Search results for: ranking approach

Authors: Lois Cheung

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This article examines the impact of League Tables on non-elite universities in the English higher education system. The purpose of this study is to explore the use of rankings in strategic planning by low-ranked universities in this highly competitive higher education market. A sample of non-elite universities was selected for a content analysis based on the measures used by The Guardian rankings. Interestingly, these universities care about their rankings within a single national system. The content analysis appears to be an effective approach to investigating the presence of such influences. It is particularly noteworthy that all sampled universities use these measure terminologies in their strategic plans, missions and news coverage on their institutional web-pages. This analysis may be an example of the key challenges that many low-ranking universities in England are probably facing in the highly competitive and diversified higher education market. These universities use rankings to communicate with their stakeholders, mainly students, in order to fill places to secure their major source of funding. The study concludes with comments on the likely effects of the rankings paradigm in undermining the contributions of non-elite universities.

Keywords: League tables, measures, post-1992 universities, ranking, strategy

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Authors: L. V. S. S. Phaneendra Bolem, S. Shankar

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Low Volume Rural Roads (LVRRs) constitute an integral component of the road system in all countries. These encompass all aspects of the social and economic development of rural communities. It is known that on a worldwide basis the number of low traffic roads far exceeds the length of high volume roads. Across India, 90% of the roads are LVRRs, and they often form the most important link in terms of providing access to educational, medical, recreational and commercial activities in local and regional areas. In the recent past, Government of India (GoI), with the initiation of the ambitious programme namely 'Pradhan Mantri Gram Sadak Yojana' (PMGSY) gave greater importance to LVRRs realizing their role in economic development of rural communities. The vast expansion of the road network has brought connectivity to the rural areas of the country. Further, it is noticed that due to increasing axle loads and lack of timely maintenance, is accelerated the process of deterioration of LVRRs. In addition to this due to limited budget for maintenance of these roads systematic and scientific approach in utilizing the available resources has been necessitated. This would enable better prioritization and ranking for the maintenance and make ‘all-weather roads’. Taking this into account the present study has adopted a multi-criteria approach. The multi-criteria approach includes parameters such as social, economic, environmental and pavement condition as the main criterion and some sub-criteria to find the best suitable parameters and their weight. For this purpose the expert’s opinion survey was carried out using Delphi Technique (DT) considering Likert scale, pairwise comparison and ranking methods and entire data was analyzed. Finally, this study developed the maintenance criterion considering the socio-economic, environmental and pavement condition parameters for effective maintenance of low volume roads based on the engineering judgment.

Keywords: Delphi technique, experts opinion survey, low volume rural road maintenance, multi criteria analysis

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Authors: Mohammad Reza Boromand, Masoud Moradi, Amin Eskandari

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The present study attempts to determine ranking of managerial parameters impacting upon performance of football referees in Iran. The population consisted of all referees in Leagues 1, 2 and 3 as well as super league of Iran (N=273), of which we selected 160 referees and assistant referees in 2013-2014. A research-designed questionnaire was used for data collection which was divided into two sections: (1) Demographic details (age range, Marital status, employment, refereeing experience, education level, refereeing level and proficiency) and (2) items related to parameters impacting upon performance of referees (structural parameters, operational parameters, environmental parameters, temporal parameters, economic parameters, facilities and tools, personal performance and performance evaluation). Internal consistency was calculated by Cronbach's alpha (r=0.85). For data analysis, we performed Freedman's Test and used SPSS software (α>0.05), along with descriptive statistics. The findings showed the following ranking for the above-mentioned managerial parameters: Facilities and tools, personal performance, economic parameters, structural parameters, operational parameters, environmental parameters, temporal parameters, and performance evaluation.

Keywords: Iran, football referees, managerial parameters, performance

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Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

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Authors: Aodai Abdul-Illah Ismail

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Even though the dramatic progress that has been made in traffic safety, but still millions of peoples get killed or injured as a result of traffic crashes, besides the huge amount of economic losses due to these crashes. So traffic safety continues to be one of the most important serious issues worldwide, and it affects everyone who uses the road network system, whether you drive, walk, cycle, or push a pram. One of the most important sides that offers promise for further progress in relation to traffic safety is related to risky groups (special population groups) who may have higher potential to be involved in accidents. Traffic safety needs of risky groups are different from each other and also from the average population. Due to the various limitations between these special groups from each other and from the average population, it is not possible to address all the issues –at the same time- raising the importance ranking among the other safety issues. This paper explains a procedure used to identify the most critical traffic safety issues of five risky groups, which include younger, older and female drivers, people with disabilities and school aged children. Multi criteria used in selecting the critical issues because the single criteria is not sufficient. Highway safety professionals were surveyed to obtain the ranking of importance among the risky groups and then to develop the final ranking among issues by applying weight for each of the criteria.

Keywords: traffic safety, risky groups, old drivers, young drivers

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Authors: Saleh Abu Dabous, Khaled Hamad, Rami Al-Ruzouq

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Bridge condition assessment and rating provide essential information needed for bridge management. This paper reviews bridge inspection and condition rating practices and introduces a defect-based urgency index. The index is estimated at the element-level based on the extent and severity of the different defects typical to the bridge element. The urgency index approach has the following advantages: (1) It facilitates judgment submission, i.e. instead of rating the bridge element with a specific linguistic overall expression (which can be subjective and used differently by different people), the approach is based on assessing the defects; (2) It captures multiple defects that can be present within a deteriorated element; and (3) It reflects how critical the element is through quantifying critical defects and their severity. The approach can be further developed and validated. It is expected to be useful for practical purposes as an early-warning system for critical bridge elements.

Keywords: condition rating, deterioration, inspection, maintenance

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Authors: George Mariano Soriano

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In this study, a Rapid Earthquake Risk Ranking Criteria was formulated by integrating various existing maps and databases by the Department of Public Works and Highways (DPWH) and Philippine Institute of Volcanology and Seismology (PHIVOLCS). Utilizing Geographic Information System (GIS) software, the above-mentioned maps and databases were used in extracting seismic hazard parameters and bridge vulnerability characteristics in order to rank the seismic damage risk rating of bridges in the National Capital Region.

Keywords: bridge, earthquake, GIS, hazard, risk, vulnerability

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Authors: Hagos Abraham, Solomon Gizaw, Mengistu Urge

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A sound breeding objective is the basis for genetic improvement in overall economic merit of farm animals. Begait goat is one of the identified breeds in Ethiopia, which is a multipurpose breed as it serves as source of cash income and source of food (meat and milk). Despite its importance, no formal breeding objectives exist for Begait goat. The objective of the present study was to identify breeding objectives for the breed through two approaches: using own-flock ranking experiment and developing deterministic bio-economic models as a preliminary step towards designing sustainable breeding programs for the breed. In the own-flock ranking experiment, a total of forty five households were visited at their homesteads and were asked to select, with reasons, the first best, second best, third best and the most inferior does from their own flock. Age, previous reproduction and production information of the identified animals were inquired; live body weight and some linear body measurements were taken. The bio-economic model included performance traits (weights, daily weight gain, kidding interval, litter size, milk yield, kid mortality, pregnancy and replacement rates) and economic (revenue and costs) parameters. It was observed that there was close agreement between the farmers’ ranking and bio-economic model results. In general, the results of the present study indicated that Begait goat owners could improve performance of their goats and profitability of their farms by selecting for litter size, six month weight, pre-weaning kid survival rate and milk yield.

Keywords: bio-economic model, economic parameters, own-flock ranking, performance traits

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Authors: H. Moalla, A. Frikha

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Multi-criteria decision aid methods consider decision problems where numerous alternatives are evaluated on several criteria. These methods are used to deal with perfect information. However, in practice, it is obvious that this information requirement is too much strict. In fact, the imperfect data provided by more or less reliable decision makers usually affect decision results since any decision is closely linked to the quality and availability of information. In this paper, a PROMETHEE-BELIEF approach is proposed to help multi-criteria decisions based on incomplete information. This approach solves problems with incomplete decision matrix and unknown weights within PROMETHEE method. On the base of belief function theory, our approach first determines the distributions of belief masses based on PROMETHEE’s net flows and then calculates weights. Subsequently, it aggregates the distribution masses associated to each criterion using Murphy’s modified combination rule in order to infer a global belief structure. The final action ranking is obtained via pignistic probability transformation. A case study of real-world application concerning the location of a waste treatment center from healthcare activities with infectious risk in the center of Tunisia is studied to illustrate the detailed process of the BELIEF-PROMETHEE approach.

Keywords: belief function theory, incomplete information, multiple criteria analysis, PROMETHEE method

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Authors: I. Khutsishvili, G. Sirbiladze, B. Ghvaberidze

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This work proposes a fuzzy methodology to support the investment decisions. While choosing among competitive investment projects, the methodology makes ranking of projects using the new aggregation OWA operator – AsPOWA, presented in the environment of possibility uncertainty. For numerical evaluation of the weighting vector associated with the AsPOWA operator the mathematical programming problem is constructed. On the basis of the AsPOWA operator the projects’ group ranking maximum criteria is constructed. The methodology also allows making the most profitable investments into several of the project using the method developed by the authors for discrete possibilistic bicriteria problems. The article provides an example of the investment decision-making that explains the work of the proposed methodology.

Keywords: expert evaluations, investment decision making, OWA operator, possibility uncertainty

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: B. Z. Abubakar, J. P. Voh, B. F. Umar, S. Khalid, A. A. Barau, J. Aigbe

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The study was conducted to identify and assess the various community development programmes designed and executed by Sokoto Agricultural and Community Development Project (SACDP) with the assistance of International Funds for Agricultural Development (IFAD) among women beneficiaries in Kwacciyar-lalle and Mogonho communities of Sokoto state. A simple random sampling technique was employed to select 20 project beneficiaries in each of the selected communities, making a total of 40 beneficiaries. Structured questionnaire, descriptive statistics such as frequencies and percentages and also participatory methodologies such as focus group discussion and pair wise ranking were used to analyze the data. Results showed that majority of the beneficiaries (75%) were married and undertook animal rearing as their major occupation. Results further showed that (85%) of the beneficiaries were involved in decision making, which enhanced their participation. Pair-wise ranking showed dug well as the most preferred activity, followed by construction of Islamic school in Kwacciyar-lalle while well construction followed by provision of improved animal species were most preferred in Mogonho. Recommendations made in the light of achieving people’s participation include provision of more infrastructural facilities and working materials.

Keywords: community development, focus group, pair-wise ranking, infrastructure

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Authors: Ahmad Shahin, Fadi Chakik, Walid Moudani

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Our study is about elaborating a potential solution for a search engine that involves semantic technology to retrieve information and display it significantly. Semantic search engines are not used widely over the web as the majorities are still in Beta stage or under construction. Many problems face the current applications in semantic search, the major problem is to analyze and calculate the meaning of query in order to retrieve relevant information. Another problem is the ontology based index and its updates. Ranking results according to concept meaning and its relation with query is another challenge. In this paper, we are offering a light meta-engine (QESM) which uses Google search, and therefore Google’s index, with some adaptations to its returned results by adding multi-query expansion. The mission was to find a reliable ranking algorithm that involves semantics and uses concepts and meanings to rank results. At the beginning, the engine finds synonyms of each query term entered by the user based on a lexical database. Then, query expansion is applied to generate different semantically analogous sentences. These are generated randomly by combining the found synonyms and the original query terms. Our model suggests the use of semantic similarity measures between two sentences. Practically, we used this method to calculate semantic similarity between each query and the description of each page’s content generated by Google. The generated sentences are sent to Google engine one by one, and ranked again all together with the adapted ranking method (QESM). Finally, our system will place Google pages with higher similarities on the top of the results. We have conducted experimentations with 6 different queries. We have observed that most ranked results with QESM were altered with Google’s original generated pages. With our experimented queries, QESM generates frequently better accuracy than Google. In some worst cases, it behaves like Google.

Keywords: semantic search engine, Google indexing, query expansion, similarity measures

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Authors: Fatemeh Jaferi, Moslem Parsa, Heshmatolah Shams Khorramabadi

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In this modern fluctuating world, organizations need to outsource some parts of their activities (project) to providers in order to show a quick response to their changing requirements. In fact, a number of companies and institutes have contractors do their projects and have some specific criteria in contractor selection. Therefore, a set of scientific tools is needed to select the best contractors to execute the project according to appropriate criteria. Multi-criteria decision making (MCDM) has been employed in the present study as a powerful tool in ranking and selecting the appropriate contractor. In this study, devolving second-source (civil) project to contractors in the National Gas Company of Lorestan Province (Iran) has been found and therefore, 5 civil companies have been evaluated. Evaluation criteria include executive experience, qualification of technical staff, good experience and company's rate, technical interview, affordability, equipment and machinery. Criteria's weights are found through experts' opinions along with AHP and contractors ranked through TOPSIS and AHP. The order of ranking contractors based on MCDM methods differs by changing the formula in the study. In the next phase, the number of criteria and their weights has been sensitivity analysed through using AHP. Adding each criterion changed contractors' ranking. Similarly, changing weights resulted in a change in ranking. Adopting the stated strategy resulted in the facts that not only is an appropriate scientific method available to select the most qualified contractors to execute gas project, but also a great attention is paid to picking needed criteria for selecting contractors. Consequently, executing such project is undertaken by most qualified contractors resulted in optimum use of limited resource, accelerating the implementation of project, increasing quality and finally boosting organizational efficiency.

Keywords: multi-criteria decision making, project, management, contractor selection, gas company

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Authors: E. Koyuncu

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The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling

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Authors: Roseliza Mat Alipiah, David Raffaelli, J. C. R. Smart

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This research is a new approach as it integrates information from both environmental and social sciences to inform effective management of the wetlands. A three-stage research framework was developed for modelling the drivers and pressures imposed on the wetlands and their impacts to the ecosystem and the local communities. Firstly, a Bayesian Belief Network (BBN) was used to predict the probability of anthropogenic activities affecting the delivery of different key wetland ecosystem services under different management scenarios. Secondly, Choice Experiments (CEs) were used to quantify the relative preferences which key wetland stakeholder group (aquaculturists) held for delivery of different levels of these key ecosystem services. Thirdly, a Multi-Criteria Decision Analysis (MCDA) was applied to produce an ordinal ranking of the alternative management scenarios accounting for their impacts upon ecosystem service delivery as perceived through the preferences of the aquaculturists. This integrated ecosystem management approach was applied to a wetland ecosystem in Setiu, Terengganu, Malaysia which currently supports a significant level of aquaculture activities. This research has produced clear guidelines to inform policy makers considering alternative wetland management scenarios: Intensive Aquaculture, Conservation or Ecotourism, in addition to the Status Quo. The findings of this research are as follows: The BBN revealed that current aquaculture activity is likely to have significant impacts on water column nutrient enrichment, but trivial impacts on caged fish biomass, especially under the Intensive Aquaculture scenario. Secondly, the best fitting CE models identified several stakeholder sub-groups for aquaculturists, each with distinct sets of preferences for the delivery of key ecosystem services. Thirdly, the MCDA identified Conservation as the most desirable scenario overall based on ordinal ranking in the eyes of most of the stakeholder sub-groups. Ecotourism and Status Quo scenarios were the next most preferred and Intensive Aquaculture was the least desirable scenario. The methodologies developed through this research provide an opportunity for improving planning and decision making processes that aim to deliver sustainable management of wetland ecosystems in Malaysia.

Keywords: Bayesian belief network (BBN), choice experiments (CE), multi-criteria decision analysis (MCDA), aquaculture

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Authors: M. Kubilay Önal

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The objective of this study was to determine the adaptabilities of native apricot materials collected from Southeast Anatolia region of Turkey to Aegean Region conditions. Different phenological and pomological characteristics of the cultivars were observed during study. Determination of promising types for adaptation trials were performed employing the 'weighed-ranking' method. To determine them the relative points were given to the characteristics such as yield, average fruit weight, attractiveness, soluble solid, seed ratio by weight and aroma. As a result of two-year evaluation studies on the phenological and pomological characteristics of 22 types, 9 out of them, viz., nos. 2235, 2236, 2237, 2239, 2242, 2244, 2246, 2249, 2257 were selected as promising ones.

Keywords: apricot, phenological characters, pomological characters, weight-ranking method

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Authors: Farhad Nouparast

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For more production we need more capital formation. Capital formation in each country should be based on comparative advantages in different economic sectors due to the different production possibility curves. In regional planning, recognizing the relative advantages and consequently investing in more production requires identifying areas with the necessary capabilities and location of each region compared to other regions. In this article, ranking of Iran's provinces is done according to the specific and given variables as the best investment position in agricultural activity. So we can provide the necessary background for investment analysis in different regions of the country to formulate national and regional planning and execute investment projects. It is used factor analysis technique and numerical taxonomy analysis to do this in thisarticle. At first, the provinces are homogenized and graded according to the variables using cross-sectional data obtained from the agricultural census and population and housing census of Iran as data matrix. The results show that which provinces have the most potential for capital formation in agronomy sub-sector. Taxonomy classifies organisms based on similar genetic traits in biology and botany. Numerical taxonomy using quantitative methods controls large amounts of information and get the number of samples and categories and take them based on inherent characteristics and differences indirectly accommodates. Numerical taxonomy is related to multivariate statistics.

Keywords: Capital Formation, Factor Analysis, Multivariate statistics, Numerical Taxonomy Analysis, Production, Ranking, Spatial Planning

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Authors: Lien-Fa Lin, Yung-Ming Li, Fu-Shun Hsieh

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With the advancement of information technology and development of group commerce, people have obviously changed in their lifestyle. However, group commerce faces some challenging problems. The products or services provided by vendors do not satisfactorily reflect customers’ opinions, so that the sale and revenue of group commerce gradually become lower. On the other hand, the process for a formed customer group to reach group-purchasing consensus is time-consuming and the final decision is not the best choice for each group members. In this paper, we design a social decision support mechanism, by using group discussion message to recommend suitable options for group members and we consider social influence and personal preference to generate option ranking list. The proposed mechanism can enhance the group purchasing decision making efficiently and effectively and venders can provide group products or services according to the group option ranking list.

Keywords: social network, group decision, text mining, group commerce

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Authors: Nor Sahida Ibrahim, Ruhaila Maskat, Aishah Ahmad

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Almost all tertiary-level students will undergo some form of training in organisations prior to their graduation. This practice provides the necessary exposure and experience to allow students to cope with actual working environment and culture in the future. Nevertheless, a particular degree of “matching” between what is expected and what can be offered between students and organisations underpins how effective and enriching the experience is. This matching of students and organisations is challenging when preferences from both parties must be satisfied. This work developed a web-based system, namely the OrganisationMatcher, which leverage on the use of preference weights to score each organisation and rank them based on “suitability”. OrganisationMatcher has been implemented on a relational database, designed using object-oriented methods and developed using PHP programming language for browser front-end access. We outline the challenges and limitations of our system and discuss future improvements to the system, specifically in the utilisation of intelligent methods.

Keywords: student industrial placement, information system, web-based, ranking

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Authors: Andy S.K. Cheng, Samuel Leung, Cindy Kwok, Hector Tsang

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Background: Telephone counselling is one of the essential interventions that can be found in most of the Employee Assistance Programs (EAP). The purposes of this study were to (1) explore the trend of the telephone counselling from 2003-2016 in Hong Kong; (2) explore which EAP issue requires more follow-up; and 3) examine the relationship between the EAP issues and demographic data such as gender and job ranking. Method: Date of EAP services usage was collected from EAP providers in Hong Kong during 2003-2016. EAP issues were categorized into two domains, namely workplace issues and personal issues. Each domain has 12 sub-categories. Two hypotheses were formulated in this study (1) there was a gender difference in EAP issues and the follow-up hours; and (2) there was a significant difference between job ranking, EAP issues and follow-up hours. Results: A total of eight hundred and ninety-three valid cases were identified for analysis. Of them, three hundred and forty-three cases sought for follow-up. The duration of follow-up by hours was calculated for each of the follow-up cases. The results of the study shows that the top three workplace issues that required the longest duration of follow-up were (1) workload, (2) supervisor-subordinate relationship; and (3) team member’s relationship. On the other hand, the top three personal issues that required the longest duration of follow-up were (1) parenting/parent-child relationship, (2) family care, and (3) marital relationship. Two-way ANOVA was performed to compare the total follow-up hours (excluding first intake) between gender and EAP issues. There was no statistical significance for gender (p =.891), but a statistically significant main effect for EAP issues (p <.001) was found. Post-hoc analysis (Tukey’s test) showed that total follow-up hour in personal issues was statistically significant higher than that in handling workplace issues (p <.001). However, there was no statistically significant interaction effect between gender and EAP issues (p=.879) and between job ranking and EAP issues (p=.843). Conclusion: Telephone counselling is a very common intervention in addressing EAP issues arising from workplace and personal level in Hong Kong. It was frequently used to handle interpersonal relationships and the service usage was independent of gender and job ranking.

Keywords: employee assistance program, follow-up time, interpersonal relationships, telephone counselling

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Authors: Arbolino R., Boffardi R., L. De Simone

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The success of a development policy requires the definition of a proper investment planning on behalf of policymakers. Such planning should consider both tangible and intangible features characterizing a territory and, moreover, evaluate both state of place and an ideal situation to be achieved, that represents the final goal of the policy. The aim of this research is to propose a methodological approach to implement this ideal solution or the best solution appliable to the Italian regions. It consists of two steps: the first one is a measure of regional inequality through building a composite indicator for analyzing the level of development and compare the differences among the regions. It is constructed by means of a principal component analysis. Ranking regions according to the scores achieved is useful as benchmark, to identify a best solution towards which other regions should strive. Thus, this distance is measured through a revised Sen index that allows to assign a weight on which calculate the financing resource programming. The results show that this approach is a good instrument to fairly and efficiently allocate public funds, in order to reduce regional inequalities.

Keywords: public economics, inequalities, growth, development

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Authors: Subodh Chandra Shakya, Rajendra Sapkota, Aakash Tamang, Shushant Pudasaini, Sujan Adhikari, Sajjan Adhikari

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Lots of efforts have been made in order to measure the semantic similarity between the text corpora in the documents. Techniques have been evolved to measure the similarity of two documents. One such state-of-art technique in the field of Natural Language Processing (NLP) is word to vector models, which converts the words into their word-embedding and measures the similarity between the vectors. We found this to be quite useful for the task of resume ranking. So, this research paper is the implementation of the word2vec model along with other Natural Language Processing techniques in order to rank the resumes for the particular job description so as to automate the process of hiring. The research paper proposes the system and the findings that were made during the process of building the system.

Keywords: chunking, document similarity, information extraction, natural language processing, word2vec, word embedding

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Authors: Guang-Ho Cha

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This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.

Keywords: context-sensitive search, image search, similarity ranking, similarity search

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Authors: Li Xiaoge, Wang Chaodong

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We introduce the first Chinese Coreference Resolution Model based on BERT (CCRM-BERT) and show that it significantly outperforms all previous work. The key idea is to consider the features of the mention, such as part of speech, width of spans, distance between spans, etc. And the influence of each features on the model is analyzed. The model computes mention embeddings that combine BERT with features. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the Chinese OntoNotes benchmark.

Keywords: BERT, coreference resolution, deep learning, nature language processing

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Authors: Anna Siuda-Bak

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This paper adopts a comparative approach to examining the determinants of international mobility of German, Italian and British researchers who completed their doctoral education in the UK. Structured sampling and data collection techniques have been developed in order to retrieve information on participants from publicly available sources. This systematically collected data was supplemented with an on-line survey which captures participants’ job trajectories, including movements between positions, institutions and countries. In total, data on 949 German, Italian and British PhDs was collected. Logistic regression was employed to identify factors associated with one’s probability of moving outside the UK after his or her graduation. The predictor variables included factors associated with one’s PhD (field of study, ranking of the university which awarded the PhD degree) and family factors (having a child, nationality of the partner). Then, 9 constrained models were estimated to test the effect each variable has on probability of going to a specific destination, being English-speaking country, non-English speaking country or returning to the home country. The results show that females, arts and humanities graduates, and respondents with a partner from the UK are less mobile than their counterparts. The effect of the ranking of the university differed in two groups. The UK graduates from higher ranked universities were more likely to move abroad than to stay in the UK after their graduation. In contrast, non-UK natives from the same universities were less likely to be internationally mobile than non-UK natives from lower ranked universities. The nationality of the partner was the most important predictor of the specific destination choices. Graduates with partner from the home county were more likely to return home and those with a partner from the third country least likely to return.

Keywords: doctoral graduates, international mobility, nationality, UK

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Authors: Wiem Daoud Ben Amor, Luis Martínez López, Hela Moalla Frikha

Abstract:

Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain contexts where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ARAS-ELH). Within the ARAS-ELH approach, the DM can diagnose the results (the ranking of the alternatives) in a decomposed style, i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e the collective final results of all experts able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ARAS-ELH technique makes it easier for decision-makers to understand the results. Finally, An MCGDM case study is given to illustrate the proposed approach.

Keywords: additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts

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Authors: Abdulkadir Abu Lawal

Abstract:

For the dearth of reliable cardinal numerical data, the linked phenomena in productivity indices such as operational costs and company turnovers, etc. could not be investigated. This would not give us insight to the root of productivity problems at unique sites. So, ordinal ranking by professionals who were most directly involved with construction sites was applied for Kendall’s concordance. Responses gathered from independent architects, builders/engineers, and quantity surveyors were herein analyzed. They were responses based on factors that affect sites productivity, and these factors were categorized as head office factors, resource management effectiveness factors, motivational factors, and training/skill development factors. It was found that productivity is low and has to be improved in order to facilitate Nigerian efforts in bridging its infrastructure deficit. The significance of this work is underlined with the Kendall’s coefficient of concordance of 0.78, while remedial measures must be emphasized to stimulate better productivity. Further detailed study can be undertaken by using Fuzzy logic analysis on wider Delphi survey.

Keywords: factors, Kendall's coefficient of concordance, magnitude of agreement, percentage magnitude of dichotomy, ranking variables

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Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

Abstract:

Cloud computing and virtualization technology have brought an innovative way for people to develop and use software nowadays. However, conventional virtualization comes at the expense of performance loss for applications. Container-based virtualization could be an option as it potentially reduces overhead and minimizes performance decline of the service platform. In this paper, we introduce a system framework and present an implementation of resource broker for dynamic cloud service deployment on the container-based platform to facilitate the efficient execution and improve the utilization. We target the load-aware service deployment approach for task ranking scenario. This proposed effort can collaborate with resource management system to adaptively deploy services according to the different requests. In particular, our approach relies on composing service immediately onto appropriate container according to user’s requirement in order to conserve the waiting time. Our evaluation shows how efficient of the service deployment is and how to expand its applicability to support the variety of cloud service.

Keywords: cloud computing, container-based virtualization, resource broker, service deployment

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Authors: Chen Chih-Cheng, Chen I-Cheng, Lee Yung-Tan, Kuo Yen-Whea, Yu Chin-Hung

Abstract:

The purpose of this study is to construct a model for best spike player selection in a top volleyball tournament of the world. Data consisted of the records of 2013 World Grand Prix declared by International Volleyball Federation (FIVB). Simple Multiple-Attribute Rating Technique (SMART) was used for optimal decision-making model on the best spike player selection. The research results showed that the best spike player ranking by SMART is different than the ranking by FIVB. The results demonstrated the effectiveness and feasibility of the proposed model.

Keywords: simple multiple-attribute rating technique, World Grand Prix, best spike player, International Volleyball Federation

Procedia PDF Downloads 437