Search results for: fuzzy linear regression

Authors: Wen-Pai Wang, Mei-Ching Tang

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The service sector continues to grow and the percentage of GDP accounted for by service industries keeps increasing. The growth and importance of service to an economy is not just a phenomenon of advanced economies, service is now a majority of the world gross domestic products. However, the performance evaluation process of new service development problems generally involves uncertain and imprecise data. This paper presents a 2-tuple fuzzy linguistic computing approach to dealing with heterogeneous information and information loss problems while the processes of subjective evaluation integration. The proposed method based on group decision-making scenario to assist business managers in measuring performance of new service development manipulates the heterogeneity integration processes and avoids the information loss effectively.

Keywords: Heterogeneity, Multigranular linguistic computing, New service development, Performance evaluation.

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Authors: M. Kalamani, S. Valarmathy, M. Krishnamoorthi

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In this paper, Fuzzy C-Means clustering with Expectation Maximization-Gaussian Mixture Model based hybrid modeling algorithm is proposed for Continuous Tamil Speech Recognition. The speech sentences from various speakers are used for training and testing phase and objective measures are between the proposed and existing Continuous Speech Recognition algorithms. From the simulated results, it is observed that the proposed algorithm improves the recognition accuracy and F-measure up to 3% as compared to that of the existing algorithms for the speech signal from various speakers. In addition, it reduces the Word Error Rate, Error Rate and Error up to 4% as compared to that of the existing algorithms. In all aspects, the proposed hybrid modeling for Tamil speech recognition provides the significant improvements for speechto- text conversion in various applications.

Keywords: Speech Segmentation, Feature Extraction, Clustering, HMM, EM-GMM, CSR.

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian Automotive Sector, Stock Market Decisions, Equity Portfolio Analysis, Decision Tree Classifiers, Statistical Data Analysis.

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Authors: T. Yamaguchi, Y. Kurosawa, S. Maruyama, K. Tobita, Y. Hirano, K. Yokouchi, K. Kihara, T. Sunaga

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This paper describes dynamic analysis using proposed fast finite element method for a shock absorbing structure including a sponge. The structure is supported by nonlinear concentrated springs. The restoring force of the spring has cubic nonlinearity and linear hysteresis damping. To calculate damping properties for the structures including elastic body and porous body, displacement vectors as common unknown variable are solved under coupled condition. Under small amplitude, we apply asymptotic method to complex eigenvalue problem of this system to obtain modal parameters. And then expressions of modal loss factor are derived approximately. This approach was proposed by one of the authors previously. We call this method as Modal Strain and Kinetic Energy Method (MSKE method). Further, using the modal loss factors, the discretized equations in physical coordinate are transformed into the nonlinear ordinary coupled equations using normal coordinate corresponding to linear natural modes. This transformation yields computation efficiency. As a numerical example of a shock absorbing structures, we adopt double skins with a sponge. The double skins are supported by nonlinear concentrated springs. We clarify influences of amplitude of the input force on nonlinear and chaotic responses.

Keywords: Dynamic response, Nonlinear and chaotic motions, Finite Element analysis, Numerical analysis.

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Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

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This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system.

Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, Fault location, Underground Cable, Wavelet Transform.

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Authors: T. Yamaguchi, Y. Fujii, A. Takita, T. Kanai

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To compute dynamic characteristics of nonlinear viscoelastic springs with elastic structures having huge degree-of-freedom, Yamaguchi proposed a new fast numerical method using finite element method [1]-[2]. In this method, restoring forces of the springs are expressed using power series of their elongation. In the expression, nonlinear hysteresis damping is introduced. In this expression, nonlinear complex spring constants are introduced. Finite element for the nonlinear spring having complex coefficients is expressed and is connected to the elastic structures modeled by linear solid finite element. Further, to save computational time, the discrete equations in physical coordinate are transformed into the nonlinear ordinary coupled equations using normal coordinate corresponding to linear natural modes. In this report, the proposed method is applied to simulation for impact responses of a viscoelastic shock absorber with an elastic structure (an S-shaped structure) by colliding with a concentrated mass. The concentrated mass has initial velocities and collides with the shock absorber. Accelerations of the elastic structure and the concentrated mass are measured using Levitation Mass Method proposed by Fujii [3]. The calculated accelerations from the proposed FEM, corresponds to the experimental ones. Moreover, using this method, we also investigate dynamic errors of the S-shaped force transducer due to elastic mode in the S-shaped structure.

Keywords: Transient response, Finite Element analysis, Numerical analysis, Viscoelastic shock absorber, Force transducer.

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Authors: M. H. M. Rashid

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Given H a Hilbert space and B(H) the algebra of bounded linear operator in H, let δAB denote the generalized derivation defined by A and B. The main objective of this article is to study Weyl type theorems for generalized derivation for (A,B) satisfying a couple of Fuglede.

Keywords: Fuglede Property, Weyl’s theorem, generalized derivation, Aluthge Transformation.

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Authors: Görkem Arslan Kılınç

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Due to the high construction, operation, and maintenance costs of tall buildings, quantification of the area in the plan layout which provides a financial return is an important design criterion. The area of the “core and the structural system elements” does not provide financial return but must exist in the plan layout. Some characteristic items of tall office buildings affect the size of these areas. From this point of view, 15 tall office buildings were systematically investigated. The typical office floor plans of these buildings were re-produced digitally. The area of the “core and the structural system elements” in each building and the characteristic items of each building were calculated. These characteristic items are the size of the long and short plan edge, plan length/width ratio, size of the core long and short edge, core length/width ratio, core area, slenderness, building height, number of floors, and floor height. These items were analyzed by correlation and regression analyses. Results of this paper put forward that; characteristic items which affect the area of "core and structural system elements" are plan long and short edge size, core short edge size, building height, and the number of floors. A one-unit increase in plan short side size increases the area of the "core and structural system elements" in the plan by 12,378 m2. An increase in core short edge size increases the area of the core and structural system elements in the plan by 25,650 m2. Subsequent studies can be conducted by expanding the sample of the study and considering the geographical location of the building.

Keywords: Core area, correlation analysis, floor area, regression analysis, space efficiency, tall office buildings.

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: Deregulated energy market, forecasting, machine learning, system marginal price, energy efficiency and quality.

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Authors: Wen-Pai Wang

Abstract:

The growing influence of service industries has prompted greater attention being paid to service operations management. However, service managers often have difficulty articulating the veritable effects of their service innovation. Especially, the performance evaluation process of service innovation problems generally involves uncertain and imprecise data. This paper presents a 2-tuple fuzzy linguistic computing approach to dealing with heterogeneous information and information loss problems while the processes of subjective evaluation integration. The proposed method based on group decision-making scenario to assist business managers in measuring performance of service innovation manipulates the heterogeneity integration processes and avoids the information loss effectively.

Keywords: Group decision-making, Heterogeneity, Linguisticcomputing, Multi-criteria, Service innovation

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Authors: A. M. Alaskari, S. E. Oraby

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The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of the different elements of the system: tool-machineworkpart- cutting parameters. However, one of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Time-dependent modeling is beneficial when modern machining systems, such as adaptive control techniques are considered, where the state of the machined surface and the health of the cutting edge are monitored, assessed and controlled online using realtime information provided by the variability encountered in the measured force signals. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge-s random deformation.

Keywords: Dynamic force signals, surface roughness (finish), tool wear and deformation, tool wear modes (nose, flank)

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Authors: Vitomir Struc, Nikola Pavesic

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Over the past decades, automatic face recognition has become a highly active research area, mainly due to the countless application possibilities in both the private as well as the public sector. Numerous algorithms have been proposed in the literature to cope with the problem of face recognition, nevertheless, a group of methods commonly referred to as appearance based have emerged as the dominant solution to the face recognition problem. Many comparative studies concerned with the performance of appearance based methods have already been presented in the literature, not rarely with inconclusive and often with contradictory results. No consent has been reached within the scientific community regarding the relative ranking of the efficiency of appearance based methods for the face recognition task, let alone regarding their susceptibility to appearance changes induced by various environmental factors. To tackle these open issues, this paper assess the performance of the three dominant appearance based methods: principal component analysis, linear discriminant analysis and independent component analysis, and compares them on equal footing (i.e., with the same preprocessing procedure, with optimized parameters for the best possible performance, etc.) in face verification experiments on the publicly available XM2VTS database. In addition to the comparative analysis on the XM2VTS database, ten degraded versions of the database are also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in "real-life" operating conditions. Our experimental results suggest that linear discriminant analysis ensures the most consistent verification rates across the tested databases.

Keywords: Biometrics, face recognition, appearance based methods, image degradations, the XM2VTS database.

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Authors: Ferhat Erdal, Osman Tunca, Serkan Tas, Serdar Carbas

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Web-expanded steel beams provide an easy and economical solution for the systems having longer structural members. The main goal of manufacturing these beams is to increase the moment of inertia and section modulus, which results in greater strength and rigidity. Until recently, there were two common types of open web-expanded beams: with hexagonal openings, also called castellated beams, and beams with circular openings referred to as cellular beams, until the generation of sinusoidal web-expanded beams. In the present research, the optimum design of a new generation beams, namely sinusoidal web-expanded beams, will be carried out and the design results will be compared with castellated and cellular beam solutions. Thanks to a reduced fabrication process and substantial material savings, the web-expanded beam with sinusoidal holes (Angelina™ Beam) meets the economic requirements of steel design problems while ensuring optimum safety. The objective of this research is to carry out non-linear finite element analysis (FEA) of the web-expanded beam with sinusoidal holes. The FE method has been used to predict their entire response to increasing values of external loading until they lose their load carrying capacity. FE model of each specimen that is utilized in the experimental studies is carried out. These models are used to simulate the experimental work to verify of test results and to investigate the non-linear behavior of failure modes such as web-post buckling, shear buckling and vierendeel bending of beams.

Keywords: Steel structures, web-expanded beams, Angelina™ beam, optimum design, failure modes, finite element analysis.

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Authors: Catalin Gales, Ionel Dumitrel Ghiba

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This paper studies questions of continuous data dependence and uniqueness for solutions of initial boundary value problems in linear micropolar thermoelastic mixtures. Logarithmic convexity arguments are used to establish results with no definiteness assumptions upon the internal energy.

Keywords: Cellular materials, continuous dependence, micro polar mixtures, uniqueness.

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Authors: Seung You Na, Daejung Shin, Jin Young Kim, Joo Hyun Jung, Yong-Gwan Won

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To explore pipelines is one of various bio-mimetic robot applications. The robot may work in common buildings such as between ceilings and ducts, in addition to complicated and massive pipeline systems of large industrial plants. The bio-mimetic robot finds any troubled area or malfunction and then reports its data. Importantly, it can not only prepare for but also react to any abnormal routes in the pipeline. The pipeline monitoring tasks require special types of mobile robots. For an effective movement along a pipeline, the movement of the robot will be similar to that of insects or crawling animals. During its movement along the pipelines, a pipeline monitoring robot has an important task of finding the shapes of the approaching path on the pipes. In this paper we propose an effective solution to the pipeline pattern recognition, based on the fuzzy classification rules for the measured IR distance data.

Keywords: Bio-mimetic robots, Plant pipes monitoring, Pipepattern recognition.

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Authors: M. Moeinaddini, Z. Asadi-Shekari, Z. Sultan, M. Zaly Shah

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Happiness can be related to everything that can provide a feeling of satisfaction or pleasure. This study tries to consider the relationship between land use factors and feeling of happiness at the neighbourhood level. Land use variables (beautiful and attractive neighbourhood design, availability and quality of shopping centres, sufficient recreational spaces and facilities, and sufficient daily service centres) are used as independent variables and the happiness score is used as the dependent variable in this study. In addition to the land use variables, socio-economic factors (gender, race, marital status, employment status, education, and income) are also considered as independent variables. This study uses the Oxford happiness questionnaire to estimate happiness score of more than 300 people living in six neighbourhoods. The neighbourhoods are selected randomly from Skudai neighbourhoods in Johor, Malaysia. The land use data were obtained by adding related questions to the Oxford happiness questionnaire. The strength of the relationship in this study is found using generalised linear modelling (GLM). The findings of this research indicate that increase in happiness feeling is correlated with an increasing income, more beautiful and attractive neighbourhood design, sufficient shopping centres, recreational spaces, and daily service centres. The results show that all land use factors in this study have significant relationship with happiness but only income, among socio-economic factors, can affect happiness significantly. Therefore, land use factors can affect happiness in Skudai more than socio-economic factors.

Keywords: Neighbourhood land use, neighbourhood design, happiness, socio-economic factors, generalised linear modelling.

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Authors: T. S. Chou, K. K. Yen, J. Luo

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The network traffic data provided for the design of intrusion detection always are large with ineffective information and enclose limited and ambiguous information about users- activities. We study the problems and propose a two phases approach in our intrusion detection design. In the first phase, we develop a correlation-based feature selection algorithm to remove the worthless information from the original high dimensional database. Next, we design an intrusion detection method to solve the problems of uncertainty caused by limited and ambiguous information. In the experiments, we choose six UCI databases and DARPA KDD99 intrusion detection data set as our evaluation tools. Empirical studies indicate that our feature selection algorithm is capable of reducing the size of data set. Our intrusion detection method achieves a better performance than those of participating intrusion detectors.

Keywords: Intrusion detection, feature selection, k-nearest neighbors, fuzzy clustering, Dempster-Shafer theory

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Authors: Ayman M. Mansour

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In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Keywords: Fuzzy Logic, Inference system, Monitoring system, Multi-agent system.

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Authors: Khalil Shihab, Nida Al-Chalabi

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This article describes Uruk, the virtual museum of Iraq that we developed for visual exploration and retrieval of image collections. The system largely exploits the loosely-structured hierarchy of XML documents that provides a useful representation method to store semi-structured or unstructured data, which does not easily fit into existing database. The system offers users the capability to mine and manage the XML-based image collections through a web-based Graphical User Interface (GUI). Typically, at an interactive session with the system, the user can browse a visual structural summary of the XML database in order to select interesting elements. Using this intermediate result, queries combining structure and textual references can be composed and presented to the system. After query evaluation, the full set of answers is presented in a visual and structured way.

Keywords: Data-centric XML, graphical user interfaces, information retrieval, case-based reasoning, fuzzy sets

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Authors: Maumita Bhattacharya

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Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, many real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations. Use of evolutionary algorithms in such problem domains is thus practically prohibitive. An attractive alternative is to build meta models or use an approximation of the actual fitness functions to be evaluated. These meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. Many regression and interpolation tools are available to build such meta models. This paper briefly discusses the architectures and use of such meta-modeling tools in an evolutionary optimization context. We further present two evolutionary algorithm frameworks which involve use of meta models for fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [14] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the metamodel are generated from a single uniform model. This does not take into account uncertain scenarios involving noisy fitness functions. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle noisy functions [15]. Empirical results obtained by evaluating the frameworks using several benchmark functions demonstrate their efficiency

Keywords: Meta model, Evolutionary algorithm, Stochastictechnique, Fitness function, Optimization, Support vector machine.

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Authors: Haider Javed Uppal, Javed Yunas Uppal

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In today's globalized world, it is necessary to develop a form of music that is able to evoke equal emotional responses among people from diverse cultural backgrounds. Indigenous cultures throughout history have developed their own music cognition, specifically in terms of the connections between music and mood. With the advancements in artificial intelligence technologies, it has become possible to analyze and categorize music features such as timbre, harmony, melody, and rhythm, and relate them to the resulting mood effects experienced by listeners. This paper presents a model that utilizes a screenshot translator to convert music from different origins into waveforms, which are then analyzed using machine learning and information retrieval techniques. By connecting these waveforms with Thayer's matrix of moods, a mood classifier has been developed using fuzzy logic algorithms to determine the emotional impact of different types of music on listeners from various cultures.

Keywords: Cognition, world music, artificial intelligence, Thayer’s matrix.

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Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate is questioned as a risk factor for weight gain. The relations between basal metabolic rate and body composition have not been cleared yet. The impact of fat mass on basal metabolic rate is also uncertain. Within this context, indices based upon total body mass as well as total body fat mass are available. In this study, the aim is to investigate the potential clinical utility of these indices in the adult population. 287 individuals, aged from 18 to 79 years, were included into the scope of the study. Based upon body mass index values, 10 underweight, 88 normal, 88 overweight, 81 obese, and 20 morbid obese individuals participated. Anthropometric measurements including height (m), and weight (kg) were performed. Body mass index, diagnostic obesity notation model assessment index I, diagnostic obesity notation model assessment index II, basal metabolic rate-to-weight ratio were calculated. Total body fat mass (kg), fat percent (%), basal metabolic rate, metabolic age, visceral adiposity, fat mass of upper as well as lower extremities and trunk, obesity degree were measured by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical evaluations were performed by statistical package (SPSS) for Windows Version 16.0. Scatterplots of individual measurements for the parameters concerning correlations were drawn. Linear regression lines were displayed. The statistical significance degree was accepted as p < 0.05. The strong correlations between body mass index and diagnostic obesity notation model assessment index I as well as diagnostic obesity notation model assessment index II were obtained (p < 0.001). A much stronger correlation was detected between basal metabolic rate and diagnostic obesity notation model assessment index I in comparison with that calculated for basal metabolic rate and body mass index (p < 0.001). Upon consideration of the associations between basal metabolic rate-to-weight ratio and these three indices, the best association was observed between basal metabolic rate-to-weight and diagnostic obesity notation model assessment index II. In a similar manner, this index was highly correlated with fat percent (p < 0.001). Being independent of the indices, a strong correlation was found between fat percent and basal metabolic rate-to-weight ratio (p < 0.001). Visceral adiposity was much strongly correlated with metabolic age when compared to that with chronological age (p < 0.001). In conclusion, all three indices were associated with metabolic age, but not with chronological age. Diagnostic obesity notation model assessment index II values were highly correlated with body mass index values throughout all ranges starting with underweight going towards morbid obesity. This index is the best in terms of its association with basal metabolic rate-to-weight ratio, which can be interpreted as basal metabolic rate unit.

Keywords: Basal metabolic rate, body mass index, children, diagnostic obesity notation model assessment index, obesity.

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Authors: M. A. Bajaber, M. A. Taha

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Contractor selection in Saudi Arabia is very important due to the large construction boom and the contractor role to get over construction risks. The need for investigating contractor selection is due to the following reasons; large number of defaulted or failed projects (18%), large number of disputes attributed to contractor during the project execution stage (almost twofold), the extension of the General Agreement on Tariffs and Trade (GATT) into construction industry, and finally the few number of researches. The selection strategy is not perfect and considered as the reason behind irresponsible contractors. As a response, this research was conducted to review the contractor selection strategies as an integral part of a long advanced research to develop a good selection model. Many techniques can be used to form a selection strategy; multi criteria for optimizing decision, prequalification to discover contractor-s responsibility, bidding process for competition, third party guarantee to enhance the selection, and fuzzy techniques for ambiguities and incomplete information.

Keywords: Bidding, Construction industry, Contractor selection, Saudi Arabia.

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Authors: Steven W. Carruthers

Abstract:

The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Keywords: Effectiveness, equipercentile equating, IRT, learning games, linear equating, mean-sigma equating.

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Authors: Kemalettin Erbatur, Özer Koca, Evrim Taşkıran, Metin Yılmaz, Utku Seven

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Recent fifteen years witnessed fast improvements in the field of humanoid robotics. The human-like robot structure is more suitable to human environment with its supreme obstacle avoidance properties when compared with wheeled service robots. However, the walking control for bipedal robots is a challenging task due to their complex dynamics. Stable reference generation plays a very important role in control. Linear Inverted Pendulum Model (LIPM) and the Zero Moment Point (ZMP) criterion are applied in a number of studies for stable walking reference generation of biped walking robots. This paper follows this main approach too. We propose a natural and continuous ZMP reference trajectory for a stable and human-like walk. The ZMP reference trajectories move forward under the sole of the support foot when the robot body is supported by a single leg. Robot center of mass trajectory is obtained from predefined ZMP reference trajectories by a Fourier series approximation method. The Gibbs phenomenon problem common with Fourier approximations of discontinuous functions is avoided by employing continuous ZMP references. Also, these ZMP reference trajectories possess pre-assigned single and double support phases, which are very useful in experimental tuning work. The ZMP based reference generation strategy is tested via threedimensional full-dynamics simulations of a 12-degrees-of-freedom biped robot model. Simulation results indicate that the proposed reference trajectory generation technique is successful.

Keywords: Biped robot, Linear Inverted Pendulum Model, Zero Moment Point, Fourier series approximation.

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Authors: M. F. Nawaz, S. Gul, T. H. Farooq, M. T. Siddiqui, M. Asif, I. Ahmad, N. K. Niazi

Abstract:

In Pakistan, major demands of fuel wood and timber wood are fulfilled by agroforestry. However, the information regarding economic significance of agroforestry and its productivity in Pakistan is still insufficient and unreliable. Survey of field conditions to examine the agroforestry status at local level helps us to know the future trends and to formulate the policies for sustainable wood supply. The objectives of this research were to examine the actual status and potential of agroforestry and to point out the barriers that are faced by farmers in the adoption of agroforestry. Research was carried out in Chiniot district, Pakistan because it is the famous city for furniture industry that is largely dependent on farm trees. A detailed survey of district Chiniot was carried out from 150 randomly selected farmer respondents using multi-objective oriented and pre-tested questionnaire. It was found that linear tree planting method was more adopted (45%) as compared to linear + interplanting (42%) and/or compact planting (12.6%). Chi-square values at P-value <0.5 showed that age (11.35) and education (17.09) were two more important factors in the quick adoption of agroforestry as compared to land holdings (P-value of 0.7). The major reason of agroforestry adoption was to obtain income, fodder and fuelwood. The most dominant species in farmlands was shisham (Dalbergia sissoo) but since last five years, mostly farmers were growing Sufeida (Eucalyptus camaldulensis), kikar (Acacia nilotica) and popular (Populus deltoides) on their fields due to “Shisham die-back” problem. It was found that agro-forestry can be increased by providing good quality planting material to farmers and improving wood markets.

Keywords: Agroforestry, trees, services, agriculture, farmers.

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Authors: Nameesh Miglani, Rajeev Saha, R. S. Parihar

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Estimation of the quality regarding higher education within a university is practically long drawn process besides being difficult to measure primarily due to lack of a standard scale. National Assessment and Accreditation Council (NAAC) evolved a methodology of assessment which involves self-appraisal by each university/college and an assessment of performance by an expert committee. The attributes involved in assessing a university may not be totally independent from each other thereby necessitating the consideration of interdependencies. The present study focuses on evaluation of assessment criteria using graph theoretic approach and fuzzy treatment of data collected from the students. The technique will provide a suitable platform to university management team to cross check assessment of education quality by considering interdependencies of the attributes using graph theory.

Keywords: Graph theory, NAAC accreditation criteria, Indian University accreditation process.

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Authors: K. S. Sivakumaran, Bo Chen

Abstract:

The floor beams of steel buildings, cold-formed steel floor joists in particular, often require large web openings, which may affect their shear capacities. A cost effective way to mitigate the detrimental effects of such openings is to weld/fasten reinforcements. A difficulty associated with an experimental investigation to establish suitable reinforcement schemes for openings in shear zone is that moment always coexists with the shear, and thus, it is impossible to create pure shear state in experiments, resulting in moment influenced results. However, Finite Element Method (FEM) based analysis can be conveniently used to investigate the pure shear behaviour of webs including webs with reinforced openings. This paper presents the details associated with the finite element analysis of thick/thin-plates (representing the web of hot-rolled steel beam, and the web of a cold-formed steel member) having a large reinforced opening. The study considered simply-supported rectangular plates subjected to in-plane shear loadings until failure (including post-buckling behaviour). The plate was modelled using geometrically non-linear quadrilateral shell elements, and non-linear stress-strain relationship based on experiments. Total Langrangian with large displacement/small strain formulation was used for such analyses. The model also considered the initial geometric imperfections. This study considered three reinforcement schemes, namely, flat, lip, and angle reinforcements. This paper discusses the modelling considerations and presents the results associated with the various reinforcement schemes under consideration.

Keywords: Cold-formed steel, finite element analysis, opening, reinforcement, shear resistance.

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Authors: Noraini Othman, Aizzat Mohd Nasurdin

Abstract:

The purpose of this study was to investigate the relationship between hope and resilience with work engagement. A total of 422 staff nurses working in three public hospitals in Peninsular Malaysia participated in this study. Statistical results using regression analysis revealed that hope and resilience were positively related to work engagement. Possible reasons for these findings, as well as their implications and future research directions are discussed.

Keywords: hope, nurses, resilience, work engagement

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Authors: Yuan-Jye Tseng, Jia-Shu Li

Abstract:

To design a product with the given product requirement and design objective, there can be alternative ways to propose the detailed design specifications of the product. In the design modeling stage, alternative design cases with detailed specifications can be modeled to fulfill the product requirement and design objective. Therefore, in the design evaluation stage, it is required to perform an evaluation of the alternative design cases for deciding the final design. The purpose of this research is to develop a product evaluation model for evaluating the alternative design cases by integrated evaluating the criteria of functional design, Kansei design, and design for supply chain. The criteria in the functional design group include primary function, expansion function, improved function, and new function. The criteria in the Kansei group include geometric shape, dimension, surface finish, and layout. The criteria in the design for supply chain group include material, manufacturing process, assembly, and supply chain operation. From the point of view of value and cost, the criteria in the functional design group and Kansei design group represent the design value of the product. The criteria in the design for supply chain group represent the supply chain and manufacturing cost of the product. It is required to evaluate the design value and the supply chain cost to determine the final design. For the purpose of evaluating the criteria in the three criteria groups, a fuzzy analytic network process (FANP) method is presented to evaluate a weighted index by calculating the total relational values among the three groups. A method using the technique for order preference by similarity to ideal solution (TOPSIS) is used to compare and rank the design alternative cases according to the weighted index using the total relational values of the criteria. The final decision of a design case can be determined by using the ordered ranking. For example, the design case with the top ranking can be selected as the final design case. Based on the criteria in the evaluation, the design objective can be achieved with a combined and weighted effect of the design value and manufacturing cost. An example product is demonstrated and illustrated in the presentation. It shows that the design evaluation model is useful for integrated evaluation of functional design, Kansei design, and design for supply chain to determine the best design case and achieve the design objective.

Keywords: Design evaluation, functional design, Kansei design, supply chain, design value, manufacturing cost, fuzzy analytic network process, technique for order preference by similarity to ideal solution.

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