Search results for: Parking site selection

Authors: Othoman Elsayah, Naren Gupta, Binsheng Zhang

Abstract:

The construction sector constitutes one of the most important sectors in the economy of any country. Contractor selection is a critical decision that is undertaken by client organizations and is central to the success of any construction project. Contractor selection (CS) is a process which involves investigating, screening and determining whether candidate contractors have the technical and financial capability to be accepted to formally tender for construction work. The process should be conducted prior to the award of contract, characterized by many factors such as: contactor’s skills, experience on similar projects, track- record in the industry, and financial stability. However, this paper evaluates the current state of knowledge in relation to contractor selection process and demonstrates the findings from the analysis of the data collected from the Delphi questionnaire survey. The survey was conducted with a group of 12 experts working in the Libyan construction industry (LCI). The paper starts by briefly explaining the general outline of the questionnaire including the survey participation rate, the different fields the experts came from, and the business titles of the participants. Then the paper describes the tests used to determine when the experts had reached consensus. The paper is based on research which aims to develop rank contractor selection criteria with specific application to make construction projects in the Libyan context. The findings of this study will be utilized to establish the scope of work that will be used as part of a PhD research.

Keywords: Contractor selection, Libyan construction industry, Decision experts and Delphi technique.

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Authors: C. Ardil

Abstract:

Neutrosophic logic decision analysis is proposed as a method of stealth fighter aircraft selection for Turkish Air Force. The opinion of experts is employed to rank the alternatives across a set of criteria. The analyst uses neutrosophic logic numbers to describe the experts' preferences. This approach can handle the situation in the case of unavailability of precise data, which is most commonly the case in stealth fighter aircraft selection. Neutrosophic logic numbers can consider the imprecision of the factors affecting decision making such as stealth analysis, survivability analysis, and performance analysis. Neutrosophic logic ranking is achieved using weighted arithmetic operator and weighted geometric operator and the alternatives are ranked from best to worst. An example is also presented to illustrate the applicability and effectiveness of the proposed method. 

Keywords: Neutrosophic set theory, stealth fighter aircraft selection, multiple criteria decision-making, neutrosophic logic decision making, Turkish Air Force, MCDM

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Authors: Ryuya Uda

Abstract:

On existing online shopping on the web, SSL and password are usually used to achieve the secure trades. SSL shields communication from the third party who is not related with the trade, and indicates that the trader's web site is authenticated by one of the certification authority. Password certifies a customer as the same person who has visited the trader's web site before, and protects the customer's privacy such as what the customer has bought on the site. However, there is no forensics for the trades in those cased above. With existing methods, no one can prove what is ordered by customers, how many products are ordered and even whether customers have ordered or not. The reason is that the third party has to guess what were traded with logs that are held by traders and by customers. The logs can easily be created, deleted and forged since they are electronically stored. To enhance security with digital forensics for electronic commerce on the web, I indicate a secure method with cellular phones.

Keywords: Cellular Phone, Digital Forensics, ElectronicCommerce, Information Security

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Authors: C. Ardil

Abstract:

Using the aid of Hausdorff distance function and Minkowski distance function, this study proposes a novel method for selecting combat aircraft for Air Force. In order to do this, the proximity measure method was developed with determinate fuzzy degrees based on the relationship between attributes and combat aircraft alternatives. The combat aircraft selection attributes were identified as payloadability, maneuverability, speedability, stealthability, and survivability. Determinate fuzzy data from the combat aircraft attributes was then aggregated using the determinate fuzzy weighted arithmetic average operator. For the selection of combat aircraft, correlation analysis of the ranking order patterns of options was also examined. A numerical example from military aviation is used to demonstrate the applicability and effectiveness of the proposed method.

Keywords: Combat aircraft selection, multiple criteria decision making, fuzzy sets, determinate fuzzy sets, intuitionistic fuzzy sets, proximity measure method, Hausdorff distance function, Minkowski distance function, PMM, MCDM

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: Corporate credit rating prediction, feature selection, genetic algorithms, instance selection, multiclass support vector machines.

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Authors: V. Sulakatko, F. U. Vogdt, I. Lill

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Construction technology and on-site construction activities have a direct influence on the life cycle costs of energy efficiently renovated apartment buildings. The systematic inadequacies of the External Thermal Insulation Composite System (ETICS) which occur during the construction phase increase the risk for all stakeholders, reduce mechanical durability and increase the life cycle costs of the building. The economic effect of these shortcomings can be minimised if the risk of the most significant on-site activities is recognised. The objective of the presented ETICS economic assessment concept is to evaluate the economic influence of on-site shortcomings and reveal their significance to the foreseeable future repair costs. The model assembles repair techniques, discusses their direct cost calculation methods, argues over the proper usage of net present value over the life cycle of the building, and proposes a simulation tool to evaluate the risk of on-site activities. As the technique is dependent on the selected real interest rate, a sensitivity analysis is anticipated to determine the validity of the recommendations. After the verification of the model on the sample buildings by the industry, it is expected to increase economic rationality of resource allocation and reduce high-risk systematic shortcomings during the construction process of ETICS.

Keywords: Activity-based cost estimating, Cost estimation, ETICS, Life cycle costing.

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Authors: Yousef S. Al-Othman

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The growth and expansion of the industrial facilities comes proportional to the market increasing demand of products and services. Furthermore, raw material producers such as oil companies usually undergo massive revamping projects to maintain a synchronized supply. These revamping projects are usually delivered through challenging construction projects held and associated with daily site risks related to the construction process. Henceforth, a case study related to these risks and corresponding on-spot corrective measurements has been made on a certain number of construction project contractors at Kuwait Oil Company (KOC) to derive the benefits and overall effectiveness of the on-spot corrective measurements during the construction phase of a project, and how would the same help in avoiding major incidents, ensuring a smooth, cost effective and on time delivery of the project. Findings of this case study shall have an added value to the overall risk management process by minimizing the daily site risks that may affect the project lead time, resulting in an undisturbed on-site construction process.

Keywords: Oil and gas, risk management, construction projects, project lead time.

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Authors: N. Arulanand, P. M. Ananth

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Quality of Service (QoS) attributes as part of the service description is an important factor for service attribute. It is not easy to exactly quantify the weight of each QoS conditions since human judgments based on their preference causes vagueness. As web services selection requires optimization, evolutionary computing based on heuristics to select an optimal solution is adopted. In this work, the evolutionary computing technique Particle Swarm Optimization (PSO) is used for selecting a suitable web services based on the user’s weightage of each QoS values by optimizing the QoS weight vector and thereby finding the best weight vectors for best services that is being selected. Finally the results are compared and analyzed using static inertia weight and deterministic inertia weight of PSO.

Keywords: QoS, Optimization, Particle Swarm Optimization (PSO), weight vector, web services, web service selection.

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Authors: Liping Jing, Michael K. Ng, Tieyong Zeng

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Microarray data profiles gene expression on a whole genome scale, therefore, it provides a good way to study associations between gene expression and occurrence or progression of cancer. More and more researchers realized that microarray data is helpful to predict cancer sample. However, the high dimension of gene expressions is much larger than the sample size, which makes this task very difficult. Therefore, how to identify the significant genes causing cancer becomes emergency and also a hot and hard research topic. Many feature selection algorithms have been proposed in the past focusing on improving cancer predictive accuracy at the expense of ignoring the correlations between the features. In this work, a novel framework (named by SGS) is presented for stable gene selection and efficient cancer prediction . The proposed framework first performs clustering algorithm to find the gene groups where genes in each group have higher correlation coefficient, and then selects the significant genes in each group with Bayesian Lasso and important gene groups with group Lasso, and finally builds prediction model based on the shrinkage gene space with efficient classification algorithm (such as, SVM, 1NN, Regression and etc.). Experiment results on real world data show that the proposed framework often outperforms the existing feature selection and prediction methods, say SAM, IG and Lasso-type prediction model.

Keywords: Gene Selection, Cancer Prediction, Lasso, Clustering, Classification.

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Authors: Rameswar Debnath, Haruhisa Takahashi

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An evolutionary method whose selection and recombination operations are based on generalization error-bounds of support vector machine (SVM) can select a subset of potentially informative genes for SVM classifier very efficiently [7]. In this paper, we will use the derivative of error-bound (first-order criteria) to select and recombine gene features in the evolutionary process, and compare the performance of the derivative of error-bound with the error-bound itself (zero-order) in the evolutionary process. We also investigate several error-bounds and their derivatives to compare the performance, and find the best criteria for gene selection and classification. We use 7 cancer-related human gene expression datasets to evaluate the performance of the zero-order and first-order criteria of error-bounds. Though both criteria have the same strategy in theoretically, experimental results demonstrate the best criterion for microarray gene expression data.

Keywords: support vector machine, generalization error-bound, feature selection, evolutionary algorithm, microarray data

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Authors: Ashok Kumar, Narottam Chand, Vinod Kumar

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Due to the limited energy resources, energy efficient operation of sensor node is a key issue in wireless sensor networks. Clustering is an effective method to prolong the lifetime of energy constrained wireless sensor network. However, clustering in wireless sensor network faces several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we propose a protocol supporting an energy efficient clustering, cluster head selection/rotation and data routing method to prolong the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection/rotation and data routing.

Keywords: Wireless sensor networks, clustering, energy efficient, localization.

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Authors: Nasyairi Mat Nasir, Zulhabri Ismail, Faridah Ismail, Sharifah Nur Aina Syed Alwee, Masnizan Che Mat

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The utilisation of Industrial Building System (IBS) in construction industry will lead to a safe site condition since minimum numbers of workers are required to be on-site, timely material delivery, systematic component storage, reduction of construction material and waste. These matters are being promoted in the Construction Industry Master Plan (CIMP 2006-2015). However, the enabling factors of IBS that will foster a safer working environment are indefinite; on that basis a research has been conducted. The purpose of this paper is to discuss and identify the relevant factors towards safety improvement for IBS. A quantitative research by way of questionnaire surveys have been conducted to 314 construction companies. The target group was Grade 5 to Grade 7 contractors registered with Construction Industry Development Board (CIDB) which specialise in IBS. The findings disclosed seven factors linked to the safety improvement of IBS construction site in Malaysia. The factors were historical, economic, psychological, technical, procedural, organisational and the environmental factors. From the findings, a psychological factor ranked as the highest and most crucial factor contributing to safer IBS construction site. The psychological factor included the self-awareness and influences from workmates behaviour. Followed by organisational factors, where project management style will encourage the safety efforts. From the procedural factors, it was also found that training was one of the significant factors to improve safety culture of IBS construction site. Another important finding that formed as a part of the environmental factor was storage of IBS components, in which proper planning of the layout would able to contribute to a safer site condition. To conclude, in order to improve safety of IBS construction site, a welltrained and skilled workers are required for IBS projects, thus proper training is permissible and should be emphasised.

Keywords: Enabling Factors, Industrialised Building System, Safety Improvement.

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Authors: Khin May Win, Nan Sai Moon Kham

Abstract:

Identification of cancer genes that might anticipate the clinical behaviors from different types of cancer disease is challenging due to the huge number of genes and small number of patients samples. The new method is being proposed based on supervised learning of classification like support vector machines (SVMs).A new solution is described by the introduction of the Maximized Margin (MM) in the subset criterion, which permits to get near the least generalization error rate. In class prediction problem, gene selection is essential to improve the accuracy and to identify genes for cancer disease. The performance of the new method was evaluated with real-world data experiment. It can give the better accuracy for classification.

Keywords: Microarray data, feature selection, recursive featureelimination, support vector machines.

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Authors: Emre Ipekci Cetin, Ebru Tarcan Icigen

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Personnel selection process is considered as one of the most important and most difficult issues in human resources management. At the stage of personnel selection, the applicants are handled according to certain criteria, the candidates are dealt with, and efforts are made to select the most appropriate candidate. However, this process can be more complicated in terms of the managers who will carry out the staff selection process. Candidates should be evaluated according to different criteria such as work experience, education, foreign language level etc. It is crucial that a rational selection process is carried out by considering all the criteria in an integrated structure. In this study, the problem of choosing the front office manager of a 5 star accommodation enterprise operating in Antalya is addressed by using multi-criteria decision-making methods. In this context, SWARA (Step-wise weight assessment ratio analysis) and MOORA (Multi-Objective Optimization on the basis of ratio analysis) methods, which have relatively few applications when compared with other methods, have been used together. Firstly SWARA method was used to calculate the weights of the criteria and subcriteria that were determined by the business. After the weights of the criteria were obtained, the MOORA method was used to rank the candidates using the ratio system and the reference point approach. Recruitment processes differ from sector to sector, from operation to operation. There are a number of criteria that must be taken into consideration by businesses in accordance with the structure of each sector. It is of utmost importance that all candidates are evaluated objectively in the framework of these criteria, after these criteria have been carefully selected in the selection of suitable candidates for employment. In the study, staff selection process was handled by using SWARA and MOORA methods together.

Keywords: Accommodation establishments, human resource management, MOORA, multi criteria decision making, SWARA.

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Authors: Marco Raciti Castelli, Ernesto Benini

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This work presents a comparison between the Annual Energy Output (AEO) of two commercial vertical-axis wind turbines (VAWTs) for a low-wind urban site: both a drag-driven and a liftdriven concepts are examined in order to be installed on top of the new Via dei Giustinelli building, Trieste (Italy). The power-curves, taken from the product specification sheets, have been matched to the wind characteristics of the selected installation site. The influence of rotor swept area and rated power on the performance of the two proposed wind turbines have been examined in detail, achieving a correlation between rotor swept area, electrical generator size and wind distribution, to be used as a guideline for the calculation of the AEO.

Keywords: Annual Energy Output, micro-generationtechnology, urban environment, Vertical-Axis Wind Turbine

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Authors: Chiu-Wen Chen, Chih-Feng Chen, Cheng-Di Dong

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The distribution, enrichment, and accumulation of zinc (Zn) in the sediments of Kaohsiung Ocean Disposal Site (KODS), Taiwan were investigated. Sediment samples from two outer disposal site stations and nine disposed stations in the KODS were collected per quarterly in 2009 and characterized for Zn, aluminum, organic matter, and grain size. Results showed that the mean Zn concentrations varied from 48 mg/kg to 456 mg/kg. Results from the enrichment factor (EF) and geo-accumulation index (Igeo) analyses imply that the sediments collected from the KODS can be characterized between moderate and moderately severe degree enrichment and between none and none to medium accumulation of Zn, respectively. However, results of potential ecological risk index indicate that the sediment has low ecological potential risk. The EF, Igeo, and Zn concentrations at the disposed stations were slightly higher than those at outer disposal site. This indicated that the disposed area centers may be subjected to the disposal impaction of harbor dredged sediments.

Keywords: ocean dispose; zinc; enrichment factor; potential ecological risk index.

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Authors: Bojan Korizma, Zeljko Panian

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Online auctions are not very popular in Croatia. The main reason for this is a very limited number of services which can be used by Croatian users. Until recent times, even selling through the most popular online auction site eBay wasn't possible because PayPal services could not make payment to bank or debit card accounts in Croatia. Furthermore, many foreign sellers do not offer delivery of their products to Croatia which means that large quantities of goods initially offered on such sites are not available. With that in mind, it is necessary to analyze the buying and selling habits of Croatian users and existing online auction sites, both Croatian and foreign, and create a model for new domestic site. This site will have to exploit every positive aspect of existing models and neutralize every negative perception indicated by users in the survey so that, hopefully, it would attract new users.

Keywords: online auction, eBay, safe payment, product delivery

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Authors: Pei-Chann Chang, Wei-Hsiu Huang, Ching-Jung Ting, Hwei-Wen Luo, Yu-Peng Yu

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Artificial Immune System is applied as a Heuristic Algorithm for decades. Nevertheless, many of these applications took advantage of the benefit of this algorithm but seldom proposed approaches for enhancing the efficiency. In this paper, a Self-evolving Artificial Immune System is proposed via developing the T and B cell in Immune System and built a self-evolving mechanism for the complexities of different problems. In this research, it focuses on enhancing the efficiency of Clonal selection which is responsible for producing Affinities to resist the invading of Antigens. T and B cell are the main mechanisms for Clonal Selection to produce different combinations of Antibodies. Therefore, the development of T and B cell will influence the efficiency of Clonal Selection for searching better solution. Furthermore, for better cooperation of the two cells, a co-evolutional strategy is applied to coordinate for more effective productions of Antibodies. This work finally adopts Flow-shop scheduling instances in OR-library to validate the proposed algorithm.

Keywords: Artificial Immune System, Clonal Selection, Flow-shop Scheduling Problems, Co-evolutional strategy

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Authors: C. Ardil

Abstract:

This paper presents an original application of multiple criteria decision making analysis theory to the evaluation of aircraft selection problem. The selection of an optimal, efficient and reliable fleet, network and operations planning policy is one of the most important factors in aircraft selection problem. Given that decision making in aircraft selection involves the consideration of a number of opposite criteria and possible solutions, such a selection can be considered as a multiple criteria decision making analysis problem. This study presents a new integrated approach to decision making by considering the multiple criteria utility theory and the maximal regret minimization theory methods as well as aircraft technical, economical, and environmental aspects. Multiple criteria decision making analysis method uses different normalization techniques to allow criteria to be aggregated with qualitative and quantitative data of the decision problem. Therefore, selecting a suitable normalization technique for the model is also a challenge to provide data aggregation for the aircraft selection problem. To compare the impact of different normalization techniques on the decision problem, the vector, linear (sum), linear (max), and linear (max-min) data normalization techniques were identified to evaluate aircraft selection problem. As a logical implication of the proposed approach, it enhances the decision making process through enabling the decision maker to: (i) use higher level knowledge regarding the selection of criteria weights and the proposed technique, (ii) estimate the ranking of an alternative, under different data normalization techniques and integrated criteria weights after a posteriori analysis of the final rankings of alternatives. A set of commercial passenger aircraft were considered in order to illustrate the proposed approach. The obtained results of the proposed approach were compared using Spearman's rho tests. An analysis of the final rank stability with respect to the changes in criteria weights was also performed so as to assess the sensitivity of the alternative rankings obtained by the application of different data normalization techniques and the proposed approach.

Keywords: Normalization Techniques, Aircraft Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, MCDMA

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Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

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In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: Churn prediction, data mining, decision-theoretic rough set, feature selection.

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Authors: Mohammadamin Zanganeh, Vahid Khalajzadeh

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The problems associated with wind predictions of WAsP model in complex terrain are already the target of several studies in the last decade. In this paper, the influence of surrounding orography on accuracy of wind data analysis of a train is investigated. For the case study, a site with complex surrounding orography is considered. This site is located in Manjil, one of the windiest cities of Iran. For having precise evaluation of wind regime in the site, one-year wind data measurements from two metrological masts are used. To validate the obtained results from WAsP, the cross prediction between each mast is performed. The analysis reveals that WAsP model can estimate the wind speed behavior accurately. In addition, results show that this software can be used for predicting the wind regime in flat sites with complex surrounding orography.

Keywords: Complex terrain, Meteorological mast, WAsPmodel, Wind prediction

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Authors: M. A. Stoian, D. M. Cocarta, A. Badea

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The main sources of soil pollution due to petroleum contaminants are industrial processes involve crude oil. Soil polluted with crude oil is toxic for plants, animals, and humans. Human exposure to the contaminated soil occurs through different exposure pathways: Soil ingestion, diet, inhalation, and dermal contact. The present study research is focused on soil contamination with heavy metals as a consequence of soil pollution with petroleum products. Human exposure pathways considered are: Accidentally ingestion of contaminated soil and dermal contact. The purpose of the paper is to identify the human health risk (carcinogenic risk) from soil contaminated with heavy metals. The human exposure and risk were evaluated for five contaminants of concern of the eleven which were identified in soil. Two soil samples were collected from a bioremediation platform from Muntenia Region of Romania. The soil deposited on the bioremediation platform was contaminated through extraction and oil processing. For the research work, two average soil samples from two different plots were analyzed: The first one was slightly contaminated with petroleum products (Total Petroleum Hydrocarbons (TPH) in soil was 1420 mg/kg_d.w.), while the second one was highly contaminated (TPH in soil was 24306 mg/kg_d.w.). In order to evaluate risks posed by heavy metals due soil pollution with petroleum products, five metals known as carcinogenic were investigated: Arsenic (As), Cadmium (Cd), Chromium^VI (Cr^VI), Nickel (Ni), and Lead (Pb). Results of the chemical analysis performed on samples collected from the contaminated soil evidence soil contamination with heavy metals as following: As in Site 1 = 6.96 mg/kg_d.w; As in Site 2 = 11.62 mg/kg_d.w, Cd in Site 1 = 0.9 mg/kg_d.w; Cd in Site 2 = 1 mg/kg_d.w; Cr^VI was 0.1 mg/kg_d.w for both sites; Ni in Site 1 = 37.00 mg/kg_d.w; Ni in Site 2 = 42.46 mg/kg_d.w; Pb in Site 1 = 34.67 mg/kg_d.w; Pb in Site 2 = 120.44 mg/kg_d.w. The concentrations for these metals exceed the normal values established in the Romanian regulation, but are smaller than the alert level for a less sensitive use of soil (industrial). Although, the concentrations do not exceed the thresholds, the next step was to assess the human health risk posed by soil contamination with these heavy metals. Results for risk were compared with the acceptable one (10^-6, according to World Human Organization). As, expected, the highest risk was identified for the soil with a higher degree of contamination: Individual Risk (IR) was 1.11×10^-5 compared with 8.61×10^-6. 

Keywords: Carcinogenic risk, heavy metals, human health risk assessment, soil pollution.

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Authors: M. Kargar, A. Isazadeh, F. Fartash, T. Saderi

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In this paper we suggest a method for setting electronic credits for the customers. In this method banks and market-sites help each other to make doing large shopping through internet so easy. By developing this system, the people who have less money to buy most of the things they want, become able to buy all of them just through a credit. This credit is given by market-sites through a banking control on it. The method suggested can stop being imprisoned because of banking debts.

Keywords: E-Business, E-Credit, Market-site, Buy-site, Bank, E-Commerce.

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Authors: C. Ardil

Abstract:

This paper considers a comparative analysis of multiple criteria decision making analysis methods for strategic, tactical, and operational decisions in military fighter aircraft selection for the air force fleet planning. The evaluation criteria governing the decision analysis process are determined from the literature for the three existing military combat aircraft. Military fighter aircraft selection problem is structured using "preference analysis for reference ideal solution (PARIS)” approach in multiple criteria decision analysis (MCDMA). Systematic comparisons were made with existing MCDMA methods (PARIS, and TOPSIS) to verify the stability and accuracy of the results obtained. The proposed integrated MCDMA systematic approach is expected to address the issues encountered in the aircraft selection process. The comparative analysis results show that the proposed method is an effective and accurate tool that can help analysts make better strategic, tactical, and operational decisions.

Keywords: aircraft, military fighter aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS, Saab Gripen, Dassault Rafale, Eurofighter Typhoon

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Authors: K. Akilandeswari, G. M. Nasira

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Brain-Computer Interfaces (BCIs) measure brain signals activity, intentionally and unintentionally induced by users, and provides a communication channel without depending on the brain’s normal peripheral nerves and muscles output pathway. Feature Selection (FS) is a global optimization machine learning problem that reduces features, removes irrelevant and noisy data resulting in acceptable recognition accuracy. It is a vital step affecting pattern recognition system performance. This study presents a new Binary Particle Swarm Optimization (BPSO) based feature selection algorithm. Multi-layer Perceptron Neural Network (MLPNN) classifier with backpropagation training algorithm and Levenberg-Marquardt training algorithm classify selected features.

Keywords: Brain-Computer Interfaces (BCI), Feature Selection (FS), Walsh–Hadamard Transform (WHT), Binary Particle Swarm Optimization (BPSO), Multi-Layer Perceptron (MLP), Levenberg–Marquardt algorithm.

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Authors: Aik Heng Lee, Hamid Nikraz, Yung Tse Hung

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Decomposition processes take place in landfill generate leachates that can be categorized mainly of acetogenic and methanogenic in nature. BOD:COD ratio computed in this study for a landfill site over a 3 years duration revealed as a good indicator to identify acetogenic leachate from methanogenic leachate. Correlation relationships to predict pollutant level taking into consideration of climatic condition are derived.

Keywords: Acetogenic Leachate, Methanogenic Leachate, BOD:COD Ratio.

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Authors: Tunjo Perić, Marin Fatović

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In this paper a new methodology for vendor selection and supply quotas determination (VSSQD) is proposed. The problem of VSSQD is solved by the model that combines revised weighting method for determining the objective function coefficients, and a multiple objective linear programming (MOLP) method based on the cooperative game theory for VSSQD. The criteria used for VSSQD are: (1) purchase costs and (2) product quality supplied by individual vendors. The proposed methodology has been tested on the example of flour purchase for a bakery with two decision makers.

Keywords: Cooperative game theory, multiple objective linear programming, revised weighting method, vendor selection.

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

Abstract:

Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: Feature selection, multi-objective evolutionary computation, unsupervised classification, behavior assessment system for children.

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Authors: C. Ardil

Abstract:

Multiple criteria decision making analysis (MCDMA) methods are applied to many real - life problems in different fields of engineering science and technology. The "preference analysis for reference ideal solution (PARIS)" method is proposed for an efficient MCDMA evaluation of decision problems. The multiple criteria aircraft evaluation approach is based on the integrated the mean weight, entropy weight, PARIS, and TOPSIS method, which eliminates the subjective importance weight assignment process. The evaluation criteria were identified from an extensive literature review of aircraft selection process. The aim of this study is to propose an efficient methodology for handling the aircraft selection process in which the proposed method solves effectively the MCDMA problem. A numerical example is presented to demonstrate the applicability and validity of the proposed MCDMA approach. 

Keywords: aircraft selection, aircraft, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS, VIKOR, ELECTRE, PROMETHEE

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Authors: C. Ardil

Abstract:

This paper proposes entropic programming for the freighter aircraft selection problem using the multiple criteria decision analysis method. The study aims to propose a systematic and comprehensive framework by focusing on the perspective of freighter aircraft selection. In order to achieve this goal, an integrated entropic programming approach was proposed to evaluate and rank alternatives. The decision criteria and aircraft alternatives were identified from the research data analysis. The objective criteria weights were determined by the mean weight method and the standard deviation method. The proposed entropic programming model was applied to a practical decision problem for evaluating and selecting freighter aircraft. The proposed entropic programming technique gives robust, reliable, and efficient results in modeling decision making analysis problems. As a result of entropic programming analysis, Boeing B747-8F, a freighter aircraft alternative ( a3), was chosen as the most suitable freighter aircraft candidate.   

Keywords: entropic programming, additive weighted model, multiple criteria decision making analysis, MCDMA, TOPSIS, aircraft selection, freighter aircraft, Boeing B747-8F, Boeing B777F, Airbus A350F

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