Search results for: statistical convergence

Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: Classification, classifier fusion, CNN, Deep Learning, prediction, SNR.

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Authors: J. Mehena, M. C. Adhikary

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In this paper, a spatial multiple-kernel fuzzy C-means (SMKFCM) algorithm is introduced for segmentation problem. A linear combination of multiples kernels with spatial information is used in the kernel FCM (KFCM) and the updating rules for the linear coefficients of the composite kernels are derived as well. Fuzzy cmeans (FCM) based techniques have been widely used in medical image segmentation problem due to their simplicity and fast convergence. The proposed SMKFCM algorithm provides us a new flexible vehicle to fuse different pixel information in medical image segmentation and detection of MR images. To evaluate the robustness of the proposed segmentation algorithm in noisy environment, we add noise in medical brain tumor MR images and calculated the success rate and segmentation accuracy. From the experimental results it is clear that the proposed algorithm has better performance than those of other FCM based techniques for noisy medical MR images.

Keywords: Clustering, fuzzy C-means, image segmentation, MR images, multiple kernels.

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Authors: L. Fauziana, M. F. Siti Atiqah, Z. A. Ahmad Noor Syukri

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The aim of the study was to identify seat belt wearing factor among road users in Malaysia. Evidence-based approach through in-depth crash investigation was utilised to determine the intended objectives. The objective was scoped into crashes investigated by Malaysian Institute of Road Safety Research (MIROS) involving passenger vehicles within 2007 and 2010. Crash information of a total of 99 crash cases involving 240 vehicles and 864 occupants were obtained during the study period. Statistical test and logistic regression analysis have been performed. Results of the analysis revealed that gender, seat position and age were associated with seat belt wearing compliance in Malaysia. Males are 97.6% more likely to wear seat belt compared to females (95% CI 1.317 to 2.964). By seat position, the finding indicates that frontal occupants were 82 times more likely to be wearing seat belt (95% CI 30.199 to 225.342) as compared to rear occupants. It is also important to note that the odds of seat belt wearing increased by about 2.64% (95% CI 1.0176 to 1.0353) for every one year increase in age. This study is essential in understanding the Malaysian tendency in belting up while being occupied in a vehicle. The factors highlighted in this study should be emphasized in road safety education in order to increase seat belt wearing rate in this country and ultimately in preventing deaths due to road crashes.

Keywords: crash investigation, risk compensation, road safety, seat belt wearing, statistical analysis.

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Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima

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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.

Keywords: Box-Jenkins’s problem, Double-input rule module, Fuzzy inference model, Obstacle avoidance, Single-input rule module.

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Authors: G. H. Senussi

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The present work is concerned with the effect of turning process parameters (cutting speed, feed rate, and depth of cut) and distance from the center of work piece as input variables on the chip micro-hardness as response or output. Three experiments were conducted; they were used to investigate the chip micro-hardness behavior at diameter of work piece for 30[mm], 40[mm], and 50[mm]. Response surface methodology (R.S.M) is used to determine and present the cause and effect of the relationship between true mean response and input control variables influencing the response as a two or three dimensional hyper surface. R.S.M has been used for designing a three factor with five level central composite rotatable factors design in order to construct statistical models capable of accurate prediction of responses. The results obtained showed that the application of R.S.M can predict the effect of machining parameters on chip micro-hardness. The five level factorial designs can be employed easily for developing statistical models to predict chip micro-hardness by controllable machining parameters. Results obtained showed that the combined effect of cutting speed at it?s lower level, feed rate and depth of cut at their higher values, and larger work piece diameter can result increasing chi micro-hardness.

Keywords: Machining Parameters, Chip Micro-Hardness, CNCMachining, 304-Austenic Stainless Steel.

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Authors: Roman Klas, František Pochylý, Pavel Rudolf

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This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design. 

Keywords: CFD, radiaxial pump, spiral case, stability

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Authors: Karuppaiya Maruthai, Viruthagiri Thangavelu, Manikandan Kanagasabai

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In the present study, effect of critical medium components (a total of fifteen components) on ethanol production from waste cashew apple juice (CAJ) using yeast Saccharomyces diasticus was studied. A statistical response surface methodology (RSM) based Plackett-Burman Design (PBD) was used for the design of experiments. The design contains a total of 32 experimental trails. The effect of medium components on ethanol was studied at two different levels such as low concentration level (-) and high concentration levels (+). The dependent variables selected in this study were ethanol concentration (g/L) and cellmass concentration (g/L). Data obtained from RSM on ethanol production were subjected to analysis of variance (ANOVA). In general, initial substrate concentration significantly influenced the microbial growth and product formation. Of the medium components evaluated, CAJ concentration, yeast extract, (NH4)2SO4, and malt extract showed significant effect on ethanol fermentation. A second-order polynomial model was used to predict the experimental data and the model fitted the data with a high correlation coefficient (R2 > 0.98). Maximum ethanol (15.3 g/L) and biomass (6.4 g/L) concentrations were obtained at the optimum medium composition and at optimum condition (temperature-30°C; initial pH-6.8) after 72 h fermentation using S.diasticus.

Keywords: cashew apple juice, ethanol, fermentation, yeast, response surface methodology

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Authors: N. Phanthuna V. Phupha N. Rugthaicharoencheep, S. Lerdwanittip

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This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction

Keywords: Particle Swarm Optimization, Economic Load Dispatch, Generator Constraints.

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Authors: Ibtisam Mahmoud Mohammed Sultan

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The present research aims at identifying the level of both emotional security and emotional competence among Tikrit University students. It also meant to know the statistically significant differences according to variables such as gender variables (m-f) and specialization variables (scientific-humanities). The research also attempts to learn what kind of relationship is there between emotional security and emotional efficiency Tikrit University students have achieved. We constructed emotional security measure which consists of 54 items as well as a measure of emotional competence consisting of 46 items. We extracted full psychometric characteristics of both scales. The research sample consisted of 600 students selected randomly and applying the scales on a basic research sample and processed statistical data using a variety of methods, including statistical measure Pearson correlation coefficient, we found a set of results as follows: Tikrit University students possess a high level of emotional security, males enjoy more emotional security than females, there is no difference between students of scientific and humanitarian specialization in variable emotional security, Tikrit University students enjoy a high level of emotional competence, females outperform males in emotional competence level, the humanitarian specialization students excel in emotional competence more than those specialized in non-humanitarian sciences. Furthermore, the research comes up with a positive correlative relationship between these two variables. Through research results, we developed a set of conclusions, proposals, and recommendations.

Keywords: Emotional security, gender variable, specialization variable, Tikrit University students.

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Authors: Ndidi F. Amulu, Godian O. Mbah, Maxwel I. Onyiah, Callistus N. Ude

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Analysis of the properties of coconut (Cocos nucifera) and its oil was evaluated in this work using standard analytical techniques. The analyses carried out include proximate composition of the fruit, extraction of oil from the fruit using different process parameters and physicochemical analysis of the extracted oil. The results showed the percentage (%) moisture, crude lipid, crude protein, ash and carbohydrate content of the coconut as 7.59, 55.15, 5.65, 7.35 and 19.51 respectively. The oil from the coconut fruit was odourless and yellowish liquid at room temperature (30oC). The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant differences (P<0.05) in the yield of oil from coconut flour. The oil yield ranged between 36.25%-49.83%. Lipid indices of the coconut oil indicated the acid value (AV) as 10.05Na0H/g of oil, free fatty acid (FFA) as 5.03%, saponification values (SV) as 183.26mgKOH-1g of oil, iodine value (IV) as 81.00 I2/g of oil, peroxide value (PV) as 5.00 ml/ g of oil and viscosity (V) as 0.002. A standard statistical package minitab version 16.0 program was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to generate various plots such as single effect plot, interactions effect plot and contour plot. The response or yield of oil from the coconut flour was used to develop a mathematical model that correlates the yield to the process variables studied. The maximum conditions obtained that gave the highest yield of coconut oil were leaching time of 2hrs, leaching temperature of 50oC and solute/solvent ratio of 0.05g/ml.

Keywords: Coconut, oil-extraction, optimization, physicochemical, proximate.

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Authors: V. Prapulla, A. Mitra, R. Bhattacharjee, S. Nandi

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We present a simplified equalization technique for a π/4 differential quadrature phase shift keying ( π/4 -DQPSK) modulated signal in a multipath fading environment. The proposed equalizer is realized as a fractionally spaced adaptive decision feedback equalizer (FS-ADFE), employing exponential step-size least mean square (LMS) algorithm as the adaptation technique. The main advantage of the scheme stems from the usage of exponential step-size LMS algorithm in the equalizer, which achieves similar convergence behavior as that of a recursive least squares (RLS) algorithm with significantly reduced computational complexity. To investigate the finite-precision performance of the proposed equalizer along with the π/4 -DQPSK modem, the entire system is evaluated on a 16-bit fixed point digital signal processor (DSP) environment. The proposed scheme is found to be attractive even for those cases where equalization is to be performed within a restricted number of training samples.

Keywords: Adaptive decision feedback equalizer, Fractionally spaced equalizer, π/4 DQPSK signal, Digital signal processor.

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Authors: Xiaoshu Lu, Päivi Leino-Arjas, Kustaa Piha, Akseli Aittomäki, Peppiina Saastamoinen, Ossi Rahkonen, Eero Lahelma

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Sickness absence represents a major economic and social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model selection and a critical analysis of the temporal trends, the occurrence and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model applicability to complicated longitudinal data.

Keywords: Sickness absence, longitudinal data, methodologies, mix-distribution model.

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Authors: P. Shunmugapriya, S. Kanmani, P. Jude Fredieric, U. Vignesh, J. Reman Justin, K. Vivek

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Vehicle Routing Problem (VRP) is a complex combinatorial optimization problem and it is quite difficult to find an optimal solution consisting of a set of routes for vehicles whose total cost is minimum. Evolutionary and swarm intelligent (SI) algorithms play a vital role in solving optimization problems. While the SI algorithms perform search, the diversity between the solutions they exploit is very important. This is because of the need to avoid early convergence and to get an appropriate balance between the exploration and exploitation. Therefore, it is important to check how far the solutions are diverse. In this paper, we measure the similarity between solutions, which ABC exploits while optimizing VRP. The similar solutions found are discarded at the end of the iteration and only unique solutions are passed on to the next iteration. The bees of discarded solutions become scouts and they start searching for new solutions. This process is continued and results show that the solution is optimized at lesser number of iterations but with the overhead of computing similarity in all the iterations. The problem instance from Solomon benchmarked dataset has been used for evaluating the presented methodology.

Keywords: ABC algorithm, vehicle routing problem, optimization, Jaccard’s similarity measure.

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Authors: Hadi Gholizadeh, Ali Tajdin

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: Goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression.

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Authors: Pramod Goyal, S. K. Saxena

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The convergence of heterogeneous wireless access technologies characterizes the 4G wireless networks. In such converged systems, the seamless and efficient handoff between different access technologies (vertical handoff) is essential and remains a challenging problem. The heterogeneous co-existence of access technologies with largely different characteristics creates a decision problem of determining the “best" available network at “best" time to reduce the unnecessary handoffs. This paper proposes a dynamic decision model to decide the “best" network at “best" time moment to handoffs. The proposed dynamic decision model make the right vertical handoff decisions by determining the “best" network at “best" time among available networks based on, dynamic factors such as “Received Signal Strength(RSS)" of network and “velocity" of mobile station simultaneously with static factors like Usage Expense, Link capacity(offered bandwidth) and power consumption. This model not only meets the individual user needs but also improve the whole system performance by reducing the unnecessary handoffs.

Keywords: Dynamic decision model, Seamless handoff, Vertical handoff, Wireless networks

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Authors: Udomsak Thongkrajay, Padej Pao-La-Or, Thanatchai Kulworawanichpong

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Installation of power compensation equipment in some cases places additional buses into the system. Therefore, a total number of power flow equations and voltage unknowns increase due to additional locations of installed devices. In this circumstance, power flow calculation is more complicated. It may result in a computational convergence problem. This paper presents a power flow calculation by using Newton-Raphson iterative method together with the proposed load transfer technique. This concept is to eliminate additional buses by transferring installed loads at the new buses to existing two adjacent buses. Thus, the total number of power flow equations is not changed. The overall computational speed is expectedly shorter than that of solving the problem without applying the load transfer technique. A 15-bus test system is employed for test to evaluate the effectiveness of the proposed load transfer technique. As a result, the total number of iteration required and execution time is significantly reduced.

Keywords: Load transfer technique, Newton-Raphson power flow, ill-condition

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Authors: A. Gandomkar, R. Dehghani

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Climate change is a phenomenon has been based on the available evidence from a very long time ago and now its existence is very probable. The speed and nature of climate parameters changes at the middle of twentieth century has been different and its quickness more than the before and its trend changed to some extent comparing to the past. Climate change issue now regarded as not only one of the most common scientific topic but also a social political one, is not a new issue. Climate change is a complicated atmospheric oceanic phenomenon on a global scale and long-term. Precipitation pattern change, fast decrease of snowcovered resources and its rapid melting, increased evaporation, the occurrence of destroying floods, water shortage crisis, severe reduction at the rate of harvesting agricultural products and, so on are all the significant of climate change. To cope with this phenomenon, its consequences and events in which public instruction is the most important but it may be climate that no significant cant and effective action has been done so far. The present article is included a part of one surrey about climate change in Fars. The study area having annually mean temperature 14 and precipitation 320 mm .23 stations inside the basin with a common 37 year statistical period have been applied to the meteorology data (1974-2010). Man-kendal and change factor methods are two statistical methods, applying them, the trend of changes and the annual mean average temperature and the annual minimum mean temperature were studied by using them. Based on time series for each parameter, the annual mean average temperature and the mean of annual maximum temperature have a rising trend so that this trend is clearer to the mean of annual maximum temperature.

Keywords: Climate change, Coefficient Variation, Fars province, Man-Kendal method.

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Authors: Fethi Soltani, Adel Almarashi, Idir Mechai

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Tikhonov regularization and reproducing kernels are the most popular approaches to solve ill-posed problems in computational mathematics and applications. And the Fourier multiplier operators are an essential tool to extend some known linear transforms in Euclidean Fourier analysis, as: Weierstrass transform, Poisson integral, Hilbert transform, Riesz transforms, Bochner-Riesz mean operators, partial Fourier integral, Riesz potential, Bessel potential, etc. Using the theory of reproducing kernels, we construct a simple and efficient representations for some class of Fourier multiplier operators Tm on the Paley-Wiener space Hh. In addition, we give an error estimate formula for the approximation and obtain some convergence results as the parameters and the independent variables approaches zero. Furthermore, using numerical quadrature integration rules to compute single and multiple integrals, we give numerical examples and we write explicitly the extremal function and the corresponding Fourier multiplier operators.

Keywords: Fourier multiplier operators, Gauss-Kronrod method of integration, Paley-Wiener space, Tikhonov regularization.

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Authors: Orkide Donma, Mustafa M. Donma

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Morbid obesity is a health threatening condition particularly in children. Generally, it leads to the development of metabolic syndrome (MetS) characterized by central obesity, elevated fasting blood glucose (FBG), triglyceride (TRG), blood pressure values and suppressed high density lipoprotein cholesterol (HDL-C) levels. However, some ambiguities exist during the diagnosis of MetS in children below 10 years of age. Therefore, clinicians are in the need of some surrogate markers for the laboratory assessment of pediatric MetS. In this study, the aim is to develop an index, which will be more helpful during the evaluation of further risks detected in morbid obese (MO) children. A total of 235 children with normal body mass index (N-BMI), with varying degrees of obesity; overweight (OW), obese (OB), MO as well as MetS participated in this study. The study was approved by the Institutional Ethical Committee. Informed consent forms were obtained from the parents of the children. Obesity states of the children were classified using BMI percentiles adjusted for age and sex. For the purpose, tabulated data prepared by WHO were used. MetS criteria were defined. Systolic and diastolic blood pressure values were measured. Parameters related to glucose and lipid metabolisms were determined. FBG, insulin (INS), HDL-C, TRG concentrations were determined. Diagnostic Obesity Notation Model Assessment Laboratory (DONMA_LAB) Index [ln TRG/HDL-C*INS] was introduced. Commonly used insulin resistance (IR) indices such as Homeostatic Model Assessment for IR (HOMA-IR) as well as ratios such as TRG/HDL-C, TRG/HDL-C*INS, HDL-C/TRG*INS, TRG/HDL-C*INS/FBG, log, and ln versions of these ratios were calculated. Results were interpreted using statistical package program (SPSS Version 16.0) for Windows. The data were evaluated using appropriate statistical tests. The degree for statistical significance was defined as 0.05. 35 N, 20 OW, 47 OB, 97 MO children and 36 with MetS were investigated. Mean ± SD values of TRG/HDL-C were 1.27 ± 0.69, 1.86 ± 1.08, 2.15 ± 1.22, 2.48 ± 2.35 and 4.61 ± 3.92 for N, OW, OB, MO and MetS children, respectively. Corresponding values for the DONMA_LAB index were 2.17 ± 1.07, 3.01 ± 0.94, 3.41 ± 0.93, 3.43 ± 1.08 and 4.32 ± 1.00. TRG/HDL-C ratio significantly differed between N and MetS groups. On the other hand, DONMA_LAB index exhibited statistically significant differences between N and all the other groups except the OW group. This index was capable of discriminating MO children from those with MetS. Statistically significant elevations were detected in MO children with MetS (p < 0.05). Multiple parameters are commonly used during the assessment of MetS. Upon evaluation of the values obtained for N, OW, OB, MO groups and for MO children with MetS, the [ln TRG/HDL-C*INS] value was unique in discriminating children with MetS.

Keywords: Children, index, laboratory, metabolic syndrome, obesity.

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Authors: A. R. Ommani, M. Chizari

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The purpose of the study reported here was designing Information Dissemination System (IDS) based E-learning in agricultural of Iran. A questionnaire was developed to designing Information Dissemination System. The questionnaire was distributed to 96 extension agents who work for Management of Extension and Farming System of Khuzestan province of Iran. Data collected were analyzed using the Statistical Package for the Social Sciences (SPSS). Appropriate statistical procedures for description (frequencies, percent, means, and standard deviations) were used. In this study there was a significant relationship between the age , IT skill and knowledge, years of extension work, the extend of information seeking motivation, level of job satisfaction and level of education with use of information technology by extension agent. According to extension agents five factors were ranked respectively as five top essential items to designing Information Dissemination System (IDS) based E-learning in agricultural of Iran. These factors include: 1) Establish communication between farmers, coordinators (extension agents), agricultural experts, research centers, and community by information technology. 2) The communication between all should be mutual. 3) The information must be based farmers need. 4) Internet used as a facility to transfer the advanced agricultural information to the farming community. 5) Farmers can be illiterate and speak a local and they are not expected to use the system directly. Knowledge produced by the agricultural scientist must be transformed in to computer understandable presentation. To designing Information Dissemination System, electronic communication, in the agricultural society and rural areas must be developed. This communication must be mutual between all factors.

Keywords: E-learning, information dissemination system, information technology.

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Authors: Chaiwat Waree

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This research aims at development of the Multiple Intelligences Measurement of Elementary Students. The structural accuracy test and normality establishment are based on the Multiple Intelligences Theory of Gardner. This theory consists of eight aspects namely linguistics, logic and mathematics, visual-spatial relations, body and movement, music, human relations, self-realization/selfunderstanding and nature. The sample used in this research consists of elementary school students (aged between 5-11 years). The size of the sample group was determined by Yamane Table. The group has 2,504 students. Multistage Sampling was used. Basic statistical analysis and construct validity testing were done using confirmatory factor analysis. The research can be summarized as follows; 1. Multiple Intelligences Measurement consisting of 120 items is content-accurate. Internal consistent reliability according to the method of Kuder-Richardson of the whole Multiple Intelligences Measurement equals .91. The difficulty of the measurement test is between .39-.83. Discrimination is between .21-.85. 2). The Multiple Intelligences Measurement has construct validity in a good range, that is 8 components and all 120 test items have statistical significance level at .01. Chi-square value equals 4357.7; p=.00 at the degree of freedom of 244 and Goodness of Fit Index equals 1.00. Adjusted Goodness of Fit Index equals .92. Comparative Fit Index (CFI) equals .68. Root Mean Squared Residual (RMR) equals 0.064 and Root Mean Square Error of Approximation equals 0.82. 3). The normality of the Multiple Intelligences Measurement is categorized into 3 levels. Those with high intelligence are those with percentiles of more than 78. Those with moderate/medium intelligence are those with percentiles between 24 and 77.9. Those with low intelligence are those with percentiles from 23.9 downwards.

Keywords: Multiple Intelligences, Measurement, Elementary Students.

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Authors: Mustafa M. Donma

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Metabolic syndrome (MetS) components are noteworthy among children with obesity and morbid obesity, because they point out the cases with MetS, which have the great tendency to severe health problems such as cardiovascular diseases both in childhood and adulthood. In clinical practice, considerable efforts are being observed to bring into the open the striking differences between morbid obese cases and those with MetS findings. The most privileged aspect is concerning cardiometabolic features. The aim of this study was to derive an index, which behaves different in children with and without MetS from the cardiac point of view. For the purpose, aspartate transaminase (AST), a cardiac enzyme still being used independently to predict cardiac-related problems was used. 124 children were recruited from the outpatient clinic of Department of Pediatrics in Tekirdag Namik Kemal University, Faculty of Medicine. 43 children with normal body mass index, 41 and 40 morbid obese (MO) children with MetS and without the characteristic features of MetS, respectively, were included in the study. Weight, height, waist circumference (WC), hip circumference (HC), head circumference (HdC), neck circumference (NC), systolic and diastolic blood pressure values were measured and recorded. Body mass index and anthropometric ratios were calculated. Fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein cholesterol (HDL-C) analyses were performed. The values for AST, alanine transaminase (ALT) and AST/ALT were obtained. Advanced Donma cardiac index (ADCI) values were calculated. Statistical evaluations including correlation analysis were done by a statistical package program. The statistical significance degree was accepted as p < 0.05. The index, ADCI, was developed from both anthropometric and biochemical parameters. All anthropometric measurements except weight were included in the equation. Besides all biochemical parameters concerning MetS components were also added. This index was tested in each of three groups. Its performance was compared with the performance of cardiometabolic index (CMI). It was also checked whether it was compatible with AST activity. The performance of ADCI was better than that of CMI. Instead of double increase, the increase of three times was observed in children with MetS compared to MO children. The index was correlated with AST in MO group and with AST/ALT in MetS group. In conclusion, this index was superior in discovering cardiac problems in MO and in diagnosing MetS in MetS groups. It was also arbiter to point out cardiovascular and MetS aspects among the groups.

Keywords: Aspartate transaminase, cardiac index, metabolic syndrome, obesity.

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Authors: T. O. Olwal, K. Djouani, B. J. van Wyk, Y. Hamam, P. Siarry, N. Ntlatlapa

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Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in wireless mesh networks (WMNs). In this paper, we present asynchronous multiple-state based power control for MRMC WMNs. First, WMN is represented as a set of disjoint Unified Channel Graphs (UCGs). Second, each network interface card (NIC) or radio assigned to a unique UCG adjusts transmission power using predicted multiple interaction state variables (IV) across UCGs. Depending on the size of queue loads and intra- and inter-channel states, each NIC optimizes transmission power locally and asynchronously. A new power selection MRMC unification protocol (PMMUP) is proposed that coordinates interactions among radios. The efficacy of the proposed method is investigated through simulations.

Keywords: Asynchronous convergence, Multi-Radio Multi-Channel (MRMC), Power Selection Multi-Radio Multi-Channel Unification Protocol (PMMUP) and Wireless Mesh Networks(WMNs)

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Authors: Rohit Gupta, Ravinder Agarwal

Abstract:

Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: Classifiers, feature selection, locomotion, sEMG.

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Authors: Sambit Prasad Kar, P.Palanisamy

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In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.

Keywords: Frequency estimation, peak search, subspace-based method without eigen decomposition, quadratic convex function.

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Authors: M. Esmaeeli Shahrakht, A. Kazemi

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Due to uncertainty of wind velocity, wind power generators don’t have deterministic output power. Utilizing wind power generation and thermal power plants together create new concerns for operation engineers of power systems. In this paper, a model is presented to implement the uncertainty of load and generated wind power which can be utilized in power system operation planning. Stochastic behavior of parameters is simulated by generating scenarios that can be solved by deterministic method. A mixed-integer linear programming method is used for solving deterministic generation scheduling problem. The proposed approach is applied to a 12-unit test system including 10 thermal units and 2 wind farms. The results show affectivity of piecewise linear model in unit commitment problems. Also using linear programming causes a considerable reduction in calculation times and guarantees convergence to the global optimum. Neglecting the uncertainty of wind velocity causes higher cost assessment of generation scheduling.

Keywords: Load uncertainty, linear programming, scenario generation, unit commitment, wind farm.

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Authors: Feras Al-Obeidat, Nabil Belacel, Juan A. Carretero, Prabhat Mahanti,

Abstract:

In this paper, a new learning algorithm based on a hybrid metaheuristic integrating Differential Evolution (DE) and Reduced Variable Neighborhood Search (RVNS) is introduced to train the classification method PROAFTN. To apply PROAFTN, values of several parameters need to be determined prior to classification. These parameters include boundaries of intervals and relative weights for each attribute. Based on these requirements, the hybrid approach, named DEPRO-RVNS, is presented in this study. In some cases, the major problem when applying DE to some classification problems was the premature convergence of some individuals to local optima. To eliminate this shortcoming and to improve the exploration and exploitation capabilities of DE, such individuals were set to iteratively re-explored using RVNS. Based on the generated results on both training and testing data, it is shown that the performance of PROAFTN is significantly improved. Furthermore, the experimental study shows that DEPRO-RVNS outperforms well-known machine learning classifiers in a variety of problems.

Keywords: Knowledge Discovery, Differential Evolution, Reduced Variable Neighborhood Search, Multiple criteria classification, PROAFTN, Supervised Learning.

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Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma

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All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.

Keywords: MIMO, Artificial Neural Network (ANN), CMA, LS, CSI.

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Authors: Orkide Donma, Mustafa M. Donma

Abstract:

Obesity may lead to growing serious health problems throughout the world. Vitamin D appears to play a role in cardiovascular and metabolic health. Vitamin D deficiency may add to derangements in human metabolic systems, particularly those of children. Childhood obesity is associated with an increased risk of chronic and sophisticated diseases. The aim of this study is to investigate associations as well as possible differences related to parameters affected by obesity and their relations with vitamin D status in obese (OB) and morbid obese (MO) children. This study included a total of 78 children. Of them, 41 and 37 were OB and MO, respectively. WHO BMI-for age percentiles were used for the classification of obesity. The values above 99 percentile were defined as MO. Those between 95 and 99 percentiles were included into OB group. Anthropometric measurements were recorded. Basal metabolic rates (BMRs) were measured. Vitamin D status is determined by the measurement of 25-hydroxy cholecalciferol [25- hydroxyvitamin D3, 25(OH)D] using high-performance liquid chromatography. Vitamin D status was evaluated as deficient, insufficient and sufficient. Values < 20.0 ng/ml, values between 20-30 ng/ml and values > 30.0 ng/ml were defined as vitamin D deficient, insufficient and sufficient, respectively. Optimal 25(OH)D level was defined as ≥ 30 ng/ml. SPSSx statistical package program was used for the evaluation of the data. The statistical significance degree was accepted as p < 0.05. Mean ages did not differ between the groups. Significantly increased body mass index (BMI), waist circumference (C) and neck C as well as significantly decreased fasting blood glucose (FBG) and vitamin D values were observed in MO group (p < 0.05). In OB group, 37.5% of the children were vitamin D deficient, and in MO group the corresponding value was 53.6%. No difference between the groups in terms of lipid profile, systolic blood pressure (SBP), diastolic blood pressure (DBP) and insulin values was noted. There was a severe statistical significance between FBG values of the groups (p < 0.001). Important correlations between BMI, waist C, hip C, neck C and both SBP as well as DBP were found in OB group. In MO group, correlations only with SBP were obtained. In a similar manner, in OB group, correlations were detected between SBP-BMR and DBP-BMR. However, in MO children, BMR correlated only with SBP. The associations of vitamin D with anthropometric indices as well as some lipid parameters were defined. In OB group BMI, waist C, hip C and triglycerides (TRG) were negatively correlated with vitamin D concentrations whereas none of them were detected in MO group. Vitamin D deficiency may contribute to the complications associated with childhood obesity. Loss of correlations between obesity indices-DBP, vitamin D-TRG, as well as relatively lower FBG values, observed in MO group point out that the emergence of MetS components starts during obesity state just before the transition to morbid obesity. Aside from its deficiency state, associations of vitamin D with anthropometric measurements, blood pressures and TRG should also be evaluated before the development of morbid obesity.

Keywords: Children, morbid obesity, obesity, vitamin D.

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Authors: Ahmed M. Farag, Wael F. Mohamed, Atef A. Ata, Burhamy M. Burhamy

Abstract:

The main objective of the present paper is to derive an easy numerical technique for the analysis of the free vibration through the stepped regions of plates. Based on the utilities of the step by step integration initial values IV and Finite differences FD methods, the present improved Initial Value Finite Differences (IVFD) technique is achieved. The first initial conditions are formulated in convenient forms for the step by step integrations while the upper and lower edge conditions are expressed in finite difference modes. Also compatibility conditions are created due to the sudden variation of plate thickness. The present method (IVFD) is applied to solve the fourth order partial differential equation of motion for stepped plate across two different panels under the sudden step compatibility in addition to different types of end conditions. The obtained results are examined and the validity of the present method is proved showing excellent efficiency and rapid convergence.

Keywords: Vibrations, Step by Step Integration, Stepped plate, Boundary.

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