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

Science.gov (United States)

Van der Fels-Klerx, H J; Van Asselt, E D; Raley, M; Poulsen, M; Korsgaard, H; Bredsdorff, L; Nauta, M; D'agostino, M; Coles, D; Marvin, H J P; Frewer, L J

2018-01-22

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 socio-economic sciences. The review used a predefined search protocol, and covered the bibliographic databases Scopus, CAB Abstracts, Web of Sciences, and PubMed over the period 1993-2013. All references deemed relevant, on the basis of predefined evaluation criteria, were included in the review, 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 (HALY), 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. The method to be used should be selected on the basis of risk manager/assessor requirements, data availability, and the characteristics of the method. Recommendations for future use and application are provided.

Advanced Acid Gas Separation Technology for the Utilization of Low Rank Coals

Energy Technology Data Exchange (ETDEWEB)

Kloosterman, Jeff

2012-12-31

Air Products has developed a potentially ground-breaking technology – Sour Pressure Swing Adsorption (PSA) – to replace the solvent-based acid gas removal (AGR) systems currently employed to separate sulfur containing species, along with CO{sub 2} and other impurities, from gasifier syngas streams. The Sour PSA technology is based on adsorption processes that utilize pressure swing or temperature swing regeneration methods. Sour PSA technology has already been shown with higher rank coals to provide a significant reduction in the cost of CO{sub 2} capture for power generation, which should translate to a reduction in cost of electricity (COE), compared to baseline CO{sub 2} capture plant design. The objective of this project is to test the performance and capability of the adsorbents in handling tar and other impurities using a gaseous mixture generated from the gasification of lower rank, lignite coal. The results of this testing are used to generate a high-level pilot process design, and to prepare a techno-economic assessment evaluating the applicability of the technology to plants utilizing these coals.

Evaluating intergenerational risks: Probabillity adjusted rank-discounted utilitarianism

OpenAIRE

Asheim, Geir B.; Zuber, Stéphane

2015-01-01

Climate policies have stochastic consequences that involve a great number of generations. This calls for evaluating social risk (what kind of societies will future people be born into) rather than individual risk (what will happen to people during their own lifetimes). As a response we propose and axiomatize probability adjusted rank-discounted critical-level generalized utilitarianism (PARDCLU), through a key axiom that requires that the social welfare order both be ethical and satisfy first...

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

Science.gov (United States)

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.

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.

Environmental restoration risk-based prioritization work package planning and risk ranking methodology. Revision 2

International Nuclear Information System (INIS)

Dail, J.L.; Nanstad, L.D.; White, R.K.

1995-06-01

This document presents the risk-based prioritization methodology developed to evaluate and rank Environmental Restoration (ER) work packages at the five US Department of Energy, Oak Ridge Field Office (DOE-ORO) sites [i.e., Oak Ridge K-25 Site (K-25), Portsmouth Gaseous Diffusion Plant (PORTS), Paducah Gaseous Diffusion Plant (PGDP), Oak Ridge National Laboratory (ORNL), and the Oak Ridge Y-12 Plant (Y-12)], the ER Off-site Program, and Central ER. This prioritization methodology was developed to support the increased rigor and formality of work planning in the overall conduct of operations within the DOE-ORO ER Program. Prioritization is conducted as an integral component of the fiscal ER funding cycle to establish program budget priorities. The purpose of the ER risk-based prioritization methodology is to provide ER management with the tools and processes needed to evaluate, compare, prioritize, and justify fiscal budget decisions for a diverse set of remedial action, decontamination and decommissioning, and waste management activities. The methodology provides the ER Program with a framework for (1) organizing information about identified DOE-ORO environmental problems, (2) generating qualitative assessments of the long- and short-term risks posed by DOE-ORO environmental problems, and (3) evaluating the benefits associated with candidate work packages designed to reduce those risks. Prioritization is conducted to rank ER work packages on the basis of the overall value (e.g., risk reduction, stakeholder confidence) each package provides to the ER Program. Application of the methodology yields individual work package ''scores'' and rankings that are used to develop fiscal budget requests. This document presents the technical basis for the decision support tools and process

Dietary risk ranking for residual antibiotics in cultured aquatic products around Tai Lake, China.

Science.gov (United States)

Song, Chao; Li, Le; Zhang, Cong; Qiu, Liping; Fan, Limin; Wu, Wei; Meng, Shunlong; Hu, Gengdong; Chen, Jiazhang; Liu, Ying; Mao, Aimin

2017-10-01

Antibiotics are widely used in aquaculture and therefore may be present as a dietary risk in cultured aquatic products. Using the Tai Lake Basin as a study area, we assessed the presence of 15 antibiotics in 5 widely cultured aquatic species using a newly developed dietary risk ranking approach. By assigning scores to each factor involved in the ranking matrices, the scores of dietary risks per antibiotic and per aquatic species were calculated. The results indicated that fluoroquinolone antibiotics posed the highest dietary risk in all aquatic species. Then, the total scores per aquatic species were summed by all 15 antibiotic scores of antibiotics, it was found that Crab (Eriocheir sinensis) had the highest dietary risks. Finally, the most concerned antibiotic category and aquatic species were selected. This study highlighted the importance of dietary risk ranking in the production and consumption of cultured aquatic products around Tai Lake. Copyright © 2017 Elsevier Inc. All rights reserved.

Conservation threats and the phylogenetic utility of IUCN Red List rankings in Incilius toads.

Science.gov (United States)

Schachat, Sandra R; Mulcahy, Daniel G; Mendelson, Joseph R

2016-02-01

Phylogenetic analysis of extinction threat is an emerging tool in the field of conservation. However, there are problems with the methods and data as commonly used. Phylogenetic sampling usually extends to the level of family or genus, but International Union for Conservation of Nature (IUCN) rankings are available only for individual species, and, although different species within a taxonomic group may have the same IUCN rank, the species may have been ranked as such for different reasons. Therefore, IUCN rank may not reflect evolutionary history and thus may not be appropriate for use in a phylogenetic context. To be used appropriately, threat-risk data should reflect the cause of extinction threat rather than the IUCN threat ranking. In a case study of the toad genus Incilius, with phylogenetic sampling at the species level (so that the resolution of the phylogeny matches character data from the IUCN Red List), we analyzed causes of decline and IUCN threat rankings by calculating metrics of phylogenetic signal (such as Fritz and Purvis' D). We also analyzed the extent to which cause of decline and threat ranking overlap by calculating phylogenetic correlation between these 2 types of character data. Incilius species varied greatly in both threat ranking and cause of decline; this variability would be lost at a coarser taxonomic resolution. We found far more phylogenetic signal, likely correlated with evolutionary history, for causes of decline than for IUCN threat ranking. Individual causes of decline and IUCN threat rankings were largely uncorrelated on the phylogeny. Our results demonstrate the importance of character selection and taxonomic resolution when extinction threat is analyzed in a phylogenetic context. © 2015 Society for Conservation Biology.

Consumer preference in ranking walking function utilizing the walking index for spinal cord injury II.

Science.gov (United States)

Patrick, M; Ditunno, P; Ditunno, J F; Marino, R J; Scivoletto, G; Lam, T; Loffree, J; Tamburella, F; Leiby, B

2011-12-01

Blinded rank ordering. To determine consumer preference in walking function utilizing the walking Index for spinal cord injury II (WISCI II) in individuals with spinal cord injury (SCI)from the Canada, the Italy and the United States of America. In all, 42 consumers with incomplete SCI (25 cervical, 12 thoracic, 5 lumbar) from Canada (12/42), Italy (14/42) and the United States of America (16/42) ranked the 20 levels of the WISCI II scale by their individual preference for walking. Subjects were blinded to the original ranking of the WISCI II scale by clinical scientists. Photographs of each WISCI II level used in a previous pilot study were randomly shuffled and rank ordered. Percentile, conjoint/cluster and graphic analyses were performed. All three analyses illustrated consumer ranking followed a bimodal distribution. Ranking for two levels with physical assistance and two levels with a walker were bimodal with a difference of five to six ranks between consumer subgroups (quartile analysis). The larger cluster (N=20) showed preference for walking with assistance over the smaller cluster (N=12), whose preference was walking without assistance and more devices. In all, 64% (27/42) of consumers ranked WISCI II level with no devices or braces and 1 person assistance higher than multiple levels of the WISCI II requiring no assistance. These results were unexpected, as the hypothesis was that consumers would rank independent walking higher than walking with assistance. Consumer preference for walking function should be considered in addition to objective measures in designing SCI trials that use significant improvement in walking function as an outcome measure.

Health Risk Ranking of Lead Contaminated Sites in Bagega Community, Zamfara State, Nigeria

Directory of Open Access Journals (Sweden)

Alaba Olanreaju Clement

2017-09-01

Full Text Available Background: The release of lead dust during the processing of lead-gold ore has become an environmental threat. Therefore the protection of miners’ health and their environment required remediation which can be achieved by ranking the risk posed by lead in order to prioritize the allocation of resources during remediation. Methods: Soil and water samples were collected at BRC, BRG, BVC, BPA and BFA; BWE, BBH and BPO using stratified random and grab sampling methods. Lead concentrations in the samples were determined using AAS while health risk index (HRI via ingestion was estimated using USEPA equations. The ranking of HRI was done using Detailed Quantitative Risk Assessment while the difference between the HRI and USEPA standard were determined using one sample t test. Results: The result showed that BRC/10, BRG/03, BVC/11, BPA/02 and BFA/08 were ranked highest in soil samples, while BWE/02, BBH/09 and BPO/04 were ranked highest in water samples as they posed elevated health risk effects to miners. One sample t test established that the BRC, BPA, BFA and BPO were significantly different from United States Environmental Protection Agency (US EPA standard. Conclusion: The study discovered that the users of both the lead contaminated soil and water were seriously exposed to potential health risk. It therefore suggested that decision makers should give priority in allocating resources to those sites with elevated lead concentrations during the remediation.

EFSA Panel on Biological Hazards (BIOHAZ); Scientific Opinion on on the development of a risk ranking framework on biological hazards

DEFF Research Database (Denmark)

Hald, Tine

between the time frame and the requirements of the risk ranking exercise was stressed as well as the interaction between the risk managers and the risk assessors in the definition of the risk ranking purpose and the presentation of the results. Furthermore the development of a risk ranking toolbox based...

What's wrong with hazard-ranking systems? An expository note.

Science.gov (United States)

Cox, Louis Anthony Tony

2009-07-01

Two commonly recommended principles for allocating risk management resources to remediate uncertain hazards are: (1) select a subset to maximize risk-reduction benefits (e.g., maximize the von Neumann-Morgenstern expected utility of the selected risk-reducing activities), and (2) assign priorities to risk-reducing opportunities and then select activities from the top of the priority list down until no more can be afforded. When different activities create uncertain but correlated risk reductions, as is often the case in practice, then these principles are inconsistent: priority scoring and ranking fails to maximize risk-reduction benefits. Real-world risk priority scoring systems used in homeland security and terrorism risk assessment, environmental risk management, information system vulnerability rating, business risk matrices, and many other important applications do not exploit correlations among risk-reducing opportunities or optimally diversify risk-reducing investments. As a result, they generally make suboptimal risk management recommendations. Applying portfolio optimization methods instead of risk prioritization ranking, rating, or scoring methods can achieve greater risk-reduction value for resources spent.

Dynamic decision making without expected utility

DEFF Research Database (Denmark)

Nielsen, Thomas Dyhre; Jaffray, Jean-Yves

2006-01-01

Non-expected utility theories, such as rank dependent utility (RDU) theory, have been proposed as alternative models to EU theory in decision making under risk. These models do not share the separability property of expected utility theory. This implies that, in a decision tree, if the reduction...... maker’s discordant goals at the different decision nodes. Relative to the computations involved in the standard expected utility evaluation of a decision problem, the main computational increase is due to the identification of non-dominated strategies by linear programming. A simulation, using the rank...

The predictive validity of prospect theory versus expected utility in health utility measurement.

Science.gov (United States)

Abellan-Perpiñan, Jose Maria; Bleichrodt, Han; Pinto-Prades, Jose Luis

2009-12-01

Most health care evaluations today still assume expected utility even though the descriptive deficiencies of expected utility are well known. Prospect theory is the dominant descriptive alternative for expected utility. This paper tests whether prospect theory leads to better health evaluations than expected utility. The approach is purely descriptive: we explore how simple measurements together with prospect theory and expected utility predict choices and rankings between more complex stimuli. For decisions involving risk prospect theory is significantly more consistent with rankings and choices than expected utility. This conclusion no longer holds when we use prospect theory utilities and expected utilities to predict intertemporal decisions. The latter finding cautions against the common assumption in health economics that health state utilities are transferable across decision contexts. Our results suggest that the standard gamble and algorithms based on, should not be used to value health.

Importance measures in risk-informed decision making: Ranking, optimisation and configuration control

Energy Technology Data Exchange (ETDEWEB)

Vaurio, Jussi K., E-mail: jussi.vaurio@pp1.inet.fi [Prometh Solutions, Hiihtaejaenkuja 3K, 06100 Porvoo (Finland)

2011-11-15

This paper describes roles, extensions and applications of importance measures of components and configurations for making risk-informed decisions relevant to system operations, maintenance and safety. Basic importance measures and their relationships are described for independent and mutually exclusive events and for groups of events associated with common cause failures. The roles of importances are described mainly in two groups of activities: (a) ranking safety significance of systems, structures, components and human actions for preventive safety assurance activities, and (b) making decisions about permissible permanent and temporary configurations and allowed configuration times for regulation, technical specifications and for on-line risk monitoring. Criticality importance and sums of criticalities turn out to be appropriate measures for ranking and optimization. Several advantages are pointed out and consistent ranking of pipe segments for in-service inspection is provided as an example. Risk increase factor and its generalization risk gain are most appropriately used to assess corrective priorities and acceptability of a situation when components are already failed or when planning to take one or more components out of service for maintenance. Precise definitions are introduced for multi-failure configurations and it is shown how they can be assessed under uncertainties, in particular when common cause failures or success states may be involved. A general weighted average method is compared to other candidate methods in benchmark cases. It is the preferable method for prediction when a momentary configuration is known or only partially known. Potential applications and optimization of allowed outage times are described. The results show how to generalize and apply various importance measures to ranking and optimization and how to manage configurations in uncertain multi-failure situations. - Highlights: > Rigorous methods developed for using importances

Importance measures in risk-informed decision making: Ranking, optimisation and configuration control

International Nuclear Information System (INIS)

Vaurio, Jussi K.

2011-01-01

This paper describes roles, extensions and applications of importance measures of components and configurations for making risk-informed decisions relevant to system operations, maintenance and safety. Basic importance measures and their relationships are described for independent and mutually exclusive events and for groups of events associated with common cause failures. The roles of importances are described mainly in two groups of activities: (a) ranking safety significance of systems, structures, components and human actions for preventive safety assurance activities, and (b) making decisions about permissible permanent and temporary configurations and allowed configuration times for regulation, technical specifications and for on-line risk monitoring. Criticality importance and sums of criticalities turn out to be appropriate measures for ranking and optimization. Several advantages are pointed out and consistent ranking of pipe segments for in-service inspection is provided as an example. Risk increase factor and its generalization risk gain are most appropriately used to assess corrective priorities and acceptability of a situation when components are already failed or when planning to take one or more components out of service for maintenance. Precise definitions are introduced for multi-failure configurations and it is shown how they can be assessed under uncertainties, in particular when common cause failures or success states may be involved. A general weighted average method is compared to other candidate methods in benchmark cases. It is the preferable method for prediction when a momentary configuration is known or only partially known. Potential applications and optimization of allowed outage times are described. The results show how to generalize and apply various importance measures to ranking and optimization and how to manage configurations in uncertain multi-failure situations. - Highlights: → Rigorous methods developed for using importances

Dose-volume based ranking of incident beam direction and its utility in facilitating IMRT beam placement

International Nuclear Information System (INIS)

Schreibmann, Eduard; Xing Lei

2005-01-01

Purpose: Beam orientation optimization in intensity-modulated radiation therapy (IMRT) is computationally intensive, and various single beam ranking techniques have been proposed to reduce the search space. Up to this point, none of the existing ranking techniques considers the clinically important dose-volume effects of the involved structures, which may lead to clinically irrelevant angular ranking. The purpose of this work is to develop a clinically sensible angular ranking model with incorporation of dose-volume effects and to show its utility for IMRT beam placement. Methods and Materials: The general consideration in constructing this angular ranking function is that a beamlet/beam is preferable if it can deliver a higher dose to the target without exceeding the tolerance of the sensitive structures located on the path of the beamlet/beam. In the previously proposed dose-based approach, the beamlets are treated independently and, to compute the maximally deliverable dose to the target volume, the intensity of each beamlet is pushed to its maximum intensity without considering the values of other beamlets. When volumetric structures are involved, the complication arises from the fact that there are numerous dose distributions corresponding to the same dose-volume tolerance. In this situation, the beamlets are not independent and an optimization algorithm is required to find the intensity profile that delivers the maximum target dose while satisfying the volumetric constraints. In this study, the behavior of a volumetric organ was modeled by using the equivalent uniform dose (EUD). A constrained sequential quadratic programming algorithm (CFSQP) was used to find the beam profile that delivers the maximum dose to the target volume without violating the EUD constraint or constraints. To assess the utility of the proposed technique, we planned a head-and-neck and abdominal case with and without the guidance of the angular ranking information. The qualities of the

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).

An alternative approach to risk rank chemicals on the threat they pose to the aquatic environment.

Science.gov (United States)

Johnson, Andrew C; Donnachie, Rachel L; Sumpter, John P; Jürgens, Monika D; Moeckel, Claudia; Pereira, M Gloria

2017-12-01

This work presents a new and unbiased method of risk ranking chemicals based on the threat they pose to the aquatic environment. The study ranked 12 metals, 23 pesticides, 11 other persistent organic pollutants (POPs), 13 pharmaceuticals, 10 surfactants and similar compounds and 2 nanoparticles (total of 71) of concern against one another by comparing their median UK river water and median ecotoxicity effect concentrations. To complement this, by giving an assessment on potential wildlife impacts, risk ranking was also carried out by comparing the lowest 10th percentile of the effects data with the highest 90th percentile of the exposure data. In other words, risk was pared down to just toxicity versus exposure. Further modifications included incorporating bioconcentration factors, using only recent water measurements and excluding either lethal or sub-lethal effects. The top ten chemicals, based on the medians, which emerged as having the highest risk to organisms in UK surface waters using all the ecotoxicity data were copper, aluminium, zinc, ethinylestradiol (EE2), linear alkylbenzene sulfonate (LAS), triclosan, manganese, iron, methomyl and chlorpyrifos. By way of contrast, using current UK environmental quality standards as the comparator to median UK river water concentrations would have selected 6 different chemicals in the top ten. This approach revealed big differences in relative risk; for example, zinc presented a million times greater risk then metoprolol and LAS 550 times greater risk than nanosilver. With the exception of EE2, most pharmaceuticals were ranked as having a relatively low risk. Copyright © 2017 Elsevier B.V. All rights reserved.

Method ranks competing projects by priorities, risk

International Nuclear Information System (INIS)

Moeckel, D.R.

1993-01-01

A practical, objective guide for ranking projects based on risk-based priorities has been developed by Sun Pipe Line Co. The deliberately simple system guides decisions on how to allocate scarce company resources because all managers employ the same criteria in weighing potential risks to the company versus benefits. Managers at all levels are continuously having to comply with an ever growing amount of legislative and regulatory requirements while at the same time trying to run their businesses effectively. The system primarily is designed for use as a compliance oversight and tracking process to document, categorize, and follow-up on work concerning various issues or projects. That is, the system consists of an electronic database which is updated periodically, and is used by various levels of management to monitor progress of health, safety, environmental and compliance-related projects. Criteria used in determining a risk factor and assigning a priority also have been adapted and found useful for evaluating other types of projects. The process enables management to better define potential risks and/or loss of benefits that are being accepted when a project is rejected from an immediate work plan or budget. In times of financial austerity, it is extremely important that the right decisions are made at the right time

Evaluation of treatment effects by ranking

DEFF Research Database (Denmark)

Halekoh, U; Kristensen, K

2008-01-01

In crop experiments measurements are often made by a judge evaluating the crops' conditions after treatment. In the present paper an analysis is proposed for experiments where plots of crops treated differently are mutually ranked. In the experimental layout the crops are treated on consecutive...... plots usually placed side by side in one or more rows. In the proposed method a judge ranks several neighbouring plots, say three, by ranking them from best to worst. For the next observation the judge moves on by no more than two plots, such that up to two plots will be re-evaluated again...... in a comparison with the new plot(s). Data from studies using this set-up were analysed by a Thurstonian random utility model, which assumed that the judge's rankings were obtained by comparing latent continuous utilities or treatment effects. For the latent utilities a variance component model was considered...

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.

Risk-informed ranking of engineering projects

International Nuclear Information System (INIS)

Jyrkama, M.; Pandey, M.

2011-01-01

Refurbishment planning requires prudent investment decisions with respect to the various systems and components at the station. These decisions are influenced by many factors, including engineering, safety, regulatory, economic, and political constraints. From an engineering perspective, the concept of cost-benefit analysis is a common way to allocate capital among various projects. Naturally, the 'best' or optimal project should have the lowest cost and the highest benefit. In the context of risk-informed decision making (RIDM), a process that has been widely embraced by the global nuclear community, the costs and benefits must further be 'weighted' by probabilities to estimate the underlying risk associated with the various planning alternatives. The main purpose of this study is to illustrate how risk and reliability information can be integrated into the refurbishment planning process to facilitate more objective and transparent investment decisions. The methodology is based on the concept of generation risk assessment (GRA) which provides a systematic approach for balancing investment costs with the reduction in overall financial risk. In addition to reliability predictions, the model provides estimates for the level of risk reduction associated with each system/project and also the break-even point for investment. This information is vital for project ranking, and helps to address the key question of whether capital investment should be made in the most risk critical systems, or in systems that reduce the overall risk the most. The application of the proposed methodology requires only basic information regarding the current reliability of each engineering system, which should be readily available from plant records and routine condition assessments. Because the methodology can be readily implemented in a Microsoft Excel spreadsheet, all plausible (e.g., bounding) planning scenarios, with or without investment, can also be generated quickly and easily, while

Risk and utility in portfolio optimization

Science.gov (United States)

Cohen, Morrel H.; Natoli, Vincent D.

2003-06-01

Modern portfolio theory (MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk, conflating uncertainty with risk. There have been many subsequent attempts to alleviate that weakness which, typically, combine utility and risk. We present here a modification of MPT based on the inclusion of separate risk and utility criteria. We define risk as the probability of failure to meet a pre-established investment goal. We define utility as the expectation of a utility function with positive and decreasing marginal value as a function of yield. The emphasis throughout is on long investment horizons for which risk-free assets do not exist. Analytic results are presented for a Gaussian probability distribution. Risk-utility relations are explored via empirical stock-price data, and an illustrative portfolio is optimized using the empirical data.

Occupational stress and cardiovascular risk factors in high-ranking government officials and office workers.

Science.gov (United States)

Mirmohammadi, Seyyed Jalil; Taheri, Mahmoud; Mehrparvar, Amir Houshang; Heydari, Mohammad; Saadati Kanafi, Ali; Mostaghaci, Mehrdad

2014-08-01

Cardiovascular diseases are among the most important sources of mortality and morbidity, and have a high disease burden. There are some major well-known risk factors, which contribute to the development of these diseases. Occupational stress is caused due to imbalance between job demands and individual's ability, and it has been implicated as an etiology for cardiovascular diseases. This study was conducted to evaluate the cardiovascular risk factors and different dimensions of occupational stress in high-ranking government officials, comparing an age and sex-matched group of office workers with them. We invited 90 high-ranking officials who managed the main governmental offices in a city, and 90 age and sex-matched office workers. The subjects were required to fill the occupational role questionnaire (Osipow) which evaluated their personal and medical history as well as occupational stress. Then, we performed physical examination and laboratory tests to check for cardiovascular risk factors. Finally, the frequency of cardiovascular risk factors and occupational stress of two groups were compared. High-ranking officials in our study had less work experience in their current jobs and smoked fewer pack-years of cigarette, but they had higher waist and hip circumference, higher triglyceride level, more stress from role overload and responsibility, and higher total stress score. Our group of office workers had more occupational stress because of role ambiguity and insufficiency, but their overall job stress was less than officials. The officials have higher scores in some dimensions of occupational stress and higher overall stress score. Some cardiovascular risk factors were also more frequent in managers.

Validation of a model for ranking aquaculture facilities for risk-based disease surveillance.

Science.gov (United States)

Diserens, Nicolas; Falzon, Laura Cristina; von Siebenthal, Beat; Schüpbach-Regula, Gertraud; Wahli, Thomas

2017-09-15

A semi-quantitative model for risk ranking of aquaculture facilities in Switzerland with regard to the introduction and spread of Viral Haemorrhagic Septicaemia (VHS) and Infectious Haematopoietic Necrosis (IHN) was developed in a previous study (Diserens et al., 2013). The objective of the present study was to validate this model using data collected during field visits on aquaculture sites in four Swiss cantons compared to data collected through a questionnaire in the previous study. A discrepancy between the values obtained with the two different methods was found in 32.8% of the parameters, resulting in a significant difference (pranking of Swiss aquaculture facilities according to their risk of getting infected with or spreading of VHS and IHN, as the five facilities that tested positive for these diseases in the last ten years were ranked as medium or high risk. Moreover, because the seven fish farms that were infected with Infectious Pancreatic Necrosis (IPN) during the same period also belonged to the risk categories medium and high, the classification appeared to correlate with the occurrence of this third viral fish disease. Copyright © 2017 Elsevier B.V. All rights reserved.

Utility of high-resolution computed tomography for predicting risk of sputum smear-negative pulmonary tuberculosis

International Nuclear Information System (INIS)

Nakanishi, Masanori; Demura, Yoshiki; Ameshima, Shingo; Kosaka, Nobuyuki; Chiba, Yukio; Nishikawa, Satoshi; Itoh, Harumi; Ishizaki, Takeshi

2010-01-01

Background: To diagnose sputum smear-negative pulmonary tuberculosis (PTB) is difficult and the ability of high-resolution computed tomography (HRCT) for diagnosing PTB has remained unclear in the sputum smear-negative setting. We retrospectively investigated whether or not this imaging modality can predict risk for sputum smear-negative PTB. Methods: We used HRCT to examine the findings of 116 patients with suspected PTB despite negative sputum smears for acid-fast bacilli (AFB). We investigated their clinical features and HRCT-findings to predict the risk for PTB by multivariate analysis and a combination of HRCT findings by stepwise regression analysis. We then designed provisional HRCT diagnostic criteria based on these results to rank the risk of PTB and blinded observers assessed the validity and reliability of these criteria. Results: A positive tuberculin skin test alone among clinical laboratory findings was significantly associated with an increase of risk of PTB. Multivariate regression analysis showed that large nodules, tree-in-bud appearance, lobular consolidation and the main lesion being located in S1, S2, and S6 were significantly associated with an increased risk of PTB. Stepwise regression analysis showed that coexistence of the above 4 factors was most significantly associated with an increase in the risk for PTB. Ranking of the results using our HRCT diagnostic criteria by blinded observers revealed good utility and agreement for predicting PTB risk. Conclusions: Even in the sputum smear-negative setting, HRCT can predict the risk of PTB with good reproducibility and can select patients having a high probability of PTB.

Utility of high-resolution computed tomography for predicting risk of sputum smear-negative pulmonary tuberculosis

Energy Technology Data Exchange (ETDEWEB)

Nakanishi, Masanori [Departments of Respiratory Medicine, Faculty of Medical Sciences, University of Fukui, 23 Shimoaizuki Eiheizi-cho, Fukui 910-1193 (Japan)], E-mail: mnakanishi@nifty.ne.jp; Demura, Yoshiki; Ameshima, Shingo [Departments of Respiratory Medicine, Faculty of Medical Sciences, University of Fukui, 23 Shimoaizuki Eiheizi-cho, Fukui 910-1193 (Japan); Kosaka, Nobuyuki [Departments of Radiology, Faculty of Medical Sciences, University of Fukui, 23 Shimoaizuki Eiheizi-cho, Fukui 910-1193 (Japan); Chiba, Yukio [Department of Respiratory Medicine, National Hospital Organization, Fukui Hospital, Tsuruga, Fukui 914-0195 (Japan); Nishikawa, Satoshi [Department of Radiology, National Hospital Organization, Fukui Hospital, Tsuruga, Fukui 914-0195 (Japan); Itoh, Harumi [Departments of Radiology, Faculty of Medical Sciences, University of Fukui, 23 Shimoaizuki Eiheizi-cho, Fukui 910-1193 (Japan); Ishizaki, Takeshi [Departments of Respiratory Medicine, Faculty of Medical Sciences, University of Fukui, 23 Shimoaizuki Eiheizi-cho, Fukui 910-1193 (Japan)

2010-03-15

Background: To diagnose sputum smear-negative pulmonary tuberculosis (PTB) is difficult and the ability of high-resolution computed tomography (HRCT) for diagnosing PTB has remained unclear in the sputum smear-negative setting. We retrospectively investigated whether or not this imaging modality can predict risk for sputum smear-negative PTB. Methods: We used HRCT to examine the findings of 116 patients with suspected PTB despite negative sputum smears for acid-fast bacilli (AFB). We investigated their clinical features and HRCT-findings to predict the risk for PTB by multivariate analysis and a combination of HRCT findings by stepwise regression analysis. We then designed provisional HRCT diagnostic criteria based on these results to rank the risk of PTB and blinded observers assessed the validity and reliability of these criteria. Results: A positive tuberculin skin test alone among clinical laboratory findings was significantly associated with an increase of risk of PTB. Multivariate regression analysis showed that large nodules, tree-in-bud appearance, lobular consolidation and the main lesion being located in S1, S2, and S6 were significantly associated with an increased risk of PTB. Stepwise regression analysis showed that coexistence of the above 4 factors was most significantly associated with an increase in the risk for PTB. Ranking of the results using our HRCT diagnostic criteria by blinded observers revealed good utility and agreement for predicting PTB risk. Conclusions: Even in the sputum smear-negative setting, HRCT can predict the risk of PTB with good reproducibility and can select patients having a high probability of PTB.

A Simple Model to Rank Shellfish Farming Areas Based on the Risk of Disease Introduction and Spread.

Science.gov (United States)

Thrush, M A; Pearce, F M; Gubbins, M J; Oidtmann, B C; Peeler, E J

2017-08-01

The European Union Council Directive 2006/88/EC requires that risk-based surveillance (RBS) for listed aquatic animal diseases is applied to all aquaculture production businesses. The principle behind this is the efficient use of resources directed towards high-risk farm categories, animal types and geographic areas. To achieve this requirement, fish and shellfish farms must be ranked according to their risk of disease introduction and spread. We present a method to risk rank shellfish farming areas based on the risk of disease introduction and spread and demonstrate how the approach was applied in 45 shellfish farming areas in England and Wales. Ten parameters were used to inform the risk model, which were grouped into four risk themes based on related pathways for transmission of pathogens: (i) live animal movement, (ii) transmission via water, (iii) short distance mechanical spread (birds) and (iv) long distance mechanical spread (vessels). Weights (informed by expert knowledge) were applied both to individual parameters and to risk themes for introduction and spread to reflect their relative importance. A spreadsheet model was developed to determine quantitative scores for the risk of pathogen introduction and risk of pathogen spread for each shellfish farming area. These scores were used to independently rank areas for risk of introduction and for risk of spread. Thresholds were set to establish risk categories (low, medium and high) for introduction and spread based on risk scores. Risk categories for introduction and spread for each area were combined to provide overall risk categories to inform a risk-based surveillance programme directed at the area level. Applying the combined risk category designation framework for risk of introduction and spread suggested by European Commission guidance for risk-based surveillance, 4, 10 and 31 areas were classified as high, medium and low risk, respectively. © 2016 Crown copyright.

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...

Evaluations and utilizations of risk importances

International Nuclear Information System (INIS)

Vesely, W.E.; Davis, T.C.

1985-08-01

This report presents approaches for utilizing Probabilistic Risk Analyses (PRA's) to determine risk importances. Risk importances are determined for design features, plant operations, and other factors that can affect risk. PRA's can be used to identify the importances of risk contributors or proposed changes to designs or operations. The objective of this report is to serve as a handbook and guide in evaluating and applying risk importances. The utilization of both qualitative risk importances and quantitative risk importances is described in this report. Qualitative risk importances are based on the logic models in the PRA, while quantitative risk importances are based on the quantitative results of the PRA. Both types of importances are among the most robust and meaningful information a PRA can provide. A wide variety of risk importance evaluations are described including evaluations of the importances of design changes, testing, maintenance, degrading environments, and aging. Specific utilizations are described in inspection and in reliability assurance programs, however the general approaches have widespread applicability. The role of personal computers and decision support programs in applying risk importance evaluations is also described

Risk ranking of environmental contaminants in Xiaoqing River, a heavily polluted river along urbanizing Bohai Rim.

Science.gov (United States)

Li, Qifeng; Zhang, Yueqing; Lu, Yonglong; Wang, Pei; Suriyanarayanan, Sarvajayakesavalu; Meng, Jing; Zhou, Yunqiao; Liang, Ruoyu; Khan, Kifayatullah

2018-08-01

Xiaoqing River, located in the Laizhou Bay of Bohai Sea, is heavily polluted by various pollutants including heavy metals, polycyclic aromatic hydrocarbons (PAHs), hexachlorocyclohexanes (HCHs), perfluoroalkyl acids (PFAAs), bisphenol A (BPA) and pharmaceutical and personal care products (PPCPs). The aim of this study is to identify the relative risks of such contaminants that currently affect the coastal ecosystem. The median and highest concentrations of PFAAs and perfluorooctanoic acid (PFOA) were 3.23 μg L -1 and 325.28 μg L -1 , and 0.173 μg L -1 and 276.24 μg L -1 , respectively, which were ranked higher when compared with global level concentrations. To assess the relative risk levels of perfluorooctane sulfonic acid (PFOS), PFOA, and other contaminants in the upstream and downstream of the Xiaoqing River and in its tributary, a risk ranking analysis was carried out. Copper (Cu), Zinc (Zn), and arsenic (As) showed the highest risk values in the Xiaoqing River, while the relative risks of PFOA and PFOS differed across the various segments. The risk ranking of PFOA was the second highest in the tributary and the fourth highest in the downstream portion of the river, whereas the PFOS was found to be the lowest in all the segments. Heavy metals and PFOA are the main chemicals that should be controlled in the Xiaoqing River. The results of the present study provide a better understanding of the potential ecological risks of the contaminants in Xiaoqing River. Copyright © 2018 Elsevier Ltd. All rights reserved.

On the consistency of risk acceptance criteria with normative theories for decision-making

Energy Technology Data Exchange (ETDEWEB)

Abrahamsen, E.B. [University of Stavanger, 4036 Stavanger (Norway)], E-mail: eirik.abrahamsen@uis.no; Aven, T. [University of Stavanger, 4036 Stavanger (Norway)

2008-12-15

In evaluation of safety in projects it is common to use risk acceptance criteria to support decision-making. In this paper, we discuss to what extent the risk acceptance criteria is in accordance with the normative theoretical framework of the expected utility theory and the rank-dependent utility theory. We show that the use of risk acceptance criteria may violate the independence axiom of the expected utility theory and the comonotonic independence axiom of the rank-dependent utility theory. Hence the use of risk acceptance criteria is not in general consistent with these theories. The level of inconsistency is highest for the expected utility theory.

On the consistency of risk acceptance criteria with normative theories for decision-making

International Nuclear Information System (INIS)

Abrahamsen, E.B.; Aven, T.

2008-01-01

In evaluation of safety in projects it is common to use risk acceptance criteria to support decision-making. In this paper, we discuss to what extent the risk acceptance criteria is in accordance with the normative theoretical framework of the expected utility theory and the rank-dependent utility theory. We show that the use of risk acceptance criteria may violate the independence axiom of the expected utility theory and the comonotonic independence axiom of the rank-dependent utility theory. Hence the use of risk acceptance criteria is not in general consistent with these theories. The level of inconsistency is highest for the expected utility theory

FDA-iRISK--a comparative risk assessment system for evaluating and ranking food-hazard pairs: case studies on microbial hazards.

Science.gov (United States)

Chen, Yuhuan; Dennis, Sherri B; Hartnett, Emma; Paoli, Greg; Pouillot, Régis; Ruthman, Todd; Wilson, Margaret

2013-03-01

Stakeholders in the system of food safety, in particular federal agencies, need evidence-based, transparent, and rigorous approaches to estimate and compare the risk of foodborne illness from microbial and chemical hazards and the public health impact of interventions. FDA-iRISK (referred to here as iRISK), a Web-based quantitative risk assessment system, was developed to meet this need. The modeling tool enables users to assess, compare, and rank the risks posed by multiple food-hazard pairs at all stages of the food supply system, from primary production, through manufacturing and processing, to retail distribution and, ultimately, to the consumer. Using standard data entry templates, built-in mathematical functions, and Monte Carlo simulation techniques, iRISK integrates data and assumptions from seven components: the food, the hazard, the population of consumers, process models describing the introduction and fate of the hazard up to the point of consumption, consumption patterns, dose-response curves, and health effects. Beyond risk ranking, iRISK enables users to estimate and compare the impact of interventions and control measures on public health risk. iRISK provides estimates of the impact of proposed interventions in various ways, including changes in the mean risk of illness and burden of disease metrics, such as losses in disability-adjusted life years. Case studies for Listeria monocytogenes and Salmonella were developed to demonstrate the application of iRISK for the estimation of risks and the impact of interventions for microbial hazards. iRISK was made available to the public at http://irisk.foodrisk.org in October 2012.

Decision support for utility environmental risk management

International Nuclear Information System (INIS)

Balson, W.E.; Wilson, D.S.

1991-01-01

This paper reviews a number of decision support methods developed and applied by Decision Focus Incorporated to help utility personnel manage current environmental problems. This work has been performed for the Environmental Risk Analysis Program of EPRI's Environment Division, and also for a number of electric utilities across the country. These are two distinct types of decision support software tools that have been created: economic risk management and environmental risk analysis. These types differ primarily in the identification of who will make a decision. Economic risk management tools are directed primarily at decisions made by electric utilities. Environmental risk analysis tools are directed primarily at decisions made by legislative or regulatory agencies, about which a utility may wish to comment

Risks identification and ranking using AHP and group decision making technique: Presenting “R index”

Directory of Open Access Journals (Sweden)

Safar Fazli

2013-02-01

Full Text Available One of the primary concerns in project development is to detect all sorts of risks associated with a particular project. The main objective of this article is to identify the risks in the construction project and to grade them based on their importance on the project. The designed indicator in this paper is the combinational model of the Analytical Hierarchal Process (AHP method and the group decision – making applied for risks measurement and ranking. This indicator is called "R" which includes three main steps: creating the risks broken structure (RBS, obtaining each risk weight and efficacy, and finally performing the model to rank the risks. A questionnaire is used for gathering data. Based on the results of this survey, there are important risks associated with construction projects. There we need to use some guidelines to reduce the inherent risks including recognition of the common risks beside the political risks; suggestion of a simple, understandable, and practical model; and using plenty of the experts and specialists' opinions through applying step. After analyzing data, the final result from applying R index showed that the risk “economic changes / currency rate and inflation change" has the most importance for the analysis. In the other words, if these risks occur, the project may face with the more threats and it is suggested that an organization should centralize its equipment, personnel, cost, and time on the risk more than ever. The most obvious issue in this paper is a tremendous difference between an importance of the financial risks and the other risks.

Explaining Distortions in Utility Elicitation through the Rank-Dependent Model for Risky Choices

NARCIS (Netherlands)

P.P. Wakker (Peter); A.M. Stiggelbout (Anne)

1995-01-01

textabstractThe standard gamble (SG) method has been accepted as the gold standard for the elicitation of utility when risk or uncertainty is involved in decisions, and thus for the measurement of utility in medical decisions. Unfortunately, the SG method is distorted by a general dislike for

Development of a risk-ranking framework to evaluate potential high-threat microorganisms, toxins, and chemicals in food.

Science.gov (United States)

Newsome, R; Tran, N; Paoli, G M; Jaykus, L A; Tompkin, B; Miliotis, M; Ruthman, T; Hartnett, E; Busta, F F; Petersen, B; Shank, F; McEntire, J; Hotchkiss, J; Wagner, M; Schaffner, D W

2009-03-01

Through a cooperative agreement with the U.S. Food and Drug Administration, the Institute of Food Technologists developed a risk-ranking framework prototype to enable comparison of microbiological and chemical hazards in foods and to assist policy makers, risk managers, risk analysts, and others in determining the relative public health impact of specific hazard-food combinations. The prototype is a bottom-up system based on assumptions that incorporate expert opinion/insight with a number of exposure and hazard-related risk criteria variables, which are propagated forward with food intake data to produce risk-ranking determinations. The prototype produces a semi-quantitative comparative assessment of food safety hazards and the impacts of hazard control measures. For a specific hazard-food combination the prototype can produce a single metric: a final risk value expressed as annual pseudo-disability adjusted life years (pDALY). The pDALY is a harmonization of the very different dose-response relationships observed for chemicals and microbes. The prototype was developed on 2 platforms, a web-based user interface and an Analytica(R) model (Lumina Decision Systems, Los Gatos, Calif., U.S.A.). Comprising visual basic language, the web-based platform facilitates data input and allows use concurrently from multiple locations. The Analytica model facilitates visualization of the logic flow, interrelationship of input and output variables, and calculations/algorithms comprising the prototype. A variety of sortable risk-ranking reports and summary information can be generated for hazard-food pairs, showing hazard and dose-response assumptions and data, per capita consumption by population group, and annual p-DALY.

An empirical investigation on ranking financial risk factors using AHP method

Directory of Open Access Journals (Sweden)

Hassan Ghodrati

2014-05-01

Full Text Available This paper determines and ranks financial risk factors in Iranian corporations, using analytical hierarchy process (AHP. The present research includes one main question and four sub- questions. Its universe population includes managers, production and financial personnel of great corporations activating in Tehran Stock Exchange, who were selected to explain importance and weight of economic risks indices. The source of great corporations recognition is the Companies Registration Organization in Tehran Province, and according to this, there are 120 corporations. The results have indicated that financing risk maintains the highest priority followed by credit risk, liquidity risk, inflation risk and exchange risk. In terms of different risks associated with financing risk, risk of profit per share has been the number one priority followed by the risk of divisional profit per share, the risk of recessionary or boom and the risk of increasing partial pay profit rate. In terms of credit risk, the risk of loan has been number one priority followed by the risk of inability of loan payment and interest payment. Liquidity risk is another risk factor where demand has been the most important factor followed by rules and regulations and inflation risk. In terms of inflation, producers price risk has been the most important factor followed by consumer price risk, gross domestic product and producers price risk. Finally, in terms of different factors influencing exchange risk, export related issues are considered as the most important factors.

Low-rank coal study. Volume 4. Regulatory, environmental, and market analyses

Energy Technology Data Exchange (ETDEWEB)

1980-11-01

The regulatory, environmental, and market constraints to development of US low-rank coal resources are analyzed. Government-imposed environmental and regulatory requirements are among the most important factors that determine the markets for low-rank coal and the technology used in the extraction, delivery, and utilization systems. Both state and federal controls are examined, in light of available data on impacts and effluents associated with major low-rank coal development efforts. The market analysis examines both the penetration of existing markets by low-rank coal and the evolution of potential markets in the future. The electric utility industry consumes about 99 percent of the total low-rank coal production. This use in utility boilers rose dramatically in the 1970's and is expected to continue to grow rapidly. In the late 1980's and 1990's, industrial direct use of low-rank coal and the production of synthetic fuels are expected to start growing as major new markets.

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.

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.

Resolving inconsistencies in utility measurement under risk: Tests of generalizations of expected utility

OpenAIRE

Han Bleichrodt; José María Abellán-Perpiñan; JoséLuis Pinto; Ildefonso Méndez-Martínez

2005-01-01

This paper explores inconsistencies that occur in utility measurement under risk when expected utility theory is assumed and the contribution that prospect theory and some other generalizations of expected utility can make to the resolution of these inconsistencies. We used five methods to measure utilities under risk and found clear violations of expected utility. Of the theories studied, prospect theory was the most consistent with our data. The main improvement of prospect theory over expe...

A Relative Ranking Approach for Nano-Enabled Applications to Improve Risk-Based Decision Making: A Case Study of Army Materiel

Science.gov (United States)

2014-12-24

accidental expo- sures to carbon nanotubes and copper flakes incorporated into energy and obscurant materiel by Army workers rank highest relative to...that inhalation from accidental exposures to carbon nanotubes and copper flakes incorporated into energy and obscurant materiel by Army workers rank... copper (Cu), and titanium (Ti) flakes used in smokes and obscurants ranked the highest on the risk scale for sce- narios primarily involving accidental

Mining Feedback in Ranking and Recommendation Systems

Science.gov (United States)

Zhuang, Ziming

2009-01-01

The amount of online information has grown exponentially over the past few decades, and users become more and more dependent on ranking and recommendation systems to address their information seeking needs. The advance in information technologies has enabled users to provide feedback on the utilities of the underlying ranking and recommendation…

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

Identifying drug risk perceptions in Danish youths: Ranking exercises in focus groups

DEFF Research Database (Denmark)

Demant, Jakob; Ravn, Signe

2010-01-01

Abstract: Background: This paper develops an analytical approach for understanding the perceptions of risks associated with drugs among youths in general. These perceptions are central in order to understand how certain drugs become popular, leading to increasing prevalence of use, while others do...... not. As such, this approach can become an efficient policy tool. Methods: Focus groups are used to investigate risk perceptions. We develop a specific methodology that combines a ranking exercise with discourse theory as an analytical approach. This methodology produces detailed information...... and provides a relatively efficient way of investigating normative risk perceptions at a national or subcultural level. The paper develops this methodology in relation to a Danish case with 12 focus group interviews with youths aged from 17 to 22. Results: The analysis identifies five discourses articulated...

Identifying drug risk perceptions in Danish youths: Ranking exercises in focus groups

DEFF Research Database (Denmark)

Demant, Jakob Johan; Ravn, Signe

2010-01-01

not. As such, this approach can become an efficient policy tool. Methods: Focus groups are used to investigate risk perceptions. We develop a specific methodology that combines a ranking exercise with discourse theory as an analytical approach. This methodology produces detailed information......Abstract: Background: This paper develops an analytical approach for understanding the perceptions of risks associated with drugs among youths in general. These perceptions are central in order to understand how certain drugs become popular, leading to increasing prevalence of use, while others do...... and provides a relatively efficient way of investigating normative risk perceptions at a national or subcultural level. The paper develops this methodology in relation to a Danish case with 12 focus group interviews with youths aged from 17 to 22. Results: The analysis identifies five discourses articulated...

Risk assessment and ranking methodologies for hazardous chemical defense waste: a state-of-the-art review and evaluation. Task 1 report

International Nuclear Information System (INIS)

Chu, M.S.Y.; Rodricks, J.V.; St Hilaire, C.; Bras, R.L.

1986-06-01

This report summarizes the work performed under Task 1 of the Risk Assessment Evaluation Task under the Hazardous Chemical Defense Waste Management Program of the Department of Energy (DOE). The objective of Task 1 was to identify, review, and evaluate the state-of-the-art tools and techniques available for ranking and evaluating disposal facilities. These tools were evaluated for their applicability to DOE's mixed hazardous chemical and radioactive waste sites. Various ranking methodologies were reviewed and three were evaluated in detail. Areas that were found to be deficient in each ranking methodology were presented in the report. Recommendations were given for the development of an improved ranking methodology for use on DOE's sites. A literature review was then performed on the various components of a risk assessment methodology. They include source term evaluation, geosphere transport models, exposure pathways models, dose effects models, and sensitivity/uncertainty techniques. A number of recommendations have been made in the report based on the review and evaluation for the development of a comprehensive risk assessment methodology in evaluating mixed waste disposal sites

Risk Aversion and Expected-Utility Theory: A Calibration Theorem.

OpenAIRE

Matthew Rabin.

2000-01-01

Within the expected-utility framework, the only explanation for risk aversion is that the utility function for wealth is concave: A person has lower marginal utility for additional wealth when she is wealthy than when she is poor. This paper provides a theorem showing that expected-utility theory is an utterly implausible explanation for appreciable risk aversion over modest stakes: Within expected-utility theory, for any concave utility function, even very little risk aversion over modest st...

The Axiomatic Basis of Anticipated Utility: A Clarification

NARCIS (Netherlands)

J. Quiggin (John); P.P. Wakker (Peter)

1994-01-01

textabstractQuiggin (J. Econ. Behav. Organization3 (1982), 323-345) introduced anticipated ("rank-dependent") utility theory into decision making under risk. Questions have been raised about mathematical aspects of Quiggin′s analysis. This paper settles these questions and shows that a minor

Ranking businesses and municipal locations by spatiotemporal cardiac arrest risk to guide public defibrillator placement

Science.gov (United States)

Sun, Christopher L. F.; Brooks, Steven C.; Morrison, Laurie J.; Chan, Timothy C.Y.

2017-01-01

Background Efforts to guide automated external defibrillator (AED) placement for out-of-hospital cardiac arrest (OHCA) treatment have focused on identifying broadly defined location categories without considering hours of operation. Broad location categories may be composed of many businesses with varying accessibility. Identifying specific locations for AED deployment incorporating operating hours and time of OHCA occurrence may improve AED accessibility. We aim to identify specific businesses and municipal locations that maximize OHCA coverage based on spatiotemporal assessment of OHCA risk in the immediate vicinity of franchise locations. Methods This study was a retrospective population-based cohort study using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all non-traumatic public OHCAs occurring in Toronto, Canada from Jan. 2007–Dec. 2015. We identified 41 unique businesses and municipal location types with 20 or more locations in Toronto from the YellowPages, Canadian Franchise Association, and the City of Toronto Open Data Portal. We obtained their geographic coordinates and hours of operation from websites, phone, or in-person. We determined the number of OHCAs that occurred within 100 m of each location when it was open (spatiotemporal coverage) for Toronto overall and downtown. The businesses and municipal locations were then ranked by spatiotemporal OHCA coverage. To evaluate temporal stability of the rankings, we calculated intra-class correlation (ICC) of the annual coverage values. Results There were 2,654 non-traumatic public OHCAs. Tim Hortons ranked first in Toronto covering 286 OHCAs. Starbucks ranked first in downtown covering 110 OHCAs. Coffee shops and bank machines from the five largest Canadian banks occupied eight of the top 10 spots in both Toronto and downtown. The rankings exhibited high temporal stability with ICC values of 0.88 (95% CI, 0.83–0.93) in Toronto and 0.79 (95% CI, 0.71–0.86) in

Ranking Businesses and Municipal Locations by Spatiotemporal Cardiac Arrest Risk to Guide Public Defibrillator Placement.

Science.gov (United States)

Sun, Christopher L F; Brooks, Steven C; Morrison, Laurie J; Chan, Timothy C Y

2017-03-21

Efforts to guide automated external defibrillator placement for out-of-hospital cardiac arrest (OHCA) treatment have focused on identifying broadly defined location categories without considering hours of operation. Broad location categories may be composed of many businesses with varying accessibility. Identifying specific locations for automated external defibrillator deployment incorporating operating hours and time of OHCA occurrence may improve automated external defibrillator accessibility. We aim to identify specific businesses and municipal locations that maximize OHCA coverage on the basis of spatiotemporal assessment of OHCA risk in the immediate vicinity of franchise locations. This study was a retrospective population-based cohort study using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all nontraumatic public OHCAs occurring in Toronto, ON, Canada, from January 2007 through December 2015. We identified 41 unique businesses and municipal location types with ≥20 locations in Toronto from the YellowPages, Canadian Franchise Association, and the City of Toronto Open Data Portal. We obtained their geographic coordinates and hours of operation from Web sites, by phone, or in person. We determined the number of OHCAs that occurred within 100 m of each location when it was open (spatiotemporal coverage) for Toronto overall and downtown. The businesses and municipal locations were then ranked by spatiotemporal OHCA coverage. To evaluate temporal stability of the rankings, we calculated intraclass correlation of the annual coverage values. There were 2654 nontraumatic public OHCAs. Tim Hortons ranked first in Toronto, covering 286 OHCAs. Starbucks ranked first in downtown, covering 110 OHCAs. Coffee shops and bank machines from the 5 largest Canadian banks occupied 8 of the top 10 spots in both Toronto and downtown. The rankings exhibited high temporal stability with intraclass correlation values of 0.88 (95

Complete hazard ranking to analyze right-censored data: An ALS survival study.

Science.gov (United States)

Huang, Zhengnan; Zhang, Hongjiu; Boss, Jonathan; Goutman, Stephen A; Mukherjee, Bhramar; Dinov, Ivo D; Guan, Yuanfang

2017-12-01

Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

Ranking ecological risks of multiple chemical stressors on amphibians.

Science.gov (United States)

Fedorenkova, Anastasia; Vonk, J Arie; Lenders, H J Rob; Creemers, Raymond C M; Breure, Anton M; Hendriks, A Jan

2012-06-01

Populations of amphibians have been declining worldwide since the late 1960s. Despite global concern, no studies have quantitatively assessed the major causes of this decline. In the present study, species sensitivity distributions (SSDs) were developed to analyze the sensitivity of anurans for ammonium, nitrate, heavy metals (cadmium, copper), pesticides (18 compounds), and acidification (pH) based on laboratory toxicity data. Ecological risk (ER) was calculated as the probability that a measured environmental concentration of a particular stressor in habitats where anurans were observed would exceed the toxic effect concentrations derived from the species sensitivity distributions. The assessment of ER was used to rank the stressors according to their potential risk to anurans based on a case study of Dutch freshwater bodies. The derived ERs revealed that threats to populations of anurans decreased in the sequence of pH, copper, diazinon, ammonium, and endosulfan. Other stressors studied were of minor importance. The method of deriving ER by combining field observation data and laboratory data provides insight into potential threats to species in their habitats and can be used to prioritize stressors, which is necessary to achieve effective management in amphibian conservation. Copyright © 2012 SETAC.

Complete hazard ranking to analyze right-censored data: An ALS survival study.

Directory of Open Access Journals (Sweden)

Zhengnan Huang

2017-12-01

Full Text Available Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

Optimization of the two-sample rank Neyman-Pearson detector

Science.gov (United States)

Akimov, P. S.; Barashkov, V. M.

1984-10-01

The development of optimal algorithms concerned with rank considerations in the case of finite sample sizes involves considerable mathematical difficulties. The present investigation provides results related to the design and the analysis of an optimal rank detector based on a utilization of the Neyman-Pearson criteria. The detection of a signal in the presence of background noise is considered, taking into account n observations (readings) x1, x2, ... xn in the experimental communications channel. The computation of the value of the rank of an observation is calculated on the basis of relations between x and the variable y, representing interference. Attention is given to conditions in the absence of a signal, the probability of the detection of an arriving signal, details regarding the utilization of the Neyman-Pearson criteria, the scheme of an optimal rank, multichannel, incoherent detector, and an analysis of the detector.

Ranking of psychosocial and traditional risk factors by importance for coronary heart disease

DEFF Research Database (Denmark)

Schnohr, Peter; Marott, Jacob L; Kristensen, Tage S.

2015-01-01

.001] and systolic blood pressure (≥160 mmHg or blood pressure medication vs. never smoker; HR 1.74; 95% CI, 1.43-2.11; P ...-statistics and net reclassification improvement. During the follow-up, 1731 non-fatal and fatal coronary events were registered. In men, the highest ranking risk factors for coronary heart disease were vital exhaustion [high vs. low; hazard ratio (HR) 2.36; 95% confidence interval (CI), 1.70-3.26; P

Critical review of methodology and application of risk ranking for prioritisation of food and feed related issues, on the basis of the size of anticipated health impact

DEFF Research Database (Denmark)

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

, an overarching framework was developed for selection of the appropriate method(s) that could be used for risk ranking of feed and food related hazards, on the basis of human health impact. This framework has the format of a decision tool, with which – given the characteristics of the risk ranking question...... at hand - the most appropriate method(s) can be selected. Application of this overall framework to several case studies showed it can be a useful tool for risk managers/assessors to select the most suitable method for risk ranking of feed/food and diet related hazards, on the basis of expected human......This study aimed to critically review methodologies for ranking of risks related to feed/food safety and nutritional hazards, on the basis of their anticipated human health impact. An extensive systematic literature review was performed to identify and characterize the available methodologies...

Risk measures on networks and expected utility

International Nuclear Information System (INIS)

Cerqueti, Roy; Lupi, Claudio

2016-01-01

In reliability theory projects are usually evaluated in terms of their riskiness, and often decision under risk is intended as the one-shot-type binary choice of accepting or not accepting the risk. In this paper we elaborate on the concept of risk acceptance, and propose a theoretical framework based on network theory. In doing this, we deal with system reliability, where the interconnections among the random quantities involved in the decision process are explicitly taken into account. Furthermore, we explore the conditions to be satisfied for risk-acceptance criteria to be consistent with the axiomatization of standard expected utility theory within the network framework. In accordance with existing literature, we show that a risk evaluation criterion can be meaningful even if it is not consistent with the standard axiomatization of expected utility, once this is suitably reinterpreted in the light of networks. Finally, we provide some illustrative examples. - Highlights: • We discuss risk acceptance and theoretically develop this theme on the basis of network theory. • We propose an original framework for describing the algebraic structure of the set of the networks, when they are viewed as risks. • We introduce the risk measures on networks, which induce total orders on the set of networks. • We state conditions on the risk measures on networks to let the induced risk-acceptance criterion be consistent with a new formulation of the expected utility theory.

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.

Drug utilization research and risk management

NARCIS (Netherlands)

Mazzaglia, Giampiero; Mol, Peter G. M.; Elseviers, Monique; Wettermark, Björn; Almarsdóttir, Anna Birna; Andersen, Morten; Benko, Ria; Bennie, Marion; Eriksson, Irene; Godman, Brian; Krska, Janet; Poluzzi, Elisabetta; Taxis, Katja; Vlahovic-Palcevski, Vera; Stichele, Robert Vander

2016-01-01

Good risk management requires continuous evaluation and improvement of planned activities. The evaluation impact of risk management activities requires robust study designs and carefully selected outcome measures. Key learnings and caveats from drug utilization research should be applied to the

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.

Building uncertainty into cost-effectiveness rankings: portfolio risk-return tradeoffs and implications for decision rules.

Science.gov (United States)

O'Brien, B J; Sculpher, M J

2000-05-01

Current principles of cost-effectiveness analysis emphasize the rank ordering of programs by expected economic return (eg, quality-adjusted life-years gained per dollar expended). This criterion ignores the variance associated with the cost-effectiveness of a program, yet variance is a common measure of risk when financial investment options are appraised. Variation in health care program return is likely to be a criterion of program selection for health care managers with fixed budgets and outcome performance targets. Characterizing health care resource allocation as a risky investment problem, we show how concepts of portfolio analysis from financial economics can be adopted as a conceptual framework for presenting cost-effectiveness data from multiple programs as mean-variance data. Two specific propositions emerge: (1) the current convention of ranking programs by expected return is a special case of the portfolio selection problem in which the decision maker is assumed to be indifferent to risk, and (2) for risk-averse decision makers, the degree of joint risk or covariation in cost-effectiveness between programs will create incentives to diversify an investment portfolio. The conventional normative assumption of risk neutrality for social-level public investment decisions does not apply to a large number of health care resource allocation decisions in which health care managers seek to maximize returns subject to budget constraints and performance targets. Portfolio theory offers a useful framework for studying mean-variance tradeoffs in cost-effectiveness and offers some positive predictions (and explanations) of actual decision making in the health care sector.

Risks associated with utilization of radiation

International Nuclear Information System (INIS)

Matsuoka, Satoshi; Kumazawa, Shigeru; Aoki, Yoshiro; Nakamura, Yuji; Takeda, Atsuhiko; Kusama, Tomoko; Inaba, Jiro; Tanaka, Yasumasa.

1993-01-01

When mankind decides action, the conveniences and the risks obtained by the action are weighed up. When socially important judgement is done, the logical discussion based on objective data is indispensable. The utilization of radiation spread from industrial circles to general public, accordingly the circumstances changed from the recognition of its risks by professionals to that by general public. The radiation exposure dose of public has increased rapidly by medical treatment. The global radioactivity contamination accompanying nuclear explosion experiment and the Chernobyl accident raised the psychological risk recognition of public. Now, the fear of the potential radioactivity which may be released from nuclear power plants and nuclear fuel cycle facilities expanded. The radiation exposure due to its utilization in recent years is mostly at the level below natural radiation. The acute radiation syndrome by whole body exposure is shown, and the effect is probabilistic. The evaluation of the risks due to radiation in the early effect, the hereditary effect and the delayed effect including canceration is explained. The risks in general human activities, the concept of risks in radiation protection, the effect of Chernobyl accident and the perception of general public on radiation risks are reported. (K.I.)

Society of Thoracic Surgeons Risk Score Predicts Hospital Charges and Resource Utilization After Aortic Valve Replacement

Science.gov (United States)

Arnaoutakis, George J.; George, Timothy J.; Alejo, Diane E.; Merlo, Christian A.; Baumgartner, William A.; Cameron, Duke E.; Shah, Ashish S.

2011-01-01

Context The impact of Society of Thoracic Surgeons (STS) predicted mortality risk score on resource utilization after aortic valve replacement (AVR) has not been previously studied. Objective We hypothesize that increasing STS risk scores in patients having AVR are associated with greater hospital charges. Design, Setting, and Patients Clinical and financial data for patients undergoing AVR at a tertiary care, university hospital over a ten-year period (1/2000–12/2009) were retrospectively reviewed. The current STS formula (v2.61) for in-hospital mortality was used for all patients. After stratification into risk quartiles (Q), index admission hospital charges were compared across risk strata with Rank-Sum tests. Linear regression and Spearman’s coefficient assessed correlation and goodness of fit. Multivariable analysis assessed relative contributions of individual variables on overall charges. Main Outcome Measures Inflation-adjusted index hospitalization total charges Results 553 patients had AVR during the study period. Average predicted mortality was 2.9% (±3.4) and actual mortality was 3.4% for AVR. Median charges were greater in the upper Q of AVR patients [Q1–3,$39,949 (IQR32,708–51,323) vs Q4,$62,301 (IQR45,952–97,103), p=<0.01]. On univariate linear regression, there was a positive correlation between STS risk score and log-transformed charges (coefficient: 0.06, 95%CI 0.05–0.07, p<0.01). Spearman’s correlation R-value was 0.51. This positive correlation persisted in risk-adjusted multivariable linear regression. Each 1% increase in STS risk score was associated with an added $3,000 in hospital charges. Conclusions This study showed increasing STS risk score predicts greater charges after AVR. As competing therapies such as percutaneous valve replacement emerge to treat high risk patients, these results serve as a benchmark to compare resource utilization. PMID:21497834

Proceedings of the sixteenth biennial low-rank fuels symposium

International Nuclear Information System (INIS)

1991-01-01

Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium

Proceedings of the sixteenth biennial low-rank fuels symposium

Energy Technology Data Exchange (ETDEWEB)

1991-01-01

Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium.

Using Power-Law Degree Distribution to Accelerate PageRank

Directory of Open Access Journals (Sweden)

Zhaoyan Jin

2012-12-01

Full Text Available The PageRank vector of a network is very important, for it can reflect the importance of a Web page in the World Wide Web, or of a people in a social network. However, with the growth of the World Wide Web and social networks, it needs more and more time to compute the PageRank vector of a network. In many real-world applications, the degree and PageRank distributions of these complex networks conform to the Power-Law distribution. This paper utilizes the degree distribution of a network to initialize its PageRank vector, and presents a Power-Law degree distribution accelerating algorithm of PageRank computation. Experiments on four real-world datasets show that the proposed algorithm converges more quickly than the original PageRank algorithm.

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

Science.gov (United States)

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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.

Risk aversion in medical decision making: a survey

OpenAIRE

Liliana Chicaíza; Mario García; Giancarlo Romano

2011-01-01

This article surveys the literature on risk aversion in medical decision making. The search covered Econlit, Jstor Science Direct and Springer Link since 1985. The results are classified in three topics: Risk aversion in the frameworks of Expected Utility and Rank Dependent Expected Utility theories, and the methodologies for measuring risk aversion and its applications to clinical situations from the points of view of economics and psychology. It was found that, despite conceptual and method...

A statistical approach to rank multiple priorities in Environmental Epidemiology: an example from high-risk areas in Sardinia, Italy

Directory of Open Access Journals (Sweden)

Dolores Catelan

2008-11-01

Full Text Available In Environmental Epidemiology, long lists of relative risk estimates from exposed populations are compared to a reference to scrutinize the dataset for extremes. Here, inference on disease profiles for given areas, or for fixed disease population signatures, are of interest and summaries can be obtained averaging over areas or diseases. We have developed a multivariate hierarchical Bayesian approach to estimate posterior rank distributions and we show how to produce league tables of ranks with credibility intervals useful to address the above mentioned inferential problems. Applying the procedure to a real dataset from the report “Environment and Health in Sardinia (Italy” we selected 18 areas characterized by high environmental pressure for industrial, mining or military activities investigated for 29 causes of deaths among male residents. Ranking diseases highlighted the increased burdens of neoplastic (cancerous, and non-neoplastic respiratory diseases in the heavily polluted area of Portoscuso. The averaged ranks by disease over areas showed lung cancer among the three highest positions.

Estimating Bird / Aircraft Collision Probabilities and Risk Utilizing Spatial Poisson Processes

Science.gov (United States)

2012-06-10

ESTIMATING BIRD/AIRCRAFT COLLISION PROBABILITIES AND RISK UTILIZING SPATIAL POISSON PROCESSES GRADUATE...AND RISK UTILIZING SPATIAL POISSON PROCESSES GRADUATE RESEARCH PAPER Presented to the Faculty Department of Operational Sciences...COLLISION PROBABILITIES AND RISK UTILIZING SPATIAL POISSON PROCESSES Brady J. Vaira, BS, MS Major, USAF Approved

Low-rank coal research. Quarterly report, January--March 1990

Energy Technology Data Exchange (ETDEWEB)

1990-08-01

This document contains several quarterly progress reports for low-rank coal research that was performed from January-March 1990. Reports in Control Technology and Coal Preparation Research are in Flue Gas Cleanup, Waste Management, and Regional Energy Policy Program for the Northern Great Plains. Reports in Advanced Research and Technology Development are presented in Turbine Combustion Phenomena, Combustion Inorganic Transformation (two sections), Liquefaction Reactivity of Low-Rank Coals, Gasification Ash and Slag Characterization, and Coal Science. Reports in Combustion Research cover Fluidized-Bed Combustion, Beneficiation of Low-Rank Coals, Combustion Characterization of Low-Rank Coal Fuels, Diesel Utilization of Low-Rank Coals, and Produce and Characterize HWD (hot-water drying) Fuels for Heat Engine Applications. Liquefaction Research is reported in Low-Rank Coal Direct Liquefaction. Gasification Research progress is discussed for Production of Hydrogen and By-Products from Coal and for Chemistry of Sulfur Removal in Mild Gas.

Multi-attribute utility theory. Toward a more general framework

International Nuclear Information System (INIS)

Beaudoin, F.; Munier, B.; Serquin, Y.; Ecole Normale Superieure, 94 - Cachan

1997-12-01

Optimizing maintenance programs for nuclear power plants is a difficult task. Beyond the reliability of the systems at hand, one has to consider several conflicting objectives such as safety, availability, maintenance costs, personal exposure to radiations, all under risk. Multi-Attributed Utility Theory is a widely used framework to cope with such problems. This procedure is, however, based on a set of axioms which imply an expected utility treatment of risk. It has been shown elsewhere that the risk structure to be considered in such cases does not correspond to behavior consistent with such a treatment of risk, but would rather correspond to a rank dependent evaluation type of model. The question raised is then how to use a multi-attributed scheme of preferences under such conditions. (author)

EFSA BIOHAZ Panel (EFSA Panel on Biological Hazards), 2015. Scientific Opinion on the development of a risk ranking toolbox for the EFSA BIOHAZ Panel

DEFF Research Database (Denmark)

Hald, Tine

-down tool to rank pathogens. Uncertainty needs to be addressed and communicated to decision makers and stakeholders as one of the outcomes of the risk ranking process. Uncertainty and variability can be represented by means of probability distributions. Techniques such as the NUSAP (numeral, unit, spread...

Incorporating linguistic, probabilistic, and possibilistic information in a risk-based approach for ranking contaminated sites.

Science.gov (United States)

Zhang, Kejiang; Achari, Gopal; Pei, Yuansheng

2010-10-01

Different types of uncertain information-linguistic, probabilistic, and possibilistic-exist in site characterization. Their representation and propagation significantly influence the management of contaminated sites. In the absence of a framework with which to properly represent and integrate these quantitative and qualitative inputs together, decision makers cannot fully take advantage of the available and necessary information to identify all the plausible alternatives. A systematic methodology was developed in the present work to incorporate linguistic, probabilistic, and possibilistic information into the Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), a subgroup of Multi-Criteria Decision Analysis (MCDA) methods for ranking contaminated sites. The identification of criteria based on the paradigm of comparative risk assessment provides a rationale for risk-based prioritization. Uncertain linguistic, probabilistic, and possibilistic information identified in characterizing contaminated sites can be properly represented as numerical values, intervals, probability distributions, and fuzzy sets or possibility distributions, and linguistic variables according to their nature. These different kinds of representation are first transformed into a 2-tuple linguistic representation domain. The propagation of hybrid uncertainties is then carried out in the same domain. This methodology can use the original site information directly as much as possible. The case study shows that this systematic methodology provides more reasonable results. © 2010 SETAC.

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

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.

Prudence, preapproval, risk, and utility accountability

International Nuclear Information System (INIS)

Anon.

1992-01-01

This section discusses the inherent risk in utility compliance planning and some means of reducing this risk. The risk originates from the fact that a compliance plan is extremely complex and involves forecasting situations fifteen or twenty years into the future. Two additional uncertainties peculiar to CAAA compliance are that the increased demand for low-sulfur coal and other substitute fuels is expected to place an unanticipatable premium on them and that the price of future emissions allowances is unknown. The prudent investment test and the issue of preapproval are also discussed. 14 refs

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

Science.gov (United States)

Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

Defining utility trace substance emissions and risks

International Nuclear Information System (INIS)

Torrens, I.M.

1993-01-01

An update is presented on the activities of EPRI and other organizations, including DOE, aimed at improving the quality of available information on utility trace element emissions, control technologies and risks. Because of these efforts, the state of knowledge is advancing rapidly. The 1990 Clean Air Act Amendments aim to reduce emissions of 189 substances that they designate as hazardous air pollutants - commonly called air toxics. The more neutral term open-quotes trace substancesclose quotes is used in this paper, since most are emitted in extremely low concentrations from utility stacks. The degree of toxicity or hazard at these concentrations is subject to considerable uncertainty, and clarifying this is one of the objectives of the work in progress. The most clear and urgent need emanating from the CAAA has been to obtain reliable information on which of the substances on the CAAA list are emitted from different types of power plants - in what amounts, what risks they pose, how much is removed by today's pollution control equipment. EPRI is addressing the issue on several fronts, e.g.; developing a data base and tools that will enable utilities to estimate emissions levels from their power facilities, given the types of fuels burned and plant characteristics; developing a better understanding of how emissions are transported and transformed before they encounter humans and ecological systems; and assessing the risk to public health and the environment posed by utility releases of these substances

Subjective expected utility with non-increasing risk aversion

NARCIS (Netherlands)

Wakker, P.P.

1989-01-01

It is shown that assumptions about risk aversion, usually studied under the presupposition of expected utility maximization, have a surprising extra merit at an earlier stage of the measurement work: together with the sure-thing principle, these assumptions imply subjective expected utility

Ranking species in mutualistic networks

Science.gov (United States)

Domínguez-García, Virginia; Muñoz, Miguel A.

2015-02-01

Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic ``nested'' structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm -similar in spirit to Google's PageRank but with a built-in non-linearity- here we propose a method which -by exploiting their nested architecture- allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made.

Economics versus psychology.Risk, uncertainty and the expected utility theory

OpenAIRE

Schilirò, Daniele

2017-01-01

The present contribution examines the emergence of expected utility theory by John von Neumann and Oskar Morgenstern, the subjective the expected utility theory by Savage, and the problem of choice under risk and uncertainty, focusing in particular on the seminal work “The Utility Analysis of Choices involving Risk" (1948) by Milton Friedman and Leonard Savage to show how the evolution of the theory of choice has determined a separation of economics from psychology.

Does resident ranking during recruitment accurately predict subsequent performance as a surgical resident?

Science.gov (United States)

Fryer, Jonathan P; Corcoran, Noreen; George, Brian; Wang, Ed; Darosa, Debra

2012-01-01

While the primary goal of ranking applicants for surgical residency training positions is to identify the candidates who will subsequently perform best as surgical residents, the effectiveness of the ranking process has not been adequately studied. We evaluated our general surgery resident recruitment process between 2001 and 2011 inclusive, to determine if our recruitment ranking parameters effectively predicted subsequent resident performance. We identified 3 candidate ranking parameters (United States Medical Licensing Examination [USMLE] Step 1 score, unadjusted ranking score [URS], and final adjusted ranking [FAR]), and 4 resident performance parameters (American Board of Surgery In-Training Examination [ABSITE] score, PGY1 resident evaluation grade [REG], overall REG, and independent faculty rating ranking [IFRR]), and assessed whether the former were predictive of the latter. Analyses utilized Spearman correlation coefficient. We found that the URS, which is based on objective and criterion based parameters, was a better predictor of subsequent performance than the FAR, which is a modification of the URS based on subsequent determinations of the resident selection committee. USMLE score was a reliable predictor of ABSITE scores only. However, when we compared our worst residence performances with the performances of the other residents in this evaluation, the data did not produce convincing evidence that poor resident performances could be reliably predicted by any of the recruitment ranking parameters. Finally, stratifying candidates based on their rank range did not effectively define a ranking cut-off beyond which resident performance would drop off. Based on these findings, we recommend surgery programs may be better served by utilizing a more structured resident ranking process and that subsequent adjustments to the rank list generated by this process should be undertaken with caution. Copyright © 2012 Association of Program Directors in Surgery

Risk Decision Making Model for Reservoir Floodwater resources Utilization

Science.gov (United States)

Huang, X.

2017-12-01

Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

Expected utility and catastrophic risk in a stochastic economy-climate model

Energy Technology Data Exchange (ETDEWEB)

Ikefuji, M. [Institute of Social and Economic Research, Osaka University, Osaka (Japan); Laeven, R.J.A.; Magnus, J.R. [Department of Econometrics and Operations Research, Tilburg University, Tilburg (Netherlands); Muris, C. [CentER, Tilburg University, Tilburg (Netherlands)

2010-11-15

In the context of extreme climate change, we ask how to conduct expected utility analysis in the presence of catastrophic risks. Economists typically model decision making under risk and uncertainty by expected utility with constant relative risk aversion (power utility); statisticians typically model economic catastrophes by probability distributions with heavy tails. Unfortunately, the expected utility framework is fragile with respect to heavy-tailed distributional assumptions. We specify a stochastic economy-climate model with power utility and explicitly demonstrate this fragility. We derive necessary and sufficient compatibility conditions on the utility function to avoid fragility and solve our stochastic economy-climate model for two examples of such compatible utility functions. We further develop and implement a procedure to learn the input parameters of our model and show that the model thus specified produces quite robust optimal policies. The numerical results indicate that higher levels of uncertainty (heavier tails) lead to less abatement and consumption, and to more investment, but this effect is not unlimited.

Use of mechanistic simulations as a quantitative risk-ranking tool within the quality by design framework.

Science.gov (United States)

Stocker, Elena; Toschkoff, Gregor; Sacher, Stephan; Khinast, Johannes G

2014-11-20

The purpose of this study is to evaluate the use of computer simulations for generating quantitative knowledge as a basis for risk ranking and mechanistic process understanding, as required by ICH Q9 on quality risk management systems. In this specific publication, the main focus is the demonstration of a risk assessment workflow, including a computer simulation for the generation of mechanistic understanding of active tablet coating in a pan coater. Process parameter screening studies are statistically planned under consideration of impacts on a potentially critical quality attribute, i.e., coating mass uniformity. Based on computer simulation data the process failure mode and effects analysis of the risk factors is performed. This results in a quantitative criticality assessment of process parameters and the risk priority evaluation of failure modes. The factor for a quantitative reassessment of the criticality and risk priority is the coefficient of variation, which represents the coating mass uniformity. The major conclusion drawn from this work is a successful demonstration of the integration of computer simulation in the risk management workflow leading to an objective and quantitative risk assessment. Copyright © 2014. Published by Elsevier B.V.

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}.

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

Science.gov (United States)

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

Assessing safety risk in electricity distribution processes using ET & BA improved technique and its ranking by VIKOR and TOPSIS models in fuzzy environment

Directory of Open Access Journals (Sweden)

S. Rahmani

2016-04-01

  Conclusion: The height and electricity are of the main causes of accidents in electricity transmission and distribution industry which caused the overhead power networks to be ranked as high risk. Application of decision-making models in fuzzy environment minimizes the judgment of assessors in the risk assessment process.

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.

Escaping the repugnant conclusion: rank-discounted utilitarianism with variable population

OpenAIRE

Asheim, Geir Bjarne; Zuber, Stéphane

2014-01-01

We contribute to population ethics by proposing and axiomatizing rank-discounted critical-level generalized utilitarianism (RDCLU). Population ethics is needed for evaluation of policies, e.g., concerning climate change, where population size depends on the chosen policy. We show that critical-level generalized utilitarianism and (a version of) critical-level leximin are the limits of RDCLU for extreme values of the rank utility discount factor. Moreover, we establish how RDCLU avoids serious...

An empirical study for ranking risk factors using linear assignment: A case study of road construction

Directory of Open Access Journals (Sweden)

Amin Foroughi

2012-04-01

Full Text Available Road construction projects are considered as the most important governmental issues since there are normally heavy investments required in such projects. There is also shortage of financial resources in governmental budget, which makes the asset allocation more challenging. One primary step in reducing the cost is to determine different risks associated with execution of such project activities. In this study, we present some important risk factors associated with road construction in two levels for a real-world case study of rail-road industry located between two cities of Esfahan and Deligan. The first group of risk factors includes the probability and the effects for various attributes including cost, time, quality and performance. The second group of risk factors includes socio-economical factors as well as political and managerial aspects. The study finds 21 main risk factors as well as 193 sub risk factors. The factors are ranked using groups decision-making method called linear assignment. The preliminary results indicate that the road construction projects could finish faster with better outcome should we carefully consider risk factors and attempt to reduce their impacts.

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.

Appraising longitudinal trends in the strategic risks cited by risk managers in the international water utility sector, 2005-2015.

Science.gov (United States)

Chalker, Rosemary T C; Pollard, Simon J T; Leinster, Paul; Jude, Simon

2018-03-15

We report dynamic changes in the priorities for strategic risks faced by international water utilities over a 10year period, as cited by managers responsible for managing them. A content analysis of interviews with three cohorts of risk managers in the water sector was undertaken. Interviews probed the focus risk managers' were giving to strategic risks within utilities, as well as specific questions on risk analysis tools (2005); risk management cultures (2011) and the integration of risk management with corporate decision-making (2015). The coding frequency of strategic (business, enterprise, corporate) risk terms from 18 structured interviews (2005) and 28 semi-structured interviews (12 in 2011; 16 in 2015) was used to appraise changes in the perceived importance of strategic risks within the sector. The aggregated coding frequency across the study period, and changes in the frequency of strategic risks cited at three interview periods identified infrastructure assets as the most significant risk over the period and suggests an emergence of extrinsic risk over time. Extended interviews with three utility risk managers (2016) from the UK, Canada and the US were then used to contextualise the findings. This research supports the ongoing focus on infrastructure resilience and the increasing prevalence of extrinsic risk within the water sector, as reported by the insurance sector and by water research organisations. The extended interviews provided insight into how strategic risks are now driving the implementation agenda within utilities, and into how utilities can secure tangible business value from proactive risk governance. Strategic external risks affecting the sector are on the rise, involve more players and are less controllable from within a utility's own organisational boundaries. Proportionate risk management processes and structures provide oversight and assurance, whilst allowing a focus on the tangible business value that comes from managing strategic

an investigation into n investigation into index ranking technique

African Journals Online (AJOL)

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probability theory, namely, the Monte C. Simulation ... The study shows that the utility of the ranking technique may be limited by em. Therefore ... in decision making under fuzzy. The use of ... thereby making decision making impossible or.

Risk ranking of LANL nuclear material storage containers for repackaging prioritization.

Science.gov (United States)

Smith, Paul H; Jordan, Hans; Hoffman, Jenifer A; Eller, P Gary; Balkey, Simon

2007-05-01

Safe handling and storage of nuclear material at U.S. Department of Energy facilities relies on the use of robust containers to prevent container breaches and subsequent worker contamination and uptake. The U.S. Department of Energy has no uniform requirements for packaging and storage of nuclear materials other than those declared excess and packaged to DOE-STD-3013-2000. This report describes a methodology for prioritizing a large inventory of nuclear material containers so that the highest risk containers are repackaged first. The methodology utilizes expert judgment to assign respirable fractions and reactivity factors to accountable levels of nuclear material at Los Alamos National Laboratory. A relative risk factor is assigned to each nuclear material container based on a calculated dose to a worker due to a failed container barrier and a calculated probability of container failure based on material reactivity and container age. This risk-based methodology is being applied at LANL to repackage the highest risk materials first and, thus, accelerate the reduction of risk to nuclear material handlers.

Electric-utility returns and risk in the light of Three Mile Island

International Nuclear Information System (INIS)

Brooks, L.D.; D'Souza, R.E.

1982-01-01

The impact of the Three Mile Island nuclear-generating-unit failure on the performance of nuclear-dependent electric utilities is examined in this article. A comparative examination of the time series of abnormal returns and risk measures on nuclear-dependent utilities and nondependent utilities prior to the TMI incident, at the time of the incident, and subsequent to it was performed by the authors. The results are consistent with a hypothesis that investors associate a decline in future profitability or increased risk with nuclear-associated utilities. However, the more-objective measures indicate a clear reduction in risk for nuclear-associated utilities since the TMI incident, both in relation to the market as a whole and in relation to electric utilities which are not nuclear-associated. 4 references, 1 figure, 3 tables

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)

International Nuclear Information System (INIS)

Gao, Hao; Osher, Stanley; Yu, Hengyong; Wang, Ge

2011-01-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. (papers)

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

Science.gov (United States)

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.

NNP-LANL Utilities - Condition Assessment and Project Approach

Energy Technology Data Exchange (ETDEWEB)

Stewart, Grant Lorenz [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-21

This report is a presentation on LANL Utilities & Transportation Asset Management; Utility Assets Overview; Condition Assessment; Utilities Project Nominations & Ranking; and Utilities Project Execution.

RANKL/RANK: from bone loss to the prevention of breast cancer.

Science.gov (United States)

Sigl, Verena; Jones, Laundette P; Penninger, Josef M

2016-11-01

RANK and RANKL, a receptor ligand pair belonging to the tumour necrosis factor family, are the critical regulators of osteoclast development and bone metabolism. Besides their essential function in bone, RANK and RANKL have also been identified as the key factors for the formation of a lactating mammary gland in pregnancy. Mechanistically, RANK and RANKL link the sex hormone progesterone with stem cell expansion and proliferation of mammary epithelial cells. Based on their normal physiology, RANKL/RANK control the onset of hormone-induced breast cancer through the expansion of mammary progenitor cells. Recently, we and others were able to show that RANK and RANKL are also critical regulators of BRCA1-mutation-driven breast cancer. Currently, the preventive strategy for BRCA1-mutation carriers includes preventive mastectomy, associated with wide-ranging risks and psychosocial effects. The search for an alternative non-invasive prevention strategy is therefore of paramount importance. As our work strongly implicates RANK and RANKL as key molecules involved in the initiation of BRCA1-associated breast cancer, we propose that anti-RANKL therapy could be a feasible preventive strategy for women carrying BRCA1 mutations, and by extension to other women with high risk of breast cancer. © 2016 The Authors.

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.

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...

Are university rankings useful to improve research? A systematic review.

Science.gov (United States)

Vernon, Marlo M; Balas, E Andrew; Momani, Shaher

2018-01-01

Concerns about reproducibility and impact of research urge improvement initiatives. Current university ranking systems evaluate and compare universities on measures of academic and research performance. Although often useful for marketing purposes, the value of ranking systems when examining quality and outcomes is unclear. The purpose of this study was to evaluate usefulness of ranking systems and identify opportunities to support research quality and performance improvement. A systematic review of university ranking systems was conducted to investigate research performance and academic quality measures. Eligibility requirements included: inclusion of at least 100 doctoral granting institutions, be currently produced on an ongoing basis and include both global and US universities, publish rank calculation methodology in English and independently calculate ranks. Ranking systems must also include some measures of research outcomes. Indicators were abstracted and contrasted with basic quality improvement requirements. Exploration of aggregation methods, validity of research and academic quality indicators, and suitability for quality improvement within ranking systems were also conducted. A total of 24 ranking systems were identified and 13 eligible ranking systems were evaluated. Six of the 13 rankings are 100% focused on research performance. For those reporting weighting, 76% of the total ranks are attributed to research indicators, with 24% attributed to academic or teaching quality. Seven systems rely on reputation surveys and/or faculty and alumni awards. Rankings influence academic choice yet research performance measures are the most weighted indicators. There are no generally accepted academic quality indicators in ranking systems. No single ranking system provides a comprehensive evaluation of research and academic quality. Utilizing a combined approach of the Leiden, Thomson Reuters Most Innovative Universities, and the SCImago ranking systems may provide

Hazard-ranking of agricultural pesticides for chronic health effects in Yuma County, Arizona.

Science.gov (United States)

Sugeng, Anastasia J; Beamer, Paloma I; Lutz, Eric A; Rosales, Cecilia B

2013-10-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam-sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. Copyright © 2013 Elsevier B.V. All rights reserved.

Hazard-Ranking of Agricultural Pesticides for Chronic Health Effects in Yuma County, Arizona

Science.gov (United States)

Sugeng, Anastasia J.; Beamer, Paloma I.; Lutz, Eric A.; Rosales, Cecilia B.

2013-01-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. PMID:23783270

Synfuels from low-rank coals at the Great Plains Gasification Plant

International Nuclear Information System (INIS)

Pollock, D.

1992-01-01

This presentation focuses on the use of low rank coals to form synfuels. A worldwide abundance of low rank coals exists. Large deposits in the United States are located in Texas and North Dakota. Low rank coal deposits are also found in Europe, India and Australia. Because of the high moisture content of lignite ranging from 30% to 60% or higher, it is usually utilized in mine mouth applications. Lignite is generally very reactive and contains varying amounts of ash and sulfur. Typical uses for lignite are listed. A commercial application using lignite as feedstock to a synfuels plant, Dakota Gasification Company's Great Plains Gasification Plant, is discussed

RankProdIt: A web-interactive Rank Products analysis tool

Directory of Open Access Journals (Sweden)

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

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.

Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy.

Science.gov (United States)

Tian, Yuling; Zhang, Hongxian

2016-01-01

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic-there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.

Small Stakes Risk Aversion in the Laboratory

DEFF Research Database (Denmark)

Harrison, Glenn W.; Lau, Morten; Ross, Don

Evidence of risk aversion in laboratory settings over small stakes leads to a priori implausible levels of risk aversion over large stakes under certain assumptions. One core assumption in standard statements of this calibration puzzle is that individuals define utility over terminal wealth......, and that terminal wealth is defined as the sum of extra-lab wealth and any wealth accumulated in the lab. This assumption is often used in Expected Utility Theory, as well as popular alternatives such as RankDependent Utility theory. Another core assumption is that the small-stakes risk aversion is observed over...... all levels of wealth, or over a “sufficiently large” range of wealth. Although this second assumption if often viewed as self-evident from the vast experimental literature showing risk aversion over laboratory stakes, it actually requires that lab wealth be varied for a given subject as one takes...

Risk management strategies utilized by small scale poultry farmers ...

African Journals Online (AJOL)

Birds can only tolerate narrow temperature changes; therefore, poultry flocks are vulnerable to climate induced risk. This study investigated risk management strategies utilized by small scale poultry farmers in Oyo state. A total of 118 respondents were sampled using multi stage sampling procedure. Interview schedule was ...

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.

Applying the Analytic Hierarchy Process to Oil Sands Environmental Compliance Risk Management

Science.gov (United States)

Roux, Izak Johannes, III

Oil companies in Alberta, Canada, invested $32 billion on new oil sands projects in 2013. Despite the size of this investment, there is a demonstrable deficiency in the uniformity and understanding of environmental legislation requirements that manifest into increased project compliance risks. This descriptive study developed 2 prioritized lists of environmental regulatory compliance risks and mitigation strategies and used multi-criteria decision theory for its theoretical framework. Information from compiled lists of environmental compliance risks and mitigation strategies was used to generate a specialized pairwise survey, which was piloted by 5 subject matter experts (SMEs). The survey was validated by a sample of 16 SMEs, after which the Analytic Hierarchy Process (AHP) was used to rank a total of 33 compliance risks and 12 mitigation strategy criteria. A key finding was that the AHP is a suitable tool for ranking of compliance risks and mitigation strategies. Several working hypotheses were also tested regarding how SMEs prioritized 1 compliance risk or mitigation strategy compared to another. The AHP showed that regulatory compliance, company reputation, environmental compliance, and economics ranked the highest and that a multi criteria mitigation strategy for environmental compliance ranked the highest. The study results will inform Alberta oil sands industry leaders about the ranking and utility of specific compliance risks and mitigations strategies, enabling them to focus on actions that will generate legislative and public trust. Oil sands leaders implementing a risk management program using the risks and mitigation strategies identified in this study will contribute to environmental conservation, economic growth, and positive social change.

Wilcoxon's signed-rank statistic: what null hypothesis and why it matters.

Science.gov (United States)

Li, Heng; Johnson, Terri

2014-01-01

In statistical literature, the term 'signed-rank test' (or 'Wilcoxon signed-rank test') has been used to refer to two distinct tests: a test for symmetry of distribution and a test for the median of a symmetric distribution, sharing a common test statistic. To avoid potential ambiguity, we propose to refer to those two tests by different names, as 'test for symmetry based on signed-rank statistic' and 'test for median based on signed-rank statistic', respectively. The utility of such terminological differentiation should become evident through our discussion of how those tests connect and contrast with sign test and one-sample t-test. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Multi-Label Classification Based on Low Rank Representation for Image Annotation

Directory of Open Access Journals (Sweden)

Qiaoyu Tan

2017-01-01

Full Text Available Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels. To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR. MLC-LRR firstly utilizes low rank representation in the feature space of images to compute the low rank constrained coefficient matrix, then it adapts the coefficient matrix to define a feature-based graph and to capture the global relationships between images. Next, it utilizes low rank representation in the label space of labeled images to construct a semantic graph. Finally, these two graphs are exploited to train a graph-based multi-label classifier. To validate the performance of MLC-LRR against other related graph-based multi-label methods in annotating images, we conduct experiments on a public available multi-label remote sensing images (Land Cover. We perform additional experiments on five real-world multi-label image datasets to further investigate the performance of MLC-LRR. Empirical study demonstrates that MLC-LRR achieves better performance on annotating images than these comparing methods across various evaluation criteria; it also can effectively exploit global structure and label correlations of multi-label images.

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.

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.

Low-rank coal research, Task 5.1. Topical report, April 1986--December 1992

Energy Technology Data Exchange (ETDEWEB)

1993-02-01

This document is a topical progress report for Low-Rank Coal Research performed April 1986 - December 1992. Control Technology and Coal Preparation Research is described for Flue Gas Cleanup, Waste Management, Regional Energy Policy Program for the Northern Great Plains, and Hot-Gas Cleanup. Advanced Research and Technology Development was conducted on Turbine Combustion Phenomena, Combustion Inorganic Transformation (two sections), Liquefaction Reactivity of Low-Rank Coals, Gasification Ash and Slag Characterization, and Coal Science. Combustion Research is described for Atmospheric Fluidized-Bed Combustion, Beneficiation of Low-Rank Coals, Combustion Characterization of Low-Rank Fuels (completed 10/31/90), Diesel Utilization of Low-Rank Coals (completed 12/31/90), Produce and Characterize HWD (hot-water drying) Fuels for Heat Engine Applications (completed 10/31/90), Nitrous Oxide Emission, and Pressurized Fluidized-Bed Combustion. Liquefaction Research in Low-Rank Coal Direct Liquefaction is discussed. Gasification Research was conducted in Production of Hydrogen and By-Products from Coals and in Sulfur Forms in Coal.

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.

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.

Prospect relativity: how choice options influence decision under risk.

Science.gov (United States)

Stewart, Neil; Chater, Nick; Stott, Henry P; Reimers, Stian

2003-03-01

In many theories of decision under risk (e.g., expected utility theory, rank-dependent utility theory, and prospect theory), the utility of a prospect is independent of other options in the choice set. The experiments presented here show a large effect of the available options, suggesting instead that prospects are valued relative to one another. The judged certainty equivalent for a prospect is strongly influenced by the options available. Similarly, the selection of a preferred prospect is strongly influenced by the prospects available. Alternative theories of decision under risk (e.g., the stochastic difference model, multialternative decision field theory, and range frequency theory), where prospects are valued relative to one another, can provide an account of these context effects.

Ranking environmental liabilities at a petroleum refinery

International Nuclear Information System (INIS)

Lupo, M.

1995-01-01

A new computer model is available to allow the management of a petroleum refinery to prioritize environmental action and construct a holistic approach to remediation. A large refinery may have numerous solid waste management units regulated by the Resource Conservation and Recovery Act (RCRA), as well as process units that emit hazardous chemicals into the environment. These sources can impact several environmental media, potentially including the air, the soil, the groundwater, the unsaturated zone water, and surface water. The number of chemicals of concern may be large. The new model is able to rank the sources by considering the impact of each chemical in each medium from each source in terms of concentration, release rate, and a weighted index based on toxicity. In addition to environmental impact, the sources can be ranked in three other ways: (1) by cost to remediate, (2) by environmental risk reduction caused by the remediation in terms of the decreases in release rate, concentration, and weighted index, and (3) by cost-benefit, which is the environmental risk reduction for each source divided by the cost of the remedy. Ranking each unit in the refinery allows management to use its limited environmental resources in a pro-active strategic manner that produces long-term results, rather than in reactive, narrowly focused, costly, regulatory-driven campaigns that produce only short-term results

Optimal investment and indifference pricing when risk aversion is not monotone: SAHARA utility functions

NARCIS (Netherlands)

Chen, A.; Pelsser, A.; Vellekoop, M.

2008-01-01

Abstract. We develop a new class of utility functions, SAHARA utility, with the dis- tinguishing feature that they implement the assumption that agents may become less risk-averse for very low values of wealth. This means that SAHARA utility can be used to characterize risk gambling behavior of an

Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

Directory of Open Access Journals (Sweden)

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.

Geographic exposure risk of variant Creutzfeldt-Jakob disease in US blood donors: a risk-ranking model to evaluate alternative donor-deferral policies.

Science.gov (United States)

Yang, Hong; Huang, Yin; Gregori, Luisa; Asher, David M; Bui, Travis; Forshee, Richard A; Anderson, Steven A

2017-04-01

Variant Creutzfeldt-Jakob disease (vCJD) has been transmitted by blood transfusion (TTvCJD). The US Food and Drug Administration (FDA) recommends deferring blood donors who resided in or traveled to 30 European countries where they may have been exposed to bovine spongiform encephalopathy (BSE) through beef consumption. Those recommendations warrant re-evaluation, because new cases of BSE and vCJD have markedly abated. The FDA developed a risk-ranking model to calculate the geographic vCJD risk using country-specific case rates and person-years of exposure of US blood donors. We used the reported country vCJD case rates, when available, or imputed vCJD case rates from reported BSE and UK beef exports during the risk period. We estimated the risk reduction and donor loss should the deferral be restricted to a few high-risk countries. We also estimated additional risk reduction by leukocyte reduction (LR) of red blood cells (RBCs). The United Kingdom, Ireland, and France had the greatest vCJD risk, contributing approximately 95% of the total risk. The model estimated that deferring US donors who spent extended periods of time in these three countries, combined with currently voluntary LR (95% of RBC units), would reduce the vCJD risk by 89.3%, a reduction similar to that achieved under the current policy (89.8%). Limiting deferrals to exposure in these three countries would potentially allow donations from an additional 100,000 donors who are currently deferred. Our analysis suggests that a deferral option focusing on the three highest risk countries would achieve a level of blood safety similar to that achieved by the current policy. © 2016 AABB.

World Health Organization Ranking of Antimicrobials According to Their Importance in Human Medicine: A Critical Step for Developing Risk Management Strategies for the Use of Antimicrobials in Food Production Animals

DEFF Research Database (Denmark)

Collignon, P.; Powers, J. H.; Chiller, T. M.

2009-01-01

stakeholders can use this ranking when developing risk management strategies for the use of antimicrobials in food production animals. The ranking allows stakeholders to focus risk management efforts on drugs used in food animals that are the most important to human medicine and, thus, need to be addressed......The use of antimicrobials in food animals creates an important source of antimicrobial-resistant bacteria that can spread to humans through the food supply. Improved management of the use of antimicrobials in food animals, particularly reducing the usage of those that are "critically important...

VaRank: a simple and powerful tool for ranking genetic variants

Directory of Open Access Journals (Sweden)

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/.

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.

Organ utilization from increased infectious risk donors: An observational study.

Science.gov (United States)

L'Huillier, Arnaud G; Humar, Atul; Payne, Clare; Kumar, Deepali

2017-12-01

Donors with an increased risk of transmitting human immunodeficiency virus (HIV), hepatitis B virus (HBV), or hepatitis C virus (HCV) (increased risk donors [IRDs]) are a potential source of organs for transplant. Organs from IRDs can be utilized with appropriate recipient consent and post-transplant follow-up. We reviewed the characteristics and utilization of IRDs in our Organ Procurement Organization (OPO) over a 2-year period. Donor information from April 1, 2013 to March 31, 2015 was obtained through the OPO database. Only consented donors were included. Donors were categorized as IRDs according to Health Canada/Canadian Standards Association (CSA) criteria. A total of 494 potential donors were identified, of which 92 (18.6%) were IRDs. Of these, at least one organ was transplanted from 76 (82.6%). Risk factors for IRDs included injection drug user (IDU) (12%), men having sex with men (MSM) (7%), commercial sex worker (CSW) (4%), and incarceration (24%). Fifty-nine percent (253/429) of IRD organs were utilized. The most frequently used organ was kidney, followed by liver. Median number of organs recovered per IRD was 3 (interquartile range: 2-5). Nucleic acid testing (NAT) was performed in 18.5% (17/92) of IRDs. Reasons for NAT were IDU (n = 2), MSM (n = 2), CSW (n = 2), and previous incarceration (n = 7). Organ utilization from donors that had NAT was similar to donors who did not (94% vs 80%, P = .29). Follow-up NAT was done in multiple factors contribute to the perception of infectious risk from such organs. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

Stochastic optimization under risk constraint and utility functions

International Nuclear Information System (INIS)

Seck, B.

2008-09-01

In a context of concurrence and emergence of energy markets, the production of electricity is affected by the new sources of risks which are the price variations on the energy markets. These new sources of risks generate a new risk: the market risk. In this research, the author explores the possibility of introducing constraints, expressed by measurements of risk, into the process of optimization of electricity production when financial contracts are signed on the energy market. The author makes the distinction between the engineering approach (taking the risk into account by risk measurements) and the economist approach (taking the risk into account by utility functions). After an overview of these both approaches in a static framework, he gives an economical formulation (a Maccheroni type one) for a static optimization problem under a risk constraint when the risk measurement is written under the form of an expected infimum like the variance, the 'conditional value at risk', and so on. The obtained results are then extended to a dynamic optimization framework under risk constraints. A numerical application of this approach is presented to solve a problem of electricity production management under a constraint of 'conditional value at risk' on a middle term

Project risk management for development of non-utility power generators (NUGs)

International Nuclear Information System (INIS)

Lau, T.

1990-01-01

The growing Non-Utility Generation (NUG) industry has brought new opportunities and challenges for the insurance industry. There can be unique engineering and financial risks involved in the development of Non-Utility Power Generation projects. The use of new technologies to meet stringent environmental regulations and to improve project performance and efficiency presents new challenges to the project developers and designers. The lack of funding, resources and experience of some of these projects may create unusual risks that could result in failure or deficiency in the performance of the projects

Screening and ranking framework (SRF) for geologic CO2 storagesite selection on the basis of HSE risk

Energy Technology Data Exchange (ETDEWEB)

Oldenburg, Curtis M.

2006-11-27

A screening and ranking framework (SRF) has been developedto evaluate potential geologic carbon dioxide (CO2) storage sites on thebasis of health, safety, and environmental (HSE) risk arising from CO2leakage. The approach is based on the assumption that CO2 leakage risk isdependent on three basic characteristics of a geologic CO2 storage site:(1) the potential for primary containment by the target formation; (2)the potential for secondary containment if the primary formation leaks;and (3) the potential for attenuation and dispersion of leaking CO2 ifthe primary formation leaks and secondary containment fails. Theframework is implemented in a spreadsheet in which users enter numericalscores representing expert opinions or published information along withestimates of uncertainty. Applications to three sites in Californiademonstrate the approach. Refinements and extensions are possible throughthe use of more detailed data or model results in place of propertyproxies.

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.

Balancing Cost and Risk: The Treatment of Renewable Energy in Western Utility Resource Plans

Energy Technology Data Exchange (ETDEWEB)

Bolinger, Mark; Wiser, Ryan

2005-08-10

Markets for renewable energy have historically been motivated primarily by policy efforts, but a less widely recognized driver is poised to also play a major role in the coming years: utility integrated resource planning (IRP). Resource planning has re-emerged in recent years as an important tool for utilities and regulators, particularly in regions where retail competition has failed to take root. In the western United States, the most recent resource plans contemplate a significant amount of renewable energy additions. These planned additions--primarily coming from wind power--are motivated by the improved economics of wind power, a growing acceptance of wind by electric utilities, and an increasing recognition of the inherent risks (e.g., natural gas price risk, environmental compliance risk) in fossil-based generation portfolios. This report examines how twelve western utilities treat renewable energy in their recent resource plans. In aggregate, these utilities supply approximately half of all electricity demand in the western United States. Our purpose is twofold: (1) to highlight the growing importance of utility IRP as a current and future driver of renewable energy, and (2) to identify methodological/modeling issues, and suggest possible improvements to methods used to evaluate renewable energy as a resource option. Here we summarize the key findings of the report, beginning with a discussion of the planned renewable energy additions called for by the twelve utilities, an overview of how these plans incorporated renewables into candidate portfolios, and a review of the specific technology cost and performance assumptions they made, primarily for wind power. We then turn to the utilities' analysis of natural gas price and environmental compliance risks, and examine how the utilities traded off portfolio cost and risk in selecting a preferred portfolio.

Judging statistical models of individual decision making under risk using in- and out-of-sample criteria.

Science.gov (United States)

Drichoutis, Andreas C; Lusk, Jayson L

2014-01-01

Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample.

Judging statistical models of individual decision making under risk using in- and out-of-sample criteria.

Directory of Open Access Journals (Sweden)

Andreas C Drichoutis

Full Text Available Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample.

A Model-Free Scheme for Meme Ranking in Social Media.

Science.gov (United States)

He, Saike; Zheng, Xiaolong; Zeng, Daniel

2016-01-01

The prevalence of social media has greatly catalyzed the dissemination and proliferation of online memes (e.g., ideas, topics, melodies, tags, etc.). However, this information abundance is exceeding the capability of online users to consume it. Ranking memes based on their popularities could promote online advertisement and content distribution. Despite such importance, few existing work can solve this problem well. They are either daunted by unpractical assumptions or incapability of characterizing dynamic information. As such, in this paper, we elaborate a model-free scheme to rank online memes in the context of social media. This scheme is capable to characterize the nonlinear interactions of online users, which mark the process of meme diffusion. Empirical studies on two large-scale, real-world datasets (one in English and one in Chinese) demonstrate the effectiveness and robustness of the proposed scheme. In addition, due to its fine-grained modeling of user dynamics, this ranking scheme can also be utilized to explain meme popularity through the lens of social influence.

Ranking Tool Created for Medicinal Plants at Risk of Being Overharvested in the Wild

Directory of Open Access Journals (Sweden)

Lisa Marie Castle

2014-05-01

Full Text Available We developed an adaptable, transparent tool that can be used to quantify and compare vulnerability to overharvest for wild collected medicinal plants. Subsequently, we are creating a list of the most threatened medicinal plants in temperate North America. The new tool scores species according to their life history, the effects of harvest, their abundance and range, habitat, and demand. The resulting rankings, based on explicit criteria rather than expert opinion, will make it easier to discuss areas of vulnerability and set conservation priorities. Here we present scores for 40 species assessed using the At-Risk Tool and discuss the traits that led to different scores for six example species: echinacea (Echinacea angustifolia DC. Asteraceae, peyote (Lophophora williamsii (Lem. ex Salm-Dyck J.M. Coult. Cactaceae, sandalwood (Santalum spp. L. Santalaceae, stinging nettle (Urtica dioica L. Urticaceae, American ginseng (Panax quinquefolius L. Araliaceae and mayapple (Podophyllum peltatum L. Berberidaceae.

Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

Science.gov (United States)

Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

2017-10-12

Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

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

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

Implications of deregulation in natural gas industry on utility risks and returns

Science.gov (United States)

Addepalli, Rajendra P.

This thesis examines the changes in risk and required return on capital for local distribution utility companies in the increasingly competitive natural gas industry. The deregulation in the industry impacts the LDCs in several ways. First, with the introduction of competition consumers have been given choices among suppliers besides the traditional monopoly, the local utility, for purchasing their natural gas supply needs. Second, with the introduction of competition, some of the interstate pipelines were stuck with 'Take Or Pay' contracts and other costs that resulted in 'stranded costs', which have been passed on to customers of the pipeline including the LDCs. Third, the new obligation for the LDCs to purchase gas from the market, as opposed to buying it from pipelines and passing on the costs to its customers, brought opportunities and risks as well. Finally, with the introduction of competition, in some states LDCs have been allowed to enter into unregulated ventures to increase their profits. In the thesis we first develop a multifactor model (MFM) to explain historical common stock returns of individual utilities and of utility portfolios. We use 'rolling regression' analysis to analyze how different variables explain the variation in stock returns over time. Second, we conduct event studies to analyze the events in the deregulation process that had significant impacts on the LDC returns. Finally we assess the changes in risk and required return on capital for the LDCs over a 15 year time frame, covering the deregulation period. We employ four aspects in the examination of risk and return profile of the utilities: measuring (a) changes in required return on common equity and Weighted Average Cost of Capital, (b) changes in risk premium (WACC less an interest rate proxy), (c) changes in utility bond ratings, and (d) changes in dividend payments, new debt and equity issuances. We perform regression analysis to explain the changes in the required WACC using

Low-rank coal research. Final technical report, April 1, 1988--June 30, 1989, including quarterly report, April--June 1989

Energy Technology Data Exchange (ETDEWEB)

1989-12-31

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).

Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization.

Science.gov (United States)

Jia, Zhilong; Zhang, Xiang; Guan, Naiyang; Bo, Xiaochen; Barnes, Michael R; Luo, Zhigang

2015-01-01

RNA-sequencing is rapidly becoming the method of choice for studying the full complexity of transcriptomes, however with increasing dimensionality, accurate gene ranking is becoming increasingly challenging. This paper proposes an accurate and sensitive gene ranking method that implements discriminant non-negative matrix factorization (DNMF) for RNA-seq data. To the best of our knowledge, this is the first work to explore the utility of DNMF for gene ranking. When incorporating Fisher's discriminant criteria and setting the reduced dimension as two, DNMF learns two factors to approximate the original gene expression data, abstracting the up-regulated or down-regulated metagene by using the sample label information. The first factor denotes all the genes' weights of two metagenes as the additive combination of all genes, while the second learned factor represents the expression values of two metagenes. In the gene ranking stage, all the genes are ranked as a descending sequence according to the differential values of the metagene weights. Leveraging the nature of NMF and Fisher's criterion, DNMF can robustly boost the gene ranking performance. The Area Under the Curve analysis of differential expression analysis on two benchmarking tests of four RNA-seq data sets with similar phenotypes showed that our proposed DNMF-based gene ranking method outperforms other widely used methods. Moreover, the Gene Set Enrichment Analysis also showed DNMF outweighs others. DNMF is also computationally efficient, substantially outperforming all other benchmarked methods. Consequently, we suggest DNMF is an effective method for the analysis of differential gene expression and gene ranking for RNA-seq data.

Novel Opportunistic Network Routing Based on Social Rank for Device-to-Device Communication

Directory of Open Access Journals (Sweden)

Tong Wang

2017-01-01

Full Text Available In recent years, there has been dramatic proliferation of research concerned with fifth-generation (5G mobile communication networks, among which device-to-device (D2D communication is one of the key technologies. Due to the intermittent connection of nodes, the D2D network topology may be disconnected frequently, which will lead to failure in transmission of large data files. In opportunistic networks, in case of encountering nodes which never meet before a flood message blindly to cause tremendous network overhead, a novel opportunistic network routing protocol based on social rank and intermeeting time (SRIT is proposed in this paper. An improved utility approach applied in utility replication based on encounter durations and intermeeting time is put forward to enhance the routing efficiency. Meanwhile, in order to select better candidate nodes in the network, a social graph among people is established when they socially relate to each other in social rank replication. The results under the scenario show an advantage of the proposed opportunistic network routing based on social rank and intermeeting time (SRIT over the compared algorithms in terms of delivery ratio, average delivery latency, and overhead ratio.

Perceptions of climate-related risk among water sector professionals in Africa-Insights from the 2016 African Water Association Congress.

Science.gov (United States)

Connolly, Katherine; Mbutu, Mwaura; Bartram, Jamie; Fuente, David

2018-04-23

The ability of water and wastewater utilities to provide safe and reliable water and sanitation services now and in the future will be determined, in part, by their resilience to climate change. Investment in infrastructure, planning, and operational practices that increase resilience are affected, in turn, by how water sector professionals perceive the risks posed to utilities by climate change and its related impacts. We surveyed water sector professionals at the 2016 African Water Association's Congress in Nairobi, Kenya to assess their perceptions of climate-specific and general risks that may disrupt utility service. We find that water sector professionals are most concerned about climate-specific and general risks that affect utility water supplies (quantity), followed by adequacy of utility infrastructure. We also find that professionals tend to rank climate-specific risks as less concerning than general risks facing utilities. Furthermore, non-utility professionals are more concerned about climate-specific risks and climate change in general than utility professionals. These findings highlight the multiple, competing risks utilities face and the need for adaptation strategies that simultaneously address climate-specific and general concerns of utilities. Copyright © 2018 Elsevier GmbH. All rights reserved.

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.

Evaluation and Ranking of Geothermal Resources for Electrical Generation or Electrical Offset in Idaho, Montana, Oregon and Washington. Volume II.

Energy Technology Data Exchange (ETDEWEB)

Bloomquist, R. Gordon

1985-06-01

This volume contains appendices on: (1) resource assessment - electrical generation computer results; (2) resource assessment summary - direct use computer results; (3) electrical generation (high temperature) resource assessment computer program listing; (4) direct utilization (low temperature) resource assessment computer program listing; (5) electrical generation computer program CENTPLANT and related documentation; (6) electrical generation computer program WELLHEAD and related documentation; (7) direct utilization computer program HEATPLAN and related documentation; (8) electrical generation ranking computer program GEORANK and related documentation; (9) direct utilization ranking computer program GEORANK and related documentation; and (10) life cycle cost analysis computer program and related documentation. (ACR)

Expert opinion on landslide susceptibility elicted by probabilistic inversion from scenario rankings

Science.gov (United States)

Lee, Katy; Dashwood, Claire; Lark, Murray

2016-04-01

For many natural hazards the opinion of experts, with experience in assessing susceptibility under different circumstances, is a valuable source of information on which to base risk assessments. This is particularly important where incomplete process understanding, and limited data, limit the scope to predict susceptibility by mechanistic or statistical modelling. The expert has a tacit model of a system, based on their understanding of processes and their field experience. This model may vary in quality, depending on the experience of the expert. There is considerable interest in how one may elicit expert understanding by a process which is transparent and robust, to provide a basis for decision support. One approach is to provide experts with a set of scenarios, and then to ask them to rank small overlapping subsets of these with respect to susceptibility. Methods of probabilistic inversion have been used to compute susceptibility scores for each scenario, implicit in the expert ranking. It is also possible to model these scores as functions of measurable properties of the scenarios. This approach has been used to assess susceptibility of animal populations to invasive diseases, to assess risk to vulnerable marine environments and to assess the risk in hypothetical novel technologies for food production. We will present the results of a study in which a group of geologists with varying degrees of expertise in assessing landslide hazards were asked to rank sets of hypothetical simplified scenarios with respect to land slide susceptibility. We examine the consistency of their rankings and the importance of different properties of the scenarios in the tacit susceptibility model that their rankings implied. Our results suggest that this is a promising approach to the problem of how experts can communicate their tacit model of uncertain systems to those who want to make use of their expertise.

Smoking is rank! But, not as rank as other drugs and bullying say New Zealand parents of pre-adolescent children.

Science.gov (United States)

Glover, Marewa; Kira, Anette; Min, Sandar; Scragg, Robert; Nosa, Vili; McCool, Judith; Bullen, Chris

2011-12-01

Despite the established risks associated with smoking, 21% of New Zealand adults smoke. Prevalence among Māori (indigenous) and Pacific Island New Zealanders is disproportionately high. Prevention of smoking initiation is a key component of tobacco control. Keeping Kids Smokefree--a quasi-experimental trial--aimed to do this by changing parental smoking behaviour and attitudes. However, little is known about parents' attitudes to smoking in comparison with other concerns. Parents of 4,144 children attending five urban schools in a high smoking prevalence population in Auckland, New Zealand, were asked to rank seven concerns on a paper-based questionnaire, including smoking, alcohol and bullying, from most to least serious. Methamphetamine and other illicit 'hard' drugs were ranked as most serious followed by marijuana smoking, alcohol drinking, bullying, cigarette smoking, sex and obesity. Never smokers ranked cigarette smoking as more serious than current or ex-smokers. Parents' under-estimation of the serious nature of tobacco smoking relative to other drugs could partly explain low participation rates in parent-focused smoking initiation prevention programs.

Investigation into the risk perceptions of investors in the securities of nuclear-dependent electric utilities

International Nuclear Information System (INIS)

Spudeck, R.E.

1983-01-01

Two weeks prior to the Three Mile Island accident, March 15, 1979, the Nuclear Regulatory Commission ordered five operating nuclear plants shut down in order to reexamine safety standards in these plants. Reports in the popular and trade press during this time suggested that these events, particularly the accident at Three Mile Island, caused investors in the securities of electric utilities that had nuclear-generation facilities to revise their risk perceptions. This study was designed to examine the impact of both the Nuclear Regulatory Commission order and the accident at Three Mile Island on investor risk perceptions. Selected categories of electric utilities were chosen to examine any differential risk effects resulting from these events. An asset pricing model devoid of many of the restrictive assumptions of more familiar models was used to model investor behavior. The findings suggest that the events described did cause investors to revise upward their perceptions of systematic risk regarding different categories of electric utilities. More specifically, those electric utilities that were operating nuclear plants in 1979 experienced the largest and most sustained increase in systematic risk. However, electric utilities that in 1979 had no operating nuclear plants, but had planned and committed funds for nuclear plants in the future, also experienced increases in systematic risk

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.

Balancing Cost and Risk: The Treatment of Renewable Energy inWestern Utility Resource Plans

Energy Technology Data Exchange (ETDEWEB)

Wiser, Ryan; Bolinger, Mark

2005-09-01

Markets for renewable electricity have grown significantly in recent years, motivated in part by federal tax incentives and in part by state renewables portfolio standards and renewable energy funds. State renewables portfolio standards, for example, motivated approximately 45% of the 4,300 MW of wind power installed in the U.S. from 2001 through 2004, while renewable energy funds supported an additional 15% of these installations. Despite the importance of these state policies, a less widely recognized driver for renewable energy market growth is poised to also play an important role in the coming years: utility integrated resource planning (IRP). Formal resource planning processes have re-emerged in recent years as an important tool for utilities and regulators, particularly in regions where retail competition has failed to take root. In the western United States, recent resource plans contemplate a significant amount of renewable energy additions. These planned additions - primarily coming from wind power - are motivated by the improved economics of wind power, a growing acceptance of wind by electric utilities, and an increasing recognition of the inherent risks (e.g., natural gas price risk, environmental compliance risk) in fossil-based generation portfolios. The treatment of renewable energy in utility resource plans is not uniform, however. Assumptions about the direct and indirect costs of renewable resources, as well as resource availability, differ, as do approaches to incorporating such resources into the candidate portfolios that are analyzed in utility IRPs. The treatment of natural gas price risk, as well as the risk of future environmental regulations, also varies substantially. How utilities balance expected portfolio cost versus risk in selecting a preferred portfolio also differs. Each of these variables may have a substantial effect on the degree to which renewable energy contributes to the preferred portfolio of each utility IRP. This article

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.

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.

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 ...

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.

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.

Hierarchical partial order ranking

International Nuclear Information System (INIS)

Carlsen, Lars

2008-01-01

Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

Qualitative risk assessment as a remediation management tool

International Nuclear Information System (INIS)

Knutson, D.E.

1991-01-01

The technique used to complete this thesis utilizes existing NRC and EPA guidance on health-based risk to qualitatively prioritize preliminary assessments and provide a tool for the direction and management of remediation activities. This method is intended as a decision making tool to aid in prioritizing the remediation effort and manage the remedial investigation and feasibility study (RI/FS) process. It is not a replacement for the RI/FS. The methodology for qualitative risk assessment utilizes data gathered in preliminary assessments and calculates the health-based hazards and consequences from contaminants found at each individual location. The health-based qualitative risk indicated that number-sign 6 fuel oil, carbon tetrachloride, depleted uranium, and enriched uranium were the contaminants of major concern, in that order. Plutonium ranked approximately sixth in the contaminant of concern priority. 38 refs., 1 fig., 9 tabs

Utility of the exercise electrocardiogram testing in sudden cardiac death risk stratification.

Science.gov (United States)

Refaat, Marwan M; Hotait, Mostafa; Tseng, Zian H

2014-07-01

Sudden cardiac death (SCD) remains a major public health problem. Current established criteria identifying those at risk of sudden arrhythmic death, and likely to benefit from implantable cardioverter defibrillators (ICDs), are neither sensitive nor specific. Exercise electrocardiogram (ECG) testing was traditionally used for information concerning patients' symptoms, exercise capacity, cardiovascular function, myocardial ischemia detection, and hemodynamic responses during activity in patients with hypertrophic cardiomyopathy. We conducted a systematic review of MEDLINE on the utility of exercise ECG testing in SCD risk stratification. Exercise testing can unmask suspected primary electrical diseases in certain patients (catecholaminergic polymorphic ventricular tachycardia or concealed long QT syndrome) and can be effectively utilized to risk stratify patients at an increased (such as early repolarization syndrome and Brugada syndrome) or decreased risk of SCD, such as the loss of preexcitation on exercise testing in asymptomatic Wolff-Parkinson-White syndrome. Exercise ECG testing helps in SCD risk stratification in patients with and without arrhythmogenic hereditary syndromes. © 2014 Wiley Periodicals, Inc.

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...

Determinants of Mental Health Care Utilization in a Suicide High-risk Group With Suicidal Ideation

Directory of Open Access Journals (Sweden)

Hyun-Soo Kim

2016-01-01

Full Text Available Objectives: The suicide rate in Korea is increasing every year, and is the highest among the Organization for Economic Cooperation and Development countries. Psychiatric patients in particular have a higher risk of suicide than other patients. This study was performed to evaluate determinants of mental health care utilization among individuals at high risk for suicide. Methods: Korea Health Panel data from 2009 to 2011 were used. Subjects were individuals at high risk of suicide who had suicidal ideation, a past history of psychiatric illness, or had utilized outpatient services for a psychiatric disorder associated with suicidal ideation within the past year. The chi-square test and hierarchical logistic regression were used to identify significant determinants of mental health care utilization. Results: The total number of subjects with complete data on the variables in our model was 989. Individuals suffering from three or more chronic diseases used mental health care more frequently. Mental health care utilization was higher in subjects who had middle or high levels of educational attainment, were receiving Medical Aid, or had a large family size. Conclusions: It is important to control risk factors in high-risk groups as part of suicide prevention strategies. The clinical approach, which includes community-based intervention, entails the management of reduction of suicidal risk. Our study identified demographic characteristics that have a significant impact on mental health care utilization and should be considered in the development of suicide prevention strategies. Further studies should examine the effect of mental health care utilization on reducing suicidal ideation.

Determinants of Mental Health Care Utilization in a Suicide High-risk Group With Suicidal Ideation.

Science.gov (United States)

Kim, Hyun-Soo; Lee, Moo-Sik; Hong, Jee-Young

2016-01-01

The suicide rate in Korea is increasing every year, and is the highest among the Organization for Economic Cooperation and Development countries. Psychiatric patients in particular have a higher risk of suicide than other patients. This study was performed to evaluate determinants of mental health care utilization among individuals at high risk for suicide. Korea Health Panel data from 2009 to 2011 were used. Subjects were individuals at high risk of suicide who had suicidal ideation, a past history of psychiatric illness, or had utilized outpatient services for a psychiatric disorder associated with suicidal ideation within the past year. The chi-square test and hierarchical logistic regression were used to identify significant determinants of mental health care utilization. The total number of subjects with complete data on the variables in our model was 989. Individuals suffering from three or more chronic diseases used mental health care more frequently. Mental health care utilization was higher in subjects who had middle or high levels of educational attainment, were receiving Medical Aid, or had a large family size. It is important to control risk factors in high-risk groups as part of suicide prevention strategies. The clinical approach, which includes community-based intervention, entails the management of reduction of suicidal risk. Our study identified demographic characteristics that have a significant impact on mental health care utilization and should be considered in the development of suicide prevention strategies. Further studies should examine the effect of mental health care utilization on reducing suicidal ideation.

A Model-Free Scheme for Meme Ranking in Social Media

Science.gov (United States)

He, Saike; Zheng, Xiaolong; Zeng, Daniel

2015-01-01

The prevalence of social media has greatly catalyzed the dissemination and proliferation of online memes (e.g., ideas, topics, melodies, tags, etc.). However, this information abundance is exceeding the capability of online users to consume it. Ranking memes based on their popularities could promote online advertisement and content distribution. Despite such importance, few existing work can solve this problem well. They are either daunted by unpractical assumptions or incapability of characterizing dynamic information. As such, in this paper, we elaborate a model-free scheme to rank online memes in the context of social media. This scheme is capable to characterize the nonlinear interactions of online users, which mark the process of meme diffusion. Empirical studies on two large-scale, real-world datasets (one in English and one in Chinese) demonstrate the effectiveness and robustness of the proposed scheme. In addition, due to its fine-grained modeling of user dynamics, this ranking scheme can also be utilized to explain meme popularity through the lens of social influence. PMID:26823638

Earth observation for disaster risk reduction in Pakistan

International Nuclear Information System (INIS)

Rafiq, L.

2012-01-01

This thesis investigates the role of Earth Observation (EO) for disaster risk reduction for Pakistan. It demonstrates that significant improvements are possible through the utilization of EO data for natural disaster risk reduction activities in Pakistan. In this thesis, a multi hazard approach is proposed in order to identify vulnerability and risk at district level in Pakistan. In particular, a methodology for ranking hazards, vulnerabilities and risks based on Delphi methods is developed. This method is implemented and the results are mapped for four selected hazards i.e., earthquakes, floods, cyclones and droughts. Based on the final risk rankings, the potential of EO is explored with a focus on vulnerability assessment through detailed analysis of two case studies i.e.; Flood and Cyclone/Tsunami. The study also reviews and evaluates the institutional framework of the National Disaster Management Authority of Pakistan in order to identify existing gaps and address them in view of modern technology being used globally. Results reveal that these gaps are mainly related to policies, coordination and communication of different stakeholders at the national level. The work also reviews the available Early Warning System (EWS) in Pakistan and particularly its usage during disasters. Within the context of EWS, multi-sensor satellite data have been utilized for the analysis of structure of an Arabian Sea tropical Cyclone. Results of this focal study provide useful information for operational analysis and forecasting as well as for designing disaster mitigation measures. This information may also play a major role in the development of cyclone warning strategies in the future. (author)

Individual Differences in Subjective Utility and Risk Preferences: The Influence of Hedonic Capacity and Trait Anxiety

Science.gov (United States)

Howlett, Jonathon R.; Paulus, Martin P.

2017-01-01

Individual differences in decision-making are important in both normal populations and psychiatric conditions. Variability in decision-making could be mediated by different subjective utilities or by other processes. For example, while traditional economic accounts attribute risk aversion to a concave subjective utility curve, in practice other factors could affect risk behavior. This distinction may have important implications for understanding the biological basis of variability in decision-making and for developing interventions to improve decision-making. Another aspect of decision-making that may vary between individuals is the sensitivity of subjective utility to counterfactual outcomes (outcomes that could have occurred, but did not). We investigated decision-making in relation to hedonic capacity and trait anxiety, two traits that relate to psychiatric conditions but also vary in the general population. Subjects performed a decision-making task, in which they chose between low- and high-risk gambles to win 0, 20, or 40 points on each trial. Subjects then rated satisfaction after each outcome on a visual analog scale, indicating subjective utility. Hedonic capacity was positively associated with the subjective utility of winning 20 points but was not associated with the concavity of the subjective utility curve (constructed using the mean subjective utility of winning 0, 20, or 40 points). Consistent with economic theory, concavity of the subjective utility curve was associated with risk aversion. Hedonic capacity was independently associated with risk seeking (i.e., not mediated by the shape of the subjective utility curve), while trait anxiety was unrelated to risk preferences. Contrary to our expectations, counterfactual sensitivity was unrelated to hedonic capacity and trait anxiety. Nevertheless, trait anxiety was associated with a self-report measure of regret-proneness, suggesting that counterfactual influences may occur via a pathway that is separate

Individual Differences in Subjective Utility and Risk Preferences: The Influence of Hedonic Capacity and Trait Anxiety.

Science.gov (United States)

Howlett, Jonathon R; Paulus, Martin P

2017-01-01

Individual differences in decision-making are important in both normal populations and psychiatric conditions. Variability in decision-making could be mediated by different subjective utilities or by other processes. For example, while traditional economic accounts attribute risk aversion to a concave subjective utility curve, in practice other factors could affect risk behavior. This distinction may have important implications for understanding the biological basis of variability in decision-making and for developing interventions to improve decision-making. Another aspect of decision-making that may vary between individuals is the sensitivity of subjective utility to counterfactual outcomes (outcomes that could have occurred, but did not). We investigated decision-making in relation to hedonic capacity and trait anxiety, two traits that relate to psychiatric conditions but also vary in the general population. Subjects performed a decision-making task, in which they chose between low- and high-risk gambles to win 0, 20, or 40 points on each trial. Subjects then rated satisfaction after each outcome on a visual analog scale, indicating subjective utility. Hedonic capacity was positively associated with the subjective utility of winning 20 points but was not associated with the concavity of the subjective utility curve (constructed using the mean subjective utility of winning 0, 20, or 40 points). Consistent with economic theory, concavity of the subjective utility curve was associated with risk aversion. Hedonic capacity was independently associated with risk seeking (i.e., not mediated by the shape of the subjective utility curve), while trait anxiety was unrelated to risk preferences. Contrary to our expectations, counterfactual sensitivity was unrelated to hedonic capacity and trait anxiety. Nevertheless, trait anxiety was associated with a self-report measure of regret-proneness, suggesting that counterfactual influences may occur via a pathway that is separate

Individual Differences in Subjective Utility and Risk Preferences: The Influence of Hedonic Capacity and Trait Anxiety

Directory of Open Access Journals (Sweden)

Jonathon R. Howlett

2017-05-01

Full Text Available Individual differences in decision-making are important in both normal populations and psychiatric conditions. Variability in decision-making could be mediated by different subjective utilities or by other processes. For example, while traditional economic accounts attribute risk aversion to a concave subjective utility curve, in practice other factors could affect risk behavior. This distinction may have important implications for understanding the biological basis of variability in decision-making and for developing interventions to improve decision-making. Another aspect of decision-making that may vary between individuals is the sensitivity of subjective utility to counterfactual outcomes (outcomes that could have occurred, but did not. We investigated decision-making in relation to hedonic capacity and trait anxiety, two traits that relate to psychiatric conditions but also vary in the general population. Subjects performed a decision-making task, in which they chose between low- and high-risk gambles to win 0, 20, or 40 points on each trial. Subjects then rated satisfaction after each outcome on a visual analog scale, indicating subjective utility. Hedonic capacity was positively associated with the subjective utility of winning 20 points but was not associated with the concavity of the subjective utility curve (constructed using the mean subjective utility of winning 0, 20, or 40 points. Consistent with economic theory, concavity of the subjective utility curve was associated with risk aversion. Hedonic capacity was independently associated with risk seeking (i.e., not mediated by the shape of the subjective utility curve, while trait anxiety was unrelated to risk preferences. Contrary to our expectations, counterfactual sensitivity was unrelated to hedonic capacity and trait anxiety. Nevertheless, trait anxiety was associated with a self-report measure of regret-proneness, suggesting that counterfactual influences may occur via a pathway

Effects of Geographic Diversification on Risk Pooling to Mitigate Drought-Related Financial Losses for Water Utilities

Science.gov (United States)

Baum, Rachel; Characklis, Gregory W.; Serre, Marc L.

2018-04-01

As the costs and regulatory barriers to new water supply development continue to rise, drought management strategies have begun to rely more heavily on temporary conservation measures. While these measures are effective, they often lead to intermittent and unpredictable reductions in revenues that are financially disruptive to water utilities, raising concerns over lower credit ratings and higher rates of borrowing for this capital intensive sector. Consequently, there is growing interest in financial risk management strategies that reduce utility vulnerabilities. This research explores the development of financial index insurance designed to compensate a utility for drought-related losses. The focus is on analyzing candidate hydrologic indices that have the potential to be used by utilities across the US, increasing the potential for risk pooling, which would offer the possibility of both lower risk management costs and more widespread implementation. This work first analyzes drought-related financial risks for 315 publicly operated water utilities across the country and examines the effectiveness of financial contracts based on several indices both in terms of their correlation with utility revenues and their spatial autocorrelation across locations. Hydrologic-based index insurance contracts are then developed and tested over a 120 year period. Results indicate that risk pooling, even under conditions in which droughts are subject to some level of spatial autocorrelation, has the potential to significantly reduce the cost of managing financial risk.

Disentangling the effects of forage, social rank, and risk on movement autocorrelation of elephants using Fourier and wavelet analyses.

Science.gov (United States)

Wittemyer, George; Polansky, Leo; Douglas-Hamilton, Iain; Getz, Wayne M

2008-12-09

The internal state of an individual-as it relates to thirst, hunger, fear, or reproductive drive-can be inferred by referencing points on its movement path to external environmental and sociological variables. Using time-series approaches to characterize autocorrelative properties of step-length movements collated every 3 h for seven free-ranging African elephants, we examined the influence of social rank, predation risk, and seasonal variation in resource abundance on periodic properties of movement. The frequency domain methods of Fourier and wavelet analyses provide compact summaries of temporal autocorrelation and show both strong diurnal and seasonal based periodicities in the step-length time series. This autocorrelation is weaker during the wet season, indicating random movements are more common when ecological conditions are good. Periodograms of socially dominant individuals are consistent across seasons, whereas subordinate individuals show distinct differences diverging from that of dominants during the dry season. We link temporally localized statistical properties of movement to landscape features and find that diurnal movement correlation is more common within protected wildlife areas, and multiday movement correlations found among lower ranked individuals are typically outside of protected areas where predation risks are greatest. A frequency-related spatial analysis of movement-step lengths reveal that rest cycles related to the spatial distribution of critical resources (i.e., forage and water) are responsible for creating the observed patterns. Our approach generates unique information regarding the spatial-temporal interplay between environmental and individual characteristics, providing an original approach for understanding the movement ecology of individual animals and the spatial organization of animal populations.

Tools for Microbiological risk assessment

DEFF Research Database (Denmark)

Bassett, john; Nauta, Maarten; Lindqvist, Roland

can increase the understanding of microbiological risks in foods. It is timely to inform food safety professionals about the availability and utility of MRA tools. Therefore, the focus of this report is to aid the food safety manager by providing a concise summary of the tools available for the MRA......Microbiological Risk Assessment (MRA) has emerged as a comprehensive and systematic approach for addressing the risk of pathogens in specific foods and/or processes. At government level, MRA is increasingly recognised as a structured and objective approach to understand the level of risk in a given...... food/pathogen scenario. Tools developed so far support qualitative and quantitative assessments of the risk that a food pathogen poses to a particular population. Risk can be expressed as absolute numbers or as relative (ranked) risks. The food industry is beginning to appreciate that the tools for MRA...

Medicare Utilization for Part A

Data.gov (United States)

U.S. Department of Health & Human Services — This link takes you to the Medicare utilization statistics for Part A (Hospital Insurance HI) which include the Medicare Ranking for all Short-Stay Hospitals by...

Integrated Transport Planning Framework Involving Combined Utility Regret Approach

DEFF Research Database (Denmark)

Wang, Yang; Monzon, Andres; Di Ciommo, Floridea

2014-01-01

Sustainable transport planning requires an integrated approach involving strategic planning, impact analysis, and multicriteria evaluation. This study aimed at relaxing the utility-based decision-making assumption by newly embedding anticipated-regret and combined utility regret decision mechanisms...... in a framework for integrated transport planning. The framework consisted of a two-round Delphi survey, integrated land use and transport model for Madrid, and multicriteria analysis. Results show that (a) the regret-based ranking has a similar mean but larger variance than the utility-based ranking does, (b......) the least-regret scenario forms a compromise between the desired and the expected scenarios, (c) the least-regret scenario can lead to higher user benefits in the short term and lower user benefits in the long term, (d) the utility-based, the regret-based, and the combined utility- and regret...

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.

Ranking of critical species to preserve the functionality of mutualistic networks using the k-core decomposition.

Science.gov (United States)

García-Algarra, Javier; Pastor, Juan Manuel; Iriondo, José María; Galeano, Javier

2017-01-01

Network analysis has become a relevant approach to analyze cascading species extinctions resulting from perturbations on mutualistic interactions as a result of environmental change. In this context, it is essential to be able to point out key species, whose stability would prevent cascading extinctions, and the consequent loss of ecosystem function. In this study, we aim to explain how the k -core decomposition sheds light on the understanding the robustness of bipartite mutualistic networks. We defined three k -magnitudes based on the k -core decomposition: k -radius, k -degree, and k -risk. The first one, k -radius, quantifies the distance from a node to the innermost shell of the partner guild, while k -degree provides a measure of centrality in the k -shell based decomposition. k -risk is a way to measure the vulnerability of a network to the loss of a particular species. Using these magnitudes we analyzed 89 mutualistic networks involving plant pollinators or seed dispersers. Two static extinction procedures were implemented in which k -degree and k -risk were compared against other commonly used ranking indexes, as for example MusRank, explained in detail in Material and Methods. When extinctions take place in both guilds, k -risk is the best ranking index if the goal is to identify the key species to preserve the giant component. When species are removed only in the primary class and cascading extinctions are measured in the secondary class, the most effective ranking index to identify the key species to preserve the giant component is k -degree. However, MusRank index was more effective when the goal is to identify the key species to preserve the greatest species richness in the second class. The k -core decomposition offers a new topological view of the structure of mutualistic networks. The new k -radius, k -degree and k -risk magnitudes take advantage of its properties and provide new insight into the structure of mutualistic networks. The k -risk and k

Ranking of critical species to preserve the functionality of mutualistic networks using the k-core decomposition

Directory of Open Access Journals (Sweden)

Javier García-Algarra

2017-05-01

Full Text Available Background Network analysis has become a relevant approach to analyze cascading species extinctions resulting from perturbations on mutualistic interactions as a result of environmental change. In this context, it is essential to be able to point out key species, whose stability would prevent cascading extinctions, and the consequent loss of ecosystem function. In this study, we aim to explain how the k-core decomposition sheds light on the understanding the robustness of bipartite mutualistic networks. Methods We defined three k-magnitudes based on the k-core decomposition: k-radius, k-degree, and k-risk. The first one, k-radius, quantifies the distance from a node to the innermost shell of the partner guild, while k-degree provides a measure of centrality in the k-shell based decomposition. k-risk is a way to measure the vulnerability of a network to the loss of a particular species. Using these magnitudes we analyzed 89 mutualistic networks involving plant pollinators or seed dispersers. Two static extinction procedures were implemented in which k-degree and k-risk were compared against other commonly used ranking indexes, as for example MusRank, explained in detail in Material and Methods. Results When extinctions take place in both guilds, k-risk is the best ranking index if the goal is to identify the key species to preserve the giant component. When species are removed only in the primary class and cascading extinctions are measured in the secondary class, the most effective ranking index to identify the key species to preserve the giant component is k-degree. However, MusRank index was more effective when the goal is to identify the key species to preserve the greatest species richness in the second class. Discussion The k-core decomposition offers a new topological view of the structure of mutualistic networks. The new k-radius, k-degree and k-risk magnitudes take advantage of its properties and provide new insight into the structure of

Best practices in ranking communicable disease threats: a literature review, 2015.

Science.gov (United States)

O'Brien, Eleanor Charlotte; Taft, Rachel; Geary, Katie; Ciotti, Massimo; Suk, Jonathan E

2016-04-28

The threat of serious, cross-border communicable disease outbreaks in Europe poses a significant challenge to public health and emergency preparedness because the relative likelihood of these threats and the pathogens involved are constantly shifting in response to a range of changing disease drivers. To inform strategic planning by enabling effective resource allocation to manage the consequences of communicable disease outbreaks, it is useful to be able to rank and prioritise pathogens. This paper reports on a literature review which identifies and evaluates the range of methods used for risk ranking. Searches were performed across biomedical and grey literature databases, supplemented by reference harvesting and citation tracking. Studies were selected using transparent inclusion criteria and underwent quality appraisal using a bespoke checklist based on the AGREE II criteria. Seventeen studies were included in the review, covering five methodologies. A narrative analysis of the selected studies suggests that no single methodology was superior. However, many of the methods shared common components, around which a 'best-practice' framework was formulated. This approach is intended to help inform decision makers' choice of an appropriate risk-ranking study design.

Critical review of methodology and application of risk ranking for prioritisation of food and feed related issues, on the basis of the size of anticipated health impact

NARCIS (Netherlands)

Fels-Klerx, van der H.J.; Asselt, van E.D.; Raley, M.; Poulsen, M.; Korsgaard, H.; Bredsdorff, L.; Nauta, M.; Flari, V.; Agostino, D' M.; Coles, D.G.; Frewer, L.J.

2015-01-01

This study aimed to critically review methodologies for ranking of risks related to feed/food safety and nutritional hazards, on the basis of their anticipated human health impact. An extensive systematic literature review was performed to identify and characterize the available methodologies for

Using Spatial Multi-Criteria Analysis and Ranking Tool (SMART in earthquake risk assessment: a case study of Delhi region, India

Directory of Open Access Journals (Sweden)

Nishant Sinha

2016-03-01

Full Text Available This article is aimed at earthquake hazard, vulnerability and risk assessment as a case study to demonstrate the applicability of Spatial Multi-Criteria Analysis and Ranking Tool (SMART, which is based on Saaty's multi-criteria decision analysis (MCDA technique. The three specific study sites of Delhi were chosen for research as it corresponds to a typical patch of the urban environs, completely engrossed with residential, commercial and industrial units. The earthquake hazard affecting components are established in the form of geographic information system data-set layers including seismic zone, peak ground acceleration (PGA, soil characteristics, liquefaction potential, geological characteristics, land use, proximity to fault and epicentre. The physical vulnerability layers comprising building information, namely number of stories, year-built range, area, occupancy and construction type, derived from remote sensing imagery, were only considered for the current research. SMART was developed for earthquake risk assessment, and weights were derived both at component and its element level. Based on weighted overlay techniques, the earthquake hazard and vulnerability layers were created from which the risk maps were derived through multiplicative analysis. The developed risk maps may prove useful in decision-making process and formulating risk mitigation measures.

University Rankings and Social Science

OpenAIRE

Marginson, S.

2014-01-01

University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real outputs are of no common value. It is necessary that rankings be soundly based in scientific terms if a virtuous relationship between performance and...

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...

Differences in Health Care Costs and Utilization among Adults with Selected Lifestyle-Related Risk Factors.

Science.gov (United States)

Tucker, Larry A.; Clegg, Alan G.

2002-01-01

Examined the relationship between lifestyle-related health risks and health care costs and utilization among young adults. Data collected at a primarily white collar worksite in over 2 years indicated that health risks, particularly obesity, stress, and general lifestyle, were significant predictors of health care costs and utilization among these…

On Page Rank

NARCIS (Netherlands)

Hoede, C.

In this paper the concept of page rank for the world wide web is discussed. The possibility of describing the distribution of page rank by an exponential law is considered. It is shown that the concept is essentially equal to that of status score, a centrality measure discussed already in 1953 by

Citation graph based ranking in Invenio

CERN Document Server

Marian, Ludmila; Rajman, Martin; Vesely, Martin

2010-01-01

Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods. (The original publication is ava...

Risk-Sensitive Multiagent Decision-Theoretic Planning Based on MDP and One-Switch Utility Functions

Directory of Open Access Journals (Sweden)

Wei Zeng

2014-01-01

Full Text Available In high stakes situations decision-makers are often risk-averse and decision-making processes often take place in group settings. This paper studies multiagent decision-theoretic planning under Markov decision processes (MDPs framework with considering the change of agent’s risk attitude as his wealth level varies. Based on one-switch utility function that describes agent’s risk attitude change with his wealth level, we give the additive and multiplicative aggregation models of group utility and adopt maximizing expected group utility as planning objective. When the wealth level approaches infinity, the characteristics of optimal policy are analyzed for the additive and multiplicative aggregation model, respectively. Then a backward-induction method is proposed to divide the wealth level interval from negative infinity to initial wealth level into subintervals and determine the optimal policy in states and subintervals. The proposed method is illustrated by numerical examples and the influences of agent’s risk aversion parameters and weights on group decision-making are also analyzed.

Evolution of strategic risks under future scenarios for improved utility master plans.

Science.gov (United States)

Luís, Ana; Lickorish, Fiona; Pollard, Simon

2016-01-01

Integrated, long-term risk management in the water sector is poorly developed. Whilst scenario planning has been applied to singular issues (e.g. climate change), it often misses a link to risk management because the likelihood of impacts in the long-term are frequently unaccounted for in these analyses. Here we apply the morphological approach to scenario development for a case study utility, Empresa Portuguesa das Águas Livres (EPAL). A baseline portfolio of strategic risks threatening the achievement of EPAL's corporate objectives was evolved through the lens of three future scenarios, 'water scarcity', 'financial resource scarcity' and 'strong economic growth', built on drivers such as climate, demographic, economic, regulatory and technological changes and validated through a set of expert workshops. The results represent how the baseline set of risks might develop over a 30 year period, allowing threats and opportunities to be identified and enabling strategies for master plans to be devised. We believe this to be the first combined use of risk and futures methods applied to a portfolio of strategic risks in the water utility sector. Copyright © 2015 Elsevier Ltd. All rights reserved.

A multimedia retrieval framework based on semi-supervised ranking and relevance feedback.

Science.gov (United States)

Yang, Yi; Nie, Feiping; Xu, Dong; Luo, Jiebo; Zhuang, Yueting; Pan, Yunhe

2012-04-01

We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust Laplacian matrix for data ranking. In LRGA, for each data point, a local linear regression model is used to predict the ranking scores of its neighboring points. A unified objective function is then proposed to globally align the local models from all the data points so that an optimal ranking score can be assigned to each data point. Second, we propose a semi-supervised long-term Relevance Feedback (RF) algorithm to refine the multimedia data representation. The proposed long-term RF algorithm utilizes both the multimedia data distribution in multimedia feature space and the history RF information provided by users. A trace ratio optimization problem is then formulated and solved by an efficient algorithm. The algorithms have been applied to several content-based multimedia retrieval applications, including cross-media retrieval, image retrieval, and 3D motion/pose data retrieval. Comprehensive experiments on four data sets have demonstrated its advantages in precision, robustness, scalability, and computational efficiency.

Development of a system utilizing data of risk assessment

International Nuclear Information System (INIS)

Nagasaka, Akihiko; Takano, Kenichi; Ebisu, Mitsuhiro; Aikawa, Tadashi; Hayase, Kenichi

2004-01-01

This report deals with a concrete method of utilizing data of risk assessment. First, the authors point out the necessity to assess all stages of jobs (planning, meeting with contractors, performing phase of task, etc.) in risk assessment bout jobs in electric power company, because most jobs are performed by contract system and risks of a job are distributed over electric company, contractors and subcontractors. Secondly, risks estimated from past accidents and near-miss events must be included. If these 2 requirements are fulfilled, data of risk assessment can be more useful. Then below 4 forms of present data of risk assessment were developed. A form to be used in job planning stage in electric companies for efficient investment planning in safety measures. A form to be used in meetings between electric companies and contractors for checking accident prevention methods. A form to be used in meetings between contractors and subcontractors for enhancing a shared awareness of risk. A form to be used in tool box meetings for confirming safe condition and inheriting of ability of risk perception. Additionally, a data base system of risk assessment about 4 jobs was developed. This system prints out about 4 forms for each job and is useful for PDCA of safety activities. (author)

Comparison of Document Index Graph Using TextRank and HITS Weighting Method in Automatic Text Summarization

Science.gov (United States)

Hadyan, Fadhlil; Shaufiah; Arif Bijaksana, Moch.

2017-01-01

Automatic summarization is a system that can help someone to take the core information of a long text instantly. The system can help by summarizing text automatically. there’s Already many summarization systems that have been developed at this time but there are still many problems in those system. In this final task proposed summarization method using document index graph. This method utilizes the PageRank and HITS formula used to assess the web page, adapted to make an assessment of words in the sentences in a text document. The expected outcome of this final task is a system that can do summarization of a single document, by utilizing document index graph with TextRank and HITS to improve the quality of the summary results automatically.

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.

University Rankings: The Web Ranking

Science.gov (United States)

Aguillo, Isidro F.

2012-01-01

The publication in 2003 of the Ranking of Universities by Jiao Tong University of Shanghai has revolutionized not only academic studies on Higher Education, but has also had an important impact on the national policies and the individual strategies of the sector. The work gathers the main characteristics of this and other global university…

Ranking Specific Sets of Objects.

Science.gov (United States)

Maly, Jan; Woltran, Stefan

2017-01-01

Ranking sets of objects based on an order between the single elements has been thoroughly studied in the literature. In particular, it has been shown that it is in general impossible to find a total ranking - jointly satisfying properties as dominance and independence - on the whole power set of objects. However, in many applications certain elements from the entire power set might not be required and can be neglected in the ranking process. For instance, certain sets might be ruled out due to hard constraints or are not satisfying some background theory. In this paper, we treat the computational problem whether an order on a given subset of the power set of elements satisfying different variants of dominance and independence can be found, given a ranking on the elements. We show that this problem is tractable for partial rankings and NP-complete for total rankings.

Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

Science.gov (United States)

Li, Jun; Zhao, Patrick X

2016-01-01

Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/.

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)

LANL environmental restoration site ranking system: System description. Final report

International Nuclear Information System (INIS)

Merkhofer, L.; Kann, A.; Voth, M.

1992-01-01

The basic structure of the LANL Environmental Restoration (ER) Site Ranking System and its use are described in this document. A related document, Instructions for Generating Inputs for the LANL ER Site Ranking System, contains detailed descriptions of the methods by which necessary inputs for the system will be generated. LANL has long recognized the need to provide a consistent basis for comparing the risks and other adverse consequences associated with the various waste problems at the Lab. The LANL ER Site Ranking System is being developed to help address this need. The specific purpose of the system is to help improve, defend, and explain prioritization decisions at the Potential Release Site (PRS) and Operable Unit (OU) level. The precise relationship of the Site Ranking System to the planning and overall budget processes is yet to be determined, as the system is still evolving. Generally speaking, the Site Ranking System will be used as a decision aid. That is, the system will be used to aid in the planning and budgetary decision-making process. It will never be used alone to make decisions. Like all models, the system can provide only a partial and approximate accounting of the factors important to budget and planning decisions. Decision makers at LANL will have to consider factors outside of the formal system when making final choices. Some of these other factors are regulatory requirements, DOE policy, and public concern. The main value of the site ranking system, therefore, is not the precise numbers it generates, but rather the general insights it provides

LANL environmental restoration site ranking system: System description. Final report

Energy Technology Data Exchange (ETDEWEB)

Merkhofer, L.; Kann, A.; Voth, M. [Applied Decision Analysis, Inc., Menlo Park, CA (United States)

1992-10-13

The basic structure of the LANL Environmental Restoration (ER) Site Ranking System and its use are described in this document. A related document, Instructions for Generating Inputs for the LANL ER Site Ranking System, contains detailed descriptions of the methods by which necessary inputs for the system will be generated. LANL has long recognized the need to provide a consistent basis for comparing the risks and other adverse consequences associated with the various waste problems at the Lab. The LANL ER Site Ranking System is being developed to help address this need. The specific purpose of the system is to help improve, defend, and explain prioritization decisions at the Potential Release Site (PRS) and Operable Unit (OU) level. The precise relationship of the Site Ranking System to the planning and overall budget processes is yet to be determined, as the system is still evolving. Generally speaking, the Site Ranking System will be used as a decision aid. That is, the system will be used to aid in the planning and budgetary decision-making process. It will never be used alone to make decisions. Like all models, the system can provide only a partial and approximate accounting of the factors important to budget and planning decisions. Decision makers at LANL will have to consider factors outside of the formal system when making final choices. Some of these other factors are regulatory requirements, DOE policy, and public concern. The main value of the site ranking system, therefore, is not the precise numbers it generates, but rather the general insights it provides.

Environmental and health hazard ranking and assessment of plastic polymers based on chemical composition

Energy Technology Data Exchange (ETDEWEB)

Lithner, Delilah, E-mail: delilah.lithner@gmail.com; Larsson, Ake; Dave, Goeran

2011-08-15

Plastics constitute a large material group with a global annual production that has doubled in 15 years (245 million tonnes in 2008). Plastics are present everywhere in society and the environment, especially the marine environment, where large amounts of plastic waste accumulate. The knowledge of human and environmental hazards and risks from chemicals associated with the diversity of plastic products is very limited. Most chemicals used for producing plastic polymers are derived from non-renewable crude oil, and several are hazardous. These may be released during the production, use and disposal of the plastic product. In this study the environmental and health hazards of chemicals used in 55 thermoplastic and thermosetting polymers were identified and compiled. A hazard ranking model was developed for the hazard classes and categories in the EU classification and labelling (CLP) regulation which is based on the UN Globally Harmonized System. The polymers were ranked based on monomer hazard classifications, and initial assessments were made. The polymers that ranked as most hazardous are made of monomers classified as mutagenic and/or carcinogenic (category 1A or 1B). These belong to the polymer families of polyurethanes, polyacrylonitriles, polyvinyl chloride, epoxy resins, and styrenic copolymers. All have a large global annual production (1-37 million tonnes). A considerable number of polymers (31 out of 55) are made of monomers that belong to the two worst of the ranking model's five hazard levels, i.e. levels IV-V. The polymers that are made of level IV monomers and have a large global annual production (1-5 million tonnes) are phenol formaldehyde resins, unsaturated polyesters, polycarbonate, polymethyl methacrylate, and urea-formaldehyde resins. This study has identified hazardous substances used in polymer production for which the risks should be evaluated for decisions on the need for risk reduction measures, substitution, or even phase out

Health Risk Assessment of Harmful Chemicals: Case Study in a Petrochemical Industry

Directory of Open Access Journals (Sweden)

M. Motovagheh

2011-01-01

Full Text Available Background and aims In the most chemical process industries, workers are exposed to various chemicals and working with these chemicals without considering safety and health considerations can lead to different harmful symptoms. For deciding about control measures and reducing risk to acceptable level , it is necessary to assess the health risk of exposing to harmful chemicals by aid of specific risk assessment techniques in the process industries. The purpose of this study was to assess the health risks arising from the exposures to chemicals in a petrochemical industry.  methods A simple and applied method was used for health risk assessment of chemicals in a petrochemical industry. Firstly job tasks and work process were determined and then different chemicals in each tasks identified and risk ranking was calculated in each job task by aid of hazard and exposure rate.   Results The result showed that workers are exposed to 10 chemicals including Methyl ethyl ketone, Epichlorohydrin, Sulfuric acid, Phenol, Chlorobenzene, Toluene, Isopropanol, Methylene chloride, Chlorideric Acid and Acetone during their work in plant. From these chemicals, the highest risk level was for Epichlorohydrin in the jobs of tank and utility operations and maintenance workers. The next high risk level was for Epichlorohydrin in technical inspecting and Methyl ethyl ketone in Tank and utility operations operator.     Conclusion Hazard information and monitoring data of chemical agents in the chemical industries can be used for assessing health risks from exposures to chemicals and ranking jobs by their risk level. These data can be used for resource allocation for control measures and reducing risk level to acceptable level.    

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.

University Rankings and Social Science

Science.gov (United States)

Marginson, Simon

2014-01-01

University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real…

Brachytherapy Boost Utilization and Survival in Unfavorable-risk Prostate Cancer.

Science.gov (United States)

Johnson, Skyler B; Lester-Coll, Nataniel H; Kelly, Jacqueline R; Kann, Benjamin H; Yu, James B; Nath, Sameer K

2017-11-01

There are limited comparative survival data for prostate cancer (PCa) patients managed with a low-dose rate brachytherapy (LDR-B) boost and dose-escalated external-beam radiotherapy (DE-EBRT) alone. To compare overall survival (OS) for men with unfavorable PCa between LDR-B and DE-EBRT groups. Using the National Cancer Data Base, we identified men with unfavorable PCa treated between 2004 and 2012 with androgen suppression (AS) and either EBRT followed by LDR-B or DE-EBRT (75.6-86.4Gy). Treatment selection was evaluated using logistic regression and annual percentage proportions. OS was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards, and propensity score matching. We identified 25038 men between 2004 and 2012, during which LDR-B boost utilization decreased from 29% to 14%. LDR-B was associated with better OS on univariate (7-yr OS: 82% vs 73%; pLDR-B boost (HR 0.74, 95% CI 0.66-0.89). The OS benefit of LDR-B boost persisted when limited to men aged LDR-B boost utilization declined and was associated with better OS compared to DE-EBRT alone. LDR-B boost is probably the ideal treatment option for men with unfavorable PCa, pending long-term results of randomized trials. We compared radiotherapy utilization and survival for prostate cancer (PCa) patients using a national database. We found that low-dose rate brachytherapy (LDR-B) boost, a method being used less frequently, was associated with better overall survival when compared to dose-escalated external-beam radiotherapy alone for men with unfavorable PCa. Randomized trials are needed to confirm that LDR-B boost is the ideal treatment. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Adsorption isotherms and kinetics of activated carbons produced from coals of different ranks.

Science.gov (United States)

Purevsuren, B; Lin, Chin-Jung; Davaajav, Y; Ariunaa, A; Batbileg, S; Avid, B; Jargalmaa, S; Huang, Yu; Liou, Sofia Ya-Hsuan

2015-01-01

Activated carbons (ACs) from six coals, ranging from low-rank lignite brown coal to high-rank stone coal, were utilized as adsorbents to remove basic methylene blue (MB) from an aqueous solution. The surface properties of the obtained ACs were characterized via thermal analysis, N2 isothermal sorption, scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and Boehm titration. As coal rank decreased, an increase in the heterogeneity of the pore structures and abundance of oxygen-containing functional groups increased MB coverage on its surface. The equilibrium data fitted well with the Langmuir model, and adsorption capacity of MB ranged from 51.8 to 344.8 mg g⁻¹. Good correlation coefficients were obtained using the intra-particle diffusion model, indicating that the adsorption of MB onto ACs is diffusion controlled. The values of the effective diffusion coefficient ranged from 0.61 × 10⁻¹⁰ to 7.1 × 10⁻¹⁰ m² s⁻¹, indicating that ACs from lower-rank coals have higher effective diffusivities. Among all the ACs obtained from selected coals, the AC from low-rank lignite brown coal was the most effective in removing MB from an aqueous solution.

Two-dimensional ranking of Wikipedia articles

Science.gov (United States)

Zhirov, A. O.; Zhirov, O. V.; Shepelyansky, D. L.

2010-10-01

The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.

The Effects of Variability and Risk in Selection Utility Analysis: An Empirical Comparison.

Science.gov (United States)

Rich, Joseph R.; Boudreau, John W.

1987-01-01

Investigated utility estimate variability for the selection utility of using the Programmer Aptitude Test to select computer programmers. Comparison of Monte Carlo results to other risk assessment approaches (sensitivity analysis, break-even analysis, algebraic derivation of the distribtion) suggests that distribution information provided by Monte…

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. ...

Rank-based Tests of the Cointegrating Rank in Semiparametric Error Correction Models

NARCIS (Netherlands)

Hallin, M.; van den Akker, R.; Werker, B.J.M.

2012-01-01

Abstract: This paper introduces rank-based tests for the cointegrating rank in an Error Correction Model with i.i.d. elliptical innovations. The tests are asymptotically distribution-free, and their validity does not depend on the actual distribution of the innovations. This result holds despite the

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 the adaptive capacity of nations to climate change when socio-political goals are explicit

International Nuclear Information System (INIS)

Haddad, B.M.

2005-01-01

The typical categories for measuring national adaptive capacity to climate change include a nation's wealth, technology, education, information, skills, infrastructure, access to resources, and management capabilities. Resulting rankings predictably mirror more general rankings of economic development, such as the Human Development Index. This approach is incomplete since it does not consider the normative or motivational context of adaptation. For what purpose or toward what goal does a nation aspire, and in that context, what is its adaptive capacity? This paper posits 11 possible national socio-political goals that fall into the three categories of teleological legitimacy, procedural legitimacy, and norm-based decision rules. A model that sorts nations in terms of adaptive capacity based on national socio-political aspirations is presented. While the aspiration of maximizing summed utility matches typical existing rankings, alternative aspirations, including contractarian liberalism, technocratic management, and dictatorial/religious rule alter the rankings. An example describes how this research can potentially inform how priorities are set for international assistance for climate change adaptation. (author)

Minkowski metrics in creating universal ranking algorithms

Directory of Open Access Journals (Sweden)

Andrzej Ameljańczyk

2014-06-01

Full Text Available The paper presents a general procedure for creating the rankings of a set of objects, while the relation of preference based on any ranking function. The analysis was possible to use the ranking functions began by showing the fundamental drawbacks of commonly used functions in the form of a weighted sum. As a special case of the ranking procedure in the space of a relation, the procedure based on the notion of an ideal element and generalized Minkowski distance from the element was proposed. This procedure, presented as universal ranking algorithm, eliminates most of the disadvantages of ranking functions in the form of a weighted sum.[b]Keywords[/b]: ranking functions, preference relation, ranking clusters, categories, ideal point, universal ranking algorithm

Supplier Selection Using Weighted Utility Additive Method

Science.gov (United States)

Karande, Prasad; Chakraborty, Shankar

2015-10-01

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

Statistical regularities in the rank-citation profile of scientists.

Science.gov (United States)

Petersen, Alexander M; Stanley, H Eugene; Succi, Sauro

2011-01-01

Recent science of science research shows that scientific impact measures for journals and individual articles have quantifiable regularities across both time and discipline. However, little is known about the scientific impact distribution at the scale of an individual scientist. We analyze the aggregate production and impact using the rank-citation profile c(i)(r) of 200 distinguished professors and 100 assistant professors. For the entire range of paper rank r, we fit each c(i)(r) to a common distribution function. Since two scientists with equivalent Hirsch h-index can have significantly different c(i)(r) profiles, our results demonstrate the utility of the β(i) scaling parameter in conjunction with h(i) for quantifying individual publication impact. We show that the total number of citations C(i) tallied from a scientist's N(i) papers scales as [Formula: see text]. Such statistical regularities in the input-output patterns of scientists can be used as benchmarks for theoretical models of career progress.

Recurrent fuzzy ranking methods

Science.gov (United States)

Hajjari, Tayebeh

2012-11-01

With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

Optimising risk reduction: An expected utility approach for marginal risk reduction during regulatory decision making

International Nuclear Information System (INIS)

Li Jiawei; Pollard, Simon; Kendall, Graham; Soane, Emma; Davies, Gareth

2009-01-01

In practice, risk and uncertainty are essentially unavoidable in many regulation processes. Regulators frequently face a risk-benefit trade-off since zero risk is neither practicable nor affordable. Although it is accepted that cost-benefit analysis is important in many scenarios of risk management, what role it should play in a decision process is still controversial. One criticism of cost-benefit analysis is that decision makers should consider marginal benefits and costs, not present ones, in their decision making. In this paper, we investigate the problem of regulatory decision making under risk by applying expected utility theory and present a new approach of cost-benefit analysis. Directly taking into consideration the reduction of the risks, this approach achieves marginal cost-benefit analysis. By applying this approach, the optimal regulatory decision that maximizes the marginal benefit of risk reduction can be considered. This provides a transparent and reasonable criterion for stakeholders involved in the regulatory activity. An example of evaluating seismic retrofitting alternatives is provided to demonstrate the potential of the proposed approach.

Ranking Operations Management conferences

NARCIS (Netherlands)

Steenhuis, H.J.; de Bruijn, E.J.; Gupta, Sushil; Laptaned, U

2007-01-01

Several publications have appeared in the field of Operations Management which rank Operations Management related journals. Several ranking systems exist for journals based on , for example, perceived relevance and quality, citation, and author affiliation. Many academics also publish at conferences

Risk based modelling

International Nuclear Information System (INIS)

Chapman, O.J.V.; Baker, A.E.

1993-01-01

Risk based analysis is a tool becoming available to both engineers and managers to aid decision making concerning plant matters such as In-Service Inspection (ISI). In order to develop a risk based method, some form of Structural Reliability Risk Assessment (SRRA) needs to be performed to provide a probability of failure ranking for all sites around the plant. A Probabilistic Risk Assessment (PRA) can then be carried out to combine these possible events with the capability of plant safety systems and procedures, to establish the consequences of failure for the sites. In this way the probability of failures are converted into a risk based ranking which can be used to assist the process of deciding which sites should be included in an ISI programme. This paper reviews the technique and typical results of a risk based ranking assessment carried out for nuclear power plant pipework. (author)

Low-rank coal study : national needs for resource development. Volume 2. Resource characterization

Energy Technology Data Exchange (ETDEWEB)

1980-11-01

Comprehensive data are presented on the quantity, quality, and distribution of low-rank coal (subbituminous and lignite) deposits in the United States. The major lignite-bearing areas are the Fort Union Region and the Gulf Lignite Region, with the predominant strippable reserves being in the states of North Dakota, Montana, and Texas. The largest subbituminous coal deposits are in the Powder River Region of Montana and Wyoming, The San Juan Basin of New Mexico, and in Northern Alaska. For each of the low-rank coal-bearing regions, descriptions are provided of the geology; strippable reserves; active and planned mines; classification of identified resources by depth, seam thickness, sulfur content, and ash content; overburden characteristics; aquifers; and coal properties and characteristics. Low-rank coals are distinguished from bituminous coals by unique chemical and physical properties that affect their behavior in extraction, utilization, or conversion processes. The most characteristic properties of the organic fraction of low-rank coals are the high inherent moisture and oxygen contents, and the correspondingly low heating value. Mineral matter (ash) contents and compositions of all coals are highly variable; however, low-rank coals tend to have a higher proportion of the alkali components CaO, MgO, and Na/sub 2/O. About 90% of the reserve base of US low-rank coal has less than one percent sulfur. Water resources in the major low-rank coal-bearing regions tend to have highly seasonal availabilities. Some areas appear to have ample water resources to support major new coal projects; in other areas such as Texas, water supplies may be constraining factor on development.

A ranking method for the concurrent learning of compounds with various activity profiles.

Science.gov (United States)

Dörr, Alexander; Rosenbaum, Lars; Zell, Andreas

2015-01-01

In this study, we present a SVM-based ranking algorithm for the concurrent learning of compounds with different activity profiles and their varying prioritization. To this end, a specific labeling of each compound was elaborated in order to infer virtual screening models against multiple targets. We compared the method with several state-of-the-art SVM classification techniques that are capable of inferring multi-target screening models on three chemical data sets (cytochrome P450s, dehydrogenases, and a trypsin-like protease data set) containing three different biological targets each. The experiments show that ranking-based algorithms show an increased performance for single- and multi-target virtual screening. Moreover, compounds that do not completely fulfill the desired activity profile are still ranked higher than decoys or compounds with an entirely undesired profile, compared to other multi-target SVM methods. SVM-based ranking methods constitute a valuable approach for virtual screening in multi-target drug design. The utilization of such methods is most helpful when dealing with compounds with various activity profiles and the finding of many ligands with an already perfectly matching activity profile is not to be expected.

Country-specific determinants of world university rankings

OpenAIRE

Pietrucha, Jacek

2017-01-01

This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42–71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: econom...

A logical framework for ranking landslide inventory maps

Science.gov (United States)

Santangelo, Michele; Fiorucci, Federica; Bucci, Francesco; Cardinali, Mauro; Ardizzone, Francesca; Marchesini, Ivan; Cesare Mondini, Alessandro; Reichenbach, Paola; Rossi, Mauro; Guzzetti, Fausto

2014-05-01

Landslides inventory maps are essential for quantitative landslide hazard and risk assessments, and for geomorphological and ecological studies. Landslide maps, including geomorphological, event based, multi-temporal, and seasonal inventory maps, are most commonly prepared through the visual interpretation of (i) monoscopic and stereoscopic aerial photographs, (ii) satellite images, (iii) LiDAR derived images, aided by more or less extensive field surveys. Landslide inventory maps are the basic information for a number of different scientific, technical and civil protection purposes, such as: (i) quantitative geomorphic analyses, (ii) erosion studies, (iii) deriving landslide statistics, (iv) urban development planning (v) landslide susceptibility, hazard and risk evaluation, and (vi) landslide monitoring systems. Despite several decades of activity in landslide inventory making, still no worldwide-accepted standards, best practices and protocols exist for the ranking and the production of landslide inventory maps. Standards for the preparation (and/or ranking) of landslide inventories should indicate the minimum amount of information for a landslide inventory map, given the scale, the type of images, the instrumentation available, and the available ancillary data. We recently attempted at a systematic description and evaluation of a total of 22 geomorphological inventories, 6 multi-temporal inventories, 10 event inventories, and 3 seasonal inventories, in the scale range between 1:10,000 and 1:500,000, prepared for areas in different geological and geomorphological settings. All of the analysed inventories were carried out by using image interpretation techniques, or field surveys. Firstly, a detailed characterisation was performed for each landslide inventory, mainly collecting metadata related (i) to the amount of information used for preparing the landslide inventory (i.e. images used, instrumentation, ancillary data, digitalisation method, legend, validation

Universal emergence of PageRank

Energy Technology Data Exchange (ETDEWEB)

Frahm, K M; Georgeot, B; Shepelyansky, D L, E-mail: frahm@irsamc.ups-tlse.fr, E-mail: georgeot@irsamc.ups-tlse.fr, E-mail: dima@irsamc.ups-tlse.fr [Laboratoire de Physique Theorique du CNRS, IRSAMC, Universite de Toulouse, UPS, 31062 Toulouse (France)

2011-11-18

The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter {alpha} Element-Of ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when {alpha} {yields} 1. The whole network can be divided into a core part and a group of invariant subspaces. For {alpha} {yields} 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at {alpha} {yields} 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

Universal emergence of PageRank

International Nuclear Information System (INIS)

Frahm, K M; Georgeot, B; Shepelyansky, D L

2011-01-01

The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter α ∈ ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when α → 1. The whole network can be divided into a core part and a group of invariant subspaces. For α → 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at α → 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

Concave utility, transaction costs, and risk in measuring discounting of delayed rewards.

Science.gov (United States)

Kirby, Kris N; Santiesteban, Mariana

2003-01-01

Research has consistently found that the decline in the present values of delayed rewards as delay increases is better fit by hyperbolic than by exponential delay-discounting functions. However, concave utility, transaction costs, and risk each could produce hyperbolic-looking data, even when the underlying discounting function is exponential. In Experiments 1 (N = 45) and 2 (N = 103), participants placed bids indicating their present values of real future monetary rewards in computer-based 2nd-price auctions. Both experiments suggest that utility is not sufficiently concave to account for the superior fit of hyperbolic functions. Experiment 2 provided no evidence that the effects of transaction costs and risk are large enough to account for the superior fit of hyperbolic functions.

Application of third order stochastic dominance algorithm in investments ranking

Directory of Open Access Journals (Sweden)

Lončar Sanja

2012-01-01

Full Text Available The paper presents the use of third order stochastic dominance in ranking Investment alternatives, using TSD algorithms (Levy, 2006for testing third order stochastic dominance. The main goal of using TSD rule is minimization of efficient investment set for investor with risk aversion, who prefers more money and likes positive skew ness.

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.

Human and Veterinary Antibiotics Used in Portugal—A Ranking for Ecosurveillance

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Anabela Almeida

2014-05-01

Full Text Available Antibiotics represent a pharmacotherapeutic group widely used in both human and veterinary medicine for which ecosurveillance has been continually recommended. It is urgent to rank the antibiotics and highlight those that may pose potential risk to the environment, a key step for the risk management. The absence of this type of contributions applied to the Portuguese reality supported the idea of compiling the data presented herein. With such purpose the most recent and representative data is used to draw a comparative contribution of each antimicrobial classes according to their intended use, i.e., in human versus veterinary medicine. The aim was to assess: (1 the amount and patterns of antimicrobials usage between human and animals; (2 the qualitative comparison between the antimicrobial classes used in each practice (human and veterinary or specific use; (3 the potential to enter the environment, metabolism, mode of action and environmental occurrences. This manuscript will, thus, identify priorities for the environmental risk assessment, considering the ranking of the antimicrobials by their usage and potential environmental exposure. Ultimately, this study will serve as a basis for future monitoring programs, guiding the policy of regulatory agencies.

Dynamic Matrix Rank

DEFF Research Database (Denmark)

Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

2009-01-01

We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

Statistical methods for ranking data

CERN Document Server

Alvo, Mayer

2014-01-01

This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

Hitting the Rankings Jackpot

Science.gov (United States)

Chapman, David W.

2008-01-01

Recently, Samford University was ranked 27th in the nation in a report released by "Forbes" magazine. In this article, the author relates how the people working at Samford University were surprised at its ranking. Although Samford is the largest privately institution in Alabama, its distinguished academic achievements aren't even…

A tilting approach to ranking influence

KAUST Repository

Genton, Marc G.

2014-12-01

We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking the data in terms of that influence. Our method is based on, first, perturbing the value of the statistic by ‘tilting’, or reweighting, each data value, where the total amount of tilt is constrained to be the least possible, subject to achieving a given small perturbation of the statistic, and, then, taking the ranking of the influence of data values to be that which corresponds to ranking the changes in data weights. It is shown, both theoretically and numerically, that this ranking does not depend on the size of the perturbation, provided that the perturbation is sufficiently small. That simple result leads directly to an elegant geometric interpretation of the ranks; they are the ranks of the lengths of projections of the weights onto a ‘line’ determined by the first empirical principal component function in a generalized measure of covariance. To illustrate the generality of the method we introduce and explore it in the case of functional data, where (for example) it leads to generalized boxplots. The method has the advantage of providing an interpretable ranking that depends on the statistic under consideration. For example, the ranking of data, in terms of their influence on the value of a statistic, is different for a measure of location and for a measure of scale. This is as it should be; a ranking of data in terms of their influence should depend on the manner in which the data are used. Additionally, the ranking recognizes, rather than ignores, sign, and in particular can identify left- and right-hand ‘tails’ of the distribution of a random function or vector.

Ranking the adaptive capacity of nations to climate change when socio-political goals are explicit

Energy Technology Data Exchange (ETDEWEB)

Haddad, B.M. [University of California, Santa Cruz, CA (United States)

2005-07-01

The typical categories for measuring national adaptive capacity to climate change include a nation's wealth, technology, education, information, skills, infrastructure, access to resources, and management capabilities. Resulting rankings predictably mirror more general rankings of economic development, such as the Human Development Index. This approach is incomplete since it does not consider the normative or motivational context of adaptation. For what purpose or toward what goal does a nation aspire, and in that context, what is its adaptive capacity? This paper posits 11 possible national socio-political goals that fall into the three categories of teleological legitimacy, procedural legitimacy, and norm-based decision rules. A model that sorts nations in terms of adaptive capacity based on national socio-political aspirations is presented. While the aspiration of maximizing summed utility matches typical existing rankings, alternative aspirations, including contractarian liberalism, technocratic management, and dictatorial/religious rule alter the rankings. An example describes how this research can potentially inform how priorities are set for international assistance for climate change adaptation. (author)

Coping with nuclear power risks: the electric utility incentives

International Nuclear Information System (INIS)

Starr, C.; Whipple, C.

1982-01-01

The financial risks associated with nuclear power accidents are estimated by interpolating between frequency-vs.-severity data from routine outages and the frequency-vs.-severity estimates from the Nuclear Regulatory Commission's (NRC's) Reactor Safety Study (WASH-1400). This analysis indicates that the expected costs of plant damage and lost power production are large compared to the public risks estimated in WASH-1400, using values from An Approach to Quantitative Safety Goals for Nuclear Power Plants (NUREG-0739), prepared by the NRC Advisory Committee on Reactor Safeguards. Analyses of the cost-effectiveness of accident-prevention investments that include only anticipated public safety benefits will underestimate the value of such investments if reductions in power plant damage risk are not included. The analysis also suggests that utility self-interest and the public interest in safety are generally coincident. It is argued that greater use could be made of this self-interest in regulation if the relationship between the NRC and the industry were more cooperative, less adversary in nature

Ranking scientific publications: the effect of nonlinearity

Science.gov (United States)

Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; di, Zengru

2014-10-01

Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

Ranking scientific publications: the effect of nonlinearity.

Science.gov (United States)

Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; Di, Zengru

2014-10-17

Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

A study on ranking ethical factors influencing customer loyalty

Directory of Open Access Journals (Sweden)

Mahmood Modiri

2013-10-01

Full Text Available Having loyal customer is the primary objective of any business owner since loyal customers purchase on regular basis, create sustainable growth and reduce risk of bankruptcy. During the past few years, many people argue that customer loyalty must be established through ethical values. In this paper, we present an empirical investigation to detect ethical factors influencing customer loyalty. The proposed study determines five criteria including customer repurchase, interest in brand, recommending brand to others, positive attitude toward brand and cognitive loyalty to brand. These criteria have been ranked using fuzzy analytical network process. The study determines 14 different ethical values, which may play essential role on customer loyalty and using VIKOR, different ethical values are ranked. The study indicates that welcoming customers is the most important factor followed by cheerfulness, on time delivery, being informative and having appropriate standards.

Development of a multicriteria assessment model for ranking biomass feedstock collection and transportation systems.

Science.gov (United States)

Kumar, Amit; Sokhansanj, Shahab; Flynn, Peter C

2006-01-01

This study details multicriteria assessment methodology that integrates economic, social, environmental, and technical factors in order to rank alternatives for biomass collection and transportation systems. Ranking of biomass collection systems is based on cost of delivered biomass, quality of biomass supplied, emissions during collection, energy input to the chain operations, and maturity of supply system technologies. The assessment methodology is used to evaluate alternatives for collecting 1.8 x 10(6) dry t/yr based on assumptions made on performance of various assemblies of biomass collection systems. A proposed collection option using loafer/ stacker was shown to be the best option followed by ensiling and baling. Ranking of biomass transport systems is based on cost of biomass transport, emissions during transport, traffic congestion, and maturity of different technologies. At a capacity of 4 x 10(6) dry t/yr, rail transport was shown to be the best option, followed by truck transport and pipeline transport, respectively. These rankings depend highly on assumed maturity of technologies and scale of utilization. These may change if technologies such as loafing or ensiling (wet storage) methods are proved to be infeasible for large-scale collection systems.

Information risk in emerging utility markets: The role of commission- sponsored audits

Energy Technology Data Exchange (ETDEWEB)

Wirick, D.W.; Lawton, R.W.; Burns, R.E.; Lee, S.

1996-03-01

As public utilities and regulators begin to define their new relationship under various forms of regulations, some have questioned the continuing need for commission-sponsored audits. This study evaluates the role of such audits by examining their core purpose: the reduction of information risk (risk that a commission might make a wrong decision because of reliance on faulty information). It identifies five generic types of information that will be needed by commissions in the future and describes a cost-benefit analysis for identifying the appropriate method for mitigating information risk for state regulatory commissions.

Neural modelling of ranking data with an application to stated preference data

Directory of Open Access Journals (Sweden)

Catherine Krier

2013-05-01

Full Text Available Although neural networks are commonly encountered to solve classification problems, ranking data present specificities which require adapting the model. Based on a latent utility function defined on the characteristics of the objects to be ranked, the approach suggested in this paper leads to a perceptron-based algorithm for a highly non linear model. Data on stated preferences obtained through a survey by face-to-face interviews, in the field of freight transport, are used to illustrate the method. Numerical difficulties are pinpointed and a Pocket type algorithm is shown to provide an efficient heuristic to minimize the discrete error criterion. A substantial merit of this approach is to provide a workable estimation of contextually interpretable parameters along with a statistical evaluation of the goodness of fit.

Country-specific determinants of world university rankings.

Science.gov (United States)

Pietrucha, Jacek

2018-01-01

This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42-71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: economic potential of the country, research and development expenditure, long-term political stability (freedom from war, occupation, coups and major changes in the political system), and institutional variables, including government effectiveness.

Ranking in evolving complex networks

Science.gov (United States)

Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

2017-05-01

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

Groundwater contaminant plume ranking

International Nuclear Information System (INIS)

1988-08-01

Containment plumes at Uranium Mill Tailings Remedial Action (UMTRA) Project sites were ranked to assist in Subpart B (i.e., restoration requirements of 40 CFR Part 192) compliance strategies for each site, to prioritize aquifer restoration, and to budget future requests and allocations. The rankings roughly estimate hazards to the environment and human health, and thus assist in determining for which sites cleanup, if appropriate, will provide the greatest benefits for funds available. The rankings are based on the scores that were obtained using the US Department of Energy's (DOE) Modified Hazard Ranking System (MHRS). The MHRS and HRS consider and score three hazard modes for a site: migration, fire and explosion, and direct contact. The migration hazard mode score reflects the potential for harm to humans or the environment from migration of a hazardous substance off a site by groundwater, surface water, and air; it is a composite of separate scores for each of these routes. For ranking the containment plumes at UMTRA Project sites, it was assumed that each site had been remediated in compliance with the EPA standards and that relict contaminant plumes were present. Therefore, only the groundwater route was scored, and the surface water and air routes were not considered. Section 2.0 of this document describes the assumptions and procedures used to score the groundwater route, and Section 3.0 provides the resulting scores for each site. 40 tabs

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

Directory of Open Access Journals (Sweden)

Salomon Joshua A

2003-12-01

Full Text Available Abstract Background In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. Methods Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC between predictions and mean observations, and the root mean squared error of predictions at the individual level. Results Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99. Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. Conclusions

A human fecal contamination index for ranking impaired ...

Science.gov (United States)

Human fecal pollution of surface water remains a public health concern worldwide. As a result, there is a growing interest in the application of human-associated fecal source identification quantitative real-time PCR (qPCR) technologies for recreational water quality risk management. The transition from a research subject to a management tool requires the integration of standardized water sampling, laboratory, and data analysis procedures. In this study, a standardized HF183/BacR287 qPCR method was combined with a water sampling strategy and Bayesian data algorithm to establish a human fecal contamination index that can be used to rank impaired recreational water sites polluted with human waste. Stability and bias of index predictions were investigated under various parameters including siteswith different pollution levels, sampling period time range (1-15 weeks), and number of qPCR replicates per sample (2-14 replicates). Sensitivity analyses were conducted with simulated data sets (100 iterations) seeded with HF183/BacR287 qPCR laboratory measurements from water samples collected from three Southern California sites (588 qPCR measurements). Findings suggest that site ranking is feasible and that all parameters tested influence stability and bias in human fecal contamination indexscoring. Trends identified by sensitivity analyses will provide managers with the information needed to design and conduct field studies to rank impaired recreational water sites based

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.

Inhibition of osteoclastogenesis by RNA interference targeting RANK

Directory of Open Access Journals (Sweden)

Ma Ruofan

2012-08-01

Full Text Available Abstract Background Osteoclasts and osteoblasts regulate bone resorption and formation to allow bone remodeling and homeostasis. The balance between bone resorption and formation is disturbed by abnormal recruitment of osteoclasts. Osteoclast differentiation is dependent on the receptor activator of nuclear factor NF-kappa B (RANK ligand (RANKL as well as the macrophage colony-stimulating factor (M-CSF. The RANKL/RANK system and RANK signaling induce osteoclast formation mediated by various cytokines. The RANK/RANKL pathway has been primarily implicated in metabolic, degenerative and neoplastic bone disorders or osteolysis. The central role of RANK/RANKL interaction in osteoclastogenesis makes RANK an attractive target for potential therapies in treatment of osteolysis. The purpose of this study was to assess the effect of inhibition of RANK expression in mouse bone marrow macrophages on osteoclast differentiation and bone resorption. Methods Three pairs of short hairpin RNAs (shRNA targeting RANK were designed and synthesized. The optimal shRNA was selected among three pairs of shRNAs by RANK expression analyzed by Western blot and Real-time PCR. We investigated suppression of osteoclastogenesis of mouse bone marrow macrophages (BMMs using the optimal shRNA by targeting RANK. Results Among the three shRANKs examined, shRANK-3 significantly suppressed [88.3%] the RANK expression (p Conclusions These findings suggest that retrovirus-mediated shRNA targeting RANK inhibits osteoclast differentiation and osteolysis. It may appear an attractive target for preventing osteolysis in humans with a potential clinical application.

BridgeRank: A novel fast centrality measure based on local structure of the network

Science.gov (United States)

Salavati, Chiman; Abdollahpouri, Alireza; Manbari, Zhaleh

2018-04-01

Ranking nodes in complex networks have become an important task in many application domains. In a complex network, influential nodes are those that have the most spreading ability. Thus, identifying influential nodes based on their spreading ability is a fundamental task in different applications such as viral marketing. One of the most important centrality measures to ranking nodes is closeness centrality which is efficient but suffers from high computational complexity O(n3) . This paper tries to improve closeness centrality by utilizing the local structure of nodes and presents a new ranking algorithm, called BridgeRank centrality. The proposed method computes local centrality value for each node. For this purpose, at first, communities are detected and the relationship between communities is completely ignored. Then, by applying a centrality in each community, only one best critical node from each community is extracted. Finally, the nodes are ranked based on computing the sum of the shortest path length of nodes to obtained critical nodes. We have also modified the proposed method by weighting the original BridgeRank and selecting several nodes from each community based on the density of that community. Our method can find the best nodes with high spread ability and low time complexity, which make it applicable to large-scale networks. To evaluate the performance of the proposed method, we use the SIR diffusion model. Finally, experiments on real and artificial networks show that our method is able to identify influential nodes so efficiently, and achieves better performance compared to other recent methods.

On Rank and Nullity

Science.gov (United States)

Dobbs, David E.

2012-01-01

This note explains how Emil Artin's proof that row rank equals column rank for a matrix with entries in a field leads naturally to the formula for the nullity of a matrix and also to an algorithm for solving any system of linear equations in any number of variables. This material could be used in any course on matrix theory or linear algebra.

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....

A Universal Rank-Size Law

Science.gov (United States)

2016-01-01

A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations. PMID:27812192

Comparative Pessimism or Optimism: Depressed Mood, Risk-Taking, Social Utility and Desirability.

Science.gov (United States)

Milhabet, Isabelle; Le Barbenchon, Emmanuelle; Cambon, Laurent; Molina, Guylaine

2015-03-05

Comparative optimism can be defined as a self-serving, asymmetric judgment of the future. It is often thought to be beneficial and socially accepted, whereas comparative pessimism is correlated with depression and socially rejected. Our goal was to examine the social acceptance of comparative optimism and the social rejection of comparative pessimism in two dimensions of social judgment, social desirability and social utility, considering the attributions of dysphoria and risk-taking potential (studies 2 and 3) on outlooks on the future. In three experiments, the participants assessed either one (study 1) or several (studies 2 and 3) fictional targets in two dimensions, social utility and social desirability. Targets exhibiting comparatively optimistic or pessimistic outlooks on the future were presented as non-depressed, depressed, or neither (control condition) (study 1); non-depressed or depressed (study 2); and non-depressed or in control condition (study 3). Two significant results were obtained: (1) social rejection of comparative pessimism in the social desirability dimension, which can be explained by its depressive feature; and (2) comparative optimism was socially accepted on the social utility dimension, which can be explained by the perception that comparatively optimistic individuals are potential risk-takers.

Ranking alternatives based on imprecise multi-criteria data and pairwise overlap dominance relations

DEFF Research Database (Denmark)

Franco de los Rios, Camilo Andres; Hougaard, Jens Leth; Nielsen, Kurt

illustrative example is given for comparison with standard methods like PROMETHEE. The proposed methodology takes into account the risk attitudes of decision makers, organizing the alternatives and ranking them according to their relevance. The whole interactive decision support allows understanding...

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.

Ranking Hospitals Based on Colon Surgery and Abdominal Hysterectomy Surgical Site Infection Outcomes: Impact of Limiting Surveillance to the Operative Hospital.

Science.gov (United States)

Yokoe, Deborah S; Avery, Taliser R; Platt, Richard; Kleinman, Ken; Huang, Susan S

2018-03-16

Hospital-specific surgical site infection (SSI) performance following colon surgery and abdominal hysterectomies can impact hospitals' relative rankings around quality metrics used to determine financial penalties. Current SSI surveillance largely focuses on SSI detected at the operative hospital. Retrospective cohort study to assess the impact on hospitals' relative SSI performance rankings when SSI detected at non-operative hospitals are included. We utilized data from a California statewide hospital registry to assess for evidence of SSI following colon surgery or abdominal hysterectomies performed 3/1/2011-11/30/2013 using previously validated claims-based SSI surveillance methods. Risk-adjusted hospital-specific rankings based on SSI detected at operative hospitals versus any California hospital were generated. Among 60,059 colon surgeries at 285 hospitals and 64,918 abdominal hysterectomies at 270 hospitals, 5,921 (9.9%) colon surgeries and 1,481 (2.3%) abdominal hysterectomies received a diagnosis code for SSI within the 30 days following surgery. 7.2% of colon surgery and 13.4% of abdominal hysterectomy SSI would have been missed by operative hospital surveillance alone. The proportion of individual hospital's SSI detected during hospitalizations at other hospitals varied widely. Including non-operative hospital SSI resulted in improved relative ranking of 11 (3.9%) colon surgery and 13 (4.8%) hysterectomy hospitals so that they were no longer in the worst performing quartile, mainly among hospitals with relatively high surgical volumes. Standard SSI surveillance that mainly focuses on infections detected at the operative hospital causes varying degrees of SSI under-estimation, leading to inaccurate assignment or avoidance of financial penalties for approximately one in eleven to sixteen hospitals.

Rank-based testing of equal survivorship based on cross-sectional survival data with or without prospective follow-up.

Science.gov (United States)

Chan, Kwun Chuen Gary; Qin, Jing

2015-10-01

Existing linear rank statistics cannot be applied to cross-sectional survival data without follow-up since all subjects are essentially censored. However, partial survival information are available from backward recurrence times and are frequently collected from health surveys without prospective follow-up. Under length-biased sampling, a class of linear rank statistics is proposed based only on backward recurrence times without any prospective follow-up. When follow-up data are available, the proposed rank statistic and a conventional rank statistic that utilizes follow-up information from the same sample are shown to be asymptotically independent. We discuss four ways to combine these two statistics when follow-up is present. Simulations show that all combined statistics have substantially improved power compared with conventional rank statistics, and a Mantel-Haenszel test performed the best among the proposal statistics. The method is applied to a cross-sectional health survey without follow-up and a study of Alzheimer's disease with prospective follow-up. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A framework for estimating health state utility values within a discrete choice experiment: modeling risky choices.

Science.gov (United States)

Robinson, Angela; Spencer, Anne; Moffatt, Peter

2015-04-01

There has been recent interest in using the discrete choice experiment (DCE) method to derive health state utilities for use in quality-adjusted life year (QALY) calculations, but challenges remain. We set out to develop a risk-based DCE approach to derive utility values for health states that allowed 1) utility values to be anchored directly to normal health and death and 2) worse than dead health states to be assessed in the same manner as better than dead states. Furthermore, we set out to estimate alternative models of risky choice within a DCE model. A survey was designed that incorporated a risk-based DCE and a "modified" standard gamble (SG). Health state utility values were elicited for 3 EQ-5D health states assuming "standard" expected utility (EU) preferences. The DCE model was then generalized to allow for rank-dependent expected utility (RDU) preferences, thereby allowing for probability weighting. A convenience sample of 60 students was recruited and data collected in small groups. Under the assumption of "standard" EU preferences, the utility values derived within the DCE corresponded fairly closely to the mean results from the modified SG. Under the assumption of RDU preferences, the utility values estimated are somewhat lower than under the assumption of standard EU, suggesting that the latter may be biased upward. Applying the correct model of risky choice is important whether a modified SG or a risk-based DCE is deployed. It is, however, possible to estimate a probability weighting function within a DCE and estimate "unbiased" utility values directly, which is not possible within a modified SG. We conclude by setting out the relative strengths and weaknesses of the 2 approaches in this context. © The Author(s) 2014.

Managing carbon regulatory risk in utility resource planning: Current practices in the Western United States

International Nuclear Information System (INIS)

Barbose, Galen; Wiser, Ryan; Phadke, Amol; Goldman, Charles

2008-01-01

Concerns about global climate change have substantially increased the likelihood that future policy will seek to minimize carbon dioxide emissions. As such, even today, electric utilities are making resource planning and investment decisions that consider the possible implications of these future carbon regulations. In this article, we examine the manner in which utilities assess the financial risks associated with future carbon regulations within their long-term resource plans. We base our analysis on a review of the most recent resource plans filed by 15 electric utilities in the Western United States. Virtually all of these utilities made some effort to quantitatively evaluate the potential cost of future carbon regulations when analyzing alternate supply- and demand-side resource options for meeting customer load. Even without federal climate regulation in the US, the prospect of that regulation is already having an impact on utility decision-making and resource choices. That said, the methods and assumptions used by utilities to analyze carbon regulatory risk, and the impact of that analysis on their choice of a particular resource strategy, vary considerably, revealing a number of opportunities for analytic improvement. Though our review focuses on a subset of US electric utilities, this work holds implications for all electric utilities and energy policymakers who are seeking to minimize the compliance costs associated with future carbon regulations

Adiabatic quantum algorithm for search engine ranking.

Science.gov (United States)

Garnerone, Silvano; Zanardi, Paolo; Lidar, Daniel A

2012-06-08

We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of web pages. We argue that the main topological feature of the underlying web graph allowing for such a scaling is the out-degree distribution. The top-ranked log(n) entries of the quantum PageRank state can then be estimated with a polynomial quantum speed-up. Moreover, the quantum PageRank state can be used in "q-sampling" protocols for testing properties of distributions, which require exponentially fewer measurements than all classical schemes designed for the same task. This can be used to decide whether to run a classical update of the PageRank.

Comparing classical and quantum PageRanks

Science.gov (United States)

Loke, T.; Tang, J. W.; Rodriguez, J.; Small, M.; Wang, J. B.

2017-01-01

Following recent developments in quantum PageRanking, we present a comparative analysis of discrete-time and continuous-time quantum-walk-based PageRank algorithms. Relative to classical PageRank and to different extents, the quantum measures better highlight secondary hubs and resolve ranking degeneracy among peripheral nodes for all networks we studied in this paper. For the discrete-time case, we investigated the periodic nature of the walker's probability distribution for a wide range of networks and found that the dominant period does not grow with the size of these networks. Based on this observation, we introduce a new quantum measure using the maximum probabilities of the associated walker during the first couple of periods. This is particularly important, since it leads to a quantum PageRanking scheme that is scalable with respect to network size.

Risks associated with antiretroviral treatment for human immunodeficiency virus (HIV): qualitative analysis of social media data and health state utility valuation.

Science.gov (United States)

Matza, Louis S; Chung, Karen C; Kim, Katherine J; Paulus, Trena M; Davies, Evan W; Stewart, Katie D; McComsey, Grace A; Fordyce, Marshall W

2017-07-01

Despite benefits of antiretroviral therapies (ART), people with HIV infection have increased risk of cardiovascular disease, kidney disease, and low bone mineral density. Some ARTs increase risk of these events. The purpose of this study was to examine patients' perspectives of these risks and estimate health state utilities associated with these risks for use in cost-utility models. Qualitative thematic analysis was conducted to examine messages posted to the POZ/AIDSmeds Internet community forums, focusing on bone, kidney, and cardiovascular side effects and risks of HIV/AIDS medications. Then, health state vignettes were drafted based on this qualitative analysis, literature review, and clinician interviews. The health states (representing HIV, plus treatment-related risks) were valued in time trade-off interviews with general population participants in the UK. Qualitative analysis of the Internet forums documented patient concerns about ART risks, as well as treatment decisions made because of these risks. A total of 208 participants completed utility interviews (51.4% female; mean age 44.6 years). The mean utility of the HIV health state (virologically suppressed, treated with ART) was 0.86. Adding a description of risk resulted in statistically significant disutility (i.e., utility decreases): renal risk (disutility = -0.02), bone risk (-0.03), and myocardial infarction risk (-0.05). Patient concerns and treatment decisions were documented via qualitative analysis of Internet forum discussions, and the impact of these concerns was quantified in terms of health state utilities. The resulting disutilities may be useful for differentiating among ARTs in economic modeling of treatment for patients with HIV.

Error analysis of stochastic gradient descent ranking.

Science.gov (United States)

Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

2013-06-01

Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

Contests with rank-order spillovers

NARCIS (Netherlands)

M.R. Baye (Michael); D. Kovenock (Dan); C.G. de Vries (Casper)

2012-01-01

textabstractThis paper presents a unified framework for characterizing symmetric equilibrium in simultaneous move, two-player, rank-order contests with complete information, in which each player's strategy generates direct or indirect affine "spillover" effects that depend on the rank-order of her

A web-based tool for ranking landslide mitigation measures

Science.gov (United States)

Lacasse, S.; Vaciago, G.; Choi, Y. J.; Kalsnes, B.

2012-04-01

brief description, guidance on design, schematic details, practical examples and references for each mitigation measure. Each of the measures was given a score on its ability and applicability for different types of landslides and boundary conditions, and a decision support matrix was established. The web-based toolbox organizes the information in the compendium and provides an algorithm to rank the measures on the basis of the decision support matrix, and on the basis of the risk level estimated at the site. The toolbox includes a description of the case under study and offers a simplified option for estimating the hazard and risk levels of the slide at hand. The user selects the mitigation measures to be included in the assessment. The toolbox then ranks, with built-in assessment factors and weights and/or with user-defined ranking values and criteria, the mitigation measures included in the analysis. The toolbox includes data management, e.g. saving data half-way in an analysis, returning to an earlier case, looking up prepared examples or looking up information on mitigation measures. The toolbox also generates a report and has user-forum and help features. The presentation will give an overview of the mitigation measures considered and examples of the use of the toolbox, and will take the attendees through the application of the toolbox.

Hazard ranking system: hierarchical system for polluted soils; El Hazard Ranking System. Un sistema para la jerarquizacion de actuaciones en terrenos contaminados

Energy Technology Data Exchange (ETDEWEB)

Callaba de Roa, A

1998-10-01

To develop cost-effective risk minimization strategies, it is important to carefully select contaminated sites in which future tasks will take place (hierarchy of tasks). A hierarchy of sites must focus on those which really pose a significant environmental hazard. Hierarchical systems have demonstrated their performance as environmental management tools in some US programs facing risk management at contaminated sites. In this paper basic features of the hazard Ranking System, developed by US EPA for Superfund, are described. Advantages and disadvantages are discussed and, finally, the suitability of a system similar to this is considered as a management tool for the Spanish Plan Nacional de Recuperacion de Suelos Contaminados. (Author) 9 refs.

Rank distributions: A panoramic macroscopic outlook

Science.gov (United States)

Eliazar, Iddo I.; Cohen, Morrel H.

2014-01-01

This paper presents a panoramic macroscopic outlook of rank distributions. We establish a general framework for the analysis of rank distributions, which classifies them into five macroscopic "socioeconomic" states: monarchy, oligarchy-feudalism, criticality, socialism-capitalism, and communism. Oligarchy-feudalism is shown to be characterized by discrete macroscopic rank distributions, and socialism-capitalism is shown to be characterized by continuous macroscopic size distributions. Criticality is a transition state between oligarchy-feudalism and socialism-capitalism, which can manifest allometric scaling with multifractal spectra. Monarchy and communism are extreme forms of oligarchy-feudalism and socialism-capitalism, respectively, in which the intrinsic randomness vanishes. The general framework is applied to three different models of rank distributions—top-down, bottom-up, and global—and unveils each model's macroscopic universality and versatility. The global model yields a macroscopic classification of the generalized Zipf law, an omnipresent form of rank distributions observed across the sciences. An amalgamation of the three models establishes a universal rank-distribution explanation for the macroscopic emergence of a prevalent class of continuous size distributions, ones governed by unimodal densities with both Pareto and inverse-Pareto power-law tails.

Importance of intrinsic and non-network contribution in PageRank centrality and its effect on PageRank localization

OpenAIRE

Deyasi, Krishanu

2016-01-01

PageRank centrality is used by Google for ranking web-pages to present search result for a user query. Here, we have shown that PageRank value of a vertex also depends on its intrinsic, non-network contribution. If the intrinsic, non-network contributions of the vertices are proportional to their degrees or zeros, then their PageRank centralities become proportion to their degrees. Some simulations and empirical data are used to support our study. In addition, we have shown that localization ...

Ranking as parameter estimation

Czech Academy of Sciences Publication Activity Database

Kárný, Miroslav; Guy, Tatiana Valentine

2009-01-01

Roč. 4, č. 2 (2009), s. 142-158 ISSN 1745-7645 R&D Projects: GA MŠk 2C06001; GA AV ČR 1ET100750401; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : ranking * Bayesian estimation * negotiation * modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2009/AS/karny- ranking as parameter estimation.pdf

Diversifying customer review rankings.

Science.gov (United States)

Krestel, Ralf; Dokoohaki, Nima

2015-06-01

E-commerce Web sites owe much of their popularity to consumer reviews accompanying product descriptions. On-line customers spend hours and hours going through heaps of textual reviews to decide which products to buy. At the same time, each popular product has thousands of user-generated reviews, making it impossible for a buyer to read everything. Current approaches to display reviews to users or recommend an individual review for a product are based on the recency or helpfulness of each review. In this paper, we present a framework to rank product reviews by optimizing the coverage of the ranking with respect to sentiment or aspects, or by summarizing all reviews with the top-K reviews in the ranking. To accomplish this, we make use of the assigned star rating for a product as an indicator for a review's sentiment polarity and compare bag-of-words (language model) with topic models (latent Dirichlet allocation) as a mean to represent aspects. Our evaluation on manually annotated review data from a commercial review Web site demonstrates the effectiveness of our approach, outperforming plain recency ranking by 30% and obtaining best results by combining language and topic model representations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparative study to explore factors affecting E-government ranking: the case of Malaysia, Nigeria and Republic of Korea

Directory of Open Access Journals (Sweden)

Wan Rozaini Sheik Osman

2017-12-01

Full Text Available The present study aims to find out the criteria for e-government ranking generally as well as particularly focusing on Malaysia’s e-government ranking. In addition, with regard to the Malaysia’s e-government ranking, the results shown that, most of the Human Capital, Online Services and Telecommunication Infrastructure and its sub-indicators has not seen any improvement through the previous periods comparing with other countries such as Republic of Korea. Indeed, this comparative study sought to highlight of the tangible part of the e-government ranking through explored the gap between the e-government of Malaysia and other countries such as Republic of Korea. Moreover, this study discovered the weakest dimensions of e-government applications to assist the government to address them. Besides that, this comparative study also attempts to help the countries all over the world especially those developing ones in enhancing the performance of the e-government simply by understanding the reasons of the utilization by the respective stakeholders.

Ranking of VaR and ES models: performance in developed and emerging markets

Czech Academy of Sciences Publication Activity Database

Žiković, S.; Filer, Randall K.

2013-01-01

Roč. 63, č. 4 (2013), s. 327-359 ISSN 0015-1920 Institutional support: RVO:67985998 Keywords : ranking * value at risk * expected shortfall Subject RIV: AH - Economics Impact factor: 0.358, year: 2013 http://journal.fsv.cuni.cz/storage/1279_327-359-filer.pdf

Journal Rankings by Health Management Faculty Members: Are There Differences by Rank, Leadership Status, or Area of Expertise?

Science.gov (United States)

Menachemi, Nir; Hogan, Tory H; DelliFraine, Jami L

2015-01-01

Health administration (HA) faculty members publish in a variety of journals, including journals focused on management, economics, policy, and information technology. HA faculty members are evaluated on the basis of the quality and quantity of their journal publications. However, it is unclear how perceptions of these journals vary by subdiscipline, department leadership role, or faculty rank. It is also not clear how perceptions of journals may have changed over the past decade since the last evaluation of journal rankings in the field was published. The purpose of the current study is to examine how respondents rank journals in the field of HA, as well as the variation in perception by academic rank, department leadership status, and area of expertise. Data were drawn from a survey of HA faculty members at U.S. universities, which was completed in 2012. Different journal ranking patterns were noted for faculty members of different subdisciplines. The health management-oriented journals (Health Care Management Review and Journal of Healthcare Management) were ranked higher than in previous research, suggesting that journal ranking perceptions may have changed over the intervening decade. Few differences in perceptions were noted by academic rank, but we found that department chairs were more likely than others to select Health Affairs in their top three most prestigious journals (β = 0.768; p journal prestige varied between a department chair and untenured faculty in different disciplines, and this perceived difference could have implications for promotion and tenure decisions.

Algebraic and computational aspects of real tensor ranks

CERN Document Server

Sakata, Toshio; Miyazaki, Mitsuhiro

2016-01-01

This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field. Although tensor ranks have been often argued in the complex number field, it should be emphasized that this book treats real tensor ranks, which have direct applications in statistics. The book provides several interesting ideas, including determinant polynomials, determinantal ideals, absolutely nonsingular tensors, absolutely full column rank tensors, and their connection to bilinear maps and Hurwitz-Radon numbers. In addition to reviews of methods to determine real tensor ranks in details, global theories such as the Jacobian method are also reviewed in details. The book includes as well an accessible and comprehensive introduction of mathematical backgrounds, with basics of positive polynomials and calculations by using the Groebner basis. Furthermore, this book provides insights into numerical methods of finding tensor ranks through...

Report on probabilistic safety assessment (PSA) quality assurance in utilization of risk information

International Nuclear Information System (INIS)

2006-12-01

Recently in Japan, introduction of nuclear safety regulations using risk information such as probabilistic safety assessment (PSA) has been considered and utilization of risk information in the rational and practical measures on safety assurance has made a progress to start with the operation or inspection area. The report compiled results of investigation and studies of PSA quality assurance in risk-informed activities in the USA. Relevant regulatory guide and standard review plan as well as issues and recommendations were reviewed for technical adequacy and advancement of probabilistic risk assessment technology in risk-informed decision making. Useful and important information to be referred as issues in PSA quality assurance was identified. (T. Tanaka)

A methodology for ranking and hazard identification of xenobiotic organic compounds in urban stormwater

DEFF Research Database (Denmark)

Baun, Anders; Eriksson, Eva; Ledin, Anna

2006-01-01

The paper presents a novel methodology (RICH, Ranking and Identification of Chemical Hazards) for ranking and identification of xenobiotic organic compounds of environmental concern in stormwater discharged to surface water. The RICHmethod is illustrated as a funnel fitted with different filters...... in hazard/risk assessments, a justified list of stormwater priority pollutants which must be included in hazard/risk assessments, and a list of compounds which may be present in discharged stormwater, but cannot be evaluated due to lack of data. The procedure was applied to 233 xenobiotic organic chemicals...... with xenobiotic organic compounds (XOCs) found in urban stormwater, but it may be transferred to other environmental compartments and problems. Thus, the RICH procedure can be used as a stand-alone tool for selection of potential priority pollutants or it can be integrated in larger priority setting frameworks....

Virtual drug screen schema based on multiview similarity integration and ranking aggregation.

Science.gov (United States)

Kang, Hong; Sheng, Zhen; Zhu, Ruixin; Huang, Qi; Liu, Qi; Cao, Zhiwei

2012-03-26

The current drug virtual screen (VS) methods mainly include two categories. i.e., ligand/target structure-based virtual screen and that, utilizing protein-ligand interaction fingerprint information based on the large number of complex structures. Since the former one focuses on the one-side information while the later one focuses on the whole complex structure, they are thus complementary and can be boosted by each other. However, a common problem faced here is how to present a comprehensive understanding and evaluation of the various virtual screen results derived from various VS methods. Furthermore, there is still an urgent need for developing an efficient approach to fully integrate various VS methods from a comprehensive multiview perspective. In this study, our virtual screen schema based on multiview similarity integration and ranking aggregation was tested comprehensively with statistical evaluations, providing several novel and useful clues on how to perform drug VS from multiple heterogeneous data sources. (1) 18 complex structures of HIV-1 protease with ligands from the PDB were curated as a test data set and the VS was performed with five different drug representations. Ritonavir ( 1HXW ) was selected as the query in VS and the weighted ranks of the query results were aggregated from multiple views through four similarity integration approaches. (2) Further, one of the ranking aggregation methods was used to integrate the similarity ranks calculated by gene ontology (GO) fingerprint and structural fingerprint on the data set from connectivity map, and two typical HDAC and HSP90 inhibitors were chosen as the queries. The results show that rank aggregation can enhance the result of similarity searching in VS when two or more descriptions are involved and provide a more reasonable similarity rank result. Our study shows that integrated VS based on multiple data fusion can achieve a remarkable better performance compared to that from individual ones and

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...

ArgueSecure: Out-of-the-box Risk Assessment

NARCIS (Netherlands)

Ionita, Dan; Kegel, Roeland Hendrik,Pieter; Wieringa, Roelf J.; Baltuta, Andrei

Most established security risk assessment methodologies aim to produce ranked lists of risks. But ranking requires quantification of risks, which in turn relies on data which may not be available or estimations which might not be accurate. As an alternative, we have previously proposed

Comparing downside risk measures for heavy tailed distributions

NARCIS (Netherlands)

Daníelsson, J.; Jorgensen, B.N.; Sarma, M.; Vries, de C.G.

2006-01-01

Using regular variation to define heavy tailed distributions, we show that prominent downside risk measures produce similar and consistent ranking of heavy tailed risk. Thus, regardless of the particular risk measure being used, assets will be ranked in a similar and consistent manner for heavy

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...

Low-Rank Linear Dynamical Systems for Motor Imagery EEG.

Science.gov (United States)

Zhang, Wenchang; Sun, Fuchun; Tan, Chuanqi; Liu, Shaobo

2016-01-01

The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from "BCI Competition III Dataset IVa" and "BCI Competition IV Database 2a." The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP.

Opportunities in low-rank coal applications for synfuels and power industries in Mexico

International Nuclear Information System (INIS)

Winch, R.A.; Alejandro, I.; Hernandez, G.

1992-01-01

The utilization of domestic coal is an important ingredient in the generation strategy of electricity in Mexico. The relative ranking of the MICARE and Sabinas coals, compared to other coals tested at the Energy and Environmental Research Center (EERC) pilot test facility at Grand Forks is an important factor for future economic fuel studies. A test comparison between US and Mexican coals was made and observations are listed

Investigating Gender Differences under Time Pressure in Financial Risk Taking.

Science.gov (United States)

Xie, Zhixin; Page, Lionel; Hardy, Ben

2017-01-01

There is a significant gender imbalance on financial trading floors. This motivated us to investigate gender differences in financial risk taking under pressure. We used a well-established approach from behavior economics to analyze a series of risky monetary choices by male and female participants with and without time pressure. We also used second to fourth digit ratio (2D:4D) and face width-to-height ratio (fWHR) as correlates of pre-natal exposure to testosterone. We constructed a structural model and estimated the participants' risk attitudes and probability perceptions via maximum likelihood estimation under both expected utility (EU) and rank-dependent utility (RDU) models. In line with existing research, we found that male participants are less risk averse and that the gender gap in risk attitudes increases under moderate time pressure. We found that female participants with lower 2D:4D ratios and higher fWHR are less risk averse in RDU estimates. Males with lower 2D:4D ratios were less risk averse in EU estimations, but more risk averse using RDU estimates. We also observe that men whose ratios indicate a greater prenatal exposure to testosterone exhibit a greater optimism and overestimation of small probabilities of success.

Model of Decision Making through Consensus in Ranking Case

Science.gov (United States)

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).

Ranking of sabotage/tampering avoidance technology alternatives

Energy Technology Data Exchange (ETDEWEB)

Andrews, W.B.; Tabatabai, A.S.; Powers, T.B.; Daling, P.M.; Fecht, B.A.; Gore, B.F.; Overcast, T.D.; Rankin, W.R.; Schreiber, R.E.; Tawil, J.J.

1986-01-01

Pacific Northwest Laboratory conducted a study to evaluate alternatives to the design and operation of nuclear power plants, emphasizing a reduction of their vulnerability to sabotage. Estimates of core melt accident frequency during normal operations and from sabotage/tampering events were used to rank the alternatives. Core melt frequency for normal operations was estimated using sensitivity analysis of results of probabilistic risk assessments. Core melt frequency for sabotage/tampering was estimated by developing a model based on probabilistic risk analyses, historic data, engineering judgment, and safeguards analyses of plant locations where core melt events could be initiated. Results indicate the most effective alternatives focus on large areas of the plant, increase safety system redundancy, and reduce reliance on single locations for mitigation of transients. Less effective options focus on specific areas of the plant, reduce reliance on some plant areas for safe shutdown, and focus on less vulnerable targets.

Ranking of sabotage/tampering avoidance technology alternatives

International Nuclear Information System (INIS)

Andrews, W.B.; Tabatabai, A.S.; Powers, T.B.

1986-01-01

Pacific Northwest Laboratory conducted a study to evaluate alternatives to the design and operation of nuclear power plants, emphasizing a reduction of their vulnerability to sabotage. Estimates of core melt accident frequency during normal operations and from sabotage/tampering events were used to rank the alternatives. Core melt frequency for normal operations was estimated using sensitivity analysis of results of probabilistic risk assessments. Core melt frequency for sabotage/tampering was estimated by developing a model based on probabilistic risk analyses, historic data, engineering judgment, and safeguards analyses of plant locations where core melt events could be initiated. Results indicate the most effective alternatives focus on large areas of the plant, increase safety system redundancy, and reduce reliance on single locations for mitigation of transients. Less effective options focus on specific areas of the plant, reduce reliance on some plant areas for safe shutdown, and focus on less vulnerable targets

The Privilege of Ranking: Google Plays Ball.

Science.gov (United States)

Wiggins, Richard

2003-01-01

Discussion of ranking systems used in various settings, including college football and academic admissions, focuses on the Google search engine. Explains the PageRank mathematical formula that scores Web pages by connecting the number of links; limitations, including authenticity and accuracy of ranked Web pages; relevancy; adjusting algorithms;…

Probabilistic relation between In-Degree and PageRank

NARCIS (Netherlands)

Litvak, Nelli; Scheinhardt, Willem R.W.; Volkovich, Y.

2008-01-01

This paper presents a novel stochastic model that explains the relation between power laws of In-Degree and PageRank. PageRank is a popularity measure designed by Google to rank Web pages. We model the relation between PageRank and In-Degree through a stochastic equation, which is inspired by the

Quiggin's Rank Dependent Model. Review of Generalized Expected Utility Theory: The Rank-Dependent Model, by John Quiggin

NARCIS (Netherlands)

P.P. Wakker (Peter)

1994-01-01

textabstractJohn Quiggin is a professor at the centre for Economic Policy Research of the Australian National University. His research interests are decision making under risk and agricultural economics. The reviewer is an associate professor at the Medical Decision Making Unit, University of

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.

Generalized PageRank on Directed Configuration Networks

NARCIS (Netherlands)

Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana

2017-01-01

Note: formula is not displayed correctly. This paper studies the distribution of a family of rankings, which includes Google’s PageRank, on a directed configuration model. In particular, it is shown that the distribution of the rank of a randomly chosen node in the graph converges in distribution to

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...

Efficient elicitation of utility and probability weighting functions

Czech Academy of Sciences Publication Activity Database

Blavatskyy, Pavlo R.

-, č. 211 (2004), s. 1-31 ISSN 1424-0459 Institutional research plan: CEZ:AV0Z7085904 Keywords : decision theory * rank-dependent expected utility * cumulative prospect theory Subject RIV: AH - Economics http://www.iew.unizh.ch/wp/iewwp211.pdf

Ranking Theory and Conditional Reasoning.

Science.gov (United States)

Skovgaard-Olsen, Niels

2016-05-01

Ranking theory is a formal epistemology that has been developed in over 600 pages in Spohn's recent book The Laws of Belief, which aims to provide a normative account of the dynamics of beliefs that presents an alternative to current probabilistic approaches. It has long been received in the AI community, but it has not yet found application in experimental psychology. The purpose of this paper is to derive clear, quantitative predictions by exploiting a parallel between ranking theory and a statistical model called logistic regression. This approach is illustrated by the development of a model for the conditional inference task using Spohn's (2013) ranking theoretic approach to conditionals. Copyright © 2015 Cognitive Science Society, Inc.

The structure of completely positive matrices according to their CP-rank and CP-plus-rank

NARCIS (Netherlands)

Dickinson, Peter James Clair; Bomze, Immanuel M.; Still, Georg J.

2015-01-01

We study the topological properties of the cp-rank operator $\\mathrm{cp}(A)$ and the related cp-plus-rank operator $\\mathrm{cp}^+(A)$ (which is introduced in this paper) in the set $\\mathcal{S}^n$ of symmetric $n\\times n$-matrices. For the set of completely positive matrices, $\\mathcal{CP}^n$, we

Communities in Large Networks: Identification and Ranking

DEFF Research Database (Denmark)

Olsen, Martin

2008-01-01

We study the problem of identifying and ranking the members of a community in a very large network with link analysis only, given a set of representatives of the community. We define the concept of a community justified by a formal analysis of a simple model of the evolution of a directed graph. ...... and its immediate surroundings. The members are ranked with a “local” variant of the PageRank algorithm. Results are reported from successful experiments on identifying and ranking Danish Computer Science sites and Danish Chess pages using only a few representatives....

Nominal versus Attained Weights in Universitas 21 Ranking

Science.gov (United States)

Soh, Kaycheng

2014-01-01

Universitas 21 Ranking of National Higher Education Systems (U21 Ranking) is one of the three new ranking systems appearing in 2012. In contrast with the other systems, U21 Ranking uses countries as the unit of analysis. It has several features which lend it with greater trustworthiness, but it also shared some methodological issues with the other…

Development of phenomena identification and ranking table for APR1400 main steam line break

International Nuclear Information System (INIS)

Song, J. H.; Chung, B. D.; Jeong, J. J.

2003-01-01

A Phenomena Identification and Ranking Table (PIRT) was developed for the Main Steam Line Break (MSLB) event of an APR-1400 (Advanced Power Reactor-1400). A team of experts from research institutes, industries, and regulatory bodies participated in the development. The selected event was a double-ended steam line break at full power with the reactor coolant pump running. The panel selected the fuel performance as the primary safety criterion for ranking. The plant design data, the results of APR-1400 safety analysis, and the results of additional best estimate analysis by MARS2.1 were utilized. Three phases of pre-trip, rapid cool-down, and safety injection phase were identified. Then, the ranking of a system, components, phenomenon/process based on the relative importance to the primary evaluation criterion were followed for each time phase. Finally, the knowledge-level for each important process in the component was ranked in terms of the existing knowledge. The highly ranked phenomena identified for APR-1400 MSLB are tube wall heat transfer at the steam generator shell, void distribution at the steam generator shell, liquid entrainment in the separators, mixture level in the separators, boron mixing in the upper down comer, boron transport and thermal mixing in the lower plenum, stored energy release in the upper head, and flow to and/from the upper head. The PIRT will be used as a guide in planning cost effective experimental programs and code development efforts, especially for the quantification of the process and/or phenomena, which have a high importance but low knowledge level

A Comprehensive Analysis of Marketing Journal Rankings

Science.gov (United States)

Steward, Michelle D.; Lewis, Bruce R.

2010-01-01

The purpose of this study is to offer a comprehensive assessment of journal standings in Marketing from two perspectives. The discipline perspective of rankings is obtained from a collection of published journal ranking studies during the past 15 years. The studies in the published ranking stream are assessed for reliability by examining internal…

The BiPublishers ranking: Main results and methodological problems when constructing rankings of academic publishers

Directory of Open Access Journals (Sweden)

Torres-Salinas, Daniel

2015-12-01

Full Text Available We present the results of the Bibliometric Indicators for Publishers project (also known as BiPublishers. This project represents the first attempt to systematically develop bibliometric publisher rankings. The data for this project was derived from the Book Citation Index and the study time period was 2009-2013. We have developed 42 rankings: 4 by fields and 38 by disciplines. We display six indicators for publishers divided into three types: output, impact and publisher’s profile. The aim is to capture different characteristics of the research performance of publishers. 254 publishers were processed and classified according to publisher type: commercial publishers and university presses. We present the main publishers by field and then discuss the principal challenges presented when developing this type of tool. The BiPublishers ranking is an on-going project which aims to develop and explore new data sources and indicators to better capture and define the research impact of publishers.Presentamos los resultados del proyecto Bibliometric Indicators for Publishers (BiPublishers. Es el primer proyecto que desarrolla de manera sistemática rankings bibliométricos de editoriales. La fuente de datos empleada es el Book Citation Index y el periodo de análisis 2009-2013. Se presentan 42 rankings: 4 por áreas y 38 por disciplinas. Mostramos seis indicadores por editorial divididos según su tipología: producción, impacto y características editoriales. Se procesaron 254 editoriales y se clasificaron según el tipo: comerciales y universitarias. Se presentan las principales editoriales por áreas. Después, se discuten los principales retos a superar en el desarrollo de este tipo de herramientas. El ranking Bipublishers es un proyecto en desarrollo que persigue analizar y explorar nuevas fuentes de datos e indicadores para captar y definir el impacto de las editoriales académicas.

PageRank in scale-free random graphs

NARCIS (Netherlands)

Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana; Bonata, Anthony; Chung, Fan; Pralat, Paweł

2014-01-01

We analyze the distribution of PageRank on a directed configuration model and show that as the size of the graph grows to infinity, the PageRank of a randomly chosen node can be closely approximated by the PageRank of the root node of an appropriately constructed tree. This tree approximation is in

46 CFR 282.11 - Ranking of flags.

Science.gov (United States)

2010-10-01

... 46 Shipping 8 2010-10-01 2010-10-01 false Ranking of flags. 282.11 Section 282.11 Shipping... COMMERCE OF THE UNITED STATES Foreign-Flag Competition § 282.11 Ranking of flags. The operators under each... priority of costs which are representative of the flag. For liner cargo vessels, the ranking of operators...

Support vector methods for survival analysis: a comparison between ranking and regression approaches.

Science.gov (United States)

Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

2011-10-01

To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods

An Investigation into the Decision Makers's Risk Attitude Index ...

African Journals Online (AJOL)

An Investigation into the Decision Makers's Risk Attitude Index Ranking Technique for Fuzzy Critical Path Analysis. ... Nigerian Journal of Technology ... for a benchmark problem, the decision maker's risk attitude index ranking method produces unrealistic results when the decision maker's attitude towards risk was neutral.

The DEA – FUZZY ANP Department Ranking Model Applied in Iran Amirkabir University

OpenAIRE

Serpil Erol; Babak Daneshvar Rouyendegh

2010-01-01

Proposed in this study is a hybrid model for supporting the department selectionprocess within Iran Amirkabir University. This research is a two-stage model designed tofully rank the organizational departments where each department has multiple inputs andoutputs. First, the department evaluation problem is formulated by Data EnvelopmentAnalysis (DEA) and separately formulates each pair of units. In the second stage, the pairwiseevaluation matrix generated in the first stage is utilized to ful...

Low-ranking female Japanese macaques make efforts for social grooming.

Science.gov (United States)

Kurihara, Yosuke

2016-04-01

Grooming is essential to build social relationships in primates. Its importance is universal among animals from different ranks; however, rank-related differences in feeding patterns can lead to conflicts between feeding and grooming in low-ranking animals. Unifying the effects of dominance rank on feeding and grooming behaviors contributes to revealing the importance of grooming. Here, I tested whether the grooming behavior of low-ranking females were similar to that of high-ranking females despite differences in their feeding patterns. I followed 9 Japanese macaques Macaca fuscata fuscata adult females from the Arashiyama group, and analyzed the feeding patterns and grooming behaviors of low- and high-ranking females. Low-ranking females fed on natural foods away from the provisioning site, whereas high-ranking females obtained more provisioned food at the site. Due to these differences in feeding patterns, low-ranking females spent less time grooming than high-ranking females. However, both low- and high-ranking females performed grooming around the provisioning site, which was linked to the number of neighboring individuals for low-ranking females and feeding on provisioned foods at the site for high-ranking females. The similarity in grooming area led to a range and diversity of grooming partners that did not differ with rank. Thus, low-ranking females can obtain small amounts of provisioned foods and perform grooming with as many partners around the provisioning site as high-ranking females. These results highlight the efforts made by low-ranking females to perform grooming and suggest the importance of grooming behavior in group-living primates.

Low-ranking female Japanese macaques make efforts for social grooming

Science.gov (United States)

Kurihara, Yosuke

2016-01-01

Abstract Grooming is essential to build social relationships in primates. Its importance is universal among animals from different ranks; however, rank-related differences in feeding patterns can lead to conflicts between feeding and grooming in low-ranking animals. Unifying the effects of dominance rank on feeding and grooming behaviors contributes to revealing the importance of grooming. Here, I tested whether the grooming behavior of low-ranking females were similar to that of high-ranking females despite differences in their feeding patterns. I followed 9 Japanese macaques Macaca fuscata fuscata adult females from the Arashiyama group, and analyzed the feeding patterns and grooming behaviors of low- and high-ranking females. Low-ranking females fed on natural foods away from the provisioning site, whereas high-ranking females obtained more provisioned food at the site. Due to these differences in feeding patterns, low-ranking females spent less time grooming than high-ranking females. However, both low- and high-ranking females performed grooming around the provisioning site, which was linked to the number of neighboring individuals for low-ranking females and feeding on provisioned foods at the site for high-ranking females. The similarity in grooming area led to a range and diversity of grooming partners that did not differ with rank. Thus, low-ranking females can obtain small amounts of provisioned foods and perform grooming with as many partners around the provisioning site as high-ranking females. These results highlight the efforts made by low-ranking females to perform grooming and suggest the importance of grooming behavior in group-living primates. PMID:29491896

Ranking Entities in Networks via Lefschetz Duality

DEFF Research Database (Denmark)

Aabrandt, Andreas; Hansen, Vagn Lundsgaard; Poulsen, Bjarne

2014-01-01

then be ranked according to how essential their positions are in the network by considering the effect of their respective absences. Defining a ranking of a network which takes the individual position of each entity into account has the purpose of assigning different roles to the entities, e.g. agents......, in the network. In this paper it is shown that the topology of a given network induces a ranking of the entities in the network. Further, it is demonstrated how to calculate this ranking and thus how to identify weak sub-networks in any given network....

The applications of risk-informed in-service-inspection

International Nuclear Information System (INIS)

Ting, K.; Ko, T.-H.; Li, Y.-C.; Wu, W.-F.; Lu, Y.-L.; Chien, F.-T.

2005-01-01

The US NRC and nuclear industry encouraged the applications of risk-informed In-Service Inspection (RI-ISI) which can be an alternative program to the ASME Section XI In-service Inspection requirements. The Implementation of RI-ISI can improve the substantial cost as well as does reductions. From the aspect of defense in depth for nuclear safety, the achievements of these procedures can identify the inspection rank to promote the integrity of the current inspection program. Thus, this study utilizes this techniques to implement risk assessment on safety class 1 recirculation piping welds where sensitized to IGSCC of Taibei BWR-6 nuclear power plant. In the evaluation process, WinPraise code is used to calculate the failure probabilities of all welds. The result of risk evaluations can be referred to the further regulatory and plant operation. (authors)

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.

Profitability as a business goal: the multicriteria approach to the ranking of the five largest Croatian banks

Directory of Open Access Journals (Sweden)

Višnja Vojvodić Rosenzweig

2012-01-01

Full Text Available Background: The ranking of commercial banks is usually based on using a single criterion, the size of assets or income. A multicriteria approach allows a more complex analysis of their business efficiency. Objectives: This paper proposes the ranking of banks based on six financial criteria using a multicriteria approach implementing a goal programming model. The criteria are classified into three basic groups: profitability, credit risk and solvency. Methods/Approach: Business performance is evaluated using a score for each bank, calculated as the weighted sum of relative values of individual indicators. Results: In the process of solving the corresponding goal programming problem, the weights are calculated. It is assumed that the goal of each bank is the highest profitability. Because of the market competition among banks, the weights of indicators depend on the performance of each bank. This method is applied to the five biggest Croatian banks (ZABA, PBZ, ERSTE, RBA and HYPO. Conclusion: For the observed period (2010, the highest priority is given to profitability and then to credit risk. The ranking is achieved by using a multicriteria model.

Pilot research project of risk communication on nuclear technology and its utilization. Toward communication and collaboration with community

International Nuclear Information System (INIS)

Tsuchiya, Tomoko

2003-01-01

Although the importance of risk communication has been pointed out over the last decade in nuclear community, both public authorities and nuclear industry have not conducted the definite actions yet. It will be reflected in the public eye that nuclear community's attitude toward communication and consultation with the public about risk issues is half-hearted, comparing with chemical and food safety fields which recently launched their risk communication activities. In this study, we conduct risk communication experiments on some risk issues associated with nuclear technology and its utilization in Tokai village, for the purpose of establishment of risk communication in our society that might be one of the new relationships between science and technology and society. The outcomes of FY2002 study are the following threefold; 1) preparation of risk communication experiments on nuclear technology and its utilization, 2) assessment of social effects of risk communication activities, 3) preparation of practical guidebook for risk communication experiments. (J.P.N.)

A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule

Directory of Open Access Journals (Sweden)

Xiaoxiao Ji

2017-02-01

Full Text Available This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1 formulation of risk assessment hierarchy; (2 representation of both qualitative and quantitative information; (3 elicitation of attribute weights and information reliabilities; (4 aggregation of assessment information using the ER rule and (5 quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

Quiggin's Rank Dependent Model. Review of Generalized Expected Utility Theory: The Rank-Dependent Model, by John Quiggin

OpenAIRE

Wakker, Peter

1994-01-01

textabstractJohn Quiggin is a professor at the centre for Economic Policy Research of the Australian National University. His research interests are decision making under risk and agricultural economics. The reviewer is an associate professor at the Medical Decision Making Unit, University of Leiden, Leiden, The Netherlands. His main interest is decision making under uncertainty.

Written Informed Consent for Computed Tomography of the Abdomen/Pelvis is Associated with Decreased CT Utilization in Low-Risk Emergency Department Patients

Directory of Open Access Journals (Sweden)

Lisa H. Merck

2015-12-01

Full Text Available Introduction: The increasing rate of patient exposure to radiation from computerized tomography (CT raises questions about appropriateness of utilization. There is no current standard to employ informed consent for CT (ICCT. Our study assessed the relationship between informed consent and CT utilization in emergency department (ED patients. Methods: An observational multiphase before-after cohort study was completed from 4/2010-5/2011. We assessed CT utilization before and after (Time I/ Time II the implementation of an informed consent protocol. Adult patients were included if they presented with symptoms of abdominal/pelvic pathology or completed ED CT. We excluded patients with pregnancy, trauma, or altered mental status. Data on history, exam, diagnostics, and disposition were collected via standard abstraction tool. We generated a multivariate logistic model via stepwise regression, to assess CT utilization across risk groups. Logistic models, stratified by risk, were generated to include study phase and a propensity score that controlled for potential confounders of CT utilization. Results: 7,684 patients met inclusion criteria. In PHASE 2, there was a 24% (95% CI [10-36%] reduction in CT utilization in the low-risk patient group (p<0.002. ICCT did not affect CT utilization in the high-risk group (p=0.16. In low-risk patients, the propensity score was significant (p<0.001. There were no adverse events reported during the study period. Conclusion: The implementation of ICCT was associated with reduced CT utilization in low-risk ED patients. ICCT has the potential to increase informed, shared decision making with patients, as well as to reduce the risks and cost associated with CT.

Utilizing elements of the CSAU phenomena identification and ranking table (PIRT) to qualify a PWR non-LOCA transients system code

Energy Technology Data Exchange (ETDEWEB)

Greene, K.R.; Fletcher, C.D.; Gottula, R.C.; Lindquist, T.R.; Stitt, B.D. [Framatome ANP, Richland, WA (United States)

2001-07-01

Licensing analyses of Nuclear Regulatory Commission (NRC) Standard Review Plan (SRP) Chapter 15 non-LOCA transients are an important part of establishing operational safety limits and design limits for nuclear power plants. The applied codes and methods are generally qualified using traditional methods of benchmarking and assessment, sample problems, and demonstration of conservatism. Rigorous formal methods for developing code and methodology have been created and applied to qualify realistic methods for Large Break Loss-of-Coolant Accidents (LBLOCA's). This methodology, Code Scaling, Applicability, and Uncertainty (CSAU), is a very demanding, resource intensive, process to apply. It would be challenging to apply a comprehensive and complete CSAU level of analysis, individually, to each of the more than 30 non-LOCA transients that comprise Chapter 15 events. However, certain elements of the process can be easily adapted to improve quality of the codes and methods used to analyze non- LOCA transients. One of these elements is the Phenomena Identification and Ranking Table (PIRT). This paper presents the results of an informally constructed PIRT that applies to non-LOCA transients for Pressurized Water Reactors (PWR's) of the Westinghouse and Combustion Engineering design. A group of experts in thermal-hydraulics and safety analysis identified and ranked the phenomena. To begin the process, the PIRT was initially performed individually by each expert. Then through group interaction and discussion, a consensus was reached on both the significant phenomena and the appropriate ranking. The paper also discusses using the PIRT as an aid to qualify a 'conservative' system code and methodology. Once agreement was obtained on the phenomena and ranking, the table was divided into six functional groups, by nature of the transients, along the same lines as Chapter 15. Then, assessment and disposition of the significant phenomena was performed. The PIRT and

A practical sensitivity analysis method for ranking sources of uncertainty in thermal–hydraulics applications

Energy Technology Data Exchange (ETDEWEB)

Pourgol-Mohammad, Mohammad, E-mail: pourgolmohammad@sut.ac.ir [Department of Mechanical Engineering, Sahand University of Technology, Tabriz (Iran, Islamic Republic of); Hoseyni, Seyed Mohsen [Department of Basic Sciences, East Tehran Branch, Islamic Azad University, Tehran (Iran, Islamic Republic of); Hoseyni, Seyed Mojtaba [Building & Housing Research Center, Tehran (Iran, Islamic Republic of); Sepanloo, Kamran [Nuclear Science and Technology Research Institute, Tehran (Iran, Islamic Republic of)

2016-08-15

Highlights: • Existing uncertainty ranking methods prove inconsistent for TH applications. • Introduction of a new method for ranking sources of uncertainty in TH codes. • Modified PIRT qualitatively identifies and ranks uncertainty sources more precisely. • The importance of parameters is calculated by a limited number of TH code executions. • Methodology is applied successfully on LOFT-LB1 test facility. - Abstract: In application to thermal–hydraulic calculations by system codes, sensitivity analysis plays an important role for managing the uncertainties of code output and risk analysis. Sensitivity analysis is also used to confirm the results of qualitative Phenomena Identification and Ranking Table (PIRT). Several methodologies have been developed to address uncertainty importance assessment. Generally, uncertainty importance measures, mainly devised for the Probabilistic Risk Assessment (PRA) applications, are not affordable for computationally demanding calculations of the complex thermal–hydraulics (TH) system codes. In other words, for effective quantification of the degree of the contribution of each phenomenon to the total uncertainty of the output, a practical approach is needed by considering high computational burden of TH calculations. This study aims primarily to show the inefficiency of the existing approaches and then introduces a solution to cope with the challenges in this area by modification of variance-based uncertainty importance method. Important parameters are identified by the modified PIRT approach qualitatively then their uncertainty importance is quantified by a local derivative index. The proposed index is attractive from its practicality point of view on TH applications. It is capable of calculating the importance of parameters by a limited number of TH code executions. Application of the proposed methodology is demonstrated on LOFT-LB1 test facility.

A practical sensitivity analysis method for ranking sources of uncertainty in thermal–hydraulics applications

International Nuclear Information System (INIS)

Pourgol-Mohammad, Mohammad; Hoseyni, Seyed Mohsen; Hoseyni, Seyed Mojtaba; Sepanloo, Kamran

2016-01-01

Highlights: • Existing uncertainty ranking methods prove inconsistent for TH applications. • Introduction of a new method for ranking sources of uncertainty in TH codes. • Modified PIRT qualitatively identifies and ranks uncertainty sources more precisely. • The importance of parameters is calculated by a limited number of TH code executions. • Methodology is applied successfully on LOFT-LB1 test facility. - Abstract: In application to thermal–hydraulic calculations by system codes, sensitivity analysis plays an important role for managing the uncertainties of code output and risk analysis. Sensitivity analysis is also used to confirm the results of qualitative Phenomena Identification and Ranking Table (PIRT). Several methodologies have been developed to address uncertainty importance assessment. Generally, uncertainty importance measures, mainly devised for the Probabilistic Risk Assessment (PRA) applications, are not affordable for computationally demanding calculations of the complex thermal–hydraulics (TH) system codes. In other words, for effective quantification of the degree of the contribution of each phenomenon to the total uncertainty of the output, a practical approach is needed by considering high computational burden of TH calculations. This study aims primarily to show the inefficiency of the existing approaches and then introduces a solution to cope with the challenges in this area by modification of variance-based uncertainty importance method. Important parameters are identified by the modified PIRT approach qualitatively then their uncertainty importance is quantified by a local derivative index. The proposed index is attractive from its practicality point of view on TH applications. It is capable of calculating the importance of parameters by a limited number of TH code executions. Application of the proposed methodology is demonstrated on LOFT-LB1 test facility.

Fair ranking of researchers and research teams.

Science.gov (United States)

Vavryčuk, Václav

2018-01-01

The main drawback of ranking of researchers by the number of papers, citations or by the Hirsch index is ignoring the problem of distributing authorship among authors in multi-author publications. So far, the single-author or multi-author publications contribute to the publication record of a researcher equally. This full counting scheme is apparently unfair and causes unjust disproportions, in particular, if ranked researchers have distinctly different collaboration profiles. These disproportions are removed by less common fractional or authorship-weighted counting schemes, which can distribute the authorship credit more properly and suppress a tendency to unjustified inflation of co-authors. The urgent need of widely adopting a fair ranking scheme in practise is exemplified by analysing citation profiles of several highly-cited astronomers and astrophysicists. While the full counting scheme often leads to completely incorrect and misleading ranking, the fractional or authorship-weighted schemes are more accurate and applicable to ranking of researchers as well as research teams. In addition, they suppress differences in ranking among scientific disciplines. These more appropriate schemes should urgently be adopted by scientific publication databases as the Web of Science (Thomson Reuters) or the Scopus (Elsevier).

Cultural theory and risk perception: validity and utility explored in the French context

International Nuclear Information System (INIS)

Brenot, J.; Bonnefous, S.; Mays, C.

1996-01-01

Explaining perceived risk can draw upon factors related to the person (e.g. demographics, personality, social/professional status, political orientation), or to the risk source (e.g. health impacts, economic effects). According to Cultural Theory risk perceptions are culturally biased. Wildavsky and Dake operationalised the Cultural Theory with questionnaire scales and found that resulting 'cultural profiles' best predict individual differences in risk perception. A French version of their questionnaire was inserted into a representative national risk opinion survey of May 1993; 1022 adults (age 18 and over) were interviewed. Major results are presented. The four cultural scales (hierarchy, egalitarianism, fatalism and individualism) show high correlations with political orientation as expected, but also with, for example, age, gender, income and education level. However, scale relationships to perception of risk situations (twenty, mainly technological) are not as strong as expected. Sjoeberg found similar results in Sweden. The utility of the existing operationalisation of Cultural Theory for risk perception analysis is discussed. (author)

Cultural theory and risk perception: validity and utility explored in the French context

Energy Technology Data Exchange (ETDEWEB)

Brenot, J.; Bonnefous, S.; Mays, C. [CEA Centre d`Etudes de Fontenay-aux-Roses, 92 (France). Inst. de Protection et de Surete Nucleaire

1996-12-31

Explaining perceived risk can draw upon factors related to the person (e.g. demographics, personality, social/professional status, political orientation), or to the risk source (e.g. health impacts, economic effects). According to Cultural Theory risk perceptions are culturally biased. Wildavsky and Dake operationalised the Cultural Theory with questionnaire scales and found that resulting `cultural profiles` best predict individual differences in risk perception. A French version of their questionnaire was inserted into a representative national risk opinion survey of May 1993; 1022 adults (age 18 and over) were interviewed. Major results are presented. The four cultural scales (hierarchy, egalitarianism, fatalism and individualism) show high correlations with political orientation as expected, but also with, for example, age, gender, income and education level. However, scale relationships to perception of risk situations (twenty, mainly technological) are not as strong as expected. Sjoeberg found similar results in Sweden. The utility of the existing operationalisation of Cultural Theory for risk perception analysis is discussed. (author).

The development, validation, and utility of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS).

Science.gov (United States)

Sosenko, Jay M; Skyler, Jay S; Palmer, Jerry P

2015-08-01

This report details the development, validation, and utility of the Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score (DPTRS) for type 1 diabetes (T1D). Proportional hazards regression was used to develop the DPTRS model which includes the glucose and C-peptide sums from oral glucose tolerance tests at 30, 60, 90, and 120 min, the log fasting C-peptide, age, and the log BMI. The DPTRS was externally validated in the TrialNet Natural History Study cohort (TNNHS). In a study of the application of the DPTRS, the findings showed that it could be used to identify normoglycemic individuals who were at a similar risk for T1D as those with dysglycemia. The DPTRS could also be used to identify lower risk dysglycemic individuals. Risk estimates of individuals deemed to be at higher risk according to DPTRS values did not differ significantly between the DPT-1 and the TNNHS; whereas, the risk estimates for those with dysglycemia were significantly higher in DPT-1. Individuals with very high DPTRS values were found to be at such marked risk for T1D that they could reasonably be considered to be in a pre-diabetic state. The findings indicate that the DPTRS has utility in T1D prevention trials and for identifying pre-diabetic individuals.

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

Rank diversity of languages: generic behavior in computational linguistics.

Science.gov (United States)

Cocho, Germinal; Flores, Jorge; Gershenson, Carlos; Pineda, Carlos; Sánchez, Sergio

2015-01-01

Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: "heads" consist of words which almost do not change their rank in time, "bodies" are words of general use, while "tails" are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied.

Ranking the contributions of commercial fish and shellfish varieties to mercury exposure in the United States: implications for risk communication.

Science.gov (United States)

Groth, Edward

2010-04-01

Fish and shellfish have important nutritional benefits, and US per capita seafood consumption has increased substantially since 2002. Recent research has reinforced concerns about adverse effects of methylmercury exposure, suggesting that methylmercury doses associated with typical US rates of fish consumption may pose measurable risks, with no threshold. These converging trends create a need to improve risk communication about fish consumption and mercury. The analysis performed here identifies the relative importance of different fish and shellfish as sources of mercury in the US seafood supply and proposes improved consumer advice, so that the public can benefit from fish consumption while minimizing mercury exposure. I have quantified contributions to total mercury in the US seafood supply by 51 different varieties of fish and shellfish, then ranked and sorted the 51 varieties in terms of relative impact. Except for swordfish, most fish with the highest mercury levels are relatively minor contributors to total inputs. Tuna (canned light, canned albacore and fresh/frozen varieties) accounts for 37.4 percent of total mercury inputs, while two-thirds of the seafood supply and nine of the 11 most heavily consumed fish and shellfish are low or very low in mercury. Substantial improvement in risk communication about mercury in fish and seafood is needed; in particular, several population subsets need better guidance to base their seafood choices more explicitly on mercury content. I have sorted the 51 seafood varieties into six categories based on mercury levels, as a framework for improving risk communication in this regard. (c) 2009 Elsevier Inc. All rights reserved.

Ranking the Online Documents Based on Relative Credibility Measures

Directory of Open Access Journals (Sweden)

Ahmad Dahlan

2013-09-01

Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

Ranking the Online Documents Based on Relative Credibility Measures

Directory of Open Access Journals (Sweden)

Ahmad Dahlan

2009-05-01

Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

Composite Flood Risk for Virgin Island

Science.gov (United States)

The Composite Flood Risk layer combines flood hazard datasets from Federal Emergency Management Agency (FEMA) flood zones, NOAA's Shallow Coastal Flooding, and the National Hurricane Center SLOSH model for Storm Surge inundation for category 1, 2, and 3 hurricanes.Geographic areas are represented by a grid of 10 by 10 meter cells and each cell has a ranking based on variation in exposure to flooding hazards: Moderate, High and Extreme exposure. Geographic areas in each input layers are ranked based on their probability of flood risk exposure. The logic was such that areas exposed to flooding on a more frequent basis were given a higher ranking. Thus the ranking incorporates the probability of the area being flooded. For example, even though a Category 3 storm surge has higher flooding elevations, the likelihood of the occurrence is lower than a Category 1 storm surge and therefore the Category 3 flood area is given a lower exposure ranking. Extreme exposure areas are those areas that are exposed to relatively frequent flooding.The ranked input layers are then converted to a raster for the creation of the composite risk layer by using cell statistics in spatial analysis. The highest exposure ranking for a given cell in any of the three input layers is assigned to the corresponding cell in the composite layer.For example, if an area (a cell) is rank as medium in the FEMA layer, moderate in the SLOSH layer, but extreme in the SCF layer, the cell will be considere

Social signals of safety and risk confer utility and have asymmetric effects on observers' choices.

Science.gov (United States)

Chung, Dongil; Christopoulos, George I; King-Casas, Brooks; Ball, Sheryl B; Chiu, Pearl H

2015-06-01

Individuals' risk attitudes are known to guide choices about uncertain options. However, in the presence of others' decisions, these choices can be swayed and manifest as riskier or safer behavior than one would express alone. To test the mechanisms underlying effective social 'nudges' in human decision-making, we used functional neuroimaging and a task in which participants made choices about gambles alone and after observing others' selections. Against three alternative explanations, we found that observing others' choices of gambles increased the subjective value (utility) of those gambles for the observer. This 'other-conferred utility' was encoded in ventromedial prefrontal cortex, and these neural signals predicted conformity. We further identified a parametric interaction with individual risk preferences in anterior cingulate cortex and insula. These data provide a neuromechanistic account of how information from others is integrated with individual preferences that may explain preference-congruent susceptibility to social signals of safety and risk.

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

Assessment of non-backfittable concepts to improve PWR uranium utilization

International Nuclear Information System (INIS)

LaBelle, D.W.; Sankovich, M.F.; Spetz, S.W.; Uotinen, V.O.

1980-12-01

Seven non-backfittable improvements to light water reactors were assessed for Batelle/Pacific Northwest Laboratories in support of the Department of Energy's program on Advanced Reactor Studies. The objective was to provide industrial perspective as to which concepts have the best potential for development to improve fuel utilization. The concepts were rated against the assessment criteria while considering the key questions identified for each concept, and recommendations were made for further action on unresolved key questions. The concepts were subjectively ranked against each other in terms of relative investment potential. The ranking considered all criteria but, for example, weighted fuel utilization savings more heavily than development costs. Finally, conclusions and recommendations for future action were determined. The reference design for this study was the NASAP Composite Improved PWR

Beyond Low Rank: A Data-Adaptive Tensor Completion Method

OpenAIRE

Zhang, Lei; Wei, Wei; Shi, Qinfeng; Shen, Chunhua; Hengel, Anton van den; Zhang, Yanning

2017-01-01

Low rank tensor representation underpins much of recent progress in tensor completion. In real applications, however, this approach is confronted with two challenging problems, namely (1) tensor rank determination; (2) handling real tensor data which only approximately fulfils the low-rank requirement. To address these two issues, we develop a data-adaptive tensor completion model which explicitly represents both the low-rank and non-low-rank structures in a latent tensor. Representing the no...

The utility of absolute risk prediction using FRAX® and Garvan Fracture Risk Calculator in daily practice.

Science.gov (United States)

van Geel, Tineke A C M; Eisman, John A; Geusens, Piet P; van den Bergh, Joop P W; Center, Jacqueline R; Dinant, Geert-Jan

2014-02-01

There are two commonly used fracture risk prediction tools FRAX(®) and Garvan Fracture Risk Calculator (GARVAN-FRC). The objective of this study was to investigate the utility of these tools in daily practice. A prospective population-based 5-year follow-up study was conducted in ten general practice centres in the Netherlands. For the analyses, the FRAX(®) and GARVAN-FRC 10-year absolute risks (FRAX(®) does not have 5-year risk prediction) for all fractures were used. Among 506 postmenopausal women aged ≥60 years (mean age: 67.8±5.8 years), 48 (9.5%) sustained a fracture during follow-up. Both tools, using BMD values, distinguish between women who did and did not fracture (10.2% vs. 6.8%, respectively for FRAX(®) and 32.4% vs. 39.1%, respectively for GARVAN-FRC, pbetter for women who sustained a fracture (higher sensitivity) and FRAX(®) for women who did not sustain a fracture (higher specificity). Similar results were obtained using age related cut off points. The discriminant value of both models is at least as good as models used in other medical conditions; hence they can be used to communicate the fracture risk to patients. However, given differences in the estimated risks between FRAX(®) and GARVAN-FRC, the significance of the absolute risk must be related to country-specific recommended intervention thresholds to inform the patient. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

Trachomatous Scar Ranking: A Novel Outcome for Trachoma Studies.

Science.gov (United States)

Baldwin, Angela; Ryner, Alexander M; Tadesse, Zerihun; Shiferaw, Ayalew; Callahan, Kelly; Fry, Dionna M; Zhou, Zhaoxia; Lietman, Thomas M; Keenan, Jeremy D

2017-06-01

AbstractWe evaluated a new trachoma scarring ranking system with potential use in clinical research. The upper right tarsal conjunctivas of 427 individuals from Ethiopian villages with hyperendemic trachoma were photographed. An expert grader first assigned a scar grade to each photograph using the 1981 World Health Organization (WHO) grading system. Then, all photographs were ranked from least (rank = 1) to most scarring (rank = 427). Photographic grading found 79 (18.5%) conjunctivae without scarring (C0), 191 (44.7%) with minimal scarring (C1), 105 (24.6%) with moderate scarring (C2), and 52 (12.2%) with severe scarring (C3). The ranking method demonstrated good internal validity, exhibiting a monotonic increase in the median rank across the levels of the 1981 WHO grading system. Intrarater repeatability was better for the ranking method (intraclass correlation coefficient = 0.84, 95% CI = 0.74-0.94). Exhibiting better internal and external validity, this ranking method may be useful for evaluating the difference in scarring between groups of individuals.

CNN-based ranking for biomedical entity normalization.

Science.gov (United States)

Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

2017-10-03

Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

RANK und RANKL - Vom Knochen zum Mammakarzinom

Directory of Open Access Journals (Sweden)

Sigl V

2012-01-01

Full Text Available RANK („Receptor Activator of NF-κB“ und sein Ligand RANKL sind Schlüsselmoleküle im Knochenmetabolismus und spielen eine essenzielle Rolle in der Entstehung von pathologischen Knochenveränderungen. Die Deregulation des RANK/RANKL-Systems ist zum Beispiel ein Hauptgrund für das Auftreten von postmenopausaler Osteoporose bei Frauen. Eine weitere wesentliche Funktion von RANK und RANKL liegt in der Entwicklung von milchsekretierenden Drüsen während der Schwangerschaft. Dabei regulieren Sexualhormone, wie zum Beispiel Progesteron, die Expression von RANKL und induzieren dadurch die Proliferation von epithelialen Zellen der Brust. Seit Längerem war schon bekannt, dass RANK und RANKL in der Metastasenbildung von Brustkrebszellen im Knochengewebe beteiligt sind. Wir konnten nun das RANK/RANKLSystem auch als essenziellen Mechanismus in der Entstehung von hormonellem Brustkrebs identifizieren. In diesem Beitrag werden wir daher den neuesten Erkenntnissen besondere Aufmerksamkeit schenken und diese kritisch in Bezug auf Brustkrebsentwicklung betrachten.

Using incomplete citation data for MEDLINE results ranking.

Science.gov (United States)

Herskovic, Jorge R; Bernstam, Elmer V

2005-01-01

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Using centrality to rank web snippets

NARCIS (Netherlands)

Jijkoun, V.; de Rijke, M.; Peters, C.; Jijkoun, V.; Mandl, T.; Müller, H.; Oard, D.W.; Peñas, A.; Petras, V.; Santos, D.

2008-01-01

We describe our participation in the WebCLEF 2007 task, targeted at snippet retrieval from web data. Our system ranks snippets based on a simple similarity-based centrality, inspired by the web page ranking algorithms. We experimented with retrieval units (sentences and paragraphs) and with the

Neural Ranking Models with Weak Supervision

NARCIS (Netherlands)

Dehghani, M.; Zamani, H.; Severyn, A.; Kamps, J.; Croft, W.B.

2017-01-01

Despite the impressive improvements achieved by unsupervised deep neural networks in computer vision and NLP tasks, such improvements have not yet been observed in ranking for information retrieval. The reason may be the complexity of the ranking problem, as it is not obvious how to learn from

Generalization Performance of Regularized Ranking With Multiscale Kernels.

Science.gov (United States)

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

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.

Rank Diversity of Languages: Generic Behavior in Computational Linguistics

Science.gov (United States)

Cocho, Germinal; Flores, Jorge; Gershenson, Carlos; Pineda, Carlos; Sánchez, Sergio

2015-01-01

Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: “heads” consist of words which almost do not change their rank in time, “bodies” are words of general use, while “tails” are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied. PMID:25849150

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)

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.

Citation ranking versus peer evaluation of senior faculty research performance

DEFF Research Database (Denmark)

Meho, Lokman I.; Sonnenwald, Diane H.

2000-01-01

The purpose of this study is to analyze the relationship between citation ranking and peer evaluation in assessing senior faculty research performance. Other studies typically derive their peer evaluation data directly from referees, often in the form of ranking. This study uses two additional...... indicator of research performance of senior faculty members? Citation data, book reviews, and peer ranking were compiled and examined for faculty members specializing in Kurdish studies. Analysis shows that normalized citation ranking and citation content analysis data yield identical ranking results....... Analysis also shows that normalized citation ranking and citation content analysis, book reviews, and peer ranking perform similarly (i.e., are highly correlated) for high-ranked and low-ranked senior scholars. Additional evaluation methods and measures that take into account the context and content...

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...

University rankings in computer science

DEFF Research Database (Denmark)

Ehret, Philip; Zuccala, Alesia Ann; Gipp, Bela

2017-01-01

This is a research-in-progress paper concerning two types of institutional rankings, the Leiden and QS World ranking, and their relationship to a list of universities’ ‘geo-based’ impact scores, and Computing Research and Education Conference (CORE) participation scores in the field of computer...... science. A ‘geo-based’ impact measure examines the geographical distribution of incoming citations to a particular university’s journal articles for a specific period of time. It takes into account both the number of citations and the geographical variability in these citations. The CORE participation...... score is calculated on the basis of the number of weighted proceedings papers that a university has contributed to either an A*, A, B, or C conference as ranked by the Computing Research and Education Association of Australasia. In addition to calculating the correlations between the distinct university...

Comparative risk assessment for electricity generation

International Nuclear Information System (INIS)

Thoene, E.; Kallenbach, U.

1988-01-01

The following conclusions are drawn: There is no 'zero-risk option' in electricity generation. Risk comparison meets with considerable problems relating to available data and methods. Taking into account the existing uncertainties, technology ranking in terms of risks involved cannot be done, but the major risk elements of the various electricity generating systems can be clearly identified. The risks defined cannot be interpreted so as to lead to an abolishment of certain techniques due to risks involved, particularly if one sees the risks from electricity generation in relation to other health hazards. The use of coal for electricity generation clearly ranks top with regard to occupational risks and hazards to public health. (orig./HP) [de

Adaptive distributional extensions to DFR ranking

DEFF Research Database (Denmark)

Petersen, Casper; Simonsen, Jakob Grue; Järvelin, Kalervo

2016-01-01

-fitting distribution. We call this model Adaptive Distributional Ranking (ADR) because it adapts the ranking to the statistics of the specific dataset being processed each time. Experiments on TREC data show ADR to outperform DFR models (and their extensions) and be comparable in performance to a query likelihood...

Discovering author impact: A PageRank perspective

OpenAIRE

Yan, Erjia; Ding, Ying

2010-01-01

This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International So...

Social class rank, threat vigilance, and hostile reactivity.

Science.gov (United States)

Kraus, Michael W; Horberg, E J; Goetz, Jennifer L; Keltner, Dacher

2011-10-01

Lower-class individuals, because of their lower rank in society, are theorized to be more vigilant to social threats relative to their high-ranking upper-class counterparts. This class-related vigilance to threat, the authors predicted, would shape the emotional content of social interactions in systematic ways. In Study 1, participants engaged in a teasing interaction with a close friend. Lower-class participants--measured in terms of social class rank in society and within the friendship--more accurately tracked the hostile emotions of their friend. As a result, lower-class individuals experienced more hostile emotion contagion relative to upper-class participants. In Study 2, lower-class participants manipulated to experience lower subjective socioeconomic rank showed more hostile reactivity to ambiguous social scenarios relative to upper-class participants and to lower-class participants experiencing elevated socioeconomic rank. The results suggest that class affects expectations, perception, and experience of hostile emotion, particularly in situations in which lower-class individuals perceive their subordinate rank.

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)

Ranking U-Sapiens 2010-2

Directory of Open Access Journals (Sweden)

Carlos-Roberto Peña-Barrera

2011-08-01

Full Text Available Los principales objetivos de esta investigación son los siguientes: (1 que la comunidad científica nacional e internacional y la sociedad en general co-nozcan los resultados del Ranking U-Sapiens Colombia 2010_2, el cual clasifica a cada institución de educación superior colombiana según puntaje, posición y cuartil; (2 destacar los movimientos más importantes al comparar los resultados del ranking 2010_1 con los del 2010_2; (3 publicar las respuestas de algunos actores de la academia nacional con respecto a la dinámica de la investigación en el país; (4 reconocer algunas instituciones, medios de comunicación e investigadores que se han interesado a modo de reflexión, referenciación o citación por esta investigación; y (5 dar a conocer el «Sello Ranking U-Sapiens Colombia» para las IES clasificadas. El alcance de este estudio en cuanto a actores abordó todas y cada una de las IES nacionales (aunque solo algunas lograran entrar al ranking y en cuanto a tiempo, un periodo referido al primer semestre de 2010 con respecto a: (1 los resultados 2010-1 de revistas indexadas en Publindex, (2 los programas de maestrías y doctorados activos durante 2010-1 según el Ministerio de Educación Nacional, y (3 los resultados de grupos de investigación clasificados para 2010 según Colciencias. El método empleado para esta investigación es el mismo que para el ranking 2010_1, salvo por una especificación aún más detallada en uno de los pasos del modelo (las variables α, β, γ; es completamente cuantitativo y los datos de las variables que fundamentan sus resultados provienen de Colciencias y el Ministerio de Educación Nacional; y en esta ocasión se darán a conocer los resultados por variable para 2010_1 y 2010_2. Los resultados más relevantes son estos: (1 entraron 8 IES al ranking y salieron 3; (2 las 3 primeras IES son públicas; (3 en total hay 6 instituciones universitarias en el ranking; (4 7 de las 10 primeras IES son

Risks of Mergers and Acquisitions Processes

Directory of Open Access Journals (Sweden)

Skitsko Volodymyr I.

2017-06-01

Full Text Available Despite structural changes both in the economies of individual countries and in the world at large, the size of the merger/acquisition market is not declining and is tending to grow further. However, uncertainty in the global environment increases the importance of proper analysis, assessment and risk management in merger/acquisition transactions. Using the relevant research and publications by various authors, we have built a general ranking of the significance of merger and acquisition risks according to phases of the indicated process, with comparison of individual risk ratings, based on the publications by authors from Central and Eastern Europe and other countries around the world. The ranking of risks and threats of mergers/acquisitions proposed in this work can be considered one of the most complete for today. Further research needs to focus on the analysis, evaluation, and modeling of merger/acquisition risks, which occupy the top of the ranking, presented by the article.

Ranking Quality in Higher Education: Guiding or Misleading?

Science.gov (United States)

Bergseth, Brita; Petocz, Peter; Abrandt Dahlgren, Madeleine

2014-01-01

The study examines two different models of measuring, assessing and ranking quality in higher education. Do different systems of quality assessment lead to equivalent conclusions about the quality of education? This comparative study is based on the rankings of 24 Swedish higher education institutions. Two ranking actors have independently…

Blind Reduced-Rank MMSE Detector for DS-CDMA Systems

Directory of Open Access Journals (Sweden)

Xiaodong Cai

2003-01-01

Full Text Available We first develop a reduced-rank minimum mean squared error (MMSE detector for direct-sequence (DS code division multiple access (CDMA by forcing the linear MMSE detector to lie in a signal subspace of a reduced dimension. While a reduced-rank MMSE detector has lower complexity, it cannot outperform the full-rank MMSE detector. We then concentrate on the blind reduced-rank MMSE detector which is obtained from an estimated covariance matrix. Our analysis and simulation results show that when the desired user′s signal is in a low-dimensional subspace, there exists an optimal subspace so that the blind reduced-rank MMSE detector lying in this subspace has the best performance. By properly choosing a subsspace, we guarantee that the optimal blind reduced-rank MMSE detector is obtained. An adaptive blind reduced-rank MMSE detector, based on a subspace tracking algorithm, is developed. The adaptive blind reduced-rank MMSE detector exhibits superior steady-state performance and fast convergence speed.

An R package for analyzing and modeling ranking data.

Science.gov (United States)

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

Hyper-local, directions-based ranking of places

DEFF Research Database (Denmark)

Venetis, Petros; Gonzalez, Hector; Jensen, Christian S.

2011-01-01

they are numerous and contain precise locations. Specifically, the paper proposes a framework that takes a user location and a collection of near-by places as arguments, producing a ranking of the places. The framework enables a range of aspects of directions queries to be exploited for the ranking of places......, including the frequency with which places have been referred to in directions queries. Next, the paper proposes an algorithm and accompanying data structures capable of ranking places in response to hyper-local web queries. Finally, an empirical study with very large directions query logs offers insight...... into the potential of directions queries for the ranking of places and suggests that the proposed algorithm is suitable for use in real web search engines....

Reduced-Rank Adaptive Filtering Using Krylov Subspace

Directory of Open Access Journals (Sweden)

Sergueï Burykh

2003-01-01

Full Text Available A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions of linear systems. The alternative interpretation so obtained is used to study the properties of each considered technique and to relate one reduced-rank method to another as well as to algorithms used in computational linear algebra. Practical issues are discussed and low-complexity versions are also included in our study. It is believed that the insight developed in this paper can be further used to improve existing reduced-rank methods according to known results in the domain of Krylov subspace methods.

Global network centrality of university rankings

Science.gov (United States)

Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

2017-10-01

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

The effect of new links on Google PageRank

NARCIS (Netherlands)

Avrachenkov, Konstatin; Litvak, Nelli

2004-01-01

PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer and thus it reflects the popularity of a Web page. We study the effect of newly created links on Google PageRank. We discuss to

Quantum probability ranking principle for ligand-based virtual screening

Science.gov (United States)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Quantum probability ranking principle for ligand-based virtual screening.

Science.gov (United States)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

A novel three-stage distance-based consensus ranking method

Science.gov (United States)

Aghayi, Nazila; Tavana, Madjid

2018-05-01

In this study, we propose a three-stage weighted sum method for identifying the group ranks of alternatives. In the first stage, a rank matrix, similar to the cross-efficiency matrix, is obtained by computing the individual rank position of each alternative based on importance weights. In the second stage, a secondary goal is defined to limit the vector of weights since the vector of weights obtained in the first stage is not unique. Finally, in the third stage, the group rank position of alternatives is obtained based on a distance of individual rank positions. The third stage determines a consensus solution for the group so that the ranks obtained have a minimum distance from the ranks acquired by each alternative in the previous stage. A numerical example is presented to demonstrate the applicability and exhibit the efficacy of the proposed method and algorithms.

Learning to rank figures within a biomedical article.

Directory of Open Access Journals (Sweden)

Feifan Liu

Full Text Available Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1 First Author, (2 Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3 Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or

Learning to rank figures within a biomedical article.

Science.gov (United States)

Liu, Feifan; Yu, Hong

2014-01-01

Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1) First Author, (2) Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3) Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or out

Fish cell lines as a tool for the ecotoxicity assessment and ranking of engineered nanomaterials.

Science.gov (United States)

Bermejo-Nogales, A; Fernández-Cruz, M L; Navas, J M

2017-11-01

Risk assessment of engineered nanomaterials (ENMs) is being hindered by the sheer production volume of these materials. In this regard, the grouping and ranking of ENMs appears as a promising strategy. Here we sought to evaluate the usefulness of in vitro systems based on fish cell lines for ranking a set of ENMs on the basis of their cytotoxicity. We used the topminnow (Poeciliopsis lucida) liver cell line (PLHC-1) and the rainbow trout (Oncorhynchus mykiss) fibroblast-like gonadal cell line (RTG-2). ENMs were obtained from the EU Joint Research Centre repository. The size frequency distribution of ENM suspensions in cell culture media was characterized. Cytotoxicity was evaluated after 24 h of exposure. PLHC-1 cells exhibited higher sensitivity to the ENMs than RTG-2 cells. ZnO-NM was found to exert toxicity mainly by altering lysosome function and metabolic activity, while multi-walled carbon nanotubes (MWCNTs) caused plasma membrane disruption at high concentrations. The hazard ranking for toxicity (ZnO-NM > MWCNT ≥ CeO 2 -NM = SiO 2 -NM) was inversely related to the ranking in size detected in culture medium. Our findings reveal the suitability of fish cell lines for establishing hazard rankings of ENMs in the framework of integrated approaches to testing and assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

Low-Rank Sparse Coding for Image Classification

KAUST Repository

Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Xu, Changsheng; Ahuja, Narendra

2013-01-01

In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local structure information among features in an image for the purpose of image-level classification. LRSC represents densely sampled SIFT descriptors, in a spatial neighborhood, collectively as low-rank, sparse linear combinations of code words. As such, it casts the feature coding problem as a low-rank matrix learning problem, which is different from previous methods that encode features independently. This LRSC has a number of attractive properties. (1) It encourages sparsity in feature codes, locality in codebook construction, and low-rankness for spatial consistency. (2) LRSC encodes local features jointly by considering their low-rank structure information, and is computationally attractive. We evaluate the LRSC by comparing its performance on a set of challenging benchmarks with that of 7 popular coding and other state-of-the-art methods. Our experiments show that by representing local features jointly, LRSC not only outperforms the state-of-the-art in classification accuracy but also improves the time complexity of methods that use a similar sparse linear representation model for feature coding.

Low-Rank Sparse Coding for Image Classification

KAUST Repository

Zhang, Tianzhu

2013-12-01

In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local structure information among features in an image for the purpose of image-level classification. LRSC represents densely sampled SIFT descriptors, in a spatial neighborhood, collectively as low-rank, sparse linear combinations of code words. As such, it casts the feature coding problem as a low-rank matrix learning problem, which is different from previous methods that encode features independently. This LRSC has a number of attractive properties. (1) It encourages sparsity in feature codes, locality in codebook construction, and low-rankness for spatial consistency. (2) LRSC encodes local features jointly by considering their low-rank structure information, and is computationally attractive. We evaluate the LRSC by comparing its performance on a set of challenging benchmarks with that of 7 popular coding and other state-of-the-art methods. Our experiments show that by representing local features jointly, LRSC not only outperforms the state-of-the-art in classification accuracy but also improves the time complexity of methods that use a similar sparse linear representation model for feature coding.

Image Re-Ranking Based on Topic Diversity.

Science.gov (United States)

Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

2017-08-01

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

Classification of rank 2 cluster varieties

DEFF Research Database (Denmark)

Mandel, Travis

We classify rank 2 cluster varieties (those whose corresponding skew-form has rank 2) according to the deformation type of a generic fiber U of their X-spaces, as defined by Fock and Goncharov. Our approach is based on the work of Gross, Hacking, and Keel for cluster varieties and log Calabi...

Utility impact on STARFIRE design

International Nuclear Information System (INIS)

DeFreece, D.A.; Waganer, L.M.; Woklenhauer, W.C.

1981-01-01

A primary objective of STARFIRE has been to design a tokamak fusion power plant that was attractive to the utilities. To achieve this goal, several utility representatives were directly involved in the decision-making processes as the design evolved. An initial step was to establish the relative importance to the utilities for an extensive list of economic, performance, safety and environmental issues. The top twenty issues were ranked. Cost of electricity was clearly most important with very little spread in the ratings of individual evaluators. Licensing is a go/no-go factor and must be accomplished for the other factors to have meaning. The top nine factors were judged to be very important by all evaluators, as was shown by the spread of ratings from 5 to 10. There is considerably more spread in the bottom eleven, which reflects a lack of consensus as to the relative importance of the evaluation factors. This evaluation was utilized in establishing the initial design concept

The social value of mortality risk reduction: VSL versus the social welfare function approach.

Science.gov (United States)

Adler, Matthew D; Hammitt, James K; Treich, Nicolas

2014-05-01

We examine how different welfarist frameworks evaluate the social value of mortality risk reduction. These frameworks include classical, distributively unweighted cost-benefit analysis--i.e., the "value per statistical life" (VSL) approach-and various social welfare functions (SWFs). The SWFs are either utilitarian or prioritarian, applied to policy choice under risk in either an "ex post" or "ex ante" manner. We examine the conditions on individual utility and on the SWF under which these frameworks display sensitivity to wealth and to baseline risk. Moreover, we discuss whether these frameworks satisfy related properties that have received some attention in the literature, namely equal value of risk reduction, preference for risk equity, and catastrophe aversion. We show that the particular manner in which VSL ranks risk-reduction measures is not necessarily shared by other welfarist frameworks. Copyright © 2014 Elsevier B.V. All rights reserved.

Financial costs due to excess health risks among active employees of a utility company.

Science.gov (United States)

Yen, Louis; Schultz, Alyssa; Schnueringer, Elaine; Edington, Dee W

2006-09-01

The objective of this study was to examine the health risk-related excess costs of time away from work, medical claims, pharmacy claims, and total costs with and without considering the prevalence of health risks. A total of 2082 of 4266 employees of a Midwest utility participated in a health risk appraisal (HRA). Individuals were classified by their HRA participation status and also by 15 health risks. Total and excess costs were analyzed for all employees. There were significant excess costs due to individual risks and overall excess health risks in all cost measures. Both excess cost per risk and prevalence of the risk were important factors in determining the excess costs in the population. As compared with low-risk participants, HRA nonparticipants and the medium- and high-risk participants were 1.99, 2.22, and 3.97 times more likely to be high cost status. Approximately one third of corporate costs in medical claims, pharmacy claims, and time away from work could be defined as excess costs associated with excess health risks.