Search results for: Statistical analysis (RSM)

Authors: Sakda Loetpiparwanich, Preecha Vichitthamaros

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Nowadays, poor data quality is considered one of the majority costs for a data project. The data project with data quality awareness almost as much time to data quality processes while data project without data quality awareness negatively impacts financial resources, efficiency, productivity, and credibility. One of the processes that take a long time is defining the expectations and measurements of data quality because the expectation is different up to the purpose of each data project. Especially, big data project that maybe involves with many datasets and stakeholders, that take a long time to discuss and define quality expectations and measurements. Therefore, this study aimed at developing meaningful indicators to describe overall data quality for each dataset to quick comparison and priority. The objectives of this study were to: (1) Develop a practical data quality indicators and measurements, (2) Develop data quality dimensions based on statistical characteristics and (3) Develop Composite Indicator that can describe overall data quality for each dataset. The sample consisted of more than 500 datasets from public sources obtained by random sampling. After datasets were collected, there are five steps to develop the Dataset Quality Index (SDQI). First, we define standard data quality expectations. Second, we find any indicators that can measure directly to data within datasets. Thirdly, each indicator aggregates to dimension using factor analysis. Next, the indicators and dimensions were weighted by an effort for data preparing process and usability. Finally, the dimensions aggregate to Composite Indicator. The results of these analyses showed that: (1) The developed useful indicators and measurements contained ten indicators. (2) the developed data quality dimension based on statistical characteristics, we found that ten indicators can be reduced to 4 dimensions. (3) The developed Composite Indicator, we found that the SDQI can describe overall datasets quality of each dataset and can separate into 3 Level as Good Quality, Acceptable Quality, and Poor Quality. The conclusion, the SDQI provide an overall description of data quality within datasets and meaningful composition. We can use SQDI to assess for all data in the data project, effort estimation, and priority. The SDQI also work well with Agile Method by using SDQI to assessment in the first sprint. After passing the initial evaluation, we can add more specific data quality indicators into the next sprint.

Keywords: data quality, dataset quality, data quality management, composite indicator, factor analysis, principal component analysis

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Authors: Ghaleb Y. Abbasi, Israa Abu Rumman

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This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.

Keywords: ARIMA models, sales demand forecasting, time series, R code

Procedia PDF Downloads 358

Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

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Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

Procedia PDF Downloads 182

Authors: K. Y. S. Putri, Heri Fathurahman, Yuki Surisita, Widi Sagita, Kiki Dwi Arviani

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Society needs the assistance of academics in understanding and being skilled in health communication literacy. Information technology runs very fast while health communication literacy skills in getting health communication information during the pandemic are not as fast as the development of information technology. The research question is whether there is an influence of health communication on information technology in health information during the pandemic in Indonesia. The purpose of the study is to find out the influence of health communication on information technology in health information during the pandemic in Indonesia. The concepts of health communication literacy and information technology are used this study. Previous research is in support of this study. Quantitative research methods by disseminating questionnaires in this study. The validity and reliability test of this study is positive, so it can proceed to the next statistical analysis. Descriptive results of variable health communication literacy are of positive value in all dimensions. All dimensions of information technology are of positive value. Statistical tests of the influence of health communication literacy on information technology are of great value. Discussion of both variables in the influence of health communication literacy and high-value information technology because health communication literacy has a high effect in information technology. Respondents to this study have high information technology skills. So that health communication literacy in obtaining health information during the 2019-2022 pandemic is needed. Research advice is that academics are still very much needed by the community in the development of society during the pandemic.

Keywords: health information, health information needs, literacy health communication, information technology

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Authors: Oluwafemi Samuel Oyamakin

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The forest in Nigeria is currently estimated to extend to around 9.6 million hectares, but used to expand over central and southern Nigeria decades ago. The forest estate is shrinking due to long-term human exploitation for agricultural development, fuel wood demand, uncontrolled forest harvesting and urbanization, amongst other factors, compounded by population growth in rural areas. Nigeria has lost more than 50% of its forest cover since 1990 and currently less than 10% of the country is forested. The current deforestation rate is estimated at 3.7%, which is one of the highest in the world. Reducing Emissions from Deforestation and forest Degradation plus conservation, sustainable management of forests and enhancement of forest carbon stocks constituted what is referred to as REDD+. This study evaluated some of the existing way of computing carbon stocks using eight indigenous tree species like Mansonia, Shorea, Bombax, Terminalia superba, Khaya grandifolia, Khaya senegalenses, Pines and Gmelina arborea. While these components are the essential elements of REDD+ programme, they can be brought under a broader framework of systems analysis designed to arrive at optimal solutions for future predictions through statistical distribution pattern of carbon sequestrated by various species of tree. Available data on height and diameter of trees in Ibadan were studied and their respective potentials of carbon sequestration level were assessed and subjected to tests so as to determine the best statistical distribution that would describe the carbon sequestration pattern of trees. The result of this study suggests a reasonable statistical distribution for carbons sequestered in simulation studies and hence, allow planners and government in determining resources forecast for sustainable development especially where experiments with real-life systems are infeasible. Sustainable management of forest can then be achieved by projecting future condition of forests under different management regimes thereby supporting conservation and REDD+ programmes in Nigeria.

Keywords: REDD+, carbon, climate change, height and diameter

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Authors: Ana Staneva, Vessela Stoimenova

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A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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Authors: Jilu David

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Background: Schizophrenia is one of the most misunderstood mental illnesses across the globe. Lack of understanding about mental illnesses often delay treatment, severely affects the functionality of the person, and causes distress to the family. The study, Video-based Psychoeducation for Caregivers of Persons with Schizophrenia, consisted of developing a psychoeducational video about Schizophrenia, its symptoms, causes, treatment, and the importance of family support. Methodology: A quasi-experimental pre-post design was used to understand the feasibility of the study. Qualitative analysis strengthened the feasibility outcomes. Knowledge About Schizophrenia Interview was used to assess the level of knowledge of 10 participants, before and after the screening of the video. Results: Themes of usefulness, length, content, educational component, format of the intervention, and language emerged in the qualitative analysis. There was a statistically significant difference in the knowledge level of participants before and after the video screening. Conclusion: The statistical and qualitative analysis revealed that the video-based psychoeducation program was feasible and that it facilitated a general improvement in knowledge of the participants.

Keywords: Schizophrenia, mental illness, psychoeducation, video-based psychoeducation, family support

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Authors: Danish Farooq, Janos Juhasz

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Car-motorcycle accidents have been observed higher in recent years, which caused mainly riders’ fatalities and serious injuries. In-depth crash investigation methods aim to investigate the main factors which are likely involved in fatal road accidents and injury outcomes. The main objective of this study is to investigate the involved factors in car-motorcycle accidents in Budapest city. The procedure included statistical analysis and data sampling to identify car-motorcycle accidents by dominant accident types based on collision configurations. The police report was used as a data source for specified accidents, and simulation models were plotted according to scale (M 1:200). Car-motorcycle accidents were simulated in Virtual Crash software for 5 seconds before the collision. The simulation results showed that the main involved factors to car-motorcycle accidents were human behavior and view obstructions. The comprehensive, in-depth analysis also found that most of the car drivers and riders were unable to perform collision avoidance manoeuvres before the collision. This study can help the traffic safety authorities to focus on simulated involved factors to solve road safety issues in car-motorcycle accidents. The study also proposes safety measures to improve safe movements among road users.

Keywords: car motorcycle accidents, in-depth analysis, microscopic simulation, safety measures

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

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Authors: Siavash Mirahmadizoghi, Steven Bell, David Simpson

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In this work a new independent component analysis (ICA) based method for noise reduction in evoked potentials is evaluated on for auditory late responses (ALR) captured with a 63-channel electroencephalogram (EEG) from 10 normal-hearing subjects. The performance of the new method is compared with a single channel alternative in terms of signal to noise ratio (SNR), the number of channels with an SNR above an empirically derived statistical critical value and an estimate of the effect of attention on the major components in the ALR waveform. The results show that the multichannel signal processing method can significantly enhance the quality of the ALR signal and also detect the effect of the attention on the ALR better than the single channel alternative.

Keywords: auditory late response (ALR), attention, EEG, independent component analysis (ICA), multichannel signal processing

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Authors: Gizem Akcan, Erdinc Ozturk

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The purpose of the study was to determine some psychosocial variables that predict dissociation in university students. These psychosocial variables were perceived childhood trauma, alexithymia, and gender. 150 (75 males, 75 females) university students (bachelor, master and postgraduate) were enrolled in this study. They were chosen from universities in Istanbul at the education year of 2016-2017. Dissociative Experiences Scale (DES), Childhood Trauma Questionnaire (CTQ) and Toronto Alexithymia Scale were used to assess related variables. Demographic Information Form was given to students in order to have their demographic information. Frequency Distribution, Linear Regression Analysis, and t-test analysis were used for statistical analysis. Childhood trauma and alexithymia were found to have predictive value on dissociation among university students. However, physical abuse, physical neglect and emotional neglect sub dimensions of childhood trauma and externally-oriented thinking sub dimension of alexithymia did not have predictive value on dissociation. Moreover, there was no significant difference between males and females in terms of dissociation scores of participants.

Keywords: childhood trauma, dissociation, alexithymia, gender

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Authors: Sauradipta Ganguly, Akhato Sumi, Sanjeet Kumar Hom, Ajan T. Lotha

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Populus deltoides is a hardwood used predominantly for the manufacturing of plywood, matchsticks, and paper in India and hence has a higher economical significance. Wood-decaying fungi cause serious damage to Populus deltoides products, as the wood itself is perishable and vulnerable to decaying agents, decreasing their aesthetical value which in return results in significant monetary loss for the wood industries concerned. The aim of the study was to determine the antifungal activity of Cedrus deodara oil against three primary wood-decaying fungi namely white-rot fungi (Trametes versicolor), brown-rot fungi (Oligoporus placentus) and soft-rot fungi (Xylaria acuminata) on Populus deltoides samples under optimum laboratory conditions. The susceptibility of Populus deltoides samples on the fungal attack and the ability of deodar oil to control colonization of the wood rotting fungi on the samples were assessed. Three concentrations of deodar oil were considered for the study as treating solutions, i.e., 4%, 5%, and 6%. The Populus deltoides samples were treated with treating solutions, and the ability of the same to prevent a fungal attack on the samples were assessed using accelerated test in the laboratory at Biochemical Oxygen Demand incubator at temperature (25 ± 2°C) and relative humidity 70 ± 4%. Efficacy test and statistical analysis of deodar oil against Trametes versicolor, Oligoporus placentus, and Xylariaacuminataon P. deltoides samples exhibited light, minor and negligible mycelia growth at 4 %, 5% and 6% concentrations of deodar oil, respectively. Whereas, moderate to heavy attack was observed on the surface of the control samples. Statistical analysis further established that the treatments were statistically significant and had significantly inhibited fungal growth of all the three fungus spp by almost 3 to 5 times.

Keywords: populus deltoides, Trametes versicolor, Oligoporus placentus, Xylaria acuminata, Deodar oil, treatment

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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: Taner Ersoz, Filiz Ersoz

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This study was designed enable application of multivariate technique in the interpretation of categorical data for measuring health care services satisfaction in Turkey. The data was collected from a total of 17726 respondents. The establishment of the sample group and collection of the data were carried out by a joint team from The Ministry of Health and Turkish Statistical Institute (Turk Stat) of Turkey. The multiple correspondence analysis (MCA) was used on the data of 2882 respondents who answered the questionnaire in full. The multiple correspondence analysis indicated that, in the evaluation of health services females, public employees, younger and more highly educated individuals were more concerned and complainant than males, private sector employees, older and less educated individuals. Overall 53 % of the respondents were pleased with the improvements in health care services in the past three years. This study demonstrates the public consciousness in health services and health care satisfaction in Turkey. It was found that most the respondents were pleased with the improvements in health care services over the past three years. Awareness of health service quality increases with education levels. Older individuals and males would appear to have lower expectancies in health services.

Keywords: multiple correspondence analysis, multivariate categorical data, health care services, health satisfaction survey

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Authors: Priti Saha, Biswajit Paul

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Rapid urbanization and industrialization have increased the demand of groundwater. However, the present era has evident an enormous level of groundwater pollution. Therefore, water quality assessment is paramount importance to evaluate its suitability for drinking, irrigation and industrial use. This study focus to evaluate the groundwater quality of an industrial city in eastern India through interdisciplinary techniques. The multi-purpose Water Quality Index (WQI) assess the suitability for drinking as well as irrigation of forty sampling locations, where 2.5% and 15% of sampling locations have excellent water quality (WQI:0-25) as well as 15% and 40% have good quality (WQI:25-50), which represents its suitability for drinking and irrigation respectively. However, the industrial water quality was assessed through Ryznar Stability Index (LSI), which affirmed that only 2.5% of sampling locations have neither corrosive nor scale forming properties (RSI: 6.2-6.8). These techniques with the integration of geographical information system (GIS) for spatial assessment indorsed its effectiveness to identify the regions where the water bodies are suitable to use for drinking, irrigation as well as industrial activities. Further, the sources of these contaminants were identified through factor analysis (FA), which revealed that both the geogenic as well as anthropogenic sources were responsible for groundwater pollution. This research demonstrates the effectiveness of statistical and GIS techniques for the analysis of environmental contaminants.

Keywords: groundwater, water quality analysis, water quality index, WQI, factor analysis, FA, spatial assessment

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Authors: Zengmin Tian, Bin Lv, Rui Hui, Yupeng Liu, Chuan Wang, Qing Liu, Hongyu Li, Yan Qi, Li Song

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Objective Robot was used for replacement of the frame in recent years. The paper is to investigate the safety and effectiveness of frameless stereotactic surgery in the treatment of children with cerebral palsy. Methods Clinical data of 425 children with spastic cerebral palsy were retrospectively analyzed. The patients were treated with robot-assistant frameless stereotactic surgery of nuclear mass destruction. The motor function was evaluated by gross motor function measure-88 (GMFM-88) before the operation, 1 week and 3 months after the operation respectively. The statistical analysis was performed. Results The postoperative CT showed that the destruction area covered the predetermined target in all the patients. Minimal bleeding of puncture channel occurred in 2 patient, and mild fever in 3 cases. Otherwise, there was no severe surgical complication occurred. The GMFM-88 scores were 49.1±22.5 before the operation, 52.8±24.2 and 64.2±21.4 at the time of 1 week and 3 months after the operation, respectively. There was statistical difference between before and after the operation (P<0.01). After 3 months, the total effective rate was 98.1%, and the average improvement rate of motor function was 24.3% . Conclusion Replaced the traditional frame, the robot-assistant frameless stereotactic surgery is safe and reliable for children with spastic cerebral palsy, which has positive significance in improving patients’ motor function.

Keywords: cerebral palsy, robotics, stereotactic techniques, frameless operation

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Authors: Muziwandile Luthuli

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Although numerous factors predicting adherence to antiretroviral therapy (ART) among people living with HIV/AIDS (PLWHA) have been broadly studied on both regional and global level, up-to-date adherence of patients to ART remains an overarching, dynamic and multifaceted problem that needs to be investigated over time and across various contexts. There is a rarity of empirical data in the literature on interactive mechanisms by which psychosocial factors influence adherence to ART among PLWHA within the South African context. Therefore, this study was designed to investigate the relationship between depression, HIV stigma, and adherence to ART among adult patients living with HIV at a tertiary hospital in Durban, South Africa, and the mediating roles of self-efficacy and social support. The health locus of control theory and the social support theory were the underlying theoretical frameworks for this study. Using a cross-sectional research design, a total of 201 male and female adult patients aged between 18-75 years receiving ART at a tertiary hospital in Durban, KwaZulu-Natal were sampled, using time location sampling (TLS). A self-administered questionnaire was employed to collect the data in this study. Data were analysed through SPSS version 27. Several statistical analyses were conducted in this study, namely univariate statistical analysis, correlational analysis, Pearson’s chi-square analysis, cross-tabulation analysis, binary logistic regression analysis, and mediational analysis. Univariate analysis indicated that the sample mean age was 39.28 years (SD=12.115), while most participants were females 71.0% (n=142), never married 74.2% (n=147), and most were also secondary school educated 48.3% (n=97), as well as unemployed 65.7% (n=132). The prevalence rate of participants who had high adherence to ART was 53.7% (n=108), and 46.3% (n=93) of participants had low adherence to ART. Chi-square analysis revealed that employment status was the only statistically significant socio-demographic influence of adherence to ART in this study (χ2 (3) = 8.745; p < .033). Chi-square analysis showed that there was a statistically significant difference found between depression and adherence to ART (χ2 (4) = 16.140; p < .003), while between HIV stigma and adherence to ART, no statistically significant difference was found (χ2 (1) = .323; p >.570). Binary logistic regression indicated that depression was statistically associated with adherence to ART (OR= .853; 95% CI, .789–.922, P < 001), while the association between self-efficacy and adherence to ART was statistically significant (OR= 1.04; 95% CI, 1.001– 1.078, P < .045) after controlling for the effect of depression. However, the findings showed that the effect of depression on adherence to ART was not significantly mediated by self-efficacy (Sobel test for indirect effect, Z= 1.01, P > 0.31). Binary logistic regression showed that the effect of HIV stigma on adherence to ART was not statistically significant (OR= .980; 95% CI, .937– 1.025, P > .374), but the effect of social support on adherence to ART was statistically significant, only after the effect of HIV stigma was controlled for (OR= 1.017; 95% CI, 1.000– 1.035, P < .046). This study promotes behavioral and social change effected through evidence-based interventions by emphasizing the need for additional research that investigates the interactive mechanisms by which psychosocial factors influence adherence to ART. Depression is a significant predictor of adherence to ART. Thus, to alleviate the psychosocial impact of depression on adherence to ART, effective interventions must be devised, along with special consideration of self-efficacy and social support. Therefore, this study is helpful in informing and effecting change in health policy and healthcare services through its findings

Keywords: ART adherence, depression, HIV/AIDS, PLWHA

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Authors: Ahmed Saeed, Sadok Sassi, Mohammad Roshun

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Gears are important components with a vital role in many rotating machines. One of the common gear failure causes is tooth fatigue crack; however, its early detection is still a challenging task. The objective of this study is to develop a numerical model that simulates the effect of teeth cracks on the resulting gears vibrations and permits consequently to perform an early fault detection. In contrast to other published papers, this work incorporates the possibility of multiple simultaneous cracks with different depths. As cracks alter significantly the stiffness of the tooth, finite element software is used to determine the stiffness variation with respect to the angular position, for different combinations of crack orientation and depth. A simplified six degrees of freedom nonlinear lumped parameter model of a one-stage spur gear system is proposed to study the vibration with and without cracks. The model developed for calculating the stiffness with the crack permitted to update the physical parameters of the second-degree-of-freedom equations of motions describing the vibration of the gearbox. The vibration simulation results of the gearbox were by obtained using Simulink/Matlab. The effect of one crack with different levels was studied thoroughly. The change in the mesh stiffness and the vibration response were found to be consistent with previously published works. In addition, various statistical time domain parameters were considered. They showed different degrees of sensitivity toward the crack depth. Multiple cracks were also introduced at different locations and the vibration response along with the statistical parameters were obtained again for a general case of degradation (increase in crack depth, crack number and crack locations). It was found that although some parameters increase in value as the deterioration level increases, they show almost no change or even decrease when the number of cracks increases. Therefore, the use of any statistical parameters could be misleading if not considered in an appropriate way.

Keywords: Spur gear, cracked tooth, numerical simulation, time-domain parameters

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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: Hocine Terrab , Abdelhafid Bayadi, Adel Kara, Ayman El-Hag

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Insulator flashover under polluted conditions has been a serious threat on the reliability of power systems. It is known that the flashover process is mainly affected by the environmental conditions such as; the pollution level and humidity. Those are the essential parameters influencing the wetting process. This paper presents an investigation of the characteristics of leakage current (LC) developed on the surface of porcelain insulator at contaminated conditions under AC voltage. The study is done in an artificial fog chamber and the LC is characterized for different stages; dry, wetted and presence of discharge activities. Time-frequency and spectral analysis are adopted to calculate the evolution of LC characteristics with various stages prior to flashover occurrence. The preliminary results could be used in analysing the LC to develop more effective diagnosis of early signs of dry band arcing as an indication for insulation washing.

Keywords: flashover, harmonic components, leakage current, phase angle, statistical analysis

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Authors: Raya Al Khayari, Rasha Al Jassim, Muna Al Balushi, Fatma Al Moqbali, Said El Hajjar

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This study utilizes linear regression analysis to investigate the correlation between user account passwords and the probability of civil ID exposure, offering statistical insights into civil ID security. The study employs multiple linear regression (MLR) analysis to further investigate the elements that influence consumers’ views of civil ID security. This aims to increase awareness and improve preventive measures. The results obtained from the MLR analysis provide a thorough comprehension and can guide specific educational and awareness campaigns aimed at promoting improved security procedures. In summary, the study’s results offer significant insights for improving existing security measures and developing more efficient tactics to reduce risks related to civil ID security in Oman. By identifying key factors that impact consumers’ perceptions, organizations can tailor their strategies to address vulnerabilities effectively. Additionally, the findings can inform policymakers on potential regulatory changes to enhance civil ID security in the country.

Keywords: civil-id disclosure, awareness, linear regression, multiple regression

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Authors: Tamar Lazariashvili

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The development of agrotourism in Georgia has significant potential. The trend of population growth and demand for agrotourism products makes the interest and importance of the development of this field even more relevant. The article studies the trends in the development of agrotourism in Georgia; SWOT analysis reveals the potential for the development of agrotourism and assesses the perspectives, examines the factors hindering the development of agrotourism, assesses the role of the state in the development of agrotourism. Objectives: The purpose of the study is to determine the development trends of agrotourism in Georgia and to develop recommendations for prospective directions based on the assessment of the field's potential. Methodologies: Research methods are used: analysis, synthesis, induction, deduction, comparison, statistical (selection, grouping, observation, trend) and other methods, as well as SWOT analysis. Contributions: A positive trend in the development of agrotourism has been revealed. It is also shown that the demand for agrotourism products is growing. The agro touristic potential of Georgia was assessed and prospective directions for the development of the field have been determined. Conclusions: are drawn on the problems identified in the work and recommendations are proposed on ways to effectively use the potential opportunities of agrotourism and ways of long-term development.

Keywords: agrotourism, agrotourism products, agrotourism potential, development prospects.

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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: 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

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Authors: M. H. Arslan, U. K. Sahin, H. Acikgoz-Tufan, I. Gocek, I. Erdem

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Various exterior factors have perpetual effects on textile materials during wear, use and laundering in everyday life. In accordance with their frequency of use, textile materials are required to be laundered at certain intervals. The medium in which the laundering process takes place have inevitable detrimental physical and chemical effects on textile materials caused by the unique parameters of the process inherently existing. Connatural structures of various textile materials result in many different physical, chemical and mechanical characteristics. Because of their specific structures, these materials have different behaviors against several exterior factors. By modeling the behavior of commercial and test textiles as group-wise against laundering process, it is possible to disclose the relation in between these two groups of materials, which will lead to better understanding of their behaviors in terms of similarities and differences against the washing parameters of the laundering. Thus, the goal of the current research is to examine the behavior of two groups of textile materials as commercial textiles and as test textiles towards the main washing machine parameters during laundering process such as temperature, load quantity, mechanical action and level of water amount by concentrating on shrinkage, pilling, sewing defects, collar abrasion, the other defects other than sewing, whitening and overall properties of textiles. In this study, cotton fabrics were preferred as commercial textiles due to the fact that garments made of cotton are the most demanded products in the market by the textile consumers in daily life. Full factorial experimental set-up was used to design the experimental procedure. All profiles always including all of the commercial and the test textiles were laundered for 20 cycles by commercial home laundering machine to investigate the effects of the chosen parameters. For the laundering process, a modified version of ‘‘IEC 60456 Test Method’’ was utilized. The amount of detergent was altered as 0.5% gram per liter depending on varying load quantity levels. Datacolor 650®, EMPA Photographic Standards for Pilling Test and visual examination were utilized to test and characterize the textiles. Furthermore, in the current study the relation in between commercial and test textiles in terms of their performance was deeply investigated by the help of statistical analysis performed by MINITAB® package program modeling their behavior against the parameters of the laundering process. In the experimental work, the behaviors of both groups of textiles towards washing machine parameters were visually and quantitatively assessed in dry state.

Keywords: behavior against washing machine parameters, performance evaluation of textiles, statistical analysis, commercial and test textiles

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Authors: Nino Grigolaia

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Introduction: The article discusses the experience of the EU in the social field, analyzes the peculiarities of the functioning of the social system in Georgia, and reveals the priority and importance of social policy. Methodology: Different research methods are applied in the presented paper. There are used induction, deduction, analysis, synthesis, analogy, correlation, and statistical observation methodologies in the work. Main Findings: Based on the analysis of social security reforms in Georgia, the main systematic problems are detected, the recommendations on social security system components, integration of the social security field in the unified insurance system, the formation of the national social system, perfection of the legislative, regulatory framework of social protection, adoption of foreign experience are developed in the article. Conclusion: The article concludes that the social protection system in Georgia is at an early stage of development, with the significant impact of factors such as high level of unemployment, low pensions, a large number of families living under the poverty line, and other ones. Accordingly, it is well-established that the study of the social security problem in Georgia is still actual. Based on the analysis, appropriate suggestions in the field of social security are made, and relevant recommendations are proposed.

Keywords: social security, social system, social policy, social security models

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Authors: Onuchukwu Chika Christian, Chukwude Augustine Ejike

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We carried out a statistical analyse of microglitches events on a sample of radio pulsars. The distribution of microglitch events in frequency (ν) and first frequency derivatives ν˙ indicates that the size of a microglitch and sign combinations of events in ν and ν˙ are purely randomized. Assuming that the probability of a given size of a microglitch event occurring scales inversely as the absolute size of the event in both ν and ν˙, we constructed a cumulative distribution function (CDF) for the absolute sizes of microglitches. In most of the pulsars, the theoretical CDF matched the observed values. This is an indication that microglitches in pulsar may be interpreted as an avalanche process in which angular momentum is transferred erratically from the flywheel-like superfliud interior to the slowly decelerating solid crust. Analysis of the waiting time indicates that it is purely Poisson distributed with mean microglitch rate <γ> ∼ 0.98year^−1 for all the pulsars in our sample and <γ> / <∆T> ∼ 1. Correlation analysis, showed that the relative absolute size of microglitch event strongly with the rotation period of the pulsar with correlation coefficient r ∼ 0.7 and r ∼ 0.5 respectively for events in ν and ν˙. The mean glitch rate and number of microglitches (Ng) showed some dependence on spin down rate (r ∼ −0.6) and the characteristic age of the pulsar (τ) with (r ∼ −0.4/− 0.5).

Keywords: method-data analysis, star, neutron-pulsar, general

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Authors: Catherine Mary Abou-Zaid

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This quantitative study discusses the concerns with the self-directed learning (SDL) skills of the undergraduate nursing students in a medical university in Bahrain. The nursing undergraduate student SDL study was conducted taking all 4 years and compiling data collected from the students themselves by survey questionnaire. The aim of the study is to understand and change the attitudes of self-directed learning among the undergraduate students. The SDL of the undergraduate student nurses has been noticed to be lacking and motivation to actually perform without supervision while out-with classrooms are very low. Their use of the resources available on the virtual learning environment and also within the university is not as good as it should be for a university student at this level. They do not use them to their own advantage. They are not prepared for the transition from high school to an academic environment such as a university or college. For some students it is the first time in their academic lives that they have faced sharing a classroom with the opposite sex. For some this is a major issue and we as academics need to be aware of all issues that they come to higher education with. Design Methodology: The design methodology that was chosen was a quantitative design using convenience sampling of the students who would be asked to complete survey questionnaire. This sampling method was chosen because of the time constraint. This was completed by the undergraduate students themselves while in class. The questionnaire was analyzed by the statistical package for social sciences (SPSS), the results interpreted by the researcher and the findings published in the paper. The analyzed data will also be reported on and from this information we as educators will be able to see the student’s weaknesses regarding self-directed learning. The aims and objectives of the research will be used as recommendations for the improvement of resources for the students to improve their SDL skills. Conclusion: The results will be able to give the educators an insight to how we can change the self-directed learning techniques of the students and enable them to embrace the skills and to focus more on being self-directed in their studies rather than having to be put on to a SDL pathway from the educators themselves. This evidence will come from the analysis of the statistical data. It may even change the way in which the students are selected for the nursing programme. These recommendations will be reported to the head of school and also to the nursing faculty.

Keywords: self-directed learning, undergraduate students, transition, statistical package for social sciences (SPSS), higher education

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Authors: Avinash Thakur, Parmjit S. Panesar, Manohar Singh

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The distribution coefficient, KD for the reactive extraction of lactic acid from aqueous solutions of lactic acid using 10-30% (v/v) tri-n-octyl amine (extractant) dissolved in n-hexane (inert diluent) and 20% (v/v) oleyl alcohol (modifier) was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined interactive effect of seven independent variables, viz lactic acid concentration (cl), pH, TOA concentration in organic phase (ψ), treat ratio (φ), temperature (T), agitation speed (ω) and batch agitation time (τ) on distribution coefficient of lactic acid. The regression analysis recommended that the quadratic model is significant (R2 and adjusted R2 are 98.72 % and 98.69 % respectively) for analysis. A numerical optimization had resulted in maximum lactic acid distribution coefficient (KD) of 3.16 at the optimized values for test variables, cl, pH, ψ, φ, T, ω and τ as 0.15 [M], 3.0, 22.75% (v/v), 1.0 (v/v), 26°C, 145 rpm and 23 min respectively. A good agreement between the predicted and experimentally obtained values for distribution coefficient using the optimized conditions was exhibited.

Keywords: Distribution coefficient, tri-n-octylamine, lactic acid, response surface methodology

Procedia PDF Downloads 423