Search results for: flight test data

Authors: Alyaa Farouk Ibrahim, Gehan ElSayed, Ola Mamdouh, Nazek AbdelGhany

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Background: Primary health care (PHC) can be considered the first contact between the patient and the health care system. It includes all the basic health care services to be provided to the community. Patient's satisfaction regarding health care has often improved the provision of care, also considered as one of the most important measures for evaluating the health care. Objective: This study aims to identify patient’s satisfaction with services provided at the primary health care settings in Alexandria. Setting: Seven primary health care settings representing the seven zones of Alexandria governorate were selected randomly and included in the study. Subjects: The study comprised 386 patients attended the previously selected settings at least twice before the time of the study. Tools: Two tools were utilized for data collection; sociodemographic characteristics and health status structured interview schedule and patient satisfaction scale. Reliability test for the scale was done using Cronbach's Alpha test, the result of the test ranged between 0.717 and 0.967. The overall satisfaction was computed and divided into high, medium, and low satisfaction. Results: Age of the studied sample ranged between 19 and 62 years, more than half (54.2%) of them aged 40 to less than 60 years. More than half (52.8%) of the patients included in the study were diabetics, 39.1% of them were hypertensive, 19.2% had cardiovascular diseases, the rest of the sample had tumor, liver diseases, and orthopedic/neurological disorders (6.5%, 5.2% & 3.2%, respectively). The vast majority of the study group mentioned high satisfaction with overall service cost, environmental conditions, medical staff attitude and health education given at the PHC settings (87.8%, 90.7%, 86.3% & 90.9%, respectively), however, medium satisfaction was mostly reported concerning medical checkup procedures, follow-up data and referral system (41.2%, 28.5% & 28.9%, respectively). Score level of patient satisfaction with health services provided at the assessed Primary health care settings proved to be significantly associated with patients’ social status (P=0.003, X²=14.2), occupation (P=0.011, X²=11.2), and monthly income (P=0.039, X²=6.50). In addition, a significant association was observed between score level of satisfaction and type of illness (P=0.007, X²=9.366), type of medication (P=0.014, X²=9.033), prior knowledge about the health center (P=0.050, X²=3.346), and highly significant with the administrative zone (P=0.001, X²=55.294). Conclusion: The current study revealed that overall service cost, environmental conditions, staff attitude and health education at the assessed primary health care settings gained high patient satisfaction level, while, medical checkup procedures, follow-up, and referral system caused a medium level of satisfaction among assessed patients. Nevertheless, social status, occupation, monthly income, type of illness, type of medication and administrative zones are all factors influencing patient satisfaction with services provided at the health facilities.

Keywords: patient satisfaction, chronic illness, quality of health service, quality of service indicators

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Authors: Aroona Hashmi

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Parental Involvement is a strategic key to both traditional and contemporary way of ‘face-to-face’ schooling, including public/private schools and home schooling. Present research is destined to find out whether this connection happens in Pakistani schools, a land which faces educational hurdles. This study aims to find out the parental involvement in schooling of female students and its impact on their achievement at elementary level. In this study quantitative research approach is used. Survey is conducted by utilizing reliable and valid instrument named as Parental Involvement Project Questionnaire (PIP). A stratified random sampling technique applied to select twenty schools in total from District Lahore. Schools were selected from public and private sectors. All selected schools were registered with Punjab Examination Commission (PEC), therefore standardized tests are conducted by PEC for class 8 every year in Punjab province, Pakistan. In total 1000 students and their 1000 parents constituted the sample. Data were analyzed by using SPSS version 17. T-test and Regression was applied to independent samples to test the null hypotheses. The result of this study indicated that parents of female students showed more involvement as compared to parents of male students at elementary level. There was significant difference in the impact of parental involvement on achievement of female students and male students i.e. there was more impact of parental involvement found on achievement of female students as compared to male students.

Keywords: parental involvement, achievement, schooling, elementary level, PEC

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Authors: Shima Mahmoudi, Setareh Mamishi, Babak Pourakbari, Majid Marjani

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In the last years, the potential role of distinct T-cell subsets as biomarkers of active tuberculosis TB and/or latent tuberculosis infection (LTBI) has been studied. The aim of this study was to investigate the potential role of interleukin-2 (IL-2) in whole blood stimulated with M. tuberculosis-specific antigens in the QuantiFERON-TB Gold In Tube (QFT-G-IT) for the discrimination of active and latent tuberculosis. After 72-h of stimulation by antigens from the QFT-G-IT assay, IL-2 secretion was quantitated in supernatants by using ELISA (Mabtech AB, Sweden). Observing the level of IL-2 released after 72-h of incubation, we found that the level of IL-2 were significantly higher in LTBI group than in patients with active TB infection or control group (P value=0.019, Kruskal–Wallis test). The discrimination performance (assessed by the area under ROC curve) between LTBI and patients with active TB was 0.816 (95%CI: 0.72-0.97). Maximum discrimination was reached at a cut-off of 13.9 pg/mL for IL-2 following stimulation with 82% sensitivity and 86% specificity. In conclusion, although cytokine analysis has greatly contributed to the understanding of TB pathogenesis, data on cytokine profiles that might distinguish progression from latency of TB infection are scarce and even controversial. Our data indicate that the concomitant evaluation of IFN- γ and IL-2 could be instrumental in discriminating of active and latent TB infection.

Keywords: interleukin-2, discrimination, active TB, latent TB

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Authors: Rabia Genc, Aysun Eksioglu, Emine Serap Sarican, Sibel Icke

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Today the habit of cigarette smoking is among one of the most important public health concerns because of the health problems it leads to. The most important and hazardous group to use tobacco and tobacco products is adolescents and teenagers. And one of the most effective ways to prevent them from starting to smoke is education. This research is a kind of educational intervention study which was carried out in order to evaluate the effect of peer education on the teenagers' knowledge about smoking. The research was carried out between October 15, 2013 and September 9, 2015 at Ege University Ataturk Vocational Health School. The population of the research comprised of the students that have been studying at Ege University Atatürk Vocational Health School, Midwifery Department (N=390). The peer educator group that would give training on smoking consisted of 10 people, and the peer groups that would be trained were divided into two groups via simple randomization as experimental group (n=185) and control group (n=185). Questionnaire, information evaluation form, and informed consent forms were used as date collection tools. The analysis of the data which were collected in the study was carried out on Statistical Package for Social Science (SPSS 15.0). It was found out that 62.5 % of the students who were in peer educator group had smoked in some period of their lives; however, none of them continued to smoke. When they were asked about their reasons to start smoking, 25% said they just wanted to try it, and 25% of them answered that it was because of their friend groups. When the pre-peer education and post-peer education point averages of peer educator group were evaluated, the results showed that there was a significant difference between the point averages (p < 0.05). When the cigarette use of experimental group and the control group were evaluated, it was clear that 18.2% of the experimental group and 24.2%of the control group still smokes. 9.1% of the experimental group and 14.8% of control group stated that they started smoking because of their friend groups. Among the students who smoke 15.9% of the ones who belongs to the experimental group and 21.9% of the ones who belong to the control group stated they are thinking of quitting smoking. It was clear that there is a significant difference between the pre-education and post-education point averages of experimental group statistically (p ≤ 0.05); however, in terms of control group, there were no significant differences between the pre-test post-test averages statistically. Between the pre-test post-test averages of experimental and control groups there were not any statistically significant differences (p > 0.05). It was found out in the study that the peer education programme is not effective on the smoking habit of Vocational Health School students. When the future studies are being planned in order to evaluate the peer education activity, it can be taken into consideration that the peer education takes a long term and the students in the educator group will be more enthusiastic and a kind of leader in their environment.

Keywords: midwifery, peer, peer education, smoking

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Authors: Dinko Vuleta, Dejan Madić, Goran Sporiš, Nebojša Trajković

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The aim of this study was to determine the effects of gymnastics program in school on skill-related fitness in early adolescent students. The study involved 58 adolescent students (12.82±0.54 years; Height 156.81±8.16 cm; 53.46±12.31 kg) from primary school divided into two groups, following the randomization. The gymnastic group was involved in a 12 week of gymnastics classes, while the control group only participated in usual PE classes which consisted of multi-sport activities. The variables were selected within the several fitness batteries, measuring coordination (polygon backwards), upper and lower body strength standing long jump and medicine ball throw), speed (20 m sprint) and agility (4x10 test). Pre-test to post-test values showed significant improvements in all tested variables (p<0.05), except for the 4x10m test, where there were no significant improvements in neither of the groups (p>0.05). Significant interactions of time by group were observed for coordination, sprint speed, standing long jump and medicine ball throw (p<0.05). The results showed significant increase in skill-related fitness of the participants in the gymnastic group compared to the control group. Therefore, participation in gymnastics must be recommended as a positive foundational activity for school-aged children, from early childhood to adulthood. Additionally, the results can provide useful information in optimizing the training loads of pupils involved in gymnastic training throughout PE classes.

Keywords: effects, PE classes, physical fitness, training

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Authors: Solomon Olusegun Olugbenro

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The purpose of this study is to ascertain the relationship of teachers' personalty and peer pressure on adolescents' personalty in mainland local government, Lagos State, Nigeria. The research design for this study was survey. A representative fraction of the population of mainland local government of lagos was used as sample. One hundred and fifty (150) teenagers whose age ranged from 11-19 from six randomly selected public and private secondary schools in mainland local government area of lagos were used. A four-point likert type questionnaire was constructed for eliciting data for this study. Data were analysed using t-test. The study revealed that there is a significant relationship between teachers' and adolescents' personality development. The study also revealed that there is significant relationship between peer pressure and adolescents' personality development. It was recommended that teachers should be role models to students as they manipulate environmental factors to assist adolescents in their personality development.

Keywords: adolescents, behavior, development, peer pressure, personality, relationship, significant, teachers

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Authors: Dragana Calic

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The openness, availability and the sheer volume of big data have provided, what some regard as, an invaluable and rich dataset. Researchers, businesses, advertising agencies, medical institutions, to name only a few, collect, share, and analyze this data to enable their processes and decision making. However, there are important ethical considerations associated with the use of big data. The rapidly evolving nature of online technologies has overtaken the many legislative, privacy, and ethical frameworks and principles that exist. For example, should we obtain consent to use people’s online data, and under what circumstances can privacy considerations be overridden? Current guidance on how to appropriately and ethically handle big data is inconsistent. Consequently, this paper focuses on two quite distinct but related ethical considerations that are at the core of the use of big data for research purposes. They include empowering the producers of data and empowering researchers who want to study big data. The first consideration focuses on informed consent which is at the core of empowering producers of data. In this paper, we discuss some of the complexities associated with informed consent and consider studies of producers’ perceptions to inform research ethics guidelines and practice. The second consideration focuses on the researcher. Similarly, we explore studies that focus on researchers’ perceptions and experiences.

Keywords: big data, ethics, producers’ perceptions, researchers’ perceptions

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Authors: An Chengrui, Yin Zi, Wu Bingbing, Ma Yuanzhu, Jin Kaixiu, Chen Xiao, Ouyang Hongwei

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Single cell RNA sequence (scRNA-seq) is one of the effective tools to study transcriptomics of biological processes. Recently, similarity measurement of cells is Euclidian distance or its derivatives. However, the process of scRNA-seq is a multi-variate Bernoulli event model, thus we hypothesize that it would be more efficient when the divergence between cells is valued with relative entropy than Euclidian distance. In this study, we compared the performances of Euclidian distance, Spearman correlation distance and Relative Entropy using scRNA-seq data of the early, medial and late stage of limb development generated in our lab. Relative Entropy is better than other methods according to cluster potential test. Furthermore, we developed KL-SNE, an algorithm modifying t-SNE whose definition of divergence between cells Euclidian distance to Kullback–Leibler divergence. Results showed that KL-SNE was more effective to dissect cell heterogeneity than t-SNE, indicating the better performance of relative entropy than Euclidian distance. Specifically, the chondrocyte expressing Comp was clustered together with KL-SNE but not with t-SNE. Surprisingly, cells in early stage were surrounded by cells in medial stage in the processing of KL-SNE while medial cells neighbored to late stage with the process of t-SNE. This results parallel to Heatmap which showed cells in medial stage were more heterogenic than cells in other stages. In addition, we also found that results of KL-SNE tend to follow Gaussian distribution compared with those of the t-SNE, which could also be verified with the analysis of scRNA-seq data from another study on human embryo development. Therefore, it is also an effective way to convert non-Gaussian distribution to Gaussian distribution and facilitate the subsequent statistic possesses. Thus, relative entropy is potentially a better way to determine the divergence of cells in scRNA-seq data analysis.

Keywords: Single cell RNA sequence, Similarity measurement, Relative Entropy, KL-SNE, t-SNE

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Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

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Authors: V. A. Doss, R. Sowndarya, K. Juila Rose Mary

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Objective: Amino acid neurotransmitter system dysfunction plays a major role in the pathophysiology of depression. The objective of the present study was to identify the amino acids as possible metabolite biomarkers for depression using GCMS (Gas Chromatography Mass Spectrometry) before and after exercise regimen in brain samples of depression induced animal models. Methods: Depression-like behaviour was induced by Chronic Unpredictable mild stress (CUMS). Severity of depression was measured by forced swim test (FST) and sucrose consumption test (SCT). Swimming protocol was followed for 4 weeks of exercise treatment. Brain obtained from depressed and exercise treated rats were used for the metabolite analysis by GCMS. Subsequent statistical analysis obtained by ANOVA followed by post hoc test revealed significant metabolic changes. Results: Amino acids such as alanine, glycine, serine, glutamate, homocysteine, proline and branched chain aminoacids (BCAs) Leucine, Isoleucine, Valine were determined in brain samples of control, depressed and exercised groups. Among these amino acids, the levels of D-Serine and branched chain amino acids were found to be decreased in depression induced rats. After four weeks of swimming exercise regimen, there were improvements in the levels of serine and Branched chain amino acids. Conclusion: We suggest that Serine and BCAs may be investigated as potential metabolite markers using GCMS and their beneficial metabolic changes in Exercise.

Keywords: metabolomics, depression, forced swim test, exercise, amino acid metabolites, GCMS, biomarker

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Authors: Ankur Mundhra, Shubhadeep Chakraborty, Y. R. Singh, Vishal Das

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Seismic data scaling affects the dynamic range of a data and with present day lower costs of storage and higher reliability of Hard Disk data, scaling is not suggested. However, in dealing with data of different vintages, which perhaps were processed in 16 bits or even 8 bits and are need to be processed with 32 bit available data, scaling is performed. Also, scaling amplifies low amplitude events in deeper region which disappear due to high amplitude shallow events that saturate amplitude scale. We have focused on significance of scaling data to aid interpretation. This study elucidates a proper seismic loading procedure in workstations without using default preset parameters as available in most software suites. Differences and distribution of amplitude values at different depth for seismic data are probed in this exercise. Proper loading parameters are identified and associated steps are explained that needs to be taken care of while loading data. Finally, the exercise interprets the un-certainties which might arise when correlating scaled and unscaled versions of seismic data with synthetics. As, seismic well tie correlates the seismic reflection events with well markers, for our study it is used to identify regions which are enhanced and/or affected by scaling parameter(s).

Keywords: clipping, compression, resolution, seismic scaling

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Authors: Ziwen Fang, Jianran Wang, Hongtao Liu, Weiguo Kong, Kefei Wang, Qi Luo, Haifeng Hong

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A 4-stage crash energy management (CEM) system for subway rail vehicles used by Massachusetts Bay Transportation Authority (MBTA) in the USA is developed in this paper. The 4 stages of this new CEM system include 1) energy absorbing coupler (draft gear and shear bolts), 2) primary energy absorbers (aluminum honeycomb structured box), 3) secondary energy absorbers (crush tube), and 4) collision post and corner post. A sliding anti-climber and a fixed anti-climber are designed at the front of the vehicle cooperating with the 4-stage CEM to maximize the energy to be absorbed and minimize the damage to passengers and crews. In order to investigate the effectiveness of this CEM system, both finite element (FE) methods and crashworthiness test have been employed. The whole vehicle consists of 3 married pairs, i.e., six cars. In the FE approach, full-scale railway car models are developed and different collision cases such as a single moving car impacting a rigid wall, two moving cars into a rigid wall, two moving cars into two stationary cars, six moving cars into six stationary cars and so on are investigated. The FE analysis results show that the railway vehicle incorporating this CEM system has a superior crashworthiness performance. In the crashworthiness test, a simplified vehicle front end including the sliding anti-climber, the fixed anti-climber, the primary energy absorbers, the secondary energy absorber, the collision post and the corner post is built and impacted to a rigid wall. The same test model is also analyzed in the FE and the results such as crushing force, stress, and strain of critical components, acceleration and velocity curves are compared and studied. FE results show very good comparison to the test results.

Keywords: railway vehicle collision, crash energy management design, finite element method, crashworthiness test

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Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

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The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

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Authors: S. Yun, M. Kwak

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This study is about an aerodynamic brake device for a high-speed train. In order to apply an aerodynamic brake device, an influence of the aerodynamic brake device on a high-speed train was studied aerodynamically, acoustically and dynamically. Wind tunnel test was conducted to predict an effect of braking distance reduction with a scale model of 1/30. Aerodynamic drag increases by 244% with a brake panel of a 90 degree angle. Braking distance for an emergency state was predicted to decrease by 13%.

Keywords: aerodynamic brake, braking distance, drag coefficient, high-speed train, wind-tunnel test

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Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Ella Quigley, Kevin Tinkham

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Fire performance is a crucial aspect to consider when designing cladding products, and testing this performance is extremely expensive. Appropriate use of numerical simulation of fire performance has the potential to reduce the total number of fire tests required when designing a product by eliminating poor-performing design ideas early in the design phase. Due to the complexity of fire and the large spectrum of failures it can cause, multi-disciplinary models are needed to capture the complex fire behavior and its structural effects on its surroundings. Working alongside Tata Steel U.K., the authors have focused on completing a coupled CFD-FEA simulation model suited to test Polyisocyanurate (PIR) based sandwich panel products to gain confidence before costly experimental standards testing. The sandwich panels are part of a thermally insulating façade system primarily for large non-domestic buildings. The work presented in this paper compares two coupling methodologies of a replicated physical experimental standards test LPS 1181-1, carried out by Tata Steel U.K. The two coupling methodologies that are considered within this research are; one-way and two-way. A one-way coupled analysis consists of importing thermal data from the CFD solver into the FEA solver. A two-way coupling analysis consists of continuously importing the updated changes in thermal data, due to the fire's behavior, to the FEA solver throughout the simulation. Likewise, the mechanical changes will also be updated back to the CFD solver to include geometric changes within the solution. For CFD calculations, a solver called Fire Dynamic Simulator (FDS) has been chosen due to its adapted numerical scheme to focus solely on fire problems. Validation of FDS applicability has been achieved in past benchmark cases. In addition, an FEA solver called ABAQUS has been chosen to model the structural response to the fire due to its crushable foam plasticity model, which can accurately model the compressibility of PIR foam. An open-source code called FDS-2-ABAQUS is used to couple the two solvers together, using several python modules to complete the process, including failure checks. The coupling methodologies and experimental data acquired from Tata Steel U.K are compared using several variables. The comparison data includes; gas temperatures, surface temperatures, and mechanical deformation of the panels. Conclusions are drawn, noting improvements to be made on the current coupling open-source code FDS-2-ABAQUS to make it more applicable to Tata Steel U.K sandwich panel products. Future directions for reducing the computational cost of the simulation are also considered.

Keywords: fire engineering, numerical coupling, sandwich panels, thermo fluids

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Authors: H. M. B. N Jayasinghe

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The water is found almost everywhere on Earth. Water resources contain a lot of pollution. Some diseases can be spread through the water to the living beings. So to be clean water it should undergo a number of treatments necessary to make it drinkable. So it is must to have purification technology for the wastewater. So the waste water treatment plants act a major role in these issues. When considering the procedures taken after the water treatment process was always based on manual calculations and recordings. Water purification plants may interact with lots of manual processes. It means the process taking much time consuming. So the final evaluation and chemical, biological treatment process get delayed. So to prevent those types of drawbacks there are some computerized programmable calculation and analytical techniques going to be introduced to the laboratory staff. To solve this problem automated system will be a solution in which guarantees the rational selection. A decision support system is a way to model data and make quality decisions based upon it. It is widely used in the world for the various kind of process automation. Decision support systems that just collect data and organize it effectively are usually called passive models where they do not suggest a specific decision but only reveal information. This web base system is based on global positioning data adding facility with map location. Most worth feature is SMS and E-mail alert service to inform the appropriate person on a critical issue. The technological influence to the system is HTML, MySQL, PHP, and some other web developing technologies. Current issues in the computerized water chemistry analysis are not much deep in progress. For an example the swimming pool water quality calculator. The validity of the system has been verified by test running and comparison with an existing plant data. Automated system will make the life easier in productively and qualitatively.

Keywords: automated system, wastewater, purification technology, map location

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Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

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Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

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Authors: Julien Baillet

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In light of 30 years of scientific research, InCorporer Method was created in 2019 as a new approach to heal traumatic, developmental, and dissociative injuries. Following natural nervous system functions, InCorporer aims to heal, develop, and update the different defensive mammalian subsystems: fight, flight, freeze, feign death, cry for help, & energy regulator. The dimensions taken into account are: (i) Heal the traumatic injuries who are still bleeding, (ii) Develop the systems that never received the security, attention, and affection they needed. (iii) Update the parts that stayed stuck in the past, ignoring for too long that they are out of danger now. Through the Present Part and its caregiving skills, InCorporer method enables a balanced, soothed, and collaborative personality system. To be as integrative as possible, InCorporer method has been designed according to several fields of research, such as structural dissociation theory, attachment theory, and information processing theory. In this paper, the author presents how the internal caregiver is developed and trained to heal all the different parts/subsystems of our clients through mindful attention and reflex movement integration.

Keywords: PTSD, attachment, dissociation, part work

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Authors: Virginia Venturini, Elisabet Walker, Aylen Carrasco-Millan

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Latin America stands at the front of climate change impacts, with forecasts projecting accelerated temperature and sea level rises compared to the global average. These changes are set to trigger a cascade of effects, including coastal retreat, intensified droughts in some nations, and heightened flood risks in others. In Argentina, wildfires historically affected forests, but since 2004, wetland fires have emerged as a pressing concern. By 2021, the wetlands of the Paraná River faced a dangerous situation. In fact, during the year 2021, a high-risk scenario was naturally formed in the wetlands of the Paraná River, in Argentina. Very low water levels in the rivers, and excessive standing dead plant material (fuel), triggered most of the fires recorded in the vast wetland region of the Paraná during 2020-2021. During 2008 fire events devastated nearly 15% of the Paraná Delta, and by late 2021 new fires burned more than 300,000 ha of these same wetlands. Therefore, the goal of this work is to explore remote sensing tools to monitor environmental conditions and the severity of prescribed burns in the Paraná River wetlands. Thus, two prescribed burning experiments were carried out in the study area (31°40’ 05’’ S, 60° 34’ 40’’ W) during September 2023. The first experiment was carried out on Sept. 13th, in a plot of 0.5 ha which dominant vegetation were Echinochloa sp., and Thalia, while the second trial was done on Sept 29th in a plot of 0.7 ha, next to the first burned parcel; here the dominant vegetation species were Echinochloa sp. and Solanum glaucophyllum. Field campaigns were conducted between September 8th and November 8th to assess the severity of the prescribed burns. Flight surveys were conducted utilizing a DJI® Inspire II drone equipped with a Sentera® NDVI camera. Then, burn severity was quantified by analyzing images captured by the Sentera camera along with data from the Sentinel 2 satellite mission. This involved subtracting the NDVI images obtained before and after the burn experiments. The results from both data sources demonstrate a highly heterogeneous impact of fire within the patch. Mean severity values obtained with drone NDVI images of the first experience were about 0.16 and 0.18 with Sentinel images. For the second experiment, mean values obtained with the drone were approximately 0.17 and 0.16 with Sentinel images. Thus, most of the pixels showed low fire severity and only a few pixels presented moderated burn severity, based on the wildfire scale. The undisturbed plots maintained consistent mean NDVI values throughout the experiments. Moreover, the severity assessment of each experiment revealed that the vegetation was not completely dry, despite experiencing extreme drought conditions.

Keywords: prescribed-burn, severity, NDVI, wetlands

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Authors: Daniel Fundi Murithi

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Data from economic, social, clinical, and industrial studies are in some way incomplete or incorrect due to censoring. Such data may have adverse effects if used in the estimation problem. We propose the use of Maximum Likelihood Estimation (MLE) under a progressive type-II censoring scheme to remedy this problem. In particular, maximum likelihood estimates (MLEs) for the location (µ) and scale (λ) parameters of two Parameter Rayleigh distribution are realized under a progressive type-II censoring scheme using the Expectation-Maximization (EM) and the Newton-Raphson (NR) algorithms. These algorithms are used comparatively because they iteratively produce satisfactory results in the estimation problem. The progressively type-II censoring scheme is used because it allows the removal of test units before the termination of the experiment. Approximate asymptotic variances and confidence intervals for the location and scale parameters are derived/constructed. The efficiency of EM and the NR algorithms is compared given root mean squared error (RMSE), bias, and the coverage rate. The simulation study showed that in most sets of simulation cases, the estimates obtained using the Expectation-maximization algorithm had small biases, small variances, narrower/small confidence intervals width, and small root of mean squared error compared to those generated via the Newton-Raphson (NR) algorithm. Further, the analysis of a real-life data set (data from simple experimental trials) showed that the Expectation-Maximization (EM) algorithm performs better compared to Newton-Raphson (NR) algorithm in all simulation cases under the progressive type-II censoring scheme.

Keywords: expectation-maximization algorithm, maximum likelihood estimation, Newton-Raphson method, two-parameter Rayleigh distribution, progressive type-II censoring

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Authors: Sadam Alwadi

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Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

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Authors: P. Jayashree, S. Rajkumar

Abstract:

With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

Abstract:

This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

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Authors: Agah Tugrul Korucu

Abstract:

Significant changes have taken place for the better in the bulk of information and in the use of technology available in the field of education induced by technological changes in the 21st century. It is mainly the job of the teachers and pre-service teachers to integrate information and communication technologies into education by means of conveying the use of technology to individuals. While the pre-service teachers are conducting lessons by using technology, the methods they have developed are important factors for the requirements of the lesson and for the satisfaction levels of the students. The study of this study is to examine the satisfaction levels of pre-service teachers as regards e-learning in a technological environment in which there are lesson activities conducted through an online learning environment in terms of various variables. The study group of the research is composed of 156 pre-service teachers that were students in the departments of Computer and Teaching Technologies, Art Teaching and Pre-school Teaching in the academic year of 2014 - 2015. The qualitative research method was adopted for this study; the scanning model was employed in collecting the data. “The Satisfaction Scale regarding the E-learning Process”, developed by Gülbahar, and the personal information form, which was developed by the researcher, were used as means of collecting the data. Cronbach α reliability coefficient, which is the internal consistency coefficient of the scale, is 0.91. SPSS computerized statistical package program and the techniques of medium, standard deviation, percentage, correlation, t-test and variance analysis were used in the analysis of the data.

Keywords: online learning environment, integration of information technologies, e-learning, e-learning satisfaction, pre-service teachers

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Authors: Usriatur Rohma, Adji Achmad Rinaldo Fernandes

Abstract:

Nonparametric path analysis is a statistical method that does not rely on the assumption that the curve is known. The purpose of this study is to determine the best nonparametric truncated spline path function between linear and quadratic polynomial degrees with 1, 2, and 3-knot points and to determine the significance of estimating the best nonparametric truncated spline path function in the model of the effect of population migration and agricultural economic growth on rural poverty through the variable unemployment rate using the t-test statistic at the jackknife resampling stage. The data used in this study are secondary data obtained from statistical publications. The results showed that the best model of nonparametric truncated spline path analysis is quadratic polynomial degree with 3-knot points. In addition, the significance of the best-truncated spline nonparametric path function estimation using jackknife resampling shows that all exogenous variables have a significant influence on the endogenous variables.

Keywords: nonparametric path analysis, truncated spline, linear, quadratic, rural poverty, jackknife resampling

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Authors: Nordila Ahmad, Thamer Mohammad, Bruce W. Melville, Zuliziana Suif

Abstract:

Current methods for predicting local scour at wide bridge piers, were developed on the basis of laboratory studies and very limited scour prediction were tested with field data. Laboratory wide pier scour equation from previous findings with field data were presented. A wide range of field data were used and it consists of both live-bed and clear-water scour. A method for assessing the quality of the data was developed and applied to the data set. Three other wide pier-scour equations from the literature were used to compare the performance of each predictive method. The best-performing scour equation were analyzed using statistical analysis. Comparisons of computed and observed scour depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and RMSE value when compared with the large amount of laboratory and field data.

Keywords: field data, local scour, scour equation, wide piers

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Authors: Maizatulnisa Othman, Mohamad Bukhari, Zahurin Halim, Souad A. Muhammad, Khalisani Khalid

Abstract:

Sandwich structure composites produced by epoxy core and aluminium skin were developed as potential building materials. Interface bonding between core and skin was controlled by varying kenaf content. Five different weight percentage of kenaf loading ranging from 10 wt% to 50 wt% were employed in the core manufacturing in order to study the mechanical properties of the sandwich composite. Properties of skin aluminium with epoxy were found to be affected by drying time of the adhesive. Mechanical behavior of manufactured sandwich composites in relation with properties of constituent materials was studied. It was found that 30 wt% of kenaf loading contributed to increase the flexural strength and flexural modulus up to 102 MPa and 32 Gpa, respectively. Analysis were done on the flatwise and edgewise compression test. For flatwise test, it was found that 30 wt% of fiber loading could withstand maximum force until 250 kN, with compressive strength results at 96.94 MPa. However, at edgewise compression test, the sandwich composite with same fiber loading only can withstand 31 kN of the maximum load with 62 MPa of compressive strength results.

Keywords: sandwich structure composite, epoxy, aluminium, kenaf fiber

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Authors: Andreia Guimaraes Farnese, Mateus Fernandes Reu Urban, Leandro Procopio, Renato Zangaro, Regiane Albertini

Abstract:

Senescence changes include postural balance, inferring the risk of falls, and can lead to fractures, bedridden, and the risk of death. Physical activity, e.g., cardiovascular exercises, is notable for improving balance due to brain cell stimulations, but fine coordination exercises also elevate cell brain metabolism. This study aimed to verify whether the elderly person who performs fine motor activity has a balance similar to that of those who practice physical activity. The subjects were divided into three groups according to the activity practice: control group (CG) with seven participants for the sedentary individuals, motor coordination group (MCG) with six participants, and activity practitioner group (PAG) with eight participants. Data comparisons were from the Berg balance scale, Time up and Go test, and stabilometric analysis. Descriptive statistical and ANOVA analyses were performed for data analysis. The results reveal that including fine motor activities can improve the balance of the elderly and indirectly decrease the risk of falls.

Keywords: balance, barapodometer, coordination, elderly

Procedia PDF Downloads 159

Authors: Betul Taspinar, Eda O. Okur, Ismail Saracoglu, Ismail Okur, Ferruh Taspinar

Abstract:

Thoracic hyperkyphosis, is a well-known spinal phenomenon, refers to an excessive curvature (> 40 degrees) of the thoracic spine. The aim of this study was to explore the effectiveness of thrust manipulation on thoracic spine alignment. 31 young adults with hyperkyphosis diagnosed with Spinal Mouse® device were randomly assigned either thrust manipulation group (n=16, 11 female, 5 male) or sham manipulation group (n=15, 8 female, 7 male). Thrust and sham manipulations were performed by a blinded physiotherapist who is a certificated expert in musculoskeletal physiotherapy. Thoracic kyphosis degree was measured after the interventions via Spinal Mouse®. Wilcoxon test was used to analyse the data obtained before and after the manipulation for each group, whereas Mann-Whitney U test was used to compare the groups. The mean of baseline thoracic kyphosis degrees in thrust and sham groups were 50.69 o ± 7.73 and 48.27o ± 6.43, respectively. There was no statistically significant difference between groups in terms of initial thoracic kyphosis degrees (p=0.51). After the interventions, the mean of thoracic kyphosis degree in thrust and sham groups were measured as 44.06o ± 6.99 and 48.93o ± 6.57 respectively (p=0.03). There was no statistically significant difference between before and after interventions in sham group (p=0.33), while the mean of thoracic kyphosis degree in thrust group decreased significantly (p=0.00). Thrust manipulation can attenuate thoracic hyperkyphosis immediately in young adults by not using placebo effect. Manipulation might provide accurate proprioceptive (sensory) input to the spine joints and reduce kyphosis by restoring normal segment mobility. Therefore thoracic manipulation might be included in the physiotherapy programs to treat hyperkyphosis.

Keywords: hyperkyphosis, manual therapy, spinal mouse, physiotherapy

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

Abstract:

Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

Procedia PDF Downloads 542