Search results for: Language Decision

Authors: Soottipoom Yaowiwat, Manoj Lohatepanont, Proadpran Punyabukkana

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Several approaches such as linear programming, network modeling, greedy heuristic and decision support system are well-known approaches in solving irregular airline operation problem. This paper presents an alternative approach based on Multi Objective Micro Genetic Algorithm. The aim of this research is to introduce the concept of Multi Objective Micro Genetic Algorithm as a tool to solve irregular airline operation, combine and reroute problem. The experiment result indicated that the model could obtain optimal solutions within a few second.

Keywords: Irregular Airline Operation, Combine and RerouteRoutine, Genetic Algorithm, Micro Genetic Algorithm, Multi ObjectiveOptimization, Evolutionary Algorithm.

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Authors: Amalia Suzianti

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This research elaborates decision models for product innovation in the early phases, focusing on one of the most widely implemented method in marketing research: conjoint analysis and the related conjoint-based models with special focus on heuristics programming techniques for the development of optimal product innovation. The concept, potential, requirements and limitations of conjoint analysis and its conjoint-based heuristics successors are analysed and the development of conceptual framework of Genetic Algorithm (GA) as one of the most widely implemented heuristic methods for developing product innovations are discussed.

Keywords: Product Innovation, Conjoint Analysis, Heuristic Model, Genetic Algorithm

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Authors: An-Shik Yang, Chiang-Ho Cheng, Jen-Hao Wu, Yu-Hsuan Juan

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Natural ventilation has played an important role for many low energy-building designs. It has been also noticed as a essential subject to persistently bring the fresh cool air from the outside into a building. This study carried out the computational fluid dynamics (CFD)-based simulations to examine the natural ventilation development of a work area in a public building. The simulated results can be useful to better understand the indoor microclimate and the interaction of wind with buildings. Besides, this CFD simulation procedure can serve as an effective analysis tool to characterize the airing performance, and thereby optimize the building ventilation for strengthening the architects, planners and other decision makers on improving the natural ventilation design of public buildings.

Keywords: CFD simulations, Natural ventilation, Microclimate, Wind environment.

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Authors: Zhizhong Jiang, Craig Comstock

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The past decade has seen enormous growth in the amount of software produced. However, given the ever increasing complexity of the software being developed and the concomitant rise in the typical project size, managers are becoming increasingly aware of the importance of issues that influence the productivity levels of the project teams involved. By analyzing the latest release of ISBSG data repository, we report on the factors found to significantly influence the productivity among which average team size and language type are the two most essential ones. Building on this we present an original model for evaluating the potential productivity during the project planning stage.

Keywords: ISBSG, Linear Model, Productivity, SoftwareEngineering.

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Authors: Nam Lethanh, Bryan T. Adey

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In this paper, the potential use of an exponential hidden Markov model to model a hidden pavement deterioration process, i.e. one that is not directly measurable, is investigated. It is assumed that the evolution of the physical condition, which is the hidden process, and the evolution of the values of pavement distress indicators, can be adequately described using discrete condition states and modeled as a Markov processes. It is also assumed that condition data can be collected by visual inspections over time and represented continuously using an exponential distribution. The advantage of using such a model in decision making process is illustrated through an empirical study using real world data.

Keywords: Deterioration modeling, Exponential distribution, Hidden Markov model, Pavement management

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Authors: Bharatendra Rai

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Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.

Keywords: Degradation signal, drill-bit breakage, random forest, multinomial logistic regression.

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Authors: E. Mike Dison, T. Pathinathan

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Computing with Words (CWW) and Possibilistic Relational Universal Fuzzy (PRUF) are the two concepts which widely represent and measure the vaguely defined natural phenomenon. In this paper, we study the positional alteration of the phrases by which the impact of a natural language proposition gets affected and/or modified. We observe the gradations due to sensitivity/feeling of a statement towards the positional alterations. We derive the classification and modification of the meaning of words due to the positional alteration. We present the results with reference to set theoretic interpretations.

Keywords: Appositive, computing with words, PRUF, semantic sentiment analysis, set theoretic interpretations.

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Authors: S. Thirumurugan, D. R. Prince Williams

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Software Reliability is one of the key factors in the software development process. Software Reliability is estimated using reliability models based on Non Homogenous Poisson Process. In most of the literature the Software Reliability is predicted only in testing phase. So it leads to wrong decision-making concept. In this paper, two Software Reliability concepts, testing and operational phase are studied in detail. Using S-Shaped Software Reliability Growth Model (SRGM) and Exponential SRGM, the testing and operational reliability values are obtained. Finally two reliability values are compared and optimal release time is investigated.

Keywords: Error Detection Rate, Estimation of Parameters, Instantaneous Failure Rate, Mean Value Function, Non Homogenous Poisson Process (NHPP), Software Reliability.

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Authors: Youguo Wang, Lenan Wu

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Stochastic resonance (SR) is a phenomenon whereby the signal transmission or signal processing through certain nonlinear systems can be improved by adding noise. This paper discusses SR in nonlinear signal detection by a simple test statistic, which can be computed from multiple noisy data in a binary decision problem based on a maximum a posteriori probability criterion. The performance of detection is assessed by the probability of detection error Per . When the input signal is subthreshold signal, we establish that benefit from noise can be gained for different noises and confirm further that the subthreshold SR exists in nonlinear signal detection. The efficacy of SR is significantly improved and the minimum of Per can dramatically approach to zero as the sample number increases. These results show the robustness of SR in signal detection and extend the applicability of SR in signal processing.

Keywords: Probability of detection error, signal detection, stochastic resonance.

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Authors: H. Ali, K. Hameed, N. Khan

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In DMVC, we have more than one options of sources available for construction of side information. The newer techniques make use of both the techniques simultaneously by constructing a bitmask that determines the source of every block or pixel of the side information. A lot of computation is done to determine each bit in the bitmask. In this paper, we have tried to define areas that can only be well predicted by temporal interpolation and not by multiview interpolation or synthesis. We predict that all such areas that are not covered by two cameras cannot be appropriately predicted by multiview synthesis and if we can identify such areas in the first place, we don-t need to go through the script of computations for all the pixels that lie in those areas. Moreover, this paper also defines a technique based on KLT to mark the above mentioned areas before any other processing is done on the side view.

Keywords: Side Information, Distributed Multiview Video Coding, Fusion, Early Decision.

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Authors: Antonio Di Leva, Carla Reyneri, Michele Sonnessa

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PARADIGMA (PARticipative Approach to DIsease Global Management) is a pilot project which aims to develop and demonstrate an Internet based reference framework to share scientific resources and findings in the treatment of major diseases. PARADIGMA defines and disseminates a common methodology and optimised protocols (Clinical Pathways) to support service functions directed to patients and individuals on matters like prevention, posthospitalisation support and awareness. PARADIGMA will provide a platform of information services - user oriented and optimised against social, cultural and technological constraints - supporting the Health Care Global System of the Euro-Mediterranean Community in a continuous improvement process.

Keywords: Decision Support Systems, Ontology, Healt Care, Clinical Pathway

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Authors: R. Gunabalan, S. Immanuel Prabakaran, J. Reegan, S. Ganesh

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This paper describes a software approach for modeling inverter fed induction motor drive using Laboratory Virtual Instrument Engineering Workbench (LabVIEW). The reason behind the selection of LabVIEW software is because of its strong graphical interface, flexibility of its programming language combined with built-in tools designed specifically for test, measurement and control. LabVIEW is generally used in most of the applications for data acquisition, test and control. In this paper, inverter and induction motor are modeled using LabVIEW toolkits. Simulation results are presented and are validated.

Keywords: Induction motor, LabVIEW, State model.

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Authors: C. Nallusamy, A. Sabari, K. Suganya

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Geographical routing protocol requires node physical location information to make forwarding decision. Geographical routing uses location service or position service to obtain the position of a node. The geographical information is a geographic coordinates or can be obtained through reference points on some fixed coordinate system. Link can be formed between two nodes. Link lifetime plays a crucial role in MANET. Link lifetime represent how long the link is stable without any failure between the nodes. Link failure may occur due to mobility and because of link failure energy of nodes can be drained. Thus this paper proposes survey about link lifetime prediction using geographical information.

Keywords: MANET, Geographical routing, Link lifetime, Link stability.

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Authors: Phanu Waraporn

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This paper discusses the designing of knowledge integration of clinical information extracted from distributed medical ontologies in order to ameliorate a machine learning-based multilabel coding assignment system. The proposed approach is implemented using a decision tree technique of the machine learning on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding that the use of medical ontologies improves the overall system performance.

Keywords: Medical Ontology, Knowledge Integration, Machine Learning, Medical Coding, Text Assignment.

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Authors: Valene J. Gresham, MA, Laura A. Brodie

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For the last decade, statistics show traumatic brain injury (TBI) is a growing concern in our legal system. In an effort to obtain data regarding the influence of neuropsychological expert witness testimony in a criminal case, this study tested three hypotheses. H1: The majority of jurors will vote not guilty, due to mild head injury. H2: The jurors will give more credence to the testimony of the neuropsychologist rather than the psychiatrist. H3: The jurors will be more lenient in their sentencing, given the testimony of the neuropsychologist-s testimony. The criterion for inclusion in the study as a participant is identical to those used for inclusion in the eligibility for jury duty in the United States. A chisquared test was performed to analyze the data for the three hypotheses. The results supported all of the hypotheses; however statistical significance was seen in H1 and H2 only.

Keywords: Expert witness, jury decision, neuropsychology, traumatic brain injury.

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Authors: R. B. Ogunrinde

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This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.

Keywords: Differential equations, Numerical, Initial value problem, Polynomials.

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Authors: Jong-Bae Lee, Seongsoo Lee

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Local interconnect network (LIN) is a communication protocol that combines sensors, actuators, and processors to a functional module in automotive applications. In this paper, a LIN ver. 2.2A controller was designed in Verilog hardware description language (Verilog HDL) and implemented in field-programmable gate array (FPGA). Its operation was verified by making full-scale LIN network with the presented FPGA-implemented LIN controller, commercial LIN transceivers, and commercial processors. When described in Verilog HDL and synthesized in 0.18 μm technology, its gate size was about 2,300 gates.

Keywords: Local interconnect network, controller, transceiver, processor.

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Authors: Ewa. M. Sztendur, Neil T. Diamond

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Random Forests are a powerful classification technique, consisting of a collection of decision trees. One useful feature of Random Forests is the ability to determine the importance of each variable in predicting the outcome. This is done by permuting each variable and computing the change in prediction accuracy before and after the permutation. This variable importance calculation is similar to a one-factor-at a time experiment and therefore is inefficient. In this paper, we use a regular fractional factorial design to determine which variables to permute. Based on the results of the trials in the experiment, we calculate the individual importance of the variables, with improved precision over the standard method. The method is illustrated with a study of student attrition at Monash University.

Keywords: Random Forests, Variable Importance, Fractional Factorial Designs, Student Attrition.

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Authors: St. Karagiannis, A. I. Dounis, T. Chalastras, P. Tiropanis, D. Papachristos

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This work presents the design of an expert system that aims in the procurement of patient medial background and in the search for suitable skin test selections. Skin testing is the tool used most widely to diagnose allergies. The language of expert systems CLIPS is used as a tool of designing. Finally, we present the evaluation of the proposed expert system which was achieved with the import of certain medical cases and the system produced with suitable successful skin tests.

Keywords: Artificial intelligence, expert system - CLIPS, allergy and skin test.

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Authors: Michael Harre, Terry Bossomaier, Ranqing Chu, Allan Snyder

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We introduce a novel approach to measuring how humans learn based on techniques from information theory and apply it to the oriental game of Go. We show that the total amount of information observable in human strategies, called the strategic information, remains constant for populations of players of differing skill levels for well studied patterns of play. This is despite the very large amount of knowledge required to progress from the recreational players at one end of our spectrum to the very best and most experienced players in the world at the other and is in contrast to the idea that having more knowledge might imply more 'certainty' in what move to play next. We show this is true for very local up to medium sized board patterns, across a variety of different moves using 80,000 game records. Consequences for theoretical and practical AI are outlined.

Keywords: Board Games, Cognitive Capacity, Decision Theory, Information Theory.

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Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

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In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: Capacity-booking, SPA, monthly production planning, linear programming.

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Authors: Berrin Şentürk

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In this study, due to the recurrence of bovine tuberculosis, in the same areas, the risk factors for the disease were determined and evaluated at the local level. This study was carried out in 32 farms where the disease was detected in the district and center of Samsun province in 2014. Predetermined risk factors, such as farm, environmental and economic risks, were investigated with the survey method. It was predetermined that risks in the three groups are similar to the risk variables of the disease on the global scale. These risk factors that increase the susceptibility of the infection must be understood by the herd owners. The risk-based contagious disease management system approach should be applied for bovine tuberculosis by farmers, animal health professionals and public and private sector decision makers.

Keywords: Bovine tuberculosis, disease management, control, outbreak, risk analysis.

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Authors: Abbas Al-Refaie

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The research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC.

Keywords: Cluster analysis, telecom industry, switching cost, customer churn.

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Authors: Uday Hameed Farhan, Majid Tolouei-Rad, Simona O'Brien

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Modular fixtures (MFs) are very important tools in manufacturing processes in terms of reduction the cost and the production time. This paper introduces an automated approach for assembling MFs elements by employing SolidWorks as a powerful 3D CAD software. Visual Basic (VB) programming language was applied integrating with SolidWorks API (Application programming interface) functions. This integration allowed creating plug-in file and generating new menus in the SolidWorks environment. The menus allow the user to select, insert, and assemble MFs elements.

Keywords: Assembly automation, modular fixtures, SolidWorks, Visual Basic.

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Authors: Nafaâ Nacereddine, Latifa Hamami, Djemel Ziou

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In non destructive testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must be done judiciously. In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2-D histogram and locally adaptive approach for weld defect extraction in radiographic images.

Keywords: 1D and 2D histogram, locally adaptive approach, performance criteria, radiographic image, thresholding, weld defect.

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Authors: B. S. Bokuleva, R. A. Avakova, A. A. Sultangubieva, U. Schamiloglu

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It is discussed about modern usage of adopted words and their vocabularies, Turkism usage fields, phonetic, grammatical and lexis-semantic assimilation of the typological-morphological structures of entering to different Hindi languages in comparative typological aspects in this scientific article. The lexis vocabulary is rich, the prevalence area is wide and it has researched the entering process of vocabulary into the great languages of Turkic elements from the speakers- numbers. The research work has worked on the base of Hindi vocabulary.

Keywords: Adopted words, language communications, Turkism, Turkic languages.

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Authors: Defu Zhang, Qingshan Jiang, Xin Li

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This paper deals with the application of a well-known neural network technique, multilayer back-propagation (BP) neural network, in financial data mining. A modified neural network forecasting model is presented, and an intelligent mining system is developed. The system can forecast the buying and selling signs according to the prediction of future trends to stock market, and provide decision-making for stock investors. The simulation result of seven years to Shanghai Composite Index shows that the return achieved by this mining system is about three times as large as that achieved by the buy and hold strategy, so it is advantageous to apply neural networks to forecast financial time series, the different investors could benefit from it.

Keywords: Data mining, neural network, stock forecasting.

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Authors: M. Arja, G. Sauce, B. Souyri

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Overall cost is a significant consideration in any decision-making process. Although many studies were carried out on overall cost in construction, little has treated the uncertainties of real life cycle development. On the basis of several case studies, a feedback process was performed on the historical data of studied buildings. This process enabled to identify some factors causing uncertainty during the operational period. As a result, the research proposes a new method for assessing the overall cost during a part of the building-s life cycle taking account of the building actual value, its end-of-life value and the influence of the identified life cycle uncertainty factors. The findings are a step towards a higher level of reliability in overall cost evaluation taking account of some usually unexpected uncertainty factors.

Keywords: Asset management, building life cycle uncertainty, building value, overall cost.

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Authors: Su Cheng Haw, G. S. V. Radha Krishna Rao

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Over the past few years, XML (eXtensible Mark-up Language) has emerged as the standard for information representation and data exchange over the Internet. This paper provides a kick-start for new researches venturing in XML databases field. We survey the storage representation for XML document, review the XML query processing and optimization techniques with respect to the particular storage instance. Various optimization technologies have been developed to solve the query retrieval and updating problems. Towards the later year, most researchers proposed hybrid optimization techniques. Hybrid system opens the possibility of covering each technology-s weakness by its strengths. This paper reviews the advantages and limitations of optimization techniques.

Keywords: indexing, labeling scheme, query optimization, XML storage.

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Authors: Derya Eren Akyol, Gonca Tuncel, G. Mirac Bayhan

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Activity-Based Costing (ABC) represents an alternative paradigm to traditional cost accounting system and it often provides more accurate cost information for decision making such as product pricing, product mix, and make-orbuy decisions. ABC models the causal relationships between products and the resources used in their production and traces the cost of products according to the activities through the use of appropriate cost drivers. In this paper, the implementation of the ABC in a manufacturing system is analyzed and a comparison with the traditional cost based system in terms of the effects on the product costs are carried out to highlight the difference between two costing methodologies. By using this methodology, a valuable insight into the factors that cause the cost is provided, helping to better manage the activities of the company.

Keywords: Activity-based costing, manufacturing systems, product costs, traditional costing.

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