Search results for: thermal network model.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10283

Search results for: thermal network model.

8963 Producing New Composite Materials by Using Tragacanth and Waste Ash

Authors: Yasar Bicer, Serif Yilmaz

Abstract:

In present study, two kinds of thermal power plant ashes; one the fly ash and the other waste ash are mixed with adhesive tragacanth and cement to produce new composite materials. 48 new samples are produced by varying the percentages of the fly ash, waste ash, cement and tragacanth. The new samples are subjected to some tests to find out their properties such as thermal conductivity, compressive strength, tensile strength and sucking capability of water. It is found that; the thermal conductivity decreases with increasing amount of tragacanth in the mixture. The compressive, tensile strength increases when the rate of tragacanth is up to 1%, whilst as the amount of tragacanth increases up to 1.5%, the compressive, tensile strength decreases slightly. The rate of water absorption of samples was more than 30%. From this result, it is concluded that these materials can not be used as external plaster or internal plaster material that faces to water. They can be used in internal plaster unless touching water and they can be used as cover plaster under roof and riprap material in sandwich panels. It is also found that, these materials can be cut with saw, drilled with screw and painted with any kind of paint.

Keywords: Fly ash, tragacanth, cement, composite material.

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8962 The Influence of Physical-Mechanical and Thermal Properties of Hemp Filling Materials by the Addition of Energy Byproducts

Authors: Sarka Keprdova, Jiri Bydzovsky

Abstract:

This article describes to what extent the addition of energy by-products into the structures of the technical hemp filling materials influence their properties. The article focuses on the changes in physical-mechanical and thermal technical properties of materials after the addition of ash or FBC ash or slag in the binding component of material. Technical hemp filling materials are made of technical hemp shives bonded by the mixture of cement and dry hydrate lime. They are applicable as fillers of vertical or horizontal structures or roofs. The research used eight types of energy by-products of power or heating plants in the Czech Republic. Secondary energy products were dispensed in three different percentage ratios as a replacement of cement in the binding component. Density, compressive strength and determination of the coefficient of thermal conductivity after 28, 60 and 90 days of curing in a laboratory environment were determined and subsequently evaluated on the specimens produced.

Keywords: Ash, binder, cement, energy by-product, FBC ash (fluidized bed combustion ash), filling materials, shives, slag, technical hemp.

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8961 Application of Neural Network for Contingency Ranking Based on Combination of Severity Indices

Authors: S. Jadid, S. Jalilzadeh

Abstract:

In this paper, an improved technique for contingency ranking using artificial neural network (ANN) is presented. The proposed approach is based on multi-layer perceptrons trained by backpropagation to contingency analysis. Severity indices in dynamic stability assessment are presented. These indices are based on the concept of coherency and three dot products of the system variables. It is well known that some indices work better than others for a particular power system. This paper along with test results using several different systems, demonstrates that combination of indices with ANN provides better ranking than a single index. The presented results are obtained through the use of power system simulation (PSS/E) and MATLAB 6.5 software.

Keywords: composite indices, transient stability, neural network.

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8960 Location Management in Cellular Networks

Authors: Bhavneet Sidhu, Hardeep Singh

Abstract:

Cellular networks provide voice and data services to the users with mobility. To deliver services to the mobile users, the cellular network is capable of tracking the locations of the users, and allowing user movement during the conversations. These capabilities are achieved by the location management. Location management in mobile communication systems is concerned with those network functions necessary to allow the users to be reached wherever they are in the network coverage area. In a cellular network, a service coverage area is divided into smaller areas of hexagonal shape, referred to as cells. The cellular concept was introduced to reuse the radio frequency. Continued expansion of cellular networks, coupled with an increasingly restricted mobile spectrum, has established the reduction of communication overhead as a highly important issue. Much of this traffic is used in determining the precise location of individual users when relaying calls, with the field of location management aiming to reduce this overhead through prediction of user location. This paper describes and compares various location management schemes in the cellular networks.

Keywords: Cellular Networks, Location Area, MobilityManagement, Paging.

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8959 Impact Assessment of Air Pollution Stress on Plant Species through Biochemical Estimations

Authors: Govindaraju.M, Ganeshkumar.R.S, Suganthi.P, Muthukumaran.V.R, Visvanathan.P

Abstract:

The present study was conducted to investigate the response of plants exposed to lignite-based thermal power plant emission. For this purpose, five plant species were collected from 1.0 km distance (polluted site) and control plants were collected from 20.0 km distance (control site) to thermal power plant. The common tree species Cassia siamea Lamk., Polyalthia longifolia. Sonn, Acacia longifolia (Andrews) Wild., Azadirachta indica A.Juss, Ficus religiosa L. were selected as test plants. Photosynthetic pigments changes (chlorophyll a, chlorophyll b and carotenoids) and rubisco enzyme modifications were studied. Reduction was observed in the photosynthetic pigments of plants growing in polluted site and also large sub unit of the rubisco enzyme was degraded in Azadirachta indica A. Juss collected from polluted site.

Keywords: Air pollution, Lignite-based thermal power plant, Photosynthetic pigments, Rubisco enzyme.

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8958 A Neural-Network-Based Fault Diagnosis Approach for Analog Circuits by Using Wavelet Transformation and Fractal Dimension as a Preprocessor

Authors: Wenji Zhu, Yigang He

Abstract:

This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with [1] and [6], which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.

Keywords: Analog circuits, fault diagnosis, tolerance, wavelettransform, fractal dimension, box dimension.

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8957 TBC for Protection of Al Alloy Aerospace Component

Authors: P. Niranatlumpong, H. Koiprasert, C. Sukhonket, K. Ninon, N. Coompreedee

Abstract:

The use of a conventional air plasma-sprayed thermal barrier coating (TBC) and a porous, functionally graded TBC as a thermal insulator for Al7075 alloy was explored. A quench test at 1200°C employing fast heating and cooling rates was setup to represent a dynamic thermal condition of an aerospace component. During the test, coated samples were subjected the ambient temperature of 1200°C for a very short time. This was followed by a rapid drop in temperature resulting in cracking of the coatings. For the conventional TBC, it was found that the temperature of the Al7075 substrate decreases with the increase in the ZrO2 topcoat thickness. However, at the topcoat thickness of 1100 µm, large horizontal cracks can be observed in the topcoat and at the topcoat thickness of 1600 µm, the topcoat delaminate during cooling after the quench test. The porous, functionally graded TBC with 600 µm thick topcoat, on the other hand, was found to be as effective at reducing the substrate temperature as the conventional TBC with 1100 µm thick topcoat. The maximum substrate temperature is about 213°C for the former and 208°C for the latter when a heating rate of 38°C/s was used. When the quench tests were conducted with a faster heating rate of 128°C/s, the Al7075 substrate heat up faster with a reduction in the maximum substrate temperatures. The substrate temperatures dropped from 297 to 212°C for the conventional TBC and from 213 to 155°C for the porous TBC, both with 600 µm thick topcoat. Segmentation cracks were observed in both coating after the quench test.

Keywords: Thermal barrier coating, Al7075, porous TBC, Quenching.

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8956 Effects of Superheating on Thermodynamic Performance of Organic Rankine Cycles

Authors: Kyoung Hoon Kim

Abstract:

Recently ORC(Organic Rankine Cycle) has attracted much attention due to its potential in reducing consumption of fossil fuels and its favorable characteristics to exploit low-grade heat sources. In this work thermodynamic performance of ORC with superheating of vapor is comparatively assessed for various working fluids. Special attention is paid to the effects of system parameters such as the evaporating temperature and the turbine inlet temperature on the characteristics of the system such as maximum possible work extraction from the given source, volumetric flow rate per 1 kW of net work and quality of the working fluid at turbine exit as well as thermal and exergy efficiencies. Results show that for a given source the thermal efficiency increases with decrease of the superheating but exergy efficiency may have a maximum value with respect to the superheating of the working fluid. Results also show that in selection of working fluid it is required to consider various criteria of performance characteristics as well as thermal efficiency.

Keywords: organic Rankine cycle (ORC), low-grade energysource, Patel-Teja equation, thermodynamic performance

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8955 Fracture Control of the Soda-Lime Glass in Laser Thermal Cleavage

Authors: Jehnming Lin

Abstract:

The effects of the contact ball-lens on the soda lime glass in laser thermal cleavage with a cw Nd-YAG laser were investigated in this study. A contact ball-lens was adopted to generate a bending force on the crack formation of the soda-lime glass in the laser cutting process. The Nd-YAG laser beam (wavelength of 1064 nm) was focused through the ball-lens and transmitted to the soda-lime glass, which was coated with a carbon film on the surface with a bending force from a ball-lens to generate a tensile stress state on the surface cracking. The fracture was controlled by the contact ball-lens and a straight cutting was tested to demonstrate the feasibility. Experimental observations on the crack propagation from the leading edge, main section and trailing edge of the glass sheet were compared with various mechanical and thermal loadings. Further analyses on the stress under various laser powers and contact ball loadings were made to characterize the innovative technology. The results show that the distributions of the side crack at the leading and trailing edges are mainly dependent on the boundary condition, contact force, cutting speed and laser power. With the increase of the mechanical and thermal loadings, the region of the side cracks might be dramatically reduced with proper selection of the geometrical constrains. Therefore the application of the contact ball-lens is a possible way to control the fracture in laser cleavage with improved cutting qualities.

Keywords: Laser cleavage, controlled fracture, contact ball lens.

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8954 IEEE 802.11 b and g WLAN Propagation Model using Power Density Measurements at ESPOL

Authors: E. E. Mantilla, C. R. Reyes, B. G. Ramos

Abstract:

This paper describes the development of a WLAN propagation model, using Spectral Analyzer measurements. The signal is generated by two Access Points (APs) on the base floor at the administrative Communication School of ESPOL building. In general, users do not have a Q&S reference about a wireless network; however, this depends on the level signal as a function of frequency, distance and other path conditions between receiver and transmitter. Then, power density of the signal decrease as it propagates through space and data transfer rate is affected. This document evaluates and implements empirical mathematical formulation for the characterization of WLAN radio wave propagation on two aisles of the building base floor.

Keywords: frequency, Spectral Analyzer, transmitter, WLAN.

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8953 Automatic Classification of Lung Diseases from CT Images

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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8952 Multilayer Neural Network and Fuzzy Logic Based Software Quality Prediction

Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz

Abstract:

In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.

Keywords: Software quality, fuzzy logic, perceptron, prediction.

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8951 Dynamic Admission Control Based on Effective Demand for Next Generation Wireless Networks

Authors: Somenath Mukherjee, Rajdeep Ray, Raj Kumar Samanta, Mofazzal H. Khondekar, Gautam Sanyal

Abstract:

In next generation wireless networks (i.e., 4G and beyond), one of the main objectives is to ensure highest level of customer satisfaction in terms of data transfer speed, decrease in cost and delay, non-rejection and no drop of calls, availability of ‘always-on’ connectivity and services, continuity of connected services, hastle-free roaming in addition to the convenience of use of network services from anywhere and anytime. To take care of these requirements effectively, internet service providers (ISPs) and network planners have to go for major capacity enhancement of network resources and at the same time these resources are to be used effectively and efficiently to reduce cost and to increase revenue. In this work, the effective bandwidth available in a Mobile Switching Center (MSC) of a wireless network providing multi-class multimedia services is analyzed. Bandwidth requirement of the users for a customized Quality of Service (QoS) is estimated. The findings of the QoS estimation are applied for the capacity planning and admission control of the multi-class traffic flows coming into the MSC.

Keywords: Next generation wireless network, mobile switching center, multi-class traffic, quality of service, admission control, effective bandwidth.

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8950 Fuzzy Hyperbolization Image Enhancement and Artificial Neural Network for Anomaly Detection

Authors: Sri Hartati, 1Agus Harjoko, Brad G. Nickerson

Abstract:

A prototype of an anomaly detection system was developed to automate process of recognizing an anomaly of roentgen image by utilizing fuzzy histogram hyperbolization image enhancement and back propagation artificial neural network. The system consists of image acquisition, pre-processor, feature extractor, response selector and output. Fuzzy Histogram Hyperbolization is chosen to improve the quality of the roentgen image. The fuzzy histogram hyperbolization steps consist of fuzzyfication, modification of values of membership functions and defuzzyfication. Image features are extracted after the the quality of the image is improved. The extracted image features are input to the artificial neural network for detecting anomaly. The number of nodes in the proposed ANN layers was made small. Experimental results indicate that the fuzzy histogram hyperbolization method can be used to improve the quality of the image. The system is capable to detect the anomaly in the roentgen image.

Keywords: Image processing, artificial neural network, anomaly detection.

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8949 Rheological and Thermomechanical Properties of Graphene/ABS/PP Nanocomposites

Authors: Marianna I. Triantou, Konstantina I. Stathi, Petroula A. Tarantili

Abstract:

In the present study, the incorporation of graphene into blends of acrylonitrile-butadiene-styrene terpolymer with polypropylene (ABS/PP) was investigated focusing on the improvement of their thermomechanical characteristics and the effect on their rheological behavior. The blends were prepared by melt mixing in a twin-screw extruder and were characterized by measuring the MFI as well as by performing DSC, TGA and mechanical tests. The addition of graphene to ABS/PP blends tends to increase their melt viscosity, due to the confinement of polymer chains motion. Also, graphene causes an increment of the crystallization temperature (Tc), especially in blends with higher PP content, because of the reduction of surface energy of PP nucleation, which is a consequence of the attachment of PP chains to the surface of graphene through the intermolecular CH-π interaction. Moreover, the above nanofiller improves the thermal stability of PP and increases the residue of thermal degradation at all the investigated compositions of blends, due to the thermal isolation effect and the mass transport barrier effect. Regarding the mechanical properties, the addition of graphene improves the elastic modulus, because of its intrinsic mechanical characteristics and its rigidity, and this effect is particularly strong in the case of pure PP.

Keywords: Acrylonitrile-butadiene-styrene terpolymer, blends, graphene, polypropylene.

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8948 Two Day Ahead Short Term Load Forecasting Neural Network Based

Authors: Firas M. Tuaimah

Abstract:

This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity.

The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: Short-Term Load Forecasting, Artificial Neural Networks, Back propagation learning.

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8947 Generating Normally Distributed Clusters by Means of a Self-organizing Growing Neural Network– An Application to Market Segmentation –

Authors: Reinhold Decker, Christian Holsing, Sascha Lerke

Abstract:

This paper presents a new growing neural network for cluster analysis and market segmentation, which optimizes the size and structure of clusters by iteratively checking them for multivariate normality. We combine the recently published SGNN approach [8] with the basic principle underlying the Gaussian-means algorithm [13] and the Mardia test for multivariate normality [18, 19]. The new approach distinguishes from existing ones by its holistic design and its great autonomy regarding the clustering process as a whole. Its performance is demonstrated by means of synthetic 2D data and by real lifestyle survey data usable for market segmentation.

Keywords: Artificial neural network, clustering, multivariatenormality, market segmentation, self-organization

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8946 Hubs as Catalysts for Geospatial Communication in Kinship Networks

Authors: Sameer Kumar, Jariah Mohd. Jan

Abstract:

Earlier studies in kinship networks have primarily focused on observing the social relationships existing between family relatives. In this study, we pre-identified hubs in the network to investigate if they could play a catalyst role in the transfer of physical information. We conducted a case study of a ceremony performed in one of the families of a small Hindu community – the Uttar Rarhi Kayasthas. Individuals (n = 168) who resided in 11 geographically dispersed regions were contacted through our hub-based representation. We found that using this representation, over 98% of the individuals were successfully contacted within the stipulated period. The network also demonstrated a small-world property, with an average geodesic distance of 3.56.

Keywords: Social Networks, Kinship Networks, Social Network Analysis, Geospatial Communication, Hubs

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8945 Thermal Hydraulic Analysis of the IAEA 10MW Benchmark Reactor under Normal Operating Condition

Authors: Hamed Djalal

Abstract:

The aim of this paper is to perform a thermal-hydraulic analysis of the IAEA 10 MW benchmark reactor solving analytically and numerically, by mean of the finite volume method, respectively the steady state and transient forced convection in rectangular narrow channel between two parallel MTR-type fuel plates, imposed under a cosine shape heat flux. A comparison between both solutions is presented to determine the minimal coolant velocity which can ensure a safe reactor core cooling, where the cladding temperature should not reach a specific safety limit 90 °C. For this purpose, a computer program is developed to determine the principal parameter related to the nuclear core safety, such as the temperature distribution in the fuel plate and in the coolant (light water) as a function of the inlet coolant velocity. Finally, a good agreement is noticed between the both analytical and numerical solutions, where the obtained results are displayed graphically.

Keywords: Forced convection, friction factor pressure drop thermal hydraulic analysis, vertical heated rectangular channel.

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8944 Increase in Solar Thermal Energy Storage by using a Hybrid Energy Storage System

Authors: Hassan Zohoor, Zaeem M. Moosavi

Abstract:

The intermittent nature of solar energy and the energy requirements of buildings necessitate the storage of thermal energy. In this paper a hybrid system of storing solar energy has been analyzed. Adding a LHS medium to a commercial solar water heater, the required energy for heating a small room was obtained in addition to preparing hot water. In other words, the suggested hybrid storage system consists of two tanks: a water tank as a SHS medium; and a paraffin tank as a LHS medium. A computing program was used to find the optimized time schedule of charging the storage tanks during each day, according to the solar radiation conditions. The results show that the use of such system can improve the capability of energy gathering comparing to the individual water storage tank during the cold months of the year. Of course, because of the solar radiation angles and shorten daylight in December & January, the performance will be the same as the simple solar water heaters (in the northern hemisphere). But the extra energy stored in November, February, March & April, can be useful for heating a small room for 3 hours during the cold days.

Keywords: Hybrid, Optimization, Solar thermal energy, Storage.

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8943 Molecular Evolutionary Analysis of Yeast Protein Interaction Network

Authors: Soichi Ogishima, Takeshi Hase, So Nakagawa, Yasuhiro Suzuki, Hiroshi Tanaka

Abstract:

To understand life as biological system, evolutionary understanding is indispensable. Protein interactions data are rapidly accumulating and are suitable for system-level evolutionary analysis. We have analyzed yeast protein interaction network by both mathematical and biological approaches. In this poster presentation, we inferred the evolutionary birth periods of yeast proteins by reconstructing phylogenetic profile. It has been thought that hub proteins that have high connection degree are evolutionary old. But our analysis showed that hub proteins are entirely evolutionary new. We also examined evolutionary processes of protein complexes. It showed that member proteins of complexes were tend to have appeared in the same evolutionary period. Our results suggested that protein interaction network evolved by modules that form the functional unit. We also reconstructed standardized phylogenetic trees and calculated evolutionary rates of yeast proteins. It showed that there is no obvious correlation between evolutionary rates and connection degrees of yeast proteins.

Keywords: Protein interaction network, evolution, modularity, evolutionary rate, connection degrees.

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8942 Dynamic Model of a Buck Converter with a Sliding Mode Control

Authors: S. Chonsatidjamroen , K-N. Areerak, K-L. Areerak

Abstract:

This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.

Keywords: Generalized state-space averaging method, buck converter, sliding mode control, modeling, simulation.

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8941 Optimization and GIS-Based Intelligent Decision Support System for Urban Transportation Systems Analysis

Authors: Mohamad K. Hasan, Hameed Al-Qaheri

Abstract:

Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Keywords: Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.

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8940 Dynamic Measurement System Modeling with Machine Learning Algorithms

Authors: Changqiao Wu, Guoqing Ding, Xin Chen

Abstract:

In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: Dynamic system modeling, neural network, normal equation, second order gradient descent.

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8939 Quality Evaluation of Ready to Eat Potatoes’ Produce in Flexible Packaging

Authors: Sandra Muizniece-Brasava, Aija Ruzaike, Lija Dukalska, Ilze Stokmane, Liene Strauta

Abstract:

Experiments have been carried out at the Latvia University of Agriculture Department of Food Technology. The aim of this work was to assess the effect of thermal treatment in flexible retort pouch packaging on the quality of potatoes’ produce during the storage time. Samples were evaluated immediately after retort thermal treatment; and following 1; 2; 3 and 4 storage months at the ambient temperature of +18±2ºC in vacuum packaging from polyamide/polyethylene (PA/PE) and aluminum/polyethylene (Al/PE) film pouches with barrier properties. Experimentally the quality of the potatoes’ produce in dry butter and mushroom dressings was characterized by measuring pH, hardness, color, microbiological properties and sensory evaluation. The sterilization was effective in protecting the produce from physical, chemical, and microbial quality degradation. According to the study of obtained data, it can be argued that the selected product processing technology and packaging materials could be applied to provide the safety and security during four-month storage period.

Keywords: Potatoes’ produce, shelf life, retort thermal treatment and packaging.

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8938 Simulation and Design of the Geometric Characteristics of the Oscillatory Thermal Cycler

Authors: Tse-Yu Hsieh, Jyh-Jian Chen

Abstract:

Since polymerase chain reaction (PCR) has been invented, it has emerged as a powerful tool in genetic analysis. The PCR products are closely linked with thermal cycles. Therefore, to reduce the reaction time and make temperature distribution uniform in the reaction chamber, a novel oscillatory thermal cycler is designed. The sample is placed in a fixed chamber, and three constant isothermal zones are established and lined in the system. The sample is oscillated and contacted with three different isothermal zones to complete thermal cycles. This study presents the design of the geometric characteristics of the chamber. The commercial software CFD-ACE+TM is utilized to investigate the influences of various materials, heating times, chamber volumes, and moving speed of the chamber on the temperature distributions inside the chamber. The chamber moves at a specific velocity and the boundary conditions with time variations are related to the moving speed. Whereas the chamber moves, the boundary is specified at the conditions of the convection or the uniform temperature. The user subroutines compiled by the FORTRAN language are used to make the numerical results realistically. Results show that the reaction chamber with a rectangular prism is heated on six faces; the effects of various moving speeds of the chamber on the temperature distributions are examined. Regarding to the temperature profiles and the standard deviation of the temperature at the Y-cut cross section, the non-uniform temperature inside chamber is found as the moving speed is larger than 0.01 m/s. By reducing the heating faces to four, the standard deviation of the temperature of the reaction chamber is under 1.4×10-3K with the range of velocities between 0.0001 m/s and 1 m/s. The nature convective boundary conditions are set at all boundaries while the chamber moves between two heaters, the effects of various moving velocities of the chamber on the temperature distributions are negligible at the assigned time duration.

Keywords: Polymerase chain reaction, oscillatory thermal cycler, standard deviation of temperature, nature convective.

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8937 A Dynamic Hybrid Option Pricing Model by Genetic Algorithm and Black- Scholes Model

Authors: Yi-Chang Chen, Shan-Lin Chang, Chia-Chun Wu

Abstract:

Unlike this study focused extensively on trading behavior of option market, those researches were just taken their attention to model-driven option pricing. For example, Black-Scholes (B-S) model is one of the most famous option pricing models. However, the arguments of B-S model are previously mentioned by some pricing models reviewing. This paper following suggests the importance of the dynamic character for option pricing, which is also the reason why using the genetic algorithm (GA). Because of its natural selection and species evolution, this study proposed a hybrid model, the Genetic-BS model which combining GA and B-S to estimate the price more accurate. As for the final experiments, the result shows that the output estimated price with lower MAE value than the calculated price by either B-S model or its enhanced one, Gram-Charlier garch (G-C garch) model. Finally, this work would conclude that the Genetic-BS pricing model is exactly practical.

Keywords: genetic algorithm, Genetic-BS, option pricing model.

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8936 Mobile Robot Path Planning in a 2-Dimentional Mesh

Authors: Doraid Dalalah

Abstract:

A topologically oriented neural network is very efficient for real-time path planning for a mobile robot in changing environments. When using a recurrent neural network for this purpose and with the combination of the partial differential equation of heat transfer and the distributed potential concept of the network, the problem of obstacle avoidance of trajectory planning for a moving robot can be efficiently solved. The related dimensional network represents the state variables and the topology of the robot's working space. In this paper two approaches to problem solution are proposed. The first approach relies on the potential distribution of attraction distributed around the moving target, acting as a unique local extreme in the net, with the gradient of the state variables directing the current flow toward the source of the potential heat. The second approach considers two attractive and repulsive potential sources to decrease the time of potential distribution. Computer simulations have been carried out to interrogate the performance of the proposed approaches.

Keywords: Mobile robot, Path Planning, Mesh, Potential field.

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8935 Spreading Dynamics of a Viral Infection in a Complex Network

Authors: Khemanand Moheeput, Smita S. D. Goorah, Satish K. Ramchurn

Abstract:

We report a computational study of the spreading dynamics of a viral infection in a complex (scale-free) network. The final epidemic size distribution (FESD) was found to be unimodal or bimodal depending on the value of the basic reproductive number R0 . The FESDs occurred on time-scales long enough for intermediate-time epidemic size distributions (IESDs) to be important for control measures. The usefulness of R0 for deciding on the timeliness and intensity of control measures was found to be limited by the multimodal nature of the IESDs and by its inability to inform on the speed at which the infection spreads through the population. A reduction of the transmission probability at the hubs of the scale-free network decreased the occurrence of the larger-sized epidemic events of the multimodal distributions. For effective epidemic control, an early reduction in transmission at the index cell and its neighbors was essential.

Keywords: Basic reproductive number, epidemic control, scalefree network, viral infection.

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8934 Energy Efficient Clustering Algorithm with Global and Local Re-clustering for Wireless Sensor Networks

Authors: Ashanie Guanathillake, Kithsiri Samarasinghe

Abstract:

Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering  algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.

Keywords: Energy efficient, Global re-clustering, Local re-clustering, Wireless sensor networks.

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