Search results for: multilevel fuzzy decision support model

Authors: L. Mirtskhulava, M. Khunjgurua, N. Lomineishvili, K. Bakuria

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Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: Exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability.

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Authors: Ridha Ghayoula, Mbarek Traii, Ali Gharsallah

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In this paper, we intend to study the synthesis of the multibeam arrays. The synthesis implementation-s method for this type of arrays permits to approach the appropriated radiance-s diagram. The used approach is based on neural network that are capable to model the multibeam arrays, consider predetermined general criteria-s, and finally it permits to predict the appropriated diagram from the neural model. Our main contribution in this paper is the extension of a synthesis model of these multibeam arrays.

Keywords: Multibeam, modelling, neural networks, synthesis, antennas.

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Authors: Cristina-Maria Păcurar

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The paper presents an original Python-based application that outlines the advantages of combining some elementary notions of mathematics with the study of a programming language. The application support refers to some of the first lessons of analytic geometry, meaning conics and quadrics and their reduction to a standard form, as well as some related notions. The chosen programming language is Python, not only for its closer to an everyday language syntax – and therefore, enhanced readability – but also for its highly reusable code, which is of utmost importance for a mathematician that is accustomed to exploit already known and used problems to solve new ones. The purpose of this paper is, on one hand, to support the idea that one of the most appropriate means to initiate one into programming is throughout mathematics, and reciprocal, one of the most facile and handy ways to assimilate some basic knowledge in the study of mathematics is to apply them in a personal project. On the other hand, besides being a mean of learning both programming and analytic geometry, the application subject to this paper is itself a useful tool for it can be seen as an independent original Python package for analytic geometry.

Keywords: Analytic geometry, conics, Python programming language, quadrics.

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Authors: Mannan Mridha, Mohammad S. Islam

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Innovative medical technologies offer more effective medical care, with less risk to patient and healthcare personnel. Medical technology and devices when properly used provide better data, precise monitoring and less invasive treatments and can be more targeted and often less costly. The Intensive Care Unit (ICU) equipped with patient monitoring, respiratory and cardiac support, pain management, emergency resuscitation and life support devices is particularly prone to medical errors for various reasons. Many people in the developing countries now wonder whether their visit to hospital might harm rather than help them. This is because; clinicians in the developing countries are required to maintain an increasing workload with limited resources and absence of well-functioning safety system. A team of experts from the medical, biomedical and clinical engineering in Sweden and Bangladesh have worked together to study the incidents, adverse events at the ICU in Bangladesh. The study included both public and private hospitals to provide a better understanding for physical structure, organization and practice in operating processes of care, and the occurrence of adverse outcomes the errors, risks and accidents related to medical devices at the ICU, and to develop a ICT based support system in order to reduce hazards and errors and thus improve the quality of performance, care and cost effectiveness at the ICU. Concrete recommendations and guidelines have been made for preparing appropriate ICT related tools and methods for improving the routine for use of medical devices, reporting and analyzing of the incidents at the ICU in order to reduce the number of undetected and unsolved incidents and thus improve the patient safety.

Keywords: Accidents reporting system, patient car and safety, safe medical devices.

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Authors: T. K. Sriram, Joydip Dhar

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Models based on stage structure have found varied applications in population models. This paper proposes a stage structured model to study the trends in the computer and video game playing population of US. The game paying population is divided into three compartments based on their age group. After simulating the mathematical model, a forecast of the number of game players in each stage as well as an approximation of the average age of game players in future has been made.

Keywords: Age structure, Forecasting, Mathematical modeling, Stage structure.

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Authors: Mohsen Pirdashti, Masoomeh Omidi, Hemmatollah Pidashti

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Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.

Keywords: Analytical Hierarchy Process, ARP, Delphi, Multi- criteria decision making, Citrogypsum

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Authors: N. Manavizadeh, A. Dehghani, M. Rabbani

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Mixed model assembly lines (MMAL) are a type of production line where a variety of product models similar in product characteristics are assembled. The effective design of these lines requires that schedule for assembling the different products is determined. In this paper we tried to fit the sequencing problem with the main characteristics of make to order (MTO) environment. The problem solved in this paper is a multiple objective sequencing problem in mixed model assembly lines sequencing using weighted Sum Method (WSM) using GAMS software for small problem and an effective GA for large scale problems because of the nature of NP-hardness of our problem and vast time consume to find the optimum solution in large problems. In this problem three practically important objectives are minimizing: total utility work, keeping a constant production rate variation, and minimizing earliness and tardiness cost which consider the priority of each customer and different due date which is a real situation in mixed model assembly lines and it is the first time we consider different attribute to prioritize the customers which help the company to reduce the cost of earliness and tardiness. This mechanism is a way to apply an advance available to promise (ATP) in mixed model assembly line sequencing which is the main contribution of this paper.

Keywords: Available to promise, Earliness & Tardiness, GA, Mixed-Model assembly line Sequencing.

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Authors: Nevine M. Labib, Michael N. Malek

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Data Mining aims at discovering knowledge out of data and presenting it in a form that is easily comprehensible to humans. One of the useful applications in Egypt is the Cancer management, especially the management of Acute Lymphoblastic Leukemia or ALL, which is the most common type of cancer in children. This paper discusses the process of designing a prototype that can help in the management of childhood ALL, which has a great significance in the health care field. Besides, it has a social impact on decreasing the rate of infection in children in Egypt. It also provides valubale information about the distribution and segmentation of ALL in Egypt, which may be linked to the possible risk factors. Undirected Knowledge Discovery is used since, in the case of this research project, there is no target field as the data provided is mainly subjective. This is done in order to quantify the subjective variables. Therefore, the computer will be asked to identify significant patterns in the provided medical data about ALL. This may be achieved through collecting the data necessary for the system, determimng the data mining technique to be used for the system, and choosing the most suitable implementation tool for the domain. The research makes use of a data mining tool, Clementine, so as to apply Decision Trees technique. We feed it with data extracted from real-life cases taken from specialized Cancer Institutes. Relevant medical cases details such as patient medical history and diagnosis are analyzed, classified, and clustered in order to improve the disease management.

Keywords: Data Mining, Decision Trees, Knowledge Discovery, Leukemia.

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Authors: Smajo Bisanovic, Mensur Hajro, Muris Dlakic

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This paper presents one comprehensive modelling approach for maintenance scheduling problem of thermal power units in competitive market. This problem is formulated as a 0/1 mixedinteger linear programming model. Model incorporates long-term bilateral contracts with defined profiles of power and price, and weekly forecasted market prices for market auction. The effectiveness of the proposed model is demonstrated through case study with detailed discussion.

Keywords: Maintenance scheduling, bilateral contracts, market prices, profit.

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Authors: Maatoug Hassine, Mourad Hrizi

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In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: Geometric inverse source problem, heat equation, topological sensitivity, topological optimization, Kohn-Vogelius formulation.

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Authors: Ramin Javadzadeh, Zahra Afsahi, MohammadReza Meybodi

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The hybridization of artificial immune system with cellular automata (CA-AIS) is a novel method. In this hybrid model, the cellular automaton within each cell deploys the artificial immune system algorithm under optimization context in order to increase its fitness by using its neighbor-s efforts. The hybrid model CA-AIS is introduced to fix the standard artificial immune system-s weaknesses. The credibility of the proposed approach is evaluated by simulations and it shows that the proposed approach achieves better results compared to standard artificial immune system.

Keywords: Artificial Immune System, Cellular Automat, neighborhood

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Authors: Fathi Taibi

Abstract:

Reusability is a quality desired attribute in software products. Generally, it could be achieved through adopting development methods that promote it and achieving software qualities that have been linked with high reusability proneness. With the exponential growth in mobile application development, software reuse became an integral part in a substantial number of projects. Similarly, software reuse has become widely practiced in start-up companies. However, this has led to new emerging problems. Firstly, the reused code does not meet the required quality and secondly, the reuse intentions are dubious. This work aims to propose a framework to support reuse in Object-Oriented (OO) software development. The framework comprises a process that uses a proposed reusability assessment metric and a formal foundation to specify the elements of the reused code and the relationships between them. The framework is empirically evaluated using a wide range of open-source projects and mobile applications. The results are analyzed to help understand the reusability proneness of OO software and the possible means to improve it.

Keywords: Software reusability, software metrics, object-oriented software, modularity, low complexity, understandability.

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Authors: Tarek Abdel Azim Ahmed, Eman Sarhan Shaker

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This research aims to explore how well the extended model of internet commerce adoption (eMICA) model is often used to determine the extent of internet commerce adoption in the travel agencies sector in both Egypt and Kingdom of Saudi Arabia (KSA). The web content analysis method was used to analyze the level of adoption of Egyptian travel agencies and Saudi travel agencies according to data immensely available on their websites. Therefore, each site was categorized according to the phases and levels proposed. In order to achieve this, 120 websites were evaluated by the two authors over a three-month period, from August to October 2020, and then categorized according to the phases and levels of (eMICA). The results show that there are deficiencies in the application of the eMICA model by both KSA and Egyptian travel agencies, generally, updating their websites, the absence of quality certification, offering secure online payment, virtual tours, and videos using Flash animation. In general, the Egyptian companies slightly outperformed the KSA ones in applying eMICA model.

Keywords: e-commerce, eMICA, Internet marketing, travel agencies, websites.

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Authors: Khaoula Hidouri, Ali Benhmidene, Bechir Chouachi

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The purification of brackish seawater becomes a necessity and not a choice against demographic and industrial growth especially in third world countries. Two models can be used in this work: simple solar still and simple solar still coupled with a heat pump. In this research, the productivity of water by Simple Solar Distiller (SSD) and Simple Solar Distiller Hybrid Heat Pump (SSDHP) was determined by the orientation, the use of heat pump, the simple or double glass cover. The productivity can exceed 1.2 L/m²h for the SSDHP and 0.5 L/m²h for SSD model. The result of the global efficiency is determined for two models SSD and SSDHP give respectively 30%, 50%. The internal efficiency attained 35% for SSD and 60% of the SSDHP models. Convective heat coefficient can be determined by attained 2.5 W/m²°C and 0.5 W/m²°C respectively for SSDHP and SSD models.

Keywords: Productivity, efficiency, convective heat coefficient, SSD model, SSDHP model.

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Authors: P. Luangpaiboon, S. Boonhao

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This study proposes a multi-response surface optimization problem (MRSOP) for determining the proper choices of a process parameter design (PPD) decision problem in a noisy environment of a grease position process in an electronic industry. The proposed models attempts to maximize dual process responses on the mean of parts between failure on left and right processes. The conventional modified simplex method and its hybridization of the stochastic operator from the hunting search algorithm are applied to determine the proper levels of controllable design parameters affecting the quality performances. A numerical example demonstrates the feasibility of applying the proposed model to the PPD problem via two iterative methods. Its advantages are also discussed. Numerical results demonstrate that the hybridization is superior to the use of the conventional method. In this study, the mean of parts between failure on left and right lines improve by 39.51%, approximately. All experimental data presented in this research have been normalized to disguise actual performance measures as raw data are considered to be confidential.

Keywords: Grease Position Process, Multi-response Surfaces, Modified Simplex Method, Hunting Search Method, Desirability Function Approach.

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Authors: B.A.Gobin, R.K.Subramanian

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This paper gives an overview of the mapping mechanism of SEAM-a methodology for the automatic generation of knowledge models and its mapping onto Java codes. It discusses the rules that will be used to map the different components in the knowledge model automatically onto Java classes, properties and methods. The aim of developing this mechanism is to help in the creation of a prototype which will be used to validate the knowledge model which has been generated automatically. It will also help to link the modeling phase with the implementation phase as existing knowledge engineering methodologies do not provide for proper guidelines for the transition from the knowledge modeling phase to development phase. This will decrease the development overheads associated to the development of Knowledge Based Systems.

Keywords: KBS, OWL, ontology, knowledge models

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Authors: S. Zamir

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The modern era has brought with it significant organizational changes. These changes have not bypassed the academic world, and along with the old academic bonds that include a world of knowledge and ethics, academic faculty members are required more than ever not only to survive in the academic world, but also to thrive and flourish and position themselves as modern and opinionated academicians. Based upon the writings of organizational consultants, the article suggests a 10 X C model for cultivating an academic backbone, as well as emphasizing its input to the professional growth of university and college academics: Competence, Calculations of pain & gain, Character, Commitment, Communication, Curiosity, Coping, Courage, Collaboration and Celebration.

Keywords: Academic career, academicians, higher education, the 10xC Model.

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Authors: Satoshi Usami

Abstract:

Among various HLM techniques, the Multivariate Hierarchical Linear Model (MHLM) is desirable to use, particularly when multivariate criterion variables are collected and the covariance structure has information valuable for data analysis. In order to reflect prior information or to obtain stable results when the sample size and the number of groups are not sufficiently large, the Bayes method has often been employed in hierarchical data analysis. In these cases, although the Markov Chain Monte Carlo (MCMC) method is a rather powerful tool for parameter estimation, Procedures regarding MCMC have not been formulated for MHLM. For this reason, this research presents concrete procedures for parameter estimation through the use of the Gibbs samplers. Lastly, several future topics for the use of MCMC approach for HLM is discussed.

Keywords: Gibbs sampler, Hierarchical Linear Model, Markov Chain Monte Carlo, Multivariate Hierarchical Linear Model

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Authors: S. Panda, J. S. Yadav, N. P. Patidar, C. Ardil

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Order Reduction, Stability, Transfer Function, Integral Squared Error.

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Authors: Chin S. Y., Radzi, S. N. R., Maharon, I. H., Shafawi, M. A.

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A kinetic model for propane dehydrogenation in an industrial moving bed reactor is developed based on the reported reaction scheme. The kinetic parameters and activity constant are fine tuned with several sets of balanced plant data. Plant data at different operating conditions is applied to validate the model and the results show a good agreement between the model predictions and plant observations in terms of the amount of main product, propylene produced. The simulation analysis of key variables such as inlet temperature of each reactor (Tinrx) and hydrogen to total hydrocarbon ratio (H2/THC) affecting process performance is performed to identify the operating condition to maximize the production of propylene. Within the range of operating conditions applied in the present studies, the operating condition to maximize the propylene production at the same weighted average inlet temperature (WAIT) is ΔTinrx1= -2, ΔTinrx2= +1, ΔTinrx3= +1 , ΔTinrx4= +2 and ΔH2/THC= -0.02. Under this condition, the surplus propylene produced is 7.07 tons/day as compared with base case.

Keywords: kinetic model, dehydrogenation, simulation, modeling, propane

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Authors: B. S. Fatoyinbo, D. Stretch, O. T. Amoo, D. Allopi

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This study extends the use of the Drainage Area Regionalization (DAR) method in generating synthetic data and calibrating PyTOPKAPI stream yield for an ungauged basin at a daily time scale. The generation of runoff in determining a river yield has been subjected to various topographic and spatial meteorological variables, which integers form the Catchment Characteristics Model (CCM). Many of the conventional CCM models adapted in Africa have been challenged with a paucity of adequate, relevance and accurate data to parameterize and validate the potential. The purpose of generating synthetic flow is to test a hydrological model, which will not suffer from the impact of very low flows or very high flows, thus allowing to check whether the model is structurally sound enough or not. The employed physically-based, watershed-scale hydrologic model (PyTOPKAPI) was parameterized with GIS-pre-processing parameters and remote sensing hydro-meteorological variables. The validation with mean annual runoff ratio proposes a decent graphical understanding between observed and the simulated discharge. The Nash-Sutcliffe efficiency and coefficient of determination (R²) values of 0.704 and 0.739 proves strong model efficiency. Given the current climate variability impact, water planner can now assert a tool for flow quantification and sustainable planning purposes.

Keywords: Ungauged Basin, Catchment Characteristics Model, Synthetic data, GIS.

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Authors: Surender Kumar Soni, Dhirendra Pratap Singh

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Wireless Sensor Networks can be used to monitor the physical phenomenon in such areas where human approach is nearly impossible. Hence the limited power supply is the major constraint of the WSNs due to the use of non-rechargeable batteries in sensor nodes. A lot of researches are going on to reduce the energy consumption of sensor nodes. Energy map can be used with clustering, data dissemination and routing techniques to reduce the power consumption of WSNs. Energy map can also be used to know which part of the network is going to fail in near future. In this paper, Energy map is constructed using the prediction based approach. Adaptive alpha GM(1,1) model is used as the prediction model. GM(1,1) is being used worldwide in many applications for predicting future values of time series using some past values due to its high computational efficiency and accuracy.

Keywords: Adaptive Alpha GM(1, 1) Model, Energy Map, Prediction Based Data Reduction, Wireless Sensor Networks

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Authors: M. Gomez, M. D. Murcia, E. Gomez, J. L. Gomez, N. Christofi

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Excilamps are new UV sources with great potential for application in wastewater treatment. In the present work, a XeBr excilamp emitting radiation at 283 nm has been used for the photodegradation of 4-chlorophenol within a range of concentrations from 50 to 500 mg L-1. Total removal of 4-chlorophenol was achieved for all concentrations assayed. The two main photoproduct intermediates formed along the photodegradation process, benzoquinone and hydroquinone, although not being completely removed, remain at very low residual concentrations. Such concentrations are insignificant compared to the 4-chlorophenol initial ones and non-toxic. In order to simulate the process and scaleup, a kinetic model has been developed and validated from the experimental data.

Keywords: 4-chlorophenol, excilamps, kinetic model, photodegradation.

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Authors: Novi Khila Firani, Elisa Nesdyaningtyas

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Kwashiorkor is one of nutritional problem in Indonesia, which lead to decrease immune system. This condition causes susceptibility to infectious disease, especially tuberculosis. Development of new tuberculosis vaccine will be an important strategy to eliminate tuberculosis in kwashiorkor. Previous research showed that 38-kDa Mycobacterium tuberculosis protein is one of the potent immunogen. However, the role of oral immunization with 38- kDa Mycobacterium tuberculosis protein to the number of lymphocytes in the rat model of kwashiorkor is still unknown. We used kwashiorkor rat model groups with 4% and 2% low protein diet. Oral immunization with 38-kDa Mycobacterium tuberculosis protein given with 2 booster every week. The lymphocytes number were measured by flowcytometry. There was no significant difference between the number of lymphocytes in the normal rat group and the kwashiorkor rat groups. It may reveal the role of 38-kDa Mycobacterium tuberculosis protein as a potent immunogen that can increase the lymphocytes number from kwashiorkor rat model same as normal rat.

Keywords: kwashiorkor rat, lymphocytes, 38-kDa Mycobacterium tuberculosis protein

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Authors: E. Pikushchak, J. Dueck, L. Minkov

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In hydrocyclones, the particle separation efficiency is limited by the suspended fine particles, which are discharged with the coarse product in the underflow. It is well known that injecting water in the conical part of the cyclone reduces the fine particle fraction in the underflow. This paper presents a mathematical model that simulates the water injection in the conical component. The model accounts for the fluid flow and the particle motion. Particle interaction, due to hindered settling caused by increased density and viscosity of the suspension, and fine particle entrainment by settling coarse particles are included in the model. Water injection in the conical part of the hydrocyclone is performed to reduce fine particle discharge in the underflow. The model demonstrates the impact of the injection rate, injection velocity, and injection location on the shape of the partition curve. The simulations are compared with experimental data of a 50-mm cyclone.

Keywords: Classification, fine particle processing, hydrocyclone, water injection.

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Authors: A. Shooshtari, A. R. Masoodi, S. Heyrani Moghaddam

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Free vibration analysis of a gabled frame with elastic support and semi-rigid connections is performed by using a program in OpenSees software. Natural frequencies and mode shape details of frame are obtained for two states, which are semi-rigid connections and elastic supports, separately. The members of this structure are analyzed as a prismatic nonlinear beam-column element in software. The mass of structure is considered as two equal lumped masses at the head of two columns in horizontal and vertical directions. Note that the degree of freedom, allocated to all nodes, is equal to three. Furthermore, the mode shapes of frame are achieved. Conclusively, the effects of connections and supports flexibility on the natural frequencies and mode shapes of structure are investigated.  

Keywords: Natural frequency, mode shape, gabled frame, semi-rigid connection, elastic support, OpenSees software.

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Authors: Chul Kwak, Oh-Wook Kwon

Abstract:

In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.

Keywords: Heart sound classification, extreme learning machine

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Authors: Giulio Mangano, Alberto De Marco, Giovanni Zenezini

Abstract:

The concept of City Logistics (CL) has emerged to improve the impacts of last mile freight distribution in urban areas. In this paper, a System Dynamics (SD) model exploring the dynamics of the diffusion of a ICT platform for CL management across different populations is proposed. For the development of the model two sources have been used. On the one hand, the major diffusion variables and feedback loops are derived from a literature review of existing diffusion models. On the other hand, the parameters are represented by the value propositions delivered by the platform as a response to some of the users’ needs. To extract the most important value propositions the Business Model Canvas approach has been used. Such approach in fact focuses on understanding how a company can create value for her target customers. These variables and parameters are thus translated into a SD diffusion model with three different populations namely municipalities, logistics service providers, and own account carriers. Results show that, the three populations under analysis fully adopt the platform within the simulation time frame, highlighting a strong demand by different stakeholders for CL projects aiming at carrying out more efficient urban logistics operations.

Keywords: City logistics, simulation, system dynamics, business model.

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Authors: Pei-Ti Hsu, I-Ju Chen, Jeu-Jung Chen, Cheng-Fen Chang, Shiu-Yan Yang

Abstract:

Background: Taiwan now is an aging society. Research on the elderly should not be confined to caring for seniors, but should also be focused on ways to improve health and the quality of life. Senior citizens who participate in volunteer services could become less lonely, have new growth opportunities, and regain a sense of accomplishment. Thus, the question of how to get the elderly to participate in volunteer service is worth exploring. Objective: Apply the Transtheoretical Model to understand stages of change in regular volunteer service and voluntary service behaviour among the seniors. Methods: 1525 adults over the age of 65 from the Renai district of Keelung City were interviewed. The research tool was a self-constructed questionnaire, and individual interviews were conducted to collect data. Then the data was processed and analyzed using the IBM SPSS Statistics 20 (Windows version) statistical software program. Results: In the past six months, research subjects averaged 9.92 days of volunteer services. A majority of these elderly individuals had no intention to change their regular volunteer services. We discovered that during the maintenance stage, the self-efficacy for volunteer services was higher than during all other stages, but self-perceived barriers were less during the preparation stage and action stage. Self-perceived benefits were found to have an important predictive power for those with regular volunteer service behaviors in the previous stage, and self-efficacy was found to have an important predictive power for those with regular volunteer service behaviors in later stages. Conclusions/Implications for Practice: The research results support the conclusion that community nursing staff should group elders based on their regular volunteer services change stages and design appropriate behavioral change strategies.

Keywords: Seniors, stages of change in regular volunteer services, volunteer service behavior, self-efficacy, self-perceived benefits.

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Authors: Dipti Patra, Mridula J

Abstract:

In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.

Keywords: Texture Image Segmentation, Gray Level Cooccurrence Matrix, Markov Random Field Model, Ohta colour space, ICM algorithm.

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