Search results for: regional variables

Authors: Elnaz Entezar, Reza Ezzati

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In recent decades, trade flows, capital, workforce, technology and information have increased between international borders and the globalization has turned to an undeniable process in international economics. Meanwhile, despite the positive aspects of globalization, the critics of globalization opine that the risks and costs of globalization for developing vulnerable economies and the world's impoverished people are high and significant. In this regard, this study by using the data of KOF Economic Institute and the World Bank for 113 different countries during the period 2002-2012, by taking advantage of panel smooth transition regression, and by taking the gross domestic product as transmission variables discuss the nonlinear relationship between research variables. The results have revealed that globalization in low regime (countries with low GDP) has negative impact whereas in high regime (countries with high GDP) has a positive impact. In spite of the fact that in the early stages of growth, control of corruption has a positive impact on economic growth, after a threshold has a negative impact on economic growth.

Keywords: globalization, corruption, panel smooth transition model, economic growth, threshold, economic convergence

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Authors: Ahmed Bellakhdhar

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This paper aims to test the impact of various variables-namely, investment in physical capital, investment in human capital, openness to trade and foreign direct investments, and distance from the technology frontier-on economic growth in the Tunisian context during the period 1976-2010. Empirical results identify that the impact of human capital is significantly positive. This finding confirms the hypothesis that human capital is a main driver of economic performance through its role of improving the internal productive capacity and the absorption of foreign technology especially via foreign direct investments. The effect of FDI is significantly positive in all alternative regressions and the coefficient associated to physical capital variable is positive, but not significant overall. Concerning the import of technologically advanced equipments, our estimates show the absence of a significant direct impact on economic growth in Tunisia. Our empirical results also support the assumption of a non linear relationship between tax and growth and demonstrate the existence of an inverted-U curve between the two variables, in the spirit of the “Laffer curve”.

Keywords: Endogenous growth, Human capital, Technology transfer, Absorptive capacity

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Authors: Libin Ouyang

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China has experienced a very fast urbanization process in the past two decades. Due to the uncoordinated characteristics of regional development in China, a large number of people from rural areas or small towns have flooded into regional central cities, which are building new cities around them due to the shortage of construction land or the need for urban development. However, the construction of some new cities has not achieved the expected effect, the absorption capacity of industry and population is limited, and the phenomenon of capital and land waste is obvious. This paper takes the Xixian New Area in Shaanxi Province, an inland region in Northwest China, as an example, and tries to analyse the reasons for the lack of vitality in the current situation of the Xixian New Area from the perspective of site layout and urban design, analyses the practical experience of the construction of new city cores in developed countries and regions, and studies how to optimise at the level of site layout planning and urban design to improve the vitality and attractiveness of the new city, decongest the population of large cities, effectively solve the problems of large cities, and promote The study will also examine how to optimise land use planning and urban design to enhance the vitality and attractiveness of new cities, relieve the population of large cities, effectively solve the problems of large cities and promote sustainable development of new cities. The study can serve as a reference for urban planners and policy makers, provide theoretical assistance for new city construction in other less developed regions of China, and provide some case references for urban construction in other developing countries undergoing rapid urbanisation.

Keywords: new city, land use layout, urban design, attraction

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Authors: Avinash Thakur, Parmjit S. Panesar, Manohar Singh

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The distribution coefficient, KD for the reactive extraction of lactic acid from aqueous solutions of lactic acid using 10-30% (v/v) tri-n-octyl amine (extractant) dissolved in n-hexane (inert diluent) and 20% (v/v) oleyl alcohol (modifier) was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined interactive effect of seven independent variables, viz lactic acid concentration (cl), pH, TOA concentration in organic phase (ψ), treat ratio (φ), temperature (T), agitation speed (ω) and batch agitation time (τ) on distribution coefficient of lactic acid. The regression analysis recommended that the quadratic model is significant (R2 and adjusted R2 are 98.72 % and 98.69 % respectively) for analysis. A numerical optimization had resulted in maximum lactic acid distribution coefficient (KD) of 3.16 at the optimized values for test variables, cl, pH, ψ, φ, T, ω and τ as 0.15 [M], 3.0, 22.75% (v/v), 1.0 (v/v), 26°C, 145 rpm and 23 min respectively. A good agreement between the predicted and experimentally obtained values for distribution coefficient using the optimized conditions was exhibited.

Keywords: Distribution coefficient, tri-n-octylamine, lactic acid, response surface methodology

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Authors: Shanorfizah Mohd Safar, Shaizatulaqma Kamalul Ariffin

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Internationalization of halal small and medium-sized enterprises (SMEs) is necessary for SMEs to become more involved in regional trade and business cooperation. By internationalization, SMEs' profit can increase, and market expansion of SMEs is basic for rising economies of countries to contend all around in the halal industry globally. There are several modes of internationalization; exporting is one of the first steps for internationalization with less capital needed. The study examines the influential factors of export performance amongst halal SMEs in Malaysia. Specifically, this study examines the positive and significant relationships amongst human capital, managerial capability, Halal Assurance Management System (HAMS), digital transformation, government support, and networking capability on halal SMEs' export performance toward SMEs' competitive advantage. In addition, this study will examine innovation capabilities as a moderator in the relationship between independence variables and competitive advantage. Competitive advantage is the most compelling perspective that drives the export performance of halal SMEs in Malaysia. A quantitative method will be used: an online questionnaire survey distributed through emails and face-to-face toward selected halal-certificated SMEs registered in JAKIM, MATRADE website and SME Corp Malaysia website. Nevertheless, whether the halal SMEs practice global business, they will still be the potential respondents. The data were examined and obtained using the statistical software Smart PLS. The analysis used is reliability, correlation, and regression analysis to meet the research objectives. This study contributes significantly to the theory by integrating Resource Based View (RBV) theory, Technology–Organization–Environment (TOE) framework and Networking theory. In addition, this research extends the RBV by extending a variable, the Halal Assurance Management System. This study also examines a moderating role of innovation capabilities in the framework and competitive advantage as a mediator. This research aims to analyze the factors that will impact the internationalization of halal SMEs.

Keywords: internationalization, halal SMEs, competitive advantage, export performance

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Authors: Usriatur Rohma, Adji Achmad Rinaldo Fernandes

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Nonparametric path analysis is a statistical method that does not rely on the assumption that the curve is known. The purpose of this study is to determine the best nonparametric truncated spline path function between linear and quadratic polynomial degrees with 1, 2, and 3-knot points and to determine the significance of estimating the best nonparametric truncated spline path function in the model of the effect of population migration and agricultural economic growth on rural poverty through the variable unemployment rate using the t-test statistic at the jackknife resampling stage. The data used in this study are secondary data obtained from statistical publications. The results showed that the best model of nonparametric truncated spline path analysis is quadratic polynomial degree with 3-knot points. In addition, the significance of the best-truncated spline nonparametric path function estimation using jackknife resampling shows that all exogenous variables have a significant influence on the endogenous variables.

Keywords: nonparametric path analysis, truncated spline, linear, quadratic, rural poverty, jackknife resampling

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Nhi Ngoc Thien

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Franchising is a popular trend in Vietnam retail industry, especially in fast food industry. Several famous foreign fast food brands such as KFC, Lotteria, Jollibee or Pizza Hut invested on this potential market since the 1990s. Following this trend, in 2011, Burger King - the second largest fast food hamburger chain all over the world - entered Vietnam with its first store located in Tan Son Nhat International Airport, with the expectation to become the leading brand in the country. However, the business performance of Burger King was not going well in the first few years making it questioned about its strategy. The given assumption was that its business performance was affected negatively by its store location selection strategy. This research aims to investigate the current performance of Burger King Vietnam in terms of the controllable variables like store location as well as to explore the key factors influencing customer decision to choose Burger King. Therefore, a case study research method was conducted to approach deeply on the opinions and evaluations of 10 Burger King’s customers, Burger King's staffs and other fast food experts on Burger King’s performance through in-depth interview, direct observation and documentary analysis. Findings show that there are 8 determinants affecting the decision-making of Burger King’s customers, which are store location, quality of food, service quality, store atmosphere, price, promotion, menu and brand reputation. Moreover, findings present that Burger King’s staffs and fast food experts also mentioned the main problems of Burger King, which are about store location and food quality. As a result, there are some recommendations for Burger King Vietnam to improve its performance in the market and attract more Vietnamese target customers by giving suitable promotional activities among its customers and being differentiated itself from other fast food brands.

Keywords: overall retail strategy, controllable variables, store location, quality of food

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Authors: Daniel A. Montoya, Marta L. Tostes

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This investigation aims at analyzing and determining the relation between two very important variables in the human resource management: The organizational climate and the performance assessment. This study aims at contributing with knowledge in the search of the relation between the mentioned variables because the literature still does not provide solid evidence to this respect and the cases revised are incipient to reach conclusions enabling a typology about this relation.To this regard, a correlational and cross-sectional perspective was adopted in which quantitative and qualitative techniques were chosen with the total of the workers of the tourist service company PTS Peru. In order to measure the organizational climate, the OCQ (Organization Climate Questionnaire) from was used; it has 50 items and measures 9 dimensions of the Organizational Climate. Also, to assess performance, a questionnaire with 21 items and 6 dimensions was designed. As a means of assessment, a focus group was prepared and was applied to a worker in every area of the company. Additionally, interviews to human resources experts were conducted. The results of the investigation show a clear relation between the organizational climate and the personnel performance assessment as well as a relation between the nine dimensions of the organizational climate and the work performance in general and with some of its dimensions.

Keywords: job performance, job satisfaction, organization climate, performance assessment

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Authors: Usman Yakubu, Muktar Haruna

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The paper examines the impact of the audit committee on the earning quality of the listed consumer goods sector in Nigeria. The study used data collected from annual reports and accounts of the 13 sampled companies for the periods 2007 to 2018. Data were analyzed by means of descriptive statistics to provide summary statistics for the variables; also, correlation analysis was carried out using the Pearson correlation technique for the correlation between the dependent and independent variables. Regression was employed using the Generalized Least Square technique since the data has both time series and cross sectional attributes (panel data). It was found out that the audit committee had a positive and significant influence on the earning quality in the listed consumer goods companies in Nigeria. Thus, the study recommends that competency and personal integrity should be the worthwhile attributes to be considered while constituting the committee; this could enhance the quality of accounting information. In addition to that majority of the committee members should be independent directors in order to allow a high level of independency to be exercised.

Keywords: earning quality, corporate governance, audit committee, financial reporting

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Authors: Giulio Mangano, Alberto De Marco, Giovanni Zenezini

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The concept of City Logistics (CL) has emerged to improve the impacts of last mile freight distribution in urban areas. In this paper, a System Dynamics (SD) model exploring the dynamics of the diffusion of a ICT platform for CL management across different populations is proposed. For the development of the model two sources have been used. On the one hand, the major diffusion variables and feedback loops are derived from a literature review of existing diffusion models. On the other hand, the parameters are represented by the value propositions delivered by the platform as a response to some of the users’ needs. To extract the most important value propositions the Business Model Canvas approach has been used. Such approach in fact focuses on understanding how a company can create value for her target customers. These variables and parameters are thus translated into a SD diffusion model with three different populations namely municipalities, logistics service providers, and own account carriers. Results show that, the three populations under analysis fully adopt the platform within the simulation time frame, highlighting a strong demand by different stakeholders for CL projects aiming at carrying out more efficient urban logistics operations.

Keywords: city logistics, simulation, system dynamics, business model

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Authors: Chun-Qing Li, Hassan Baji, Wei Yang

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Corrosion of steel in reinforced concrete structures is a major problem worldwide. The volume expansion of corrosion products causes concrete cover cracking, which could lead to delamination of concrete cover. The time to cover cracking plays a key role to the assessment of serviceability of reinforced concrete structures subjected to corrosion. Many analytical, numerical, and empirical models have been developed to predict the time to cracking initiation due to corrosion. In this study, a numerical model based on finite element modeling of corrosion-induced cracking process is used. In order to predict the service life based on time to cover initiation, the numerical approach is coupled with a probabilistic procedure. In this procedure, all the influential factors affecting time to cover cracking are modeled as random variables. The results show that the time to cover cracking is highly variables. It is also shown that rust product expansion ratio and the size of more porous concrete zone around the rebar are the most influential factors in predicting service life of corrosion-affected structures.

Keywords: corrosion, crack width, probabilistic, service life

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Emad Mohammed Sani

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Women encounter exclusion and discrimination in varying degrees, particularly those who marry as minors. The detrimental custom of getting married young is still prevalent worldwide and affects millions of people. It has been less common over time, although it is still widespread in underdeveloped nations. Oromia Regional State is the region in Ethiopia with the highest proportion of child brides. This study aimed at evaluating the effects of early marriage on its survivors’ life conditions – specifically, empowerment and household decision-making – in Eastern Hararghe Zone of Oromia Region. This study employed community-based cross-sectional study design. It adopted mixed method approach – survey, in-depth interview and focus group discussion (FGD) – to collect, analyses and interpret data on early marriage and its effects on household decision-making processes. Narratives and analytical descriptions were integrated to substantiate and/or explain observed quantitative results, or generate contextual themes. According to this study, married women who were married at or after the age of eighteen participated more in household decision-making than child brides. Child brides were more likely to be victims of violence and other types of spousal abuse in their marriages. These changes are mostly caused by an individual's age at first marriage. Delaying marriage had a large positive impact on women's empowerment at the household level, and age at first marriage had a considerable negative impact. In order to advance women's welfare and emancipation, we advise more research to concentrate on the relationship between the home and the social-structural forms that appear at the individual and communal levels.

Keywords: child-bride, early marriage, women, ethiopia

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Authors: S. Masud, J. Merson, D. F. Robinson

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The management of environmental resources requires engagement of a range of stakeholders including public/private agencies and different community groups to implement sustainable conservation practices. The challenge which is often ignored is the analysis of agencies involved and their power relations. One of the barriers identified is the difference in risk perceptions among the agencies involved that leads to disjointed efforts of assessing and managing risks. Wood et al 2012, explains that it is important to have an integrated approach to risk management where decision makers address stakeholder perspectives. This is critical for an effective risk management policy. This abstract is part of a PhD research that looks into barriers to flood management under a changing climate and intends to identify bottlenecks that create maladaptation. Experiences are drawn from international practices in the UK and examined in the context of Australia through exploring the flood governance in a highly flood-prone region in Australia: the Hawkesbury Ne-pean catchment as a case study. In this research study several aspects of governance and management are explored: (i) the complexities created by the way different agencies are involved in assessing flood risks (ii) different perceptions on acceptable flood risk level; (iii) perceptions on community engagement in defining acceptable flood risk level; (iv) Views on a holistic flood risk management approach; and, (v) challenges of centralised information system. The study concludes that the complexity of managing a large catchment is exacerbated by the difference in the way professionals perceive the problem. This has led to: (a) different standards for acceptable risks; (b) inconsistent attempt to set-up a regional scale flood management plan beyond the jurisdictional boundaries: (c) absence of a regional scale agency with license to share and update information (d) Lack of forums for dialogue with insurance companies to ensure an integrated approach to flood management. The research takes the Hawkesbury-Nepean catchment as case example and draws from literary evidence from around the world. In addition, conclusions were extrapolated from eighteen semi-structured interviews from agencies involved in flood risk management in the Hawkesbury-Nepean catchment of NSW, Australia. The outcome of this research is to provide a better understanding of complexity in assessing risks against a rapidly changing climate and contribute towards developing effective risk communication strategies thus enabling better management of floods and achieving increased level of support from insurance companies, real-estate agencies, state and regional risk managers and the affected communities.

Keywords: adaptive governance, flood management, flood risk communication, stakeholder risk perceptions

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Authors: Ine Huybrechts, Anja Declercq, Emily Verté, Peter Raeymaeckers, Sibyl Anthierens

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Goal-oriented care is a concept gaining increased interest as an approach to go towards more coordinated and integrated primary care. It places patients’ personal life goals at the core of health care support, hereby shifting the focus from “what’s the matter with this patient” to “what matters to this patient.” In Flanders/Belgium, various primary care providers, health and social care organizations and governmental bodies have picked up this concept and have initiated actions to facilitate this approach. The implementation of goal-oriented care not only happens on the micro-level, but it also requires efforts on the meso- and macro-level. Within implementation research, there is a growing recognition that the context in which an intervention takes place strongly relates to its implementation outcomes. However, when investigating contextual variables, the external context and its impact on implementation processes is often overlooked. This study aims to explore how we can better identify and understand the external context and how it relates to the mechanism of change within the implementation process of goal-oriented care in Flanders/Belgium. Results can be used to support and guide initiatives to introduce innovative approaches such as goal-oriented care inside an organization or in the broader primary care landscape. We have conducted qualitative research, performing in-depth interviews with n=23 respondents who have affinity with the implementation of goal-oriented care within their professional function. This lead to in-depth insights from a wide range of actors, with meso-level and/or macro-level perspectives on the implementation of goal-oriented care. This means that we have interviewed actors that are not only involved with initiatives to implement goal-oriented care, but also actors that actively give form to the external context in which goal-oriented care is implemented. Data were collected using a semi-structured interview guide, audio recorded, and analyzed first inductively and then deductively using various theories and concepts that derive from organizational research. Our preliminary findings suggest t Our findings can contribute to further define actions needed for sustainable implementation of goal-oriented primary care. It gives insights in the dynamics between contextual variables and implementation efforts, hereby indicating towards those contextual variables that can be further shaped to facilitate the implementation of an innovation such as goal-oriented care. hat organizational theories can help understand the mechanism of change of implementation processes with a macro-level perspective. Institutional theories, contingency theories, resources dependency theories and others can expose the mechanism of change for an innovation such as goal-oriented care. Our findings can contribute to further define actions needed for sustainable implementation of goal-oriented primary care. It gives insights in the dynamics between contextual variables and implementation efforts, hereby indicating towards those contextual variables that can be further shaped to facilitate the implementation of an innovation such as goal-oriented care.

Keywords: goal-oriented care, implementation processes, organizational theories, person-centered care, implementation research

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Authors: Jesmin Akter, Chang Hyuk Ahn, Ilho Kim, Jaiyeop Lee

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Global pandemic coronavirus disease (COVID-19) caused by Severe acute respiratory syndrome SARS-CoV-2, to control the spread of the COVID-19 pandemic, wastewater surveillance has been used to monitor SARS-CoV2 prevalence in the community. The challenging part is establishing wastewater surveillance; there is a need for a well-equipped laboratory for wastewater sample analysis. According to many previous studies, reverse transcription-polymerase chain reaction (RT-PCR) based molecular tests are the most widely used and popular detection method worldwide. However, the RT-qPCR based approaches for the detection or quantification of SARS-CoV-2 genetic fragments ribonucleic acid (RNA) from wastewater require a specialized laboratory, skilled personnel, expensive instruments, and a workflow that typically requires 6 to 8 hours to provide results for just minimum samples. Rapid and reliable alternative detection methods are needed to enable less-well-qualified practitioners to set up and provide sensitive detection of SARS-CoV-2 within wastewater at less-specialized regional laboratories. Therefore, scientists and researchers are conducting experiments for rapid detection methods of COVID-19; in some cases, the structural and molecular characteristics of SARS-CoV-2 are unknown, and various strategies for the correct diagnosis of COVID-19 have been proposed by research laboratories, which are presented in the present study. The ongoing research and development of these highly sensitive and rapid technologies, namely RT-LAMP, ELISA, Biosensors, GeneXpert, allows a wide range of potential options not only for SARS-CoV-2 detection but also for other viruses as well. The effort of this study is to discuss the above effective and regional rapid detection and quantification methods in community wastewater as an essential step in advancing scientific goals.

Keywords: rapid detection, SARS-CoV-2, sensitive detection, wastewater surveillance

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Authors: Omar A. A. Shaebi, Matouk M. Elamari, Salaheddin Allid

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The Information Computing System of Monitoring (ICSM) for the Research Reactor of Tajoura Nuclear Research Centre (TNRC) stopped working since early 1991. According to the regulations, the computer is necessary to operate the reactor up to its maximum power (10 MW). The fund is secured via IAEA to develop a modern computer based data acquisition system to replace the old computer. This paper presents the development of the Labview based data acquisition system to allow automated measurements using National Instruments Hardware and its labview software. The developed system consists of SCXI 1001 chassis, the chassis house four SCXI 1100 modules each can maintain 32 variables. The chassis is interfaced with the PC using NI PCI-6023 DAQ Card. Labview, developed by National Instruments, is used to run and operate the DAQ System. Labview is graphical programming environment suited for high level design. It allows integrating different signal processing components or subsystems within a graphical framework. The results showed system capabilities in monitoring variables, acquiring and saving data. Plus the capability of the labview to control the DAQ.

Keywords: data acquisition, labview, signal conditioning, national instruments

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Authors: Enayatollah Yazdani

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Globalization is the most significant change in today’s world. It has caused remarkable growth in different aspects of human life. Such a strong contribution to the development would not have occurred without the role that each country and particularly great powers play in the globalization process. Among those powers is China, whose role in the globalization trend is growing fast. With its rapid economic and technological development, China has moved from a regional economic power to a global powerhouse. Accordingly, China has been supporting the development of global infrastructure through new initiatives and institutions such as the Asia Infrastructure Investment Bank and the New Development Bank, among them, the most ambitious manifestation of these efforts is China Belt and Road Initiative (BRI). BRI is seen as an important vehicle that helps China to play a more proactive role in the globalization process. China started Belt and Road initiative as a global drive in more than 65 (now more than 140) countries in Asia, the Middle East, Central Asia, Latin America, Africa, and Europe, offering the world a unique state of bigger openness, integration, and interdependence with a comprehensive approach to shared development, shared future, and shared opportunities. As a result, one can say that BRI is an attempt by China to promote international cooperation and enhance globalization. However, in this regard, China may face some challenges as well. This paper aims to address: how China is playing a role in globalization through BRI and how BRI will support the Chinese role in the globalization process. And what are the major challenges that China might be faced? Based on the analytical methodology, the paper argues that BRI is a cornucopia of international projects that offer mammoth opportunities for more economic cooperation and deeper regional and global integration, primarily among emerging economies. The paper discusses that at a time when globalization from the West appears to be in retreat, the BRI is a potent symbol of the rise of China-based globalization.

Keywords: globalization, China, belt, and road initiative

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

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Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense

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The Wairau Plains are located in the northeast of the South Island of New Zealand, with alluvial deposits of fine-grained silts and sands combined with low-lying topography suggesting the presence of liquefiable deposits over significant portions of the region. Liquefaction manifestations were observed in past earthquakes, including the 1848 Marlborough and 1855 Wairarapa earthquakes, and more recently during the 2013 Lake Grassmere and 2016 Kaikōura earthquakes. Therefore, a good understanding of the deposits that may be susceptible to liquefaction is important for land use planning in the region and to allow developers and asset owners to appropriately address their risk. For this purpose, multiple approaches have been employed to develop regional-scale maps showing the liquefaction vulnerability categories for the region. After applying semi-qualitative criteria linked to geologic age and deposit type, the higher resolution surface mapping of geomorphologic characteristics encompassing the Wairau River and the Opaoa River was used for screening. A detailed basin geologic model developed for groundwater modelling was analysed to provide a higher level of resolution than the surface-geology based classification. This is used to identify the thickness of near-surface gravel deposits, providing an improved understanding of the presence or lack of potentially non-liquefiable crust deposits. This paper describes the methodology adopted for this project and focuses on the influence of geomorphic characteristics and analysis of the detailed geologic basin model on the liquefaction classification of the Lower Wairau Plains.

Keywords: liquefaction, earthquake, cone penetration test, mapping, liquefaction-induced damage

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Authors: Lei Li, Ping Yin, Haneen Khreis

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Stroke is the second leading cause of death and a third leading cause of death and disability worldwide in 2019. Given the significant role of environmental factors in stroke development and progression, it is essential to investigate the effect of air pollution on stroke occurrence while considering the modifying effects of meteorological variables. This study aimed to evaluate the association between short-term exposure to air pollution and the incidence of stroke subtypes in Shenzhen, China, and to explore the potential interactions of meteorological factors with air pollutants. The study analyzed data from January 1, 2006, to December 31, 2014, including 88,214 cases of ischemic stroke and 30,433 cases of hemorrhagic stroke among residents of Shenzhen. Using a time-stratified case–crossover design with conditional quasi-Poisson regression, the study estimated the percentage changes in stroke morbidity associated with short-term exposure to nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter less than 10 mm in aerodynamic diameter (PM10), carbon monoxide (CO), and ozone (O₃). A five-day moving average of air pollution was applied to capture the cumulative effects of air pollution. The estimates were further stratified by sex, age, education level, and season. The additive and multiplicative interaction between air pollutants and meteorologic variables were assessed by the relative excess risk due to interaction (RERI) and adding the interactive term into the main model, respectively. The study found that NO₂ was positively associated with ischemic stroke occurrence throughout the year and in the cold season (November through April), with a stronger effect observed among men. Each 10 μg/m³ increment in the five-day moving average of NO₂ was associated with a 2.38% (95% confidence interval was 1.36% to 3.41%) increase in the risk of ischemic stroke over the whole year and a 3.36% (2.04% to 4.69%) increase in the cold season. The harmful effect of CO on ischemic stroke was observed only in the cold season, with each 1 mg/m³ increment in the five-day moving average of CO increasing the risk by 12.34% (3.85% to 21.51%). There was no statistically significant additive interaction between individual air pollutants and temperature or relative humidity, as demonstrated by the RERI. The interaction term in the model showed a multiplicative antagonistic effect between NO₂ and temperature (p-value=0.0268). For hemorrhagic stroke, no evidence of the effects of any individual air pollutants was found in the whole population. However, the RERI indicated a statistically additive and multiplicative interaction of temperature on the effects of PM10 and O₃ on hemorrhagic stroke onset. Therefore, the insignificant conclusion should be interpreted with caution. The study suggests that environmental NO₂ and CO might increase the morbidity of ischemic stroke, particularly during the cold season. These findings could help inform policy decisions aimed at reducing air pollution levels to prevent stroke and other health conditions. Additionally, the study provides valuable insights into the interaction between air pollution and meteorological variables, which underscores the need for further research into the complex relationship between environmental factors and health.

Keywords: air pollution, meteorological variables, interactive effect, seasonal pattern, stroke

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Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

Procedia PDF Downloads 87

Authors: Wajid Ali Khan

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Extensive experimentation and numerical investigation are performed to predict the machining-induced residual stresses in the end milling of AISI 1045 steel, and an optimization code has been developed using the particle swarm optimization technique. Experiments were conducted using a single factor at a time and design of experiments approach. Regression analysis was done, and a mathematical model of the cutting process was developed, thus predicting the machining-induced residual stress with reasonable accuracy. The mathematical model served as the objective function to be optimized using particle swarm optimization. The relationship between the different cutting parameters and the output variables, force, and residual stresses has been studied. The combined effect of the process parameters, speed, feed, and depth of cut was examined, and it is understood that 85% of the variation of these variables can be attributed to these machining parameters under research. A 3D finite element model is developed to predict the cutting forces and the machining-induced residual stresses in end milling operation. The results were validated experimentally and against the Johnson-cook model available in the literature.

Keywords: residual stresses, end milling, 1045 steel, optimization

Procedia PDF Downloads 93

Authors: Manojkumar Sabanayagam

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The Riemann hypothesis is an unsolved millennium problem and the search for a solution to the Riemann hypothesis is to study the pattern of prime number distribution. The scope of this paper is to identify the solution for the critical strip and the critical line axis, which has the non-trivial zero solutions using complex plane functions. The Riemann graphical plot is constructed using a linear complex variable function (X+iY) and is applicable only when X>1. But the investigation shows that complex variable behavior has two zones. The first zone is the transformation zone, where the definition of the complex plane should be a non-linear variable which is the critical strip zone in the graph (X=0 to 1). The second zone is the transformed zone (X>1) defined using linear variables conventionally. This paper deals with the Non-linear function in the transformation zone derived using cosine and sinusoidal time lag w.r.t imaginary number ‘i’. The alternate complex variable (Cosθ+i Sinθ) is used to understand the variables in the critical strip zone. It is concluded that the non-trivial zeros present in the Real part 0.5 are because the linear function is not the correct approach in the critical strip. This paper provides the solution to Reimann's hypothesis.

Keywords: Reimann hypothesis, critical strip, complex plane, transformation zone

Procedia PDF Downloads 193

Authors: Partha Saha, Uttam Kumar Banerjee

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Maternal and Child Healthcare (MCH) has always been regarded as one of the important issues globally. Reduction of maternal and child mortality rates and increase of healthcare service coverage were declared as one of the targets in Millennium Development Goals till 2015 and thereafter as an important component of the Sustainable Development Goals. Over the last decade, worldwide MCH indicators have improved but could not match the expected levels. Progress of both maternal and child mortality rates have been monitored by several researchers. Each of the studies has stated that only less than 26% of low-income and middle income countries (LMICs) were on track to achieve targets as prescribed by MDG4. Average worldwide annual rate of reduction of under-five mortality rate and maternal mortality rate were 2.2% and 1.9% as on 2011 respectively whereas rates should be minimum 4.4% and 5.5% annually to achieve targets. In spite of having proven healthcare interventions for both mothers and children, those could not be scaled up to the required volume due to fragmented health systems, especially in the developing and under-developed countries. In this research, a knowledge discovery based interactive Decision Support System (DSS) has been developed on web platform which would assist healthcare policy makers to develop evidence-based policies. To achieve desirable results in MCH, efficient resource planning is very much required. In maximum LMICs, resources are big constraint. Knowledge, generated through this system, would help healthcare managers to develop strategic resource planning for combatting with issues like huge inequity and less coverage in MCH. This system would help healthcare managers to accomplish following four tasks. Those are a) comprehending region wise conditions of variables related with MCH, b) identifying relationships within variables, c) segmenting regions based on variables status, and d) finding out segment wise key influential variables which have major impact on healthcare indicators. Whole system development process has been divided into three phases. Those were i) identifying contemporary issues related with MCH services and policy making; ii) development of the system; and iii) verification and validation of the system. More than 90 variables under three categories, such as a) educational, social, and economic parameters; b) MCH interventions; and c) health system building blocks have been included into this web-based DSS and five separate modules have been developed under the system. First module has been designed for analysing current healthcare scenario. Second module would help healthcare managers to understand correlations among variables. Third module would reveal frequently-occurring incidents along with different MCH interventions. Fourth module would segment regions based on previously mentioned three categories and in fifth module, segment-wise key influential interventions will be identified. India has been considered as case study area in this research. Data of 601 districts of India has been used for inspecting effectiveness of those developed modules. This system has been developed by importing different statistical and data mining techniques on Web platform. Policy makers would be able to generate different scenarios from the system before drawing any inference, aided by its interactive capability.

Keywords: maternal and child heathcare, decision support systems, data mining techniques, low and middle income countries

Procedia PDF Downloads 243

Authors: Apipol Penkitti

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The new normal or a new way of life stemmed from the COVID-19 outbreak, gave rise to a new form of social media: audio-based social platforms (ABSPs), known as Clubhouse, Twitter space, and Facebook live audio room. These platforms, on which audio-based communication is featured, became popular in a short span of time. The objective of the research study is to understand ABSPs users’ behaviors in Thailand. The study, in which functional attitude theory, uses and gratifications theory, and social influence theory are referred to, is conducted through consumer perceived utilitarian, hedonic, and social value that affect engagement. This research study is mixed method paradigm, utilizing Model of Triangulation as its framework. The data acquisition is proceeded through questionnaires from a sample of 384 male, female and LGBTQA+ individuals aged 25 - 34 who, from various occupations, have used audio-based social platform applications. This research study employs the structural equation modeling to analyze the relationships between variables, and it uses the semi - structured interviewing to comprehend the rationality of the variables in the study. The study found that hedonic value directly affects engagement.

Keywords: audio based social platform, engagement, hedonic, perceived value, social, utilitarian

Procedia PDF Downloads 109

Authors: Ghada Abo-Zaid

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The main objective of this study was to examine the association between the elevated level of CRP and incidence of hypertension before and after adjusting by age, BMI, gender, SES, smoking, diabetes, cholesterol LDL and cholesterol HDL and to determine whether the association were differ by race. Method: Cross sectional data for participations from age 17 to age 74 years who included in The National Health and Nutrition Examination Survey (NHANES) from 1999 to 2010 were analysed. CRP level was classified into three categories ( > 3mg/L, between 1mg/LL and 3mg/L, and < 3 mg/L). Blood pressure categorization was done using JNC 7 algorithm Hypertension defined as either systolic blood pressure (SBP) of 140 mmHg or more and disystolic blood pressure (DBP) of 90mmHg or greater, otherwise a self-reported prior diagnosis by a physician. Pre-hypertension was defined as (139 > SBP > 120 or 89 > DPB > 80). Multinominal regression model was undertaken to measure the association between CRP level and hypertension. Results: In univariable models, CRP concentrations > 3 mg/L were associated with a 73% greater risk of incident hypertension compared with CRP concentrations < 1 mg/L (Hypertension: odds ratio [OR] = 1.73; 95% confidence interval [CI], 1.50-1.99). Ethnic comparisons showed that American Mexican had the highest risk of incident hypertension (odds ratio [OR] = 2.39; 95% confidence interval [CI], 2.21-2.58).This risk was statistically insignificant, however, either after controlling by other variables (Hypertension: OR = 0.75; 95% CI, 0.52-1.08,), or categorized by race [American Mexican: odds ratio [OR] = 1.58; 95% confidence interval [CI], 0,58-4.26, Other Hispanic: odds ratio [OR] = 0.87; 95% confidence interval [CI], 0.19-4.42, Non-Hispanic white: odds ratio [OR] = 0.90; 95% confidence interval [CI], 0.50-1.59, Non-Hispanic Black: odds ratio [OR] = 0.44; 95% confidence interval [CI], 0.22-0,87]. The same results were found for pre-hypertension, and the Non-Hispanic black showed the highest significant risk for Pre-Hypertension (odds ratio [OR] = 1.60; 95% confidence interval [CI], 1.26-2.03). When CRP concentrations were between 1.0-3.0 mg/L, in an unadjusted models prehypertension was associated with higher likelihood of elevated CRP (OR = 1.37; 95% CI, 1.15-1.62). The same relationship was maintained in Non-Hispanic white, Non-Hispanic black, and other race (Non-Hispanic white: OR = 1.24; 95% CI, 1.03-1.48, Non-Hispanic black: OR = 1.60; 95% CI, 1.27-2.03, other race: OR = 2.50; 95% CI, 1.32-4.74) while the association was insignificant with American Mexican and other Hispanic. In the adjusted model, the relationship between CRP and prehypertension were no longer available. In contrary, Hypertension was not independently associated with elevated CRP, and the results were the same after grouped by race or adjusted by the confounder variables. The same results were obtained when SBP or DBP were on a continuous measure. Conclusions: This study confirmed the existence of an association between hypertension, prehypertension and elevated level of CRP, however this association was no longer available after adjusting by other variables. Ethic group differences were statistically significant at the univariable models, while it disappeared after controlling by other variables.

Keywords: CRP, hypertension, ethnicity, NHANES, blood pressure

Procedia PDF Downloads 395

Authors: Olakunle Felix Adekunle

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In the recent years several non-tariff provisions have been regarded as means holding back transboundary environmental damages. Affected countries have then increasingly come up with trade policies to compensate for or to In recent years, several non‐tariff trade provisions have been regarded as means of holding back transboundary environmental damages. Affected countries have then increasingly come up with trade policies to compensate for or to enforce the adoption of environmental policies elsewhere. These non‐tariff trade constraints are claimed to threaten the freedom of trading across nations, as well as the harmonization sought towards the distribution of income and policy measures. Therefore the ‘greening’ of world trade issues essentially ranges over whether there ought or ought not to be a trade‐off between trade and environmental policies. The impacts of free trade and environmental policies on major economic variables (such as trade flows, balances of trade, resource allocation, output, consumption and welfare) are thus studied here, and so is the EKC hypothesis, when such variables are played against the resulting emission levels. The policy response is seen as a political game, played here by two representative parties named North and South. Whether their policy choices, simulated by four scenarios, are right or wrong depends on their policy goals, split into economic and environmental ones.

Keywords: environmental, policies, strategies, constraint

Procedia PDF Downloads 314

Authors: Jonardan Koner

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The study attempts to find out the impact of infrastructural investment on state economic growth in India. It further tries to determine the magnitude of the impact of infrastructural investment on economic indicator, i.e., per-capita income (PCI) in Indian States. The study uses panel regression technique to measure the impact of infrastructural investment on per-capita income (PCI) in Indian States. Panel regression technique helps incorporate both the cross-section and time-series aspects of the dataset. In order to analyze the difference in impact of the explanatory variables on the explained variables across states, the study uses Fixed Effect Panel Regression Model. The conclusions of the study are that infrastructural investment has a desirable impact on economic development and that the impact is different for different states in India. We analyze time series data (annual frequency) ranging from 1991 to 2010. The study reveals that the infrastructural investment significantly explains the variation of economic indicators.

Keywords: infrastructural investment, multiple regression, panel regression techniques, economic development, fixed effect dummy variable model

Procedia PDF Downloads 356