Search results for: Multiple criteria classification

Authors: Denis Trcek

Abstract:

Trust is essential for further and wider acceptance of contemporary e-services. It was first addressed almost thirty years ago in Trusted Computer System Evaluation Criteria standard by the US DoD. But this and other proposed approaches of that period were actually solving security. Roughly some ten years ago, methodologies followed that addressed trust phenomenon at its core, and they were based on Bayesian statistics and its derivatives, while some approaches were based on game theory. However, trust is a manifestation of judgment and reasoning processes. It has to be dealt with in accordance with this fact and adequately supported in cyber environment. On the basis of the results in the field of psychology and our own findings, a methodology called qualitative algebra has been developed, which deals with so far overlooked elements of trust phenomenon. It complements existing methodologies and provides a basis for a practical technical solution that supports management of trust in contemporary computing environments. Such solution is also presented at the end of this paper.

Keywords: internet security, trust management, multi-agent systems, reasoning and judgment, modeling and simulation, qualitativealgebra

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Authors: Visit Hirankitti, Vuong Tran Xuan

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Multi-agent communication of Semantic Web information cannot be realized without the need to reason with ontology and agent locations. This is because for an agent to be able to reason with an external semantic web ontology, it must know where and how to access to that ontology. Similarly, for an agent to be able to communicate with another agent, it must know where and how to send a message to that agent. In this paper we propose a framework of an agent which can reason with ontology and agent locations in order to perform reasoning with multiple distributed ontologies and perform communication with other agents on the semantic web. The agent framework and its communication mechanism are formulated entirely in meta-logic.

Keywords: Semantic Web, agent communication, ontologies.

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Authors: Yury Nikulin

Abstract:

A multicriteria linear programming problem with integer variables and parameterized optimality principle "from lexicographic to Slater" is considered. A situation in which initial coefficients of penalty cost functions are not fixed but may be potentially a subject to variations is studied. For any efficient solution, appropriate measures of the quality are introduced which incorporate information about variations of penalty cost function coefficients. These measures correspond to the so-called stability and accuracy functions defined earlier for efficient solutions of a generic multicriteria combinatorial optimization problem with Pareto and lexicographic optimality principles. Various properties of such functions are studied and maximum norms of perturbations for which an efficient solution preserves the property of being efficient are calculated.

Keywords: Stability and accuracy, multicriteria optimization, lexicographic optimality.

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Authors: Ashly Joseph

Abstract:

In the era of digital transformation, full-stack observability has emerged as a crucial aspect of administering modern application stacks. This research paper presents the concept of full-stack observability, its significance in the context of contemporary application stacks, and the challenges posed by swiftly evolving digital environments. In addition, it describes how full-stack observability intends to provide complete visibility and actionable insights by correlating telemetry across multiple domains.

Keywords: Actionable insights, digital transformation, full-stack observability, performance metrics.

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Authors: Wenji Zhu, Yigang He

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This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with [1] and [6], which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.

Keywords: Analog circuits, fault diagnosis, tolerance, wavelettransform, fractal dimension, box dimension.

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Authors: Yen-Ting Wang, Kenny Wen-Chyuan Chen, I-Tsun Chiang, Lung-Ching Liang, Alex J.Y. Lee

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The aim of this study was to establish the feasibility of a minute incremental exercise testing protocol in young asthma children. Twenty-two children with clinically diagnosed mild to moderate asthma volunteered to participate. The maximum incremental exercise test was performed using a cycle ergometer with an electromagnetic braking. A warm-up unloaded for 2 minutes then the workload was started at 40 watts for 2 minutes, and then stepwise increments of 8 watts per 2 minutes were applied. The pedaling frequency was set at 50 rpm. Ventilation and gas exchange were measured with a breath-by-breath automatic metabolic measurement system. Results showed that this test was well tolerated by all asthmatic children. Most of the children reached the VO2 plateau and satisfied the criteria for maximal respiratory exchange ratio of ≥ 1. This Study demonstrated that this testing protocol was suitable for young asthmatic children.

Keywords: Asthma, Child, Exercise, Pediatrics.

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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: I. Abuiziah, A. Oulhaj, K. Sebari, D. Ouazar

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The primary objectives of transient analysis are to determine the values of transient pressures that can result from flow control operations and to establish the design criteria for system equipment and devices (such as control devices and pipe wall thickness) so as to provide an acceptable level of protection against system failure due to pipe collapse or bursting. Because of the complexity of the equations needed to describe transients, numerical computer models are used to analyze transient flow hydraulics. An effective numerical model allows the hydraulic engineer to analyze potential transient events and to identify and evaluate alternative solutions for controlling hydraulic transients, thereby protecting the integrity of the hydraulic system. This paper presents the influence of using the protection devices to control the adverse effects due to excessive and low pressure occurs in the transient.

Keywords: Flow Transient, Water hammer, Pipeline System, Surge Tank, Simulation Model, Protection Devices.

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Authors: Raymond Yeo K. W., P. Y. Lim, Farrah Wong

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Attractive and creative advertisement displays are often in high demand as they are known to have profound impact on the commercial market. In the fast advancement of technology, advertising trend has taken a great leap in attracting more and more demanding consumers. A low-cost and low-power consumption flipping advertisement board has been developed in this paper. The design of the electrical circuit and the controller of the advertisement board are presented. A microcontroller, a Darlington Pair driver and a unipolar stepper motor were used to operate the electrical flipping advertisement board. The proposed system has been implemented and the hardware has been tested to demonstrate the capability of displaying multiple advertisements in a panel.

Keywords: Advertisement board, microcontroller, stepper motor.

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Authors: P.Cordero, R.Poler, R.Sanchis

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The environmental impacts caused by the current production and consumption models, together with the impact that the current economic crisis, bring necessary changes in the European industry toward new business models based on sustainability issues that could allow them to innovate and improve their competitiveness. This paper analyzes the key environmental issues and the current and future market trends in one of the most important industrial sectors in Spain, the furniture sector. It also proposes new decision support tools -diagnostic kit, roadmap and guidelines- to guide companies to implement sustainability criteria into their organizations, including eco-design strategies and other economical and social strategies in accordance with the sustainability definition, and other available tools such as eco-labels, environmental management systems, etc., and to use and combine them to obtain the results the company expects to help improve its competitiveness.

Keywords: Furniture sector, eco-design, sustainability, economical crisis, market trends, roadmap

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Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

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Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: Additive manufacturing, decision-makings, environmental impact, predictive models.

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Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

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Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: Feature fusion, image retrieval, membership function, normalization.

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Authors: Asar Khan, Peter D. Widdop, Andrew J. Day, Aliaster S. Wood, Steve, R. Mounce, John Machell

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This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by sensors to construct an empirical model for time series prediction and classification of events. These two components have been installed, tested and verified in an experimental site in a UK water distribution system. Verification of the system has been achieved from a series of simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network management.

Keywords: Detection, leakage, neural networks, sensors, water distribution networks

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Authors: Q. Niu, X. H. Zhou, W. Liu

Abstract:

The cooling channels of injection mould play a crucial role in determining the productivity of moulding process and the product quality. It’s not a simple task to design high quality cooling channels. In this paper, an intelligent cooling channels design system including automatic layout of cooling channels, interference checking and assembly of accessories is studied. Automatic layout of cooling channels using genetic algorithm is analyzed. Through integrating experience criteria of designing cooling channels, considering the factors such as the mould temperature and interference checking, the automatic layout of cooling channels is implemented. The method of checking interference based on distance constraint algorithm and the function of automatic and continuous assembly of accessories are developed and integrated into the system. Case studies demonstrate the feasibility and practicality of the intelligent design system.

Keywords: Injection mould, cooling channel, automatic layout, interference checking.

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Authors: M. Seifi, A. Ghasemi, M. Khosravi, M. Salimi, S. Jahandideh, J. Sherizadeh, F. S. Hashemizadeh, R. Khodaei

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Atherosclerosis is the condition in which an artery wall thickens as the result of a build-up of fatty materials such as cholesterol. It is a syndrome affecting arterial blood vessels, a chronic inflammatory response in the walls of arteries, in large part due to the accumulation of macrophage white blood cells and promoted by low density (especially small particle) lipoproteins (plasma proteins that carry cholesterol and triglycerides) without adequate removal of fats and cholesterol from the macrophages by functional high density lipoproteins (HDL). It is commonly referred to as a hardening or furring of the arteries. It is caused by the formation of multiple plaques within the arteries.

Keywords: Arterial blood vessels, atherosclerosis, cholesterol.

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Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha

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Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.

Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.

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Authors: Marian Gaiceanu, Emil Rosu

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In this paper the optimal control strategy for Permanent Magnet Synchronous Motor (PMSM) based drive system is presented. The designed full optimal control is available for speed operating range up to base speed. The optimal voltage space-vector assures input energy reduction and stator loss minimization, maintaining the output energy in the same limits with the conventional PMSM electrical drive. The optimal control with three components is based on the energetically criteria and it is applicable in numerical version, being a nonrecursive solution. The simulation results confirm the increased efficiency of the optimal PMSM drive. The properties of the optimal voltage space vector are shown.

Keywords: Matlab/Simulink, optimal control, permanent magnet synchronous motor, Riccati equation, space vector PWM

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Authors: Muchiri Josephine, Qdero Agnes

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The current study was conducted during the coronavirus pandemic (COVID-19) period, soon after the lifting of the lockdown measures and schools had just re-opened. It investigated the sociodemographic correlates of Post-Traumatic Stress Disorder (PTSD) among adolescents (13-18 years) who had undergone domestic violence (DV) in Kajiado County, Kenya. The adolescents were administered a sociodemographic questionnaire to ascertain the forms of DV experienced, and those who met the criteria were assessed for the presence of PTSD using the Harvard Trauma Questionnaire (HTQ). Overall, 93 (90.3%) had experienced DV, and 57 (61.3%) had PTSD; where the severity and prevalence of PTSD increased with increased age, and it also increased significantly among those in higher academic levels, indicating that PTSD prevalence was chronic and additionally influenced by increased academic pressure. Social connections seemed to mitigate PTSD prevalence, whereas, regarding the family background, those living with guardians seemed to have more severe PTSD.

Keywords: Age, education level, gender, post-traumatic stress disorder.

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Authors: Lotfi Nabli, Achraf Jabeur Telmoudi, Radhi M'hiri

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This paper proposes a modeling method of the laws controlling manufacturing systems with temporal and non temporal constraints. A methodology of robust control construction generating the margins of passive and active robustness is being elaborated. Indeed, two paramount models are presented in this paper. The first utilizes the P-time Petri Nets which is used to manage the flow type disturbances. The second, the quality model, exploits the Intervals Constrained Petri Nets (ICPN) tool which allows the system to preserve its quality specificities. The redundancy of the robustness of the elementary parameters between passive and active is also used. The final model built allows the correlation of temporal and non temporal criteria by putting two paramount models in interaction. To do so, a set of definitions and theorems are employed and affirmed by applicator examples.

Keywords: Manufacturing systems control, flow, quality, robustness, redundancy, Petri Nets.

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Authors: H. Unger, H. Coltzau

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In Peer-to-Peer service networks, where peers offer any kind of publicly available services or applications, intuitive navigation through all services in the network becomes more difficult as the number of services increases. In this article, a concept is discussed that enables users to intuitively browse and use large scale P2P service networks. The concept extends the idea of creating virtual 3D-environments solely based on Peer-to-Peer technologies. Aside from browsing, users shall have the possibility to emphasize services of interest using their own semantic criteria. The appearance of the virtual world shall intuitively reflect network properties that may be of interest for the user. Additionally, the concept comprises options for load- and traffic-balancing. In this article, the requirements concerning the underlying infrastructure and the graphical user interface are defined. First impressions of the appearance of future systems are presented and the next steps towards a prototypical implementation are discussed.

Keywords: Internet Operating System, Peer-To-Peer, Service Exploration

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Authors: K. Badron, A. F. Ismail, A. L. Asnawi, N. F. A. Malik, S. Z. Abidin, S. Dzulkifly

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The occurrences of precipitation, also commonly referred as rain, in the form of "convective" and "stratiform" have been identified to exist worldwide. In this study, the radar return echoes or known as reflectivity values acquired from radar scans have been exploited in the process of classifying the type of rain endured. The investigation use radar data from Malaysian Meteorology Department (MMD). It is possible to discriminate the types of rain experienced in tropical region by observing the vertical characteristics of the rain structure. .Heavy rain in tropical region profoundly affects radiowave signals, causing transmission interference and signal fading. Required wireless system fade margin depends on the type of rain. Information relating to the two mentioned types of rain is critical for the system engineers and researchers in their endeavour to improve the reliability of communication links. This paper highlights the quantification of percentage occurrences over one year period in 2009.

Keywords: Stratiform, convective, tropical region, attenuation radar reflectivity.

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Authors: Vahid Khorramshahi, Alireza Behrad, Neeraj K. Kanhere

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In this paper we present a new method for over-height vehicle detection in low headroom streets and highways using digital video possessing. The accuracy and the lower price comparing to present detectors like laser radars and the capability of providing extra information like speed and height measurement make this method more reliable and efficient. In this algorithm the features are selected and tracked using KLT algorithm. A blob extraction algorithm is also applied using background estimation and subtraction. Then the world coordinates of features that are inside the blobs are estimated using a noble calibration method. As, the heights of the features are calculated, we apply a threshold to select overheight features and eliminate others. The over-height features are segmented using some association criteria and grouped using an undirected graph. Then they are tracked through sequential frames. The obtained groups refer to over-height vehicles in a scene.

Keywords: Feature extraction, over-height vehicle detection, traffic monitoring, vehicle tracking.

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Authors: Mounir Sayadi, Farhat Fnaiech

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In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.

Keywords: Texture analysis, statistical features, adaptive filters, Chandrasekhar algorithm.

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Authors: Peng Mei, Yan-Jun Qi, Yu Cui, Song Lu, He-Ping Zhang

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A lot of computer-based methods have been developed to assess the evacuation capability (EC) of high-rise buildings. Because softwares are time-consuming and not proper for on scene applications, we adopted two methods, fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to an ideal solution (TOPSIS), for EC assessment of a high-rise building in Jinan. The EC scores obtained with the two methods and the evacuation time acquired with Pathfinder 2009 for floors 47-60 of the building were compared with each other. The results show that FAHP performs better than TOPSIS for EC assessment of high-rise buildings, especially in the aspect of dealing with the effect of occupant type and distance to exit on EC, tackling complex problem with multi-level structure of criteria, and requiring less amount of computation. However, both FAHP and TOPSIS failed to appropriately handle the situation where the exit width changes while occupants are few.

Keywords: Evacuation capability assessment, FAHP, high-rise buildings, TOPSIS.

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

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Authors: Mohammad Reza Pirestani, Mehdi Shafaghati, Amir Ahmad Dehghani

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From the beginning of creation, human being has ever fought against the ecosystem by changes has made in environment. The most environmental changes on the nature have been done after starting the concentrated life in the same region. Dams are one of the most important buildings in water resources and transferring. These buildings have been made from old times without access to hydrological, hydraulically, hydro mechanical information. Dams have positive and negative effects on environment. Constructing a dam relatively causes equal ecological consequences. According to different criteria, environmental effects of dams can lead short term and long term damages. These effects may influence on the situation and treatment of meteorology, biology, culture, ancient works, etc and severely causes to change and complicate it. So considering importance of positive effects of dam construction, it is necessary to minimize negative environmental effects of dams to achieve a stable development. In this article the considered effects and their solutions in influencing on assessment of destructive environmental effects of dams construction have been surveyed and presented.

Keywords: Dam, Environment, Water Resources, Assessment

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Authors: B. Gangloff, L. Mayoral, A. Rezrazi

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Three types of salary distribution are usually proposed by the theorists of distributive justice: Equality, equity and need. Their influence has been studied, taking into consideration (in terms of equity) the performance of the employees and their degree of allegiance/rebellion in what regards discriminatory hierarchical orders, by taking into account the reasons of such allegiance/rebellion (allegiance out of conviction, legalism or opportunism/ethical rebellion). Conducted in Argentina, the study has confronted 480 students (240 male and 240 female) with a practical case in which they had to advise a manager of a real estate agency on the allocation of a bonus amongst his employees. The latter were characterized according to their respective performance, one of them being further defined as being (or not) in a financial need and as having complied (or not) with a discriminatory hierarchical order regarding foreigners. The results show that the distribution of the bonus only follows the rules of equity and need: The employees more efficient, allegiant or in need, are rewarded more than the others. It is also noteworthy that the allegiant employees are rewarded in the same way, regardless of the reason for their allegiance, and that the employee who refuses to adopt a discriminatory conduct is penalized.

Keywords: Distributive justice, equity, performance, allegiance, ethic.

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Authors: H. Nikzad, S. Yoshitomi

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This paper presents the design application and reinforcement detailing of 15 storied reinforced concrete shear wall-frame structure based on linear static analysis. Databases are generated for section sizes based on automated structural optimization method utilizing Active-set Algorithm in MATLAB platform. The design constraints of allowable section sizes, capacity criteria and seismic provisions for static loads, combination of gravity and lateral loads are checked and determined based on ASCE 7-10 documents and ACI 318-14 design provision. The result of this study illustrates the efficiency of proposed method, and is expected to provide a useful reference in designing of RC shear wall-frame structures.

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

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Authors: Dubbale Daniel A., Tsutsumi J.

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This research work takes a different approach in the discussion of urban form impacts on transport planning and auto dependency. Concentrated density represented by effective density explains auto dependency better than the conventional density and it is proved to be a realistic density representative for the urban transportation analysis. Model analysis reveals that effective density is influenced by the shopping accessibility index as well as job density factor. It is also combined with the job access variable to classify four levels of Transport Activity Centers (TACs) in Okinawa, Japan. Trip attraction capacity and levels of the newly classified TACs was found agreeable with the amount of daily trips attracted to each center. The trip attraction data set was drawn from a 2007 Okinawa personal trip survey. This research suggests a planning methodology which guides logical transport supply routes and concentrated local development schemes.

Keywords: Effective density, urban form, auto-dependency, transport activity centers

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Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

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Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: GraphViz representation, semantic relatedness, similarity measurement, WordNet similarity.

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