Search results for: R statistical software

Authors: Diego Adrian Cardenas Jorge, Gerardo Mirando Guisado, Alfredo Barrientos Padilla

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A system based on Affective Computing can detect and interpret human information like voice, facial expressions and body movement to detect emotions and execute a corresponding response. This data is important due to the fact that a person can communicate more effectively with emotions than can be possible with words. This information can be processed through technological components like Facial Recognition, Gait Recognition or Gesture Recognition. As of now, solutions proposed using this technology only consider one component at a given moment. This research investigation proposes two solutions based on Affective Computing taking into account more than one component for emotion detection. The proposals reflect the levels of dependency between hardware devices and software, as well as the interaction process between the system and the user which implies the development of scenarios where both proposals will be put to the test in a live environment. Both solutions are to be developed in code by software engineers to prove the feasibility. To validate the impact on society and business interest, interviews with stakeholders are conducted with an investment mind set where each solution is labeled on a scale of 1 through 5, being one a minimum possible investment and 5 the maximum.

Keywords: affective computing, emotions, emotion detection, face recognition, gait recognition

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Authors: Adel M. Qatawneh

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This paper aimed to determine the importance of knowledge innovation for external audit on anti-corruption in the entire Jordanian bank companies are listed in Amman Stock Exchange (ASE). The study importance arises from the need to recognize the Knowledge innovation for external audit and anti-corruption as the development in the world of business, the variables that will be affected by external audit innovation are: reliability of financial data, relevantly of financial data, consistency of the financial data, Full disclosure of financial data and protecting the rights of investors to achieve the objectives of the study a questionnaire was designed and distributed to the society of the Jordanian bank are listed in Amman Stock Exchange. The data analysis found out that the banks in Jordan have a positive importance of Knowledge innovation for external audit on anti-corruption. They agree on the benefit of Knowledge innovation for external audit on anti-corruption. The statistical analysis showed that Knowledge innovation for external audit had a positive impact on the anti-corruption and that external audit has a significantly statistical relationship with anti-corruption, reliability of financial data, consistency of the financial data, a full disclosure of financial data and protecting the rights of investors.

Keywords: knowledge innovation, external audit, anti-corruption, Amman Stock Exchange

Procedia PDF Downloads 465

Authors: Vergeena Varghese, G. Gajalakshmi, Jayarajini Vasanth

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The present study deals with the indication of prevalence of dry eye and evaluates environmental risk factors attributed to dry eye in different occupational sectors. 240 subjects above 20 years and below 45 years of age were screened for dry eye. Mcmonnies dry eye questionnaire based history and Schirmer’s test were used to diagnose dry eye. For Schirmer’s test Whatman strip and paracaine drop used as an anesthetic. Subject’s demographics include age, sex, smoking, alcoholism, occupation history and working environment. Out of a total of 240 subjects, 52 subjects were positive for dry eye syndrome (21.7%). The highest prevalence of dry eye syndrome in software sector was 14subjects (26.9%) out of a total of 40 subjects. In the construction sector, the prevalence of dry eye syndrome had 12 subjects (23.1%) out of 40 subjects and 9 subjects (17.3%) out of 40 subjects in agriculture sector. 7 subjects (13.5%) who had dry eye out of 40 subjects in the transport sector and in industrial 6 subjects (11.5%). In a normal sector, this was taken as control group had dry eye in 4 subjects (7.7%) out of 40 subjects. We also found the prevalence of dry eye in OS was higher than OD. Dry eye is a most common ocular condition. The highest prevalence of dry eye syndrome in software sector was 14 members than other sector. There was a significant correlation between environmental and occupational factors to cause dry eye. Excessive exposure to sunlight, wind, high temperature, and air pollution, electromagnetic radiation are the factors affect the tear film and ocular surface causing the dry eye syndrome.

Keywords: DES – dry eye syndrome, Mcmonnies dry eye questionnaire, schirmer’s test, whatman vstrip

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Authors: Samaneh Abolli, Kamyar Yaghmaeian, Ali Arab Aradani, Mahmood Alimohammadi

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The main route of fluoride uptake is drinking water. Fluoride absorption in the acceptable range (0.5-1.5 mg L-¹) is suitable for the body, but it's too much consumption can have irreversible health effects. To compare fluoride concentration with the WHO guidelines, 112 water samples were taken from groundwater aquifers in 22 villages of Garmsar County, the central part of Iran, during 2018 to 2019.Fluoride concentration was measured by the SPANDS method, and its non-carcinogenic impacts were calculated using EDI and HQ. The statistical population was divided into four categories of infant, children, teenagers, and adults. Linear regression and Spearman rank correlation coefficient tests were used to investigate the relationships between the well's depth and fluoride concentration in the water samples. The annual mean concentrations of fluoride in 2018 and2019 were 0.75 and 0.64 mg -¹ and, the fluoride mean concentration in the samples classifying the cold and hot seasons of the studied years was 0.709 and 0.689 mg L-¹, respectively. The amount of fluoride in 27% of the samples in both years was less than the acceptable minimum (0.5 mg L-¹). Also, 11% of the samples in2018 (6 samples) had fluoride levels higher than 1.5 mg L-¹. The HQ showed that the children were vulnerable; teenagers and adults were in the next ranks, respectively. Statistical tests showed a reverse and significant correlation (R2 = 0.02, < 0.0001) between well depth and fluoride content. The border between the usefulness/harmfulness of fluoride is very narrow and requires extensive studies.

Keywords: fluoride, groundwater, health risk assessment, hazard quotient, Garmsar

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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Over the last several years, concern has developed over how to minimize the spread of HIV/AIDS epidemic in many countries. AIDS epidemic has tremendously stimulated the development of mathematical models of infectious diseases. The transmission dynamics of HIV infection that eventually developed AIDS has taken a pivotal role of much on building mathematical models. From the initial HIV and AIDS models introduced in the 80s, various improvements have been taken into account as how to model HIV/AIDS frameworks. In this paper, we present the impact of migration on the spread of HIV/AIDS. Epidemic model is considered by a system of nonlinear differential equations to supplement the statistical method approach. The model is calibrated using HIV incidence data from Malaysia between 1986 and 2011. Bayesian inference based on Markov Chain Monte Carlo is used to validate the model by fitting it to the data and to estimate the unknown parameters for the model. The results suggest that the migrants stay for a long time contributes to the spread of HIV. The model also indicates that susceptible individual becomes infected and moved to HIV compartment at a rate that is more significant than the removal rate from HIV compartment to AIDS compartment. The disease-free steady state is unstable since the basic reproduction number is 1.627309. This is a big concern and not a good indicator from the public heath point of view since the aim is to stabilize the epidemic at the disease equilibrium.

Keywords: epidemic model, HIV, MCMC, parameter estimation

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Authors: Ghazi Faisal Najmuldeen, Wahida Amat-Fadzil, Zulkafli Hassan, Jinan B. Al-Dabbagh

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The objective of this study was to evaluate the optimum fabrication process variables to produce particleboards from oil palm fronds (OPF) particles and empty fruit bunch fiber (EFB). Response surface methodology was employed to analyse the effect of hot press temperature (150–190°C); press time (3–7 minutes) and EFB blending ratio (0–40%) on particleboards modulus of rupture, modulus of elasticity, internal bonding, water absorption and thickness swelling. A Box-Behnken experimental design was carried out to develop statistical models used for the optimisation of the fabrication process variables. All factors were found to be statistically significant on particleboards properties. The statistical analysis indicated that all models showed significant fit with experimental results. The optimum particleboards properties were obtained at optimal fabrication process condition; press temperature; 186°C, press time; 5.7 min and EFB / OPF ratio; 30.4%. Incorporating of oil palm frond and empty fruit bunch to produce particleboards has improved the particleboards properties. The OPF–EFB particleboards fabricated at optimized conditions have satisfied the ANSI A208.1–1999 specification for general purpose particleboards.

Keywords: empty fruit bunch fiber, oil palm fronds, particleboards, response surface methodology

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Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

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Model transformation, as a pivotal aspect of Model-driven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: cross-domain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons

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Authors: Waleed Al-Nuaimy, Luke Anastassiou, Manjinder Kainth

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As the process of teaching has evolved with the advent of new technologies over the ages, so has the process of learning. Educators have perpetually found themselves on the lookout for new technology-enhanced methods of teaching in order to increase learning efficiency and decrease ever expanding workloads. Shortly after the invention of the internet, web-based learning started to pick up in the late 1990s and educators quickly found that the process of providing learning material and marking assignments could change thanks to the connectivity offered by the internet. With the creation of early web-based virtual learning environments (VLEs) such as SPIDER and Blackboard, it soon became apparent that VLEs resulted in higher reported computer self-efficacy among students, but at the cost of students being less satisfied with the learning process . It may be argued that the impersonal nature of VLEs, and their limited functionality may have been the leading factors contributing to this reported dissatisfaction. To this day, often faced with the prospects of assigning colossal engineering cohorts their homework and assessments, educators may frequently choose optimally curated assessment formats, such as multiple-choice quizzes and numerical answer input boxes, so that automated grading software embedded in the VLEs can save time and mark student submissions instantaneously. A crucial skill that is meant to be learnt during most science and engineering undergraduate degrees is gaining the confidence in using, solving and deriving mathematical equations. Equations underpin a significant portion of the topics taught in many STEM subjects, and it is in homework assignments and assessments that this understanding is tested. It is not hard to see that this can become challenging if the majority of assignment formats students are engaging with are multiple-choice questions, and educators end up with a reduced perspective of their students’ ability to manipulate equations. Artificial intelligence (AI) has in recent times been shown to be an important consideration for many technologies. In our paper, we explore the use of new AI based software designed to work in conjunction with current VLEs. Using our experience with the software, we discuss its potential to solve a selection of problems ranging from impersonality to the reduction of educator workloads by speeding up the marking process. We examine the software’s potential to increase learning efficiency through its features which claim to allow more customized and higher-quality feedback. We investigate the usability of features allowing students to input equation derivations in a range of different forms, and discuss relevant observations associated with these input methods. Furthermore, we make ethical considerations and discuss potential drawbacks to the software, including the extent to which optical character recognition (OCR) could play a part in the perpetuation of errors and create disagreements between student intent and their submitted assignment answers. It is the intention of the authors that this study will be useful as an example of the implementation of AI in a practical assessment scenario insofar as serving as a springboard for further considerations and studies that utilise AI in the setting and marking of science and engineering assignments.

Keywords: engineering education, assessment, artificial intelligence, optical character recognition (OCR)

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Authors: Mohammed H. Karim, Bestoon M. Faraj

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Introduction: This study aimed to compare the effectiveness of a Dynamic Navigation System (DNS) and a three-dimensional microscope in retrieving broken rotary NiTi files when using trepan burs and the extractor system. Materials and Methods: Thirty maxillary first bicuspids with sixty separate roots were split into two comparable groups based on a comprehensive Cone-Beam Computed Tomography (CBCT) analysis of the root length and curvature. After standardized access opening, glide paths, and patency attainment with the K file (sizes 10 and 15), the teeth were arranged on 3D models (three per quadrant, six per model). Subsequently, controlled-memory heat-treated NiTi rotary files (#25/0.04) were notched 4 mm from the tips and fractured at the apical third of the roots. The C-FR1 Endo file removal system was employed under both guidance to retrieve the fragments, and the success rate, canal aberration, treatment time and volumetric changes were measured. The statistical analysis was performed using IBM SPSS software at a significance level of 0.05. Results: The microscope-guided group had a higher success rate than the DNS guidance, but the difference was insignificant (p > 0.05). In addition, the microscope-guided drills resulted in a substantially lower proportion of canal aberration, required less time to retrieve the fragments and caused minimal change in the root canal volume (p < 0.05). Conclusion: Although dynamically guided trephining with the extractor can retrieve separated instruments, it is inferior to three-dimensional microscope guidance regarding treatment time, procedural errors, and volume change.

Keywords: separated instruments retrieval, dynamic navigation system, 3D video microscope, trephine burs, extractor

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Authors: Patricia Chinyere Oranefo

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This study examined the effect of sustainability accounting disclosure on financial performance of listed Brewery firms in Nigeria. The dearth of empirical evidence and literature on “governance disclosure” as one of the explanatory variables of sustainability accounting reporting were the major motivation for this study. The main objective was to ascertain the effect of sustainability accounting disclosure on financial performance of listed Brewery firms in Nigeria. An ex–post facto research design approach was adopted for the study. The population of this study comprises of five (5) Brewery firms quoted on the floor of the Nigeria exchange group (NSX) and the sample size of four (4) listed firms was drawn using purposive sampling method. Secondary data were carefully sourced from the financial statement/annual reports and sustainability reports from 2012 to 2021 of the Brewery firms quoted on the Nigeria exchange group (NSX). Panel regression analysis by aid of E-views 10.0 software was used to test for statistical significance of the effect of sustainability accounting disclosure on financial performance of listed Brewery firms in Nigeria. The results showed that economic sustainability disclosure indexes do not significantly affect return on asset of listed Brewery firms in Nigeria. The findings further revealed that environmental sustainability disclosure indexes do not significantly affect return on equity of listed Brewery firms in Nigeria. More so, results showed that Social Sustainability disclosure indexes significantly affect Net Profit Margin of listed Brewery firms in Nigeria. Finally, the result established also that governance sustainability disclosure indexes do not significantly affect Earnings per share of listed Brewery firms in Nigeria. Consequent upon the findings, this study recommended among others; that managers of Brewers in Nigeria should improve and sustain full disclosure practices on economic, environmental, social and governance disclosures following the guidelines of the Global Reporting Index (GRI) as they are capable of exerting significant effect on financial performance of firms in Nigeria.

Keywords: sustainability, accounting, disclosure, financial performance

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Authors: Victor Pesco Kassa

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This research deals with the assessment of the contribution of GIS Technology in NRW. This research was conducted at Dar, Kawe Mzimuni Street. The data collection was obtained from existing source which is DAWASA HQ. The interpretation of the data was processed by using ArcGIS software. The data collected from the existing source reveals a good coverage of DAWASA’s water network at Mzimuni Street. Most of residents are connected to the DAWASA’s customer service. Also the collected data revealed that by using GIS DAWASA’s customer Geodatabase has been improved. Through GIS we can prepare customer location map purposely for site surveying also this map will be able to show different type of customer that are connected to DAWASA’s water service. This is a perfect contribution of the GIS Technology to address and manage the problem of NRW in DAWASA. Finally, the study recommends that the same study should be conducted in other DAWASA’s zones such as Temeke, Boko and Bagamoyo not only at Kawe Mzimuni Street. Through this study it is observed that ArcGIS software can offer powerful tools for managing and processing information geographically and in water and sanitation authorities such as DAWASA.

Keywords: DAWASA, NRW, Esri, EURA, ArcGIS

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Authors: G. H. B. Dilhari, A. A. D. T. Saparamadu

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Sri Lanka is one of the prominent countries for the coir production. The coir is one of the by-products of the coconut and the coir industry is considered to be one of the traditional industries in Sri Lanka. Because of the inherent nature of the coir industry, labourers play a significant role in the coir production process. The study has analyzed the determinants of the income of the household level coir yarn labourers. The study was conducted in the Kumarakanda Grama Niladhari division. Simple random sampling was used to generate a sample of 100 household level coir yarn labourers and structured questionnaire, personal interviews, and discussion were performed to gather the required data. The obtained data were statistically analyzed by using Statistical Package for Social Science (SPSS) software. Mann-Whitney U and Kruskal-Wallis test were performed for mean comparison. The findings revealed that the household level coir yarn industry is dominated by the female workers and it was identified that fewer numbers of workers have engaged in this industry as the main occupation. In addition to that, elderly participation in the industry is higher than the younger participation and most of them have engaged in the industry as a source of extra income. Level of education, the methods of engagement, satisfaction, engagement in the industry by the next generation, support from the government, method of government support, working hours per day, employed as a main job, number of completed units per day, suffering from job related diseases and type of the diseases were related with income level of household level coir yarn laboures. The recommendations as to flourish in future includes, technological transformation for coir yarn production, strengthening the raw material base and regulating the raw material supply, introduction of new technologies, markets and training programmes, the establishment of the labourers’ association, the initiation of micro credit schemes and better consideration about the job oriented diseases.

Keywords: coir yarn, determinants, income, Sri Lanka

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Authors: Kathaleeya Chanda, Panupong Chanplin, Suppara Charoenpoom

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This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

Keywords: teaching learning model, digital media, creative instruction model, Bo Kluea school

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Authors: Walter M. Millanzi, Stephen M. Kibusi

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Background: Currently, there has been a progressive shortage not only to the number but also the quality of medical practitioners for the most of nursing. Despite that, those who are present exhibit unethical and illegal practices, under standard care and malpractices. The concern is raised in the ways they are prepared, or there might be something missing in nursing curricula or how it is delivered. There is a need for transforming or testing new teaching modalities to enhance competent health workforces. Objective: to investigate the Effect of Facilitation in a Problem-based Environment (FPBE) on metacognition, self-directed learning and learning motivation to undergraduate nurse student in Tanzanian higher learning institutions. Methods: quasi-experimental study (quantitative research approach). A purposive sampling technique was employed to select institutions and achieving a sample size of 401 participants (interventional = 134 and control = 267). Self-administered semi-structured questionnaire; was the main data collection methods and the Statistical Package for Service Solution (v. 20) software program was used for data entry, data analysis, and presentations. Results: The pre-post test results between groups indicated noticeably significant change on metacognition in an intervention (M = 1.52, SD = 0.501) against the control (M = 1.40, SD = 0.490), t (399) = 2.398, p < 0.05). SDL in an intervention (M = 1.52, SD = 0.501) against the control (M = 1.40, SD = 0.490), t (399) = 2.398, p < 0.05. Motivation to learn in an intervention (M = 62.67, SD = 14.14) and the control (n = 267, M = 57.75), t (399) = 2.907, p < 0.01). A FPBE teaching pedagogy, was observed to be effective on the metacognition (AOR = 1.603, p < 0.05), SDL (OR = 1.729, p < 0.05) and Intrinsic motivation in learning (AOR = 1.720, p < 0.05) against conventional teaching pedagogy. Needless, was less likely to enhance Extrinsic motivation (AOR = 0.676, p > 0.05) and Amotivation (AOR = 0.538, p > 0.05). Conclusion and recommendation: FPBE teaching pedagogy, can improve student’s metacognition, self-directed learning and intrinsic motivation to learn among nurse students. Nursing curricula developers should incorporate it to produce 21st century competent and qualified nurses.

Keywords: facilitation, metacognition, motivation, self-directed

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Authors: Pedram Saadati, Zahra Nazari

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In the last decade, the role and importance of knowledge-based technological businesses in the insurance industry has greatly increased, and due to the weakness of previous studies in Iran, the current research deals with the design of the InsurTech empowerment model. In order to obtain the conceptual model of the research, a hybrid framework has been used. The statistical population of the research in the qualitative part were experts, and in the quantitative part, the InsurTech activists. The tools of data collection in the qualitative part were in-depth and semi-structured interviews and structured self-interaction matrix, and in the quantitative part, a researcher-made questionnaire. In the qualitative part, 55 indicators, 20 components and 8 concepts (dimensions) were obtained by the content analysis method, then the relationships of the concepts with each other and the levels of the components were investigated. In the quantitative part, the information was analyzed using the descriptive analytical method in the way of path analysis and confirmatory factor analysis. The proposed model consists of eight dimensions of supporter capability, supervisor of insurance innovation ecosystem, managerial, financial, technological, marketing, opportunity identification, innovative InsurTech capabilities. The results of statistical tests in identifying the relationships of the concepts with each other have been examined in detail and suggestions have been presented in the conclusion section.

Keywords: insurTech, knowledge-base, empowerment model, factor analysis, insurance

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Authors: Vikas Kumar, V. H. Saran, Arpit Mathur, Avik Kathuria

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The evaluation of biodynamic responses of the human body to whole body vibration exposure is necessary to quantify the exposure effects. A force plate model has been designed with the help of CAD software, which was investigated by performing the modal, stress and strain analysis using finite element approach in the software. The results of the modal, stress and strain analysis were under the limits for measurements of biodynamic responses to whole body vibration. The physical model of the force plate was manufactured and fixed to the vibration simulator and further used in the experimentation for the evaluation of apparent mass responses of the ten recruited subjects standing in an erect posture exposed to vertical whole body vibration. The platform was excited with sinusoidal vibration at vibration magnitude: 1.0 and 1.5 m/s2 rms at different frequency of 2, 3, 4, 5, 6, 8, 10, 12.5, 16 and 20 Hz. The results of magnitude of normalised apparent mass have shown the trend observed in the many past studies. The peak in the normalised apparent mass has been observed at 4 & 5 Hz frequency of vertical whole body vibration. The nonlinearity with respect to vibration magnitude has been also observed in the normalised apparent mass responses.

Keywords: whole body vibration, apparent mass, modeling, force plate

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Authors: Rohin Rameswarapu, Sameer Valsangkar

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Background: Globally, musculoskeletal disorders are the largest single cause of work-related illnesses accounting for over 33% of all newly reported occupational illnesses. Risk factors for MSD need to be delineated to suggest means for amelioration. Material and methods: In this current cross-sectional study, the prevalence of MSDs among workers in an electrical company assembly line, the socio-demographic and job characteristics associated with MSD were obtained through a semi-structured questionnaire. A quantitative assessment of the physical risk factors through the Rapid Upper Limb Assessment (RULA) tool, and measurement of psychosocial risk factors through a Likert scale was obtained. Statistical analysis was conducted using Epi-info software and descriptive and inferential statistics including chi-square and unpaired t test were obtained. Results: A total of 263 workers consented and participated in the study. Among these workers, 200 (76%) suffered from MSD. Most of the workers were aged between 18–27 years and majority of the workers were women with 198 (75.2%) of the 263 workers being women. A chi square test was significant for association between male gender and MSD with a P value of 0.007. Among the MSD positive group, 4 (2%) had a grand score of 5, 10 (5%) had a grand score of 6 and 186 (93%) had a grand score of 7 on RULA. There were significant differences between the non-MSD and MSD group on five out of the seven psychosocial domains, namely job demand, job monotony, co-worker support, decision control and family and environment domains. Discussion: The current cross-sectional study demonstrates a high prevalence of MSD among assembly line works with inherent physical and psychosocial risk factors and recommends that not only physical risk factors, addressing psychosocial risk factors through proper ergonomic means is also essential to the well-being of the employee.

Keywords: musculoskeletal disorders, India, occupational health, Rapid Upper Limb Assessment (RULA)

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Authors: Cansu Arslan Turan, Tuba Cimilli Ozturk, Ebru Unal Akoglu, Kemal Aygun, Ecem Deniz Kırkpantur, Ozge Ecmel Onur

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Although the mechanism of action is not well known, Intravenous Lipid Emulsion (ILE) has been shown to be effective in the treatment of lipophilic drug intoxications. It is thought that ILE probably separate the lipophilic drugs from target tissue by creating a lipid-rich compartment in the plasma. The second theory is that ILE provides energy to myocardium with high dose free fatty acids activating the voltage gated calcium channels in the myocytes. In this study, the effects of ILE treatment on digoxin overdose which are frequently observed in emergency departments was searched in an animal model in terms of cardiac side effects and survival. The study was carried out at Yeditepe University, Faculty of Medicine-Experimental Animals Research Center Labs in December 2015. 40 Sprague-Dawley rats weighing 300-400 g were divided into 5 groups randomly. As the pre-treatment, the first group received saline, the second group received lipid, the third group received DigiFab, and the fourth group received DigiFab and lipid. Following that, digoxin was infused to all groups until death except the control group. First arrhythmia and cardiac arrest occurrence times were recorded. As no medication causing arrhythmia was infused, Group 5 was excluded from the statistical analysis performed for the comparisons of first arrhythmia and death time. According to the results although there was no significant difference in the statistical analysis comparing the four groups, as the rats, only exposed to digoxin intoxication were compared with the rats pre-treated with ILE in terms of first arrhythmia time and cardiac arrest occurrence times, significant difference was observed between the groups. According to our results, using DigiFab treatment, intralipid treatment, intralipid and DigiFab treatment for the rats exposed to digoxin intoxication makes no significant difference in terms of the first arrhythmia and death occurrence time. However, it is not possible to say that at the doses we use in the study, ILE treatment might be successful at least as a known antidote. The fact that the statistical significance between the two groups is not observed in the inter-comparisons of all the groups, the study should be repeated in the larger groups.

Keywords: arrhytmia, cardiac arrest, DigiFab, digoxin intoxication

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar

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Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.

Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices

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Authors: Eric Wilson Santos Cabral, Marta Monteiro Da Costa Cruz, Fabio Luis Maciel Machado, Henrique Andrade, Rodrigo Pirola Pestana, Vivian Andrea Parreira

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The large variation in the price of diesel in Brazil directly affects the variable cost of companies operating in the transportation sector. In rail transport, the great challenge is to overcome the annual budget, cargo and ore transported with cost reduction in relation to previous years, becoming more efficient every year. Some effective measures are necessary to achieve the reduction of the liter ratio consumed by KTKB (Gross Ton per Kilometer multiplied by thousand). This acronym represents the indicator of energy efficiency of some railroads in the world. This study is divided into two parts: the first, to identify using statistical tools, part of the controlled variables in the railways, which have a correlation with the energy efficiency indicator, seeking to aid decision-making. The second, with the use of the train dynamics simulator, within scenarios defined in the operational reality of a railroad, seeks to optimize the train formations and the train stop model for the change of train drivers. With the completion of the study, companies in the rail sector are expected to be able to reduce some of their transportation costs.

Keywords: railway transport, railway simulation, energy efficiency, fuel consumption

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Authors: Mehmet Erdi Korkmaz, Mustafa Günay

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Nowadays, grinding is frequently replaced with hard turning for reducing set up time and higher accuracy. This paper focused on mathematical modeling of average surface roughness (Ra) in hard turning of AISI L2 grade (DIN 1.2210) cold work tool steel with ceramic tools. The steel was hardened to 60±1 HRC after the heat treatment process. Cutting speed, feed rate, depth of cut and tool nose radius was chosen as the cutting conditions. The uncoated ceramic cutting tools were used in the machining experiments. The machining experiments were performed according to Taguchi L27 orthogonal array on CNC lathe. Ra values were calculated by averaging three roughness values obtained from three different points of machined surface. The influences of cutting conditions on surface roughness were evaluated as statistical and experimental. The analysis of variance (ANOVA) with 95% confidence level was applied for statistical analysis of experimental results. Finally, mathematical models were developed using the artificial neural networks (ANN). ANOVA results show that feed rate is the dominant factor affecting surface roughness, followed by tool nose radius and cutting speed.

Keywords: ANN, hard turning, DIN 1.2210, surface roughness, Taguchi method

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

Procedia PDF Downloads 276

Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

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With the development of virtualization technologies, a new type of service named cloud computing service is produced. Cloud users usually encounter the problem of how to use the virtualized platform easily over the web without requiring the plug-in or installation of special software. The object of this paper is to develop a system and a method enabling process interfacing within an automation scenario for accessing remote application by using the web browser. To meet this challenge, we have devised a web-based interface that system has allowed to shift the GUI application from the traditional local environment to the cloud platform, which is stored on the remote virtual machine. We designed the sketch of web interface following the cloud virtualization concept that sought to enable communication and collaboration among users. We describe the design requirements of remote application technology and present implementation details of the web application and its associated components. We conclude that this effort has the potential to provide an elastic and resilience environment for several application services. Users no longer have to burden the system maintenances and reduce the overall cost of software licenses and hardware. Moreover, this remote application service represents the next step to the mobile workplace, and it lets user to use the remote application virtually from anywhere.

Keywords: virtualization technology, virtualized platform, web interface, remote application

Procedia PDF Downloads 288

Authors: Fina O. Faithpraise, Effiong O. Obisung, Azele E. Peter, Chris R. Chatwin

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This study investigates and identifies consumer attitude as a major influence that results in non-technical losses in the Nigerian electricity supply sector. This discovery is revealed by the combination of quantitative and qualitative research to complete a survey. The dataset employed is a simple random sampling of households using electricity (public power supply), and the number of units chosen is based on statistical power analysis. The units were subdivided into two categories (household with and without electrical meters). The hypothesis formulated was tested and analyzed using a chi-square statistical method. The results obtained shows that the critical value for the household with electrical prepared meter (EPM) was (9.488 < 427.4) and those without electrical prepared meter (EPMn) was (9.488 < 436.1) with a p-value of 0.01%. The analysis demonstrated so far established the real-time position, which shows that the wrong attitude towards handling the electricity supplied (not turning off light bulbs and electrical appliances when not in use within the rooms and outdoors within 12 hours of the day) characterized the non-technical losses in the power sector. Therefore the adoption of efficient lighting attitudes in individual households as recommended by the researcher is greatly encouraged. The results from this study should serve as a model for energy efficiency and use for the improvement of electricity consumption as well as a stable economy.

Keywords: attitudinal change, household, non-technical losses, prepared meter

Procedia PDF Downloads 179

Authors: Mehdi Modabberifar, Milad Roodi, Ehsan Souri

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In recent years, honeycomb fiber reinforced plastic (FRP) sandwich panels have been increasingly used in various industries. Low weight, low price, and high mechanical strength are the benefits of these structures. However, their mechanical properties and behavior have not been fully explored. The objective of this study is to conduct a combined numerical-statistical investigation of honeycomb FRP sandwich beams subject to torsion load. In this paper, the effect of geometric parameters of the sandwich panel on the maximum shear strain in both face and core and angle of torsion in a honeycomb FRP sandwich structures in torsion is investigated. The effect of Parameters including core thickness, face skin thickness, cell shape, cell size, and cell thickness on mechanical behavior of the structure were numerically investigated. Main effects of factors were considered in this paper and regression equations were derived. Taguchi method was employed as experimental design and an optimum parameter combination for the maximum structure stiffness has been obtained. The results showed that cell size and face skin thickness have the most significant impacts on torsion angle, maximum shear strain in face and core.

Keywords: finite element, honeycomb FRP sandwich panel, torsion, civil engineering

Procedia PDF Downloads 418

Authors: Radomir Perzina, Jaroslav Ramik

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The Analytic Hierarchy Process is frequently used approach for solving decision making problems. There exists wide range of software programs utilizing that approach. Their main disadvantage is that they are relatively expensive and missing intermediate calculations. This work introduces a Microsoft Excel add-in called DAME – Decision Analysis Module for Excel. Comparing to other computer programs DAME is free, can work with scenarios or multiple decision makers and displays intermediate calculations. Users can structure their decision models into three levels – scenarios/users, criteria and variants. Items on all levels can be evaluated either by weights or pair-wise comparisons. There are provided three different methods for the evaluation of the weights of criteria, the variants as well as the scenarios – Saaty’s Method, Geometric Mean Method and Fuller’s Triangle Method. Multiplicative and additive syntheses are supported. The proposed software package is demonstrated on couple of illustrating examples of real life decision problems.

Keywords: analytic hierarchy process, multi-criteria decision making, pair-wise comparisons, Microsoft Excel, scenarios

Procedia PDF Downloads 452

Authors: M. Bolacalı, Y. Öztürk, O. Yılmaz, M. Küçük, M. A. Karslı

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The aim of the study was to determine various body measurements from the birth to the 30-day age of Boer x Hair goats F1 crossbred kids and pure Hair goat kids raised in Van in Eastern Anatolia region, and reveal factors such as the effects of year, dame body weight, genotype, dame age, birth type and sex on this parameter. 49 kids born in 2012 and 76 kids born in 2014 were utilized in the study. In the statistical analysis of various body measurements data was performed using the General Lineer Model procedure in SPSS software. Duncan's multiple range test was used for multiple comparisons. Boer x Hair goats F1 crossbred kids and pure Hair goat kids from various body measurements cidago height, body length, chest length, chest depth, chest circumference, circumference of leg, cannon bone circumference, chest width were determinated in general respectively 29.90 and 27.88 cm; 29.49 and 27.93 cm; 17.28 and 16.68 cm; 13.34 and 12.82 cm; 31.74 and 29.85 cm; 28.43 and 23.95 cm; 5.41 and 5.15 cm; 8.71 and 7.63 cm at birth, respectively; 35.01 and 32.98 cm; 35.20 and 33.30 cm; 18.82 and 18.17 cm; 15.64 and 14.83 cm; 39.08 and 37.30 cm; 34.29 and 29.25 cm; 5.80 and 5.42 cm; 9.87 and 8.85 cm at 30 days age, respectively. Among factors affecting cidago height in this study, the effect of dame body weight and sex were not significant, but genotype, dame age and birth type were significant (P < 0,05 and P < 0,01) at birth; dame body weight effect of the cidago height was not significant, but the effect of genotype, birth type, of dame age and sex were significant (P < 0.05, P < 0.05 and P<0.001) at 30-day age. The effect of genotype and sex of body length were not significant, but dam age, dame body weight and birth type were significant (P < 0.05, P < 0.05 and P<0.001, respectively) at birth; the effect of sex to body length was not significant, but genotype, dame age, dame body weight and birth type were significant (P < 0.01, P < 0.05, P < 0.05 and P < 0.001, respectively) at 30-day age. While circumference of leg was insignificant the effect of dame age and sex, genotype, dame body weight and type of the birth were significant (P < 0.001, P < 0.05 and P < 0.001) at birth; the circumstance of leg at 30-day age was found to be important the effect of examined other factors except for sex (P < 0.05 and P < 0.001). The obtained results, when considered in terms of a variety of body sizes, from birth to 30-day age growth period, showed that the kids of Boer x Hair Goat F1 hybrids have higher values than the kids of Hair Goats.

Keywords: Boer x hair goat F1 crossbred, hair goat, body measurements, cidago height

Procedia PDF Downloads 349

Authors: Omid Khodabakhshi, Amir Rozdel

Abstract:

The subject of cloud computing security research has allocated a number of challenges and competitions because the data center is comprised of complex private information and are always faced various risks of information disclosure by hacker attacks or internal enemies. Accordingly, the security of virtual machines in the cloud computing infrastructure layer is very important. So far, there are many software solutions to develop security in virtual machines. But using software alone is not enough to solve security problems. The purpose of this article is to examine the challenges and security requirements for accessing and storing data in an insecure cloud environment. In other words, in this article, a structure is proposed for the implementation of highly isolated security-sensitive codes using secure computing hardware in virtual environments. It also allows remote code validation with inputs and outputs. We provide these security features even in situations where the BIOS, the operating system, and even the super-supervisor are infected. To achieve these goals, we will use the hardware support provided by the new Intel and AMD processors, as well as the TPM security chip. In conclusion, the use of these technologies ultimately creates a root of dynamic trust and reduces TCB to security-sensitive codes.

Keywords: code, cloud computing, security, virtual machines

Procedia PDF Downloads 191

Authors: Shazia Anwer Bukhari, Madiha Javeed Ghani, Muhammad Ibrahim Rajoka

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Objective: Biochemical, environmental, physical and genetic factors have a strong effect on the development of coronary disease (CAD). Plasma homocysteine (Hcy) level and DNA damage play a pivotal role in its development and progression. The aim of this study was to investigate the predictive strength of an oxidative stress, clinical biomarkers and total antioxidant status (TAS) in CAD patients to find the correlation of homocysteine, TOS and oxidative DNA damage with other clinical parameters. Methods: Sixty confirmed patients with CAD and 60 healthy individuals as control were included in this study. Different clinical and laboratory parameters were studied in blood samples obtained from patients and control subjects using commercially available biochemical kits and statistical software Results: As compared to healthy individuals, CAD patients had significantly higher concentrations of indices of oxidative stress: homocysteine (P=0.0001), total oxidative stress (TOS) (P=0.0001), serum cholesterol (P=0.04), low density lipoprotein cholesterol (LDL) (P=0.01), high density lipoprotein-cholesterol (HDL) (P=0.0001), and malondialdehyde (MDA) (P=0.001) than those of healthy individuals. Plasma homocysteine level and oxidative DNA damage were positively correlated with cholesterol, triglycerides, systolic blood pressure, urea, total protein and albumin (P values= 0.05). Both Hcy and oxidative DNA damage were negatively correlated with TAS and proteins. Conclusion: Coronary artery disease patients had a significant increase in homocysteine level and DNA damage due to increased oxidative stress. In conclusion, our study shows a significantly increase in lipid peroxidation, TOS, homocysteine and DNA damage in the erythrocytes of patients with CAD. A significant decrease level of HDL-C and TAS was observed only in CAD patients. Therefore these biomarkers may be useful diagnosis of patients with CAD and play an important role in the pathogenesis of CAD.

Keywords: antioxidants, coronary artery disease, DNA damage, homocysteine, oxidative stress, malondialdehyde, 8-Hydroxy-2’deoxyguanosine

Procedia PDF Downloads 485