Search results for: Fuzzy Project Selection

Authors: Nese Dikmen

Abstract:

Post-disaster reconstruction projects offer opportunities to facilitate physical, social and economic development and to reduce future hazard vulnerability long after the disasters. Sustainability of post-disaster reconstruction project conducted in the villages of Dinar following the 1995 earthquake was investigated in this paper. Officials of the Government who were involved in the project were interviewed. Besides, two field surveys were done in 12 villages of Dinar in winter months of 2008. Beneficiaries were interviewed and physical, socio-cultural and economic impacts of the reconstruction were examined. The research revealed that the postdisaster reconstruction project has negative aspects from the point view of sustainability. The physical, socio-cultural and economic factors were not considered during decision making process of the project.

Keywords: Dinar, Post-disaster reconstruction, Sustainable development, Turkey.

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Authors: R. Amandi, A. Shahbazi, A. Mohebi, M. Bazargan, Y. Jaberi, P. Emadi, A. Valizade

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The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.

Keywords: Fuzzy Logic, Probabilistic Neural Network, Tachycardia, Wavelet Transform.

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Authors: Cristina G. Dascalu, Elena Mihaela Carausu, Daniela Manuc

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The medical studies often require different methods for parameters selection, as a second step of processing, after the database-s designing and filling with information. One common task is the selection of fields that act as risk factors using wellknown methods, in order to find the most relevant risk factors and to establish a possible hierarchy between them. Different methods are available in this purpose, one of the most known being the binary logistic regression. We will present the mathematical principles of this method and a practical example of using it in the analysis of the influence of 10 different psychiatric diagnostics over 4 different types of offences (in a database made from 289 psychiatric patients involved in different types of offences). Finally, we will make some observations about the relation between the risk factors hierarchy established through binary logistic regression and the individual risks, as well as the results of Chi-squared test. We will show that the hierarchy built using the binary logistic regression doesn-t agree with the direct order of risk factors, even if it was naturally to assume this hypothesis as being always true.

Keywords: Databases, risk factors, binary logisticregression, hierarchy.

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: Information security risk treatment, Selection of risk measures, Risk acceptanceand Multi-objective optimization.

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Authors: A. Statkus, S. Paulikas

Abstract:

With increasing number of wireless devices like laptops, Wi-Fi Web Cams, network extenders, etc., a new kind of problems appeared, mostly related to poor Wi-Fi throughput or communication problems. In this paper an investigation on wireless networks and it-s saturation in Vilnius City and its surrounding is presented, covering the main problems of wireless saturation and network load during day. Also an investigation on wireless channel selection and noise levels were made, showing the impact of neighbor AP to signal and noise levels and how it changes during the day.

Keywords: IEEE 802.11b/g/n, wireless saturation, client activity, channel selection.

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Authors: Kyonghoon Kim, Wonyoung Park, Taeil Park

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Aging infrastructures became a serious social problem. This brought out the increased need for the legislation of a new strict guideline for infrastructure management. Although existing guidelines provided basics of how to evaluate and manage the condition of infrastructures, they needed improvements for their evaluation procedures. Most guidelines mainly focused on the structural condition of infrastructures and did not properly reflect service aspects of infrastructures such as performance, public demand, capacity, etc., which were significantly valuable to public. Regardless of the importance, these factors were often neglected in infrastructure evaluations, because they were quite subjective and difficult to quantify in rational manner. Thus, this study proposed a framework to properly identify and evaluate the service indicators. This study showed that service indicators could be grouped into two categories and properly evaluated using AHP and Fuzzy. Overall, proposed framework is expected to assist governmental agency in establishing effective investment strategies for infrastructure improvements.

Keywords: Infrastructure, evaluation, serviceability, fuzzy.

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Authors: Yi-an Cui, Lu Wang, Jian-ping Xiao

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This paper presents an automatic feature recognition method based on center-surround difference detecting and fuzzy logic that can be applied in ground-penetrating radar (GPR) image processing. Adopted center-surround difference method, the salient local image regions are extracted from the GPR images as features of detected objects. And fuzzy logic strategy is used to match the detected features and features in template database. This way, the problem of objects detecting, which is the key problem in GPR image processing, can be converted into two steps, feature extracting and matching. The contributions of these skills make the system have the ability to deal with changes in scale, antenna and noises. The results of experiments also prove that the system has higher ratio of features sensing in using GPR to image the subsurface structures.

Keywords: feature recognition, GPR image, matching strategy, salient image

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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: Adel Aloraini

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Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.

Keywords: Causal interactions , banks, feature selection, regularizere,

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Authors: Mazeni Ismail, Nurul Aliah, Hasmadi Hassan

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The purpose of this study is to gather the consensus of experts regarding the use of moral guidance amongst preschool teachers vis-a-vis the Islamic Project module (I-Project Module). This I-Project Module seeks to provide pertinent data on the assimilation of noble values in subject-matter teaching. To obtain consensus for the various components of the module, the Modified Delphi technique was used to develop the module. 12 subject experts from various educational fields of Islamic education, early childhood education, counselling and language fully participated in the development of this module. The Modified Delphi technique was administered in two mean cycles. The standard deviation value derived from questionnaires completed by the participating panel of experts provided the value of expert consensus reached. This was subsequently analyzed using SPSS version 22. Findings revealed that the panel of experts reached a discernible degree of agreement on five topics outlined in the module, viz; content (mean value 3.36), teaching strategy (mean value 3.28), programme duration (mean value 3.0), staff involved and attention-grabbing strategy of target group participating in the value program (mean value 3.5), and strategy to attract attention of target group to utilize i-project (mean value 3.0). With regard to the strategy to attract the attention of the target group, the experts proposed for creative activities to be added in order to enhance teachers’ creativity.

Keywords: Islamic project, modified Delphi technique, project approach, teacher moral guidance.

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Authors: Yasmin Mohd Yacob, Harsa A. Mat Sakim, Nor Ashidi Mat Isa

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Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.

Keywords: Feature ranking, decision tree, hierarchical cluster, Manhattan distance.

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Authors: Osamah A. Alsayegh

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This paper contributes to the literature by updating the analysis of the impact of the recent oil prices fall on the renewable energy (RE) industry and deployment. The research analysis uses the Renewable Energy Industrial Index (RENIXX), which tracks the world’s 30 largest publicly traded companies and oil prices daily data from January 2003 to March 2016. RENIXX represents RE industries developing solar, wind, geothermal, bioenergy, hydropower and fuel cells technologies. This paper tests the hypothesis that claims high oil prices encourage the substitution of alternate energy sources for conventional energy sources. Furthermore, it discusses RENIXX performance behavior with respect to the governments’ policies factor that investors should take into account. Moreover, the paper proposes a theoretical model that relates RE industry progress with oil prices and policies through the fuzzy logic system.

Keywords: Fuzzy logic, investment, policy, stock exchange index.

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Authors: C. Ardil

Abstract:

This article presents a multiple criteria evaluation for a trainer aircraft selection problem using "preference analysis for reference ideal solution (PARIS)” approach. The available relevant literature points to the use of multiple criteria decision making analysis (MCDMA) methods for the problem of trainer aircraft selection, which often involves conflicting multiple criteria. Therefore, this MCDMA study aims to propose a robust systematic integrated framework focusing on the trainer aircraft selection problem. For this purpose, an integrated preference analysis approach based the mean weight and entropy weight procedures with PARIS, and TOPSIS was used for a MCDMA compensating solution. In this study, six trainer aircraft alternatives were evaluated according to six technical decision criteria, and data were collected from the current relevant literature. As a result, the King Air C90GTi alternative was identified as the most suitable trainer aircraft alternative. In order to verify the stability and accuracy of the results obtained, comparisons were made with existing MCDMA methods during the sensitivity and validity analysis process.The results of the application were further validated by applying the comparative analysis-based PARIS, and TOPSIS method. The proposed integrated MCDMA systematic structure is also expected to address the issues encountered in the aircraft selection process. Finally, the analysis results obtained show that the proposed MCDMA method is an effective and accurate tool that can help analysts make better decisions.

Keywords: aircraft, trainer aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS

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Authors: Stephen C. W. Kong

Abstract:

The use of 3D computer-aided design (CAD) models to support construction project planning has been increasing in the previous year. 3D CAD models reveal more planning ideas by visually showing the construction site environment in different stages of the construction process. Using 3D CAD models together with scheduling software to prepare construction plan can identify errors in process sequence and spatial arrangement, which is vital to the success of a construction project. A number of 4D (3D plus time) CAD tools has been developed and utilized in different construction projects due to the awareness of their importance. Virtual prototyping extends the idea of 4D CAD by integrating more features for simulating real construction process. Virtual prototyping originates from the manufacturing industry where production of products such as cars and airplanes are virtually simulated in computer before they are built in the factory. Virtual prototyping integrates 3D CAD, simulation engine, analysis tools (like structural analysis and collision detection), and knowledgebase to streamline the whole product design and production process. In this paper, we present the application of a virtual prototyping software which has been used in a few construction projects in Hong Kong to support construction project planning. Specifically, the paper presents an implementation of virtual prototyping in a residential building project in Hong Kong. The applicability, difficulties and benefits of construction virtual prototyping are examined based on this project.

Keywords: construction project planning, prefabrication, simulation, virtual prototyping.

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Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

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The system is designed to show images which are related to the query image. Extracting color, texture, and shape features from an image plays a vital role in content-based image retrieval (CBIR). Initially RGB image is converted into HSV color space due to its perceptual uniformity. From the HSV image, Color features are extracted using block color histogram, texture features using Haar transform and shape feature using Fuzzy C-means Algorithm. Then, the characteristics of the global and local color histogram, texture features through co-occurrence matrix and Haar wavelet transform and shape are compared and analyzed for CBIR. Finally, the best method of each feature is fused during similarity measure to improve image retrieval effectiveness and accuracy.

Keywords: Color Histogram, Haar Wavelet Transform, Fuzzy C-means, Co-occurrence matrix; Similarity measure.

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Authors: Mihai Ciocarlie, Marcela-Simona Atanasoae, Horia Ciocarlie

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We present the development of a system of programs designed for the compilation and execution of applications for handheld computers. In introduction we describe the purpose of the project and its components. The next two paragraphs present the first two components of the project (the scanner and parser generators). Then we describe the Object Pascal compiler and the virtual machines for Windows and Palm OS. In conclusion we emphasize the ways in which the project can be extended.

Keywords: Compiler design, Palm OS applications, rapid application development, virtual machine.

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Authors: Mamoon M. Atout

Abstract:

The Middle East Gulf region has witnessed rapid growth and development in many areas over the last two decades. The development of the real-estate sector, construction industry and infrastructure projects are a major share of the development that has participated in the civilization of the countries of the Gulf. Construction industry projects were planned and managed by different types of experts, who came from all over the world having different types of experiences in construction management and industry. Some of these projects were completed on time, while many were not, due to many accumulating factors. Many accumulated factors are considered as the principle reason for the problem experienced at the project construction stage, which reflected negatively on the project success. Specific causes of delay have been identified by construction managers to avoid any unexpected delays through proper analysis and considerations to some implications such as risk assessment and analysis for many potential problems to ensure that projects will be delivered on time. Construction management implications were adopted and considered by project managers who have experience and knowledge in applying the techniques of the system of engineering construction management. The aim of this research is to determine the benefits of the implications of construction management by the construction team and level of considerations of the techniques and processes during the project development and construction phases to avoid any delay in the projects. It also aims to determine the factors that participate to project completion delays in case project managers are not well committed to their roles and responsibilities. The results of the analysis will determine the necessity of the applications required by the project team to avoid the causes of delays that help them deliver projects on time, e.g. verifying tender documents, quantities and preparing the construction method of the project.

Keywords: Construction management, control process, cost control, planning and scheduling, roles and responsibilities.

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Authors: M. Holle, M. Roth, M. R. Gürtler, U. Lindemann

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This paper gives insights into the research project “InnoCyFer” (in the form of an outlook) which is funded by the German Federal Ministry of Economics and Technology. Enabling the integrated customer individual product design as well as flexible manufacturing of these products are the main objectives of the project. To achieve this, a web-based Open Innovation-Platform containing an integrated Toolkit will be developed. This toolkit enables the active integration of the customer’s creativity and potentials of innovation in the product development process. Furthermore, the project will show the chances and possibilities of customer individualized products by building and examining the continuous process from innovation through the customers to the flexible manufacturing of individual products.

Keywords: Customer Individual Product Design, Innovation Networks, Open Innovation, Open Innovation Platform and Toolkit.

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Authors: C. Ardil

Abstract:

This paper introduces the concept of neutral sets (NSs) and explores various operations on NSs, along with their associated properties. The foundation of the Neutral Set framework lies in ontological neutrality and the principles of logic, including the Law of Non-Contradiction. By encompassing components for possibility, indeterminacy, and necessity, the NS framework provides a flexible representation of truth, uncertainty, and necessity, accommodating diverse ontological perspectives without presupposing specific existential commitments. The inclusion of Possibility acknowledges the spectrum of potential states or propositions, promoting neutrality by accommodating various viewpoints. Indeterminacy reflects the inherent uncertainty in understanding reality, refraining from making definitive ontological commitments in uncertain situations. Necessity captures propositions that must hold true under all circumstances, aligning with the principle of logical consistency and implicitly supporting the Law of Non-Contradiction. Subsequently, a neutral set-TOPSIS approach is applied in the maintenance strategy selection problem, demonstrating the practical applicability of the NS framework. The paper further explores uncertainty relations and presents the fundamental preliminaries of NS theory, emphasizing its role in fostering ontological neutrality and logical coherence in reasoning.

Keywords: Uncertainty sets, neutral sets, maintenance strategy selection multiple criteria decision-making analysis, MCDM, uncertainty decision analysis, distance function, multiple attribute, decision making, selection method, uncertainty, TOPSIS

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Authors: Zeyad Abdelmageid, Xianbin Wang

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Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterwards. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and at times better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: Channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead.

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Authors: Latha Parthiban, R. Subramanian

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Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.

Keywords: CANFIS, genetic algorithms, heart disease, membership function.

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Authors: Mehdi Nafar, Mohammad Reza Mansouri

Abstract:

The present research presents a direct active and reactive power control (DPC) of a wind energy conversion system (WECS) for the maximum power point tracking (MPPT) based on a doubly fed induction generator (DFIG) connected to electric power grid. The control strategy of the Rotor Side Converter (RSC) is targeted in extracting a maximum of power under fluctuating wind speed. A fuzzy logic speed controller (FLC) has been used to ensure the MPPT. The Grid Side Converter is directed in a way to ensure sinusoidal current in the grid side and a smooth DC voltage. To reduce fluctuations, rotor torque and voltage use of multilevel inverters is a good way to remove the rotor harmony.

Keywords: DFIG, power quality improvement, wind energy conversion system, WECS, fuzzy logic, RSC, GSC, inverter.

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Authors: Saimir Heta, Ilma Robo, Vera Ostreni, Glorja Demika, Sonila Kapaj

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Suturing, as a procedure of joining the lips of the lembo or wound, is important at the beginning of the healing process. This procedure helps to pass the healing process from the procedure per secundam to the stages of healing per primam, thus logically reducing the healing time of the wound. The purpose of this article is to publish some data on the clinical characteristics of periodontal suturing, presenting the advantages and disadvantages of different types of suture threads. The article is a mini-review type of articles selected from the application of keywords on the PubMed page. The number of articles extracted from this article publication page is in accordance with the 10-year publication time limit. The element that remains in the individual selection of the dentist applying the suture is the selection of the suture material. At a moment when some types of sutures are offered for use, some elements should be considered in the selection of the suture depending on the constituent material, the cross-section of the suture elements, and whether it collects bacteria in the "pits" created by the material. The presence of bacteria is a source of infection and possible delay in the healing of the sutured wound. The marketing of suture types offers a variety of materials, from which the selection of the most suitable suture type for specific application cases is a personal indication of the dental surgeon based on professional experiences and knowledge in this field.

Keywords: Suture, suture material, types of sutures, clinical application.

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

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In this paper, a new learning approach for network intrusion detection using naïve Bayesian classifier and ID3 algorithm is presented, which identifies effective attributes from the training dataset, calculates the conditional probabilities for the best attribute values, and then correctly classifies all the examples of training and testing dataset. Most of the current intrusion detection datasets are dynamic, complex and contain large number of attributes. Some of the attributes may be redundant or contribute little for detection making. It has been successfully tested that significant attribute selection is important to design a real world intrusion detection systems (IDS). The purpose of this study is to identify effective attributes from the training dataset to build a classifier for network intrusion detection using data mining algorithms. The experimental results on KDD99 benchmark intrusion detection dataset demonstrate that this new approach achieves high classification rates and reduce false positives using limited computational resources.

Keywords: Attributes selection, Conditional probabilities, information gain, network intrusion detection.

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Authors: M. Alassim, M. Alfayad, E. Abbott-Halpin

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The purpose of this paper is to explore the organizational factors influencing the implementation of the e-government project within the public sector in Saudi Arabia. This project (also known as the Yesser programme) was established in Saudi Arabia in 2005 to control the e-government transformation process. The aims of the project are to provide a collaborative environment for government organizations to implement e-government and increase effectiveness and efficiency within the public sector. This paper sheds light on the organizational factors that have delayed implementation and achievement of the government’s vision and plans for Yesser. A qualitative approach was employed to understand those factors, by conducting a series of interviews with government officials for the data collection required. The analysis of the data uncovered seven organizational factors that are needed to advance implementation of the e-government project in Saudi Arabia and other similar states.

Keywords: E-government, e-transformation, ICT, Saudi Arabia, Yesser.

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Authors: Vesile Evrim, Aliyu Awwal

Abstract:

By the evolvement in technology, the way of expressing opinions switched direction to the digital world. The domain of politics, as one of the hottest topics of opinion mining research, merged together with the behavior analysis for affiliation determination in texts, which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 were constituted by Linguistic Inquiry and Word Count (LIWC) features were tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that the “Decision Tree”, “Rule Induction” and “M5 Rule” classifiers when used with “SVM” and “IGR” feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “Function”, as an aggregate feature of the linguistic category, was found as the most differentiating feature among the 68 features with the accuracy of 81% in classifying articles either as Republican or Democrat.

Keywords: Politics, machine learning, feature selection, LIWC.

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Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

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Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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Authors: Murat Ayyıldız, Oya Kalıpsız, Sırma Yavuz

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Software project effort estimation is frequently seen as complex and expensive for individual software engineers. Software production is in a crisis. It suffers from excessive costs. Software production is often out of control. It has been suggested that software production is out of control because we do not measure. You cannot control what you cannot measure. During last decade, a number of researches on cost estimation have been conducted. The metric-set selection has a vital role in software cost estimation studies; its importance has been ignored especially in neural network based studies. In this study we have explored the reasons of those disappointing results and implemented different neural network models using augmented new metrics. The results obtained are compared with previous studies using traditional metrics. To be able to make comparisons, two types of data have been used. The first part of the data is taken from the Constructive Cost Model (COCOMO'81) which is commonly used in previous studies and the second part is collected according to new metrics in a leading international company in Turkey. The accuracy of the selected metrics and the data samples are verified using statistical techniques. The model presented here is based on Multi-Layer Perceptron (MLP). Another difficulty associated with the cost estimation studies is the fact that the data collection requires time and care. To make a more thorough use of the samples collected, k-fold, cross validation method is also implemented. It is concluded that, as long as an accurate and quantifiable set of metrics are defined and measured correctly, neural networks can be applied in software cost estimation studies with success

Keywords: Software Metrics, Software Cost Estimation, Neural Network.

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Authors: Kechida Ahmed, Drai Redouane, Khelil Mohamed

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In this paper we present a new approach to detecting a flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image based on texture features. Texture is one of the most important features used in recognizing patterns in an image. The paper describes texture features based on 2D Gabor functions, i.e., Gaussian shaped band-pass filters, with dyadic treatment of the radial spatial frequency range and multiple orientations, which represent an appropriate choice for tasks requiring simultaneous measurement in both space and frequency domains. The most relevant features are used as input data on a Fuzzy c-mean clustering classifier. The classes that exist are only two: 'defects' or 'no defects'. The proposed approach is tested on the T.O.F.D image achieved at the laboratory and on the industrial field.

Keywords: 2D Gabor Functions, flaw detection, fuzzy c-mean clustering, non destructive testing, texture analysis, T.O.F.D Image (Time of Flight Diffraction).

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Authors: Yousef S. Al-Othman

Abstract:

The growth and expansion of the industrial facilities comes proportional to the market increasing demand of products and services. Furthermore, raw material producers such as oil companies usually undergo massive revamping projects to maintain a synchronized supply. These revamping projects are usually delivered through challenging construction projects held and associated with daily site risks related to the construction process. Henceforth, a case study related to these risks and corresponding on-spot corrective measurements has been made on a certain number of construction project contractors at Kuwait Oil Company (KOC) to derive the benefits and overall effectiveness of the on-spot corrective measurements during the construction phase of a project, and how would the same help in avoiding major incidents, ensuring a smooth, cost effective and on time delivery of the project. Findings of this case study shall have an added value to the overall risk management process by minimizing the daily site risks that may affect the project lead time, resulting in an undisturbed on-site construction process.

Keywords: Oil and gas, risk management, construction projects, project lead time.

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