Search results for: support services

Authors: Clemens Pizzinini, Philipp Rosner, David Ziegler, Markus Lienkamp

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Transportation is a constitutional part of most supply and value chains in modern economies. Smallholder farmers in rural Ethiopia face severe challenges along their supply and value chains. In particular, suitable, affordable, and available transport services are in high demand. To develop context-specific technical solutions, a problem-to-solution methodology based on the interaction with technology is developed. With this approach, we fill the gap between proven transportation assessment frameworks and general user-centered techniques. Central to our approach is an electric test vehicle that is implemented in rural supply and value chains for research, development, and testing. Based on our objective and the derived methodological requirements, a set of existing methods is  selected. Local partners are integrated in an organizational framework that executes major parts of this research endeavour in Arsi Zone, Oromia Region, Ethiopia.

Keywords: Agricultural value chain, participatory methods, agile methods, sub-Saharan Africa, Ethiopia, electric vehicle, transport service.

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Authors: Alaa-Aldin Abdul Rahim A. Al Athmay

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E-governance is an emerging and challenging initiative in developing countries. It is not only concerning the provision of services through the use ICT but rather entails building external interactions with citizen and businesses, enhancing democracy and trust of the political institutions of government. It embraces among other principles, openness, accountability and citizen engagement in public policy process. This study aims at finding users’ satisfaction with three chosen dimensions of e-governance, namely: openness, collaborative governance, and participation. These dimensions of e-governance are neither studied before in the context of Arab countries and nor explored earlier in relation to some demographics variables. A study of 900 users of e-government in United Arab Emirates (UAE) was undertaken to examine how gender, age, education, nationality, and employment affect their satisfaction with e-governance. Generally, satisfaction ratings vary significantly with these variables. However, the overall level of satisfaction with the three attributes was less favorable. Knowing the differences of  citizen’s perceptions towards e-governance services would help policymakers in the design of effective e-governance strategy.   

Keywords: E-governance, United Arab Emirates, Citizens' perceptions.

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Authors: Federico Cabitza, Marco P. Locatelli, Marcello Sarini, Carla Simone

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The paper shows how the CASMAS modeling language, and its associated pervasive computing architecture, can be used to facilitate continuity of care by providing members of patientcentered communities of care with a support to cooperation and knowledge sharing through the usage of electronic documents and digital devices. We consider a scenario of clearly fragmented care to show how proper mechanisms can be defined to facilitate a better integration of practices and information across heterogeneous care networks. The scenario is declined in terms of architectural components and cooperation-oriented mechanisms that make the support reactive to the evolution of the context where these communities operate.

Keywords: Pervasive Computing, Communities of Care, HeterogeneousCare Networks, Multi-Agent System.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: Michele Grimaldi, Livio Cricelli, Francesco Rogo, Alessia Iannarelli

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The objective of this paper is to support the application of Open Innovation practices in firms and organizations by the assessment and management of Intellectual Capital. Intellectual Capital constituents are analyzed in order to verify their capability of acting as key drivers of Open Innovation processes and, therefore, of creating value. A methodology is defined to settle a procedure which helps to select the most relevant Intellectual Capital value drivers and to provide Communities of Innovation with strategic and managerial guidelines in sustaining Open Innovation paradigm. An application of the methodology is developed within a specifically addressed project and its results are hereafter examined.

Keywords: Assessment, Community of Innovation, Intellectual Capital, Management, Open Innovation.

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Authors: Paitoon Kraipornsak

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Government spending is categorized into consumption spending and capital spending. Three categories of private consumption are used: food consumption, nonfood consumption, and services consumption. The estimated model indicates substitution effects of government consumption spending on budget shares of private nonfood consumption and of government capital spending on budget share of private food consumption. However, the results do not indicate whether the negative effects of changes in the budget shares of the nonfood and the food consumption equates to reduce total private consumption. The concept of aggregate demand comprising consumption, investment, government spending (consumption spending and capital spending), export, and import are used to estimate their relationship by using the Vector Error Correction Mechanism. The study found no effect of government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP.

Keywords: Complementary effect, government capital spending, government consumption spending, private consumption on food, nonfood, and services, substitution effect, vector error correction mechanism.

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Authors: Jean François Chatelain, Imed Zaghbani, Gilbert Lebrun, Kaml Hasni

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Severe damages may occur during the drilling of carbon fiber reinforced plastics (CFRP). In practice, this damage is limited by adding a backup support to the drilled parts. For some aeronautical parts with curvatures, backing up parts is a demanding process. In order to simplify the operation, this research studies the effect of using a configurable setup to support parts on the resulting quality of drilled holes. The test coupons referenced in this study are twenty four-plies unidirectional laminates made of carbon fibers and epoxy resin. Different signals were measured during the drilling process for these laminates, including the thrust force, the displacement and the acceleration. The processing of these signals demonstrated that the damage is due to the combination of two main factors: the spring-back of the thin part and the thrust force. The results found were confirmed for different feeds and speeds. When the distance between supports is increased, it is observed that the spring-back increases but the thrust force decreases. The study proves the feasibility of unsupported drilling of thin CFRP laminates without creating any observable damage.

Keywords: CFRP, Damage, Drilling, Flexible setup.

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Authors: M.Stella, M. Russo, D. Begušić

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Ability of accurate and reliable location estimation in indoor environment is the key issue in developing great number of context aware applications and Location Based Services (LBS). Today, the most viable solution for localization is the Received Signal Strength (RSS) fingerprinting based approach using wireless local area network (WLAN). This paper presents two RSS fingerprinting based approaches – first we employ widely used WLAN based positioning as a reference system and then investigate the possibility of using GSM signals for positioning. To compare them, we developed a positioning system in real world environment, where realistic RSS measurements were collected. Multi-Layer Perceptron (MLP) neural network was used as the approximation function that maps RSS fingerprints and locations. Experimental results indicate advantage of WLAN based approach in the sense of lower localization error compared to GSM based approach, but GSM signal coverage by far outreaches WLAN coverage and for some LBS services requiring less precise accuracy our results indicate that GSM positioning can also be a viable solution.

Keywords: Indoor positioning, WLAN, GSM, RSS, location fingerprints, neural network.

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Authors: Carilette Fourie, Chris Cloete

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The occurrence of traditional authorities and tribal land within South Africa results in unique developmental trends and challenges. Tribal communities, typically located in rural environments, are perceived to be severely affected by poverty and poor living conditions relative to their urban counterparts. The exact extent of the socio-economic disparity between tribal and non-tribal communities is addressed in this paper. After adjustment of available census data to correspond with the delineation of tribal and non-tribal land in the Kwazulu-Natal province, seven selected socio-economic indicators were compared. The investigation revealed that although tribal areas are characterised by low employment rates and educational levels, a young population, fairly large household sizes, lower access to basic services and lower income households that are highly dependent on social grants, tribal area populations do have moderate levels of education, access to formal housing and relatively good access to services.

Keywords: KwaZulu-Natal, tribal areas, traditional authority, socio-economic, well-being.

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Authors: Jinn-Yi Yeh, Tai-Hsi Wu

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Hemodialysis patients might suffer from unhealthy care behaviors or long-term dialysis treatments. Ultimately they need to be hospitalized. If the hospitalization rate of a hemodialysis center is high, its quality of service would be low. Therefore, how to decrease hospitalization rate is a crucial problem for health care. In this study we combined temporal abstraction with data mining techniques for analyzing the dialysis patients' biochemical data to develop a decision support system. The mined temporal patterns are helpful for clinicians to predict hospitalization of hemodialysis patients and to suggest them some treatments immediately to avoid hospitalization.

Keywords: Hemodialysis, Temporal abstract, Data mining, Healthcare quality.

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Authors: Kristina Maiksteniene

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Various formal and informal brand alliances are being formed in professional service firms. Professional service corporate brand is heavily dependent on brands of professional employees who comprise them, and professional employee brands are in turn dependent on the corporate brand. Prior work provides limited scientific evidence of brand alliance effects in professional service area – i.e., how professional service corporate-employee brand allies are affected by an alliance, what are brand attitude effects after alliance formation and how these effects vary with different strengths of an ally. Scientific literature analysis and theoretical modeling are the main methods of the current study. As a result, a theoretical model is constructed for estimating spillover effects of professional service corporate-employee brand alliances and for comparison among different professional service firm expertise practice models – from “brains" to “procedure" model. The resulting theoretical model lays basis for future experimental studies.

Keywords: Brand alliances, professional services, corporatebrand, employee brand.

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Authors: Dilusha Weeraddana, Ashanie Gunathillake, Samiru Gayan

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In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment. 

Keywords: Emergency response, Firefighters, Navigation, Wireless sensor network.

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Authors: Mohamed R. Mhereeg

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The paper investigates the feasibility of constructing a software multi-agent based monitoring and classification system and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. The agents function autonomously to provide continuous and periodic monitoring of excels spreadsheet workbooks. Resulting in, the development of the MultiAgent classification System (MACS) that is in compliance with the specifications of the Foundation for Intelligent Physical Agents (FIPA). However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies that are Windows Communication Foundation (WCF) services, Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW that is in order to satisfy the monitoring and classification of the multiple developer aspect. ODM was used to automate the classification phase of MACS.

Keywords: Autonomous, Classification, MACS, Multi-Agent, SOA, WCF.

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Authors: Fatemeh Nikpay, Rodina Binti Ahmad, Babak Darvish Rouhani

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Enterprise Architecture (EA) is employed by enterprises for providing integrated Information Systems (ISs) in order to support alignment of their business and Information Technology (IT). Evaluation of EA implementation can support enterprise to reach intended goals. There are some problems in current evaluation methods of EA implementation that lead to ineffectiveness implementation of EA. This paper represents current issues on evaluation of EA implementation. In this regard, we set the framework in order to represent evaluation’s issues based on their functionality and structure. The results of this research not only increase the knowledge of evaluation, but also could be useful for both academics and practitioners in order to realize the current situation of evaluations.

Keywords: Current issues on EA, implementation evaluation, Evaluation, Enterprise Architecture, Evaluation of Enterprise Architecture Implementation.

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Authors: V. Vicente E. Mujica, Gustavo Gonzalez

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The global coverage of broadband multimedia and internet-based services in terrestrial-satellite networks demand particular interests for satellite providers in order to enhance services with low latencies and high signal quality to diverse users. In particular, the delay of on-board processing is an inherent source of latency in a satellite communication that sometimes is discarded for the end-to-end delay of the satellite link. The frame work for this paper includes modelling of an on-orbit satellite payload using an agent model that can reproduce the properties of processing delays. In essence, a comparison of different spatial interpolation methods is carried out to evaluate physical data obtained by an GEO satellite in order to define a discretization function for determining that delay. Furthermore, the performance of the proposed agent and the development of a delay discretization function are together validated by simulating an hybrid satellite and terrestrial network. Simulation results show high accuracy according to the characteristics of initial data points of processing delay for Ku bands.

Keywords: Terrestrial-satellite networks, latency, on-orbit satellite payload, simulation.

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Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

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Understanding proteins functions is a major goal in the post-genomic era. Proteins usually work in context of other proteins and rarely function alone. Therefore, it is highly relevant to study the interaction partners of a protein in order to understand its function. Machine learning techniques have been widely applied to predict protein-protein interactions. Kernel functions play an important role for a successful machine learning technique. Choosing the appropriate kernel function can lead to a better accuracy in a binary classifier such as the support vector machines. In this paper, we describe a Bayesian kernel for the support vector machine to predict protein-protein interactions. The use of Bayesian kernel can improve the classifier performance by incorporating the probability characteristic of the available experimental protein-protein interactions data that were compiled from different sources. In addition, the probabilistic output from the Bayesian kernel can assist biologists to conduct more research on the highly predicted interactions. The results show that the accuracy of the classifier has been improved using the Bayesian kernel compared to the standard SVM kernels. These results imply that protein-protein interaction can be predicted using Bayesian kernel with better accuracy compared to the standard SVM kernels.

Keywords: Bioinformatics, Protein-protein interactions, Bayesian Kernel, Support Vector Machines.

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Authors: Ali S. Al-Aufi, Paul Genoni

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The emergence of networked information and communication has transformed the accessibility and delivery of scholarly information and fundamentally impacted on the processes of research and scholarly communication. The purpose of this study is to investigate disciplinary differences in the use of networked information for research and scholarly communication at Sultan Qaboos University, Oman. This study has produced quantitative data about how and why academics within different disciplines utilize networked information that is made available either internally through the university library, or externally through networked services accessed by the Internet. The results indicate some significant differences between the attitudes and practice of academics in the science disciplines when compared to those from the social sciences and humanities. While respondents from science disciplines show overall longer and more frequent use of networked information, respondents from humanities and social sciences indicated more positive attitudes and a greater degree of satisfaction toward library networked services.

Keywords: Academics, Arab World, Disciplinary Culture, Networked Information, Scholarly Communication, Sultan QaboosUniversity, Oman.

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Authors: Ubaidillah Zuhdi, Shunsuke Mori, Kazuhisa Kamegai

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The purpose of this study is to forecast the influences of information and communication technology (ICT) on the structural changes of Japanese economies. In this study, input-output (IO) and statistical approaches are used as analysis instruments. More specifically, this study employs Leontief IO coefficients and constrained multivariate regression (CMR) model in order to achieve the purpose. The periods of initial and forecast in this study are 2005 and 2015, respectively. In this study, ICT is represented by ICT capital stocks. This study conducts two levels of analysis, namely macro and micro. The results of macro level analysis show that the dynamics of Japanese economies on the forecast period, relative to the initial period, are not so high. We focus on (1) commerce, (2) business services and office supplies, and (3) personal services sectors when conducting the analysis of the micro level. Further, we analyze its specific IO coefficients when doing this analysis. The results of the analysis explain that ICT gives a strong influence on the changes of these coefficients from initial to forecast periods.

Keywords: Forecast, ICT, Structural changes, Japanese economies.

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Authors: Zaihisma C. Cob, Alicia Y.C. Tang, Sharifah J. Syed Aziz

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This paper proposes a new model to support user queries on postgraduate research information at Universiti Tenaga Nasional. The ontology to be developed will contribute towards shareable and reusable domain knowledge that makes knowledge assets intelligently accessible to both people and software. This work adapts a methodology for ontology development based on the framework proposed by Uschold and King. The concepts and relations in this domain are represented in a class diagram using the Protégé software. The ontology will be used to support a menudriven query system for assisting students in searching for information related to postgraduate research at the university.

Keywords: Ontology, Protégé, postgraduate program, query system.

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Authors: Heejung Lee, Hyo-Won Suh

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Hybrid knowledge model is suggested as an underlying framework for product development management. It can support such hybrid features as ontologies and rules. Effective collaboration in product development environment depends on sharing and reasoning product information as well as engineering knowledge. Many studies have considered product information and engineering knowledge. However, most previous research has focused either on building the ontology of product information or rule-based systems of engineering knowledge. This paper shows that F-logic based knowledge model can support such desirable features in a hybrid way.

Keywords: Ontology, rule, F-logic, product development.

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Authors: Hamid R. S. Mojaveri, Seyed S. Mousavi, Mojtaba Heydar, Ahmad Aminian

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The aim of this paper is to present a methodology in three steps to forecast supply chain demand. In first step, various data mining techniques are applied in order to prepare data for entering into forecasting models. In second step, the modeling step, an artificial neural network and support vector machine is presented after defining Mean Absolute Percentage Error index for measuring error. The structure of artificial neural network is selected based on previous researchers' results and in this article the accuracy of network is increased by using sensitivity analysis. The best forecast for classical forecasting methods (Moving Average, Exponential Smoothing, and Exponential Smoothing with Trend) is resulted based on prepared data and this forecast is compared with result of support vector machine and proposed artificial neural network. The results show that artificial neural network can forecast more precisely in comparison with other methods. Finally, forecasting methods' stability is analyzed by using raw data and even the effectiveness of clustering analysis is measured.

Keywords: Artificial Neural Networks (ANN), bullwhip effect, demand forecasting, Support Vector Machine (SVM).

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Authors: Manisha Dubey, Gaurav Gupta, Anoop Arya

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The demand for power supply increases day by day in developing countries like India henceforth demand of reactive power support in the form of ancillary services provider also has been increased. The multi-line and multi-type Flexible alternating current transmission system (FACTS) controllers are playing a vital role to regulate power flow through the transmission line. Unified power flow controller and interline power flow controller can be utilized to control reactive power flow through the transmission line. In a restructured power system, the demand of such controller is being popular due to their inherent capability. The transmission pricing by using reactive power cost allocation through modified matrix methodology has been proposed. The FACTS technologies have quite costly assembly, so it is very useful to apportion the expenses throughout the restructured electricity industry. Therefore, in this work, after embedding the FACTS devices into load flow, the impact on the costs allocated to users in fraction to the transmission framework utilization has been analyzed. From the obtained results, it is clear that the total cost recovery is enhanced towards the Reactive Power flow through the different transmission line for 5 bus test system. The fair pricing policy towards reactive power can be achieved by the proposed method incorporating FACTS controller towards cost recovery of the transmission network.

Keywords: Inter line power flow controller, Transmission Pricing, Unified power flow controller, cost allocation.

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Authors: M.Radmehr, S.M.Anisheh, I.Yousefian

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In this work a new offline signature recognition system based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained vectors are calculated to construct a feature vector for each signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of the system several experiments are carried out. Offline signature database from signature verification competition (SVC) 2004 is used during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.

Keywords: Fractal Dimension, Offline Signature Recognition, Radon Transform, Support Vector Machine

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Authors: Nebi Gedik

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Regardless of age or gender, cardiovascular illnesses are a serious health concern because of things like poor eating habits, stress, a sedentary lifestyle, hard work schedules, alcohol use, and weight. It tends to happen suddenly and has a high rate of recurrence. Machine learning models can be implemented to assist healthcare systems in the accurate detection and diagnosis of cardiovascular disease (CVD) in patients. Improved heart failure prediction is one of the primary goals of researchers using the heart disease dataset. The purpose of this study is to identify the feature or features that offer the best classification prediction for CVD detection. The support vector machine classifier is used to compare each feature's performance. It has been determined which feature produces the best results.

Keywords: Cardiovascular disease, feature extraction, supervised learning, support vector machine.

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Authors: S. Balaji, V. Swaminathan, K. Kannan

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The Maximum Weighted Independent Set (MWIS) problem is a classic graph optimization NP-hard problem. Given an undirected graph G = (V, E) and weighting function defined on the vertex set, the MWIS problem is to find a vertex set S V whose total weight is maximum subject to no two vertices in S are adjacent. This paper presents a novel approach to approximate the MWIS of a graph using minimum weighted vertex cover of the graph. Computational experiments are designed and conducted to study the performance of our proposed algorithm. Extensive simulation results show that the proposed algorithm can yield better solutions than other existing algorithms found in the literature for solving the MWIS.

Keywords: weighted independent set, vertex cover, vertex support, heuristic, NP - hard problem.

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Authors: Monisha Isaac

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Biotechnology is a discipline which explains the use of living organisms and systems to construct a product, or we can define it as an application or technology developed to use biological systems and organisms processes for a specific use. Particularly, it includes cells and its components use for new technologies and inventions. The tools developed can be further used in diverse fields such as agriculture, industry, research and hospitals etc. The 21^st century has seen a drastic development and advancement in biotechnology in India. Significant increase in Government of India’s outlays for biotechnology over the past decade has been observed. A sectoral break up of biotechnology-based companies in India shows that most of the companies are agriculture-based companies having interests ranging from tissue culture to biopesticides. Major attention has been given by the companies in health related activities and in environmental biotechnology. The biopharmaceutical, which comprises of vaccines, diagnostic, and recombinant products is the most reliable and largest segment of the Indian Biotech industry. India has developed its vaccine markets and supplies them to various countries. Then there are the bio-services, which mainly comprise of contract researches and manufacturing services. India has made noticeable developments in the field of bio industries including manufacturing of enzymes, biofuels and biopolymers. Biotechnology is also playing a crucial and significant role in the field of agriculture. Traditional methods have been replaced by new technologies that mainly focus on GM crops, marker assisted technologies and the use of biotechnological tools to improve the quality of fertilizers and soil. It may only be a small contributor but has shown to have huge potential for growth. Bioinformatics is a computational method which helps to store, manage, arrange and design tools to interpret the extensive data gathered through experimental trials, making it important in the design of drugs.

Keywords: Biotechnology, advancement, agriculture, bio-services, bio-industries, bio-pharmaceuticals.

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Authors: Ngozi Nwogu, Edward Gobina

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A dip-coating process has been used to form an asymmetric silica membrane with improved membrane performance and reproducibility. First, we deposited repeatedly silica on top of a commercial alumina membrane support to improve its structural make up. The membrane is further processed under clean room conditions to avoid dust impurity and subsequent drying in an oven for high thermal, chemical and physical stability. The resulting asymmetric membrane exhibits a gradual change in the membrane layer thickness. Compared to the support, the dual-layer process improves the gas flow rates. For the scientific applications for natural gas purification, CO2, CH4 and H2 gas flow rates were. In addition, the membrane selectively separated hydrogen.

Keywords: Gas permeation, Silica membrane, separation factor, membrane layer thickness.

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Authors: Francisco Javier Reyes Salazar, Héctor Mauricio Ramírez

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The coastal zones are home to mangrove swamps, coral reefs, and seagrass ecosystems, which are the most biodiverse and fragile on the planet. These areas support a great diversity of marine life; they are also extraordinarily important for humans in the provision of food, water, wood, and other associated goods and services; they also contribute to climate regulation. The lack of an automated model that generates information on the dynamics of changes in coastlines and coastal erosion is identified as a central problem. In this paper, coastlines were determined from 1984 to 2020 on the Google Earth Engine platform from Landsat and Sentinel images. Then, we determined the Modified Normalized Difference Water Index (MNDWI) and used Digital Shoreline Analysis System (DSAS) v5.0. Starting from the 2020 coastline; the 10-year prediction (Year 2031) was determined with the erosion of 238.32 hectares and an accretion of 181.96 hectares. For the 20-year prediction (Year 2041) will be presented an erosion of 544.04 hectares and an accretion of 133.94 hectares. The erosion and accretion of Playa Muelle in the municipality of Puerto Colombia were established, which will register the highest value of erosion. The coverage that presented the greatest change was that of artificialized territories.

Keywords: Coastline, coastal erosion, MNDWI, Google Earth Engine, Colombia.

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Authors: Somenath Mukherjee, Raj Kumar Samanta, Gautam Sanyal

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Different services based on different switching techniques in wireless networks leads to drastic changes in the properties of network traffic. Because of these diversities in services, network traffic is expected to undergo qualitative and quantitative variations. Hence, assumption of traffic characteristics and the prediction of network events become more complex for the wireless networks. In this paper, the traffic characteristics have been studied by collecting traces from the mobile switching centre (MSC). The traces include initiation and termination time, originating node, home station id, foreign station id. Traffic parameters namely, call interarrival and holding times were estimated statistically. The results show that call inter-arrival and distribution time in this wireless network is heavy-tailed and follow gamma distributions. They are asymptotically long-range dependent. It is also found that the call holding times are best fitted with lognormal distribution. Based on these observations, an analytical model for performance estimation is also proposed.

Keywords: Wireless networks, traffic analysis, long-range dependence, heavy-tailed distribution.

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Authors: Bhavneet Sidhu, Hardeep Singh, Amit Chhabra

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The world of wireless telecommunications is rapidly evolving. Technologies under research and development promise to deliver more services to more users in less time. This paper presents the emerging technologies helping wireless systems grow from where we are today into our visions of the future. This paper will cover the applications and characteristics of emerging wireless technologies: Wireless Local Area Networks (WiFi-802.11n), Wireless Personal Area Networks (ZigBee) and Wireless Metropolitan Area Networks (WiMAX). The purpose of this paper is to explain the impending 802.11n standard and how it will enable WLANs to support emerging media-rich applications. The paper will also detail how 802.11n compares with existing WLAN standards and offer strategies for users considering higher-bandwidth alternatives. The emerging IEEE 802.15.4 (ZigBee) standard aims to provide low data rate wireless communications with high-precision ranging and localization, by employing UWB technologies for a low-power and low cost solution. WiMAX (Worldwide Interoperability for Microwave Access) is a standard for wireless data transmission covering a range similar to cellular phone towers. With high performance in both distance and throughput, WiMAX technology could be a boon to current Internet providers seeking to become the leader of next generation wireless Internet access. This paper also explores how these emerging technologies differ from one another.

Keywords: MIMO technology, WiFi, WiMAX, ZigBee.

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