Search results for: empirical marker method

Authors: Nadine Ali Hassan, Ngoc Son Nguyen, Didier Marot, Fateh Bendahmane

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This paper aims at presenting a study of the effect of scalping methods on the mechanical properties of coarse soils by resorting to numerical simulations based on the discrete element method (DEM) and experimental triaxial tests. Two reconstitution methods are used, designated as scalping method and substitution method. Triaxial compression tests are first simulated on a granular materials with a grap graded particle size distribution by using the DEM. We study the effect of these reconstitution methods on the stress-strain behavior of coarse soils with different fine contents and with different ways to control the densities of the scalped and substituted materials. Experimental triaxial tests are performed on original mixtures of sands and gravels with different fine contents and on their corresponding scalped and substituted samples. Numerical results are qualitatively compared to experimental ones. Agreements and discrepancies between these results are also discussed.

Keywords: coarse soils, mechanical behavior, scalping, replacement, triaxial devices

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Authors: Ding Jue, Li Jiahua, Lei Zhidi, Weng Peifen, Li Xiaowei

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With the rapid development of national modern industry, people begin to pay attention to environmental pollution and harm caused by industrial dust. Based on above, a numerical study on the dedusting technology of industrial environment was conducted. The dynamic models of multicomponent particles collision and coagulation, breakage and deposition are developed, and the interaction of water droplet and aerosol particle in 2-Dimension flow field was researched by Eulerian-Lagrangian method and Multi-Monte Carlo method. The effects of the droplet scale, movement speed of droplet and the flow field structure on scavenging efficiency were analyzed. The results show that under the certain condition, 30μm of droplet has the best scavenging efficiency. At the initial speed 1m/s of droplets, droplets and aerosol particles have more time to interact, so it has a better scavenging efficiency for the particle.

Keywords: water droplet, aerosol particle, collision and coagulation, multi-monte carlo method

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Authors: Maryam Akbarzadeh, F. Esmaeilzadeh, A. Poostvar, M. Manuchehri

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Preparation of regional input-output tables requires statistical methods combined with high costs and too much time. Obtained estimates by non-statistical methods have low confidence coefficient. Therefore, integrated methods for this purpose are suggested by recent input–output studies. In this study, first GRIT method is introduced as an appropriate integrated method for preparation of input-output table of Fars province. Next, input-output table is prepared for Fars province using this method. Therefore, this study is based on input-output table of national economy in 2001. Necessary modifications performed in the field of changes at level of prices and differences of regional trade compared with other areas at national level. Moreover, up to date statistics and information and technical experts view on the various economic sectors along with input-output table 33 was used in 2011 followed by investigation of general structure of the province economy based on the amounts of added value obtained from this table.

Keywords: grit, input-output, table, regional

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Authors: Muhammad Younis

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In this article, the novel (G′/G)-expansion method is successfully applied to construct the abundant travelling wave solutions to the modified Burgers’ equation with the aid of computation. The method is reliable and useful, which gives more general exact travelling wave solutions than the existing methods. These obtained solutions are in the form of hyperbolic, trigonometric and rational functions including solitary, singular and periodic solutions which have many potential applications in physical science and engineering. Some of these solutions are new and some have already been constructed. Additionally, the constraint conditions, for the existence of the solutions are also listed.

Keywords: traveling wave solutions, NLPDE, computation, integrability

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Diego De Castro Rodrigues, Marcelo Lisboa Rocha, Daniela M. De Q. Trevisan, Marcos Dias Da Conceicao, Gabriel Rosa, Rommel M. Barbosa

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The use of association rules algorithms within data mining is recognized as being of great value in the knowledge discovery in databases. Very often, the number of rules generated is high, sometimes even in databases with small volume, so the success in the analysis of results can be hampered by this quantity. The purpose of this research is to present a method for reducing the quantity of rules generated with association algorithms. Therefore, a computational algorithm was developed with the use of a Weka Application Programming Interface, which allows the execution of the method on different types of databases. After the development, tests were carried out on three types of databases: synthetic, model, and real. Efficient results were obtained in reducing the number of rules, where the worst case presented a gain of more than 50%, considering the concepts of support, confidence, and lift as measures. This study concluded that the proposed model is feasible and quite interesting, contributing to the analysis of the results of association rules generated from the use of algorithms.

Keywords: data mining, association rules, rules reduction, artificial intelligence

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

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Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

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Authors: Chih-Hsiang Chang, Pei-Shan Kao

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This paper discusses the reaction of investors in the Taiwan stock market to the most probable unknown earnings-related information and the most probable known earnings-related information. As compared with the previous literature regarding the effect of an official announcement of earnings forecast revision, this paper further analyzes investors’ cognitive bias toward the unknown and known earnings-related information, and the role of media during the investors' reactions to the foresaid information shocks. The empirical results show that both the unknown and known earnings-related information provides useful information content for a stock market. In addition, cognitive bias and disposition effect are the behavioral pitfalls that commonly occur in the process of the investors' reactions to the earnings-related information. Finally, media coverage has a remarkable influence upon the investors' trading decisions.

Keywords: cognitive bias, role of media, disposition effect, earnings-related information, behavioral pitfall

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Authors: Melody Yin

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Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.

Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time

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Authors: Isiya Salihu Shinkafi

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The focus of this paper is to elaborate on employment opportunities within the tourism sector and the solutions to youth unemployment in Africa and Nigeria in particular. Youth unemployment creates a monumental social problem to African continent, the world over and Nigeria in particular. The intelligence of this paper was collected from secondary sources using previews researches and analysis of scholars to gather empirical data. The findings revealed that unemployment in Africa and specifically Nigeria among youths were caused by certain factors which constitute a greater challenge to the economy and the existence of the continent. The tourism sector provides the enabling environment to address the different categories of unemployment among the youths. One of the unique characteristics of the tourism industry that makes it a prime sector from which employment can be engineered; especially in the case of the African countries, are its labour intensive characteristics of both experts, skilled, semi-skilled and unskilled labour.

Keywords: tourism industry, employment opportunities, youth employment

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: A. Alkattib, M. Boumaza

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Steam reforming is industrially important as it is incorporated in several major chemical processes including the production of ammonia, methanol, hydrogen and ox alcohols. Due to the strongly endothermic nature of the process, a large amount of heat is supplied by fuel burning (commonly natural gas) in the furnace chamber. Reaction conversions, tube catalyst life, energy consumption and CO2 emission represent the principal factors affecting the performance of this unit and are directly influenced by the high operating temperatures and pressures. This study presents a simulation of the performance of the reforming of methane in a primary reformer, through a developed empirical relation which enables to investigate the effects of operating parameters such as the pressure, temperature, steam to carbon ratio on the production of hydrogen, as well as the fraction of non-converted methane. It appears from this analysis that the exit temperature Te, the operating pressure as well the steam to carbon ratio has an important effect on the reforming of methane.

Keywords: reforming, methane, performance, hydrogen, parameters

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Authors: Kingsley Ononogbo, Ashiru Bello

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The purpose of this study is to determine the factors responsible for the inclination of the youths of Bida to passive recreation, with a view to finding out whether their occupations influence their attitudes towards active recreation. Using the 5-point Likert scale, a total number of 267 participants were drawn from the two major wards in Bida town. They are Cheniyan and Nassarafu. Study evidence revealed that youths were constrained from participating in active recreation due to preoccupation with family responsibilities and lack of their choices of recreational facilities. The result of the Chi Square Test showed that the youths had positive attitudes towards physical exercises, while the Spearman’s Correlation (r=0.21) signifies a positive but weak correlation. The P- value, however, equals .7610 which is greater than 0.05 and, so significant. The study concluded by suggesting regular enlightenment programmes, focusing on the values of participating in active recreation, and building and maintenance of desired neighborhood recreation facilities for youths, as a measure to encourage them to take part in the active form of recreation.

Keywords: attitudes, Bida, recreation development, recreation of youth

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Authors: D. Erdenechimeg, T. Bujinlkham, N. Erdenepurev

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The anti-corrosion performance of fatty acid coated mild steel samples is studied. Samples of structural steel coated with collector reagents deposited from surfactant in ethanol solution and overcoated with an epoxy barrier paint. A quantitative corrosion rate was determined by linear polarization resistance method using biopotentiostat/galvanostat 400. Coating morphology was determined by scanning electronic microscopy. A test for hydrophobic surface of steel by surfactant was done. From the samples, the main component or high content iron was determined by chemical method and other metal contents were determined by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) method. Prior to measuring the corrosion rate, mechanical and chemical treatments were performed to prepare the test specimens. Overcoating the metal samples with epoxy barrier paint after exposing them with surfactant the corrosion rate can be inhibited by 34-35 µm/year.

Keywords: corrosion, linear polarization resistance, coating, surfactant

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Authors: Richard Ji

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Nondestructive deflection testing has been accepted widely as a cost-effective tool for evaluating the structural condition of airfield pavements. Backcalculation of pavement layer moduli can be used to characterize the pavement existing condition in order to compute the load bearing capacity of pavement. This paper presents an improved best-fit backcalculation methodology based on deflection predictions obtained using finite element method (FEM). The best-fit approach is based on minimizing the squared error between falling weight deflectometer (FWD) measured deflections and FEM predicted deflections. Then, concrete elastic modulus and modulus of subgrade reaction were back-calculated using Heavy Weight Deflectometer (HWD) deflections collected at the National Airport Pavement Testing Facility (NAPTF) test site. It is an alternative and more versatile method in considering concrete slab geometry and HWD testing locations compared to methods currently available.

Keywords: nondestructive testing, pavement moduli backcalculation, finite element method, concrete pavements

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Authors: Vichayada Laohapiboolkul

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Introduction: As the legal use of cannabis is being widely accepted throughout the world, medical cannabis has been explored in order to become an alternative cure for patients. Tetrahydrocannabinol (THC) and Cannabidiol (CBD) are natural cannabinoids found in the Cannabis plant which is proved to have positive treatment for various diseases and symptoms such as chronic pain, neuropathic pain, spasticity resulting from multiple sclerosis, reduce cancer-associated pain, autism spectrum disorders (ASD), dementia, cannabis and opioid dependence, psychoses/schizophrenia, general social anxiety, posttraumatic stress disorder, anorexia nervosa, attention-deficit hyperactivity disorder, and Tourette's disorder. Regardless of all the medical benefits, THC, if not metabolized, can lead to mild up to severe adverse drug reactions (ADR). The enzyme CYP2C19 was found to be one of the metabolizers of THC. However, the suballele CYP2C19*2 manifests as a poor metabolizer which could lead to higher levels of THC than usual, possibly leading to various ADRs. Objective: The aim of this study was to investigate the distribution of CYP2C19, specifically CYP2C19*2, genes in Thai patients treated with medical cannabis along with adverse drug reactions. Materials and Methods: Clinical data and EDTA whole blood for DNA extraction and genotyping were collected from patients for this study. CYP2C19*2 (681G>A, rs4244285) genotyping was conducted using the Real-time PCR (ABI, Foster City, CA, USA). Results: There were 42 medical cannabis-induced ADRs cases and 18 medical cannabis tolerance controls who were included in this study. A total of 60 patients were observed where 38 (63.3%) patients were female and 22 (36.7%) were male, with a range of age approximately 19 - 87 years. The most apparent ADRs for medical cannabis treatment were dry mouth/dry throat (76.7%), followed by tachycardia (70%), nausea (30%) and a few arrhythmias (10%). In the total of 27 cases, we found a frequency of 18 CYP2C19*1/*1 alleles (normal metabolizers, 66.7%), 8 CYP2C19*1/*2 alleles (intermediate metabolizers, 29.6%) and 1 CYP2C19*2/*2 alleles (poor metabolizers, 3.7%). Meanwhile, 63.6% of CYP2C19*1/*1, 36.3% and 0% of CYP2C19*1/*2 and *2/*2 in the tolerance controls group, respectively. Conclusions: This is the first study to confirm the distribution of CYP2C19*2 allele and the prevalence of poor metabolizer genes in Thai patients who received medical cannabis for treatment. Thus, CYP2C19 allele might serve as a pharmacogenetics marker for screening before initiating treatment.

Keywords: medical cannabis, adverse drug reactions, CYP2C19, tetrahydrocannabinol, poor metabolizer

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Authors: Petar Sarajcev, Josip Vasilj, Damir Jakus

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This paper presents a novel statistical description of the counterpoise effective length due to lightning surges, where the (impulse) effective length had been obtained by means of regressive formulas applied to the transient simulation results. The effective length is described in terms of a statistical distribution function, from which median, mean, variance, and other parameters of interest could be readily obtained. The influence of lightning current amplitude, lightning front duration, and soil resistivity on the effective length has been accounted for, assuming statistical nature of these parameters. A method for determining the optimal counterpoise length, in terms of the statistical impulse effective length, is also presented. It is based on estimating the number of dangerous events associated with lightning strikes. Proposed statistical description and the associated method provide valuable information which could aid the design engineer in optimising physical lengths of counterpoises in different grounding arrangements and soil resistivity situations.

Keywords: counterpoise, grounding conductor, effective length, lightning, Monte Carlo method, statistical distribution

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Authors: Yunseok Noh, Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park

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Scripts are one of the basic text resources to understand broadcasting contents. Since broadcast media wields lots of influence over the public, tools for understanding broadcasting contents are more required. Topic modeling is the method to get the summary of the broadcasting contents from its scripts. Generally, scripts represent contents descriptively with directions and speeches. Scripts also provide scene segments that can be seen as semantic units. Therefore, a script can be topic modeled by treating a scene segment as a document. Because scripts consist of speeches mainly, however, relatively small co-occurrences among words in the scene segments are observed. This causes inevitably the bad quality of topics based on statistical learning method. To tackle this problem, we propose a method of learning with additional word co-occurrence information obtained using scene similarities. The main idea of improving topic quality is that the information that two or more texts are topically related can be useful to learn high quality of topics. In addition, by using high quality of topics, we can get information more accurate whether two texts are related or not. In this paper, we regard two scene segments are related if their topical similarity is high enough. We also consider that words are co-occurred if they are in topically related scene segments together. In the experiments, we showed the proposed method generates a higher quality of topics from Korean drama scripts than the baselines.

Keywords: broadcasting contents, scripts, text similarity, topic model

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Authors: Apurva Patil, Maithilee Kulkarni, Ashay Aswale

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This paper proposes an algorithm to develop the kinematic model of a 5 DOF robot arm. The formulation of the problem is based on finding the D-H parameters of the arm. Brute Force iterative method is employed to solve the system of non linear equations. The focus of the paper is to obtain the accurate solutions by reducing the root mean square error. The result obtained will be implemented to grip the objects. The trajectories followed by the end effector for the required workspace coordinates are plotted. The methodology used here can be used in solving the problem for any other kinematic chain of up to six DOF.

Keywords: 5 DOF robot arm, D-H parameters, inverse kinematics, iterative method, trajectories

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Authors: Ayca Bilginoglu, Belma Turan

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Metabolic syndrome, is associated impaired blood glucose level, insulin resistance, dyslipidemia caused by abdominal obesity. Also, it is related with cardiovascular risk accumulation and cardiomyopathy. The hypothesis of this study was to examine the effect of thiazolidinediones such as pioglitazone which is widely used insulin-sensitizing agents that improve glycemic control, on intracellular Na+ homeostasis in metabolic syndrome-induced cardiomyopathy in male rats. Male Wistar-Albino rats were randomly divided into three groups, namely control (Con, n=7), metabolic syndrome (MetS, n=7) and pioglitazone treated metabolic syndrome group (MetS+PGZ, n=7). Metabolic syndrome was induced by providing drinking water that was 32% sucrose, for 18 weeks. All of the animals were exposed to a 12 h light – 12 h dark cycle. Abdominal obesity and glucose intolerance had measured as a marker of metabolic syndrome. Intracellular Na+ ([Na+]i) is an important modulator of excitation–contraction coupling in heart. [Na+]i at rest and [Na+]i during pacing with electrical field stimulation in 0.2 Hz, 0.8 Hz, 2.0 Hz stimulation frequency were recorded in cardiomyocytes. Also, Na+ channel current (INa) density and I-V curve were measured to understand [Na+]i homeostasis. In results, high sucrose intake, as well as the normal daily diet, significantly increased body mass and blood glucose level of the rats in the metabolic syndrome group as compared with the non-treated control group. In MetS+PZG group, the blood glucose level and body inclined to decrease to the Con group. There was a decrease in INa density and there was a shift both activation and inactivation curve of INa. Pioglitazone reversed the shift to the control side. Basal [Na+]i either MetS and Con group were not significantly different, but there was a significantly increase in [Na+]i in stimulated cardiomyocytes in MetS group. Furthermore, pioglitazone had not effect on basal [Na+]i but it reversed the increase in [Na+]i in stimulated cardiomyocytes to the that of Con group. Results of the present study suggest that pioglitazone has a significant effect on the Na+ homeostasis in the metabolic syndrome induced cardiomyopathy in rats. All animal procedures and experiments were approved by the Animal Ethics Committee of Ankara University Faculty of Medicine (2015-2-37).

Keywords: insulin resistance, intracellular sodium, metabolic syndrome, sodium current

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Authors: Ferhat Mohamed, Boukhatem Mohamed Nadjib, Chemat Farid

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Simultaneous distillation–extraction (SDE) is routinely used by analysts for sample preparation prior to gas chromatography analysis. In this work, a new process design and operation for microwave assisted simultaneous distillation – solvent extraction (MW-SDE) of volatile compounds was developed. Using the proposed method, isolation, extraction and concentration of volatile compounds can be carried out in a single step. To demonstrate its feasibility, MW-SDE was compared with the conventional technique, Simultaneous distillation–extraction (SDE), for gas chromatography-mass spectrometry (GC-MS) analysis of volatile compounds in a fresh orange juice and a dry spice “carvi seeds”. SDE method required long time (3 h) to isolate the volatile compounds, and large amount of organic solvent (200 mL of hexane) for further extraction, while MW-SDE needed little time (only 30 min) to prepare sample, and less amount of organic solvent (10 mL of hexane). These results show that MW-SDE–GC-MS is a simple, rapid and solvent-less method for determination of volatile compounds from aromatic plants.

Keywords: essential oil, extraction, distillation, carvi seeds

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Authors: V. G. Rifert, V. V. Gorin, V. V. Sereda, V. V. Treputnev

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The analysis of heat transfer design methods in condensing inside plain tubes under existing influence of shear stress is presented in this paper. The existing discrepancy in more than 30-50% between rating heat transfer coefficients and experimental data has been noted. The analysis of existing theoretical and semi-empirical methods of heat transfer prediction is given. The influence of a precise definition concerning boundaries of phase flow (it is especially important in condensing inside horizontal tubes), shear stress (friction coefficient) and heat flux on design of heat transfer is shown. The substantiation of boundary conditions of the values of parameters, influencing accuracy of rated relationships, is given. More correct relationships for heat transfer prediction, which showed good convergence with experiments made by different authors, are substantiated in this work.

Keywords: film condensation, heat transfer, plain tube, shear stress

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Authors: Hassan M. Albishri, Fatimah Al-Shehri, Deia Abd El-Hady

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Among the analytical techniques, reverse phase liquid chromatography (RPLC) is currently used in pharmaceutical industry. Ecofriendly analytical chemistry offers the advantages of decreasing the environmental impact with the advantage of increasing operator safety which constituted a topic of industrial interest. Recently, ionic liquids have been successfully used to reduce or eliminate the conventional organic toxic solvents. In the current work, a simple and ecofriendly ionic liquid modified RPLC (IL-RPLC) method has been firstly developed and compared with RPLC under acidic and neutral mobile phase conditions for simultaneous determination of atorvastatin-calcium, rosuvastatin and simvastatin. Several chromatographic effective parameters have been changed in a systematic way. Adequate results have been achieved by mixing ILs with ethanol as a mobile phase under neutral conditions at 1 mL/min flow rate on C18 column. The developed IL-RPLC method has been validated for the quantitative determination of drugs in pharmaceutical formulations. The method showed excellent linearity for analytes in a wide range of concentrations with acceptable precise and accurate data. The current IL-RPLC technique could have vast applications particularly under neutral conditions for simple and greener (bio)analytical applications of pharmaceuticals.

Keywords: ionic liquid, RPLC, anti-hyperlipidemic drugs, ecofriendly

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Authors: Muhammad Irfan Aziz, Thomas Owens, Uzair Khaleeq uz Zaman

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The instantaneous and spatial localization for visually impaired people in dynamically changing environments with unexpected hazards and obstacles, is the most demanding and challenging issue faced by the navigation systems today. Since Bluetooth cannot utilize techniques like Time Difference of Arrival (TDOA) and Time of Arrival (TOA), it uses received signal strength indicator (RSSI) to measure Receive Signal Strength (RSS). The measurements using RSSI can be improved significantly by improving the existing methodologies related to RSSI. Therefore, the current paper focuses on proposing an improved method using trilateration for localization of Bluetooth devices for visually impaired people. To validate the method, class 2 Bluetooth devices were used along with the development of a software. Experiments were then conducted to obtain surface plots that showed the signal interferences and other environmental effects. Finally, the results obtained show the surface plots for all Bluetooth modules used along with the strong and weak points depicted as per the color codes in red, yellow and blue. It was concluded that the suggested improved method of measuring RSS using trilateration helped to not only measure signal strength affectively but also highlighted how the signal strength can be influenced by atmospheric conditions such as noise, reflections, etc.

Keywords: Bluetooth, indoor/outdoor localization, received signal strength indicator, visually impaired

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Authors: Kawinphat Lertpongmanee

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The purpose of this research is to examine the relationships among business collaboration effectiveness, modern management excellence, proactive operational management, and firm performance to bring competitive advantage to the firm. Furthermore, the population and sample selected are exporters on textile businesses in Thailand in total of 566 companies. The data were collected by questionnaire survey and sent direct to the directors or managerial managers of each company which is appropriate as the key informant of this research. Moreover, the statistic to test hypothesis uses the hierarchical multiple regression analysis and provides those five hypotheses to testing. The results show direct effect that the business collaboration effectiveness has a significantly positive influence on firm performance, meaning that, the collaboration is an important factor in global business both internal and external of firms that reflect the linkage of business to create competitive advantage and gain benefits simultaneously of the firms efficiently also.

Keywords: business collaboration effectiveness, firm performance, modern management excellence, strategic management

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Authors: Mostafa Firoozabadi, Alireza Foroughi Nematollahi

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Semi autogenous mills are designed for grinding or primary crushed ore, and are the most widely used in concentrators globally. Any defect occurrence in semi autogenous mills can stop the production line. A Gearbox is a significant part of a rotating machine or a mill, so, the gearbox monitoring is a necessary process to prevent the unwanted defects. When a defect happens in a gearbox bearing, this defect can be transferred to the other parts of the equipment like inner ring, outer ring, balls, and the bearing cage. Vibration analysis is one of the most effective and common ways to detect the bearing defects in the mills. Vibration signal in a mill can be made by different parts of the mill including electromotor, pinion girth gear, different rolling bearings, and tire. When a vibration signal, made by the aforementioned parts, is added to the gearbox vibration spectrum, an accurate and on time defect detection in the gearbox will be difficult. In this paper, a new method is proposed to detect the gearbox bearing defects in the semi autogenous mill on time and accurately, using the vibration signal analysis method. In this method, if the vibration values are increased in the vibration curve, the probability of defect occurrence is investigated by comparing the equipment vibration values and the standard ones. Then, all vibration frequencies are extracted from the vibration signal and the equipment defect is detected using the vibration spectrum curve. This method is implemented on the semi autogenous mills in the Golgohar mining and industrial company in Iran. The results show that the proposed method can detect the bearing looseness on time and accurately. After defect detection, the bearing is opened before the equipment failure and the predictive maintenance actions are implemented on it.

Keywords: condition monitoring, gearbox defects, predictive maintenance, vibration analysis

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Authors: Rashid Mahmood, Muhammad Junaid Sarwar

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Mobile ad hoc networks (MANETs) use has been well-known from the last few years in the many applications, like mission critical applications. In the (MANETS) prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in (MANETs). The authentication and encryption is considered the first solution of the MANETs problem where as now these are not sufficient as MANET use is increasing. In this paper we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in MANET and aim to comparing in some important fields.

Keywords: MANET, IDS, intrusions, signature, detection, prevention

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Authors: Aijaz A. Shaikh, Richard Glavee-Geo, Heikki Karjaluoto

Abstract:

Adoption of Information Systems (IS) is receiving increasing attention such that its implications have been closely monitored and studied by the IS management community, industry and professional gatekeepers. Building on previous research regarding the adoption of technology, this paper develops and validates an integrated model of the adoption of mobile banking. The model originates from the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB). This paper intends to offer a preliminary scrutiny of the antecedents of the adoption of mobile banking services in the context of a developing country. Data was collected from Pakistan. The findings showed that an integrated TAM and TPB model greatly explains the adoption intention of mobile banking; and perceived behavioural control and its antecedents play a significant role in predicting adoption Theoretical and managerial implications of findings are presented and discussed.

Keywords: developing country, mobile banking service adoption, technology acceptance model, theory of planned behavior

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Authors: Qiang Fu, Abu Saleh

Abstract:

Research studies are highly fragmented when an innovation management framework is being discussed. With the aim to identify an innovation management framework/assessment tool suitable for small & medium enterprises (SMEs) in the service industry, this researcher critically reviewed existing innovation management frameworks and assessment models/tools and discovered a number of literature gaps. It is established that existing literature lacks generally agreed innovation management dimensions, commonly accepted knowledge creation through empirical studies on innovation management in SMEs, effective innovation management performance measurements, and studies on innovation management in the service industry, in particular in retail SMEs. As such, there is a dire need to develop an appropriate firm-level innovation management framework suitable for SMEs in the service industry for a future research project and further study. In addition, this researcher also discussed the significance of establishing such an innovation management framework.

Keywords: innovation management, innovation management framework, innovation management assessment tools, SMEs, service industry

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