Search results for: comprehensive metrics

Authors: Gurmeet Kaur

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Agile software development methods are being recognized as popular, and efficient approach to the development of software system that has a short delivery period with high quality also that meets customer requirements with zero defect. In agile software development, quality means quality of code where in the quality is maintained through the use of methods or approaches like refactoring, test driven development, behavior driven development, acceptance test driven development, and demand driven development. Software quality is measured in term of metrics such as the number of defects during development of software. Usage of above mentioned methods or approaches, reduces the possibilities of defects in developed software, and hence improve quality. This paper focuses on study of agile based quality methods or approaches for software development that ensures improved quality of software as well as reduced cost, and customer satisfaction.

Keywords: ATDD, BDD, DDD, TDD

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Authors: Kenneth N. Ohei, Roelien Brink

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For decades, teaching and learning processes have centered on the traditional approach (Web 1.0) that promoted teacher-directed pedagogical practices. Currently, there is a realization that the traditional approach is not adequate to effectively address and improve all student-learning outcomes. The subsequent incorporation of social software, Information, and Communication Technology (ICT) tools in universities may serve as complementary to support educational goals, offering students the affordability and opportunity to educational choices and learning platforms. Consequently, educators’ inability to incorporate these instructional ICT tools in their teaching and learning practices remains a challenge. This will signify that educators still lack the ICT skills required to administer lectures and bridging learning gaps. This study probes a methodological concept with the aim of developing a framework towards the adoption of social software in HES to help facilitate business processes and can build social presence among students. A mixed method will be appropriate to develop a comprehensive framework needed in Higher Educational System (HES). After research have been conducted, the adoption of social software will be based on the developed comprehensive framework which is supposed to impact positively on education and approach of delivery, improves learning experience, engagement and finally, increases educational opportunities and easy access to educational contents.

Keywords: blended and integrated learning, learning experience and engagement, higher educational system, HES, information and communication technology, ICT, social presence, Web 1.0, Web 2.0, Web 3.0

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Authors: Samul Sahile Kebede

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Back ground: -Immune hemolytic anemia commonly affects human immune deficiency, infected individuals. Among anemic HIV patients in Africa, the burden of IHA due to autoantibody was ranged from 2.34 to 3.06 due to the drug was 43.4%. IHA due to autoimmune is potentially a fatal complication of HIV, which accompanies the greatest percent from acquired hemolytic anemia. Objective: -The main aim of this study was to determine the magnitude and associated factors of immune hemolytic anemia among human immuno deficiency virus infected adults at the university of Gondar comprehensive specialized hospital north west Ethiopia from March to April 2021. Methods: - An institution-based cross-sectional study was conducted on 358 human immunodeficiency virus-infected adults selected by systematic random sampling at the University of Gondar comprehensive specialized hospital from March to April 2021. Data for socio-demography, dietary and clinical data were collected by structured pretested questionnaire. Five ml of venous blood was drawn from each participant and analyzed by Unicel DHX 800 hematology analyzer, blood film examination, and antihuman globulin test were performed to the diagnosis of immune hemolytic anemia. Data was entered into Epidata version 4.6 and analyzed by STATA version 14. Descriptive statistics were computed and firth penalized logistic regression was used to identify predictors. P value less than 0.005 interpreted as significant. Result; - The overall prevalence of immune hemolytic anemia was 2.8 % (10 of 358 participants). Of these, 5 were males, and 7 were in the 31 to 50 year age group. Among individuals with immune hemolytic anemia, 40 % mild and 60 % moderate anemia. The factors that showed association were family history of anemia (AOR 8.30 at 95% CI 1.56, 44.12), not eating meat (AOR 7.39 at 95% CI 1.25, 45.0), and high viral load 6.94 at 95% CI (1.13, 42.6). Conclusion and recommendation; Immune hemolytic anemia is less frequent condition in human immunodeficiency virus infected adults, and moderate anemia was common in this population. The prevalence was increased with a high viral load, a family history of anemia, and not eating meat. In these patients, early detection and treatment of immune hemolytic anemia is necessary.

Keywords: anemia, hemolytic, immune, auto immune, HIV/AIDS

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Authors: Katalin Gombos, Bence Gálik, Krisztina Ildikó Kalács, Krisztina Gödöny, Ákos Várnagy, József Bódis, Attila Gyenesei, Gábor L. Kovács

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Although non-invasive pre-implantation genetic testing for aneuploidy (NIPGT-A) is potentially appropriate to assess chromosomal ploidy of the embryo, practical application of it in a routine IVF center has not been started in the absence of a recommendation. We developed a comprehensive workflow for a clinically applicable strategy for NIPGT-A based on next-generation sequencing (NGS) technology. We performed MALBAC whole genome amplification and NGS on spent blastocyst culture media of Day 3 embryos fertilized with intra-cytoplasmic sperm injection (ICSI). Spent embryonic culture media of morphologically good quality score embryos were enrolled in further analysis with the blank culture media as background control. Chromosomal abnormalities were identified by an optimized bioinformatics pipeline applying a copy number variation (CNV) detecting algorithm. We demonstrate a comprehensive workflow covering both wet- and dry-lab procedures supporting a clinically applicable strategy for NIPGT-A. It can be carried out within 48 h which is critical for the same-cycle blastocyst transfer, but also suitable for “freeze all” and “elective frozen embryo” strategies. The described integrated approach of non-invasive evaluation of embryonic DNA content of the culture media can potentially supplement existing pre-implantation genetic screening methods.

Keywords: next generation sequencing, in vitro fertilization, embryo assessment, non-invasive pre-implantation genetic testing

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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Authors: M. Mesrar, T. Lamcharfi, Nor-S. Echatoui, F. Abdi

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The solid-state reaction method was used to synthesize ferroelectric systems with lead-free properties, specifically (1-x-y)(Na₀.₅Bi₀.₅)TiO₃-xBaTiO₃-y(K₀.₅ Bi₀.₅)TiO₃. To achieve a pure perovskite phase, the optimal calcination temperature was determined to be 1000°C for 4 hours. X-ray diffraction (XRD) analysis identified the presence of the morphotropic phase boundary (MPB) in the (1-x-y)NBT xBT-yKBT ceramics for specific molar compositions, namely (0.95NBT-0.05BT, 0.84NBT-0.16KBT, and 0.79NBT-0.05BT-0.16KBT). To enhance densification, the sintering temperature was set at 1100°C for 4 hours. Scanning electron microscopy (SEM) images exhibited homogeneous distribution and dense packing of the grains in the ceramics, indicating a uniform microstructure. These materials exhibited favorable characteristics, including high dielectric permittivity, low dielectric loss, and diffused phase transition behavior. The ceramics composed of 0.79NBT-0.05BT-0.16KBT exhibited the highest piezoelectric constant (d33=148 pC/N) and electromechanical coupling factor (kp = 0.292) among all compositions studied. This enhancement in piezoelectric properties can be attributed to the presence of the morphotropic phase boundary (MPB) in the material. This study presents a comprehensive approach to improving the performance of lead-free ferroelectric systems of composition 0.79(Na₀.₅Bi₀.₅)Ti O₃-0.05BaTiO₃-0.16(K₀.₅Bi₀.₅)TiO₃.

Keywords: solid-state method, (1-x-y)NBT-xBT-yKBT, morphotropic phase boundary, Raman spectroscopy, dielectric properties

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Authors: Ibrahim Ozkan

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In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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Air Transport links markets and individuals, making regions more competitive and promoting social and economic development. The assessment of social contribution is the key objective of this paper, focusing on the definition of the components of social dimension and welfare metrics in the national scale. According to a top-down approach, the key dimensions that affect the social welfare are presented. Conventional wisdom is to provide estimations on added value to social issues caused by the air transport development and present the methodology framework for measuring the contribution of transport development in social value chain. Greece is the case study of this paper, providing results from the contribution of air transport infrastructures in national welfare. The application key findings are essential for managers and decision makers to support actions and plans towards economic recovery of an economy presenting strong seasonal characteristics (because of tourism) and suffering from recession.

Keywords: air transport, social coherence, resilient business development, socioeconomic impact

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Authors: Francis Kwesi Bondinuba, Seidu Abdullah, Nelly Bondinuba

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Purpose: The study proposes a theoretical framework for integrating sustainable project management in the construction sector, addressing the need for sustainable development practices. Methodology: The study adopts a theoretical approach by reviewing existing literature on sustainable development and project management in the construction industry. It analyses various concepts, theories, and frameworks to develop a comprehensive theoretical framework for integrating sustainable project management. Findings: The study emphasizes the importance of incorporating sustainable development practices into construction project management, focusing on collaboration, stakeholder engagement, and continuous improvement to achieve environmental conservation, social responsibility, and economic viability. Conclusion: Sustainable Project Management (SPM) in Ghana's construction industry is challenging due to lack of awareness, regulatory frameworks, financial constraints, and skill shortages, despite its benefits in promoting social inclusivity, job creation, and environmental resilience. Recommendation: The construction industry in Ghana should adopt a comprehensive approach involving local communities, government bodies, and environmental organizations. It should utilize green materials and technologies and effectively manage waste. Originality: This study presents a theoretical framework for sustainable project management in construction. It emphasizes collaboration and stakeholder engagement for long-term sustainable outcomes and considers environmental, social, and economic aspects.

Keywords: construction industry, theoretical framework, integration, project management, sustainable development

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Authors: Ben Levenger

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Social life revolves around a central meeting place or gathering space. It is where the community integrates, earns social skills, and ultimately becomes part of the community. Following this premise, public spaces are one of the most important spaces that downtowns offer, providing locations for people to be witnessed, heard, and most importantly, seamlessly integrate into the downtown as part of the community. To facilitate this, these local spaces must be envisioned and designed to meet the changing needs of a downtown, offering a space and purpose for everyone. This paper will dive deep into analyzing, designing, and implementing public space design for small plazas or gathering spaces. These spaces often require a detailed level of study, followed by a broad stroke of design implementation, allowing for adaptability. This paper will highlight how to assess needs, define needed types of spaces, outline a program for spaces, detail elements of design to meet the needs, assess your new space, and plan for change. This study will provide participants with the necessary framework for conducting a grass-roots-level assessment of public space and programming, including short-term and long-term improvements. Participants will also receive assessment tools, sheets, and visual representation diagrams. Urbanism, for the sake of urbanism, is an exercise in aesthetic beauty. An economic improvement or benefit must be attained to solidify these efforts' purpose further and justify the infrastructure or construction costs. We will deep dive into case studies highlighting economic impacts to ground this work in quantitative impacts. These case studies will highlight the financial impact on an area, measuring the following metrics: rental rates (per sq meter), tax revenue generation (sales and property), foot traffic generation, increased property valuations, currency expenditure by tenure, clustered development improvements, cost/valuation benefits of increased density in housing. The economic impact results will be targeted by community size, measuring in three tiers: Sub 10,000 in population, 10,001 to 75,000 in population, and 75,000+ in population. Through this classification breakdown, the participants can gauge the impact in communities similar to their work or for which they are responsible. Finally, a detailed analysis of specific urbanism enhancements, such as plazas, on-street dining, pedestrian malls, etc., will be discussed. Metrics that document the economic impact of each enhancement will be presented, aiding in the prioritization of improvements for each community. All materials, documents, and information will be available to participants via Google Drive. They are welcome to download the data and use it for their purposes.

Keywords: downtown, economic development, planning, strategic

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Authors: Alemayehu Ambaw, Matia Mukama, Umezuruike Linus Opara

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This study introduces a comprehensive method for designing ventilated corrugated fiberboard carton for fresh fruit packaging utilising virtual prototyping. The technique efficiently assesses and analyses the mechanical and thermal capabilities of fresh fruit packing boxes prior to making production investments. Comprehensive structural, aerodynamic, and thermodynamic data from designs were collected and evaluated in comparison to real-world packaging needs. Physical prototypes of potential designs were created and evaluated afterward. The virtual prototype is created with computer-aided graphics, computational structural dynamics, and computational fluid dynamics technologies. The virtual prototyping quickly generated data on carton compression strength, airflow resistance, produce cooling rate, spatiotemporal temperature, and product quality map in the cold chain within a few hours. Six distinct designs were analysed. All the various carton designs showed similar effectiveness in preserving the quality of the goods. The innovative packaging box design is more compact, resulting in a higher freight density of 1720 kg more fruit per reefer compared to the commercial counterpart. The precooling process was improved, resulting in a 17% increase in throughput and a 30% reduction in power usage.

Keywords: postharvest, container logistics, space/volume usage, computational method, packaging technology

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

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Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: Rodrigo Aguiar, Adelino Ferreira

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Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

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Authors: Marina Yurievna Aleksandrova

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Research of the Holocaust retains value not only for history but also for sociology and psychology. One of the most important fields of study is how people were coping during and after this traumatic event. The aim of this paper is to identify the main contexts of the topic of love and to determine which contexts are more characteristic for different groups of victims of the Holocaust (gender, nationality, age). In this research, transcripts of interviews with Holocaust victims that were collected during 1946 for the "Voices of the Holocaust" project were used as data. Main contexts were analyzed with methods of network analysis and latent semantic analysis and classified by gender, age, and nationality with random forest. The results show that love is articulated and described significantly differently for male and female informants, nationality is shown results with lower values of quality metrics, as well as the age.

Keywords: Holocaust, latent semantic analysis, network analysis, text-mining, random forest

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Authors: Eun-Taek Sin, Hyun-Ju Jang, Chang Geun Song, Yong-Sik Han

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Due to the climate change, the coastal urban area repeatedly suffers from the loss of property and life by flooding. There are three main causes of inland submergence. First, when heavy rain with high intensity occurs, the water quantity in inland cannot be drained into rivers by increase in impervious surface of the land development and defect of the pump, storm sewer. Second, river inundation occurs then water surface level surpasses the top of levee. Finally, Coastal inundation occurs due to rising sea water. However, previous studies ignored the complex mechanism of flooding, and showed discrepancy and inadequacy due to linear summation of each analysis result. In this study, inland flooding and river inundation were analyzed together by HDM-2D model. Petrov-Galerkin stabilizing method and flux-blocking algorithm were applied to simulate the inland flooding. In addition, sink/source terms with exponentially growth rate attribute were added to the shallow water equations to include the inland flooding analysis module. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. To consider the coastal surge, another module was developed by adding seawater to the existing Inland Flooding-River Inundation binding module for comprehensive flooding analysis. Based on the combined modules, the Coastal Inundation – Inland & River Flow Interface was simulated by inputting the flow rate and depth data in artificial flume. Accordingly, it was able to analyze the flood patterns of coastal cities over time. This study is expected to help identify the complex causes of flooding in coastal areas where complex flooding occurs, and assist in analyzing damage to coastal cities. Acknowledgements—This research was supported by a grant ‘Development of the Evaluation Technology for Complex Causes of Inundation Vulnerability and the Response Plans in Coastal Urban Areas for Adaptation to Climate Change’ [MPSS-NH-2015-77] from the Natural Hazard Mitigation Research Group, Ministry of Public Safety and Security of Korea.

Keywords: flooding analysis, river inundation, inland flooding, 2D hydrodynamic model

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Authors: Mareye Zeleke Mekonen

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The Kafficho language has distinct issues in information retrieval because of its restricted resources and dearth of standardized methods. In this endeavor, with the cooperation and support of linguists and native speakers, we investigate the creation of information retrieval systems specifically designed for the Kafficho language. The Kafficho information retrieval system allows Kafficho speakers to access information easily in an efficient and effective way. Our objective is to conduct an information retrieval experiment using 220 Kafficho text files, including fifteen sample questions. Tokenization, normalization, stop word removal, stemming, and other data pre-processing chores, together with additional tasks like term weighting, were prerequisites for the vector space model to represent each page and a particular query. The three well-known measurement metrics we used for our word were Precision, Recall, and and F-measure, with values of 87%, 28%, and 35%, respectively. This demonstrates how well the Kaffiho information retrieval system performed well while utilizing the vector space paradigm.

Keywords: Kafficho, information retrieval, stemming, vector space

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Authors: Obioma Uche

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Due to the recent volatility in oil & gas prices as well as increased development of non-conventional resources, it has become even more essential to critically evaluate the profitability of petroleum prospects prior to making any investment decisions. Traditionally, simple Monte Carlo (MC) algorithms have been used to randomly sample probability distributions of economic and geological factors (e.g. price, OPEX, CAPEX, reserves, productive life, etc.) in order to obtain probability distributions for profitability metrics such as Net Present Value (NPV). In recent years, second-order MC algorithms have been shown to offer an advantage over simple MC techniques due to the added consideration of uncertainties associated with the probability distributions of the relevant variables. Here, a strategy for the application of the second-order MC technique to a case study is demonstrated to analyze its effectiveness as a tool for portfolio management.

Keywords: Monte Carlo algorithms, portfolio management, profitability, risk analysis

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Authors: Morgan Dempsey, Sam Lewis, Maggie Pierce, Alex Goodman

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This research investigates the impact of equine-assisted therapy programs on occupational engagement for children with intellectual and developmental disabilities. There is a general lack of evidence for equine-based services for this population, so this research aims to decrease gaps in the current literature. To gain comprehensive insight, data will be collected from both the child and their caregiver. This study takes a qualitative approach utilizing online surveys and in-person guided interviews. The participants are individuals ages 4-17 with a diagnosed intellectual or developmental disability who are currently participating in a PATH int. certified equine-assisted therapy program. Also, caregivers of individuals who meet this criterion are included. This study decreases gaps in the literature by providing comprehensive data regarding the impacts of these services on occupational engagement. The addressed domains are physical, behavioral, emotional, and social functioning, as well as overall activity engagement and impacts in everyday life. With a better understanding of how equine-assisted therapy affects relevant outcomes for children with disabilities, an increased number of occupational therapists can implement these uniquely effective services while adhering to standards of evidence-based practice. Ultimately, this research strives to contribute to generalizable data in occupational therapy by supporting the implementation of equine-assisted services for children with intellectual and/or developmental disabilities and their caregivers/families.

Keywords: occupational therapy, pediatric, rehabilitation, hippotherapy

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Authors: Amber Brittain-Hale

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This research investigates the evolving role of social media in crisis situations by employing discourse analysis methodology and honing in on the Russo-Ukrainian War, particularly Ukraine's use of LinkedIn. The study posits that social media platforms, such as LinkedIn, play a crucial role in shaping communication, disseminating information, and influencing geopolitical strategies during conflicts. Focusing on Ukraine's official state account on LinkedIn and analyzing its posts and interactions, the research aims to unveil discourse dynamics in high-stakes scenarios and provide valuable insights for leaders navigating complex global challenges. A comprehensive analysis of the data will contribute to a deeper understanding of the tactics adopted by political leaders in managing communication, the bidirectional nature of discourse provided by online social networks, and the rapid advancement of technology that has led to the growing significance of social media platforms in crisis situations. Through this approach, the geopolitical factors that influenced the country's social media strategy during the Russo-Ukrainian War will be illuminated, offering a broader perspective on the role of social media in such challenging times. Ultimately, the study seeks to uncover lessons that can be drawn from Ukraine's LinkedIn approach, informing future strategies for utilizing social media during crises and advancing the understanding of how social media can be harnessed to address intricate global issues.

Keywords: russo-ukrainian war, social media, crisis, discourse analysis

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Authors: Michael Adebayo, Saheed Lawal

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The Comprehensive Geriatric Assessment (CGA) is the multidimensional tool used to assess elderly, frail patients either on admission to hospital care or at a community level in primary care. It is a tool designed with the aim of using a holistic approach to managing patients. A Cochrane review of CGA use in 2011 found that the likelihood of being alive and living in their own home rises by 30% post-discharge. RCTs have also discovered 10–15% reductions in readmission rates and reductions in institutionalization, and resource use and costs. Past audit cycles at King’s College Hospital, Denmark Hill had shown inconsistent evidence of CGA completion inpatient discharge summaries (less than 50%). Junior Doctors in the Health and Ageing (HAU) wards have struggled to sustain the efforts of past audit cycles due to the quick turnover in staff (four-month placements for trainees). This 7th cycle created a multi-faceted approach to solving this problem amongst staff and creating lasting change. Methods: 1. We adopted multidisciplinary team involvement to support Doctors. MDT staff e.g. Nurses, Physiotherapists, Occupational Therapists and Dieticians, were actively encouraged to fill in the CGA document. 2. We added a CGA Document Pro-forma to “Sunrise EPR” (Trust computer system). These CGAs were to automatically be included the discharge summary. 3. Prior to assessing uptake, we used a spot audit questionnaire to assess staff awareness/knowledge of what a CGA was. 4. We designed and placed posters highlighting domains of CGA and MDT roles suited to each domain on geriatric “Health and Ageing Wards” (HAU) in the hospital. 5. We performed an audit of % discharge summaries which include CGA and MDT role input. 6. We nominated ward champions on each ward from each multidisciplinary specialty to monitor and encourage colleagues to actively complete CGAs. 7. We initiated further education of ward staff on CGA's importance by discussion at board rounds and weekly multidisciplinary meetings. Outcomes: 1. The majority of respondents to our spot audit were aware of what a CGA was, but fewer had used the EPR document to complete one. 2. We found that CGAs were not being commenced for nearly 50% of patients discharged on HAU wards and the Frailty Assessment Unit.

Keywords: comprehensive geriatric assessment, CGA, multidisciplinary team, quality of life, mortality

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Authors: Aly Elshafei, Daniela Romano

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With the development of autonomous vehicles, a human-machine interaction (HMI) system is needed for a safe transition of control when a takeover request (TOR) is required. An important part of the HMI system is the ability to monitor the level of situational awareness (SA) of any driver in real-time, in different scenarios, and without any pre-calibration. Presenting state-of-the-art machine learning models used to measure SA is the purpose of this systematic review. Investigating the limitations of each type of sensor, the gaps, and the most suited sensor and computational model that can be used in driving applications. To the author’s best knowledge this is the first literature review identifying online and offline classification methods used to measure SA, explaining which measurements are subject or session-specific, and how many classifications can be done with each classification model. This information can be very useful for researchers measuring SA to identify the most suited model to measure SA for different applications.

Keywords: situational awareness, autonomous driving, gaze metrics, EEG, ECG

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Authors: Siti Nor Amira Bt. Mohamad, Mohamad Yazis B. Ali Basah, Muhammad Ridhwan B. Ab. Aziz, Khairil Faizal B. Khairi, Mazlynda Bt. Md. Yusuf, Hisham B. Sabri

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The understanding of risk and the concept of it occurs associated in Islamic financing was well-known in the financial industry by the using of Profit-and-Loss Sharing (PLS). It was presently in any Islamic financial transactions in order to comply with shariah rules. However, the existence of risk in Murabahah contract of financing is an ability that the counterparty is unable to complete its obligations within the agreed terms. Therefore, it is called as credit or default risk. Credit risk occurs when the client fails to make timely payment after the bank makes complete delivery of assets. Thus, it affects the growth of the bank as the banking business is in no position to have appropriate measures to cover the risk. Therefore, the bank may impose penalty on the outstanding balance. This paper aims to highlight the credit risk determinant and issues surrounding in Islamic bank in Malaysia in terms of Murabahah financing and how to manage it by using the proper techniques. Finally, it explores the credit risk management concept that might solve the problems arise. The study found that the credit risk can be managed properly by improving the use of comprehensive reference checklist of business partners on their character and past performance as well as their comprehensive database. Besides that, prevention of credit risk can be done by using collateral as security against the risk and we also argue on the Shariah guidelines and procedures should be implement coherently by the banking business because so that the risk would be control by having an effective instrument for Islamic modes of financing.

Keywords: Islamic banking, credit risk, Murabahah financing, risk mitigation

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Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

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Authors: Malizgani Paul Chavula

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Background: Comprehensive sexuality education (CSE) plays a critical role in promoting youth and adolescents’ sexual and reproductive health and well-being. However, little is known about the enablers and barriers affecting the integration of CSE into educational programmes. The aim of this review is to explore positive and negative factors influencing the integration of CSE into national curricula and educational systems in low- and middle-income countries. Methods: We conducted a systematic literature review (January 2010 to August 2022). The results accord with the Preferred Reporting Items for Systematic Reviews and Meta-analysis standards for systematic reviews. Data were retrieved from the PubMed, Cochrane, Google Scholar, and Web of Hinari databases. The search yielded 431 publications, of which 23 met the inclusion criteria for full-text screening. The review is guided by an established conceptual framework that incorporates the integration of health innovations into health systems. Data were analyzed using a thematic synthesis approach. Results: The magnitude of the problem is evidenced by sexual and reproductive health challenges such as high teenage pregnancies, early marriages, and sexually transmitted infections. Awareness of these challenges can facilitate the development of interventions and the implementation and integration of CSE. Reported aspects of the interventions include core CSE content, delivery methods, training materials and resources, and various teacher-training factors. Reasons for adoption include perceived benefits of CSE, experiences and characteristics of both teachers and learners, and religious, social, and cultural factors. Broad system characteristics include strengthening links between schools and health facilities, school and community-based collaboration, coordination of CSE implementation, and the monitoring and evaluation of CSE. Ultimately, the availability of resources, national policies and laws, international agendas, and political commitment will impact upon the extent and level of integration. Conclusion: Social, economic, cultural, political, legal, and financial contextual factors influence the implementation and integration of CSE into national curricula and educational systems. Stakeholder collaboration and involvement in the design and appropriateness of interventions is critical.

Keywords: comprehensive sexuality education, factors, integration, sexual reproductive health rights

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Authors: Serhat Tuzun, Tufan Demirel

Abstract:

Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

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Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim

Abstract:

Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.

Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

Abstract:

Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

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Authors: Wenjuan Lu

Abstract:

China and Hungary have risen from a friendly and comprehensive cooperative relationship to a comprehensive strategic partnership in recent years, and the economic and trade relations between the two countries have developed smoothly. As an important country along the ‘Belt and Road’, Hungary and China have strong economic complementarities and have unique advantages in carrying China's industrial transfer and economic transformation and development. The construction of the China-Hungary Economic and Trade Cooperation Zone, which was initiated by the ‘Sino-Hungarian Borsod Industrial Zone’ and the ‘Hungarian Central European Trade and Logistics Cooperation Park’ has promoted infrastructure construction, optimized production capacity, promoted industrial restructuring, and formed brand and agglomeration effects. Enhancing the influence of Chinese companies in the European market has also promoted economic development in Hungary and even in Central and Eastern Europe. However, as the China-Hungary Economic and Trade Cooperation Zone is still in its infancy, there are still shortcomings such as small scale, single function, and no prominent platform. In the future, based on the needs of China's cooperation with ‘17+1’ and China-Hungary cooperation, on the basis of appropriately expanding the scale of economic and trade cooperation zones and appropriately increasing the number of economic and trade cooperation zones, it is better to focus on optimizing and adjusting its functions and highlighting different economic and trade cooperation. The differentiated function of the trade zones strengthens the multi-faceted cooperation of economic and trade cooperation zones and highlights its role as a platform for cooperation in information, capital, and services.

Keywords: ‘One Belt, One Road’ Initiative, China-Hungary economic and trade cooperation zone, function optimization, Central and Eastern Europe

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

Abstract:

In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

Procedia PDF Downloads 67