Search results for: center–focus problem
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4979

Search results for: center–focus problem

1619 Design of Nonlinear Observer by Using Augmented Linear System based on Formal Linearization of Polynomial Type

Authors: Kazuo Komatsu, Hitoshi Takata

Abstract:

The objective of this study is to propose an observer design for nonlinear systems by using an augmented linear system derived by application of a formal linearization method. A given nonlinear differential equation is linearized by the formal linearization method which is based on Taylor expansion considering up to the higher order terms, and a measurement equation is transformed into an augmented linear one. To this augmented dimensional linear system, a linear estimation theory is applied and a nonlinear observer is derived. As an application of this method, an estimation problem of transient state of electric power systems is studied, and its numerical experiments indicate that this observer design shows remarkable performances for nonlinear systems.

Keywords: nonlinear system, augmented linear system, nonlinear observer, formal linearization, electric power system.

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1618 Analytical Solution for Free Vibration of Rectangular Kirchhoff Plate from Wave Approach

Authors: Mansour Nikkhah-Bahrami, Masih Loghmani, Mostafa Pooyanfar

Abstract:

In this paper, an analytical approach for free vibration analysis of four edges simply supported rectangular Kirchhoff plates is presented. The method is based on wave approach. From wave standpoint vibration propagate, reflect and transmit in a structure. Firstly, the propagation and reflection matrices for plate with simply supported boundary condition are derived. Then, these matrices are combined to provide a concise and systematic approach to free vibration analysis of a simply supported rectangular Kirchhoff plate. Subsequently, the eigenvalue problem for free vibration of plates is formulated and the equation of plate natural frequencies is constructed. Finally, the effectiveness of the approach is shown by comparison of the results with existing classical solution.

Keywords: Kirchhoff plate, propagation matrix, reflection matrix, vibration analysis.

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1617 Specialization-based parallel Processing without Memo-trees

Authors: Hidemi Ogasawara, Kiyoshi Akama, Hiroshi Mabuchi

Abstract:

The purpose of this paper is to propose a framework for constructing correct parallel processing programs based on Equivalent Transformation Framework (ETF). ETF regards computation as In the framework, a problem-s domain knowledge and a query are described in definite clauses, and computation is regarded as transformation of the definite clauses. Its meaning is defined by a model of the set of definite clauses, and the transformation rules generated must preserve meaning. We have proposed a parallel processing method based on “specialization", a part of operation in the transformations, which resembles substitution in logic programming. The method requires “Memo-tree", a history of specialization to maintain correctness. In this paper we proposes the new method for the specialization-base parallel processing without Memo-tree.

Keywords: Parallel processing, Program correctness, Equivalent transformation, Specializer generation rule

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1616 Improving Load Frequency Control of Multi-Area Power System by Considering Uncertainty by Using Optimized Type 2 Fuzzy Pid Controller with the Harmony Search Algorithm

Authors: Mehrdad Mahmudizad, Roya Ahmadi Ahangar

Abstract:

This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers.

Keywords: Load Frequency Control, Fuzzy-PID controller, Type 2 fuzzy system, Harmony Search algorithm.

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1615 Optimal Bayesian Control of the Proportion of Defectives in a Manufacturing Process

Authors: Viliam Makis, Farnoosh Naderkhani, Leila Jafari

Abstract:

In this paper, we present a model and an algorithm for the calculation of the optimal control limit, average cost, sample size, and the sampling interval for an optimal Bayesian chart to control the proportion of defective items produced using a semi-Markov decision process approach. Traditional p-chart has been widely used for controlling the proportion of defectives in various kinds of production processes for many years. It is well known that traditional non-Bayesian charts are not optimal, but very few optimal Bayesian control charts have been developed in the literature, mostly considering finite horizon. The objective of this paper is to develop a fast computational algorithm to obtain the optimal parameters of a Bayesian p-chart. The decision problem is formulated in the partially observable framework and the developed algorithm is illustrated by a numerical example.

Keywords: Bayesian control chart, semi-Markov decision process, quality control, partially observable process.

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1614 Polymorphic Marker Designed from Bioinformatics Sequences Related to Cell Wall Strength for Discrimination of Mangosteen (Garcinia mangostana L.) Clones Resistant to Gamboge Disorder

Authors: E. Mansyah, Sobir, E. Santosa, A. Sisharmini, Sulassih

Abstract:

Gamboge disorder (GD) or fruit damage by the yellow sap is a major problem in mangosteen. Mangosteen plants varied in the level of GD, from very low or non GD to low, moderate and high GD. However it was difficult to differentiate between GD and non GD plants because evaluation of the disorder is strongly influenced by environment. In this study we investigated the usefulness of primer designed from bioinformatics related to cell wall strength, termed as MCWS, to predict GD. Plant materials used were 28 mangosteen plants selected based on percentage of GD categorized as high, moderate, low and very low or non GD. The result showed that the specific DNA fragments were absent in the high GD accessions. The MCWS marker suggests as a novel polymorphic marker for GD in mangosteen as well as a marker for detect variability in mangosteen as apomictic plant.

Keywords: Bioinformatics, cell wall strength, gamboge disorder, mangosteen, polymorphic marker.

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1613 A Decision Boundary based Discretization Technique using Resampling

Authors: Taimur Qureshi, Djamel A Zighed

Abstract:

Many supervised induction algorithms require discrete data, even while real data often comes in a discrete and continuous formats. Quality discretization of continuous attributes is an important problem that has effects on speed, accuracy and understandability of the induction models. Usually, discretization and other types of statistical processes are applied to subsets of the population as the entire population is practically inaccessible. For this reason we argue that the discretization performed on a sample of the population is only an estimate of the entire population. Most of the existing discretization methods, partition the attribute range into two or several intervals using a single or a set of cut points. In this paper, we introduce a technique by using resampling (such as bootstrap) to generate a set of candidate discretization points and thus, improving the discretization quality by providing a better estimation towards the entire population. Thus, the goal of this paper is to observe whether the resampling technique can lead to better discretization points, which opens up a new paradigm to construction of soft decision trees.

Keywords: Bootstrap, discretization, resampling, soft decision trees.

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1612 Towards the Design of a GIS-Linked Agent-Based Model for the Lake Chad Basin Region: Challenges and Opportunities

Authors: Stephen Akuma, Isaac Terngu Adom, Evelyn Doofan Akuma

Abstract:

Generation after generation of humans has experienced conflicts leading to needless deaths. Usually, it begins as a minor argument that occasionally escalates into a full-fledged conflict. There has been a lingering crisis in the Lake Chad Basin (LCB) of Africa for over a decade leading to bloodshed that has claimed thousands of lives. The terrorist group, Boko Haram has claimed responsibility for these deaths. Efforts have been made by the governments in the LCB region to end the crisis through kinetic approaches, but the conflict persists. In this work, we explored non-kinetic methods used by social scientists in resolving conflicts, with a focus on computational approaches due to the increasing processing power of the computer. Firstly, we reviewed the innovative computational methods available for researchers working on conflict, violence, and peace. Secondly, we described how an Agent-Based Model (ABM) can be linked with a Geographic Information System (GIS) to model the LCB. Finally, this research discusses the challenges and opportunities in constructing a Geographic Information System linked Agent-Based Model of the LCB region.

Keywords: Agent-based modelling, conflict, Geographical Information Systems, Lake Chad Basin, simulation.

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1611 Analysis of Diverse Cluster Ensemble Techniques

Authors: S. Sarumathi, N. Shanthi, P. Ranjetha

Abstract:

Data mining is the procedure of determining interesting patterns from the huge amount of data. With the intention of accessing the data faster the most supporting processes needed is clustering. Clustering is the process of identifying similarity between data according to the individuality present in the data and grouping associated data objects into clusters. Cluster ensemble is the technique to combine various runs of different clustering algorithms to obtain a general partition of the original dataset, aiming for consolidation of outcomes from a collection of individual clustering outcomes. The performances of clustering ensembles are mainly affecting by two principal factors such as diversity and quality. This paper presents the overview about the different cluster ensemble algorithm along with their methods used in cluster ensemble to improve the diversity and quality in the several cluster ensemble related papers and shows the comparative analysis of different cluster ensemble also summarize various cluster ensemble methods. Henceforth this clear analysis will be very useful for the world of clustering experts and also helps in deciding the most appropriate one to determine the problem in hand.

Keywords: Cluster Ensemble, Consensus Function, CSPA, Diversity, HGPA, MCLA.

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1610 Thermodynamic Analysis of R507A-R23 Cascade Refrigeration System

Authors: A. D. Parekh, P. R. Tailor

Abstract:

The present work deals with thermodynamic analysis of cascade refrigeration system using ozone friendly refrigerants pair R507A and R23. R507A is azeotropic mixture composed of HFC refrigerants R125/R143a (50%/50% wt.). R23 is a single component HFC refrigerant used as replacement to CFC refrigerant R13 in low temperature applications. These refrigerants have zero ozone depletion potential and are non-flammable and as R507A an azeotropic mixture there is no problem of temperature glide. This study thermodynamically analyzed R507A-R23 cascade refrigeration system to optimize the design and operating parameters of the system. The design and operating parameters include: Condensing, evaporating, subcooling and superheating temperatures in the high temperature circuit, temperature difference in the cascade heat exchanger, Condensing, evaporating, subcooling and superheating temperatures in the low temperature circuit.

Keywords: COP, R507A, R23, cascade refrigeration system

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1609 Approach Based on Fuzzy C-Means for Band Selection in Hyperspectral Images

Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

Abstract:

Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: Band selection, fuzzy C-means, K-means, hyperspectral image.

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1608 Fatigue Life Prediction on Steel Beam Bridges under Variable Amplitude Loading

Authors: M. F. V. Montezuma, E. P. Deus, M. C. Carvalho

Abstract:

Steel bridges are normally subjected to random loads with different traffic frequencies. They are structures with dynamic behavior and are subject to fatigue failure process, where the nucleation of a crack, growth and failure can occur. After locating and determining the size of an existing fault, it is important to predict the crack propagation and the convenient time for repair. Therefore, fracture mechanics and fatigue concepts are essential to the right approach to the problem. To study the fatigue crack growth, a computational code was developed by using the root mean square (RMS) and the cycle-by-cycle models. One observes the variable amplitude loading influence on the life structural prediction. Different loads histories and initial crack length were considered as input variables. Thus, it was evaluated the dispersion of results of the expected structural life choosing different initial parameters.

Keywords: Fatigue crack propagation, life prediction, variable loadings, steel bridges.

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1607 A Strategy for Scaling-Up Vitamin A Supplementation in a Remote Rural Setting

Authors: Wisdom G. Dube, Talent Makoni, Tasiana K. Nyadzayo, Namukolo M. Covic

Abstract:

Vitamin A deficiency is a public health problem in Zimbabwe. Addressing vitamin A deficiency has the potential of enhancing resistance to disease and reducing mortality especially in children less than 5 years. We implemented and adapted vitamin A outreach supplementation strategy within the National Immunization Days and Extended Programme of Immunization in a rural district in Zimbabwe. Despite usual operational challenges faced this approach enabled the district to increase delivery of supplementation coverage. This paper describes the outreach strategy that was implemented in the remote rural district. The strategy covered 63 outreach sites with 2 sites being covered per day and visited once per month for the whole year. Coverage reached 71% in an area of previous coverage rates of around less than 50%. We recommend further exploration of this strategy by others working in similar circumstances. This strategy can be a potential way for use by Scaling-Up-Nutrition member states.

Keywords: Coverage, Strategy, Supplementation, Vitamin A.

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1606 Acceptance and Commitment Therapy for Work Stress: Variation in Perceived Group Process and Outcomes

Authors: William H. O'Brien, Erin Bannon, M.A., Heather McCarren, Eileen Delaney

Abstract:

Employees commonly encounter unpredictable and unavoidable work related stressors. Exposure to such stressors can evoke negative appraisals and associated adverse mental, physical, and behavioral responses. Because Acceptance and Commitment Therapy (ACT) emphasizes acceptance of unavoidable stressors and diffusion from negative appraisals, it may be particularly beneficial for work stress. Forty-five workers were randomly assigned to an ACT intervention for work stress (n = 21) or a waitlist control group (n = 24). The intervention consisted of two 3-hour sessions spaced one week apart. An examination of group process and outcomes was conducted using the Revised Sessions Rating Scale. Results indicated that the ACT participants reported that they perceived the intervention to be supportive, task focused, and without adverse therapist behaviors (e.g., feelings of being criticized or discounted). Additionally, the second session (values clarification and commitment to action) was perceived to be more supportive and task focused than the first session (mindfulness, defusion). Process ratings were correlated with outcomes. Results indicated that perceptions of therapy supportiveness and task focus were associated with reduced psychological distress and improved perceived physical health.

Keywords: Work stress, Acceptance and Commitment Therapy, therapy process.

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1605 WPRiMA Tool: Managing Risks in Web Projects

Authors: Thamer Al-Rousan, Shahida Sulaiman, Rosalina Abdul Salam

Abstract:

Risk management is an essential fraction of project management, which plays a significant role in project success. Many failures associated with Web projects are the consequences of poor awareness of the risks involved and lack of process models that can serve as a guideline for the development of Web based applications. To circumvent this problem, contemporary process models have been devised for the development of conventional software. This paper introduces the WPRiMA (Web Project Risk Management Assessment) as the tool, which is used to implement RIAP, the risk identification architecture pattern model, which focuses upon the data from the proprietor-s and vendor-s perspectives. The paper also illustrates how WPRiMA tool works and how it can be used to calculate the risk level for a given Web project, to generate recommendations in order to facilitate risk avoidance in a project, and to improve the prospects of early risk management.

Keywords: Architecture pattern model, risk factors, risk identification, web project, web project risk management assessment.

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1604 Mission of Russian Orthodox Church in Kazakhstan in the XIX Century: Activity, Expectations and Results

Authors: Z. Sadvokasova Tulehanovna

Abstract:

The focus of this research is in the area of the soviet period and the mission of the Russian Orthodox Church in Kazakhstan in the XIX century. There was close connection of national customs and traditions with religious practices, outlooks and attitudes. In particular, such an approach has alleged estimation by Kazakh historians of the process of Christianization of the local population. Some of them are inclined to consider the small number of Christening Kazakhs as evidence that the Russian Orthodox Church didn’t achieve its mission. The number of historians who think that the church didn’t achieve its mission has thousand over the last centuries, however our calculations of the number of Kazakhs who became Orthodox Christian is much more than other historians think. Such Christians can be divided into 3 groups: Some remained Christian until their deaths, others had two faiths and the third hid their true religions, having returned to their former belief. Therefore, to define the exact amount of Christening Kazakhs represented a challenge. Some data does not create a clear picture of the level of Christianization, constant and accurate was not collected. The data appearing in reports of spiritual attendants and civil authorities is not always authentic. Article purpose is illumination and the analysis missionary activity of Russian Orthodox Church in Kazakhstan. 

Keywords: Russian expansion, Christianization, tsarism, Russian Orthodox Church in Kazakhstan, neophytes.

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1603 Mining of Interesting Prediction Rules with Uniform Two-Level Genetic Algorithm

Authors: Bilal Alatas, Ahmet Arslan

Abstract:

The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.

Keywords: Classification rule mining, data mining, genetic algorithms.

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1602 Tomato Ripeness Influence on Fruit Quality

Authors: A. Radzevičius, P. Viškelis, R. Karklelienė, J. Viškelis, Č. Bobinas, E. Dambrauskienė andS. Sakalauskienė

Abstract:

Tomato nutrition value, color, flavor of their fruits and products depends mainly on lycopene, β-carotene, ascorbic acid, sugars and their ratio. The two most important carotenoids in fruits of tomato are lycopene, which determined fruits red color, and β- carotene, which accounts for approximately 7% of the tomato carotenoids. Therefore, tomato products and their quality can be well characterized by the content of these elements.Maturity at harvest is very important to composition and quality of tomatoes. This is especially a problem with tomatoes picked green since it is difficult to differentiate between mature and immature-green fruits. Typical and advanced mature-green tomatoes will usually attain a much better flavor than those picked at the immature or partially mature stages.To better understand the synthesis of biochemical compounds, their concentration should be compared not only at the last stage of maturity, but also during all fruit ripening period in different varieties.

Keywords: quality, ripeness, tomato, variety

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1601 Evaluation of Electronic Payment Systems Using Fuzzy Multi-Criteria Decision Making Approach

Authors: Gülfem Alptekin, S. Emre Alptekin

Abstract:

Global competitiveness has recently become the biggest concern of both manufacturing and service companies. Electronic commerce, as a key technology enables the firms to reach all the potential consumers from all over the world. In this study, we have presented commonly used electronic payment systems, and then we have shown the evaluation of these systems in respect to different criteria. The payment systems which are included in this research are the credit card, the virtual credit card, the electronic money, the mobile payment, the credit transfer and the debit instruments. We have realized a systematic comparison of these systems in respect to three main criteria: Technical, economical and social. We have conducted a fuzzy multi-criteria decision making procedure to deal with the multi-attribute nature of the problem. The subjectiveness and imprecision of the evaluation process are modeled using triangular fuzzy numbers.

Keywords: Electronic payment systems, fuzzy multi-criteriadecision making, analytical hierarchy process.

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1600 Institutional Determinants of Economic Growth in Georgia and in Other Post-Communist Economies

Authors: Nazira Kakulia, Tsotne Zhghenti

Abstract:

The institutional development is one of the actual topics in economics science. New trends and directions of institutional development mostly depend on its structure and framework. Transformation of institutions is an important problem for every economy, especially for developing countries. The first research goal is to determine the importance and interactions between different institutions in Georgia. Using World Governance Indicators and Economic Freedom indexes it can be calculated the size for each institutional group. The second aim of this research is to evaluate Georgian institutional backwardness in comparison to other post-communist economies. We use statistical and econometric methods to evaluate the difference between the levels of institutional development in Georgia and in leading post-communist economies. Within the scope of this research, major findings are coefficients which are an assessment of their deviation (i.e. lag) of institutional indicators between Georgia and leading post-communist country which should be compared. The last part of the article includes analysis around the selected coefficients.

Keywords: Post-communist transition, institutions, economic growth, institutional development.

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1599 Geochemistry of Coal Ash in the Equatorial Wet Disposal System Environment

Authors: Kolay P. K., Singh H.

Abstract:

The coal utilization in thermal power plants in Malaysia has increased significantly which produces an enormous amount of coal combustion by-product (CCBP) or coal ash and poses severe disposal problem. As each coal ash is distinct, this study presents the geochemistry of the coal ash, in particular fly ash, produced from the combustion of local coal from Kuching Sarawak, Malaysia. The geochemical composition of the ash showed a high amount of silica, alumina, iron oxides and alkalies which was found to be a convenient starting material for the hydrothermal synthesis of zeolites with the higher Na2O percentage being a positive factor for its alkaline activation; while the mineral phases are mainly quartz, mullite, calcium oxide, silica, and iron oxide hydrate. The geochemical changes upon alkali activation that can be predicted in a similar type of ash have been described in this paper. The result shows that this particular ash has a good potential for a high value industrial product like zeolites upon alkali activation.

Keywords: Coal ash, chemical composition, mineralogical composition, alkali activation, SEM.

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1598 Training Engineering Students in Sustainable Development

Authors: Hoong C. Chin, Soon H. Chew, Zhaoxia Wang

Abstract:

Work on sustainable developments and the call for action in education for sustainable development have been ongoing for a number of years. Training engineering students with the relevant competencies, particularly in sustainable development literacy, has been identified as an urgent task in universities. This requires not only a holistic, multi-disciplinary approach to education but also a suitable training environment to develop the needed skills and to inculcate the appropriate attitudes in students towards sustainable development. To demonstrate how this can be done, a module involving an overseas field trip was introduced in 2013 at the National University of Singapore. This paper provides details of the module and describes its training philosophy and methods. Measured against the student learning outcomes, stipulated by the Engineering Accreditation Board, the module scored well on all of them, particularly those related to complex problem solving, environmental and sustainability awareness, multi-disciplinary team work and varied-level communications.

Keywords: Civil engineering education, student learning outcomes, sustainable development.

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1597 Optimal Based Damping Controllers of Unified Power Flow Controller Using Adaptive Tabu Search

Authors: Rungnapa Taithai, Anant Oonsivilai

Abstract:

This paper presents optimal based damping controllers of Unified Power Flow Controller (UPFC) for improving the damping power system oscillations. The design problem of UPFC damping controller and system configurations is formulated as an optimization with time domain-based objective function by means of Adaptive Tabu Search (ATS) technique. The UPFC is installed in Single Machine Infinite Bus (SMIB) for the performance analysis of the power system and simulated using MATLAB-s simulink. The simulation results of these studies showed that designed controller has an tremendous capability in damping power system oscillations.

Keywords: Adaptive Tabu Search (ATS), damping controller, Single Machine Infinite Bus (SMIB), Unified Power Flow Controller (UPFC).

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1596 Public Private Partnership for Infrastructure Projects: Mapping the Key Risks

Authors: Julinda Keçi

Abstract:

In many countries, governments have been promoting the involvement of private sector entities to enter into long-term agreements for the development and delivery of large infrastructure projects, with a focus on overcoming the limitations upon public fund of the traditional approach. The involvement of private sector through public private partnerships (PPP) brings in new capital investments, value for money and additional risks to handle. Worldwide research studies have shown that an objective, systematic, reliable and useroriented risk assessment process and an optimal allocation mechanism among different stakeholders is crucial to the successful completion. In this framework, this paper, which is the first stage of a research study, aims to identify the main risks for the delivery of PPP projects. A review of cross-countries research projects and case studies was performed to map the key risks affecting PPP infrastructure delivery. The matrix of mapping offers a summary of the frequency of factors, clustered in eleven categories: construction, design, economic, legal, market, natural, operation, political, project finance, project selection and relationship. Results will highlight the most critical risk factors, and will hopefully assist the project managers in directing the managerial attention in the further stages of risk allocation.

Keywords: Construction, infrastructure, public private partnerships, risks.

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1595 Mining Frequent Patterns with Functional Programming

Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

Abstract:

Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.

Keywords: Association, frequent pattern mining, functionalprogramming, pattern matching.

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1594 The Water Quantity and Quality for Conjunctive Use in Saline Soil Problem Area

Authors: P. Mekpruksawong, S. Chuenchooklin, T. Ichikawa

Abstract:

The aim of research project is to evaluate quantity and quality for conjunctive use of groundwater and surface water in lower in the Lower Nam Kam area, Thailand, even though there have been hints of saline soil and water. The mathematical model named WUSMO and MIKE Basin were applied for the calculation of crop water utilization. Results of the study showed that, in irrigation command area, water consumption rely on various sources; rain water 21.56%, irrigation water 78.29%, groundwater and some small surface storage 0.15%. Meanwhile, for non-irrigation command area, water consumption depends on the Nam Kam and Nambang stream 42%, rain water 36.75% and groundwater and some small surface storage 19.18%. Samples of surface water and groundwater were collected for 2 seasons. The criterion was determined for the assessment of suitable water for irrigation. It was found that this area has very limited sources of suitable water for irrigation.

Keywords: Conjunctive use, Groundwater, Surface water, Saline soil.

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1593 Avoiding Catastrophic Forgetting by a Dual-Network Memory Model Using a Chaotic Neural Network

Authors: Motonobu Hattori

Abstract:

In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.

Keywords: catastrophic forgetting, chaotic neural network, complementary learning systems, dual-network

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1592 Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series

Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser

Abstract:

In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.

Keywords: Dynamic Bayesian networks, structure learning, gene networks, Markov chain Monte Carlo, microarray data.

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1591 Inverse Dynamics of the Mould Base of Blow Molding Machines

Authors: Vigen Arakelian

Abstract:

This paper deals with the study of devices for displacement of the mould base of blow-molding machines. The displacement of the mould in the studied case is carried out by a linear actuator, which ensures the descent of the mould base and by extension springs, which return the letter in the initial position. The aim of this paper is to study the inverse dynamics of the device for displacement of the mould base of blow-molding machines and to determine its optimum parameters for higher rate of production. In the other words, it is necessary to solve the inverse dynamic problem to find the equation of motion linking applied forces with displacements. This makes it possible to determine the stiffness coefficient of the spring to turn the mold base back to the initial position for a given time. The obtained results are illustrated by a numerical example. It is shown that applying a spring with stiffness returns the mould base of the blow molding machine into the initial position in 0.1 sec.

Keywords: Design, blow-molding machines, dynamics.

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1590 Using a Semantic Self-Organising Web Page-Ranking Mechanism for Public Administration and Education

Authors: Marios Poulos, Sozon Papavlasopoulos, V. S. Belesiotis

Abstract:

In the proposed method for Web page-ranking, a novel theoretic model is introduced and tested by examples of order relationships among IP addresses. Ranking is induced using a convexity feature, which is learned according to these examples using a self-organizing procedure. We consider the problem of selforganizing learning from IP data to be represented by a semi-random convex polygon procedure, in which the vertices correspond to IP addresses. Based on recent developments in our regularization theory for convex polygons and corresponding Euclidean distance based methods for classification, we develop an algorithmic framework for learning ranking functions based on a Computational Geometric Theory. We show that our algorithm is generic, and present experimental results explaining the potential of our approach. In addition, we explain the generality of our approach by showing its possible use as a visualization tool for data obtained from diverse domains, such as Public Administration and Education.

Keywords: Computational Geometry, Education, e-Governance, Semantic Web.

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