Search results for: correlation matrix memory

Authors: Cenk Sezen, Turgay Partal

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North Sea Caspian Pattern Index (NCP) refers to an atmospheric teleconnection between the North Sea and North Caspian at the 500 hPa geopotential height level. The aim of this study is to search for effects of NCP on annual and seasonal mean temperature and also annual and seasonal precipitation totals in the Aegean region of Turkey. The study contains the data that consist of 46 years obtained from nine meteorological stations. To determine the relationship between NCP and the climatic parameters, firstly the Pearson correlation coefficient method was utilized. According to the results of the analysis, most of the stations in the region have a high negative correlation NCPI in all seasons, especially in the winter season in terms of annual and seasonal mean temperature (statistically at significant at the 90% level). Besides, high negative correlation values between NCPI and precipitation totals are observed during the winter season at the most of stations. Furthermore, the NCPI values were divided into two group as NCPI(-) and NCPI(+), and then mean temperature and precipitation total values, which are grouped according to the NCP(-) and NCP(+) phases, were determined as annual and seasonal. During the NCPI(-), higher mean temperature values are observed in all of seasons, particularly in the winter season compared to the mean temperature values under effect of NCP(+). Similarly, during the NCPI(-) in winter season precipitation total values have higher than the precipitation total values under the effect of NCP(+); however, in other seasons there no substantial changes were observed between the precipitation total values. As a result of this study, significant proof is obtained with regards to the influences of NCP on the temperature and precipitation regime in the Aegean region of Turkey.

Keywords: Aegean Region, North Sea Caspian Pattern, precipitation, temperature.

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Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

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In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: Energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis.

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Authors: Ayad Al-Mahturi, Herman Wahid

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This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed.

Keywords: Linear quadratic regulator, LQR controller, optimal control, particle swarm optimization, PSO, two-rotor aero-dynamical system, TRAS.

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Authors: O. S. Eludoyin, A. A. Aiyeloja, O. C. Ndife

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The study investigated the spatial analysis of trees composition, diversity and richness in the built up area of University of Port Harcourt, Nigeria. Four quadrats of 25m x 25m size were laid randomly in each of the three parks and inventories of trees ≥10cm girth at breast height were taken and used to calculate the species composition, diversity and richness. Results showed that species composition and diversity in Abuja Park was the highest with 134 species and 0.866 respectively while the species richness was highest in Choba Park with a value of 2.496. The correlation between the size of park (spatial coverage) and species composition was 0.99 while the correlation between the size of the park and species diversity was 0.78. There was direct relationship between species composition and diversity while the relationship between species composition and species richness was inversely proportional. Rational use of these resources is encouraged.

Keywords: Built up area, composition, diversity, richness, spatial analysis, urban tree.

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Authors: Aarati Susan Mathew, Radhika Narendra Patel, Jiji Mathew

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A retrospective study conducted at Christian Medical College (CMC) Teaching Hospital, Vellore, India on 14th August 2014 to assess the accuracy of clinically estimated foetal weight upon labour admission. Estimating foetal weight is a crucial factor in assessing maternal and foetal complications during and after labour. Medical notes of ninety-eight postnatal women who fulfilled the inclusion criteria were studied to evaluate the correlation between their recorded Estimated Foetal Weight (EFW) on admission and actual birth weight (ABW) of the newborn after delivery. Data concerning maternal and foetal demographics was also noted. Accuracy was determined by absolute percentage error and proportion of estimates within 10% of ABW. Actual birth weights ranged from 950-4080g. A strong positive correlation between EFW and ABW (r=0.904) was noted. Term deliveries (≥40 weeks) in the normal weight range (2500-4000g) had a 59.5% estimation accuracy (n=74) compared to pre-term (<40 weeks) with an estimation accuracy of 0% (n=2). Out of the term deliveries, macrosomic babies (>4000g) were underestimated by 25% (n=3) and low birthweight (LBW) babies were overestimated by 12.7% (n=9). Registrars who estimated foetal weight were accurate in babies within normal weight ranges. However, there needs to be an improvement in predicting weight of macrosomic and LBW foetuses. We have suggested the use of an amended version of the Johnson’s formula for the Indian population for improvement and a need to re-audit once implemented.

Keywords: Clinical palpation, estimated foetal weight, pregnancy, India, Johnson’s formula.

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Authors: Abbas Siefi, Mohammad Javad Karimifar

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We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.

Keywords: Spatial design of experiments, maximum entropy sampling, computer experiments, genetic algorithm.

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Authors: Munir Majdalawieh, Adam Marks

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In today’s very competitive higher education industry (HEI), HEIs are faced with the primary concern of developing, deploying, and sustaining high quality academic programs. Today, the HEI has well-established accreditation systems endorsed by a country’s legislation and institutions. The accreditation system is an educational pathway focused on the criteria and processes for evaluating educational programs. Although many aspects of the accreditation process highlight both the past and the present (prove), the “program review” assessment is "forward-looking assessment" (improve) and thus transforms the process into a continuing assessment activity rather than a periodic event. The purpose of this study is to propose a conceptual measurement framework for program review to be used by HEIs to undertake a robust and targeted approach to proactively and continuously review their academic programs to evaluate its practicality and effectiveness as well as to improve the education of the students. The proposed framework consists of two main components: program review principles and the program review measurement matrix.

Keywords: Academic program, program review principles, curriculum development, accreditation, evaluation, assessment, review measurement matrix, program review process, information technologies supporting learning, learning/teaching methodologies and assessment.

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Authors: U. Achutha Kini, S. S. Sharma, K. Jagannath, P. R. Prabhu, Gowri Shankar M. C.

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Aluminium matrix composites with alumina reinforcements give superior mechanical & physical properties. Their applications in several fields like automobile, aerospace, defense, sports, electronics, bio-medical and other industrial purposes are becoming essential for the last several decades. In the present work, fabrication of hybrid composite was done by Stir casting technique using Al 6061 as a matrix with alumina and silicon carbide (SiC) as reinforcement materials. The weight percentage of alumina is varied from 2 to 4% and the silicon carbide weight percentage is maintained constant at 2%. Hardness and wear tests are performed in the as cast and heat treated conditions. Age hardening treatment was performed on the specimen with solutionizing at 550°C, aging at two temperatures (150 and 200°C) for different time durations. Hardness distribution curves are drawn and peak hardness values are recorded. Hardness increase was very sensitive with respect to the decrease in aging temperature. There was an improvement in wear resistance of the peak aged material when aged at lower temperature. Also increase in weight percent of alumina, increases wear resistance at lower temperature but opposite behavior was seen when aged at higher temperature.

Keywords: Hybrid composite, hardness test, wear test, heat treatment, pin on disc wear testing machine.

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Authors: Hisashi Imai, Kuan-Yu Chen, Katsuyoshi Kondoh, Hung-Yin Tsai, Junko Umeda

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Microstructural and electrical properties of Cu-chromium alloy (Cu-Cr) dispersed with vapor-grown carbon fiber (VGCF) prepared by powder metallurgy (P/M) process have been investigated. Cu-0.7 mass% Cr pre-alloyed powder (Cu-Cr) made by water atomization process was used as raw materials, which contained solid solute Cr elements in Cu matrix. The alloy powder coated with un-bundled VGCF by using oil coating process was consolidated at 1223 K in vacuum by spark plasma sintering, and then extruded at 1073 K. The extruded Cu-Cr alloy (monolithic alloy) had 209.3 MPa YS and 80.4 IACS% conductivity. The extruded Cu-Cr with 0.1 mass% VGCF composites revealed a small decrease of YS compared to the monolithic Cu-Cr alloy. On the other hand, the composite had a higher electrical conductivity than that of the monolithic alloy. For example, Cu-Cr with 0.1 mass% VGCF composite sintered for 5 h showed 182.7 MPa YS and 89.7 IACS% conductivity. In the case of Cu-Cr with VGCFs composites, the Cr concentration was observed around VGCF by SEM-EDS analysis, where Cr23C6 compounds were detected by TEM observation. The amount of Cr solid solution in the matrix of the Cu-Cr composites alloy was about 50% compared to the monolithic Cu-Cr sintered alloy, and resulted in the remarkable increment of the electrical conductivity.

Keywords: Powder metallurgy Cu-Cr alloy powder, vapor-grown carbon fiber, electrical conductivity.

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Authors: Rose Shayeghi, Pejman Hosseinioun

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The Multiple Intelligences theory characterizes human intelligence as a multifaceted entity that exists in all human beings with varying degrees. The most important contribution of this theory to the field of English Language Teaching (ELT) is its role in identifying individual differences and designing more learnercentered programs. The present study aims at investigating the relationship between different elements of multiple intelligence and grammar scores. To this end, 63 female Iranian EFL learner selected from among intermediate students participated in the study. The instruments employed were a Nelson English language test, Michigan Grammar Test, and Teele Inventory for Multiple Intelligences (TIMI). The results of Pearson Product-Moment Correlation revealed a significant positive correlation between grammatical accuracy and linguistic as well as interpersonal intelligence. The results of Stepwise Multiple Regression indicated that linguistic intelligence contributed to the prediction of grammatical accuracy.

Keywords: Multiple intelligence, grammar, ELT, EFL, TIMI.

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Authors: Zeinab A.Hussein, Manal S. Abd El-Wahab, Shorouk A. W. El-Shennawy

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Children with hemiplgic cerebral palsy often walk with diminished reciprocal arm swing so the purpose of this study was to describe kinematic characteristics in children with hemiplegic cerebral palsy (CP) during the gait suphases, and find if there is a correlation between upper(shoulder and elbow) and lower(hip, knee, and ankle) limb joints either in involved or uninvolved.48 children with hemiplegic cerebral palsy (18boys, 30girls) with an average age of (5.1±0.87) years were selected randomly to evaluate joint angles during gait by 3D motion analysis system with 6 pro reflex cameras in a sagittal plane for both sides of the body. The results showed increased shoulder and elbow flexion, increased hip angular displacement, decreased knee and ankle arcs during gait cycle, also there is correlation between shoulder and elbow to hip, knee, and ankle joints during various subphases of gait.

Keywords: Cerebral palsy, Gait, Hemiplegia, Motion analysis.

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Authors: Michal Mardiak, Jaroslav Polec

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In this paper we proposed comparison of four content based objective metrics with results of subjective tests from 80 video sequences. We also include two objective metrics VQM and SSIM to our comparison to serve as “reference” objective metrics because their pros and cons have already been published. Each of the video sequence was preprocessed by the region recognition algorithm and then the particular objective video quality metric were calculated i.e. mutual information, angular distance, moment of angle and normalized cross-correlation measure. The Pearson coefficient was calculated to express metrics relationship to accuracy of the model and the Spearman rank order correlation coefficient to represent the metrics relationship to monotonicity. The results show that model with the mutual information as objective metric provides best result and it is suitable for evaluating quality of video sequences.

Keywords: Objective quality metrics, mutual information, region recognition, content based metrics

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Authors: Baisa L. Gunjal, Suresh N. Mali

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Medical images require special safety and confidentiality because critical judgment is done on the information provided by medical images. Transmission of medical image via internet or mobile phones demands strong security and copyright protection in telemedicine applications. Here, highly secured and robust watermarking technique is proposed for transmission of image data via internet and mobile phones. The Region of Interest (ROI) and Non Region of Interest (RONI) of medical image are separated. Only RONI is used for watermark embedding. This technique results in exact recovery of watermark with standard medical database images of size 512x512, giving 'correlation factor' equals to 1. The correlation factor for different attacks like noise addition, filtering, rotation and compression ranges from 0.90 to 0.95. The PSNR with weighting factor 0.02 is up to 48.53 dBs. The presented scheme is non blind and embeds hospital logo of 64x64 size.

Keywords: Compression, DWT, ROI, Scrambling, Vertices

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Authors: S. Mahmoodzadeh, J. Shahrabi, M. A. Torkamani, J. Sabaghzadeh Ghomi

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Recognizing behavioral patterns of financial markets is essential for traders. Japanese candlestick chart is a common tool to visualize and analyze such patterns in an economic time series. Since the world was introduced to Japanese candlestick charting, traders saw how combining this tool with intelligent technical approaches creates a powerful formula for the savvy investors. This paper propose a generalization to box counting method of Grassberger-Procaccia, which is based on computing the correlation dimension of Japanese candlesticks instead commonly used 'close' points. The results of this method applied on several foreign exchange rates vs. IRR (Iranian Rial). Satisfactorily show lower chaotic dimension of Japanese candlesticks series than regular Grassberger-Procaccia method applied merely on close points of these same candles. This means there is some valuable information inside candlesticks.

Keywords: Chaos, Japanese candlestick, generalized box counting, strange attractor.

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Authors: Sundararajan Sangeetha, Joseph Jesu Christopher, Swaminathan Ramakrishnan

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In this work, the primary compressive strength components of human femur trabecular bone are qualitatively assessed using image processing and wavelet analysis. The Primary Compressive (PC) component in planar radiographic femur trabecular images (N=50) is delineated by semi-automatic image processing procedure. Auto threshold binarization algorithm is employed to recognize the presence of mineralization in the digitized images. The qualitative parameters such as apparent mineralization and total area associated with the PC region are derived for normal and abnormal images.The two-dimensional discrete wavelet transforms are utilized to obtain appropriate features that quantify texture changes in medical images .The normal and abnormal samples of the human femur are comprehensively analyzed using Harr wavelet.The six statistical parameters such as mean, median, mode, standard deviation, mean absolute deviation and median absolute deviation are derived at level 4 decomposition for both approximation and horizontal wavelet coefficients. The correlation coefficient of various wavelet derived parameters with normal and abnormal for both approximated and horizontal coefficients are estimated. It is seen that in almost all cases the abnormal show higher degree of correlation than normals. Further the parameters derived from approximation coefficient show more correlation than those derived from the horizontal coefficients. The parameters mean and median computed at the output of level 4 Harr wavelet channel was found to be a useful predictor to delineate the normal and the abnormal groups.

Keywords: Image processing, planar radiographs, trabecular bone and wavelet analysis.

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Authors: Amine Rezzoug, Said Abdi, Nadjet Bouhelal, Ismail Daoud

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This paper investigates the application of metallic coatings on high fiber volume fraction carbon/epoxy polymer matrix composites. For the grip of the metallic layer, a method of modifying the surface of the composite by introducing a mixture of copper and steel powder (filler powders) which can reduce the impact of thermal spray particles. The powder was introduced to the surface at the time of the forming. Arc spray was used to project the zinc coating layer. The substrate was grit blasted to avoid poor adherence. The porosity, microstructure, and morphology of layers are characterized by optical microscopy, SEM and image analysis. The samples were studied also in terms of hardness and erosion resistance. This investigation did not reveal any visible evidence damage to the substrates. The hardness of zinc layer was about 25.94 MPa and the porosity was around (∼6.70%). The erosion test showed that the zinc coating improves the resistance to erosion. Based on the results obtained, we can conclude that thermal spraying allows the production of protective coating on PMC. Zinc coating has been identified as a compatible material with the substrate. The filler powders layer protects the substrate from the impact of hot particles and allows avoiding the rupture of brittle carbon fibers.

Keywords: Arc spray, coating, composite, erosion.

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Authors: Rezki Akkal, Mohamed Khodja, Slimane Azzi

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Acidification is a technique used in oil reservoirs to improve annual production, reduce the skin and increase the pressure of an oil well while eliminating the formation damage that occurs during the drilling process, completion and, amongst others, to create new channels allowing the easy circulation of oil around a producing well. This is achieved by injecting an acidizing fluid at a relatively low pressure to prevent fracturing formation. The treatment fluid used depends on the type and nature of the reservoir rock traversed as well as its petrophysical properties. In order to understand the interaction mechanisms between the treatment fluids used for the reservoir rock acidizing, several candidate wells for stimulation were selected in the large Hassi Messaoud deposit in southern Algeria. The stimulation of these wells is completed using different fluids composed mainly of HCl acid with other additives such as corrosion inhibitors, clay stabilizers and iron controllers. These treatment fluids are injected over two phases, namely with clean tube (7.5% HCl) and matrix aidizing with HCl (15%). The stimulation results obtained are variable according to the type of rock traversed and its mineralogical composition. These results show that there has been an increase in production flow and head pressure respectively from 1.99 m3 / h to 3.56 m3 / h and from 13 Kgf / cm2 to 20 kgf / cm2 in the sands formation having good petrophysical properties of (porosity = 16%) and low amount of clay (Vsh = 6%).

Keywords: Acidizing, Hassi-Messaoud reservoir, tube clean, matrix stimulation.

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Pranee Pathomchaiwat

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The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).

Keywords: English language, language learning strategies, English learning achievement, students majoring in English, Business English

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Authors: A. Mitra, Y. V. Subba Rao, S. R. M. Prasanna

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This paper proposes a new approach for image encryption using a combination of different permutation techniques. The main idea behind the present work is that an image can be viewed as an arrangement of bits, pixels and blocks. The intelligible information present in an image is due to the correlations among the bits, pixels and blocks in a given arrangement. This perceivable information can be reduced by decreasing the correlation among the bits, pixels and blocks using certain permutation techniques. This paper presents an approach for a random combination of the aforementioned permutations for image encryption. From the results, it is observed that the permutation of bits is effective in significantly reducing the correlation thereby decreasing the perceptual information, whereas the permutation of pixels and blocks are good at producing higher level security compared to bit permutation. A random combination method employing all the three techniques thus is observed to be useful for tactical security applications, where protection is needed only against a casual observer.

Keywords: Encryption, Permutation, Good key, Combinationalpermutation, Pseudo random index generator.

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Authors: V. Tereshchenko, V. Muravitskiy

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We consider the methods of construction simple polygons for a set S of n points and applying them for searching the minimal area polygon. In this paper we propose the approximate algorithm, which generates the simple polygonalizations of a fixed set of points and finds the minimal area polygon, in O (n3) time and using O(n2) memory.

Keywords: simple polygon, approximate algorithm, minimal area polygon, polygonalizations

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Authors: Towfeeq Fairooz, Salim Istyaq

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The passive electrical properties of a tissue depends on the intrinsic constituents and its structure, therefore by measuring the complex electrical impedance of the tissue it might be possible to obtain indicators of the tissue state or physiological activity [1]. Complete bio-impedance information relative to physiology and pathology of a human body and functional states of the body tissue or organs can be extracted by using a technique containing a fourelectrode measurement setup. This work presents the estimation measurement setup based on the four-electrode technique. First, the complex impedance is estimated by three different estimation techniques: Fourier, Sine Correlation and Digital De-convolution and then estimation errors for the magnitude, phase, reactance and resistance are calculated and analyzed for different levels of disturbances in the observations. The absolute values of relative errors are plotted and the graphical performance of each technique is compared.

Keywords: Electrical Impedance, Fast Fourier Transform, Additive White Gaussian Noise, Total Least Square, Digital De-Convolution, Sine-Correlation.

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Authors: Sen-Chi Yu, Wei-Hsin Hsu, Min-Ning Yu, Hao-Yi Hsu

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The aim of this study was to investigate the correlation between Facebook involvement and internet addiction. We sampled 577 university students in Taiwan and administered a survey of Facebook usage, Facebook involvement scale (FIS), and internet addiction scale. The FIS comprises three factors (salience, emotional support, and amusement). Results showed that the Facebook involvement scale had good reliability and validity. The correlation between Facebook involvement and internet addiction was measured at .395. This means that a higher degree of Facebook involvement indicates a greater degree of psychological dependency on the internet, and a greater propensity towards social withdrawal and other negative psychological consequences associated with internet addiction. Besides, the correlations between three factors of FIS (salience, emotional support, and amusement) and internet addiction ranged from .313-372, indicating that these neither of these factors (salience, emotional support, and amusement) is more effective than the others in predicting internet dependency.

Keywords: Social networking sites, Facebook, Facebook Involvement, Internet Addiction

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Authors: Popoola, C. F., Akinsanya, K., Babarinde, S. B., Farinde, D. A.

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This study investigated published financial statement as correlate of investment decision among commercial bank stakeholders in Nigeria. A correlation research design was used in the study. 180 users of published financial statement were purposively sampled from Lagos and Ibadan. Data generated were analyzed using Pearson correlation and regression. The findings of the study revealed that, balance sheet is negatively related with investment decision (r= -.483; p<.01) while income statement (r= .249; p<.001), notes on the account (r= .230; p<.001), cash flow statement (r= .202; p<.001), value added statement (r= .328; p<.001) and five-year financial summary (r= .191; p<.01) are positively related with investment decision. Findings also revealed that components of published financial statement significantly predicted good investment decision (R²= .983; F_(5,175)=284.5; p<.05) for commercial bank stakeholders. Therefore, it was suggested that Nigeria banks and professional bodies should instigate programs that will increase the knowledge of stakeholders on published financial statement.

Keywords: Commercial banks, Financial statement, Income Statement, Investment decision, Stakeholders.

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Authors: Rehab I. Abdul Rahman, Mazhar B. Tayel

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This paper presents a method of hardening the 8051 micro-controller, able to assure reliable operation in the presence of bit flips caused by radiation. Aiming at avoiding such faults in the 8051 micro-controller, Hamming code protection was used in its SRAM memory and registers. A VHDL code has been used for this hamming code protection.

Keywords: Radiation, hardening, bitflip, hamming code.

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Authors: M. Hajzler, J. Klimesova, T. Streda, K. Vejrazka, V. Marecek, T. Cholastova

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The most planted cover crops in the Czech Republic are mustard (Sinapis alba) and phacelia (Phacelia tanacetifolia Benth.). A field trial was executed to evaluate root system size (RSS) in eight varieties of mustard and five varieties of phacelia on two locations, in three BBCH phases and in two years. The relationship between RSS and aboveground biomass was inquired. The root system was assessed by measuring its electric capacity. Aboveground mass and root samples to be evaluated by means of a digital image analysis were recovered in the BBCH phase 70. The yield of aboveground biomass of mustard was always statistically significantly higher than that of phacelia. Mustard showed a statistically significant negative correlation between root length density (RLD) within 10 cm and aboveground biomass weight (r = - 0.46*). Phacelia featured a statistically significant correlation between aboveground biomass production and nitrate nitrogen content in soil (r=0.782**).

Keywords: Aboveground Biomass, Cover crop, Nitrogen content, Root system size

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Authors: Shohreh Ajoudanian, Mohammad Davarpanah Jazi

Abstract:

The rapid expansion of the web is causing the constant growth of information, leading to several problems such as increased difficulty of extracting potentially useful knowledge. Web content mining confronts this problem gathering explicit information from different web sites for its access and knowledge discovery. Query interfaces of web databases share common building blocks. After extracting information with parsing approach, we use a new data mining algorithm to match a large number of schemas in databases at a time. Using this algorithm increases the speed of information matching. In addition, instead of simple 1:1 matching, they do complex (m:n) matching between query interfaces. In this paper we present a novel correlation mining algorithm that matches correlated attributes with smaller cost. This algorithm uses Jaccard measure to distinguish positive and negative correlated attributes. After that, system matches the user query with different query interfaces in special domain and finally chooses the nearest query interface with user query to answer to it.

Keywords: Content mining, complex matching, correlation mining, information extraction.

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Authors: Benjamin D. Leiby, Darryl K. Ahner

Abstract:

This study demonstrates an alternative stochastic imputation approach for large datasets when preferred commercial packages struggle to iterate due to numerical problems. A large country conflict dataset motivates the search to impute missing values well over a common threshold of 20% missingness. The methodology capitalizes on correlation while using model residuals to provide the uncertainty in estimating unknown values. Examination of the methodology provides insight toward choosing linear or nonlinear modeling terms. Static tolerances common in most packages are replaced with tailorable tolerances that exploit residuals to fit each data element. The methodology evaluation includes observing computation time, model fit, and the comparison of known  values to replaced values created through imputation. Overall, the country conflict dataset illustrates promise with modeling first-order interactions, while presenting a need for further refinement that mimics predictive mean matching.

Keywords: Correlation, country conflict, imputation, stochastic regression.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

Abstract:

This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. Crisp description for a concept usually cannot represent human knowledge completely and practically. In the proposed Learning Classifier System initial population is constructed as a random collection of HPR–trees (related production rules) and crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is suggested for the proposed system and based on Subsumption Matrix (SM), a suitable fitness function is proposed. Suitable genetic operators are proposed for the chosen chromosome representation method. For implementing reinforcement a suitable reward and punishment scheme is also proposed. Experimental results are presented to demonstrate the performance of the proposed system.

Keywords: Hierarchical Production Rule, Data Mining, Learning Classifier System, Fuzzy Subsumption Relation, Subsumption matrix, Reinforcement Learning.

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Authors: Innocent Kafodya, Guijun Xian

Abstract:

This paper presents effects of distilled water, seawater and sustained bending strains of 30% and 50% ultimate strain at room temperature, on the durability of unidirectional pultruded carbon fiber reinforced polymer (CFRP) plates. In this study, dynamic mechanical analyzer (DMA) was used to investigate the synergic effects of the immersions and bending strains on the viscoelastic properties of (CFRP) such as storage modulus, tan delta and glass transition temperature. The study reveals that the storage modulus and glass transition temperature increase while tan delta peak decreases in the initial stage of both immersions due to the progression of curing. The storage modulus and Tg subsequently decrease and tan delta increases due to the matrix plasticization. The blister induced damages in the unstrained seawater samples enhance water uptake and cause more serious degradation of Tg and storage modulus than in water immersion. Increasing sustained bending decreases Tg and storage modulus in a long run for both immersions due to resin matrix cracking and debonding. The combined effects of immersions and strains are not clearly reflected due to the statistical effects of DMA sample sizes and competing processes of molecular reorientation and postcuring.

Keywords: Pultruded CFRP plate, bending strain, glass transition temperature, storage modulus, tan delta.

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