Search results for: rate based model.

Authors: Dariusz Dymek, Leszek Kotulski

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Modeling of the distributed systems allows us to represent the whole its functionality. The working system instance rarely fulfils the whole functionality represented by model; usually some parts of this functionality should be accessible periodically. The reporting system based on the Data Warehouse concept seams to be an intuitive example of the system that some of its functionality is required only from time to time. Analyzing an enterprise risk associated with the periodical change of the system functionality, we should consider not only the inaccessibility of the components (object) but also their functions (methods), and the impact of such a situation on the system functionality from the business point of view. In the paper we suggest that the risk attributes should be estimated from risk attributes specified at the requirements level (Use Case in the UML model) on the base of the information about the structure of the model (presented at other levels of the UML model). We argue that it is desirable to consider the influence of periodical changes in requirements on the enterprise risk estimation. Finally, the proposition of such a solution basing on the UML system model is presented.

Keywords: Risk assessing, software maintenance, UML, graph grammars.

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Authors: Ngono Mindzeng Terencia

Abstract:

Community based tourism, as a sustainable tourism approach, has been adopted as a tool for development among local communities in third world countries with income generation as the main driver. However, an analysis of community based tourism and development brings to light another driving force which is paramount to development strategies in the difficult conditions of third world countries: this driving force is “place revitalization”. This paper seeks to assess the relevance of “place revitalization” to the enhancement of development within the challenging context of developing countries. The research provides a community based tourism model to development in third world countries through a three step process based on awareness, mentoring and empowerment at the local level. It also tries to examine how effectively this model can address the development problems faced by the local communities of third world countries. The case study for this research is the Bamiléké region of Cameroon, the breeding ground of community based tourism initiatives and a region facing the difficulties of third world countries that are great impediments to community based tourism.

Keywords: Awareness, empowerment, local communities, mentoring, place revitalization, third world countries.

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Authors: Abdelghani Dendouga, Nour-Eddine Bouguechal, Souhil Kouda, Samir Barra

Abstract:

A behavioral model of a second order switchedcapacitor Sigma-Delta modulator is presented. The purpose of this work is the presentation of a behavioral model of a second order switched capacitor ΣΔ modulator considering (Error due to Clock Jitter, Thermal noise Amplifier Noise, Amplifier Slew-Rate, Non linearity of amplifiers, Gain error, Charge Injection, Clock Feedthrough, and Nonlinear on-resistance). A comparison between the use of MOS switches and the use transmission gate switches use is analyzed.

Keywords: Charge injection, clock feed through, Sigma Deltamodulators, Sigma Delta non-idealities, switched capacitor.

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Authors: Chanchai Supaartagorn

Abstract:

E-retailing is the sale of goods online that takes place over the Internet. The Internet has shrunk the entire World. World eretailing is growing at an exponential rate in the Americas, Europe and Asia. However, e-retailing costs require expensive investment, such as hardware, software, and security systems. Cloud computing technology is internet-based computing for the management and delivery of applications and services. Cloud-based e-retailing application models allow enterprises to lower their costs with their effective implementation of e-retailing activities. In this paper, we describe the concept of cloud computing and present the architecture of cloud computing, combining the features of e-retailing. In addition, we propose a strategy for implementing cloud computing with e-retailing. Finally, we explain the benefits from the architecture.

Keywords: Architecture, cloud computing, e-retailing, internet-based.

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Authors: Ali Reza Mehrabian, Caro Lucas

Abstract:

In this paper a new control strategy based on Brain Emotional Learning (BEL) model has been introduced. A modified BEL model has been proposed to increase the degree of freedom, controlling capability, reliability and robustness, which can be implemented in real engineering systems. The performance of the proposed BEL controller has been illustrated by applying it on different nonlinear uncertain systems, showing very good adaptability and robustness, while maintaining stability.

Keywords: Learning control systems, emotional decision making, nonlinear systems, adaptive control.

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Authors: Ines Hamdi, Mohamed Ben Ahmed

Abstract:

The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower

Keywords: Ontological model, spatio-temporal modeling, Genetic Regulatory Networks (GRNs), knowledge representation.

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Authors: Ismail Muratoglu, Ahmet Meyveci, Abdurrahman Tuncer, Erkan Demirci

Abstract:

This study is dedicated to the analysis of the problems of occupational safety in Turkey, Italy and Poland. The need analysis was applied to three different countries which are Turkey; 4, Poland; 1, Italy; 1 state. The number of the subjects is 891 in Turkey. The number of the subjects is 26 in Italy and the number of the subjects is 19 in Poland. The total number of samples of study is 936. Four different forms (Job Security Experts Form, Student Form, Teacher Form and Company Form) were applied. Results of experts of job security forms are rate of 7.1%. Then, the students’ forms are rate of 34.3%, teacher or instructor forms are rate of 9.9%. The last corporation forms are rate of 48.7%.

Keywords: Europe, need analysis, occupational safety, Turkey, vocational education.

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Authors: Husam Kaid, Abdulrahman Al-Ahmari, Zhiwu Li

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This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.

Keywords: Automated manufacturing system, colored Petri net, deadlock, siphon.

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Authors: Gopu Sreenivasulu, Bimlesh Kumar, Achanta Ramakrishna Rao

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To define or predict incipient motion in an alluvial channel, most of the investigators use a standard or modified form of Shields- diagram. Shields- diagram does give a process to determine the incipient motion parameters but an iterative one. To design properly (without iteration), one should have another equation for resistance. Absence of a universal resistance equation also magnifies the difficulties in defining the model. Neural network technique, which is particularly useful in modeling a complex processes, is presented as a tool complimentary to modeling incipient motion. Present work develops a neural network model employing the RBF network to predict the average velocity u and water depth y based on the experimental data on incipient condition. Based on the model, design curves have been presented for the field application.

Keywords: Incipient motion, Prediction error, Radial-Basisfunction, Sediment transport, Shields' diagram.

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Authors: Mohamed Abdallah, Mostafa Warith, Roberto Narbaitz, Emil Petriu, Kevin Kennedy

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Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.

Keywords: Adaptive neural fuzzy inference system (ANFIS), gas production, landfill

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

Abstract:

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: Adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm.

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Authors: Valeria M. Pequeno, Joao Carlos G. M. Pires

Abstract:

Data Warehouses (DWs) are repositories which contain the unified history of an enterprise for decision support. The data must be Extracted from information sources, Transformed and integrated to be Loaded (ETL) into the DW, using ETL tools. These tools focus on data movement, where the models are only used as a means to this aim. Under a conceptual viewpoint, the authors want to innovate the ETL process in two ways: 1) to make clear compatibility between models in a declarative fashion, using correspondence assertions and 2) to identify the instances of different sources that represent the same entity in the real-world. This paper presents the overview of the proposed framework to model the ETL process, which is based on the use of a reference model and perspective schemata. This approach provides the designer with a better understanding of the semantic associated with the ETL process.

Keywords: conceptual data model, correspondence assertions, data warehouse, data integration, ETL process, object relational database.

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Authors: Irtaza M. Syed, Kaamran Raahemifar

Abstract:

This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize the TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of a boost converter (BC), maximum power point tracking (MPPT) control, and a three-leg voltage source inverter (VSI). The operational model of VSI is used to synthesize the sinusoidal current and track the reference. The model is validated using a 35.7 kW PV system in Matlab/Simulink. Implementation results show simplicity and accuracy, as well as reliability of the model.

Keywords: Model predictive control, three phase voltage source inverter, PV system, Matlab/Simulink.

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Authors: Yi Chao Ma, Cheng Siong Chin, Wai Lok Woo

Abstract:

Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and threedimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who are the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system, which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: Hard disk drive noise, jury test, neural network model, psychoacoustic annoyance.

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Authors: Yanhui Zhang, Wenyu Yang

Abstract:

One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.

Keywords: Bayesian method, damage detection, fiber Bragg grating, structural health monitoring.

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Authors: Hamid Reza Nejati, Amin Nazerigivi, Ahmad Reza Sayadi

Abstract:

Failure mechanism of rocks is one of the fundamental aspects to study rock engineering stability. Rock is a material that contains flaws, initial damage, micro-cracks, etc. Failure of rock structure is largely due to tensile stress and was influenced by various parameters. In the present study, the effect of brittleness and loading rate on the physical and mechanical phenomena produced in rock during loading sequences is considered. For this purpose, Acoustic Emission (AE) technique is used to monitor fracturing process of three rock types (onyx marble, sandstone and soft limestone) with different brittleness and sandstone samples under different loading rate. The results of experimental tests revealed that brittleness and loading rate have a significant effect on the mode and number of induced fracture in rocks. An increase in rock brittleness increases the frequency of induced cracks, and the number of tensile fracture decreases when loading rate increases.

Keywords: Brittleness, loading rate, acoustic emission, tensile fracture, shear fracture.

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Authors: Noor S. Nasri, Eric C. A. Tatt, Usman D. Hamza, Jibril Mohammed, Husna M. Zain

Abstract:

Catalytic combustion of methane is imperative due to stability of methane at low temperature. Methane (CH4), therefore, remains unconverted in vehicle exhausts thereby causing greenhouse gas GHG emission problem. In this study, heterogeneous catalysts of palladium with bio-char (2 wt% Pd/Bc) and Al2O3 (2wt% Pd/ Al2O3) supports were prepared by incipient wetness impregnation and then subsequently tested for catalytic combustion of CH4. Support-porous heterogeneous catalytic combustion (HCC) material were selected based on factors such as surface area, porosity, thermal stability, thermal conductivity, reactivity with reactants or products, chemical stability, catalytic activity, and catalyst life. Sustainable and renewable support-material of bio-mass char derived from palm shell waste material was compared with those from the conventional support-porous materials. Kinetic rate of reaction was determined for combustion of methane on Palladium (Pd) based catalyst with Al2O3 support and bio-char (Bc). Material characterization was done using TGA, SEM, and BET surface area. The performance test was accomplished using tubular quartz reactor with gas mixture ratio of 3% methane and 97% air. The methane porous-HCC conversion was carried out using online gas analyzer connected to the reactor that performed porous-HCC. BET surface area for prepared 2 wt% Pd/Bc is smaller than prepared 2wt% Pd/ Al2O3 due to its low porosity between particles. The order of catalyst activity based on kinetic rate on reaction of catalysts in low temperature was 2wt% Pd/Bc>calcined 2wt% Pd/ Al2O3> 2wt% Pd/ Al2O3>calcined 2wt% Pd/Bc. Hence agro waste material can successfully be utilized as an inexpensive catalyst support material for enhanced CH4 catalytic combustion.

Keywords: Catalytic-combustion, Environmental, Support-bio-char material, Sustainable, Renewable material.

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Authors: Ondruska Marek, Matustik Ondrej

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The main goal of the article is to present new model of application architecture of banking IT solution providing the Internet Banking services that is particularly outsourced. At first, we propose business rationale and a SWOT analysis to explain the reasons for the model in the article. The most important factor for our model is nowadays- big boom around smart phones and tablet devices. As next, we focus on IT architecture viewpoint where we design application, integration and security model. Finally, we propose a generic governance model that serves as a basis for the specialized governance model. The specialized instance of governance model is designed to ensure that the development and the maintenance of different parts of the IT solution are well governed in time.

Keywords: governance model, front-end application, Internet Banking, smart phones

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Authors: Nikhil, Bestamin Özkaya, Ari Visa, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

Abstract:

The performance of a sucrose-based H2 production in a completely stirred tank reactor (CSTR) was modeled by neural network back-propagation (BP) algorithm. The H2 production was monitored over a period of 450 days at 35±1 ºC. The proposed model predicts H2 production rates based on hydraulic retention time (HRT), recycle ratio, sucrose concentration and degradation, biomass concentrations, pH, alkalinity, oxidation-reduction potential (ORP), acids and alcohols concentrations. Artificial neural networks (ANNs) have an ability to capture non-linear information very efficiently. In this study, a predictive controller was proposed for management and operation of large scale H2-fermenting systems. The relevant control strategies can be activated by this method. BP based ANNs modeling results was very successful and an excellent match was obtained between the measured and the predicted rates. The efficient H2 production and system control can be provided by predictive control method combined with the robust BP based ANN modeling tool.

Keywords: Back-propagation, biohydrogen, bioprocessmodeling, neural networks.

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Authors: Fayez M. Idris, Nehal I. AlZubaidi

Abstract:

Breast cancer detection techniques have been reported to aid radiologists in analyzing mammograms. We note that most techniques are performed on uncompressed digital mammograms. Mammogram images are huge in size necessitating the use of compression to reduce storage/transmission requirements. In this paper, we present an algorithm for the detection of microcalcifications in the JPEG2000 domain. The algorithm is based on the statistical properties of the wavelet transform that the JPEG2000 coder employs. Simulation results were carried out at different compression ratios. The sensitivity of this algorithm ranges from 92% with a false positive rate of 4.7 down to 66% with a false positive rate of 2.1 using lossless compression and lossy compression at a compression ratio of 100:1, respectively.

Keywords: Breast cancer, JPEG2000, mammography, microcalcifications.

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Authors: O. P. Rishi, Rekha Govil, Madhavi Sinha

Abstract:

Online learning with Intelligent Tutoring System (ITS) is becoming very popular where the system models the student-s learning behavior and presents to the student the learning material (content, questions-answers, assignments) accordingly. In today-s distributed computing environment, the tutoring system can take advantage of networking to utilize the model for a student for students from other similar groups. In the present paper we present a methodology where using Case Based Reasoning (CBR), ITS provides student modeling for online learning in a distributed environment with the help of agents. The paper describes the approach, the architecture, and the agent characteristics for such system. This concept can be deployed to develop ITS where the tutor can author and the students can learn locally whereas the ITS can model the students- learning globally in a distributed environment. The advantage of such an approach is that both the learning material (domain knowledge) and student model can be globally distributed thus enhancing the efficiency of ITS with reducing the bandwidth requirement and complexity of the system.

Keywords: CBR, ITS, student modeling, distributed system, intelligent agent.

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Authors: Farzad Khajavi, Farzaneh Jalilfar, Faranak Jafari, Leila Shokrani

Abstract:

Formulation of gliclazide in the form of extended-release tablet in 30 and 60 mg dosage forms was performed using hypromellose (HPMC K4M) as a retarding agent. Drug-release profiles were investigated in comparison with references Diamicron MR 30 and 60 mg tablets. The effect of size of powder particles, the amount of hypromellose in formulation, hardness of tablets, and also the effect of halving the tablets were investigated on drug release profile. A mathematical model which describes hypromellose behavior in initial times of drug release was proposed for the estimation of hypromellose content in modified-release gliclazide 60 mg tablet. This model is based on erosion of hypromellose in dissolution media. The model is applicable to describe release profiles of insoluble drugs. Therefore, by using dissolved amount of drug in initial times of dissolution and the model, the amount of hypromellose in formulation can be predictable. The model was used to predict the HPMC K4M content in modified-release gliclazide 30 mg and extended-release quetiapine 200 mg tablets.

Keywords: Hypromellose, gliclazide, drug release, modified-release tablet, mathematical model.

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Authors: Xu Tao, Yilun Xu, Dingwei Xiang, Yaofei Sun

Abstract:

The practice of urban planning and construction based on the concept of the “low carbon eco-city” has been universally accepted by the academic community in response to urban issues such as population, resources, environment, and social development. Based on this, the current article first analyzes the concepts of low carbon eco-city, then builds a complex adaptive system (CAS) theory based on Chinese traditional philosophical thinking, and analyzes the adaptive relationship between material and non-material elements. A three-dimensional evaluation model of natural ecology, economic low carbon, and social harmony was constructed. Finally, the construction of a low carbon eco-city index system in Hexi Newtown of Nanjing was used as an example to verify the effectiveness of the research results; this paradigm provides a new way to achieve a low carbon eco-city system.

Keywords: Complex adaptive system, low carbon ecology, index system, model.

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: Malaria, deep learning, DL, convolution neural network, CNN, thin blood smears.

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Authors: Chih-Wei Lin, Duen-Ren Liu, Hui-Fang Chen

Abstract:

Effective knowledge support relies on providing operation-relevant knowledge to workers promptly and accurately. A knowledge flow represents an individual-s or a group-s knowledge-needs and referencing behavior of codified knowledge during operation performance. The flow has been utilized to facilitate organizational knowledge support by illustrating workers- knowledge-needs systematically and precisely. However, conventional knowledge-flow models cannot work well in cooperative teams, which team members usually have diverse knowledge-needs in terms of roles. The reason is that those models only provide one single view to all participants and do not reflect individual knowledge-needs in flows. Hence, we propose a role-based knowledge-flow view model in this work. The model builds knowledge-flow views (or virtual knowledge flows) by creating appropriate virtual knowledge nodes and generalizing knowledge concepts to required concept levels. The customized views could represent individual role-s knowledge-needs in teamwork context. The novel model indicates knowledge-needs in condensed representation from a roles perspective and enhances the efficiency of cooperative knowledge support in organizations.

Keywords: cooperative knowledge support, knowledge flow, knowledge-flow view, role-based models

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Authors: A. Ito, S. Okamoto

Abstract:

We constructed an atomic structure model for a PAN-based carbon fiber containing amorphous structures using molecular dynamics methods. It was found that basic physical properties such as crystallinity, Young’s modulus, and thermal conductivity of our model were nearly identical to those of real carbon fibers. We then obtained the tensile strength of a carbon fiber, which has no macro defects. We finally determined that the limitation of the tensile strength was 19 GPa.

Keywords: Amorphous, carbon fiber, molecular dynamics, tensile strength.

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Authors: H. Achache, Y. Madani, A. Benzerdjeb

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The present study is based on the three-dimensional digital analysis by the finite elements method of the mechanical loading effect on the delamination of unidirectional and multidirectional stratified composites. The aim of this work is the determination of the release energy rate G in mode I and the Von Mises equivalent constraint distribution along the damaged area under the influence of several parameters such as the applied load and the delamination size. The results obtained in this study show that the unidirectional composite laminates have better mechanical resistance one the loading line than the multidirectional composite laminates.

Keywords: Delamination, release energy rate, stratified composite, finite element method and ply.

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Authors: Saeed AL-Rashdy, Qing Guo

Abstract:

The IEEE802.16 standard which has emerged as Broadband Wireless Access (BWA) technology, promises to deliver high data rate over large areas to a large number of subscribers in the near future. This paper analyze the effect of overheads over capacity of downlink (DL) of orthogonal frequency division multiple access (OFDMA)–based on the IEEE802.16e mobile WiMAX system with and without overheads. The analysis focuses in particular on the impact of Adaptive Modulation and Coding (AMC) as well as deriving an algorithm to determine the maximum numbers of subscribers that each specific WiMAX sector may support. An analytical study of the WiMAX propagation channel by using Cost- 231 Hata Model is presented. Numerical results and discussion estimated by using Matlab to simulate the algorithm for different multi-users parameters.

Keywords: BWA, mobile WiMAX, capacity, AMC , overheads.

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Authors: Héctor Rivera-Gómez, Eva Selene Hernández-Gress, Oscar Montaño-Arango, Jose Ramon Corona-Armenta

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This research studies the joint production, maintenance and subcontracting control policy for an unreliable deteriorating manufacturing system. Production activities are controlled by a derivation of the Hedging Point Policy, and given that the system is subject to deterioration, it reduces progressively its capacity to satisfy product demand. Multiple deterioration effects are considered, reflected mainly in the quality of the parts produced and the reliability of the machine. Subcontracting is available as support to satisfy product demand; also, overhaul maintenance can be conducted to reduce the effects of deterioration. The main objective of the research is to determine simultaneously the production, maintenance and subcontracting rate, which minimize the total, incurred cost. A stochastic dynamic programming model is developed and solved through a simulation-based approach composed of statistical analysis and optimization with the response surface methodology. The obtained results highlight the strong interactions between production, deterioration and quality, which justify the development of an integrated model. A numerical example and a sensitivity analysis are presented to validate our results.

Keywords: Deterioration, simulation, subcontracting, production planning.

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