Search results for: National database

Authors: Florenda B. Cardinoza

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This study was conducted to determine the determinants of Grade III and grade VI pupils’ performance in the National Achievement Test in the Division of Cavite City, School Year 2011-2012. Specifically, the research aimed to: (1) describe the demographic profile of the respondents in terms of age, sex, birth order, family size, family income, and occupation of parents; (2) determine the level of attitude towards NAT; and (3) describe the degree of relationship between the following variables: school support, teachers’ support, and lastly family support for the pupils’ performance in 2012 NAT. The study used the descriptive-correlation research method to investigate the determinants of pupils’ performance in the National Achievement Test of Public Elementary Schools in the Division of Cavite City. The instrument used in data gathering was a self-structured survey. The NAT result for SY 2011-2012 provided by NETRC and DepEd Cavite City was also utilized. The statistical tools used to process and analyze the data were frequency distribution, percentage, mean, standard deviation, Kruskall Wallis, Mann-Whitney, t-test for independent samples, One-way ANOVA, and Spearman Rank Correlational Coefficient. Results revealed that there were more female students than males in the Division of Cavite City; out of 659 respondents, 345 were 11 years old and above; 390 were females; 283 were categorized as first child in the family; 371 of the respondents were from small family; 327 had Php5000 and below family income; 450 of the fathers’ respondents were non professionals; and 431 of the mothers respondents had no occupation. The attitude towards NAT, with a mean of 1.65 and SD of .485, shows that respondents considered NAT important. The school support towards NAT, with a mean of 1.89 and SD of .520, shows that respondents received school support. The pupils had a very high attitude towards teachers’ support in NAT with a mean of 1.60 and SD of .572. Family support, with t-test of 16.201 with a p-value of 0.006, shows significant at 5 percent level. Thus, the determinants of pupils’ performance in NAT in terms of family support for NAT preparation is not significant according to their family income. The grade level, with the t-test is 4.420 and a p-value of 0.000, is significant at 5 percent level. Therefore, the determinants of pupils’ performance in NAT in terms of grade level for NAT preparation vary according to their grade level. For the determinants of pupils’ performance of NAT sample test for attitude towards NAT, school support, teachers’ support, and family support were noted highly significant with a p value of 0.000.

Keywords: achievement, determinants, national, performance, public, pupils', test

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Authors: E. N. R. de Silva

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The main purpose of this research is to set a policy framework for establishing a legal, institutional and social infrastructure that enhances the welfare, health, safety and economic interest of the consumers in Sri Lanka. It will help to develop an approach to continuously and successfully advocate for a consumer protection legal reform agenda and also it is significant as it gives directions to create national consumer protection associations in Sri Lanka. The methodology adopted for this research is purely a qualitative approach and it is generally and specifically categorized. Generally, part of this research looked at the existing laws, regulations and how effective they are in order to protect consumers. It will analyze the consumer protection framework and specially, consumer protection enhanced by the public organizations in Japan. This research offers a model with methods and legal instruments to enforce advocacy group to enhance consumer welfare, also brings out reforms to be made in the national legal framework on consumer welfare.

Keywords: consumer protection association, consumer protection law, consumer welfare, legal framework

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Authors: Usman Dutse, Eldah Ephraim Buba, Dalhatu Sa’idu

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The popularity of foreign football leagues are getting a soaring in Africa. Nigerian youths are following these leagues with high sense of dedication and devotion. The paper examines the factors behind the growing popularity of foreign football league in Nigeria and its socio economic implications on the country. Primary data were largely used for the study and collected through the use of questionnaire and interview. The data collected were analysed with the use of descriptive and qualitative methods of analysis. The findings made from the analysis indicates that the reasons why foreign league is popular in Nigeria is because the quality of national league in Nigeria is poor, the matches are not mostly televised, corruption/match fixing is common; for the above mentioned reasons national football league become uninteresting compared to foreign leagues. It was also confirmed that the overwhelming popularity of foreign league has the following social effects: friendship and acquaintance are created between supporters of the same club via social media and viewing centres, it has increased the knowledge and awareness of youth about the economics and politics of international sports. However, it has also brewed rivalry between supporters of clubs, drugs are sold in viewing centres and it sometimes serves as a meeting point for miscreants and criminals. Some of the economic effects were also identified as follows: small entrepreneurs establish commercial viewing centres and they employ other supporting staff to operate. On the strength of the above findings, the following were recommended: There is the urgent need to reform our national league to an acceptable standard; improve the quality of the team, the facilities and media coverage of the matches. This might make Nigerians to channel some of the love for foreign leagues to the local leagues.

Keywords: foreign, league, socioeconomic, implications

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Authors: B. Gepts, E. Meex, E. Nuyts, E. Knaepen, G. Verbeeck

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The importance of resource efficiency and environmental impact assessment has raised the interest in knowing the amount of materials used in buildings. If no BIM model or energy performance certificate is available, material quantities can be obtained through an estimation or time-consuming calculation. For the interior wall area, no validated estimation method exists. However, in the case of environmental impact assessment or evaluating the existing building stock as future material banks, knowledge of the material quantities used in interior walls is indispensable. This paper presents a validated method for the estimation of the interior wall area for dwellings based on easy-to-collect building characteristics. A database of 4963 residential buildings spread all over Belgium is used. The data are collected through onsite measurements of the buildings during the construction phase (between mid-2010 and mid-2017). The interior wall area refers to the area of all interior walls in the building, including the inner leaf of exterior (party) walls, minus the area of windows and doors, unless mentioned otherwise. The two predictive modelling techniques used are 1) a (stepwise) linear regression and 2) a decision tree. The best estimation method is selected based on the best R² k-fold (5) fit. The research shows that the building volume is by far the most important variable to estimate the interior wall area. A stepwise regression based on building volume per building, building typology, and type of house provides the best fit, with R² k-fold (5) = 0.88. Although the best R² k-fold value is obtained when the other parameters ‘building typology’ and ‘type of house’ are included, the contribution of these variables can be seen as statistically significant but practically irrelevant. Thus, if these parameters are not available, a simplified estimation method based on only the volume of the building can also be applied (R² k-fold = 0.87). The robustness and precision of the method (output) are validated three times. Firstly, the prediction of the interior wall area is checked by means of alternative calculations of the building volume and of the interior wall area; thus, other definitions are applied to the same data. Secondly, the output is tested on an extension of the database, so it has the same definitions but on other data. Thirdly, the output is checked on an unrelated database with other definitions and other data. The validation of the estimation methods demonstrates that the methods remain accurate when underlying data are changed. The method can support environmental as well as economic dimensions of impact assessment, as it can be used in early design. As it allows the prediction of the amount of interior wall materials to be produced in the future or that might become available after demolition, the presented estimation method can be part of material flow analyses on input and on output.

Keywords: buildings as material banks, building stock, estimation method, interior wall area

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Authors: Rinyu Shei Mercy

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Protected areas are the potential areas for the development of ecotourism because of their biodiversity, landscapes, waterfalls, lakes, caves, salt lick and cultural heritage of local or indigenous people. These potentials have not yet been valorized, so this study will enable to investigate the evaluation and possibilities of valorization of ecotourism potentials in the Mbam and Djerem National Park. Hence, this was done by employing a combination of field observations, examination, data collection and evaluation, using a SWOT analysis. The SWOT provides an analysis to determine the strengths, weaknesses, opportunities and threats, and strategic suggestions for ecological planning. The study helps to determine an ecotouristic inventory and mapping of ecotourism potentials of the park, evaluate the degree of valorization of these potentials and the possibilities of valorization. Finally, the study has proven that the park has much natural potentials such as rivers, salt licks, waterfall and rapids, lakes, caves and rocks, etc. Also, from the study, it was realized that as concerns the degree of valorization of these ecotourism potentials, 50% of the population visit the salt lick of Pkayere because it’s a biodiversity hotspot and rich in mineral salt attracting a lot of animals and the least is the lake Miyere with 1% due to the fact that it is sacred. Moreover, from the results, there are possibilities that these potentials can be valorized and put into use because of their attractive nature such as creating good roads and bridges, good infrastructural facilities, good communication network etc. So, the study recommends that, in this process, MINTOUR, WCS, tour operators must interact sufficiently in order to develop the potential interest to ecotourism, ecocultural tourism and scientific tourism.

Keywords: ecotourism, national park Mbam and Djerem, valorization of biodiversity, protected areas of Cameroon

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Authors: Nuo Xu, Sijing Chen

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Background: Childbirth is considered a critical traumatic event throughout our lives, positively or negatively impacting the mother's physiology, psychology, and even the whole family. Adverse birth experiences, such as labor pain, anxiety, and fear can negatively impact the mother. Studies had shown that the immersive nature of VR can distract attention from pain and increase focus on interventions for pain relief. However, the existing studies that applied VR to maternal delivery were still in their infancy and showed disparate results, and the small sample size is not representative, so this review analyzed the effects of VR in labor, such as on maternal pain and anxiety, with a view to providing a basis for future applications. Search strategy: We searched Pubmed, Embase, Web of Science, the Cochrane Library, CINAHL, China National Knowledge Infrastructure, Wan-Fang database from the building to November 17, 2021. Selection Criteria: Randomized controlled trials (RCTs) that intervened the pregnant women aged 18-35 years with gestational >34 weeks and without complications with VR technology were contained within this review. Data Collection and Analysis: Two researchers completed the study selection, data extraction, and assessment of study quality. For quantitative data we used MD or SMD, and RR (risk ratio) for qualitative data. Random-effects model and 95% confidence interval (95% CI) were used. Main Results: 12 studies were included. Using VR could relieve pain during labor (MD=-1.81, 95% CI (-2.04, -1.57), P< 0.00001) and active period (SMD=-0.41, 95% CI (-0.68, -0.14), P= 0.003), reduce anxiety (SMD=-1.39, 95% CI (-1.99, -0.78), P< 0.00001) and improve satisfaction (RR = 1.32; 95% CI (1.10, 1.59); P = 0.003), but the effect on the duration of first (SMD=-1.12, 95% CI (-2.38, 0.13), P=0.08) and second (SMD=-0.22, 95% CI (-0.67, 0.24), P=0.35) stage of labor was not statistically significant. Conclusions: Compared with conventional care, VR technology can relieve labor pain and anxiety and improve satisfaction. However, extensive experimental validation is still needed.

Keywords: virtual reality, delivery, labor pain, anxiety, meta-analysis, systematic review

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Authors: Junyu Chen, Peng Xu

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In the context of global efforts to enhance building energy efficiency, accurate thermal load forecasting is crucial for both device sizing and predictive control. Variable Refrigerant Flow (VRF) systems are widely used in buildings around the world, yet VRF zonal load prediction has received limited attention. Due to differences between VRF zones in building-level prediction methods, zone-level load forecasting could significantly enhance accuracy. Given that modern VRF systems generate high-quality data, this paper introduces transfer learning to leverage this data and further improve prediction performance. This framework also addresses the challenge of predicting load for building zones with no historical data, offering greater accuracy and usability compared to pure white-box models. The study first establishes an initial variable set of VRF zonal building loads and generates a foundational white-box database using EnergyPlus. Key variables for VRF zonal loads are identified using methods including SRRC, PRCC, and Random Forest. XGBoost and LSTM are employed to generate pre-trained black-box models based on the white-box database. Finally, real-world data is incorporated into the pre-trained model using transfer learning to enhance its performance in operational buildings. In this paper, zone-level load prediction was integrated with transfer learning, and a framework was proposed to improve the accuracy and applicability of VRF zonal load prediction.

Keywords: zonal load prediction, variable refrigerant flow (VRF) system, transfer learning, energyplus

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Authors: Jerzy Banski

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Small towns represent a key element of settlement structure and serve a number of important functions associated with the servicing of rural areas that surround them. It is in light of this that scientific studies have paid considerable attention to the functional structure of centers of this kind, as well as the relationships with both surrounding rural areas and other urban centers. But a preliminary to such research has typically involved attempts at classifying the urban centers themselves, with this also assisting with the planning and shaping of development policy on different spatial scales. The purpose of the work is to test out the methods underpinning three different classifications of small urban centers, as well as to offer a preliminary interpretation of the outcomes obtained. Research took in 722 settlement units in Poland, granted town rights and populated by fewer than 20,000 inhabitants. A morphologically-based classification making reference to the database of topographic objects as regards land cover within the administrative boundaries of towns and cities was carried out, and it proved possible to distinguish the categories of “housing-estate”, industrial and R&R towns, as well as towns characterized by dichotomy. Equally, a functional/morphological approach taken with the same database allowed for the identification – via an alternative method – of three main categories of small towns (i.e., the monofunctional, multifunctional or oligo functional), which could then be described in far greater detail. A third, multi-criterion classification made simultaneous reference to the conditioning of a structural, a location-related, and an administrative hierarchy-related nature, allowing for distinctions to be drawn between small towns in 9 different categories. The results obtained allow for multifaceted analysis and interpretation of the geographical differentiation characterizing the distribution of Poland’s urban centers across space in the country.

Keywords: small towns, classification, local planning, Poland

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Etibar Guliyev, Durdana Jafarli

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The breakdown of the Soviet Union in the early 1990s and the 9/11 attacks resulted in the global changes created a totally new geopolitical situation for the Muslim populated republics of the former Soviet Union. Located between great powers such as China and Russia, as well as theocratic states like Iran and Afghanistan, the newly independent Central Asian states were facing a dilemma to choose a new politico-ideological course for development. Policies dubbed Perestroyka and Glasnost leading to the collapse of the world’s once superpower brought about a considerable rise in the national and religious self-consciousness of the Muslim population of the USSR where the religion was prohibited under the strict communist rule. Moreover, the religious movements prohibited during the Soviet era acted as a part of national straggle to gain their freedom from Moscow. The policies adopted by the Central Asian countries to manage the religious revival and extremism in their countries vary dramatically from each other. As Kazakhstan and Kyrgyzstan are located between Russia and China and hosting a considerable number of the Russian population, these countries treated Islamic revival more tolerantly trying benefit from it in the nation-building process. The importance of the topic could be explained with the fact that it investigates an alternative way of management of religious activities and movements. The recent developments in the Middle East, Syria and Iraq in particular, and the fact that hundreds of fighters from the Central Asian republics joined the ISIL terrorist organization once again highlights the implications of the proper regulation of religious activities not only for domestic, but also for regional and global politics. The paper is based on multiple research methods. The process trace method was exploited to better understand the Russification and anti-religious policies to which the Central Asian countries were subject during the Soviet era. The comparative analyse method was also used to better understand the common and distinct features of the politics of religion of Kazakhstan and Kyrgyzstan and the rest of the Central Asian countries. Various legislation acts, as well as secondary sources were investigated to this end. Mostly constructivist approach and a theory suggesting that religion supports national identity when there is a third cohesion that threatens both and when elements of national identity are weak. Preliminary findings suggest that in line with policies aimed at gradual reduction of Russian influence, as well as in the face of ever-increasing migration from China, the mentioned countries incorporated some Islamic elements into domestic policies as a part and parcel of national culture. Kazakhstan and Kyrgyzstan did not suppress religious activities, which was case in neighboring states, but allowed in a controlled way Islamic movements to have a relatively freedom of action which in turn led to the less violent religious extremism further boosting national identity.

Keywords: identity, Islam, nationalism, terrorism

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Authors: Sisay Tiroro Salato

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Background: Ethiopia has been implementing the maternal death surveillance and response system to provide real-time actionable information, including causes of death and contributing factors. Analysis of maternal mortality surveillance data was conducted to identify the causes and underlying factors in Addis Ababa, Ethiopia. Methods: We carried out a retrospective surveillance data analysis of 324 maternal deaths reported in Addis Ababa, Ethiopia, from 2017 to 2021. The data were extracted from the national maternal death surveillance and response database, including information from case investigation, verbal autopsy, and facility extraction forms. The data were analyzed by computing frequency and presented in numbers, proportions, and ratios. Results: Of 324 maternal deaths, 92% died in the health facilities, 6.2% in transit, and 1.5% at home. The mean age at death was 28 years, ranging from 17 to 45. The maternal mortality ratio per 100,000 live births was 77for the five years, ranging from 126 in 2017 to 21 in 2021. The direct and indirect causes of death were responsible for 87% and 13%, respectively. The direct causes included obstetric haemorrhage, hypertensive disorders in pregnancy, puerperal sepsis, embolism, obstructed labour, and abortion. The third delay (delay in receiving care after reaching health facilities) accounted for 57% of deaths, while the first delay (delay in deciding to seek health care) and the second delay (delay in reaching health facilities) and accounted for 34% and 24%, respectively. Late arrival to the referral facility, delayed management after admission, andnon-recognition of danger signs were underlying factors. Conclusion: Over 86% of maternal deaths were attributed by avoidable direct causes. The majority of women do try to reach health services when an emergency occurs, but the third delays present a major problem. Improving the quality of care at the healthcare facility level will help to reduce maternal death.

Keywords: maternal death, surveillance, delays, factors

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Authors: Carolyn Cameron

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Stop Food Waste Australia is working with the industry to co-design sector action plans to prevent and reduce food waste across the supply chain. We are a public-private partnership, funded in 2021 by the Australian national government under the 2017 National Food Waste Strategy. Our partnership has representatives from all levels of government, industry associations from farm to fork, and food rescue groups. Like many countries, Australia has adopted the Sustainable Development Goal (SDG) target of 12.3 to halve food waste by 2030. A seminal 2021 study, the National Food Waste Feasibility Report, developed a robust national baseline, illustrating hotspots in commodities and across the supply chain. This research found that the consumption stages – households, food service, and institutions - account for over half of all food waste, and 22% of food produced never leaves the farm gate. Importantly the study found it is feasible for Australia to meet SDG 12.3, but it will require unprecedented action by governments, industry, and the community. Sector Action Plans (Plan) are one of the four main initiatives of Stop Food Waste Australia, including a voluntary commitment, a coordinated food waste communications hub, and robust monitoring and reporting framework. These plans provide a systems-based approach to reducing food loss and waste while realising multiple benefits for supply chain partners and other collaborators. Each plan is being co-designed with the key stakeholders most able to directly control or influence the root cause(s) of food waste hotspots and to take action to reduce or eliminate food waste in their value chain.  The initiatives in the Plans are fit-for-purpose, reflecting current knowledge and recognising priorities may refocus over time. To date, sector action plans have been developed with the Food Rescue, Cold Chain, Bread and Bakery, and Dairy Sectors. Work is currently underway on Meat and Horticulture, and we are also developing supply-chain stage plans for food services and institutions. The study will provide an overview of Australia’s food waste baseline and challenges, the important role of sector action plans in reducing food waste, and case studies of implementation outcomes.

Keywords: co-design, horticulture, sector action plans, voluntary

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Authors: Ejeh Benjamin Ijuo

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The purpose of this study was to investigate the influence of social, economic, political, and legal environment of sport organizations on sport development in zone ten (10) national zonal sport offices in Nigeria (Plateau, Nasarawa, Benue and F.C.T Abuja). To achieve this purpose, a structured 26 item questionnaire (ISEPLESOQ) designed by the researcher was used for this study. Related literature to this study was reviewed. 311 copies of questionnaire were administered to randomly selected respondents. Out of this number, 306 was dully completed and returned representing 98.4%. The respondents included: Athletes, games masters/ mistresses, coaches in state sport councils, zonal sport coordinators, team managers, directors of state sports council. Four research questions were answered using the mean and standard deviation, while the inferential statistics of chi-square(x2) test of goodness of fit was used to test the four hypotheses at 0.05 alpha levels. The findings of this study revealed that the social, economic, political and legal environment of sport organizations significantly influenced sport development in zone ten (10) national zonal sport offices in Nigeria. It was also established that the general environment of sport organizations influences people’s participation in sport, funding and sponsorship of sports, sitting of equipment and facilities at different locations, selection of athletes. It was therefore, recommended among other things that government should privatize and commercialized sport programmes to enable corporate organizations and individuals participation. Lt was further suggested that the federal government should harness her social, economic, political and legal environment to improve sport development in Nigeria.

Keywords: sport organization, sport development, sport environment, zonal sport offices

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Authors: Santosh Ghosh, Vinod Kumar Yadav, Vivekananda Mukherjee, Ishta Garg

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India, akin to the rest of the world today, is grappling with balancing act between ever increasing demand for energy and alarmingly high level of green house gas emission, which is inevitable corollary of energy production in the conventional way. Researchers and energy policy makers around the world are now focusing on renewable energy (RE) technologies to find solution to this crisis. In India various agencies at both national and state level has been set up and bestowed with responsibility of development of renewable energy technologies, viz. Ministry of New Renewable Energy (MNRE), National Vidyut Vyapar Nigam Ltd. (NVVNL), Indian Renewable Energy Development Agency Limited (IREDA) and RE Development Agencies in respective states. In the present work, the preparedness of India in terms of forming institutional and policy frame work briefly discussed. Status of implementation of RE technologies state wise and of India as a whole, critically reviewed.

Keywords: energy policy, energy sustainability, renewable energy, IREDA

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Authors: Izzati Nabiyla Risfa

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The role of civil society has become an important issue in national and international level nowadays. Government all over the world started to realize that the involvement of civil society can boost up public services and better policy making. Global Policy Forum stated that there are five good reasons for civil society to be engaged in global governance; (1) to conferring legitimacy on policy decisions; (2) to increasing the pool of policy ideas; (3) to support less powerful governments; (4) countering a lack of political will; and (5) helping states to put nationalism aside. Indonesia also keeps up with this good trend. In November 2011, Indonesian Government set up LAPOR! (means “to report” in Indonesian), an online portal for complaints about public services, which is accessible through its website lapor.ukp.go.id. LAPOR! also accessible through social media (Twitter, Facebook) and text message. This program is an initiative from the government to provide an integrated and accessible portal for the Indonesian public to submit complaints and inquiries as a means of enhancing public participation in national development programs. LAPOR! aims to catalyze public participation as well as to have a more coordinated national complaint handling mechanism. The goal of this program is to increase the role of civil society in order to develop better public services. Thus, LAPOR! works in a simplest way possible. Public can submit any complaints or report their problem concerning development programs and public services simply through the website, short message services to 1708 and mobile applications for BlackBerry and Android. LAPOR! will then transfer every validated input to relevant institutions to be featured and responded on the website. LAPOR! is now integrated with 81 Ministries, 5 local government, and 44 State Owned Enterprise. Public can also give comments, likes or share them through Facebook and Twitter to have a discussion and to ensure the completeness of the reports. LAPOR! has unexpectedly contributed to various successful cases concerning public services. So far the portal has over 280,704 registered users, receiving an average of 1,000 reports every day. Government's response rate increase time to time, with 81% of complaints and inquiries have been solved or are being investigated. This paper will examine the effectiveness of LAPOR! as a tools to increase the role of civil society in order to develop better public services in Indonesia. Beside their promising story, there still are various difficulties that need to be solved. With qualitative approach as methodology for this research, writers will also explore potential improvement of LAPOR! so it can perform effectively as a leading national complaint handling system in Indonesia.

Keywords: civil society, government, Indonesia, public services

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Authors: Herke Csongor

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The artificial intelligence (AI) has been used in the United States of America in the decisionmaking process of the criminal justice system for decades. In the field of law, including criminal law, AI can provide serious assistance in decision-making in many places. The paper reviews four main areas where AI still plays a role in the criminal justice system and where it is expected to play an increasingly important role. The first area is the predictive policing: a number of algorithms are used to prevent the commission of crimes (by predicting potential crime locations or perpetrators). This may include the so-called linking hot-spot analysis, crime linking and the predictive coding. The second area is the Big Data analysis: huge amounts of data sets are already opaque to human activity and therefore unprocessable. Law is one of the largest producers of digital documents (because not only decisions, but nowadays the entire document material is available digitally), and this volume can only and exclusively be handled with the help of computer programs, which the development of AI systems can have an increasing impact on. The third area is the criminal statistical data analysis. The collection of statistical data using traditional methods required enormous human resources. The AI is a huge step forward in that it can analyze the database itself, based on the requested aspects, a collection according to any aspect can be available in a few seconds, and the AI itself can analyze the database and indicate if it finds an important connection either from the point of view of crime prevention or crime detection. Finally, the use of AI during decision-making in both investigative and judicial fields is analyzed in detail. While some are skeptical about the future role of AI in decision-making, many believe that the question is not whether AI will participate in decision-making, but only when and to what extent it will transform the current decision-making system.

Keywords: artificial intelligence, international criminal cooperation, planning and organizing of the investigation, risk assessment

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Authors: Akbar Salimi, Mehdi Moghimi

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Goal: Today, the cooperative and systemic work is of importance and guarantees higher efficiency. This research was done with the aim of understanding the guidelines for co-op between police and the national media in order to reduce the juvenile delinquency. Method: This research is applied in terms of goal and of a compound type, which was done through a descriptive-analytical methodology. The data were collected through field surveys and documents. The statistical population included the professors of a higher education center in the area of education affairs, where as many as 36 people were randomly selected. The data collection procedure was by way of interview and researcher made questionnaire. Findings and results: Problems caused by the national media in the area of adolescents are categorized in three levels of production, broadcasting and consumption and elimination and reduction of the problems entail a set of estimations and predictions and also some education which the police forces has the capability to operationalize them. Thus, three hypotheses were defined and by conducting t and Friedman tests, all three hypotheses were confirmed and their rating was identified.

Keywords: management, media, TV, adolscents, delinquency

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Authors: Roli Pradhan

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All over the globe, the resources of the government are declining, and the funding requirements in education are on a constant rise. The governments are desperately increasing the budgetary allocation for higher education, the economic plans have been labeling investment in higher education to be immensely vital for development of the nation. Still the fact is that the government of the developing nations like India lacks the potential to fund the rising demands of this sector. In the face of declining government funding for higher education, there are the growing needs and justifiable pressure for direct beneficiaries to bear a reasonable part of the cost of higher education. The supply-demand gap in higher education in India is on the increase. This paper evaluates the Indian National Education Policy over the past three decades, furnishes the need of financing of education by private players. The paper also covers the aspects of incorporating the different forms of financing in education and also focuses on the regulations pertaining to quality maintenance in the education system. The paper also targets to suggest policy imperatives for the future education policy for India.

Keywords: national education policy, privatisation, private financing, government funding

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Authors: Chi-Ching Lee, Po-Jung Huang, Kuo-Yang Huang, Petrus Tang

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Background: Recent advances in high-throughput research technologies such as new-generation sequencing and multi-dimensional liquid chromatography makes it possible to dissect the complete transcriptome and proteome in a single run for the first time. However, it is almost impossible for many laboratories to handle and analysis these “BIG” data without the support from a bioinformatics team. We aimed to provide a web-based analysis platform for users with only limited knowledge on bio-computing to study the functional genomics and proteomics. Method: We use NCI-60 as an example dataset to demonstrate the power of the web-based analysis platform and data delivering system: C-eXpress takes a simple text file that contain the standard NCBI gene or protein ID and expression levels (rpkm or fold) as input file to generate a distribution map of gene/protein expression levels in a heatmap diagram organized by color gradients. The diagram is hyper-linked to a dynamic html table that allows the users to filter the datasets based on various gene features. A dynamic summary chart is generated automatically after each filtering process. Results: We implemented an integrated database that contain pre-defined annotations such as gene/protein properties (ID, name, length, MW, pI); pathways based on KEGG and GO biological process; subcellular localization based on GO cellular component; functional classification based on GO molecular function, kinase, peptidase and transporter. Multiple ways of sorting of column and rows is also provided for comparative analysis and visualization of multiple samples.

Keywords: cancer, visualization, database, functional annotation

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Authors: Driss Cherqaoui, Nouhaila Ait Lahcen, Ismail Hdoufane, Mehdi Oubahmane, Wissal Liman, Christelle Delaite, Mohammed M. Alanazi

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The Ebola virus is a highly contagious and deadly pathogen that causes Ebola virus disease. The Ebola virus glycoprotein (EBOV-GP) is a key factor in viral entry into host cells, making it a critical target for therapeutic intervention. Using a combination of computational approaches, this study focuses on the identification of natural compounds that could serve as potent inhibitors of EBOV-GP. The 3D structure of EBOV-GP was selected, with missing residues modeled, and this structure was minimized and equilibrated. Two large natural compound databases, COCONUT and NPASS, were chosen and filtered based on toxicity risks and Lipinski’s Rule of Five to ensure drug-likeness. Following this, a pharmacophore model, built from 22 reported active inhibitors, was employed to refine the selection of compounds with a focus on structural relevance to known Ebola inhibitors. The filtered compounds were subjected to virtual screening via molecular docking, which identified ten promising candidates (five from each database) with strong binding affinities to EBOV-GP. These compounds were then validated through molecular dynamics simulations to evaluate their binding stability and interactions with the target. The top three compounds from each database were further analyzed using ADMET profiling, confirming their favorable pharmacokinetic properties, stability, and safety. These results suggest that the selected compounds have the potential to inhibit EBOV-GP, offering new avenues for antiviral drug development against the Ebola virus.

Keywords: EBOV-GP, Ebola virus glycoprotein, high-throughput drug screening, molecular docking, molecular dynamics, natural compounds, pharmacophore modeling, virtual screening

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Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

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Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

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Authors: Almahd Alshereef, Ahmed Alkilany, Hammad Said, Azuraliza Abu Bakar

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From time to time, electrical power grid is directed by the National Electricity Operator to conduct load shedding, which involves hours' power outages on the area of this study, Southern Electrical Grid of Libya (SEGL). Load shedding is conducted in order to alleviate pressure on the National Electricity Grid at times of peak demand. This approach has chosen a set of categories to study load-shedding problem considering the effect of the demand priorities on the operation of the power system during emergencies. Classification of category region for load shedding problem is solved by a new algorithm (the harmony algorithm) based on the "random generation list of category region", which is a possible solution with a proximity degree to the optimum. The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on SEGL.

Keywords: optimization, harmony algorithm, load shedding, classification

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Authors: Raghavi C. Janaswamy

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In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

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Authors: Natacha Fery, Guilherme L. Dalledonne, Xiangyang Zheng, Cheng Tang, Roberto Mayerle

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A Decision Support System (DSS) for supporting decision makers in the management of the Shandong Peninsula has been developed. Emphasis has been given to coastal protection, coastal cage aquaculture and harbors. The investigations were done in the framework of a joint research project funded by the German Ministry of Education and Research (BMBF) and the Chinese Academy of Sciences (CAS). In this paper, a description of the DSS, the development of its components, and results of its application are presented. The system integrates in-situ measurements, process-based models, and a database management system. Numerical models for the simulation of flow, waves, sediment transport and morphodynamics covering the entire Bohai Sea are set up based on the Delft3D modelling suite (Deltares). Calibration and validation of the models were realized based on the measurements of moored Acoustic Doppler Current Profilers (ADCP) and High Frequency (HF) radars. In order to enable cost-effective and scalable applications, a database management system was developed. It enhances information processing, data evaluation, and supports the generation of data products. Results of the application of the DSS to the management of coastal protection, coastal cage aquaculture and harbors are presented here. Model simulations covering the most severe storms observed during the last decades were carried out leading to an improved understanding of hydrodynamics and morphodynamics. Results helped in the identification of coastal stretches subjected to higher levels of energy and improved support for coastal protection measures.

Keywords: coastal protection, decision support system, in-situ measurements, numerical modelling

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Authors: Sintayehu W. Dejene

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An ecological and biodiversity conservation study on species composition, population status and habitat association of large mammals and the impact of human interference on their distribution was carried out in Awash National Park, Ethiopia during October, 2012 to July, 2013. A total of 25 species of large mammals were recorded from the study area. Representative sample sites were taken from each habitat type and surveyed using random line transect method. For medium and large mammal survey, indirect methods (foot print and dung) and direct observations were used. Twenty three species of medium to large-sized mammals were identified and recorded from ANP. A total of 25 species of median and large size mammals were recorded from the study area. Out of this, 20 species were rodents of three families and five species were insectivores of two families. Beisa Oryx (Oryx beisa beisa),Soemmerings gazelle (Gazella soemmeringi),Defassa waterbuck (Kobus defassa), Lesser Kudu (Strepsiceros imberbis), Greater Kudu (Strepsiceros strepsiceros), Warthog (Phacochoerus aethiopicus), Baboon (Papio anubis baboon) and Salt's dikdik (Madoqua saltiana) were the most common seen median and large mammals in the study area. Beisa Oryx (Oryx beisa beisa) and Sommering Gazelles (Gazella soemmeringi) are commonly found in the open areas, where as Greater Kudus (Strepsiceros strepsiceros) and Lesser Kudus (Strepsiceros imberbis) was seen in the bushed areas. Defarsa waterbuck (Kobus defassa) was observed in the bushy river area in Northern part of the Park. Anubis baboon (Papio anubis baboon) was seen near to the river side. Hamadryas baboon founded in semi-desert areas of Awash National Park, particularly in Filwoha area. The area is one of a key biodiversity conservation and provide pure water, air, food, grazing land and storage of carbon.

Keywords: awash national park, biodiversity, ecosystem value, habitat association, large mammals, population status, species composition

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Authors: Jawaad Saleem, Hannah Wright, Peter Sommerville, Adrian Hopper

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Introduction: Inpatient falls are the most commonly reported patient safety incidents, and carry a significant burden on resources, morbidity, and mortality. Ensuring adequate post falls management of patients by staff is therefore paramount to maintaining patient safety especially in out of hours and resource stretched settings. Aims: This quality improvement project aims to improve the current practice of falls management at Guys St Thomas Hospital, London as compared to our 2016 Quality Improvement Project findings. Furthermore, it looks to increase current junior doctors confidence in managing falls and their use of new guidance protocols. Methods: Multifaceted Interventions implemented included: the development of new trust wide guidelines detailing management pathways for patients post falls, available for intranet access. Furthermore, the production of 2000 lanyard cards distributed amongst junior doctors and staff which summarised these guidelines. Additionally, a ‘safety signal’ email was sent from the Trust chief medical officer to all staff raising awareness of falls and the guidelines. Formal falls teaching was also implemented for new doctors at induction. Using an established incident database, 189 consecutive falls in 2017were retrospectively analysed electronically to assess and compared to the variables measured in 2016 post interventions. A separate serious incident database was used to analyse 50 falls from May 2015 to March 2018 to ascertain the statistical significance of the impact of our interventions on serious incidents. A similar questionnaire for the 2017 cohort of foundation year one (FY1) doctors was performed and compared to 2016 results. Results: Questionnaire data demonstrated improved awareness and utility of guidelines and increased confidence as well as an increase in training. 97% of FY1 trainees felt that the interventions had increased their awareness of the impact of falls on patients in the trust. Data from the incident database demonstrated the time to review patients post fall had decreased from an average of 130 to 86 minutes. Improvement was also demonstrated in the reduced time to order and schedule X-ray and CT imaging, 3 and 5 hours respectively. Data from the serious incident database show that ‘the time from fall until harm was detected’ was statistically significantly lower (P = 0.044) post intervention. We also showed the incidence of significant delays in detecting harm ( > 10 hours) reduced post intervention. Conclusions: Our interventions have helped to significantly reduce the average time to assess, order and schedule appropriate imaging post falls. Delays of over ten hours to detect serious injuries after falls were commonplace; since the intervention, their frequency has markedly reduced. We suggest this will lead to identifying patient harm sooner, reduced clinical incidents relating to falls and thus improve overall patient safety. Our interventions have also helped increase clinical staff confidence, management, and awareness of falls in the trust. Next steps include expanding teaching sessions, improving multidisciplinary team involvement to aid this improvement.

Keywords: patient safety, quality improvement, serious incidents, falls, clinical care

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Authors: Marcos Centurion-Vicencio

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This study discusses the idea of ‘dominance’ in economic policy and its practical influence over monetary decisions. The discretionary use of repurchase agreements in Brazil over the period 2006-2016 and its effects on the overall price level are the specific issues we will be focusing on. The set of in-depth interviews carried out with public servants at the Brazilian central bank and national treasury, alongside data collected from the National Institution of Statistics (IBGE), suggest that monetary and fiscal dominance do not differ in nature once the assumption of depoliticized central bankers is relaxed. In both regimes, the pursuit of private gains via public institutions affects price stability. While short-sighted politicians in the latter are at the origin of poor monetary decisions, the action of short-sighted financial interest groups is likely to generate a similar outcome in the former. This study then contributes to rethinking monetary policy theory as well as the nature of public borrowing.

Keywords: fiscal and monetary interactions, interest groups, monetary capture, public borrowing

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Authors: P. Susheela, Mary Rosaline, R. Radha

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This research was designed to determine the bioactive compounds present in the nest samples of the mud dauber wasp, Sceliophron caementarium. Insects and insect-based products have been used for the treatment of various ailments from a very long time. It has been found that all over the world including the western societies and the indigenous populations, the usage of insect-based medicine plays an important role in various healing practices and magic rituals. Studies on the therapeutic usage of insects are negligible when compared to plants, the. In the present scenario, it is important to explore bioactive compounds from natural sources rather than depending on synthetic drugs that have adverse effects on human body. Keeping this in view, an attempt was made to analyze and identify bioactive components from the nest sample of the mud dauber wasp, Sceliophron caementarium. The nests of the mud dauber wasp, Sceliophron caementarium were collected from Coimbatore, Tamil Nadu, India. The nest sample was extracted with ethanol for 6-8 hours using Soxhlet apparatus. The final residue was obtained by filtering the extract through Whatman filter paper No.41. The GCMS analysis of the nest sample was performed using Perkin Elmer Elite - 5 capillary column. The resultant compounds were compared with the database of National Institute Standard and Technology (NIST), WILEY8, FAME. The GC-MS analysis of the concentrated ethanol extract revealed the presence of eight constituents like Methylene chloride, Eicosanoic acid, 1, 1’:3’, 1’’-Terphenyl, 5'-Phenyl, Di-N-Decylsulfone, 1, 2-Bis (Trimethylsilyl) Benzene, Androstane-11, 17-Dione, 3-[(Trimethylsilyl) Oxy]-, 17-[O-(Phenylmethyl) O. Most of the identified compounds were reported as having biological activities viz. anti-inflammatory, antibacterial and antifungal properties that can be of pharmaceutical importance and further study of these isolated compounds may prove their medicinal importance in future.

Keywords: Sceliophron caementarium, Gas chromatography-mass spectrometry, ethanol extract, bioactive compounds

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Authors: Khaleel Bader Bataineh

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Past studies have maintained that the Arab learners' beliefs about language learning hold vital effects on their performance. Thus, this study was carried out to investigate the language learning beliefs of Irbid National University students. It aimed at identifying the language learning beliefs according to gender. This study is a descriptive design that employed survey questionnaire of Language Learning Beliefs Inventory (BALLI). The data were elicited from 83 English major students during the class sessions. The data were analyzed using an SPSS program in which frequency analysis and t-test were performed to examine the students’ responses. Thus, the major findings of this research indicated that there is a variation in responses with regards to the subjects’ beliefs about English learning. Also, the findings show significant differences in four questionnaire items according to gender. It is hoped that the findings provide valuable insights to educators about the learners’ beliefs which assist them to develop the teaching and learning English language process in Jordan universities.

Keywords: foreign language, students’ beliefs, language learning, Arab students

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Authors: Dogaru-Ulieru Valentin, Sălișteanu Ioan Corneliu, Ardeleanu Mihăiță Nicolae, Broscăreanu Ștefan, Sălișteanu Bogdan, Mihai Mihail

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The SiaMOTO system is a communications and data processing platform for vehicle traffic. The human factor is the most important factor in the generation of this data, as the driver is the one who dictates the trajectory of the vehicle. Like any trajectory, specific parameters refer to position, speed and acceleration. Constant knowledge of these parameters allows complex analyses. Roadways allow many vehicles to travel through their confined space, and the overlapping trajectories of several vehicles increase the likelihood of collision events, known as road accidents. Any such event has causes that lead to its occurrence, so the conditions for its occurrence are known. The human factor is predominant in deciding the trajectory parameters of the vehicle on the road, so monitoring it by knowing the events reported by the DiaMOTO device over time, will generate a guide to target any potentially high-risk driving behavior and reward those who control the driving phenomenon well. In this paper, we have focused on detailing the communication infrastructure of the DiaMOTO device with the traffic data collection server, the infrastructure through which the database that will be used for complex AI/DLM analysis is built. The central element of this description is the data string in CODEC-8 format sent by the DiaMOTO device to the SiaMOTO collection server database. The data presented are specific to a functional infrastructure implemented in an experimental model stage, by installing on a number of 50 vehicles DiaMOTO unique code devices, integrating ADAS and GPS functions, through which vehicle trajectories can be monitored 24 hours a day.

Keywords: DiaMOTO, Codec-8, ADAS, GPS, driver monitoring

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