Search results for: content accuracy
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3326

Search results for: content accuracy

2966 A Case Study of Bee Algorithm for Ready Mixed Concrete Problem

Authors: W. Wongthatsanekorn, N. Matheekrieangkrai

Abstract:

This research proposes Bee Algorithm (BA) to optimize Ready Mixed Concrete (RMC) truck scheduling problem from single batch plant to multiple construction sites. This problem is considered as an NP-hard constrained combinatorial optimization problem. This paper provides the details of the RMC dispatching process and its related constraints. BA was then developed to minimize total waiting time of RMC trucks while satisfying all constraints. The performance of BA is then evaluated on two benchmark problems (3 and 5construction sites) according to previous researchers. The simulation results of BA are compared in term of efficiency and accuracy with Genetic Algorithm (GA) and all problems show that BA approach outperforms GA in term of efficiency and accuracy to obtain optimal solution. Hence, BA approach could be practically implemented to obtain the best schedule.

Keywords: Bee Colony Optimization, Ready Mixed Concrete Problem.

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2965 Application of Smooth Ergodic Hidden Markov Model in Text to Speech Systems

Authors: Armin Ghayoori, Faramarz Hendessi, Asrar Sheikh

Abstract:

In developing a text-to-speech system, it is well known that the accuracy of information extracted from a text is crucial to produce high quality synthesized speech. In this paper, a new scheme for converting text into its equivalent phonetic spelling is introduced and developed. This method is applicable to many applications in text to speech converting systems and has many advantages over other methods. The proposed method can also complement the other methods with a purpose of improving their performance. The proposed method is a probabilistic model and is based on Smooth Ergodic Hidden Markov Model. This model can be considered as an extension to HMM. The proposed method is applied to Persian language and its accuracy in converting text to speech phonetics is evaluated using simulations.

Keywords: Hidden Markov Models, text, synthesis.

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2964 A Family Cars- Life Cycle Cost (LCC)-Oriented Hybrid Modelling Approach Combining ANN and CBR

Authors: Xiaochuan Chen, Jianguo Yang, Beizhi Li

Abstract:

Design for cost (DFC) is a method that reduces life cycle cost (LCC) from the angle of designers. Multiple domain features mapping (MDFM) methodology was given in DFC. Using MDFM, we can use design features to estimate the LCC. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and emission volume. At the conceptual design stage, cars- LCC were estimated using back propagation (BP) artificial neural networks (ANN) method and case-based reasoning (CBR). Hamming space was used to measure the similarity among cases in CBR method. Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA) were used in ANN. The differences of LCC estimation model between CBR and artificial neural networks (ANN) were provided. ANN and CBR separately each method has its shortcomings. By combining ANN and CBR improved results accuracy was obtained. Firstly, using ANN selected some design features that affect LCC. Then using LCC estimation results of ANN could raise the accuracy of LCC estimation in CBR method. Thirdly, using ANN estimate LCC errors and correct errors in CBR-s estimation results if the accuracy is not enough accurate. Finally, economically family cars and sport utility vehicle (SUV) was given as LCC estimation cases using this hybrid approach combining ANN and CBR.

Keywords: case-based reasoning, life cycle cost (LCC), artificialneural networks (ANN), family cars

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2963 Performance Analysis of Genetic Algorithm with kNN and SVM for Feature Selection in Tumor Classification

Authors: C. Gunavathi, K. Premalatha

Abstract:

Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.

Keywords: F-Test, Gene Expression, Genetic Algorithm, k- Nearest-Neighbor, Microarray, Signal-to-Noise Ratio, Support Vector Machine, T-statistics, Tumor Classification.

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2962 Effective Design Parameters on the End Effect in Single-Sided Linear Induction Motors

Authors: A. Zare Bazghaleh, M. R. Naghashan, H. Mahmoudimanesh, M. R. Meshkatoddini

Abstract:

Linear induction motors are used in various industries but they have some specific phenomena which are the causes for some problems. The most important phenomenon is called end effect. End effect decreases efficiency, power factor and output force and unbalances the phase currents. This phenomenon is more important in medium and high speeds machines. In this paper a factor, EEF , is obtained by an accurate equivalent circuit model, to determine the end effect intensity. In this way, all of effective design parameters on end effect is described. Accuracy of this equivalent circuit model is evaluated by two dimensional finite-element analysis using ANSYS. The results show the accuracy of the equivalent circuit model.

Keywords: Linear induction motor, end effect, equivalent circuitmodel, finite-element method.

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2961 Antioxidant Properties and Nutritive Values of Raw and Cooked Pool Barb (Puntius sophore) of Eastern Himalayas

Authors: Ch. Sarojnalini, Wahengbam Sarjubala Devi

Abstract:

Antioxidant properties and nutritive values of raw and cooked Pool barb, Puntius sophore (Hamilton-Buchanan) of Eastern Himalayas, India were determined. Antioxidant activity of the methanol extract of the raw, steamed, fried and curried Pool barb was evaluated by using 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging assay. In DPPH scavenging assay the IC50 value of the raw, steamed, fried and curried Pool barb was 1.66 micro-gram/ml, 16.09 micro-gram/ml, 8.99 micro-gram/ml, 0.59 micro-gram/ml whereas the IC50 of the reference ascorbic acid was 46.66miro-gram/ml. These results showed that the fish have high antioxidant activity. Protein content was found highest in raw (20.50±0.08%) and lowest in curried (18.66±0.13%). Moisture content in raw, fried and curried was 76.35±0.09, 46.27±0.14 and 57.46±0.24 respectively. Lipid content was recorded 2.46±0.14% in raw and 21.76±0.10% in curried. Ash content varied from 12.57±0.11 to 22.53±0.07%. The total amino acids varied from 36.79±0.02 and 288.43±0.12 mg/100g. Eleven essential mineral elements were found abundant in all the samples. The samples had considerable amount of Fe ranging from 152.17 to 320.39 milli-gram/100gram, Ca 902.06 to 1356.02 milli-gram/100gram, Zn 91.07 to 138.14 milli-gram/100gram, K 193.25 to 261.56 milli-gram/100gram, Mg 225.06 to 229.10 milli-gram/100gram. Ni was not detected in the curried fish. The Mg and K contents were significantly decreased in frying method; however the Fe, Cu, Ca, Co and Mn contents were increased significantly in all the cooked samples. The Mg and Na contents were significantly increased in curried sample and the Cr content was decreased significantly (p<0.05) in all the cooked samples.

Keywords: Antioxidant property, Pool barb, minerals, amino acids, proximate composition, cooking methods.

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2960 Taguchi-Based Optimization of Surface Roughness and Dimensional Accuracy in Wire EDM Process with S7 Heat Treated Steel

Authors: Joseph C. Chen, Joshua Cox

Abstract:

This research focuses on the use of the Taguchi method to reduce the surface roughness and improve dimensional accuracy of parts machined by Wire Electrical Discharge Machining (EDM) with S7 heat treated steel material. Due to its high impact toughness, the material is a candidate for a wide variety of tooling applications which require high precision in dimension and desired surface roughness. This paper demonstrates that Taguchi Parameter Design methodology is able to optimize both dimensioning and surface roughness successfully by investigating seven wire-EDM controllable parameters: pulse on time (ON), pulse off time (OFF), servo voltage (SV), voltage (V), servo feed (SF), wire tension (WT), and wire speed (WS). The temperature of the water in the Wire EDM process is investigated as the noise factor in this research. Experimental design and analysis based on L18 Taguchi orthogonal arrays are conducted. This paper demonstrates that the Taguchi-based system enables the wire EDM process to produce (1) high precision parts with an average of 0.6601 inches dimension, while the desired dimension is 0.6600 inches; and (2) surface roughness of 1.7322 microns which is significantly improved from 2.8160 microns.

Keywords: Taguchi parameter design, surface roughness, dimensional accuracy, Wire EDM.

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2959 Genetic Content-Based MP3 Audio Watermarking in MDCT Domain

Authors: N. Moghadam, H. Sadeghi

Abstract:

In this paper a novel scheme for watermarking digital audio during its compression to MPEG-1 Layer III format is proposed. For this purpose we slightly modify some of the selected MDCT coefficients, which are used during MPEG audio compression procedure. Due to the possibility of modifying different MDCT coefficients, there will be different choices for embedding the watermark into audio data, considering robustness and transparency factors. Our proposed method uses a genetic algorithm to select the best coefficients to embed the watermark. This genetic selection is done according to the parameters that are extracted from the perceptual content of the audio to optimize the robustness and transparency of the watermark. On the other hand the watermark security is increased due to the random nature of the genetic selection. The information of the selected MDCT coefficients that carry the watermark bits, are saves in a database for future extraction of the watermark. The proposed method is suitable for online MP3 stores to pursue illegal copies of musical artworks. Experimental results show that the detection ratio of the watermarks at the bitrate of 128kbps remains above 90% while the inaudibility of the watermark is preserved.

Keywords: Content-Based Audio Watermarking, Genetic AudioWatermarking.

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2958 Feature Subset Selection approach based on Maximizing Margin of Support Vector Classifier

Authors: Khin May Win, Nan Sai Moon Kham

Abstract:

Identification of cancer genes that might anticipate the clinical behaviors from different types of cancer disease is challenging due to the huge number of genes and small number of patients samples. The new method is being proposed based on supervised learning of classification like support vector machines (SVMs).A new solution is described by the introduction of the Maximized Margin (MM) in the subset criterion, which permits to get near the least generalization error rate. In class prediction problem, gene selection is essential to improve the accuracy and to identify genes for cancer disease. The performance of the new method was evaluated with real-world data experiment. It can give the better accuracy for classification.

Keywords: Microarray data, feature selection, recursive featureelimination, support vector machines.

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2957 Blind Low Frequency Watermarking Method

Authors: Dimitar Taskovski, Sofija Bogdanova, Momcilo Bogdanov

Abstract:

We present a low frequency watermarking method adaptive to image content. The image content is analyzed and properties of HVS are exploited to generate a visual mask of the same size as the approximation image. Using this mask we embed the watermark in the approximation image without degrading the image quality. Watermark detection is performed without using the original image. Experimental results show that the proposed watermarking method is robust against most common image processing operations, which can be easily implemented and usually do not degrade the image quality.

Keywords: Blind, digital watermarking, low frequency, visualmask.

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2956 Co-composting Cow Manure with Food Waste: The Influence of Lipids Content

Authors: Neves, L., Ferreira, V., Oliveira, R.

Abstract:

Addition of an oily waste to a co-composting process of dairy cow manure with food waste, and the influence in the final product was evaluated. Three static composting piles with different substrates concentrations were assessed. Sawdust was also added to all composting piles to attain 60%, humidity at the beginning of the process. In pile 1, the co-substrates were the solid-phase of dairy cow manure, food waste and sawdust as bulking agent. In piles 2 and 3 there was an extra input of oily waste of 7 and 11% of the total volume, respectively, corresponding to 18 and 28% in dry weight. The results showed that the co-composting process was feasible even at the highest fat content. Another positive effect due to the oily waste addition was the requirement of extra humidity, due to the hydrophobic properties of this specific waste, which may imply reduced need of a bulking agent. Moreover, this study shows that composting can be a feasible way of adding value to fatty wastes. The three final composts presented very similar and suitable properties for land application.

Keywords: Cow manure, composting, food waste, lipids content.

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2955 Numerical Modeling of Benzene Transport in Andosol and Sand: Adequacy of Diffusion and Equilibrium Adsorption Equations

Authors: Ping Du, Masaki Sagehashi, Akihiko Terada, Masaaki Hosomi

Abstract:

Prediction of benzene transport in soil and volatilization from soil to the atmosphere is important for the preservation of human health and management of contaminated soils. The adequacy of a simple numerical model, assuming two-phase diffusion and equilibrium of liquid/solid adsorption, was investigated by experimental data of benzene concentration in a flux chamber (with headspace) where Andosol and sand were filled. Adsorption experiment for liquid phase was performed to determine an adsorption coefficient. Furthermore, adequacy of vapor phase adsorption was also studied through two runs of experiment using sand with different water content. The results show that the model adequately predicted benzene transport and volatilization from Andosol and sand with water content of 14.0%. In addition, the experiment additionally revealed that vapor phase adsorption should be considered in diffusion model for sand with very low water content.

Keywords: Benzene; Transport Model, Adsorption, Soil Contaminant.

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2954 Physicochemical Characterization of Waste from Vegetal Extracts Industry for Use as Briquettes

Authors: Maíra O. Palm, Cintia Marangoni, Ozair Souza, Noeli Sellin

Abstract:

Wastes from a vegetal extracts industry (cocoa, oak, Guarana and mate) were characterized by particle size, proximate and ultimate analysis, lignocellulosic fractions, high heating value, thermal analysis (Thermogravimetric analysis – TGA, and Differential thermal analysis - DTA) and energy density to evaluate their potential as biomass in the form of briquettes for power generation. All wastes presented adequate particle sizes to briquettes production. The wastes showed high moisture content, requiring previous drying for use as briquettes. Cocoa and oak wastes had the highest volatile matter contents with maximum mass loss at 310 ºC and 450 ºC, respectively. The solvents used in the aroma extraction process influenced in the moisture content of the wastes, which was higher for mate due to water has been used as solvent. All wastes showed an insignificant loss mass after 565 °C, hence resulting in low ash content. High carbon and hydrogen contents and low sulfur and nitrogen contents were observed ensuring a low generation of sulfur and nitrous oxides. Mate and cocoa exhibited the highest carbon and lignin content, and high heating value. The dried wastes had high heating value, from 17.1 MJ/kg to 20.8 MJ/kg. The results indicate the energy potential of wastes for use as fuel in power generation.

Keywords: Agro-industrial waste, biomass, briquettes, combustion.

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2953 Characterization of Candlenut Shells and Its Application to Remove Oil and Fine Solids of Produced Water in Nutshell Filters of Water Cleaning Plant

Authors: Annur Suhadi, Haris B. Harahap, Zaim Arrosyidi, Epan, Darmapala

Abstract:

Oilfields under waterflood often face the problem of plugging injectors either by internal filtration or external filter cake built up inside pore throats. The content of suspended solids shall be reduced to required level of filtration since corrective action of plugging is costly expensive. The performance of nutshell filters, where filtration takes place, is good using pecan and walnut shells. Candlenut shells were used instead of pecan and walnut shells since they were abundant in Indonesia, Malaysia, and East Africa. Physical and chemical properties of walnut, pecan, and candlenut shells were tested and the results were compared. Testing, using full-scale nutshell filters, was conducted to determine the oil content, turbidity, and suspended solid removal, which was based on designed flux rate. The performance of candlenut shells, which were deeply bedded in nutshell filters for filtration process, was monitored. Cleaned water outgoing nutshell filters had total suspended solids of 17 ppm, while oil content could be reduced to 15.1 ppm. Turbidity, using candlenut shells, was below the specification for injection water, which was less than 10 Nephelometric Turbidity Unit (NTU). Turbidity of water, outgoing nutshell filter, was ranged from 1.7-5.0 NTU at various dates of operation. Walnut, pecan, and candlenut shells had moisture content of 8.98 wt%, 10.95 wt%, and 9.95 wt%, respectively. The porosity of walnut, pecan, and candlenut shells was significantly affected by moisture content. Candlenut shells had property of toluene solubility of 7.68 wt%, which was much higher than walnut shells, reflecting more crude oil adsorption. The hardness of candlenut shells was 2.5-3 Mohs, which was close to walnut shells’ hardness. It was advantage to guarantee the cleaning filter cake by fluidization process during backwashing.

Keywords: Candlenut shells, walnut shells, pecan shells, nutshell filter, filtration.

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2952 The Selection of the Nearest Anchor Using Received Signal Strength Indication (RSSI)

Authors: Hichem Sassi, Tawfik Najeh, Noureddine Liouane

Abstract:

The localization information is crucial for the operation of WSN. There are principally two types of localization algorithms. The Range-based localization algorithm has strict requirements on hardware, thus is expensive to be implemented in practice. The Range-free localization algorithm reduces the hardware cost. However, it can only achieve high accuracy in ideal scenarios. In this paper, we locate unknown nodes by incorporating the advantages of these two types of methods. The proposed algorithm makes the unknown nodes select the nearest anchor using the Received Signal Strength Indicator (RSSI) and choose two other anchors which are the most accurate to achieve the estimated location. Our algorithm improves the localization accuracy compared with previous algorithms, which has been demonstrated by the simulating results.

Keywords: WSN, localization, DV-hop, RSSI.

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2951 Property of Polyurethane: from Soy-derived Phosphate Ester

Authors: Flora Elvistia Firdaus

Abstract:

Polyurethane foams (PUF) were formed by a chemical reaction of polyol and isocyanate. The polyol was manufactured by ring-opening hydrolysis of epoxidized soybean oil in the presence of phosphoric acid under varying experimental conditions. Other factors in the foam formulation such as water content and surfactant were kept constant. The effect of the amount of solvents, phosphoric acid, and their derivates in the foam formulation on the properties of polyurethane foams were studied. The properties of the material were measured via a number of parameters, which are water content of prepared polyol, polymer density and cellular structures.

Keywords: soy, polyurethane, phosporic acid

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2950 Application of BP Neural Network Model in Sports Aerobics Performance Evaluation

Authors: Shuhe Shao

Abstract:

This article provides partial evaluation index and its standard of sports aerobics, including the following 12 indexes: health vitality, coordination, flexibility, accuracy, pace, endurance, elasticity, self-confidence, form, control, uniformity and musicality. The three-layer BP artificial neural network model including input layer, hidden layer and output layer is established. The result shows that the model can well reflect the non-linear relationship between the performance of 12 indexes and the overall performance. The predicted value of each sample is very close to the true value, with a relative error fluctuating around of 5%, and the network training is successful. It shows that BP network has high prediction accuracy and good generalization capacity if being applied in sports aerobics performance evaluation after effective training.

Keywords: BP neural network, sports aerobics, performance, evaluation.

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2949 Alternative Approach toward Waste Treatment: Biodrying for Solid Waste in Malaysia

Authors: Nurul' Ain Ab Jalil, Hassan Basri

Abstract:

This paper reviews the objectives, methods and results of previous studies on biodrying of solid waste in several countries. Biodrying of solid waste is a novel technology in developing countries such as in Malaysia where high moisture content in organic waste makes the segregation process for recycling purposes complicated and diminishes the calorific value for the use of fuel source. In addition, the high moisture content also encourages the breeding of vectors and disease-bearing animals. From the laboratory results, the average moisture content of organic waste, paper, plastics and metals are 58.17%, 37.93%, 29.79% and 1.03% respectively for UKM campus. Biodrying of solid waste is a simple method of waste treatment as well as a cost-efficient technology to dry the solid waste. The process depends on temperature monitoring and air flow control along with the natural biodegradable process of organic waste. This review shows that the biodrying of solid waste method has high potential in treatment and recycling of solid waste, be useful for biodrying study and implementation in Malaysia.

Keywords: Biodrying of solid waste, Organic waste, Fuel source.

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2948 Stochastic Learning Algorithms for Modeling Human Category Learning

Authors: Toshihiko Matsuka, James E. Corter

Abstract:

Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.

Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.

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2947 Face Recognition Using Principal Component Analysis, K-Means Clustering, and Convolutional Neural Network

Authors: Zukisa Nante, Wang Zenghui

Abstract:

Face recognition is the problem of identifying or recognizing individuals in an image. This paper investigates a possible method to bring a solution to this problem. The method proposes an amalgamation of Principal Component Analysis (PCA), K-Means clustering, and Convolutional Neural Network (CNN) for a face recognition system. It is trained and evaluated using the ORL dataset. This dataset consists of 400 different faces with 40 classes of 10 face images per class. Firstly, PCA enabled the usage of a smaller network. This reduces the training time of the CNN. Thus, we get rid of the redundancy and preserve the variance with a smaller number of coefficients. Secondly, the K-Means clustering model is trained using the compressed PCA obtained data which select the K-Means clustering centers with better characteristics. Lastly, the K-Means characteristics or features are an initial value of the CNN and act as input data. The accuracy and the performance of the proposed method were tested in comparison to other Face Recognition (FR) techniques namely PCA, Support Vector Machine (SVM), as well as K-Nearest Neighbour (kNN). During experimentation, the accuracy and the performance of our suggested method after 90 epochs achieved the highest performance: 99% accuracy F1-Score, 99% precision, and 99% recall in 463.934 seconds. It outperformed the PCA that obtained 97% and KNN with 84% during the conducted experiments. Therefore, this method proved to be efficient in identifying faces in the images.

Keywords: Face recognition, Principal Component Analysis, PCA, Convolutional Neural Network, CNN, Rectified Linear Unit, ReLU, feature extraction.

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2946 Using Fly Ash as a Reinforcement to Increase Wear Resistance of Pure Magnesium

Authors: E. Karakulak, R. Yamanoğlu, M. Zeren

Abstract:

In the current study, fly ash obtained from a thermal power plant was used as reinforcement in pure magnesium. The composite materials with different fly ash contents were produced with powder metallurgical methods. Powder mixtures were sintered at 540oC under 30 MPa pressure for 15 minutes in a vacuum assisted hot press. Results showed that increasing ash content continuously increases hardness of the composite. On the other hand, minimum wear damage was obtained at 2 wt. % ash content. Addition of higher level of fly ash results with formation of cracks in the matrix and increases wear damage of the material.

Keywords: Mg composite, fly ash, wear, powder metallurgy.

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2945 Effect of Steel Fibers on Flexural Behavior of Normal and High Strength Concrete

Authors: K. M. Aldossari, W. A. Elsaigh, M. J. Shannag

Abstract:

An experimental study was conducted to investigate the effect of hooked-end steel fibers on the flexural behavior of normal and high strength concrete matrices. The fibers content appropriate for the concrete matrices investigated was also determined based on flexural tests on standard prisms. Parameters investigated include: matrix compressive strength ranging from 45 MPa to 70 MPa, corresponding to normal and high strength concrete matrices respectively; fibers volume fraction including 0, 0.5%, 0.76% and 1%, equivalent to 0, 40, 60, and 80 kg/m3 of hooked-end steel fibers respectively. Test results indicated that flexural strength and toughness of normal and high strength concrete matrices were significantly improved with the increase in the fibers content added; whereas a slight improvement in compressive strength was observed for the same matrices. Furthermore, the test results indicated that the effect of increasing the fibers content was more pronounced on increasing the flexural strength of high strength concrete than that of normal concrete.

Keywords: Concrete, flexural strength, toughness, steel fibers.

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2944 Acoustic Source Localization Based On the Extended Kalman Filter for an Underwater Vehicle with a Pair of Hydrophones

Authors: ByungHoon Kang, Jeawook Shin, Ju-man Song, Hyun-Taek Choi, PooGyeon Park

Abstract:

In this study, we consider a special situation that only a pair of hydrophone on a moving underwater vehicle is available to localize a fixed acoustic source of far distance. The trigonometry can be used in this situation by using two different DOA of different locations. Notice that the distance between the two locations should be measured. Therefore, we assume that the vehicle is sailing straightly and the moving distance for each unit time is measured continuously. However, the accuracy of the localization using the trigonometry is highly dependent to the accuracy of DOAs and measured moving distances. Therefore, we proposed another method based on the extended Kalman filter that gives more robust and accurate localization result.

Keywords: Localization, acoustic, underwater, extended Kalman filter.

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2943 Nutritional Composition of Iranian Desi and Kabuli Chickpea (Cicer Arietinum L.) Cultivars in Autumn Sowing

Authors: Khosro Mohammadi

Abstract:

The grain quality of chickpea in Iran is low and instable, which may be attributed to the evolution of cultivars with a narrow genetic base making them vulnerable to biotic stresses. Four chickpea varieties from diverse geographic origins were chosen and arranged in a randomized complete block design. Mesorhizobium sp. cicer strain SW7 was added to all the chickpea seeds. Chickpea seeds were planted on October 9, 2013. Each genotype was sown 5 m in length, with 35 cm inter-row spacing, in 3 rows. Weeds were removed manually in all plots. Results showed that Analysis of variance on the studied traits showed significant differences among genotypes for N, P, K and Fe contents of chickpea, but there is not a significant difference among Ca, Zn and Mg continents of chickpea. The experimental coefficient of variation (CV) varied from 7.3 to 15.8. In general, the CV value lower than 20% is considered to be good, indicating the accuracy of conducted experiments. The highest grain N was observed in Hashem and Jam cultivars. The highest grain P was observed in Jam cultivar. Phosphorus content (mg/100g) ranged from 142.3 to 302.3 with a mean value of 221.3. The negative correlation (-0.126) was observed between the N and P of chickpea cultivars. The highest K and Fe contents were observed in Jam cultivar.

Keywords: Cultivar, genotype, nitrogen, nutrient, yield.

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2942 ELD79-LGD2006 Transformation Techniques Implementation and Accuracy Comparison in Tripoli Area, Libya

Authors: Jamal A. Gledan, Othman A. Azzeidani

Abstract:

During the last decade, Libya established a new Geodetic Datum called Libyan Geodetic Datum 2006 (LGD 2006) by using GPS, whereas the ground traversing method was used to establish the last Libyan datum which was called the Europe Libyan Datum 79 (ELD79). The current research paper introduces ELD79 to LGD2006 coordinate transformation technique, the accurate comparison of transformation between multiple regression equations and the three – parameters model (Bursa-Wolf). The results had been obtained show that the overall accuracy of stepwise multi regression equations is better than that can be determined by using Bursa-Wolf transformation model.

Keywords: Geodetic datum, horizontal control points, traditional similarity transformation model, unconventional transformation techniques.

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2941 Drafting the Design and Development of Micro- Controller Based Portable Soil Moisture Sensor for Advancement in Agro Engineering

Authors: Guneet Mander, Gurinder Pal Singh

Abstract:

Moisture is an important consideration in many aspects ranging from irrigation, soil chemistry, golf course, corrosion and erosion, road conditions, weather predictions, livestock feed moisture levels, water seepage etc. Vegetation and crops always depend more on the moisture available at the root level than on precipitation occurrence. In this paper, design of an instrument is discussed which tells about the variation in the moisture contents of soil. This is done by measuring the amount of water content in soil by finding the variation in capacitance of soil with the help of a capacitive sensor. The greatest advantage of soil moisture sensor is reduced water consumption. The sensor is also be used to set lower and upper threshold to maintain optimum soil moisture saturation and minimize water wilting, contributes to deeper plant root growth ,reduced soil run off /leaching and less favorable condition for insects and fungal diseases. Capacitance method is preferred because, it provides absolute amount of water content and also measures water content at any depth.

Keywords: Capacitive Sensors, aluminum, Water, Irrigation.

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2940 Effects of Paste Content on Flow Characteristics of SCC Containing Local Natural Pozzolan

Authors: Muhammad Nouman Haral, Abdulaziz I. Al-Negheimesh, Galal Fares, Mohammad Iqbal Khan, Abdulrahman M. Alhozaimy

Abstract:

Natural pozzolan (NP) is one of the potential prehistoric alternative binders in the construction industry. It has been investigated as cement replacement in ordinary concrete by several researchers for many purposes. Various supplementary cementitious materials (SCMs) such as fly ash, limestone dust and silica fume are widely used in the production of SCC; however, limited studies to address the effect of NP on the properties of SCC are documented. The current research is composed of different SCC paste and concrete mixtures containing different replacement levels of local NP as an alternative SCM. The effect of volume of paste containing different amounts of local NP related to W/B ratio and cement content on SCC fresh properties was assessed. The variations in the fresh properties of SCC paste and concrete represented by slump flow (flowability) and the flow rate were determined and discussed. The results indicated that the flow properties of SCC paste and concrete mixtures, at their optimized superplasticizer dosages, were affected by the binder content of local NP and the total volume fraction of SCC paste.

Keywords: Binder, fresh properties, natural pozzolan, paste, SCC.

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2939 Slice Bispectrogram Analysis-Based Classification of Environmental Sounds Using Convolutional Neural Network

Authors: Katsumi Hirata

Abstract:

Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: Bispectrum, convolutional neural network, environmental sound, slice bispectrogram, spectrogram.

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2938 A Recommender System Fusing Collaborative Filtering and User’s Review Mining

Authors: Seulbi Choi, Hyunchul Ahn

Abstract:

Collaborative filtering (CF) algorithm has been popularly used for recommender systems in both academic and practical applications. It basically generates recommendation results using users’ numeric ratings. However, the additional use of the information other than user ratings may lead to better accuracy of CF. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's review can be regarded as the new informative source for identifying user's preference with accuracy. Under this background, this study presents a hybrid recommender system that fuses CF and user's review mining. Our system adopts conventional memory-based CF, but it is designed to use both user’s numeric ratings and his/her text reviews on the items when calculating similarities between users.

Keywords: Recommender system, collaborative filtering, text mining, review mining.

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2937 Bi-Lateral Comparison between NIS-Egypt and NMISA-South Africa for the Calibration of an Optical Spectrum Analyzer

Authors: Osama Terra, Hatem Hussein, Adriaan Van Brakel

Abstract:

Dense wavelength division multiplexing (DWDM) technology requires tight specification and therefore measurement of wavelength accuracy and stability of the telecommunication lasers. Thus, calibration of the used Optical Spectrum Analyzers (OSAs) that are used to measure wavelength is of a great importance. Proficiency testing must be performed on such measuring activity to insure the accuracy of the measurement results. In this paper, a new comparison scheme is introduced to test the performance of such calibrations. This comparison scheme is implemented between NIS-Egypt and NMISA-South Africa for the calibration of the wavelength scale of an OSA. Both institutes employ reference gas cell to calibrate OSA according to the standard IEC/ BS EN 62129 (2006). The result of this comparison is compiled in this paper.

Keywords: OSA calibration, HCN gas cell, DWDM technology, wavelength measurement.

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