Old World primates generally support the model, studies on the relation between grooming and dominance rank in the New World genus Cebus have found conflicting results, showing considerable variability across groups and species. In this study, we investigated the pattern of grooming in wild tufted capuchin females (Cebus apella nigritus) in Iguazú National Park, Argentina by testing both the assumption (i.e., that females gain rank-related return benefits from grooming) and predictions (i.e., that females direct grooming up the dominance hierarchy and the majority of grooming occurs between females with adjacent ranks) of Seyfarth's model. Study subjects were 9 adult females belonging to a single group. Results showed that grooming was given in return for tolerance during naturally occurring feeding, a benefit that higher-ranking females can more easily grant. Female grooming was directed up the hierarchy and was given more often to partners with similar rank. These findings provide supporting evidence for both the assumption and predictions of Seyfarth's model and represent, more generally, the first evidence of reciprocal behavioural interchanges driven by rank-related benefits in New World female primates.

University Programme Preferences of High School Science Students in Singapore and Reasons that Matter in their Preferences: A Rasch analysis

Science.gov (United States)

Oon, Pey-Tee; Subramaniam, R.

2015-01-01

This study explored an under-researched area in science education-the university programmes preferred by high school students who take physical science subjects and the reasons that matter in their preferences. A total of 1,071 upper secondary and pre-university students in Singapore, who take physical science subjects among their range of subjects, participated in this study. A survey method was adopted and the Rasch model was used to analyse the data. Overall, Business Studies was ranked as the predominant choice; nonetheless, scientific programmes such as Science, Engineering, and Mathematics are generally still well liked by the students. When gender differences were examined, we found that students largely followed gender-typical programme preferences, in which males tend to incline towards Engineering while females tend to incline towards Arts and Social Sciences. Students prefer a university programme based on their individual interest and ability, with career aspiration and remuneration coming next. Interestingly, females place greater emphasis on career aspiration than males. Some implications of the study are discussed.

Multimodal biometric system using rank-level fusion approach.

Science.gov (United States)

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.

Assessing the Readability of Medical Documents: A Ranking Approach.

Science.gov (United States)

Zheng, Jiaping; Yu, Hong

2018-03-23

The use of electronic health record (EHR) systems with patient engagement capabilities, including viewing, downloading, and transmitting health information, has recently grown tremendously. However, using these resources to engage patients in managing their own health remains challenging due to the complex and technical nature of the EHR narratives. Our objective was to develop a machine learning-based system to assess readability levels of complex documents such as EHR notes. We collected difficulty ratings of EHR notes and Wikipedia articles using crowdsourcing from 90 readers. We built a supervised model to assess readability based on relative orders of text difficulty using both surface text features and word embeddings. We evaluated system performance using the Kendall coefficient of concordance against human ratings. Our system achieved significantly higher concordance (.734) with human annotators than did a baseline using the Flesch-Kincaid Grade Level, a widely adopted readability formula (.531). The improvement was also consistent across different disease topics. This method's concordance with an individual human user's ratings was also higher than the concordance between different human annotators (.658). We explored methods to automatically assess the readability levels of clinical narratives. Our ranking-based system using simple textual features and easy-to-learn word embeddings outperformed a widely used readability formula. Our ranking-based method can predict relative difficulties of medical documents. It is not constrained to a predefined set of readability levels, a common design in many machine learning-based systems. Furthermore, the feature set does not rely on complex processing of the documents. One potential application of our readability ranking is personalization, allowing patients to better accommodate their own background knowledge. ©Jiaping Zheng, Hong Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 23.03.2018.

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

2014-01-01

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

The effect of pressure and quadrupolar interactions on the nematic-isotropic transition properties: Numerical results for a system of prolate ellipsoids including second and fourth rank orientational order parameters

International Nuclear Information System (INIS)

Singh, K.

1992-10-01

The theory of isotropic-nematic transition described in earlier papers is applied to investigate the influence of quadrupolar interactions and pressure on the stability, ordering and thermodynamic transition properties retaining second and fourth rank orientational order parameters in the calculation for a system of hard ellipsoids of revolution characterized by its length-to-width ratio (x 0 = 2a/2b). Results are in accordance with experimental observations. (author). 9 refs, 1 tab

Activity of coals of different rank to ozone

Directory of Open Access Journals (Sweden)

Vladimir Kaminskii

2017-12-01

Full Text Available Coals of different rank were studied in order to characterize their activity to ozone decomposition and changes of their properties at interaction with ozone. Effects of coal rank on their reactivity to ozone were described by means of kinetic modeling. To this end, a model was proposed for evaluation of kinetic parameters describing coals activity to ozone. This model considers a case when coals surface properties change during interaction with ozone (deactivation processes. Two types of active sites (zones at the surface that are able to decompose ozone were introduced in the model differing by their deactivation rates. Activity of sites that are being deactivated at relatively higher rate increases with rank from 2400 1/min for lignite to 4000 1/min for anthracite. Such dependence is related to increase of micropores share in coals structure that grows from lignites to anthracites. Parameter characterizing initial total activity of coals to ozone decomposition also depends on rank by linear trend and vary between 2.40 for lignites up to 4.98 for anthracite. The proposed model could further be used in studies of coals oxidation processes and tendency to destruction under the weathering and oxidation conditions.

A Review of Studies on Color Preference%颜色偏好研究进展

Institute of Scientific and Technical Information of China (English)

孙青青; 陈本友; 赵伶俐

2011-01-01

.Usually people used geometry color cards,color words to research color,and meaningful geometry color cards,life items to study specific color.Both required the subjects to choose their favor colors or to rank colors according to their preference.color preference research reveals people＇s general color preferences.Specific color preference reflects the favorite color of particular objects in life,highlighting the relationship between the subject and the object.Compared with the study of color preference,specific color preference is more specific and practical.The studies have found that people show preference for both,but neither is the same,and the favorite colors of different objects are also different.Color preference is influenced by many factors,such as personality,gender,age,nationality, etc.Researchers have made different theoretical interpretation of color preference such as biological mechanism,color emotion, and put forward the ecological valence theory.Although the researches have achieved a lot,some limitations have been found in the previous research＇s content,materials and subjects.Research content is simple：people often not only accept monochrome in their daily life,but face more complex stimulations.Therefore,only monochrome color preference research is not enough.Future research should use much more complex color materials.Furthermore,the research neglected color attributes,color appearance modes,and environment, which may affect color preferences.In addition,most of researches adopted subjective survey methods.Recently,the research use more objective methods,such as eye movements,which may be the research direction in the future.

People learn other people's preferences through inverse decision-making.

Science.gov (United States)

Jern, Alan; Lucas, Christopher G; Kemp, Charles

2017-11-01

People are capable of learning other people's preferences by observing the choices they make. We propose that this learning relies on inverse decision-making-inverting a decision-making model to infer the preferences that led to an observed choice. In Experiment 1, participants observed 47 choices made by others and ranked them by how strongly each choice suggested that the decision maker had a preference for a specific item. An inverse decision-making model generated predictions that were in accordance with participants' inferences. Experiment 2 replicated and extended a previous study by Newtson (1974) in which participants observed pairs of choices and made judgments about which choice provided stronger evidence for a preference. Inverse decision-making again predicted the results, including a result that previous accounts could not explain. Experiment 3 used the same method as Experiment 2 and found that participants did not expect decision makers to be perfect utility-maximizers. Copyright © 2017 Elsevier B.V. All rights reserved.

Ranking of delay factors in construction projects after Egyptian revolution

Directory of Open Access Journals (Sweden)

Remon Fayek Aziz

2013-09-01

Full Text Available Time is one of the major considerations throughout project management life cycle and can be regarded as one of the most important parameters of a project and the driving force of project success. Time delay is a very frequent phenomenon and is almost associated with nearly all constructing projects. However, little effort has been made to curtail the phenomenon, this research work attempts to identify, investigate, and rank factors perceived to affect delays in the Egyptian construction projects with respect to their relative importance so as to proffer possible ways of coping with this phenomenon. To achieve this objective, researcher invited practitioners and experts, comprising a statistically representative sample to participate in a structured questionnaire survey. Brain storming was taken into consideration, through which a number of delay factors were identified in construction projects. Totally, ninety-nine (99 factors were short-listed to be made part of the questionnaire survey and were identified and categorized into nine (9 major categories. The survey was conducted with experts and representatives from private, public, and local general construction firms. The data were analyzed using Relative Importance Index (RII, ranking and simple percentages. Ranking of factors and categories was demonstrated according to their importance level on delay, especially after 25/1/2011 (Egyptian revolution. According to the case study results, the most contributing factors and categories (those need attention to delays were discussed, and some recommendations were made in order to minimize and control delays in construction projects. Also, this paper can serve as a guide for all construction parties with effective management in construction projects to achieve a competitive level of quality and a time effective project.

Development of a health effects based priority ranking system for air emissions reductions from oil refineries in Canada

International Nuclear Information System (INIS)

McColl, S.; Gower, S.; Hicks, J.; Shortreed, J.; Craig, L.

2004-01-01

This paper presents the concept and methodologies behind the development of a health effects priority ranking tool for the reduction of air emissions from oil refineries. The Health Effects Indicators Decision Index- Versions 2 (Heidi II) was designed to assist policy makers in prioritizing air emissions reductions on the basis of estimated risk to human health. Inputs include facility level rankings of potential health impacts associated with carcinogenic air toxics, non-carcinogenic air toxics and criteria air contaminants for each of the 20 refineries in Canada. Rankings of estimated health impacts are presented on predicted incidence of health effects. Heidi II considers site-specific annual pollutant emission data, ambient air concentrations associated with releases and concentration response functions for various types of health effects. Additional data includes location specific background air concentrations, site-specific population densities, and the baseline incidence of different health effects endpoints, such as cancer, non-cancer illnesses and cardiorespiratory illnesses and death. Air pollutants include the 29 air toxics reported annually in Environment Canada's National Pollutant Release Inventory. Three health impact ranking outputs are provided for each facility: ranking of pollutants based on predicted number of annual cases of health effects; ranking of pollutants based on simplified Disability Adjusted Life Years (DALYs); and ranking of pollutants based on more complex DALYs that consider types of cancer, systemic disease or types of cardiopulmonary health effects. Rankings rely on rough statistical estimates of predicted incidence rates for health endpoints. The models used to calculate rankings can provide useful guidance by comparing estimated health impacts. Heidi II has demonstrated that it is possible to develop a consistent and objective approach for ranking priority reductions of air emissions. Heidi II requires numerous types and

A face for all seasons: Searching for context-specific leadership traits and discovering a general preference for perceived health

Science.gov (United States)

Spisak, Brian R.; Blaker, Nancy M.; Lefevre, Carmen E.; Moore, Fhionna R.; Krebbers, Kleis F. B.

2014-01-01

Previous research indicates that followers tend to contingently match particular leader qualities to evolutionarily consistent situations requiring collective action (i.e., context-specific cognitive leadership prototypes) and information processing undergoes categorization which ranks certain qualities as first-order context-general and others as second-order context-specific. To further investigate this contingent categorization phenomenon we examined the “attractiveness halo”—a first-order facial cue which significantly biases leadership preferences. While controlling for facial attractiveness, we independently manipulated the underlying facial cues of health and intelligence and then primed participants with four distinct organizational dynamics requiring leadership (i.e., competition vs. cooperation between groups and exploratory change vs. stable exploitation). It was expected that the differing requirements of the four dynamics would contingently select for relatively healthier- or intelligent-looking leaders. We found perceived facial intelligence to be a second-order context-specific trait—for instance, in times requiring a leader to address between-group cooperation—whereas perceived health is significantly preferred across all contexts (i.e., a first-order trait). The results also indicate that facial health positively affects perceived masculinity while facial intelligence negatively affects perceived masculinity, which may partially explain leader choice in some of the environmental contexts. The limitations and a number of implications regarding leadership biases are discussed. PMID:25414653

A face for all seasons: Searching for context-specific leadership traits and discovering a general preference for perceived health

Directory of Open Access Journals (Sweden)

Brian R. Spisak

2014-11-01

Full Text Available Previous research indicates that followers tend to contingently match particular leader qualities to evolutionarily consistent situations requiring collective action (i.e., context-specific cognitive leadership prototypes and information processing undergoes categorization which ranks certain qualities as first-order context-general and others as second-order context-specific. To further investigate this contingent categorization phenomenon we examined the attractiveness halo – a first-order facial cue which significantly biases leadership preferences. While controlling for facial attractiveness, we independently manipulated the underlying facial cues of health and intelligence and then primed participants with four distinct organizational dynamics requiring leadership (i.e., competition versus cooperation between groups and exploratory change versus stable exploitation. It was expected that the differing requirements of the four dynamics would contingently select for relatively healthier- or intelligent-looking leaders. We found perceived facial intelligence to be a second-order context-specific trait – for instance, in times requiring a leader to address between-group cooperation – whereas perceived health is significantly preferred across all contexts (i.e., a first-order trait. The results also indicate that facial health positively affects perceived masculinity while facial intelligence negatively affects perceived masculinity, which may partially explain leader choice in some of the environmental contexts. The limitations and a number of implications regarding leadership biases are discussed.

Do objective neighbourhood characteristics relate to residents' preferences for certain sports locations? A cross-sectional study using a discrete choice modelling approach

NARCIS (Netherlands)

Deelen, Ineke; Jansen, Marijke; Dogterom, Nico J.; Kamphuis, Carlijn B.M.; Ettema, Dick

2017-01-01

Background: The number of sports facilities, sports clubs, or city parks in a residential neighbourhood may affect the likelihood that people participate in sports and their preferences for a certain sports location. This study aimed to assess whether objective physical and socio-spatial

Quantitative assessments of municipal waste management systems: using different indicators to compare and rank programs in New York State.

Science.gov (United States)

Greene, Krista L; Tonjes, David J

2014-04-01

The primary objective of waste management technologies and policies in the United States is to reduce the harmful environmental impacts of waste, particularly those relating to energy consumption and climate change. Performance indicators are frequently used to evaluate the environmental quality of municipal waste systems, as well as to compare and rank programs relative to each other in terms of environmental performance. However, there currently is no consensus on the best indicator for performing these environmental evaluations. The purpose of this study is to examine the common performance indicators used to assess the environmental benefits of municipal waste systems to determine if there is agreement between them regarding which system performs best environmentally. Focus is placed on how indicator selection influences comparisons between municipal waste management programs and subsequent system rankings. The waste systems of ten municipalities in the state of New York, USA, were evaluated using each common performance indicator and Spearman correlations were calculated to see if there was a significant association between system rank orderings. Analyses showed that rank orders of waste systems differ substantially when different indicators are used. Therefore, comparative system assessments based on indicators should be considered carefully, especially those intended to gauge environmental quality. Insight was also gained into specific factors which may lead to one system achieving higher rankings than another. However, despite the insufficiencies of indicators for comparative quality assessments, they do provide important information for waste managers and they can assist in evaluating internal programmatic performance and progress. To enhance these types of assessments, a framework for scoring indicators based on criteria that evaluate their utility and value for system evaluations was developed. This framework was used to construct an improved model for

Predicting consumer liking and preference based on emotional responses and sensory perception: A study with basic taste solutions.

Science.gov (United States)

Samant, Shilpa S; Chapko, Matthew J; Seo, Han-Seok

2017-10-01

Traditional methods of sensory testing focus on capturing information about multisensory perceptions, but do not necessarily measure emotions elicited by these food and beverages. The objective of this study was to develop an optimum model of predicting overall liking (rating) and preference (choice) based on taste intensity and evoked emotions. One hundred and two participants (51 females) were asked to taste water, sucrose, citric acid, salt, and caffeine solutions. Their emotional responses toward each sample were measured by a combination of a self-reported emotion questionnaire (EsSense25), facial expressions, and autonomic nervous system (ANS) responses. In addition, their perceived intensity and overall liking were measured. After a break, participants re-tasted the samples and ranked them according to their preference. The results showed that emotional responses measured using self-reported emotion questionnaire and facial expression analysis along with perceived taste intensity performed best to predict overall liking as well as preference, while ANS measures showed limited contribution. Contrary to some previous research, this study demonstrated that not only negative emotions, but also positive ones could help predict consumer liking and preference. In addition, since there were subtle differences in the prediction models of overall liking and preference, both aspects should be taken into account to understand consumer behavior. In conclusion, combination of evoked emotions along with sensory perception could help better understand consumer acceptance as well as preference toward basic taste solutions. Published by Elsevier Ltd.

Time evolution of Wikipedia network ranking

Science.gov (United States)

Eom, Young-Ho; Frahm, Klaus M.; Benczúr, András; Shepelyansky, Dima L.

2013-12-01

We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003-2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007-2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80% of top universities of Shanghai ranking during the considered time period.

Semantic Descriptor Ranking: A Quantitative Method for Evaluating Qualitative Verbal Reports of Visual Cognition in the Laboratory or the Clinic

Directory of Open Access Journals (Sweden)

Matthew eMaestri

2014-03-01

Full Text Available For scientific, clinical, and machine learning purposes alike, it is desirable to quantify the verbal reports of high-level visual percepts. Methods to do this simply do not exist at present. Here we propose a novel methodological principle to help fill this gap, and provide empirical evidence designed to serve as the initial ‘proof’ of this principle. In the proposed method, subjects view images real-world scenes and describe, in their own words, what they saw. The verbal description is independently evaluated by several evaluators. Each evaluator assigns a rank score to the subject’s description of each visual object in each image using a novel ranking principle, which takes advantage of the well-known fact that semantic descriptions of real-life objects and scenes can usually be rank-ordered. Thus, for instance, ‘animal’, ‘dog’, and ‘retriever’ can be regarded as increasingly finer-level, and therefore higher-ranking, descriptions of a given object. These numeric scores can preserve the richness of the original verbal description, and can be subsequently evaluated using conventional statistical procedures. We describe an exemplar implementation of this method and empirical data that show its feasibility. With appropriate future standardization and validation, this novel method can serve as an important tool to help quantify the subjective experience of the visual world. In addition to being a novel, potentially powerful testing tool, our method also represents, to our knowledge, the only available method for numerically representing verbal accounts of real-world experience. Given that its minimal requirements, i.e., a verbal description and the ground truth that elicited the description, our method has a wide variety of potential real-world applications.

Preference score of units in the presence of ordinal data

International Nuclear Information System (INIS)

Jahanshahloo, G.R.; Soleimani-damaneh, M.; Mostafaee, A.

2009-01-01

This study deals with the ordinal data in the performance analysis framework and provides a weight-restricted DEA model to obtain the preference score of each unit under assessment. The obtained scores are used to rank DMUs. Furthermore, to decrease the complexity of the provided model, the number of the constraints is decreased by some linear transformations

Preference score of units in the presence of ordinal data

Energy Technology Data Exchange (ETDEWEB)

Jahanshahloo, G.R.; Soleimani-damaneh, M. [Department of Mathematics, Teacher Training University, Tehran (Iran, Islamic Republic of); Mostafaee, A. [Department of Mathematics, North-Tehran Branch, Islamic Azad University, Tehran (Iran, Islamic Republic of)], E-mail: mostafaee_m@yahoo.com

2009-01-15

This study deals with the ordinal data in the performance analysis framework and provides a weight-restricted DEA model to obtain the preference score of each unit under assessment. The obtained scores are used to rank DMUs. Furthermore, to decrease the complexity of the provided model, the number of the constraints is decreased by some linear transformations.

Zero forcing parameters and minimum rank problems

NARCIS (Netherlands)

Barioli, F.; Barrett, W.; Fallat, S.M.; Hall, H.T.; Hogben, L.; Shader, B.L.; Driessche, van den P.; Holst, van der H.

2010-01-01

The zero forcing number Z(G), which is the minimum number of vertices in a zero forcing set of a graph G, is used to study the maximum nullity/minimum rank of the family of symmetric matrices described by G. It is shown that for a connected graph of order at least two, no vertex is in every zero

A multiple criteria decision making for raking alternatives using preference relation matrix based on intuitionistic fuzzy sets

Directory of Open Access Journals (Sweden)

Mehdi Bahramloo

2013-10-01

Full Text Available Ranking various alternatives has been under investigation and there are literally various methods and techniques for making a decision based on various criteria. One of the primary concerns on ranking methodologies such as analytical hierarchy process (AHP is that decision makers cannot express his/her feeling in crisp form. Therefore, we need to use linguistic terms to receive the relative weights for comparing various alternatives. In this paper, we discuss ranking different alternatives based on the implementation of preference relation matrix based on intuitionistic fuzzy sets.

A controllability test for general first-order representations

NARCIS (Netherlands)

U. Helmke; J. Rosenthal; J.M. Schumacher (Hans)

1995-01-01

textabstractIn this paper we derive a new controllability rank test for general first-order representations. The criterion generalizes the well-known controllability rank test for linear input-state systems as well as a controllability rank test by Mertzios et al. for descriptor systems.

Pharmacy students' preference for using mobile devices in a clinical setting for practice-related tasks.

Science.gov (United States)

Richard, Craig A H; Hastings, Justine F; Bryant, Jennifer E

2015-03-25

To examine pharmacy students' ownership of, use of, and preference for using a mobile device in a practice setting. Eighty-one pharmacy students were recruited and completed a pretest that collected information about their demographics and mobile devices and also had them rank the iPhone, iPad mini, and iPad for preferred use in a pharmacy practice setting. Students used the 3 devices to perform pharmacy practice-related tasks and then completed a posttest to again rank the devices for preferred use in a pharmacy practice setting. The iPhone was the most commonly owned mobile device (59.3% of students), and the iPad mini was the least commonly owned (18.5%). About 70% of the students used their mobile devices at least once a week in a pharmacy practice setting. The iPhone was the most commonly used device in a practice setting (46.9% of students), and the iPod Touch was the least commonly used device (1.2%). The iPad mini was the most preferred device for use in a pharmacy practice setting prior to performing pharmacy practice-related tasks (49.4% of students), and was preferred by significantly more students after performing the tasks (70.4%). Pharmacy students commonly use their mobile devices in pharmacy practice settings and most selected the iPad mini as the preferred device for use in a practice setting even though it was the device owned by the fewest students.

Best Friends: Alliances, Friend Ranking, and the MySpace Social Network.

Science.gov (United States)

DeScioli, Peter; Kurzban, Robert; Koch, Elizabeth N; Liben-Nowell, David

2011-01-01

Like many topics of psychological research, the explanation for friendship is at once intuitive and difficult to address empirically. These difficulties worsen when one seeks, as we do, to go beyond "obvious" explanations ("humans are social creatures") to ask deeper questions, such as "What is the evolved function of human friendship?" In recent years, however, a new window into human behavior has opened as a growing fraction of people's social activity has moved online, leaving a wealth of digital traces behind. One example is a feature of the MySpace social network that allows millions of users to rank their "Top Friends." In this study, we collected over 10 million people's friendship decisions from MySpace to test predictions made by hypotheses about human friendship. We found particular support for the alliance hypothesis, which holds that human friendship is caused by cognitive systems that function to create alliances for potential disputes. Because an ally's support can be undermined by a stronger outside relationship, the alliance model predicts that people will prefer partners who rank them above other friends. Consistent with the alliance model, we found that an individual's choice of best friend in MySpace is strongly predicted by how partners rank that individual. © The Author(s) 2011.

Crawling and walking infants encounter objects differently in a multi-target environment.

Science.gov (United States)

Dosso, Jill A; Boudreau, J Paul

2014-10-01

From birth, infants move their bodies in order to obtain information and stimulation from their environment. Exploratory movements are important for the development of an infant's understanding of the world and are well established as being key to cognitive advances. Newly acquired motor skills increase the potential actions available to the infant. However, the way that infants employ potential actions in environments with multiple potential targets is undescribed. The current work investigated the target object selections of infants across a range of self-produced locomotor experience (11- to 14-month-old crawlers and walkers). Infants repeatedly accessed objects among pairs of objects differing in both distance and preference status, some requiring locomotion. Overall, their object actions were found to be sensitive to object preference status; however, the role of object distance in shaping object encounters was moderated by movement status. Crawlers' actions appeared opportunistic and were biased towards nearby objects while walkers' actions appeared intentional and were independent of object position. Moreover, walkers' movements favoured preferred objects more strongly for children with higher levels of self-produced locomotion experience. The multi-target experimental situation used in this work parallels conditions faced by foraging organisms, and infants' behaviours were discussed with respect to optimal foraging theory. There is a complex interplay between infants' agency, locomotor experience, and environment in shaping their motor actions. Infants' movements, in turn, determine the information and experiences offered to infants by their micro-environment.

Multiplex PageRank.

Directory of Open Access Journals (Sweden)

Arda Halu

Full Text Available Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Multiplex PageRank.

Science.gov (United States)

Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

2013-01-01

Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Outlier Ranking via Subspace Analysis in Multiple Views of the Data

DEFF Research Database (Denmark)

Muller, Emmanuel; Assent, Ira; Iglesias, Patricia

2012-01-01

, a novel outlier ranking concept. Outrank exploits subspace analysis to determine the degree of outlierness. It considers different subsets of the attributes as individual outlier properties. It compares clustered regions in arbitrary subspaces and derives an outlierness score for each object. Its...... principled integration of multiple views into an outlierness measure uncovers outliers that are not detectable in the full attribute space. Our experimental evaluation demonstrates that Outrank successfully determines a high quality outlier ranking, and outperforms state-of-the-art outlierness measures....

Improving Ranking Using Quantum Probability

OpenAIRE

Melucci, Massimo

2011-01-01

The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

Efficient Tensor Completion for Color Image and Video Recovery: Low-Rank Tensor Train.

Science.gov (United States)

Bengua, Johann A; Phien, Ho N; Tuan, Hoang Duong; Do, Minh N

2017-05-01

This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its definition from a well-balanced matricization scheme. Accordingly, new optimization formulations for tensor completion are proposed as well as two new algorithms for their solution. The first one called simple low-rank tensor completion via TT (SiLRTC-TT) is intimately related to minimizing a nuclear norm based on TT rank. The second one is from a multilinear matrix factorization model to approximate the TT rank of a tensor, and is called tensor completion by parallel matrix factorization via TT (TMac-TT). A tensor augmentation scheme of transforming a low-order tensor to higher orders is also proposed to enhance the effectiveness of SiLRTC-TT and TMac-TT. Simulation results for color image and video recovery show the clear advantage of our method over all other methods.

A scoring mechanism for the rank aggregation of network robustness

Science.gov (United States)

Yazdani, Alireza; Dueñas-Osorio, Leonardo; Li, Qilin

2013-10-01

To date, a number of metrics have been proposed to quantify inherent robustness of network topology against failures. However, each single metric usually only offers a limited view of network vulnerability to different types of random failures and targeted attacks. When applied to certain network configurations, different metrics rank network topology robustness in different orders which is rather inconsistent, and no single metric fully characterizes network robustness against different modes of failure. To overcome such inconsistency, this work proposes a multi-metric approach as the basis of evaluating aggregate ranking of network topology robustness. This is based on simultaneous utilization of a minimal set of distinct robustness metrics that are standardized so to give way to a direct comparison of vulnerability across networks with different sizes and configurations, hence leading to an initial scoring of inherent topology robustness. Subsequently, based on the inputs of initial scoring a rank aggregation method is employed to allocate an overall ranking of robustness to each network topology. A discussion is presented in support of the presented multi-metric approach and its applications to more realistically assess and rank network topology robustness.

How Many Alternatives Can Be Ranked? A Comparison of the Paired Comparison and Ranking Methods.

Science.gov (United States)

Ock, Minsu; Yi, Nari; Ahn, Jeonghoon; Jo, Min-Woo

2016-01-01

To determine the feasibility of converting ranking data into paired comparison (PC) data and suggest the number of alternatives that can be ranked by comparing a PC and a ranking method. Using a total of 222 health states, a household survey was conducted in a sample of 300 individuals from the general population. Each respondent performed a PC 15 times and a ranking method 6 times (two attempts of ranking three, four, and five health states, respectively). The health states of the PC and the ranking method were constructed to overlap each other. We converted the ranked data into PC data and examined the consistency of the response rate. Applying probit regression, we obtained the predicted probability of each method. Pearson correlation coefficients were determined between the predicted probabilities of those methods. The mean absolute error was also assessed between the observed and the predicted values. The overall consistency of the response rate was 82.8%. The Pearson correlation coefficients were 0.789, 0.852, and 0.893 for ranking three, four, and five health states, respectively. The lowest mean absolute error was 0.082 (95% confidence interval [CI] 0.074-0.090) in ranking five health states, followed by 0.123 (95% CI 0.111-0.135) in ranking four health states and 0.126 (95% CI 0.113-0.138) in ranking three health states. After empirically examining the consistency of the response rate between a PC and a ranking method, we suggest that using five alternatives in the ranking method may be superior to using three or four alternatives. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Combinatoric Models of Information Retrieval Ranking Methods and Performance Measures for Weakly-Ordered Document Collections

Science.gov (United States)

Church, Lewis

2010-01-01

This dissertation answers three research questions: (1) What are the characteristics of a combinatoric measure, based on the Average Search Length (ASL), that performs the same as a probabilistic version of the ASL?; (2) Does the combinatoric ASL measure produce the same performance result as the one that is obtained by ranking a collection of…

Optimization of olive-fruit paste production using a methodological proposal based on a sensory and objective color analysis

Energy Technology Data Exchange (ETDEWEB)

Escudero-Gilete, M. L.; Melendez-Martinez, A. J.; Heredia, F. J.; Vicario, I. M.

2009-07-01

This paper deals with the optimization of the conditions to formulate paste based on olive fruits. The processing stages included: washing, blending, oil addition and preservation. Pair-comparisons and ranking tests were carried out by both a trained panel and a consumer panel to single out the preferred sample at each stage. The sensory attributes considered were taste, visual texture, texture in the mouth and overall preference. The results of the sensory analyses were processed statistically by means of ANOVA and the Friedman test to select the most appropriate processing conditions: washing for 30 minutes three times, blending at 2000 r.p.m, and the addition of 10 ml of oil. Several pasteurization conditions were assayed (62.5, 75, 85 and 95 degree centigrade for 15 minutes). No significant color differences (p < 0.05) were found for the objective color measurement (CIELAB) of the pastes submitted to the different pasteurization conditions. Based on the results of the preference test, the pasteurization conditions selected were heating at 85 degree centigrade for 15 minutes. (Author) 30 refs.

Neophilia Ranking of Scientific Journals.

Science.gov (United States)

Packalen, Mikko; Bhattacharya, Jay

2017-01-01

The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)-these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists' incentives to pursue innovative work.

A method to measure the effect of food appearance factors on children's visual preferences

DEFF Research Database (Denmark)

Kildegaard, Heidi; Olsen, Annemarie; Gabrielsen, Gorm

2011-01-01

The aim of the study was to examine children’s visual preferences for two food products; yoghurts and smoothies, by using a conjoint layout. In total, 274 children performed an incomplete ranking of 8 pictures formed by three factors each with two levels (23 design). The three food appearance...... for the eight smoothies. The children visually preferred the two products without visible fruit and colour had a large influence on visual preferences too. As regards the yoghurts, the children accepted a less simple variant whereas the most preferred smoothie was very simple. Significant synergetic effects...... between food appearance factors and segmentation factors were found. Additionally gender and ethnicity were found to be influential drivers for food choice....

Happy faces are preferred regardless of familiarity--sad faces are preferred only when familiar.

Science.gov (United States)

Liao, Hsin-I; Shimojo, Shinsuke; Yeh, Su-Ling

2013-06-01

Familiarity leads to preference (e.g., the mere exposure effect), yet it remains unknown whether it is objective familiarity, that is, repetitive exposure, or subjective familiarity that contributes to preference. In addition, it is unexplored whether and how different emotions influence familiarity-related preference. The authors investigated whether happy or sad faces are preferred or perceived as more familiar and whether this subjective familiarity judgment correlates with preference for different emotional faces. An emotional face--happy or sad--was paired with a neutral face, and participants rated the relative preference and familiarity of each of the paired faces. For preference judgment, happy faces were preferred and sad faces were less preferred, compared with neutral faces. For familiarity judgment, happy faces did not show any bias, but sad faces were perceived as less familiar than neutral faces. Item-by-item correlational analyses show preference for sad faces--but not happy faces--positively correlate with familiarity. These results suggest a direct link between positive emotion and preference, and argue at least partly against a common cause for familiarity and preference. Instead, facial expression of different emotional valence modulates the link between familiarity and preference.

A Survey on PageRank Computing

OpenAIRE

Berkhin, Pavel

2005-01-01

This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much mor...

A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production.

Science.gov (United States)

Ahmad, Farah B; Zhang, Zhanying; Doherty, William O S; O'Hara, Ian M

2015-08-01

Oleaginous microorganisms have potential to be used to produce oils as alternative feedstock for biodiesel production. Microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa), and fungi (Aspergillus oryzae and Mucor plumbeus) were investigated for their ability to produce oil from glucose, xylose and glycerol. Multi-criteria analysis (MCA) using analytic hierarchy process (AHP) and preference ranking organization method for the enrichment of evaluations (PROMETHEE) with graphical analysis for interactive aid (GAIA), was used to rank and select the preferred microorganisms for oil production for biodiesel application. This was based on a number of criteria viz., oil concentration, content, production rate and yield, substrate consumption rate, fatty acids composition, biomass harvesting and nutrient costs. PROMETHEE selected A. oryzae, M. plumbeus and R. mucilaginosa as the most prospective species for oil production. However, further analysis by GAIA Webs identified A. oryzae and M. plumbeus as the best performing microorganisms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Consumer preferences and willingness to pay for the health aspects of food

Directory of Open Access Journals (Sweden)

Simona Miškolci

2011-01-01

Full Text Available Agri-food systems in the Czech Republic are currently undergoing a profound transformation toward high-value products. Appropriate policies are needed to guide this transformation, presupposing good understanding of consumer preferences. Having established a general framework for the analysis of food choice and quality perception, second part of the paper gives overview of results of stated preference evaluation studies conducted in the Czech Republic. The objective of secondary data analysis is to evaluate consumer preferences and willingness to pay for the food quality with the special attention to an evaluation of consumer preferences for health aspects of the food. The consumers’ relative preferences toward the different dimensions of a product’s quality are measured from the consumers’ perspective via their preference scores on various dimensions of quality derived from Analytic Hierarchy Process (AHP. Price premium consumers are willing to pay for the high quality product is investigated using Contingent valuation method (CV. In general, the empirical evidence supports the hypothesis that health ensuring and enhancing characteristics together with sensorial characteristics significantly affect consumers’ preferences for food and most consumers are willing to pay a price premium in order to ensure required quality of food.

Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

Science.gov (United States)

Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

2017-11-01

This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.