Search results for: data communication

Authors: Adrian Ionita, Ana-Maria Ghimes

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The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

Procedia PDF Downloads 156

Authors: Mohammad H. Yarmohammadian, Reza Safdari, Mahmoud Keyvanara, Nahid Tavakoli

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One of the greatest challenges in disaster and emergencies is patient tracking. The concept of tracking has different denotations. One of the meanings refers to tracking patients’ physical locations and the other meaning refers to tracking patients ‘medical needs during emergency services. The main goal of patient tracking is to provide patient safety during disaster and emergencies and manage the flow of patient and information in different locations. In most of cases, there are not sufficient and accurate data regarding the number of injuries, medical conditions and their accommodation and transference. The objective of the present study is to survey on patient tracking issue in natural disaster and emergencies. Methods: This was a narrative study in which the population was E-Journals and the electronic database such as PubMed, Proquest, Science direct, Elsevier, etc. Data was gathered by Extraction Form. All data were analyzed via content analysis. Results: In many countries there is no appropriate and rapid method for tracking patients and transferring victims after the occurrence of incidents. The absence of reliable data of patients’ transference and accommodation, even in the initial hours and days after the occurrence of disasters, and coordination for appropriate resource allocation, have faced challenges for evaluating needs and services challenges. Currently, most of emergency services are based on paper systems, while these systems do not act appropriately in great disasters and incidents and this issue causes information loss. Conclusion: Patient tracking system should update the location of patients or evacuees and information related to their states. Patients’ information should be accessible for authorized users to continue their treatment, accommodation and transference. Also it should include timely information of patients’ location as soon as they arrive somewhere and leave therein such a way that health care professionals can be able to provide patients’ proper medical treatment.

Keywords: patient tracking, challenges, disaster, emergency

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Authors: Neda Zamani

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The present study aimed to investigate the effectiveness of training courses and their limitations using the CIPP model. The investigations were done on Isfahan Refinery as a case study. From a purpose point of view, the present paper is included among applied research and from a data gathering point of view, it is included among descriptive research of the field type survey. The population of the study included participants in training courses, their supervisors and experts of the training department. Probability-proportional-to-size (PPS) was used as the sampling method. The sample size for participants in training courses included 195 individuals, 30 supervisors and 11 individuals from the training experts’ group. To collect data, a questionnaire designed by the researcher and a semi-structured interview was used. The content validity of the data was confirmed by training management experts and the reliability was calculated through 0.92 Cronbach’s alpha. To analyze the data in descriptive statistics aspect (tables, frequency, frequency percentage and mean) were applied, and inferential statistics (Mann Whitney and Wilcoxon tests, Kruskal-Wallis test to determine the significance of the opinion of the groups) have been applied. Results of the study indicated that all groups, i.e., participants, supervisors and training experts, absolutely believe in the importance of training courses; however, participants in training courses regard content, teacher, atmosphere and facilities, training process, managing process and product as to be in a relatively appropriate level. The supervisors also regard output to be at a relatively appropriate level, but training experts regard content, teacher and managing processes as to be in an appropriate and higher than average level.

Keywords: training courses, limitations of training effectiveness, CIPP model, Isfahan oil refinery company

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Authors: Kumar Manoj, Ramesh Kumar, Kumari Arti, Kumar Prashant

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Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper we compare AODV, DSDV, DSR and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyses these routing protocols by extensive simulations in OPNET simulator and show that how pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, data traffic sent, throughput, retransmission attempts.

Keywords: MANET, AODV, DSDV, DSR, ZRP

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Authors: Larisa Akhmylovskaia, Andriana Barysh

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The present paper is introducing the translation score developing methodology and methods in the cross-cultural communication. The ideas and examples presented by the authors illustrate the universal character of translation score developing methods under analysis. Personal experience in the international theatre-making projects, opera laboratories, cross-cultural master-classes give more opportunities to single out the conditions, forms, means and principles of translation score developing as well as the translator/interpreter’s functions as cultural liaison for multiethnic collaboration.

Keywords: methodology of translation score developing, pre-production, analysis, production, post-production, ethnic scene theory, theatre anthropology, laboratory, master-class, educational project, academic project, participant observation, super-objective

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Authors: Boumediene Hamzi, Turky N. AlOtaiby, Saleh AlShebeili, Arwa AlAnqary

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We introduce a data-driven method for seizure detection drawing on recent progress in Machine Learning. The method is based on embedding probability measures in a high (or infinite) dimensional reproducing kernel Hilbert space (RKHS) where the Maximum Mean Discrepancy (MMD) is computed. The MMD is metric between probability measures that are computed as the difference between the means of probability measures after being embedded in an RKHS. Working in RKHS provides a convenient, general functional-analytical framework for theoretical understanding of data. We apply this approach to the problem of seizure detection.

Keywords: kernel methods, maximum mean discrepancy, seizure detection, machine learning

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Authors: Fouzia Amireche-Ziar, Ilham Mokbel, Jacques Jose

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The vapour pressures of the three binary mixtures: 1, 2- dichloroethane + 1,3-dioxolane, + 1,4-dioxane or + tetrahydropyrane, are carried out at ten temperatures ranging from 273 to 353.15 K. An accurate static device was employed for these measurements. The VLE data were reduced using the Redlich-Kister equation by taking into consideration the vapour pressure non-ideality in terms of the second molar virial coefficient. The experimental data were compared to the results predicted with the DISQUAC and Dortmund UNIFAC group contribution models for the total pressures P and the excess molar Gibbs energies GE.

Keywords: disquac model, dortmund UNIFAC model, excess molar Gibbs energies GE, VLE

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Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

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As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Panwasn Mahalawalert

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The purposes of this research were analyzed differential item functioning and differential test functioning of SWUSAT aptitude test classification by sex variable. The data used in this research is the secondary data from Srinakharinwirot University Scholastic Aptitude Test 2013 (SWUSAT). SWUSAT test consists of four subjects. There are verbal ability test, number ability test, reasoning ability test and spatial ability test. The data analysis was analyzed in 2 steps. The first step was analyzing descriptive statistics. In the second step were analyzed differential item functioning (DIF) and differential test functioning (DTF) by using the DIFAS program. The research results were as follows: The results of DIF and DTF analysis for all 10 tests in year 2013. Gender was the characteristic that found DIF all 10 tests. The percentage of item number that found DIF is between 6.67% - 60%. There are 5 tests that most of items favors female group and 2 tests that most of items favors male group. There are 3 tests that the number of items favors female group equal favors male group. For Differential test functioning (DTF), there are 8 tests that have small level.

Keywords: aptitude test, differential item functioning, differential test functioning, educational measurement

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Authors: J. F. Reinoso-Gordo, F. J. Ariza-López, A. Mozas-Calvache, J. L. García-Balboa, S. Eddargani

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The DEMs quality may depend on several factors such as data source, capture method, processing type used to derive them, or the cell size of the DEM. The two most important capture methods to produce regional-sized DEMs are photogrammetry and LiDAR; DEMs covering entire countries have been obtained with these methods. The quality of these DEMs has traditionally been evaluated by the national cartographic agencies through punctual sampling that focused on its vertical component. For this type of evaluation there are standards such as NMAS and ASPRS Positional Accuracy Standards for Digital Geospatial Data. However, it seems more appropriate to carry out this evaluation by means of a method that takes into account the superficial nature of the DEM and, therefore, its sampling is superficial and not punctual. This work is part of the Research Project "Functional Quality of Digital Elevation Models in Engineering" where it is necessary to control the quality of a DEM whose data source is an experimental LiDAR flight with a density of 14 points per square meter to which we call Point Cloud Product (PCpro). In the present work it is described the capture data on the ground and the postprocessing tasks until getting the point cloud that will be used as reference (PCref) to evaluate the PCpro quality. Each PCref consists of a patch 50x50 m size coming from a registration of 4 different scan stations. The area studied was the Spanish region of Navarra that covers an area of 10,391 km2; 30 patches homogeneously distributed were necessary to sample the entire surface. The patches have been captured using a Leica BLK360 terrestrial laser scanner mounted on a pole that reached heights of up to 7 meters; the position of the scanner was inverted so that the characteristic shadow circle does not exist when the scanner is in direct position. To ensure that the accuracy of the PCref is greater than that of the PCpro, the georeferencing of the PCref has been carried out with real-time GNSS, and its accuracy positioning was better than 4 cm; this accuracy is much better than the altimetric mean square error estimated for the PCpro (<15 cm); The kind of DEM of interest is the corresponding to the bare earth, so that it was necessary to apply a filter to eliminate vegetation and auxiliary elements such as poles, tripods, etc. After the postprocessing tasks the PCref is ready to be compared with the PCpro using different techniques: cloud to cloud or after a resampling process DEM to DEM.

Keywords: data quality, DEM, LiDAR, terrestrial laser scanner, accuracy

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Authors: Yemisrach Mihertu Amsale

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The purpose of this study was to compare burnout and coping strategies between HIV counselors in face to face and online counseling settings in Addis Ababa. The study was mixed approach design that was quantitative and qualitative. For the quantitative data the participants involved in this study included 64 face to face and 47 online HIV counselors in both counseling settings. In addition, 23 participants were involved to offer qualitative data from both counseling settings. For the purpose of gathering the quantitative data, the instruments, namely, demographic questionnaire, Maslach Burnout Inventory and the COPE questionnaire, were used to gather quantitative data. Qualitative data was also gathered in the FGD Guide and Interview Guide. Thus, this study revealed that HIV counselors in online counseling settings scored high on emotional exhaustion, depersonalization and low in personal accomplishment dimensions of burnout as compared to HIV counselors in face to face setting and the difference was statistically significant in emotional exhaustion and personal accomplishment, but there was no a significant difference on depersonalization dimension of burnout between the two groups. In addition, the present study revealed a statistically significant difference on problem focused coping strategy between the two groups and yet for on the emotion focused coping strategy the difference was not statistically significant. Statistically negative correlation was observed between some demographic variables such as age with emotional exhaustion and depersonalization dimensions of burnout; years of experiences and personal accomplishment dimension of burnout. A statistically positive correlation was also observed between average number of clients served per day and emotional exhaustion. Sex was having a statistically positive correlation with coping strategy. Lastly, a significant positive correlation was also observed in the emotional exhaustion dimension of the burnout and the emotional focused coping strategy. Generally, this study has shown that HIV counselors suffer from moderate to high level of burnout. Based on the findings, conclusions were made and recommendations were forwarded.

Keywords: counseling, burnout management, psychological, behavioral sciences

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Authors: Jamuna Loganath

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Education is the key to the development of any individual’s personality. Today’s students will be tomorrow’s citizens of the global society. The education of the student is the edifice on which his/her future will be built. Schools therefore should provide an all-round development of students so as to foster a healthy society. The behaviors and the attitude of the students in school play an essential role for the success of the education process. Frequent reports of misbehaviors such as clowning, harassing classmates, verbal insults are becoming common in schools today. If this issue is left unattended, it may develop a negative attitude and increase the delinquent behavior. So, the need of the hour is to find a solution to this problem. To solve this issue, it is important to monitor the students’ behaviors in school and give necessary feedback and mentor them to develop a positive attitude and help them to become a successful grownup. Nevertheless, measuring students’ behavior and attitude is extremely challenging. None of the present technology has proven to be effective in this measurement process because actions, reactions, interactions, response of the students are rarely used in the course of the data due to complexity. The purpose of this proposal is to recommend an effective supervising system after carrying out a feasibility study by measuring the behavior of the Students. This can be achieved by equipping schools with CCTV cameras. These CCTV cameras installed in various schools of the world capture the facial expressions and interactions of the students inside and outside their classroom. The real time raw videos captured from the CCTV can be uploaded to the cloud with the help of a network. The video feeds get scooped into various nodes in the same rack or on the different racks in the same cluster in Hadoop HDFS. The video feeds are converted into small frames and analyzed using various Pattern recognition algorithms and MapReduce algorithm. Then, the video frames are compared with the bench marking database (good behavior). When misbehavior is detected, an alert message can be sent to the counseling department which helps them in mentoring the students. This will help in improving the effectiveness of the education process. As Video feeds come from multiple geographical areas (schools from different parts of the world), BIG DATA helps in real time analysis as it analyzes computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It also analyzes data that can’t be analyzed by traditional software applications such as RDBMS, OODBMS. It has also proven successful in handling human reactions with ease. Therefore, BIG DATA could certainly play a vital role in handling this issue. Thus, effectiveness of the education process can be enhanced with the help of video analytics using the latest BIG DATA technology.

Keywords: big data, cloud, CCTV, education process

Procedia PDF Downloads 236

Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Ismail Seçer, Kerime Meryem Dereli̇oğlu

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This study is conducted to determine the effects of group counseling program on secondary school 9th grade students’ assertiveness skills. The study group was formed of 100 students who have received education in Erzurum Kültür Elementary School in 2015-2016 education years. RAE-Rathus Assertiveness Schedule developed by Voltan Acar was applied on this group to gather data. 40 students who got lower grades from the inventory were divided randomly into experimental and control groups. Each group is formed of 20 students. Group counseling program was carried out on the experimental group to improve the students’ assertiveness skills for 8 weeks. Single-way and two-way analysis of covariance (ANCOVA) were used in the analysis of the data. The data was analyzed by using the SPSS 19.00. The results of the study show that assertiveness skills of the students who participate in the group counseling program increased meaningfully compared to the control group and pre-experiment. Besides, it was determined that the change observed in the experimental group occurred separately from the age and socio-economic level variables, and it was determined with the monitoring test applied after four months that this affect was continued. According to this result, it can be said that the applied group counseling program is an effective means to improve the assertiveness skills of secondary school students.

Keywords: high school, assertiveness, assertiveness inventory, assertiveness education

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Authors: Jihad S. Daba, J. P. Dubois, Yvette Antar

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With the exponential growth of cellular users, a new generation of cellular networks is needed to enhance the required peak data rates. The co-channel interference between neighboring base stations inhibits peak data rate increase. To overcome this interference, multi-cell cooperation known as coordinated multipoint transmission is proposed. Such a solution makes use of multiple-input-multiple-output (MIMO) systems under two different structures: Micro- and macro-diversity. In this paper, we study the capacity and bit error rate in cellular networks using MIMO technology. We analyse both micro- and macro-diversity schemes and develop a hybrid model that switches between macro- and micro-diversity in the case of hard handoff based on a cut-off range of signal-to-noise ratio values. We conclude that our hybrid switched micro-macro MIMO system outperforms classical MIMO systems at the cost of increased hardware and software complexity.

Keywords: cooperative multipoint transmission, ergodic capacity, hard handoff, macro-diversity, micro-diversity, multiple-input-multiple output systems, orthogonal frequency division multiplexing

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

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Authors: Seval Kizildag, Ozge Can Aran

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The effective intervention of counselors’ in conflict between spouses may be effective in increasing the quality of marital relationship. At this point, it is necessary for counselors to consider their own value systems at first and then reflect this correctly to the counseling process. For this reason, it is primarily important to determine the needs of counselors. Starting from this point of view, in this study, it is aimed to reveal the perspective of counselor candidates about the universal values in marriage relation. The study group of the survey was formed by sampling, which is one of the prospective sampling methods. As a criterion being a candidate for counseling area and having knowledge of the concepts of the Marriage and Family Counseling course is based, because, that candidate students have a comprehensive knowledge of the field and that students have mastered the concepts of marriage and family counseling will strengthen the findings of this study. For this reason, 61 counselor candidates, 32 (52%) female and 29 (48%) male counselor candidates, who were about to graduate from a university in south-east Turkey and who took a Marriage and Family Counseling course, voluntarily participated in the study. The average age of counselor candidates’ is 23. At the same time, 70 % of the parents of these candidates brought about their marriage through arranged marriage, 13% through flirting, 8% by relative marriage, 7% through friend circles and 2% by custom. The data were collected through Demographic Information Form and a form titled ‘Universal Values Form in Marriage’ which consists of six questions prepared by researchers. After the data were transferred to the computer, necessary statistical evaluations were made on the data. The qualitative data analysis was used on the data which was obtained in the study. The universal values which include six basic values covering trustworthiness, respect, responsibility, fairness, caring, citizenship, determined under the name as ‘six pillar of character’ are used as base and frequency values of the data were calculated trough content analysis. According to the findings of the study, while the value which most students find the most important value in marriage relation is being reliable, the value which they find the least important is to have citizenship consciousness. Also in this study, it is found out that counselor candidates associate the value of being trustworthiness ‘loyalty’ with (33%) as the highest in terms of frequency, the value of being respect ‘No violence’ with (23%), the value of responsibility ‘in the context of gender roles and spouses doing their owns’ with (35%) the value of being fairness ‘impartiality’ with (25%), the value of being caring ‘ being helpful’ with (25%) and finally as to the value of citizenship ‘love of country’ with (14%) and’ respect for the laws ‘ with (14%). It is believed that these results of the study will contribute to the arrangements for the development of counseling skills for counselor candidates regarding value in marriage and family counseling curricula.

Keywords: caring, citizenship, counselor candidate, fairness, marriage relationship, respect, responsibility, trustworthiness, value system

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Authors: Cathy Basterfield

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Issue: To engage in one’s own health care, health professionals need to be aware of an individual’s specific skills and abilities for best communication. One of the most discussed is health literacy. One of the assumed skills and abilities for adults is an individuals’ health literacy. Background: A review of publicly available health content appears to assume all adult readers will have a broad and full capacity to read at a high level of literacy, often at a post-school education level. Health information writers and clinicians need to recognise one critical area for why there may be little or no change in a person’s behaviour, or no-shows to appointments. Perhaps unintentionally, they are miscommunicating with the majority of the adult population. Health information contains many literacy domains. It usually includes technical medical terms or jargon. Many fact sheets and other information require scientific literacy with or without specific numerical literacy. It may include graphs, percentages, timing, distance, or weights. Each additional word or concept in these domains decreases the readers' ability to meaningfully read, understand and know what to do with the information. An attempt to begin to read the heading where long or unfamiliar words are used will reduce the readers' motivation to attempt to read. Critically people who have low literacy are overwhelmed when pages are covered with lots of words. People attending a health environment may be unwell or anxious about a diagnosis. These make it harder to read, understand and know what to do with the information. But access to health information must consider an even wider range of adults, including those with poor school attainment, migrants, and refugees. It is also homeless people, people with mental health illnesses, or people who are ageing. People with low literacy also may include people with lifelong disabilities, people with acquired disabilities, people who read English as a second (or third) language, people who are Deaf, or people who are vision impaired. Outcome: This paper will discuss Easy English, which is developed for adults. It uses the audiences’ everyday words, short sentences, short words, and no jargon. It uses concrete language and concrete, specific images to support the text. It has been developed in Australia since the mid-2000s. This paper will showcase various projects in the health domain which use Easy English to improve the understanding and functional use of written information for the large numbers of adults in our communities who do not have the health literacy to manage a range of day to day reading tasks. See examples from consent forms, fact sheets and choice options, instructions, and other functional documents, where Easy English has been developed. This paper will ask individuals to reflect on their own work practice and consider what written information must be available in Easy English. It does not matter how cutting-edge a new treatment is; when adults can not read or understand what it is about and the positive and negative outcomes, they are less likely to be engaged in their own health journey.

Keywords: health literacy, inclusion, Easy English, communication

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Authors: Mme Hamani Née Guessas Ghaniya

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The transport is the base of the development of the exchanges and the business, being both a recognized determiner of the economic and social development. The development of the transport is in the center of the big challenges of development of countries, but it is also at the heart of big contradictions, since we integrate the environmental issues which are bound to him, in particular through the questions of energy. Indeed, the energy consumption by the sector of transport is one of bigger concerns, because it is increasing and it has a big impact on our environment. The main consequences are, the atmospheric pollution causing an increase of the greenhouse effect which causes a global warming. These global warming risks to engender a partial cast iron of polar caps so raising the level of seas, flooding the low coastal zones, certain islands and the deltas. Thus, the purpose of this communication is to present the impact of the energy consumption by the sector of transport on the air quality, showing its effect on the health and on the global warming.

Keywords: energy consumption, sector of transport, air quality, atmospheric pollution

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Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

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Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

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Authors: Jayanta Bora, Sukhvinder Kaur, Ashok Agarwal, Sangeeta Kaul

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Background: It is important for targeted interventions to consider vulnerabilities of female sex workers (FSWs) such as poverty, work-related mobility and literacy for effective human immunodeficiency virus (HIV) prevention. This paper examines the association between vulnerability and behavioural outcomes among FSWs in Thane district, Maharashtra under USAID PHFI-PIPPSE project. Methods: Data were used from the Behavioural Tracking Survey, a cross-sectional behavioural study conducted in 2015 with 503 FSWs randomly selected from 12 TI-NGOs which were functioning and providing services to FSWs in Thane district prior to April 2014 in Thane district of Maharashtra. We have created the “vulnerability index”, a composite index of literacy, factors of dependence (alternative livelihood options, current debt), and aspects of sex work (mobility and duration in sex work) as a dependent variable. The key independent measures used were program exposure to intervention, service uptake, self-confidence, and self-identity. Bi-variate and multivariate logistic regressions were used to examine the study objectives. Results: A higher proportion of FSWs who were in the age-group 18–25 years from brothel/street /home/ lodge-based were categorized as highly vulnerable to HIV risk as compared to bar-based sex worker (74.1% versus 59.8%, P,0.002); regression analysis highlighted lower odds of vulnerability among FSWs who were aware of services and visited NGO clinic for medical check-up and counselling for STI [AOR= 0.092, 95% CI 0.018-0.460; P,0.004], However, lower odds of vulnerability on confident in supporting fellow sex worker in crisis [AOR= 0.601, 95% CI 0.476-0.758; P, 0.000] and were able to turn away clients when they refused to use a condom during sex [AOR= 0.524, 95% CI 0.342-0.802; P, 0.003]. Conclusion: The results highlight that FSWs associated with TIs and getting services are less vulnerable and highly empowered. As a result of behavioural change communication and other services provided by TIs, FSWs were able to successfully negotiate about condom use with their clients and manage solidarity in the crisis situation for fellow FSWs. Therefore, it is evident from study paper that TI prevention programs may transform the lives of masses considerably and may open a window of opportunity to infuse the information and awareness about HIV risk.

Keywords: female sex worker, HIV prevention, HIV service uptake, vulnerability

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Authors: Adel S. Alanazi

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The transition of a student with a disability from school to work is the most crucial phase while moving from the stage of adolescence into early adulthood. In this process, young individuals face various difficulties and challenges in order to accomplish the next venture of life successfully. In this respect, this paper aims to examine the challenges encountered by the individuals with intellectual disabilities in transition to work in Saudi Arabia. For this purpose, this study has undertaken a qualitative research-based methodology; wherein interpretivist philosophy has been followed along with inductive approach and exploratory research design. The data for the research has been gathered with the help of semi-structured interviews, whose findings are analysed with the help of thematic analysis. Semi-structured interviews were conducted with parents of persons with intellectual disabilities, officials, supervisors and specialists of two vocational rehabilitation centres providing training to intellectually disabled students, in addition to that, directors of companies and websites in hiring those individuals. The total number of respondents for the interview was 15. The purposive sampling method was used to select the respondents for the interview. This sampling method is a non-probability sampling method which draws respondents from a known population and allows flexibility and suitability in selecting the participants for the study. The findings gathered from the interview revealed that the lack of awareness among their parents regarding the rights of their children who are intellectually disabled; the lack of adequate communication and coordination between various entities; concerns regarding their training and subsequent employment are the key difficulties experienced by the individuals with intellectual disabilities. Training in programmes such as bookbinding, carpentry, computing, agriculture, electricity and telephone exchange operations were involved as key training programmes. The findings of this study also revealed that information technology and media were playing a significant role in smoothing the transition to employment of individuals with intellectual disabilities. Furthermore, religious and cultural attitudes have been identified to be restricted for people with such disabilities in seeking advantages from job opportunities. On the basis of these findings, it can be implied that the information gathered through this study will serve to be highly beneficial for Saudi Arabian schools/ rehabilitation centres for individuals with intellectual disability to facilitate them in overcoming the problems they encounter during the transition to work.

Keywords: intellectual disability, transition services, rehabilitation centre, employment

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Authors: Rutusha Bhutada, Gaurav Chavan, Sarvesh Kasat, Varsha Mujumdar

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This software system will be an Augmented Reality application designed to maximize the doctor’s productivity by providing tools to assist in automating the patient recognition and updating patient’s records using face and voice recognition features, which would otherwise have to be performed manually. By maximizing the doctor’s work efficiency and production, the application will meet the doctor’s needs while remaining easy to understand and use. More specifically, this application is designed to allow a doctor to manage his productive time in handling the patient without losing eye-contact with him and communicate with a group of other doctors for consultation, for in-place treatments through video streaming, as a video study. The system also contains a relational database containing a list of doctor, patient and display techniques.

Keywords: augmented reality, hand-held devices, head-mounted devices, marker based systems, speech recognition, face detection

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Authors: W. Linthicum-Blackhorse, P. Martens

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This present study seeks to discover attitudinal commonalities and differences within a musician population relative to the communication of emotion via music. We hypothesized that instrument type, as well as age and gender, would bear significantly on musicians’ opinions. A survey was administered to 178 participants; 152 were current music majors (mean age 20.3 years, 62 female) and 26 were adult participants in a community choir (mean age 54.0 years, 12 female). The adult participants were all vocalists, while student participants represented the full range of orchestral instruments. The students were grouped by degree program, (performance, music education, or other) and instrument type (voice, brass, woodwinds, strings, percussion). The survey asked 'How important are each of the following areas to you for portraying emotion in music?' Participants were asked to rate each of 15 items on a scale of 1 (not at all important) to 10 (very important). Participants were also instructed to leave blank any item that they did not understand. The 15 items were: dynamic contrast, overall volume, phrasing, facial expression, staging (placement), pitch accuracy, tempo changes, bodily movement, your mood, your attitude, vibrato, rubato, stage/room lighting, clothing type, and clothing color. Contrary to our hypothesis, there was no overall effect of gender or age, and neither did any single response item show a significant difference due to these subject parameters. Among the student participants, however, one-way ANOVA revealed a significant effect of degree program on the rated importance of four items: dynamic contrast, tempo changes, vibrato, and rubato. Significant effects of instrument type were found in the responses to eight items: facial expression, staging, body movement, vibrato, rubato, lighting, clothing type, and clothing color. Post hoc comparisons (Tukey) show that some variation follows from obvious differences between instrument types (e.g. string players are more concerned with vibrato than everyone but woodwind players; vocalists are significantly more concerned with facial expression than everyone but string players), but other differences could point to communal mindsets toward vicarious cues within instrument type. These mindsets could be global (e.g. brass players deeming body movement significantly less important than string players, being less often featured as soloists and appearing less often at the front of the stage) or local (e.g. string players being significantly more concerned than all other groups about both clothing color and type, perhaps due to the strongly-expressed opinions of specific teachers). Future work will attempt to identify the source of these self-appraisals, whether enculturated via explicit pedagogy, or whether absorbed from individuals' observations and performance experience.

Keywords: performance, vicarious cues, communication, emotion

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Authors: Phanumas Khumsat, Chalermchai Janmane

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Low-voltage instrumentation amplifier has been proposed for 3-lead electrocardiogram measurement system. The circuit’s interference rejection technique is based upon common-mode feed-forwarding where common-mode currents have cancelled each other at the output nodes. The common-mode current for cancellation is generated by means of common-mode sensing and emitter or source followers with resistors employing only one transistor. Simultaneously this particular transistor also provides common-mode feedback to the patient’s right/left leg to further reduce interference entering the amplifier. The proposed designs have been verified with simulations in 0.18-µm CMOS process operating under 1.0-V supply with CMRR greater than 80dB. Moreover ECG signals have experimentally recorded with the proposed instrumentation amplifiers implemented from discrete BJT (BC547, BC558) and MOSFET (ALD1106, ALD1107) transistors working with 1.5-V supply.

Keywords: electrocardiogram, common-mode feedback, common-mode feedforward, communication engineering

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Authors: A. Capodieci, G. Del Fiore, L. Mainetti

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Recently, the use of web 2.0 tools has increased in companies and public administration organizations. This phenomenon, known as "Enterprise 2.0", has, de facto, modified common organizational and operative practices. This has led “knowledge workers” to change their working practices through the use of Web 2.0 communication tools. Unfortunately, these tools have not been integrated with existing enterprise information systems, a situation that could potentially lead to a loss of information. This is an important problem in an organizational context, because knowledge of information exchanged within the organization is needed to increase the efficiency and competitiveness of the organization. In this article we demonstrate that it is possible to capture this knowledge using collaboration processes, which are processes of abstraction created in accordance with design patterns and applied to new organizational operative practices.

Keywords: business practices, business process patterns, collaboration tools, enterprise 2.0, knowledge workers

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Authors: Mehry Daraei

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The goal of this study was to survey the components and affective factors on organizational commitment of Islamic Azad university Khoramabad Baranch’s faculty members. The research method was correlation by causal modeling and data were gathered by questionnaire. Statistical society consisted of 147 faculty members in Islamic Azad University Khoramabad Branch and sample size was determined as 106 persons by Morgan’s sample table that were selected by class sampling. Correlation test, T-single group test and path analysis test were used for analysis of data. Data were analyzed by Lisrel software. The results showed that organizational corporate was the most effective element on organizational commitment and organizational corporate, experience work and organizational justice were only in direct relation with organizational commitment. Also, job security had direct and indirect effect on OC. Job security had effect on OC by gender. Gender variable had direct and indirect effect on OC. Gender had effect on OC by organizational corporate. Job opportunities out of university also had direct and indirect effect on OC, which means job opportunities had indirect effect on OC by organizational corporate.

Keywords: organization, commitment, job security, Islamic Azad University

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an artificial neural network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study includes granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R²), Root mean square error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: national development, granite, profitability assessment, ANN models

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