Search results for: loss function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2994

Search results for: loss function

2904 Time-Domain Analysis Approaches of Soil-Structure Interaction: A Comparative Study

Authors: Abdelrahman Taha, Niloofar Malekghaini, Hamed Ebrahimian, Ramin Motamed

Abstract:

This paper compares the substructure and direct approaches for soil-structure interaction (SSI) analysis in the time domain. In the substructure approach, the soil domain is replaced by a set of springs and dashpots, also referred to as the impedance function, derived through the study of the behavior of a massless rigid foundation. The impedance function is inherently frequency dependent, i.e., it varies as a function of the frequency content of the structural response. To use the frequency-dependent impedance function for time-domain SSI analysis, the impedance function is approximated at the fundamental frequency of the coupled soil-structure system. To explore the potential limitations of the substructure modeling process, a two-dimensional (2D) reinforced concrete frame structure is modeled and analyzed using the direct and substructure approaches. The results show discrepancy between the simulated responses of the direct and substructure models. It is concluded that the main source of discrepancy is likely attributed to the way the impedance functions are calculated, i.e., assuming a massless rigid foundation without considering the presence of the superstructure. Hence, a refined impedance function, considering the presence of the superstructure, shall alternatively be developed. This refined impedance function is expected to improve the simulation accuracy of the substructure approach.

Keywords: Direct approach, impedance function, massless rigid foundation, soil-structure interaction, substructure approach.

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2903 Probabilistic Robustness Assessment of Structures under Sudden Column-Loss Scenario

Authors: Ali Y Al-Attraqchi, P. Rajeev, M. Javad Hashemi, Riadh Al-Mahaidi

Abstract:

This paper presents a probabilistic incremental dynamic analysis (IDA) of a full reinforced concrete building subjected to column loss scenario for the assessment of progressive collapse. The IDA is chosen to explicitly account for uncertainties in loads and system capacity. Fragility curves are developed to predict the probability of progressive collapse given the loss of one or more columns. At a broader scale, it will also provide critical information needed to support the development of a new generation of design codes that attempt to explicitly quantify structural robustness.

Keywords: Incremental dynamic analysis, progressive collapse, structural engineering, pushdown analysis.

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2902 Function Approximation with Radial Basis Function Neural Networks via FIR Filter

Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

Abstract:

Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore , the number of centers will be considered since it affects the performance of approximation.

Keywords: Extended kalmin filter (EKF), classification problem, radial basis function networks (RBFN), finite impulse response (FIR)filter.

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2901 Learning Flexible Neural Networks for Pattern Recognition

Authors: A. Mirzaaghazadeh, H. Motameni, M. Karshenas, H. Nematzadeh

Abstract:

Learning the gradient of neuron's activity function like the weight of links causes a new specification which is flexibility. In flexible neural networks because of supervising and controlling the operation of neurons, all the burden of the learning is not dedicated to the weight of links, therefore in each period of learning of each neuron, in fact the gradient of their activity function, cooperate in order to achieve the goal of learning thus the number of learning will be decreased considerably. Furthermore, learning neurons parameters immunes them against changing in their inputs and factors which cause such changing. Likewise initial selecting of weights, type of activity function, selecting the initial gradient of activity function and selecting a fixed amount which is multiplied by gradient of error to calculate the weight changes and gradient of activity function, has a direct affect in convergence of network for learning.

Keywords: Back propagation, Flexible, Gradient, Learning, Neural network, Pattern recognition.

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2900 Effect of Modeling of Hydraulic Form Loss Coefficient to Break on Emergency Core Coolant Bypass

Authors: Young S. Bang, Dong H. Yoon, Seung H. Yoo

Abstract:

Emergency Core Coolant Bypass (ECC Bypass) has been regarded as an important phenomenon to peak cladding temperature of large-break loss-of-coolant-accidents (LBLOCA) in nuclear power plants (NPP). A modeling scheme to address the ECC Bypass phenomena and the calculation of LBLOCA using that scheme are discussed in the present paper. A hydraulic form loss coefficient (HFLC) from the reactor vessel downcomer to the broken cold leg is predicted by the computational fluid dynamics (CFD) code with a variation of the void fraction incoming from the downcomer. The maximum, mean, and minimum values of FLC are derived from the CFD results and are incorporated into the LBLOCA calculation using a system thermal-hydraulic code, MARS-KS. As a relevant parameter addressing the ECC Bypass phenomena, the FLC to the break and its range are proposed.

Keywords: CFD analysis, ECC Bypass, hydraulic form loss coefficient, system thermal-hydraulic code.

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2899 Characterization of Three Photodetector Types for Computed Tomography Dosimetry

Authors: C. M. M. Paschoal, D. do N. Souza, L. A. P. Santos

Abstract:

In this study three commercial semiconductor devices were characterized in the laboratory for computed tomography dosimetry: one photodiode and two phototransistors. It was evaluated four responses to the irradiation: dose linearity, energy dependence, angular dependence and loss of sensitivity after X ray exposure. The results showed that the three devices have proportional response with the air kerma; the energy dependence displayed for each device suggests that some calibration factors would be applied for each one; the angular dependence showed a similar pattern among the three electronic components. In respect to the fourth parameter analyzed, one phototransistor has the highest sensitivity however it also showed the greatest loss of sensitivity with the accumulated dose. The photodiode was the device with the smaller sensitivity to radiation, on the other hand, the loss of sensitivity after irradiation is negligible. Since high accuracy is a desired feature for a dosimeter, the photodiode can be the most suitable of the three devices for dosimetry in tomography. The phototransistors can also be used for CT dosimetry, however it would be necessary a correction factor due to loss of sensitivity with accumulated dose.

Keywords: Dosimetry, computed tomography, phototransistor, photodiode

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2898 Certain Conditions for Strongly Starlike and Strongly Convex Functions

Authors: Sukhwinder Singh Billing, Sushma Gupta, Sukhjit Singh Dhaliwal

Abstract:

In the present paper, we investigate a differential subordination involving multiplier transformation related to a sector in the open unit disk E = {z : |z| < 1}. As special cases to our main result, certain sufficient conditions for strongly starlike and strongly convex functions are obtained.

Keywords: Analytic function, Multiplier transformation, Strongly starlike function, Strongly convex function.

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2897 Determination of Soil Loss by Erosion in Different Land Covers Categories and Slope Classes in Bovilla Watershed, Tirana, Albania

Authors: Valmir Baloshi, Fran Gjoka, Nehat Çollaku, Elvin Toromani

Abstract:

As a sediment production mechanism, soil erosion is the main environmental threat to the Bovilla watershed, including the decline of water quality of the Bovilla reservoir that provides drinking water to Tirana city (the capital of Albania). Therefore, an experiment with 25 erosion plots for soil erosion monitoring has been set up since June 2017. The aim was to determine the soil loss on plot and watershed scale in Bovilla watershed (Tirana region) for implementation of soil and water protection measures or payments for ecosystem services (PES) programs. The results of erosion monitoring for the period June 2017 - May 2018 showed that the highest values of surface runoff were noted in bare land of 38829.91 liters on slope of 74% and the lowest values in forest land of 12840.6 liters on slope of 64% while the highest values of soil loss were found in bare land of 595.15 t/ha on slope of 62% and lowest values in forest land of 18.99 t/ha on slope of 64%. These values are much higher than the average rate of soil loss in the European Union (2.46 ton/ha/year). In the same sloping class, the soil loss was reduced from orchard or bare land to the forest land, and in the same category of land use, the soil loss increased with increasing land slope. It is necessary to conduct chemical analyses of sediments to determine the amount of chemical elements leached out of the soil and end up in the reservoir of Bovilla. It is concluded that PES programs should be implemented for rehabilitation of sub-watersheds Ranxe, Vilez and Zall-Bastar of the Bovilla watershed with valuable conservation practices.

Keywords: ANOVA, Bovilla, land cover, slope, soil loss, watershed management.

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2896 Development and Usability Assessment of a Connected Resistance Exercise Band Application for Strength-Monitoring

Authors: J. A. Batsis, G. G. Boateng, L. M. Seo, C. L. Petersen, K. L. Fortuna, E. V. Wechsler, R. J. Peterson, S. B. Cook, D. Pidgeon, R. S. Dokko, R. J. Halter, D. F. Kotz

Abstract:

Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting are fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time, and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults with obesity participating in a weight-loss intervention (n=20). The system was favorable, acceptable and provided iterative information that could assist in future deployment on ubiquitous platforms. Our formative work provides the foundation to deliver home-based monitoring interventions in a high-risk, older adult population.

Keywords: Application, mHealth, older adult, resistance exercise band, sarcopenia.

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2895 Customer Segmentation in Foreign Trade based on Clustering Algorithms Case Study: Trade Promotion Organization of Iran

Authors: Samira Malekmohammadi Golsefid, Mehdi Ghazanfari, Somayeh Alizadeh

Abstract:

The goal of this paper is to segment the countries based on the value of export from Iran during 14 years ending at 2005. To measure the dissimilarity among export baskets of different countries, we define Dissimilarity Export Basket (DEB) function and use this distance function in K-means algorithm. The DEB function is defined based on the concepts of the association rules and the value of export group-commodities. In this paper, clustering quality function and clusters intraclass inertia are defined to, respectively, calculate the optimum number of clusters and to compare the functionality of DEB versus Euclidean distance. We have also study the effects of importance weight in DEB function to improve clustering quality. Lastly when segmentation is completed, a designated RFM model is used to analyze the relative profitability of each cluster.

Keywords: Customers segmentation, Customer relationship management, Clustering, Data Mining

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2894 Simulation of Loss-of-Flow Transient in a Radiant Steam Boiler with Relap5/Mod3.2

Authors: A.L.Deghal.Cheridi, A.Chaker, A.Loubar

Abstract:

loss of feedwater accident is one of the frequently sever accidents in steam boiler facilities. It threatens the system structural integrity and generates serious hazards and economic loses. The safety analysis of the thermal installations, based extensively on the numeric simulation. The simulation analysis using realistic computer codes like Relap5/Mod3.2 will help understand steam boiler thermal-hydraulic behavior during normal and abnormal conditions. In this study, we are interested on the evaluation of the radiant steam boiler assessment and response to loss-of-feedwater accident. Pressure, temperature and flow rate profiles are presented in various steam boiler system components. The obtained results demonstrate the importance and capability of the Relap5/Mod3.2 code in the thermal-hydraulic analysis of the steam boiler facilities.

Keywords: Radiant steam boiler, Relap5/Mod3.2 code system, Steady-state simulation, Transient simulation, Loss of feedwateraccident

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2893 Super-ellipsoidal Potential Function for Autonomous Collision Avoidance of a Teleoperated UAV

Authors: Mohammed Qasim, Kyoung-Dae Kim

Abstract:

In this paper, we present the design of the super-ellipsoidal potential function (SEPF), that can be used for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of SEPF, we have the full control over the shape and size of the potential function. In particular, we can adjust the length, width, height, and the amount of flattening at the tips of the potential function so that the collision avoidance motion vector generated from the potential function can be adjusted accordingly. Based on the idea of the SEPF, we also propose an approach for the local autonomy of a UAV for its collision avoidance when the UAV is teleoperated by a human operator. In our proposed approach, a teleoperated UAV can not only avoid collision autonomously with other surrounding objects but also track the operator’s control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAVs collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation of quadrotor UAV teleoperation using virtual robot experimentation platform (v-rep) and Matlab programs.

Keywords: Artificial potential function, autonomy, collision avoidance, teleoperation, quadrotor, UAV.

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2892 Performance Evaluation of Complex Valued Neural Networks Using Various Error Functions

Authors: Anita S. Gangal, P. K. Kalra, D. S. Chauhan

Abstract:

The backpropagation algorithm in general employs quadratic error function. In fact, most of the problems that involve minimization employ the Quadratic error function. With alternative error functions the performance of the optimization scheme can be improved. The new error functions help in suppressing the ill-effects of the outliers and have shown good performance to noise. In this paper we have tried to evaluate and compare the relative performance of complex valued neural network using different error functions. During first simulation for complex XOR gate it is observed that some error functions like Absolute error, Cauchy error function can replace Quadratic error function. In the second simulation it is observed that for some error functions the performance of the complex valued neural network depends on the architecture of the network whereas with few other error functions convergence speed of the network is independent of architecture of the neural network.

Keywords: Complex backpropagation algorithm, complex errorfunctions, complex valued neural network, split activation function.

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2891 Characterization and Modeling of Packet Loss of a VoIP Communication

Authors: L. Estrada, D. Torres, H. Toral

Abstract:

In this work, a characterization and modeling of packet loss of a Voice over Internet Protocol (VoIP) communication is developed. The distributions of the number of consecutive received and lost packets (namely gap and burst) are modeled from the transition probabilities of two-state and four-state model. Measurements show that both models describe adequately the burst distribution, but the decay of gap distribution for non-homogeneous losses is better fit by the four-state model. The respective probabilities of transition between states for each model were estimated with a proposed algorithm from a set of monitored VoIP calls in order to obtain representative minimum, maximum and average values for both models.

Keywords: Packet loss, gap and burst distribution, Markovchain, VoIP measurements.

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2890 On the Numbers of Various Young Tableaux

Authors: Hsuan-Chu Li

Abstract:

We demonstrate a way to count the number of Young tableau u of shape λ = (k, k,L, k) with | λ |= lk by expanding Schur function. This result gives an answer to the question that was put out by Jenny Buontempo and Brian Hopkins.

Keywords: Young tableau, Schur function.

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2889 A New Quadrature Rule Derived from Spline Interpolation with Error Analysis

Authors: Hadi Taghvafard

Abstract:

We present a new quadrature rule based on the spline interpolation along with the error analysis. Moreover, some error estimates for the reminder when the integrand is either a Lipschitzian function, a function of bounded variation or a function whose derivative belongs to Lp are given. We also give some examples to show that, practically, the spline rule is better than the trapezoidal rule.

Keywords: Quadrature, Spline interpolation, Trapezoidal rule, Numericalintegration, Error analysis.

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2888 Estimation of the Upper Tail Dependence Coefficient for Insurance Loss Data Using an Empirical Copula-Based Approach

Authors: Adrian O’Hagan, Robert McLoughlin

Abstract:

Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.

Keywords: Empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient.

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2887 Mapping Semantic Networks to Undirected Networks

Authors: Marko A. Rodriguez

Abstract:

There exists an injective, information-preserving function that maps a semantic network (i.e a directed labeled network) to a directed network (i.e. a directed unlabeled network). The edge label in the semantic network is represented as a topological feature of the directed network. Also, there exists an injective function that maps a directed network to an undirected network (i.e. an undirected unlabeled network). The edge directionality in the directed network is represented as a topological feature of the undirected network. Through function composition, there exists an injective function that maps a semantic network to an undirected network. Thus, aside from space constraints, the semantic network construct does not have any modeling functionality that is not possible with either a directed or undirected network representation. Two proofs of this idea will be presented. The first is a proof of the aforementioned function composition concept. The second is a simpler proof involving an undirected binary encoding of a semantic network.

Keywords: general-modeling, multi-relational networks, semantic networks

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2886 The Kinetic of Biodegradation Lignin in Water Hyacinth (Eichhornia Crassipes) by Phanerochaete Chrysosporium using Solid State Fermentation (SSF) Method for Bioethanol Production, Indonesia

Authors: Eka Sari, Siti Syamsiah, Hary Sulistyo, Muslikhin

Abstract:

Lignocellulosic materials are considered the most abundant renewable resource available for the Bioethanol Production. Water Hyacinth is one of potential raw material of the world-s worst aquatic plant as a feedstock to produce Bioethanol. The purposed this research is obtain reduced of matter for biodegradation lignin in Biological pretreatment with White Rot Fungi eg. Phanerochaete Chrysosporium using Solid state Fermentation methods. Phanerochaete Chrysosporium is known to have the best ability to degraded lignin, but simultaneously it can also degraded cellulose and hemicelulose. During 8 weeks incubation, water hyacinth occurred loss of weight reached 34,67%, while loss of lignin reached 67,21%, loss of cellulose reached 11,01% and loss of hemicellulose reached 36,56%. The kinetic of losses lignin using regression linear plot, the results is obtained constant rate (k) of reduction lignin is -0.1053 and the equation of reduction of lignin is y = wo - 0, 1.53 x

Keywords: Biodegradation, lignin, PhanerochaeteChrysosporium, SSF, Water Hyacinth, Bioethanol

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2885 Improved MARS Ciphering Using a Metamorphic-Enhanced Function

Authors: Moataz M. Naguib, Hatem Khater, A. Baith Mohamed

Abstract:

MARS is a shared-key (symmetric) block cipher algorithm supporting 128-bit block size and a variable key size of between 128 and 448 bits. MARS has a several rounds of cryptographic core that is designed to take advantage of the powerful results for improving security/performance tradeoff over existing ciphers. In this work, a new function added to improve the ciphering process it is called, Meta-Morphic function. This function use XOR, Rotating, Inverting and No-Operation logical operations before and after encryption process. The aim of these operations is to improve MARS cipher process and makes a high confusion criterion for the Ciphertext.

Keywords: AES, MARS, Metamorphic, Cryptography, Block Cipher.

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2884 Advanced Hybrid Particle Swarm Optimization for Congestion and Power Loss Reduction in Distribution Networks with High Distributed Generation Penetration through Network Reconfiguration

Authors: C. Iraklis, G. Evmiridis, A. Iraklis

Abstract:

Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: Congestion, distribution networks, loss reduction, particle swarm optimization, smart grid.

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2883 Use of Gaussian-Euclidean Hybrid Function Based Artificial Immune System for Breast Cancer Diagnosis

Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

Abstract:

Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

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2882 Indigenous Dayak People’s Perceptions of Wildlife Loss and Gain Related to Oil Palm Development

Authors: A. Sunkar, A. Saraswati, Y. Santosa

Abstract:

Controversies surrounding the impacts of oil palm plantations have resulted in some heated debates, especially concerning biodiversity loss and indigenous people well-being. The indigenous people of Dayak generally used wildlife to fulfill their daily needs thus were assumed to have experienced negative impacts due to oil palm developments within and surrounding their settlement areas. This study was conducted to identify the characteristics of the Dayak community settled around an oil palm plantation, to determine their perceptions of wildlife loss or gain as the results of the development of oil palm plantations, and to identify the determinant characteristic of the perceptions. The research was conducted on March 2018 in Nanga Tayap and Tajok Kayong Villages, which were located around the oil palm plantation of NTYE of Ketapang, West Kalimantan-Indonesia. Data were collected through in depth-structured interview, using closed and semi-open questionnaires and three-scale Likert statements. Interviews were conducted with 74 respondents using accidental sampling, and categorized into respondents who were dependent on oil palm for their livelihoods and those who were not. Data were analyzed using quantitative statistics method, Likert Scale, Chi-Square Test, Spearman Test, and Mann-Whitney Test. The research found that the indigenous Dayak people were aware of wildlife species loss and gain since the establishment of the plantation. Nevertheless, wildlife loss did not affect their social, economic, and cultural needs since they could find substitutions. It was found that prior to the plantation’s development, the local Dayak communities were already slowly experiencing some livelihood transitions through local village development. The only determinant characteristic of the community that influenced their perceptions of wildlife loss/gain was level of education.

Keywords: Wildlife, oil palm plantations, indigenous Dayak, biodiversity loss and gain.

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2881 An Iterated Function System for Reich Contraction in Complete b Metric Space

Authors: R. Uthayakumar, G. Arockia Prabakar

Abstract:

In this paper, we introduce R Iterated Function System and employ the Hutchinson Barnsley theory (HB) to construct a fractal set as its unique fixed point by using Reich contractions in a complete b metric space. We discuss about well posedness of fixed point problem for b metric space.

Keywords: Fractals, Iterated Function System, Compact set, Reich Contraction, Well posedness.

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2880 Implementation of a New Neural Network Function Block to Programmable Logic Controllers Library Function

Authors: Hamid Abdi, Abolfazl Salami, Abolfazl Ahmadi

Abstract:

Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.

Keywords: Programmable Logic Controller, PLC Programming, Neural Networks, Perception Network, Intelligent Control.

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2879 On Fractional (k,m)-Deleted Graphs with Constrains Conditions

Authors: Sizhong Zhou, Hongxia Liu

Abstract:

Let G be a graph of order n, and let k  2 and m  0 be two integers. Let h : E(G)  [0, 1] be a function. If e∋x h(e) = k holds for each x  V (G), then we call G[Fh] a fractional k-factor of G with indicator function h where Fh = {e  E(G) : h(e) > 0}. A graph G is called a fractional (k,m)-deleted graph if there exists a fractional k-factor G[Fh] of G with indicator function h such that h(e) = 0 for any e  E(H), where H is any subgraph of G with m edges. In this paper, it is proved that G is a fractional (k,m)-deleted graph if (G)  k + m + m k+1 , n  4k2 + 2k − 6 + (4k 2 +6k−2)m−2 k−1 and max{dG(x), dG(y)}  n 2 for any vertices x and y of G with dG(x, y) = 2. Furthermore, it is shown that the result in this paper is best possible in some sense.

Keywords: Graph, degree condition, fractional k-factor, fractional (k, m)-deleted graph.

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2878 Analysis of Gamma-Ray Spectra Using Levenberg-Marquardt Method

Authors: A. H. Fatah, A. H. Ahmed

Abstract:

Levenberg-Marquardt method (LM) was proposed to be applied as a non-linear least-square fitting in the analysis of a natural gamma-ray spectrum that was taken by the Hp (Ge) detector. The Gaussian function that composed of three components, main Gaussian, a step background function and tailing function in the lowenergy side, has been suggested to describe each of the y-ray lines mathematically in the spectrum. The whole spectrum has been analyzed by determining the energy and relative intensity for the strong y-ray lines.

Keywords: Gamma-Ray, Spectrum analysis, Non-linear leastsquare fitting.

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2877 Slip Suppression Sliding Mode Control with Various Chattering Functions

Authors: Shun Horikoshi, Tohru Kawabe

Abstract:

This study presents performance analysis results of SMC (Sliding mode control) with changing the chattering functions applied to slip suppression problem of electric vehicles (EVs). In SMC, chattering phenomenon always occurs through high frequency switching of the control inputs. It is undesirable phenomenon and degrade the control performance, since it causes the oscillations of the control inputs. Several studies have been conducted on this problem by introducing some general saturation function. However, study about whether saturation function was really best and the performance analysis when using the other functions, weren’t being done so much. Therefore, in this paper, several candidate functions for SMC are selected and control performance of candidate functions is analyzed. In the analysis, evaluation function based on the trade-off between slip suppression performance and chattering reduction performance is proposed. The analyses are conducted in several numerical simulations of slip suppression problem of EVs. Then, we can see that there is no difference of employed candidate functions in chattering reduction performance. On the other hand, in slip suppression performance, the saturation function is excellent overall. So, we conclude the saturation function is most suitable for slip suppression sliding mode control.

Keywords: Sliding mode control, chattering function, electric vehicle, slip suppression, performance analysis.

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2876 Flow Transformation: An Investigation on Theoretical Aspects and Numerical Computation

Authors: Abhisek Sarkar, Abhimanyu Gaur

Abstract:

In this report we have discussed the theoretical aspects of the flow transformation, occurring through a series of bifurcations. The parameters and their continuous diversion, the intermittent bursts in the transition zone, variation of velocity and pressure with time, effect of roughness in turbulent zone, and changes in friction factor and head loss coefficient as a function of Reynolds number for a transverse flow across a cylinder have been discussed. An analysis of the variation in the wake length with Reynolds number was done in FORTRAN.

Keywords: Attractor, Bifurcation, Energy cascade, Energy spectra, Intermittence, Vortex stretching.

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2875 Using Genetic Algorithm to Improve Information Retrieval Systems

Authors: Ahmed A. A. Radwan, Bahgat A. Abdel Latef, Abdel Mgeid A. Ali, Osman A. Sadek

Abstract:

This study investigates the use of genetic algorithms in information retrieval. The method is shown to be applicable to three well-known documents collections, where more relevant documents are presented to users in the genetic modification. In this paper we present a new fitness function for approximate information retrieval which is very fast and very flexible, than cosine similarity fitness function.

Keywords: Cosine similarity, Fitness function, Genetic Algorithm, Information Retrieval, Query learning.

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