Search results for: Decision Making for cultural tourism

Authors: Sahar Elkaee Behjati

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Air pollution, particularly with dust, is one of the biggest issues Tehran is dealing with, and the city's green space which consists of trees has a critical role in absorption of it. The question this study aimed to investigate was which tree species the highest uptake capacity of the dust and carbon have suspended in the air. On this basis, 30 samples of trees from two different districts in Tehran were collected, and after washing and centrifuging, the samples were oven dried. The results of the study revealed that Ulmus minor had the highest amount of deposited dust in both districts. In addition, it was found that in Chamran district Ailanthus altissima and in Gandi district Ulmus minor has had the highest absorption of deposited carbon. Therefore, it could be argued that decision making on the selection of species for urban green spaces should take the above-mentioned parameters into account.

Keywords: Dust, leaves, uptake total carbon, tehran, tree species.

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Authors: D. Triantakonstantis, D. Stathakis

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Urban areas have been expanded throughout the globe. Monitoring and modelling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modelling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: Artificial Neural Networks, CORINE, Urban Atlas, Urban Growth Prediction.

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Authors: P.W. C. Prasad, A. Assi, A. Harb, V.C. Prasad

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This paper presents an improved variable ordering method to obtain the minimum number of nodes in Reduced Ordered Binary Decision Diagrams (ROBDD). The proposed method uses the graph topology to find the best variable ordering. Therefore the input Boolean function is converted to a unidirectional graph. Three levels of graph parameters are used to increase the probability of having a good variable ordering. The initial level uses the total number of nodes (NN) in all the paths, the total number of paths (NP) and the maximum number of nodes among all paths (MNNAP). The second and third levels use two extra parameters: The shortest path among two variables (SP) and the sum of shortest path from one variable to all the other variables (SSP). A permutation of the graph parameters is performed at each level for each variable order and the number of nodes is recorded. Experimental results are promising; the proposed method is found to be more effective in finding the variable ordering for the majority of benchmark circuits.

Keywords: Binary decision diagrams, graph representation, Boolean functions representation, variable ordering.

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Authors: Dewan Md. Farid, Nguyen Huu Hoa, Jerome Darmont, Nouria Harbi, Mohammad Zahidur Rahman

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In this paper, we present a new learning algorithm for anomaly based network intrusion detection using improved self adaptive naïve Bayesian tree (NBTree), which induces a hybrid of decision tree and naïve Bayesian classifier. The proposed approach scales up the balance detections for different attack types and keeps the false positives at acceptable level in intrusion detection. In complex and dynamic large intrusion detection dataset, the detection accuracy of naïve Bayesian classifier does not scale up as well as decision tree. It has been successfully tested in other problem domains that naïve Bayesian tree improves the classification rates in large dataset. In naïve Bayesian tree nodes contain and split as regular decision-trees, but the leaves contain naïve Bayesian classifiers. The experimental results on KDD99 benchmark network intrusion detection dataset demonstrate that this new approach scales up the detection rates for different attack types and reduces false positives in network intrusion detection.

Keywords: Detection rates, false positives, network intrusiondetection, naïve Bayesian tree.

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Authors: J. Burlakovs, Y. Jani, L. Grinberga, M. Kriipsalu, O. Anne, I. Grinfelde, W. Hogland

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The worldwide future sustainable economies are oriented towards the sea: the maritime economy is becoming one of the strongest driving forces in many regions as population growth is the highest in coastal areas. For hundreds of years sea resources were depleted unsustainably by fishing, mining, transportation, tourism, and waste. European Sustainable Development Strategy is identifying and developing actions to enable the EU to achieve a continuous, long-term improvement of the quality of life through the creation of sustainable communities. The aim of this paper is to provide insight in Baltic Sea Region case studies on implemented actions on tourism industry waste and beach wrack management in coastal areas, hazardous contaminants and plastic flow treatment from waste, wastewaters and stormwaters. These projects mentioned in study promote successful prevention of contaminant flows to the sea environments and provide perspectives for creation of valuable new products from residuals for future circular economy are the step forward to green innovation winning streak.

Keywords: Resilience, hazardous waste, phytoremediation, water management, circular economy.

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Authors: Amirhossein Karamoozian, Desheng Wu, Behzad Abbasnejad

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Building information modelling (BIM) is a new technology to enhance the efficiency of project management in the construction industry. In addition to the potential benefits of this useful technology, there are various risks and obstacles to applying it in construction projects. In this study, a decision making approach is presented for risk assessment in BIM adoption in construction projects. Various risk factors of exerting BIM during different phases of the project lifecycle are identified with the help of Delphi method, experts’ opinions and related literature. Afterward, Shannon’s entropy and Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) are applied to derive priorities of the identified risk factors. Results indicated that lack of knowledge between professional engineers about workflows in BIM and conflict of opinions between different stakeholders are the risk factors with the highest priority.

Keywords: Risk, BIM, Shannon’s entropy, Fuzzy TOPSIS, construction projects.

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Authors: Y. Q. Lv, C.K.M. Lee

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This paper develops a quality estimation method with the application of fuzzy hierarchical clustering. Quality estimation is essential to quality control and quality improvement as a precise estimation can promote a right decision-making in order to help better quality control. Normally the quality of finished products in manufacturing system can be differentiated by quality standards. In the real life situation, the collected data may be vague which is not easy to be classified and they are usually represented in term of fuzzy number. To estimate the quality of product presented by fuzzy number is not easy. In this research, the trapezoidal fuzzy numbers are collected in manufacturing process and classify the collected data into different clusters so as to get the estimation. Since normal hierarchical clustering methods can only be applied for real numbers, fuzzy hierarchical clustering is selected to handle this problem based on quality standards.

Keywords: Quality Estimation, Fuzzy Quality Mean, Fuzzy Hierarchical Clustering, Fuzzy Number, Manufacturing system

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Authors: Yousra Zakaria Ahmed, Ahmed El Gendy, Salah El Haggar

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In this paper, our methodology to assess sustainability of wastewater treatment technologies in Egypt is presented. The preliminary list of factors to be considered, as well as their ranking listed. The factors include, but are not limited to pollutants removal efficiency and energy consumption under the environmental dimension, construction cost, operation and maintenance costs and required land area cost under the economic dimension and public acceptance, noise and generating job opportunities for local residents. This methodology is intended to be a user-friendly screening tool to support the decision making process when investigating different wastewater treatment technologies in Egypt. Based on the research work results presented in this paper, it can be generally concluded that the categorization of some of the social and environmental aspects of sustainability is subjective and highly dependent on the local conditions and researchers’ background.

Keywords: Sustainability, wastewater treatment, sustainability assessment, Egypt.

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Authors: Masaaki Saito, Qin Tang, Hiroyuki Umemuro

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The purpose of this paper is to propose a text mining approach to evaluate companies- practices on affective management. Affective management argues that it is critical to take stakeholders- affects into consideration during decision-making process, along with the traditional numerical and rational indices. CSR reports published by companies were collected as source information. Indices were proposed based on the frequency and collocation of words relevant to affective management concept using text mining approach to analyze the text information of CSR reports. In addition, the relationships between the results obtained using proposed indices and traditional indicators of business performance were investigated using correlation analysis. Those correlations were also compared between manufacturing and non-manufacturing companies. The results of this study revealed the possibility to evaluate affective management practices of companies based on publicly available text documents.

Keywords: Affective management, Affect, Stakeholder, Text mining.

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Authors: Dhanashree Nansaheb Kharde, Justus Selwyn

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These days customer satisfaction plays vital role in any business. When customer searches for a product, significantly a junk of irrelevant information is what is given, leading to customer dissatisfaction. To provide exactly relevant information on the searched product, we are proposing a model of KaaS (Knowledge as a Service), which pre-processes the information using decision making paradigm using Multi-agents. Information obtained from various sources is taken to derive knowledge and they are linked to Cloud to capture new idea. The main focus of this work is to acquire relevant information (knowledge) related to product, then convert this knowledge into a service for customer satisfaction and deploy on cloud. For achieving these objectives we are have opted to use multi agents. They are communicating and interacting with each other, manipulate information, provide knowledge, to take decisions. The paper discusses about KaaS as an intelligent approach for Knowledge acquisition.

Keywords: Knowledge acquisition, multi-agents, intelligent user interface, ontology, intelligent agent.

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Authors: Arati Siddharth Petkar, Joel E. M. Macwan

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Preferences for residential location are of a diverse nature. Primarily they are based on the socio-economic, socio-cultural, socio-demographic characteristics of the household. It also depends on character, and the growth potential of different areas in a city. In the present study, various criteria affecting residential location preferences from the Urban Dwellers’ perspective have been analyzed. The household survey has been conducted in two parts: Existing Buyers’ survey and Future Buyers’ survey. The analysis reveals that workplace location is the most governing criterion in deciding residential location from the majority of the urban dwellers perspective. For analyzing the importance of varied criteria, Analytical Hierarchy Process approach has been explored. The suggested approach will be helpful for urban planners, decision makers and developers, while designating a new residential area or redeveloping an existing one.

Keywords: Analytical hierarchy process, household, preferences, residential location preferences, residential land use, urban dwellers.

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Authors: Prateep Wajeetongratana

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This study is a descriptive-normative research. It attempted to investigate the restaurants’ firm performance in terms of the customers and restaurant personnel’s degree of satisfaction. A total of 12 restaurants in Bangkok, Thailand that offer Thai cuisine were included in this study. It involved 24 stockholders/managers, 120 subordinates and 360 customers. General Managers and restaurants’ stockholders, 10 staffs, and 30 costumers for each restaurant were chosen for random sampling. This study found that respondents are slightly satisfied with their work environment but are generally satisfied with the accessibility to transportation, to malls, convenience, safety, recreation, noise-free, and attraction; customers find the Quality of Food in most Thai Cuisines like services, prices of food, sales promotion, and capital and length of service satisfactory. Therefore, both stockholder-related and personnel-related factors which are influenced by restaurant, personnel, and customer-related factors are partially accepted whereas; customer-related factors which are influenced by restaurant, personnel and customer-related factors are rejected.

Keywords: Firm performance, Thai Cuisine, Tourism industry.

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Authors: Siva Prasad Darla, C. D. Naiju, K. Annamalai, Y. Upendra Sravan

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In recent years, environment regulation forcing manufactures to consider recovery activity of end-of- life products and/or return products for refurbishing, recycling, remanufacturing/repair and disposal in supply chain management. In this paper, a mathematical model is formulated for single product production-inventory system considering remanufacturing/reuse of return products and rate of return products follows a demand like function, dependent on purchasing price and acceptance quality level. It is useful in decision making to determine whether to go for remanufacturing or disposal of returned products along with newly produced products to satisfy a stationary demand. In addition, a modified genetic algorithm approach is proposed, inspired by particle swarm optimization method. Numerical analysis of the case study is carried out to validate the model.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Production, Remanufacturing.

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Authors: Thiago R. Pereira

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The philosophical hermeneutics is able to change the Brazilian Judiciary because of the understanding of the characteristics of the human being. It is impossible for humans, to be invested in the function of being a judge, making absolutely neutral decisions, but the philosophical hermeneutics can assist the judge making impartial decisions, based on the federal constitution. The normative legal positivism imagined a neutral judge, a judge able to try without any preconceived ideas, without allowing his/her background to influence him/her. When a judge arbitrates based on legal rules, the problem is smaller, but when there are no clear legal rules, and the judge must try based on principles, the risk of the decision is based on what they believe in. Solipsistically, this issue gains a huge dimension. Today, the Brazilian judiciary is independent, but there must be a greater knowledge of philosophy and the philosophy of law, partially because the bigger problem is the unpredictability of decisions made by the judiciary. Actually, when a lawsuit is filed, the result of this judgment is absolutely unpredictable. It is almost a gamble. There must be the slightest legal certainty and predictability of judicial decisions, so that people, with similar cases, may not receive opposite sentences. The relativism, since classical antiquity, believes in the possibility of multiple answers. Since the Greeks in in the sixth century before Christ, through the Germans in the eighteenth century, and even today, it has been established the constitution as the great law, the Groundnorm, and thus, the relativism of life can be greatly reduced when a hermeneut uses the Constitution as North interpretational, where all interpretation must act as the hermeneutic constitutional filter. For a current philosophy of law, that inside a legal system with a Federal Constitution, there is a single correct answer to a specific case. The challenge is how to find this right answer. The only answer to this question will be that we should use the constitutional principles. But in many cases, a collision between principles will take place, and to resolve this issue, the judge or the hermeneut will choose a solipsism way, using what they personally believe to be the right one. For obvious reasons, that conduct is not safe. Thus, a theory of decision is necessary to seek justice, and the hermeneutic philosophy and the linguistic turn will be necessary for one to find the right answer. In order to help this difficult mission, it will be necessary to use philosophical hermeneutics in order to find the right answer, which is the constitutionally most appropriate response. The constitutionally appropriate response will not always be the answer that individuals agree to, but we must put aside our preferences and defend the answer that the Constitution gives us. Therefore, the hermeneutics applied to Law, in search constitutionally appropriate response, should be the safest way to avoid judicial individual decisions. The aim of this paper is to present the science of law starting from the linguistic turn, the philosophical hermeneutics, moving away from legal positivism. The methodology used in this paper is qualitative, academic and theoretical, philosophical hermeneutics with the mission to conduct research proposing a new way of thinking about the science of law. The research sought to demonstrate the difficulty of the Brazilian courts to depart from the secular influence of legal positivism. Moreover, the research sought to demonstrate the need to think science of law within a contemporary perspective, where the linguistic turn, philosophical hermeneutics, will be the surest way to conduct the science of law in the present century.

Keywords: Hermeneutic, right answer, solipsism, Brazilian Judiciary.

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Authors: Giovanni Luca Masala

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A typical definition of the Computer Aided Diagnosis (CAD), found in literature, can be: A diagnosis made by a radiologist using the output of a computerized scheme for automated image analysis as a diagnostic aid. Often it is possible to find the expression Computer Aided Detection (CAD or CADe): this definition emphasizes the intent of CAD to support rather than substitute the human observer in the analysis of radiographic images. In this article we will illustrate the application of CAD systems and the aim of these definitions. Commercially available CAD systems use computerized algorithms for identifying suspicious regions of interest. In this paper are described the general CAD systems as an expert system constituted of the following components: segmentation / detection, feature extraction, and classification / decision making. As example, in this work is shown the realization of a Computer- Aided Detection system that is able to assist the radiologist in identifying types of mammary tumor lesions. Furthermore this prototype of station uses a GRID configuration to work on a large distributed database of digitized mammographic images.

Keywords: Computer Aided Detection, Computer Aided Diagnosis, mammography, GRID.

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Authors: Vitalice K. Oduol, C. Ardil

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A method is presented for obtaining the error probability for block codes. The method is based on the eigenvalueeigenvector properties of the code correlation matrix. It is found that under a unary transformation and for an additive white Gaussian noise environment, the performance evaluation of a block code becomes a one-dimensional problem in which only one eigenvalue and its corresponding eigenvector are needed in the computation. The obtained error rate results show remarkable agreement between simulations and analysis.

Keywords: bit error rate, block codes, code correlation matrix, eigenstructure, soft-decision decoding, weight vector.

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Authors: Madina Hamiane, Amina Khunji

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Detecting changes in multiple images of the same scene has recently seen increased interest due to the many contemporary applications including smart security systems, smart homes, remote sensing, surveillance, medical diagnosis, weather forecasting, speed and distance measurement, post-disaster forensics and much more. These applications differ in the scale, nature, and speed of change. This paper presents an application of image processing techniques to implement a real-time change detection system. Change is identified by comparing the RGB representation of two consecutive frames captured in real-time. The detection threshold can be controlled to account for various luminance levels. The comparison result is passed through a filter before decision making to reduce false positives, especially at lower luminance conditions. The system is implemented with a MATLAB Graphical User interface with several controls to manage its operation and performance.

Keywords: Image change detection, Image processing, image filtering, thresholding, B/W quantization.

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Authors: Takayuki Shiina

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Mathematical programming has been applied to various problems. For many actual problems, the assumption that the parameters involved are deterministic known data is often unjustified. In such cases, these data contain uncertainty and are thus represented as random variables, since they represent information about the future. Decision-making under uncertainty involves potential risk. Stochastic programming is a commonly used method for optimization under uncertainty. A stochastic programming problem with recourse is referred to as a two-stage stochastic problem. In this study, we consider a stochastic programming problem with simple integer recourse in which the value of the recourse variable is restricted to a multiple of a nonnegative integer. The algorithm of a dynamic slope scaling procedure for solving this problem is developed by using a property of the expected recourse function. Numerical experiments demonstrate that the proposed algorithm is quite efficient. The stochastic programming model defined in this paper is quite useful for a variety of design and operational problems.

Keywords: stochastic programming problem with recourse, simple integer recourse, dynamic slope scaling procedure

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Authors: Kitti Koonsanit, Chuleerat Jaruskulchai, Poonsak Miphokasap, Apisit Eiumnoh

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In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.

Keywords: Plant varieties selection system, decision tree, expert recommendation.

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Authors: D. Uma Devi, P. Seetha Ramaiah

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Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using fuzzy theory. Our previous work concentrated on a neuro-fuzzy algorithm where training using the neuro system substantially improved the prediction result of the voting system. Weight training of Neural Network is sub-optimal. This study proposes to optimize the weights of the Neural Network using Artificial Bee Colony algorithm. Experimental results show the proposed system improves the decision making of the voting algorithms.

Keywords: Voting algorithms, Fault tolerance, Fault masking, Neuro-Fuzzy System (NFS), Artificial Bee Colony (ABC)

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Authors: Miho Tsukamoto

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Beppu hot spring provides medical treatment as well as comfort visitors and mental easiness for many years. This paper studies hot spring in Beppu and Tōji, medical treatment in hot spring, and investigates how people’s visit to Beppu has changed with Tōji, and how Beppu Tourism Office tries to regain visitors in Beppu. In this paper, firstly, hot spring history in Beppu will be explained especially focusing on Beppu Hattou (eight major hot springs) and Jigoku Meguri (eight major hell hot spring tours). Secondly, Tōji, a long-residential hot spring with the purpose of medical treatment along with the information about chemical efficacy of hot springs will be analyzed. Then, finally, the change of the long-stay type to short-stay Onsen programs with the combination of multiplex tourism resources will be focused along with the decrease of Onsen or hot spring visitors. It is concluded that Tōji is not only physically and mentally cure people but also bring people mental easiness and release them from their stressful life. All in all, it can be concluded that because Onsen is involved in people’s life in Beppu and keep local people united in the community. Tōji’s attraction is shown when local people try to create the new type of Onsen program so as to keep their traditional way of Tōji.

Keywords: Hot spring, Tōji, Treatment.

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Authors: Kong Fah Tee, Lutfor Rahman Khan, Hongshuang Li

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An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.

Keywords: Underground pipelines, Probability of failure, Reliability and Subset Simulation.

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Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai

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Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper, a novel automatic method which combined Genetic Algorithm (GA) and classification algorithm to extract classification features is proposed. In this method, the optimal features and classification model are approached via evolutional study step by step. It is proved by theory analysis and experiment test that this method has advantages in improving classification efficiency, precision and robustness whereas using less features and the dimension of extracted classification features can be controlled.

Keywords: Classification, functional data, feature extraction, genetic algorithm, wavelet.

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Authors: Muslihah Wook, Zawiyah M. Yusof, Mohd Zakree Ahmad Nazri

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Data mining has been integrated into application systems to enhance the quality of the decision-making process. This study aims to focus on the integration of data mining technology and Knowledge Management System (KMS), due to the ability of data mining technology to create useful knowledge from large volumes of data. Meanwhile, KMS vitally support the creation and use of knowledge. The integration of data mining technology and KMS are popularly used in business for enhancing and sustaining organizational performance. However, there is a lack of studies that applied data mining technology and KMS in the education sector; particularly students- academic performance since this could reflect the IHL performance. Realizing its importance, this study seeks to integrate data mining technology and KMS to promote an effective management of knowledge within IHLs. Several concepts from literature are adapted, for proposing the new integrative data mining technology and KMS framework to an IHL.

Keywords: Data mining, Institutions of Higher Learning, Knowledge Management System, Students' academic performance.

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Authors: Shaheena Erkiah, Adjnu Damar Ladkoo

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Worldwide, improving tourism competitiveness has been on the agendas of many stakeholders of the hotel sector, and they seem to have agreed that one of the best ways to compete is via the implementation of electronic customer relationship management (e-CRM). In so doing, the organizations enjoy strategic positioning on the competitive market by managing better not only the customers but, other business components including knowledge and employee management. Over the recent years, the tourism industry in Mauritius has witnessed a drastic economic boom at international and national levels; providing a new outlook to boost business performance through existing and potential customers. E-CRM has been one of the management tools used to achieving this position. Thus, this insightful context- Mauritius- was opted for the study. The aim was to assess the effectiveness of e-CRM as a strategic tool in the hotel sector in Mauritius through the implementation of business strategy to create competitive advantage and impact on the business performance. To achieve the objectives of the study, a quantitative research methodology was adopted and the research revealed that e-CRM is indeed an effective strategic tool in the hotel industry in Mauritius that can provide a competitive advantage and impact positively on the organization’s performance.

Keywords: Customer, electronic, management, relationship, strategic.

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Authors: J. Maksimainen

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The values of managers and employees in organizations are phenomena that have captured the interest of researchers at large. Despite this attention, there continues to be a lack of agreement on what values are and how they influence individuals, or how they are constituted in individuals- mind. In this article content-based approach is presented as alternative reference frame for exploring values. In content-based approach human thinking in different contexts is set at the focal point. Differences in valuations can be explained through the information contents of mental representations. In addition to the information contents, attention is devoted to those cognitive processes through which mental representations of values are constructed. Such informational contents are in decisive role for understanding human behavior. By applying content-based analysis to an examination of values as mental representations, it is possible to reach a deeper to the motivational foundation of behaviors, such as decision making in organizational procedures, through understanding the structure and meanings of specific values at play.

Keywords: Content-based Approach, Mental Content, Mental Representations, Organizational values, Values

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Authors: Mohammadreza Razzazi, Maryam Bayat

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Selection of the best possible set of suppliers has a significant impact on the overall profitability and success of any business. For this reason, it is usually necessary to optimize all business processes and to make use of cost-effective alternatives for additional savings. This paper proposes a new efficient context-aware supplier selection model that takes into account possible changes of the environment while significantly reducing selection costs. The proposed model is based on data clustering techniques while inspiring certain principles of online algorithms for an optimally selection of suppliers. Unlike common selection models which re-run the selection algorithm from the scratch-line for any decision-making sub-period on the whole environment, our model considers the changes only and superimposes it to the previously defined best set of suppliers to obtain a new best set of suppliers. Therefore, any recomputation of unchanged elements of the environment is avoided and selection costs are consequently reduced significantly. A numerical evaluation confirms applicability of this model and proves that it is a more optimal solution compared with common static selection models in this field.

Keywords: Supplier Selection, Context-Awareness, OnlineAlgorithms, Data Clustering.

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Authors: Abdallah A. Alshennawy, Ayman A. Aly

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The fuzzy technique is an operator introduced in order to simulate at a mathematical level the compensatory behavior in process of decision making or subjective evaluation. The following paper introduces such operators on hand of computer vision application. In this paper a novel method based on fuzzy logic reasoning strategy is proposed for edge detection in digital images without determining the threshold value. The proposed approach begins by segmenting the images into regions using floating 3x3 binary matrix. The edge pixels are mapped to a range of values distinct from each other. The robustness of the proposed method results for different captured images are compared to those obtained with the linear Sobel operator. It is gave a permanent effect in the lines smoothness and straightness for the straight lines and good roundness for the curved lines. In the same time the corners get sharper and can be defined easily.

Keywords: Fuzzy logic, Edge detection, Image processing, computer vision, Mechanical parts, Measurement.

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Authors: M. Mahli, A.I. Che-Ani, M.Z. Abd-Razak. N.M. Tawil, H. Yahaya

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Building condition assessment is a critical activity in Malaysia-s Comprehensive Asset Management Model. It is closely related to building performance that impact user-s life and decision making. This study focuses on public primary school, one of the most valuable assets for the country. The assessment was carried out based on CSP1 Matrix in Kuching Division of Sarawak, Malaysia. Based on the matrix used, three main criteria of the buildings has successfully evaluate: the number of defects; schools rating; and total schools rating. The analysis carried out on 24 schools found that the overall 4, 725 defects has been identified. Meanwhile, the overall score obtained was 45, 868 and the overall rating is 9.71, which is at the fair condition. This result has been associated with building age to evaluate its impacts on school buildings condition. The findings proved that building condition is closely related to building age and its support the theory that 'the ageing building has more defect than the new one'.

Keywords: building condition, CSP1 Matrix, assessment, school, Malaysia

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Authors: David Wiese

Abstract:

In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.

Keywords: Data Warehousing, OLAP, Multidimensional Navigation, Performance Diagnosis, Performance Management, Performance Tuning.

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