Search results for: Framework for evaluation.

Authors: Boon Yih Mah

Abstract:

Web-based Cognitive Writing Instruction (WeCWI) is a hybrid e-framework for the development of a web-based instruction (WBI), which contributes towards instructional design and language development. WeCWI divides its contribution in instructional design into macro and micro perspectives. In macro perspective, being a 21st century educator by disseminating knowledge and sharing ideas with the in-class and global learners is initiated. By leveraging the virtue of technology, WeCWI aims to transform an educator into an aggregator, curator, publisher, social networker and ultimately, a web-based instructor. Since the most notable contribution of integrating technology is being a tool of teaching as well as a stimulus for learning, WeCWI focuses on the use of contemporary web tools based on the multiple roles played by the 21st century educator. The micro perspective in instructional design draws attention to the pedagogical approaches focusing on three main aspects: reading, discussion, and writing. With the effective use of pedagogical approaches through free reading and enterprises, technology adds new dimensions and expands the boundaries of learning capacity. Lastly, WeCWI also imparts the fundamental theories and models for web-based instructors’ awareness such as interactionist theory, cognitive information processing (CIP) theory, computer-mediated communication (CMC), e-learning interactionalbased model, inquiry models, sensory mind model, and leaning styles model.

Keywords: WeCWI, instructional discovery, technological discovery, pedagogical discovery, theoretical discovery.

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: Artificial Intelligence, machine learning, deep learning, convolutional neural networks.

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Authors: Daniel Y. Abebe, Jaehyouk Choi

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The idea of adding metallic energy dissipaters to a structure to absorb a large part of the seismic energy began four decades ago. There are several types of metal-based devices conceived as dampers for the seismic energy absorber whereby damages to the major structural components could be minimized for both new and existing structures. This paper aimed to develop and evaluate structural performance of both stiffened and non stiffened circular shear panel damper for passive seismic energy protection by inelastic deformation. Structural evaluation was done using commercially available nonlinear FE simulation program. Diameter-to-thickness ratio is employed as main parameter to investigate the hysteresis performance of stiffened and unstiffened circular shear panel. Depending on these parameters three different buckling mode and hysteretic behavior was found: yielding prior to buckling without strength degradation, yielding prior to buckling with strength degradation and yielding with buckling and strength degradation which forms pinching at initial displacement. Hence, the hysteresis behavior is identified, specimens which deform without strength degradation so it will be used as passive energy dissipating device in civil engineering structures.

Keywords: Circular shear panel damper, FE analysis, Hysteretic behavior, Large deformation.

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Authors: Vijay Shankar

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Evapotranspiration (ET) is a major component of the hydrologic cycle and its accurate estimation is essential for hydrological studies. In past, various estimation methods have been developed for different climatological data, and the accuracy of these methods varies with climatic conditions. Reference crop evapotranspiration (ET0) is a key variable in procedures established for estimating evapotranspiration rates of agricultural crops. Values of ET0 are used with crop coefficients for many aspects of irrigation and water resources planning and management. Numerous methods are used for estimating ET0. As per internationally accepted procedures outlined in the United Nations Food and Agriculture Organization-s Irrigation and Drainage Paper No. 56(FAO-56), use of Penman-Monteith equation is recommended for computing ET0 from ground based climatological observations. In the present study, seven methods have been selected for performance evaluation. User friendly software has been developed using programming language visual basic. The visual basic has ability to create graphical environment using less coding. For given data availability the developed software estimates reference evapotranspiration for any given area and period for which data is available. The accuracy of the software has been checked by the examples given in FAO-56.The developed software is a user friendly tool for estimating ET0 under different data availability and climatic conditions.

Keywords: Crop coefficient, Crop evapotranspiration, Field moisture, Irrigation Scheduling.

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Authors: Mojtaba Heydarizad

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Andarokh basin is one of the main karstic regions in Khorasan Razavi province NE Iran. This basin is part of Kopeh-Dagh mega zone extending from Caspian Sea in the east to northern Afghanistan in the west. This basin is covered by Mozdooran Formation, Ngr evaporative formation and quaternary alluvium deposits in descending order of age. Mozdooran carbonate formation is notably karstified. The main surface karstic features in Mozdooran formation are Groove karren, Cleft karren, Rain pit, Rill karren, Tritt karren, Kamintza, Domes, and Table karren. In addition to surface features, deep karstic feature Andarokh Cave also exists in the region. Studying Ca, Mg, Mn, Sr, Fe concentration and Sr/Mn ratio in Mozdooran formation samples with distance to main faults and joints system using PCA analyses demonstrates intense meteoric digenesis role in controlling carbonate rock geochemistry. The karst evaluation in Andarokh basin varies from early stages 'deep seated karst' in Mesozoic to mature karstic system 'Exhumed karst' in quaternary period. Andarokh cave (the main cave in Andarokh basin) is rudimentary branch work consists of three passages of A, B and C and two entrances Andarokh and Sky.

Keywords: Andarokh basin, Andarokh cave, geochemical analyses and karst evaluation.

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Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

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The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: Logistic Regression LoR, Kernel Density Estimator KDE, Handwriting, Confidence Interval, Repeatability, Reproducibility.

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Authors: A. A. Ladele, N. T. Meludu, O. Ezekiel, T. F. Olaoye, O. M. Okanlawon

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Value addition to agricultural produce is of possible potential in reducing poverty, improving food security and malnutrition, therefore the need to develop small and microenterprises of sweet potato production. A study was carried out in Nigeria to determine the acceptability of blends sweet potato (Ipomea batatas) and commodities yellow maize (Zea mays), millet (Pennisetum glaucum), soybean (Glycine max), bambara groundnut (Vigna subterranean), guinea corn (Sorghum vulgare), wheat (Triticum aestivum), and roselle (Hibiscus sabdariffa) through sensory evaluation. Sweet potato (Ipomea batatas) roots were processed using two methods: oven and sun drying. The blends were also assessed in terms of functional, chemical and color properties. Most acceptable blends include BAW (80:20 of sweet potato/wheat), BBC (80:20 of sweet potato/guinea corn), AAB (60:40 of sweet potato/guinea corn), YTE (100% soybean), TYG (100% sweet potato), KTN (100% wheat flour), XGP (80:20 of sweet potato/soybean), XAX (60:40 of sweet potato/wheat), LSS (100% Roselle), CHK (100% Guinea corn), and ABC (60:40% of sweet potato/ yellow maize). In addition, carried out chemical analysis revealed that sweet potato has high percentage of vitamins A and C, potassium (K), manganese (Mn), calcium (Ca), magnesium (Mg) and iron (Fe) and fibre content. There is also an increase of vitamin A and Iron in the blended products.

Keywords: Blends, diversification, sensory evaluation, sweet potato, utilization.

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Authors: Sarabjeet Kaur Kochhar

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With a surge of stream processing applications novel techniques are required for generation and analysis of association rules in streams. The traditional rule mining solutions cannot handle streams because they generally require multiple passes over the data and do not guarantee the results in a predictable, small time. Though researchers have been proposing algorithms for generation of rules from streams, there has not been much focus on their analysis. We propose Association rule profiling, a user centric process for analyzing association rules and attaching suitable profiles to them depending on their changing frequency behavior over a previous snapshot of time in a data stream. Association rule profiles provide insights into the changing nature of associations and can be used to characterize the associations. We discuss importance of characteristics such as predictability of linkages present in the data and propose metric to quantify it. We also show how association rule profiles can aid in generation of user specific, more understandable and actionable rules. The framework is implemented as SUPAR: System for Usercentric Profiling of Association Rules in streaming data. The proposed system offers following capabilities: i) Continuous monitoring of frequency of streaming item-sets and detection of significant changes therein for association rule profiling. ii) Computation of metrics for quantifying predictability of associations present in the data. iii) User-centric control of the characterization process: user can control the framework through a) constraint specification and b) non-interesting rule elimination.

Keywords: Data Streams, User subjectivity, Change detection, Association rule profiles, Predictability.

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Authors: Valentina Obradović, Josip Mesić, Maja Ergović Ravančić, Kamila Mijowska, Brankica Svitlica

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French oak and American oak barrels are most famous all over the world, but barrels of different origin can also be used for obtaining high quality wines. The aim of this research was to compare the influence of different Slovenian (Croatian) and French oak barrels on the quality of Chardonnay wine. Grapes were grown in the Croatian wine growing region of Kutjevo in 2015. Chardonnay wines were tested for basic oenological parameters (alcohol, extract, reducing sugar, SO₂, acidity), total polyphenols content (Folin-Ciocalteu method), antioxidant activity (ABTS and DPPH method) and colour density. Sensory evaluation was performed by students of viticulture/oenology. Samples produced by classical fermentation and ageing in French oak barrels had better results for polyphenols and sensory evaluation (especially low toasting level) than samples in Slovenian barrels. All tested samples were scored as a “quality” or “premium quality” wines. Sur lie method of fermentation and ageing in Slovenian oak barrel had very good extraction of polyphenols and high antioxidant activity with the usage of authentic yeasts, while commercial yeast strain resulted in worse chemical and sensory parameters.

Keywords: Chardonnay, French oak, Slovenian oak, sur lie.

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Authors: Wojciech Górecki, Anna Sowiżdżał, Grzegorz Machowski, Tomasz Maćkowski, Bartosz Papiernik, Michał Stefaniuk

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The article shows results of the project which aims at evaluating possibilities of effective development and exploitation of natural gas from argillaceous series of the Autochthonous Miocene in the Carpathian Foredeep. To achieve the objective, the research team develop a world-trend based but unique methodology of processing and interpretation, adjusted to data, local variations and petroleum characteristics of the area. In order to determine the zones in which maximum volumes of hydrocarbons might have been generated and preserved as shale gas reservoirs, as well as to identify the most preferable well sites where largest gas accumulations are anticipated a number of task were accomplished. Evaluation of petrophysical properties and hydrocarbon saturation of the Miocene complex is based on laboratory measurements as well as interpretation of well-logs and archival data. The studies apply mercury porosimetry (MICP), micro CT and nuclear magnetic resonance imaging (using the Rock Core Analyzer). For prospective location (e.g. central part of Carpathian Foredeep – Brzesko-Wojnicz area) reprocessing and reinterpretation of detailed seismic survey data with the use of integrated geophysical investigations has been made. Construction of quantitative, structural and parametric models for selected areas of the Carpathian Foredeep is performed on the basis of integrated, detailed 3D computer models. Modeling are carried on with the Schlumberger’s Petrel software. Finally, prospective zones are spatially contoured in a form of regional 3D grid, which will be framework for generation modelling and comprehensive parametric mapping, allowing for spatial identification of the most prospective zones of unconventional gas accumulation in the Carpathian Foredeep. Preliminary results of research works indicate a potentially prospective area for occurrence of unconventional gas accumulations in the Polish part of Carpathian Foredeep.

Keywords: Autochthonous Miocene, Carpathian Foredeep, Poland, shale gas.

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Authors: Jindřiška Šedová

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In the past 20 years the economy of the Czech Republic has experienced substantial changes. In the 1990s the development was affected by the transformation which sought to establish the right conditions for privatization and creation of elementary market relations. In the last decade the characteristic elements such as private ownership and corresponding institutional framework have been strengthened. This development was marked by the accession of the Czech Republic to the EU. The Czech Republic is striving to reduce the difference between its level of economic development and the quality of institutional framework in comparison with other developed countries. The process of finding the adequate solutions has been hampered by the negative impact of the world financial crisis on the Czech Republic and the standard of living of its inhabitants. This contribution seeks to address the question of whether and to which extent the economic development of the transitive Czech economy is affected by the change in behaviour of households and their tendency to consumption, i.e. in the sense of reduction or increase in demand for goods and services. It aims to verify whether the increasing trend of household indebtedness and decreasing trend of saving pose a significant risk in the Czech Republic. At a general level the analysis aims to contribute to finding an answer to the question of whether the debt increase of Czech households is connected to the risk of "eating through" the borrowed money and whether Czech households risk falling into a debt trap. In addition to household indebtedness risks in the Czech Republic the analysis will focus on identification of specifics of the transformation phase of the Czech economy in comparison with the EU countries, or selected OECD countries.

Keywords: household indebtedness, household consumption, credits, financial literacy

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Authors: N. Utaberta, A. Jalali, S. Johar, M. Surat, A. I. Che-Ani

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Buildings are considered as significant part in the cities, which plays main role in organization and arrangement of city appearance, which is affects image of that building facades, as an connective between inner and outer space, have a main role in city image and they are classified as rich image and poor image by people evaluation which related to visual architectural and urban elements in building facades. the buildings in Karimi street , in Lahijan city where, lies in north of Iran, contain the variety of building's facade types which, have made a city image in Historical part of Lahijan city, while reflected the Iranian cities identity. The study attempt to identify the architectural and urban elements that impression the image of building facades in historical area, based on public evaluation. Quantitative method were used and the data was collected through questionnaire survey, the result presented architectural style, color, shape, and design evaluated by people as most important factor which should be understate in future development. in fact, the rich architectural style with strong design make strong city image as weak design make poor city image.

Keywords: Building's facade, historical area.

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Authors: An Hong Nguyen, Chatpan Chintanapakdee, Toshiro Hayashikawa

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Presented herein is an assessment of current nonlinear static procedures (NSPs) for seismic evaluation of bucklingrestrained braced frames (BRBFs) which have become a favorable lateral-force resisting system for earthquake resistant buildings. The bias and accuracy of modal, improved modal pushover analysis (MPA, IMPA) and mass proportional pushover (MPP) procedures are comparatively investigated when they are applied to BRBF buildings subjected to two sets of strong ground motions. The assessment is based on a comparison of seismic displacement demands such as target roof displacements, peak floor/roof displacements and inter-story drifts. The NSP estimates are compared to 'exact' results from nonlinear response history analysis (NLRHA). The response statistics presented show that the MPP procedure tends to significantly overestimate seismic demands of lower stories of tall buildings considered in this study while MPA and IMPA procedures provide reasonably accurate results in estimating maximum inter-story drift over all stories of studied BRBF systems.

Keywords: Buckling-restrained braced frames, nonlinearresponse history analysis, nonlinear static procedure, seismicdemands.

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Authors: C. Ardil

Abstract:

In this research, a multidimensional  compromise optimization method is proposed for multidimensional decision making analysis in the development ranking of the Gulf Cooperation Council Countries and Turkey. The proposed approach presents ranking solutions resulting from different multicriteria decision analyses, which yield different ranking orders for the same ranking problem, consisting of a set of alternatives in terms of numerous competing criteria when they are applied with the same numerical data. The multiobjective optimization decision making problem is considered in three sequential steps. In the first step, five different criteria related to the development ranking are gathered from the research field. In the second step, identified evaluation criteria are, objectively, weighted using standard deviation procedure. In the third step, a country selection problem is illustrated with a numerical example as an application of the proposed multidimensional  compromise optimization model. Finally, multidimensional  compromise optimization approach is applied to rank the Gulf Cooperation Council Countries and Turkey. 

Keywords: Standard deviation, performance evaluation, multicriteria decision making, multidimensional compromise optimization, vector normalization, multicriteria decision making, multicriteria analysis, multidimensional decision analysis.

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Authors: S. Mezghani, E. Perrin, J. L Bodnar, J. Marthe, B. Cauwe, V. Vrabie

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Non contact evaluation of the thickness of paint coatings can be attempted by different destructive and nondestructive methods such as cross-section microscopy, gravimetric mass measurement, magnetic gauges, Eddy current, ultrasound or terahertz. Infrared thermography is a nondestructive and non-invasive method that can be envisaged as a useful tool to measure the surface thickness variations by analyzing the temperature response. In this paper, the thermal quadrupole method for two layered samples heated up with a pulsed excitation is firstly used. By analyzing the thermal responses as a function of thermal properties and thicknesses of both layers, optimal parameters for the excitation source can be identified. Simulations show that a pulsed excitation with duration of ten milliseconds allows obtaining a substrate-independent thermal response. Based on this result, an experimental setup consisting of a near-infrared laser diode and an Infrared camera was next used to evaluate the variation of paint coating thickness between 60 μm and 130 μm on two samples. Results show that the parameters extracted for thermal images are correlated with the estimated thicknesses by the Eddy current methods. The laser pulsed thermography is thus an interesting alternative nondestructive method that can be moreover used for nonconductive substrates.

Keywords: Nondestructive, paint coating, thickness, infrared thermography, laser, heterogeneity.

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Authors: Amira Abbes Kheriji, Faouzi Bouani, Mekki Ksouri, Mohamed Ben Ahmed

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Model Predictive Control (MPC) is increasingly being proposed for real time applications and embedded systems. However comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprises as well as a transformer of organizations and markets. Recently, advances in microelectronics and software allow such technique to be implemented in embedded systems. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In fact in this paper, we propose an efficient framework for implementation of Generalized Predictive Control (GPC) in the performed STM32 microcontroller. The STM32 keil starter kit based on a JTAG interface and the STM32 board was used to implement the proposed GPC firmware. Besides the GPC, the PID anti windup algorithm was also implemented using Keil development tools designed for ARM processor-based microcontroller devices and working with C/Cµ langage. A performances comparison study was done between both firmwares. This performances study show good execution speed and low computational burden. These results encourage to develop simple predictive algorithms to be programmed in industrial standard hardware. The main features of the proposed framework are illustrated through two examples and compared with the anti windup PID controller.

Keywords: Embedded systems, Model Predictive Control, microcontroller, Keil tool.

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Authors: Mustafa M. Donma, Orkide Donma

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A well-defined insulin resistance (IR) is one of the requirements for the good understanding and evaluation of metabolic syndrome (MetS). However, underlying causes for the development of IR are not clear. Endothelial dysfunction also participates in the pathogenesis of this disease. IR indices are being determined in various obesity groups and also in diagnosing MetS. Components of MetS have been well established and used in adult studies. However, there are some ambiguities particularly in the field of pediatrics. The aims of this study were to compare the performance of fasting blood glucose (FBG), one of MetS components, with some other IR indices and check whether FBG may be replaced by some other parameter or ratio for a better evaluation of pediatric MetS. Five-hundred and forty-nine children were involved in the study. Five groups were constituted. Groups 109, 40, 100, 166, 110, 24 children were included in normal-body mass index (N-BMI), overweight (OW), obese (OB), morbid obese (MO), MetS with two components (MetS2) and MetS with three components (MetS3) groups, respectively. Age and sex-adjusted BMI percentiles tabulated by World Health Organization were used for the classification of obesity groups. MetS components were determined. Aside from one of the MetS components-FBG, eight measures of IR [homeostatic model assessment of IR (HOMA-IR), homeostatic model assessment of beta cell function (HOMA-%β), alanine transaminase-to-aspartate transaminase ratio (ALT/AST), alanine transaminase (ALT), insulin (INS), insulin-to-FBG ratio (INS/FBG), the product of fasting triglyceride and glucose (TyG) index, McAuley index] were evaluated. Statistical analyses were performed. A p value less than 0.05 was accepted as the statistically significance degree. Mean values for BMI of the groups were 15.7 kg/m², 21.0 kg/m², 24.7 kg/m², 27.1 kg/m², 28.7 kg/m², 30.4 kg/m² for N-BMI, OW, OB, MO, MetS2, MetS3, respectively. Differences between the groups were significant (p < 0.001). The only exception was MetS2-MetS3 couple, in spite of an increase detected in MetS3 group. Waist-to-hip circumference ratios significantly differed only for N-BMI vs, OB, MO, MetS2; OW vs MO; OB vs MO, MetS2 couples. ALT and ALT/AST did not differ significantly among MO-MetS2-MetS3. HOMA-%β differed only between MO and MetS2. INS/FBG, McAuley index and TyG were not significant between MetS2 and MetS3. HOMA-IR and FBG were not significant between MO and MetS2. INS was the only parameter, which showed statistically significant differences between MO-MetS2, MO-MetS3, and MetS2-MetS3. In conclusion, these findings have suggested that FBG presently considered as one of the five MetS components, may be replaced by INS during the evaluation of pediatric morbid obesity and MetS.

Keywords: Children, insulin resistance indices, metabolic syndrome, obesity.

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Authors: Rahil Garnavi, Mohammad Aldeen, M. Emre Celebi, Alauddin Bhuiyan, Constantinos Dolianitis, George Varigos

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Automatic segmentation of skin lesions is the first step towards development of a computer-aided diagnosis of melanoma. Although numerous segmentation methods have been developed, few studies have focused on determining the most discriminative and effective color space for melanoma application. This paper proposes a novel automatic segmentation algorithm using color space analysis and clustering-based histogram thresholding, which is able to determine the optimal color channel for segmentation of skin lesions. To demonstrate the validity of the algorithm, it is tested on a set of 30 high resolution dermoscopy images and a comprehensive evaluation of the results is provided, where borders manually drawn by four dermatologists, are compared to automated borders detected by the proposed algorithm. The evaluation is carried out by applying three previously used metrics of accuracy, sensitivity, and specificity and a new metric of similarity. Through ROC analysis and ranking the metrics, it is shown that the best results are obtained with the X and XoYoR color channels which results in an accuracy of approximately 97%. The proposed method is also compared with two state-ofthe- art skin lesion segmentation methods, which demonstrates the effectiveness and superiority of the proposed segmentation method.

Keywords: Border detection, Color space analysis, Dermoscopy, Histogram thresholding, Melanoma, Segmentation.

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Authors: O. F. Elkommos

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Teaching English as a Second Language (TESL) has become a very rich area of research. Practitioners or teachers of English as a foreign or a second language are now promoting both collaborative learning and collaborative teaching. Students learning a language collaboratively and cooperatively are learning in a better environment of team work where they learn from each other. Further, teaching English collaboratively also creates an enriching environment that is also very enriching to students’ and teachers’ experiences of learning and teaching. Moreover, action research stems from actual teacher concerns and students’ needs. Reflection in turn, on the experience of the material taught and the delivery of material is becoming an integral part of the teaching and learning experience self- evaluation and self-development. In this case, the concern of the research field in the area of TESL will be the development of teaching delivery, material and quality of learning. In the present research, the TESL module taught to year two students in the Faculty of Arts and Humanities, British University in Egypt (BUE) will be evaluated reflexively by the students and teachers. The module was taught to students in two different specialisms. It was taught and delivered through collaborative teaching and was evaluated by both teachers and students as very successful and enjoyable. The reflections of both teachers and students as well as student results confirm that it was a success.

Keywords: Action research, addressing differentiation, collaborative teaching, reflective teaching and learning, reflexive learning, reflexive teaching, self-development, self-evaluation, TESL.

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Authors: M. A. Meslem

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For precise geoid determination, we use a reference field to subtract long and medium wavelength of the gravity field from observations data when we use the remove-compute-restore technique. Therefore, a comparison study between considered models should be made in order to select the optimal reference gravity field to be used. In this context, two recent global geopotential models have been selected to perform this comparison study over Northern Algeria. The Earth Gravitational Model (EGM2008) and the Global Gravity Model (GECO) conceived with a combination of the first model with anomalous potential derived from a GOCE satellite-only global model. Free air gravity anomalies in the area under study have been used to compute residual data using both gravity field models and a Digital Terrain Model (DTM) to subtract the residual terrain effect from the gravity observations. Residual data were used to generate local empirical covariance functions and their fitting to the closed form in order to compare their statistical behaviors according to both cases. Finally, height anomalies were computed from both geopotential models and compared to a set of GPS levelled points on benchmarks using least squares adjustment. The result described in details in this paper regarding these two models has pointed out a slight advantage of GECO global model globally through error degree variances comparison and ground-truth evaluation.

Keywords: Quasigeoid, gravity anomalies, covariance, GGM.

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Authors: W. I. Wan Rosli, M. S. Aishah

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The grey oyster mushroom, Pleurotus sajor-caju (PSC), is a common edible mushroom and is now grown commercially around the world for food. This fungus has been broadly used as food or food ingredients in various food products for a long time. To enhance the nutritional quality and sensory attributes of bakery-based products, PSC powder is used in the present study to partially replace wheat flour in baked product formulations. The nutrient content and sensory properties of rice-porridge and unleavened bread (paratha) incorporated with various levels of PSC powder were studied. These food items were formulated with either 0%, 2%, 4% or 6% of PSC powder. Results show PSC powder recorded β-glucan at 3.57g/100g. In sensory evaluation, consumers gave higher score to both rice-porridge and paratha bread containing 2-4% PSC compared to those that are not added with PSC powder. The paratha containing 4% PSC powder can be formulated with the intention in improving overall acceptability of paratha bread. Meanwhile, for rice-porridge, consumers prefer the formulated product added with 4% PSC powder. In conclusion, the addition of PSC powder to partially wheat flour can be recommended for the purpose of enhancing nutritional composition and maintaining the acceptability of carbohydrate-based products.

Keywords: Pleurotus sajor-caju (PSC), nutrient contents, sensory evaluation

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Authors: Akiko Kondo, Akio Kondo

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We are facing serious problems related to long-term depopulation and an aging society with a falling birth rate in Japan. In this situation, we are suffering from a shortfall in human resources as well as a shortage of workforce in rural regions. In addition, we are struggling with a protracted economic slump and excess concentration of population in the Tokyo Metropolitan area. It is an urgent national issue to consider how to live in this country and what kind of structure of society and administration policy is needed. It is necessary to clarify people’s desire for their way of living and social assistance to be provided. The aim of this study is to clarify the characteristics of regional issues and the degree of their seriousness in local municipalities of Japan. We conducted a questionnaire survey about regional agenda in all local municipalities in Japan. We obtained responses concerning the degree of seriousness of regional issues and degree of importance of policies. Based on the data gathered from the survey, it is apparent that many local municipalities are facing an aging population and declining population. We constructed a model to analyze factors for declining population. Using the model, it was clarified that a population’s age structure, job opportunities and income level affect the decline of population. In addition, we showed the way of the evaluation of state of local municipality.

Keywords: Evaluation, Local municipality, Regional analysis, Regional issue.

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Authors: Kaishuan Shen, Pan Changyu, Yuhsiang Lu, Zongshao Liu, Chishxsin Chuang, Minyuan Ma

Abstract:

The culture of riding heavy motorcycles originates from advanced countries and mainly comes from Europe, North America, and Japan. Heavy duty motorcycle riders are different from people who view motorcycles as a convenient mean of transportation. They regard riding them as a kind of enjoyment and high-level taste. The activities of riding heavy duty motorcycles have formes a distinctive landscape in domestic land in Taiwan. Previous studies which explored motorcycle culture in Taiwan still focused on the objects of motorcycle engine displacement under 50 cc.. The study aims to study the heavy duty motorcycles of engine displacement over 550 cc. and explores where their attractiveness is. For finding the attractiveness of heavy duty motorcycle, the study chooses Miryoku Engineering (Preference-Based Design) approach. Two steps are adopted to proceed the research. First, through arranging the letters obtained from interviewing experts, EGM (The Evaluation Grid Method) was applied to find out the structure of attractiveness. The attractive styles are eye-dazzling, leisure, classic, and racing competitive styles. Secondarily, Quantification Theory Type I analysis was adopted as a tool for analyzing the importance of attractiveness. The relationship between style and attractive parts was also discussed. The results could contribute to the design and research development of heavy duty motorcycle industry in Taiwan.

Keywords: attractiveness, evaluation, heavy dutymotorcycle, miryoku engineering

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Authors: M. Linek

Abstract:

This article presents the comparison of selected evaluation methods regarding microstructure modification of hardened cement concrete intended for airfield pavements. Basic test results were presented for two pavement quality concrete lots. Analysis included standard concrete used for airfield pavements and modern material solutions based on concrete composite modification. In case of basic grain size distribution of concrete cement CEM I 42,5HSR NA, fine aggregate and coarse aggregate fractions in the form of granite chippings, water and admixtures were considered. In case of grain size distribution of modified concrete, the use of modern modifier as substitute of fine aggregate was suggested. Modification influence on internal concrete structure parameters using scanning electron microscope was defined. Obtained images were compared to the results obtained using computed tomography. Opportunity to use this type of equipment for internal concrete structure diagnostics and an attempt of its parameters evaluation was presented. Obtained test results enabled to reach a conclusion that both methods can be applied for pavement quality concrete diagnostics, with particular purpose of airfield pavements.

Keywords: Scanning electron microscope, computed tomography, cement concrete, airfield pavements.

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

Abstract:

The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluates the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: lexical semantics, feature representation, semantic decision, convolutional neural network, electronic medical record

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Authors: Yesubai Rubavathi Charles, Ravi Ramraj

Abstract:

In order to retrieve images efficiently from a large database, a unique method integrating color and texture features using genetic programming has been proposed. Opponent color histogram which gives shadow, shade, and light intensity invariant property is employed in the proposed framework for extracting color features. For texture feature extraction, fast discrete curvelet transform which captures more orientation information at different scales is incorporated to represent curved like edges. The recent scenario in the issues of image retrieval is to reduce the semantic gap between user’s preference and low level features. To address this concern, genetic algorithm combined with relevance feedback is embedded to reduce semantic gap and retrieve user’s preference images. Extensive and comparative experiments have been conducted to evaluate proposed framework for content based image retrieval on two databases, i.e., COIL-100 and Corel-1000. Experimental results clearly show that the proposed system surpassed other existing systems in terms of precision and recall. The proposed work achieves highest performance with average precision of 88.2% on COIL-100 and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3% on Corel. Thus, the experimental results confirm that the proposed content based image retrieval system architecture attains better solution for image retrieval.

Keywords: Content based image retrieval, Curvelet transform, Genetic algorithm, Opponent color histogram, Relevance feedback.

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Authors: C. Caçador, M. J. Reis Lima, J. Oliveira, M. J. Veiga, M. Teixeira Veríssimo, F. Ramos, M. C. Castilho, E. Teixeira-Lemos

Abstract:

In the present study we evaluated the nutritional status of 214 institutionalized elderly residents of both genders, aged 65 years and older of 11 care homes located in the district of Viseu (center of Portugal). The evaluation was based on anthropometric measurements and the Mini Nutritional Assessment (MNA) score.

The mean age of the subjects was 82.3 ± 6.1 years-old. Most of the elderly residents were female (72.0%). The majority had 4 years of formal education (51.9%) and was widowed (74.3%) or married (14.0%).

Men presented a mean age of 81.2±8.5 years-old, weight 69.3±14.5 kg and BMI 25.33±6.5 kg/m². In women, the mean age was 84.5±8.2 years-old, weight 61.2±14.7 kg and BMI 27.43±5.6 kg/m².

The evaluation of the nutritional status using the MNA score showed that 24.0% of the residents show a risk of undernutrition and 76.0% of them were well nourished.

There was a high prevalence of obese (24.8%) and overweight residents (33.2%) according to the BMI. 7.5% were considered underweight.

We also found that according to their waist circumference measurements 88.3% of the residents were at risk for cardiovascular disease (CVD) and 64.0% of them presented very high risk for CVD (WC≥88 cm for women and WC ≥102 cm for men).

The present study revealed the coexistence of a dual form of malnutrition (undernourished and overweight) among the institutionalized Portuguese concomitantly with an excess of abdominal adiposity. The high prevalence of residents at high risk for CVD should not be overlooked.

Given the vulnerability of the group of institutionalized elderly, our study highlights the importance of the classification of nutritional status based on both instruments: the BMI and the MNA.

Keywords: Nutritional status, MNA, BMI, elderly.

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Authors: Anthony Wachs, Guillaume Vinay, Gilles Ferrer, Jacques Kouakou, Calin Dan, Laurence Girolami

Abstract:

An original Direct Numerical Simulation (DNS) method to tackle the problem of particulate flows at moderate to high concentration and finite Reynolds number is presented. Our method is built on the framework established by Glowinski and his coworkers [1] in the sense that we use their Distributed Lagrange Multiplier/Fictitious Domain (DLM/FD) formulation and their operator-splitting idea but differs in the treatment of particle collisions. The novelty of our contribution relies on replacing the simple artificial repulsive force based collision model usually employed in the literature by an efficient Discrete Element Method (DEM) granular solver. The use of our DEM solver enables us to consider particles of arbitrary shape (at least convex) and to account for actual contacts, in the sense that particles actually touch each other, in contrast with the simple repulsive force based collision model. We recently upgraded our serial code, GRIFF 1 [2], to full MPI capabilities. Our new code, PeliGRIFF 2, is developed under the framework of the full MPI open source platform PELICANS [3]. The new MPI capabilities of PeliGRIFF open new perspectives in the study of particulate flows and significantly increase the number of particles that can be considered in a full DNS approach: O(100000) in 2D and O(10000) in 3D. Results on the 2D/3D sedimentation/fluidization of isometric polygonal/polyedral particles with collisions are presented.

Keywords: Particulate flow, distributed lagrange multiplier/fictitious domain method, discrete element method, polygonal shape, sedimentation, distributed computing, MPI

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Authors: Olayiwola M.O., Gbolagade A .W., Akinpelu F. O.

Abstract:

In this work, we present a reliable framework to solve boundary value problems with particular significance in solid mechanics. These problems are used as mathematical models in deformation of beams. The algorithm rests mainly on a relatively new technique, the Variational Iteration Method. Some examples are given to confirm the efficiency and the accuracy of the method.

Keywords: Variational iteration method, boundary value problems, convergence, restricted variation.

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

Abstract:

Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: Binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct.

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