Search results for: Modified artificial bee colony.

Authors: M. Khosravy-el-Hossani, Q. Dorosti

Abstract:

One of the important applications of gas turbines is their utilization for heat recovery steam generator in combine-cycle technology. Exhaust flow and energy are two key parameters for determining heat recovery steam generator performance which are mainly determined by the main gas turbine components performance data. For this reason a method was developed for determining the exhaust energy in the new edition of ASME PTC22. The result of this investigation shows that the method of standard has considerable error. Therefore in this paper a new method is presented for modifying of the performance calculation. The modified method is based on exhaust gas constituent analysis and combustion calculations. The case study presented here by two kind of General Electric gas turbine design data for validation of methodologies. The result shows that the modified method is more precise than the ASME PTC22 method. The exhaust flow calculation deviation from design data is 1.5-2 % by ASME PTC22 method so that the deviation regarding with modified method is 0.3-0.5%. Based on precision of analyzer instruments, the method can be suitable alternative for gas turbine standard performance test. In advance two methods are proposed based on known and unknown fuel in modified method procedure. The result of this paper shows that the difference between the two methods is below than %0.02. In according to reasonable esult of the second procedure (unknown fuel composition), the method can be applied to performance evaluation of gas turbine, so that the measuring cost and data gathering should be reduced.

Keywords: Gas turbine, Performance test code, Combined cycle.

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Authors: E.Sasikumar, T.Viruthagiri

Abstract:

Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.

Keywords: Sugarcane bagasse, ethanol, optimization, Pachysolen tannophilus.

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Authors: R. Eslami-Farsani, S. M. S. Mousavi Bafrouyi

Abstract:

During past decades, increasing demand of modified Fiber Metal Laminates (FMLs) has stimulated a strong trend towards the development of these structures. FMLs contain several thin layers of metal bonded with composite materials. Characteristics of FMLs such as low specific mass, high bearing strength, impact resistance, corrosion resistance and high fatigue life are attractive. Nowadays, increasing development can be observed to promote the properties of polymer-based composites by nanofillers. By dispersing strong, nanofillers in polymer matrix, modified composites can be developed and tailored to individual applications. On the other hand, the synergic effects of nanoparticles such as graphene and carbon nanotube can significantly improve the mechanical, electrical and thermal properties of nanocomposites. In present paper, the modifying of FMLs by nanofillers and the dispersing of nanoparticles in the polymers matrix are discussed. The evaluations have revealed that this approach is acceptable. Finally, a prospect is presented. This paper will lead to further work on these modified FML species.

Keywords: Fiber metal laminate, nanofiller, polymer matrix, property modification.

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Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

Abstract:

This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine dataset, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: Artificial Neural Networks, Holonic Approach, Feature Selection, Bee Algorithm.

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Authors: A. Golmohammadi, B. Jahandideh

Abstract:

One of the determinants of a firm-s prosperity is the customers- perceived service quality and satisfaction. While service quality is wide in scope, and consists of various dimensions, there may be differences in the relative importance of these dimensions in affecting customers- overall satisfaction of service quality. Identifying the relative rank of different dimensions of service quality is very important in that it can help managers to find out which service dimensions have a greater effect on customers- overall satisfaction. Such an insight will consequently lead to more effective resource allocation which will finally end in higher levels of customer satisfaction. This issue – despite its criticality- has not received enough attention so far. Therefore, using a sample of 240 bank customers in Iran, an artificial neural network is developed to address this gap in the literature. As customers- evaluation of service quality is a subjective process, artificial neural networks –as a brain metaphor- may appear to have a potentiality to model such a complicated process. Proposing a neural network which is able to predict the customers- overall satisfaction of service quality with a promising level of accuracy is the first contribution of this study. In addition, prioritizing the service quality dimensions in affecting customers- overall satisfaction –by using sensitivity analysis of neural network- is the second important finding of this paper.

Keywords: service quality, customer satisfaction, relative importance, artificial neural network.

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Authors: J. Hossen, A. Rahman, K. Samsudin, F. Rokhani, S. Sayeed, R. Hasan

Abstract:

The Neuro-Fuzzy hybridization scheme has become of research interest in pattern classification over the past decade. The present paper proposes a novel Modified Adaptive Fuzzy Inference Engine (MAFIE) for pattern classification. A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data sets. A TSK type fuzzy inference system is constructed by the automatic generation of membership functions and rules by the fuzzy c-means clustering and Apriori algorithm technique, respectively. The generated adaptive fuzzy inference engine is adjusted by the least-squares fit and a conjugate gradient descent algorithm towards better performance with a minimal set of rules. The proposed MAFIE is able to reduce the number of rules which increases exponentially when more input variables are involved. The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher-s Iris and Wisconsin breast cancer data sets and shown to be very competitive.

Keywords: Apriori algorithm, Fuzzy C-means, MAFIE, TSK

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Authors: Chun-Yao Lee, Yi-Xing Shen, Jung-Cheng Cheng, Yi-Yin Li, Chih-Wen Chang

Abstract:

This paper proposes the method combining artificial neural network (ANN) with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. First, the measurements of wind speed, rotor speed of wind power generator and output power of wind power generator are applied to train artificial neural network and to estimate the wind speed. Second, the method mentioned above is applied to estimate and control the optimal rotor speed of the wind turbine so as to output the maximum power. Finally, the result reveals that the control system discussed in this paper extracts the maximum output power of wind generator within the short duration even in the conditions of wind speed and load impedance variation.

Keywords: Maximum power point tracking, artificial neuralnetwork, particle swarm optimization.

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Authors: Rupali Verma, Maitreyee Dutta, Renu Vig

Abstract:

Encryption and decryption in RSA are done by modular exponentiation which is achieved by repeated modular multiplication. Hence efficiency of modular multiplication directly determines the efficiency of RSA cryptosystem. This paper designs a Modified Montgomery Modular Multiplication in which addition of operands is computed by 4:2 compressor. The basic logic operations in addition are partitioned over two iterations such that parallel computations are performed. This reduces the critical path delay of proposed Montgomery design. The proposed design and RSA are implemented on Virtex 2 and Virtex 5 FPGAs. The two factors partitioning and parallelism have improved the frequency and throughput of proposed design.

Keywords: RSA, Montgomery modular multiplication, 4:2 compressor, FPGA.

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

Abstract:

The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: Neural network computing, information processing, input-output mapping, training time, computers with high memory.

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Authors: F. Alwafie

Abstract:

In this paper, we present the simulation of the propagation characteristics of the picocellular propagation channel environment. The first aim has been to find a correct description of the environment for received wave.

The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A modified 3D ray tracing image method tool has been utilized for the coverage prediction. A detailed analysis of the dependence of the indoor wave on the wideband characteristics of the channel: root mean square (RMS) delay spread characteristics and Mean excess delay, is also investigated.

Keywords: Propagation, Ray Tracing.

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

Abstract:

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

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

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Authors: Phillip Garrad, Saritha Unnikrishnan

Abstract:

The increase in connected and autonomous vehicles (CAV) creates more opportunities for cyber-attacks. Cyber-attacks can be performed with malicious intent or for research and testing purposes. As connected vehicles approach full autonomy, the possible impact of these cyber-attacks also grows. This review analyses the challenges faced in CAV cybersecurity testing. This includes access and cost of the representative test setup and lack of experts in the field A review of potential solutions to overcome these challenges is presented. Studies have demonstrated Artificial Intelligence (AI) as a promising technique to reduce runtime, enhance effectiveness and comprehensively cover all the standard test aspects in penetration testing in other industries. However, this review has identified a significant gap in the systematic implementation of AI for penetration testing in the CAV cybersecurity domain. The expectation from this review is to investigate potential AI algorithms, which can demonstrate similar improvements in runtime and efficiency for a CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: Cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing.

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Authors: Mangesh R. Phate, V. H. Tatwawadi

Abstract:

This paper is intended to develop an artificial neural network (ANN) based model of material removal rate (MRR) in the turning of ferrous and nonferrous material in a Indian small-scale industry. MRR of the formulated model was proved with the testing data and artificial neural network (ANN) model was developed for the analysis and prediction of the relationship between inputs and output parameters during the turning of ferrous and nonferrous materials. The input parameters of this model are operator, work-piece, cutting process, cutting tool, machine and the environment.

The ANN model consists of a three layered feedforward back propagation neural network. The network is trained with pairs of independent/dependent datasets generated when machining ferrous and nonferrous material. A very good performance of the neural network, in terms of contract with experimental data, was achieved. The model may be used for the testing and forecast of the complex relationship between dependent and the independent parameters in turning operations.

Keywords: Field data based model, Artificial neural network, Simulation, Convectional Turning, Material removal rate.

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Authors: Naoto Suzuki

Abstract:

Many ophthalmologists find it difficult to distinguish between small retinal hemorrhages and dust artifacts when using fundus photography for the diagnosis of diabetic retinopathy. Six patients with diabetic retinopathy underwent fundus photography, which revealed dust artifacts in the photographs of some patients. We constructed an experimental device similar to the optical system of the fundus camera and colored the fundi of the artificial eyes with khaki, sunset, rose and sunflower colors. Using the experimental device, we photographed dust artifacts using each artificial eyes. We used Scilab 5.4.0 and SIVP 0.5.3 softwares to convert the red, green, and blue (RGB) color space to the hue, saturation, and value (HSV) color space. We calculated the differences between the areas of manifestations and perimanifestations and the areas of dust artifacts and periartifacts using average HSVs. The V values in HSV for the manifestations were as follows: hemorrhages, 0.06 ± 0.03; hard exudates, −0.12 ± 0.06; and photocoagulation marks, 0.07 ± 0.02. For dust artifacts, visualized in the human and artificial eyes, the V values were as follows: human eye, 0.19 ± 0.03; khaki, 0.41 ± 0.02; sunset, 0.43 ± 0.04; rose, 0.47 ± 0.11; and sunflower, 0.59 ± 0.07. For the human and artificial eyes, we calculated two sensitivity values of dust artifacts compared to manifestation areas. V values of the HSV color space enabled the differentiation of small hemorrhages, hard exudates, and photocoagulation marks from dust artifacts.

Keywords: Diabetic retinopathy, HSV color space, small hemorrhages, hard exudates, photocoagulation marks.

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Authors: Hazem M. El-Bakry, Qiangfu Zhao

Abstract:

Recently, neural networks have shown good results for detection of a certain pattern in a given image. In our previous papers [1-5], a fast algorithm for pattern detection using neural networks was presented. Such algorithm was designed based on cross correlation in the frequency domain between the input image and the weights of neural networks. Image conversion into symmetric shape was established so that fast neural networks can give the same results as conventional neural networks. Another configuration of symmetry was suggested in [3,4] to improve the speed up ratio. In this paper, our previous algorithm for fast neural networks is developed. The frequency domain cross correlation is modified in order to compensate for the symmetric condition which is required by the input image. Two new ideas are introduced to modify the cross correlation algorithm. Both methods accelerate the speed of the fast neural networks as there is no need for converting the input image into symmetric one as previous. Theoretical and practical results show that both approaches provide faster speed up ratio than the previous algorithm.

Keywords: Fast Pattern Detection, Neural Networks, Modified Cross Correlation

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Authors: Essam Al Daoud

Abstract:

This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: Least squares, neighbor joining, phylogenetic tree, wild dogpack.

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Authors: Haoyu Ma, Bin Hu, Mike Jackson, Jingzhi Yan, Wen Zhao

Abstract:

In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.

Keywords: Sleep, Sleep stage, Automatic sleep scoring, Electroencephalography, Decision tree, Artificial neural network

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Authors: T. Khampan, N. Thavarungkul, J. Tiansuwan, S. Kamthai

Abstract:

This research aimed to modify pineapple leaf paper (PALP) for using as wet media in the evaporation cooling system by improving wet mechanical property (tensile strength) without compromising water absorption property. Polyamideamineepichorohydrin resin (PAE) and carboxymethylcellulose (CMC) were used to strengthen the paper, and the PAE and CMC ratio of 80:20 showed the optimum wet and dry tensile index values, which were higher than those of the commercial cooling pad (CCP). Compared with CCP, PALP itself and all the PAE/CMC modified PALP possessed better water absorption. The PAE/CMC modified PALP had potential to become a new type of wet media.

Keywords: wet strength, evaporative cooling, pineapple leaves, polyamideamine-epichorohydrin, carboxymethylcellulose.

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Authors: Changjin Xu, Yusen Wu

Abstract:

In this paper, a asymptotically periodic predator-prey model with Modified Leslie-Gower and Holling-Type II schemes is investigated. Some sufficient conditions for the uniformly strong persistence of the system are established. Our result is an important complementarity to the earlier results.

Keywords: Predator-prey model, uniformly strong persistence, asymptotically periodic, Holling-type II.

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Authors: Chi-Yuan Huang, Mei-Chuan Kuo, Ching-Yi Hsiao

Abstract:

In this study, acids with various chain lengths (C₆, C₈, C₁₀ and C₁₂) modified by methane sulfonic acid (MSA) and temperature were used to modify tapioca starch (TPS), then the glycerol (GA) were added into modified starch, to prepare new blends. The mechanical properties, thermal properties and physical properties of blends were studied. This investigation was divided into two parts.  First, the biodegradable materials were used such as starch and glycerol with hexanedioic acid (HA), suberic acid (SBA), sebacic acid (SA), decanedicarboxylic acid (DA) manufacturing with different temperatures (90, 110 and 130 °C). And then, the solution was added into modified starch to prepare the blends by using single-screw extruder. The FT-IR patterns indicated that the characteristic peak of C=O in ester was observed at 1730 cm^-1. It is proved that different chain length acids (C₆, C₈, C₁₀ and C₁₂) reacted with glycerol by esterification and these are used to plasticize blends during extrusion. In addition, the blends would improve the hydrolysis and thermal stability. The water contact angle increased from 43.0° to 64.0°.  Second, the HA (110 °C), SBA (110 °C), SA (110 °C), and DA blends (130 °C) were used in study, because they possessed good mechanical properties, water resistances and thermal stability. On the other hand, the various contents (0, 0.005, 0.010, 0.020 g) of MSA were also used to modify the mechanical properties of blends. We observed that the blends were added to MSA, and then the FT-IR patterns indicated that the C=O ester appeared at 1730 cm^-1. For this reason, the hydrophobic blends were produced. The water contact angle of the MSA blends increased from 55.0° to 71.0°. Although break elongation of the MSA blends reduced from the original 220% to 128%, the stress increased from 2.5 MPa to 5.1 MPa. Therefore, the optimal composition of blends was the DA blend (130 °C) with adding of MSA (0.005 g).

Keywords: Chain length acids, methane sulfonic acid, tapioca starch, tensile stress.

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Authors: A. Rawangpai, B. Maraungsri, N. Chomnawang

Abstract:

This paper presents the experimental results on artificial ageing test of 22 kV XLPE cable for distribution system application in Thailand. XLPE insulating material of 22 kV cable was sliced to 60-70 μm in thick and was subjected to ac high voltage at 23 Ôùª C, 60 Ôùª C and 75 Ôùª C. Testing voltage was constantly applied to the specimen until breakdown. Breakdown voltage and time to breakdown were used to evaluate life time of insulating material. Furthermore, the physical model by J. P. Crine for predicts life time of XLPE insulating material was adopted as life time model and was calculated in order to compare the experimental results. Acceptable life time results were obtained from Crine-s model comparing with the experimental result. In addition, fourier transform infrared spectroscopy (FTIR) for chemical analysis and scanning electron microscope (SEM) for physical analysis were conducted on tested specimens.

Keywords: Artificial accelerated ageing test, XLPE cable, distribution system, insulating material, life time, life time model

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Authors: Hao He, Shaoqian Li

Abstract:

In this paper, we study the cooperative communications where multiple cognitive radio (CR) transmit-receive pairs competitive maximize their own throughputs. In CR networks, the influences of primary users and the spectrum availability are usually different among CR users. Due to the existence of multiple relay nodes and the different spectrum availability, each CR transmit-receive pair should not only select the relay node but also choose the appropriate channel. For this distributed problem, we propose a game theoretic framework to formulate this problem and we apply a regret-matching learning algorithm which is leading to correlated equilibrium. We further formulate a modified regret-matching learning algorithm which is fully distributed and only use the local information of each CR transmit-receive pair. This modified algorithm is more practical and suitable for the cooperative communications in CR network. Simulation results show the algorithm convergence and the modified learning algorithm can achieve comparable performance to the original regretmatching learning algorithm.

Keywords: cognitive radio, cooperative communication, relay selection, channel choice, regret-matching learning, correlated equilibrium.

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Authors: I Made Darmayuda, Chai Tshun Chuan Kevin, Je Minkyu

Abstract:

Plenty researches have reported techniques to harvest energy from piezoelectric transducer. In the earlier years, the researches mainly report linear energy harvesting techniques whereby interface circuitry is designed to have input impedance that match with the impedance of the piezoelectric transducer. In recent years non-linear techniques become more popular. The non-linear technique employs voltage waveform manipulation to boost the available-for-extraction energy at the time of energy transfer.  The fact that non-linear energy extraction provides larger available-for-extraction energy doesn’t mean the linear energy extraction is completely obsolete. In some scenarios, such as where initial power is not available, linear energy extraction is still preferred. A modified Buck Boost circuit which is capable of harvesting piezoelectric energy using both linear and non-linear techniques is reported in this paper. Efficiency of at least 64% can be achieved using this circuit. For linear extraction, the modified Buck Boost circuit is controlled using a fix frequency and duty cycle clock. A voltage sensor and a pulse generator are added as the controller for the non-linear extraction technique. 

Keywords: Buck boost, energy harvester, linear energy harvester, non-linear energy harvester, piezoelectric, synchronized charge extraction.

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Authors: M. Jaenen, M. de Bouw, A. Verdonck, M. Leus

Abstract:

During the interwar period artificial materials were often preferred, but many Antwerp architects relied on the application of wood for most of the interior finishing works and furnishings. Archival, literature and on site research of interwar suburban townhouses and the Belgian wood and furniture industry gave a new insight to the application of wood in the interwar interior. Many interwar designers favored the decorative values in all treatments of wood because of its warmth, comfort, good-wearing, and therefore, economic qualities. For the creation of a successful modern interior the texture and surface of the wood becomes as important as the color itself. This aesthetics valuation was the result of the modernization of the wood industry. The development of veneer and plywood gave the possibility to create strong, flat, long and plain wooden surfaces which are capable of retaining their shape. Also the modernization of cutting machines resulted in high quality and diversity in texture of veneer. The flat and plain plywood surfaces were modern decorated with all kinds of veneer-sliced options. In addition, wood species from the former Belgian Colony Congo were imported. Limba (Terminalia superba), kambala (Chlorophora excelsa), mubala (Pentaclethra macrophylla) and sapelli (Entandrophragma cylindricum) were used in the interior of many Antwerp interwar suburban town houses. From the thirties onwards Belgian wood firms established modern manufactures in Congo. There the local wood was dried, cut and prepared for exportation to the harbor of Antwerp. The presence of all kinds of strong and decorative Congolese wood products supported its application in the interwar interior design. The Antwerp architects combined them in their designs for doors, floors, stairs, built-in-furniture, wall paneling and movable furniture.

Keywords: Antwerp, Congo, furniture, interwar.

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Authors: K.Manimala, Dr.K.Selvi, R.Ahila

Abstract:

Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge financial and other losses. It is therefore necessary that critical loads be supplied with electricity of acceptable quality. Recognition of the presence of any disturbance and classifying any existing disturbance into a particular type is the first step in combating the problem. In this work two classes of AI methods for Power quality data mining are studied: Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). We show that SVMs are superior to ANNs in two critical respects: SVMs train and run an order of magnitude faster; and SVMs give higher classification accuracy.

Keywords: back propagation network, power quality, probabilistic neural network, radial basis function support vector machine

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Authors: Rossitza M. Setchi, Nikolaos Lagos

Abstract:

Problem solving has traditionally been one of the principal research areas for artificial intelligence. Yet, although artificial intelligence reasoning techniques have been employed in several product support systems, the benefit of integrating product support, knowledge engineering, and problem solving, is still unclear. This paper studies the synergy of these areas and proposes a knowledge engineering framework that integrates product support systems and artificial intelligence techniques. The framework includes four spaces; the data, problem, hypothesis, and solution ones. The data space incorporates the knowledge needed for structured reasoning to take place, the problem space contains representations of problems, and the hypothesis space utilizes a multimodal reasoning approach to produce appropriate solutions in the form of virtual documents. The solution space is used as the gateway between the system and the user. The proposed framework enables the development of product support systems in terms of smaller, more manageable steps while the combination of different reasoning techniques provides a way to overcome the lack of documentation resources.

Keywords: Knowledge engineering framework, product support, case-based reasoning, model-based reasoning, multimodal reasoning.

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Authors: M. Zeghid, M. Machhout, L. Khriji, A. Baganne, R. Tourki

Abstract:

With the fast evolution of digital data exchange, security information becomes much important in data storage and transmission. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. In this paper, we analyze the Advanced Encryption Standard (AES), and we add a key stream generator (A5/1, W7) to AES to ensure improving the encryption performance; mainly for images characterised by reduced entropy. The implementation of both techniques has been realized for experimental purposes. Detailed results in terms of security analysis and implementation are given. Comparative study with traditional encryption algorithms is shown the superiority of the modified algorithm.

Keywords: Cryptography, Encryption, Advanced EncryptionStandard (AES), ECB mode, statistical analysis, key streamgenerator.

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Authors: Hui-Yu Huang, Shih-Hsu Chang

Abstract:

In this paper, we propose a high capacity image hiding technology based on pixel prediction and the difference of modified histogram. This approach is used the pixel prediction and the difference of modified histogram to calculate the best embedding point. This approach can improve the predictive accuracy and increase the pixel difference to advance the hiding capacity. We also use the histogram modification to prevent the overflow and underflow. Experimental results demonstrate that our proposed method within the same average hiding capacity can still keep high quality of image and low distortion

Keywords: data hiding, predictor

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Authors: Cheng-Fang Huang, Meei-Ling Hung, Teh-Lu Liao, Her-Terng Yau, Jun-Juh Yan

Abstract:

The design of chaos-based secure communication via synchronized modified Chua-s systems is investigated in this paper. A continuous control law is proposed to ensure synchronization of the master and slave modified Chua-s systems by using the variable structure control technique. Particularly, the concept of extended systems is introduced such that a continuous control input is obtained to avoid chattering phenomenon. Then, it becomes possible to ensure that the message signal embedded in the transmitter can be recovered in the receiver.

Keywords: Chaos, Secure communication, Synchronization, Variable structure control (VSC)

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Authors: S. Al-Enezi, J. Samuel, A. Al-Banna

Abstract:

Polymer based membranes are one of the low-cost technologies available for the gas separation. Three major elements required for a commercial gas separating membrane are high permeability, high selectivity, and good mechanical strength. Poly(vinylidene fluoride) (PVDF) is a commercially available fluoropolymer and a widely used membrane material in gas separation devices since it possesses remarkable thermal, chemical stability, and excellent mechanical strength. The PVDF membrane was chemically modified by soaking in different ionic liquids and dried. The thermal behavior of modified membranes was investigated by differential scanning calorimetry (DSC), and thermogravimetry (TGA), and the results clearly show the best affinity between the ionic liquid and the polymer support. The porous structure of the PVDF membranes was clearly seen in the scanning electron microscopy (SEM) images. The CO₂ permeability of blended membranes was explored in comparison with the unmodified matrix. The ionic liquid immobilized in the hydrophobic PVDF support exhibited good performance for separations of CO₂/N₂. The improved permeability of modified membrane (PVDF-IL) is attributed to the high concentration of nitrogen rich imidazolium moieties.

Keywords: PVDF, gas permeability, polymer membrane, ionic liquid.

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