Search results for: Quality frame selection

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: Carrie Ho, Darshana J. Kumar

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Urbanization has been found to impact stormwater runoff quantity and quality. A study catchment with mixed land use, residential and industrial were investigated and the water quality discharged from the catchment were sampled and tested for four basic water quality parameters; BOD5, NH3-N, NO3-N and P. One dry weather flow and several stormwater runoff were sampled. Results were compared to the USEPA stormwater quality benchmark values and the Interim National Water Quality Standards for Malaysia (INWQS). The concentration of the parameters was found to vary significantly between storms and the pollutant of concern was found to be NO3-N.

Keywords: Mixed land-use, urban runoff, water quality.

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Authors: Khin May Win, Nan Sai Moon Kham

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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: Afef Salhi, Ameni Yengui Jammaoussi

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This paper presents a implementation of an object tracking system in a video sequence. This object tracking is an important task in many vision applications. The main steps in video analysis are two: detection of interesting moving objects and tracking of such objects from frame to frame. In a similar vein, most tracking algorithms use pre-specified methods for preprocessing. In our work, we have implemented several object tracking algorithms (Meanshift, Camshift, Kalman filter) with different preprocessing methods. Then, we have evaluated the performance of these algorithms for different video sequences. The obtained results have shown good performances according to the degree of applicability and evaluation criteria.

Keywords: Tracking, meanshift, camshift, Kalman filter, evaluation.

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Authors: Takumi Ito, Kurumi Kurokawa, Dong Hang Wu, Takashi Nagumo, Haruhiko Hirata

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The structural system of wooden house by two-by-four method is widely adopted in any countries, and a various type of vibration control system for building structures has been developed on country with frequent earthquake. In this study, a vibration control device called “Scaling Frame” (SF) is suggested, and which is applied to wooden two-by-four method structures. This paper performs the experimental study to investigate the restoring force characteristics of two-by-four with SF device installed. The seismic resistant performance is estimated experimentally, and also the applicability and effectiveness are discussing.

Keywords: Two-by-four method, seismic vibration control, horizontally loading test, restoring force characteristics.

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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: Yu Ren Lin, Yi Feng Su

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Using vision based solution in intelligent vehicle application often needs large memory to handle video stream and image process which increase complexity of hardware and software. In this paper, we present a FPGA implement of a vision based lane departure warning system. By taking frame of videos, the line gradient of line is estimated and the lane marks are found. By analysis the position of lane mark, departure of vehicle will be detected in time. This idea has been implemented in Xilinx Spartan6 FPGA. The lane departure warning system used 39% logic resources and no memory of the device. The average availability is 92.5%. The frame rate is more than 30 frames per second (fps).

Keywords: Lane departure warning system, image, FPGA.

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

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 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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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: Benjamin Kuester, Bjoern Eilert, Malte Stonis, Ludger Overmeyer

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Increasing quality requirements make reliable and effective quality management indispensable. This includes the complaint handling in which the 8D method is widely used. The 8D report as a written documentation of the 8D method is one of the key quality documents as it internally secures the quality standards and acts as a communication medium to the customer. In practice, however, the 8D report is mostly faulty and of poor quality. There is no quality control of 8D reports today. This paper describes the use of natural language processing for the automated evaluation of 8D reports. Based on semantic analysis and text-mining algorithms the presented system is able to uncover content and formal quality deficiencies and thus increases the quality of the complaint processing in the long term.

Keywords: 8D report, complaint management, evaluation system, text-mining.

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Authors: P. M. Arun Kumar, S. Chandramathi

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The proliferation of multimedia technology and services in today’s world provide ample research scope in the frontiers of visual signal processing. Wide spread usage of video based applications in heterogeneous environment needs viable methods of Video Quality Assessment (VQA). The evaluation of video quality not only depends on high QoS requirements but also emphasis the need of novel term ‘QoE’ (Quality of Experience) that perceive video quality as user centric. This paper discusses two vital video quality assessment methods namely, subjective and objective assessment methods. The evolution of various video quality metrics, their classification models and applications are reviewed in this work. The Mean Opinion Score (MOS) based subjective measurements and algorithm based objective metrics are discussed and their challenges are outlined. Further, this paper explores the recent progress of VQA in emerging technologies such as mobile video and 3D video.

Keywords: 3D-Video, no reference metric, quality of experience, video quality assessment, video quality metrics.

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Authors: B. O. Olawale, C. R. Chatwin, R. C. D. Young, P. M. Birch, F. O. Faithpraise, A. O. Olukiran

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In this paper, we present a four-step ortho-rectification procedure for real-time geo-referencing of video data from a low-cost UAV equipped with a multi-sensor system. The basic procedures for the real-time ortho-rectification are: (1) decompilation of the video stream into individual frames; (2) establishing the interior camera orientation parameters; (3) determining the relative orientation parameters for each video frame with respect to each other; (4) finding the absolute orientation parameters, using a self-calibration bundle and adjustment with the aid of a mathematical model. Each ortho-rectified video frame is then mosaicked together to produce a mosaic image of the test area, which is then merged with a well referenced existing digital map for the purpose of geo-referencing and aerial surveillance. A test field located in Abuja, Nigeria was used to evaluate our method. Video and telemetry data were collected for about fifteen minutes, and they were processed using the four-step ortho-rectification procedure. The results demonstrated that the geometric measurement of the control field from ortho-images is more accurate when compared with those from original perspective images when used to pin point the exact location of targets on the video imagery acquired by the UAV. The 2-D planimetric accuracy when compared with the 6 control points measured by a GPS receiver is between 3 to 5 metres.

Keywords: Geo-referencing, ortho-rectification, video frame, self-calibration, UAV, target tracking.

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Authors: Hmway Hmway Tar, Thi Thi Soe Nyaunt

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Documents clustering become an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering technique play core topics. Text clustering or shortly clustering is about discovering semantically related groups in an unstructured collection of documents. Clustering has been very popular for a long time because it provides unique ways of digesting and generalizing large amounts of information. One of the issues of clustering is to extract proper feature (concept) of a problem domain. The existing clustering technology mainly focuses on term weight calculation. To achieve more accurate document clustering, more informative features including concept weight are important. Feature Selection is important for clustering process because some of the irrelevant or redundant feature may misguide the clustering results. To counteract this issue, the proposed system presents the concept weight for text clustering system developed based on a k-means algorithm in accordance with the principles of ontology so that the important of words of a cluster can be identified by the weight values. To a certain extent, it has resolved the semantic problem in specific areas.

Keywords: Clustering, Concept Weight, Document clustering, Feature Selection, Ontology

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Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: Structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures.

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Authors: C. Ardil

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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: Daniele Losanno, Giorgio Serino

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This paper focuses on parametric analysis of reinforced concrete structures equipped with supplemental damping braces. Practitioners still luck sufficient data for current design of damper added structures and often reduce the real model to a pure damper braced structure even if this assumption is neither realistic nor conservative. In the present study, the damping brace is modelled as made by a linear supporting brace connected in series with the viscous/hysteretic damper. Deformation capacity of existing structures is usually not adequate to undergo the design earthquake. In spite of this, additional dampers could be introduced strongly limiting structural damage to acceptable values, or in some cases, reducing frame response to elastic behavior. This work is aimed at providing useful considerations for retrofit of existing buildings by means of supplemental damping braces. The study explicitly takes into consideration variability of (a) relative frame to supporting brace stiffness, (b) dampers’ coefficient (viscous coefficient or yielding force) and (c) non-linear frame behavior. Non-linear time history analysis has been run to account for both dampers’ behavior and non-linear plastic hinges modelled by Pivot hysteretic type. Parametric analysis based on previous studies on SDOF or MDOF linear frames provide reference values for nearly optimal damping systems design. With respect to bare frame configuration, seismic response of the damper-added frame is strongly improved, limiting deformations to acceptable values far below ultimate capacity. Results of the analysis also demonstrated the beneficial effect of stiffer supporting braces, thus highlighting inadequacy of simplified pure damper models. At the same time, the effect of variable damping coefficient and yielding force has to be treated as an optimization problem.

Keywords: Brace stiffness, dissipative braces, non-linear analysis, plastic hinges, reinforced concrete.

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Authors: Antonios Paraskevas, Michael Madas

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For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes on the multi-criteria nature of the problem and on how decision makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of significant degree of ambiguity and indeterminacy observed in decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model stands out within the realm of related literature as one of the few studies to employ N-DM in the context of academic staff selection. As a case study, it was decided to use our method to a real problem of academic personnel selection, having as main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherit ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: Analytical Hierarchy Process, Delphi Method, Multi-criteria decision making methods, neutrosophic set theory, personnel recruitment.

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Authors: Cigdem Safak Saglam

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Most thermal power plants use steam as working fluid in their power cycle. Therefore, in addition to fuel, water is the other main input for thermal plants. Water and steam must be highly pure in order to protect the systems from corrosion, scaling and biofouling. Pure process water is produced in water treatment plants having many several treatment methods. Treatment plant design is selected depending on raw water source and required water quality. Although working principle of fossil-fuel fired thermal power plants are same, there is no standard design and equipment arrangement valid for all thermal power plant utility systems. Besides that, there are many other technology evaluation and selection criteria for designing the most optimal water systems meeting the requirements such as local conditions, environmental restrictions, electricity and other consumables availability and transport, process water sources and scarcity, land use constraints etc. Aim of this study is explaining the adopted methodology for technology selection for process water preparation and industrial waste water treatment plant in a thermal power plant project located in Tufanbeyli, Adana Province in Turkey. Thermal power plant is fired with indigenous lignite coal extracted from adjacent lignite reserves. This paper addresses all above-mentioned factors affecting the thermal power plant water treatment facilities (demineralization + waste water treatment) design and describes the ultimate design of Tufanbeyli Thermal Power Plant Water Treatment Plant.

Keywords: Thermal power plant, lignite coal, pre-treatment, demineralization, electrodialysis, recycling, waste water, process water.

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Authors: M. K. Bhuyan

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The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4, with each VOP corresponding to one semantically meaningful hand position. Next, the key VOPs are selected on the basis of the amount of change in hand shape – for a given key frame in the sequence the next key frame is the one in which the hand changes its shape significantly. Thus, an entire video clip is transformed into a small number of representative frames that are sufficient to represent a gesture sequence. Subsequently, we model a particular gesture as a sequence of key frames each bearing information about its duration. These constitute a finite state machine. For recognition, the states of the incoming gesture sequence are matched with the states of all different FSMs contained in the database of gesture vocabulary. The core idea of our proposed representation is that redundant frames of the gesture video sequence bear only the temporal information of a gesture and hence discarded for computational efficiency. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction, subsequent gesture summarization and finally gesture recognition.

Keywords: Hand gesture, MPEG-4, Hausdorff distance, finite state machine.

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

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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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Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

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In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.

Keywords: Green supplier selection, expert system, ranking approach, interval-valued hesitant fuzzy setting.

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Authors: Bachir Bentouati, Lakhdar Chaib, Saliha Chettih, Gai-Ge Wang

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The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

Keywords: Stud Krill Herd, economic dispatch, crossover, stud selection, valve-point effect.

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Authors: F. Hejazi, J. Noorzaei, M. S. Jaafar, A. A. Abang Abdullah

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This paper describes the development of a numerical finite element algorithm used for the analysis of reinforced concrete structure equipped with shakes energy absorbing device subjected to earthquake excitation. For this purpose a finite element program code for analysis of reinforced concrete frame buildings is developed. The performance of developed program code is evaluated by analyzing of a reinforced concrete frame buildings model. The results are show that using damper device as seismic energy dissipation system effectively can reduce the structural response of framed structure during earthquake occurrence.

Keywords: Viscous Damper, finite element, program coding

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Authors: Kateřina Struhařová

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The paper gives the evidence of quality of accounting information of Czech private companies. In general the private companies in the Czech Republic do not see the benefits of providing accounting information of high quality. Based on the research of financial statements of entrepreneurs and companies in Zlin region it was confirmed that the quality of accounting information differs among the private entities and that the major impact on the accounting information quality has the fact if the financial statements are audited as well as the size of the entity. Also the foreign shareholders and lenders have some impact on the accounting information quality.

Keywords: Accounting information quality, Financial Statements, Czech Republic.

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Authors: Myunghoun Jang, Yongkyu Yi

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Appropriate selection of lifting equipments for a high-rise building construction project is one of the important factors to the project’s success. Proper position of a tower crane on a construction site is so important to be determined by an expert or an experienced construction manager who draws working range of a tower crane and moves it over a 2D (dimensional) site layout plan. But it is not usual to use 3D CAD, BIM or virtual reality for temporary facility planning or selection of a tower crane. This study proposes a method to use augmented reality to select proper position of tower cranes. An augmented reality prototype is implemented on a smart device to verify the practicability of the proposed method.

Keywords: Augmented Reality, Construction Planning, Site Layout, Temporary Facility Management, Tower Crane

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Authors: Atul Dev, Pankaj Jha

Abstract:

Dr. Genichi Taguchi looked at quality in a broader term and gave an excellent definition of quality in terms of loss to society. However the scope of this definition is limited to the losses imparted by a poor quality product to the customer only and are considered during the useful life of the product and further in a certain situation this loss can even be zero. In this paper, it has been proposed that the scope of quality of a product shall be further enhanced by considering the losses imparted by a poor quality product to society at large, due to associated environmental and safety related factors, over the complete life cycle of the product. Moreover, though these losses can be further minimized with the use of techno-safety interventions, the net losses to society however can never be made zero. This paper proposes an entirely new approach towards defining product quality and is based on Taguchi’s definition of quality.

Keywords: Existing concept, goal post philosophy, life cycle, proposed concept, quality loss function.

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