Search results for: Simple Weighted Average
2795 The Performance Analysis of Error Saturation Nonlinearity LMS in Impulsive Noise based on Weighted-Energy Conservation
Authors: T Panigrahi, G Panda, Mulgrew
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This paper introduces a new approach for the performance analysis of adaptive filter with error saturation nonlinearity in the presence of impulsive noise. The performance analysis of adaptive filters includes both transient analysis which shows that how fast a filter learns and the steady-state analysis gives how well a filter learns. The recursive expressions for mean-square deviation(MSD) and excess mean-square error(EMSE) are derived based on weighted energy conservation arguments which provide the transient behavior of the adaptive algorithm. The steady-state analysis for co-related input regressor data is analyzed, so this approach leads to a new performance results without restricting the input regression data to be white.Keywords: Error saturation nonlinearity, transient analysis, impulsive noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17812794 Investigation of Various Physical and Physiological Properties of Elite Male Ethiopian Distance Runners
Authors: Getaye F. Gelaw
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The purpose of this study was to investigate the key physical and physiological characteristics of 16 elite male Ethiopian national team distance runners, who have an average age of 28.1 ± 4.3 years, a height of 175.0 ± 5.6 cm, a weight of 59.1 ± 3.9 kg, a BMI of 19.6 ± 1.5, and training age of 10.1 ± 5.1 yrs. The average weekly distance is 196.3 ± 13.8 km, the average 10,000 m time is 27:14 ± 0.5 min sec, the average half marathon time is 59:30 ± 0.6 min sec, the average marathon time is 2:04:20 ± 2.7 hr min ss. In addition, the average Cooper test (12-minute run test) is 4525.4 ± 139.7 meters, and the average VO2 max is 90.8 ± 3.1 ml/kg/m. All athletes have a high profile and compete on the international label, and according to the World Athletics athletes' ranking system in 2021, 56.3% of the 16 participants were platinum label status, while the remaining 43.7% were gold label status-completed an incremental treadmill test for the assessment of VO2peak, submaximal running, lactate threshold and test during which they ran continuously at 21 km/h. The laboratory determined VO2peak was 91.4 ± 1.7 mL/kg/min with anaerobic threshold of 74.2 ± 1.6 mL/min/kg and VO2 max 81%. The speed at the Anaerobic Threshold (AT) is 15.9 ± 0.6 kmh and the altitude is 4.0%. The Respiratory Compensation Point (RCP) was reached at 88.7 ± 1.1 mL/min/kg and 97% of VO2 max. On RCP, the speed is 17.6 ± 0.4 km/h and the altitude/slope are 5.5%, and the speed at Maximum effort is 19.5 ± 1.5 and the elevation is 6.0%. The data also suggest that Ethiopian distance top athletes have considerably higher VO2 max values than those found in earlier research.
Keywords: Long-distance running, Ethiopians, VO2 max, World Athletics, Anthropometric.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2752793 A Simple Autonomous Hovering and Operating Control of Multicopter Using Only Web Camera
Authors: Kazuya Sato, Toru Kasahara, Junji Kuroda, Tomoyuki Izu
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In this paper, an autonomous hovering control method of multicopter using only Web camera is proposed. Recently, various control method of an autonomous flight for multicopter are proposed. But, in the previous proposed methods, a motion capture system (i. e., OptiTrack) and laser range finder are often used to measure the position and posture of multicopter. To achieve an autonomous flight control of multicopter with simple equipments, we propose an autonomous flight control method using AR marker and Web camera. AR marker can measure the position of multicopter with Cartesian coordinate in three dimensional, then its position connects with aileron, elevator, and accelerator throttle operation. A simple PID control method is applied to the each operation and adjust the controller gains. Experimental results are given to show the effectiveness of our proposed method. Moreover, another simple operation method for autonomous flight control multicopter is also proposed.Keywords: Autonomous hovering control, multicopter, Web camera.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18302792 Application of Feed-Forward Neural Networks Autoregressive Models in Gross Domestic Product Prediction
Authors: Ε. Giovanis
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In this paper we present an autoregressive model with neural networks modeling and standard error backpropagation algorithm training optimization in order to predict the gross domestic product (GDP) growth rate of four countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer after the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model in the out-of-sample period. The idea behind this approach is to propose a parametric regression with weighted variables in order to test for the statistical significance and the magnitude of the estimated autoregressive coefficients and simultaneously to estimate the forecasts.Keywords: Autoregressive model, Error back-propagation Feed-Forward neural networks, , Gross Domestic Product
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14202791 Reducing CO2 Emission Using EDA and Weighted Sum Model in Smart Parking System
Authors: Rahman Ali, Muhammad Sajjad, Farkhund Iqbal, Muhammad Sadiq Hassan Zada, Mohammed Hussain
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Emission of Carbon Dioxide (CO2) has adversely affected the environment. One of the major sources of CO2 emission is transportation. In the last few decades, the increase in mobility of people using vehicles has enormously increased the emission of CO2 in the environment. To reduce CO2 emission, sustainable transportation system is required in which smart parking is one of the important measures that need to be established. To contribute to the issue of reducing the amount of CO2 emission, this research proposes a smart parking system. A cloud-based solution is provided to the drivers which automatically searches and recommends the most preferred parking slots. To determine preferences of the parking areas, this methodology exploits a number of unique parking features which ultimately results in the selection of a parking that leads to minimum level of CO2 emission from the current position of the vehicle. To realize the methodology, a scenario-based implementation is considered. During the implementation, a mobile application with GPS signals, vehicles with a number of vehicle features and a list of parking areas with parking features are used by sorting, multi-level filtering, exploratory data analysis (EDA, Analytical Hierarchy Process (AHP)) and weighted sum model (WSM) to rank the parking areas and recommend the drivers with top-k most preferred parking areas. In the EDA process, “2020testcar-2020-03-03”, a freely available dataset is used to estimate CO2 emission of a particular vehicle. To evaluate the system, results of the proposed system are compared with the conventional approach, which reveal that the proposed methodology supersedes the conventional one in reducing the emission of CO2 into the atmosphere.
Keywords: CO2 emission, IoT, EDA, Weighted Sum Model, WSM, regression, smart parking system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7432790 A State Aggregation Approach to Singularly Perturbed Markov Reward Processes
Authors: Dali Zhang, Baoqun Yin, Hongsheng Xi
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In this paper, we propose a single sample path based algorithm with state aggregation to optimize the average rewards of singularly perturbed Markov reward processes (SPMRPs) with a large scale state spaces. It is assumed that such a reward process depend on a set of parameters. Differing from the other kinds of Markov chain, SPMRPs have their own hierarchical structure. Based on this special structure, our algorithm can alleviate the load in the optimization for performance. Moreover, our method can be applied on line because of its evolution with the sample path simulated. Compared with the original algorithm applied on these problems of general MRPs, a new gradient formula for average reward performance metric in SPMRPs is brought in, which will be proved in Appendix, and then based on these gradients, the schedule of the iteration algorithm is presented, which is based on a single sample path, and eventually a special case in which parameters only dominate the disturbance matrices will be analyzed, and a precise comparison with be displayed between our algorithm with the old ones which is aim to solve these problems in general Markov reward processes. When applied in SPMRPs, our method will approach a fast pace in these cases. Furthermore, to illustrate the practical value of SPMRPs, a simple example in multiple programming in computer systems will be listed and simulated. Corresponding to some practical model, physical meanings of SPMRPs in networks of queues will be clarified.Keywords: Singularly perturbed Markov processes, Gradient of average reward, Differential reward, State aggregation, Perturbed close network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16362789 A New Bound on the Average Information Ratio of Perfect Secret-Sharing Schemes for Access Structures Based On Bipartite Graphs of Larger Girth
Authors: Hui-Chuan Lu
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In a perfect secret-sharing scheme, a dealer distributes a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of the participants in any unqualified subset is statistically independent of the secret. The access structure of the scheme refers to the collection of all qualified subsets. In a graph-based access structures, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme realizing a given access structure is the ratio of the average length of the shares given to the participants to the length of the secret. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing an access structure is called the optimal average information ratio of that access structure. We study the optimal average information ratio of the access structures based on bipartite graphs. Based on some previous results, we give a bound on the optimal average information ratio for all bipartite graphs of girth at least six. This bound is the best possible for some classes of bipartite graphs using our approach.
Keywords: Secret-sharing scheme, average information ratio, star covering, deduction, core cluster.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14342788 The Nature of the Complicated Fabric Textures: How to Represent in Primary Visual Cortex
Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao
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Fabric textures are very common in our daily life. However, the representation of fabric textures has never been explored from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. We choose 140 types of fabrics to get the classical fabric textures as materials. Experiment results indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.Keywords: Fabric Texture, Receptive Filed, Simple Cell, Spare Coding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14742787 Geochemical and Mineralogical Characteristics of Soils in Areas Affected by the Fires on August 2021 at the Ilia Prefecture, Greece
Authors: D. Panagiotaras, P. Avramidis, D. Papoulis, D. Koulougliotis, D. C. Christodoulopoulos, D. Lekka, D. Nifora, D. Drouvari, A. Skalioti
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This study delineates the geochemical, mineralogical and sedimentological characteristics of soils collected from woodland and forest areas affected by the fires of August 2021 at the Pelopio region, Ancient Olympia Municipality, Ilia prefecture, Greece. The mineralogical composition of the samples consists of quartz, calcite, feldspars (albite, oligoclase, anorthite) and clay minerals mostly smectite, kaolinite, and illite. Quartz ranges from 38% to 57% with an average of 48%, calcite ranges from 2% to 25% with an average of 14%, feldspars ranges from 7% to 26% with an average of 17% and clays ranges from 4% to 43% with an average of 21%. Sedimentological analyses classify most of the samples as loam to silt loam. Sand percentage ranges from 14.76% to 71.11% with an average of 35.01%, silt ranges from 21.68% to 62.34% with an average of 44.96%. Geochemical analyses of the soil samples applied for total organic carbon (TOC), total nitrogen (TN), total phosphorous (TP), Cu, Zn, Mn and Fe. TOC ranges from 0.28-0.83%, TN from 0.09-0.48 mg/g, TP from 0.02-0.26 mg/g, Cu from 10-21 ppm, Zn from 15-34 ppm, Mn from 612-1204 ppm, Fe from 9528-27500 ppm. The pH ranges from 7.5 to 9.07 with an average of 8.74, while the values of electrical conductivity (EC) range from 0.05-0.12 mS/cm, with an average of 0.07 mS/cm. Statistical analysis of the data shows a positive correlation between clays and Zn, Mn, Fe. TOC and TN show a strong positive correlation, while Fe shows a strong negative correlation with calcite.
Keywords: Soils, geochemistry, mineralogy, sedimentology, woodland, forest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1032786 A Particle Swarm Optimization Approach for the Earliness-Tardiness No-Wait Flowshop Scheduling Problem
Authors: Sedighe Arabameri, Nasser Salmasi
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In this researcha particle swarm optimization (PSO) algorithm is proposedfor no-wait flowshopsequence dependent setuptime scheduling problem with weighted earliness-tardiness penalties as the criterion (|, |Σ " ).The smallestposition value (SPV) rule is applied to convert the continuous value of position vector of particles in PSO to job permutations.A timing algorithm is generated to find the optimal schedule and calculate the objective function value of a given sequence in PSO algorithm. Twodifferent neighborhood structures are applied to improve the solution quality of PSO algorithm.The first one is based on variable neighborhood search (VNS) and the second one is a simple one with invariable structure. In order to compare the performance of two neighborhood structures, random test problems are generated and solved by both neighborhood approaches.Computational results show that the VNS algorithmhas better performance than the other one especially for the large sized problems.Keywords: minimization of summation of weighed earliness and tardiness, no-wait flowshop scheduling, particle swarm optimization, sequence dependent setup times
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16262785 W3-Miner: Mining Weighted Frequent Subtree Patterns in a Collection of Trees
Authors: R. AliMohammadzadeh, M. Haghir Chehreghani, A. Zarnani, M. Rahgozar
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Mining frequent tree patterns have many useful applications in XML mining, bioinformatics, network routing, etc. Most of the frequent subtree mining algorithms (i.e. FREQT, TreeMiner and CMTreeMiner) use anti-monotone property in the phase of candidate subtree generation. However, none of these algorithms have verified the correctness of this property in tree structured data. In this research it is shown that anti-monotonicity does not generally hold, when using weighed support in tree pattern discovery. As a result, tree mining algorithms that are based on this property would probably miss some of the valid frequent subtree patterns in a collection of trees. In this paper, we investigate the correctness of anti-monotone property for the problem of weighted frequent subtree mining. In addition we propose W3-Miner, a new algorithm for full extraction of frequent subtrees. The experimental results confirm that W3-Miner finds some frequent subtrees that the previously proposed algorithms are not able to discover.Keywords: Semi-Structured Data Mining, Anti-Monotone Property, Trees.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13812784 Enhancing the Performance of Wireless Sensor Networks Using Low Power Design
Authors: N. Mahendran, R. Madhuranthi
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Wireless sensor networks (WSNs), are constantly in demand to process information more rapidly with less energy and area cost. Presently, processor based solutions have difficult to achieve high processing speed with low-power consumption. This paper presents a simple and accurate data processing scheme for low power wireless sensor node, based on reduced number of processing element (PE). The presented model provides a simple recursive structure (SRS) to process the sampled data in the wireless sensor environment and to reduce the power consumption in wireless sensor node. Based on this model, to process the incoming samples and produce a smaller amount of data sufficient to reconstruct the original signal. The ModelSim simulator used to simulate SRS structure. Functional simulation is carried out for the validation of the presented architecture. Xilinx Power Estimator (XPE) tool is used to measure the power consumption. The experimental results show the average power consumption of 91 mW; this is 42% improvement compared to the folded tree architecture.Keywords: Power consumption, energy efficiency, low power WSN node, recursive structure, sleep/wake scheduling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10142783 Optimal Placement and Sizing of SVC for Load Margin Improvement Using BF Algorithm
Authors: Santi Behera, M. Tripathy, J. K. Satapathy
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Power systems are operating under stressed condition due to continuous increase in demand of load. This can lead to voltage instability problem when face additional load increase or contingency. In order to avoid voltage instability suitable size of reactive power compensation at optimal location in the system is required which improves the load margin. This work aims at obtaining optimal size as well as location of compensation in the 39- bus New England system with the help of Bacteria Foraging and Genetic algorithms. To reduce the computational time the work identifies weak candidate buses in the system, and then picks only two of them to take part in the optimization. The objective function is based on a recently proposed voltage stability index which takes into account the weighted average sensitivity index is a simpler and faster approach than the conventional CPF algorithm. BFOA has been found to give better results compared to GA.
Keywords: BFOA, GA, SSVSL, WASI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21902782 Genetic Algorithm Application in a Dynamic PCB Assembly with Carryover Sequence- Dependent Setups
Authors: M. T. Yazdani Sabouni, Rasaratnam Logendran
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We consider a typical problem in the assembly of printed circuit boards (PCBs) in a two-machine flow shop system to simultaneously minimize the weighted sum of weighted tardiness and weighted flow time. The investigated problem is a group scheduling problem in which PCBs are assembled in groups and the interest is to find the best sequence of groups as well as the boards within each group to minimize the objective function value. The type of setup operation between any two board groups is characterized as carryover sequence-dependent setup time, which exactly matches with the real application of this problem. As a technical constraint, all of the boards must be kitted before the assembly operation starts (kitting operation) and by kitting staff. The main idea developed in this paper is to completely eliminate the role of kitting staff by assigning the task of kitting to the machine operator during the time he is idle which is referred to as integration of internal (machine) and external (kitting) setup times. Performing the kitting operation, which is a preparation process of the next set of boards while the other boards are currently being assembled, results in the boards to continuously enter the system or have dynamic arrival times. Consequently, a dynamic PCB assembly system is introduced for the first time in the assembly of PCBs, which also has characteristics similar to that of just-in-time manufacturing. The problem investigated is computationally very complex, meaning that finding the optimal solutions especially when the problem size gets larger is impossible. Thus, a heuristic based on Genetic Algorithm (GA) is employed. An example problem on the application of the GA developed is demonstrated and also numerical results of applying the GA on solving several instances are provided.Keywords: Genetic algorithm, Dynamic PCB assembly, Carryover sequence-dependent setup times, Multi-objective.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15692781 A Study on the Average Information Ratio of Perfect Secret-Sharing Schemes for Access Structures Based On Bipartite Graphs
Authors: Hui-Chuan Lu
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A perfect secret-sharing scheme is a method to distribute a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of participants in any unqualified subset is statistically independent of the secret. The collection of all qualified subsets is called the access structure of the perfect secret-sharing scheme. In a graph-based access structure, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme realizing the access structure based on G is defined as AR = (Pv2V (G) H(v))/(|V (G)|H(s)), where s is the secret and v is the share of v, both are random variables from and H is the Shannon entropy. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing a given access structure is called the optimal average information ratio of that access structure. Most known results about the optimal average information ratio give upper bounds or lower bounds on it. In this present structures based on bipartite graphs and determine the exact values of the optimal average information ratio of some infinite classes of them.
Keywords: secret-sharing scheme, average information ratio, star covering, core sequence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15792780 An Investigation of Customers’ Perception and Attitude towards Krung Thai Bank in Thailand
Authors: Phatthanan Chaiyabut
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The purposes of this research were to identify the perception of customers towards Krung Thai Bank’s image and to understand the customer attitude towards Krung Thai Bank’s image in Bangkok, Thailand. This research utilized quantitative approach and used questionnaire as data collection tool. A sample size of 420 respondents was selected by simple random sampling. The findings revealed that the majority of respondents received information, news, and feeds concerning the bank through televisions the most. This information channel had significantly influenced on the customers and their decisions to utilize the bank’s products and services.
From the information concerning the attitudes towards overall image of the bank, it was found that the majority respondents rated the bank’s image at the good level. The top three average attitudes included the bank’s images in supports government's monetary policies, being renowned and stable, and contributing in economical amendments and developments, with the mean average of 4.01, 3.96 and 3.81 respectively. The attitudes toward the images included a business leader in banking, marketing, and competitions. Offering prompt services, and provided appropriate servicing time were rated moderate with the attitudes of 3.36 and 3.30 respectively.
Keywords: Attitude, Image, Krung Thai bank, Perception.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16292779 A Simple Adaptive Atomic Decomposition Voice Activity Detector Implemented by Matching Pursuit
Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic
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A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30d B SNR as a reference for voice activity.Keywords: Atomic Decomposition, Gabor, Gammatone, Matching Pursuit, Voice Activity Detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17932778 Application of Feed-Forward Neural Networks Autoregressive Models with Genetic Algorithm in Gross Domestic Product Prediction
Authors: E. Giovanis
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In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16722777 An Approach to the Solving Non-Steiner Minimum Link Path Problem
Authors: V. Tereshchenko, A. Tregubenko
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In this study we survey the method for fast finding a minimum link path between two arbitrary points within a simple polygon, which can pass only through the vertices, with preprocessing.
Keywords: Minimum link path, simple polygon, Steiner points, optimal algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15112776 Iterative Image Reconstruction for Sparse-View Computed Tomography via Total Variation Regularization and Dictionary Learning
Authors: XianYu Zhao, JinXu Guo
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Recently, low-dose computed tomography (CT) has become highly desirable due to increasing attention to the potential risks of excessive radiation. For low-dose CT imaging, ensuring image quality while reducing radiation dose is a major challenge. To facilitate low-dose CT imaging, we propose an improved statistical iterative reconstruction scheme based on the Penalized Weighted Least Squares (PWLS) standard combined with total variation (TV) minimization and sparse dictionary learning (DL) to improve reconstruction performance. We call this method "PWLS-TV-DL". In order to evaluate the PWLS-TV-DL method, we performed experiments on digital phantoms and physical phantoms, respectively. The experimental results show that our method is in image quality and calculation. The efficiency is superior to other methods, which confirms the potential of its low-dose CT imaging.Keywords: Low dose computed tomography, penalized weighted least squares, total variation, dictionary learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8352775 Performance Analysis of Fuzzy Logic Based Unified Power Flow Controller
Authors: Lütfü Saribulut, Mehmet Tümay, İlyas Eker
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FACTS devices are used to control the power flow, to increase the transmission capacity and to optimize the stability of the power system. One of the most widely used FACTS devices is Unified Power Flow Controller (UPFC). The controller used in the control mechanism has a significantly effects on controlling of the power flow and enhancing the system stability of UPFC. According to this, the capability of UPFC is observed by using different control mechanisms based on P, PI, PID and fuzzy logic controllers (FLC) in this study. FLC was developed by taking consideration of Takagi- Sugeno inference system in the decision process and Sugeno-s weighted average method in the defuzzification process. Case studies with different operating conditions are applied to prove the ability of UPFC on controlling the power flow and the effectiveness of controllers on the performance of UPFC. PSCAD/EMTDC program is used to create the FLC and to simulate UPFC model.Keywords: FACTS, Fuzzy Logic Controller, UPFC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28822774 Multiple Criteria Decision Making for Turkish Air Force Stealth Fighter Aircraft Selection
Authors: C. Ardil
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Neutrosophic logic decision analysis is proposed as a method of stealth fighter aircraft selection for Turkish Air Force. The opinion of experts is employed to rank the alternatives across a set of criteria. The analyst uses neutrosophic logic numbers to describe the experts' preferences. This approach can handle the situation in the case of unavailability of precise data, which is most commonly the case in stealth fighter aircraft selection. Neutrosophic logic numbers can consider the imprecision of the factors affecting decision making such as stealth analysis, survivability analysis, and performance analysis. Neutrosophic logic ranking is achieved using weighted arithmetic operator and weighted geometric operator and the alternatives are ranked from best to worst. An example is also presented to illustrate the applicability and effectiveness of the proposed method.
Keywords: Neutrosophic set theory, stealth fighter aircraft selection, multiple criteria decision-making, neutrosophic logic decision making, Turkish Air Force, MCDM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4972773 Engineering Geological Characteristics of Soil Materials, East Nile Delta, Egypt
Authors: A. I. M. Ismail, N. Ryden
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This paper is concerned with the study of mineralogy and engineering characteristics of soil materials derived from the eastern part of Nile Delta. The clay minerals of the studied soil by using X- ray diffraction are mainly illite (average 72.6 %) and kaolinite (average 2.6 %), expandable portion in illite-smectite mixed layer (average 7 %). Smectite is more abundant in fluviatile clays, whereas kaolinite is more abundant in lagoonal clays. On the other hand, illite and illite-smectite are more abundant in marine clays. The geotechnical results show that the soil under study consists mainly of about 0.3 % gravel, 5 % sand, 51.5 % silt and 42.2 % clay in average. The average shrinkage limit attains 11 % whereas the average value of the plasticity index is 23.4 %. The free swelling ranges from 40 % to 75 % and has a value of 55 % giving an indication about the inadequacy of such soil under foundations. From a construction point of view, the soil under investigation poses many problems even under light foundations due to the swelling and shrinkage. Such swelling and shrinkage is due to the high content of soil materials in the expandable clay minerals of illite and smectite. Based on the results of the present and earlier studies, trial application of soil stabilisation is recommended.Keywords: Engineering Geological Investigations, Nile Delta, Swelling, Shrinkage
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37852772 Influence of Parameters of Modeling and Data Distribution for Optimal Condition on Locally Weighted Projection Regression Method
Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri
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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.
Keywords: Local nonlinear estimation, LWPR algorithm, Online training method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16012771 Average Current Estimation Technique for Reliability Analysis of Multiple Semiconductor Interconnects
Authors: Ki-Young Kim, Jae-Ho Lim, Deok-Min Kim, Seok-Yoon Kim
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Average current analysis checking the impact of current flow is very important to guarantee the reliability of semiconductor systems. As semiconductor process technologies improve, the coupling capacitance often become bigger than self capacitances. In this paper, we propose an analytic technique for analyzing average current on interconnects in multi-conductor structures. The proposed technique has shown to yield the acceptable errors compared to HSPICE results while providing computational efficiency.Keywords: current moment, interconnect modeling, reliability analysis, worst-case switching
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13872770 Advanced Jet Trainer and Light Attack Aircraft Selection Using Composite Programming in Multiple Criteria Decision Making Analysis Method
Authors: C. Ardil
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In this paper, composite programming is discussed for aircraft evaluation and selection problem using the multiple criteria decision analysis method. The decision criteria and aircraft alternatives were identified from the literature review. The importance of criteria weights was determined by the standard deviation method. The proposed model is applied to a practical decision problem for evaluating and selecting advanced jet trainer and light attack aircraft. The proposed technique gives robust and efficient results in modeling multiple criteria decisions. As a result of composite programming analysis, Hürjet, an advanced jet trainer and light attack aircraft alternative (a3), was chosen as the most suitable aircraft candidate.
Keywords: composite programming, additive weighted model, multiplicative weighted model, multiple criteria decision making analysis, MCDMA, aircraft selection, advanced jet trainer and light attack aircraft, M-346, FA-50, Hürjet
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4882769 Robust Statistics Based Algorithm to Remove Salt and Pepper Noise in Images
Authors: V.R.Vijaykumar, P.T.Vanathi, P.Kanagasabapathy, D.Ebenezer
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In this paper, a robust statistics based filter to remove salt and pepper noise in digital images is presented. The function of the algorithm is to detect the corrupted pixels first since the impulse noise only affect certain pixels in the image and the remaining pixels are uncorrupted. The corrupted pixels are replaced by an estimated value using the proposed robust statistics based filter. The proposed method perform well in removing low to medium density impulse noise with detail preservation upto a noise density of 70% compared to standard median filter, weighted median filter, recursive weighted median filter, progressive switching median filter, signal dependent rank ordered mean filter, adaptive median filter and recently proposed decision based algorithm. The visual and quantitative results show the proposed algorithm outperforms in restoring the original image with superior preservation of edges and better suppression of impulse noise
Keywords: Image denoising, Nonlinear filter, Robust Statistics, and Salt and Pepper Noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22022768 Proposal of a Model Supporting Decision-Making Based On Multi-Objective Optimization Analysis on Information Security Risk Treatment
Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu
Abstract:
Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.
Keywords: Information security risk treatment, Selection of risk measures, Risk acceptanceand Multi-objective optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17212767 General Purpose Graphic Processing Units Based Real Time Video Tracking System
Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai
Abstract:
Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.
Keywords: Connected components, Embrace threads, Local weighted kernel, Structuring element.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11722766 Security over OFDM Fading Channels with Friendly Jammer
Authors: Munnujahan Ara
Abstract:
In this paper, we investigate the effect of friendly jamming power allocation strategies on the achievable average secrecy rate over a bank of parallel fading wiretap channels. We investigate the achievable average secrecy rate in parallel fading wiretap channels subject to Rayleigh and Rician fading. The achievable average secrecy rate, due to the presence of a line-of-sight component in the jammer channel is also evaluated. Moreover, we study the detrimental effect of correlation across the parallel sub-channels, and evaluate the corresponding decrease in the achievable average secrecy rate for the various fading configurations. We also investigate the tradeoff between the transmission power and the jamming power for a fixed total power budget. Our results, which are applicable to current orthogonal frequency division multiplexing (OFDM) communications systems, shed further light on the achievable average secrecy rates over a bank of parallel fading channels in the presence of friendly jammers.
Keywords: Fading parallel channels, Wire-tap channel, OFDM, Secrecy capacity, Power allocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2249