Search results for: gradient training method

Authors: Nada Jasim Habeeb, Rana Saad Mohammed, Muntaha Khudair Abbass

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For more efficient and fast video summarization, this paper presents a surveillance video summarization method. The presented method works to improve video summarization technique. This method depends on temporal differencing to extract most important data from large video stream. This method uses histogram differencing and Sum Conditional Variance which is robust against to illumination variations in order to extract motion objects. The experimental results showed that the presented method gives better output compared with temporal differencing based summarization techniques.

Keywords: temporal differencing, video summarization, histogram differencing, sum conditional variance

Procedia PDF Downloads 331

Authors: M. Y. Waziri, M. A. Aliyu

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The paper proposes an approach to improve the performance of Broyden’s method for solving systems of nonlinear equations. In this work, we consider the information from two preceding iterates rather than a single preceding iterate to update the Broyden’s matrix that will produce a better approximation of the Jacobian matrix in each iteration. The numerical results verify that the proposed method has clearly enhanced the numerical performance of Broyden’s Method.

Keywords: mulit-step Broyden, nonlinear systems of equations, computational efficiency, iterate

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Authors: Hoora Dehghani, Meisam Shahbazi, Reza Zare

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During the previous decade, a significant evolution has occurred in the number of private educational centers and, accordingly, the increase in the number of providers and students of these centers around the world. The number of language teaching institutes in Iran that are considered private educational sectors is also growing exponentially as the request for learning foreign languages has extremely increased in recent years. This fact caused competition among the institutions in improving better services tailored to the students’ demands to win the competition. Along with the growth in the industry of education, higher education institutes should apply the marketing-related concepts and view students as customers because students’ outlooks are similar to consumers with education. Studying the influential factors in the selection of an institute has multiple benefits. Firstly, it acknowledges the institutions of the students’ choice factors. Secondly, the institutions use the obtained information to improve their marketing methods. It also helps institutions know students’ outlooks that can be applied to expand the student know-how. Moreover, it provides practical evidence for educational centers to plan useful amenities and programs, and use efficient policies to cater to the market, and also helps them execute the methods that increase students’ feeling of contentment and assurance. Thus, this study explored the influencing factors in the selection of a language learning institute by language learners and examined and compared the importance among the varying age groups and genders. In the first phase of the study, the researchers selected 15 language learners as representative cases within the specified age ranges and genders purposefully and interviewed them to explore the comprising elements in their language institute selection process and analyzed the results qualitatively. In the second phase, the researchers identified elements as specified items of a questionnaire, and 1000 English learners across varying educational contexts rated them. The TOPSIS method was used to analyze the data quantitatively by representing the level of importance of the items for the participants generally and specifically in each subcategory; genders and age groups. The results indicated that the educational quality, teaching method, duration of training course, establishing need-oriented courses, and easy access were the most important elements. On the other hand, offering training in different languages, the specialized education of only one language, the uniform and appropriate appearance of office staff, having native professors to the language of instruction, applying Computer or online tests instead of the usual paper tests respectively as the least important choice factors in selecting a language institute. Besides, some comparisons among different groups’ ratings of choice factors were made, which revealed the differences among different groups' priorities in choosing a language institute.

Keywords: choice factors, EFL institute selection, english learning, need analysis, TOPSIS

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: Mohammadamin Abbasnejad

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The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

Procedia PDF Downloads 339

Authors: John Gray, Andy Smith, Hazel James

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With the introduction of projects such as GP referral and other medical exercise schemes, there has been a shift in the cosmology underpinning exercise leadership. That is, the knowledge base of exercise leaders, specifically personal trainers, has moved from a cosmology based on aesthetic and physical fitness demands to one requiring interaction with the dominant biomedical model underpinning contemporary medicine. In line with this shift research has demonstrated that personal trainer education has aligned itself to a biotechnological model. However, whilst there is a need to examine exercise as medicine, and consider the role of personal trainers as prescribers of these interventions, the possible issues surrounding the growing medicalization of the exercise cosmology have not been explored. Using a phenomenological methodology, and the novel approach of photo-elicitation, this research examined the practices of successful personal trainers. The findings highlight that a growing focus on an iatro-biological based scientific process of exercise prescription may prove problematical. Through the development of a model of practitioner-based knowledge, it is argued there is a possible growing disconnection between the theoretical basis of exercise science and the working cosmology of exercise practitioners.

Keywords: biomedicine, cosmology, personal training, photo-elicitation

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Authors: Tohru Kawabe

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In this paper, a new SMC (Sliding Mode Control) method with MP (Model Predictive Control) integral action for the slip suppression of EV (Electric Vehicle) under braking is proposed. The proposed method introduce the integral term with standard SMC gain , where the integral gain is optimized for each control period by the MPC algorithms. The aim of this method is to improve the safety and the stability of EVs under braking by controlling the wheel slip ratio. There also include numerical simulation results to demonstrate the effectiveness of the method.

Keywords: sliding mode control, model predictive control, integral action, electric vehicle, slip suppression

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Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

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Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R-colour component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: feature extraction, remote sensing, image retrieval, chromaticity, water index, spectral library, integrated method

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Authors: Ali Dehgan Moroozeh, B. Farhadi Bansouleh

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Evapotranspiration is one of the most important components of the hydrological cycle. Evapotranspiration (ETo) is an important variable in water and energy balances on the earth’s surface, and knowledge of the distribution of ET is a key factor in hydrology, climatology, agronomy and ecology studies. Many researchers have a valid relationship, which is a function of climate factors, to estimate the potential evapotranspiration presented to the plant water stress or water loss, prevent. The FAO-Penman method (PM) had been recommended as a standard method. This method requires many data and these data are not available in every area of world. So, other methods should be evaluated for these conditions. When sufficient or reliable data to solve the PM equation are not available then Hargreaves equation can be used. The Hargreaves equation (HG) requires only daily mean, maximum and minimum air temperature extraterrestrial radiation .In this study, Hargreaves method (HG) were evaluated in 12 stations in the North West region of Iran. Results of HG and M.HG methods were compared with results of PM method. Statistical analysis of this comparison showed that calibration process has had significant effect on efficiency of Hargreaves method.

Keywords: evapotranspiration, hargreaves, equation, FAO-Penman method

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Authors: Zahra Nouri Sangedehy

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There are two anthropologies considered in Protagoras. The first of them (Protagoras) considers the appearance of man, like all other beings, as the result of a natural evolution without a predetermined plan and aim. Not only the human's corporeal existence is the result of evolution and natural choices, but also his moral and social life can be explained in the light of this factor. In this anthropology, the moral and political laws derive from the contract and the people's majority agreement of society to survive. Society and socio-political institutions are the reason for the education and training (paidia) of virtues in general. The second anthropology is Socrates's, which is not clearly projected and is hidden behind his arguments. In this way, man's moral and social life is intrinsic. Man is intrinsically a moral and social being. Socrates intends to criticize the theory of the contractual nature of ethics by demonstrating the unity of virtues on the one hand and the identity of virtue and knowledge, and the problem of the teaching of virtues based on intrinsic and a priori knowledge of human beings, on the other hand, albeit with a new kind of education and training, which will replace the Sophists' education. Therefore, ethics will have undoubted foundations, and human beings will be defined again.

Keywords: Protagoras, techne, arête, paidia

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Authors: F. Boufera, F. Debbat

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This paper deals with an approach based on limit-cycles method for the problem of obstacle avoidance of mobile robots in unknown environments for any form of obstacles. The purpose of this approach is the improvement of limit-cycles method in order to obtain safe and flexible navigation. The proposed algorithm has been successfully tested in different configuration on simulation.

Keywords: mobile robot, navigation, avoidance of obstacles, limit-cycles method

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

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The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow

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Authors: Ranjit Singh

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Body fat % lean body mass and body type play vital role in sports performance. A sports person who is having optional body composition can show its performance flawlessly whereas other who is not physical fit may be more prone to injury. Competitive swimming is an association of plethora of aspects like morphological, physiological, biochemical, biomechanical and psychological. The primary key of the present research is to examine the correlation among selected morphological dimensions such as height, weight, body fat%, lean body mass, somatotype and swimming performance. The present study also focused to investigate by potential deficiencies if any and to find out remedial measures to curb the training stresses. Thirty (age group 10-14 years) swimmers undergoing training under skilled and professional coaches were selected in the present study. The morphological variables and performance criterion like 50 meter swimming time and speed were calculated by using standard training methodology. Correlation coefficient among body composition, somatotype and performance variables were assessed by using standard statistical package SPSS. Mean height, weight, fat% and lean body mass of the present group is 150.97±8.68 cm, 44.0±9.34 kg., 15.97±4.42 % and 37.10±8.77 kg respectively. Somatotype of the young swimmers of this research is revealed ectomorphic mesomorph. The analysis of the results Illustrated that swimming performance is significantly correlated (p<0.05) with height, body weight, mesomorphoic component and lean body mass. Body fat is significantly and negatively correlated (p<0.05) with mesomorphic component, lean body mass and swimming speed. From this present study, it can be concluded that along with techniques and tactics other the physical attributes also play significant role in swimming performance which can help the swimmers to excel in higher level of competition and swimmers having improved morphological qualities can ultimately perform well.

Keywords: body fat, mass, mesomorphic component, somatotype

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Authors: Andreas Ahrens, Jelena Zascerinska

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Emotions are crucial in online classes in adult education. Despite that, little attention was devoted to the emotional experience of being an online teacher in the field of andragogy, and the online teacher’s emotional perspectives in ever-changing environments have to be analysed. The paper aims the analysis of teachers’ emotional experience in online classes in adult education in selected European countries. The research tends to propose implications for training teachers who work in online classes in adult education. The survey was conducted in April 2022. In the selected European countries, 78 respondents took part in the study. Among them, 30 respondents represented Germany, 28 respondents participated in the study in Greece, and 20 respondents from Italy took part in the survey. The theoretical findings allow for defining teacher emotional experience. The analysis of the elements of the respondents’ emotional experience allows concluding that teachers’ attitude to online classes has to be developed. The key content for teacher training is presented. Directions for further work are proposed.

Keywords: adult education, emotions, online classes, teacher emotional experience

Procedia PDF Downloads 199

Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: K. M. Damodara Gowda

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Background: Maternal health and nutrition are considered as the predominant factors influencing brain functional development. If the mother is free of illness and genetic defects, maternal nutrition would be one of the most critical factors affecting the brain development. Calorie restrictions cause significant impairment in spatial learning ability and the levels of Brain Derived Neurotrophic Factor (BDNF) in rats. But, the mechanism by which the prenatal under-nutrition leads to impairment in brain learning and memory function is still unclear. In the present study, prenatal Astaxanthin supplementation on BDNF level, spatial learning and memory performance in the offspring’s of normal, calorie restricted and Astaxanthin supplemented rats was investigated. Methodology: The rats were administered with 6mg and 12 mg of astaxanthin /kg bw for 21 days following which acquisition and retention of spatial memory was tested in a partially-baited eight arm radial maze. The BDNF level in different regions of the brain (cerebral cortex, hippocampus and cerebellum) was estimated by ELISA method. Results: Calorie restricted animals treated with astaxanthin made significantly more correct choices (P < 0.05), and fewer reference memory errors (P < 0.05) on the tenth day of training compared to offsprings of calorie restricted animals. Calorie restricted animals treated with astaxanthin also made significantly higher correct choices (P < 0.001) than untreated calorie restricted animals in a retention test 10 days after the training period. The mean BDNF level in cerebral cortex, Hippocampus and cerebellum in Calorie restricted animals treated with astaxanthin didnot show significant variation from that of control animals. Conclusion: Findings of the study indicated that memory and learning was impaired in the offspring’s of calorie restricted rats which was effectively modulated by astaxanthin at the dosage of 12 mg/kg body weight. In the same way the BDNF level at cerebral cortex, Hippocampus and Cerebellum was also declined in the offspring’s of calorie restricted animals, which was also found to be effectively normalized by astaxanthin.

Keywords: calorie restiction, learning, Memory, Cerebral cortex, Hippocampus, Cerebellum, BDNF, Astaxanthin

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Authors: S. Bayona, J. Nunez, D. Paez, C. Diaz

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The application of Lean manufacturing tools continues to be an effective solution for increasing productivity, reducing costs and eliminating waste in the manufacture of goods and services. This article analyzes the production process of a hot asphalt manufacturing company from an administrative and technical perspective. Three main phases were analyzed, the first phase was related to the determination of the risk priority number of the main operations in asphalt mix production process by an FMEA (Failure Mode Effects Analysis), in the second phase the Value Stream Mapping (VSM) of the production line was performed and in the third phase a SWOT (Strengths, Weaknesses Opportunities, Threats) matrix was constructed. Among the most valued failure modes were the lack training of workers in occupational safety and health issues, the lack of signaling and classification of granulated material, and the overweight of vehicles loaded. The analysis of the results in the three phases agree on the importance of training operational workers, improve communication with external actors in order to minimize delays in material orders and strengthen control suppliers.

Keywords: asphalt, lean manufacturing, productivity, process

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Authors: A. H. Choudhury

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In this paper, a highly accurate numerical method for the solution of one-dimensional fourth-order wave equation is derived. This hyperbolic problem is solved by using semidiscrete approximations. The space direction is discretized by wavelet-Galerkin method, and the time variable is discretized by using Newmark schemes.

Keywords: hyperbolic problem, semidiscrete approximations, stability, Wavelet-Galerkin Method

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Authors: Ashlyn Smith, Chloe Zampelli, Vincent Manna, Vernon Murray

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According to Polaris (a UN affiliate), there are currently 44 million human trafficking victims globally. Using a sample of 137 labor trafficking victims in Poland, we found that all were Ukrainian citizens. We categorized victims according to the “Victim Intervention Marketing” (Murray) social marketing framework. The largest victim type consisted of “Willing Assimilators” (57%). This means they entered their particular trafficking situations without coercion and were left at will. Such victims are typically driven by financial desperation. Twenty percent (20%) of Willing Assimilators were men, and 80% were women. Victims who were not Willing Assimilators were forced as either “Enlightened Apostates” (37%) or “Tricked and Trapped” (7%). All of the forced victims were women. Crosstabs with Chi-square test (Pearson Chi-Square test significance = .002) results indicated that the male victims were all between 30 and 38 years old, while female victim ages ranged from 24 to 47. Accordingly, labor trafficking victim interventions in Poland should be age-sensitive and focus on three areas: 1) economic development for the Willing Assimilators, 2) training to identify fraudulent job postings, etc. for the Tricked and Trapped segment, and 3) training to equip potential victims to distrust certain close “loved ones” for the Enlightened Apostates.

Keywords: Poland, labor trafficking, social marketing, victim intervention marketing

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Authors: Rahman Dashti, Ehsan Gord

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In this paper, an improved impedance based fault location method is proposed. In this method, online fault locating is performed using voltage and current information at the beginning of the feeder. Determining precise fault location in a short time increases reliability and efficiency of the system. The proposed method utilizes information about main component of voltage and current at the beginning of the feeder and distributed generation unit (DGU) in order to precisely locate different faults in acceptable time. To evaluate precision and accuracy of the proposed method, a 13-node is simulated and tested using MATLAB.

Keywords: distribution network, fault section determination, distributed generation units, distribution protection equipment

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Authors: Sonika Raj, Amarjeet Singh, Vijay Lakshmi Sharma

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Introduction: In 21st century, due to revolution in Information and Communication Technologies (ICTs), there has been phenomenal development in quality and quantity of knowledge in the field of medical science. So, the access to relevant information to physicians is critical to the delivery of effective healthcare services to patients. The study was conducted to assess the information needs and attitudes of the medical professionals; to determine the sources and channels of information used by them; to ascertain the current usage of ICTs and the barriers faced by them in utilization of ICTs in health information access. Methodology: This descriptive cross-sectional study was carried in 2015 on hundred medical professionals working in public and private sectors of Chandigarh. The study used both quantitative and qualitative method for data collection. A semi structured questionnaire and interview schedule was used to collect data on information seeking needs, access to ICTs and barriers to healthcare information access. Five Data analysis was done using SPSS-16 and qualitative data was analyzed using thematic approach. Results: The most preferred sources to access healthcare information were internet (85%), trainings (61%) and communication with colleagues (57%). They wanted information on new drug therapy and latest developments in respective fields. All had access to computer with but almost half assessed their computer knowledge as average and only 3% had received training regarding usage. Educational status (p=0.004), place of work (p=0.004), number of years in job (p=0.004) and sector of job (p=0.04) of doctors were found to be significantly associated with their active search for information. The major themes that emerged from in-views were need; types and sources of healthcare information; exchange of information among different levels of healthcare providers; usage of ICTs to obtain and share information; barriers to access of healthcare information and quality of health information materials and involvement in their development process Conclusion and Recommendations: The medical professionals need information in their in their due course of work. However, information needs of medical professionals were not being adequately met. There should be training of professional regarding internet skills and the course on bioinformatics should be incorporated in the curricula of medical students. The policy framework must be formulated that will encourage and promote the use of ICTs as tools for health information access and dissemination.

Keywords: health information, ICTs, medical professionals, qualitative

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Authors: A. Abdi, A. Abbasi Daloee, A. Barari

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Aim: The adaptations that occur in human body after doing exercises training are a factor to help healthy people stay away from certain diseases. One of the main adaptations is a change in blood circulation, especially in vessels. The increase of capillary density is dependent on the balance between angiogenic and angiostatic factors. Most studies show that the changes made to angiogenic developmental factors resulted from physical exercises indicate the low level of stimulators compared with inhibitors. It is believed that the plasma level of VEGF-A, the important angiogenic factor, is reduced after physical exercise. Findings indicate that the extract of crataegus plant reduces the platelet-derived growth factor receptor (PDGFR) autophosphorylation in human's fibroblast. More importantly, crataegus (1 to 100 mg in liter) clearly leads to the inhibition of PDGFR autophosphorylation in vascular smooth muscle cells (VSMCs). Angiogenesis is a process that can be classified into physiological and pathophysiological forms. collagen XVIII is a part of extracellular protein and heparan sulfate proteoglycans in vascular epithelial and endothelial basement membrane cause the release of endostatin from noncollagenous collagen XVIII. Endostatin inhibits the growth of endothelial cells, inhibits angiogenesis, weakens different types of cancer, and the growth of tumors. The purpose of the current study was to investigate the effect of intensive aerobic running with or without aqueous extraction of black Crataegus elbursensis on Collagen XVIII in male rats. Design: Thirty-two Wistar male rats (4-6 weeks old, 125-135 gr weight) were acquired from the Pasteur's Institute (Amol, Mazandaran), and randomly assigned into control (n = 16) and training (n = 16) groups. Rats were further divided into saline-control (SC) (n=8), saline-training (ST) (n=8), crataegus pentaegyna extraction -control (CPEC) (n=8), and crataegus pentaegyna extraction - training (CPET) (n=8). The control (SC and CPEC) groups remained sedentary; whereas the training groups underwent a high running exercise program. plasma were excised and immediately frozen in liquid nitrogen. Statistical analysis was performed using a one way analysis of variance and Tukey test. Significance was accepted at P = 0.05. Results: The results show that aerobic exercise group had the highest concentration collagen XVIII compared to other groups and then respectively black crataegus, training-crataegus and control groups. Conclusion: In general, researchers in this study concluded that the increase of collagen XVIII (albeit insignificant) as a result of physical activity and consumption of black crataegus extract could possibly serve as a regional inhibitor of angiogenesis and another evidence for the anti-cancer effects of physical activities. Since the research has not managed in this study to measure the amount of plasma endostatin, it is suggested that both indices are measured with important angiogenic factors so that we can have a more accurate interpretation of changes to angiogenic and angiostatic factors resulted from physical exercises.

Keywords: aerobic running, Crataegus elbursensis, Collagen XVIII

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Authors: W. S. Lawal, T. Akande

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Abstract— Four (4) difference methods were employed to detoxify Jatropha carcas, they were physical method (it include soaking and sun drying) Chemical (the use of methylated sprit, hexane and methane). Biological (the use of Aspergillus niger and then sundry for 7days and then Bacillus lichiformis) and Combined method (the combination of chemical and biological methods). Phobol esther analysis was carried out after the detoxification methods and it was found that the combined method is better off (P<0.05). Detoxified Jatropha from each of this methods was sundry and grinded for easy inclusion into poultry feed, detoxified jatropha was included at 0%, 0.5%, 1%, 2%, 3%, 4%, and 5% but the combined method was increased up to 7% because the birds were able to tolerate it, the 0% was the control experiment. 405 day old broiler chicks was used to test the effect of detoxified Jatropha carcas on their performance, there are 5birds per treatment and there are 3 replicates, the experiment lasted for 8weeks,highest number of mortality was obtained in physical method, birds in chemical method tolerated up to 3% Jatropha carcas, biological method is better, as birds there were comfortable at 5% but the best of them is combined method the birds did very well at 7% as there were less mortality and highest weight gain was achieved here (P<0.05) and it was recommended.

Keywords: phobol esther, inclusion level, tolerance level, Jatropha carcas

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Authors: Hadi Farhadian, Homayoon Katibeh

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In this paper, groundwater seepage into Amirkabir tunnel has been estimated using analytical and numerical methods for 14 different sections of the tunnel. Site Groundwater Rating (SGR) method also has been performed for qualitative and quantitative classification of the tunnel sections. The obtained results of above-mentioned methods were compared together. The study shows reasonable accordance with results of the all methods unless for two sections of tunnel. In these two sections there are some significant discrepancies between numerical and analytical results mainly originated from model geometry and high overburden. SGR and the analytical and numerical calculations, confirm the high concentration of seepage inflow in fault zones. Maximum seepage flow into tunnel has been estimated 0.425 lit/sec/m using analytical method and 0.628 lit/sec/m using numerical method occurred in crashed zone. Based on SGR method, six sections of 14 sections in Amirkabir tunnel axis are found to be in "No Risk" class that is supported by the analytical and numerical seepage value of less than 0.04 lit/sec/m.

Keywords: water Seepage, Amirkabir Tunnel, analytical method, DEM, SGR

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Authors: Pradeep Singh, Shrish Verma

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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

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Authors: S. A. M. Yatim, Z. B. Ibrahim, K. I. Othman, M. Suleiman

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The method of solving second order stiff ordinary differential equation (ODEs) that is based on backward differentiation formula (BDF) is considered in this paper. We derived the method by increasing the order of the existing method using an improved strategy in choosing the step size. Numerical results are presented to compare the efficiency of the proposed method to the MATLAB’s suite of ODEs solvers namely ode15s and ode23s. The method was found to be efficient to solve second order ordinary differential equation.

Keywords: backward differentiation formulae, block backward differentiation formulae, stiff ordinary differential equation, variable step size

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Authors: Wincharles Coker

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This study troubles the role the state as the chief sponsor of higher education plays in shaping communication training in Ghana. Using a public university as a case study, it explores how the government of Ghana, through its regimes of control, exercises its authority over the means of production in the academy. Based on Wenger’s community of practice theory and critical theory, the research analyzes the political economy within which higher education in the country operates, focusing on the mandates of two of its bodies: the National Council for Tertiary Education (NCTE) and the National Accreditation Board (NAB). Results show that communication training in Ghana is shaped by three basic strategies of control: developmentalism, bureaucratization, and corporatization. This governmentality, the research reveals nonetheless, largely constrains the agency and practices of the community of communication faculty and administrators, and thus presents a major challenge to the exercise of intellectual freedom, and the self-critical nature of the academy. The study bears implications for further research in the political economy of communication studies, the administration of higher education, and critical/cultural studies in education.

Keywords: communication, developmentalism, educattion, governmentality

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Authors: Susmita Panda, Arnab Banerjee, Ajinkya Baxy, Bappaditya Manna

Abstract:

The design of short to medium-span high-speed bridges in critical locations is an essential aspect of vehicle-bridge interaction. Due to dynamic interaction between moving load and bridge, mathematical models or finite element modeling computations become time-consuming. Thus, to reduce the computational effort, a universal approximator using an artificial neural network (ANN) has been used to evaluate the dynamic response of the bridge. The data set generation and training of surrogate models have been conducted over the results obtained from mathematical modeling. Further, the robustness of the surrogate model has been investigated, which showed an error percentage of less than 10% with conventional methods. Additionally, the dependency of the dynamic response of the bridge on various load and bridge parameters has been highlighted through a parametric study.

Keywords: artificial neural network, mode superposition method, moving load analysis, surrogate models

Procedia PDF Downloads 85

Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

Abstract:

This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Abbes Lounis, Kahina Louadj, Mohamed Aidene

Abstract:

This paper presents an optimal control problem applied to a robot; the problem is to determine a command which makes it possible to reach a final state from a given initial state in record time. The approach followed to solve this optimization problem with constraints on the control starts by presenting the equations of motion of the dynamic system then by applying Pontryagin's maximum principle (PMP) to determine the optimal control, and Picard's successive approximation method combined with the shooting method to solve the resulting differential system.

Keywords: robotics, Pontryagin's Maximum Principle, PMP, Picard's method, shooting method, non-linear differential systems

Procedia PDF Downloads 241