Search results for: regional vector

Authors: Jeanne-Mari Retief

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As of November 2016, three African states have withdrawn from the International Criminal Court (ICC) and more are expected to follow. The alleged abuse of universal jurisdiction and targeting of African states by the ICC motivated the withdrawals. These historical exits raise many questions, especially in regard to the adequate investigation and prosecution of international crimes in a continent with a history of impunity. Even though African courts exist and one more is proposed, many issues remain i.e. adequate access to the courts, the extent of the courts’ jurisdiction, and proposed methods of effectively dealing with international crimes in Africa. This paper seeks to address the practical effects of the withdrawal from the ICC and the problems posed through utilizing regional courts. It will specifically look at the practical challenges existing courts face, the lack of access to the latter, issues concerning the proposed African Court for Justice and Human Rights, and the shocking promotion of impunity in Africa. These all have severe implications for African citizens and victims of the most heinous crimes. The mantra of African solutions to African problems places an important duty on states to ensure the actual provision of these solutions, which can only be achieved through a critical analysis of the questions above.

Keywords: ACJHR, Africa, impunity, justice, Malabo protocol

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Authors: M. Elham Ghabouli

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Intermediate cities which also called medium size cities have an important role in the process of globalization. It is argued that, in some cases this type of cities may be depopulated or in otherwise may be transformed as the periphery of metropolitans so that the personal identity of the city and its local cultural heritage could suffer from its neighbor metropolitan. Over the last decades, the role of tourism in development process and the cultural heritage is increased. The effect of tourism in socio-economic growth makes motivation for study on tourism development in regional and urban planning process. Tourism potentially has a specific role in promoting sustainable development especially by its economic and socio-cultural effects. The positive role of tourism in local development and in cultural heritage should be empowered by urban and regional planning. Damavand is an intermediate city located in Tehran province, Iran. Considering its local specific characteristic like social structure, antiquities and natural monuments made a suitable case study for studying on urban tourism planning method. Focusing on recognition of historical and cultural heritage of Damavand, this paper tried to peruse cultural-historical heritage protecting issue through “base plan methodology” which is introduced as a first step of urban planning for intermediate cities.

Keywords: urban planning, tourism, cultural heritage, intermediate cities

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Authors: Risikat Oladoyin S. Dauda, Onyebuchi Iwegbu

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This study investigates the response of human development outcomes to selected macroeconomic indicators in Nigeria. Human development outcomes is measured by human development index while the selected macroeconomic variables are inflation rate, real interest rate, government capital expenditure, real exchange rate, current account balance, and savings. Structural Vector Autoregression (SVAR) technique is employed in examining the response of human development index to the macroeconomic shocks. The result from the forecast error variance decomposition and Impulse-Response analysis reveals that fiscal policy (government capital expenditure) shock is the greatest determinant of human development outcomes. This result reiterates the role which the government plays in improving the welfare of the citizenry. The fiscal policy tool is pivotal in human development which comes in the form of investment in education, health, housing, and infrastructure. Further conclusion drawn from this study is that human development outcome positively and significantly responds to shocks from real interest rate, a monetary policy transmission variable and is felt greatly in the short run period. The policy implication of this study is that if capital budget implementation falls below expectations, human development will be engendered. Hence, efforts should be made to ensure that full implementation and appraisal of government capital expenditure is taken sacrosanct as any shock from such plan, engenders human development outcome.

Keywords: human development outcome, macroeconomic outcomes, structural vector autoregression, SVAR

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Authors: C. Q. Geng, Y. K. Hsiao

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We study direct CP-violating asymmetries (CPAs) in the baryonic B decays of B- -> p\bar{p}M and Λb decays of Λb ®pM andΛb -> J/ΨpM with M=π-, K-,ρ-,K*- based on the generalized factorization method in the standard model (SM). In particular, we show that the CPAs in the vector modes of B-®p\bar{p}K* and Λb -> p K*- can be as large as 20%. We also discuss the simplest purely baryonic decays of Λb-> p\bar{p}n, p\bar{p}Λ, Λ\bar{p}Λ, and Λ\bar{Λ}Λ. We point out that some of CPAs are promising to be measured by the current as well as future B facilities.

Keywords: CP violation, B decays, baryonic decays, Λb decays

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Authors: Se-Hwa Park, En-Kyung Han, Jae-Young Lim, Hye-Jung Ahn

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Purpose: The objective of this study is to provide basic data for understanding the substance of inpatient life with CRPS (Complex Regional Pain Syndrome) and developing efficient and effective nursing intervention. Methods: From September 2018 to November, we have interviewed 10 CRPS patients about inpatient experiences. To understand the implication of inpatient life experiences with CRPS and intrinsic structure, we have used the question: 'How about the inpatient experiences with CRPS'. For data analysis, the method suggested by Colaizzi was applied as a phenomenological method. Results: According to the analysis, the study participants' inpatient life process was structured in six categories: (a) breakthrough pain experience (b) the limitation of pain treatment, (c) worsen factors of pain during inpatient period, (d) treat method for pain, (e) positive experience for inpatient period, (f) requirements for medical team, family and people in hospital room. Conclusion: Inpatient with CRPS have experienced the breakthrough pain. They had expected immediate treatment for breakthrough pain, but they experienced severe pain because immediate treatment was not implemented. Pain-worsening factors which patients with CRPS are as follows: personal factors from negative emotions such as insomnia, stress, sensitive character, pain part touch or vibration stimulus on the bed, physical factors from high threshold or rapid speed during fast transfer, conflict with other people, climate factors such as humidity or low temperature, noise, smell, lack of space because of many visitors. Patients actively manage the pain committing into another tasks or diversion. And also, patients passively manage the pain, just suppress, give-up. They think positively about rehabilitation treatment. And they require the understanding and sympathy for other people, and emotional support, immediate intervention for medical team. Based on the results of this study, we suppose the guideline of systematic breakthrough pain management for the relaxation of sudden pain, using notice of informing caution for touch or vibration. And we need to develop non-medicine pain management nursing intervention.

Keywords: breakthrough pain, CRPS, complex regional pain syndrome, inpatient life experiences, phenomenological method

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Authors: Jan Muhammad, Saad Malik, Fadia W. Al-Azawi, Ali Imran

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In the era of climate variability, rising temperatures are the most significant aspect. In this study PRECIS model data and observed data are used for assessing the temperature change scenarios of Sindh province during the first half of present century. Observed data from various meteorological stations of Sindh are the primary source for temperature change detection. The current scenario (1961–1990) and the future one (2010-2050) are acted by the PRECIS Regional Climate Model at a spatial resolution of 25 * 25 km. Regional Climate Model (RCM) can yield reasonably suitable projections to be used for climate-scenario. The main objective of the study is to map the simulated temperature as obtained from climate model-PRECIS and their comparison with observed temperatures. The analysis is done on all the districts of Sindh in order to have a more precise picture of temperature change scenarios. According to results the temperature is likely to increases by 1.5 - 2.1°C by 2050, compared to the baseline temperature of 1961-1990. The model assesses more accurate values in northern districts of Sindh as compared to the coastal belt of Sindh. All the district of the Sindh province exhibit an increasing trend in the mean temperature scenarios and each decade seems to be warmer than the previous one. An understanding of the change in temperatures is very vital for various sectors such as weather forecasting, water, agriculture, and health, etc.

Keywords: PRECIS Model, real observed data, Arc GIS, interpolation techniques

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Authors: Olumide A. Fafore, Khondlo Mtshali

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The beginning of the 21st century saw the emergence of new and global threats to national and transnational security in West Africa and the Asia Pacific regions as a result of the spread of jihadist terrorism across borders, a manifestation of the rise of radical Islam. Extremist and armed Islamic movements influenced by Salafism, the Jihad in Afghanistan and the Muslim Brotherhood are prevalent in Northern Nigeria, Niger, Cameroon, Mali, Chad, Pakistan, Afghanistan, and India. Carrying out attacks across borders, including assassinations, murders, armed robberies, and kidnapping, assisted by open and porous borders and large flow of illegal immigrants across borders. This paper examines the effect of Radical Islam on Transnational security through a review of past literature and the social and security consequences on the people of the regions. Our findings indicate that the activities of armed Islamic movements such as Boko Haram, Ansaru and Al-Qaeda are having a negative impact on the economy, development, and security of the states and people of West Africa and the Asia Pacific. It stresses the importance of regional, transnational and international cooperation, as these threats to national and transnational security can no longer be solved in a national or regional framework.

Keywords: Islamic movements, jihadist terrorism, radical Islam, transnational security

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Authors: Tanmay Bisen, Aastha Shayla

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This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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Authors: Yohannes Haile, Dipo Onipede, Jr., Omar Ashour

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The main thrust of our research is to determine Industry 4.0 readiness of small and mid-size manufacturing companies in our region and assist them to implement Cyber Physical Production System (CPPS) capabilities. Adopting CPPS capabilities will help organizations realize improved quality, order delivery, throughput, new value creation, and reduced idle time of machines and work centers of their manufacturing operations. The key metrics for the assessment include the level of intelligence, internal and external connections, responsiveness to internal and external environmental changes, capabilities for customization of products with reference to cost, level of additive manufacturing, automation, and robotics integration, and capabilities to manufacture hybrid products in the near term, where near term is defined as 0 to 18 months. In our initial evaluation of several manufacturing firms which are profitable and successful in what they do, we found low level of Physical-Digital-Physical (PDP) loop in their manufacturing operations, whereas 100% of the firms included in this research have specialized manufacturing core competencies that have differentiated them from their competitors. The level of automation and robotics integration is low to medium range, where low is defined as less than 30%, and medium is defined as 30 to 70% of manufacturing operation to include automation and robotics. However, there is a significant drive to include these capabilities at the present time. As it pertains to intelligence and connection of manufacturing systems, it is observed to be low with significant variance in tying manufacturing operations management to Enterprise Resource Planning (ERP). Furthermore, it is observed that the integration of additive manufacturing in general, 3D printing, in particular, to be low, but with significant upside of integrating it in their manufacturing operations in the near future. To hasten the readiness of the local and regional manufacturing companies to Industry 4.0 and transitions towards CPPS capabilities, our working group (ADMAR Working Group) in partnership with our university have been engaged with the local and regional manufacturing companies. The goal is to increase awareness, share know-how and capabilities, initiate joint projects, and investigate the possibility of establishing the Center for Cyber Physical Production Systems Innovation (C2P2SI). The center is intended to support the local and regional university-industry research of implementing intelligent factories, enhance new value creation through disruptive innovations, the development of hybrid and data enhanced products, and the creation of digital manufacturing enterprises. All these efforts will enhance local and regional economic development and educate students that have well developed knowledge and applications of cyber physical manufacturing systems and Industry 4.0.

Keywords: automation, cyber-physical production system, digital manufacturing enterprises, disruptive innovation, new value creation, physical-digital-physical loop

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Authors: Vijaya K. Srivastava, Davide Spinello

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This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: constrained integer problems, enumerative search algorithm, Heuristic algorithm, Tunneling algorithm

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Authors: Christopher Meyer, Laima Gerlitz

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European ports are facing high political pressure through the implementation of initiatives such as the European Green Deal or IMO's 2030 targets (Fit for 55). However, small and medium-sized ports face even higher challenges compared to bigger ones due to lower capacities in various fields such as investments, infra-structure, Human Resources, and funding opportunities. Small and Medium-Sized Ports (SMPs) roles in economic systems are various depending on their specific functionality in maritime ecosystems. Depending on their different situations, being an actor in multiport gateways, aligned to core ports, regional nodes in peripheries for the hinterland, specialized cluster members, or logistical nodes, different strategic business models may be applied to increase SMPs' competitiveness among other bigger ports. Additionally, SMPs are facing more challenges for future development in terms of digital and green transition of their operations. Thus, it is necessary to evaluate the own strategical position and apply management strategies alongside the regional growth and innovation strategies for diversification or specialisation of own port businesses. The research uses inductive perspectives to set up a transferable framework based on case studies to be analysed. In line with particular research and document analysis, qualitative approaches were considered. The research is based on a deep literature review on SMPs as well as theories on diversification and specialisation. Existing theories from different fields are evaluated on their application for the port sector and these specific maritime actors, paying respect to enabling innovation incorporation to enhance digital and environmental transition with fu-ture perspectives for SMPs. The paper aims to provide a decision-making matrix for the strategic positioning of SMPs in Europe, including opportunities to get access to particular EU funds for future development alongside the Regional In-novation Strategies on Smart Specialisation.

Keywords: strategic planning, sustainability transition, competitiveness portfolio, EU green deal

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Authors: Wan-Ling Jiang, Hsin Chi, Jia-Lu Cheng, Ming-Fang Cheng

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Background: Investigating the risk factors for the fecal carriage of third-generation cephalosporin-resistant E.coli could contribute to further disease prevention. Previous research on third-generation cephalosporin-resistant prevalence in children in different regions of Taiwan is limited. This project aims to explore the risk factors and regional differences in the prevalence of third-generation cephalosporin-resistant and other antibiotic-resistant E. coli in the northern, southern, and eastern regions of Taiwan. Methods: We collected data from children aged 0 to 18 from community or outpatient clinics from July 2022 to May 2023 in southern, northern, and eastern Taiwan. The questionnaire was designed to survey the characteristics of participants and possible risk factors, such as clinical information, household environment, drinking water, and food habits. After collecting fecal samples and isolating stool culture with E.coli, antibiotic sensitivity tests and MLST typing were performed. Questionnaires were used to analyze the risk factors of third-generation cephalosporin-resistant E. coli in the three different regions of Taiwan. Results: In the total 246 stool samples, third-generation cephalosporin-resistant E.coli accounted for 37.4% (97/246) of all isolates. Among the three different regions of Taiwan, the highest prevalence of fecal carriage with third-generation cephalosporin-resistant E.coli was observed in southern Taiwan (42.7%), followed by northern Taiwan (35.5%) and eastern Taiwan (28.4%). Multi-drug resistant E. coli had prevalence rates of 51.9%, 66.3%, and 37.1% in the northern, southern, and eastern regions, respectively. MLST typing revealed that ST131 was the most prevalent type (11.8%). The prevalence of ST131 in northern, southern, and eastern Taiwan was 10.1%, 12.3%, and 13.2%, respectively. Risk factors analysis identified lower paternal education, overweight status, and non-vegetarian diet as statistical significance risk factors for third-generation cephalosporin-resistant E.coli. Conclusion: The fecal carriage rates of antibiotic-resistant E. coli among Taiwanese children were on the rise. This study found regional disparities in the prevalence of third-generation cephalosporin-resistant and multi-drug-resistant E. coli, with southern Taiwan having the highest prevalence. Lower paternal education, overweight, and non-vegetarian diet were the potential risk factors of third-generation cephalosporin-resistant E. coli in this study.

Keywords: Escherichia coli, fecal carriage, antimicrobial resistance, risk factors, prevalence

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Authors: Kuo-Wei Hsu, Shu-Fang Huang

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Global trend in creative economies promoted the modernization process of the development of cultural and creative industries and technology coincided with the craft industry towards value-added industrial restructuring. Due to government support and economic motivation in the private sector, regional craft products have emerged across counties and cities all over Taiwan which have led to an increased focus on craft culture promotion. However, most craft industry corporations in Taiwan are micro-enterprise, restricted operating profitability. This phenomenon shows the weakness of craft industry constitution when facing the rapid expansion of global economic commerce and manufacturing. In recent years, combining public and private enterprise, Platform business models revolutionary changed in craft industries’ original operation and transaction models. Therefore, this study attempts to explore the effects by implementing platform strategy on bamboo industry development in Nantou, the hometown of crafts in Taiwan, with an experimental investigation. This study concluded that platform strategy increases essence and insubstantial value for the bamboo industry in Taiwan. This study explored the economic value added of Taiwan bamboo village with three perspectives: Community participation, Culture Conservation, Regional Rejuvenation.

Keywords: platform strategy, craft industry, economic value-added

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Authors: Tooraj Karimi, Mohammadreza Sadeghi Moghadam

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Grey set theory has the advantage of using fewer data to analyze many factors, and it is therefore more appropriate for system study rather than traditional statistical regression which require massive data, normal distribution in the data and few variant factors. So, in this paper grey clustering and entropy of coefficient vector of grey evaluations are used to analyze energy consumption in buildings of the Oil Ministry in Tehran. In fact, this article intends to analyze the results of energy audit reports and defines most favorable characteristics of system, which is energy consumption of buildings, and most favorable factors affecting these characteristics in order to modify and improve them. According to the results of the model, ‘the real Building Load Coefficient’ has been selected as the most important system characteristic and ‘uncontrolled area of the building’ has been diagnosed as the most favorable factor which has the greatest effect on energy consumption of building. Grey clustering in this study has been used for two purposes: First, all the variables of building relate to energy audit cluster in two main groups of indicators and the number of variables is reduced. Second, grey clustering with variable weights has been used to classify all buildings in three categories named ‘no standard deviation’, ‘low standard deviation’ and ‘non- standard’. Entropy of coefficient vector of Grey evaluations is calculated to investigate greyness of results. It shows that among the 38 buildings surveyed in terms of energy consumption, 3 cases are in standard group, 24 cases are in ‘low standard deviation’ group and 11 buildings are completely non-standard. In addition, clustering greyness of 13 buildings is less than 0.5 and average uncertainly of clustering results is 66%.

Keywords: energy audit, grey set theory, grey incidence matrixes, grey clustering, Iran oil ministry

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Authors: Kalpana Rajouriya, Ajay Taneja

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The objective of the present study is to investigate the regional and lobar deposition of size-segregated PM in respiratory tract of human body. PM in different fractions is monitored using the Grimm portable environmental dust monitor during winter season in Firozabad; a Glass city of India. PM10 concentration (200.817g/m³) was 4.46 and 2.0 times higher than the limits prescribed by WHO (45g/m⁻³) and NAAQS (100g/m⁻³) government agencies. PM2.5 concentration (83.538 g/m3) was 5.56 and 1.39 times higher from WHO (15g/m-3) and NAAQS (60g/m⁻³) limits. Results inferred that PM10 and PM2.5 was highest deposited in head region (0.3477-0.5622 & 0.366-0.4704) followed by pulmonary region, especially in the 9-21year old persons. The variation in deposition percentage in our study is mainly due to the airway geometry, PM size, and its deposition mechanisms. The coarse fraction, due to its large size, cannot follow the airway path and mostly gets deposited by inertial impaction in the head region and its bifurcations. The present study results inferred that Coarse and fine PM deposition was highly visualized in 9 (8.45610⁻⁴ g, 2.91110⁻⁴g) year and 3 (1.49610⁻⁴ g, 8.59310⁻⁵g) month age category. So, the 9year children and 3month infants category have high level of health risk.

Keywords: particulate matter, MPPD model, regional deposition, lobar deposition, health risk

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Tina Melkoshvili

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Drastic development of information and communication technologies in Georgia has led to the necessity of launching conceptually new, effective, flexible, transparent and society oriented form of government that is e-government. Through applying information technologies, the electronic system enables to raise the efficacy of state governance and increase citizens’ participation in the process. Focusing on the topic of e-government allows us to analyze success stories, attributed benefits and, at the same time, observes challenges hampering the government development process. There are number of methodologies elaborated to study the conditions in the field of electronic governance. They enable us to find out if the government is ready to apply broad opportunities of information and communication technologies and if the government is apt to improve the accessibility and quality of delivering mainly social services. This article seeks to provide comparative analysis of widely spread methodologies used for Electronic government projects’ assessment. It has been concluded that applying current methods of assessment in Georgia is related to difficulties due to inaccessible data and the necessity of involving number of experts. The article presents new indicators for e-government development assessment that reflect efficacy of e-government conception realization in the regions of Georgia and enables to provide quantitative evaluation of regional e-government projects including all significant aspects of development.

Keywords: development methodology, e-government in Georgia, information and communication technologies, regional government

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Authors: Enayatollah Yazdani

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In the post-Cold War era, the world is facing a new emerging global order with the rise of multiple actors in the international arena. China, as a rising global power, has great leverage in internal relations. In particular, during the last two decades, China has rapidly transformed its economy into a global leader in advanced technologies. As a rising power and as one of the two major founding members of the Shanghai Cooperation Organization (SCO), China has tried to use this regional organization, which has the potential to become an important political and security organization of the major states located in the vast Eurasian landmass, for its “go global” strategy. In fact, for Beijing, the SCO represents a new and unique cooperation model, reflecting its vision of a multipolar world order. China has used the SCO umbrella as a multilateral platform to address external threats posed by non-state actors on its vulnerable western border; to gain a strong economic and political foothold in Central Asia without putting the Sino-Russian strategic partnership at risk; and to enhance its energy security through large-scale infrastructure investment in, and trade with, the Central Asian member states. In other words, the SCO is one of the successful outcomes of Chines foreign policy in the post-Cold War era. The expansion of multilateral ties all over the world by dint of pursuing institutional strategies as SCO identifies China as a more constructive power. SCO became a new model of cooperation that was formed on the remains of collapsed Soviet system and predetermined China's geopolitical role in the region. As the fast developing effective regional mechanism, SCO now has more of an external impact on the international system and forms a new type of interaction for promoting China's grand strategy of 'peaceful rise.' This paper aims to answer this major question: How the Chinese government has manipulated the SCO for its foreign policy and global and regional influence? To answer this question, the main discussion is that with regard to the SCO capabilities and politico-economic potential, this organization has been used by China as a platform to expand influence beyond its borders.

Keywords: China, the Shanghai Cooperation Organization (SCO), Central Asia, global policy, foreign policy

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Authors: Gabriella Fardhiyanti, Victor Wee

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Air connectivity is the crucial factors to boost a region economics growth. It will open the accessibility to support regional competitiveness and helps to achieve ASEAN (Association of Southeast Asian Nations) integration in term of economic integration, business investment, promote intra-regional trade, and creates the sense of belongingness among ASEAN people in the region. An increasing number of air connectivity and transportation will be benefiting the region because air transportation is a vital hub for ASEAN. The aim of this paper is to address the importance of air connectivity in promoting ASEAN Integration, by focusing on the ASEAN vision for a more integrated region. The assessment uses based on the Netscan Air connectivity model based on the flight destination and airport connectivity index, further analysis present that air connectivity significantly influence ASEAN tourism sector. Follow by the implications of open skies policy for the liberation of the aviation industry and the growth of low cost-carriers (LCCs) in the region. This paper provides recommendation and strategy for overcoming the challenges faced by ASEAN to boost ASEAN tourism integration successfully. The findings can assist in guiding policy and industry stakeholders in the future decision relating to air liberalization and more integrated system in the region.

Keywords: air connectivity, ASEAN integration, low-cost carries, NetScan connectivity model, open skies policy

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the easy creation of an institutional risk profile for endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support risk factors set up with just the most important values that are important for a particular organisation. Subsequently, the risk profile employs fuzzy models and associated configurations for the file format metadata aggregator to support digital preservation experts with a semi-automatic estimation of endangerment level for file formats. Our goal is to make use of a domain expert knowledge base aggregated from a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation and analysis of risk factors for a requried dimension. The proposed methods improve the visibility of risk factor information and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and automatically aggregated file format metadata from linked open data sources. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: digital information management, file format, endangerment analysis, fuzzy models

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Authors: Muhammet Baldan, Emel Timuçin

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Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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Authors: Inda Annisa Fauzani, Rahayu Setyawati Arifin

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The development of Special Economic Zones in Indonesia cannot be separated from the development of the communities in them. In accordance with the SEZ's objectives as a driver of economic growth, the focus of SEZ development does not only prioritize investment receipts and infrastructure development. The community as one of the stakeholders must also be considered. This becomes a challenge when the development of an SEZ has the potential to have an impact on the community in it. These impacts occur due to changes in the development of the area in the form of changes in the main regional industries and changes in the main livelihoods of the community. As a result, people can feel threats and disturbances. The community as the object of development is required to be able to have resilience in order to achieve a synergy between regional development and community development. A lack of resilience in the community can eliminate the ability to recover from disturbances and difficulty to adapt to changes that occur in their area. Social resilience is the ability of the community to be able to recover from disturbances and changes that occur. The achievement of social resilience occurs when the community gradually has the capacity in the form of coping capacity, adaptive capacity, and transformative capacity. It is hoped that when social resilience is achieved, the community will be able to develop linearly with regional development so that the benefits of this development can have a positive impact on these communities. This study aims to identify and analyze social factors that influence the achievement of social resilience in the community in Special Economic Zones in Indonesia and develop a program framework for achieving social resilience capacity in the community so that it can be used as a strategy to support the successful development of Special Economic Zones in Indonesia that provide benefits to the local community. This study uses a quantitative research method approach. Questionnaires are used as research instruments which are distributed to predetermined respondents. Respondents in this study were determined by using purposive sampling of the people living in areas that were developed into Special Economic Zones. Respondents were given a questionnaire containing questions about the influence of social factors on the achievement of social resilience. As x variables, 42 social factors are provided, while social resilience is used as y variables. The data collected from the respondents is analyzed in SPSS using Spearman Correlation to determine the relation between x and y variables. The correlated factors are then used as the basis for the preparation of programs to increase social resilience capacity in the community.

Keywords: community development, program management, social factor, social resilience

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Ernest Boateng Nuako

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This research is to find the effects of sports hooliganism on Ashanti school sports and find out some possible ways of amending or controlling them if we are to still experience them in our sporting fraternity. The researcher limited himself to the Ashanti region. The sample population was made up of officials, performances, and spectators drawn from four major second-cycle institutions and four basic schools in Ashanti. In all, 150 respondents were used, and all of them fell into the set of population, that is, performers, officials, and spectators. A structured questionnaire consisting of 29 statements where used to solicit views and opinions from the respondents on the effects of sports hooliganism in Ashanti school sports. Microsoft Office Excel tool (MS Excel) was used to analyze the response of the respondents, and the results were expressed in percentages. The study is aimed at finding out the effect sports hooliganism has on school sports festivals in Ghana with the Ashanti region as a case study and identify possible controlling measures to curb down the fast-pace effect of hooliganism on Ashanti regional schools. The research seeks to assist sports officials to identify some effects of sports hooliganism in Ashanti regional schools. It is also there to help officials to identify the influence hooliganism has on sports. This research also serves as a guide to other researchers who want to go into researching sports in the region. This research revealed that sports hooliganism has, in diverse ways, affected school sports in the region. It was also evident from the research study that sanctions, the presence of security, and other employable remedies could be used in controlling this unfortunate incident during our school sports competitions.

Keywords: officiating officials, school sports, hooliganism, spectators, performer

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Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: artificial neural network, load estimation, regional survey, rural electrification

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Authors: Amina R. Issae, Godfrey C. Katusi, Beda J. Mwang’Onde, Ladslaus L. Mnyone, Allen L. Malisa

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Background: The fluctuating composition of mosquito species over time, driven by ecological changes in specific regions, plays a pivotal role in the transmission of malaria. Grasping these dynamics is fundamental for establishing a baseline understanding and is crucial for identifying transmission patterns. This knowledge is essential in devising effective strategies for managing and controlling vector populations. Our study focused on examining the species composition and Plasmodium infection rates of malaria vectors, aiming to enhance the health and well-being of communities affected by malaria. Methods: Species composition was determined through a cross-sectional collection of mosquitoes, conducted once in the village, in four selected villages of Kilosa district, Tanzania. Mosquitoes were collected indoors and outdoors using CDC light traps. A sub-sample of all collected mosquitoes was subjected to PCR identification and assayed for Plasmodium porozoites. Results: A total of 6493 female Anophelines mosquitoes were collected, of which eight species were identified as Anopheles gambiaes.l., An. funestus group, An. coustani, An. pharoensis, An. squamosus, and An. rufipes. The abundance of the Anopheles gambiaes.s.and An. funestuss.s. varied with location and village. A total of 5 sporozoite-positive mosquitoes were found, of which 4 were An. funestuss.s. and 1 was An. gambiaes.s. Conclusions: Anopheles gambiaes.s.and An. funestuss.s. were identified as the most abundant malaria vectors, respectively. Sporozoite analysis indicated this for An. funestuss.s. contribute to most of the malaria transmission in the area. Further studies are required to assess the role of seasonal shifts in vector abundance, insecticide resistance and malaria transmission of the vectors.

Keywords: mosquito, composition, malaria, sporozoites

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Authors: Mark Wenyi Lai

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The very lethal weapon of nuclear warhead had threatened the survival of the world for half of the 20th century. When most of the countries have already denounced and stopped the development, one country is eager to produce and use them. Since 2006, Pyongyang has launched six times of nuclear tests. The most recent one in September 2017 signaled North Korea’s military capability to project the mass destruction through ICBM (Intercontinental Ballistic Missile) over Seoul, Tokyo, Guam, Hawaii, Alaska or probably the West Coast of the United States with the explosive energy ten times of the atom bombing of Hiroshima in 1945. This research paper adopted time-series content analysis focusing on the related countries responses to North Korea’s tests in 2006, 2009, 2013, and 2016. The preliminary hypotheses are first, North Korea determined to protect the regime by having triad nuclear capability. Negotiations are mere means to this end. Second, South Korea is paralyzed by its ineffective domestic politics and unable to develop its independent strategy toward the North. Third, Japan was using the external threat to campaign for its rearmament plan and brought instability in foreign relations. Fourth, China found herself in the strange position of defending the loyal buffer state meanwhile witnessing the fourth and dangerous neighboring country gaining the card into nuclear club. Fifth, the United States had admitted that North Korea’s going nuclear is unstoppable. Therefore, to keep the regional stability in the East Asia, the US relied on the new balance of power formed by everyone versus Pyongyang. But, countries in East Asia actually have problems getting along with each other. Sixth, Russia distanced herself from the North Kore row but benefitted by advancing its strategic importance in the Far East. Tracing back the history of nuclear states, this research paper concluded that North Korea will head on becoming a more confident country. The regional stability will restore once related countries deal with the new fact and treat Pyongyang regime with a new strategy. The gradual opening and economic reform are on the way for the North Korea in the near future.

Keywords: nuclear test, North Korea, six party talk, US foreign policy

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Authors: Tasawar Ashraf

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The paper argues that the European Union’s securitized recourse to migration management which is lacking on the principle of solidarity has enhanced the sufferings of the asylum seekers by influencing the asylum policies of the non-EU states in the Eastern Mediterranean. The research critically analyses the development of the Turkish Asylum Policy and advocates that due to extraordinary burden of refugees and conceivable chances of getting EU membership, Turkey is developing its asylum policy essentially on the footprints of the EU. Such political and economic domination of the EU are resulting in the development of broader securitized migration zone in the EU and MENA region. Therefore, this paper critically analyses two interconnected issues, i.e., securitization of the migration in the EU and MENA region and the deficiency of the principle of solidarity and burden sharing in the European Agenda on Migration and how it reflects on Turkish asylum policy. This paper suggests that the EU must adopt a more generous resettle scheme ensuring the division of the refugee burden on all member and regional states by considering different political, social, and economic factors. Only such corporation can increase the pool of refugee hosting states by collaborating with the regional states to develop their asylum systems in accordance with international law.

Keywords: European Agenda on Migration (EAM), EU, Middle East and North Africa (MENA), Treaty on the Functioning of the European Union (TFEU)

Procedia PDF Downloads 164