Search results for: Process Recommendation Social Collaboration

Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: A-shaped compact microstrip antenna, Artificial Neural Network (ANN), adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM).

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Authors: Ebtehal Aljedaani, Maha Aljohani

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Privacy and security patterns are both important for developing software that protects users' data and privacy. Privacy patterns are designed to address common privacy problems, such as unauthorized data collection and disclosure. Security patterns are designed to protect software from attack and ensure reliability and trustworthiness. Using privacy and security patterns, software engineers can implement security and privacy by design principles, which means that security and privacy are considered throughout the software development process. These patterns are available to translate "security and privacy-by-design" into practical advice for software engineering. Previous research on privacy and security patterns has typically focused on one category of patterns at a time. This paper aims to bridge this gap by merging the two categories and identifying their similarities and differences. To do this, we conducted a systematic literature review of 40 research papers on privacy and security patterns. The papers were analyzed based on the category of the pattern, the classification of the pattern, and the security requirements that the pattern addresses. This paper presents the results of a comprehensive review of privacy and security design patterns. The review is intended to help future IT designers understand the relationship between the two types of patterns and how to use them to design secure and privacy-preserving software. The paper provides a clear classification of privacy and security design patterns, along with examples of each type. We found that there is only one widely accepted classification of privacy design patterns, while there are several competing classifications of security design patterns. Three types of security design patterns were found to be the most used.

Keywords: Design patterns, security, privacy, classification of patterns, security patterns, privacy patterns.

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Authors: L. A. Muhammad, M. S. Argungu

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Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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Authors: Hao Liu, Lihui Zheng, Chinedu J. Okere, Chao Wang, Xiangchun Wang, Peng Zhang

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The coalbed methane (CBM) extraction industry (an unconventional energy source) has not established guidelines for experimental evaluation of sensitivity damage for coal samples. The existing experimental process of previous researches mainly followed the industry standard for conventional oil and gas reservoirs (CIS). However, the existing evaluation method ignores certain critical differences between CBM reservoirs and conventional reservoirs, which could inevitably result in an inaccurate evaluation of sensitivity damage and, eventually, poor decisions regarding the formulation of formation damage prevention measures. In this study, we propose improved experimental guidelines for evaluating seepage sensitivity damage of CBM reservoirs by leveraging on the shortcomings of the existing methods. The proposed method was established via a theoretical analysis of the main drawbacks of the existing methods and validated through comparative experiments. The results show that the proposed evaluation technique provided reliable experimental results that can better reflect actual reservoir conditions and correctly guide the future development of CBM reservoirs. This study is pioneering the research on the optimization of experimental parameters for efficient exploration and development of CBM reservoirs.

Keywords: Coalbed methane, formation damage, permeability, unconventional energy source.

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Authors: A. Esra İdemen, Sinan M. Şener, Emrah Acar

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The technological paradigm of the disaster management field, especially in the case of governmental intervention strategies, is generally based on rapid and flexible accommodation solutions. From various technical solution patterns used to address the immediate housing needs of disaster victims, the adaptive re-use of existing buildings can be considered to be both low-cost and practical. However, there is a scarcity of analytical methods to screen, select and adapt buildings to help decision makers in cases of emergency. Following an extensive literature review, this paper aims to highlight key points and problem areas associated with the adaptive re-use of buildings within the disaster management context. In other disciplines such as real estate management, the adaptive re-use potential (ARP) of existing buildings is typically based on the prioritization of a set of technical and non-technical criteria which are then weighted to arrive at an economically viable investment decision. After a disaster, however, the assessment of the ARP of buildings requires consideration of different/additional layers of analysis which stem from general disaster management principles and the peculiarities of different types of disasters, as well as of their victims. In this paper, a discussion of the development of an adaptive re-use potential (ARP) assessment model is presented. It is thought that governmental and non-governmental decision makers who are required to take quick decisions to accommodate displaced masses following disasters are likely to benefit from the implementation of such a model.

Keywords: Adaptive re-use of buildings, assessment model, disaster management, temporary housing.

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Authors: Shyam Sunder Kawan

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Museums are enclosed buildings encompassing and displaying creative artworks, artefacts and discoveries for people’s knowledge and observation. In the context of Nepal, museums and exhibition areas are either adaptive to small gallery spaces in residences or ‘neo-classical palatial complexes’ that evolved during the 19th century. This study accepts the sparse occurrence of a diverse range of artworks and expressions in the country's complex cultural manifestations within vivid ethnic groups. This study explores the immense potential of one such prevalence beyond the delimitation of physical boundaries. Taking Bhaktapur World Heritage Site as a case, the study perpetuates its investigation into real-time life activities that this city and its cultural landscapes ensemble. Seeking the ‘musealization’ as an urban process to induce museums into the city precinct, this study anticipates art-space into urban spaces to offer a limitless experience for this contemporary world. Unveiling art as an experiential component, this study aims in conceptualizing a living heritage as an infinite resource for museum interpretation beyond just educational institute purposes.

Keywords: Living museum, site museum, musealization, contemporary arts, cultural heritage, historic cities.

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Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: Medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis.

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Authors: Safwa Yargui

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This research is about the quest for a post-war American epic poem in the age of late capitalism. This paper explores the possibility of an epic poem in the context of post-war late capitalist America, despite the prevailing scholarly scepticism regarding the existence of epic poetry after Milton’s Paradise Lost. The aim of this paper is to demonstrate the possibility of a post-war American epic through the argument of epic consciousness by distinguishing the scholarly views on the impossibility of an epic poem and the counterargument of epic consciousness which contends that American epic poetry is possible. Epic consciousness provides a significant nuance to the reading of the post-war American epic by focusing on the epic’s responsiveness to late capitalism, via various language forms; cultural manifestations; and conscious distortions of late capitalist media-related language; in addition to the epic’ conscious inclusion of the process of writing a post-war epic that requires a direct engagement with American-based materials. By focusing on interdisciplinary theoretical approaches, this paper includes both socio-cultural literary theories as well as literary and epic approaches developed by scholars that respectively contextualise the late capitalist situation and the question of post-war American epic poetry. In examining the role of consciousness, this paper aims to suggest a re-thinking of the post-war American epic that is capable of self-commitment, for the purpose of achieving a new sense of epic poetry in post-war late capitalist America.

Keywords: American epic, epic consciousness, late capitalism, post-war poetry.

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Authors: T. A. Abegunde, O. B. Oyewole, T. A. Sanni

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A process of conversion of flour from three varieties of cassava, namely Odongbo, ofege and TMS30752 to ethanol using α-amylase locally sourced from germinated unhusked paddy rice and yeast isolated from palm wine was developed. It involves the germination of paddy rice for a period of 15days to produce α-amylase for starch hydrolysis and isolation of yeast from palm wine for fermentation. The results showed that optimum amylase yield of “ofada” rice paddy was at 6^th day germination which was 576.9ml/g. Ethanol yield for TMS30572 (440.3%) was significantly higher than “Odongbo” (160.2%) and “Ofege’’ (115.1%), Sugar conversion efficiency were 311.0%v/v, 268.2%v/v and 186.84%v/v for TMS30572, “Odongbo” and “Ofege” respectively. The ethanol boiling points were 78^oC, 76^oC and 80^oC for TMS30572, “Odongbo” and “Ofege” respectively. This study showed that cassava varieties affects quality of ethanol produced and germination of “ofada” rice for 6 days ensures optimum production of crude amylase enzyme.

Keywords: Cassava, ethanol, fermentation, hydrolysis, α-amylase.

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Authors: Amir Farkhonde

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The major objective of this study was to devise a method for solving mathematical problems. Three concepts including faculty of understanding, faculty of guess, and free mind or beginner's mind provided the foundation for this method. An explanatory approach along with a hermeneutic process was taken in this study to support the assumption that mathematical knowledge is constantly developing and it seems essential for students to solve math problems on their own using their faculty of understanding (interpretive dialogue) and faculty of guess. For doing so, a kind of movement from the mathematical problem to mathematical knowledge should be adopted for teaching students a new math topic. The research method of this paper is review, descriptive and conception development. This paper first reviews the research findings on the NRICH’S project (NRICH is part of the family of activities in the Millennium Mathematics Project) with the aim that these findings form the theoretical basis of the problem-solving method. Then, the curriculum, the conceptual structure of the new method, how to design the problem and an example of it are discussed. In this way, students are immersed in the story of discovering and understanding the problem formula, and interpretive dialogue with the text continues by following the questions posed by the problem and constantly reconstructing the answer to find a formula or solution to solve the problem.

Keywords: Interpretive dialogue, NRICH, inventing, a method of problem solving.

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Authors: Ryota Sugino, Satoshi Mizoguchi, Koji Kimita, Keiichi Muramatsu, Tatsunori Matsui, Yoshiki Shimomura

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Improving added value and productivity of services entails improving both value-in-exchange and value-in-use. Value-in-use is realized by value co-creation, where providers and receivers create value together. In higher education services, value-in-use comes from learners achieving learning outcomes (e.g., knowledge and skills) that are consistent with their learning goals. To enhance the learning outcomes of a learner, it is necessary to enhance and utilize the abilities of the teacher along with the abilities of the learner. To do this, however, the learner and the teacher need to build a consensus about their respective roles. Teachers need to provide effective learning content; learners need to choose the appropriate learning strategies by using the learning content through consensus building. This makes consensus building an important factor in value co-creation. However, methods to build a consensus about their respective roles may not be clearly established, making such consensus difficult. In this paper, we propose some strategies for consensus building between a teacher and a learner in value co-creation. We focus on a teacher and learner co-design and propose an analysis method to clarify a collaborative design process to realize value co-creation. We then analyze some counseling data obtained from a university class. This counseling aimed to build a consensus for value-in-use, learning outcomes, and learning strategies between the teacher and the learner.

Keywords: Consensus building, value co-creation, higher education, learning service.

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Authors: Sangamesh G. Sakri, Akash N. Patil, Sadashivappa M. Kotli

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Agro based industries in India are considered as the micro, small and medium enterprises (MSME). In India, MSMEs contribute approximately 8 percent of the country’s GDP, 42 percent of the manufacturing output and 40 percent of exports. The toor dal (scientific name Cajanus cajan, commonly known as yellow gram, pigeon pea) is the second largest pulse crop in India accounting for about 20% of total pulse production. The toor dal milling industry in India is one of the major agro-processing industries in the country. Most of the dal mills are concentrated in pulse producing areas, which are spread all over the country. In Karnataka state, Gulbarga is a district, where toor dal is the main crop and is grown extensively. There are more than 500 dal mills in and around the Gulbarga district to process dal. However, the majority of these dal milling units use traditional methods of processing which are energy and capital intensive. There exists a huge energy saving potential in these mills. An energy audit is conducted on a dal mill in Gulbarga to understand the energy consumption pattern to assess the energy saving potential, and an economic analysis is conducted to identify energy conservation opportunities.

Keywords: Conservation, demand side management, load curve, toor dal.

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Authors: Rudolf Egger

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This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: Lifelong learning, Trade unions, Non-formal learning, Educational/vocational policies.

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Authors: Anshu Manik, William G. Buttlar, Kasthurirangan Gopalakrishnan

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Over the years, there is a growing trend towards quality-based specifications in highway construction. In many Quality Control/Quality Assurance (QC/QA) specifications, the contractor is primarily responsible for quality control of the process, whereas the highway agency is responsible for testing the acceptance of the product. A cooperative investigation was conducted in Illinois over several years to develop a prototype End-Result Specification (ERS) for asphalt pavement construction. The final characteristics of the product are stipulated in the ERS and the contractor is given considerable freedom in achieving those characteristics. The risk for the contractor or agency depends on how the acceptance limits and processes are specified. Stochastic simulation models are very useful in estimating and analyzing payment risk in ERS systems and these form an integral part of the Illinois-s prototype ERS system. This paper describes the development of an innovative methodology to estimate the variability components in in-situ density, air voids and asphalt content data from ERS projects. The information gained from this would be crucial in simulating these ERS projects for estimation and analysis of payment risks associated with asphalt pavement construction. However, these methods require at least two parties to conduct tests on all the split samples obtained according to the sampling scheme prescribed in present ERS implemented in Illinois.

Keywords: Asphalt Pavement, Risk Analysis, StochasticSimulation, QC/QA.

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Authors: O. M. Bamigbola, A. A. Ibrahim

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Analysis of real life problems often results in linear systems of equations for which solutions are sought. The method to employ depends, to some extent, on the properties of the coefficient matrix. It is not always feasible to solve linear systems of equations by direct methods, as such the need to use an iterative method becomes imperative. Before an iterative method can be employed to solve a linear system of equations there must be a guaranty that the process of solution will converge. This guaranty, which must be determined apriori, involve the use of some criterion expressible in terms of the entries of the coefficient matrix. It is, therefore, logical that the convergence criterion should depend implicitly on the algebraic structure of such a method. However, in deference to this view is the practice of conducting convergence analysis for Gauss- Seidel iteration on a criterion formulated based on the algebraic structure of Jacobi iteration. To remedy this anomaly, the Gauss- Seidel iteration was studied for its algebraic structure and contrary to the usual assumption, it was discovered that some property of the iteration matrix of Gauss-Seidel method is only diagonally dominant in its first row while the other rows do not satisfy diagonal dominance. With the aid of this structure we herein fashion out an improved version of Gauss-Seidel iteration with the prospect of enhancing convergence and robustness of the method. A numerical section is included to demonstrate the validity of the theoretical results obtained for the improved Gauss-Seidel method.

Keywords: Linear system of equations, Gauss-Seidel iteration, algebraic structure, convergence.

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Authors: Abdallah Al-Shammari

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This study discusses the effect of uncertainty on production levels of a petrochemical complex. Uncertainly or variations in some model parameters, such as prices, supply and demand of materials, can affect the optimality or the efficiency of any chemical process. For any petrochemical complex with many plants, there are many sources of uncertainty and frequent variations which require more attention. Many optimization approaches are proposed in the literature to incorporate uncertainty within the model in order to obtain a robust solution. In this work, a stability analysis approach is applied to a deterministic LP model of a petrochemical complex consists of ten plants to investigate the effect of such variations on the obtained optimal production levels. The proposed approach can determinate the allowable variation ranges of some parameters, mainly objective or RHS coefficients, before the system lose its optimality. Parameters with relatively narrow range of variations, i.e. stability limits, are classified as sensitive parameters or constraints that need accurate estimate or intensive monitoring. These stability limits offer easy-to-use information to the decision maker and help in understanding the interaction between some model parameters and deciding when the system need to be re-optimize. The study shows that maximum production of ethylene and the prices of intermediate products are the most sensitive factors that affect the stability of the optimum solution

Keywords: Linear programming, Petrochemicals, stability analysis, uncertainty

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Authors: Mananya Meenakorn

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This research aims to investigate: (1) Relationship between the quality of working life and organizational commitment of municipal employee in Samut Sakhon Province. (2) To compare the quality of working life and the organizational commitment of municipal employee in Samut Sakhon Province by the gender, age, education, official experience, position, division, and income. This study is a quantitative research; data was collected by questionnaires distributed to the municipal employee in Samut Sakhon province for 241 sample by stratified random sampling. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including t-test, F-test and Pearson correlation for hypothesis testing. Finding showed that the quality of working life and the organizational commitment of municipal Employee in Samut Sakhon province in terms of compensation and fair has a positive correlation (r = 0.673) and the comparison of the quality of working life and organizational commitment of municipal employees in Samut Sakhon province by gender. We found that the overall difference was statistically significant at the 0.05 level and we also found stability and progress in career path and the characteristics are beneficial to society has a difference was statistically significant at the 0.01 level, and the participation and social acceptance has a difference was statistically significant at the 0.05 level.

Keywords: Quality of working life, organizational commitment, municipal employee, Samut Sakhon province.

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Authors: Justinian Anatory, Ekael Stephen Manase

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The use of mobile phones is growing tremendously all over the world. In Tanzania there are a number of operators licensed by Tanzania Communications Regulatory Authority (TCRA) aiming at attracting customers into their networks. So far telecommunications market competition has been very stiff. Various measures are being taken by mobile operators to survive in the market. Such measure include introducing of different air time bundles on daily, weekly and monthly at lower tariffs. Other measures include the introduction of normal tariff, tourist package and one network. Despite of all these strategies, there is a dynamic competition in the market which needs to be explored. Some influences which attract customers to choose a certain mobile operator are of particular interest. This paper is investigating if the network effects and Quality of Services (QoS) influence mobile customers in selection of their mobile network operators. Seventy seven students from high learning institutions in Dodoma Municipality in Tanzania participated in responding to prepared questionnaires. The data was analyzed using Statistical Package for Social Science (SPSS) Software. The results indicate that, network coverage does influence customers in selection of mobile operators. In addition, this paper proposes further research in some areas especially where the study came up with different findings from what the theory has in place.

Keywords: Network effects, Quality of services, Consumer Buying, mobile operators.

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Authors: Ali Ridho Barakbah, Yasushi Kiyoki

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This paper presents a new approach for image segmentation by applying Pillar-Kmeans algorithm. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after optimized by Pillar Algorithm. The Pillar algorithm considers the pillars- placement which should be located as far as possible from each other to withstand against the pressure distribution of a roof, as identical to the number of centroids amongst the data distribution. This algorithm is able to optimize the K-means clustering for image segmentation in aspects of precision and computation time. It designates the initial centroids- positions by calculating the accumulated distance metric between each data point and all previous centroids, and then selects data points which have the maximum distance as new initial centroids. This algorithm distributes all initial centroids according to the maximum accumulated distance metric. This paper evaluates the proposed approach for image segmentation by comparing with K-means and Gaussian Mixture Model algorithm and involving RGB, HSV, HSL and CIELAB color spaces. The experimental results clarify the effectiveness of our approach to improve the segmentation quality in aspects of precision and computational time.

Keywords: Image segmentation, K-means clustering, Pillaralgorithm, color spaces.

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Authors: Luís Pina

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The conservation of marine biodiversity keeps ecosystems in balance and ensures the sustainable use of resources. In this context, technological resources have been used for monitoring marine species to allow biologists to obtain data in real-time. There are different mobile applications developed for data collection for monitoring purposes, but these systems are designed to be utilized only on third-generation (3G) phones or smartphones with Internet access and in rural parts of the developing countries, Internet services and smartphones are scarce. Thus, the objective of this work is to develop a system to monitor marine turtles using Unstructured Supplementary Service Data (USSD), which users can access through basic mobile phones. The system aims to improve the data collection mechanism and enhance the effectiveness of current systems in monitoring sea turtles using any type of mobile device without Internet access. The system will be able to report information related to the biological activities of marine turtles. Also, it will be used as a platform to assist marine conservation entities to receive reports of illegal sales of sea turtles. The system can also be utilized as an educational tool for communities, providing knowledge and allowing the inclusion of communities in the process of monitoring marine turtles. Therefore, this work may contribute with information to decision-making and implementation of contingency plans for marine conservation programs.

Keywords: GSM, marine biology, marine turtles, USSD.

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Authors: R. F. B. Gonçalves, E. N. Iwama, J. A. F. F. Rocco, K. Iha

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Propellants based on Hydroxyl Terminated Polybutadiene/Ammonium Perchlorate (HTPB/AP) are the most commonly used in most of the rocket engines used by the Brazilian Armed Forces. This work aimed at the possibility of extending its useful life (currently in 10 years) by performing kinetic-chemical analyzes of its energetic material via Differential Scanning Calorimetry (DSC) and also performing computer simulation of aging process using the software Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). Thermal analysis via DSC was performed in triplicates and in three heating ratios (5 ºC, 10 ºC, and 15 ºC) of rocket motor with 11 years shelf-life, using the Arrhenius equation to obtain its activation energy, using Ozawa and Kissinger kinetic methods, allowing comparison with manufacturing period data (standard motor). In addition, the kinetic parameters of internal pressure of the combustion chamber in 08 rocket engines with 11 years of shelf-life were also acquired, for comparison purposes with the engine start-up data.

Keywords: Shelf-life, thermal analysis, Ozawa method, Kissinger method, LAMMPS software, thrust.

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Authors: Aspalella A. Rahman

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Money laundering has been described by many as the lifeblood of crime and is a major threat to the economic and social well-being of societies. It has been recognized that the banking system has long been the central element of money laundering. This is in part due to the complexity and confidentiality of the banking system itself. It is generally accepted that effective anti-money laundering (AML) measures adopted by banks will make it tougher for criminals to get their "dirty money" into the financial system. In fact, for law enforcement agencies, banks are considered to be an important source of valuable information for the detection of money laundering. However, from the banks- perspective, the main reason for their existence is to make as much profits as possible. Hence their cultural and commercial interests are totally distinct from that of the law enforcement authorities. Undoubtedly, AML laws create a major dilemma for banks as they produce a significant shift in the way banks interact with their customers. Furthermore, the implementation of the laws not only creates significant compliance problems for banks, but also has the potential to adversely affect the operations of banks. As such, it is legitimate to ask whether these laws are effective in preventing money launderers from using banks, or whether they simply put an unreasonable burden on banks and their customers. This paper attempts to address these issues and analyze them against the background of the Malaysian AML laws. It must be said that effective coordination between AML regulator and the banking industry is vital to minimize problems faced by the banks and thereby to ensure effective implementation of the laws in combating money laundering.

Keywords: Banking Industry, Bank Negara Money, Laundering, Malaysia.

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Authors: Thuraya M. Qaradaghi, Newroz N. Abdulrazaq

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The McEliece cryptosystem is an asymmetric type of cryptography based on error correction code. The classical McEliece used irreducible binary Goppa code which considered unbreakable until now especially with parameter [1024, 524, and 101], but it is suffering from large public key matrix which leads to be difficult to be used practically. In this work Irreducible and Separable Goppa codes have been introduced. The Irreducible and Separable Goppa codes used are with flexible parameters and dynamic error vectors. A Comparison between Separable and Irreducible Goppa code in McEliece Cryptosystem has been done. For encryption stage, to get better result for comparison, two types of testing have been chosen; in the first one the random message is constant while the parameters of Goppa code have been changed. But for the second test, the parameters of Goppa code are constant (m=8 and t=10) while the random message have been changed. The results show that the time needed to calculate parity check matrix in separable are higher than the one for irreducible McEliece cryptosystem, which is considered expected results due to calculate extra parity check matrix in decryption process for g2(z) in separable type, and the time needed to execute error locator in decryption stage in separable type is better than the time needed to calculate it in irreducible type. The proposed implementation has been done by Visual studio C#.

Keywords: McEliece cryptosystem, Goppa code, separable, irreducible.

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Authors: Soyoon Bak, Sunyoung Bu, Philsu Kim

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In this paper, a backward semi-Lagrangian scheme combined with the second-order backward difference formula is designed to calculate the numerical solutions of nonlinear advection-diffusion equations. The primary aims of this paper are to remove any iteration process and to get an efficient algorithm with the convergence order of accuracy 2 in time. In order to achieve these objects, we use the second-order central finite difference and the B-spline approximations of degree 2 and 3 in order to approximate the diffusion term and the spatial discretization, respectively. For the temporal discretization, the second order backward difference formula is applied. To calculate the numerical solution of the starting point of the characteristic curves, we use the error correction methodology developed by the authors recently. The proposed algorithm turns out to be completely iteration free, which resolves the main weakness of the conventional backward semi-Lagrangian method. Also, the adaptability of the proposed method is indicated by numerical simulations for Burgers’ equations. Throughout these numerical simulations, it is shown that the numerical results is in good agreement with the analytic solution and the present scheme offer better accuracy in comparison with other existing numerical schemes.

Keywords: Semi-Lagrangian method, Iteration free method, Nonlinear advection-diffusion equation.

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Authors: Marcia T. Mitchell

Abstract:

This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely Cµ programming. In this domain all the keywords and programming concepts are known and understood.

Keywords: Natural language understanding, computational linguistics, knowledge representation, linguistic theories.

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Authors: Fatima M. Kabbashi, Abdalla M. Abdalla, Hussam K. Hamad, Elias S. Hassan

Abstract:

This study investigates the production of renewable energy (biogas) from biomedical hazard waste (blood) and eco-friendly disposal. Biogas is produced by the bacterial anaerobic digestion of biomaterial (blood). During digestion process bacterial feeding result in breaking down chemical bonds of the biomaterial and changing its features, by the end of the digestion (biogas production) the remains become manure as known. That has led to the economic and eco-friendly disposal of hazard biomedical waste (blood). The samples (Whole blood, Red blood cells 'RBCs', Blood platelet and Fresh Frozen Plasma ‘FFP’) are collected and measured in terms of carbon to nitrogen C/N ratio and total solid, then filled in connected flasks (three flasks) using water displacement method. The results of trails showed that the platelet and FFP failed to produce flammable gas, but via a gas analyzer, it showed the presence of the following gases: CO, HC, CO₂, and NOX. Otherwise, the blood and RBCs produced flammable gases: Methane-nitrous CH₃NO (99.45%), which has a blue color flame and carbon dioxide CO₂ (0.55%), which has red/yellow color flame. Methane-nitrous is sometimes used as fuel for rockets, some aircraft and racing cars.

Keywords: Renewable energy, biogas, biomedical waste, blood, anaerobic digestion, eco-friendly disposal.

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

Abstract:

The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter.

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Authors: Madhuri Bhavsar, Anupam K Singh, Shrikant Pradhan

Abstract:

Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.

Keywords: Climate model, Computational Grid, GridApplication, Heterogeneous Grid

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Authors: Subramaniam Chandran

Abstract:

The significance of psychology in studying politics is embedded in philosophical issues as well as behavioural pursuits. For the former is often associated with Sigmund Freud and his followers. The latter is inspired by the writings of Harold Lasswell. Political psychology or psychopolitics has its own impression on political thought ever since it deciphers the concept of human nature and political propaganda. More importantly, psychoanalysis views political thought as a textual content which needs to explore the latent from the manifest content. In other words, it reads the text symptomatically and interprets the hidden truth. This paper explains the paradigm of dream interpretation applied by Freud. The dream work is a process which has four successive activities: condensation, displacement, representation and secondary revision. The texts dealing with political though can also be interpreted on these principles. Freud's method of dream interpretation draws its source after the hermeneutic model of philological research. It provides theoretical perspective and technical rules for the interpretation of symbolic structures. The task of interpretation remains a discovery of equivalence of symbols and actions through perpetual analogies. Psychoanalysis can help in studying political thought in two ways: to study the text distortion, Freud's dream interpretation is used as a paradigm exploring the latent text from its manifest text; and to apply Freud's psychoanalytic concepts and theories ranging from individual mind to civilization, religion, war and politics.

Keywords: Psychoanalysis, political thought, dreaminterpretation, latent content, manifest content

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Authors: A. Baith Mohamed, Ayman Abdel-Hamid, Kareem Youssri Mohamed

Abstract:

Current proposals for E-passport or ID-Card is similar to a regular passport with the addition of tiny contactless integrated circuit (computer chip) inserted in the back cover, which will act as a secure storage device of the same data visually displayed on the photo page of the passport. In addition, it will include a digital photograph that will enable biometric comparison, through the use of facial recognition technology at international borders. Moreover, the e-passport will have a new interface, incorporating additional antifraud and security features. However, its problems are reliability, security and privacy. Privacy is a serious issue since there is no encryption between the readers and the E-passport. However, security issues such as authentication, data protection and control techniques cannot be embedded in one process. In this paper, design and prototype implementation of an improved E-passport reader is presented. The passport holder is authenticated online by using GSM network. The GSM network is the main interface between identification center and the e-passport reader. The communication data is protected between server and e-passport reader by using AES to encrypt data for protection will transferring through GSM network. Performance measurements indicate a 19% improvement in encryption cycles versus previously reported results.

Keywords: RFID "Radio Frequency Identification", EPC"Electronic Product Code", ICAO "International Civil Aviation Organization", IFF "Identify Friend or Foe"

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