Search results for: patient support program

Authors: Altab Hossain, Ataur Rahman, A. K. M. Mohiuddin, Yulfian Aminanda

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Modeling of the dynamic behavior and motion are renewed interest in the improved tractive performance of an intelligent air-cushion tracked vehicle (IACTV). This paper presents a new dynamical model for the forces on the developed small scale intelligent air-cushion tracked vehicle moving over swamp peat. The air cushion system partially supports the 25 % of vehicle total weight in order to make the vehicle ground contact pressure 7 kN/m2. As the air-cushion support system can adjust automatically on the terrain, so the vehicle can move over the terrain without any risks. The springdamper system is used with the vehicle body to control the aircushion support system on any undulating terrain by making the system sinusoidal form. Experiments have been carried out to investigate the relationships among tractive efficiency, slippage, traction coefficient, load distribution ratio, tractive effort, motion resistance and power consumption in given terrain conditions. Experiment and simulation results show that air-cushion system improves the vehicle performance by keeping traction coefficient of 71% and tractive efficiency of 62% and the developed model can meet the demand of transport efficiency with the optimal power consumption.

Keywords: Air-cushion system, ground contact pressure, slippage, power consumption.

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Authors: Mohamed M. Ragab, Neveen A. Abdel Raoof, Reham H. Diab

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Background: Delayed onset muscle soreness (DOMS) is the most common symptom when ordinary individuals and athletes are exposed to unaccustomed physical activity, especially eccentric contraction which impairs athletic performance, ordinary people work ability and physical functioning. Multitudes of methods have been investigated to reduce DOMS. One of the valuable methods to control DOMS is repeated bout effect (RBE) as a prophylactic method. Purpose: To compare the repeated bout effect of submaximal eccentric with maximal isometric contraction on induced DOMS. Methods: Sixty normal male volunteers were assigned randomly into three equal groups: Group A (first study group): 20 subjects received submaximal eccentric contraction on non-dominant elbow flexors as a prophylactic exercise. Group B (second study group): 20 subjects received maximal isometric contraction on nondominant elbow flexors as a prophylactic exercise. Group C (control group): 20 subjects did not receive any prophylactic exercises. Maximal isometric peak torque of elbow flexors and patient related elbow evaluation (PREE) scale were measured for each subject 3 times before, immediately after, and 48 hours after induction of DOMS. Results: Post-hoc test for maximal isometric peak torque and PREE scale immediately and 48 hours after induction of DOMS revealed that group (A) and group (B) resulted in significant decrease in maximal isometric strength loss and elbow pain and disability rather than control group (C), but submaximal eccentric group (A) was more effective than maximal isometric group (B) as it showed more rapid recovery of functional strength and less degrees of elbow pain and disability. Conclusion: Both submaximal eccentric contraction and maximal isometric contraction were effective in prevention of DOMS but submaximal eccentric contraction produced a greater protective effect against muscle damage induced by maximal eccentric exercise performed 2 days later.

Keywords: Delayed onset muscle soreness, maximal isometric peak torque, patient related elbow evaluation scale, repeated bout effect.

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Authors: Ljerka Hrženjak-Šego, Željko Polić, Zdravka Aljinović

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In general, reports are a form of representing data in such way that user gets the information he needs. They can be built in various ways, from the simplest (“select from") to the most complex ones (results derived from different sources/tables with complex formulas applied). Furthermore, rules of calculations could be written as a program hard code or built in the database to be used by dynamic code. This paper will introduce two types of reports, defined in the DB structure. The main goal is to manage calculations in optimal way, keeping maintenance of reports as simple and smooth as possible.

Keywords: Data Definition diagram, Server Model Diagram, system modelling, reports.

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Authors: Cheng Shen, LaiHong Shen

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Ammonia is an important carrier of hydrogen energy, with the characteristics of high hydrogen content density and no carbon dioxide emission. Safe and efficient ammonia capture for ammonia synthesis from biomass is an important way to alleviate the energy crisis and solve the energy problem. Metal chloride has a chemical adsorption effect on ammonia and can be desorbed at high temperatures to obtain high-concentration ammonia after combining with ammonia, which has a good development prospect in ammonia capture and separation technology. In this paper, the ammonia adsorption properties of CuCl2 were measured, and the composite adsorbents were prepared by using silicon and multi-walled carbon nanotubes, respectively to support CuCl2, and the ammonia adsorption properties of the composite adsorbents were studied. The study found that the ammonia adsorption capacity of the three adsorbents decreased with the increase in temperature, so metal chlorides were more suitable for the low-temperature adsorption of ammonia. Silicon and multi-walled carbon nanotubes have an enhanced effect on the ammonia adsorption of CuCl2. The reason is that the porous material itself has a physical adsorption effect on ammonia, and silicon can play the role of skeleton support in cupric chloride particles, which enhances the pore structure of the adsorbent, thereby alleviating sintering.

Keywords: Ammonia, adsorption properties, metal chloride, MWCNTs, silicon.

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Authors: L. Korpinen, T. Kava, I. Salmi

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This study aimed to describe the operating model of obstructive sleep apnea. Due to the large number of patients, the role of nurses in the diagnosis and treatment of sleep apnea was important. Pulmonary physicians met only a minority of the patients. The sleep apnea study in 2018 included about 800 patients, of which about 28% were normal and 180 patients were classified as severe (apnea-hypopnea index [AHI] over 30). The operating model has proven to be workable and appropriate. The patients understand well that they may not be referred to a pulmonary doctor. However, specialized medical follow-up on professional drivers continues every year.

Keywords: Sleep, apnea patient, operating model, hospital.

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Authors: J. F. Arthur, R. M. Hodge

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The Defence Materials Technology Centre has evolved from the Australian Cooperative Research Centres Program. The Centre receives funding from Government, industry and research sources to fund collaborative research within its participant organisations. The research centre is structured as a company with a small administrative staff and plays the role of the “honest broker” within the collaboration. A corporate culture has been established that is pervasive into the research projects are undertaken. The model is an effective mechanism to deliver outcomes to each of the participant stakeholders.

Keywords: Collaboration, Research Centre.

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Authors: S. Seyedtabaii, L. Seyedtabaii

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Artifact free photoplethysmographic (PPG) signals are necessary for non-invasive estimation of oxygen saturation (SpO2) in arterial blood. Movement of a patient corrupts the PPGs with motion artifacts, resulting in large errors in the computation of Sp02. This paper presents a study on using Kalman Filter in an innovative way by modeling both the Artillery Blood Pressure (ABP) and the unwanted signal, additive motion artifact, to reduce motion artifacts from corrupted PPG signals. Simulation results show acceptable performance regarding LMS and variable step LMS, thus establishing the efficacy of the proposed method.

Keywords: Kalman filter, Motion artifact, PPG, Photoplethysmography.

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Authors: Karel Frydrýšek, Pavel Koštial, Karla Barabaszová, Jana Kukutschová

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This paper deals with a new way for designing external fixators applied in traumatology and orthopaedics. These fixators can be applied in the treatment of open and unstable fractures or for lengthening human or animal bones etc. The new design is based on the development of Ilizarov and other techniques (i.e. shape and weight optimalization based on composite materials, application of smart materials, nanotechnology, low x-ray absorption, antibacterial protection, patient's comfort, reduction in the duration of the surgical treatment, and cost).

Keywords: biomechanics, design, external fixators, newmaterials, traumatology

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Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

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This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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Authors: Shin-Jer Yang, Kai-Tai Yang

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In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: Cloud service, multi-tenancy, NFC, IAM, mobile device.

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Authors: Charles P. Mukumba, Kahilu K. Shakantu

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Achieving the Sustainable Development Goals (SDGs) is critical to achieving transformational results that support Zambia's developmental agenda. Public procurement is integral to the government's mission to deliver goods and services in a timely and economical manner beyond the value of money spent. This study explores the link between sustainable public procurement and the SDGs in Zambia. To validate the established links with public sector procurement in Zambia, the study employed qualitative research using semi-structured interviews with 12 public procurement officials. The collected data were analysed using thematic analysis. The findings indicate that public procurement plays a fundamental role in achieving the SDGs by helping deliver core public services that support SDGs and systematizing and co-delivering added value along the way. The study further established the importance of sustainable public procurement within the development context. The interviews were limited to mainstream public sector procurement entities in Lusaka, Zambia. Sustainable public procurement actions have the potential to impact SDGs. Promoting sustainable public procurement will enhance sustainable development and significantly improve the supply chain, benefiting the economy, society and environment. Findings will inform policy-makers how to strategically design sustainable public procurement policy by attuning it to procuring entities' objectives and priorities to contribute to attaining SDGs.

Keywords: Sustainable public procurement, sustainable development goals, SDG targets, Zambia.

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Authors: Saeed Sedighizadeh, Abbas Mansoori, Mohammad Reza Pirestani, Davoud Sedighizadeh

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The usual method of river flow diversion involves construction of tunnels and cofferdams. Given the fact that the cost of diversion works could be as high as 10-20% of the total dam construction cost, due attention should be paid to optimum design of the diversion works. The cost of diversion works depends, on factors, such as: the tunnel dimensions and the intended tunneling support measures during and after excavation; quality and characterizes of the rock through which the tunnel should be excavated; the dimensions of the upstream (and downstream) cofferdams; and the magnitude of river flood the system is designed to divert. In this paper by use of the cost of unit prices for tunnel excavation, tunnel lining, tunnel support (rock bolt + shotcrete) and cofferdam fill the cost function was determined. The function is then minimized by the aid of PSO Algorithm (particle swarm optimization). It is found that the optimum diameter and the total diversion cost are directly related to the river flood discharge (Q). It has also shown that in addition to optimum diameter design discharge (Q), river length, tunnel length, is mainly a function of the ratios (not the absolute values) of the unit prices and does not depend on the overall price levels in the respective country. The results of optimization use in some of the case study lead us to significant changes in the cost.

Keywords: Diversion Tunnel, Optimization, PSO Algorithm

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Authors: C. Gunavathi, K. Premalatha

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Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.

Keywords: F-Test, Gene Expression, Genetic Algorithm, k- Nearest-Neighbor, Microarray, Signal-to-Noise Ratio, Support Vector Machine, T-statistics, Tumor Classification.

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Authors: Anežka Jurčíková, Miroslav Rosmanit

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The subject of this paper is to verify the behavior of the truss-type CHS joint which is beyond the scope of use of the EN 1993-1-8. This is performed by using the numerical modeling in program ANSYS and the analytical methods recommended in the CIDECT publication. The recommendations for numerical modeling of such types of joints as well as for evaluation of load-bearing capacity of the joint are given in this paper. The results from both analytical and numerical models are compared.

Keywords: ANSYS, CHS joints, FEM, Lattice structure

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Authors: Mrs.K.Kavitha, S.Arivazhagan

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A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Keywords: Multi-class, Run Length features, PCA, ICA, classification and Support Vector Machines.

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Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

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One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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Authors: Raúl González Muñoz, Essam Shehab, Martin Weinitzke, Chris Fowler, Paul Baguley

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Software applications have become crucial to the aerospace industry, providing a wide range of functionalities and capabilities used during the design, manufacturing and support of aircraft. However, as this criticality increases, so too does the risk for business operations when facing a software failure. Hence, there is a need for new methodologies to be developed to support aerospace companies in effectively managing their software portfolios, avoiding the hazards of business disruption and additional costs. This paper aims to provide a definition of operational software maturity, and how this can be used to assess software operational behaviour, as well as a view on the different aspects that drive software maturity within the aerospace industry. The key research question addressed is, how can operational software maturity monitoring assist the aerospace industry in effectively managing large software portfolios? This question has been addressed by conducting an in depth review of current literature, by working closely with aerospace professionals and by running an industry case study within a major aircraft manufacturer. The results are a software maturity model composed of a set of drivers and a prototype tool used for the testing and validation of the research findings. By utilising these methodologies to assess the operational maturity of software applications in aerospace, benefits in maintenance activities and operations disruption avoidance have been observed, supporting business cases for system improvement.

Keywords: Aerospace, capability maturity model, software maturity, software lifecycle.

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Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

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Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: Decision support system, event sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine.

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Authors: Aleksandra Zysk, Pawel Badura

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Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: Classification, singing, spectral analysis, vocal emission, vocal register.

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Authors: Subramaniam Chandran

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This paper presents an assessment study conducted among the distance learners in India. Open and distance learning systems have traveled a long way since its inception and its journey has witnessed the evolution and adoption of different generations of technology. This study focuses on the distant learners in India. Sampling for this study has been derived from the mass enrollment from Tamil Nadu area, a southern state of India. Learners were chosen from dual mode universities, private universities, Tamil Nadu Open University and IGNOU. The main focus of the study is to examine the coverage and appropriation of students support services and learning aids. It explores two aspects: the facilities available and the awareness and use of such services. It includes, self-learning materials, face-to-face counseling, multimedia learning materials, website, e-learning, radio and television services etc. While exploring the student-s perspective on these learning aspects, it is important to understand the perspectives of the teachers. Two different interests are visible among the teachers. Majority of the teachers support faceto- face counseling. However, the young teachers are in favour of online learning and multimedia supports in teaching. Through the awareness is somewhat high, the actual participation in online is very low. This is due to the inadequate infrastructure as well as the traditional attitudes of the teachers. Still the face-to-face sessions remain popular than online.

Keywords: Face-to-face session, online session, distance learning, multimedia

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Authors: Xun Ge

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Recently, X. Ge and J. Qian investigated some relations between higher mathematics scores and calculus scores (resp. linear algebra scores, probability statistics scores) for Chinese university students. Based on rough-set theory, they established an information system S = (U,CuD,V, f). In this information system, higher mathematics score was taken as a decision attribute and calculus score, linear algebra score, probability statistics score were taken as condition attributes. They investigated importance of each condition attribute with respective to decision attribute and strength of each condition attribute supporting decision attribute. In this paper, we give further investigations for this issue. Based on the above information system S = (U, CU D, V, f), we analyze the decision rules between condition and decision granules. For each x E U, we obtain support (resp. strength, certainty factor, coverage factor) of the decision rule C —>x D, where C —>x D is the decision rule induced by x in S = (U, CU D, V, f). Results of this paper gives new analysis of on higher mathematics scores for Chinese university students, which can further lead Chinese university students to raise higher mathematics scores in Chinese graduate student entrance examination.

Keywords: Rough set, support, strength, certainty factor, coverage factor.

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Authors: M. Graus, K. Westhoff, X. Xu

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The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: Data analytics, green production, industrial energy management, optimization, renewable energies, simulation.

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Authors: Eun-Geun Kim, Won-Pil Park, Dae-Gon Woo, Chang-Yong Ko, Yong-Heum Lee, Dohyung Lim, Tae-Min Shin, Han-Sung Kim, Gyoun-Jung Lee

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Functional gastrointestinal disorders affect millions of people spread all age regardless of race and sex. There are, however, rare diagnostic methods for the functional gastrointestinal disorders because functional disorders show no evidence of organic and physical causes. Our research group identified recently that the gastrointestinal tract well in the patients with the functional gastrointestinal disorders becomes more rigid than healthy people when palpating the abdominal regions overlaying the gastrointestinal tract. Aim of this study is, therefore, to develop a diagnostic system for the functional gastrointestinal disorders based on ultrasound technique, which can quantify the characteristic above related to the rigidity of the gastrointestinal tract well. Ultrasound system was designed. The system consisted of transmitter, ultrasonic transducer, receiver, TGC, and CPLD, and verified via a phantom test. For the phantom test, ten soft-tissue specimens were harvested from porcine. Five of them were then treated chemically to mimic a rigid condition of gastrointestinal tract well, which was induced by functional gastrointestinal disorders. Additionally, the specimens were tested mechanically to identify if the mimic was reasonable. The customized ultrasound system was finally verified through application to human subjects with/without functional gastrointestinal disorders (Normal and Patient Groups). It was identified from the mechanical test that the chemically treated specimens were more rigid than normal specimen. This finding was favorably compared with the result obtained from the phantom test. The phantom test also showed that ultrasound system well described the specimen geometric characteristics and detected an alteration in the specimens. The maximum amplitude of the ultrasonic reflective signal in the rigid specimens (0.2±0.1Vp-p) at the interface between the fat and muscle layers was explicitly higher than that in the normal specimens (0.1±0.0Vp-p). Clinical tests using our customized ultrasound system for human subject showed that the maximum amplitudes of the ultrasonic reflective signals near to the gastrointestinal tract well for the patient group (2.6±0.3Vp-p) were generally higher than those in normal group (0.1±0.2Vp-p). Here, maximum reflective signals was appeared at 20mm depth approximately from abdominal skin for all human subjects, corresponding to the location of the boundary layer close to gastrointestinal tract well. These results suggest that newly designed diagnostic system based on ultrasound technique may diagnose enough the functional gastrointestinal disorders.

Keywords: Functional Gastrointestinal Disorders, DiagnosticSystem, Phantom Test, Ultrasound System.

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Authors: G. Vici, L. Cesanelli, L. Belli, R. Ceci, V. Polzonetti

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Several factors contribute to success in sport and diet is one of them. Evidence-based sport nutrition guidelines underline the importance of macro- and micro-nutrients’ balance and timing in order to improve athlete’s physical status and performance. Nevertheless, a high content of proteins is commonly found in resistance training athletes’ diet with carbohydrate intake that is not enough or not well planned. The aim of the study was to evaluate the impact of different protein and carbohydrate diet contents on body composition and sport performance on a group of resistance training athletes. Subjects were divided as study group (n=16) and control group (n=14). For a period of 4 months, both groups were subjected to the same resistance training fitness program with study group following a specific diet and control group following an ab libitum diet. Body compositions were evaluated trough anthropometric measurement (weight, height, body circumferences and skinfolds) and Bioimpedence Analysis. Physical strength and training status of individuals were evaluated through the One Repetition Maximum test (RM1). Protein intake in studied group was found to be lower than in control group. There was a statistically significant increase of body weight, free fat mass and body mass cell of studied group respect to the control group. Fat mass remains almost constant. Statistically significant changes were observed in quadriceps and biceps circumferences, with an increase in studied group. The MR1 test showed improvement in study group’s strength but no changes in control group. Usually people consume hyper-proteic diet to achieve muscle mass development. Through this study, it was possible to show that protein intake fixed at 1,7 g/kg/d can meet the individual's needs. In parallel, the increased intake of carbohydrates, focusing on quality and timing of assumption, has enabled the obtainment of desired results with a training protocol supporting a hypertrophic strategy. Therefore, the key point seems related to the planning of a structured program both from a nutritional and training point of view.

Keywords: Body composition, diet, exercise, protein.

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Authors: J. P. Dubois, O. M. Abdul-Latif

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Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.

Keywords: Least square-support vector machine, on-off keying, matched filter, maximum likelihood detector, wireless infrared communication.

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Authors: Sadaf Khalid, Fahim Arif

Abstract:

Wide applicability of concurrent programming practices in developing various software applications leads to different concurrency errors amongst which data race is the most important. Java provides greatest support for concurrent programming by introducing various concurrency packages. Aspect oriented programming (AOP) is modern programming paradigm facilitating the runtime interception of events of interest and can be effectively used to handle the concurrency problems. AspectJ being an aspect oriented extension to java facilitates the application of concepts of AOP for data race detection. Volatile variables are usually considered thread safe, but they can become the possible candidates of data races if non-atomic operations are performed concurrently upon them. Various data race detection algorithms have been proposed in the past but this issue of volatility and atomicity is still unaddressed. The aim of this research is to propose some suggestions for incorporating certain conditions for data race detection in java programs at the volatile fields by taking into account support for atomicity in java concurrency packages and making use of pointcuts. Two simple test programs will demonstrate the results of research. The results are verified on two different Java Development Kits (JDKs) for the purpose of comparison.

Keywords: Aspect Bench Compiler (abc), Aspect OrientedProgramming (AOP), AspectJ, Aspects, Concurrency packages, Concurrent programming, Cross-cutting Concerns, Data race, Eclipse, Java, Java Development Kits (JDKs), Pointcuts

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Authors: Angelica S. Valeriani, Lorenzo Biasiolo

Abstract:

In recent years, the scale of the impact of climate change and its related side effects has become ever more massive and devastating. Sustainable Development Goals (SDGs), promoted by United Nations, aim to front issues related to climate change, among others. In particular, the project CROWD4SDG focuses on a bunch of SDGs, since it promotes environmental activities and climate-related issues. In this context, we developed a prototype of an application, under advanced development considering web design, that focuses on SDG 13 (SDG on climate action) by providing users with useful instruments to face environmental crises and climate-related disasters. Our prototype is thought and structured for both web and mobile development. The main goal of the application, POLI4SDG, is to help users to get through emergency services. To this extent, an organized overview and classification prove to be very effective and helpful to people in need. A careful analysis of data related to environmental crises prompted us to integrate the user contribution, i.e. exploiting a core principle of Citizen Science, into the realization of a public catalog, available for consulting and organized according to typology and specific features. In addition, gender equality and opportunity features are considered in the prototype, in order to allow women, often the most vulnerable category, to have direct support. The overall description of the application functionalities is detailed. Moreover, implementation features and properties of the prototype are discussed.

Keywords: Crowdsourcing, social media, SDG, climate change, natural disasters, gender equality.

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Authors: S. Sadallah

Abstract:

In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: Management, software, optimal, greedy algorithm, graph-diagram.

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Authors: Sharan Badiger, Prema T. Akkasaligar, Patil LS, Manish Patel, Biradar MS

Abstract:

Human immunodeficiency virus infection and acquired immunodeficiency syndrome is a global pandemic with cases reporting from virtually every country and continues to be a common infection in developing country like India. Microalbuminuria is a manifestation of human immunodeficiency virus associated nephropathy. Therefore, microalbuminuria may be an early marker of human immunodeficiency virus associated nephropathy, and screening for its presence may be beneficial. A strikingly high prevalence of microalbuminuria among human immunodeficiency virus infected patients has been described in various studies. Risk factors for clinically significant proteinuria include African - American race, higher human immunodeficiency virus ribonucleic acid level and lower CD4 lymphocyte count. The cardiovascular risk factors of increased systolic blood pressure and increase fasting blood sugar level are strongly associated with microalbuminuria in human immunodeficiency virus patient. These results suggest that microalbuminuria may be a sign of current endothelial dysfunction and micro-vascular disease and there is substantial risk of future cardiovascular disease events. Positive contributing factors include early kidney disease such as human immunodeficiency virus associated nephropathy, a marker of end organ damage related to co morbidities of diabetes or hypertension, or more diffuse endothelial cells dysfunction. Nevertheless after adjustment for non human immunodeficiency virus factors, human immunodeficiency virus itself is a major risk factor. The presence of human immunodeficiency virus infection is independent risk to develop microalbuminuria in human immunodeficiency virus patient. Cardiovascular risk factors appeared to be stronger predictors of microalbuminuria than markers of human immunodeficiency virus severity person with human immunodeficiency virus infection and microalbuminuria therefore appear to potentially bear the burden of two separate damage related to known vascular end organ damage related to know vascular risk factors, and human immunodeficiency virus specific processes such as the direct viral infection of kidney cells.The higher prevalence of microalbuminuria among the human immunodeficiency virus infected could be harbinger of future increased risks of both kidney and cardiovascular disease. Further study defining the prognostic significance of microalbuminuria among human immunodeficiency virus infected persons will be essential. Microalbuminuria seems to be a predictor of cardiovascular disease in diabetic and non diabetic subjects, hence it can also be used for early detection of micro vascular disease in human immunodeficiency virus positive patients, thus can help to diagnose the disease at the earliest.

Keywords: Acquired immunodeficiency syndrome, Human immunodeficiency virus, Microalbuminuria.

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Authors: M. Peña Aguilar Juan, Ríos Hernández Ezequiel, R. Valencia Luis

Abstract:

For certification, certain goods of public interest, such as medicines and food, it is required the preparation and delivery of a dossier. For its elaboration, legal and administrative knowledge must be taken, as well as organization of the documents of the process, and an order that allows the file verification. Therefore, a virtual platform was developed to support the process of management and elaboration of the dossier, providing accessibility to the information and interfaces that allow the user to know the status of projects. The development of dossier system on the cloud allows the inclusion of the technical requirements for the software management, including the validation and the manufacturing in the field industry. The platform guides and facilitates the dossier elaboration (report, file or history), considering Mexican legislation and regulations, it also has auxiliary tools for its management. This technological alternative provides organization support for documents and accessibility to the information required to specify the successful development of a dossier. The platform divides into the following modules: System control, catalog, dossier and enterprise management. The modules are designed per the structure required in a dossier in those areas. However, the structure allows for flexibility, as its goal is to become a tool that facilitates and does not obstruct processes. The architecture and development of the software allows flexibility for future work expansion to other fields, this would imply feeding the system with new regulations.

Keywords: Electronic dossier, technologies for management, web software, dossier elaboration, pharmaceutical industry.

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