Search results for: option selection

Authors: Saleem Z. Ramadan

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The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: optimization, material selection, process selection, genetic algorithm

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Authors: Benhamouda Sara, Guezouli Larbi

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Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.

Keywords: distributed information retrieval, relevance, server selection, collection selection

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Authors: Seyyedeh Faezeh Hassani Ziabari, Sadegh Eskandari, Maziar Salahi

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Infinite Feature Selection (IFS) algorithm is an efficient feature selection algorithm that selects a subset of features of all sizes (including infinity). In this paper, we present an improved version of it, called clustering IFS (CIFS), by clustering the dataset in advance. To do so, first, we apply the K-means algorithm to cluster the dataset, then we apply IFS. In the CIFS method, the spatial and temporal complexities are reduced compared to the IFS method. Experimental results on 6 datasets show the superiority of CIFS compared to IFS in terms of accuracy, running time, and memory consumption.

Keywords: feature selection, infinite feature selection, clustering, graph

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Authors: Christoph Köster

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Supplier selection is one of the key challenges in supply chain management and can be considered a multi-criteria decision-making (MCDM) problem. In the 1960s, it evolved from considering only economic criteria, such as price, quality, and performance, to including environmental and social criteria nowadays. Although receiving considerable attention from scholars and practitioners over the past decades, existing research has not considered governance criteria so far. This is, however, surprising, as ESG (environmental, social, and governance) criteria have gained considerable attention. In order to complement ESG criteria in the supplier selection process, this study investigates German DAX and MDAX companies and evaluates the impact of governance criteria along their supplier selection process. Moreover, it proposes a set of criteria for the respective process steps. Specifically, eleven criteria for the first process step and five criteria for the second process step are identified. This paper contributes to a better understanding of the supplier selection process by elucidating the relevance of governance criteria in the supplier selection process and providing a set of empirically developed governance criteria. These results can be applied by practitioners to complement the criteria set in the supplier selection process and thus balance economic, environmental, social, and governance targets.

Keywords: ESG, governance, sustainable supplier selection, sustainability

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Authors: Christoph Koester

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Supplier selection is one of the key issues in supply chain management with a growing emphasis on sustainability driven by increasing stakeholder expectations and proactivity. In addition, new regulations, such as the German Supply Chain Act, fostered the inclusion of sustainable incl. governance selection criteria in the selection process. In order to provide a systematic approach to select the most suitable sustainable suppliers, this study quantifies the importance and prioritizes the relevant selection criteria across 17 German industries using the Fuzzy Analytical Hierarchy Process. Results show that economic criteria are still the most important in the selection decision averaging a global weight of 51%. However, environmental, social, and governance (ESG) criteria are combined, on average, almost equally important, with global weights of 22%, 16%, and 11%, respectively. While the type of industry influences criteria weights, other factors, such as type of purchasing or demographic factors, appear to have little impact.

Keywords: ESG, fuzzy analytical hierarchy process, sustainable supplier selection, sustainability

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Authors: Yusuf A. Bako, Olubunmi O. Kolawole

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This study sought to establish the effect of recruitment and selection on the employee performance in hospitality industries. The success of any organization in this modern business environment depends on the caliber of the manpower that steer the affairs of the organization. History has shown that recruitment and selection as a function of human resources management practices have a pivotal role in determining the level of employee performance in an organization. The hospitality industries have been faced with challenges of performance due to unconventional selection and placement practices in terms of poor policy in selecting candidate, inconsistency in selection process, sidetracking employment test and interview, godfatherism and regional selection process etc. The overall objective of the study was to determine how recruitment and selection affect employee performance in hospitality industry in Ogun State, Nigeria. This study adopts descriptive and inferential research design while population was drawn from leading hotels in Ogun State, Nigeria. The samples size was 100 employees and questionnaire was used to collect data while Cronbach alpha was used to test the instrument. The result of the study reveals that correlation between employee performance and recruitment and selection were highly significant.

Keywords: employee performance, human resources management, practices, recruitment, selection

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Authors: Manas Shah

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Black Scholes option pricing model is one of the most important concepts in modern world of computational finance. However, its practical use can be challenging as one of the input parameters must be estimated; implied volatility of the underlying security. The more precisely these values are estimated, the more accurate their corresponding estimates of theoretical option prices would be. Here, we present a novel model based on Cuckoo Search Optimization (CS) which finds more precise estimates of implied volatility than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).

Keywords: black scholes model, cuckoo search optimization, particle swarm optimization, genetic algorithm

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Authors: K. -H. Yang

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Supplier selection problem is one of the important issues of supply chain problems. Two categories of methodologies include qualitative and quantitative approaches which can be applied to supplier selection problems. However, due to the complexities of the problem and lacking of reliable and quantitative data, qualitative approaches are more than quantitative approaches. This study considers operational cost and supplier’s reliability factor and solves the problem by using a quantitative approach. A mixed integer programming model is the primary analytic tool. Analyses of different scenarios with variable cost and reliability structures show that the effectiveness of this approach to the supplier selection problem.

Keywords: mixed integer programming, quantitative approach, supplier’s reliability, supplier selection

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Authors: Mario Winkelhaus, Franz Vallée

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Many companies see horizontal cooperation as a promising possibility to increase their efficiency in outbound logistics. The selection of suitable partners has particular importance in the formation of horizontal cooperation. Up until now, literature mainly focused on general applicable methods for the identification of cooperation partners without a closer examination of the specific area where the cooperation takes place. Thus, specific criteria as a basis for the partner selection in the field of logistics cooperation are missing. To close this scientific gap, an explorative research approach is used to answer the open question of the article. To collect the needed criteria, a qualitative experiment with 20 participants from 16 companies was done. Within this workshop, general criteria, as well as sector-specific requirements, have been identified which were integrated in a partner selection model.

Keywords: horizontal cooperation, logistics cooperation partnering criteria, partner selection

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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Authors: Laicheng Cao, Xiangqian Su, Youxiao Wu

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Feature selection is one of the important problems in network security, pattern recognition, data mining and other fields. In order to remove redundant features, effectively improve the detection speed of intrusion detection system, proposes a new feature selection method, which is based on the invasive weed optimization (IWO) algorithm and tabu search algorithm(TS). Use IWO as a global search, tabu search algorithm for local search, to improve the results of IWO algorithm. The experimental results show that the feature selection method can effectively remove the redundant features of network data information in feature selection, reduction time, and to guarantee accurate detection rate, effectively improve the speed of detection system.

Keywords: intrusion detection, feature selection, iwo, tabu search

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Authors: Chiranjit Das, Sanjay Jharkharia

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This study is focused on transport mode selection under lead time variability and emissions constraint. In order to reduce the carbon emissions generation due to transportation, organization has often faced a dilemmatic choice of transport mode selection since logistic cost and emissions reduction are complementary with each other. Another important aspect of transportation decision is lead-time variability which is least considered in transport mode selection problem. Thus, in this study, we provide a comprehensive mathematical based analytical model to decide transport mode selection under emissions constraint. We also extend our work through analysing the effect of lead time variability in the transport mode selection by a sensitivity analysis. In order to account lead time variability into the model, two identically normally distributed random variables are incorporated in this study including unit lead time variability and lead time demand variability. Therefore, in this study, we are addressing following questions: How the decisions of transport mode selection will be affected by lead time variability? How lead time variability will impact on total supply chain cost under carbon emissions? To accomplish these objectives, a total transportation cost function is developed including unit purchasing cost, unit transportation cost, emissions cost, holding cost during lead time, and penalty cost for stock out due to lead time variability. A set of modes is available to transport each node, in this paper, we consider only four transport modes such as air, road, rail, and water. Transportation cost, distance, emissions level for each transport mode is considered as deterministic and static in this paper. Each mode is having different emissions level depending on the distance and product characteristics. Emissions cost is indirectly affected by the lead time variability if there is any switching of transport mode from lower emissions prone transport mode to higher emissions prone transport mode in order to reduce penalty cost. We provide a numerical analysis in order to study the effectiveness of the mathematical model. We found that chances of stock out during lead time will be higher due to the higher variability of lead time and lad time demand. Numerical results show that penalty cost of air transport mode is negative that means chances of stock out zero, but, having higher holding and emissions cost. Therefore, air transport mode is only selected when there is any emergency order to reduce penalty cost, otherwise, rail and road transport is the most preferred mode of transportation. Thus, this paper is contributing to the literature by a novel approach to decide transport mode under emissions cost and lead time variability. This model can be extended by studying the effect of lead time variability under some other strategic transportation issues such as modal split option, full truck load strategy, and demand consolidation strategy etc.

Keywords: carbon emissions, inventory theoretic model, lead time variability, transport mode selection

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Authors: Anupam Chanda

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Presently Packaging plays a significant role for drug discoveries. The process of selecting materials and the type of packaging also offers an opportunity for the Packaging scientist to look for biological delivery choices. Most injectable protein products were supplied in some sort of glass vial, prefilled syringe, cartridge. Those product having high Ph content there is a chance of “delamination “from inner surface of glass vial. With protein-based drugs, the biggest issue is the effect of packaging derivatives on the protein’s threedimensional and surface structure. These are any effects that relate to denaturation or aggregation of the protein due to oxidation or interactions from contaminants or impurities in the preparation. The potential for these effects needs to be carefully considered in choosing the container and the container closure system to avoid putting patients in jeopardy. Cause of Delamination : -Formulations with a high pH include phosphate and citrate buffers increase the risk of glass delamination. -High alkali content in glass could accelerate erosion. -High temperature during the vial-forming process increase the risk of glass delamination. -Terminal sterilization (irradiated at 20-40 kGy for 150 min) also is a risk factor for specific products(veterinary parenteral administration),could cause delamination. -High product-storage temperatures and long exposure times can increase the rate and severity of glass delamination. How to prevent Delamination -Treating the surface of the glass vials with materials, such as ammonium sulfate or siliconization can reduce the rate of glass erosion. -Consider alternative sterilization methods only in rare cases. -The correct specification for the glass to ensure its suitability for the pH of the product. -Use Cyclic olefin copolymer(COC)/Cyclic olefin Polymer(COP) Adsorption of protein and Solutions: Option#1 Coat with linear methoxylated polyglycerol and hyperbranchedmethoxylated polyglycerol. Option#2 Thehyperbranched non-methoxylated coating performed best. Option#3 Coat with hyperbranched polyglycerol Option#4 Right selection of Sterilization of glass vial/syringe.

Keywords: delamination of glass, ptrotien adoptions inside the glass surface, extractable & leachable solutions, injectable designs for new drugs

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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Authors: Gopinath Ganapathy, Chellammal Surianarayanan

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Services are growing rapidly and generally they are aggregated into a composite service to accomplish complex business processes. There may be several services that offer the same required function of a particular task in a composite service. Hence a choice has to be made for selecting suitable services from alternative functionally similar services. Quality of Service (QoS)plays as a discriminating factor in selecting which component services should be selected to satisfy the quality requirements of a user during service composition. There are two categories of approaches for QoS based service selection, namely global and local approaches. Global approaches are known to be Non-Polynomial (NP) hard in time and offer poor scalability in large scale composition. As an alternative to global methods, local selection methods which reduce the search space by breaking up the large/complex problem of selecting services for the workflow into independent sub problems of selecting services for individual tasks are coming up. In this paper, distributed architecture for selecting services based on QoS using local selection is presented with an overview of local selection methodology. The architecture describes the core components, namely, selection manager and QoS manager needed to implement the local approach and their functions. Selection manager consists of two components namely constraint decomposer which decomposes the given global or workflow level constraints in local or task level constraints and service selector which selects appropriate service for each task with maximum utility, satisfying the corresponding local constraints. QoS manager manages the QoS information at two levels namely, service class level and individual service level. The architecture serves as an implementation model for local selection.

Keywords: architecture of service selection, local method for service selection, QoS based service selection, approaches for QoS based service selection

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Authors: M. Pramila Devi, J. Praveena

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In today’s industrial scenario, the expectations and demand of customers are reaching great heights. In order to satisfy the customer requirements the users are increasingly turning towards fourth party logistics (4PL) service providers to manage their total supply chain operations. In this present research, initially, the criteria for the selection of integrated service providers have been identified and an integrated modal based on their inter-relationship has been developed with help of shippers, with this idea of what factors to be considered and their inter-relationships while selecting integrated service provider. Later, various methods deriving the priority weights viz. Analytical Hierarchy Process (AHP) have been employed for 4PL service provider selection. The derived priorities of 4PL alternatives using methods have been critically analyzed and compared for effective selection. The use of the modal indicates that the computed quantitative evaluation can be applied to improve the precision of the selection.

Keywords: analytical hierarchy process, fourth party logistics, priority weight, criteria selection

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Authors: I. Diamant, R. Srouji

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Applicant perceptions are attitudes, feelings, and cognitions which individuals have about selection procedures and have been mostly studied in the context of personnel selection. The main aim of the present study is to expand the understanding of applicant perceptions, using the framework of Organizational Justice Theory, in the domain of selection for higher education. The secondary aim is to explore the relationships between individual differences in social anxiety and applicants’ perceptions. The selection process is an accept/reject situation; it was hypothesized that applicants with higher social anxiety would experience negative perceptions and a lower success estimation, especially when subjected to social interaction elements in the process (interview and group simulation). Also, the effects of prior preparation and post-process explanations offered at the end of the selection process were explored. One hundred sixty psychology M.A. program applicants participated in this research, and following the selection process completed questionnaires measuring social anxiety, social exclusion, ratings on several justice dimensions for each of the methods in the selection process, feelings of success, and self-estimation of compatibility. About half of the applicants also received explanations regarding the significance and the aims of the selection process. Results provided support for most of our hypotheses: applicants with higher social anxiety experienced an increased level of social exclusion in the selection process, perceived the selection as less fair and ended with a lower feeling of success relative to those applicants without social anxiety. These relationships were especially salient in the selection procedures which included social interaction. Additionally, preparation for the selection process was positively related to the favorable perception of fairness in the selection process. Finally, contrary to our hypothesis, it was found that explanations did not affect the applicant’s perceptions. The results enhance our understanding of which factors affect applicant perceptions in applicants to higher education studies and contribute uniquely to the understanding of the effect of social anxiety on different aspects of selection experienced by applicants. The findings clearly show that some individuals may be predisposed to react unfavorably to certain selection situations. In an age of increasing awareness towards fairness in evaluation and selection and hiring procedures, these findings may be of relevance and may contribute to the design of future personnel selection methods in general and of higher education selection in particular.

Keywords: applicant perceptions, selection and assessment, organizational justice theory, social anxiety

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Authors: F. O. Adeosun, I. O. Orubuloye, O. O. Babalola

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Although caesarean section has greatly improved obstetric care throughout the world, in developing countries there is a great aversion to caesarean section. This study was carried out to examine the rate at which pregnant women with pre-eclampsia choose caesarean section over natural birth. A cross-sectional study was conducted among 500 pre-eclampsia antenatal clients seen at the States University Teaching Hospitals in the last one year. The sample selection was purposive. Information on their educational background, beliefs and attitudes were collected. Data analysis was presented using simple percentages. Out of 500 women studied, 38% favored caesarean section while 62% were against it. About 89% of them understood what caesarean section is, 57.3% of those who understood what caesarean section is will still not choose it as an option. Over 85% of the women believed caesarean section is done for medical reasons. If caesarean section is given as an option for childbirth, 38% would go for it, 29% would try religious intervention, 5.5% would not choose it because of fear, while 27.5% would reject it because they believe it is culturally wrong. Majority of respondents (85%) who favored caesarean delivery are aware of the risk attached to choosing virginal birth but go an extra mile in sourcing funds for a caesarean session while over 64% cannot afford the cost of caesarean delivery. It is therefore pertinent to encourage research in prediction methods and prevention of occurrence, since this would assist patients to plan on how to finance treatment.

Keywords: caesarean section, choice, cost, pre eclampsia, prediction methods

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Authors: Sevde D. Karayel, Ediz Atmaca

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Supplier selection subject is vital because of development competitiveness and performance of firms which have right, rapid and with low cost procurement. Considering the fact that competition between firms is no longer on their supply chains, hence it is very clear that performance of the firms’ not only depend on their own success but also success of all departments in supply chain. For this purpose, firms want to work with suppliers which are cost effective, flexible in terms of demand and high quality level for customer satisfaction. However, diversification and redundancy of their expectations from suppliers, supplier selection problems need to be solved as a hard problem. In this study, supplier selection problem is discussed for critical piece, which is using almost all production of products in and has troubles with lead time from supplier, in a firm that produces medical devices. Analyzing policy in the current situation of the firm in the supplier selection indicates that supplier selection is made based on the purchasing department experience and other authorized persons’ general judgments. Because selection do not make based on the analytical methods, it is caused disruptions in production, lateness and extra cost. To solve the problem, AHP and TOPSIS which are multi-criteria decision making techniques, which are effective, easy to implement and can analyze many criteria simultaneously, are used to make a selection among alternative suppliers.

Keywords: AHP-TOPSIS methods, multi-criteria decision making, supplier selection problem, supply chain management

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: Younies Saeed Hassan Mahmoud, Mai Mabrouk, Elsayed Sallam

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Analysing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics

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Authors: Fatih Iscan, Ceren Yagci

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Rapid population growth, urbanization and industrialization are known as the most important factors of environment problems. Elimination and management of solid wastes are also within the most important environment problems. One of the main problems in solid waste management is the selection of the best site for elimination of solid wastes. Lately, Geographical Information System (GIS) has been used for easing selection of landfill area. GIS has the ability of imitating necessary economical, environmental and political limitations. They play an important role for the site selection of landfill area as a decision support tool. In this study; map layers will be studied for minimum effect of environmental, social and cultural factors and maximum effect for engineering/economical factors for site selection of landfill areas and using GIS for an decision support mechanism in solid waste landfill areas site selection will be presented in Aksaray/TURKEY city, Güzelyurt district practice.

Keywords: GIS, landfill, solid waste, spatial analysis

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Authors: Georgiana Onicescu, Yuqian Shen

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Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.

Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection

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Authors: Paulo Fernando Silva Filho, Elcio Hideiti Shiguemori

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The selection of specific landmarks for an Unmanned Aerial Vehicles’ Visual Navigation systems based on Automatic Landmark Recognition has significant influence on the precision of the system’s estimated position. At the same time, manual selection of the landmarks does not guarantee a high recognition rate, which would also result on a poor precision. This work aims to develop an automatic landmark selection that will take the image of the flight area and identify the best landmarks to be recognized by the Visual Navigation Landmark Recognition System. The criterion to select a landmark is based on features detected by ORB or AKAZE and edges information on each possible landmark. Results have shown that disposition of possible landmarks is quite different from the human perception.

Keywords: clustering, edges, feature points, landmark selection, X-means

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Authors: Guillaume Leduc

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In this paper, we describe a broad setting under which the error of the approximation can be quantified, controlled, and for which convergence occurs at a speed of n⁻¹ for European and American options. We describe how knowledge of the error allows for arbitrarily fast acceleration of the convergence.

Keywords: random walk approximation, European and American options, rate of convergence, option pricing

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Authors: Tonny Ograh, Joshua Ayarkwa, Dickson Osei-Asibey, Alex Acheampong, Peter Amoah

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Theories are used to improve the conceptualization of research ideas. These theories enhance valuable elucidations that help us to grasp the meaning of research findings. Nevertheless, the use of theories to promote studies in green supplier selection in procurement decisions has attracted little attention. With the emergence of sustainable procurement, public procurement practitioners in Ghana are yet to achieve relevant knowledge on green supplier selections due to insufficient knowledge and inadequate appropriate frameworks. The flagrancy of the consequences of public procurers’ failure to integrate environmental considerations into supplier selection explains the adoption of a multi-theory approach for comprehension of the dynamics of green integration into supplier selection. In this paper, the practicality of three theories for improving the understanding of the influential factors enhancing the integration of environmental sustainability into supplier selection was reviewed. The three theories are Resource-Based Theory, Human Capital Theory and Absorptive Capacity Theory. This review uncovered knowledge management, top management commitment, and environmental management capabilities as important elements needed for the integration of environmental sustainability into supplier selection in public procurement. The theoretical review yielded a framework that conceptualizes knowledge and capabilities of practitioners relevant to the incorporation of environmental sustainability into supplier selection in public procurement.

Keywords: environmental, sustainability, supplier selection, environmental procurement, sustainable procurement

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics

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Authors: Cavidan Yakupoglu, Kurt Rohloff

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In this study, we aim to provide a novel parameter selection model for the BFVrns scheme, which is one of the prominent FHE schemes. Parameter selection in lattice-based FHE schemes is a practical challenges for experts or non-experts. Towards a solution to this problem, we introduce a hybrid principles-based approach that combines theoretical with experimental analyses. To begin, we use regression analysis to examine the parameters on the performance and security. The fact that the FHE parameters induce different behaviors on performance, security and Ciphertext Expansion Factor (CEF) that makes the process of parameter selection more challenging. To address this issue, We use a multi-objective optimization algorithm to select the optimum parameter set for performance, CEF and security at the same time. As a result of this optimization, we get an improved parameter set for better performance at a given security level by ensuring correctness and security against lattice attacks by providing at least 128-bit security. Our result enables average ~ 5x smaller CEF and mostly better performance in comparison to the parameter sets given in [1]. This approach can be considered a semiautomated parameter selection. These studies are conducted using the PALISADE homomorphic encryption library, which is a well-known HE library. The abstract goes here.

Keywords: lattice cryptography, fully homomorphic encryption, parameter selection, LWE, RLWE

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Authors: Kozik Renata, Leśniak Agnieszka, Plebankiewicz Edyta

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Contracting authorities in the public sector are obligated to apply the principles provided for in the Polish law for the evaluation and selection of contractors. To analyze the methods of contractors, applied in practice by public clients, the notices of contract award results for construction works were analyzed. The analysis shows that the procedure selected more and more often is open to competitive bidding, where the assessment of the competence of contractors is not very precise, as well as non-competitive bidding, i.e. single source procurement. The share of procurement procedures, where the only criterion is price, is increasing. The solution to the problems existing here might be the introduction of one of the forms of pre-selection of contractors. The article also briefly discusses verification systems for companies applying for public contracts used in EU countries.

Keywords: certification, contractors selection, open tendering, public investors

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Authors: Seifoddini Hamid, Mardikoraeem Mahsa, Ghorayshi Roya

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Manufacturing facility location selection is an important strategic decision for many industrial corporations. In this paper, a new approach to the manufacturing location selection problem is proposed. In this approach, cluster analysis is employed to identify suitable manufacturing locations based on economic, social, environmental, and political factors. These factors are quantified using the existing real world data.

Keywords: manufacturing facility, manufacturing sites, real world data

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