Search results for: financial%20regulation

Authors: Nicolas D. Norboge

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Purchasers of municipal bonds in primary and secondary markets are increasingly expecting issuers to disclose environmental, social, and governance factors (ESG) inissuance and continuing disclosure documents. U.S. tolling authorities are slowly catching up with other transportation sectors, such as public transit, in integrating ESG factors into their bond disclosure documents. A systematic mixed-methods evaluation of publicly available bond disclosure documents from 2010-2022 suggest that only a small number of U.S. tolling authorities disclosedall ESG factors; however, the pace has accelerated significantly from 2020-2022. Because many tolling authorities have a direct financial stake in the growth of passenger vehicle miles traveled on their toll facilities, and in turn the burning of more climate-warming fossil fuels, one crucial questionthat remains is how bond purchasers will view increasedESG transparency. Recent moves by large institutional investors, credit rating agencies, and regulators suggestan expectation of ESG disclosure is a trend likely to endure. This researchsuggests tolling authorities will need to proactively consider these emerging trends and carefully adapt their disclosure practiceswhere possible. Building on these findings, this research also provides a basic sketch framework for how issuers can responsibly position themselves within the changing global municipal debt marketplace.

Keywords: debt policy, ESG, municipal bonds, public-private partnerships, public tolling authorities, transportation finance, and policy

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Authors: Samanta Tiague, Igor Michel Gachig

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The practice of inclusive education within general education classrooms is becoming more prevalent in Cameroon. In this context, quality Education is an important driver of the development agenda in this era of global sustainable development. This requires that the Cameroon’s educational system be strategically restructured to provide every citizen with the needed quality education for sustainable development. This study thus examined the need for the restructuring of the Cameroon educational system towards inclusive education as a target of the Sustainable Development Goal #4 (Ensure Quality Education), from a critical disability theory perspective. Special focus was on the education of children with visual impairment in the early childhood classroom. This study is suggesting a model design of responsive and contextual inclusive education policies, and the provision of quality human, material and financial educational resources to support the improvement of curriculums and inclusive instructional strategies. This paper is therefore designed as a basic starting point for early childhood educators with limited to no experience in working with students having visual impairments. Ultimately, this work represents a contribution to early childhood educators toward understanding visual impairment challenges and innovative practices to approach accessibility in a meaningful way to students in Cameroon. This is important to achieve quality education due to the peculiar nature of the educational needs of children with visual impairment, toward attainment of the global sustainable development agenda.

Keywords: early childhood educators, inclusive education, sustainable development, visual impairment

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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: 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: 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: 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: 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: 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: 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: 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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Authors: B. O. Diyaolu

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Viability and competency during competition is the dream of every team sports so as to have a good result. But it seems factors abound which deter the performance of even a good sports team. Different individuals with different state of mind all come together to perform in team sports with different degree of satisfaction. This study investigated the role of satisfaction on performance among Afe Babalola University team sports. Descriptive survey research design was used and the population consists of all male and female athletes in the team sports that participated in the last 2019 Ekiti State Higher Institution games (ESHIGA). Total enumeration technique was used for the three team sports; football (44), basketball (24) and volleyball (24). A total of 92 participants were involved in the research. The instrument used for the study was a modified Athlete Satisfaction Scale (ASS). The questionnaire was divided into two sections. The Cronbach’s Alpha reliability coefficient of 0.71 was obtained. The hypotheses were tested at 0.05 significant levels. The completed questionnaire was collated, coded, and analyzed using descriptive statistics of frequency counts and percentage and inferential statistics of chi-square (X²). Findings of this study revealed that satisfaction significantly influences team sports performance among Athletes of Afe Babalola University. The responsibility of satisfying athlete lies on the coaches, fans, sports administrators as well as organizers of such event, as it is not only financial reward that gives satisfaction. The performance of a team sports is quiet important and its being determined by the degree of satisfaction of each individual that make up the team. All effort must be made to satisfy athlete in order to guarantee optimum performance.

Keywords: athlete satisfaction, optimum achievement, optimum performance, sports performance and team sports

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Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

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The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

Procedia PDF Downloads 183

Authors: Ali Haratian, Soroosh Emami Meybodi

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Using viable microbial cultures within hydrocarbon reservoirs so as to the enhancement of oil recovery through metabolic activities is exactly what we recognize as microbial enhanced oil recovery (MEOR). In similar to many other processes in industries, there are some cons and pros following with MEOR. The creation of sulfides such as hydrogen sulfide as a result of injecting the sulfate-containing seawater into hydrocarbon reservoirs in order to maintain the required reservoir pressure leads to production and growth of sulfate reducing bacteria (SRB) approximately near the injection wells, turning the reservoir into sour; however, SRB is not considered as the only microbial process stimulating the formation of sulfides. Along with SRB, thermochemical sulfate reduction or thermal redox reaction (TSR) is also known to be highly effective at resulting in having extremely concentrated zones of ?2S in the reservoir fluids eligible to cause corrosion. Owing to extent of the topic, more information on the formation of ?₂S is going to be put finger on. Besides, confronting the undesirable production of sulfide species in the reservoirs can lead to serious operational, environmental, and financial problems, in particular the transporting pipelines. Consequently, conjuring up reservoir souring control strategies on the way production of oil and gas is the only way to prevent possible damages in terms of environment, finance, and manpower which requires determining the compound’s reactivity, origin, and partitioning behavior. This article is going to provide a comprehensive review of progress made in this field and the possible advent of new strategies in this technologically advanced world of the petroleum industry.

Keywords: corrosion, hydrogen sulfide, NRB, reservoir souring, SRB

Procedia PDF Downloads 206

Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

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The retrofitting of existing buildings to resist the seismic loads is very important to avoid losing lives or financial disasters. The aim at retrofitting processes is increasing total structure strength by increasing stiffness or ductility ratio. In addition, the response modification factors (R) have to satisfy the code requirements for suggested retrofitting types. In this study, two types of jackets are used, i.e. full reinforced concrete jackets and surrounding steel plate jackets. The study is carried out on an existing building in Madinah by performing static pushover analysis before and after retrofitting the columns. The selected model building represents nearly all-typical structure lacks structure built before 30 years ago in Madina City, KSA. The comparison of the results indicates a good enhancement of the structure respect to the applied seismic forces. Also, the response modification factor of the RC building is evaluated for the studied cases before and after retrofitting. The design of all vertical elements (columns) is given. The results show that the design of retrofitted columns satisfied the code's design stress requirements. However, for some retrofitting types, the ductility requirements represented by response modification factor do not satisfy KSA design code (SBC- 301).

Keywords: concrete jackets, steel jackets, RC buildings, pushover analysis, non-Linear analysis

Procedia PDF Downloads 353

Authors: Anna Paola Micheli, Anna Maria Calce, Loris Di Nallo

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Sustainable finance identifies the process that leads, in the adoption of investment decisions, to take into account environmental and social factors, with the aim of orienting investments towards sustainable and long-term activities. Considering that the topic is at the center of the interest of national agendas, long-term investments will no longer be analyzed only by looking at financial data, but environmental, social, and governance (ESG) factors will be increasingly important and will play a fundamental role in determining the risk and return of an investment. Although this perspective does not deny the orientation to profit, ESG mutual funds represent sustainable finance applied to the world of mutual funds. So the goal of this paper is to verify this attitude, in particular in the energy sector. The choice of the sector is not casual: ESG is the acronym for environmental, social, and governance, and energy companies are strictly related to the environmental theme. The methodology adopted leads to a comparison between a sample of ESG funds and a sample of ESG funds with similar characteristics, using the most important indicators of literature: yield, standard deviation, and Sharpe index. The analysis is focused on equity funds. Results that are partial, due to the lack of historicity, show a good performance of ESG funds, testifying how a sustainable approach does not necessarily mean lower profits. It is clear that these first findings do not involve an absolute preference for ESG funds in terms of performance because the persistence of results is requested. Furthermore, these findings are to be verified in other sectors and in bond funds.

Keywords: mutual funds, ESG, performance, energy

Procedia PDF Downloads 97

Authors: Suvankar Chakraborty

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Introduction: Corporate Social Responsibility means the obligations of business to act in a manner which will serve the best interests of the Society. The Companies Act , 2013 for the first time has emphasized on the fact that every company having net worth of rupees five hundred crore or more, or turnover of rupees one thousand crore or more or a net profit of rupees five crore or more during any financial year shall constitute a Corporate Social Responsibility Committee of the Board consisting of three or more directors, out of which at least one director shall be an independent director. In the previous Companies Act, 1956 there was no such compulsion for constituting a Corporate Social Responsibility Committee. Objective: This study examines the changes in the perception of corporate sectors so far as social responsibility is concerned. Methodology: The study is based on secondary data obtained from various websites of different corporate sectors and the Gazette of India related to Companies Act, 1956 and the new Companies Act, 2013. For capturing the perception of the corporate world regarding the provisions of CSR in the new Companies Act, 2013, primary data has been collected through structured questionnaire. Findings: Corporate Social Responsibility can put a company on a strong base of sustainable development and in facing the business risk of foreclosure or winding up. Shouldering social responsibility on a long-term basis can help a company not only in increasing its reputation in the business world but also helps in minimizing Government intervention. . But, there can hardly be any universal rule that the area of social responsibility being wholly and solely dependent on the ethical aspect of the corporate sectors. But having said that it may be asserted that business ethics may be a key driver of CSR activities rather than rule based CSR activities in the years to come.

Keywords: business ethics, corporate social responsibility, companies act, 2013, CSR committee

Procedia PDF Downloads 288

Authors: Ashiqul Amin Khan, Mohsin Ul Amin Khan

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The aim of this research is to find the relationship between good governance and shareholder wealth maximisation. The concept of good governance has become more objective in nature over time through various regulations, professionalisation, and practices. This has led to a number of methods for scoring and ranking corporate governance practices. Since shareholder wealth maximisation remains the key corporate goal for managers and governors alike, the effect of good governance in increasing the value of corporations is commented to be an important aspect. In measuring the value relevance of good governance, statistical measures of various yields of listed companies in the UK have been used in this research. Yields reflect required returns on investments from different investment tenets. Historical yields, calculated using historical fundamental data of such companies, reflect expected yields to a great extent. These yields, in turn, reflect the expected risk premium and growth associated with the stocks of the companies. Using fundamental data, the yields have been adjusted to reflect the risk premium required by the investors along various value paradigms. Good governance should naturally lead to lower required risk premium since good corporate governance provided assurance to the investors in terms of sustainability of future performance and desired financial conduct. This, in turn, increases the wealth of stockholders. The findings of this research confirm such nature of the relationship between good governance and value of the company in the long run.

Keywords: corporate governance, good governance practices, short-termism, shareholder value relevance, wealth maximisation, yield

Procedia PDF Downloads 349

Authors: Veniamin Boiarkin, Bruno Bogaz Zarpelão, Muttukrishnan Rajarajan

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The manufacturing sector is a vital component of most economies, which leads to a large number of cyberattacks on organisations, whereas disruption in operation may lead to significant economic consequences. Adversaries aim to disrupt the production processes of manufacturing companies, gain financial advantages, and steal intellectual property by getting unauthorised access to sensitive data. Access to sensitive data helps organisations to enhance the production and management processes. However, the majority of the existing data-sharing mechanisms are either susceptible to different cyber attacks or heavy in terms of computation overhead. In this paper, a privacy-preserving data-sharing scheme for smart utilities is proposed. First, a customer’s privacy adjustment mechanism is proposed to make sure that end-users have control over their privacy, which is required by the latest government regulations, such as the General Data Protection Regulation. Secondly, a local differential privacy-based mechanism is proposed to ensure the privacy of the end-users by hiding real data based on the end-user preferences. The proposed scheme may be applied to different industrial control systems, whereas in this study, it is validated for energy utility use cases consisting of smart, intelligent devices. The results show that the proposed scheme may guarantee the required level of privacy with an expected relative error in utility.

Keywords: data-sharing, local differential privacy, manufacturing, privacy-preserving mechanism, smart utility

Procedia PDF Downloads 62

Authors: Sun-Ki Choi

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The U.S. student loan policy was initiated to improve the equality of educational opportunity and help low-income families to provide higher education opportunities for their children. However, with the increase in the average student loan amount, college graduates with student loans experience problems and restrictions in their early-career choices. This study examines the early career labor market choices of college graduates who obtained student loans to finance their higher education. In this study, National Survey of College Graduates (NSCG) data for 2017 and 2019 was used to estimate the effects of student loans on the employment status and current job wages of graduates with student loans. In the analysis, two groups of workers, those with student loans and those without loans, were compared. Using basic models and Mahalanobis distance matching, it was found that graduates who rely on student loans to finance their education are more likely to participate in the labor market than those who do not. Moreover, in entry-level jobs, graduates with student loans receive lower salaries than those without student loans. College graduates make job-related decisions based on their current and future wages and fringe benefits. Graduates with student loans tend to demonstrate risk-averse behaviors due to their financial restrictions. Thus, student loan debt creates inequity in the early-career labor market for college graduates. Furthermore, this study has implications for policymakers and researchers in terms of the student loan policy.

Keywords: student loan, wage differential, unintended consequences, mahalanobis distance matching

Procedia PDF Downloads 106