Search results for: financial risks

Authors: Anisul Islam

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The U.S. has a very strong trade relationship with China but with a large and persistent trade deficit. Some has argued that the undervalued Chinese Yuan is to be blamed for the persistent trade deficit. The empirical results are mixed at best. This paper empirically estimates the U.S. export function along with the U.S. import function with its trade with China with the purpose of testing for the existence of the Marshall-Lerner (ML) condition as well for the possible existence of the J-curve hypothesis. Annual export and import data will be utilized for as long as the time series data exists. The export and import functions will be estimated using advanced econometric techniques, along with appropriate diagnostic tests performed to examine the validity and reliability of the estimated results. The annual time-series data covers from 1975 to 2022 with a sample size of 48 years, the longest period ever utilized before in any previous study. The data is collected from several sources, such as the World Bank’s World Development Indicators, IMF Financial Statistics, IMF Direction of Trade Statistics, and several other sources. The paper is expected to shed important light on the ongoing debate regarding the persistent U.S. trade deficit with China and the policies that may be useful to reduce such deficits over time. As such, the paper will be of great interest for the academics, researchers, think tanks, global organizations, and policy makers in both China and the U.S.

Keywords: exports, imports, marshall-lerner condition, j-curve hypothesis, united states, china

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Authors: Godfrey Muiya Mukala

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This research looks at an array of fields in Sub-Saharan Africa comprising agriculture, food enterprises, medicine, organisms genetically modified, microbiology, and nanotechnology that can be gained from biotechnological research and development. Findings into dangerous organisms, mainly bacterial germs, rickettsia, fungi, parasites, or organisms that are genetically engineered, have immensely posed questions attributed to the biological danger they bring forth to human beings and the environment because of their uncertainties. In addition, the recurrence of previously managed diseases or the inception of new diseases are connected to biosafety challenges, especially in rural set-ups in low and middle-income countries. Notably, biotechnology laboratories are required to adopt biosafety measures to protect their workforce, community, environment, and ecosystem from unforeseen materials and organisms. Sensitization and inclusion of educational frameworks for laboratory workers are essential to acquiring a solid knowledge of harmful biological agents. This is in addition to human pathogenicity, susceptibility, and epidemiology to the biological data used in research and development. This article reviews and analyzes research intending to identify the proper implementation of universally accepted practices in laboratory safety and biological hazards. This research identifies ideal microbiological methods, adequate containment equipment, sufficient resources, safety barriers, specific training, and education of the laboratory workforce to decrease and contain biological hazards. Subsequently, knowledge of standardized microbiological techniques and processes, in addition to the employment of containment facilities, protective barriers, and equipment, is far-reaching in preventing occupational infections. Similarly, reduction of risks and prevention may be attained by training, education, and research on biohazards, pathogenicity, and epidemiology of the relevant microorganisms. In this technique, medical professionals in rural setups may adopt the knowledge acquired from the past to project possible concerns in the future.

Keywords: sub-saharan africa, biotechnology, laboratory, infections, health

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Authors: Hameed Rukayat Opeyemi, Pericles Pilidis, Pagone Emanuele

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An infinitesimal increase in performance can have immense reduction in operating and capital expenses in a power generation system. Therefore, constant studies are being carried out to improve both conventional and novel power cycles. Globally, power producers are constantly researching on ways to minimize emission and to collectively downsize the total cost rate of power plants. A substantial spurt of developmental technologies of low carbon cycles have been suggested and studied, however they all have their limitations and financial implication. In the area of carbon abatement in power plants, three major objectives conflict: The cost rate of the plant, Power output and Environmental impact. Since, an increase in one of this parameter directly affects the other. This poses a multi-objective problem. It is paramount to be able to discern the point where improving one objective affects the other. Hence, the need for a Pareto-based optimization algorithm. Pareto-based optimization algorithm helps to find those points where improving one objective influences another objective negatively and stops there. The application of Pareto-based optimization algorithm helps the user/operator/designer make an informed decision. This paper sheds more light on areas that multi-objective optimization has been applied in carbon abatement technologies in the last five years, developments and prospects.

Keywords: gas turbine, low carbon technology, pareto optimal, multi-objective optimization

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Authors: Faride Hashemiannejad, Shima Oloomi

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Imagination is one of the important elements of creative thinking which as a skill needs attention by the educational system. Although most students learn reading, writing, and arithmetic skills well, they lack high level thinking skills like creative thinking. Therefore, in the information age and in the beginning of entry to knowledge-based society, the educational system needs to think over its goals and mission, and concentrate on creativity-based curriculum. From among curriculum elements-goals, content, method and evaluation “method” is a major domain whose reform can pave the way for fostering imagination and creativity. The purpose of this study was examining the relationship between creativity development and curriculum. Research questions were: (1) is there a relationship between the cognitive-emotional structure of the classroom and creativity development? (2) Is there a relationship between the environmental-social structure of the classroom and creativity development? (3) Is there a relationship between the thinking structure of the classroom and creativity development? (4) Is there a relationship between the physical structure of the classroom and creativity development? (5) Is there a relationship between the instructional structure of the classroom and creativity development? Method: This research is a applied research and the research method is Correlational research. Participants: The total number of participants in this study included 894 students from High school through 11th grade from seven schools of seven zones in Mashad city. Sampling Plan: Sampling was selected based on Random Multi State. Measurement: The dependent measure in this study was: (a) the Test of Creative Thinking, (b) The researcher-made questionnaire includes five fragments, cognitive, emotional structure, environmental social structure, thinking structure, physical structure, and instructional structure. The Results Show: There was significant relationship between the cognitive-emotional structure of the classroom and student’s creativity development (sig=0.139). There was significant relationship between the environmental-social structure of the classroom and student’s creativity development (sig=0.006). There was significant relationship between the thinking structure of the classroom and student’s creativity development (sig=0.004). There was not significant relationship between the physical structure of the classroom and student’s creativity development (sig=0.215). There was significant relationship between the instructional structure of the classroom and student’s creativity development (sig=0.003). These findings denote if students feel secure, calm and confident, they can experience creative learning. Also the quality of coping with students’ questions, imaginations and risks can influence on their creativity development.

Keywords: imagination, creativity, curriculum, bioinformatics, biomedicine

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Authors: Haruna Abdu Usman, Bashir Usman Mohammed, Mohammed Umar Jamil

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Municipal solid waste management constitutes a serious problem bedeviling environmental protection agencies in many cities of developing countries. Most agencies do not collect the totality of the waste generated in their cities. This study presents the current solid waste management practices and problems in Bauchi metropolis, Bauchi state Nigeria. The general feature is characterized by inefficient, insufficient and irrational collection and improper disposal alternatives. The consequent environmental effects of these problems depict clogged city drains, uncollected heap of waste on road sides of residential areas, vacant plots and uncompleted buildings and highways. This contributes immensely to flooding in the city. The major challenges facing the state environmental protection agency includes; lack of collection and disposal points, technical and institutional arrangements, financial resources and general attitude of the serving public among others. The study suggested a comprehensive and integrated approach to the solid waste management which recognizes and incorporates the interventionist role of the state government, the private formal and informal waste management operators and the serving public.

Keywords: municipal solid waste, bauchi metropolitan area, environmental protection agency, solid waste management, waste disposal

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Authors: L. Kolatorova, J. Vitku, K. Adamcova, M. Simkova, M. Hill, A. Parizek, M. Duskova

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Endocrine disruptors (EDs) are substances leaching from various industrial products, which are able to interfere with the endocrine system. Their harmful effects on human health are generally well-known, and exposure during fetal development may have lasting effects. Fetal exposure and transplacental transport of bisphenol A (BPA) have been recently studied; however, less is known about alternatives such as bisphenol S (BPS), bisphenol F (BPF) and bisphenol AF (BPAF), which have started to appear in consumer products. The human organism is usually exposed to the mixture of EDs, out of which parabens are otherwise known to transfer placenta. The usage of many cosmetic, pharmaceutical and consumer products during the pregnancy that may contain parabens and bisphenols has led to the need for investigation. The aim of the study was to investigate the transplacental transport of BPA, its alternatives, and parabens, and to study their relation to fetal steroidogenesis. BPA, BPS, BPF, BPAF, methylparaben, ethylparaben, propylparaben, butylparaben, benzylparaben and 15 steroids including estrogens, corticoids, androgens and immunomodulatory ones were determined in 27 maternal (37th week of gestation) and cord plasma samples using liquid chromatography - tandem mass spectrometry methods. The statistical evaluation of the results showed significantly higher levels of BPA (p=0.0455) in cord plasma compared to maternal plasma. The results from multiple regression models investigated that in cord plasma, methylparaben, propylparaben and the sum of all measured parabens were inversely associated with testosterone levels. To our best knowledge, this study is the first attempt to determine the levels of alternative bisphenols in the maternal and cord blood, and also the first study reporting the simultaneous detection of bisphenols, parabens, and steroids in these biological fluids. Our study confirmed the transplacental transport of BPA, with likely accumulation in the fetal compartment. The negative association of cord blood parabens and testosterone levels highlights their possible risks, especially for the development of male fetuses. Acknowledgements: This work was supported by the project MH CR 17-30528 A from the Czech Health Research Council, MH CZ - DRO (Institute of Endocrinology - EÚ, 00023761) and by the MEYS CR (OP RDE, Excellent research - ENDO.CZ).

Keywords: bisphenol, endocrine disruptor, paraben, pregnancy, steroid

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Authors: Mohammad-Ali Latifi, Harry Bouwman

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Changes in the business environment accelerated dramatically over the last decades as a result of changes in technology, regulation, market, and competitors’ behavior. Firms need to change the way they do business in order to survive or maintain their growth. Innovating business model (BM) can create competitive advantages and enhance firm performance. However, many companies fail to achieve expected outcomes in practice, mostly due to irreversible fundamental changes in key components of the company’s BM. This leads to more ambiguity, uncertainty, and risks associated with business performance. However, the relationship among BM Innovation, moderating factors, and the firm’s overall performance is by and large ignored in the current literature. In this study, we identified twenty moderating factors from our comprehensive literature review. We categorized these factors based on two criteria regarding the extent to which: the moderating factors can be controlled and managed by firms, and they are generic or specific changes to the firms. This leads to four moderation groups. The first group is BM implementation, which includes management support, employees’ commitment, employees’ skills, communication, detailed plan. The second group is called BM practices, which consists of BM tooling, BM experimentation, the scope of change, speed of change, degree of novelty. The third group is Firm characteristics, including firm size, age, and ownership. The last group is called Industry characteristics, which considers the industry sector, competitive intensity, industry life cycle, environmental dynamism, high-tech vs. low-tech industry. Through collecting data from 508 European small and medium-sized enterprises (SMEs) and using the structural equation modeling technique, the developed moderation model was examined. Results revealed that all factors highlighted through these four groups moderate the relation between BMI and firm performance significantly. Particularly, factors related to BM-Implementation and BM-Practices are more manageable and would potentially improve firm overall performance. We believe that this result is more important for researchers and practitioners since the possibility of working on factors in Firm characteristics and Industry characteristics groups are limited, and the firm can hardly control and manage them to improve the performance of BMI efforts.

Keywords: business model innovation, firm performance, implementation, moderation

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Authors: Hanen Khaldi

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This paper aims to study the impact of international migration on human security in the Southeastern region of Asia, especially after Asian Financial Crisis 1997-98. International migration has impacts on many dimensions of security: the state security (sovereignty and autonomy); international relationships security (conflicts, terrorism, etc); and immigrants security. The paper aims to improve our comprehension of the impact of international migration on immigrant security in the region of Southeast Asia, particularly “vulnerable workers’’ whose number is growing very fast in the region. The literature review carried out on this matter led us to ask the following two question: 1) Did the creation of ASEAN Community matter on the evolution of immigrants in the region? And How governments try to resolve the gap between economic objectifs and security of immigrants in the region? To answer these two questions, the paper is subdivided in three parts: Firstly, we will show how the creation of the ASEAN Community, especially ASEAN Economic Community, had a significant impact on the pattern of evolution of immigration in this region. Secondly, we will paint a portrait illustrating the vulnerability of immigrants in Southeast Asia, particularly unskilled workers. Finally, using the theories of regional integration, we will assess how governments try to ensure the security and safety of the immigrants. Overall, our analysis illustrate the significant change of the official discourse of the leaders of the ASEAN member states, now more conciliator and especially more open to cooperation, as well as the proliferation of meetings and initiatives between these countries to control mobility flows in the region, and the ensure immigrants security.

Keywords: migrant workers, human security, human rights

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Authors: Adel Fathy Sadek Abdalla

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The issue of respect for human rights in Southeast Asia has become a major concern and is attracting the attention of the international community. Basically, the Association of Southeast Asian Nations (ASEAN) made human rights one of its main issues and in the ASEAN Charter in 2008. Subsequently, the Intergovernmental Commission on Human Rights ASEAN Human Rights (AICHR) was established. AICHR is the Southeast Asia Human Rights Enforcement Commission charged with the responsibilities, functions and powers to promote and protect human rights. However, at the end of 2016, the protective function assigned to the AICHR was not yet fulfilled. This is shown by several cases of human rights violations that are still ongoing and have not yet been solved. One case that has recently come to light is human rights violations against the Rohingya people in Myanmar. Using a legal-normative approach, the study examines the urgency of establishing a human rights tribunal in Southeast Asia capable of making a decision binding on ASEAN members or guilty parties. Data shows ASEAN needs regional courts to deal with human rights abuses in the ASEAN region. In addition, the study also highlights three important factors that ASEAN should consider when establishing a human rights tribunal, namely: Volume. a significant difference in terms of democracy and human rights development among the members, a consistent implementation of the principle of non-interference and the financial issue of the continuation of the court.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security.

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Authors: Gregory Kelly, Gary Chai, Sittampalam Manoharan, Deborah Delaney

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A Structural Number (SN) can be calculated for a road pavement from the properties and thicknesses of the surface, base course, sub-base, and subgrade. Historically, the cost of collecting structural data has been very high. Data were initially collected using Benkelman Beams and now by Falling Weight Deflectometer (FWD). The structural strength of pavements weakens over time due to environmental and traffic loading factors, but due to a lack of data, no structural deterioration curve for pavements has been implemented in a Pavement Management System (PMS). International Roughness Index (IRI) is a measure of the road longitudinal profile and has been used as a proxy for a pavement’s structural integrity. This paper offers two conceptual methods to develop Pavement Structural Deterioration Curves (PSDC). Firstly, structural data are grouped in sets by design Equivalent Standard Axles (ESA). An ‘Initial’ SN (ISN), Intermediate SN’s (SNI) and a Terminal SN (TSN), are used to develop the curves. Using FWD data, the ISN is the SN after the pavement is rehabilitated (Financial Accounting ‘Modern Equivalent’). Intermediate SNIs, are SNs other than the ISN and TSN. The TSN was defined as the SN of the pavement when it was approved for pavement rehabilitation. The second method is to use Traffic Speed Deflectometer data (TSD). The road network already divided into road blocks, is grouped by traffic loading. For each traffic loading group, road blocks that have had a recent pavement rehabilitation, are used to calculate the ISN and those planned for pavement rehabilitation to calculate the TSN. The remaining SNs are used to complete the age-based or if available, historical traffic loading-based SNI’s.

Keywords: conceptual, pavement structural number, pavement structural deterioration curve, pavement management system

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Authors: Monique de Ritter, Annemieke Roobeek

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This study takes a holistic multi-layered systems approach on entrepreneurship, innovation, and sustainability. Concretely we looked how mission driven entrepreneurs (level 1) employ new business models and launch innovative products and/or ideas in their enterprises, which are (level 2) operating in entrepreneurial ecosystems (level 3), and how these in turn may generate higher level sustainable change (level 4). We employed a qualitative grounded research approach in which our aim is to contribute to theory. Fourteen in-depth semi-structured interviews were conducted with mission driven entrepreneurs in the Netherlands in which their individual drives, business models, and ecosystems were discussed. Interview transcripts were systematically coded and analysed and the ecosystems were visually mapped. Most important patterns include 1) entrepreneurs have a clear sustainable mission and regard this mission as de raison d’être of their enterprise; 2) entrepreneurs employ new business models with a focus on collaboration for innovation; the business model supports or enhances the sustainable mission of the enterprise, 3) entrepreneurs collaborate in ecosystems in which a) they also regard suppliers as partners for innovation and clients as ambassadors for the sustainable mission, b) would like to improve their relationships with financial institutions as they are in the entrepreneurs’ perspective often lagging behind with their innovative ideas and models, c) they collaborate for knowledge and innovation with several parties, d) personal informal connections are very important, and e) in which the higher sustainable mission is not a point of competition but of collaboration.

Keywords: sustainability, entrepreneurship, innovation, ecosystem, business models

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Authors: Mennatallah M. Hussein, Olivier de Weck

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The advancement of space exploration demands a robust space launch services program capable of reliably propelling payloads into orbit. Despite rigorous testing and quality assurance, launch failures still occur, leading to significant financial losses and jeopardizing mission objectives. Traditional failure prediction methods often lack the sophistication to account for multi-mode failure scenarios, as well as the predictive capability in complex dynamic systems. Traditional approaches also rely on expert judgment, leading to variability in risk prioritization and mitigation strategies. Hence, there is a pressing need for robust approaches that enhance launch vehicle reliability from lift-off until it reaches its parking orbit through comprehensive simulation techniques. In this study, the developed model proposes a multi-mode launch vehicle simulation framework for predicting failure scenarios when incorporating new technologies, such as new propulsion systems or advanced staging separation mechanisms in the launch system. To this end, the model combined a 6-DOF system dynamics with comprehensive data analysis to simulate multiple failure modes impacting launch performance. The simulator utilizes high-fidelity physics-based simulations to capture the complex interactions between different subsystems and environmental conditions.

Keywords: launch vehicle, failure prediction, propulsion anomalies, rocket launch simulation, rocket dynamics

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Authors: Riccardo Cacciotti, Jiri Frankl, Benjamin Wolf, Michael Machacek

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Moisture fluctuations govern the occurrence of fungi-related problems in buildings, which may impose significant health risks for users and even lead to structural failures. Several numerical engineering models attempt to capture the complexity of mold growth on building materials. From real life observations, in cases with suppressed daily variations of boundary conditions, e.g. in crawlspaces, mold growth model predictions well correspond with the observed mold growth. On the other hand, in cases with substantial diurnal variations of boundary conditions, e.g. in the ventilated cavity of a cold flat roof, mold growth predicted by the models is significantly overestimated. This study, founded by the Grant Agency of the Czech Republic (GAČR 20-12941S), aims at gaining a better understanding of mold growth behavior on solid wood, under varying boundary conditions. In particular, the experimental investigation focuses on the response of mold to changing conditions in the boundary layer and its influence on heat and moisture transfer across the surface. The main results include the design and construction at the facilities of ITAM (Prague, Czech Republic) of an innovative device allowing for the simulation of changing environmental conditions in buildings. It consists of a square section closed circuit with rough dimensions 200 × 180 cm and cross section roughly 30 × 30 cm. The circuit is thermally insulated and equipped with an electric fan to control air flow inside the tunnel, a heat and humidity exchange unit to control the internal RH and variations in temperature. Several measuring points, including an anemometer, temperature and humidity sensor, a loading cell in the test section for recording mass changes, are provided to monitor the variations of parameters during the experiments. The research is ongoing and it is expected to provide the final results of the experimental investigation at the end of 2022.

Keywords: moisture, mold growth, testing, wood

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Authors: Sergejs Kolesovs, Pavels Semjonovs

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Whey and dairy wastewaters if disposed in the environment without proper treatment, cause serious environmental risks contributing to overall and particular environmental pollution and climate change. Biological treatment of wastewater is considered to be most eco-friendly approach, as compared to the chemical treatment methods. Research shows, that dairy wastewater can potentially be remediated by use of microalgae thussignificantly reducing the content of carbohydrates, P, N, K and other pollutants. Moreover, it has been shown, that use of dairy wastewaters results in higher microalgae biomass production. In recent decades microalgal biomass has entailed a big interest for its potential applications in pharmaceuticals, biomedicine, health supplementation, cosmetics, animal feed, plant protection, bioremediation and biofuels. It was shown, that lipids productivity on whey and dairy wastewater is higher as compared with standard cultivation media and occurred without the necessity of inducing specific stress conditions such as N starvation. Moreover, microalgae biomass production as usually associated with high production costs may benefit from perspective of both reasons – enhanced microalgae biomass or target substances productivity on cheap growth substrate and effective management of whey and dairy wastewaters, which issignificant for decrease of total production costs in both processes. Obviously, it became especially important when large volume and low cost industrial microalgal biomass production is anticipated for further use in agriculture of crops as plant growth stimulants, biopesticides soil fertilisers or remediating solutions. Environmental load of dairy wastewaters can be significantly decreased when microalgae are grown in coculture with other microorganisms. This enhances the utilisation of lactose, which is main C source in whey and dairy wastewaters when it is not metabolised easily by most microalgal species chosen. Our study showsthat certain microalgae strains can be used in treatment of residual sugars containing industrial wastewaters and decrease of their concentration thus approving that further extensive research on dairy wastewaters pre-treatment optionsfor effective cultivation of microalgae, carbon uptake and metabolism, strain selection and choice of coculture candidates is needed for further optimisation of the process.

Keywords: microalgae, whey, dairy wastewaters, sustainability, plant biostimulants

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Authors: Akinnubi Rufus Temidayo

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Coastal West Africa is highly sensitive to climate variability, driven by complex ocean-atmosphere interactions that shape temperature, precipitation, and extreme weather. Radiative feedback mechanisms—such as water vapor feedback, cloud-radiation interactions, and surface albedo—play a critical role in modulating these patterns. Yet, limited research addresses these feedbacks in climate models specific to West Africa’s coastal zones, creating challenges for accurate climate projections and adaptive planning. This study aims to evaluate the influence of radiative feedbacks on the coastal climate of West Africa by quantifying the effects of water vapor, cloud cover, and sea surface temperature (SST) on the region’s radiative balance. The study uses a regional climate model (RCM) to simulate feedbacks over a 20-year period (2005-2025) with high-resolution data from CORDEX and satellite observations. Key mechanisms investigated include (1) Water Vapor Feedback—the amplifying effect of humidity on warming, (2) Cloud-Radiation Interactions—the impact of cloud cover on radiation balance, especially during the West African Monsoon, and (3) Surface Albedo and Land-Use Changes—effects of urbanization and vegetation on the radiation budget. Preliminary results indicate that radiative feedbacks strongly influence seasonal climate variability in coastal West Africa. Water vapor feedback amplifies dry-season warming, cloud-radiation interactions moderate surface temperatures during monsoon seasons, and SST variations in the Atlantic affect the frequency and intensity of extreme rainfall events. The findings suggest that incorporating these feedbacks into climate planning can strengthen resilience to climate impacts in West African coastal communities. Further research should refine regional models to capture anthropogenic influences like greenhouse gas emissions, guiding sustainable urban and resource planning to mitigate climate risks.

Keywords: west africa, radiative, climate, resilence, anthropogenic

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Authors: Salako Emmanuel Adekunle

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Computer education is referred to as the knowledge and ability to use computers and related technology efficiently, with a range of skills covering levels from basic use to advance. Computer continues to make an ever-increasing impact on all aspect of human endeavours such as education. With numerous benefits of computer education, what are the insights of students on computer education? This study investigated the perception of senior secondary school students on computer education in Federal Capital Territory (FCT), Abuja, Nigeria. A sample of 7500 senior secondary schools students was involved in the study, one hundred (100) private and fifty (50) public schools within FCT. They were selected by using simple random sampling technique. A questionnaire [PSSSCEQ] was developed and validated through expert judgement and reliability co-efficient of 0.84 was obtained. It was used to gather relevant data on computer education. Findings confirmed that the students in the FCT had positive perception on computer education. Some factors were identified that affect students’ perception on computer education. The null hypotheses were tested using t-test and ANOVA statistical analyses at 0.05 level of significance. Based on these findings, some recommendations were made which include competent teachers should be employed into all secondary schools; this will help students to acquire relevant knowledge in computer education, technological supports should be provided to all secondary schools; this will help the users (students) to solve specific problems in computer education and financial supports should be provided to procure computer facilities that will enhance the teaching and the learning of computer education.

Keywords: computer education, perception, secondary school, students

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Authors: Zulkifli Mohamed Udin, Lee Khai-Loon, Mohamad Ghozali Hassan

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In today’s dynamic business environment, the competition is no longer between firms, but between supply chains to gain competitive advantages. The global manufacturing sector, especially the textile and apparel industry are essentially known for its supply chain dependency. The delicate nature of its business leads to emphasis on the smooth movement of upstream and downstream supply chain. The nature of this industry, however, result in huge dynamic flow of physical, information, and financial. The dynamic management of these flows requires adoption of supply chain technologies. Even though technology is widely implemented and studied in many industries by researchers, adoption of supply chain technologies in Malaysian textile and apparel industry is limited. There is relatively a handful academic study conducted on recent developments in Malaysian textile and apparel industry and supply chain technology adoption indicate a major gap in supply chain performance studies. Considering the importance given to Third Industrial Master Plan by the government Malaysia, it is necessary to understand the power of supply chain technology adoptions. This study aims to investigate supply chain technology adoption by textile and apparel companies in Malaysia. The result highlighted the benefits perceived by textile and apparel companies from supply chain technologies. The indifference of small and medium enterprises to operation management acts as a major inhibitor to the adoption of supply chain technologies, since they have resource limitations. This study could be used as a precursor for further detailed studies on this issue.

Keywords: supply chain technology adoption, supply chain performance, textile, apparel industry

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Authors: Mohamed Khiatine, Amal Medjnoun, Ramdane Bahar

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The North Algeria is a highly seismic zone, as evidenced by the historical seismicity. During the past two decades, it has experienced several moderate to strong earthquakes. Therefore, the geotechnical engineering problems that involve dynamic loading of soils and soil-structure interaction system requires, in the presence of saturated loose sand formations, liquefaction studies. Bejaia city, located in North-East of Algiers, Algeria, is a part of the alluvial plain which covers an area of approximately 750 hectares. According to the Algerian seismic code, it is classified as moderate seismicity zone. This area had not experienced in the past urban development because of the different hazards identified by hydraulic and geotechnical studies conducted in the region. The low bearing capacity of the soil, its high compressibility and the risk of liquefaction and flooding are among these risks and are a constraint on urbanization. In this area, several cases of structures founded on shallow foundations have suffered damages. Hence, the soils need treatment to reduce the risk. Many field and laboratory investigations, core drilling, pressuremeter test, standard penetration test (SPT), cone penetrometer test (CPT) and geophysical down hole test, were performed in different locations of the area. The major part of the area consists of silty fine sand , sometimes heterogeneous, has not yet reached a sufficient degree of consolidation. The ground water depth changes between 1.5 and 4 m. These investigations show that the liquefaction phenomenon is one of the critical problems for geotechnical engineers and one of the obstacles found in design phase of projects. This paper presents an analysis to evaluate the liquefaction potential, using the empirical methods based on Standard Penetration Test (SPT), Cone Penetration Test (CPT) and shear wave velocity and numerical analysis. These liquefaction assessment procedures indicate that liquefaction can occur to considerable depths in silty sand of harbor zone of Bejaia.

Keywords: earthquake, modeling, liquefaction potential, laboratory investigations

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Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Hiba Taim

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This abstract falls within the scope of entrepreneurship and regulates cultural and creative entrepreneurship. It tackles the topic of "The Ecosystem in Cultural and Creative Entrepreneurship in North Africa". This piece of work deals with the problem of the absence of the ecosystem in cultural and creative enterprises in North Africa, meaning the absence of a clear structure of the ecosystem in the field of cultural and creative entrepreneurship in North Africa. The aim of this research is to create an integrated ecosystem that brings together all those involved in cultural and creative entrepreneurship in North Africa: from training, financial support, continuing, international organizations, government banks, and means of communication. This study is significant not only because it suggests some activities to develop this system but also because it provides all of the information to cultural and creative entrepreneurs in order for them to create project opportunities and activate the entrepreneurship process. It will also enable the creation of opportunities to work among them and formulate common cultural policies to develop the quality of cultural and creative services in North Africa. This research paper uses a qualitative approach to gather information of good quality about the problem being tackled, as well as studying and analyzing different documents and conducting interviews with cultural entrepreneurs, which will help to collect all the information on the state of the ecosystem in North Africa. For the moment, this paperwork is at the stage of collecting preliminary data regarding the problem and developing appropriate schedules for all the phases of the research in order to be productive and deliver this study in the coming months.

Keywords: cultural innovation, design innovation, design thinking, cultural entrepreneurship

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Authors: Simone Medio

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If we observe many modern cities from above, we are typically confronted with a sea of asphalt-clad flat rooftops. In contrast to the modernist expectation of a populated flat roof, flat rooftops in modern multi-story buildings are rarely used. On the contrary, they typify a desolate and abandoned landscape encouraging mechanical system allocation. Flat roof technology continues to be seen as a state-of-fact in most multi-storey building designs and its greening its prevalent environmental justification. This paper aims to seek a change in the approach to flat roofing. It makes a case for the opportunity at hand for architectonically resolute, sheltered, livable spaces that make a better use of the environment at rooftop level. The researcher is looking for the triggers that allow for that change to happen in the design process of case study buildings. The paper begins by exploring Han Slawick covered roof terrace in Amsterdam as a simple and essential example of transforming the flat roof in a usable, inhabitable space. It investigates the design challenges and the logistic, financial and legislative hurdles faced by the architect, and the outcomes in terms of building performance and occupant use and satisfaction. The researcher uses a grounded research methodology with direct interview process to the architect in charge of the building and the building user. Energy simulation tools and calculation of running costs are also used as further means of validating change.

Keywords: environmental design, flat rooftop persistence, roof re-habitation, tectonics

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Authors: E. Kharaishvili, G. Erkomaishvili, M. Chavleishvili

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The paper evaluates the natural and resource potential of agriculture, a traditional sector for Georgia. It is concluded that despite favorable conditions the rate of development of the sector is lower compared to other sectors of the economy, self-sufficiency rate for locally produced agricultural products is low; on average, import of food is 4 times higher compared to export, and the country faces considerable challenges in this regard. Tendencies of self-sufficiency rates are studied, and it is concluded that the indicators of export and import of agro-food products increase in accordance with the tendency of increasing production in agricultural sector. The paper substantiates stimulating impact of international trade on agricultural development. Two alternative strategies are assessed in this respect: 1) export stimulation, and 2) import replacement strategies. It is concluded that significant tendencies are observed in agro-food sector of Georgia; in particular, productivity is low; import volume significantly exceeds the export volume. It is considered that the growth of export will allow Georgia to overcome limited opportunities of local market and encourage increasing competitiveness. Various tools of economic policy are suggested for achieving these goals; in particular to subsidize export, optimize trade barriers, manage exchange rates effectively, offer special financial services, provide insurance for export, etc.

Keywords: agro-food sector, trend of production, export stimulation, economic policy

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Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

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We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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Authors: Baglan Bazylova

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The purpose of our article is to consider the social and psychological conflicts in Lyudmila Petrushevskaya’s stories as an artistic presentation of gender structure of modern society; to reveal originality of the characters’ inner world, the models of their behavior expressing the gender specific nature of modern feminine prose. Gender conflicts have taken the leading place in the modern prose. L. Petrushevskaya represents different types of conflicts including those which are shown in the images of real contradictions in the stories "Narratrix", "Thanks to Life”, "Virgin's Case", "Father and Mother". In the prose of Petrushevskaya the gender conflicts come out in two dimensions: The first one is love relations between a man and a woman. Because of the financial indigence, neediness a woman can’t afford herself even to fall in love and arrange her family happiness. The second dimension is the family conflict because of the male adultery. Petrushevskaya fixed on the unmanifistated conflict in detail. In the real life such gender conflict can appear in different forms but for the writer is important to show it as a life basis, hidden behind the externally safe facade of “the family happiness”. In the stories of L. Petrushevskaya the conflicts reflect the common character of the social and historical situations in which her heroines find themselves, in situations where a woman feels her opposition to the customary mode of life. The types of gender conflicts of these stories differ in character of verbal images. They are presented by the verbal and event ranks creating the conflicts just in operation.

Keywords: gender behavior of heroes, gender conflict, gender picture of the world, gender structure

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Authors: Javad Izadi, Sahar Majioud

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This study presents an approach of assessing the choice of performance measures of companies in the United Kingdom after the application of IFRS in 2005. The aim of this study is to investigate the effects of IFRS on the choice of performance evaluation methods for UK companies. We analyse through an econometric model the relationship of the dependent variable, the firm’s performance, which is a nominal variable with the independent ones. Independent variables are split into two main groups: the first one is the group of accounting-based measures: Earning per share, return on assets and return on equities. The second one is the group of market-based measures: market value of property plant and equipment, research and development, sales growth, market to book value, leverage, segment and size of companies. Concerning the regression used, it is a multinomial logistic regression performed on a sample of 130 UK listed companies. Our finding shows after IFRS adoption, and companies give more importance to some variables such as return on equities and sales growth to assess their performance, whereas the return on assets and market to book value ratio does not have as much importance as before IFRS in evaluating the performance of companies. Also, there are some variables that have no impact on the performance measures anymore, such as earning per share. This article finding is empirically important for business in subjects related to IFRS and companies’ performance measurement.

Keywords: performance’s Measure, nominal variable, econometric model, evaluation methods

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Authors: Mustapha Ouardouz, Mina Amharref, Abdessamed Bernoussi

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The future energy, for limited energy resources countries, goes through renewable energies (solar, wind etc.). The renewable energies constitute a major component of the energy strategy to cover a substantial part of the growing needs and contribute to environmental protection by replacing fossil fuels. Indeed, sustainable development involves the promotion of renewable energy and the preservation of the environment by the use of clean energy technologies to limit emissions of greenhouse gases and reducing the pressure exerted on the forest cover. So the impact studies, of the energy use on the environment and farm-related risks are necessary. For that, a global approach integrating all the various sectors involved in such project seems to be the best approach. In this paper we present an approach based on the multi criteria analysis and the realization of one pilot to achieve the development of an innovative geo-intelligent environmental platform. An implementation of this platform will collect, process, analyze and manage environmental data in connection with the nature of used energy in the studied region. As an application we consider a region in the north of Morocco characterized by intense agricultural and industrials activities and using diverse renewable energy. The strategic goals of this platform are; the decision support for better governance, improving the responsiveness of public and private companies connected by providing them in real time with reliable data, modeling and simulation possibilities of energy scenarios, the identification of socio-technical solutions to introduce renewable energies and estimate technical and implantable potential by socio-economic analyzes and the assessment of infrastructure for the region and the communities, the preservation and enhancement of natural resources for better citizenship governance through democratization of access to environmental information, the tool will also perform simulations integrating environmental impacts of natural disasters, particularly those linked to climate change. Indeed extreme cases such as floods, droughts and storms will be no longer rare and therefore should be integrated into such projects.

Keywords: renewable energies, decision aided tool, environment, simulation

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Sopit Tubtimhin, Chaliya Wamaloon, Anchalee Supattagorn

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Background and Significance: Breast cancer is the most frequently diagnosed and leading cause of cancer death among women. This study aims to determine factors potentially predicting recurrence and long-term survival after the first recurrence in surgically treated patients between postmenopausal and younger women. Methods and Analysis: A retrospective cohort study was performed on 498 Thai women with invasive breast cancer, who had undergone mastectomy and been followed-up at Ubon Ratchathani Cancer Hospital, Thailand. We collected based on a systematic chart audit from medical records and pathology reports between January 1, 2002, and December 31, 2011. The last follow-up time point for surviving patients was December 31, 2016. A Cox regression model was used to calculate hazard ratios of recurrence and death. Findings: The median age was 49 (SD ± 9.66) at the time of diagnosis, 47% was post-menopausal women ( ≥ 51years and not experienced any menstrual flow for a minimum of 12 months), and 53 % was younger women ( ˂ 51 years and have menstrual period). Median time from the diagnosis to the last follow-up or death was 10.81 [95% CI = 9.53-12.07] years in younger cases and 8.20 [95% CI = 6.57-9.82] years in postmenopausal cases. The recurrence-free survival (RFS) for younger estimates at 1, 5 and 10 years of 95.0 %, 64.0% and 58.93% respectively, appeared slightly better than the 92.7%, 58.1% and 53.1% for postmenopausal women [HRadj = 1.25, 95% CI = 0.95-1.64]. Regarding overall survival (OS) for younger at 1, 5 and 10 years were 97.7%, 72.7 % and 52.7% respectively, for postmenopausal patients, OS at 1, 5 and 10 years were 95.7%, 70.0% and 44.5 respectively, there were no significant differences in survival [HRadj = 1.23, 95% CI = 0.94 -1.64]. Multivariate analysis identified five risk factors for negatively impacting on survival were triple negative [HR= 2.76, 95% CI = 1.47-5.19], Her2-enriched [HR = 2.59, 95% CI = 1.37-4.91], luminal B [HR = 2.29, 95 % CI=1.35-3.89], not free margin [HR = 1.98, 95%CI=1.00-3.96] and patients who received only adjuvant chemotherapy [HR= 3.75, 95% CI = 2.00-7.04]. Statistically significant risks of overall cancer recurrence were Her2-enriched [HR = 5.20, 95% CI = 2.75-9.80], triple negative [HR = 3.87, 95% CI = 1.98-7.59], luminal B [HR= 2.59, 95% CI = 1.48-4.54,] and patients who received only adjuvant chemotherapy [HR= 2.59, 95% CI = 1.48-5.66]. Discussion and Implications: Outcomes from this studies have shown that postmenopausal women have been associated with increased risk of recurrence and mortality. As the results, it provides useful information for planning the screening and treatment of early-stage breast cancer in the future.

Keywords: breast cancer, menopause status, recurrence-free survival, overall survival

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Authors: Herdina Indrijati

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This research aims to describe teenager delinquency behavior (Juvenile Delinquency) of senior high school students in Surabaya, Indonesia. Juvenile Delinquency is a broad range of behaviors start from socially unacceptable behavior (overreact in school), violation (escape from home) to crimes (like stealing). This research uses quantitative descriptive method using 498 students who come from 8 different schools in Surabaya as subjects. Juvenile Delinquency behavior form questionnaire has been completed by subjects and was used to measure and describe the behavior. The result of this research is presented in statistic descriptive forms. Result shows that 169 subjects skip school, 55 subjects get out of home without parent’s permission, 110 subjects engage in smoking behavior, 74 subjects damage other people properties, 32 subjects steal, 16 subjects exploit others and 7 subjects engage in drug abuse. Frequency of the top five mentioned behavior are 1-10 times. It is also found that subject’s peers are most likely to be the victim of Juvenile Delinquency. The reasons teenagers engage in Juvenile Delinquency include (1) feeling tired, bored or lazy – that contributes to their skip school behavior (2) Having a lot of problem with parents - contrives them to run away from home, (3) accidentally damage other people’s properties, (4) financial problems – force them to steal and exploit, (5) feeling like having a lot of life problems – that makes them do drugs (6) trying smoking for experience.

Keywords: juvenile delinquency, senior high school, student

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Authors: Neha Ahirwar

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In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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