Search results for: random generation

Authors: Min Wu, Shuming Shen, Xuhong Yang, Rencheng Tang

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Every year, numerous organic wastes from fiber byproducts of the wool textile industry, poor quality raw wools not fit for spinning, horns, nails and feathers from butchery are disposed. These wastes are abundant in keratin which is a renewable material. Wool fiber/keratin/PVA composites with different proportions were prepared in this study, and the influence of the proportions on their structure and properties were studied, aiming to understand the potential application of keratin in the field of biomedicine, degradable wrapper, and cosmetics film, and provide a new way to reuse keratin wastes. The urea / sodium sulfide / sodium dodecyl sulfate (SDS) method was used to dissolve the wool. After filtration and dialysis, the wool keratin solution was achieved. Then the keratin solution and polyvinal (PVA) solution were blended in different proportions, and the wool fibers cut into a certain length were cast into the blended solution. Thereby, various wool fiber/keratin/PVA composite films with different proportions were formed through pouring the solution into a flat box and drying at room temperature. The surface morphology, molecular structure, and mechanical property of the composite films were studied. The results showed that, there are α-helix structure, β-sheet and random coil conformations in the pure keratin film, as well as in the wool fiber. Compared with wool fiber, the crystallinity of keratin decreased. PVA can obviously improve the mechanical property of the blended film. When the blended ratio of keratin and PVA is 20:80, the mechanical property of the blended film is greatly improved. The composite films with 8%-16% of wool fibers have better flexibility than those without wool fibers.

Keywords: composite film, keratin, mechanical property, morphological structure, PVA, wool fiber

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Authors: M. Dyah Ayu Yuli, S. Faisal Dhio, P. Johandi, P. Muhammad Sofyan

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Pulp and paper mills generate various quantities of energy-rich biomass as wastes, depending on technological level, pulp and paper grades and wood quality. These wastes are produced in all stages of the process: wood preparation, pulp and paper manufacture, chemical recovery, recycled paper processing, waste water treatment. Energy recovery from wastes of different origin has become a generally accepted alternative to their disposal. Pulp and paper industry expresses an interest in adapting and integrating advanced biomass energy conversion technologies into its mill operations using Fluidized Bed Combustion. Industrial adoption of these new technologies has the potential for higher efficiency, lower capital cost, and safer operation than conventional operations that burn fossil fuels for energy. Incineration with energy recovery has the advantage of hygienic disposal, volume reduction, and the recovery of thermal energy by means of steam or super heated water that can be used for heating and power generation.

Keywords: biomass, fluidized bed combustion, pulp and paper mills, waste

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Authors: A. S. Haruna, M. U. Tambawal, A. A. Salawu

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The psychological impact of peer influence on its individual group members, can make them resist HIV/AIDS counselling and testing. This study investigated the correlate of peer influence and resistance to HIV/AIDS counselling and testing among students in tertiary institutions in Kano state, Nigeria. To achieve this, three null hypotheses were postulated and tested. Cross-Sectional Survey Design was employed in which 1512 sample was selected from a student population of 104,841.Simple Random Sampling was used in the selection. A self-developed 20-item scale called Peer Influence and Psychological Resistance Inventory (PIPRI) was used for data collection. Pearson Product Moment Correlation (PPMCC) via test-retest method was applied to estimate a reliability coefficient of 0.86 for the scale. Data obtained was analyzed using t-test and PPMCC at 0.05 level of confidence. Results reveal 26.3% (397) of the respondents being influenced by their peer group, while 39.8% showed resistance. Also, the t-tests and PPMCC statistics were greater than their respective critical values. This shows that there was a significant gender difference in peer influence and a difference between peer influence and resistance to HIV/AIDS counselling and testing. However, a positive relationship between peer influence and resistance to HIV/AIDS counselling and testing was shown. A major recommendation offered suggests the use of reinforcement and social support for positive attitudes and maintenance of safe behaviour among students who patronize HIV/AIDS counselling.

Keywords: peer group influence, HIV/AIDS counselling and testing, psychological resistance, students

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Authors: K. Ivandic, F. Dodigovic, D. Stuhec, S. Strelec

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A characteristic value of certain geotechnical parameter results from an engineering assessment. Its selection has to be based on technical principles and standards of engineering practice. It has been shown that the results of engineering assessment of different authors for the same problem and input data are significantly dispersed. A survey was conducted in which participants had to estimate the force that causes a 10 cm displacement at the top of a axially in-situ compressed pile. Fifty experts from all over the world took part in it. The lowest estimated force value was 42% and the highest was 133% of measured force resulting from a mentioned static pile load test. These extreme values result in significantly different technical solutions to the same engineering task. In case of selecting a characteristic value of a geotechnical parameter the importance of the influence of an engineering assessment can be reduced by using statistical methods. An informative annex of Eurocode 1 prescribes the method of selecting the characteristic values of material properties. This is followed by Eurocode 7 with certain specificities linked to selecting characteristic values of geotechnical parameters. The paper shows the procedure of selecting characteristic values of a geotechnical parameter by using a statistical method with different initial conditions. The aim of the paper is to quantify an engineering assessment in the example of determining a characteristic value of a specific geotechnical parameter. It is assumed that this assessment is a random variable and that its statistical features will be determined. For this purpose, a survey research was conducted among relevant experts from the field of geotechnical engineering. Conclusively, the results of the survey and the application of statistical method were compared.

Keywords: characteristic values, engineering judgement, Eurocode 7, statistical methods

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Authors: Alireza Monzavi Chaleshtori, Mahnaz Aliakbari Dehkordi, Maryam Aliakbari, Solmaz Seyed Mostafaii

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Objective: Considering the growing obesity among children and the role of mother's psychological factors as well as the need to prevent childhood obesity, this study aimed to investigate the mediating role of mother's self-efficacy in the relationship between mother's stress and depression and child obesity. Method: For this purpose, in a descriptive-correlation study, 222 mothers and children aged 1 to 5 years in Tehran, who had the opportunity to answer an online questionnaire, were selected by random sampling and to the depression scales of the Kroenke and Spitzer Patient Health Questionnaire, Cohen's stress and Self-efficacy of Berkeley mothers answered. Pearson correlation test and path analysis were used for data analysis. Findings: The findings showed that maternal depression had an indirect and significant effect on child obesity, and the effect of stress and depression on child obesity was indirect and non-significant. Therefore, the model has a good fit with the research data, and stress and depression indirectly predicted child obesity with the mediating role of self-efficacy. Conclusion: The hypothesized model tested based on mother's stress and depression with the mediating role of mother's self-efficacy was a good model in explaining the prediction of child obesity. Based on the findings of this research, a practical framework can be provided to explain the psychological factors of the mother in relation to child obesity and its treatment.

Keywords: stress, self-efficacy, child obesity, depression

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Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

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The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Diego Giuseppe Romano, Gianvito Apuleo, Jiri Duda

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Mobility is one of the most important societal needs for amusement, business activities and health. Thus, transport needs are continuously increasing, with the consequent traffic congestion and pollution increase. Aeronautic effort aims at smarter infrastructures use and in introducing greener concepts. A possible solution to address the abovementioned topics is the development of Small Air Transport (SAT) system, able to guarantee operability from today underused airfields in an affordable and green way, helping meanwhile travel time reduction, too. In the framework of Horizon2020, EU (European Union) has funded the Clean Sky 2 SAT TA (Transverse Activity) initiative to address market innovations able to reduce SAT operational cost and environmental impact, ensuring good levels of operational safety. Nowadays, most of the key technologies to improve passenger comfort and to reduce community noise, DOC (Direct Operating Costs) and pilot workload for SAT have reached an intermediate level of maturity TRL (Technology Readiness Level) 3/4. Thus, the key technologies must be developed, validated and integrated on dedicated ground and flying aircraft demonstrators to reach higher TRL levels (5/6). Particularly, SAT TA focuses on the integration at aircraft level of the following technologies [1]: 1)    Low-cost composite wing box and engine nacelle using OoA (Out of Autoclave) technology, LRI (Liquid Resin Infusion) and advance automation process. 2) Innovative high lift devices, allowing aircraft operations from short airfields (< 800 m). 3) Affordable small aircraft manufacturing of metallic fuselage using FSW (Friction Stir Welding) and LMD (Laser Metal Deposition). 4)       Affordable fly-by-wire architecture for small aircraft (CS23 certification rules). 5) More electric systems replacing pneumatic and hydraulic systems (high voltage EPGDS -Electrical Power Generation and Distribution System-, hybrid de-ice system, landing gear and brakes). 6) Advanced avionics for small aircraft, reducing pilot workload. 7) Advanced cabin comfort with new interiors materials and more comfortable seats. 8) New generation of turboprop engine with reduced fuel consumption, emissions, noise and maintenance costs for 19 seats aircraft. (9) Alternative diesel engine for 9 seats commuter aircraft. To address abovementioned market innovations, two different platforms have been designed: Reference and Green aircraft. Reference aircraft is a virtual aircraft designed considering 2014 technologies with an existing engine assuring requested take-off power; Green aircraft is designed integrating the technologies addressed in Clean Sky 2. Preliminary integration of the proposed technologies shows an encouraging reduction of emissions and operational costs of small: about 20% CO₂ reduction, about 24% NO_x reduction, about 10 db (A) noise reduction at measurement point and about 25% DOC reduction. Detailed description of the performed studies, analyses and validations for each technology as well as the expected benefit at aircraft level are reported in the present paper.

Keywords: affordable, European, green, mobility, technologies development, travel time reduction

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Authors: S. K. Ashiquer Rahman

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the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem.

Keywords: hourly compensation, Unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model

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Authors: Brahim Brahmi, Mohammed Hamza Laraki, Mohammad Habibur Rahman, Islam M. Rasedul, M. Assad Uz-Zaman

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The humanoid robot, specifically the NAO robot must be able to provide a highly dynamic performance on the soccer field. Maintaining the balance of the humanoid robot during the required motion is considered as one of a challenging problems especially when the robot is subject to external disturbances, as contact with other robots. In this paper, a dynamic controller is proposed in order to ensure a robust walking (stabilization) and to improve the dynamic balance of the robot during its contact with the environment (external disturbances). The generation of the trajectory of the center of mass (CoM) is done by a model predictive controller (MPC) conjoined with zero moment point (ZMP) technique. Taking into account the properties of the rotational dynamics of the whole-body system, a modified previous control mixed with feedback control is employed to manage the angular momentum and the CoM’s acceleration, respectively. This latter is dedicated to provide a robust gait of the robot in the presence of the external disturbances. Simulation results are presented to show the feasibility of the proposed strategy.

Keywords: preview control, Nao robot, model predictive control

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Authors: Laila Khaled Almawaldi, Hiew Khai Hang, Sugumaran A. l. Nallusamy

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Legacy systems are crucial for organizations, but their intricacy and lack of documentation pose challenges for maintenance and enhancement. Redocumentation of legacy systems is vital for automatically or semi-automatically creating documentation for software lacking sufficient records. It aims to enhance system understandability, maintainability, and knowledge transfer. However, existing redocumentation methods need improvement in data processing performance and document generation efficiency. This stems from the necessity to efficiently handle the extensive and complex code of legacy systems. This paper proposes a method for semi-automatic legacy system re-documentation using semantic parallel processing and ontology. Leveraging parallel processing and ontology addresses current challenges by distributing the workload and creating documentation with logically interconnected data. The paper outlines challenges in legacy system redocumentation and suggests a method of redocumentation using parallel processing and ontology for improved efficiency and effectiveness.

Keywords: legacy systems, redocumentation, big data analysis, parallel processing

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Authors: Jamuna Rajeswaran

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In the past two decades, with a population of more than a billion. India is passing through a major socio-demographic and epidemiological transition with consequent changes in health scenario. TBI constitute significant burden on health care resources in India The impact on a person and family can be devastating. Patients with TBI experience persistent cognitive deficits, emotional changes, which contribute to the disruption of life activities. The recovery of TBI would be maximized by appropriate rehabilitation. Neurofeedback is an emerging neuroscience-based clinical application. Sixty patients were recruited for this study after obtaining informed consent. Rivermead Head Injury Follow-up Questionnaire, Rivermead Post Concussion Symptoms Questionnaire and Visual Analog Scale were used to assess the behavioral and symptomotolgy associated with post TBI. Neuropsychological assessment was carried out using NIMHANS neuropsychological battery 2004. The Intervention group received neurofeedback training and the waitlist group did not receive any treatment during this phase. Patients were allocated to intervention and waitlist group at random. There were 30 patients in each group. Patients were given 20 sessions of NFT Patients were trained on the O1 and O2 channels for alpha theta training. Each session was of 40 minutes duration with 5-6 sessions per week. The post-training assessment was carried out for the intervention group after 20 sessions of NFT. The waitlist group underwent assessment after one month. Results showed neurofeedback training is effective in ameliorating deficits in cognitive functions and quality of life in patients with TBI. Improvements were corroborated by the clinical interview with patients and significant others post NFT.

Keywords: assessment, rehabilitation, cognition, EEG neurofeedback

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Authors: Sujata Gupta Kedar, Fasiha Fayaz

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This paper presents various studies being carried out by various researchers globally on the attitude of lecturers towards the advent of information technology and e-learning. An effort has been made in this paper to study the various trends being presented by researchers and draw some general conclusions. These show the effect of the lecturer’s gender, age and educational background on their attitude towards the e-learning. Also the favorable attitude of teachers' towards using new technology in teaching will certainly make teachers use them in appropriate situations in teaching and thus measuring of teachers attitude towards using new technology in teaching is very much needed. The sample of 50 males and 50 females were studied from different colleges of Bangalore “Attitudes towards using new technology scale” by Dr. Rajasekar was used. It was seen that male and female had no significant difference in hardware and software use, whereas both had favorable attitude. And there was a significant difference at 1% level among female lecturers belonging to arts faculty. There is no significant difference between the gender and age, because higher the age lower the score is. Irrespective of teaching experience males had no significant difference, whereas females are significant at 1% level, which says that higher the teaching experience of lecturers less knowledge they have towards the use of ICT, as the younger generation is more expose to technology.

Keywords: e-learning, ICT, attitudes, lecturers, communication technology

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Authors: Muhamad Saiful Bahri Yusoff

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This study aimed to evaluate the construct, convergent, and discriminant validity of the Secondary School Stressor Questionnaire (3SQ) as well as to evaluate its internal consistency among adolescents in Malaysian secondary schools. A cross-sectional study was conducted on 700 secondary school students in five secondary schools. Stratified random sampling was used to select schools and participants. The confirmatory factor analysis was performed by AMOS to examine construct, convergent, and discriminant validity. The reliability analysis was performed by SPSS to determine internal consistency. The results showed that the original six-factor model with 44 items failed to achieve acceptable values of the goodness of fit indices, suggesting poor model fit. The new five-factor model of 3SQ with 22 items demonstrated acceptable level of goodness of fit indices to signify a model fit. The overall Cronbach’s alpha value for the new version 3SQ was 0.93, while the five constructs ranged from 0.68 to 0.94. The composite reliability values of each construct ranged between 0.68 and 0.93, indicating satisfactory to high level of convergent validity. Our study did not support the construct validity of the original version of 3SQ. We found the new version 3SQ showed more convincing evidence of validity and reliability to measure stressors of adolescents. Continued research is needed to verify and maximize the psychometric credentials of 3SQ across countries.

Keywords: stressors, adolescents, secondary school students, 3SQ, psychometric properties

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Authors: Bahram Asghari Aghdam, Ali Mahjoub

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The purpose of this study is to evaluate the effect of emotional intelligence on the motivation and performance of East Azarbaijan the Red Crescent staff. In this study, EI is determined as the independent variable component of self awareness, self management, social awareness, and relations management, motivation and performance as dependent variables. The research method is descriptive-survey. In this study, simple random sampling method is used and research sample consists of 130 East Azarbaijan the Red Crescent staff that uses Cochran's formula 100 of them were selected and questionnaires were filled by them. Three types of questionnaires were used in this study for emotional intelligence, consisting of the Bradbury Travis and Jane Greaves standard questionnaire; and for motivation and performance a questionnaire is regulated by the researcher with help of professionals and experts in this field that consists of 33 questions about the motivation and 15 questions about performance and content validity were used to obtain the necessary credit. Reliability by using the Cronbach's alpha coefficient /948 was approved. Also, in this study to test the hypothesis of the Spearman correlation coefficient and linear regressions and determine fitness of variables' of structural equation modeling is used. The results show that emotional intelligence with coefficient /865, motivation and performance of in East Azerbaijan the Red Crescent employees has a positive effect. Based on Friedman Test ranking the most influence in motivation and performance of staff in respondents' opinion is in order of self-awareness, relations management, social awareness and self-management.

Keywords: emotional intelligence, self-awareness, self-management, social awareness, relations management, motivation, performance

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Authors: Debalkie Demissie Addisu, Ejigu Alemu Abebe, Tsegay Tensay Assefa

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This study examines the indirect effect of servant leadership on organizational citizenship behavior through perceptions of organizational politics moderated by political skill. This study reports the responses of 321 respondents from six federal public service organizations in Ethiopia. A multi-stage random sampling procedure was employed to select the sampled federal public service organizations. To test hypotheses, the study employed structural equation modeling using AMOS version-26 software. The result revealed that all direct effects have a significant effect. Specifically, servant leadership has a positive effect on organizational citizenship behavior. Likewise, servant leadership has a negative effect on perceptions of organizational politics. Also, a perception of organizational politics has a negative effect on organizational citizenship behavior. Moreover, perceptions of organizational politics competitively mediated the effect of servant leadership on organizational citizenship behavior. As well, political skill moderated the effect of perceptions of organizational politics on organizational citizenship behavior but not the indirect effect. To the best of our knowledge, no one else employs perceptions of organizational politics as a mediating effect between servant leadership and organizational citizenship behavior. Furthermore, we are not aware of anyone else employing political skill as a moderating role in the indirect effect of servant leadership on organizational citizenship behavior through perceptions of organizational politics.

Keywords: servant leadership, organizational citizenship behavior, perceptions of organizational politics, political skill, public service organization, Ethiopia

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Authors: Janis E. Campbell

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Most of what is known about complementary, alternative or traditional medicine (CATM) in the United States today is known from either the National Health Interview Survey a cross-sectional survey with a few questions or from small cross-sectional or cohort studies with specific populations. The broad geographical distribution in CATM use or providers is not known. For this project, we used geospatial cluster analysis to determine if there were clusters of CATM provider by county in the US. In this analysis, we used the National Provider Index to determine the geographic distribution of providers in the US. Of the 215,769 CAMT providers 211,603 resided in the contiguous US: Acupuncturist (26,563); Art, Poetry, Music and Dance Therapist (2,752); Chiropractor (89,514); Doula/Midwife (3,535); Exercise (507); Homeopath (380); Massage Therapist (36,540); Mechanotherapist (1,888); Naprapath (146); Naturopath (4,782); Nutrition (42,036); Reflexologist (522); Religious (2,438). ESRI® spatial autocorrelation was used to determine if the geographic location of CATM providers were random or clustered. For global analysis, we used Getis-Ord General G and for Local Indicators of Spatial Associations with an Optimized Hot Spot Analysis using an alpha of 0.05. Overall, CATM providers were clustered with both low and high. With Chiropractors, focusing in the Midwest, religious providers having very small clusters in the central US, and other types of CAMT focused in the northwest and west coast, Colorado and New Mexico, the great lakes areas and Florida. We will discuss some of the implications of this study, including associations with health, economic, social, and political systems.

Keywords: complementary medicine, alternative medicine, geospatial, United States

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Authors: Manuela Nayantara Jeyaraj

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'Digital Divide' is a concept that has existed in this paradigm ever since the discovery of the first-generation technologies. Before the turn of the century, it was basically used to describe the gap between those with telephone communication access and those without it. At present, it is plainly descriptive in itself to illustrate the cavity among those with Internet access and those without. Though the concept of digital divide has been merely lying in sight for as long as time itself, the friction it caused has not yet been fully realized to solve major crisis situations. Unlike well-developed countries, Sri Lanka is still in the verge of moving farther away from a developing country in the race towards reaching a developed state. Access to technological resources varies from region to region, even within the island itself, with one region having a considerable percentage of its community exposed to the Internet and its related technologies, and the other unaware of such. Thus, this paper intends to analyze the roots for the still-extant gap instigated based on the concept of ‘Digital Divide’ and explores the plausible potentials that could be brought about by narrowing this prevailing percentage among the population, specifically entrenching the advantages reaped towards an economic augmentation and culture or lifestyle revolution on the path towards development.

Keywords: communication, digital divide, society, Sri Lanka

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Claudia Troccoli

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Childbearing constitutes one of the key factors affecting labour market differences between men and women, accounting for almost a quarter of the gender wage gap. Family leave policies, such as maternity, paternity, and parental leave, represent potential key policy tools to address these inequalities, as they can promote mothers' job continuity and career progression. This paper analyses four major reforms implemented in Finland between the 1960s and the early 1980s. It studies the effects of these maternity and parental leave extensions on mothers' short- and long-run labour market outcomes. Eligibility to longer leave was determined on the basis of the child's date of birth. Therefore, estimation of the causal effects of the reforms is possible by exploiting random variation in children's birthdates and comparing the outcomes of mothers giving birth just before and just after the reform cutoff date. Overall, the three maternity leave reforms did not significantly improve mothers' earnings or employment rates. On the contrary, the estimates, although imprecise, seem to indicate negative effects on women's labour market outcomes. The extension of parental leave is, on the other hand, the only reform that improved mothers' short- and long-term labour market outcomes, both in terms of earnings and employment rate. At the same time, fathers appeared to be negatively affected by the reform. These results provide suggestive evidence that shareable parental leave might have more beneficial effects on mothers' job continuity, as it weakens the connotation of childcare as a task reserved for mothers.

Keywords: family policies, Finland, maternal labour market outcomes, maternity leave

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Authors: Tahere Fazilat

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Caspian red deer or maral (Cervus elaphus maral) is the largest type of deer in iran. Maral in the past has lived in the north forests of Iran from the Caspian sea coast, Alborz mountains chain and oak forest of Zagros margin from the Azarbaijan up to fars province. However, the generation of them was completely destroyed in the north west and west of Iran. According to reports about 50 years and out of reach of humans. In the present studies, data were collected from 2004 to 2014 in the Mazandaran state Hyrcanian forest by means of guard of environment and justiciary office of department of environment of Mazandaran in this process the all arrested illegal hunting of red deer and the population census, estimation and the correlation of these data was assayed. We provide a first evaluation of how suitable these methods are by comparing the results with population estimates obtained using cohort analysis, and by analyzing the within-season variation in number of seen deer. The data gave us the future of red deer in northern forest of Iran and the results of policy of department of environment in Iran in red deer conservation.

Keywords: illegal hunting, red deer, census, concervation

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Authors: Kasbparast Mehdi, Hassani Zainab

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Aim: The purpose of this research was to investigate the effectiveness of therapeutical sensorimotor exercise. The statistical population of women who were diagnosed with patellofemoral pain syndrome by a doctor and were between the ages of 35 and 45 and registered for the first time in a sports club in the 4th district of Tehran, 30 people by random sampling and according to The include and exclude criteria were selected and divided into 2 equal control and experimental and homogeneous groups (in terms of height, weight and BMI).In both control and experimental groups, the pain was measured using a Visual Analog Scale(VAS) functionality was measured using the step-down test and quality of life was measured using a World Health Organization Quality of Life Scale (WHOQOL-BREF) (pre-test). Then, only the experimental group performed sensorimotor exercises for 12 weeks and 3 sessions each week, a total of 24 sessions and each session for 1 hour, and during this period, the control group only continued their daily activities. After the end of the training period, the desired factors were evaluated again (post-test) in the same way as the pre-test was done for them (experimental group and control group), with the same quality. Findings: The statistical results showed that in the experimental group, the amount of pain, function and quality of life had a statistical improvement (P≤0.05). Conclusion: In general conclusion, it can be stated that using sensorimotor exercises not only improved functionality and quality of life but also reduced the amount of pain in people with patellofemoral pain syndrome.

Keywords: pain, PFPS, sensori motor training, functionality

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Agnes Havril

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The aim of this paper is to introduce some partial findings of an ongoing research project which is investigating the improvement of intercultural competence of Saudi female university students in English as a Second Language academic environment at the multicultural Jazan University. Since previous research results support the idea that this university generation has the desire to become interculturally or globally competent university students, the present-day investigation is focusing on the assessment of Saudi-specific cultural terms and intercultural competence components in comparison with the Anglo-Saxon oriented western perspective of intercultural competence theories and models. On this stage of the research quantitative research methodology is applied and a survey is being conducted among the female university students in different academic specializations. This paper discusses some empirical data with the aim of identifying and evaluating certain supplementary aspects of intercultural dimensions and components of the intercultural competence construct. The research results also highlight several gender issues in the gender separated higher education in the Kingdom of Saudi Arabia.

Keywords: gender separation, globally competent university student, intercultural competence, intercultural competence construct, higher education

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Authors: Musthaya Patchanee

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The aim of this research is to study potential factors relating to the decision of return migration of Myanmar migrant workers in Prachuap Khiri Khan Province by conducting a random sampling of 400 people aged between 15-59 who migrated from Myanmar. The information collected through interviews was analyzed to find a percentage and mean using the Stepwise Multiple Regression Analysis. The results have shown that 33.25% of Myanmar migrant workers want to return to their home country within the next 1-5 years, 46.25%, in 6-10 years and the rest, in over 10 years. The factors relating to such decision can be concluded that the scale of the decision of return migration has a positive relationship with a statistical significance at 0.05 with a conformity with friends and relatives (r=0.886), a relationship with family and community (r=0.782), possession of land in hometown (r=0.756) and educational level (r=0.699). However, the factor of property possession in Prachuap Khiri Khan is the only factor with a high negative relationship (r=0.-537). From the Stepwise Multiple Regression Analysis, the results have shown that the conformity with friends and relatives and educational level factors are influential to the decision of return migration of Myanmar migrant workers in Prachuap Khiri Khan Province, which can predict the decision at 86.60% and the multiple regression equation from the analysis is Y= 6.744+1.198 conformity + 0.647 education.

Keywords: decision of return migration, factors of return migration, Myanmar migrant workers, Prachuap Khiri Khan Province

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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Authors: Samson Olusegun Apantaku, Adetayo K. Aromolaran, Giyatt Hammed

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The study assessed the use of participatory research methods among Federal University of Agriculture Abeokuta, Nigeria (FUNAAB) researchers. Simple random sampling technique was used to select one hundred and twenty respondents from the study area. Data were collected using a questionnaire. Data collected were subjected to descriptive and inferential statistical analyses. Results showed that 75.8% of the respondents were males while only 21.3% were female. The mean age of the respondents was 38.8 years and most (77.5%) of them were married. 15% of the respondents were in professorial cadre, 21.7% and 20% of the respondents were senior lecturers/fellow and lecturer/research fellow I&II respectively. The results further revealed that 93.3% of the respondents were aware of participatory research methods and 82.5% of the respondents have utilized it before. The average period of usage was 2.7 years and participation by consultation (86.7%) and interactive participation (76.7%) were mostly used. Most (94.2%) indicated that fund was the major hindrance to the use of participatory research methods. The result of correlation analysis showed that there was significant relationship between the years of research experience, designation post (status) of the respondents and usage of participatory research methods (r = 0.034, 0.031, p < 0.05). The study concluded that most of the researchers were aware of and used participatory research methods, which could influence the quality of their research or make it acceptable to the end users. It was recommended that more funds should be made available and accessible for participatory research. All researchers should be trained and encouraged to make use of participatory research methods in their research activities so as to achieve effective research and capacity building that could enhance adoption of technologies and increase agricultural production in the country. Farmers’ capacity to participate in agricultural research should also be enhanced.

Keywords: participatory research, participatory research methods, awareness, utilization

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Authors: Arash Esmaeili, Zhibang Liu, Yang Xiang, Jimmy Yun, Lei Shao

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A high-pressure carbon dioxide (CO₂) absorption from a specific off-gas in a conventional column has been evaluated for the environmental concerns by the Aspen HYSYS simulator using a wide range of single absorbents and piperazine (PZ) blended solutions to estimate the outlet CO₂ concentration, CO₂ loading, reboiler power supply, and regeneration heat duty to choose the most efficient solution in terms of CO₂ removal and required heat duty. The property package, which is compatible with all applied solutions for the simulation in this study, estimates the properties based on the electrolyte non-random two-liquid (E-NRTL) model for electrolyte thermodynamics and Peng-Robinson equation of state for vapor phase and liquid hydrocarbon phase properties. The results of the simulation indicate that piperazine, in addition to the mixture of piperazine and monoethanolamine (MEA), demands the highest regeneration heat duty compared with other studied single and blended amine solutions, respectively. The blended amine solutions with the lowest PZ concentrations (5wt% and 10wt%) were considered and compared to reduce the cost of the process, among which the blended solution of 10wt%PZ+35wt%MDEA (methyldiethanolamine) was found as the most appropriate solution in terms of CO₂ content in the outlet gas, rich-CO₂ loading, and regeneration heat duty.

Keywords: absorption, amine solutions, aspen HYSYS, CO₂ loading, piperazine, regeneration heat duty

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Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

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Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

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Authors: Mohsen Hajian Foroushani, Samane Maroufi, Rasoul Khayyam Nekouei, Veena Sahajwalla

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Lithium (Li) metal possesses outstanding characteristics, with the highest specific capacity (3860 mAh g-1) and the lowest electrochemical potential (-3.04 V vs. SHE) among available metal anodes. The collaborative impact of Li and sulfur, featuring a specific capacity of 1670 mAh g-1, positions Li–S batteries (LSBs) as highly promising contenders for the next generation of high-energy-density batteries. However, the comprehensive commercialization of LSBs relies on addressing various challenges inherent to these batteries. One of the most formidable hurdles is the widespread issue of Li dendrite nucleation and growth on the anode surface, stemming from the inherent instability of the solid electrolyte interphase (SEI) layer. In this study, we employed a Zn-based coating derived from waste materials, significantly enhancing the performance of the symmetrical cell across various current densities. The applied coating not only improved the cyclability of the cell by more than fourfold but also reduced the charge transfer resistance from over 300 to less than 10 before cycling. Examination through SEM micrographs of both samples revealed the successful suppression of Li dendrites by the applied coating.

Keywords: Li-S batteries, Li dendrite, sustainability, Li anode

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