Search results for: load estimation

Authors: N. Rezaee, M Nayeripour, A. Roosta, T. Niknam

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With the prevalence of computer and development of information technology, Geographic Information Systems (GIS) have long used for a variety of applications in electrical engineering. GIS are designed to support the analysis, management, manipulation and mapping of spatial data. This paper presents several usages of GIS in power utilities such as automated route selection for the construction of new power lines which uses a dynamic programming model for route optimization, load forecasting and optimizing planning of substation-s location and capacity with comprehensive algorithm which involves an accurate small-area electric load forecasting procedure and simulates the different cost functions of substations.

Keywords: Geographic information systems (GIS), optimallocation and capacity, power distribution planning, route selection, spatial load forecasting.

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Authors: Úrsula B. Ferraz, Paulo F. Seixas, Webber E. Aguiar

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This paper presents a dynamic model for mechanical loads of an electric drive, including angular misalignment and including load unbalance. The misalignment model represents the effects of the universal joint between the motor and the mechanical load. Simulation results are presented for an induction motor driving a mechanical load with angular misalignment for both flexible and rigid coupling. The models presented are very useful in the study of mechanical fault detection in induction motors, using mechanical and electrical signals already available in a drive system, such as speed, torque and stator currents.

Keywords: Angular misalignment, fault modeling, unbalance, universal joint.

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Authors: Parvinder S. Sandhu, Porush Bassi, Amanpreet Singh Brar

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Various models have been derived by studying large number of completed software projects from various organizations and applications to explore how project sizes mapped into project effort. But, still there is a need to prediction accuracy of the models. As Neuro-fuzzy based system is able to approximate the non-linear function with more precision. So, Neuro-Fuzzy system is used as a soft computing approach to generate model by formulating the relationship based on its training. In this paper, Neuro-Fuzzy technique is used for software estimation modeling of on NASA software project data and performance of the developed models are compared with the Halstead, Walston-Felix, Bailey-Basili and Doty Models mentioned in the literature.

Keywords: Effort Estimation, Neural-Fuzzy Model, Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model.

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Authors: Labiba Gilani, Asifullah Khan, Anwar M. Mirza

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This paper introduces a technique of distortion estimation in image watermarking using Genetic Programming (GP). The distortion is estimated by considering the problem of obtaining a distorted watermarked signal from the original watermarked signal as a function regression problem. This function regression problem is solved using GP, where the original watermarked signal is considered as an independent variable. GP-based distortion estimation scheme is checked for Gaussian attack and Jpeg compression attack. We have used Gaussian attacks of different strengths by changing the standard deviation. JPEG compression attack is also varied by adding various distortions. Experimental results demonstrate that the proposed technique is able to detect the watermark even in the case of strong distortions and is more robust against attacks.

Keywords: Blind Watermarking, Genetic Programming (GP), Fitness Function, Discrete Cosine Transform (DCT).

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Authors: Seok Hong Min, Tae Kwon Ha

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In this study, thermal fatigue properties of 400 series ferritic stainless steels have been evaluated in the temperature ranges of 200-800oC and 200-900oC. Systematic methods for control of temperatures within the predetermined range and measurement of load applied to specimens as a function of temperature during thermal cycles have been established. Thermal fatigue tests were conducted under fully constrained condition, where both ends of specimens were completely fixed. It has been revealed that load relaxation behavior at the temperatures of thermal cycle was closely related with the thermal fatigue property. Thermal fatigue resistance of 430J1L stainless steel is found to be superior to the other steels.

Keywords: Ferritic stainless steel, automotive exhaust, thermal fatigue, microstructure, load relaxation.

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Authors: Y. Shpungin

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Estimating the lifetime distribution of computer networks in which nodes and links exist in time and are bound for failure is very useful in various applications. This problem is known to be NP-hard. In this paper we present efficient combinatorial approaches to Monte Carlo estimation of network lifetime distribution. We also present some simulation results.

Keywords: Combinatorial spectrum, Monte Carlo, Networklifetime, Unreliable nodes and edges.

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Authors: Toshinori Takabatake, Yoshikazu Komano

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Recently, the improvements in processing performance of a computer and in high speed communication of an optical fiber have been achieved, so that the amount of data which are processed by a computer and flowed on a network has been increasing greatly. However, in a client-server system, since the server receives and processes the amount of data from the clients through the network, a load on the server is increasing. Thus, there are needed to introduce a server with high processing ability and to have a line with high bandwidth. In this paper, concerning to P2P networks to resolve the load on a specific server, a criterion called an Indexed-Priority Metric is proposed and its performance is evaluated. The proposed metric is to allocate some files to each node. As a result, the load on a specific server can distribute them to each node equally well. A P2P file sharing system using the proposed metric is implemented. Simulation results show that the proposed metric can make it distribute files on the specific server.

Keywords: peer-to-peer, file-sharing system, load-balancing, dependability

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Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You

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The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.

Keywords: Clustering algorithm, potential function, speech signal, the UBSS model.

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Authors: M. Bastanfard, S. Jafari, B.Jalaeian

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Ultrasound images are very useful diagnostic tool to distinguish benignant from malignant masses of the breast. However, there is a considerable overlap between benignancy and malignancy in ultrasonic images which makes it difficult to interpret. In this paper, a new noise removal algorithm was used to improve the images and classification process. The masses are classified by wavelet transform's coefficients, morphological and textural features as a novel feature set for this goal. The Bayesian estimation theory is used to classify the tissues in three classes according to their features.

Keywords: Bayesian estimation theory, breast, ultrasound, wavelet.

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Authors: R. Suzana, T. Wardah, A.B. Sahol Hamid

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The use of radar in Quantitative Precipitation Estimation (QPE) for radar-rainfall measurement is significantly beneficial. Radar has advantages in terms of high spatial and temporal condition in rainfall measurement and also forecasting. In Malaysia, radar application in QPE is still new and needs to be explored. This paper focuses on the Z/R derivation works of radarrainfall estimation based on rainfall classification. The works developed new Z/R relationships for Klang River Basin in Selangor area for three different general classes of rain events, namely low (<10mm/hr), moderate (>10mm/hr, <30mm/hr) and heavy (>30mm/hr) and also on more specific rain types during monsoon seasons. Looking at the high potential of Doppler radar in QPE, the newly formulated Z/R equations will be useful in improving the measurement of rainfall for any hydrological application, especially for flood forecasting.

Keywords: Radar, Quantitative Precipitation Estimation, Z/R development, flood forecasting

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Authors: Akinola Ikudayisi, Josiah Adeyemo

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The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.

Keywords: Irrigation, principal component analysis, reference evapotranspiration, Vaalharts.

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Authors: Dana M. Ragab, Jasim A. Ghaeb

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The three-phase power system suffers from different challenging problems, e.g. voltage unbalance conditions at the load side. The voltage unbalance usually degrades the power quality of the electric power system. Several techniques can be considered for load balancing including load reconfiguration, static synchronous compensator and static reactive power compensator. In this work an efficient neural network is designed to control the unbalanced condition in the Aqaba-Qatrana-South Amman (AQSA) electric power system. It is designed for highly enhanced response time of the reactive compensator for voltage balancing. The neural network is developed to determine the appropriate set of firing angles required for the thyristor-controlled reactor to balance the three load voltages accurately and quickly. The parameters of AQSA power system are considered in the laboratory model, and several test cases have been conducted to test and validate the proposed technique capabilities. The results have shown a high performance of the proposed Neural Network Control (NNC) technique for correcting the voltage unbalance conditions at three-phase load based on accuracy and response time.

Keywords: Three-phase power system, reactive power control, voltage unbalance factor, neural network, power quality.

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Authors: Dinesh Rao, M.G.M. Khan, Sabiha Khan

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Calibration estimation is a method of adjusting the original design weights to improve the survey estimates by using auxiliary information such as the known population total (or mean) of the auxiliary variables. A calibration estimator uses calibrated weights that are determined to minimize a given distance measure to the original design weights while satisfying a set of constraints related to the auxiliary information. In this paper, we propose a new multivariate calibration estimator for the population mean in the stratified sampling design, which incorporates information available for more than one auxiliary variable. The problem of determining the optimum calibrated weights is formulated as a Mathematical Programming Problem (MPP) that is solved using the Lagrange multiplier technique.

Keywords: Calibration estimation, Stratified sampling, Multivariate auxiliary information, Mathematical programming problem, Lagrange multiplier technique.

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Authors: Chan Hee Park, Arim Lee, Jung Min Lee, Joo Hyun Moon

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Accident in spent fuel pool (SFP) of Fukushima Daiichi Unit 4 showed the importance of continuous monitoring of the key environmental parameters such as water temperature, water level, and radiation level in the SFP at accident conditions. Because the SFP water temperature is one of the key parameters indicating SFP conditions, its behavior at accident conditions shall be understood to prepare appropriate measures. This study estimated temporal change in the SFP water temperature at Kori Unit 1 with 587 MWe for 1 hour after initiation of a loss-of-pool-cooling accident. For the estimation, ANSYS CFX 13.0 code was used. The estimation showed that the increasing rate of the water temperature was 3.90C per hour and the SFP water temperature could reach 1000C in 25.6 hours after the initiation of loss-of-pool-cooling accident.

Keywords: Spent fuel pool, water temperature, Kori Unit 1, a loss-of-pool-cooling accident.

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Authors: Saurabh Chanana, Monika Arora

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Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand. 

Keywords: Demand response, Home energy management Programmable communicating thermostat, Thermostatically controlled appliances.

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Authors: Sang Hyun Kim

Abstract:

In this paper, a fast motion compensation algorithm is proposed that improves coding efficiency for video sequences with brightness variations. We also propose a cross entropy measure between histograms of two frames to detect brightness variations. The framewise brightness variation parameters, a multiplier and an offset field for image intensity, are estimated and compensated. Simulation results show that the proposed method yields a higher peak signal to noise ratio (PSNR) compared with the conventional method, with a greatly reduced computational load, when the video scene contains illumination changes.

Keywords: Motion estimation, Fast motion compensation, Brightness variation compensation, Brightness change detection, Cross entropy.

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Authors: H. Bakhshi, E. Khayyamian

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Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: Cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, Rayleigh fading channel.

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Authors: A. Falsafain, S. M. Taheri, M. Mashinchi

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Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameters of two Normal distributions, as well as the parameters of the Exponential and Poisson distributions.

Keywords: Confidence interval. Fuzzy number. Fuzzy estimation.

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Authors: Ajay Shekhar Pandey, D. Singh, S. K. Sinha

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A clustering based technique has been developed and implemented for Short Term Load Forecasting, in this article. Formulation has been done using Mean Absolute Percentage Error (MAPE) as an objective function. Data Matrix and cluster size are optimization variables. Model designed, uses two temperature variables. This is compared with six input Radial Basis Function Neural Network (RBFNN) and Fuzzy Inference Neural Network (FINN) for the data of the same system, for same time period. The fuzzy inference system has the network structure and the training procedure of a neural network which initially creates a rule base from existing historical load data. It is observed that the proposed clustering based model is giving better forecasting accuracy as compared to the other two methods. Test results also indicate that the RBFNN can forecast future loads with accuracy comparable to that of proposed method, where as the training time required in the case of FINN is much less.

Keywords: Load forecasting, clustering, fuzzy inference.

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Authors: Rami A. Maher, Ibraheem K. Ibraheem

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This work presents a comparison study between the state-space and polynomial methods for the design of the robust governor for load frequency control of steam turbine power systems. The robust governor is synthesized using the two approaches and the comparison is extended to include time and frequency domains performance, controller order, and uncertainty representation, weighting filters, optimality and sub-optimality. The obtained results are represented through tables and curves with reasons of similarities and dissimilarities.

Keywords: Robust control, load frequency control, steam turbine, H∞-norm, system uncertainty, load disturbance.

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Authors: Shih-Hsu Wang, Yuan-Yuan Cheng, Ming-Tsung Lee, Wei-Chih Wang

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Determining reasonable fees is the main objective of designing the cost estimation and payment systems for consultant contracts. However, project clients utilize different cost estimation and payment systems because of their varying views on the reasonableness of consultant fees. This study reviews the cost estimation and payment systems of consultant contracts for five countries, including the US (Washington State Department of Transportation), Japan (Ministry of Land, Infrastructure, Transport and Tourism), China (Engineering Design Charging Standard) and UK (Her Majesty's Treasure). Specifically, this work investigates the budgeting process, contractor selection method, contractual price negotiation process, cost review, and cost-control concept of the systems used in these countries. The main finding indicates that that project client-s view on whether the fee is high will affect the way he controls it. In the US, the fee is commonly considered to be high. As a result, stringent auditing system (low flexibility given to the consultant) is then applied. In the UK, the fee is viewed to be low by comparing it to the total life-cycle project cost. Thus, a system that has high flexibility in budgeting and cost reviewing is given to the consultant. In terms of the flexibility allowed for the consultant, the systems applied in Japan and China fall between those of the US and UK. Both the US and UK systems are helpful in determining a reasonable fee. However, in the US system, rigid auditing standards must be established and additional cost-audit manpower is required. In the UK system, sufficient historical cost data should be needed to evaluate the reasonableness of the consultant-s proposed fee

Keywords: Consultant Services, Cost Estimation and Payment System, Payment Flexibility, Cost-control Concept

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Authors: Keuk Jong Yu, Sang Hee Kang, Sung Chang You

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In Korea, the technology of a load fo nuclear power plant has been being developed. automatic controller which is able to control temperature and axial power distribution was developed. identification algorithm and a model predictive contact former transforms the nuclear reactor status into numerically. And the latter uses them and ge manipulated values such as two kinds of control ro this automatic controller, the performance of a coperation was evaluated. As a result, the automatic generated model parameters of a nuclear react to nuclear reactor average temperature and axial power the desired targets during a daily load follow.

Keywords: axial power distribution, model reactor temperature, system identification

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: Short term load forecasting, prediction interval, type 2 fuzzy logic systems.

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, Prediction modeling, rail track degradation.

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Authors: Azhar Hussain, Kashif Shahzad, Chunming Tang

Abstract:

this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.

Keywords: Defuzzification, Fuzzy similarity approach, lane cropping, Maximum a Posterior Probability (MAP) estimator, Speed estimation

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Authors: Hironori Kakuta, Kajiro Watanabe, Yosuke Kurihara

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Water leakage is a serious problem in the maintenance of a waterworks facility. Monitoring the water flow rate is one way to locate leakage. However, conventional flowmeters such as the wet-type flowmeter and the clamp-on type ultrasonic flowmeter require additional construction for their installation and are therefore quite expensive. This paper proposes a novel estimation system for the flow rate in a water pipeline, which employs a vibration sensor. This assembly can be attached to any water pipeline without the need for additional high-cost construction. The vibration sensor is designed based on a condenser microphone. This sensor detects vibration caused by water flowing through a pipeline. It is possible to estimate the water flow rate by measuring the amplitude of the output signal from the vibration sensor. We confirmed the validity of the proposed sensing system experimentally.

Keywords: Condenser microphone, Flow rate estimation, Piping vibration, Water pipe.

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Authors: V.K.Ananthashayana, Pushpa.M.K

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In this paper a new Joint Adaptive Block Matching Search (JABMS) algorithm is proposed to generate motion vector and search a best match macro block by classifying the motion vector movement based on prediction error. Diamond Search (DS) algorithm generates high estimation accuracy when motion vector is small and Adaptive Rood Pattern Search (ARPS) algorithm can handle large motion vector but is not very accurate. The proposed JABMS algorithm which is capable of considering both small and large motions gives improved estimation accuracy and the computational cost is reduced by 15.2 times compared with Exhaustive Search (ES) algorithm and is 1.3 times less compared with Diamond search algorithm.

Keywords: Adaptive rood pattern search, Block matching, Diamond search, Joint Adaptive search, Motion estimation.

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Authors: Mehran Pourgholi , Amin Lotfi Eghlim

Abstract:

These Nowadays the explosion of bombs or explosive materials such as gas and oil near or inside the buildings cause some losses in installations and building components. This has made the engineers to make the buildings and their components resistance against the effects of explosion. These activities lead to provide regulations and different methods. The above regulations are mostly focused on the explosion effects resulting from the vehicles around the buildings. Therefore, the explosion resulting from the vehicles outside the buildings will be studied in this research. In the present study, the main goals are to investigate the explosion load effects on the structures located on the piles with the specific quantity of plasticity and observing the permissible response of these structures. The concentrated mass system and the spring with two degree of freedom will be used to study the structural system.

Keywords: Concrete-Framework Building, Explosion Load, piles.

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Authors: B. Kędra, R. Małkowski

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This paper presents information on Power System Component Simulator – a device designed for LINTE^2 laboratory owned by Gdansk University of Technology in Poland. In this paper, we first provide an introductory information on the Power System Component Simulator and its capabilities. Then, the concept of the unit is presented. Requirements for the unit are described as well as proposed and introduced functions are listed. Implementation details are given. Hardware structure is presented and described. Information about used communication interface, data maintenance and storage solution, as well as used Simulink real-time features are presented. List and description of all measurements is provided. Potential of laboratory setup modifications is evaluated. Lastly, the results of experiments performed using Power System Component Simulator are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area.

Keywords: Power converter, Simulink real-time, MATLAB, load, tap controller.

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Authors: T. Yilmaz, N. Kirac

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Beam-column elements are defined as structural members subjected to a combination of axial and bending forces. Lateral torsional buckling is one of the major failure modes in which beam-columns that are bent about its strong axis may buckle out of the plane by deflecting laterally and twisting. This study presents a compact closed-form equation that it can be used for calculating critical lateral torsional-buckling load of beam-columns with monosymmetric sections in the presence of a known axial load. Lateral-torsional buckling behavior of beam-columns subjected to constant axial force and various transverse load cases are investigated by using Ritz method in order to establish proposed equation. Lateral-torsional buckling loads calculated by presented formula are compared to finite element model results. ABAQUS software is utilized to generate finite element models of beam-columns. It is found out that lateral-torsional buckling load of beam-columns with monosymmetric sections can be determined by proposed equation and can be safely used in design.

Keywords: Lateral-torsional buckling, stability, beam-column, monosymmetric section.

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