Search results for: Document color modeling

Authors: Alessandro Bevilacqua, Alessandro Gherardi, Filippo Piccinini

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Image mosaicing techniques are usually employed to offer researchers a wider field of view of microscopic image of biological samples. a mosaic is commonly achieved using automated microscopes and often with one “color" channel, whether it refers to natural or fluorescent analysis. In this work we present a method to achieve three subsequent mosaics of the same part of a stem cell culture analyzed in phase contrast and in fluorescence, with a common non-automated inverted microscope. The mosaics obtained are then merged together to mark, in the original contrast phase images, nuclei and cytoplasm of the cells referring to a mosaic of the culture, rather than to single images. The experiments carried out prove the effectiveness of our approach with cultures of cells stained with calcein (green/cytoplasm and nuclei) and hoechst (blue/nuclei) probes.

Keywords: Microscopy, image mosaicing, fluorescence, stem cells.

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Authors: Harlida Abdul Wahab

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Discrimination in employment has its wider social and economic consequences other than mere violating a basic human right. Discrimination involves treating people differently because of certain grounds such as race, color, or sex, which results in the impairment of equality of opportunity and treatment. As an essential part of promoting decent work, combating discrimination through the principle of non-discrimination has been established by the International Labor Organization (ILO) through the Declaration on Fundamental Principles and Rights at Work 1998. Considering elimination of discrimination in employment as a core labor standard, member states are expected to respect, promote and implement it to their national laws and policies. Being a member state, Malaysia has to position herself align with this international requirement. The author discusses the related convention together with Malaysia-s responses on the matter. At the closing stage, the prospect of Malaysia is presumed taking into account of the current positions and reports submitted to the ILO.

Keywords: Discrimination, employment, international labor standard, Malaysia.

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Authors: Clement M. Matasane, Mohamed T. Kahn

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Biomass resources such as animal waste, agricultural and acro-industrial residues, forestry and woodland waste, and industrial and municipal solid wastes provide alternative means to utilize its untapped potential for biomass/biofuel renewable energy systems. In addition, crop residues (i.e., grain, starch, and energy crops) are commonly available in the district and play an essential role in community farming activities. The remote sensing technology (mappings) and geographic information systems tool will be used to determine the biomass potential in the Vhembe District Municipality. The detailed assessment, estimation, and modeling in quantifying their distribution, abundance, and quality yield an effective and efficient use of their potential. This paper aims to examine the potential and prospects of deploying bioenergy systems in small or micro-systems in the district for community use and applications. This deployment of the biofuels/biomass systems will help communities for sustainable energy supply from their traditional energy use into innovative and suitable methods that improve their livelihood. The study demonstrates the potential applications of Geographical Information Systems (GIS) in spatial mapping analysis, evaluation, modeling, and decision support for easy access to renewable energy systems.

Keywords: Agricultural crops, waste materials, biomass potentials, bioenergy potentials, GIS mappings, environmental data, renewable energy deployment, sustainable energy supply.

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Authors: A. Lauvray, F. Poulhaon, P. Michaud, P. Joyot, E. Duc

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Additive Friction Stir Manufacturing, or AFSM, is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. There is still a lack in understanding of the physical phenomena taking place during the process. This research aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system due to pure friction. An analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable, due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes through a numerical modeling followed by an experimental validation to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, frictional heat generation, process

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Authors: M. Taha, Hala H. Zayed, T. Nazmy, M. Khalifa

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Recently, traffic monitoring has attracted the attention of computer vision researchers. Many algorithms have been developed to detect and track moving vehicles. In fact, vehicle tracking in daytime and in nighttime cannot be approached with the same techniques, due to the extreme different illumination conditions. Consequently, traffic-monitoring systems are in need of having a component to differentiate between daytime and nighttime scenes. In this paper, a HSV-based day/night detector is proposed for traffic monitoring scenes. The detector employs the hue-histogram and the value-histogram on the top half of the image frame. Experimental results show that the extraction of the brightness features along with the color features within the top region of the image is effective for classifying traffic scenes. In addition, the detector achieves high precision and recall rates along with it is feasible for real time applications.

Keywords: Day/night detector, daytime/nighttime classification, image classification, vehicle tracking, traffic monitoring.

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Authors: Yazan M. Alatrash, Han-ok Kang, Hyun-gi Yoon, Shen Zhang, Juhyeon Yoon

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Flow coastdown phenomena are very important to secure nuclear fuel integrity during loss of off-site power accidents. In this study, primary coolant flow coastdown phenomena are investigated for the Jordan Research and Training Reactor (JRTR) using a simulation software package, Modular Modeling System (MMS). Two MMS models are built. The first one is a simple model to investigate the characteristics of the primary coolant pump only. The second one is a model for a simulation of the Primary Coolant System (PCS) loop, in which all the detailed design data of the JRTR PCS system are modeled, including the geometrical arrangement data. The same design data for a PCS pump are used for both models. Coastdown curves obtained from the two models are compared to study the PCS loop coolant inertia effect on a flow coastdown. Results showed that the loop coolant inertia effect is found to be small in the JRTR PCS loop, i.e., about one second increases in a coastdown half time required to halve the coolant flow rate. The effects of different flywheel inertia on the flow coastdown are also investigated. It is demonstrated that the coastdown half time increases with the flywheel inertia linearly. The designed coastdown half time is proved to be well above the design requirement for the fuel integrity.

Keywords: Flow Coastdown, Loop Coolant Inertia, Modeling, Research Reactor.

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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This paper presents a new meta-heuristic bio-inspired optimization algorithm which is called Cuttlefish Algorithm (CFA). The algorithm mimics the mechanism of color changing behavior of the cuttlefish to solve numerical global optimization problems. The colors and patterns of the cuttlefish are produced by reflected light from three different layers of cells. The proposed algorithm considers mainly two processes: reflection and visibility. Reflection process simulates light reflection mechanism used by these layers, while visibility process simulates visibility of matching patterns of the cuttlefish. To show the effectiveness of the algorithm, it is tested with some other popular bio-inspired optimization algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Bees Algorithm (BA) that have been previously proposed in the literature. Simulations and obtained results indicate that the proposed CFA is superior when compared with these algorithms.

Keywords: Cuttlefish Algorithm, bio-inspired algorithms, optimization.

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Authors: K. Vasupen, S. Wongsuthavas, S. Bureenok, B. Saenmahayak, K. Ampaporn, C. Yuangklang

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This study was designed to determine effect of supplemented tomato pomace and fobrolytic enzyme on egg production and egg quality. A total of 40 CP brown laying hens (95 week old) were used in completely randomized design in 2x2 factorial arrangement with or without enzyme supplementation. Four dietary treatments included: Control (C), Fibrolytic enzyme (FE), 10% Tomato pomace (TP), and Fibrolytic enzyme + 10 % Tomato pomace (FE+TP). Each of the four dietary treatments was fed up to 30 days (10 birds/treatment). Live performance, egg production, egg weight and quality were determined for whole period. Dietary treatments had no effect (P>0.05) on live performance, egg weight, yolk color, and egg production. Therefore, laying hens fed diets with fibrolytic enzyme were significantly (P<0.05) increased yolk weight (17.37 g) as compared to other treatments. Additional of dietary tomato pomace had reduced capital costs for egg production.

Keywords: Hen, Tomato Pomace, Fibrolytic Enzyme, Egg Quality.

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Authors: Jui-Liang Hsu

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The purpose of this study was to investigate the impact of the development of Szuchung Creek take for the cause of the critical success factors, This research is to use the depth interviews, document analysis and Modified-Delphi technique survey of nine depth interviews with experts and 14 experts of Modified-Delphi technique questionnaire and inviting as the research object, Szuchung Creek Hot Springs for the scope of the study. The results show, Szuchung Creek Hot Springs development take for career success factors for the following reasons: 1. Government. 2. Opportunities. 3. Factors of production. 4. Demand conditions. 5. Corporate structure and the degree of competition. 6. Related and supporting industries. Furthermore, Szuchung Creek hot springs, itself already has a number of critical success factors. Contingent less than or inadequacies by Szuchung Creek take for the enterprise development to take for the cause of the critical success factors as the basis for correcting, planning out for local use improvement strategies to achieve the objective of sustainable management.

Keywords: Hot spring industry, Critical Success Fators, Szuchung Creek, Take for the enterprise, Modified-Delphi technique, Hot Spring Areas.

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Authors: S. Kulsri, M. Jaroensutasinee, K. Jaroensutasinee

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We developed a new method based on quasimolecular modeling to simulate the cavity flow in three cavity shapes: rectangular, half-circular and bucket beer in cgs units. Each quasi-molecule was a group of particles that interacted in a fashion entirely analogous to classical Newtonian molecular interactions. When a cavity flow was simulated, the instantaneous velocity vector fields were obtained by using an inverse distance weighted interpolation method. In all three cavity shapes, fluid motion was rotated counter-clockwise. The velocity vector fields of the three cavity shapes showed a primary vortex located near the upstream corners at time t ~ 0.500 s, t ~ 0.450 s and t ~ 0.350 s, respectively. The configurational kinetic energy of the cavities increased as time increased until the kinetic energy reached a maximum at time t ~ 0.02 s and, then, the kinetic energy decreased as time increased. The rectangular cavity system showed the lowest kinetic energy, while the half-circular cavity system showed the highest kinetic energy. The kinetic energy of rectangular, beer bucket and half-circular cavities fluctuated about stable average values 35.62 x 103, 38.04 x 103 and 40.80 x 103 ergs/particle, respectively. This indicated that the half-circular shapes were the most suitable shape for a shrimp pond because the water in shrimp pond flows best when we compared with rectangular and beer bucket shape.

Keywords: Quasi-molecular modelling, particle modelling, lid driven cavity flow.

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Authors: Wai Phyo Aung

Abstract:

Wheeled Mobile Robots (WMRs) are built with their Wheels- drive machine, Motors. Depend on their desire design of WMR, Technicians made used of DC Motors for motion control. In this paper, the author would like to analyze how to choose DC motor to be balance with their applications of especially for WMR. Specification of DC Motor that can be used with desire WMR is to be determined by using MATLAB Simulink model. Therefore, this paper is mainly focus on software application of MATLAB and Control Technology. As the driving system of DC motor, a Peripheral Interface Controller (PIC) based control system is designed including the assembly software technology and H-bridge control circuit. This Driving system is used to drive two DC gear motors which are used to control the motion of WMR. In this analyzing process, the author mainly focus the drive system on driving two DC gear motors that will control with Differential Drive technique to the Wheeled Mobile Robot . For the design analysis of Motor Driving System, PIC16F84A is used and five inputs of sensors detected data are tested with five ON/OFF switches. The outputs of PIC are the commands to drive two DC gear motors, inputs of Hbridge circuit .In this paper, Control techniques of PIC microcontroller and H-bridge circuit, Mechanism assignments of WMR are combined and analyzed by mainly focusing with the “Modeling and Simulink of DC Motor using MATLAB".

Keywords: Control System Design, DC Motors, DifferentialDrive, H-bridge control circuit, MATLAB Simulink model, Peripheral Interface Controller (PIC), Wheeled Mobile Robots.

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: Adaptive sampling, batch bulk methyl methacrylate polymerization, large margin nearest neighbor regression, machine learning.

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Authors: Huihai Wu, Xiaohui Liu

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Using Dynamic Bayesian Networks (DBN) to model genetic regulatory networks from gene expression data is one of the major paradigms for inferring the interactions among genes. Averaging a collection of models for predicting network is desired, rather than relying on a single high scoring model. In this paper, two kinds of model searching approaches are compared, which are Greedy hill-climbing Search with Restarts (GSR) and Markov Chain Monte Carlo (MCMC) methods. The GSR is preferred in many papers, but there is no such comparison study about which one is better for DBN models. Different types of experiments have been carried out to try to give a benchmark test to these approaches. Our experimental results demonstrated that on average the MCMC methods outperform the GSR in accuracy of predicted network, and having the comparable performance in time efficiency. By proposing the different variations of MCMC and employing simulated annealing strategy, the MCMC methods become more efficient and stable. Apart from comparisons between these approaches, another objective of this study is to investigate the feasibility of using DBN modeling approaches for inferring gene networks from few snapshots of high dimensional gene profiles. Through synthetic data experiments as well as systematic data experiments, the experimental results revealed how the performances of these approaches can be influenced as the target gene network varies in the network size, data size, as well as system complexity.

Keywords: Genetic regulatory network, Dynamic Bayesian network, GSR, MCMC.

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Authors: Rossitza M. Setchi, Qiao Tang

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Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

Keywords: Concepts, indexing, machine learning, ontology, tagging.

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Authors: Xiuzhan Guo, Arthur Berrill, Ajinkya Kulkarni, Kostya Belezko, Min Luo

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Ontology operations, e.g., aligning and merging, were studied and implemented extensively in different settings, such as, categorical operations, relation algebras, typed graph grammars, with different concerns. However, aligning and merging operations in the settings share some generic properties, e.g., idempotence, commutativity, associativity, and representativity, which are defined on an ontology merging system, given by a nonempty set of the ontologies concerned, a binary relation on the set of the ontologies modeling ontology aligning, and a partial binary operation on the set of the ontologies modeling ontology merging. Given an ontology repository, a finite subset of the set of the ontologies, its merging closure is the smallest subset of the set of the ontologies, which contains the repository and is closed with respect to merging. If idempotence, commutativity, associativity, and representativity properties are satisfied, then both the set of the ontologies and the merging closure of the ontology repository are partially ordered naturally by merging, the merging closure of the ontology repository is finite and can be computed, compared, and sorted efficiently, including sorting, selecting, and querying some specific elements, e.g., maximal ontologies and minimal ontologies. An ontology Valignment pair is a pair of ontology homomorphisms with a common domain. We also show that the ontology merging system, given by ontology V-alignment pairs and pushouts, satisfies idempotence, commutativity, associativity, and representativity properties so that the merging system is partially ordered and the merging closure of a given repository with respect to pushouts can be computed efficiently.

Keywords: Ontology aligning, ontology merging, merging system, poset, merging closure, ontology V-alignment pair, ontology homomorphism, ontology V-alignment pair homomorphism, pushout.

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Authors: Abdulbasit G. A. Abdulsayid

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The main focus of the work was concerned with hydrodynamic and thermal analysis of the plate heat exchanger channel with corrugation patterns suggested to be triangular, sinusoidal, and square corrugation. This study was to numerically model and validate the triangular corrugated channel with dimensions/parameters taken from open literature, and then model/analyze both sinusoidal, and square corrugated channel referred to the triangular model. Initially, 2D modeling with local extensive analysis for triangular corrugated channel was carried out. By that, all local pressure drop, wall shear stress, friction factor, static temperature, heat flux, Nusselt number, and surface heat coefficient, were analyzed to interpret the hydrodynamic and thermal phenomena occurred in the flow. Furthermore, in order to facilitate confidence in this model, a comparison between the values predicted, and experimental results taken from literature for almost the same case, was done. Moreover, a holistic numerical study for sinusoidal and square channels together with global comparisons with triangular corrugation under the same condition, were handled. Later, a comparison between electric, and fluid cooling through varying the boundary condition was achieved. The constant wall temperature and constant wall heat flux boundary conditions were employed, and the different resulted Nusselt numbers as a consequence were justified. The results obtained can be used to come up with an optimal design, a 'compromise' between heat transfer and pressure drop.

Keywords: Corrugated Channel, CFD, Heat Exchanger, Heat Enhancement.

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Authors: Yuan L. Lai, Yong R. Chen, Jui P. Hung, Tzuo L. Luo, Hsi H. Hsiao

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Chatter vibration has been a troublesome problem for a machine tool toward the high precision and high speed machining. Essentially, the machining performance is determined by the dynamic characteristics of the machine tool structure and dynamics of cutting process. Therefore the dynamic vibration behavior of spindle tool system greatly determines the performance of machine tool. The purpose of this study is to investigate the influences of the machine frame structure on the dynamic frequency of spindle tool unit through finite element modeling approach. To this end, a realistic finite element model of the vertical milling system was created by incorporated the spindle-bearing model into the spindle head stock of the machine frame. Using this model, the dynamic characteristics of the milling machines with different structural designs of spindle head stock and identical spindle tool unit were demonstrated. The results of the finite element modeling reveal that the spindle tool unit behaves more compliant when the excited frequency approaches the natural mode of the spindle tool; while the spindle tool show a higher dynamic stiffness at lower frequency that may be initiated by the structural mode of milling head. Under this condition, it is concluded that the structural configuration of spindle head stock associated with the vertical column of milling machine plays an important role in determining the machining dynamics of the spindle unit.

Keywords: Machine tools, Compliance, Frequency response function, Machine frame structure, Spindle unit

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Authors: Su-Yan Tang, Wei Zhang, Shan Mei, Yi-Fan Zhu

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Network-Centric Air Defense Missile Systems (NCADMS) represents the superior development of the air defense missile systems and has been regarded as one of the major research issues in military domain at present. Due to lack of knowledge and experience on NCADMS, modeling and simulation becomes an effective approach to perform operational analysis, compared with those equation based ones. However, the complex dynamic interactions among entities and flexible architectures of NCADMS put forward new requirements and challenges to the simulation framework and models. ABS (Agent-Based Simulations) explicitly addresses modeling behaviors of heterogeneous individuals. Agents have capability to sense and understand things, make decisions, and act on the environment. They can also cooperate with others dynamically to perform the tasks assigned to them. ABS proves an effective approach to explore the new operational characteristics emerging in NCADMS. In this paper, based on the analysis of network-centric architecture and new cooperative engagement strategies for NCADMS, an agent-based simulation framework by expanding the simulation framework in the so-called System Effectiveness Analysis Simulation (SEAS) was designed. The simulation framework specifies components, relationships and interactions between them, the structure and behavior rules of an agent in NCADMS. Based on scenario simulations, information and decision superiority and operational advantages in NCADMS were analyzed; meanwhile some suggestions were provided for its future development.

Keywords: air defense missile systems, network-centric, agent-based simulation, simulation framework, information superiority, decision superiority, operational advantages

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Authors: Jeffrey A. Dunne, Kevin Ligozio

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In many applications there is a broad variety of information relevant to a focal “object" of interest, and the fusion of such heterogeneous data types is desirable for classification and categorization. While these various data types can sometimes be treated as orthogonal (such as the hull number, superstructure color, and speed of an oil tanker), there are instances where the inference and the correlation between quantities can provide improved fusion capabilities (such as the height, weight, and gender of a person). A service-oriented architecture has been designed and prototyped to support the fusion of information for such “object-centric" situations. It is modular, scalable, and flexible, and designed to support new data sources, fusion algorithms, and computational resources without affecting existing services. The architecture is designed to simplify the incorporation of legacy systems, support exact and probabilistic entity disambiguation, recognize and utilize multiple types of uncertainties, and minimize network bandwidth requirements.

Keywords: Data fusion, distributed computing, service-oriented architecture, SOA

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

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The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications.

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Authors: Konstantinos B. Petrotos, Fani K. Karkanta, Paschalis E. Gkoutsidis, Ioannis Giavasis, Konstantinos N. Papatheodorou, Alexandros C. Ntontos

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In the course of the present work, plain (nonencapsulated) and microencapsulated polyphenols were produced using olive mill wastewater (OMW) as raw material, in order to be used for enrichment of yogurt and dairy products. The OMW was first clarified by using membrane technology and subsequently the contained poly-phenols were isolated by adsorption-desorption technique using selective macro-porous resins and finally recovered in dry form after been processed by RO membrane technique followed by freeze drying. Moreover, the polyphenols were encapsulated in modified starch by freeze drying in order to mask the color and bitterness effect and improve their functionality. The two products were used successfully as additives in yogurt preparations and the produced products were acceptable by the consumers and presented with certain advantage to the plain yogurt. For the herein proposed production scheme a patent application was already submitted.

Keywords: OMW, polyphenol-enriched yogurt, encapsulation, bio-active dairy products

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Authors: Amitabh Wahi, Sundaramurthy S.

Abstract:

Natural outdoor scene classification is active and promising research area around the globe. In this study, the classification is carried out in two phases. In the first phase, the features are extracted from the images by wavelet decomposition method and stored in a database as feature vectors. In the second phase, the neural classifiers such as back-propagation neural network (BPNN) and resilient back-propagation neural network (RPNN) are employed for the classification of scenes. Four hundred color images are considered from MIT database of two classes as forest and street. A comparative study has been carried out on the performance of the two neural classifiers BPNN and RPNN on the increasing number of test samples. RPNN showed better classification results compared to BPNN on the large test samples.

Keywords: BPNN, Classification, Feature extraction, RPNN, Wavelet.

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Authors: J. P. Panda, K. Sasmal, H. V. Warrior

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Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD.

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Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: Basketball, deep learning, feature extraction, single-camera, tracking.

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Authors: B. Vadiraj, S. N. Omkar, B. Kapil Bharadwaj, Yash Vardhan Gupta

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During manned exploration of space, missions will require astronaut crewmembers to perform Extra Vehicular Activities (EVAs) for a variety of tasks. These EVAs take place after long periods of operations in space, and in and around unique vehicles, space structures and systems. Considering the remoteness and time spans in which these vehicles will operate, EVA system operations should utilize common worksites, tools and procedures as much as possible to increase the efficiency of training and proficiency in operations. All of the preparations need to be carried out based on studies of astronaut motions. Until now, development and training activities associated with the planned EVAs in Russian and U.S. space programs have relied almost exclusively on physical simulators. These experimental tests are expensive and time consuming. During the past few years a strong increase has been observed in the use of computer simulations due to the fast developments in computer hardware and simulation software. Based on this idea, an effort to develop a computational simulation system to model human dynamic motion for EVA is initiated. This study focuses on the simulation of an astronaut moving the orbital replaceable units into the worksites or removing them from the worksites. Our physics-based methodology helps fill the gap in quantitative analysis of astronaut EVA by providing a multisegment human arm model. Simulation work described in the study improves on the realism of previous efforts, incorporating joint stops to account for the physiological limits of range of motion. To demonstrate the utility of this approach human arm model is simulated virtually using ADAMS/LifeMOD^® software. Kinematic mechanism for the astronaut’s task is studied from joint angles and torques. Simulation results obtained is validated with numerical simulation based on the principles of Newton-Euler method. Torques determined using mathematical model are compared among the subjects to know the grace and consistency of the task performed. We conclude that due to uncertain nature of exploration-class EVA, a virtual model developed using multibody dynamics approach offers significant advantages over traditional human modeling approaches.

Keywords: Extra vehicular activity, biomechanics, inverse kinematics, human body modeling.

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Authors: Astiaj Khoramshahi, Hossein Ahmadi Danesh Ashtiani, Ahmad Khoshgard, Hamidreza Damghani, Leila Damghani

Abstract:

Solar energy systems using various storages are required to be evaluated based on energy requirements and applications. Also, modeling and analysis of storage systems are necessary to increase the effectiveness of combinations of these systems. In this paper, analysis based on the MATLAB software has been analyzed to evaluate the response of the hybrid energy system considering various technologies of renewable energy and energy storage. In the present study, three different simulation scenarios are presented. Simulation output results using software for the first scenario show that the battery is effective in smoothing the overall power demand to the consumer studied during a day, but temporary loads on the grid with high frequencies, effectively cannot be canceled due to the limited response speed of battery control. Simulation outputs for the second scenario using the energy storage system show that sudden changes in demand power are paved by super saving. The majority of these sudden changes in power demand are caused by sewing consumers and receiving variable solar power (due to clouds passing through the solar array). Simulation outputs for the third scenario show the effects of the hybrid system for the same consumer and the output of the solar array, leading to the smallest amount of power demand fed into the grid, as well as demand at peak times. According to the "battery only" scenario, the displacement technique of the peak load has been significantly reduced.

Keywords: Storage system, super storage, standalone, microgrid.

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Authors: S. Malathi, P. Seenuvasakumaran

Abstract:

Nanomaterials ferrites have applications in making permanent magnets, high density information devices, color imaging etc. In the present examination, lithium ferrite is synthesized by sol-gel process. The x-ray diffraction (XRD) result shows that the structure of lithium ferrite is monoclinic structure. The average particle size 22 nm is calculated by Scherer formula. The lattice parameters and dislocation density (δ) are calculated from XRD data. Strain (ε) values are evaluated from Williamson – hall plot. The FT-IR study reveals the formation of ferrites showing the significant absorption bands. The VU-VIS spectroscopic data is used to calculate direct and indirect optical band gap (Eg) of 1.57eV and 1.01eV respectively for lithium ferrite by using Tauc plot at the edge of the absorption band. The energy dispersive x-ray analysis spectra showed that the expected elements exist in the material. The magnetic behaviour of the materials studied using vibrating sample magnetometer (VSM).

Keywords: Sol-gel, dislocation density, energy band gap, VSM.

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Authors: Abimbola M. Enitan, Josiah Adeyemo

Abstract:

Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (μmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (d¯¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: Brewery wastewater, methane generation model, environment, anaerobic modeling.

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Authors: Ying Shen, Weihua Zhu

Abstract:

Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: Magnetic Resonance Image, C-means model, image segmentation, information entropy.

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Authors: Paola Lecca

Abstract:

Modeling and simulation of biochemical reactions is of great interest in the context of system biology. The central dogma of this re-emerging area states that it is system dynamics and organizing principles of complex biological phenomena that give rise to functioning and function of cells. Cell functions, such as growth, division, differentiation and apoptosis are temporal processes, that can be understood if they are treated as dynamic systems. System biology focuses on an understanding of functional activity from a system-wide perspective and, consequently, it is defined by two hey questions: (i) how do the components within a cell interact, so as to bring about its structure and functioning? (ii) How do cells interact, so as to develop and maintain higher levels of organization and functions? In recent years, wet-lab biologists embraced mathematical modeling and simulation as two essential means toward answering the above questions. The credo of dynamics system theory is that the behavior of a biological system is given by the temporal evolution of its state. Our understanding of the time behavior of a biological system can be measured by the extent to which a simulation mimics the real behavior of that system. Deviations of a simulation indicate either limitations or errors in our knowledge. The aim of this paper is to summarize and review the main conceptual frameworks in which models of biochemical networks can be developed. In particular, we review the stochastic molecular modelling approaches, by reporting the principal conceptualizations suggested by A. A. Markov, P. Langevin, A. Fokker, M. Planck, D. T. Gillespie, N. G. van Kampfen, and recently by D. Wilkinson, O. Wolkenhauer, P. S. Jöberg and by the author.

Keywords: Mathematical structure, algorithmic implementation, biochemical network models.

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