Search results for: localization average error

Authors: Abdulrahman Abdulrahman

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When the Manning equation is used, a unique value of normal depth in the uniform flow exists for a given channel geometry, discharge, roughness, and slope. Depending on the value of normal depth relative to the critical depth, the flow type (supercritical or subcritical) for a given characteristic of channel conditions is determined whether or not flow is uniform. There is no general solution of Manning's equation for determining the flow depth for a given flow rate, because the area of cross section and the hydraulic radius produce a complicated function of depth. The familiar solution of normal depth for a rectangular channel involves 1) a trial-and-error solution; 2) constructing a non-dimensional graph; 3) preparing tables involving non-dimensional parameters. Author in this paper has derived semi-analytical solution to Manning's equation for determining the flow depth given the flow rate in rectangular open channel. The solution was derived by expressing Manning's equation in non-dimensional form, then expanding this form using Maclaurin's series. In order to simplify the solution, terms containing power up to 4 have been considered. The resulted equation is a quartic equation with a standard form, where its solution was obtained by resolving this into two quadratic factors. The proposed solution for Manning's equation is valid over a large range of parameters, and its maximum error is within -1.586%.

Keywords: Channel design, civil engineering, hydraulic engineering, open channel flow, Manning's equation, normal depth, uniform flow.

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Authors: S. Z. Sayed Hassen

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The load frequency control problem of power systems has attracted a lot of attention from engineers and researchers over the years. Increasing and quickly changing load demand, coupled with the inclusion of more generators with high variability (solar and wind power generators) on the network are making power systems more difficult to regulate. Frequency changes are unavoidable but regulatory authorities require that these changes remain within a certain bound. Engineers are required to perform the tricky task of adjusting the control system to maintain the frequency within tolerated bounds. It is well known that to minimize frequency variations, a large proportional feedback gain (speed regulation constant) is desirable. However, this improvement in performance using proportional feedback comes about at the expense of a reduced stability margin and also allows some steady-state error. A conventional PI controller is then included as a secondary control loop to drive the steadystate error to zero. In this paper, we propose a robust controller to replace the conventional PI controller which guarantees performance and stability of the power system over the range of variation of the speed regulation constant. Simulation results are shown to validate the superiority of the proposed approach on a simple single-area power system model.

Keywords: Robust control, power system, integral action, minimax LQG control.

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Authors: A. Giniatoulline

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A model of the mathematical fluid dynamics which describes the motion of a three-dimensional viscous rotating fluid in a homogeneous gravitational field with the consideration of the salinity and heat transfer is considered in a vertical finite layer. The model is a generalization of the linearized Navier-Stokes system with the addition of the Coriolis parameter and the equations for changeable density, salinity, and heat transfer. An explicit solution is constructed and the proof of the existence and uniqueness theorems is given. The localization and the structure of the spectrum of inner waves is also investigated. The results may be used, in particular, for constructing stable numerical algorithms for solutions of the considered models of fluid dynamics of the Atmosphere and the Ocean.

Keywords: Fourier transform, generalized solutions, Navier-Stokes equations, stratified fluid.

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

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Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: Airborne laser scanning, digital terrain models, filtering, forested areas.

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Authors: Altab Hossain, Ataur Rahman, A. K. M. Mohiuddin, Yulfian Aminanda

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Fuzzy logic system (FLS) is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring the vehicle traction force (TF), motion resistance (MR), cushion clearance height (CH) and cushion pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic system to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.

Keywords: Cushion pressure, Fuzzy logic, Motion resistance, Traction force.

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Authors: Somtop Keawchuer

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The objective of this research was to study the factors related to the satisfaction of consumers who purchased a Toyota SUV Fortuner. This paper was a survey data which collected 400 samples from 65 car dealerships. The survey was conducted mainly in Bangkok, Thailand. The statistics utilized in this paper included percentage, mean, standard deviation and Pearson Product-Moment. The findings revealed that the majority of respondent were male with an undergraduate degree, married and live together. The average income of the respondents was between 20,001 - 30,000 baht. Most of them worked for private companies. Most of them had a family with the average of 4 members. The hypotheses testing revealed that the factors of marketing mix in terms of product (ability, gas mileage, and safety) were related to overall satisfaction at the medium level. However, the findings also revealed that the factors of marketing mix in terms of product (image), price, and promotion, and service center were related to the overall satisfaction at the low level.

Keywords: Car Consumers, Factors related, Overall Satisfaction.

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Authors: Ching-Sheng Wang, Xin-Mao Huang, Ming-Yu Hung

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In this paper, we present a method named Signal Level Matrix (SLM) which can improve the accuracy and stability of active RFID indoor positioning system. Considering the accuracy and cost, we use uniform distribution mode to set up and separate the overlapped signal covering areas, in order to achieve preliminary location setting. Then, based on the proposed SLM concept and the characteristic of the signal strength value that attenuates as the distance increases, this system cross-examines the distribution of adjacent signals to locate the users more accurately. The experimental results indicate that the adaptive positioning method proposed in this paper could improve the accuracy and stability of the positioning system effectively and satisfyingly.

Keywords: RFID positioning, localization, indoor, location-aware.

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Authors: A. Soria-Salinas, M.-P. Zorzano, J. Martín-Torres, J. Sánchez-García-Casarrubios, J.-L. Pérez-Díaz, A. Vakkada-Ramachandran

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The current state-of-the-art methods of mass gauging of Electric Propulsion (EP) propellants in microgravity conditions rely on external measurements that are taken at the surface of the tank. The tanks are operated under a constant thermal duty cycle to store the propellant within a pre-defined temperature and pressure range. We demonstrate using computational fluid dynamics (CFD) simulations that the heat-transfer within the pressurized propellant generates temperature and density anisotropies. This challenges the standard mass gauging methods that rely on the use of time changing skin-temperatures and pressures. We observe that the domes of the tanks are prone to be overheated, and that a long time after the heaters of the thermal cycle are switched off, the system reaches a quasi-equilibrium state with a more uniform density. We propose a new gauging method, which we call the Improved PVT method, based on universal physics and thermodynamics principles, existing TRL-9 technology and telemetry data. This method only uses as inputs the temperature and pressure readings of sensors externally attached to the tank. These sensors can operate during the nominal thermal duty cycle. The improved PVT method shows little sensitivity to the pressure sensor drifts which are critical towards the end-of-life of the missions, as well as little sensitivity to systematic temperature errors. The retrieval method has been validated experimentally with CO₂ in gas and fluid state in a chamber that operates up to 82 bar within a nominal thermal cycle of 38 °C to 42 °C. The mass gauging error is shown to be lower than 1% the mass at the beginning of life, assuming an initial tank load at 100 bar. In particular, for a pressure of about 70 bar, just below the critical pressure of CO₂, the error of the mass gauging in gas phase goes down to 0.1% and for 77 bar, just above the critical point, the error of the mass gauging of the liquid phase is 0.6% of initial tank load. This gauging method improves by a factor of 8 the accuracy of the standard PVT retrievals using look-up tables with tabulated data from the National Institute of Standards and Technology.

Keywords: Electric propulsion, mass gauging, propellant, PVT, xenon.

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Authors: Ashraf M. A. Ahmad

Abstract:

Delivering streaming video over wireless is an important component of many interactive multimedia applications running on personal wireless handset devices. Such personal devices have to be inexpensive, compact, and lightweight. But wireless channels have a high channel bit error rate and limited bandwidth. Delay variation of packets due to network congestion and the high bit error rate greatly degrades the quality of video at the handheld device. Therefore, mobile access to multimedia contents requires video transcoding functionality at the edge of the mobile network for interworking with heterogeneous networks and services. Therefore, to guarantee quality of service (QoS) delivered to the mobile user, a robust and efficient transcoding scheme should be deployed in mobile multimedia transporting network. Hence, this paper examines the challenges and limitations that the video transcoding schemes in mobile multimedia transporting network face. Then handheld resources, network conditions and content based mobile and wireless video transcoding is proposed to provide high QoS applications. Exceptional performance is demonstrated in the experiment results. These experiments were designed to verify and prove the robustness of the proposed approach. Extensive experiments have been conducted, and the results of various video clips with different bit rate and frame rate have been provided.

Keywords: Content, Object detection, Transcoding, Texture, Temporal, Video.

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Authors: Altab Hossain, Ataur Rahman, A. K. M. Mohiuddin, Yulfian Aminanda

Abstract:

Fuzzy logic approach is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring the vehicle traction force (TF), motion resistance (MR), cushion clearance height (CH) and cushion pressure (CP). Sinkage measuring sensor, magnetic switch, pressure sensor, micro controller, control valves and battery are incorporated with the Fuzzy logic system (FLS) to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.

Keywords: Cushion pressure, Fuzzy logic, Motion resistance, Traction force.

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Authors: Anjan Kumar Kakati, M. Chandrasekaran, Amitava Mandal, Amit Kumar Singh

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End milling process is one of the common metal cutting operations used for machining parts in manufacturing industry. It is usually performed at the final stage in manufacturing a product and surface roughness of the produced job plays an important role. In general, the surface roughness affects wear resistance, ductility, tensile, fatigue strength, etc., for machined parts and cannot be neglected in design. In the present work an experimental investigation of end milling of aluminium alloy with carbide tool is carried out and the effect of different cutting parameters on the response are studied with three-dimensional surface plots. An artificial neural network (ANN) is used to establish the relationship between the surface roughness and the input cutting parameters (i.e., spindle speed, feed, and depth of cut). The Matlab ANN toolbox works on feed forward back propagation algorithm is used for modeling purpose. 3-12-1 network structure having minimum average prediction error found as best network architecture for predicting surface roughness value. The network predicts surface roughness for unseen data and found that the result/prediction is better. For desired surface finish of the component to be produced there are many different combination of cutting parameters are available. The optimum cutting parameter for obtaining desired surface finish, to maximize tool life is predicted. The methodology is demonstrated, number of problems are solved and algorithm is coded in Matlab®.

Keywords: End milling, Surface roughness, Neural networks.

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Authors: S. Panda, J. S. Yadav, N. P. Patidar, C. Ardil

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Order Reduction, Stability, Transfer Function, Integral Squared Error.

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Authors: Ana Pauna

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The Expert Witness Testimony in the Battered Woman Syndrome Expert witness testimony (EWT) is a kind of information given by an expert specialized in the field (here in BWS) to the jury in order to help the court better understand the case. EWT does not always work in favor of the battered women. Two main decision-making models are discussed in the paper: the Mathematical model and the Explanation model. In the first model, the jurors calculate ″the importance and strength of each piece of evidence″ whereas in the second model they try to integrate the EWT with the evidence and create a coherent story that would describe the crime. The jury often misunderstands and misjudges battered women for their action (or in this case inaction). They assume that these women are masochists and accept being mistreated for if a man abuses a woman constantly, she should and could divorce him or simply leave at any time. The research in the domain found that indeed, expert witness testimony has a powerful influence on juror’s decisions thus its quality needs to be further explored. One of the important factors that need further studies is a bias called the dispositionist worldview (a belief that what happens to people is of their own doing). This kind of attributional bias represents a tendency to think that a person’s behavior is due to his or her disposition, even when the behavior is clearly attributed to the situation. Hypothesis The hypothesis of this paper is that if a juror has a dispositionist worldview then he or she will blame the rape victim for triggering the assault. The juror would therefore commit the fundamental attribution error and believe that the victim’s disposition caused the rape and not the situation she was in. Methods The subjects in the study were 500 randomly sampled undergraduate students from McGill, Concordia, Université de Montréal and UQAM. Dispositional Worldview was scored on the Dispositionist Worldview Questionnaire. After reading the Rape Scenarios, each student was asked to play the role of a juror and answer a questionnaire consisting of 7 questions about the responsibility, causality and fault of the victim. Results The results confirm the hypothesis which states that if a juror has a dispositionist worldview then he or she will blame the rape victim for triggering the assault. By doing so, the juror commits the fundamental attribution error because he will believe that the victim’s disposition, and not the constraints or opportunities of the situation, caused the rape scenario.

Keywords: bias, expert/witness testimony, attribution error, jury, rape myth

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Authors: Routsukol Sunalai

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This research purpose is to study and compare the administration of Buddhist monks at northeastern Thailand. The samples used in the study are the priest in the Northeast by simple random sampling for 190 sampling. The tools used in this study is questioner were created in the 40 question items. The statistics used for data analysis were percentage, average, and standard deviation. The research found that the human resources management for the Buddhist monks as a whole is moderate. But it was found that the highest average is the policy followed by the management information. The Buddhist monks aged less than 25 years old with the overall difference was not significant. The priests who are less than 10 years in the monk experience and the priest has long held in the position for 10 years are not different in the significant level.

Keywords: Buddhist monks, human resources management, Northeastern Thailand, hotel industry, the administration of Buddhist monks.

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: Wavelet transform, computational error, computational duration, strong ground motion data.

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Authors: Bikramaditya Das, Susmita Das

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Study on suppression of interference in time domain equalizers is attempted for high data rate impulse radio (IR) ultra wideband communication system. The narrow band systems may cause interference with UWB devices as it is having very low transmission power and the large bandwidth. SRAKE receiver improves system performance by equalizing signals from different paths. This enables the use of SRAKE receiver techniques in IRUWB systems. But Rake receiver alone fails to suppress narrowband interference (NBI). A hybrid SRake-MMSE time domain equalizer is proposed to overcome this by taking into account both the effect of the number of rake fingers and equalizer taps. It also combats intersymbol interference. A semi analytical approach and Monte-Carlo simulation are used to investigate the BER performance of SRAKEMMSE receiver on IEEE 802.15.3a UWB channel models. Study on non-line of sight indoor channel models (both CM3 and CM4) illustrates that bit error rate performance of SRake-MMSE receiver with NBI performs better than that of Rake receiver without NBI. We show that for a MMSE equalizer operating at high SNR-s the number of equalizer taps plays a more significant role in suppressing interference.

Keywords: IR-UWB, UWB, IEEE 802.15.3a, NBI, data rate, bit error rate.

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Authors: I. Laurence Aroquiaraj, K. Thangavel

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Breast region segmentation is an essential prerequisite in computerized analysis of mammograms. It aims at separating the breast tissue from the background of the mammogram and it includes two independent segmentations. The first segments the background region which usually contains annotations, labels and frames from the whole breast region, while the second removes the pectoral muscle portion (present in Medio Lateral Oblique (MLO) views) from the rest of the breast tissue. In this paper we propose hybridization of Connected Component Labeling (CCL), Fuzzy, and Straight line methods. Our proposed methods worked good for separating pectoral region. After removal pectoral muscle from the mammogram, further processing is confined to the breast region alone. To demonstrate the validity of our segmentation algorithm, it is extensively tested using over 322 mammographic images from the Mammographic Image Analysis Society (MIAS) database. The segmentation results were evaluated using a Mean Absolute Error (MAE), Hausdroff Distance (HD), Probabilistic Rand Index (PRI), Local Consistency Error (LCE) and Tanimoto Coefficient (TC). The hybridization of fuzzy with straight line method is given more than 96% of the curve segmentations to be adequate or better. In addition a comparison with similar approaches from the state of the art has been given, obtaining slightly improved results. Experimental results demonstrate the effectiveness of the proposed approach.

Keywords: X-ray Mammography, CCL, Fuzzy, Straight line.

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Authors: Hai Quang Hong Dam, Hai Ho, Minh Hoang Le Ngo

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This paper investigates the problem of blind speech separation from the speech mixture of two speakers. A voice activity detector employing the Steered Response Power - Phase Transform (SRP-PHAT) is presented for detecting the activity information of speech sources and then the desired speech signals are extracted from the speech mixture by using an optimal beamformer. For evaluation, the algorithm effectiveness, a simulation using real speech recordings had been performed in a double-talk situation where two speakers are active all the time. Evaluations show that the proposed blind speech separation algorithm offers a good interference suppression level whilst maintaining a low distortion level of the desired signal.

Keywords: Blind speech separation, voice activity detector, SRP-PHAT, optimal beamformer.

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: Classifier ensemble, breast cancer survivability, data mining, SEER.

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Authors: Gautam Sarkar, Anjan Rakshit, Amitava Chatterjee, Kesab Bhattacharya

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The present paper describes the development of a low cost, highly accurate low capacitance measurement system that can be used over a range of 0 – 400 pF with a resolution of 1 pF. The range of capacitance may be easily altered by a simple resistance or capacitance variation of the measurement circuit. This capacitance measurement system uses quad two-input NAND Schmitt trigger circuit CD4093B with hysteresis for the measurement and this system is integrated with PIC 18F2550 microcontroller for data acquisition purpose. The microcontroller interacts with software developed in the PC end through USB architecture and an attractive graphical user interface (GUI) based system is developed in the PC end to provide the user with real time, online display of capacitance under measurement. The system uses a differential mode of capacitance measurement, with reference to a trimmer capacitance, that effectively compensates lead capacitances, a notorious error encountered in usual low capacitance measurements. The hysteresis provided in the Schmitt-trigger circuits enable reliable operation of the system by greatly minimizing the possibility of false triggering because of stray interferences, usually regarded as another source of significant error. The real life testing of the proposed system showed that our measurements could produce highly accurate capacitance measurements, when compared to cutting edge, high end digital capacitance meters.

Keywords: Capacitance measurement, NAND Schmitt trigger, microcontroller, GUI, lead compensation, hysteresis.

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Authors: Amjad Abdullah, Amjad Yahya, Bushra Aljohani, Amani S. Alghamdi

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Change point detection is an important part of data analysis. The presence of a change point refers to a significant change in the behavior of a time series. In this article, we examine the detection of multiple change points of parameters of the exponential Lomax distribution, which is broad and flexible compared with other distributions while fitting data. We used the Schwarz information criterion and binary segmentation to detect multiple change points in publicly available data on the average temperature in the ozone layer. The change points were successfully located.

Keywords: Binary segmentation, change point, exponential Lomax distribution, information criterion.

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Authors: Eman. K. Ramadan, Abdelgawad. S. El-Tahawy

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The objective of this study was to evaluate the effects of calving season on the production and economic efficiency of dairy farms in Egypt. Our study was performed at dairy production farms in the Alexandria, Behera, and Kafr El-Sheikh provinces of Egypt from summer 2010 to winter 2013. The randomly selected dairy farms had herds consisting of Baladi, Holstein-Friesian, or cross-bred (Baladi × Holstein-Friesian) cows. The data were collected from production records and responses to a structured questionnaire. The average total return differed significantly (P < 0.05) between the different cattle breeds and calving seasons. The average total return was highest for the Holstein- Friesian cows that calved in the winter (29106.42 EGP/cow/year), and it was lowest for Baladi cows that calved in the summer (12489.79 EGP/cow/year). Differences in total returns between the cows that calved in the winter or summer or between the foreign and native breeds, as well as variations in calf prices, might have contributed to the differences in milk yield. The average net profit per cow differed significantly (P < 0.05) between the cattle breeds and calving seasons. The average net profit values for the Baladi cows that calved in the winter or summer were 2413 and 2994.96 EGP/cow/year, respectively, and those for the Holstein- Friesian cows were 10744.17 and 7860.56 EGP/cow/year, respectively, whereas those for the cross-bred cows were 10174.86 and 7571.33 EGP/cow/year, respectively. The variations in net profit might have resulted from variation in the availability or price of feed materials, milk prices, or sales volumes. Our results show that the breed and calving season of dairy cows significantly affected the economic efficiency of dairy farms in Egypt. The cows that calved in the winter produced more milk than those that calved in the summer, which may have been the result of seasonal influences, such as temperature, humidity, management practices, and the type of feed or green fodder available.

Keywords:

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: Deep learning, long-short-term memory, energy, renewable energy load forecasting.

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Authors: J. S. Yadav, N. P. Patidar, J. Singhai, S. Panda, C. Ardil

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In this paper a mixed method by combining an evolutionary and a conventional technique is proposed for reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM). In the conventional technique, the mixed advantages of Mihailov stability criterion and continued Fraction Expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. Then, retaining the numerator polynomial, the denominator polynomial is recalculated by an evolutionary technique. In the evolutionary method, the recently proposed Differential Evolution (DE) optimization technique is employed. DE method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. The proposed method is illustrated through a numerical example and compared with ROM where both numerator and denominator polynomials are obtained by conventional method to show its superiority.

Keywords: Reduced Order Modeling, Stability, Mihailov Stability Criterion, Continued Fraction Expansions, Differential Evolution, Integral Squared Error.

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Authors: A. G. Margaryan

Abstract:

Ability of adaptation of the organism is considered as an important component of health in maintaining relative dynamic constancy of the hemostasis and functioning of all organs and systems. Among the various forms of adaptation (individual, species and mental), social adaptation of the organism has a particular role. The aim of this study was to evaluate the subjective perception of social factors, social welfare and the level of adaptability of Armenian physicians. The survey involved 2,167 physicians (592 men and 1,575 women). According to the survey, most physicians (75.1%) were married. It was found that 88.6% of respondents had harmonious family relationships, 7.6% of respondents – tense relationships, and 1.0% – marginal relationships. The results showed that the average monthly salary with all premium payments amounted to 88 263.6±5.0 drams, and 16.7% of physicians heavily relied on the material support of parents or other relatives. Low material welfare was also confirmed by the analysis of the living conditions. Analysis of the results showed that the degree of subjective perception of social factors of different specialties averaged 11.3±3.1 points, which corresponds to satisfactory results (a very good result – 4.0 points). The degree of social adaptation of physicians on average makes 4.13±1.9 points, which corresponds to poor results (allowable less than 3.0 points). The distribution of the results of social adaptation severity revealed that the majority of physicians (58.6%) showed low social adaptation, average social adaptation is observed in 22.4% of the physicians and high adaptation – in only 17.4% of physicians. In conclusions, the findings of this study suggest that the degree of social adaptation of currently practicing physicians is low.

Keywords: Physician's health, social adaptation, social factor, social health.

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Authors: Mamdouh Y. Saleh, Gaber EL Enany, Medhat H. Elzahar, Mohamed Z. Elshikhipy, Rana Hamouda

Abstract:

The heavy metals pollution in water, sediments and fish of Lake Manzala affected form the disposal of wastewater, industrial and agricultural drainage water into the lake on the environmental situation. A pilot plant with an industrial discharge flow of 135L/h designed according to the activated sludge plant to simulate between the biological and chemical treatment with the addition of alum to the aeration tank with dosages of 100, 150, 200 and 250 mg/L. The industrial discharge had concentrations of Lead and BOD₅ with an average range 1.22, 145mg/L respectively. That means the average Pb was high up to 25 times than the allowed permissible concentration. The optimization of the chemical-biological process using 200mg/L Alum dosage compared has improvement of Lead and BOD₅ removal efficiency to 61.76% and 56% respectively.

Keywords: Industrial wastewater, Activated sludge, BOD5, Lead, Alum salt.

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Authors: Vijay R. Khawale, Shashank B. Thakare

Abstract:

The experiment was carried out to study the performance of solar crop dryer coupled with reversed absorber type solar air heater (SD2). Excel software is used to analyse the raw data obtained from the drying experiment to develop a model. An attempt is made in this paper to correlate the collector efficiency, dryer efficiency and pick-up efficiency. All these efficiencies are dependent on the parameters such as solar flux, ambient temperature, collector outlet temperature and moisture content. The simulation equation was developed to predict the values of collector efficiency. The parameters a, n and drying constant k were determined from a plot of curve using a drying models. Experimental data of drying red chili in conventional solar dryer and solar dryer coupled with reversed absorber solar air heater was compared by fitting with three drying models. The moisture content will be rapidly reduced in solar dryer with reversed absorber due to higher drying temperatures. The best fit model was selected to describe the drying behavior of red chili. For SD2 the values of the coefficient of determination (R²=0.997), mean bias error (MBE=0.00026) and root mean square error (RMSE=0.016) were used to determine the goodness or the quality of the fit. Pages model showed a better fit to drying red chili among Newton model and Henderson & Pabis model.

Keywords: Solar dryer, red chili, reversed absorber, reflector, Buckingham pi theorem, drying model.

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Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi

Abstract:

In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index, average sample number, Bayesian approach.

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Authors: Jihyung Kim, Taejin Kim, Sungho Park, Jun-Dong Cho

Abstract:

In this paper, we address the problem of reducing the switching activity (SA) in on-chip buses through the use of a bus binding technique in high-level synthesis. While many binding techniques to reduce the SA exist, we present yet another technique for further reducing the switching activity. Our proposed method combines bus binding and data sequence reordering to explore a wider solution space. The problem is formulated as a multiple traveling salesman problem and solved using simulated annealing technique. The experimental results revealed that a binding solution obtained with the proposed method reduces 5.6-27.2% (18.0% on average) and 2.6-12.7% (6.8% on average) of the switching activity when compared with conventional binding-only and hybrid binding-encoding methods, respectively.

Keywords: low power, bus binding, switching activity, multiple traveling salesman problem, data sequence reordering

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Authors: Shih-Bin Wang, Ping Yuan, Syu-Fang Liu, Ming-Jun Kuo

Abstract:

By the application of an improved back-propagation neural network (BPNN), a model of current densities for a solid oxide fuel cell (SOFC) with 10 layers is established in this study. To build the learning data of BPNN, Taguchi orthogonal array is applied to arrange the conditions of operating parameters, which totally 7 factors act as the inputs of BPNN. Also, the average current densities achieved by numerical method acts as the outputs of BPNN. Comparing with the direct solution, the learning errors for all learning data are smaller than 0.117%, and the predicting errors for 27 forecasting cases are less than 0.231%. The results show that the presented model effectively builds a mathematical algorithm to predict performance of a SOFC stack immediately in real time. Also, the calculating algorithms are applied to proceed with the optimization of the average current density for a SOFC stack. The operating performance window of a SOFC stack is found to be between 41137.11 and 53907.89. Furthermore, an inverse predicting model of operating parameters of a SOFC stack is developed here by the calculating algorithms of the improved BPNN, which is proved to effectively predict operating parameters to achieve a desired performance output of a SOFC stack.

Keywords: a SOFC stack, BPNN, inverse predicting model of operating parameters, optimization of the average current density

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