Search results for: attribute selection

Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: Samina Khalid, Shamila Nasreen

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Dimensionality reduction as a preprocessing step to machine learning is effective in removing irrelevant and redundant data, increasing learning accuracy, and improving result comprehensibility. However, the recent increase of dimensionality of data poses a severe challenge to many existing feature selection and feature extraction methods with respect to efficiency and effectiveness. In the field of machine learning and pattern recognition, dimensionality reduction is important area, where many approaches have been proposed. In this paper, some widely used feature selection and feature extraction techniques have analyzed with the purpose of how effectively these techniques can be used to achieve high performance of learning algorithms that ultimately improves predictive accuracy of classifier. An endeavor to analyze dimensionality reduction techniques briefly with the purpose to investigate strengths and weaknesses of some widely used dimensionality reduction methods is presented.

Keywords: age related macular degeneration, feature selection feature subset selection feature extraction/transformation, FSA’s, relief, correlation based method, PCA, ICA

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Authors: Odd Jarl Borch, Marina Z. Solesvik

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The paper analyses partner selection approaches related to large scale R&D-based innovation projects at the different stages of development. We emphasize innovation projects in the maritime value chain and how partners are selected to improve quality according to high spec customer demands, and to reduce investment costs on new production technology such as advanced offshore service vessels. We elaborate on the differences in innovation approach and especially the role that purposive inflows and outflows of knowledge from external partners may be used to accelerate internal innovation. We present three cases related to different projects in terms of specificity and scope. We explore how the partner selection criteria change over time when the goals move from wide scope to a very specific R&D tasks.

Keywords: partner selection, innovation, offshore industry, concept design

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Authors: Niranjana Devi N.

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Test case selection is to select the subset of only the fit test cases and remove the unfit, ambiguous, redundant, unnecessary test cases which in turn improve the quality and reduce the cost of software testing. Test cases optimization is the problem of finding the best subset of test cases from a pool of the test cases to be audited. It will meet all the objectives of testing concurrently. But most of the research have evaluated the fitness of test cases only on single parameter fault detecting capability and optimize the test cases using a single objective. In the proposed approach, nine parameters are considered for test case selection and the best subset of parameters for test case selection is obtained using Interval Type-2 Fuzzy Rough Set. Test case selection is done in two stages. The first stage is the fuzzy entropy-based filtration technique, used for estimating and reducing the ambiguity in test case fitness evaluation and selection. The second stage is the ant colony optimization-based wrapper technique with a forward search strategy, employed to select test cases from the reduced test suite of the first stage. The results are evaluated using the Coverage parameters, Precision, Recall, F-Measure, APSC, APDC, and SSR. The experimental evaluation demonstrates that by this approach considerable computational effort can be avoided.

Keywords: ant colony optimization, fuzzy entropy, interval type-2 fuzzy rough set, test case selection

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Authors: Mehtap Dursun, Zeynep Şener

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Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment criteria. A house of quality (HOQ) which translates purchased product features into supplier assessment criteria is built using the weights obtained by DEMATEL approach to determine the desired levels of supplier assessment criteria. Supplier alternatives are ranked by a distance-based method.

Keywords: DEMATEL, group decision making, QFD, supplier selection

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Authors: Sahar Shahsavaripour Ghazanfarpour

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As our daily life depends on quality of built services by systems and using devices in our environment; so education and model of software′s quality will be so important. By daily growth in software′s systems and using them so much, progressing process and requirements′ evaluation in primary level of progress especially architecture level in software get more important. Modern driver architecture changes an in dependent model of a level into some specific models that their purpose is reducing number of software changes into an executive model. Process of designing software engineering is mid-automated. The needed quality attribute in designing architecture and quality attribute in representation are in architecture models. The main problem is the relationship between needs, and elements in some aspect with implicit models and input sources in process. It’s because there is no detection ability. The MART profile is use to describe real-time properties and perform plat form modeling.

Keywords: MDA, DW, OMG, UML, AKB, software architecture, ontology, evaluation

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Authors: Zheng Baichuan, Li Shenghui, Li Bingqian, Zhang Ning, Chen Kai

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Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons.

Keywords: knowledge graph, entity alignment, transformer, deep learning

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Authors: Saleem Abuleil, Khalid S. Alsamara

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Events represent a significant source of information on the web; they deliver information about events that occurred around the world in all kind of subjects and areas. These events can be collected and organized to provide valuable and useful information for decision makers, researchers, as well as any person seeking knowledge. In this paper, we discuss an ongoing research to target stock markets domain to observe and record changes (events) when they happen, collect them, understand the meaning of each one of them, and organize the information along with meaning in a well-structured format. By using Semantic Role Labeling (SRL) technique, we identified four factors for each event in this paper: verb of action and three roles associated with it, entity name, attribute, and attribute value. We have generated a set of rules and techniques to support our approach to analyze and understand the meaning of the events taking place in stock markets.

Keywords: natuaral language processing, Arabic language, event extraction and understanding, sematic role labeling, stock market

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Authors: Natasha Petrovska, Mirjana Pavlovic, Maria M. Larrondo-Petrie

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Neural stem cells (NSCs) are multi-potent, self-renewing cells that generate new neurons. Three subtypes of NSCs can be separated regarding the stages of NSC lineage: quiescent neural stem cells (qNSCs), activated neural stem cells (aNSCs) and neural progenitor cells (NPCs), but their gene expression signatures are not utterly understood yet. Single-cell examinations have started to elucidate the complex structure of NSC populations. Nevertheless, there is a lack of thorough molecular interpretation of the NSC lineage heterogeneity and an increasing need for tools to analyze and improve the efficiency and correctness of single-cell sequencing data. Feature selection and ordering can identify and classify the gene expression signatures of these subtypes and can discover novel subpopulations during the NSCs activation and differentiation processes. The aim here is to review the implementation of the feature selection technique on NSC subtypes and the classification techniques that have been used for the identification of gene expression signatures.

Keywords: feature selection, feature similarity, neural stem cells, genes, feature selection methods

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Authors: Mladen Hraste, Igor Jelaska, Ivan Granic

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The scope of this research is the identification and explanation of differences of three levels of water polo players in some parameters of effectiveness. The sample for this study was 132 matches of the Adriatic Water Polo League in the 2013/14 competition season. Using the Kruskal-Wallis test and multiple comparisons of mean ranks for all groups at the significance level of α=0, 05, the hypothesis that there are significant differences between groups of respondents in ten of the seventeen variables of effectiveness was confirmed. There is a reasonable possibility that the differences are caused by the degree of learned and implemented tactical knowledge, the degree of scoring ability and the best selection for certain roles in the team. The results of this study can be applied to selection of teams and players, for the selection of the appropriate match concept and for organizing training process.

Keywords: scoring abilities, selection, tactical knowledge, water polo effectiveness

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Authors: G. S. Thakur

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This paper presents a Fuzzy Soft Recruitment Model (FSRM) for faculty selection of MHRD technical institutions. The selection criteria are based on 4-tier flexible structure in the institutions. The Advisory Committee on Faculty Recruitment (ACoFAR) suggested nine criteria for faculty in the proposed FSRM. The model Fuzzy Soft is proposed with consultation of ACoFAR based on selection criteria. The Fuzzy Soft distance similarity measures are applied for finding best faculty from the applicant pool.

Keywords: fuzzy soft set, fuzzy sets, fuzzy soft distance, fuzzy soft similarity measures, ACoFAR

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Authors: Eylem Koç, Hasan Arda Burhan

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Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: analytic network process (ANP), BOCR, multi-actor decision making, multi-criteria decision making, real-life problem, location selection

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Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

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This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

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Authors: Gupta Amit, Kumar Ramesh, P. C. Tewari

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Globalization is putting enormous pressure on the business organizations specially manufacturing one to rethink the supply chain in innovative manners. Inventory consumes major portion of total sale revenue. Effective and efficient inventory management plays a vital role for the successful functioning of any organization. Selection of inventory policy is one of the important purchasing activities. This paper focuses on selection and ranking of alternative inventory policies. A deterministic quantitative model-based on Distance Based Approach (DBA) method has been developed for evaluation and ranking of inventory policies. We have employed this concept first time for this type of the selection problem. Four inventory policies Economic Order Quantity (EOQ), Just in Time (JIT), Vendor Managed Inventory (VMI) and monthly policy are considered. Improper selection could affect a company’s competitiveness in terms of the productivity of its facilities and quality of its products. The ranking of inventory policies is a multi-criteria problem. There is a need to first identify the selection criteria and then processes the information with reference to relative importance of attributes for comparison. Criteria values for each inventory policy can be obtained either analytically or by using a simulation technique or they are linguistic subjective judgments defined by fuzzy sets, like, for example, the values of criteria. A methodology is developed and applied to rank the inventory policies.

Keywords: inventory policy, ranking, DBA, selection criteria

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Authors: Ahmad Mohsin, Syda Fatima, Falak Nawaz, Aman Ullah Khan

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Selection of an appropriate architectural style is vital to the success of target web service under development. The nature of architecture design and selection for service-oriented computing applications is quite different as compared to traditional software. Web Services have complex and rigorous architectural styles to choose. Due to this, selection for accurate architectural style for web services development has become a more complex decision to be made by architects. Architectural style selection is a multi-criteria decision and demands lots of experience in service oriented computing. Decision support systems are good solutions to simplify the selection process of a particular architectural style. Our research suggests a new approach using DSS for selection of architectural styles while developing a web service to cater FRs and NFRs. Our proposed DSS helps architects to select right web service architectural pattern according to the domain and non-functional requirements. In this paper, a rule base DSS has been developed using CLIPS (C Language Integrated Production System) to support decisions using multi-criteria requirements. This DSS takes architectural characteristics, domain requirements and software architect preferences for NFRs as input for different architectural styles in use today in service-oriented computing. Weighted sum model has been applied to prioritize quality attributes and domain requirements. Scores are calculated using multiple criterions to choose the final architecture style.

Keywords: software architecture, web-service, rule-based, DSS, multi-criteria requirements, quality attributes

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Authors: Zainab S. Mahmood, Aisha H. Hashim, Wan Haslina Hassan, Farhat Anwar

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The wide use of the internet-based applications bring many challenges to the researchers to guarantee the continuity of the connections needed by the mobile hosts and provide reliable Internet access for them. One of proposed solutions by Internet Engineering Task Force (IETF) is to connect the local, multi-hop, and infrastructure-less Mobile Ad hoc Network (MANET) with Internet structure. This connection is done through multi-interface devices known as Internet Gateways. Many issues are related to this connection like gateway discovery, hand off, address auto-configuration and selecting the optimum gateway when multiple gateways exist. Many studies were done proposing gateway selection schemes with a single selection criterion or weighted multiple criteria. In this research, a review of some of these schemes is done showing the differences, the features, the challenges and the drawbacks of each of them.

Keywords: Internet Gateway, MANET, mobility, selection criteria

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Authors: Sarita Pinmanee, Saipan Krapbia, Rataya Yanaphan

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Hemp (Cannabis sativa L.) is multi-purpose crop delivering fibers, shives, and seed. The fiber is used today for special paper, insulation material, and biocomposites. This research was to improve low delta-9 Tetrahydrocannabinol (THC) hemp variety for high fiber contents. Mass selection for increased fiber content in four low THC Thai cultivars (including RPF1, RPF2, RPF3, and RPF4) was carried out in highland areas in the northern Thailand. Research work was conducted for three consecutive growing seasons during 2012 to 2014 at Pangda Royal Agricultural Station, Samoeng District, Chiang Mai Province, Thailand. Results of selection indicated that after selecting for three successive generations, the average fiber content of four low THC Thai cultivars increased to 28-36 %. The resulted of selection was found that fiber content of RPF1, RPF2, RPF3 and RPF4 increased to 20.6, 19.1, 19.9 and 22.8%, respectively. In addition, THC contents of these four varieties were 0.07, 0.138, 0.08 and 0.072 % respectively. As well, mass selection method was considered as an effective and suitable method for improving this fiber content.

Keywords: Hemp, mass selection, fiber content, low THC content

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Authors: Saniye Çeşmecioğlu

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The importance of project sustainability and success has become increasingly significant due to the proliferation of external environmental factors that have decreased project resistance in contemporary times. The primary approach to forestall the failure of projects is to ensure their long-term viability through the strategic selection of projects as creating judicious project selection framework within the organization. Decision-makers require precise decision contexts (models) that conform to the company's business objectives and sustainability expectations during the project selection process. The establishment of a rational model for project selection enables organizations to create a distinctive and objective framework for the selection process. Additionally, for the optimal implementation of this decision-making model, it is crucial to establish a Project Management Office (PMO) team and Project Steering Committee within the organizational structure to oversee the framework. These teams enable updating project selection criteria and weights in response to changing conditions, ensuring alignment with the company's business goals, and facilitating the selection of potentially viable projects. This paper presents a multi-criteria decision model for selecting project sustainability and project success criteria that ensures timely project completion and retention. The model was developed using MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) and was based on broadcaster companies’ expectations. The ultimate results of this study provide a model that endorses the process of selecting the appropriate project objectively by utilizing project selection and sustainability criteria along with their respective weights for organizations. Additionally, the study offers suggestions that may ascertain helpful in future endeavors.

Keywords: project portfolio management, project selection, multi-criteria decision making, project sustainability and success criteria, MACBETH

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Authors: Ming Lun Wang, Yan Wang, Ning Ruo Sun

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With the development of cloud computing, more and more users start to utilize the cloud storage service. However, there exist some issues: 1) cloud server steals the shared data, 2) sharers collude with the cloud server to steal the shared data, 3) cloud server tampers the shared data, 4) sharers and key generation center (KGC) conspire to steal the shared data. In this paper, we use advanced encryption standard (AES), hash algorithms, and accountable key-policy attribute-based encryption without key escrow (WOKE-AKP-ABE) to build a security cloud storage scheme. Moreover, the data are encrypted to protect the privacy. We use hash algorithms to prevent the cloud server from tampering the data uploaded to the cloud. Analysis results show that this scheme can resist conspired attacks.

Keywords: cloud storage security, sharing storage, attributes, Hash algorithm

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Authors: Mehdi Assefi, Keihan Hataminezhad

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One of the efficient architectures for exploring the resources in wireless ad-hoc networks is contact-based architecture. In this architecture, each node assigns a unique zone for itself and each node keeps all information from inside the zone, as well as some from outside the zone, which is called contact. Reducing the overlap between different zones of a node and its contacts increases its performance, therefore Edge Method (EM) is designed for this purpose. Contacts selected by EM do not have any overlap with their sources, but for choosing the contact a vast amount of information must be transmitted. In this article, we will offer a new protocol for contact selection, which is called PEM. The objective would be reducing the volume of transmitted information, using Non-Uniform Dissemination Probabilistic Protocols. Consumed energy for contact selection is a function of the size of transmitted information between nodes. Therefore, by reducing the content of contact selection message using the PEM will decrease the consumed energy. For evaluation of the PEM we applied the simulation method. Results indicated that PEM consumes less energy compared to EM, and by increasing the number of nodes (level of nodes), performance of PEM will improve in comparison with EM.

Keywords: wireless ad-hoc networks, contact selection, method for CARD, energy-efficient

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Authors: Brian W. Mandikiana

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Homestead food production has the potential to alleviate hunger, improve health and nutrition for children and adults. This article examines the relationship between self-reported hunger and homestead food production using the ordered probit model. A sample of households participating in homestead food production was drawn from the first wave of the South African National Income Dynamics Survey, a nationally representative cross-section. The sample selection problem was corrected using an ordered probit model with sample selection approach. The findings show that homestead food production exerts a positive and significant impact on children and adults’ ability to cope with hunger and malnutrition. Yet, on the contrary, potential gains of homestead food production are threatened by shocks such as crop failure.

Keywords: agriculture, hunger, nutrition, sample selection

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Authors: Samah Benmerbi, Kamal Amroun, Abdelkamel Tari

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The increasing number of Web service (WS)providers throughout the globe, have produced numerous Web services providing the same or similar functionality. Therefore, there is a need of tools developing the best answer of queries by selecting and composing services with total transparency. This paper reviews various QoS based Web service selection mechanisms and architectures which facilitate qualitatively optimal selection, in other fact Web service composition is required when a request cannot be fulfilled by a single web service. In such cases, it is preferable to integrate existing web services to satisfy user’s request. We introduce an automatic Web service composition method based on hypergraph decomposition using hypertree decomposition method. The problem of selection and the composition of the web services is transformed into a resolution in a hypertree by exploring the relations of dependency between web services to get composite web service via employing an execution order of WS satisfying global request.

Keywords: web service, web service selection, web service composition, QoS, hypergraph decomposition, BE hypergraph decomposition, hypertree resolution

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

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Authors: Mine Koyaz, M. Cem Altun

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Selection of the materials satisfying the expected performances is significantly important for any design. Today, with the constantly evolving and developing technologies, the material options are so wide that the necessity of the use of some support tools in the selection process is arising. Therefore, as a sub process of building element design, a systematic material selection tool is developed, that defines four main steps of the material selection; definition, research, comparison and decision. The main purpose of the tool is being an educational instrument that would show a methodic way of material selection in architectural detailing for the use of architecture students. The tool predefines the possible uses of various material databases and other sources of information on material properties. Hence, it is to be used as a guidance for designers, especially with a limited material knowledge and experience. The material selection tool not only embraces technical properties of materials related with building elements’ functional requirements, but also its sensual properties related with the identity of design and its environmental impacts with respect to the sustainability of the design. The method followed in the development of the tool has two main sections; first the examination and application of the existing methods and second the development of trial versions and their applications. Within the scope of the existing methods; design support tools, methodic approaches for the building element design and material selection process, material properties, material databases, methodic approaches for the decision making process are examined. The existing methods are applied by architecture students and newly graduate architects through different design problems. With respect to the results of these applications, strong and weak sides of the existing material selection tools are presented. A main flow chart of the material selection tool has been developed with the objective to apply the strong aspects of the existing methods and develop their weak sides. Through different stages, a different aspect of the material selection process is investigated and the tool took its final form. Systematic material selection tool, within the building element design process, guides the users with a minimum background information, to practically and accurately determine the ideal material that is to be chosen, satisfying the needs of their design. The tool has a flexible structure that answers different needs of different designs and designers. The trial version issued in this paper shows one of the paths that could be followed and illustrates its application over a design problem.

Keywords: architectural education, building element design, material selection tool, systematic approach

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Authors: Tayyaba Hussain, Sobia Jangsher, Saqib Ali, Saqib Ejaz

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Unmanned Aerial vehicles (UAV’s) have gained great popularity due to their remoteness, ease of deployment and high maneuverability in different applications like real-time surveillance, image capturing, weather atmospheric studies, disaster site monitoring and mapping. These applications can involve a real-time communication with the ground station. However, altitude and mobility possess a few challenges for the communication. UAV’s at high altitude usually require more transmit power. One possible solution can be with the use of multi hops (UAV’s acting as relays) and exploiting the mobility pattern of the UAV’s. In this paper, we studied a relay (UAV’s acting as relays) selection for a reliable transmission to a destination UAV. We exploit the mobility information of the UAV’s to propose a Mobility-Aware Relay Selection (MARS) algorithm with the objective of giving improved data rates. The results are compared with Non Mobility-Aware relay selection scheme and optimal values. Numerical results show that our proposed MARS algorithm gives 6% better achievable data rates for the mobile UAV’s as compared with Non MobilityAware relay selection scheme. On average a decrease of 20.2% in data rate is achieved with MARS as compared with SDP solver in Yalmip.

Keywords: mobility aware, relay selection, time division multiple acess, unmanned aerial vehicle

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Authors: Subhash Chandra Sharma, Mohammad Soleimani

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Selection of the correct lubricant for the top of rail application is a complex process. In this paper, the selection of the proper lubricant for a Top-Of-Rail (TOR) lubrication system based on graph theory and matrix approach has been developed. Attributes influencing the selection process and their influence on each other has been represented through a digraph and an equivalent matrix. A matrix function which is called the Permanent Function is derived. By substituting the level of inherent contribution of the influencing parameters and their influence on each other qualitatively, a criterion called Suitability Index is derived. Based on these indices, lubricants can be ranked for their suitability. The proposed model can be useful for maintenance engineers in selecting the best lubricant for a TOR application. The proposed methodology is illustrated step–by-step through an example.

Keywords: lubricant selection, top of rail lubrication, graph-theory, Ranking of lubricants

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: Amirhossein Mahlouji

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In current business market, the concept of integrating environmental sustainability into long-term as well as routine operations is becoming a prevailing trend. Therefore, several stimuli are helping organization to move toward environmental sustainability. The concept of green supply chain management can help provide a strategic framework to develop a customized sustainability roadmap for each organization. In this regard, this paper is mainly focused on presenting a strategic decision making framework that will assist top level decision-making issues. This decision-making tool is based on literature and practice in the area of environmentally conscious business practices. The goal of this paper will be on the components and parameters of green supply chain management and how they serve as a baseline for the decision framework. Later, the applicability of a multi-input multi-output decision model (MIMO), will be analyzed as the analytical network process, within the green supply chain.

Keywords: Multi-attribute, Green Supply Chain, Environmental, Sustainability

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Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

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This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine data set, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: artificial neural network, bees algorithm, feature selection, Holon

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Authors: Synthia A. Sari

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The transparent nomination and selection process is the first step to obtaining qualified members of board. It is believed as the representative (agent) of the owners, members of the board must consist of competent and professional people. However, the development of transparent and ideal nomination and selection process in Indonesian State-owned enterprises (SOEs) has been based on relatively little research. Considering the relative importance attached by boards to conduct their roles in their principal’s interest in a variety of governance tasks in state-owned enterprises, the primary aim of this paper is to shed light on the extent of nomination and selection process impact performance of the board in implementing good corporate governance in Indonesian SOEs. The exploratory nature of this study led to the adoption of a qualitative research methodology which uses semi-structured interviews and publically available documents to collect a range of data pertaining board nomination and selection and the work of boards. Interviews were conducted with four informants from three Indonesian SOEs and Ministry of SOEs. Findings in this study demonstrate unclear job description and expectations board members as a result of unclear functions of the board in Indonesian SOEs make transparent and accountable nomination and selection process hard to conduct. This situation is vulnerable to the influences from political interest and that even the process itself can degenerate into situations of political interference. In the end, it leads to choosing the wrong person for membership of the board. This study makes a significant contribution to several fields; the human resource management, corporate governance, and Southeast studies by addressing the basic research gaps of board selection process issues in Indonesian SOEs. The gap is addressed by providing a more coherent framework for effective nomination and selection system which reflects more clearly the real experiences of those actually involved at board level.

Keywords: board selection and nomination process, Indonesian stated-owned enterprises, good corporate governance, political influence

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