Search results for: thermal network model.

Authors: Ashmin Aryal, Pipat Chaiwiwatworakul, Surapong Chirarattananon

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Radiant chilled ceiling (RCC) has been perceived to save more energy and provide better thermal comfort than the traditional air conditioning system. However, its application has been rather limited by some reasons e.g., the scarce information about the thermal characteristic in the radiant room and the local climate influence on the system performance, etc. To bridge such gap, an office-like experiment room with a RCC was constructed in the hot and humid climate of Thailand. This paper presents exemplarily results from the RCC experiments to give an insight into the thermal environment in a radiant room and the cooling load associated to maintain the room's comfort condition. It gave a demonstration of the RCC system operation for its application to achieve thermal comfort in offices in a hot humid climate, as well.

Keywords: Radiant chilled ceiling, thermal comfort, cooling load, outdoor air unit.

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Authors: Kais Hafsaoui

Abstract:

In this paper, we propose to study the synthesis of the vertical dipole antenna over imperfect ground. The synthesis implementation-s method for this type of antenna permits to approach the appropriated radiance-s diagram. The used approach is based on neural network. Our main contribution in this paper is the extension of a synthesis model of this vertical dipole antenna over imperfect ground.

Keywords: Vertical dipole antenna, imperfect ground, neural network.

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Authors: K. M. Faraoun, A. Boukelif

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In the present work, we propose a new technique to enhance the learning capabilities and reduce the computation intensity of a competitive learning multi-layered neural network using the K-means clustering algorithm. The proposed model use multi-layered network architecture with a back propagation learning mechanism. The K-means algorithm is first applied to the training dataset to reduce the amount of samples to be presented to the neural network, by automatically selecting an optimal set of samples. The obtained results demonstrate that the proposed technique performs exceptionally in terms of both accuracy and computation time when applied to the KDD99 dataset compared to a standard learning schema that use the full dataset.

Keywords: Neural networks, Intrusion detection, learningenhancement, K-means clustering

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Authors: H. Pahlavanzadeh, A.R.Jahangiri, I. Noshadi

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In this paper, the solubility of CO2 in AMP solution have been measured at temperature range of ( 293, 303 ,313,323) K.The amine concentration ranges studied are (2.0, 2.8, and 3.4) M. A solubility apparatus was used to measure the solubility of CO2 in AMP solution on samples of flue gases from Thermal and Central Power Plants of Esfahan Steel Company. The modified Kent Eisenberg model was used to correlate and predict the vapor-liquid equilibria of the (CO2 + AMP + H2O) system. The model predicted results are in good agreement with the experimental vapor-liquid equilibrium measurements.

Keywords: AMP, Carbon dioxide; loading, Flue gases, Modified Kent Eisenberg model

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Authors: Toufic Abd El-Latif Sadek

Abstract:

The asphalt object represents the asphalted areas like roads, and the concrete object represents the concrete areas like concrete buildings. The efficient extraction of asphalt and concrete objects from one satellite thermal image occurred at a specific time, by preventing the gaps in times which give the close and same brightness values between asphalt and concrete, and among other objects. So that to achieve efficient extraction and then better analysis. Seven sample objects were used un this study, asphalt, concrete, metal, rock, dry soil, vegetation, and water. It has been found that, the best timing for capturing satellite thermal images to extract the two objects asphalt and concrete from one satellite thermal image, saving time and money, occurred at a specific time in different months. A table is deduced shows the optimal timing for capturing satellite thermal images to extract effectively these two objects.

Keywords: Asphalt, concrete, satellite thermal images, timing.

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Authors: Z.A. Rasid, R. Zahari, A. Ayob, D.L. Majid, A.S.M. Rafie

Abstract:

Aerospace vehicles are subjected to non-uniform thermal loading that may cause thermal buckling. A study was conducted on the thermal post-buckling of shape memory alloy composite plates subjected to the non-uniform tent-like temperature field. The shape memory alloy wires were embedded within the laminated composite plates to add recovery stress to the plates. The non-linear finite element model that considered the recovery stress of the shape memory alloy and temperature dependent properties of the shape memory alloy and composite matrix along with its source codes were developed. It was found that the post-buckling paths of the shape memory alloy composite plates subjected to various tentlike temperature fields were stable within the studied temperature range. The addition of shape memory alloy wires to the composite plates was found to significantly improve the post-buckling behavior of laminated composite plates under non-uniform temperature distribution.

Keywords: Post-buckling, shape memory alloy, temperaturedependent property, tent-like temperature distribution

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Authors: Faraj Farhat El Dabee, Rajab Abdullah Hokoma

Abstract:

Supply Chain Management (SCM) is the integration between manufacturer, transporter and customer in order to form one seamless chain that allows smooth flow of raw materials, information and products throughout the entire network that help in minimizing all related efforts and costs. The main objective of this paper is to develop a model that can accept a specified number of spare-parts within the supply chain, simulating its inventory operations throughout all stages in order to minimize the inventory holding costs, base-stock, safety-stock, and to find the optimum quantity of inventory levels, thereby suggesting a way forward to adapt some factors of Just-In-Time to minimizing the inventory costs throughout the entire supply chain. The model has been developed using Micro- Soft Excel & Visual Basic in order to study inventory allocations in any network of the supply chain. The application and reproducibility of this model were tested by comparing the actual system that was implemented in the case study with the results of the developed model. The findings showed that the total inventory costs of the developed model are about 50% less than the actual costs of the inventory items within the case study.

Keywords: Holding Costs, Inventory, JIT, Modeling, SCM

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Authors: Raja Das, M. K. Pradhan

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This paper presents a comparative study between two neural network models namely General Regression Neural Network (GRNN) and Back Propagation Neural Network (BPNN) are used to estimate radial overcut produced during Electrical Discharge Machining (EDM). Four input parameters have been employed: discharge current (Ip), pulse on time (Ton), Duty fraction (Tau) and discharge voltage (V). Recently, artificial intelligence techniques, as it is emerged as an effective tool that could be used to replace time consuming procedures in various scientific or engineering applications, explicitly in prediction and estimation of the complex and nonlinear process. The both networks are trained, and the prediction results are tested with the unseen validation set of the experiment and analysed. It is found that the performance of both the networks are found to be in good agreement with average percentage error less than 11% and the correlation coefficient obtained for the validation data set for GRNN and BPNN is more than 91%. However, it is much faster to train GRNN network than a BPNN and GRNN is often more accurate than BPNN. GRNN requires more memory space to store the model, GRNN features fast learning that does not require an iterative procedure, and highly parallel structure. GRNN networks are slower than multilayer perceptron networks at classifying new cases.

Keywords: Electrical-discharge machining, General Regression Neural Network, Back-propagation Neural Network, Radial Overcut.

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Authors: Jianzheng Wei, Duo Zhen, Zhihan Yang, Huifeng Tan

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The deployable descent technology is a lightweight entry method using an inflatable heat shield. The heatshield consists of a pressurized core which is covered by different layers of thermal insulation and flexible ablative materials in order to protect against the thermal loads. In this paper, both aluminum and silicon-aluminum aerogels were prepared by freeze-drying method. The latter material has bigger specific surface area and nano-scale pores. Mullite fibers are used as the reinforcing fibers to prepare the aerogel matrix to improve composite flexibility. The flexible composite materials were performed as an insulation layer to an underlying aramid fabric by a thermal shock test at a heat flux density of 120 kW/m² and uniaxial tensile test. These results show that the aramid fabric with untreated mullite fibers as the thermal protective layer is completely carbonized at the heat of about 60 s. The aramid fabric as a thermal resistance layer of the composite material still has good mechanical properties at the same heat condition.

Keywords: Aerogel, aramid fabric, flexibility, thermal resistance.

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Authors: K. Chandra Sekaran

Abstract:

This paper describes a paradigmatic approach to develop architecture of secure systems by describing the requirements from four different points of view: that of the owner, the administrator, the user, and the network. Deriving requirements and developing architecture implies the joint elicitation and describing the problem and the structure of the solution. The view points proposed in this paper are those we consider as requirements towards their contributions as major parties in the design, implementation, usage and maintenance of secure systems. The dramatic growth of the technology of Internet and the applications deployed in World Wide Web have lead to the situation where the security has become a very important concern in the development of secure systems. Many security approaches are currently being used in organizations. In spite of the widespread use of many different security solutions, the security remains a problem. It is argued that the approach that is described in this paper for the development of secure architecture is practical by all means. The models representing these multiple points of view are termed the requirements model (views of owner and administrator) and the operations model (views of user and network). In this paper, this multiple view paradigm is explained by first describing the specific requirements and or characteristics of secure systems (particularly in the domain of networks) and the secure architecture / system development methodology.

Keywords: Multiple view paradigms, requirements model, operations model, secure system, owner, administrator, user, network.

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Authors: Niti Kammuang-lue, Kritsada On-ai, Phrut Sakulchangsatjatai, Pradit Terdtoon

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The objectives of this paper are to investigate effects of dimensionless numbers on thermal performance of the vertical closed-loop pulsating heat pipe (VCLPHP) and to establish a correlation to predict the thermal performance of the VCLPHP. The CLPHPs were made of long copper capillary tubes with inner diameters of 1.50, 1.78, and 2.16mm and bent into 26 turns. Then, both ends were connected together to form a loop. The evaporator, adiabatic, and condenser sections length were equal to 50 and 150 mm. R123, R141b, acetone, ethanol, and water were chosen as variable working fluids with constant filling ratio of 50% by total volume. Inlet temperature of heating medium and adiabatic section temperature was constantly controlled at 80 and 50^oC, respectively. Thermal performance was represented in a term of Kutateladze number (Ku). It can be concluded that when Prandtl number of liquid working fluid (Pr_l), and Karman number (Ka) increases, thermal performance increases. On contrary, when Bond number (Bo), Jacob number (Ja), and Aspect ratio (L_e/D_i) increases, thermal performance decreases. Moreover, the correlation to predict more precise thermal performance has been successfully established by analyzing on all dimensionless numbers that have effect on the thermal performance of the VCLPHP.

Keywords: Vertical closed-loop pulsating heat pipe, working fluid, thermal performance, dimensionless parameter.

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Authors: D. Zabala, Y. Cárdenas, G. Núñez

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In this work the numerical simulation of transient heat transfer in a cylindrical probe is done. An experiment was conducted introducing a steel cylinder in a heating chamber and registering its surface temperature along the time during one hour. In parallel, a mathematical model was solved for one dimension transient heat transfer in cylindrical coordinates, considering the boundary conditions of the test. The model was solved using finite difference method, because the thermal conductivity in the cylindrical steel bar and the convection heat transfer coefficient used in the model are considered temperature dependant functions, and both conditions prevent the use of the analytical solution. The comparison between theoretical and experimental results showed the average deviation is below 2%. It was concluded that numerical methods are useful in order to solve engineering complex problems. For constant k and h, the experimental methodology used here can be used as a tool for teaching heat transfer in mechanical engineering, using mathematical simplified models with analytical solutions.

Keywords: Heat transfer experiment, thermal conductivity, finite difference, engineering education.

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Authors: M. Mahdavi, E. Mahdavi

Abstract:

In this research, STNEP is being studied considering network adequacy and limitation of investment cost by decimal codification genetic algorithm (DCGA). The goal is obtaining the maximum of network adequacy with lowest expansion cost for a specific investment. Finally, the proposed idea is applied to the Garvers 6-bus network. The results show that considering the network adequacy for solution of STNEP problem is caused that among of expansion plans for a determined investment, configuration which has relatively lower expansion cost and higher adequacy is proposed by GA based method. Finally, with respect to the curve of adequacy versus expansion cost it can be said that more optimal configurations for expansion of network are obtained with lower investment costs.

Keywords: TNEP, Network Adequacy, Investment Cost, GA

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Authors: Chetan Mahawar, Sarath Chandran, Sridhar Panigrahi, V. P. Shaji

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The ever-growing advancement in space exploration has led to an alarming concern for space debris removal as it restricts further launch operations and adventurous space missions; hence various technologies and methods are explored for re-entry predictions and material selection processes for mitigating space debris. The selection of material and operating conditions is determined with the objective of lightweight structure and ability to demise faster subject to spacecraft survivability during its mission. The various evolving thermal material properties such as emissivity, specific heat capacity, thermal conductivity, radiation intensity, etc. affect demisability of spacecraft. Thus, this paper presents the analysis of evolving thermal material properties of spacecraft, which affect the demisability process and thus estimate demise time using the demisability model by incorporating evolving thermal properties for sensible heating followed by the complete or partial break-up of spacecraft. The demisability analysis thus concludes that the best suitable spacecraft material is based on the least estimated demise time, which fulfills the criteria of design-for-survivability and as well as of design-for-demisability.

Keywords: Demisability, emissivity, lightweight, re-entry, survivability.

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Authors: Zhi-Jun Lu, Qi Lu, Meng Wu, Qian Xiang, Jun Gu

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The analysis of perforated steel members is a 3D problem in nature, therefore the traditional analytical expressions for the ultimate load of thin-walled steel sections cannot be used for the perforated steel member design. In this study, finite element method (FEM) and artificial neural network (ANN) were used to simulate the process of stub column tests based on specific codes. Results show that compared with those of the FEM model, the ultimate load predictions obtained from ANN technique were much closer to those obtained from the physical experiments. The ANN model for the solving the hard problem of complex steel perforated sections is very promising.

Keywords: Artificial neural network, finite element method, perforated sections, thin-walled steel, ultimate load.

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Authors: B. Q. Huang, Tarik Rashid, M-T. Kechadi

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this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.

Keywords: Gradient descent method, recurrent neural network, learning algorithms, time series, BP

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Authors: B. L. Ho, L. Shi, D. F. Wang, V. C. T. Mok

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The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.

Keywords: Functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity.

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Authors: Bin Su

Abstract:

The 'wind-rain' house has a courtyard with glazed roof, which allows more direct sunlight to come into indoor spaces during the winter. The glazed roof can be partially opened or closed and automatically controlled to provide natural ventilation in order to adjust for indoor thermal conditions and the roof area can be shaded by reflective insulation materials during the summer. Two field studies for evaluating indoor thermal conditions of the two 'windrain' houses have been carried out by author in 2009 and 2010. Indoor and outdoor air temperature and relative humidity adjacent to floor and ceiling of the two sample houses were continuously tested at 15-minute intervals, 24 hours a day during the winter months. Based on field study data, this study investigates relationships between building design and indoor thermal condition of the 'windrain' house to improve the future house design for building thermal comfort and energy efficiency

Keywords: Courtyard, house design, indoor thermal comfort, 'wind-rain' house

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Authors: Sumitra Nuanmeesri

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The research focus on study, analyze and design the model of the infrastructure and computer networks for distance education, online learning via new media, e-learning and blended learning. The collected information from study and analyze process that information was evaluated by the index of item objective congruence (IOC) by 9 specialists to design model. The results of evaluate the model with the mean and standard deviation by the sample of 9 specialists value is 3.85. The results showed that the infrastructure and computer networks are designed to be appropriate to a great extent appropriate to a great extent.

Keywords: Blended Learning, New Media, Infrastructure and Computer Network, Tele-Education, Online Learning.

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Authors: Yu-Wei Chang, Chiao-Hung Cheng, Wen-Fang Wu, Sih-Li Chen

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This article experimentally investigates the thermal performance of thermoelectric air-cooling module which comprises a thermoelectric cooler (TEC) and an air-cooling heat sink. The influences of input current and heat load are determined. And performances under each situation are quantified by thermal resistance analysis. Since TEC generates Joule heat, this nature makes construction of thermal resistance network difficult. To simplify the analysis, this article emphasizes on the resistance heat load might meet when passing through the device. Therefore, the thermal resistances in this paper are to divide temperature differences by heat load. According to the result, there exists an optimum input current under every heating power. In this case, the optimum input current is around 6A or 7A. The performance of the heat sink would be improved with TEC under certain heating power and input current, especially at a low heat load. According to the result, the device can even make the heat source cooler than the ambient. However, TEC is not always effective at every heat load and input current. In some situation, the device works worse than the heat sink without TEC. To determine the availability of TEC, this study figures out the effective operating region in which the TEC air-cooling module works better than the heat sink without TEC. The result shows that TEC is more effective at a lower heat load. If heat load is too high, heat sink with TEC will perform worse than without TEC. The limit of this device is 57W. Besides, TEC is not helpful if input current is too high or too low. There is an effective range of input current, and the range becomes narrower when the heat load grows.

Keywords: Thermoelectric cooler, TEC, electronic cooling, heat sink.

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model.

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Authors: Resul Fikir

Abstract:

Unmanned Aircraft Systems (UAS) become indispensable parts of modern airpower as force multiplier. One of the main advantages of UAS is long endurance. UAS have to take extra payloads to accomplish different missions but these payloads decrease endurance of aircraft because of increasing drag. There are continuing researches to increase the capability of UAS. There are some vertical thermal air currents, which can cause climb and increase endurance, in nature. Birds and gliders use thermals to gain altitude with no effort. UAS have wide wings which can use thermals like birds and gliders. Thermal regions, which is area of 2000-3000 meter (1 NM), exist all around the world. It is natural and infinite source. This study analyses if thermal regions can be adopted and implemented as an assistant tool for UAS route planning. First and second part of study will contain information about the thermal regions and current applications about UAS in aviation and climbing performance with a real example. Continuing parts will analyze the contribution of thermal regions to UAS endurance. Contribution is important because planning declaration of UAS navigation rules will be in 2015.

Keywords: Airways, Thermals, UAS, UAS Roadmap.

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Authors: Sachin Man Bajimaya, SangChul Park, Gi-Nam Wang

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The objective of this paper is to estimate realistic principal extrusion process parameters by means of artificial neural network. Conventionally, finite element analysis is used to derive process parameters. However, the finite element analysis of the extrusion model does not consider the manufacturing process constraints in its modeling. Therefore, the process parameters obtained through such an analysis remains highly theoretical. Alternatively, process development in industrial extrusion is to a great extent based on trial and error and often involves full-size experiments, which are both expensive and time-consuming. The artificial neural network-based estimation of the extrusion process parameters prior to plant execution helps to make the actual extrusion operation more efficient because more realistic parameters may be obtained. And so, it bridges the gap between simulation and real manufacturing execution system. In this work, a suitable neural network is designed which is trained using an appropriate learning algorithm. The network so trained is used to predict the manufacturing process parameters.

Keywords: Artificial Neural Network (ANN), Indirect Extrusion, Finite Element Analysis, MES.

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Authors: Eugene Grichuk, Margarita Kuzmina, Eduard Manykin

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A network of coupled stochastic oscillators is proposed for modeling of a cluster of entangled qubits that is exploited as a computation resource in one-way quantum computation schemes. A qubit model has been designed as a stochastic oscillator formed by a pair of coupled limit cycle oscillators with chaotically modulated limit cycle radii and frequencies. The qubit simulates the behavior of electric field of polarized light beam and adequately imitates the states of two-level quantum system. A cluster of entangled qubits can be associated with a beam of polarized light, light polarization degree being directly related to cluster entanglement degree. Oscillatory network, imitating qubit cluster, is designed, and system of equations for network dynamics has been written. The constructions of one-qubit gates are suggested. Changing of cluster entanglement degree caused by measurements can be exactly calculated.

Keywords: network of stochastic oscillators, one-way quantumcomputations, a beam of polarized light.

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Authors: Azza A. Al-Ghamdi, Abir S. Abdel-Naby

Abstract:

Cellulose acetate (CA) is a natural biodegradable polymer. It forms transparent films by the casting technique. CA suffers from high degree of water permeability as well as the low thermal stability at high temperatures. To adjust the CA polymeric films to the manufacture of food packaging, its thermal and mechanical properties should be improved. The modification of CA by grafting it with N-Amino phenyl maleimide (N-APhM) led to the construction of hydrophobic branches throughout the polymeric matrix which reduced its wettability as compared to the parent CA. The branches built onto the polymeric chains had been characterized by UV/Vis, ¹³C-NMR and ESEM. The improvement of the thermal properties was investigated and compared to the parent CA using thermal gravimetric analysis (TGA), differential scanning calorimetry (DSC), differential thermal analysis (DTA), contact angle and mechanical testing measurements. The results revealed that the water-uptake was reduced by increasing the graft percentage. The thermal and mechanical properties were also improved.

Keywords: Cellulose acetate, food packaging, graft copolymerization.

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Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices over the past five years of 10 major tech companies: Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We implemented and tested three models – a linear regressor model, a k-nearest neighbor model (KNN), and a sequential neural network – and two algorithms – Multiplicative Weight Update and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: Finance, machine learning, opening price, stock market.

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Authors: M. Safa, S. Samarasinghe

Abstract:

An artificial neural network (ANN) approach was used to model the energy consumption of wheat production. This study was conducted over 35,300 hectares of irrigated and dry land wheat fields in Canterbury in the 2007-2008 harvest year.1 In this study several direct and indirect factors have been used to create an artificial neural networks model to predict energy use in wheat production. The final model can predict energy consumption by using farm condition (size of wheat area and number paddocks), farmers- social properties (education), and energy inputs (N and P use, fungicide consumption, seed consumption, and irrigation frequency), it can also predict energy use in Canterbury wheat farms with error margin of ±7% (± 1600 MJ/ha).

Keywords: Artificial neural network, Canterbury, energy consumption, modelling, New Zealand, wheat.

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Authors: Hidehiko Okada

Abstract:

The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks. 

Keywords: Evolutionary algorithms, differential evolution, neural network, neuroevolution, interval arithmetic.

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: Metabolic network, gene knockout, flux balance analysis, microarray data, integration.

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Authors: Khine Phyu, Aung Myint Aye

Abstract:

This paper presents results of measurements campaign carried out at a carrier frequency of 24GHz with the help of TPLINK router in indoor line-of-sight (LOS) scenarios. Firstly, the radio wave propagation strategies are analyzed in some rooms with router of point to point Ad hoc network. Then floor attenuation is defined for 3 floors in experimental region. The free space model and dual slope models are modified by considering the influence of corridor conditions on each floor. Using these models, indoor signal attenuation can be estimated in modeling of indoor radio wave propagation. These results and modified models can also be used in planning the networks of future personal communications services.

Keywords: radio wave signal analyzing, LOS radio wavepropagation, indoor radio wave propagation, free space model, tworay model and indoor attenuation.

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