Search results for: evaluation of entrepreneurship education (EE) curriculum

Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

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Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

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In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

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Authors: Mahmoud Abdel Hameed Shahin

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Job demands that are incompatible with an employee's skills, resources, or needs cause unpleasant emotional and physical reactions known as job stress. Nurses offer care in hospital emergency rooms all around the world, and since they operate in such a dynamic and unpredictable setting, they are constantly under pressure. It has been discovered that job stress has harmful impacts on nurses' health as well as their capacity to handle the demands of their jobs. The purpose of this study was to evaluate the level of job stress experienced by the emergency department nurses at King Fahad Specialist Hospital in Buraidah City, Saudi Arabia. In October 2021, a cross-sectional descriptive study was conducted. 80 nurses were conveniently selected for the study, the bulk of them worked at King Fahad Specialist Hospital's emergency department. An electronic questionnaire with a sociodemographic data sheet and a job stress scale was given to the participating nurses after ethical approval was received from the Ministry of Health's representative bodies. Using SPSS Version 26, both descriptive and inferential statistics were employed to analyze and tabulate the acquired data. According to the findings, the factors that contributed to the most job stress in the clinical setting were having an excessive amount of work to do and working under arbitrary deadlines, whereas the factors that contributed to the least stress were receiving the proper recognition or rewards for good work. In the emergency room of King Fahad Specialist Hospital, nurses had a moderate level of stress (M=3.32 ± 0.567/5). Based on their experience, emergency nurses' levels of job stress varied greatly, with nurses with less than a year of experience notably experiencing the lowest levels of job stress. The amount of job stress did not differ significantly based on the emergency nurses' age, nationality, gender, marital status, position, or level of education. The causes and impact of stress on emergency nurses should be identified and alleviated by hospitals through the implementation of interventional programs.

Keywords: emergency nurses, job pressure, Qassim, Saudi Arabia, job stress

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Authors: David Whitehouse

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Some of the strengths of online teaching include flexibility, creativity, and comprehensiveness. A challenge can be motivation. How can an instructor repeating the same lessons over and over, day in and day out, year after year, maintain motivation? Enthusiasm? Does motivating the student and creating enthusiasm in class build the same things inside the instructor? The answers lie in the adoption of what I label EUQ—The Empathy and Understanding Quotient. In the online environment, students who are adults have many demands on their time: civilian careers, families (spouse, children, older parents), and sometimes even military service. Empathetic responses on the part of the instructor will lead to open and honest communication on the part of the student, which will lead to understanding on the part of the instructor and a rise in motivation in both parties. Understanding the demands can inform an instructor’s relationship with the student throughout the temporal parameters of classwork. In practicing EUQ, instructors can build motivation in their students and find internal motivation in an enhanced classroom dynamic. The presentation will look at what motivates a student to accomplish more than the minimum required and how that can lead to excellent results for an instructor’s own motivation. Through direct experience of having students give high marks on post-class surveys and via direct messaging, the presentation will focus on how applying EUQ in granting extra time, searching for intent while grading, communicating with students via Quick Notes, responses in Forums, comments in Assignments, and comments in grading areas - - - how applying these things infuses enthusiasm and energy in the instructor which drive creativity in teaching. Three primary ways of communicating with students will be given as examples. The positive response and negative response each for a Forum, an Assignment, and a Message will be explored. If there is time, participants will be invited to craft their own EUQ responses in a role playing exercise involving two common classroom scenarios—late work and plagiarism.

Keywords: education, instruction, motivation, online, teaching

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Authors: Peifang Hsieh

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The prevention of child abuse has aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported child abuse cases that doubled over the past decade and the scarcity of social workers. New Taipei city, with the most population in Taiwan and over 70% of its 4 million citizens are migrant families in which the needs of children can be easily neglected due to insufficient support from relatives and communities, sees urgency for a social support system, by preemptively identifying and outreaching high-risk families of child abuse, so as to offer timely assistance and preventive measure to safeguard the welfare of the children. Big data analysis is the inspiration. As it was clear that high-risk families of child abuse have certain characteristics in common, New Taipei city decides to consolidate detailed background information data from departments of social affairs, education, labor, and health (for example considering status of parents’ employment, health, and if they are imprisoned, fugitives or under substance abuse), to cross-reference for accurate and prompt identification of the high-risk families in need. 'The Service Center for High-Risk Families' (SCHF) was established to integrate data cross-departmentally. By utilizing the machine learning 'random forest method' to build a risk prediction model which can early detect families that may very likely to have child abuse occurrence, the SCHF marks high-risk families red, yellow, or green to indicate the urgency for intervention, so as to those families concerned can be provided timely services. The accuracy and recall rates of the above model were 80% and 65%. This prediction model can not only improve the child abuse prevention process by helping social workers differentiate the risk level of newly reported cases, which may further reduce their major workload significantly but also can be referenced for future policy-making.

Keywords: child abuse, high-risk families, big data analysis, risk prediction model

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Authors: Elida Tafupenji Kamanga

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Cancer of the cervix remains one of the high causes of death among Malawian women. Despite the government introduction of free screening services throughout the country, patronage still remains low and lack of knowledge high. Given the critical role mass media plays in relaying different information to the public including health and its influence on health behaviours, the study sought to analyse Malawi media coverage of the disease and its effectiveness. The findings of the study will help inform media advocacy directed at changing any coverage impeding the effective dissemination of cervical cancer message which consequently will help increase awareness and accessing of screening behaviours among women. A content analysis of 29 newspapers and promotional messages on cervical from a local radio station was conducted for the period from 2012 to 2015. Overall the results showed media coverage in terms of content and frequency increased for the four-year period. However, of concern was the quality of information both media presented to the public. The lapse in information provided means there is little education taking place through the media which could be contributing to the knowledge gap the women have thereby affecting their decision to screen. Also lack of adequate funding to media institutions and lack of collaboration between media institutions and stakeholders involved in the fight against the disease were noted as other contributing factors to low coverage of the disease. Designing messages that are not only informative and educative but also innovative may help increase awareness; improve the knowledge gap and potential adoption of preventive screening behaviour by Malawian women. Conversely, good communication between the media institutions and researchers involved in the fight against the disease through the channelling of new findings back to the public as well as increasing funding towards similar cause should be considered.

Keywords: cervical cancer, effectiveness, media coverage, screening

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Authors: Peter Olasupo Ogunjuyigbe, Sarafa Shittu

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This paper emphasizes the relevance of conjugal relationship and spousal communication towards enhancing men’s involvement in contraceptive use among the Yorubas of South Western Nigeria. An understanding of males influence and the role they play in reproductive decision making can throw better light on mechanisms through which egalitarianness of husband/wife decision making influences contraceptive use. The objective of this study was to investigate how close conjugal relationships can be a good indicator of joint decision making among couples using data derived from a survey conducted in three states of South Western Nigeria. The study sample consisted of five hundred and twenty one (521) male respondents aged 15-59 years and five hundred and forty seven (547) female respondents aged 15-49 years. The study used both quantitative and qualitative approached to elicit information from the respondents. In order that the study would be truly representative of the towns, each of the study locations in the capital cities was divided into four strata: The traditional area, the migrant area, the mixed area (i.e. traditional and migrant), and the elite area. In the rural areas, selection of the respondents was by simple random sampling technique. However, the random selection was made in such a way that all the different parts of the locations were represented. Generally, the data collected were analysed at univariate, bivariate, and multivariate levels. Logistic regression models were employed to examine the interrelationships between male reproductive behaviour, conjugal relationship and contraceptive use. The study indicates that current use of contraceptive is high among this major ethnic group in Nigeria because of the improved level of communication among couples. The problem, however, is that men still have lower exposure rate when it comes to question of family planning information, education and counseling. This has serious implications on fertility regulation in Nigeria.

Keywords: behavior, conjugal, communication, counseling, spouse

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Authors: Siti Noor Syahirah Mohd Sabri

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The oil and gas industry is committed to net zero carbon emissions because the consequences of climate change could be catastrophic unless responded to very soon. One way of reducing CO₂ emissions is to inject it into a depleted reservoir buried underground. This greenhouse gas reduction technique significantly reduces CO₂ released into the atmosphere. In general, depleted oil and gas reservoirs provide readily available sites for the storage of CO₂ in offshore areas. This is mainly due to the hydrocarbons have been optimally produced and the existence of voids for effective CO₂ storage. Hence, make it a good candidate for a CO₂ well injector location. Geological storage sites are often evaluated in terms of capacity, injectivity and containment. Leakage through the cap rock or existing well is the main concern in the depleted fields. In order to develop these fields as CO₂ storage sites, the long-term integrity of wells drilled in these oil & gas fields must be ascertained to ensure good CO₂ containment. Well, integrity is often defined as the ability to contain fluids without significant leakage through the project lifecycle. Most plugged and abandoned (P & A) wells in Peninsular Malaysia have drilled 20 – 30 years ago and were not designed to withstand downhole conditions having >50%vol CO₂ and CO₂/H₂O mixture. In addition, Corrosive-Resistant Alloy (CRA) tubular and CO₂-resistant cement was not used during good construction. The reservoir pressure and temperature conditions may have further degraded the material strength and elevated the corrosion rate. Understanding all the uncertainties that may have affected cement-casing bonds, such as the quality of cement behind the casing, subsidence effect, corrosion rate, etc., is the first step toward well integrity evaluation. Secondly, proper quantification of all the uncertainties involved needs to be done to ensure long-term underground storage objectives of CO₂ are achieved. This paper will discuss challenges associated with estimating the performance of well barrier elements in existing P&A wells. Risk ranking of the existing P&A wells is to be carried out in order to ensure the integrity of the storage site is maintained for long-term CO₂ storage. High-risk existing P&A wells are to be re-entered to restore good integrity and to reduce future leakage that may happen. In addition, the requirement to design a fit-for-purpose monitoring and mitigation technology package for potential CO₂ leakage/seepage in the marine environment will be discussed accordingly. The holistic approach will ensure that the integrity is maintained, and CO₂ is contained underground for years to come.

Keywords: CCUS, well integrity, co₂ storage, offshore

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: A. Mohammad Abdul Motalib Momin, B. Sheikh Mohammad Adil Uddin, C. Md Mamunur Rashid, D. Sheikh Arman Mahbub, E. Mohammad Sazzad Rahman, F. Abdullah Faruque

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The present study was designed to investigate the antioxidant and cytotoxicity potential of methanol and pet ether extracts of the Lagenaria siceraria (LM, LP), Cucumis sativus (CSM, CSP), Cucurbita maxima (CMM, CMP) plants. For the phytochemical screening, crude extract was tested for the presence of different chemical groups. In Lagenaria siceraria the following groups were identified: alkaloids, steroids, glycosides and saponins for methanol extract and alkaloids, steroids, glycosides, tannins and saponins are for pet ether extract. Glycosides, steroids, alkaloids, saponins and tannins are present in the methanol extract of Cucumis sativus; the pet ether extract has the alkaloids, steroids and saponins. Glycosides, steroids, alkaloids, saponins and tannins are present in both the methanolic and pet ether extract of Cucurbita maxima. In vitro antioxidant activity of the extracts were performed using DPPH radical scavenging, nitric oxide (NO) scavenging, total antioxidant capacity, total phenol content, total flavonoid content, and Cupric Reducing Antioxidant Capacity assays. The most prominent antioxidant activity was observed with the CSM in the DPPH free radical scavenging test with an IC50 value of 1667.23±11.00271 μg/ml as opposed to that of standard ascorbic acid (IC50 value of 15.707± 1.181 μg/ml.) In total antioxidant capacity method, CMP showed the highest activity (427.81±11.4 mg ascorbic acid/g). The total phenolic and flavonoids content were determined by Folin-Ciocalteu Reagent and aluminium chloride colorimetric method, respectively. The highest total phenols and total flavonoids content were found in CMM and LP with the value of 79.06±16.06 mg gallic acid/g & 119.0±1.41 mg quercetin/g, respectively. In nitric oxide (NO) scavenging the most prominent antioxidant activity was observed in CMM with an IC50 value of 8.119± 0.0036 μg/ml. The Cupric reducing capacity of the extracts was strong and dose dependent manner and CSM showed lowest reducing capacity. The cytotoxicity was determined by Brine shrimp lethality test and among these extracts most potent cytotoxicity was shown by CMM with LC50 value 16.98 µg/ml. The obtained results indicate that the investigated plants could be potential sources of natural antioxidants and can be used for various types of diseases.

Keywords: antioxidant, cytotoxicity, methanol, petroleum ether

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Authors: Fatema Akram, Mohammad G. Rasul, M. Masud K. Khan, M. Sharif I. I. Amir

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Australia is a country of some 7,700 million square kilometres with a population of about 22.6 million. At present water security is a major challenge for Australia. In some areas the use of water resources is approaching and in some parts it is exceeding the limits of sustainability. A focal point of proposed national water conservation programs is the recycling of both urban storm-water and treated wastewater. But till now it is not widely practiced in Australia, and particularly storm-water is neglected. In Australia, only 4% of storm-water and rainwater is recycled, whereas less than 1% of reclaimed wastewater is reused within urban areas. Therefore, accurately monitoring, assessing and predicting the availability, quality and use of this precious resource are required for better management. As storm-water is usually of better quality than untreated sewage or industrial discharge, it has better public acceptance for recycling and reuse, particularly for non-potable use such as irrigation, watering lawns, gardens, etc. Existing storm-water recycling practice is far behind of research and no robust technologies developed for this purpose. Therefore, there is a clear need for using modern technologies for assessing feasibility of storm-water harvesting and reuse. Numerical modelling has, in recent times, become a popular tool for doing this job. It includes complex hydrological and hydraulic processes of the study area. The hydrologic model computes storm-water quantity to design the system components, and the hydraulic model helps to route the flow through storm-water infrastructures. Nowadays water quality module is incorporated with these models. Integration of Geographic Information System (GIS) with these models provides extra advantage of managing spatial information. However for the overall management of a storm-water harvesting project, Decision Support System (DSS) plays an important role incorporating database with model and GIS for the proper management of temporal information. Additionally DSS includes evaluation tools and Graphical user interface. This research aims to critically review and discuss all the aspects of storm-water harvesting and reuse such as available guidelines of storm-water harvesting and reuse, public acceptance of water reuse, the scopes and recommendation for future studies. In addition to these, this paper identifies, understand and address the importance of modern technologies capable of proper management of storm-water harvesting and reuse.

Keywords: storm-water management, storm-water harvesting and reuse, numerical modelling, geographic information system, decision support system, database

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Authors: Nasrin Nejatbakhsh, Anita Kaiser, Sander Hitzig, Colleen McGillivray

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Following spinal cord injury (SCI), many individuals experience anxiety in adjusting to their lives, and its impacts on their sexuality. Research has demonstrated that regaining sexual function is a very high priority for individuals with SCI. Despite this, sexual health is one of the least likely areas of focus in rehabilitating individuals with SCI. There is currently a considerable gap in appropriate education and resources that address sexual health concerns and needs of people with spinal cord injury. Furthermore, the determinants of sexual health in individuals with SCI are poorly understood and thus poorly addressed. The purpose of this study was to improve current practices by informing a service delivery model that rehabilitation centers can adopt for appropriate delivery of their services. Methodology: We utilized qualitative methods in the form of a semi-structured interview containing open-ended questions to assess 1) sexual health concerns, 2) helpful strategies in current resources, 3) unhelpful strategies in current resources, and 4) Barriers to obtaining sexual health information. In addition to the interviews, participants completed surveys to identify socio-demographic factors. Data gathered was coded and evaluated for emerging themes and subthemes through a ‘code-recode’ technique. Results: We have identified several robust themes that are important for SCI sexual health resource development. Through analysis of these themes and their subthemes, several important concepts have emerged that could provide agencies with helpful strategies for providing sexual health resources. Some of the important considerations are that services be; anonymous, accessible, frequent, affordable, mandatory, casual and supported by peers. Implications: By incorporating the perspectives of individuals with SCI, the finding from this study can be used to develop appropriate sexual health services and improve access to information through tailored needs based program development.

Keywords: spinal cord injury, sexual health, determinants of health, resource development

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Authors: Anna Triwijayati, Etsa Astridya Setiyati, Titik Desi Harsoyo

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Culture is the important determinant of human behavior and desire. Culture influences the consumer through the norms and values established by the society in which they live and reflect it. The cultural values of Javanese society certainly have united in the Javanese society behavior in consumption. This research is expected to give big enough theoretical benefits in the findings of cultural value in consumption in Javanese society. These can be an incentive in finding the local cultural value in many tribes in Indonesia, so one time, the local cultural value in Indonesia about consumption can be fundamental part in education and consumption practice in Indonesia. The approach used in this research is non positivist research or is known as qualitative approach. The method or type of research used in this research is ethnomethodology. The collection data is done in Central Java region. The research subject or informant is determined by the purposive technique by certain criteria determined by the researcher. The data is collected by deep interview and observation. Before the data analysis, the researcher does the storing method data stage and implements the data validity procedures. Then, the data is analyzed by the theme and interactive analysis technique. The Javanese Mataraman society has such consumption values such as has to be sufficient, be careful, economical, submit to the one who creates the life, the way life flow, and the present problem is thought in the present also. In the financial management for consumption, the consumer should have the simple life principles, has to be sufficient, has to be able to eat, has to be able to self-press, well-managed/diligent/accurate/careful, the open or transparent management, has the struggle effort, like to self-sacrifice and think about the future. The meaning of consumption value in family is centered to the submission and full-trust to God. These consumption values are applied in consumer behavior in self, family, investment and credit need in short term and long term perspective.

Keywords: values, consumer, consumption, Javanese Mataraman, ethnomethodology

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Authors: Namekong Fokeng Armand

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Background: Zoonoses are nowadays a serious public health problem in both developing and developed countries. They contribute to increase the economic burden. In case of emergence, rural populations are the most affected, hence the need to investigate risk practices in rural households of Penka-Michel (West Cameroon). Methods: This cross-sectional study was conducted from October to November 2021 among 200 heads of households living in the Penka-Michel health district (West Cameroon). It was done using a pre-tested and validated questionnaire, allowing to obtain socio-demographic, economic data, and data on zoonotic risk practices. Results: The participants [women (56%), men (44%)] worked mainly in the informal private sector (53%) and practiced agriculture secondarily (90%). Their highest level of education, for the most part, was a secondary school (50%); the average household size was 06 persons with a monthly income > 36270 FCFA (72%). 74% of household heads thought that animals can transmit diseases, and 17% had heard about zoonotic diseases through the media (65%). Rats caught in households (60%) were consumed there (74%), as was bush meat (61%) or dog meat (18%). For family food (90%), animals were slaughtered within the household (97%), rarely preceded by a veterinary inspection (6%). 87% of households practiced traditional rites with animal blood, 65% shared the same habitat as their animals, 41% did not systematically wash their hands after handling animals. More than 50% of households owned one or more dogs, usually strays (41%) and 48% of which were vaccinated (rabies). Many households had at least one: poultry (98%); pig (50%); dog (57%), cat (52%). 25% of households slaughtered sick animals for consumption, and 27% ate dead animals. Conclusion: This study identified numerous zoonotic risk practices in households in the Penka-Michel health district (West Cameroon). Concerted, multisectoral communication / awareness-raising actions are needed to break with these practices.

Keywords: zoonoses, risky practices, rural households, penka-michel, cameroon

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Authors: James Boylan, Denny Meyer, Won Sun Chen

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Background: Globally, there is an increasing trend of road traffic deaths, reaching 1.35 million in 2016 in comparison to 1.3 million a decade ago, and overall, road traffic injuries are ranked as the eighth leading cause of death for all age groups. The reported death rate for younger drivers aged 16-19 years is almost twice the rate reported for older drivers aged 25 and above, with a rate of 3.5 road traffic fatalities per annum for every 10,000 licenses held. Telematics refers to a system with the ability to capture real-time data about vehicle usage. The data collected from telematics can be used to better assess a driver's risk. It is typically used to measure acceleration, turn, braking, and speed, as well as to provide locational information. With the Australian government creating the National Telematics Framework, there has been an increase in the government's focus on using telematics data to improve road safety outcomes. The purpose of this study is to test the hypothesis that improvements in telematics measured driving behaviour to relate to improvements in road safety attitudes measured by the Driving Behaviour Questionnaire (DBQ). Methodology: 28 participants were recruited and given a telematics device to insert into their vehicles for the duration of the study. The participant's driving behaviour over the course of the first month will be compared to their driving behaviour in the second month to determine whether feedback from telematics devices improves driving behaviour. Participants completed the DBQ, evaluated using a 6-point Likert scale (0 = never, 5 = nearly all the time) at the beginning, after the first month, and after the second month of the study. This is a well-established instrument used worldwide. Trends in the telematics data will be captured and correlated with the changes in the DBQ using regression models in SAS. Results: The DBQ has provided a reliable measure (alpha = .823) of driving behaviour based on a sample of 23 participants, with an average of 50.5 and a standard deviation of 11.36, and a range of 29 to 76, with higher scores, indicating worse driving behaviours. This initial sample is well stratified in terms of gender and age (range 19-27). It is expected that in the next six weeks, a larger sample of around 40 will have completed the DBQ after experiencing in-vehicle telematics for 30 days, allowing a comparison with baseline levels. The trends in the telematics data over the first 30 days will be compared with the changes observed in the DBQ. Conclusions: It is expected that there will be a significant relationship between the improvements in the DBQ and the trends in reduced telematics measured aggressive driving behaviours supporting the hypothesis.

Keywords: telematics, driving behavior, young drivers, driving behaviour questionnaire

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Authors: Laura Cami Vorpsi

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This research paper examines the potential of private law as a means to promote and safeguard human rights while also addressing the associated challenges and limitations of adopting such an approach. Historically, private law mechanisms, namely contract law, tort law, and property law, have been employed to govern and oversee private relationships and transactions. Nevertheless, it is increasingly acknowledged that private law can also assume a significant role in safeguarding and advancing human rights, particularly in circumstances where the safeguards provided by public law are insufficient or inaccessible. This study assesses the benefits associated with the utilization of private law as a complementary measure to public law safeguards. These advantages encompass enhanced efficacy and efficiency of remedies, as well as the capacity to customize solutions to suit the unique requirements and circumstances of individuals. Nevertheless, the present study also considers the constraints associated with private law mechanisms, such as the financial and procedural intricacies of legal proceedings, the possibility of imbalanced negotiation power, and the potential to worsen pre-existing disparities and systemic inequities. The paper posits that the adoption of a private law-based approach to human rights necessitates a meticulous design and implementation process in order to mitigate potential risks and optimize the advantages. In conclusion, this study examines the ramifications of these discoveries on policy and practice, highlighting the necessity for heightened awareness and education regarding the capacity of private law to advance and safeguard human rights. Additionally, it underscores the significance of establishing efficient and easily accessible mechanisms for upholding human rights within the private domain. The paper concludes by providing recommendations for future research in this domain, specifically emphasizing the necessity for additional empirical investigations to assess the efficacy and consequences of private law-oriented strategies in safeguarding human rights.

Keywords: private law, human rights, promoting, protecting, access to justice

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Authors: Laura Pytel, Georg Baumann, Gregor Gstrein, Corina Klug

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Premium cars often coat the instrument panels with a bilaminate consisting of a soft foam and a plastic skin. The coating is torn open during the passenger airbag deployment under high strain rates. Characterizing and simulating the top coat layer is crucial for predicting the attenuation that delays the airbag deployment, effecting the design of the restrain system and to reduce the demand of simulation adjustments through expensive physical component testing.Up to now, bilaminates used within cars either have been modelled by using a two-dimensional shell formulation for the whole coating system as one which misses out the interaction of the two layers or by combining a three-dimensional formulation foam layer with a two-dimensional skin layer but omitting the foam in the significant parts like the expected tear line area and the hinge where high compression is expected. In both cases, the properties of the coating causing the attenuation are not considered. Further, at present, the availability of material information, as there are failure dependencies of the two layers, as well as the strain rate of up to 200 1/s, are insufficient. The velocity of the passenger airbag flap during an airbag shot has been measured with about 11.5 m/s during first ripping; the digital image correlation evaluation showed resulting strain rates of above 1500 1/s. This paper provides a high strain rate material characterization of a bilaminate consisting of a thin polypropylene foam and a thermoplasctic olefins (TPO) skin and the creation of validated material models. With the help of a Split Hopkinson tension bar, strain rates of 1500 1/s were within reach. The experimental data was used to calibrate and validate a more physical modelling approach of the forced ripping of the bilaminate. In the presented model, the three-dimensional foam layer is continuously tied to the two-dimensional skin layer, allowing failure in both layers at any possible position. The simulation results show a higher agreement in terms of the trajectory of the flaps and its velocity during ripping. The resulting attenuation of the airbag deployment measured by the contact force between airbag and flaps increases and serves usable data for dimensioning modules of an airbag system.

Keywords: bilaminate ripping behavior, High strain rate material characterization and modelling, induced material failure, TPO and foam

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Authors: Laxmi R. Kasaraneni

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The Internet connects all the networks, including the nation’s critical infrastructure that are used extensively by not only a nation’s government and military to protect sensitive information and execute missions, but also the primary infrastructure that provides services that enable modern conveniences such as education, potable water, electricity, natural gas, and financial transactions. It has become the central nervous system for the government, the citizens, and the industries. When it is attacked, the effects can ripple far and wide impacts not only to citizens’ well-being but nation’s economy, civil infrastructure, and national security. As such, these critical services may be targeted by malicious hackers during cyber warfare, it is imperative to not only protect them and mitigate any immediate or potential threats, but to also understand the current or potential impacts beyond the IT networks or the organization. The Nation’s IT infrastructure which is now vital for communication, commerce, and control of our physical infrastructure, is highly vulnerable to attack. While existing technologies can address some vulnerabilities, fundamentally new architectures and technologies are needed to address the larger structural insecurities of an infrastructure developed in a more trusting time when mass cyber attacks were not foreseen. This research is intended to improve the core functions of the Internet and critical-sector information systems by providing a clear path to create a safe, secure, and resilient cyber environment that help stakeholders at all levels of government, and the private sector work together to develop the cybersecurity capabilities that are key to our economy, national security, and public health and safety. This research paper also emphasizes the present and future cyber security threats, the capabilities and goals of cyber attackers, a strategic concept and steps to implement cybersecurity for maximum effectiveness, enabling technologies, some strategic assumptions and critical challenges, and the future of cyberspace.

Keywords: critical challenges, critical infrastructure, cyber security, enabling technologies, national security

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Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

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Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: Bello, A., Muhammed Ibrahim Abba., Abdullahi, M., Dauda, Sabo, & Shittu, A. T.

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This study investigated the Predictors of Lecturers Knowledge Sharing Acceptance on Open Educational Resources (OER) in North-East Nigerian in Universities. The study population comprised of 632 lecturers of Federal Universities in North-east Nigeria. The study sample covered 338 lecturers who were selected purposively from Adamawa, Bauchi and Borno State Federal Universities in Nigeria. The study adopted a prediction correlational research design. The instruments used for data collection was the questionnaire. Experts in the field of educational technology validated the instrument and tested it for reliability checks using Cronbach’s alpha. The constructs on lecturers’ acceptance to share OER yielded a reliability coefficient of; α = .956 for Performance Expectancy, α = .925; for Effort Expectancy, α = .955; for Social Influence, α = .879; for Facilitating Conditions and α = .948 for acceptance to share OER. the researchers contacted the Deanery of faculties of education and enlisted local coordinators to facilitate the data collection process at each university. The data was analysed using multiple sequential regression statistic at a significance level of 0.05 using SPSS version 23.0. The findings of the study revealed that performance expectancy (β = 0.658; t = 16.001; p = 0.000), effort expectancy (β = 0.194; t = 3.802; p = 0.000), social influence (β = 0.306; t = 5.246; p = 0.000), collectively indicated that the variables have a predictive capacity to stimulate lecturer’s acceptance to share their resources on OER repository. However, the finding revealed that facilitating conditions (β = .053; t = .899; p = 0.369), does not have a predictive capacity to stimulate lecturer’s acceptance to share their resources on OER repository. Based on these findings, the study recommends among others that the university management should consider adjusting OER policy to be centered around actualizing lecturers career progression.

Keywords: acceptance, lecturers, open educational resources, knowledge sharing

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Authors: Franco Primo Soffietti, Diego Fernando Turello, Federico Pinto

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Shear waves that propagate through the ground impose deformations that must be taken into account in the design and assessment of buried longitudinal structures such as tunnels, pipelines, and piles. Conventional engineering approaches for seismic evaluation often rely on a Euler-Bernoulli beam models supported by a Winkler foundation. This approach, however, falls short in capturing the distortions induced when the structure is subjected to shear waves. To overcome these limitations, in the present work an analytical solution is proposed considering a Timoshenko beam and including transverse and rotational springs. The present research proposes ground springs derived as closed-form analytical solutions of the equations of elasticity including the seismic wavelength. These proposed springs extend the applicability of previous plane-strain models. By considering variations in displacements along the longitudinal direction, the presented approach ensures the springs do not approach zero at low frequencies. This characteristic makes them suitable for assessing pseudo-static cases, which typically govern structural forces in kinematic interaction analyses. The results obtained, validated against existing literature and a 3D Finite Element model, reveal several key insights: i) the cutoff frequency significantly influences transverse and rotational springs; ii) neglecting displacement variations along the structure axis (i.e., assuming plane-strain deformation) results in unrealistically low transverse springs, particularly for wavelengths shorter than the structure length; iii) disregarding lateral displacement components in rotational springs and neglecting variations along the structure axis leads to inaccurately low spring values, misrepresenting interaction phenomena; iv) transverse springs exhibit a notable drop in resonance frequency, followed by increasing damping as frequency rises; v) rotational springs show minor frequency-dependent variations, with radiation damping occurring beyond resonance frequencies, starting from negative values. This comprehensive analysis sheds light on the complex behavior of embedded longitudinal structures when subjected to shear waves and provides valuable insights for the seismic assessment.

Keywords: shear waves, Timoshenko beams, Winkler springs, sol-structure interaction

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Authors: T. Aragaw, P. Gari

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In spite of social, political, and economic marginalization, women are still considered as the backbone of Ethiopia, one of the least developed countries in the world. The general purpose of this study was to assess factors that affect participation of women in politics, social and economic decisions at Kelem-Wollega Administrative Zone of Oromia Regional State, Ethiopia. Data used in this paper is mainly primary, and a few secondary data were incorporated. Respondents were selected using a systematic random sampling method and were placed questionnaires containing open-ended and closed-ended. Focus group discussion was also used for the study subjects in two offices. According to the information collected from the KWAZ Development and Social Service Office, a total of 18,473 tax-paying employees are present in the Zone, which is 14% of the total population of the Zone. Among the total number of employees in the Zone, 2,617 have been recruited for this study based on the criteria stated. This showed 1.8% of them were comprised of several churches and religious owned integrated development projects in the KWAZ. The 2,103 (80.34%) study participants responded personally, and they completed and returned the questionnaire to the researchers. The study revealed that in public institutions existed in KWAZ, the majority of women were having an educational status of diploma and lower, practicing lower non-decision making and leadership positions. Conclusion: Major barriers hindering women include: Socio-cultural attitudes, lack of necessary experience, education, the burden of domestic responsibilities, and lack of role models of women leaders in the Zone. Empowerment of women via social organizations, critical involvement of the government, and Affirmative action for women is critical. Further research is needed on the scope and challenges in implementing the strategies.

Keywords: women, affirmative action, leadership, empowerment, Ethiopia

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Mahdi PourAsghar, Abbas Mas'udzadeh, Abdulhakim Tirgari, Saeed Dabiri Roushan, Hooman Rashidi, Fariba Salehi

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Objective: One of the major objectives in sports areas is to achieve maximum athletic performance. Physical and psychological preparations are the basic factors for achieving maximum performance in athletes. Unfortunately, in the field of physical preparation, we can see maximum attention and planning of trainers and sports officials. But despite the importance of psychological preparation of athletes and its serious and profound effect on athletic performance, the results of sports competitions show that less attention is paid to this topic, and it is less under the control of counselors and psychologists in different areas of our sport. Therefore, this study aimed to evaluate the attitude of athletes and coaches to sport psychology. Materials and methods: A descriptive study with a sample size of 234 elite athletes and 216 skilled coaches was conducted in different areas of sports, in Sari, Mazandaran in 2015.The instrument was a questionnaire consisting of two parts of demographic data and Martin questionnaire, assessing the attitude to sport psychology. The data from this study were analyzed using Spss version 18, descriptive statistics tests, and Chi-square test. Results: In this study, positive attitudes of participants in need and confidence towards sport psychology consultation in athletes and coaches group were 55/1 and 56/5 percent, respectively. The positive attitude of female athletes in belief to psychology consultation was more than male athletes. Athletes with higher education had more positive attitude towards the presence of psychologists and psychiatrists in fields of sports. Conclusion: According to the findings based on the need to the psychology consultation in different areas of sports, it is recommended that through training of specialists in the field of sport psychology and review of sports programs in different fields of sports, the presence of these counselors to maintain the psychological preparation of athletes to achieve maximum athletic performance and reduce anxiety and stress be used.

Keywords: Keywords: Athletes, Eliteathletes, Coaches, Attitude, Sport psychology.

Procedia PDF Downloads 325

Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: Anastasia Papachristou, Anastasia Ntikoudi, Vasileios Saridakis

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The safety and health care needs of refugees have become an increasingly important issue all over the world especially during last few decades. Wars are the primary reason for refugees to leave their countries. Moreover, refugees are frequently exposed to a variety of stressors such as socioeconomic disadvantages, poverty, changes in family structure and functioning, losing social support, difficulty to access education, living in very crowded places, experiencing racism and isolation. This systematic review included research studies published between 2007-2017 from the search databases Medline, Scopus, Cinahl and PubMed, with keywords 'war survivors', 'war trauma', 'psychiatric disorders', 'refugees'. In order to meet the purpose of the systematic review, further research for complementary studies was conducted into the literature references of the research articles included in this study that would meet the criteria. Overall, 14 studies were reviewed and evaluated. The majority of them demonstrated that the most common psychiatric disorders observed among war refugees are post-traumatic stress disorder (PTSD), depression, anxiety and multiple somatic complaints. Moreover, significant relationship was shown between the number of traumatic events experienced by the refugees and sociodemographic features such as gender, age and previous family history of any psychological disorder. War violence is highly traumatic, causing multiple, long-term negative outcomes such as the aforementioned psychiatric disorders. The number of the studies reviewed in this systematic review is not representative of the problem and its significance. The need for care of the survivors and their families is vital. Further research is necessary in order to clarify the role of predictive factors in the development and maintenance of post-traumatic stress and the rest psychiatric disorders following war trauma. In conclusion, it is necessary to have large multicenter studies in the future in order to be able to draw reliable conclusions about the effects of war.

Keywords: psychiatric disorders, refugees, war survivors, war trauma

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: Aryan Sood, Shruti Pathak, Dipanshu Chaudhary, Shreyanshi, Yogesh Pal

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In this comprehensive meta-analysis, the study delves into the widespread issue of body shaming, revealing its pervasive impact on various aspects of human life and its profound implications for mental health. The paper first explores the origins of body shaming, including societal norms, media influences, and interpersonal dynamics. It highlights the various forms it takes and its detrimental effects on self-esteem, body image, and psychological well-being. Particularly among adolescents and teenagers in today's social media-driven world, the pressure to conform to idealized beauty standards is significant, leading to negative consequences for their development and health. The research emphasizes the long-lasting mental health effects of body shaming, including depression, body dysmorphia, low self-esteem, and eating disorders. The study also discusses the emergence of body positivity movements as a means to challenge societal norms and promote inclusivity and empathy. Furthermore, the research addresses body shaming in the workplace and presents strategies to combat it, stressing the importance of awareness campaigns, education, and policy changes. In conclusion, the study underscores the critical need for a culture of acceptance and support, the promotion of positive body image, and efforts to mitigate the severe mental health toll that body shaming takes on individuals and communities. Overall, this research provides a comprehensive overview of body shaming, its root causes, and its far-reaching impacts on mental health and well-being. It highlights the urgency of addressing this issue in various contexts, from adolescence to the workplace, and offers solutions, such as awareness campaigns and societal changes, to foster a more inclusive and empathetic future.

Keywords: body shaming, mental health, age, gender, societal norms, appearance-based discrimination, cyberbullying, self-esteem, social media, depression, acceptance

Procedia PDF Downloads 51

Authors: Jaspreet Kaur, Parminder Nain, Vipin Saini, Sumitra Dahiya

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Elaeocarpus sphaericus has been traditionally used in the Indian traditional medicine system for the treatment of stress, anxiety, depression, palpitation, epilepsy, migraine and lack of concentration. The study was investigated to evaluate the neurological potential such as anxiolytic, muscle relaxant and sedative activity of methanolic extract of Elaeocarpus sphaericus stem bark (MEESSB) in mice. Preliminary phytochemical screening and acute oral toxicity of MEESSB was carried out by using standard methods. The anxiety was induced by employing Elevated Plus-Maze (EPM), Light and Dark Test (LDT), Open Field Test (OFT) and Social Interaction test (SIT). The motor coordination and sedative effect was also observed by using actophotometer, rota-rod apparatus and ketamine-induced sleeping time, respectively. Animals were treated with different doses of MEESSB (i.e.100, 200, 400 and 800 mg/kg orally) and diazepam (2 mg/kg i.p) for 21 days. Brain neurotransmitters like dopamine, serotonin and nor-epinephrine level were estimated by validated methods. Preliminary phytochemical analysis of the extract revealed the presence of tannins, phytosterols, steroids and alkaloids. In the acute toxicity studies, MEESSB was found to be non-toxic and with no mortality. In anxiolytic studies, the different doses of MEESSB showed a significant (p<0.05) effect on EPM and LDT. In OFT and SIT, a significant (p<0.05) increase in ambulation, rearing and social interaction time was observed. In the case of motor coordination activity, the MEESSB does not cause any significant effect on the latency to fall off from the rotarod bar as compared to the control group. Moreover, no significant effects on ketamine-induced sleep latency and total sleeping time induced by ketamine were observed. Results of neurotransmitter estimation revealed the increased concentration of dopamine, whereas the level of serotonin and nor-epinephrine was found to be decreased in the mice brain, with MEESSB at dose 800 mg/kg only. The study has validated the folkloric use of the plant as an anxiolytic in Indian traditional medicine while also suggesting potential usefulness in the treatment of stress and anxiety without causing sedation.

Keywords: anxiolytic, behavior experiments, brain neurotransmitters, elaeocarpus sphaericus

Procedia PDF Downloads 159