Search results for: Statistical Analysis

Authors: Mohammad A. Khasawneh

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Asphalt concrete pavements gradually lose their skid resistance causing safety problems especially under wet conditions and high driving speeds. In order to enact the actual field polishing and wearing process of asphalt pavement surfaces in a laboratory setting, several laboratory-scale accelerated polishing devices were developed by different agencies. To mimic the actual process, friction and texture measuring devices are needed to quantify surface deterioration at different polishing intervals that reflect different stages of the pavement life. The test could still be considered lengthy and to some extent labor-intensive. Therefore, there is a need to come up with another method that can assist in investigating the bituminous pavement surface characteristics in a practical and time-efficient test procedure. The purpose of this paper is to utilize a well-developed image analysis technique to characterize asphalt pavement surfaces without the need to use conventional friction and texture measuring devices in an attempt to shorten and simplify the polishing procedure in the lab. Promising findings showed the possibility of using image analysis in lieu of the labor-sensitive-variable-in-nature friction and texture measurements. It was found that the exposed aggregate surface area of asphalt specimens made from limestone and gravel aggregates produced solid evidence of the validity of this method in describing asphalt pavement surfaces. Image analysis results correlated well with the British Pendulum Numbers (BPN), Polish Values (PV) and Mean Texture Depth (MTD) values.

Keywords: friction, image analysis, polishing, statistical analysis, texture

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Authors: Jane A. Luke

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Persistent pressure passed on to manufacturers from escalating consumer expectations and the ever growing global competitiveness have produced a rapidly increasing interest in the development of various manufacturing strategy models. Academic and industrial circles are taking keen interest in the field of manufacturing strategy. Many manufacturing strategies are currently centered on the traditional concepts of focused manufacturing capabilities such as quality, cost, dependability and innovation. Process capability indices was conducted assuming that the process under study is in statistical control and independent observations are generated over time. However, in practice, it is very common to come across processes which, due to their inherent natures, generate autocorrelated observations. The degree of autocorrelation affects the behavior of patterns on control charts. Even, small levels of autocorrelation between successive observations can have considerable effects on the statistical properties of conventional control charts. When observations are autocorrelated the classical control charts exhibit nonrandom patterns and lack of control. Many authors have considered the effect of autocorrelation on the performance of statistical process control charts. In this paper, the effect of autocorrelation on confidence intervals for different PCIs was included. Stationary Gaussian processes is explained. Effect of autocorrelation on PCIs is described in detail. Confidence intervals for Cp and Cpk are constructed for PCIs when data are both independent and autocorrelated. Confidence intervals for Cp and Cpk are computed. Approximate lower confidence limits for various Cpk are computed assuming AR(1) model for the data. Simulation studies and industrial examples are considered to demonstrate the results.

Keywords: autocorrelation, AR(1) model, Bissell’s approximation, confidence intervals, statistical process control, specification limits, stationary Gaussian processes

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Authors: S. Ghafoori, A. Al-Harbi, B. Al-Ajmi, A. Al-Shaalan, A. Al-Ajmi, M. Ali Juma

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Seismic methods play an important role in the exploration for hydrocarbon reservoirs. However, the success of the method depends strongly on the reliability of the measured or predicted information regarding the velocity of sound in the media. Speed of sound has been used to study the thermodynamic properties of fluids. In this study, experimental data are reported and analyzed on the speed of sound in toluene and octane binary mixture. Three-factor three-level Box-Benhkam design is used to determine the significance of each factor, the synergetic effects of the factors, and the most significant factors on speed of sound. The developed mathematical model and statistical analysis provided a critical analysis of the simultaneous interactive effects of the independent variables indicating that the developed quadratic models were highly accurate and predictive.

Keywords: experimental design, octane, speed of sound, toluene

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Authors: Chaitanya Varma, Arpan Mehar

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The present study demonstrates the procedure to analyse speed data collected on various four-lane divided sections in India. Field data for the study was collected at different straight and curved sections on rural highways with the help of radar speed gun and video camera. The data collected at the sections were analysed and parameters pertain to speed distributions were estimated. The different statistical distribution was analysed on vehicle type speed data and for mixed traffic speed data. It was found that vehicle type speed data was either follows the normal distribution or Log-normal distribution, whereas the mixed traffic speed data follows more than one type of statistical distribution. The most common fit observed on mixed traffic speed data were Beta distribution and Weibull distribution. The separate operating speed model based on traffic and roadway geometric parameters were proposed in the present study. The operating speed model with traffic parameters and curve geometry parameters were established. Two different operating speed models were proposed with variables 1/R and Ln(R) and were found to be realistic with a different range of curve radius. The models developed in the present study are simple and realistic and can be used for forecasting operating speed on four-lane highways.

Keywords: highway, mixed traffic flow, modeling, operating speed

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Authors: Nasrin Badrkhani, Hosein Dehghani

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Teaching is an interaction between the teacher, student, and the concept in the classroom. As society needs thoughtful and creative people, there is a necessity to change the teaching methods and use modern and active methods of teaching. Teaching has to involve the student in thinking activities. Problem-solving, creativity, cooperation, and scientific thinking skills. Among the prominent characteristics of the modern methods, paying attention to the student struggle and the gradual and continuous learning (process-centered), emphasizing evaluating the students’ entire abilities and talents, and evaluating the students’ maximum ability can be mentioned. And student-centered teaching has to replace teacher-centered teaching. Among the modern methods, group work, role-playing, group discussion, cooperation, and engagement in judgments concerning societal values can be mentioned. This research uses a survey and a questionnaire with 38 questions on the Likert scale to examine the teacher’s ideas about the impact of modern methods of teaching on the quality of teaching. And also studies the relation between this factor and sex, major, and the teaching experience. The statistical population of this research is the teachers of Shiraz-Iran high schools. Morgan table is used for sampling; discriminant analysis is used for the mental of the questions. For the final examination of the questionnaire, Cronbach’s Alpha test and for the statistical analysis of SPSS Software are used. And in the inferential statistic level, T test and one-way variance are used. The results of this research showed that the teachers of this city have positive viewpoints about the use of modern teaching methods except engage in judgments concerning societal values. Both male and female teachers have the same viewpoints, and there isn’t any significant difference between the education degree and the use of modern methods. Also, this research confirms the results of similar research which were done in and out of Iran.

Keywords: learning, teaching, student, teacher, modern methods

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Authors: Shraddha Gopal, Jayam Lazarus

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Aims: To study the referral practice and impact of DAT-scan in the diagnosis or exclusion of Parkinson’s disease. Settings and Designs: A retrospective study Materials and methods: A retrospective study of the results of 60 patients who were referred for a DAT scan over a period of 2 years from the Department of Neurology at Northern Lincolnshire and Goole NHS trust. The reason for DAT scan referral was noted under 5 categories against Parkinson’s disease; drug-induced Parkinson’s, essential tremors, diagnostic dilemma, not responding to Parkinson’s treatment, and others. We assessed the number of patients who were diagnosed with Parkinson’s disease against the number of patients in whom Parkinson’s disease was excluded or an alternative diagnosis was made. Statistical methods: Microsoft Excel was used for data collection and statistical analysis, Results: 30 of the 60 scans were performed to confirm the diagnosis of early Parkinson’s disease, 13 were done to differentiate essential tremors from Parkinsonism, 6 were performed to exclude drug-induced Parkinsonism, 5 were done to look for alternative diagnosis as the patients were not responding to anti-Parkinson medication and 6 indications were outside the recommended guidelines. 55% of cases were confirmed with a diagnosis of Parkinson’s disease. 43.33% had Parkinson’s disease excluded. 33 of the 60 scans showed bilateral abnormalities and confirmed the clinical diagnosis of Parkinson’s disease. Conclusion: DAT scan provides valuable information in confirming Parkinson’s disease in 55% of patients along with excluding the diagnosis in 43.33% of patients aiding an alternative diagnosis.

Keywords: DATSCAN, Parkinson's disease, diagnosis, essential tremors

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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

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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: 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: 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

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Authors: Marianna Ciaccia, Gennaro Agrimi, Isabella Pisano, Maurizio Bettiga, Silvia Rapacioli, Giulia Mensa, Monica Marzagalli

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Objective: Untargeted metabolomic analysis of extracellular metabolites is a powerful approach that focuses on comprehensively profiling in the extracellular space. In this study, we applied extracellular metabolomic analysis to investigate the metabolism of two probiotic microorganisms with health benefits that extend far beyond the digestive tract and the immune system. Methods: Analytical techniques employed in extracellular metabolomic analysis encompass various technologies, including mass spectrometry (MS), which enables the identification of metabolites present in the fermentation media, as well as the comparison of metabolic profiles under different experimental conditions. Multivariate statistical analysis techniques like principal component analysis (PCA) or partial least squares-discriminant analysis (PLS-DA) play a crucial role in uncovering metabolic signatures and understanding the dynamics of metabolic networks. Results: Different types of supernatants from fermentation processes, such as dairy-free, not dairy-free media and media with no cells or pasteurized, were subjected to metabolite profiling, which contained a complex mixture of metabolites, including substrates, intermediates, and end-products. This profiling provided insights into the metabolic activity of the microorganisms. The integration of advanced software tools has facilitated the identification and characterization of metabolites in different fermentation conditions and microorganism strains. Conclusions: In conclusion, untargeted extracellular metabolomic analysis, combined with software tools, allowed the study of the metabolites consumed and produced during the fermentation processes of probiotic microorganisms. Ongoing advancements in data analysis methods will further enhance the application of extracellular metabolomic analysis in fermentation research, leading to improved bioproduction and the advancement of sustainable manufacturing processes.

Keywords: biotechnology, metabolomics, lactic bacteria, probiotics, postbiotics

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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: 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: 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: 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: 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: 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: Mahshid Arabi

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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

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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: 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

Abstract:

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: Muziwandile Luthuli

Abstract:

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

Abstract:

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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