Search results for: pollution risk assessment

Authors: Jay Ananth

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The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

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Authors: Hiba Dakroub, Danilo Russo, Luca Cistrone, Francesco Serra, Giovanna Fusco, Esterina De Carlo, Maria Grazia Amoroso

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The question of the origin of SARS-CoV-2 and the cycle of transmission between humans and animals is still unanswered. One serious concern associated with the SARS-CoV-2 pandemic is that the virus might spill back from humans to wildlife, which would render some animal species reservoirs of the human virus. The aim of the present study is to monitor the potential risk of SARS-CoV-2 reverse infection from humans to bats, by performing bat surveillance from different sites in Central-Southern Italy. We collected 240 droppings or saliva from 129 bats and tested them using specific and general primers of SARS-COV-2 and coronaviruses respectively. All samples, including 127 nasal swabs and 113 fecal droppings resulted negative for SARS-COV-2, and these results were confirmed by testing the samples with the Droplet Digital PCR. Also, an end-point RT-PCR was performed and no sample showed specific bands. The absence of SARS-CoV-2 in the bats we surveyed is a first step towards a better understanding of reverse transmission to bats of this virus. We hope our first contribution will encourage the establishment of systematic surveillance of wildlife, and specifically bats, to help prevent reverse zoonotic episodes that would jeopardize human health as well as biodiversity conservation and management.

Keywords: coronaviruses, bats, zoonotic viruses, spillback, SARS-CoV-2

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Authors: Priya Kedia, Kiranmoy Das

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There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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Authors: Sabiha Shahid Antora, Young Ki Chang

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Along with various farm management technologies, imagery is an important tool that facilitates crop assessment, monitoring, and management. As a consequence, drone imaging technology is playing a vital role to capture the state of the entire field for yield mapping, crop scouting, weed detection, and so on. Although it is essential to inspect the cultivable lands in real-time for making rapid decisions regarding field variable inputs to combat stresses and diseases, drone imagery is still evolving in this area of interest. Cost margin and post-processing complexions of the image stream are the main challenges of imaging technology. Therefore, this proposed project involves the cost-effective field programmable gate array (FPGA) based image processing device that would process the image stream in real-time as well as providing the processed output to support on-the-spot decisions in the crop field. As a result, the real-time FPGA-based image processing system would reduce operating costs while minimizing a few intermediate steps to deliver scalable field decisions.

Keywords: real-time, FPGA, drone imagery, image processing, crop monitoring

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Authors: Sankalp Devanand, Prateek Agasimani, Shamith V. S., Rohith Neeraje

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Machine translation has witnessed significant advancements in recent years, but the translation of languages with distinct linguistic characteristics, such as English and Sanskrit, remains a challenging task. This research presents the development of a dedicated English-to-Sanskrit machine translation model, aiming to bridge the linguistic and cultural gap between these two languages. Using a variety of natural language processing (NLP) approaches, including FastText embeddings, this research proposes a thorough method to improve word meaning retrieval. Data preparation, part-of-speech tagging, dictionary searches, and transliteration are all included in the methodology. The study also addresses the implementation of an interpreter pattern and uses a word similarity task to assess the quality of word embeddings. The experimental outcomes show how the suggested approach may be used to enhance word meaning retrieval tasks with greater efficacy, accuracy, and adaptability. Evaluation of the model's performance is conducted through rigorous testing, comparing its output against existing machine translation systems. The assessment includes quantitative metrics such as BLEU scores, METEOR scores, Jaccard Similarity, etc.

Keywords: machine translation, English to Sanskrit, natural language processing, word meaning retrieval, fastText embeddings

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Authors: Nadia Elouaer

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Tax revenue is the main state resource and one of the important variables in tax policy. Nevertheless, this resource is continually decreasing, so it is important to focus on the reasons for this decline. Several studies show that the taxpayer is reluctant to pay taxes, especially in countries at risk or in countries in transition, including Tunisia. This study focuses on the tax evasion behavior of a Tunisian taxpayer under the influence of his political beliefs, as well as the influence of different tax compliance variables. Using a questionnaire, a sample of 500 Tunisian taxpayers is used to examine the relationship between political beliefs and taxpayer affiliations and tax compliance variables, as well as the study of the causal link between political beliefs and fraudulent behavior. The data were examined using correlation, factor, and regression analysis and found a positive and statistically significant relationship between the different tax compliance variables and the tax evasion behavior. There is also a positive and statistically significant relationship between tax evasion and political beliefs and affiliations. The study of the relationship between political beliefs and compliance variables shows that they are closely related. The conclusion is to admit that tax evasion and political beliefs are closely linked, and the government should update its tax policy and modernize its administration in order to strengthen the credibility and disclosure of information in order to restore a relationship of trust between public authorities and the taxpayer.

Keywords: fiscal policy, political beliefs, tax evasion, taxpayer behavior

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Authors: Hien T. T. Ho, Tsunemi Watanabe

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The regulatory and market pressures on the restriction of nonylphenol and its ethoxylates in textile articles have confronted the textile manufacturers, particularly those in developing countries. This study aimed to examine the tentative behavior of the textile manufacturers in Vietnam from the perspectives of attitude and the perceptions of technical and organizational adaptabilities, risks, benefits, and barriers. Personal interviews were conducted with five technical specialists from four textile firms and one chemical supplier. The environmental regulatory and market situations regarding the chemical use in Vietnam were also described. The findings revealed two main opposing trends of chemical substitution depending on the market orientation of firms that governed the patterns of risk and benefit perception. The indirect influence of perceived adaptabilities on firm tentative behavior through perceived risks was elucidated, which initiated a conceptual model of firm’s behavior combining the organizational-based and the rational-based relationships. The intermediary role of non-governmental textile and garment industrial/ trade associations is highlighted to strengthen private firm’s informative capacity.

Keywords: firm behavior, institutional analysis, organizational adaptation, technical adaptation

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Authors: Hesham Osman

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The challenges facing aging urban infrastructure systems require a more holistic and comprehensive approach to their management. The large number of urban infrastructure renewal activities occurring in cities throughout the world leads to social, economic and environmental impacts on the communities in its vicinity. As such, a coordinated effort is required to streamline these activities. This paper presents a framework to enable temporal (time-based) coordination of water, sewer and road intervention activities. Intervention activities include routine maintenance, renewal, and replacement of physical assets. The coordination framework considers 1) Life-cycle costs, 2) Infrastructure level-of-service, and 3) Risk exposure to system operators. The model enables infrastructure asset managers to trade-off options of delaying versus bringing forward intervention activities of one system in order to be executed in conjunction with another co-located system in the right-of-way. The framework relies on a combination of meta-heuristics and goal-based optimization. In order to demonstrate the applicability of the framework, a case study for a major infrastructure corridor in Cairo, Egypt is taken as an example. Results show that the framework can be scaled-up to include other infrastructure systems located in the right-of-way like electricity, gas and telecom, provided that information can be shared among these entities.

Keywords: infrastructure, rehabilitation, construction, optimization

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Tanmaya Kumar Dash, Tarun Karamshetty, Soumitra Paul

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The Barkhausen Noise Analysis (BNA) technique has been utilized to assess surface integrity of steels. But the BNA technique is not very successful in evaluating surface integrity of ground steels that exhibit poor micro-magnetic response. A new approach has been proposed for the processing of BN signal with Fast Fourier transforms while Wavelet transforms has been used to remove noise from the BN signal, with judicious choice of the ‘threshold’ value, when the micro-magnetic response of the work material is poor. In the present study, the effect of down feed induced upon conventional plunge surface grinding of hardened bearing steel has been investigated along with an ultrasonically cleaned, wet polished and a sample ground with spark out technique for benchmarking. Moreover, the FFT analysis has been established, at different sets of applied voltages and applied frequency and the pattern of the BN signal in the frequency domain is analyzed. The study also depicts the wavelet transforms technique with different levels of decomposition and different mother wavelets, which has been used to reduce the noise value in BN signal of materials with poor micro-magnetic response, in order to standardize the procedure for all BN signals depending on the frequency of the applied voltage.

Keywords: barkhausen noise analysis, grinding, magnetic properties, signal processing, micro-magnetic response

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Authors: Fahad Al Beyahi, Justin Thomas, Md Mamunur Rashid

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Various definitions of digital well-being have emerged in recent years, most of which center on the impacts -beneficial and detrimental- of digital technology on health and well-being (psychological, social, and financial). Other definitions go further, emphasizing the attainment of balance, viewing digital well-being as wholly subjective, the individual’s perception of optimal balance between the benefits and ills associated with online connectivity. Based on this broad conceptualization of digital well-being, we undertook a global survey measuring various dimensions of this emerging construct. The survey was administered across 35 nations and 7 world regions, with 1000 participants within each territory (N= 35000). Along with attitudinal, behavioral, and sociodemographic variables, the survey included measures of depression, anxiety, problematic social media use, gaming disorder, and other relevant metrics. Coupled with nation-level policy audits, these data were used to create a multinational (global) digital well-being index. Nations are ranked based on various dimensions of digital well-being, and predictive models are used to identify resilience and risk factors for problem technology use. In this paper, we will discuss key findings from the survey and the index. This work can inform public policy and shape our responses to the emerging implications of lives increasingly lived online and interconnected with digital technology.

Keywords: technology, health, behavioral addiction, digital wellbeing

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Authors: Ilhan Keskin, Hasan Bulent Kantarci

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In this study, one of the tools of Islamic financing known as “Sukuk” a non-interest bearing investment which has started to be implemented in Turkey and the world as a whole is discussed. In order to increase the vitality and efficiency of the economy, by taking lessons from the recent economic crisis new developments in the banking and investment sector are being expanded. The purpose of all investors is to obtain more revenue through the use of capital. The inability of traditional investment tools to meet the expectations of investors and the interest based financial system where one investor benefits at the expense of another there has been the need for a different, reliable and non-interest bearing financial market that is consistent with the Islamic rule. As a result an alternative and more reliable interest free financing tool “Sukuk” rental certificates covering people who are sensitive to Islamic rules, appeal to all segments, hidden remaining capital that contributes to the economy, reduce disparities in income distribution, common risk sharing system of profit and loss sharing has emerged. Today, for the structural countries by examining the state of the world market economy the applicability, enactment and future issues associated with this attractive kind of Islamic finance namely the “Sukuk” market has been explained.

Keywords: Islamic finance, islamic markets, non-interest bearing, rental certificates

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Authors: H. Medjadji, A. Boulahouache, N. Salhi, A. Boudjemaa, M. Trari

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Hydrogen from renewable sources, such as solar, is referred to as green hydrogen. The splitting water process using semiconductors, such as photocatalysts, has attracted significant attention due to its potential application for solving the energy crisis and environmental pollution. Spinel ferrites of the MF₂O₄ type have shown broad interest in diverse energy conversion processes, including fuel cells and photo electrocatalytic water splitting. This work focuses on preparing nano-spinels based on iron AFe₂O₄ (A= Ca, Co, and Cu) as photocatalysts using the nitrate method. These materials were characterized both physically and optically and subsequently tested for hydrogen generation under visible light irradiation. Various techniques were used to investigate the properties of the materials, including TGA-DT, X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), UV-visible spectroscopy, Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM-EDX) and X-ray Photoelectron Spectroscopy (XPS) was also undertaken. XRD analysis confirmed the formation of pure phases at 850°C, with crystalline sizes of 31 nm for CaFe₂O₄, 27 nm for CoFe₂O₄, and 40 nm for CuFe₂O₄. The energy gaps, calculated from recorded diffuse reflection data, are 1.85 eV for CaFe₂O₄, 1.27 eV for CoFe₂O₄, and 1.64 eV for CuFe₂O₄. SEM micrographs showed homogeneous grains with uniform shapes and medium porosity in all samples. EDX elemental analysis determined the absence of any contaminating elements, highlighting the high purity of the prepared materials via the nitrate route. XPS spectra revealed the presence of Fe3+ and O in all samples. Additionally, XPS analysis revealed the presence of Ca²⁺, Co²⁺, and Cu²⁺ on the surface of CaFe₂O₄ and CoFe₂O₄ spinels, respectively. The photocatalytic activity was successfully evaluated by measuring H₂ evolution through the water-splitting process. The best performance was achieved with CaFe₂O₄ in a neutral medium (pH ~ 7), yielding 189 µmol at an optimal temperature of ~50°C. The highest hydrogen production rates for CoFe₂O₄ and CuFe₂O₄ were obtained at pH ~ 12 with release rates of 65 and 85 µmol, respectively, under visible light irradiation at the same optimal temperature. Various conditions were investigated including the pH of the solution, the hole sensors utilization and recyclability.

Keywords: hydrogen, MFe₂O₄, nitrate route, spinel ferrite

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Authors: Abubakar Salisu Garba

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The objective of the paper is to highlight the nature of entrepreneurial activities in the Sub Sahara Africa. Five countries in the Sub Sahara African that are participating in Global Entrepreneurship Monitor (GEM) research have been studied to understand the types of entrepreneurial activities and their socio-economic implications in the region. The importance of entrepreneurial activities in boosting socio-economic development has been recognized not only in developing countries, but across the entire global economies. Some people believe that the wealth and poverty of developing countries is associated with nature and type of entrepreneurial activity. Policy makers are not only concern about the rate of business start up, but the growth and development of those starts up is of paramount importance to the development of the country’s economy. Although, the supply of entrepreneurs is essential, sometimes it does not really matters in boosting economic performance. What is more important is having high impact entrepreneurs who could make meaningful contribution to the economy. High growth oriented entrepreneurs are more stable and contribute greatly in enhancing the economic performance. When entrepreneurs are facing difficulties in sustaining and growing their businesses, it may be unlikely for entrepreneurship to reduce unemployment and poverty. Inadequate financial supports, insufficient infrastructure, lack of enforcing laws protecting the right of entrepreneurs are some of the problems making business environment difficult in Sub-Saharan Africa.

Keywords: entrepreneurship, entrepreneurial activity, job creation, poverty reduction, Sub-Saharan Africa

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Authors: Nyasha Agnes Gurira, Petronella Katekwe

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Traditional management systems (TMS) are a vital source of knowledge for conserving cultural and natural heritage. TMS’s are renowned for their ability to preserve both tangible and intangible manifestations of heritage. They are a construct of the intricate relationship that exists between heritage and host communities, where communities are recognized as owners of heritage and so, set up management mechanisms to ensure its adequate conservation. Multiple heritage condition surveys were conducted to assess the effectiveness of using TMS in the conservation of both natural and cultural heritage. Surveys were done at Nharira Hills, Mahwemasimike, Dzimbahwe, Manjowe Rock art sites and Norumedzo forest which are heritage places in Zimbabwe. It assessed the state of conservation of the five case studies and assessed the role that host communities play in the management of these heritage places. It was revealed that TMS’s are effective in the conservation of natural heritage, however in relation to heritage forms with cultural manifestations, there are major disparities. These range from differences in appreciation and perception of value within communities leading to vandalism, over emphasis in the conservation of the intangible element as opposed to the tangible. This leaves the tangible element at risk. Despite these issues, TMS are a reliable knowledge base which enables more holistic conservation approaches for cultural and natural heritage.

Keywords: communities, cultural intangible, tangible heritage, traditional management systems, natural

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Authors: Sungwoo Park

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The paper attempts to investigate the correlation between climate change and migration that has caused violent disputes in some regions of the world. Recently, NGOs and educational institutions have proposed claims that migratory patterns and violent uprisings are intertwined with climate change. Thus, the paper is primarily concerned with collecting evidences provided from scholars, validating this significant connection between climate change and migration, and evaluating and suggesting current and future research approaches respectively to enhance the acknowledgment and protection of environmental refugees. In order to examine the linkage of environmental migration, primary sources, such as political speeches, and secondary sources like theses from environmental policy analysts, books, and reports are used. More specifically, the investigation focuses on an civil war in Syria to draw a connection between environmental migration and violent dispute that threatens the global security. The examination undertaken specifically analyzes examples where forced migration occurred due to climate change. In Bangladesh, Pakistan, and Kiribati, residents have been at risk of fleeing their countries because of abnormal climate patterns, such as the rise of sea level or an excessive heat stress. As the brutal uprising in Syria has proven that climate change can pose a significant threat to global security, correlation between climate change and migration is surely worth delving into.

Keywords: climate change, climate migration, global security, refugee crisis

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Authors: Leon Pan

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The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate.

Keywords: extreme-based teaching model, innovative pedagogical methods, project-based learning, team-based learning

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Authors: Kwasi Dartey-Baah, Mias De Klerk

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Project complexity has been cited as one of the essential areas of project management. It can be observed from environmental, social, technological, and organisational viewpoints, and its handling is critical to project success. Conceptualised in varied industries, this paper seeks to ascertain the meaning and understanding of project complexity within the Ghanaian construction industry based on the three dimensions of complexities (faith, fact, and interaction) using experts' opinions. Taking the form of a focus group discussion, the paper sought to gain an in-depth understanding of project complexity issues in Ghana’s construction industry. The method use obtained data from experts (a purposely selected group) comprising project leaders and project management academics. The findings indicated that the experts broadly agreed with the complexity items but offered varied reasons for their agreement. In the composite assessment of the complexity dimensions of (faith, fact, and interaction), it emerged that there was some agreement with the complexity dimensions of fact and interaction within Ghana’s construction industry. On the other hand, with the dimension for complexity by faith, it was noted that the experts in Ghana’s construction construed complexity by faith, not as the absence of evidence but the evidence that hinges on at least a member of the project team. It is expected that other researches on project complexity will focus on other industries to enhance the knowledge of the same within the field of project management.

Keywords: project complexity, complexity by faith, complexity by fact, complexity by interaction, construction industry, Ghana

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Authors: Yousuf N. Al Khamisi, Eduardo M. Hernandez, Khurshid M. Khan

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Purpose: This paper presents a model of a Knowledge-Based (KB) using Lean Six Sigma (L6σ) principles to enhance the performance of healthcare leadership. Design/methodology/approach: Using L6σ principles to enhance healthcare leaders’ performance needs a pre-assessment of the healthcare organisation’s capabilities. The model will be developed using a rule-based approach of KB system. Thus, KB system embeds Gauging Absence of Pre-requisite (GAP) for benchmarking and Analytical Hierarchy Process (AHP) for prioritization. A comprehensive literature review will be covered for the main contents of the model with a typical output of GAP analysis and AHP. Findings: The proposed KB system benchmarks the current position of healthcare leadership with the ideal benchmark one (resulting from extensive evaluation by the KB/GAP/AHP system of international leadership concepts in healthcare environments). Research limitations/implications: Future work includes validating the implementation model in healthcare environments around the world. Originality/value: This paper presents a novel application of a hybrid KB combines of GAP and AHP methodology. It implements L6σ principles to enhance healthcare performance. This approach assists healthcare leaders’ decision making to reach performance improvement against a best practice benchmark.

Keywords: Lean Six Sigma (L6σ), Knowledge-Based System (KBS), healthcare leadership, Gauge Absence Prerequisites (GAP), Analytical Hierarchy Process (AHP)

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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The use of Geographic Information System (GIS) tools in the analysis of traffic crash data can help to identify locations or hotspots with high instances or risk of traffic crashes. The identification of traffic crash hotspots can effectively improve road safety measures. Mapping of road traffic crash hotspots can help the concerned authorities to give priority and take targeted measures and improvements to the road structure at these locations to reduce traffic crashes and fatalities. In Oman, there are countless rural roads that have more risks for traveling vehicles compared to urban roads. The likelihood of traffic crashes as well as fatality rate may increase with the presence of risks that are associated with the rural type of community. In this paper, the traffic crash hotspots on rural roads in Oman are specified using spatial analysis methods in GIS and traffic crash data. These hotspots are ranked based on the frequency of traffic crash occurrence (i.e., number of traffic crashes) and the rate of fatalities. The result of this study presents a map visualization of locations on rural roads with high traffic crashes and high fatalities rates.

Keywords: road safety, rural roads, traffic crash, GIS tools

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Authors: Mao Ju

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The system of general counsel (GC) is an important governance structure designed for the construction of state-owned enterprises (SOEs) under the rule of law. This article is based on the setting of mergers and acquisitions (M&As) and takes the efficiency of M&As to examine the implementation effect of the system of GC for SOEs. Research has found that: (1) companies implementing the system of GC for SOEs have higher efficiency in M&As, manifested in better operational and market performance, and this effect depends on the professional ability and power of the GC. This indicates that the GC of SOEs has played a positive role in the decision-making process of M&As, which helps to improve the efficiency of M&As. (2) The impact of the GC of SOEs on the efficiency of M&As is heterogeneous, and this positive effect is mainly reflected in local and commercial SOEs. (3) The path of this impact is that the GC of SOEs can help reduce ineffective M&As in advance, enhance the ability to integrate M&As after the fact and reduce the risk of goodwill impairment and bankruptcy. This article reveals the impact of the construction of SOEs under the rule of law with the system of GC as the core of M&As activities, providing intuitive evidence for the implementation effect of the GC of SOEs. The research conclusion has important practical guiding value for comprehensively deepening the construction of the rule of SOEs under the rule of law and writing a good chapter on the Chinese path to modernization of SOEs.

Keywords: the system of general counsel, merger and acquisition efficiency, state-owned enterprises, mergers and acquisitions

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Authors: Stephen J Futter, Michael I Okereke

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This paper presents an investigation of the premature in-service failure of the engine mounting towers that form part of the bedframe commonly used for industrial power generation applications. The client during a routine in-service assessment of the generator set observed that the engine mounting towers had cracked. Thus, this study has investigated in detail the origin of the crack and proffered solutions to prevent a re-occurrence. Seven step problem solving methodology was followed during this paper. The study used both experimental and numerical approaches to understand, monitor and evaluate the cause and evolution of the premature failure. Findings from this study indicated that the failure resulted from a combination of varied processes from procurement of material parts, material selection, welding processes and inaptly designed load-bearing mechanics of the generating set and its mounting arrangement. These in-field observations and experimental simulations provided insights to design and validate a numerical finite element sub-model of the cracked bedframe considering thermal cycling: designed as part of these investigations. Resulting findings led to a recommendation of several procedural changes that should be adopted by the manufacturer, in order to prevent the re-occurrence of such pre-mature failure in future industrial applications.

Keywords: Engine, Premature Failure, Failure Analysis, Finite Element Model

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: S. A. Agbalajobi, W. A. Bello

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The study carried out analysis on slope stability in an excavated gneiss rock using geological strength index (GSI) in Ilorin, Kwara State, Nigeria. A kinematic analysis of planar discontinuity sets in a gneiss deposit was carried out to ascertain the degree of slope stability. Discontinuity orientations in the rock mass were mapped using compass clinometers. The average result of physical and mechanical properties such as specific gravity, unit weight, uniaxial compressive strength, point load index, and Schmidt rebound value are 2.64 g/m3, 25.95 kN/m3, 156 MPa, 6.5 MPa, and 53.12 respectively. Also, a statistical model equation relating the rock strength was developed. The analyses states that the rock face is susceptible to wedge failures having all the geometrical conditions associated with the occurrence of such failures were noticeable. It can be concluded that analyses of discontinuity orientation in relation to cut face direction in rock excavation is essential for mine planning to forestall mine accidents. Assessment of excavated slope methods was evident that one excavation method (blasting and/or use of hydraulic hammer) is applicable for the given rock strength, the ease of excavation decreases as the rock mass quality increases, thus blasting most suitable for such operation.

Keywords: slope stability, wedge failure, geological strength index (GSI), discontinuities and excavated slope

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Authors: Mohammad Lemar Zalmai, Osman Hurol Turkakin, Cemil Akcay, Ekrem Manisali

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Most of the construction projects are exposed to time and cost overruns due to various factors and this is a major problem. As a solution to this, the Earned Value Management (EVM) method is considered. EVM is a powerful and well-known method used in monitoring and controlling the project. EVM is a technique that project managers use to track the performance of their project against project baselines. EVM gives an early indication that either project is delayed or not, and the project is either over budget or under budget at any particular day by tracking it. Thus, it helps to improve the management control system of a construction project, to detect and control the problems in potential risk areas and to suggest the importance and purpose of monitoring the construction work. This paper explains the main parameters of the EVM system involved in the calculation of time and cost for construction projects. In this study, the project management software Primavera P6 is used to deals with the project monitoring process of a seven-storeyed (G+6) faculty building whose construction is in progress at Istanbul, Turkey. A comparison between the planned progress of construction activities and actual progress is performed, and the analysis results are interpreted. This case study justifies the benefits of using EVM for project cash flow analysis and forecasting.

Keywords: earned value management (EVM), construction cost management, construction planning, primavera P6, project management, project scheduling

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Authors: Berrak Yildiz, Hinal Shah, Justine Fernandez, Nazje James, Anna Brown

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Cervical ectopic pregnancy, a rare type of ectopic pregnancies, is defined by blastocyst implantation within the cervical canal rather than the endometrium. Its rarity and potential for severe hemorrhage make cervical ectopic pregnancy a diagnostic and therapeutic challenge. A 39-year-old woman, G5P2022, with a history of two cesarean sections and two elective terminations, presented to the emergency department with vaginal bleeding and pelvic pain. Initial assessment showed a beta-hCG level of 2,853 mIU/mL, and transvaginal ultrasound revealed a small, irregular gestational sac at the level of the internal cervical os. Serial betahCG measurements over subsequent visits showed a declining trend, consistent with a nonviable pregnancy. The patient was ultimately treated with methotrexate at a dose of 50 mg/m² (total 100 mg), following which she reported no further symptoms. On follow-up, her beta-hCG level returned to the normal non-pregnant range, with no additional intervention needed. This case highlights the importance of early diagnosis in cervical ectopic pregnancy to avoid complications like hysterectomy. Methotrexate is an effective first-line treatment in hemodynamically stable patients, offering a conservative approach that can preserve fertility. The success in this patient underscores the role of prompt diagnosis and careful management in achieving resolution while minimizing invasive procedures.

Keywords: beta-hCG, cervical, ectopic, methotrexate

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Authors: G. A. Gevorgyan, A. S. Mamyan, L. G. Stepanyan, L. R. Hambaryan

Abstract:

Bacterio- and phytoplankton growth rates in 'Yerevanyan lich' reservoir and the Hrazdan river in Yerevan city, Armenia were investigated in April and June-August, 2015. Phytoplankton sampling and analysis were performed by the standard methods accepted in hydrobiological studies. The quantitative analysis of aerobic, coliform and E. coli bacteria is done by the 'RIDA COUNT' medium sheets (coated with ready-to-use culture medium). The investigations showed that the insufficient management of household discharges in Yerevan city caused the organic and fecal pollution of the Hrazdan river in this area which in turn resulted in an increase in bacterial count and increased sanitary and pathogenic risks to the environment and human health. During the investigation in April, the representatives of diatom algae prevailed quantitatively in the coastal area of 'Yerevanyan lich' reservoir, nevertheless, a significant change in the phytoplankton community in June occurred: due to green algae bloom in the reservoir, the quantitative parameters of phytoplankton increased significantly. This was probably conditioned by a seasonal increase in the water temperature in the conditions of the sufficient concentration of nutrients. However, a succession in phytoplankton groups during July-August occurred, and a dominant group (according to quantitative parameters) in the phytoplankton community was changed as follows: green algae-diatom algae-blue-green algae. Rapid increase in the quantitative parameters of diatom and blue-green algae in the reservoir may have been conditioned by increased organic matter level resulted from green algae bloom. Algal bloom in 'Yerevanyan lich' reservoir caused changes in phytoplankton community and an increase in bacterioplankton count not only in the reservoir but also in the Hrazdan river sites located in the downstream from the reservoir. Thus, the insufficient management of urban discharges and aquatic ecosystems in Yerevan city led to unfavorable changes in water quality and microbial and phytoplankton communities in “Yerevanyan lich” reservoir and the Hrazdan river which in turn caused increased sanitary and pathogenic risks to the environment and human health.

Keywords: algal bloom, bacterioplankton, phytoplankton, Hrazdan river, Yerevanyan lich reservoir

Procedia PDF Downloads 276

Authors: Muhamad Ammar Bin Mohd Asri, Muhammad Hamizan Bin Yusof, Muhammad Haziq Bin Abdul Khalil, Esman Hanief Bin Khairul Anuar, Muhammad Fikri Bin Ishak, Amril Azim Bin Mohd Norrahim, Muhammad Danial Fakhri Bin Fakhruddin, Muhammad Khairul Nizam in Hosnodin, Muhammad Ezzat Hariz Bin Norhisam

Abstract:

Ergonomics is the science of creating and arranging workplaces, products, and systems to increase human performance, comfort, and safety. This study researched ergonomics as a solution for preventing workplace injuries, specifically musculoskeletal disorders, among employers and employees. The method will be used in this project is a literature review which means conducting a study about ergonomics with peer-reviewed journal articles and books. It focuses on employees and employers who are in one company on other departments under the protection of Occupational Safety and Health (OSHA). These solutions include ergonomic assessments, workplace design improvements, effective training and education, and the use of ergonomic tools and equipment. Employers can build workplaces that are safer and more productive by putting these solutions in place, and employees can work comfortably and prevent accidents from bad ergonomics. Overall, the paper highlights how crucial it is to take injury prevention measures and consider ergonomics at work.

Keywords: occupational safety and health, musculoskeletal disorders, ergonomic, ergonomic risk

Procedia PDF Downloads 227

Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

Abstract:

High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

Procedia PDF Downloads 234

Authors: Lu Yu Jyun

Abstract:

Background: Health education is important nursing work aiming to strengthen patients’ self-caring ability and family members. Our department educates through three methods, including speech education, flyer and demonstration video education. The satisfaction rate of health education tool use is 54.3% in nursing staff. The main reason is there hadn’t been a storage area for flyers, causing extra workload in assessing flyers. The satisfaction rate of health education in patients and families is 70.7%. We aim to improve this situation between 13th April and 6th June 2021. Method: We introduce the ECRS method to erase repetitive and redundant actions. We redesign the health education tool usage workflow to improve nursing staffs’ efficiency and further enhance nursing staffs care quality and working satisfaction. Result: The satisfaction rate of health education tool usage in nursing staff elevated from 54.3% to 92.5%. The satisfaction rate of health education in patients and families elevated from 70.7% to 90.2%. Conclusion: The assessment time of health care tools dropped from 10minutes to 3minutes. This significantly reduced the nursing staffs’ workload. 1213 paper is saved in one month and 14,556 a year in the estimate; we save the environment via this action. Health education map implemented in other nursing departments since October due to its’ high efficiency and makes health care tools more humanize.

Keywords: health, education tools, satisfaction, nursing staff

Procedia PDF Downloads 153