Search results for: data infrastructure

Authors: Asal Pournaghshband, Mohammed A. Zaki

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This paper presents a detailed numerical investigation into the structural performance of splay anchor configurations for strengthening concrete beams with Carbon Fiber Reinforced Polymer (CFRP) sheets. CFRP is widely used in retrofitting concrete structures to improve flexural strength and extend service life. However, premature debonding limits the tensile capacity of CFRP sheets, reducing the effectiveness of these applications. This study addresses this limitation by exploring the potential of splay anchors as an emerging anchorage technique that mitigates debonding issues through improved load transfer mechanisms. Building on existing experimental studies, the research uses ABAQUS software to validate different splay anchor configurations and simulate real-world performance. The parametric study examines key anchor parameters, including diameter, spacing, and embedment depth, to evaluate their effects on bond strength, load distribution, and the flexural capacity of strengthened beams. Systematic analysis of these parameters allows for identifying configurations that enhance debonding resistance and increase the load-carrying capacity of CFRP-strengthened beams. Improved debonding resistance contributes to greater structural durability, reduced maintenance costs, and extended service life for retrofitted structures, particularly relevant for aging infrastructure like bridges and buildings. This approach not only advances sustainable retrofitting practices but also provides practical solutions tailored to infrastructure demands.

Keywords: CFRP strengthening, splay anchors, concrete beams, structural retrofitting, numerical analysis

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Authors: Eglė Bilevičiūtė, Vidmantas Egidijus Kurapka, Snieguolė Matulienė, Sigutė Stankevičiūtė

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The Council of European Union (EU Council) has stressed on several occasions the need for a concerted, comprehensive and effective solution to delinquency problems in EU communities. In the context of establishing a European Forensic Science Area and the development of forensic science infrastructure in Europe, EU Council believes that forensic science can significantly contribute to the efficiency of law enforcement, crime prevention and combating crimes. Lithuanian scientists have consolidated to implement a project named “Conception of the vision for European Forensic Science 2020 implementation in Lithuania” (the project is funded for the period of 1 March 2014 - 31 December 2016) with the objective to create a conception of implementation of the vision for European Forensic Science 2020 in Lithuania by 1) evaluating the current status of Lithuania’s forensic system and opportunities for its improvement; 2) analysing achievements and knowledge in investigation of crimes listed in conclusions of EU Council on the vision for European Forensic Science 2020 including creation of a European Forensic Science Area and the development of forensic science infrastructure in Europe: trafficking in human beings, organised crime and terrorism; 3) analysing conceptions of criminalistics, which differ in different EU member states due to the variety of forensic schools, and finding means for their harmonization. Apart from the conception of implementation of the vision for European Forensic Science 2020 in Lithuania, the project is expected to suggest provisions that will be relevant to other EU countries as well. Consequently, the presented conception of implementation of vision for European Forensic Science 2020 in Lithuania could initiate a project for a common vision of European Forensic Science and contribute to the development of the EU as an area of freedom, security and justice. The article presents main ideas of the project of the conception of the vision for European Forensic Science 2020 of EU Council and analyses its legal background, as well as prospects of and challenges for its implementation in Lithuania and the EU.

Keywords: EUROVIFOR, standardization, vision for European Forensic Science 2020, Lithuania

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

Procedia PDF Downloads 166

Authors: Bhaargav Gupta P., Vignesh N., Nithish Kumar R., Rahul J., Nivetha Ruvah D.

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Delivering essential medical supplies to rural and underserved areas is challenging due to infrastructure limitations and logistical barriers, often resulting in inefficiencies and delays. Traditional delivery methods are hindered by poor road networks, long distances, and difficult terrains, compromising timely access to vital resources, especially in emergencies. This paper introduces an autonomous drone system engineered to optimize last-mile delivery. By utilizing advanced navigation and object-detection algorithms, such as region-based convolutional neural networks (R-CNN), our drones efficiently avoid obstacles, identify safe landing zones, and adapt dynamically to varying environments. Equipped with high-precision GPS and autonomous capabilities, the drones effectively navigate complex, remote areas with minimal dependence on established infrastructure. The system includes a dedicated mobile application for secure order placement and real-time tracking, and a secure payload box with OTP verification ensures tamper-resistant delivery to authorized recipients. This project demonstrates the potential of automated drone technology in healthcare logistics, offering a scalable and eco-friendly approach to enhance accessibility and service delivery in underserved regions. By addressing logistical gaps through advanced automation, this system represents a significant advancement toward sustainable, accessible healthcare in remote areas.

Keywords: region-based convolutional neural network, one time password, global positioning system, autonomous drones, healthcare logistics

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Authors: Melaku Tsehay

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The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

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Authors: Tsegay Kahsay Gebrekidan, Gebremariam Gebrezgabher Gebremedhin, Abraha Kahsay Weldemariam, Meaza Kidane Teferi

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Municipal solid waste management (MSWM) in Ethiopia is a complex issue with institutional, social, political, environmental, and economic dimensions, impacting sustainable development. Effective MSWM planning necessitates understanding the generation rate and composition of waste. This systematic review synthesizes qualitative and quantitative data from various sources to aggregate current knowledge, identify gaps, and provide a comprehensive understanding of municipal solid waste management in Ethiopia. The findings reveal that the generation rate of municipal solid waste in Ethiopia is 0.38 kg/ca/day, with the waste composition being predominantly food waste, followed by ash, dust, and sand, and yard waste. Over 85% of this MSW is either reusable or recyclable, with a significant portion being organic matter (73.13% biodegradable) and 11.78% recyclable materials. Physicochemical analyses reveal that Ethiopian MSW is suitable for composting and biogas production, offering opportunities to reduce environmental pollution, and GHGs, support urban agriculture, and create job opportunities. However; challenges persist, including a lack of political will, weak municipal planning, limited community awareness, and inadequate waste management infrastructure, and only 31.8% of MSW is collected legally, leading to inefficient and harmful disposal practices. To improve MSWM, Ethiopia should focus on public awareness; increased funding, infrastructure investment, private sector partnerships, and implementing the 4 R principles (reduce, reuse, and recycle). An integrated approach involving government, industry, and civil society is essential. Further research on the physicochemical properties and strategic uses of MSW is needed to enhance management practices. Implications: The comprehensive study of municipal solid waste management (MSWM) in Ethiopia reveals the intricate interplay of institutional, social, political, environmental, and economic factors that influence the nation’s sustainable development. The findings underscore the urgent need for tailored, integrated waste management strategies that are informed by a thorough understanding of MSW generation rates, composition, and current management practices. Ethiopia’s lower per capita MSW generation compared to developed countries and the predominantly organic composition of its waste present significant opportunities for sustainable waste management practices such as composting and recycling. These practices can not only minimize the environmental impact but also support urban greening, agriculture, and renewable energy production. The high organic content, suitable physicochemical properties of MSW for composting, and potential for biogas and briquette production highlight pathways for creating employment, reducing waste, and enhancing soil fertility. Despite these opportunities, Ethiopia faces substantial challenges due to inadequate political will, weak municipal planning, limited community awareness, insufficient waste management infrastructure, and poor policy implementation. The high rate of illegal waste disposal further exacerbates environmental and health issues, emphasizing the need for a more effective and integrated MSWM approach. To address these challenges and harness the potential of MSW, Ethiopia must prioritize increasing public awareness; investing in infrastructure, fostering private sector partnerships, and implementing the principles of reduce, reuse, and recycle (3 R). Developing strategies that involve all stakeholders and turning waste into valuable resources is crucial. Government, industry, and civil society must collaborate to implement integrated MSWM systems that focus on waste reduction at the source, alternative material use, and advanced recycling technologies. Further research at both federal and regional levels is essential to optimize the physicochemical analysis and strategic use of MSW. Prompt action is required to transform waste management into a pillar of sustainable urban development, ultimately improving environmental quality and human health in Ethiopia.

Keywords: biodegradable, healthy environment, integrated solid waste management, municipal

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Authors: Chamaraja Parulli

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Family is an important social institution devoted to the growth of a child, and parents are the important agents of socialization. Mentally challenged children are those who are affected by intellectual disability, which is manifested by limitation in intellectual functioning and adoptive behavior. Intellectual disability affects about 3-4 percentage of the general population. Intellectual disability is caused by genetic condition, problems during pregnancy, problems during childbirth, or illness. Mental retardation is the world’s most complex and challenging issue. The stigmatization of disability results in social and economic marginalization. Parents of the mentally challenged children will have a very high level of parenting stress, which is significantly more than the stress perceived by the parents of the children without disability. The prevalence of severe mental disorder called Schizophrenia is among 1.1 percent of the total population in India. On the other hand, 11 to 12 percent is the overall lifetime occurrence rate of mental disorders. While the government has a separate program for mental health, the segment is marred by lack of adequate doctors and infrastructure. Mentally retarded children have certain limitations in mental functioning and skills, which makes them slow learners in speaking, walking, and taking care of their personal needs such as dressing and eating. Accepting a child with mental handicap becomes difficult for parents and to the whole family, as they have to face many problems, including those of management, finance, deprivation of rest, and leisure. Also, the problems faced by the parents can be seen in different areas like – educational, psychological, social, emotional, financial and family related issues. The study brought out various difficulties and problems faced by the parents as well as family members. The findings revealed that the mental retardation is not only a medico-psychological problem but also a socio-cultural problem. The study results, however, indicate that the quality of life of the family having children with mental retardation can be improved to a greater extent by building up a child-friendly ambience at home. The main aim of the present study is to assess the problems faced by the parents of mentally challenged children, with the help of personal interview data collected from the parents of mentally challenged children, residing in Shimoga District of Karnataka State, India. These individuals were selected using stratified random sampling method. Organizing effective intervention programs for parents, family, society, and educational institutions towards reduction of family stress, augmenting the family’s strengths, increasing child’s competence and enhancing the positive attitudes and values of the society will go a long way for the peaceful existence of the mentally challenged children.

Keywords: mentally challenged children, intellectual disability, special children, social infrastructure, differently abled, psychological stress, marginalization

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Authors: Mehmet Akif Bütüner, İlhan Koşalay

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Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

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Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

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Authors: Zoe Wong

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The purpose of this paper is to develop a framework for internet education. This framework uses the personalized learning approach for everyone who can freely develop their qualifications & careers. The key components of the framework includes students, teachers, assessments and infrastructure. It allows remove the challenges and limitations of the current educational system and allows learners' to cope with progressing learning materials.

Keywords: internet education, personalized approach, information technology, framework

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Authors: A. Falenski, A. Kaesbohrer, M. Filter

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Introduction: Risk assessments can be performed in various ways and in different degrees of complexity. In order to assess risks associated with imported foods additional information needs to be taken into account compared to a risk assessment on regional products. The present review is an overview on currently available best practise approaches and data sources used for food import risk assessments (IRAs). Methods: A literature review has been performed. PubMed was searched for articles about food IRAs published in the years 2004 to 2014 (English and German texts only, search string “(English [la] OR German [la]) (2004:2014 [dp]) import [ti] risk”). Titles and abstracts were screened for import risks in the context of IRAs. The finally selected publications were analysed according to a predefined questionnaire extracting the following information: risk assessment guidelines followed, modelling methods used, data and software applied, existence of an analysis of uncertainty and variability. IRAs cited in these publications were also included in the analysis. Results: The PubMed search resulted in 49 publications, 17 of which contained information about import risks and risk assessments. Within these 19 cross references were identified to be of interest for the present study. These included original articles, reviews and guidelines. At least one of the guidelines of the World Organisation for Animal Health (OIE) and the Codex Alimentarius Commission were referenced in any of the IRAs, either for import of animals or for imports concerning foods, respectively. Interestingly, also a combination of both was used to assess the risk associated with the import of live animals serving as the source of food. Methods ranged from full quantitative IRAs using probabilistic models and dose-response models to qualitative IRA in which decision trees or severity tables were set up using parameter estimations based on expert opinions. Calculations were done using @Risk, R or Excel. Most heterogeneous was the type of data used, ranging from general information on imported goods (food, live animals) to pathogen prevalence in the country of origin. These data were either publicly available in databases or lists (e.g., OIE WAHID and Handystatus II, FAOSTAT, Eurostat, TRACES), accessible on a national level (e.g., herd information) or only open to a small group of people (flight passenger import data at national airport customs office). In the IRAs, an uncertainty analysis has been mentioned in some cases, but calculations have been performed only in a few cases. Conclusion: The current state-of-the-art in the assessment of risks of imported foods is characterized by a great heterogeneity in relation to general methodology and data used. Often information is gathered on a case-by-case basis and reformatted by hand in order to perform the IRA. This analysis therefore illustrates the need for a flexible, modular framework supporting the connection of existing data sources with data analysis and modelling tools. Such an infrastructure could pave the way to IRA workflows applicable ad-hoc, e.g. in case of a crisis situation.

Keywords: import risk assessment, review, tools, food import

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Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

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Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

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Authors: Issam A. Al-Khatib

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In order to achieve a significant reduction of waste amount flowing into landfills, it is important to first understand the composition of the solid municipal waste generated. Hence a detailed analysis of municipal solid waste composition has been conducted in Nablus city. The aim is to provide data on the potential recyclable fractions in the actual waste stream, with a focus on the plastic fraction. Hence, waste-sorting campaigns were conducted on mixed waste containers from five districts in Nablus city. The districts vary in terms of infrastructure and average income. The target is to obtain representative data about the potential quantity and quality of household plastic waste. The study has measured the composition of municipal solid waste collected/ transported by Nablus municipality. The analysis was done by categorizing the samples into eight primary fractions (organic and food waste, paper and cardboard, glass, metals, textiles, plastic, a fine fraction (<10 mm), and others). The study results reveal that the MSW stream in Nablus city has a significant bio- and organic waste fraction (about 68% of the total MSW). The second largest fraction is paper and cardboard (13.6%), followed by plastics (10.1%), textiles (3.2%), glass (1.9%), metals (1.8%), a fine fraction (0.5%), and other waste (0.3%). After this complete and detailed characterization of MSW collected in Nablus and taking into account the content of biodegradable organic matter, the composting could be a solution for the city of Nablus where the surrounding areas of Nablus city have agricultural activities and could be a natural outlet to the compost product. Different waste management options could be practiced in the future in addition to composting, such as energy recovery and recycling, which result in a greater possibility of reducing substantial amounts that are disposed of at landfills.

Keywords: developing countries, composition, management, recyclable, waste.

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Authors: Da-Hye Jang, Woo-Jeong Cho

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Marine leisure tourism contributes greatly to the national economy in which the sea is located nearby and many countries are using marine tourism to create value added. The interest and investment of government and local governments on marine leisure tourism growing as a major trend of marine tourism is steadily increasing. But indiscriminate investment in marine leisure tourism such as duplicated business wastes limited resources. In other words, government and local governments need to select and concentrate on the goal they pursue by drawing priority on maritime leisure tourism policies. The purpose of this study is to analyze development strategies on supplier for marine leisure tourism and thus provide a comprehensive and rational framework for developing marine leisure tourism. In order to achieve the purpose, this study is to analyze priorities for each evaluation criterion of marine leisure tourism development policies using Analytic Hierarchy Process. In this study, a questionnaire was used as the survey tool and was developed based on the previous studies, government report, regional report, related thesis and literature for marine leisure tourism. The questionnaire was constructed by verifying the validity of contents from the expert group related to marine leisure tourism after conducting the first and second preliminary surveys. The AHP survey was conducted to experts (university professors, researchers, field specialists and related public officials) from April 6, 2018 to April 30, 2018 by visiting in person or e-mail. This study distributed 123 questionnaires and 68 valid questionnaires were used for data analysis. As a result, 4 factors with 12 detail strategies were analyzed using Excel. Extracted factors of development strategies of marine leisure tourism are consist of 4 factors such as infrastructure, popularization, law & system improvement and advancement. In conclusion, the results of the pairwise comparison of the four major factor on the first class were infrastructure, popularization, law & system improvement and advancement in order. Second, marine water front space maintenance had higher priority than marina facilities expansion and the establishment of marine leisure education center. Third, marine leisure safety·culture improvement had higher priority than strengthening experience·education program and the upkeep and open promotion event. Fourth, specialization·cluster of marine leisure tourism had higher priority than business support system of marine leisure tourism. Fifth, the revision of water-related leisure activities safety act had higher priority than an enactment of marine tourism promotion act and the foster of marina service industry. Finally, marine water front space maintenance was the most important development plan to boost marine leisure tourism.

Keywords: marine leisure tourism, marine leisure, marine tourism, analytic hierarchy process

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Authors: Ismatilla Mardanov

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There are three types of countries, the first of which is willing to attract foreign direct investment (FDI) in enormous amounts and do whatever it takes to make this happen. Therefore, FDI pours into such countries. In the second cluster of countries, even if the country is suffering tremendously from the shortage of investments, the governments are hesitant to attract investments because they are at the hands of local oligarchs/cartels. Therefore, FDI inflows are moderate to low in such countries. The third type is countries whose companies prefer investing in the most efficient locations globally and are hesitant to invest in the homeland. Sorting countries into such clusters, the present study examines the essential institutions and economic factors that make these countries different. Past literature has discussed various determinants of FDI in all kinds of countries. However, it did not classify countries based on government motivation, institutional setup, and economic factors. A specific approach to each target country is vital for corporate foreign direct investment risk analysis and decisions. The research questions are 1. What specific institutional and economic factors paint the pictures of the three clusters; 2. What specific institutional and economic factors are determinants of FDI; 3. Which of the determinants are endogenous and exogenous variables? 4. How can institutions and economic and political variables impact corporate investment decisions Hypothesis 1: In the first type, country institutions and economic factors will be favorable for FDI. Hypothesis 2: In the second type, even if country economic factors favor FDI, institutions will not. Hypothesis 3: In the third type, even if country institutions favorFDI, economic factors will not favor domestic investments. Therefore, FDI outflows occur in large amounts. Methods: Data come from open sources of the World Bank, the Fraser Institute, the Heritage Foundation, and other reliable sources. The dependent variable is FDI inflows. The independent variables are institutions (economic and political freedom indices) and economic factors (natural, material, and labor resources, government consumption, infrastructure, minimum wage, education, unemployment, tax rates, consumer price index, inflation, and others), the endogeneity or exogeneity of which are tested in the instrumental variable estimation. Political rights and civil liberties are used as instrumental variables. Results indicate that in the first type, both country institutions and economic factors, specifically labor and logistics/infrastructure/energy intensity, are favorable for potential investors. In the second category of countries, the risk of loss of assets is very high due to governmentshijacked by local oligarchs/cartels/special interest groups. In the third category of countries, the local economic factors are unfavorable for domestic investment even if the institutions are well acceptable. Cluster analysis and instrumental variable estimation were used to reveal cause-effect patterns in each of the clusters.

Keywords: foreign direct investment, economy, institutions, instrumental variable estimation

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Authors: Arya S. S.

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India is one of the powerful country in the world .India and Maldives having common interests in regional security and economic growth, this relationship has seen substantial change in recent years. This paper examines the complex dynamics of this bilateral relationship, emphasizing the careful balancing act that both countries perform in order to advance regional prosperity. It looks at historical connections, geopolitical factors, and current issues like economic cooperation, climate change, and marine security. The study highlights how India's involvement in the Maldives contributes to both bilateral ties and regional stability by examining important initiatives including trade agreements and infrastructure projects. It also discusses the effects of outside factors and the necessity for both nations to strategically manage their interests. In order to contribute to a more affluent and stable Indian Ocean area, this study ultimately seeks to shed light on how India and the Maldives may cooperate to promote sustainable development while tackling security issues. The India Maldives relation is very crucial in the regional stability of Indian ocean region. The initiatives like building infrastructure, giving financial support, and establishing the India-Maldives Friendship Bridge demonstrate India's dedication to Maldivian prosperity. In addition to boosting the Maldives' economy, these investments strengthen India's clout in the area, which is essential for preserving its maritime security interests in the face of growing Chinese dominance. Both India and China involved in a strategic tug of war in order to enhance their dominance in Maldives. There are difficulties with this collaboration including, political unrest in the Maldives has occasionally resulted in changes to foreign policy, particularly under regimes that support stronger ties with China. India has expressed concern about losing strategic footholds in the Indian Ocean as a result of China's extension of influence through debt diplomacy and infrastructure projects. India must therefore strike a balance between advancing its objectives and upholding Maldivian sovereignty as well as the goals of its people and government. In summary, the partnership between India and the Maldives is a complex balancing act that is marked by cultural links, security cooperation, and economic dependency. Both countries must negotiate the complexity of international relations as they work for regional prosperity, especially in light of both internal and external factors. India and the Maldives can strengthen their positions as key actors in the changing dynamics of the Indian Ocean by promoting cooperation and communication. This would not only protect their particular interests but also help create a stable and prosperous South Asian region.

Keywords: regional security, balancing act, debt trap diplomacy, strategic tug of war

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Authors: Olayeye Olubunmi Shola

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Amidst increasing global environmental concerns, sustainable urban planning has emerged as a vital strategy in counteracting the negative impacts of urbanization on the environment. However, the emphasis on sustainability often disregards crucial elements of fairness and equal participation within urban settings. This abstract presents a comprehensive overview of the challenges, objectives, significance, and methodologies for addressing social inequalities in the development of eco-cities, with a specific focus on Abuja, Nigeria. Sustainable urban planning, particularly in the context of developing eco-cities, aims to construct cities prioritizing environmental sustainability and resilience. Nonetheless, a significant gap exists in addressing the enduring social disparities within these initiatives. Equitable distribution of resources, access to services, and social inclusivity are essential components that must be integrated into urban planning frameworks for cities that are genuinely sustainable and habitable. Abuja, the capital city of Nigeria, provides a distinctive case for examining the intersection of sustainability and social justice in urban planning. Despite the urban development, Abuja grapples with challenges such as socio-economic disparities, unequal access to essential services, and inadequate housing among its residents. Recognizing and redressing these disparities within the framework of eco-city development is critical for nurturing an inclusive and sustainable urban environment. The primary aim of this study is to scrutinize and pinpoint the social discrepancies within Abuja's initiatives for eco-city development. Specific objectives include: Evaluating the current socio-economic landscape of Abuja to identify disparities in resource, service, and infrastructure access. Comprehending the existing sustainable urban planning initiatives and their influence on social fairness. Suggesting strategies and recommendations to improve fairness and inclusivity within Abuja's plans for eco-city development. This research holds substantial importance for urban planning practices and policy formulation, not only in Abuja but also on a global scale. By highlighting the crucial role of social equity and inclusivity in the development of eco-cities, this study aims to provide insights that can steer more comprehensive, people-centered urban planning practices. Addressing social disparities within sustainability initiatives is crucial for achieving genuinely sustainable and fair urban spaces. The study will employ qualitative and quantitative methodologies. Data collection will involve surveys, interviews, and observations to capture the diverse experiences and perspectives of various social groups within Abuja. Furthermore, quantitative data on infrastructure, service access, and socio-economic indicators will be collated from government reports, academic sources, and non-governmental organizations. Analytical tools such as Geographic Information Systems (GIS) will be utilized to map and visualize spatial disparities in resource allocation and service access. Comparative analyses and case studies of successful interventions in other cities will be conducted to derive applicable strategies for Abuja's context. In conclusion, this study aims to contribute to the discourse on sustainable urban planning by advocating for equity and inclusivity in the development of eco-cities. By centering on Abuja as a case study, it aims to provide practical insights and solutions for the creation of more fair and sustainable urban environments.

Keywords: fairness, sustainability, geographical information system, equity

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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Authors: Marian Emmanuel Okon

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Introduction: The Niger Delta region of Nigeria has a vast reserve of oil and gas, which has globally positioned the nation as the sixth largest exporter of crude oil. Production rapidly rose following oil discovery. In most oil producing nations of the world, the wealth generated from oil production and export has propelled economic advancement, enabling the development of industries and other relevant infrastructures. Therefore, it can be assumed that majority of the oil resource such as Nigeria’s, has the potential to improve the health of the population via job creation and derived revenues. However, the health benefits of this economic development might be offset by the environmental consequences of oil exploitation and production. Objective: This research aims to evaluate the balance between the health benefits of oil-led economic development and harmful environmental consequences of crude oil exploitation in Nigeria. Study Design: A pathway has been designed to guide data search and this study. The model created will assess the relationship between oil-led economic development and population health development via job creation, improvement of education, development of infrastructure and other forms of development as well as through harmful environmental consequences from oil activities. Data/Emerging Findings: Diverse potentially suitable datasets which are at different geographical scales have been identified, obtained or applied for and the dataset from the World Bank has been the most thoroughly explored. This large dataset contains information that would enable the longitudinal assessment of both the health benefits and harms from oil exploitation in Nigeria as well as identify the disparities that exist between the communities, states and regions. However, these data do not extend far back enough in time to capture the start of crude oil production. Thus, it is possible that the maximum economic benefits and health harms could be missed. To deal with this shortcoming, the potential for a comparative study with countries like United Kingdom, Morocco and Cote D’ivoire has also been taken into consideration, so as to evaluate the differences between these countries as well as identify the areas of improvement in Nigeria’s environmental and health policies. Notwithstanding, these data have shown some differences in each country’s economic, environmental and health state over time as well as a corresponding summary statistics. Conclusion: In theory, the beneficial effects of oil exploitation to the health of the population may be substantial as large swaths of the ‘wider determinants’ of population heath are influenced by the wealth of a nation. However, if uncontrolled, the consequences from environmental pollution and degradation may outweigh these benefits. Thus, there is a need to address this, in order to improve environmental and population health in Nigeria.

Keywords: environmental pollution, health benefits, oil-led economic development, petroleum exploitation

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Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

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Authors: Charles Amoatey, Ebenezer Kumah

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Purpose: The purpose of this paper is to assess the effects of implementation of Distributor Management Solution (DMS) on supply chain performance in the Fast Moving Consumer Goods (FMCG) industry in Ghana. Methodology: A purposive sampling approach was used in selecting the respondents for the study. Data was collected from senior management and field supervisors from sales, distribution and customer service units of the case study firm and its channel members. This study made use of systematic literature review and results of survey data analysis to assess how information system has been used to improve supply chain performance. Findings: Results from the study showed that the critical effect factors from implementation of a DMS include (1) Obtain prompt and reliable feedback from the market; (2) Building the capacity and skills levels of employees as well as 3rd Party Agents; (3) Motivated top management to invest in MIS; and (4) Performance improvement in sales route management. The most critical challenges to an effective and sustainable MIS implementation are lack of enough trained IT employees and high barriers to cultural change especially with distributors. The paper recommends consistent investment in IS infrastructure and development of IT skills. Research limitations/implications: This study contributes to the literature by exploring the effects of distribution management solution implementation and supply chain performance in a developing country context. Considering the fact that this study is based on data from only one case study firm and its channel members, generalization of the results should be treated with caution. Practical implications: The findings have confirmed the benefits of implementing a Management Information System. The result should encourage channel members to allocate adequate resources for building MIS capacity to enhance their supply chain performance. Originality/Value: In this paper, the relationship between DMS/MIS implementation and improvement in supply chain performance, in the Ghanaian context, has been established.

Keywords: distributor management solution, fast-moving consumer goods, supply chain management, information systems, Ghana

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Authors: Bei Zhang, Zhaoxin Zhang, Lidong Zhao

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Green infrastructures (GIs) for rainwater management can directly meet the multiple purposes of urban greening and non-point source pollution control. To reveal the overall layout law of GIs dominated by typical woody plants and their impact on urban environmental effects, we constructed a HYDRUS-1D and Stormwater management (SWMM) coupling model to simulate the response of typical root woody plant planting methods on urban hydrological. The results showed that the coupling model had high adaptability to the simulation of urban surface runoff control effect under different woody plant planting methods (NSE ≥0.64 and R² ≥ 0.71). The regulation effect on surface runoff showed that the average runoff reduction rate of GIs increased from 60 % to 71 % with the increase of planting area (5% to 25%) under the design rainfall event of the 2-year recurrence interval. Sophora japonica with tap roots was slightly higher than that of without plants (control) and Malus baccata (M. baccata) with fibrous roots. The comprehensive benefit evaluation system of rainwater utilization technology was constructed by using an analytic hierarchy process. The coupling model was used to evaluate the comprehensive benefits of woody plants with different planting areas in the study area in terms of environment, economy, and society. The comprehensive benefit value of planting 15% M. baccata was the highest, which was the first choice for the planting of woody plants in the study area. This study can provide a scientific basis for the decision-making of green facility layouts of woody plants.

Keywords: green infrastructure, comprehensive benefits, runoff regulation, woody plant layout, coupling model

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Basiru Amuneni

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Astronomy is one domain with a rise in data. Traditional tools for data management have been employed in the quest for knowledge discovery. However, these traditional tools become limited in the face of big. One means of maximizing knowledge discovery for big data is the use of scientific visualisation. The aim of the work is to explore the possibilities offered by emerging creative technologies of Virtual Reality (VR) systems and game engines to visualize multiwavelength datasets. Game Engines are primarily used for developing video games, however their advanced graphics could be exploited for scientific visualization which provides a means to graphically illustrate scientific data to ease human comprehension. Modern astronomy is now in the era of multiwavelength data where a single galaxy for example, is captured by the telescope several times and at different electromagnetic wavelength to have a more comprehensive picture of the physical characteristics of the galaxy. Visualising this in an immersive environment would be more intuitive and natural for an observer. This work presents a standalone VR application that accesses galaxy FITS files. The application was built using the Unity Game Engine for the graphics underpinning and the OpenXR API for the VR infrastructure. The work used a methodology known as Design Science Research (DSR) which entails the act of ‘using design as a research method or technique’. The key stages of the galaxy modelling pipeline are FITS data preparation, Galaxy Modelling, Unity 3D Visualisation and VR Display. The FITS data format cannot be read by the Unity Game Engine directly. A DLL (CSHARPFITS) which provides a native support for reading and writing FITS files was used. The Galaxy modeller uses an approach that integrates cleaned FITS image pixels into the graphics pipeline of the Unity3d game Engine. The cleaned FITS images are then input to the galaxy modeller pipeline phase, which has a pre-processing script that extracts, pixel, galaxy world position, and colour maps the FITS image pixels. The user can visualise image galaxies in different light bands, control the blend of the image with similar images from different sources or fuse images for a holistic view. The framework will allow users to build tools to realise complex workflows for public outreach and possibly scientific work with increased scalability, near real time interactivity with ease of access. The application is presented in an immersive environment and can use all commercially available headset built on the OpenXR API. The user can select galaxies in the scene, teleport to the galaxy, pan, zoom in/out, and change colour gradients of the galaxy. The findings and design lessons learnt in the implementation of different use cases will contribute to the development and design of game-based visualisation tools in immersive environment by enabling informed decisions to be made.

Keywords: astronomy, visualisation, multiwavelenght dataset, virtual reality

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Emma Pope, Demos Parapanos

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Rural tourism has become more obvious and prevalent, with tourists’ increasingly seeking authentic experiences. This movement accelerated post-Covid, putting destinations in danger of reaching levels of saturation called ‘overtourism’. Whereas the phenomenon of overtourism has been frequently discussed in the urban context by academics and practitioners over recent years, it has hardly been referred to in the context of rural tourism, where perhaps it is even more difficult to manage. Rural tourism was historically considered small-scale, marked by its traditional character and by having little impact on nature and rural society. The increasing number of rural areas experiencing overtourism, however, demonstrates the need for new approaches, especially as the impacts and enablers of overtourism are context specific. Cumbria, with approximately 47 million visitors each year, and 23,000 operational enterprises, is one of these rural areas experiencing overtourism in the UK. Using the county of Cumbria as an example, this paper aims to explore better planning and management in rural destinations by clustering the area into rural and ‘urban-rural’ tourism zones. To achieve the aim, this study uses secondary data from a variety of sources to identify variables relating to visitor economy development and demand. These data include census data relating to population and employment, tourism industry-specific data including tourism revenue, visitor activities, and accommodation stock, and big data sources such as Trip Advisor and All Trails. The combination of these data sources provides a breadth of tourism-related variables. The subsequent analysis of this data draws upon various validated models. For example, tourism and hospitality employment density, territorial tourism pressure, and accommodation density. In addition to these statistical calculations, other data are utilized to further understand the context of these zones, for example, tourist services, attractions, and activities. The data was imported into ARCGIS where the density of the different variables is visualized on maps. This study aims to provide an understanding of the geographical context of visitor economy development and tourist behavior in rural areas. The findings contribute to an understanding of the spatial dynamics of tourism within the region of Cumbria through the creation of thematized maps. Different zones of tourism industry clusters are identified, which include elements relating to attractions, enterprises, infrastructure, tourism employment and economic impact. These maps visualize hot and cold spots relating to a variety of tourism contexts. It is believed that the strategy used to provide a visual overview of tourism development and demand in Cumbria could provide a strategic tool for rural areas to better plan marketing opportunities and avoid overtourism. These findings can inform future sustainability policy and destination management strategies within the areas through an understanding of the processes behind the emergence of both hot and cold spots. It may mean that attract and disperse needs to be reviewed in terms of a strategic option. In other words, to use sector or zonal policies for the individual hot or cold areas with transitional zones dependent upon local economic, social and environmental factors.

Keywords: overtourism, rural tourism, sustainable tourism, tourism planning, tourism zones

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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: Christopher Muhawe, Masooda Bashir

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With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

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Authors: Alireza Saviz, Sedigheh Zarei

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Foreign Direct Investment (FDI) is an integral part of an open and effective international economic system and a major catalyst to development. Developing countries, emerging economies and countries in transition have come increasingly to see FDI as a source of economic development modernization, income growth and employment. FDI is an important vehicle for the transfer of technology, contributing relatively more to growth than domestic investment. Exploratory research is being conducted here. The data for the study is collected from secondary sources like research papers, journals, websites and reports. This paper aim was to generate knowledge on Iran’s situation through these factors after lifting sanction in comparison to Turkey. Although the most important factors that influence foreign investor decisions vary depending on the countries, sectors, years, and the objective of investor, nowadays governments should pay more attention to human resources education, marketing, infrastructure and administrative process in order to attracting foreign investors. A proper understanding of these findings will help governments to create appropriate policies in order to encourage more foreign investors

Keywords: foreign direct investment, host country, competitive advantage, FDI

Procedia PDF Downloads 488