Search results for: decision rule

Authors: Hyu Sang Jo, Gyo Woo Lee

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In this study, the evaluation of thermal stability of the micrometer-sized silica particle reinforced epoxy composite was carried out through the measurement of thermal expansion coefficient and Young’s modulus of the specimens. For all the specimens in this study from the baseline to those containing 50 wt% silica filler, the thermal expansion coefficients and the Young’s moduli were gradually decreased down to 20% and increased up to 41%, respectively. The experimental results were compared with fillervolume- based simple empirical relations. The experimental results of thermal expansion coefficients correspond with those of Thomas’s model which is modified from the rule of mixture. However, the measured result for Young’s modulus tends to be increased slightly. The differences in increments of the moduli between experimental and numerical model data are quite large.

Keywords: Thermal Stability, Silica-Reinforced, Epoxy Composite, Coefficient of Thermal Expansion, Empirical Model.

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Authors: Mourad Ykhlef, Hebah ElGibreen

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Mining Sequential Patterns in large databases has become an important data mining task with broad applications. It is an important task in data mining field, which describes potential sequenced relationships among items in a database. There are many different algorithms introduced for this task. Conventional algorithms can find the exact optimal Sequential Pattern rule but it takes a long time, particularly when they are applied on large databases. Nowadays, some evolutionary algorithms, such as Particle Swarm Optimization and Genetic Algorithm, were proposed and have been applied to solve this problem. This paper will introduce a new kind of hybrid evolutionary algorithm that combines Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) to mine Sequential Pattern, in order to improve the speed of evolutionary algorithms convergence. This algorithm is referred to as SP-GAPSO.

Keywords: Genetic Algorithm, Hybrid Evolutionary Algorithm, Particle Swarm Optimization algorithm, Sequential Pattern mining.

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Authors: Mariann Veresne Somosi, Zoltan Nagy, Krisztina Varga

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Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.

Keywords: Factors of social innovation, methodological combination, social innovation process, supporting decision-making.

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Authors: N. Clavijo Buriticá, L. M. Correa Lópezand J. R., Sánchez Rodríguez

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The environmental impact caused by industries is an issue that, in the last 20 years, has become very important in terms of society, economics and politics in Colombia. Particularly, the tannery process is extremely polluting because of uneffective treatments and regulations given to the dumping process and atmospheric emissions. Considering that, this investigation is intended to propose a management model based on the integration of Lean Supply Chain, Green Supply Chain, Cleaner Production and ISO 14001-2004, that prioritizes the strategic components of the organizations. As a result, a management model will be obtained and it will provide a strategic perspective through a systemic approach to the tanning process. This will be achieved through the use of Multicriteria Decision tools, along with Quality Function Deployment and Fuzzy Logic. The strategic approach that embraces the management model using the alignment of Lean Supply Chain, Green Supply Chain, Cleaner Production and ISO 14001-2004, is an integrated perspective that allows a gradual frame of the tactical and operative elements through the correct setting of the information flow, improving the decision making process. In that way, Small Medium Enterprises (SMEs) could improve their productivity, competitiveness and as an added value, the minimization of the environmental impact. This improvement is expected to be controlled through a Dashboard that helps the Organization measure its performance along the implementation of the model in its productive process.

Keywords: Integration, environmental impact, management, systemic organization.

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Authors: S. Parida, S. C. Mohanty

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The free vibration behavior of thick pretwisted cantilevered functionally graded material (FGM) plate subjected to the thermal environment is investigated numerically in the present paper. A mathematical model is developed in the framework of higher order shear deformation theory (HOST) with C⁰ finite element formulation i.e. independent displacement and rotations. The material properties are assumed to be temperature dependent and vary continuously through the thickness based on the volume fraction exponent in simple power rule. The finite element model has been discretized into eight node quadratic serendipity elements with node wise seven degrees of freedom. The effect of plate geometry, temperature field, material composition, and the modal analysis on the vibrational characteristics is examined. Finally, the results are verified by comparing with those available in literature.

Keywords: FGM, pretwisted plate, thermal environment, HOST, simple power law.

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Authors: Elizabeth B. Varghese, M. Wilscy

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A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.

Keywords: Face Recognition, Vector Quantization, Integrated Adaptive Fuzzy Clustering, Self Organization Map.

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Authors: A. S. Adesuyi, Z. Munch

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This study investigates the use of a time-series of MODIS NDVI data to identify agricultural land cover change on an annual time step (2007 - 2012) and characterize the trend. Following an ISODATA classification of the MODIS imagery to selectively mask areas not agriculture or semi-natural, NDVI signatures were created to identify areas cereals and vineyards with the aid of ancillary, pictometry and field sample data for 2010. The NDVI signature curve and training samples were used to create a decision tree model in WEKA 3.6.9 using decision tree classifier (J48) algorithm; Model 1 including ISODATA classification and Model 2 not. These two models were then used to classify all data for the study area for 2010, producing land cover maps with classification accuracies of 77% and 80% for Model 1 and 2 respectively. Model 2 was subsequently used to create land cover classification and change detection maps for all other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices. Over the years as predicted by the land cover classification. Forty one percent of the catchment comprised of cereals with 35% possibly following a crop rotation system. Vineyards largely remained constant with only one percent conversion to vineyard from other land cover classes.

Keywords: Change detection, Land cover, NDVI, time-series.

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Authors: Watcharapan Sukkerd, Teeradej Wuttipornpun

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This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.

Keywords: Capacitated MRP, non-population search algorithms, linear programming, assembly flow shop.

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Authors: Huei-Wen Lin, Huei-Fu Lu

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Event sport tourism (EST) has become an especially important economic sector around the world. As the magnitude continues to grow, attracting more tourists, media, and investment for the host community, and many local areas/regions and states have identified the expenditures by visitors as a potential source of economic or employment growth. The main purposes of this study are to investigate stakeholders’ insights into the feature of hosting EST and using them as a regional development strategy. Continuing the focus of previous literature on the regional development and economic benefits by hosting EST, a total of fıve semi-structured interview questions are designed and a thematic analysis is employed to conduct with eight key sport and tourism decision makers in Atlanta during July to August 2016. Through the depth interviews, the study will contribute to a better understanding of stakeholders’ decision-making, identifying benefits and constraints as well as leveraging the impacts of hosting EST. These findings have provided stakeholders’ perspectives of hosting EST and using them as a reference of regional development in emerging sport tourism markets in the US. Additionally, this study examines key considerations and issues that affect and are critical to reliable understanding of the economic impacts of hosting EST on the regional development, and it will be able to benefit future management authorities (i.e. governments and communities) in their sport tourism development endeavors in defining and hosting successful EST. Furthermore, the insights gained from the qualitative analysis could help other cities/regions analyzing the economic impacts of hosting EST and using it as an instrument of city development strategy.

Keywords: Event sport tourism, regional economic development, thematic analysis, stakeholder.

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Authors: Leehter Yao, Chin-Chin Lin

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An adaptive fuzzy PID controller with gain scheduling is proposed in this paper. The structure of the proposed gain scheduled fuzzy PID (GS_FPID) controller consists of both fuzzy PI-like controller and fuzzy PD-like controller. Both of fuzzy PI-like and PD-like controllers are weighted through adaptive gain scheduling, which are also determined by fuzzy logic inference. A modified genetic algorithm called accumulated genetic algorithm is designed to learn the parameters of fuzzy inference system. In order to learn the number of fuzzy rules required for the TSK model, the fuzzy rules are learned in an accumulated way. In other words, the parameters learned in the previous rules are accumulated and updated along with the parameters in the current rule. It will be shown that the proposed GS_FPID controllers learned by the accumulated GA perform well for not only the regular linear systems but also the higher order and time-delayed systems.

Keywords: Gain scheduling, fuzzy PID controller, adaptive control, genetic algorithm.

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Authors: Susmitha Vekkot, Pancham Shukla

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In this paper, we focus on the fusion of images from different sources using multiresolution wavelet transforms. Based on reviews of popular image fusion techniques used in data analysis, different pixel and energy based methods are experimented. A novel architecture with a hybrid algorithm is proposed which applies pixel based maximum selection rule to low frequency approximations and filter mask based fusion to high frequency details of wavelet decomposition. The key feature of hybrid architecture is the combination of advantages of pixel and region based fusion in a single image which can help the development of sophisticated algorithms enhancing the edges and structural details. A Graphical User Interface is developed for image fusion to make the research outcomes available to the end user. To utilize GUI capabilities for medical, industrial and commercial activities without MATLAB installation, a standalone executable application is also developed using Matlab Compiler Runtime.

Keywords: Filter mask, GUI, hybrid architecture, image fusion, Matlab Compiler Runtime, wavelet transform.

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Authors: Claudineia Brazil, Elison Eduardo Bierhals, Francisco Pereira, José Leandro Néris, Matheus Rippel, Luciane Salvi

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The global concern about climate change has been increasing, since the emission of gases from human activities contributes to the greenhouse effect in the atmosphere, indicating significant impacts to the planet in the coming years. The study of precipitation regime is fundamental for the development of research in several areas. Among them are hydrology, agriculture, and electric sector. Using the climatic projections of the models belonging to the CMIP5, the main objective of the paper was to present an analysis of the impacts of climate change without rainfall in the Uruguay River basin. After an analysis of the results, it can be observed that for the future climate, there is a tendency, in relation to the present climate, for larger numbers of dry events, mainly in the winter months, changing the pluviometric regime for wet summers and drier winters. Given this projected framework, it is important to note the importance of adequate management of the existing water sources in the river basin, since the value of rainfall is reduced for the next years, it may compromise the dynamics of the ecosystems in the region. Facing climate change is fundamental issue for regions and cities all around the world. Society must improve its resilience to phenomenon impacts, and spreading the knowledge among decision makers and citizens is also essential. So, these research results can be subsidies for the decision-making in planning and management of mitigation measures and/or adaptation in south Brazil.

Keywords: Climate change, hydrological potential, precipitation, mitigation.

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Authors: David Calderón Villegas, Thomas Kalitzky

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Run-of-river (RoR) hydropower projects represent a viable, clean, and cost-effective alternative to dam-based plants and provide decentralized power production. However, RoR schemes’ cost-effectiveness depends on the proper selection of site and design flow, which is a challenging task because it requires multivariate analysis. In this respect, this study presents the development of an investment decision support tool for assessing the optimal size of an RoR scheme considering the technical, environmental, and cost constraints. The net present value (NPV) from a project perspective is used as an objective function for supporting the investment decision. The tool has been tested by applying it to an actual RoR project recently proposed in Colombia. The obtained results show that the optimum point in financial terms does not match the flow that maximizes energy generation from exploiting the river's available flow. For the case study, the flow that maximizes energy corresponds to a value of 5.1 m3/s. In comparison, an amount of 2.1 m3/s maximizes the investors NPV. Finally, a sensitivity analysis is performed to determine the NPV as a function of the debt rate changes and the electricity prices and the CapEx. Even for the worst-case scenario, the optimal size represents a positive business case with an NPV of 2.2 USD million and an internal rate of return (IRR) 1.5 times higher than the discount rate. 

Keywords: small hydropower, renewable energy, RoR schemes, optimal sizing, financial analysis

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Authors: Su-Yan Tang, Wei Zhang, Shan Mei, Yi-Fan Zhu

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Network-Centric Air Defense Missile Systems (NCADMS) represents the superior development of the air defense missile systems and has been regarded as one of the major research issues in military domain at present. Due to lack of knowledge and experience on NCADMS, modeling and simulation becomes an effective approach to perform operational analysis, compared with those equation based ones. However, the complex dynamic interactions among entities and flexible architectures of NCADMS put forward new requirements and challenges to the simulation framework and models. ABS (Agent-Based Simulations) explicitly addresses modeling behaviors of heterogeneous individuals. Agents have capability to sense and understand things, make decisions, and act on the environment. They can also cooperate with others dynamically to perform the tasks assigned to them. ABS proves an effective approach to explore the new operational characteristics emerging in NCADMS. In this paper, based on the analysis of network-centric architecture and new cooperative engagement strategies for NCADMS, an agent-based simulation framework by expanding the simulation framework in the so-called System Effectiveness Analysis Simulation (SEAS) was designed. The simulation framework specifies components, relationships and interactions between them, the structure and behavior rules of an agent in NCADMS. Based on scenario simulations, information and decision superiority and operational advantages in NCADMS were analyzed; meanwhile some suggestions were provided for its future development.

Keywords: air defense missile systems, network-centric, agent-based simulation, simulation framework, information superiority, decision superiority, operational advantages

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Authors: Robert O. Abolade, Olumide O. Ajayi, Zacheaus K. Adeyemo, Solomon A. Adeniran

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Link adaptation is an important strategy for achieving robust wireless multimedia communications based on quality of service (QoS) demand. Scheme switching in multiple-input multiple-output (MIMO) systems is an aspect of link adaptation, and it involves selecting among different MIMO transmission schemes or modes so as to adapt to the varying radio channel conditions for the purpose of achieving QoS delivery. However, finding the most appropriate switching method in MIMO links is still a challenge as existing methods are either computationally complex or not always accurate. This paper presents an intelligent switching method for the MIMO system consisting of two schemes - transmit diversity (TD) and spatial multiplexing (SM) - using fuzzy logic technique. In this method, two channel quality indicators (CQI) namely average received signal-to-noise ratio (RSNR) and received signal strength indicator (RSSI) are measured and are passed as inputs to the fuzzy logic system which then gives a decision – an inference. The switching decision of the fuzzy logic system is fed back to the transmitter to switch between the TD and SM schemes. Simulation results show that the proposed fuzzy logic – based switching technique outperforms conventional static switching technique in terms of bit error rate and spectral efficiency.

Keywords: Channel quality indicator, fuzzy logic, link adaptation, MIMO, spatial multiplexing, transmit diversity.

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Authors: Soltani Amir, Wang Xuan

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The advantage of using non-linear passive damping  system in vibration control of two adjacent structures is investigated  under their base excitation. The base excitation is El Centro  earthquake record acceleration. The damping system is considered as  an optimum and effective non-linear viscous damper that is  connected between two adjacent structures. A MATLAB program is  developed to produce the stiffness and damping matrices and to  determine a time history analysis of the dynamic motion of the  system. One structure is assumed to be flexible while the other has a  rule as laterally supporting structure with rigid frames. The response  of the structure has been calculated and the non-linear damping  coefficient is determined using optimum LQR algorithm in an  optimum vibration control system. The non-linear parameter of  damping system is estimated and it has shown a significant advantage  of application of this system device for vibration control of two  adjacent tall building.

Keywords: Structural Control, Active and passive damping, Vibration control, Seismic isolation.

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Authors: Y. Djouadi., F. Souam.

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Most of the existing text mining approaches are proposed, keeping in mind, transaction databases model. Thus, the mined dataset is structured using just one concept: the “transaction", whereas the whole dataset is modeled using the “set" abstract type. In such cases, the structure of the whole dataset and the relationships among the transactions themselves are not modeled and consequently, not considered in the mining process. We believe that taking into account structure properties of hierarchically structured information (e.g. textual document, etc ...) in the mining process, can leads to best results. For this purpose, an hierarchical associations rule mining approach for textual documents is proposed in this paper and the classical set-oriented mining approach is reconsidered profits to a Direct Acyclic Graph (DAG) oriented approach. Natural languages processing techniques are used in order to obtain the DAG structure. Based on this graph model, an hierarchical bottom up algorithm is proposed. The main idea is that each node is mined with its parent node.

Keywords: Graph based association rules mining, Hierarchical document structure, Text mining.

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Authors: Sedighe Arabameri, Nasser Salmasi

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In this researcha particle swarm optimization (PSO) algorithm is proposedfor no-wait flowshopsequence dependent setuptime scheduling problem with weighted earliness-tardiness penalties as the criterion (
|, |Σ   " ).The smallestposition value (SPV) rule is applied to convert the continuous value of position vector of particles in PSO to job permutations.A timing algorithm is generated to find the optimal schedule and calculate the objective function value of a given sequence in PSO algorithm. Twodifferent neighborhood structures are applied to improve the solution quality of PSO algorithm.The first one is based on variable neighborhood search (VNS) and the second one is a simple one with invariable structure. In order to compare the performance of two neighborhood structures, random test problems are generated and solved by both neighborhood approaches.Computational results show that the VNS algorithmhas better performance than the other one especially for the large sized problems.

Keywords: minimization of summation of weighed earliness and tardiness, no-wait flowshop scheduling, particle swarm optimization, sequence dependent setup times

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Authors: Claude Alavoine, Ferkan Kaplanseren

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Negotiation is a specific form of interaction based on communication in which the parties enter into deliberately, each with clear but different interests or goals and a mutual dependency towards a decision due to be taken at the end of the confrontation. Consequently, negotiation is a complex activity involving many different disciplines from the strategic aspects and the decision making process to the evaluation of alternatives or outcomes and the exchange of information. While gender differences can be considered as one of the most researched topic within negotiation studies, empirical works and theory present many conflicting evidences and results about the role of gender in the process or the outcome. Furthermore, little interest has been shown over gender differences in the definition of what is negotiation, its essence or fundamental elements. Or, as differences exist in practices, it might be essential to study if the starting point of these discrepancies does not come from different considerations about what is negotiation and what will encourage the participants in their strategic decisions. Some recent and promising experiments made with diverse groups show that male and female participants in a common and shared situation barely consider the same way the concepts of power, trust or stakes which are largely considered as the usual driving forces of any negotiation. Furthermore, results from Human Resource self-assessment tests display and confirm considerable differences between individuals regarding essential behavioral dimensions like capacity to improvise and to achieve, aptitude to conciliate or to compete and orientation towards power and group domination which are also part of negotiation skills. Our intention in this paper is to confront these dimensions with negotiation’s usual driving forces in order to build up new paths for further research.

Keywords: Gender, negotiation, personality, power, stakes, trust.

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Authors: Shiuh-Jer Huang, Ming-Tien Su

Abstract:

Since the driving speed and control accuracy of commercial optical disk are increasing significantly, it needs an efficient controller to monitor the track seeking and following operations of the servo system for achieving the desired data extracting response. The nonlinear behaviors of the actuator and servo system of the optical disk drive will influence the laser spot positioning. Here, the model-free fuzzy control scheme is employed to design the track seeking servo controller for a d.c. motor driving optical disk drive system. In addition, the sliding model control strategy is introduced into the fuzzy control structure to construct a 1-D adaptive fuzzy rule intelligent controller for simplifying the implementation problem and improving the control performance. The experimental results show that the steady state error of the track seeking by using this fuzzy controller can maintain within the track width (1.6 μm ). It can be used in the track seeking and track following servo control operations.

Keywords: Fuzzy control, gain tuning and optical disk drive.

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Authors: Debajyoti Mishra, Urmila Bhanja

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In this paper, a novel fuzzy approach is developed while solving the Dynamic Routing and Wavelength Assignment (DRWA) problem in optical networks with Wavelength Division Multiplexing (WDM). In this work, the effect of nonlinear and linear impairments such as Four Wave Mixing (FWM) and amplifier spontaneous emission (ASE) noise are incorporated respectively. The novel algorithm incorporates fuzzy logic controller (FLC) to reduce the effect of FWM noise and ASE noise on a requested lightpath referred in this work as FWM aware fuzzy dynamic routing and wavelength assignment algorithm. The FWM crosstalk products and the static FWM noise power per link are pre computed in order to reduce the set up time of a requested lightpath, and stored in an offline database. These are retrieved during the setting up of a lightpath and evaluated online taking the dynamic parameters like cost of the links into consideration.

Keywords: Amplifier spontaneous emission (ASE), Dynamic routing and wavelength assignment, Four wave mixing (FWM), Fuzzy rule based system (FRBS).

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Authors: P. C. Tewari, Parveen Kumar

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The paper describes the availability analysis of milling system of a rice milling plant using probabilistic approach. The subsystems under study are special purpose machines. The availability analysis of the system is carried out to determine the effect of failure and repair rates of each subsystem on overall performance (i.e. steady state availability) of system concerned. Further, on the basis of effect of repair rates on the system availability, maintenance repair priorities have been suggested. The problem is formulated using Markov Birth-Death process taking exponential distribution for probable failures and repair rates. The first order differential equations associated with transition diagram are developed by using mnemonic rule. These equations are solved using normalizing conditions and recursive method to drive out the steady state availability expression of the system. The findings of the paper are presented and discussed with the plant personnel to adopt a suitable maintenance policy to increase the productivity of the rice milling plant.

Keywords: Markov process, milling system, availability modeling, rice milling plant.

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Authors: Kanthida Kusonmano, Michael Netzer, Bernhard Pfeifer, Christian Baumgartner, Klaus R. Liedl, Armin Graber

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Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.

Keywords: Classification, High dimensional data, Machine learning

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Authors: Xiaohui Zhao, Shahan Mafuz

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Context-aware technologies provide system applications with the awareness of environmental conditions, customer behaviours, object movements, etc. Further, with such capability system applications can be smart to intelligently adapt their responses to the changing conditions. In regard to business operations, this promises businesses that their business processes can run more intelligently, adaptively and flexibly, and thereby either improve customer experience, enhance reliability of service delivery, or lower operational cost, to make the business more competitive and sustainable. Aiming at realising such context-aware business process management, this paper firstly explores its potential benefit, and then identifies some gaps between the current business process management support and the expected. In addition, some preliminary solutions are also discussed in regard to context definition, rule-based process execution, run-time process evolution, etc. A framework is also presented to give a conceptual architecture of context-aware business process management system to guide system implementation.

Keywords: Business process adaptation, business process evolution, business process modelling, and context awareness.

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Authors: K. Shakeri, M. Mohebbi

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In order to consider the effects of the higher modes in the pushover analysis, during the recent years several multi-modal pushover procedures have been presented. In these methods the response of the considered modes are combined by the square-rootof- sum-of-squares (SRSS) rule while application of the elastic modal combination rules in the inelastic phases is no longer valid. In this research the feasibility of defining an efficient alternative combination method is investigated. Two steel moment-frame buildings denoted SAC-9 and SAC-20 under ten earthquake records are considered. The nonlinear responses of the structures are estimated by the directed algebraic combination of the weighted responses of the separate modes. The weight of the each mode is defined so that the resulted response of the combination has a minimum error to the nonlinear time history analysis. The genetic algorithm (GA) is used to minimize the error and optimize the weight factors. The obtained optimal factors for each mode in different cases are compared together to find unique appropriate weight factors for each mode in all cases.

Keywords: Genetic Algorithm, Modal Pushover, Optimalweight.

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Authors: K. Majumdar, S. Datta

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Electricity is recognized as fundamental to industrialization and improving the quality of life of the people. Harnessing the immense untapped hydropower potential in Tripura region opens avenues for growth and provides an opportunity to improve the well-being of the people of the region, while making substantial contribution to the national economy. Gumti hydro power plant generates power to mitigate the crisis of power in Tripura, India. The first unit of hydro power plant (5MW) was commissioned in June 1976 & another two units of 5 MW was commissioned simultaneously. But out of 15MW capacity at present only 8MW- 9MW power is produced from Gumti hydro power plant during rainy season. But during lean season the production reduces to 0.5MW due to shortage of water. Now, it is essential to implement some mitigation measures so that the further atrocities can be prevented and originality will be possible to restore. The decision making ability of the Analytic Hierarchy Process (AHP) and Concordance Analysis Techniques (CAT) are utilized to identify the better decision or solution to the present problem. Some related attributes are identified by the method of surveying within the experts and the available reports and literatures. Similar criteria are removed and ultimately seven relevant ones are identified. All the attributes are compared with each other and rated accordingly to their importance over the other with the help of Pair wise Comparison Matrix. In the present investigation different mitigation measures are identified and compared to find the best suitable alternative which can solve the present uncertainties involving the existence of the Gumti Hydro Power Plant.

Keywords: Concordance Analysis Techniques, Analytic Hierarchy Process, Hydro Power.

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Authors: Othoman Elsayah, Naren Gupta, Binsheng Zhang

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

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

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Authors: El Kaak, Rachid, El Bikri, Khalid, Benamar, Rhali

Abstract:

This paper describes a study of geometrically nonlinear free vibration of thin circular functionally graded (CFGP) plates resting on Winkler elastic foundations. The material properties of the functionally graded composites examined here are assumed to be graded smoothly and continuously through the direction of the plate thickness according to a power law and are estimated using the rule of mixture. The theoretical model is based on the classical Plate theory and the Von-Kármán geometrical nonlinearity assumptions. An homogenization procedure (HP) is developed to reduce the problem considered here to that of isotropic homogeneous circular plates resting on Winkler foundation. Hamilton-s principle is applied and a multimode approach is derived to calculate the fundamental nonlinear frequency parameters which are found to be in a good agreement with the published results. On the other hand, the influence of the foundation parameters on the nonlinear fundamental frequency has also been analysed.

Keywords: Functionally graded materials, nonlinear vibrations, Winkler foundation.

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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Authors: Shima Nabinejad, Holger Schüttrumpf

Abstract:

Farmers who are living in flood-prone areas such as coasts are exposed to storm surges increased due to climate change. Crop cultivation is the most important economic activity of farmers, and in the time of flooding, agricultural lands are subject to inundation. Additionally, overflow saline water causes more severe damage outcomes than riverine flooding. Agricultural crops are more vulnerable to salinity than other land uses for which the economic damages may continue for a number of years even after flooding and affect farmers’ decision-making for the following year. Therefore, it is essential to assess what extent the agricultural areas are flooded and how much the associated flood damage to each individual farmer is. To address these questions, we integrated farmers’ decision-making at farm-scale with flood risk management. The integrated model includes identification of hazard scenarios, failure analysis of structural measures, derivation of hydraulic parameters for the inundated areas and analysis of the economic damages experienced by each farmer. The present study has two aims; firstly, it attempts to investigate the flooded cropland and potential crop damages for the whole area. Secondly, it compares them among farmers’ field for three flood scenarios, which differ in breach locations of the flood protection structure. To achieve its goal, the spatial distribution of fields and cultivated crops of farmers were fed into the flood risk model, and a 100-year storm surge hydrograph was selected as the flood event. The study area was Pellworm Island that is located in the German Wadden Sea National Park and surrounded by North Sea. Due to high salt content in seawater of North Sea, crops cultivated in the agricultural areas of Pellworm Island are 100% destroyed by storm surges which were taken into account in developing of depth-damage curve for analysis of consequences. As a result, inundated croplands and economic damages to crops were estimated in the whole Island which was further compared for six selected farmers under three flood scenarios. The results demonstrate the significance and the flexibility of the proposed model in flood risk assessment of flood-prone areas by integrating flood risk management and decision-making.

Keywords: Crop damages, flood risk analysis, individual farmer, inundated cropland, Pellworm Island, storm surges.

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