Borda Count Method Research Articles

The features of evaluation technical experts’ competence in the field of metrology

In the paper the improved method was proposed for evaluation of technical experts’ competence in metrology. Comparative analysis of the proposed method which is laid the basis for the software algorithm “Competence TE 1.0” and Borda Count method is applied to the electric power measurements was done for group technical experts. Experimental evaluation of accuracy proposed approach and traditional Borda Count method of voting is done in the field of electricity measurement.

Borda and Plurality Comparison with Regard to Compromise as a Sorites Paradox

Social choice decision aggregation is a form of complex system modelling which is based upon voters' rankings over a set of candidates. Different social choice functions, such as Borda count, plurality count or Condorcet methods models different aspects of social choice decision criteria. One of such criteria which has not been fully described or modelled, is the notion of compromise. This article aims to define a measure which would capture the notion of compromise on a given profile of voter preferences, about certain candidate being appointed to a certain position by a certain social welfare function. The goal is to define what compromise should mean, and proposes the so called d measure of as a measure of divergence for some candidate to be positioned to a certain position. This study compares the results of two well established social welfare functions, Borda and plurality count d-measure of divergence.

Potential of Agricultural Biomass: Comparative Review of Selected EU Regions and Region of Vojvodina

Summary Owing to the fact that the EU is committed to reducing greenhouse gas emissions by 20% below 1990 levels by 2020, and having in mind their high dependence on import of oil and oil derivatives, which, in turn, causes instability of power supply, increasing attention is being paid to renewable energy sources. Given the ongoing pre-accession process of the Republic of Serbia in relation to the EU, in order to determine the capacity of the country to increase the share of energy use from renewable sources, in this paper clustering of selected regions in the EU-28 has been carried out, after which a comparative analysis of regions was performed in terms of potential of agricultural biomass, for the purpose of generating energy. The aim of this study is to determine the level of the region of Vojvodina in relation to ten selected EU regions, based on parameters that affect the potential for using renewable energy sources, primarily residues from agriculture. By applying the K-means method, Borda count method and comparative analysis, and based on empirical data, results show that the region of Vojvodina takes a significant fifth place. Its share of agricultural land ranks it as the first, whereas production of cereals and the total number of farms larger than 100 ha rank it as the second. It could be concluded that Vojvodina is an agricultural region with large quantities of plant remains, primarily those left over from harvest, which represents a significant potential for energy generation from agricultural biomass.

Reference Point Approach for Multi-objective Assessment and Reduction of Ground-Level O3 Air Quality Monitoring Network in Vojvodina Province, Serbia

A monitoring network of ground-level ozone (O3) concentration levels in Vojvodina Province, Serbia, has been established in several phases, resulting in nine sampling sites (monitoring stations). Because maintenance of a monitoring network is financially very demanding, identifying potentially redundant ozone sites and reducing the network to a cost-effective and functional one are challenging and complex tasks. To provide an easily applicable but reliable analytical framework that will allow decision-makers and other stakeholders to identify redundant ground O3 monitors, the reference point approach, presented by Cetinkaya and Harmancioglu (Journal of Hydrology, 2014), is adopted for a multi-objective assessment of the O3 monitoring network. The evaluation process of the stations’ performance and their ranking is implemented in several phases. Firstly, a comprehensive set of 13 performance attributes is defined and associated with location and environmental criteria, followed by defining the set of alternatives. Next, all required attribute data are collected and stations are evaluated using the reference point approach. Finally, verification of the results is performed by aggregation of ranks obtained using the ideal point multi-criteria methods compromise programing and Technique for Order of Preference by Similarity to Ideal Solution. The aggregation process is performed using the Borda count and Kemeny social choice theory methods. Results indicate that the number of stations can be significantly reduced by 67%. Also, selection of the three best performing stations enabled identification of a core network that is expected to be functionally and financially sustainable under growing environmental and economic pressure.

Evolutionary dynamic multi-objective optimization algorithm based on Borda count method

In this paper, a novel dynamic multi-objective optimization algorithm is introduced. The proposed method is composed of three parts: change detection, response to change, and optimization process. The first step is to use Sentry solutions to detect the environmental change and advises the algorithm when a change occurs. Then, to increase the diversity of solutions, the worst solutions should be elected and removed from population and re-initialized with new solutions. The main idea is to use Borda count method which is an optimal rank aggregation technique that ranks the solutions in order of preference and nominates the worst solutions that should be removed. The last step is optimization process which is done by multi-objective Cat swarm optimization (CSO) in this paper. CSO utilizes the population that has been improved from the previous step to estimate the best solutions and converges to optimal Pareto front. The performance of the proposed algorithm is tested on dynamic multi-objective benchmarks, and the results are compared with the ones achieved by previous algorithms. The simulation results indicate that the proposed algorithm can effectively track the time-varying optimal Pareto front and achieves competitive results in comparison with traditional approaches.

A Patch-Based Saliency Detection Method for Assessing the Visual Privacy Levels of Objects in Photos

Photo privacy protection has recently received increasing attention from the public. However, the overprotection of photo privacy by hiding too much visual information can make photos meaningless. To avoid this, visual information with different degrees of privacy sensitivity can be filtered out using various image-processing techniques. Objects in a photo usually contain visual information that can potentially reveal private information; this potential depends on both the visual saliency of the objects and on the specific categories to which the objects belong. In this paper, we aim to quantitatively evaluate the influence of visual saliency information on privacy and objectively evaluate the levels of visual privacy that objects contain. Meeting this objective faces two challenges: 1) determining a method of effectively detecting generic objects in a photo for the extraction of saliency information and 2) determining a scientific method for assessing the visual private information contained in objects. To cope with these challenges, we first propose a hierarchical saliency detection method that combines a patch-based saliency detection strategy with an objectness estimation strategy to effectively locate salient objects and obtain the saliency information of each object. The proposed method results in a small set of class-independent locations with high quality and a mean average best overlap score of 0.627 at 1150 locations, which is superior to the score of other saliency detection methods. Second, we build a computational privacy assessment system to scientifically calculate and rank the privacy risks of objects in a photo by creating an improved risk matrix and using the Borda count method. The proposed computational privacy assessment method matches human evaluations to a relatively high degree.

A framework for identification of maintenance significant items in reliability centered maintenance

Identification of Maintenance Significant Items (MSI) is one of the key phases of the Reliability Centered Maintenance (RCM), which is a screening phase where the number of items for analysis is reduced. But at present, there is little systematic and convenient operation method to identify the MSI. In this paper, we presented a framework for identification of the MSI through combination of quantitative analysis with qualitative analysis. Firstly, we screened out part of non-MSI through the first screening which defines a system boundary, set up a system hierarchy tree and do a Risk Analysis (RA) of a 2th order risk matrix. And secondly, we omitted another part non-MSI in the second screening which carried out a Failure Mode and Effects Analysis (FMEA) and do a RA based on a 5th order risk matrix. Moreover, we carried on a quantitative analysis by establishing evaluation indexes and scoring standard of the MSI based on the Analytic Hierarchy Process (AHP) and Fuzzy Borda Count method (FBC). Finally, we completed a case study about the drilling pump to prove the feasibility and practicality of the method. This study is helpful for the applicable and effective Preventive Maintenance (PM) tasks.

A Framework for Sustainable Strategic Planning of Water Demand and Supply in Arid Regions

AbstractThis paper addresses strategic planning of water resources in an arid region based on sustainable development criteria (SDC). Three multi‐criteria decision‐making (MCDM) models, simple additive weighting (SAW), the analytic hierarchy process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), were used for detailed ranking of the strategies and assessing the result of the Quantitative Strategic Planning Matrix (QSPM). The results of the MCDM models were not identical, so we used aggregation approaches including mean rank, Borda count and Copeland's methods to integrate rankings. The results of sensitivity analysis revealed that all MCDM models were sensitive to the social and environmental criteria. The SAW and AHP models were also less sensitive to changes in criterion weights than the TOPSIS model. The results showed the priority of the MCDM models over QSPM analysis in incorporating SDC in detailed evaluation of the strategies. Copyright © 2016 John Wiley & Sons, Ltd and ERP Environment

Preexposure Prophylaxis Modality Preferences Among Men Who Have Sex With Men and Use Social Media in the United States.

BackgroundPreexposure prophylaxis (PrEP) is available as a daily pill for preventing infection with the human immunodeficiency virus (HIV). Innovative methods of administering PrEP systemically or topically are being discussed and developed.ObjectiveThe objective of our study was to assess attitudes toward different experimental modalities of PrEP administration.MethodsFrom April to July 2015, we recruited 1106 HIV-negative men who have sex with men through online social media advertisements and surveyed them about their likelihood of using different PrEP modalities. Participants responded to 5-point Likert-scale items indicating how likely they were to use each of the following PrEP modalities: a daily oral pill, on-demand pills, periodic injection, penile gel (either before or after intercourse), rectal gel (before/after), and rectal suppository (before/after). We used Wilcoxon signed rank tests to determine whether the stated likelihood of using any modality differed from daily oral PrEP. Related items were combined to assess differences in likelihood of use based on tissue or time of administration. Participants also ranked their interest in using each modality, and we used the modified Borda count method to determine consensual rankings.ResultsMost participants indicated they would be somewhat likely or very likely to use PrEP as an on-demand pill (685/1105, 61.99%), daily oral pill (528/1036, 50.97%), injection (575/1091, 52.70%), or penile gel (438/755, 58.01% before intercourse; 408/751, 54.33% after). The stated likelihoods of using on-demand pills (median score 4) and of using a penile gel before intercourse (median 4) were both higher than that of using a daily oral pill (median 4, P<.001 and P=.001, respectively). Compared with a daily oral pill, participants reported a significantly lower likelihood of using any of the 4 rectal modalities (Wilcoxon signed rank test, all P<.001). On 10-point Likert scales created by combining application methods, the reported likelihood of using a penile gel (median 7) was higher than that of using a rectal gel (median 6, P<.001), which was higher than the likelihood of using a rectal suppository (median 6, P<.001). The modified Borda count ranked on-demand pills as the most preferred modality. There was no difference in likelihood of use of PrEP (gel or suppository) before or after intercourse.ConclusionsParticipants typically prefer systemic PrEP and are less likely to use a modality that is administered rectally. Although most of these modalities are seen as favorable or neutral, attitudes may change as information about efficacy and application becomes available. Further data on modality preference across risk groups will better inform PrEP development.

A multi-stakeholder framework for urban runoff quality management: Application of social choice and bargaining techniques

In this paper, an integrated framework is proposed for urban runoff management. To control and improve runoff quality and quantity, Low Impact Development (LID) practices are utilized. In order to determine the LIDs' areas and locations, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which considers three objective functions of minimizing runoff volume, runoff pollution and implementation cost of LIDs, is utilized. In this framework, the Storm Water Management Model (SWMM) is used for stream flow simulation. The non-dominated solutions provided by the NSGA-II are considered as management scenarios. To select the most preferred scenario, interactions among the main stakeholders in the study area with conflicting utilities are incorporated by utilizing bargaining models including a non-cooperative game, Nash model and social choice procedures of Borda count and approval voting. Moreover, a new social choice procedure, named pairwise voting method, is proposed and applied. Based on each conflict resolution approach, a scenario is identified as the ideal solution providing the LIDs' areas, locations and implementation cost. The proposed framework is applied for urban water quality and quantity management in the northern part of Tehran metropolitan city, Iran. Results show that the proposed pairwise voting method tends to select a scenario with a higher percentage of reduction in TSS (Total Suspended Solid) load and runoff volume, in comparison with the Borda count and approval voting methods. Besides, the Nash method presents a management scenario with the highest cost for LIDs' implementation and the maximum values for percentage of runoff volume reduction and TSS removal. The results also signify that selection of an appropriate management scenario by stakeholders in the study area depends on the available financial resources and the relative importance of runoff quality improvement in comparison with reducing the runoff volume.

EVALUATION OF EXCAVATOR TECHNOLOGIES: APPLICATION OF DATA FUSION BASED MULTIMOORA METHODS

Excavators are quite expensive vehicles. Therefore, there may be huge losses for decision makers if a wrong decision is made during the purchasing process. A good evaluation of excavator alternatives both reduces costs and increases the benefits the excavator for the purchaser. The aim of this study is to prioritise excavator technologies to help decision makers during the purchasing process and to apply three different “data fusion methods” instead of the “theory of dominance” of the original MULTI MOORA method. The MULTI MOORA method is composed of three methods, namely: the ratio analysis as a part of MOORA, Reference Point Theory (the reference point approach as a part of MOORA) and the Full Multiplicative Form. It is used to prioritise excavator technologies in this study. The MULTI - MOORA method combines three results obtained from these three methods using the theory of dominance. Dominance directed graph, Rank position method and Borda count method as data fusion methods are also used to combine these three results instead of the “theory of dominance”. The results from this study show that there is no difference between the data fusion methods and the MULTI MOORA method can be applied to technology evaluation of the excavator alternatives successfully.

Risk assessments and control strategies of plague in five key surveillance counties, Zhejiang province

To analyze the epidemiology data on plague in five counties in Zhejiang province and to evaluate the risk of plague in theses areas. We selected five monitoring stations as a risk assessment (Qingyuan county, Longquan city, Yiwu city, Wencheng county, and Ruian city) in Zhejiang province where the plague epidemic more serious in the history. At least one constant site and 1-4 variable sites where plague occurred in history were selected for monitoring. We collected the five counties (cities) surveillance data of indoor rat density, indoor Rattus flavipectus density, the Xenopsylla cheopis index of rat, the Xenopsylla cheopis index of Rattus flavipectus in 1995-2014. Isolation of Yersinia pestis was conducted among 171,201 liver samples and F1 antibody were detected among 228,775 serum samples. Risk matrix, Borda count method, and Delphi approach were conducted to assess risk of the plague of five counties (cities) in Zhejiang province. Indoor rat density in Qingyuan county, Longquan city, Yiwu city, Wencheng county, Ruian city was 1.58%-5.50%, 1.13%-9.76%, 0.56%-3.67%, 2.83%-16.08%, 7.16%-15.96%, respectively; Indoor Rattus flavipectus density of five counties (cities) was 0.08%-2.23%, 0-2.02%, 0-0.54%, 0.71%-5.58%, 0.55%-4.92%, respectively. The Xenopsylla cheopis index of rat in Qingyuan county and Wencheng county was 0.011-0.500 and 0.015-0.227, respectively; The Xenopsylla cheopis index of Rattus flavipectus of Qingyuan county and Wencheng county was 0.119-3.412 and 0.100-1.430, respectively; Ruian City and Yiwu city cannot collected Xenopsylla cheopis, Long quan city only collected the Xenopsylla cheopis index of rat in the five years. Yersinia pestis were not isolated in five counties (cities).There were 3 Apodemus agrarius samples positive of plague F1 antibody test, in Longquan city and Yiwu city in 2005. Borda count method to assess the Longquan city, Yiwu (Borda point were both 321) plague risk was higher than three other regions; Delphi approach to evaluation five counties (cities) belong to the plague had a lower risk areas, according to the level of risk score (Pf) Longquan city and Yiwu (Pf was 0.314, 0.292, respectively) plague risk were higher than three other regions (Pf were all 0.292). The main host and media were lower in five key plague surveillance counties (cities) of Zhejiang province; The result of Borda count method and Delphi approach for risk assessment indicated that endogenous plague recrudescence was at lower level, but Longquan city and Yiwu city risk were higher than other counties (cities).

An Effective Security Based Wireless Information System Based on Fusion Principal Component Analysis

In the real world applications, wireless networks are an integral part of day-to-day life for many people, with businesses and home users relying on them for connectivity and communication. This paper examines the problems relating to the topic of wireless security and the background literature. The biometric systems often face limitations because of sensitivity to noise, intra class invariability, data quality, and other factors. Improving the performance of individual matchers in the aforementioned situation may not be effective. Multi biometric systems are used to overcome this problem by providing multiple pieces of evidence of the same identity. This system provides effective fusion scheme that combines information presented by the multiple domain experts based on the Rank level fusion integration method, thereby increasing the efficiency of the system which is not possible by the unimodal biometric system. The proposed multimodal biometric system has a number of unique qualities, starting from utilizing principal component analysis and fisher's linear discriminant methods for individual matchers authentication and the novel rank level fusion method is used in order to consolidate the results obtained from different biometric matchers. The ranks of the individual matchers are combined using highest rank, Borda count, and logistic regression method. From the results it can be concluded that the overall performances of the wireless security based multi biometric systems are improved even in the presence of quality of data.

Prioritizing Commodities in Southeast Sulawesi Province of Indonesia Using AHP Based Borda Count Method

This study aimed to determine the priority of agricultural commodities in the province of Southeast Sulawesi,Indonesia using combination of AHP (Analytical Hierarchy Process) and Borda Count (BC). In this way,pairwise comparison among alternative commodities was done using AHP, and the AHP ranking was thenanalyzed with BC. Six districts out of 12 districts in the province were selected as study location. Data andinformation were obtained through questionnaire survey and interviews with 30 decision makers (DMs) fromdistrict-level government institutions. Selected DMs came from (i) food crops division, (ii) estate crops division,(iii) livestock division, (iv) fisheries division, and (v) development planning agency. Study results show thatdistricts have different priority commodities depending on their agroecological characteristics andsocio-economic conditions. At the province level, the first priority commodity is sea weed, and the other top ninepriority commodities in order of ranking are rice, cocoa, beef cattle, maize, cashew nut, skipjack tuna, coconut,cassava, and citrus. The method has been proven robust, simple, flexible, and adequate to achieve the studyobjectives. This information about priority commodities can be used by the provincial government to renew itsfocus on developing agriculture sector.

Multiple Classifier System for Offline Malayalam Character Recognition

This paper presents a multiple classifier system for the recognition of offline handwritten Malayalam characters. The features used are the gradient and density based features. These feature sets are fed as input to two feedforward neural networks. The results of both these neural networks are combined using four different combination schemes: Max rule, Sum rule, Product rule and Borda count method. The best combination ensemble with an accuracy of 81.82% is obtained by using the Product rule combination scheme.

A cognitive model for aggregating people's rankings.

We develop a cognitive modeling approach, motivated by classic theories of knowledge representation and judgment from psychology, for combining people's rankings of items. The model makes simple assumptions about how individual differences in knowledge lead to observed ranking data in behavioral tasks. We implement the cognitive model as a Bayesian graphical model, and use computational sampling to infer an aggregate ranking and measures of the individual expertise. Applications of the model to 23 data sets, dealing with general knowledge and prediction tasks, show that the model performs well in producing an aggregate ranking that is often close to the ground truth and, as in the “wisdom of the crowd” effect, usually performs better than most of individuals. We also present some evidence that the model outperforms the traditional statistical Borda count method, and that the model is able to infer people's relative expertise surprisingly well without knowing the ground truth. We discuss the advantages of the cognitive modeling approach to combining ranking data, and in wisdom of the crowd research generally, as well as highlighting a number of potential directions for future model development.

Comparing topological and reliability-based vulnerability analysis of Iran power transmission network

Power grids are one of the most important and critical infrastructures which societies rely upon for well-being. Their topological (structural) characteristics related to vulnerability can be analyzed from the viewpoint of complex network theory. In this article, we incorporate into this viewpoint some relevant reliability properties and apply the analysis framework to study the high-voltage power grid in Iran. To identify weak points in the structure, we look at four different centrality measures, namely, degree, betweenness, information and closeness, and analyze their correlation properties. This allows providing a more comprehensive picture of the vulnerability characteristics of the power grid structure. By our analysis, we show that reliability-based characteristics are different from purely topological ones as they are mostly uncorrelated. We also use a voting aggregation method, the Borda Count method, to perform an overall ranking of the most vulnerable nodes, considering both intentional attacks and random failures.

홍수 취약성 평가를 위한 그룹 의사결정 접근법

유역 환경에 대한 복잡성의 증가는 단일 의사결정자들이 의사결정문제의 모든 부분을 고려하는 것을 점점 더 불가능하게 만들기 때문에 불확실성은 더욱 증가하게 된다. 따라서 본 연구는 그룹의사결정기법을 사용하여 우리나라 공간적인 홍수 취약성을 정량화하는 접근법을 제시하였다. 개인의 선호도를 분석하기위해 Fuzzy TOPSIS를 사용하였고 개인선호도의 통합을 위해 Borda count, Condorcet 그리고 Copeland 방법을 사용하였다. 마지막으로 도출된 결과를 Fuzzy TOPSIS 및 TOPSIS의 결과와 비교하였고 스피어만 순위상관계수와 켄달의 순위상관계수, Emond와 Mason이 제시한 순위상관분석을 이용하여 순위의 일치성을 검토하였다. 그 결과 일부 지역의 취약성 순위가 큰 폭으로 역전되는 현상을 보였다. 그룹의사결정 개념을 반영하여 지역별 취약성을 산정할 경우 우선순위의 변동이 클 수 있으므로 홍수 취약성 산정시 본 연구에서 제시된 모델을 고려할 필요가 있다. Increasing complexity of the basin environments makes it difficult for single decision maker to consider all relevant aspects of problem, and thus the uncertainty of decision making grows. This study attempts to develop an approach to quantify the spatial flood vulnerability of South Korea. Fuzzy TOPSIS is used to calculate individual preference by each group and then three GDM techniques (Borda count method, Condorcet method, and Copeland method) are used to integrate the individual preference. Finally, rankings from Fuzzy TOPSIS, TOPSIS, and GDM are compared with Spearman rank correlation, Kendall rank correlation, and Emond & Mason rank correlation. As a result, the rankings of some areas are dramatically changed by the use of GDM techniques. Because GDM technique in regional vulnerability assessment may cause a significant change in priorities, the model presented in this study should be considered for objective flood vulnerability assessment.

Promoting Food Tourism with Kansei Cuisine Design

Factoring the most affective elements into a tangible product is the core of Kansei design. Accordingly, one promising means to innovate the local food is to incorporate essential features of renowned international cuisine into the local gastronomy to serve as a destination marketing enabler. This paper proposes an evaluation framework by employing Analytic Network Process (ANP) and Borda count method to select an icon dish of innovative Hakka-Kaiseki hybrid cuisine for a local Hakka restaurant in Taiwan. The decision group has selected “Shrimp Tofu” as the icon dish to promote food tourism. The results show that the Kaiseki features have surpassed the Hakka features; among which, the foremost feature is shape, followed by color, material, and savory. The findings provide useful culinary guides to facilitate the chefs to develop more Kansei cuisine dishes.

A Region Ensemble for 3-D Face Recognition

In this paper, we introduce a new system for 3D face recognition based on the fusion of results from a committee of regions that have been independently matched. Experimental results demonstrate that using 28 small regions on the face allow for the highest level of 3D face recognition. Score-based fusion is performed on the individual region match scores and experimental results show that the Borda count and consensus voting methods yield higher performance than the standard sum, product, and min fusion rules. In addition, results are reported that demonstrate the robustness of our algorithm by simulating large holes and artifacts in images. To our knowledge, no other work has been published that uses a large number of 3D face regions for high-performance face matching. Rank one recognition rates of 97.2% and verification rates of 93.2% at a 0.1% false accept rate are reported and compared to other methods published on the face recognition grand challenge v2 data set.