Search results for: decision tree forest
1090 Analysis of Municipal Solid Waste Management in Nigeria
Authors: Anisa Gumel
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This study examines the present condition of solid waste management in Nigeria. The author explores the challenges and opportunities affecting municipal solid waste management in "Nigeria" and determines the most profound challenges by analysing the interdependence and interrelationship among identified variables. In this study, multiple stakeholders, including 15 waste management professionals interviewed online, were utilised to identify the difficulties and opportunities affecting municipal solid waste in Nigeria. The interviews were transcribed and coded using NVivo to produce pertinent variables. An online survey of Nigerian internet and social media users was done to validate statements made by experts on the identified variable. In addition, a panel of five experts participated in a focus group discussion to discover the most influential factors that influence municipal solid waste management in Nigeria by analysing the interrelationships as well as the driving and reliant power of variables. The results show significant factors affecting municipal solid waste in Nigeria, including inadequate funding, lack of knowledge, and absence of legislation, as well as behavioural, financial, technological, and legal concerns grouped into five categories. Some claims stated by experts in the interview are supported by the survey data, while others are not. In addition, the focus group reveals patterns, correlations, and driving forces between variables that have been analysed. This study will provide decision-makers with a roadmap for resolving important waste management concerns in Nigeria and managing scarce resources effectively. It will also help non-governmental organisations combat malaria in Nigeria and other underdeveloped nations. In addition, the work contributes to the literature for future scholars to consult.Keywords: municipal solid waste, stakeholders, public, experts
Procedia PDF Downloads 691089 VISSIM Modeling of Driver Behavior at Connecticut Roundabouts
Authors: F. Clara Fang, Hernan Castaneda
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The Connecticut Department of Transportation (ConnDOT) has constructed four roundabouts in the State of Connecticut within the past ten years. VISSIM traffic simulation software was utilized to analyze these roundabouts during their design phase. The queue length and level of service observed in the field appear to be better than predicted by the VISSIM model. The objectives of this project are to: identify VISSIM input variables most critical to accurate modeling; recommend VISSIM calibration factors; and, provide other recommendations for roundabout traffic operations modeling. Traffic data were collected at these roundabouts using Miovision Technologies. Cameras were set up to capture vehicle circulating activity and entry behavior for two weekdays. A large sample size of filed data was analyzed to achieve accurate and statistically significant results. The data extracted from the videos include: vehicle circulating speed; critical gap estimated by Maximum Likelihood Method; peak hour volume; follow-up headway; travel time; and, vehicle queue length. A VISSIM simulation of existing roundabouts was built to compare both queue length and travel time predicted from simulation with measured in the field. The research investigated a variety of simulation parameters as calibration factors for describing driver behaviors at roundabouts. Among them, critical gap is the most effective calibration variable in roundabout simulation. It has a significant impact to queue length, particularly when the volume is higher. The results will improve the design of future roundabouts in Connecticut and provide decision makers with insights on the relationship between various choices and future performance.Keywords: driver critical gap, roundabout analysis, simulation, VISSIM modeling
Procedia PDF Downloads 2831088 The Effects of Cost-Sharing Contracts on the Costs and Operations of E-Commerce Supply Chains
Authors: Sahani Rathnasiri, Pritee Ray, Sardar M. N. Isalm, Carlos A. Vega-Mejia
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This study develops a cooperative game theory-based cost-sharing contract model for a business to consumer (B2C) e-commerce supply chain to minimize the overall supply chain costs and the individual costs within an information asymmetry scenario. The objective of this study is to address the issues of strategic interactions among the key players of the e-commerce supply chain operation, which impedes the optimal operational outcomes. Game theory has been included in the field of supply chain management to resolve strategic decision-making issues; however, most of the studies are limited only to two-echelons of the supply chains. Multi-echelon supply chain optimizations based on game-theoretic models are less explored in the previous literature. This study adopts a cooperative game model to focus on the common payoff of operations and addresses the issues of information asymmetry and coordination of a three-echelon e-commerce supply chain. The cost-sharing contract model integrates operational features such as production, inventory management and distribution with the contract related constraints. The outcomes of the model highlight the importance of maintaining lower operational costs by all players to obtain benefits from the cost-sharing contract. Further, the cost-sharing contract ensures true cost revelation, and hence eliminates the information asymmetry issues among the players. Comparing the results of the contract model with the de-centralized e-commerce supply chain operation further emphasizes that the cost-sharing contract derives Pareto-improved outcomes and minimizes the costs of overall e-commerce supply chain operation.Keywords: cooperative game theory, cost-sharing contract, e-commerce supply chain, information asymmetry
Procedia PDF Downloads 1141087 A Comparative Study of Dengue Fever in Taiwan and Singapore Based on Open Data
Authors: Wei Wen Yang, Emily Chia Yu Su
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Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti
Procedia PDF Downloads 2241086 ADP Approach to Evaluate the Blood Supply Network of Ontario
Authors: Usama Abdulwahab, Mohammed Wahab
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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem
Procedia PDF Downloads 4971085 Business Program Curriculum with Industry-Recognized Certifications: An Empirical Study of Exam Results and Program Curriculum
Authors: Thomas J. Bell III
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Pursuing a business degree is fraught with perplexing questions regarding the rising tuition cost and the immediate value of earning a degree. Any decision to pursue an undergraduate business degree is perceived to have value if it facilitates post-graduate job placement. Business programs have decreased value in the absence of innovation in business programs that close the skills gap between recent graduates and employment opportunities. Industry-based certifications are seemingly becoming a requirement differentiator among job applicants. Texas Wesleyan University offers a Computer Information System (CIS) program with an innovative curriculum that integrates industry-recognized certification training into its traditional curriculum with core subjects and electives. This paper explores a culture of innovation in the CIS business program curriculum that creates sustainable stakeholder value for students, employers, the community, and the university. A quantitative research methodology surveying over one-hundred students in the CIS program will be used to examine factors influencing the success or failure of students taking certification exams. Researchers will analyze control variables to identify specific correlations between practice exams, teaching pedagogy, study time, age, work experience, etc. This study compared various exam preparation techniques to corresponding exam results across several industry certification exams. The findings will aid in understanding control variables with correlations that positively and negatively impact exam results. Such discovery may provide useful insight into pedagogical impact indicators that positively contribute to certification exam success and curriculum enhancement.Keywords: taking certification exams, exam training, testing skills, exam study aids, certification exam curriculum
Procedia PDF Downloads 761084 Bio-Hub Ecosystems: Profitability through Circularity for Sustainable Forestry, Energy, Agriculture and Aquaculture
Authors: Kimberly Samaha
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The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding biomass as a feedstock for power plants. Yet the lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. This study analyzed data and submittals to the Born Global Maine Innovation Challenge. The Innovation Challenge was a global innovation challenge to identify process innovations that could address a ‘whole-tree’ approach of maximizing the products, byproducts, energy value and process slip-streams into a circular zero-waste design. Participating companies were at various stages of developing bioproducts and included biofuels, lignin-based products, carbon capture platforms and biochar used as both a filtration medium and as a soil amendment product. This case study shows the QCA (Qualitative Comparative Analysis) methodology of the prequalification process and the resulting techno-economic model that was developed for the maximizing profitability of the Bio-Hub Ecosystem through continuous expansion of system waste streams into valuable process inputs for co-hosts. A full site plan for the integration of co-hosts (biorefinery, land-based shrimp and salmon aquaculture farms, a tomato green-house and a hops farm) at an operating forestry-based biomass to energy plant in West Enfield, Maine USA. This model and process for evaluating the profitability not only proposes models for integration of forestry, aquaculture and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. In this particular study, profitability is assessed at two levels CAPEX (Capital Expenditures) and in OPEX (Operating Expenditures). Given that these projects start with repurposing facilities where the industrial level infrastructure is already built, permitted and interconnected to the grid, the addition of co-hosts first realizes a dramatic reduction in permitting, development times and costs. In addition, using the biomass energy plant’s waste streams such as heat, hot water, CO₂ and fly ash as valuable inputs to their operations and a significant decrease in the OPEX costs, increasing overall profitability to each of the co-hosts bottom line. This case study utilizes a proprietary techno-economic model to demonstrate how utilizing waste streams of a biomass energy plant and/or biorefinery, results in significant reduction in OPEX for both the biomass plants and the agriculture and aquaculture co-hosts. Economically viable Bio-Hubs with favorable environmental and community impacts may prove critical in garnering local and federal government support for pilot programs and more wide-scale adoption, especially for those living in severely economically depressed rural areas where aging industrial sites have been shuttered and local economies devastated.Keywords: bio-economy, biomass energy, financing, zero-waste
Procedia PDF Downloads 1231083 Early Impact Prediction and Key Factors Study of Artificial Intelligence Patents: A Method Based on LightGBM and Interpretable Machine Learning
Authors: Xingyu Gao, Qiang Wu
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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.Keywords: patent influence, interpretable machine learning, predictive models, SHAP
Procedia PDF Downloads 361082 The Conceptual Exploration of Comfort Zone by Using Content Analysis
Authors: Lilla Szabó Hangya, Szilvia Jambori
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The comfort zone is less studied area in the field of psychology. One of the most important definitions is that comfort zone is a psychological state in which things feel familiar to a person with low level of anxiety and stress. But the validity of comfort zone does not confirm till now. The aim of our pilot research is to test which psychological factors could determine how young adults behave during their decision process to stay in one’s comfort zone or to leave it. Every person has a number of comfort zones, so we are not able to measure it directly, only those personality traits which predict if someone leaves his comfort zone easier or harder. In our study at first we wanted to clarify the meaning of comfort zone. 110 young adults (male: 37, female: 73; ages from 18 to 70, average age: 26,6) took part in the study. Beside their demographic datas we asked them what does the comfort zone mean for them. The results showed that the meaning of the comfort zone can be grouped in five dimensions: comfort (49,6 %), leaving it-change (8,1%), ambivalent feelings (10,6%), related to other people (10,6%), pursuit of self-realization (16,8%). Our results demonstrated age related characteristics. For young people at the age of 19 the comfort zone is related to other people, because during adolescents peer relationships become more important. Subjects at the age 20-30 answered that the comfort zone means comfort and stability for them. Their life becomes stable for a while, they are studying or working. But at the age of 25, when they finish university, most of them answered comfort zone means a changing process for them. On the other hand for subjects at the age of 27 the means of the comfort zone is pursuit of self-realization. After that period at the age of 31 when they have families and stable job the stability will also dominant. We saw that the comfort zone has much more meaning besides a pleasant psychological trait. Further we would like to determine which psychological factors relate to comfort zone, and what kind of personality traits could predict leaving or staying in one’s comfort zone. We want to observe the relationship between comfort zone and subjective well-being, life satisfaction self-efficacy or self-esteem.Keywords: comfort zone, development, personality trait, young adults
Procedia PDF Downloads 3291081 Public Policy as a Component of Entrepreneurship Ecosystems: Challenges of Implementation
Authors: José Batista de Souza Neto
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This research project has as its theme the implementation of public policies to support micro and small businesses (MSEs). The research problem defined was how public policies for access to markets that drive the entrepreneurial ecosystem of MSEs are implemented. The general objective of this research is to understand the process of implementing a public policy to support the entrepreneurial ecosystem of MSEs by the Support Service for Micro and Small Enterprises of the State of São Paulo (SEBRAESP). Public policies are constituent elements of entrepreneurship ecosystems that influence the creation and development of ventures from the action of the entrepreneur. At the end of the research, it is expected to achieve the results for the following specific objectives: (a) understand how the entrepreneurial ecosystem of MSEs is constituted; (b) understand how market access public policies for MSEs are designed and implemented; (c) understand SEBRAE's role in the entrepreneurship ecosystem; and (d) offer an action plan and monitor its execution up to march, 2023. The field research will be conducted based on Action Research, with a qualitative and longitudinal approach to the data. Data collection will be based on narratives produced since 2019 when the decision to implement Comércio Brasil program, a public policy focused on generating market access for 4280 MSEs yearly, was made. The narratives will be analyzed by the method of document analysis and narrative analysis. It is expected that the research will consolidate the relevance of public policies to market access for MSEs and the role of SEBRAE as a protagonist in the implementation of these public policies in the entrepreneurship ecosystem will be demonstrated. Action research is recognized as an intervention method, it is expected that this research will corroborate its role in supporting management processes.Keywords: entrepreneurship, entrepreneurship ecosystem, public policies, SEBRAE, action research
Procedia PDF Downloads 1761080 Comparative Study to Evaluate the Efficacy of Control Criterion in Determining Consolidation Scope in the Public Sector
Authors: Batool Zarei
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This study aims to answer this question whether control criterion with two elements of power and benefit which is introduced as 'control criterion of consolidation scope' in national and international standards of accounting in public sector (and also private sector) is efficient enough or not. The methodology of this study is comparative and the results of this research are significantly generalizable, due to the given importance to the sample of countries which were studied. Findings of this study states that in spite of pervasive use of control criterion (including 2 elements of power and benefit), criteria for determining the existence of control in public sector accounting standards, are not efficient enough to determine the consolidation scope of whole of government financial statements in a way that meet decision making and accountability needs of managers, policy makers and supervisors; specially parliament. Therefore, the researcher believes that for determining consolidation scope in public sector, in addition to economic view, it is better to pay attention to budgetary, legal and statistical concepts and also to practical and financial risk and define indicators for proving the existence of control (power and benefit) which include accountability relationships (budgetary relation, legal form and nature of activity). these findings also reveals the necessity of passing a comprehensive public financial management (PFM) legislation in order to redefine the characteristics of public sector entities and whole of government financial statements scope and review Statistics organizations and central banks duties for preparing government financial statistics and national accounts in order to achieve sustainable development and resilient economy goals.Keywords: control, consolidation scope, public sector accounting, government financial statistics, resilient economy
Procedia PDF Downloads 2501079 The Effectiveness of Water Indices in Detecting Soil Moisture as an Indicator of Mudflow in Arid Regions
Authors: Zahraa Al Ali, Ammar Abulibdeh, Talal Al-Awadhi, Midhun Mohan, Mohammed Al-Barwani, Mohammed Al-Barwani, Sara Al Nabbi, Meshal Abdullah
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This study aims to evaluate the performance and effectiveness of six spectral water indices - derived from Multispectral sentinel-2 data - to detect soil moisture and inundated area in arid regions to be used as an indicator of mudflow phenomena to predict high-risk areas. Herein, the validation of the performance of spectral indices was conducted using threshold method, spectral curve performance, and soil-line method. These indirect validation techniques play a key role in saving time, effort, and cost, particularly for large-scale and inaccessible areas. It was observed that the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (mNDWI), and RSWIR indices have the potential to detect soil moisture and inundated areas in arid regions. According to the temporal spectral curve performance, the spectral characteristics of water and soil moisture were distinct in the Near infrared (NIR), Short-wave Infrared (SWIR1,2) bands. However, the rate and degree differed between these bands, depending on the amount of water in the soil. Furthermore, the soil line method supported the appropriate selection of threshold values to detect soil moisture. However, the threshold values varied with location, time, season, and between indices. We concluded that considering the factors influencing the behavior of water and soil reflectivity could support decision-makers in identifying high-risk mudflow locations.Keywords: spectral reflectance curve, soil-line method, spectral indices, Shaheen cyclone
Procedia PDF Downloads 651078 A Methodology to Integrate Data in the Company Based on the Semantic Standard in the Context of Industry 4.0
Authors: Chang Qin, Daham Mustafa, Abderrahmane Khiat, Pierre Bienert, Paulo Zanini
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Nowadays, companies are facing lots of challenges in the process of digital transformation, which can be a complex and costly undertaking. Digital transformation involves the collection and analysis of large amounts of data, which can create challenges around data management and governance. Furthermore, it is also challenged to integrate data from multiple systems and technologies. Although with these pains, companies are still pursuing digitalization because by embracing advanced technologies, companies can improve efficiency, quality, decision-making, and customer experience while also creating different business models and revenue streams. In this paper, the issue that data is stored in data silos with different schema and structures is focused. The conventional approaches to addressing this issue involve utilizing data warehousing, data integration tools, data standardization, and business intelligence tools. However, these approaches primarily focus on the grammar and structure of the data and neglect the importance of semantic modeling and semantic standardization, which are essential for achieving data interoperability. In this session, the challenge of data silos in Industry 4.0 is addressed by developing a semantic modeling approach compliant with Asset Administration Shell (AAS) models as an efficient standard for communication in Industry 4.0. The paper highlights how our approach can facilitate the data mapping process and semantic lifting according to existing industry standards such as ECLASS and other industrial dictionaries. It also incorporates the Asset Administration Shell technology to model and map the company’s data and utilize a knowledge graph for data storage and exploration.Keywords: data interoperability in industry 4.0, digital integration, industrial dictionary, semantic modeling
Procedia PDF Downloads 831077 An Ensemble System of Classifiers for Computer-Aided Volcano Monitoring
Authors: Flavio Cannavo
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Continuous evaluation of the status of potentially hazardous volcanos plays a key role for civil protection purposes. The importance of monitoring volcanic activity, especially for energetic paroxysms that usually come with tephra emissions, is crucial not only for exposures to the local population but also for airline traffic. Presently, real-time surveillance of most volcanoes worldwide is essentially delegated to one or more human experts in volcanology, who interpret data coming from different kind of monitoring networks. Unfavorably, the high nonlinearity of the complex and coupled volcanic dynamics leads to a large variety of different volcanic behaviors. Moreover, continuously measured parameters (e.g. seismic, deformation, infrasonic and geochemical signals) are often not able to fully explain the ongoing phenomenon, thus making the fast volcano state assessment a very puzzling task for the personnel on duty at the control rooms. With the aim of aiding the personnel on duty in volcano surveillance, here we introduce a system based on an ensemble of data-driven classifiers to infer automatically the ongoing volcano status from all the available different kind of measurements. The system consists of a heterogeneous set of independent classifiers, each one built with its own data and algorithm. Each classifier gives an output about the volcanic status. The ensemble technique allows weighting the single classifier output to combine all the classifications into a single status that maximizes the performance. We tested the model on the Mt. Etna (Italy) case study by considering a long record of multivariate data from 2011 to 2015 and cross-validated it. Results indicate that the proposed model is effective and of great power for decision-making purposes.Keywords: Bayesian networks, expert system, mount Etna, volcano monitoring
Procedia PDF Downloads 2341076 MRCP as a Pre-Operative Tool for Predicting Variant Biliary Anatomy in Living Related Liver Donors
Authors: Awais Ahmed, Atif Rana, Haseeb Zia, Maham Jahangir, Rashed Nazir, Faisal Dar
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Purpose: Biliary complications represent the most common cause of morbidity in living related liver donor transplantation and detailed preoperative evaluation of biliary anatomic variants is crucial for safe patient selection and improved surgical outcomes. Purpose of this study is to determine the accuracy of preoperative MRCP in predicting biliary variations when compared to intraoperative cholangiography in living related liver donors. Materials and Methods: From 44 potential donors, 40 consecutive living related liver donors (13 females and 28 males) underwent donor hepatectomy at our centre from April 2012 to August 2013. MRCP and IOC of all patients were retrospectively reviewed separately by two radiologists and a transplant surgeon.MRCP was performed on 1.5 Tesla MR magnets using breath-hold heavily T2 weighted radial slab technique. One patient was excluded due to suboptimal MRCP. The accuracy of MRCP for variant biliary anatomy was calculated. Results: MRCP accurately predicted the biliary anatomy in 38 of 39 cases (97 %). Standard biliary anatomy was predicted by MRCP in 25 (64 %) donors (100% sensitivity). Variant biliary anatomy was noted in 14 (36 %) IOCs of which MRCP predicted precise anatomy of 13 variants (93 % sensitivity). The two most common variations were drainage of the RPSD into the LHD (50%) and the triple confluence of the RASD, RPSD and LHD (21%). Conclusion: MRCP is a sensitive imaging tool for precise pre-operative mapping of biliary variations which is critical to surgical decision making in living related liver transplantation.Keywords: intraoperative cholangiogram, liver transplantation, living related donors, magnetic resonance cholangio-pancreaticogram (MRCP)
Procedia PDF Downloads 3851075 Work System Design in Productivity for Small and Medium Enterprises: A Systematic Literature Review
Authors: Silipa Halofaki, Devi R. Seenivasagam, Prashant Bijay, Kritin Singh, Rajeshkannan Ananthanarayanan
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This comprehensive literature review delves into the effects and applications of work system design on the performance of Small and Medium-sized Enterprises (SMEs). The review process involved three independent reviewers who screened 514 articles through a four-step procedure: removing duplicates, assessing keyword relevance, evaluating abstract content, and thoroughly reviewing full-text articles. Various criteria, such as relevance to the research topic, publication type, study type, language, publication date, and methodological quality, were employed to exclude certain publications. A portion of articles that met the predefined inclusion criteria were included as a result of this systematic literature review. These selected publications underwent data extraction and analysis to compile insights regarding the influence of work system design on SME performance. Additionally, the quality of the included studies was assessed, and the level of confidence in the body of evidence was established. The findings of this review shed light on how work system design impacts SME performance, emphasizing important implications and applications. Furthermore, the review offers suggestions for further research in this critical area and summarizes the current state of knowledge in the field. Understanding the intricate connections between work system design and SME success can enhance operational efficiency, employee engagement, and overall competitiveness for SMEs. This comprehensive examination of the literature contributes significantly to both academic research and practical decision-making for SMEs.Keywords: literature review, productivity, small and medium sized enterprises-SMEs, work system design
Procedia PDF Downloads 831074 Development of Electronic Services in Georgia: Analysis of Current Situation
Authors: Dato Surmanidze, Dato Antadze, Tornike Partenadze
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Public online services in Georgia are concentrated on main target segments: public administration, business, population, non-governmental and other interested organizations. Therefore, the strategy of digital Georgia is focused on providing G2C, G2B/B2G, G2NGO and G2G services. In G2C framework sophisticated and high-technological online services have been developed in order to provide passports, identity cards, documentations concerning residence and civil acts (birth, marriage, divorce, child adoption, change of name and surname, death, etc) as well as other services. Websites like my.gov.ge and sda.gov.ge have distance services like electronic application, processing and decision making. In line with international standards automatic services like electronic tenders, product catalogues, invoices and payment have been developed. This creates better investment climate for foreign companies in Georgia in the framework of G2B politics. The website mybusiness.gov.ge creates better conditions for local business. Among electronic services is e-NRMS (electronic system for national resource management) which was introduced by the Ministry of Finance of Georgia. The system was created in order to ensure management of national resources by state and business organizations. It is integrated with bank services and provides G2C, G2B and B2G representatives with electronic services. Also a portal meteo.gov.ge was created which gives electronic services concerning air, geological, environmental and pollution issues. Also worknet.gov.ge should be mentioned which is an electronic hub of information management for employers and employees. The information portal of labor market will facilitate receipt of information, its analysis and delivery to interested people like employers and employees. However, nowadays it’s been two years that only employees portal is activated. Therefore, awareness about the portal, its competitiveness and success is undermined.Keywords: electronic services, public administration, information technology, information society
Procedia PDF Downloads 2601073 A Sustainable Design Model by Integrated Evaluation of Closed-loop Design and Supply Chain Using a Mathematical Model
Authors: Yuan-Jye Tseng, Yi-Shiuan Chen
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The paper presented a sustainable design model for integrated evaluation of the design and supply chain of a product for the sustainable objectives. To design a product, there can be alternative ways to assign the detailed specifications to fulfill the same design objectives. In the design alternative cases, different material and manufacturing processes with various supply chain activities may be required for the production. Therefore, it is required to evaluate the different design cases based on the sustainable objectives. In this research, a closed-loop design model is developed by integrating the forward design model and reverse design model. From the supply chain point of view, the decisions in the forward design model are connected with the forward supply chain. The decisions in the reverse design model are connected with the reverse supply chain considering the sustainable objectives. The purpose of this research is to develop a mathematical model for analyzing the design cases by integrated evaluating the criteria in the closed-loop design and the closed-loop supply chain. The decision variables are built to represent the design cases of the forward design and reverse design. The cost parameters in a forward design include the costs of material and manufacturing processes. The cost parameters in a reverse design include the costs of recycling, disassembly, reusing, remanufacturing, and disposing. The mathematical model is formulated to minimize the total cost under the design constraints. In practical applications, the decisions of the mathematical model can be used for selecting a design case for the purpose of sustainable design of a product. An example product is demonstrated in the paper. The test result shows that the sustainable design model is useful for integrated evaluation of the design and the supply chain to achieve the sustainable objectives.Keywords: closed-loop design, closed-loop supply chain, design evaluation, supply chain management, sustainable design model
Procedia PDF Downloads 4141072 Applications of Evolutionary Optimization Methods in Reinforcement Learning
Authors: Rahul Paul, Kedar Nath Das
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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods
Procedia PDF Downloads 711071 Molecular Characterization of Chicken B Cell Marker (ChB6) in Native Chicken of Poonch Region from International Borders of India and Pakistan
Authors: Mandeep Singh Azad.Dibyendu Chakraborty, Vikas Vohra
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Introduction: Poonch is one of the remotest districts of the Jammu and Kashmir (UT) and situated on international borders. This native poultry population in these areas is quite hardy and thrives well in adverse climatic conditions. Till date, no local breed from this area (Jammu Province) has been characterized thus present study was undertaken with the main objectives of molecular characterization of ChB6 gene in local native chicken of Poonch region located at international borders between India and Pakistan. The chicken B-cell marker (ChB6) gene has been proposed as a candidate gene in regulating B-cell development. Material and Method: RNA was isolated by Blood RNA Purification Kit (HiPura) and Trizol method from whole blood samples. Positive PCR products with size 1110 bp were selected for further purification, sequencing and analysis. The amplified PCR product was sequenced by Sangers dideoxy chain termination method. The obtained sequence of ChB6 gene of Poonchi chicken were compared by MEGAX software. BioEdit software was used to construct phylogenic tree, and Neighbor Joining method was used to infer evolutionary history. In order to compute evolutionary distance Maximum Composite Likelihood method was used. Results: The positively amplified samples of ChB6 genes were then subjected to Sanger sequencing with “Primer Walking. The sequences were then analyzed using MEGA X and BioEdit software. The sequence results were compared with other reported sequence from different breed of chicken and with other species obtained from the NCBI (National Center for Biotechnology Information). ClustalW method using MEGA X software was used for multiple sequence alignment. The sequence results of ChB6 gene of Poonchi chicken was compared with Centrocercus urophasianus, G. gallus mRNA for B6.1 protein, G. gallus mRNA for B6.2, G. gallus mRNA for B6.3, Gallus gallus B6.1, Halichoeres bivittatus, Miniopterus fuliginosus Ferringtonia patagonica, Tympanuchus phasianellus. The genetic distances were 0.2720, 0.0000, 0.0245, 0.0212, 0.0147, 1.6461, 2.2394, 2.0070 and 0.2363 for ChB6 gene of Poonchi chicken sequence with other sequences in the present study respectively. Sequencing results showed variations between different species. It was observed that AT content were higher then GC content for ChB6 gene. The lower AT content suggests less thermostable. It was observed that there was no sequence difference within the Poonchi population for ChB6 gene. The high homology within chicken population indicates the conservation of ChB6 gene. The maximum difference was observed with Miniopterus fuliginosus (Eastern bent-wing bat) followed by Ferringtonia patagonica and Halichoeres bivittatus. Conclusion: Genetic variation is the essential component for genetic improvement. The results of immune related gene Chb6 shows between population genetic variability. Therefore, further association studies of this gene with some prevalent diseases in large population would be helpful to identify disease resistant/ susceptible genotypes in the indigenous chicken population.Keywords: ChB6, sequencing, ClustalW, genetic distance, poonchi chicken, SNP
Procedia PDF Downloads 571070 Deep Learning for SAR Images Restoration
Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli
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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network
Procedia PDF Downloads 631069 Acceptance of Health Information Application in Smart National Identity Card (SNIC) Using a New I-P Framework
Authors: Ismail Bile Hassan, Masrah Azrifah Azmi Murad
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This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens’ behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens’ new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework.Keywords: unified theory of acceptance and use of technology (UTAUT) model, UTAUT2 model, smart national identity card (SNIC), health information application, privacy calculus model (PCM)
Procedia PDF Downloads 4561068 ESG and Corporate Financial Performance: Empirical Evidence from Vietnam’s Listed Construction Companies
Authors: My Linh Hoang, Van Dung Hoang
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Environmental, Social, and Governance (ESG) factors have become a focus for companies globally, as businesses are now focusing on long-term sustainable goals rather than only operating for the goals of profit maximization. According to recent research, in several countries, companies have shown positive results in their financial performance by improving their ESG performance. The construction industry is one of the most crucial components of social and economic development; as a result, considerations for ESG factors are becoming more and more essential for companies in this sector. In Vietnam, the construction industry has been growing rapidly in recent years; however, it has yet to be discussed and studied extensively in Vietnam how ESG factors create impacts on corporate financial performance in general and construction corporations’ financial performance in particular. This research aims to examine the relationship between ESG factors and financial indicators in construction companies from 2011 to 2021 through panel data analysis of 75 listed construction companies in Vietnam and to provide insights into how these companies can better integrate ESG considerations into their operations to enhance their financial performance. The data was analyzed through 3 main methods: descriptive statistics, correlation coefficient analysis applied to all dependent, explanatory and control variables, and panel data analysis method. In panel data analysis, the study uses the fixed effects model (FEM) and random effects model (REM). The Hausman test will be used to select which model is suitable to be used. The findings indicate that maintaining a strong commitment to ESG principles can have a positive impact on financial performance. Finally, FGLS estimation will be performed when the problem of autocorrelation and variable variance appears in the model. This is significant for all parties involved, including investors, company managers, decision-makers, and industry regulators.Keywords: ESG, financial performance, construction company, Vietnam
Procedia PDF Downloads 741067 Value Proposition and Value Creation in Network Environments: An Experimental Study of Academic Productivity via the Application of Bibliometrics
Authors: R. Oleko, A. Saraceni
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The aim of this research is to provide a rigorous evaluation of the existing academic productivity in relation to value proposition and creation in networked environments. Bibliometrics is a vigorous approach used to structure existing literature in an objective and reliable manner. To that aim, a thorough bibliometric analysis was performed in order to assess the large volume of the information encountered in a structured and reliable manner. A clear distinction between networks and service networks was considered indispensable in order to capture the effects of each network’s type properties on value creation processes. Via the use of bibliometric parameters, this review was able to capture the state-of-the-art in both value proposition and value creation consecutively. The results provide a rigorous assessment of the annual scientific production, the most influential journals, and the leading corresponding author countries. By means of citation analysis, the most frequently cited manuscripts and countries for each network type were identified. Moreover, by means of co-citation analysis, existing collaborative patterns were detected through the creation of reference co-citation networks and country collaboration networks. Co-word analysis was also performed in order to provide an overview of the conceptual structure in both networks and service networks. The acquired results provide a rigorous and systematic assessment of the existing scientific output in networked settings. As such, they positively contribute to a better understanding of the distinct impact of service networks on value proposition and value creation when compared to regular networks. The implications derived can serve as a guide for informed decision-making by practitioners during network formation and provide a structured evaluation that can stand as a basis for future research in the field.Keywords: bibliometrics, co-citation analysis, networks, service networks, value creation, value proposition
Procedia PDF Downloads 1951066 Internet of Health Things as a Win-Win Solution for Mitigating the Paradigm Shift inside Senior Patient-Physician Shared Health Management
Authors: Marilena Ianculescu, Adriana Alexandru
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Internet of Health Things (IoHT) has already proved to be a persuasive means to support a proper assessment of the living conditions by collecting a huge variety of data. For a customized health management of a senior patient, IoHT provides the capacity to build a dynamic solution for sustaining the shift inside the patient-physician relationship by allowing a real-time and continuous remote monitoring of the health status, well-being, safety and activities of the senior, especially in a non-clinical environment. Thus, is created a win-win solution in which both the patient and the physician enhance their involvement and shared decision-making, with significant outcomes. Health monitoring systems in smart environments are becoming a viable alternative to traditional healthcare solutions. The ongoing “Non-invasive monitoring and health assessment of the elderly in a smart environment (RO-SmartAgeing)” project aims to demonstrate that the existence of complete and accurate information is critical for assessing the health condition of the seniors, improving wellbeing and quality of life in relation to health. The researches performed inside the project aim to highlight how the management of IoHT devices connected to the RO-SmartAgeing platform in a secure way by using a role-based access control system, can allow the physicians to provide health services at a high level of efficiency and accessibility, which were previously only available in hospitals. The project aims to identify deficient aspects in the provision of health services tailored to a senior patient’s specificity and to offer a more comprehensive perspective of proactive and preventive medical acts.Keywords: health management, internet of health things, remote monitoring, senior patient
Procedia PDF Downloads 931065 An Experimental Approach to the Influence of Tipping Points and Scientific Uncertainties in the Success of International Fisheries Management
Authors: Jules Selles
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The Atlantic and Mediterranean bluefin tuna fishery have been considered as the archetype of an overfished and mismanaged fishery. This crisis has demonstrated the role of public awareness and the importance of the interactions between science and management about scientific uncertainties. This work aims at investigating the policy making process associated with a regional fisheries management organization. We propose a contextualized computer-based experimental approach, in order to explore the effects of key factors on the cooperation process in a complex straddling stock management setting. Namely, we analyze the effects of the introduction of a socio-economic tipping point and the uncertainty surrounding the estimation of the resource level. Our approach is based on a Gordon-Schaefer bio-economic model which explicitly represents the decision making process. Each participant plays the role of a stakeholder of ICCAT and represents a coalition of fishing nations involved in the fishery and decide unilaterally a harvest policy for the coming year. The context of the experiment induces the incentives for exploitation and collaboration to achieve common sustainable harvest plans at the Atlantic bluefin tuna stock scale. Our rigorous framework allows testing how stakeholders who plan the exploitation of a fish stock (a common pool resource) respond to two kinds of effects: i) the inclusion of a drastic shift in the management constraints (beyond a socio-economic tipping point) and ii) an increasing uncertainty in the scientific estimation of the resource level.Keywords: economic experiment, fisheries management, game theory, policy making, Atlantic Bluefin tuna
Procedia PDF Downloads 2461064 Unfolding the Affective Atmospheres during the COVID-19 Pandemic Crisis: The Constitution and Performance of Affective Governance in Taiwan
Authors: Sang-Ju Yu
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This paper examines the changing essences and effects of ‘affective atmosphere’ during the COVID-19 pandemic crisis, which have been facilitated and shaped the ‘affective governance’ in Taiwan. Due to long-term uncertainty and unpredictability, the COVID-19 pandemic not only caused unprecedented global crisis but triggered the public’s negative emotional responses. This paper unravels how the shortage of Personal Protective Equipment and the proliferating fake news heightened people’s fear and anxiety and how specific affective atmospheres can be provoked and manipulated to harness emotional appeals of citizens strategically in Taiwan. Through the in-depth interviews with diverse stakeholders involved, it unfolds the dynamics and strategies of affective governance, wherein public emotions and concerns are now given significant consideration in both policy measures and the affective expression of leadership, spatial arrangement, service delivery, and the interaction with citizens. Addressing psychosocial and emotional needs has become the core of crisis response mechanisms suited to dynamic affective atmospheres and pandemic situation. This paper also demonstrates that epidemic prevention and control is not merely the production of neutral or rational policy-making processes, as it is dominated by multiple emotions resulted from unexpected and salient events at different moments. It provides explicit insight into how different prevention scenarios operated effectively through political and affective mobilisation to strengthen emotional bonding and collective identity which energises collective action. Basically, successful affective governance calls for both negative and positive emotions, for both scientific and political decision-making, for both community and bureaucracy, and both quality and efficiency of private–public collaboration.Keywords: affective atmospheres, affective governance, COVID-19 pandemic, private-public collaboration
Procedia PDF Downloads 851063 Satellite-Based Drought Monitoring in Korea: Methodologies and Merits
Authors: Joo-Heon Lee, Seo-Yeon Park, Chanyang Sur, Ho-Won Jang
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Satellite-based remote sensing technique has been widely used in the area of drought and environmental monitoring to overcome the weakness of in-situ based monitoring. There are many advantages of remote sensing for drought watch in terms of data accessibility, monitoring resolution and types of available hydro-meteorological data including environmental areas. This study was focused on the applicability of drought monitoring based on satellite imageries by applying to the historical drought events, which had a huge impact on meteorological, agricultural, and hydrological drought. Satellite-based drought indices, the Standardized Precipitation Index (SPI) using Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM); Vegetation Health Index (VHI) using MODIS based Land Surface Temperature (LST), and Normalized Difference Vegetation Index (NDVI); and Scaled Drought Condition Index (SDCI) were evaluated to assess its capability to analyze the complex topography of the Korean peninsula. While the VHI was accurate when capturing moderate drought conditions in agricultural drought-damaged areas, the SDCI was relatively well monitored in hydrological drought-damaged areas. In addition, this study found correlations among various drought indices and applicability using Receiver Operating Characteristic (ROC) method, which will expand our understanding of the relationships between hydro-meteorological variables and drought events at global scale. The results of this research are expected to assist decision makers in taking timely and appropriate action in order to save millions of lives in drought-damaged areas.Keywords: drought monitoring, moderate resolution imaging spectroradiometer (MODIS), remote sensing, receiver operating characteristic (ROC)
Procedia PDF Downloads 3181062 Virtue, Truth, Freedom, And The History Of Philosophy
Authors: Ashley DelCorno
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GEM Anscombe’s 1958 essay Modern Moral Philosophy and the tradition of virtue ethics that followed has given rise to the restoration (or, more plainly, the resurrection) of Aristotle as something of an authority figure. Alisdair MacIntyre and Martha Nussbaum are proponents, for example, not just of Aristotle’s relevancy but also of his apparent implicit authority. That said, it’s not clear that the schema imagined by virtue ethicists accurately describes moral life or that it does not inadvertently work to impoverish genuine decision-making. If the label ‘virtue’ is categorically denied to some groups (while arbitrarily afforded to others), it can only turn on itself, thus rendering ridiculous its own premise. Likewise, as an inescapable feature of virtue ethics, Aristotelean binaries like ‘virtue/vice’ and ‘voluntary/involuntary’ offer up false dichotomies that may seriously compromise an agent’s ability to conceptualize choices that are truly free and rooted in meaningful criteria. Here, this topic is analyzed through a feminist lens predicated on the known paradoxes of patriarchy. The work of feminist theorists Jacqui Alexander, Katharine Angel, Simone de Beauvoir, bell hooks, Audre Lorde, Imani Perry, and Amia Srinivasan serves as important guideposts, and the argument here is built from a key tenet of black feminist thought regarding scarcity and possibility. Above all, it’s clear that though the philosophical tradition of virtue ethics presents itself as recovering the place of agency in ethics, its premises possess crippling limitations toward the achievement of this goal. These include, most notably, virtue ethics’ binding analysis of history, as well as its axiomatic attachment to obligatory clauses, problematic reading-in of Aristotle and arbitrary commitment to predetermined and competitively patriarchal ideas of what counts as a virtue.Keywords: feminist history, the limits of utopic imagination, curatorial creation, truth, virtue, freedom
Procedia PDF Downloads 781061 Social Media Advertising and Acceptability of Fast Moving Consumer Goods in Nigeria’s Manufacturing Industry
Authors: John Akinwumi Makinde
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Nigerian manufacturing industry, particularly the fast moving consumer producing firms play vital roles in Nigerian economy. This sector’s product acceptability is given very little attention along with social media advertising that communicate product information to audience across the globe need to be documented. Procter and Gamble Plc operate in Nigeria with appreciable number of fast moving consumer goods that service Nigerian economy. Social media advertising disposition of the company and product acceptability of the company deserve some elucidations. This study therefore examined the impact of social media advertising on product acceptability of FMCG in Nigerian manufacturing industry, using Procter and Gamble Plc as case study. The study employed the case study type of descriptive survey research design. The population consisted of 235 customers of G&P Plc, which were selected through random sampling method. A total of 235 copies of questionnaires titled 'Social Media Advertising and Product Acceptability (SMA-PA) Questionnaire' was administered and retrieved. Data generated were analysed using frequency distribution and regression analysis at 0.05 level. It was found that social media advertising positively and significantly motivated customers to buy product of P&G Plc (r =.147**, N= 235, p(.000) < .01). Findings also showed that social media advertising has significant impact on product acceptability of FCMG in P&G Plc (F(2,61)=22.250; R2=.629; P(.000) < .05). The study concluded that social media advertising is a determinant factor of consumer decision to accept fast moving consumer goods in Nigerian manufacturing industry. It is recommended that with the growing market of FMCG, there is need to educate the market with the product unique features, standard and quality on social media. Finally, Fast Moving Consumer Goods firms should deploy excellent marketing mix on social media.Keywords: advertising, fast moving consumer goods, manufacturing industry, product acceptability, social media
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