Search results for: gender specific data

Authors: Mohammad Didar Hossain

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Background/Purpose: The purpose of this study was to examine the associations between productive engagements and the psychological well-being of older adults in the U.S by analyzing cross-sectional data from a secondary dataset. Specifically, this paper analyzed the associations of 4 different types of productive engagements, including current work status, caregiving to the family members, volunteering and religious strengths with the psychological well-being as an outcome variable. Methods: Data and sample: The study used the data from the Health and Retirement Study (HRS). The HRS is a nationally representative prospective longitudinal cohort study that has been conducting biennial surveys since 1992 to community-dwelling individuals 50 years of age or older on diverse issues. This analysis was based on the 2016 wave (cross-sectional) of the HRS dataset and the data collection period was April 2016 through August 2017. The samples were recruited from a multistage, national area-clustered probability sampling frame. Measures: Four different variables were considered as the predicting variables in this analysis. Firstly, current working status was a binary variable that measured by 0=Yes and 1= No. The second and third variables were respectively caregiving and volunteering, and both of them were measured by; 0=Regularly, 1= Irregularly. Finally, find in strength was measured by 0= Agree and 1= Disagree. Outcome (Wellbeing) variable was measured by 0= High level of well-being, 1= Low level of well-being. Control variables including age were measured in years, education in the categories of 0=Low level of education, 1= Higher level of education and sex r in the categories 0=male, 1= female. Analysis and Results: Besides the descriptive statistics, binary logistic regression analyses were applied to examine the association between independent and dependent variables. The results showed that among the four independent variables, three of them including working status (OR: .392, p<.001), volunteering (OR: .471, p<.003) and strengths in religion (OR .588, p<.003), were significantly associated with psychological well-being while controlling for age, gender and education factors. Also, no significant association was found between the caregiving engagement of older adults and their psychological well-being outcome. Conclusions and Implications: The findings of this study are mostly consistent with the previous studies except for the caregiving engagements and their impact on older adults’ well-being outcomes. Therefore, the findings support the proactive initiatives from different micro to macro levels to facilitate opportunities for productive engagements for the older adults, and all of these may ultimately benefit their psychological well-being and life satisfaction in later life.

Keywords: productive engagements, older adults, psychological wellbeing, productive aging

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Authors: Nasrin Badrkhani

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Teaching is an interaction between the teacher, student, and the concept being taught, especially within the classroom setting. As society increasingly values thoughtful and creative individuals, there is a growing need to adopt modern, active teaching methods. These methods should engage students in activities that foster problem-solving, creativity, cooperation, and scientific thinking skills. Modern teaching methods emphasize student involvement, gradual and continuous learning (process-centered approaches), and holistic evaluation of students' abilities and talents. A shift from teacher-centered to student-centered teaching is crucial. Among these modern methods are group work, role-playing, group discussions, and activities that engage students in evaluating societal values. This research employs a survey and a 38-question Likert scale questionnaire to explore teachers' perspectives on the impact of modern teaching methods on the quality of education. The study also examines the relationship between these perspectives and variables such as gender, major, and teaching experience. The statistical population consists of high school teachers in Shiraz, Iran, with sampling done using the Morgan table. Discriminant analysis was used for the initial analysis of the questions, and Cronbach's Alpha test was employed for the final examination. SPSS Software was used for statistical analysis, including T-tests and one-way ANOVA. The results indicate that teachers in this city generally have positive attitudes towards the use of modern teaching methods, except when it comes to engaging in judgments concerning societal values. There is no significant difference in viewpoints based on gender or educational background. The findings are consistent with similar studies conducted both within Iran and internationally.

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

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Authors: Jelena Vucicevic

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Reliability analysis represents a very important task in different areas of work. In any industry, this is crucial for maintenance, efficiency, safety and monetary costs. There are ways to calculate reliability, unreliability, failure density and failure rate. This paper will try to introduce another way of calculating reliability by using R statistical software. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. The R programming environment is a widely used open source system for statistical analysis and statistical programming. It includes thousands of functions for the implementation of both standard and new statistical methods. R does not limit user only to operation related only to these functions. This program has many benefits over other similar programs: it is free and, as an open source, constantly updated; it has built-in help system; the R language is easy to extend with user-written functions. The significance of the work is calculation of time to failure or reliability in a new way, using statistic. Another advantage of this calculation is that there is no need for technical details and it can be implemented in any part for which we need to know time to fail in order to have appropriate maintenance, but also to maximize usage and minimize costs. In this case, calculations have been made on diesel generator fans but the same principle can be applied to any other part. The data for this paper came from a field engineering study of the time to failure of diesel generator fans. The ultimate goal was to decide whether or not to replace the working fans with a higher quality fan to prevent future failures. Seventy generators were studied. For each one, the number of hours of running time from its first being put into service until fan failure or until the end of the study (whichever came first) was recorded. Dataset consists of two variables: hours and status. Hours show the time of each fan working and status shows the event: 1- failed, 0- censored data. Censored data represent cases when we cannot track the specific case, so it could fail or success. Gaining the result by using R was easy and quick. The program will take into consideration censored data and include this into the results. This is not so easy in hand calculation. For the purpose of the paper results from R program have been compared to hand calculations in two different cases: censored data taken as a failure and censored data taken as a success. In all three cases, results are significantly different. If user decides to use the R for further calculations, it will give more precise results with work on censored data than the hand calculation.

Keywords: censored data, R statistical software, reliability analysis, time to failure

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Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: A. Anis, W. Bekheet, A. El Hakim

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Implementing a Road Safety Management System (SMS) in a crowded developing country such as Egypt is a necessity. Beginning a sustainable SMS requires a comprehensive reliable data system for all information pertinent to road crashes. In this paper, a survey for the available data in Egypt and validating it for using in an SMS in Egypt. The research provides some missing data, and refer to the unavailable data in Egypt, looking forward to the contribution of the scientific society, the authorities, and the public in solving the problem of missing or unreliable crash data. The required data for implementing an SMS in Egypt are divided into three categories; the first is available data such as fatality and injury rates and it is proven in this research that it may be inconsistent and unreliable, the second category of data is not available, but it may be estimated, an example of estimating vehicle cost is available in this research, the third is not available and can be measured case by case such as the functional and geometric properties of a facility. Some inquiries are provided in this research for the scientific society, such as how to improve the links among stakeholders of road safety in order to obtain a consistent, non-biased, and reliable data system.

Keywords: road safety management system, road crash, road fatality, road injury

Procedia PDF Downloads 152

Authors: Pegah Ebrahimi, Farshad Oveissi, Iman Manavi-Tehrani, Sina Naficy, David F. Fletcher, Fariba Dehghani, David S. Winlaw

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Despite advances in modern surgery, congenital heart disease remains a medical challenge and a major cause of infant mortality. Cardiovascular prostheses are routinely used in surgical procedures to address congenital malformations, for example establishing a pathway from the right ventricle to the pulmonary arteries in pulmonary valvar atresia. Current off-the-shelf options including human and adult products have limited biocompatibility and durability, and their fixed size necessitates multiple subsequent operations to upsize the conduit to match with patients’ growth over their lifetime. Non-physiological blood flow is another major problem, reducing the longevity of these prostheses. These limitations call for better designs that take into account the hemodynamical and anatomical characteristics of different patients. We have integrated tissue engineering techniques with modern medical imaging and image processing tools along with mathematical modeling to optimize the design of cardiovascular grafts in a patient-specific manner. Computational Fluid Dynamics (CFD) analysis is done according to models constructed from each individual patient’s data. This allows for improved geometrical design and achieving better hemodynamic performance. Tissue engineering strives to provide a material that grows with the patient and mimic the durability and elasticity of the native tissue. Simulations also give insight on the performance of the tissues produced in our lab and reduce the need for costly and time-consuming methods of evaluation of the grafts. We are also developing a methodology for the fabrication of the optimized designs.

Keywords: computational fluid dynamics, cardiovascular grafts, design optimization, tissue engineering

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Authors: Sameh Shahin, Nannang Arrys

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Optimizing pit slope stability and reducing strip ratio of a mining operation are two key tasks in geotechnical engineering. With a growing demand for minerals and an increasing cost associated with extraction, companies are constantly re-evaluating the viability of mineral deposits and challenging their geological understanding. Within Rio Tinto Iron Ore, the Structural Geology (SG) team investigate and collect critical data, such as point based orientations, mapping and geological inferences from adjacent pits to re-model deposits where previous interpretations have failed to account for structurally controlled slope failures. Utilizing innovative data collection methods and data-driven investigation, SG aims to address the root causes of slope instability. Committing to a resource grid drill campaign as the primary source of data collection will often bias data collection to a specific orientation and significantly reduce the capability to identify and qualify complexity. Consequently, these limitations make it difficult to construct a realistic and coherent structural model that identifies adverse structural domains. Without the consideration of complexity and the capability of capturing these structural domains, mining operations run the risk of inadequately designed slopes that may fail and potentially harm people. Regional structural trends have been considered in conjunction with surface and in-pit mapping data to model multi-batter fold structures that were absent from previous iterations of the structural model. The risk is evident in newly identified dip-slope and rock-mass controlled sectors of the geotechnical design rather than a ubiquitous dip-slope sector across the pit. The reward is two-fold: 1) providing sectors of rock-mass controlled design in previously interpreted structurally controlled domains and 2) the opportunity to optimize the slope angle for mineral recovery and reduced strip ratio. Furthermore, a resulting high confidence model with structures and geometries that can account for historic slope instabilities in structurally controlled domains where design assumptions failed.

Keywords: structural geology, geotechnical design, optimization, slope stability, risk mitigation

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Authors: Moyera Sanganeria

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In the highly competitive landscape of contemporary sports, sportspersons worldwide encounter formidable challenges, often practicing for extensive hours while contending with limited social and physical resources. A growing number of sportspersons globally are sharing their struggles with depression, anxiety, and stress arising from the complex journey and identity associated with being a sportsperson. This qualitative study aims to investigate the challenges faced by sportspersons in individual versus team sports and explore potential gender-based variations in coping strategies. It attempts to do so by recognizing the imperative to comprehend the root causes and coping mechanisms for these stressors. By employing purposive sampling, MMA and Kabaddi players from training academies across Mumbai were selected for the study. Twelve participants were interviewed through semi-structured interviews guided by an interview guide. Reflective thematic analysis was employed to discern diverse stressors and coping strategies. Key stressors encountered by young Indian sportspersons encompass injuries, socio-economic challenges, financial constraints, escalating competition, and performance anxiety. Notably, individuals engaged in team sports tended to adopt emotion-focused coping mechanisms, while those in individual sports leaned more towards problem-focused coping strategies in response to these stressors. There were no prominent gender differences found in coping strategies employed by sportspersons. This study underscores the critical issue of declining mental health among sportspersons in India, emphasizing the necessity for a structured and customized mental health intervention strategy tailored to the unique needs of this population.

Keywords: stressors, coping strategies, sports psychology, sportspersons, mental health

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Authors: Palanisamy Samyraj, Sriram Yogesh, Kishore Kumar, Vaishak Cibi

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The project is about design and analysis of crankshaft using Al-Al2O3 composite material. The project is mainly concentrated across two areas one is to design and analyze the composite material, and the other is to work on the practical model. Growing competition and the growing concern for the environment has forced the automobile manufactures to meet conflicting demands such as increased power and performance, lower fuel consumption, lower pollution emission and decrease noise and vibration. Metal matrix composites offer good properties for a number of automotive components. The work reports on studies on Al-Al2O3 as the possible alternative material for a crank shaft. These material have been considered for use in various components in engines due to the high amount of strength to weight ratio. These materials are significantly taken into account for their light weight, high strength, high specific modulus, low co-efficient of thermal expansion, good air resistance properties. In addition high specific stiffness, superior high temperature, mechanical properties and oxidation resistance of Al2O3 have developed some advanced materials that are Al-Al2O3 composites. Crankshafts are used in automobile industries. Crankshaft is connected to the connecting rod for the movement of the piston which is subjected to high stresses which cause the wear of the crankshaft. Hence using composite material in crankshaft gives good fuel efficiency, low manufacturing cost, less weight.

Keywords: metal matrix composites, Al-Al2O3, high specific modulus, strength to weight ratio

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Authors: Sadia Basar, Naila Habib, Awais Adnan

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The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

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Authors: Veronika Solopova, Oana-Iuliana Popescu, Tim Landgraf, Christoph Benzmüller

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Beginning in 2014, slowly building geopolitical tensions in Eastern Europe led to a full-blown conflict between the Russian Federation and Ukraine that generated an unprecedented amount of news articles and data from social media data, reflecting the opposing ideologies and narratives as a background and the essence of the ongoing war. These polarized informational campaigns have led to countless mutual accusations of misinformation and fake news, shaping an atmosphere of confusion and mistrust for many readers all over the world. In this study, we analyzed scraped news articles from Ukrainian, Russian, Romanian and English-speaking news outlets, on the eve of 24th of February 2022, compared to day five of the conflict (28th of February), to see how the media influenced and mirrored the changes in public opinion. We also contrast the sources opposing and supporting the stands of the Russian government in Ukrainian, Russian and Romanian media spaces. In a data-driven way, we describe how the narratives are spread throughout Eastern and Central Europe. We present predictive linguistic features surrounding war propaganda. Our results indicate that there are strong similarities in terms of rhetoric strategies in the pro-Kremlin media in both Ukraine and Russia, which, while being relatively neutral according to surface structure, use aggressive vocabulary. This suggests that automatic propaganda identification systems have to be tailored for each new case, as they have to rely on situationally specific words. Both Ukrainian and Russian outlets lean towards strongly opinionated news, pointing towards the use of war propaganda in order to achieve strategic goals.

Keywords: linguistic, news, propaganda, Russia, ukraine

Procedia PDF Downloads 123

Authors: Hassan Athari, Alireza Ruhi Sales, Amin Pourafshar, Seyyed Mehdi Pestei, Marc. A. Rosen

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In order to achieve high efficiency and high specific work with lower emissions, the use of advanced gas turbine cycles for power generation is useful and advantageous. Here, evaporative inlet air cooling is analyzed thermodynamically in the form of air film blade cooling of gas turbines. As the ambient temperature increases during summer months, the performance of gas turbines particularly the output power and energy efficiency are significantly decreased. The utilization of evaporative inlet cooling in gas turbine cycles increases gas turbine performance, which can assist to solve the problem in meeting the increasing demands for electrical power and offsetting shortages during peak load times. In the present research, because of the importance of turbine blade cooling, the turbine is investigated with cold compressed air used for cooling the turbine blades. The investigation of the basic and modified cycles shows that, by adding an evaporative cooler to a simple gas turbine cycle, for a turbine inlet temperature of 1400 °C, an ambient temperature of 45 °C and a relative humidity of 15%, the specific work can reach 331 (kJ/kg air), while the maximum specific work of a simple cycle for the same conditions is 273.7 (kJ/kg air). The exergy results reveal that the highest exergy destruction occurs in the combustion chamber, where the large temperature differences and highly exothermic chemical reactions are the main sources of the irreversibility.

Keywords: energy, exergy, wet compression, air-film cooling blade, gas turbine

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Authors: Agodo Mugenyi Herbert

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Background: A high prevalence of both HIV infection and mental disorders exists in Sub-Saharan Africa, however there is little integration of care for mental health disorders among HIV-infected individuals. The study aimed at determining the management of common mental disorders among HIV/AIDS clients attending Antiretroviral clinic in Hoima regional referral hospital. Significancy of the study: The information generated by this study would help mental health advocates, ministry of health, Civil society organizations in HIV programming to advocate for enhanced mental health care for PLWHA. The result will be used in policy development and lobbying for integration of mental health care in HIV/AIDS care. Methods: This study applied a cross sectional design. It involved data collection from clients with HIV/AIDS attending ART clinic in Hoima regional referral hospital at one specific point in time. It aimed at providing data on the entire population under study. Data was collected from Hoima Regional Referral Hospital at the ART clinic. Data analysis was performed using SPSS version 24. Results: 66 HIV/AIDS clients and 10 health workers in the ART clinic who participated fully completed the study. The overall prevalence of at least one form of mental disorder was 83%. Majority of the health care practitioner do not use pharmacological, psychological, and social interventions to manage such disorders. Conclusion: These results are suggestive of a significant proportion of the HIV-infected patients experiencing psychological difficulty for which they do not receive treatment Recommendations: Current care practices applied to patients with HIV/AIDS should be integrated more generally to include treatment services to identify and manage common mental disorders.

Keywords: common mental disorders, mental health, mental illness, and severe mental illness

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Authors: Vibha Sinha, Sumedha Chakma

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Arsenic (As) contamination in drinking water is a serious concern worldwide resulting in severe health maladies. To tackle this problem, several hydrogel based matrix which selectively uptake toxic metals from contaminated water has increasingly been examined as a potential practical method for metal removal. The major concern in hydrogels is low stability of matrix, resulting in poor performance. In this study, the potential of hybrid hydrogel-biochar matrix synthesized from natural plant polymers, specific for As removal was explored. Various compositional and functional group changes of the elements contained in the matrix due to the adsorption of As were identified. Moreover, to resolve the stability issue in hydrogel matrix, optimum and effective mixing of hydrogel with biochar was studied. Mixing varied proportions of matrix components at the time of digestion process was tested. Preliminary results suggest that partial premixing methods may increase the stability and reduce cost. Addition of nanoparticles and specific catalysts with different concentrations of As(III) and As(V) under batch conditions was performed to study their role in performance enhancement of the hydrogel matrix. Further, effect of process parameters, optimal uptake conditions and detailed mechanism derived from experimental studies were suitably conducted. This study provides an efficient, specific and a low-cost As removal method that offers excellent regeneration abilities which can be reused for value.

Keywords: arsenic, catalysts, hybrid hydrogel-biochar, water purification

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Authors: Ian Walmsley

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The aim of this paper is to explore the influence of time and temporality on the experience of coming off heroin in prison. The presentation draws on qualitative data collected during a small-scale pilot study of the role of self-care in the process of coming off drugs in prison. Time and temporality emerged as a key theme in the interview transcripts. Drug dependent prisoners experience of time in prison has not been recognized in the research literature. Instead, the literature on prison time typically views prisoners as a homogenous group or tends to focus on the influence of aging and gender on prison time. Furthermore, there is a tendency in the literature on prison drug treatment and recovery to conceptualize drug dependent prisoners as passive recipients of prison healthcare, rather than active agents. In building on these gaps, this paper argues that drug dependent prisoners experience multiple temporalities which involve an interaction between the body-times of the drug dependent prisoner and the economy of time in prison. One consequence of this interaction is the feeling that they are doing, at this point in their prison sentence, double prison time. The second part of the argument is that time and temporality were a means through which they governed their withdrawing bodies. In addition, this paper will comment on the challenges of prison research in England.

Keywords: heroin withdrawal, time and temporality, prison, body

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Authors: Mohammad Abdul Matin

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This research paper aims to investigate the use of cryptocurrency in facilitating cross-border payments, with a specific focus on the case of Bangladesh. With thousands of Bangladeshi living abroad, the demand for efficient and cost-effective remittance channels is high. This paper will examine the current challenges in cross-border payments for Bangladeshi expatriates and explore the potential benefits and barriers to the adoption of cryptocurrency as a solution. Through a combination of literature review, qualitative interviews, and data analysis, the research will provide valuable insights into the opportunities and risks associated with using cryptocurrency for cross-border payments in Bangladesh.

Keywords: cryptocurrency, cross-border payments, Bangladesh, remittance, expatriates

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Authors: Silvia Arrate, Waldo Salud, Eloy París

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The wear of cutting tools is one of the most decisive elements when planning tunneling works, programming the maintenance stops and saving the optimum stock of spare parts during the evolution of the excavation. Being able to predict the behavior of cutting tools can give a very competitive advantage in terms of costs and excavation performance, optimized to the needs of the TBM itself. The incredible evolution of data science in recent years gives the option to implement it at the time of analyzing the key and most critical parameters related to machinery with the purpose of knowing how the cutting head is performing in front of the excavated ground. Taking this as a case study, Metro Line 3 of Guadalajara in Mexico will develop the feasibility of using Specific Energy versus data science applied over parameters of Torque, Penetration, and Contact Force, among others, to predict the behavior and status of cutting tools. The results obtained through both techniques are analyzed and verified in the function of the wear and the field situations observed in the excavation in order to determine its effectiveness regarding its predictive capacity. In conclusion, the possibilities and improvements offered by the application of digital tools and the programming of calculation algorithms for the analysis of wear of cutting head elements compared to purely empirical methods allow early detection of possible damage to cutting tools, which is reflected in optimization of excavation performance and a significant improvement in costs and deadlines.

Keywords: cutting tools, data science, prediction, TBM, wear

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Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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Authors: Elvira Lumi, Hans Jazxhi

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In the works of the writer Flutura Açka, the play with these questions is acute, and in almost each of them, the act of loneliness and isolation builds in a completely involuntary way unique and frequent conceptual spaces. Because the object of study is too broad to grasp all the works, this study lays out a rapid paradox of our access to three of the novels in the line of numerous authorial works. The novel "Woman Loneliness" (2001), also marked as the first work in prose by the author, declares in the title the paradigm of what she has decided to confess. The gender segregation proclaimed in the title will be revealed step by step in the work as conventional human segregation without gender. In this novel, the analysis of the state of "loneliness" will require a contemplation beyond man, when the role of the environment and the distance from the center of the narrative base will be extremely visible in the work. The novel "Cross of Oblivion" (2004) has another form of perception of loneliness, which, unlike the one built by the characters themselves in the novel "Woman Loneliness," is imposed and obligatory to live by the circumstances. Its characters are trapped in loneliness, as loneliness that comes from impossibility, from the past, from dependence on fate, from fear of change, and from the obligation to accept it. At the heart of the novel, the plot of the novel game is dictated by the Kanun and its rules and the loneliness of the basis of life in unbroken waves towards the periphery of the event, a periphery that has very large geography and is played in today's Europe. The novel "Where are you?" (2009) has a completely different form of constructing the concept of loneliness and isolation that comes under conditions of repression and political pressure. The loneliness in this novel takes the form of the protective element from the circumstances that actually require a social inclusion; it is personal loneliness that ensures relative mental health of the characters, up to a new trap created by the circumstances, thus building life fragmentary “healthy” in the order of a mentally ill and socially ill society.

Keywords: loneliness, existential, isolation, woman, prose

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Authors: Muhammad Atif Randhawa, Adnan Amjad, Muhammad Nadeem

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Potato (Solanum tuberosum) popularly known as ‘the king of vegetables’, has emerged as fourth most important food crop after rice, wheat and maize. Potato contains carbohydrates, minerals, vitamins and antioxidants. The antioxidants of potatoes especially vitamin C helps in reducing cancer, cardiovascular diseases and high blood pressure by binding free radicals. Physical characteristics and some major chemical properties of potato tubers at fresh and stored stages were investigated. Two varieties of potatoes, Sante (V1) having white colour and Lal moti (V2) with red colour were stored for 3 months and analysis were performed after each month interval. Physical and chemical attributes including weight loss, sprouting, specific gravity, pH, total sugars (reducing and non-reducing sugars) and vitamin C were analyzed before and after storage. Value of weight loss at zero day was null but it increased to 6.45% after 90 days on average in both cultivars and sprouting increased gradually at the end of 90 days. Moreover total sugars were 3.10% at zero day but increased to 9.30% after 90 days. Ascorbic acid was decreased during storage from 17.49(mg/100g) to 3.79. Both varieties of potato were stored at 60C and 120C temperatures with 85% relative humidity in order to prolong their acceptability in the market. The storage conditions influence the potatoes quality and consequently their acceptability to consumer. The data was analyzed statistically and clarifies that total sugars, weight loss, sprouting and specific gravity increase during the storage period while ascorbic acid (Vit-C) and pH decreased. Among both varieties that were stored at 60C and 120C, Sante (V1) was better than Lal moti (V2) due to less physicochemical and quality changes at 60C as compared to store at 120C.

Keywords: physicochemical, potato, quality attributes, storage

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Authors: László Schmidt

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Technological and digital innovation is constantly and dynamically evolving, which poses an enormous challenge to both lawmaking and law enforcement. To legislation because artificial intelligence permeates many areas of people’s daily lives that the legislator must regulate. it can see how challenging it is to regulate e.g. self-driving cars/taxis/camions etc. Not to mention cryptocurrencies and Chat GPT, the use of which also requires legislative intervention. Artificial intelligence also poses an extraordinary challenge to law enforcement. In criminal cases, police and prosecutors can make great use of AI in investigations, e.g. in forensics, DNA samples, reconstruction, identification, etc. But it can also be of great help in the detection of crimes committed in cyberspace. In the case of cybercrime, on the one hand, it can be viewed as a new type of crime that can only be committed with the help of information systems, and that has a specific protected legal object, such as an information system or data. On the other hand, it also includes traditional crimes that are much easier to commit with the help of new tools. According to Hungarian Criminal Code section 375 (1), any person who, for unlawful financial gain, introduces data into an information system, or alters or deletes data processed therein, or renders data inaccessible, or otherwise interferes with the functioning of the information system, and thereby causes damage, is guilty of a felony punishable by imprisonment not exceeding three years. The Covid-19 coronavirus epidemic has had a significant impact on our lives and our daily lives. It was no different in the world of crime. With people staying at home for months, schools, restaurants, theatres, cinemas closed, and no travel, criminals have had to change their ways. Criminals were committing crimes online in even greater numbers than before. These crimes were very diverse, ranging from false fundraising, the collection and misuse of personal data, extortion to fraud on various online marketplaces. The most vulnerable age groups (minors and elderly) could be made more aware and prevented from becoming victims of this type of crime through targeted programmes. The aim of the study is to show the Hungarian judicial practice in relation to cybercrime and possible preventive solutions.

Keywords: cybercrime, COVID-19, Hungary, criminal law

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Authors: Rindra Rantoson, Hichem Nouira, Nabil Anwer, Charyar Mehdi-Souzani

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Multiple measurements by means of various data acquisition systems are generally required to measure the shape of freeform workpieces for accuracy, reliability and holisticity. The obtained data are aligned and fused into a common coordinate system within a registration technique involving coarse and fine registrations. Standardized iterative methods have been established for fine registration such as Iterative Closest Points (ICP) and its variants. For coarse registration, no conventional method has been adopted yet despite a significant number of techniques which have been developed in the literature to supply an automatic rough matching between data sets. Two main issues are addressed in this paper: the coarse registration and the fine registration. For coarse registration, two novel automated methods based on the exploitation of discrete curvatures are presented: an enhanced Hough Transformation (HT) and an improved Ransac Transformation. The use of curvature features in both methods aims to reduce computational cost. For fine registration, a new variant of ICP method is proposed in order to reduce registration error using curvature parameters. A specific distance considering the curvature similarity has been combined with Euclidean distance to define the distance criterion used for correspondences searching. Additionally, the objective function has been improved by combining the point-to-point (P-P) minimization and the point-to-plane (P-Pl) minimization with automatic weights. These ones are determined from the preliminary calculated curvature features at each point of the workpiece surface. The algorithms are applied on simulated and real data performed by a computer tomography (CT) system. The obtained results reveal the benefit of the proposed novel curvature-based registration methods.

Keywords: discrete curvature, RANSAC transformation, hough transformation, coarse registration, ICP variant, point-to-point and point-to-plane minimization combination, computer tomography

Procedia PDF Downloads 425

Authors: Thuan Nguyen

Abstract:

In the present time, data to a data-driven knowledge-based economy is the same as oil to the industrial age hundreds of years ago. Data is everywhere in vast volumes! Big data analytics is expected to help firms not only efficiently improve performance but also completely transform how they should run their business. However, employing the emergent technology successfully is not easy, and assessing the roles of big data in improving firm performance is even much harder. There was a lack of studies that have examined the impacts of big data analytics on organizational performance. This study aimed to fill the gap. The present study suggested using firms’ intellectual capital as a proxy for big data in evaluating its impact on organizational performance. The present study employed the Value Added Intellectual Coefficient method to measure firm intellectual capital, via its three main components: human capital efficiency, structural capital efficiency, and capital employed efficiency, and then used the structural equation modeling technique to model the data and test the models. The financial fundamental and market data of 100 randomly selected publicly listed firms were collected. The results of the tests showed that only human capital efficiency had a significant positive impact on firm profitability, which highlighted the prominent human role in the impact of big data technology.

Keywords: big data, big data analytics, intellectual capital, organizational performance, value added intellectual coefficient

Procedia PDF Downloads 246

Authors: Hitesh Tahbildar

Abstract:

The cost of test data generation for a program is computationally very high. In general case, no algorithm to generate test data for all types of algorithms has been found. The cost of generating test data for different types of algorithm is different. Till date, people are emphasizing the need to generate test data for different types of programming constructs rather than different types of algorithms. The test data generation methods have been implemented to find heuristics for different types of algorithms. Some algorithms that includes divide and conquer, backtracking, greedy approach, dynamic programming to find the minimum cost of test data generation have been tested. Our experimental results say that some of these types of algorithm can be used as a necessary condition for selecting heuristics and programming constructs are sufficient condition for selecting our heuristics. Finally we recommend the different heuristics for test data generation to be selected for different types of algorithms.

Keywords: ongest path, saturation point, lmax, kL, kS

Procedia PDF Downloads 408

Authors: Khader A. Almhdawi, Saddam F. Kanaan

Abstract:

Background: Allied health (AH) students, including rehabilitation sciences students, are subjected to significant levels of physical and mental stressors, which could affect their education. This study aimed to study physical and mental of Health-related Quality of Life (HR-QoL) levels along with their predictors among students of nine AH majors. Methods: Students filled validated anonymous surveys covering demographics and life style, Nordic Musculoskeletal Questionnaire, 12-item Short-Form Health Survey (SF-12), and Depression Anxiety Stress Scale (DASS- 42). SF-12 Mental (MCS) and Physical (PCS) summary scores were compared between academic majors and gender. Multiple linear regression models were conducted to examine potential predictors of PCS and MCS scores. Results: 838 students (77.4% females) participated in this study. Participants’ PCS mean score was 45.64±7.93 and found statistically different between the nine academic majors (P < 0.001). Additionally, participants’’ MCS mean score was 39.45±10.86 and significantly greater in males (P < 0.001). Significant PCS scores predictors included hip and upper back musculoskeletal pain, anxiety score, diet self-evaluation, and GPA. Finally, MCS scores were statistically associated with neck musculoskeletal pain, stress score, depression score, number of weekly clinical training hours, gender, university year, GPA, sleep quality self-evaluation, and diet self-evaluation. Conclusion: Clinical educators of AH need to account for students’ low levels of HR-QoL and their academic-related, health-related, and lifestyle-related associated factors. More studies are recommended to investigate the progression of HR-QoL throughout university years and to create effective interventions to improve HR-QoL among healthcare students.

Keywords: medical education, quality of life, stress, anxiety, depression

Procedia PDF Downloads 127

Authors: C. Cafaro, P. Ceci, L. De Giorgi

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The aim of this paper is to give an assessment of environmental effects of IPPC permit conditions of installations that are in the specific territory with a high concentration of industrial activities. The IPPC permit is the permit that each operator should hold to operate the installation as stated by the directive 2010/75/UE on industrial emissions (integrated pollution prevention and control), known as IED (Industrial Emissions Directive). The IPPC permit includes all the measures necessary to achieve a high level of protection of the environment as a whole, also defining the monitoring requirements as measurement methodology, frequency, and evaluation procedure. The emissions monitoring of a specific plant may also give indications of the contribution of these emissions on the air quality of a definite area. So, it is clear that the IPPC permits are important tools both to improve the environmental framework and to achieve the air quality standards, assisting in assessing the possible industrial sources contributions to air pollution.

Keywords: IPPC, IED, emissions, permits, air quality, large combustion plants

Procedia PDF Downloads 453

Authors: S. Khalifa, R. Chkoundali

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The specific role of banks in economic development varies, depending on scope. Firstly, the participation of banks in economic development focus around providing credit and services to generate revenues, which are then invested back into a local, national or international community. The specific roles banks play in the economic development of a small community differ from the role banks play in national or international economic development. Although the role can vary, factors such as access to credit and bank investment policies or practices remain constant, no matter the scope of economic development. This paper provides an overview of the economic situation of Africa and its short-term outlook. He referred to the progress made in the implementation of the Medium-Term Strategy (2008-2012) and some major achievements of the Bank, as the speed and flexibility with which she responded to the oil crisis, food and financial.

Keywords: economic growth, bank, Africa, economic development

Procedia PDF Downloads 462

Authors: Affan Ahmed

Abstract:

This research investigates the impact of the geomagnetic storm occurring from April 22 to April 26, 2023, on the Earth’s ionosphere, with a focus on analyzing specific ionospheric parameters to understand the storm's effects on ionospheric stability and GNSS signal propagation. Geomagnetic storms, caused by intensified solar wind-magnetosphere interactions, can significantly disturb ionospheric conditions, impacting electron density, Total Electron Content (TEC), and thermospheric composition. Such disturbances are particularly relevant to satellite-based navigation and communication systems, as fluctuations in ionospheric parameters can degrade signal integrity and reliability. In this study, data were obtained from multiple sources, including OMNIWeb for parameters like Dst, Kp, Bz, Electric Field, and solar wind pressure, GUVI for O/N₂ ratio maps, and TEC data from low-, mid-, and high-latitude stations available on the IONOLAB website. Additional Equatorial Electrojet (EEJ) and geomagnetic data were acquired from INTERMAGNET. The methodology involved comparing storm-affected data from April 22 to April 26 with quiet days in April 2023, using statistical and wavelet analysis to assess variations in parameters like TEC, O/N₂ ratio, and geomagnetic indices. The results show pronounced fluctuations in TEC and other ionospheric parameters during the main phase of the storm, with spatial variations observed across latitudes, highlighting the global response of the ionosphere to geomagnetic disturbances. The findings underline the storm’s significant impact on ionospheric composition, particularly in mid- and high-latitude regions, which correlates with increased GNSS signal interference in these areas. This study contributes to understanding the ionosphere’s response to geomagnetic activity, emphasizing the need for robust models to predict and mitigate space weather effects on GNSS-dependent technologies.

Keywords: geomagnetic storms, ionospheric disturbances, space weather effects, magnetosphere-ionosphere coupling

Procedia PDF Downloads 13