Search results for: open source data

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: Anna-Caroline Lavergne-Bril, Jean-François Colin, David Peralta, Pascale Maldivi

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Cobalt is a critical material, widely used in Li-ion batteries. Due to the planned electrification of European vehicles, cobalt needs are expending – and resources are limited. To meet the needs in cobalt to come, it is necessary to develop new efficient ways to recycle cobalt. One of the biggest sources comes from old electrical vehicles batteries (batteries sold in 2019: 500 000 tons of waste to be). A closed loop process of cobalt recycling has been developed and this presentation aims to present the selectivity mechanism of cobalt over manganese and nickel in solution. Cobalt precipitation as a ZIF material (Zeolitic Imidazolate framework) from a starting solution composed of equimolar nickel, manganese and cobalt is studied. A 2-MeIm (2-methylimidazole) linker is introduced in a multimetallic Ni, Mn, Co solution and the resulting ZIF-67 is 100% pure Co among its metallic centers. Selectivity of Co over Ni is experimentally studied and DFT modelisation calculation are conducted to understand the geometry of ligand-metal-solvent complexes in solution. Selectivity of Co over Mn is experimentally studied, and DFT modelisation calcucation are conducted to understand the link between pKa of the ligand and precipitration of Mn impurities within the final material. Those calculation open the way to other ligand being used in the same process, with more efficiency. Experimental material are synthetized from bimetallic (Ni²⁺/Co²⁺, Mn²⁺/Co²⁺, Mn²⁺/Ni²⁺) solutions. Their crystallographic structure is analysed by XRD diffraction (Brüker AXS D8 diffractometer, Cu anticathode). Morphology is studied by scanning electron microscopy, using a LEO 1530 FE-SEM microscope. The chemical analysis is performed by using ICP-OES (Agilent Technologies 700 series ICP-OES). Modelisation calculation are DFT calculation (density functional theory), using B3LYP, conducted with Orca 4.2.

Keywords: MOFs, ZIFs, recycling, closed-loop, cobalt, li-ion batteries

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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: 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

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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: Rajiv Arora

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Biodiesel may be economical if produced from inexpensive feedstock which commonly contains high level of free fatty acids (FFA) as an inhibitor in production of methyl ester. In this study, a two-step process for biodiesel production from high FFA spent bleach earth oil in a batch reactor is developed. Oil sample extracted from spent bleaching earth (SBE) was utilized for biodiesel process. In the first step, FFA of the SBE oil was reduced to 1.91% through sulfuric acid catalyzed esterification. In the second step, the product prepared from the first esterification process was carried out transesterification with an alkaline catalyst. The influence of four variables on conversion efficiency to methyl ester, i.e., methanol/ SBE oil molar ratio, catalyst amount, reaction temperature and reaction time, was studied in the second stage. The optimum process variables in the transesterification were methanol/oil molar ratio 6:1, heterogeneous catalyst conc. 5 wt %, reaction temperature 65 °C and reaction time 60 minutes to produce biodiesel. Major fuel properties of SBE biodiesel were measured to comply with ASTM and EN standards. Therefore, an optimized process for production of biodiesel from a low-cost high FFA source was accomplished.

Keywords: biodiesel, esterification, free fatty acids, residual oil, spent bleaching earth, transesterification

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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: Berna Yaylalı, Isin Can Traunmüller

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This paper explores the emergent bottom-up practices in the fields of architecture and urban design within comparative perspectives of two cities. As a temporary, easily affordable intervention that gives the possibility of transforming neglected spaces into vibrant public spaces, tactical urbanism, together with creative place-making strategies, presents alternative ways of creating sustainable developments in derelict and underused areas. This study examines the potential of social and physical developments through a reading of case studies of two creative spatial practices: a pop-up garden transformed from an unused derelict space in Favoriten, Vienna, and an urban community garden in Kuzguncuk, Istanbul. Two cities are chosen according to their multicultural population and diversity. Istanbul was selected as a design city by UNESCO Creative Cities Network in 2017, and Vienna was declared an open and livable city by its local government. This research will use media archives and reports, interviews with locals and local governments, site observations, and visual recordings as methods to provide a critical reading on creative public spaces from the view of local users in these neighborhoods. Reflecting on these emergent ways, this study aims at discussing the production process of tactile urbanism with the practices of locals and the decision-making process with cases from İstanbul and Vienna. The comparison between their place-making strategies in tactical urbanism will give important insights for future developments.

Keywords: creative city, tactical urbanism, neglected area, public space

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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: K. M. S. Weerasinghe, A. H. K. Balasooriya, S. L. Ransingha, G. D. Krishantha, R. S. Brhakamanagae, L. C. Wijethilke

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Tomato (Lycopersicon esculentum Mill.) is a major horticultural crop with an estimated global production of over 120 million metric tons and ranks first as a processing crop. The average tomato productivity in Sri Lanka (11 metric tons/ha) is much lower than the world average (24 metric tons/ha).To meet the tomato demand for the increasing population the productivity has to be intensified through the agronomic-techniques. Nutrition is one of the main factors which govern the growth and yield of tomato and the main nutrient source soil affect the plant growth and quality of the produce. Continuous cropping, improper fertilizer usage etc., cause widespread nutrient deficiencies. Therefore synthetic fertilizers and organic manures were introduced to enhance plant growth and maximize the crop yields. In this study, effects of macro and micronutrient supplementations on improvement of growth and yield of tomato were investigated. Selected tomato variety is Maheshi and plants were grown in Regional Agricultural and Research Centre Makadura under the Department of Agriculture recommended (DOA) macro nutrients and various combination of Ontario recommended dosages of secondary and micro fertilizer supplementations. There were six treatments in this experiment and each treatment was replicated in three times and each replicate consisted of six plants. Other than the DOA recommendation, five combinations of Ontario recommended dosage of secondary and micronutrients for tomato were also used as treatments. The treatments were arranged in a Randomized Complete Block Design. All cultural practices were carried out according to the DOA recommendations. The mean data was subjected to the statistical analysis using SAS package and mean separation (Duncan’s Multiple Range test at 5% probability level) procedures. Secondary and micronutrients containing treatments significantly increased most of the growth parameters. Plant height, plant girth, number of leaves, leaf area index etc. Fruits harvested from pots amended with macro, secondary and micronutrients performed best in terms of total yield; yield quality; to pots amended with DOA recommended dosage of fertilizer for tomato. It could be due to the application of all essential macro and micro nutrients that rise in photosynthetic activity, efficient translocation and utilization of photosynthates causing rapid cell elongation and cell division in actively growing region of the plant leading to stimulation of growth and yield were caused. The experiment revealed and highlighted the requirements of essential macro, secondary and micro nutrient fertilizer supplementations for tomato farming. The study indicated that, macro and micro nutrient supplementation practices can influence growth and yield performances of tomato fruits and it is a promising approach to get potential tomato yields.

Keywords: macro and micronutrients, tomato, SAS package, photosynthates

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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: Mkhokheli Sithole, Brenda N. Muchapondwa

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Food security is becoming a critical issue for people residing mainly in the rural areas where frequent droughts interrupt food production, reduce income, compromise the ability to save and erode livelihoods. This tends to increase the vulnerability of poor households to food and income insecurity, hence, malnutrition. There is an emerging need for DRR strategies to complement the existing rain fed crop production based livelihoods. One of such strategies employed by the community of Nerumedzo in Bikita district is the harvesting of Encosternum delegorguei insect. This article analyses the livelihood impacts of Encosternum delegorguei insect as a DRR strategy. The research used a combination of qualitative and quantitative approaches. The insect samples were tested in the laboratory for their nutritional composition while surveys were done on a sample of 40 community members. Participatory observations and 5 focus group discussions were also done. The results revealed that harvesting the Encosternum delegorguei insects provides a livelihood for the locals by complementing crop production thereby mitigating potential negative effects of frequent droughts. The insects are now a significant source of income to poor households in the community.

Keywords: disaster risk reduction, livelihoods, human, social sciences

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Authors: Assia Amri, Naima Layachi, Ali Ladjama

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The characterization of some Algerian honey was carried out on the basis of their physico-chemical properties: moisture,hydroxy methyl furfural, diastase activity, pH,free, total and lactonic acidity, electrical conductivity, minerals and proline content. Studied samples are found to be low in moisture and therefore safe from fermentation, low in HMF level and high in diastase activity. Additionally the diastase activity and the HMF content are widely recognized parameters indicating the freshness of honey. Phenolic compounds present in honey are classified into two groups - simple phenols and polyphenols. The simple phenols in honey are various phenol acids, but polyphenols are various flavonoids and flavonides. The aim of our work was to determine antioxidant properties of various Algerian honey samples–the total phenol content, total flavonoids content, as well as honey anti radical activity.The quality of honey samples differs on account of various factors such as season, packaging and processing conditions, floral source, geographical origin and storage period. It is important that precautions should be taken to ensure standardization and rationalization of beekeeping techniques, manufacturing procedures and storing processes to improve honey quality.

Keywords: honey, physico-chemical characterization, phenolic coumpound, HMF, diastase activity

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Authors: Qasim Kriri, Harsh B. Desai

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Water supply and sanitation in Saudi Arabia is portrayed by difficulties and accomplishments. One of the fundamental difficulties is water shortage. With a specific end goal to beat water shortage, significant ventures have been attempted in sea water desalination, water circulation, sewerage, and wastewater treatment. The motivation behind Statistical Process Control (SPC) is to decide whether the execution of a procedure is keeping up an acceptable quality level [AQL]. SPC is an analytical decision-making method. A fundamental apparatus in the SPC is the Control Charts, which follow the inconstancy in the estimations of the item quality attributes. By utilizing the suitable outline, administration can decide whether changes should be made with a specific end goal to keep the procedure in charge. The two most important quality factors in the distilled water which were taken into consideration were pH (Potential of Hydrogen) and TDS (Total Dissolved Solids). There were three stages at which the quality checks were done. The stages were as follows: (1) Water at the source, (2) water after chemical treatment & (3) water which is sent for packing. The upper specification limit, central limit and lower specification limit are taken as per Saudi water standards. The procedure capacity to accomplish the particulars set for the quality attributes of Berain water Factory chose to be focused by the proposed SPC system.

Keywords: acceptable quality level, statistical quality control, control charts, process charts

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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: Stehr Melanie

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The availability of apposite information is essential for the decision-making process of organizational buyers. Due to the constraints of the Covid-19 crisis, information channels that emphasize face-to-face contact (e.g. sales visits, trade shows) have been unavailable, and usage of digitally-driven information channels (e.g. videoconferencing, platforms) has skyrocketed. This paper explores the question in which areas the pandemic induced shift in the use of information channels could be sustainable and in which areas it is a temporary phenomenon. While information and buying behavior in B2C purchases has been regularly studied in the last decade, the last fundamental model of organizational buying behavior in B2B was introduced by Johnston and Lewin (1996) in times before the advent of the internet. Subsequently, research efforts in B2B marketing shifted from organizational buyers and their decision and information behavior to the business relationships between sellers and buyers. This study builds on the extensive literature on situational factors influencing organizational buying and information behavior and uses the economics of information theory as a theoretical framework. The research focuses on the German woodworking industry, which before the Covid-19 crisis was characterized by a rather low level of digitization of information channels. By focusing on an industry with traditional communication structures, a shift in information behavior induced by an exogenous shock is considered a ripe research setting. The study is exploratory in nature. The primary data source is 40 in-depth interviews based on the repertory-grid method. Thus, 120 typical buying situations in the woodworking industry and the information and channels relevant to them are identified. The results are combined into clusters, each of which shows similar information behavior in the procurement process. In the next step, the clusters are analyzed in terms of the post and pre-Covid-19 crisis’ behavior identifying stable and dynamic information behavior aspects. Initial results show that, for example, clusters representing search goods with low risk and complexity suggest a sustainable rise in the use of digitally-driven information channels. However, in clusters containing trust goods with high significance and novelty, an increased return to face-to-face information channels can be expected after the Covid-19 crisis. The results are interesting from both a scientific and a practical point of view. This study is one of the first to apply the economics of information theory to organizational buyers and their decision and information behavior in the digital information age. Especially the focus on the dynamic aspects of information behavior after an exogenous shock might contribute new impulses to theoretical debates related to the economics of information theory. For practitioners - especially suppliers’ marketing managers and intermediaries such as publishers or trade show organizers from the woodworking industry - the study shows wide-ranging starting points for a future-oriented segmentation of their marketing program by highlighting the dynamic and stable preferences of elaborated clusters in the choice of their information channels.

Keywords: B2B buying process, crisis, economics of information theory, information channel

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Authors: M. Cabral, A. Verdin, G. Garçon, A. Touré, C. Diop, M. Fall, S. Bouhsina, D. Dewaele, F.Cazier, A. Tall Dia, P. Shirali, A. Diouf

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This case-control study dealt with the health adverse effects within the population neighboring the Mbeubeuss waste dump, which is located near the district of Malika (Diamalaye II) in Dakar (Senegal). All the household and industrial waste arising from Dakar are stored in this open landfill without being covered and are therefore possible sources of Pb and Cd contaminated air emissions and lixiviates. The objective of this study is part of improving the health of the population neighboring Mbeubeuss by determining Pb and Cd concentrations both in environment and humans, and studying possible renal function alterations within the adults. Soil and air samples were collected in the control site (Darou Salam) and the waste dump neighboring site (Diamalaye II). Control and exposed adults were recruited as living in Darou Salam (n = 52) and in Diamalaye II (n = 77). Pb and Cd concentrations in soil, air and biological samples were determined. Moreover, we were interested in analyzing some impregnation (zinc protoporphyrin, d-aminolevulinic acid dehydratase) and oxidative stress biomarkers (malonedialdehyde, gluthatione status), in addition to several nephrotoxicity parameters (creatinuria, proteinuria, lactate dehydrogenase, CC16 protein, glutathione S-transferase-alpha and retinol binding protein) in blood and/or urine. The results showed the significant Pb and Cd contamination of the soil and air samples derived from the landfill, and therefore of the neighboring population of adults. This critical exposure to environmental Pb and Cd had some harmful consequences for their health, as shown by the reported oxidative stress and nephrotoxicity signs.

Keywords: Pb and Cd environmental exposure, impregnation markers, landfill, nephrotoxicity markers

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Authors: Muhammad Faizan Rehman Qureshi, Ahmed Al-Kaisy

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Accurate estimation of traffic loads is critical for pavement and bridge design, among other transportation applications. Given the disproportional impact of heavier axle loads on pavement and bridge structures, truck and heavy vehicle traffic is expected to be a major determinant of traffic load estimation. Further, heavy vehicle traffic is also a major input in transportation planning and economic studies. The traditional method for estimating heavy vehicle traffic primarily relies on AADT estimation using Monthly Day of the Week (MDOW) adjustment factors as well as the percent heavy vehicles observed using statewide data collection programs. The MDOW factors are developed using daily and seasonal (or monthly) variation patterns for total traffic, consisting predominantly of passenger cars and other smaller vehicles. Therefore, while using these factors may yield reasonable estimates for total traffic (AADT), such estimates may involve a great deal of approximation when applied to heavy vehicle traffic. This research aims at assessing the approximation involved in estimating heavy vehicle traffic using MDOW adjustment factors for total traffic (conventional approach) along with three other methods of using MDOW adjustment factors for total trucks (class 5-13), combination-unit trucks (class 8-13), as well as adjustment factors for each vehicle class separately. Results clearly indicate that the conventional method was outperformed by the other three methods by a large margin. Further, using the most detailed and data intensive method (class-specific adjustment factors) does not necessarily yield a more accurate estimation of heavy vehicle traffic.

Keywords: traffic loads, heavy vehicles, truck traffic, adjustment factors, traffic data collection

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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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Authors: Haleden Chiririwa, Sandile S. Gwebu

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The coatings industry is a million dollar business, and it is easy and inexpensive to set-up but it is growing very slowly in developing countries, and this study developed a paint formulation which gives better quality and good application properties. The effect of rheology modifiers, i.e. non-ionic polymers hydrophobically-modified ethoxylated urethanes (HEUR), anionic polymers hydrophobically-modified alkali soluble emulsions (HASE) and hydroxyl ethyl cellulose (HEC) on the quality and properties of water-based paints have been investigated. HEC provides the in-can viscosity and increases open working time while HASE improves application properties like spatter resistance and brush loading and HEUR provides excellent scrub resistance. Four paint recipes were prepared using four different thickeners HEC, HASE (carbopol) and Cellulose nitrate. The fourth formulation was thickened with a combination of HASE and HEC, this aimed at improving quality and at the same time reducing cost. The four samples were tested for quality tests such viscosity, sag resistance, volatile matter, tinter effect, drying times, hiding power, scrub resistance and stability on storage. Environmental factors were incorporated in the attempt to formulate an economic and green product. Hydroxyl ethyl cellulose and cellulose nitrate gave high quality and good properties of the paint. HEC and Cellulose nitrate showed stability on storage whereas carbopol thickener was very unstable.

Keywords: properties, thickeners, rheology modifiers, water based paints

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Authors: Hossein Mohammadzadeh, Mojtaba Heydarizad

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Among various water resources, the surface water has a dominant role in providing water supply in the arid and semi-arid region of Iran. Andarokh-Kardeh basin is located in 50 km from Mashhad city - the second biggest city of Iran (NE of Iran), draining by Kardeh river which provides a significant portion of potable and irrigation water needs for Mashhad. The stable isotopes (¹⁸O, ²H,¹³C-DIC, and ¹³C-DOC), as reliable and precious water fingerprints, have been measured in Kardeh river (Kharket, Mareshk, Jong, All and Kardeh stations) and in Kardeh dam reservoirs (at five different sites S1 to S5) during March to June 2011 and June 2012. On δ¹⁸O vs. δ²H diagram, the river samples were plotted between Global and Eastern Mediterranean Meteoric Water lines (GMWL and EMMWL) which demonstrate that various moisture sources are providing humidity for precipitation events in this area. The enriched δ¹⁸O and δ²H values (-6.5 ‰ and -44.5 ‰ VSMOW) of Kardeh dam reservoir are compared to Kardeh river (-8.6‰and-54.4‰), and its deviation from Mashhad meteoric water line (MMWL- δ²H=7.16δ¹⁸O+11.22) is due to evaporation from the open surface water body. The enriched value of δ ¹³C-DIC and high amount of DIC values (-7.9 ‰ VPDB and 57.23 ppm) in the river and Kardeh dam reservoir (-7.3 ‰ VPDB and 55.53 ppm) is due to dissolution of Mozdooran Carbonate Formation lithology (Jm1 to Jm3 units) (contains enriched δ¹³C DIC values of 9.2‰ to 27.7‰ VPDB) in the region. Because of the domination of C3 vegetations in Andarokh_Kardeh basin, the δ¹³C-DOC isotope of the river (-28.4‰ VPDB) and dam reservoir (-32.3‰ VPDB) demonstrate depleted values. Higher DOC concentration in dam reservoir (2.57 ppm) compared to the river (0.72 ppm) is due to more biologogical activities and organic matters in dam reservoir.

Keywords: Dam reservoir, Iran, Kardeh river, Khorasan razavi, Stable isotopes

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Authors: Dinesha Siriwardhane, Indralal De Silva, Sampath Amaratunge

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Objective of this study is to explore the recent trends, patterns and the structural changes in the labour migration from Sri Lanka to Middle East countries and to discuss the possible impacts of those changes on the remittance flow. Study uses secondary data published by Sri Lanka Bureau of Foreign Employment and Central Bank. Thematic analysis of the secondary data revealed that the migration for labour has increased rapidly during past decades. Parallel with that the gender and the skill composition of the migration flow has been changing. Similarly, the destinations for male migration have changed over the period. These show positive implications on the international remittance receipts to the country.

Keywords: migration, middle east, Sri Lanka, social sciences

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Authors: Froogh Shooshtaryzadeh, Pramod Pandey

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The present study investigates place and manner harmony in typically developing (TD) children and children with phonological disorder (PD) who are acquiring Farsi as their first language. Five TD and five PD children are examined regarding their place and manner harmony patterns. Data is collected through a Picture-Naming Task using 132 pictures of different items designed to elicit the production of 132 different words. The examination of the data has indicated some similarities and differences in harmony patterns in PD and TD children. Moreover, the results of this study on the place and manner harmony have illustrated some differences with the results of the preceding studies on languages other than Farsi. The results of this study are discussed and compared with results from other studies. Optimality Theory is employed to explain some of the findings of this study.

Keywords: place harmony, manner harmony, phonological development, Farsi

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Authors: Sourina Bej

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Since the process of decolonization in 1940, several countries in South Asia have witnessed intra-state conflicts owing to ineffective political governance. The conflicts have remained protracted as the countries have failed to make a holistic transition to a democratic state. Nepal is one such South Asian country facing a turmultous journey from monarchy to republicanism. The paper aims to focus on the democratic transition in the context of Nepal’s political, legal and economic institutions. The presence of autocratic feudalistic and centralised state structure with entrenched socio-economic inequalities has resulted in mass uprising only to see the country slip back to the old order. Even a violent civil war led by the Maoists could not overhaul the political relations or stabilize the democratic space. The paper aims to analyse the multiple political, institutional and operational challenges in the implementation of the peace agreement with the Maoist. Looking at the historical background, the paper will examine the problematic nation-building that lies at the heart of fragile peace process in Nepal. Regional dynamics have played a big role in convoluting the peace-building. The new constitution aimed at conflict resolution brought to the open, deep seated hatred among different ethnic groups in Nepal. Apart from studying the challenges to the peace process and the role of external players like India and China in the political reconstruction, the paper will debate on a viable federal solution to the ethnic conflict in Nepal. If the current government fails to pass a constitution accepted by most ethnic groups, Nepal will remain on the brink of new conflict outbreaks.

Keywords: democratisation, ethnic conflict, Nepal, peace process

Procedia PDF Downloads 277

Authors: Ross J. Maestas

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Biofuels are derived from multiple renewable bioenergy feedstocks including animal fats, wood, starchy grains, and oil seeds. Transportation agencies have considered growing the latter two on underutilized and nontraditional lands that they manage, such as in the Right of Way (ROW), abandoned weigh stations, and at maintenance yards. These crops provide the opportunity to generate revenue or supplement fuel once converted and offer a solution to increasing fuel costs and instability by creating a ‘home-grown’ alternative. Biofuels are non-toxic, biodegradable, and emit less Green House Gasses (GHG) than fossil fuels, therefore allowing agencies to meet sustainability goals and regulations. Furthermore, they enable land managers to achieve soil erosion and roadside aesthetic strategies. The research sought to understand if the cultivation of a biofuel feedstock within the Arkansas State Highway Transportation Department’s (AHTD) managed and marginalized lands is feasible by identifying potential land areas and crops. To determine potential plots the parcel data was downloaded from Arkansas’s GIS office. ArcGIS was used to query the data for all variations of the names of property owned by AHTD and a KML file was created that identifies the queried parcel data in Google Earth. Furthermore, biofuel refineries in the state were identified to optimize the harvest to transesterification process. Agricultural data was collected from federal and state agencies and universities to assess various oil seed crops suitable for conversion and suited to grow in Arkansas’s climate and ROW conditions. Research data determined that soybean is the best adapted biofuel feedstock for Arkansas with camelina and canola showing possibilities as well. Agriculture is Arkansas’s largest industry and soybean is grown in over half of the state’s counties. Successful cultivation of a feedstock in the aforementioned areas could potentially offer significant employment opportunity for which the skilled farmers already exist. Based on compiled data, AHTD manages 21,489 acres of marginalized land. The result of the feasibility assessment offer suggestions and guidance should AHTD decide to further investigate this type of initiative.

Keywords: Arkansas highways, biofuels, renewable energy initiative, marginalized lands

Procedia PDF Downloads 329