Search results for: artificial legal principles

Authors: Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson

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Artificial Intelligence (AI) in the Engineering, Procurement, and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Nevertheless, AI has become an attractive technology for organizations looking to automate repetitive tasks to reduce manual work. Meanwhile, the current AI market has started offering various solutions and services. The contribution of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to a specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

Keywords: artificial intelligence, machine learning, deep learning, innovation, engineering, procurement and construction industry, AI in the EPC industry

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Authors: Selcuk Aslan, Dervis Karaboga, Celal Ozturk

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Artificial Bee Colony (ABC) algorithm is one of the most successful swarm intelligence based metaheuristics. It has been applied to a number of constrained or unconstrained numerical and combinatorial optimization problems. In this paper, we presented a parallelized version of ABC algorithm by adapting employed and onlooker bee phases to the Compute Unified Device Architecture (CUDA) platform which is a graphical processing unit (GPU) programming environment by NVIDIA. The execution speed and obtained results of the proposed approach and sequential version of ABC algorithm are compared on functions that are typically used as benchmarks for optimization algorithms. Tests on standard benchmark functions with different colony size and number of parameters showed that proposed parallelization approach for ABC algorithm decreases the execution time consumed by the employed and onlooker bee phases in total and achieved similar or better quality of the results compared to the standard sequential implementation of the ABC algorithm.

Keywords: Artificial Bee Colony algorithm, GPU computing, swarm intelligence, parallelization

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Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

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The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

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Authors: Joon-Ho Lee, Jeong-Hwan Yoon, Jung-Hwan Yoon, Sangmo Kang, Su-Yeon Hong, Hyun-Woo Jeong, Jaeick Chae

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There are several dedicated individual chambers for sports that are supplied and used, but none of them are multi-pressured all-in-one chambers that can provide a sports multi-environment simultaneously. In this study, we design a multi-pressure (positive/atmospheric/negative pressure) integrated vessel that can be used for the sport-multi-artificial environment system. We presented additional vessel designs with enlarged space for the tall users; with reinforcement pads added to reduce the maximum stress in the joints of its shells, and then carried out numerical analysis for the structural analysis with maximum stress and structural safety. Under the targeted allowable pressure conditions, maximum stresses occurred at the joint of the shell, and the entrance, the safety of the structure was checked with the allowable stress of its material.

Keywords: structural analysis, multi-pressure, integrated vessel, sport-multi-artificial environment

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Authors: Riznaldi Akbar

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In this study, we compared the performance of the Artificial Neural Network (ANN) model with back-propagation algorithm in correctly predicting in-sample and out-of-sample external debt crisis in Indonesia. We found that exchange rate, foreign reserves, and exports are the major determinants to experiencing external debt crisis. The ANN in-sample performance provides relatively superior results. The ANN model is able to classify correctly crisis of 89.12 per cent with reasonably low false alarms of 7.01 per cent. In out-of-sample, the prediction performance fairly deteriorates compared to their in-sample performances. It could be explained as the ANN model tends to over-fit the data in the in-sample, but it could not fit the out-of-sample very well. The 10-fold cross-validation has been used to improve the out-of-sample prediction accuracy. The results also offer policy implications. The out-of-sample performance could be very sensitive to the size of the samples, as it could yield a higher total misclassification error and lower prediction accuracy. The ANN model could be used to identify past crisis episodes with some accuracy, but predicting crisis outside the estimation sample is much more challenging because of the presence of uncertainty.

Keywords: debt crisis, external debt, artificial neural network, ANN

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Authors: Mohamad Mahdi Namdari

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In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

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Authors: T. Holecki, J. Wozniak-Holecka, K. Sobczyk

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Development, implementation, and evaluation of the effects of health policy programs, resulting from the identified health needs and health status of residents, is the own task of all local government units in Poland. This is due to the obligation to provide access to healthcare services to all residents and the implementation of tasks in the field of health promotion based on specific legal acts. Until the end of 2016 local governments financed health policy programs only with their own funds. Currently, there are additional resources available from the public health insurance subsidising up to 80% of health policy programs costs in cities with a population under 5 thousand people and up to 40% in bigger cities. Changes in legal provisions do not translate automatically to increased involvement of local government units in the implementation of public health tasks. The main objective of the study was to assess the actual impact of the new legal regulation on financing local health policy programs on the engagement of local administration in this area of public health activity. To achieve this aim, we analyzed difference in the number of local governments developing and implementing health policy programs before and after the new law came into force. The aim of the study was also to estimate the level of expenditures incurred by self-government units and the National Health Fund to cover the costs of health policy programs. In the first stage of the project, legal acts concerning the subject of research and financial data published by the National Health Fund were analyzed. The material for the second, main stage of the study was the detailed financial data obtained from the National Health Fund and data obtained from local government units. The results present the situation in Poland in territorial terms, divided into 16 voivodships.

Keywords: health care system, health policy programs, local self-governments, public health

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Authors: Gustavo Funes, Eduardo Peters, Jose Delpiano

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It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more, lowering the energy production and module lifespan. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an autonomous way. We performed several experiments photographing three different types of panels, 30W, 340W and 410W. Those panels were soiled artificially with uniform and non-uniform distributed dust. The algorithm proposed uses statistical tools to provide a simulation with a 100% soiled panel and then performs a comparison to get the percentage of dirt in the experimental data set. The simulation uses a seed that is obtained by taking a dust sample from the maximum amount of dust from the dataset. The final result is the dirt percentage and the possible distribution of dust over the panel. Dust deposition is a key factor for plant owners to determine cleaning cycles or identify nonuniform depositions that could lead to module failure and hot spots.

Keywords: dust detection, photovoltaic, artificial vision, soiling

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Authors: Abigaba Sophia

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Artificial intelligence (AI) has transformed the education sector by revolutionizing educational frameworks by providing new opportunities and innovative advanced platforms for language translation during the teaching and learning process. In today's education sector, the primary key to scholarly communication is language; therefore, translation between different languages becomes vital in the process of communication. KIU-T being an International University, admits students from different nations speaking different languages, and English is the official language; some students find it hard to grasp a word during teaching and learning. This paper explores the practical aspect of using artificial intelligence technologies in an advanced language translation manner during teaching and learning. The impact of this technology is reflected in the education strategies to equip students with the necessary knowledge and skills for professional activity in the best way they understand. The researcher evaluated the demand for this practice since students have to apply the knowledge they acquire in their native language to their countries in the best way they understand. The main objective is to improve student's language competence and lay a solid foundation for their future professional development. A descriptive-analytic approach was deemed best for the study to investigate the phenomena of language translation intelligence alongside Microsoft Office during the teaching and learning process. The study analysed the responses of 345 students from different academic programs. Based on the findings, the researcher recommends using the artificial intelligence language translation technique during teaching, and this requires the wisdom of human content designers and educational experts. Lecturers and students will be trained in the basic knowledge of this technique to improve the effectiveness of teaching and learning to meet the student’s needs.

Keywords: artificial intelligence, language translation technique, teaching and learning process, Microsoft Office

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Authors: Yilin Liao, Hewen Li, Paula McConvey

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Speed skaters often face a risk of concussion when they fall on the ice floor and impact crash mats during practices and competitive races. Several variables, including those related to the skater, the crash mat, and the impact position (body side/head/feet impact), are believed to influence the severity of the skater's concussion. While computer simulation modeling can be employed to analyze these accidents, the simulation process is time-consuming and does not provide rapid information for coaches and teams to assess the skater's injury risk in competitive events. This research paper promotes the exploration of the feasibility of using AI techniques for evaluating skater’s potential concussion severity, and to develop a fast concussion prediction tool using artificial neural networks to reduce the risk of treatment delays for injured skaters. The primary data is collected through virtual tests and physical experiments designed to simulate skater-mat impact. It is then analyzed to identify patterns and correlations; finally, it is used to train and fine-tune the artificial neural networks for accurate prediction. The development of the prediction tool by employing machine learning strategies contributes to the application of AI methods in sports science and has theoretical involvements for using AI techniques in predicting and preventing sports-related injuries.

Keywords: artificial neural networks, concussion, machine learning, impact, speed skater

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Authors: Muneeb Ahmad, Ali Raza

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A computational method inspired by the immune system (IS) is presented, leveraging its shared characteristics of robustness, fault tolerance, scalability, and adaptability with swarm intelligence. This method aims to showcase flocking behaviors in a swarm of robots (SR). The innate part of the IS offers a variety of reactive and probabilistic cell functions alongside its self-regulation mechanism which have been translated to enable swarming behaviors. Although, the research is specially focused on flocking behaviors in a variety of simulated environments using e-puck robots in a physics-based simulator (CoppeliaSim); the artificial innate immune system (AIIS) can exhibit other swarm behaviors as well. The effectiveness of the immuno-inspired approach has been established with extensive experimentations, for scalability and adaptability, using standard swarm benchmarks as well as the immunological regulatory functions (i.e., Dendritic Cells’ Maturity and Inflammation). The AIIS-based approach has proved to be a scalable and adaptive solution for emulating the flocking behavior of SR.

Keywords: artificial innate immune system, flocking swarm, immune system, swarm intelligence

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Authors: F. Massri, M. Shkarneh, B. Almassri

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Water scarcity and increasing water demand especially for residential use are major challenges facing Palestine. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. The main objective of this paper is to (i) study the major factors influencing the water consumption in Palestine, (ii) understand the general pattern of Household water consumption, (iii) assess the possible changes in household water consumption and suggest appropriate remedies and (iv) develop prediction model based on the Artificial Neural Network to the water consumption in Palestinian cities. The paper is organized in four parts. The first part includes literature review of household water consumption studies. The second part concerns data collection methodology, conceptual frame work for the household water consumption surveys, survey descriptions and data processing methods. The third part presents descriptive statistics, multiple regression and analysis of the water consumption in the two Palestinian cities. The final part develops the use of Artificial Neural Network for modeling the water consumption in Palestinian cities.

Keywords: water management, demand forecasting, consumption, ANN, Ramallah

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Authors: Keroles Akram Saed Ghatas

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The near future will bring significant changes in modern organizations and management due to the growing role of intangible assets and knowledge workers. The area of copyright, intellectual property, digital (intangible) assets and media redistribution appears to be one of the greatest challenges facing business and society in general and management sciences and organizations in particular. The proposed article examines the views and perceptions of fairness in digital media sharing among Harvard Law School's LL.M.s. Students, based on 50 qualitative interviews and 100 surveys. The researcher took an ethnographic approach to her research and entered the Harvard LL.M. in 2016. at, a Face book group that allows people to connect naturally and attend in-person and private events more easily. After listening to numerous students, the researcher conducted a quantitative survey among 100 respondents to assess respondents' perceptions of fairness in digital file sharing in various contexts (based on media price, its availability, regional licenses, copyright holder status, etc.). to understand better . .). Based on the survey results, the researcher conducted long-term, open-ended and loosely structured ethnographic interviews (50 interviews) to further deepen the understanding of the results. The most important finding of the study is that Harvard lawyers generally support digital piracy in certain contexts, despite having the best possible legal and professional knowledge. Interestingly, they are also more accepting of working for the government than the private sector. The results of this study provide a better understanding of how “fairness” is perceived by the younger generation of lawyers and pave the way for a more rational application of licensing laws.

Keywords: cognitive impairments, communication disorders, death penalty, executive function communication disorders, cognitive disorders, capital murder, executive function death penalty, egyptian law absence, justice, political cases piracy, digital sharing, perception of fairness, legal profession

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Authors: Rahmi Kopar

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Legitimate expectations principle is considered one of the most dominant elements of the Fair and Equitable Treatment Standard which is today’s most relied upon treaty standard. Since its utilization by arbitral tribunals is relatively new, the contours of the legitimate expectations concept under investment treaty law have not been precisely defined yet. There are various fragmented views arising both from arbitral tribunals and scholarly writings with respect to its limits and use even though the principle is ‘firmly rooted in arbitral practice.’ International energy investments, due to their characteristics, are more prone to certain types of risks, especially the political risks. Thus, there are several mechanisms to protect an energy investment against those risks. Stabilisation is one of these investment protection methods. Stability provisions can be found under domestic legislations, as a contractual clause, or as a separate legal stability agreement. This paper will start by examining the roots of the contentious concept of legitimate expectations with reference to its application in domestic legal systems from where the doctrine under investment treaty law context was transplanted. Then the paper will turn to the investment treaty law and analyse the main contours of the doctrine as understood and applied by arbitral tribunals. 'What gives rise to the investor’s legitimate expectations?' question is answered mainly by three categories of sources: the general legal framework prevalent in a host state, the representations made by the officials or organs of a host state, and the contractual commitments. However, there is no unanimity among the arbitral tribunals and the scholars with respect to the form these sources should take. At this point, the study will discuss the sources of a stability provision and the effect of these stability provisions found in various legal sources in creating a legitimate expectation for the investor. The main questions to be discussed in this paper are as follows: a) Do the stability provisions found under different legal sources create a legitimate expectation on the investor side? b) If yes, what levels of legitimate expectations do they create? These questions will be answered mainly by reference to investment treaty jurisprudence.

Keywords: fair and equitable treatment standard, international energy investments, investment protection, legitimate expectations, stabilization

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Authors: Shaima Almalhan, Lubna Shukri, Miriam Talal, Safaa Teskieh

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Since artificial intelligence is a rapidly evolving topic that has had a significant impact on technical growth and innovation, this paper examines people's awareness, use, and engagement with the Google Translate application. To see how familiar aware users are with the app and its features, quantitative and qualitative research was conducted. The findings revealed that consumers have a high level of confidence in the application and how far people they benefit from this sort of innovation and how convenient it makes communication.

Keywords: artificial intelligence, google translate, speech recognition, language translation, camera translation, speech to text, text to speech

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Authors: Dina Mohamed Ahmed Mahmoud Bakr

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The concept of a circular economy is gaining increasing attention as a way to promote sustainable economic growth and reduce the environmental impact of human activities. The circular economy is a systemic approach that aims to keep materials and resources in use for as long as possible, minimize waste and pollution, and regenerate natural systems. The purpose of this article is to present a summary of the principles and tactics employed in the circular economy, along with examples of prosperous circular economy projects implemented in different sectors across Japan, Austria, the Netherlands, South Africa, Germany, and the United States. The paper concludes with a discussion of the challenges and opportunities associated with the transition to a circular economy and the policy interventions that can support this transition.

Keywords: circular economy, waste reduction, sustainable development, recycling

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Authors: Dini Dewi Heniarti

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In the past decades, Indonesia has suffered severe terrorist attacks, faced major terrorism challenges and has made impressive progress in countering it. The trend of terrorist groups operating in Indonesia is to focus on ‘soft’ targets. Indonesia has made notable progress in strengthening the legal regime against terrorism, in conformity with the international treaties against terrorism. Further measures are however needed to complete the legal regime building processes. This paper will demonstrate analyze socio yuridical contra and counter terrorism by Indonesia Government.

Keywords: policy, strategy, combatting terrorism, socio juridical, counter and contra terrorism

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Authors: Nwachukwu Ihiejeto Celestine

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Rural poverty in Nigeria has been the bake of the society. It has been a canker worm which has eaten deep into the fabric of Nigerian society. Different models and principles have been applied to eradicate it, such as operation feed the nation, green revolution, NAPEP etc. Little or nothing has been done in the area of entrepreneurship education to tame this monster. It is based on this that the author wants to x-ray the role entrepreneurship education which studies “the process of identifying, bringing a vision to life” could play in the eradication of rural poverty in Nigeria. This will go along in providing appropriate principles for poverty alleviation and eradication in Nigeria. Some selected states in the eastern Geo-political region could be x-rayed in this circumstance. It is hoped that policy makers etc will find the work cogent in formulating and implementing policy decisions.

Keywords: poverty, entrepreneurship, education, Nigeria

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Authors: Sandhra M. Pillai

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This article examines the relevance, difficulties, and potential applications of DNA analysis in the criminal justice system. A potent tool for connecting suspects to crime sites, clearing the innocent of wrongdoing, and resolving cold cases, DNA analysis has transformed forensic investigations. The scientific foundations of DNA analysis, including DNA extraction, sequencing, and statistical analysis, are covered in the article. To guarantee accurate and trustworthy findings, it also discusses the significance of quality assurance procedures, chain of custody, and DNA sample storage. DNA analysis has significantly advanced science, but it also brings up substantial moral and legal issues. To safeguard individual rights and uphold public confidence, privacy concerns, possible discrimination, and abuse of DNA information must be properly addressed. The paper also emphasises the effects of the criminal justice system on people and communities while highlighting the necessity of equity, openness, and fair access to DNA testing. The essay describes the obstacles and future directions for DNA analysis. It looks at cutting-edge technology like next-generation sequencing, which promises to make DNA analysis quicker and more affordable. To secure the appropriate and informed use of DNA evidence, it also emphasises the significance of multidisciplinary collaboration among scientists, law enforcement organisations, legal experts, and policymakers. In conclusion, DNA analysis has enormous potential for improving the course of criminal justice. We can exploit the potential of DNA technology while respecting the ideals of justice, fairness, and individual rights by navigating the ethical, legal, and societal issues and encouraging discussion and collaboration.

Keywords: DNA analysis, DNA evidence, reliability, validity, legal frame, admissibility, ethical considerations, impact, future direction, challenges

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Emmanuela Ngozi Maduka

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In Nigeria, civil-military relations is at its lowest point as a result of the challenges emanating from incessant initiation of military aid to civil authorities (MACA) for internal security operations. This paper is concerned with the question whether it is appropriate for the military to handle internal security crisis with exception to terrorism and armed militia. It analyses the legal framework for MACA in internal security operations which appear to be in contradiction with military tactical and equipment training. The paper argues that the expectation that transitional re-training of the military for internal security operations will reconcile these inconsistencies specifically on the issue of use of force is not practicable and will always pose challenges for both the military and the citizens. Accordingly, this paper adopts a socio-legal methodology for better clarity on the interactions between the legal framework on MACA and military internal security operations. The paper also identifies the lack of effective and proficient paramilitary within the security design of Nigeria as the key issue which results in incessant initiation of MACA and advocates for the establishment of an effective and proficient paramilitary to effectively handle internal security crisis within Nigeria.

Keywords: civil-military relations, MACA, military training, operational challenges, paramilitary, use of force

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Authors: Gianni Jacucci

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Epistemology traditionally finds its place within human research philosophies and methodologies. Artificial intelligence methods pose challenges, particularly given the unresolved relationship between AI and pivotal concepts in social arenas such as hermeneutics and accountability. We begin by examining the essential criteria governing scientific rigor in the human sciences. We revisit the three foundational philosophies underpinning qualitative research methods: empiricism, hermeneutics, and phenomenology. We elucidate the distinct attributes, merits, and vulnerabilities inherent in the methodologies they inspire. The integration of AI, e.g., deep learning algorithms, sparks an interest in evaluating these criteria against the diverse forms of AI architectures. For instance, Interpreted AI could be viewed as a hermeneutic approach, relying on a priori interpretations, while straight AI may be perceived as a descriptive phenomenological approach, processing original and uncontaminated data. This paper serves as groundwork for such explorations, offering preliminary reflections to lay the foundation and outline the initial landscape.

Keywords: artificial intelligence, deep learning, epistemology, qualitative research, methodology, hermeneutics, accountability

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Authors: Helyeh Doutaghi

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In 2005, the doctrine of Responsibility to Protect (R2P) was created by the UN Member States agreeing to not only to have the primary responsibility to protect their civilians from genocide, war crimes, crimes against humanity and ethnic cleansing, but also to be responsible towards those civilians whose State was found manifestly failing in that regard. This paper will assess the doctrine of R2P and will argue that R2P too, just like humanitarian intervention, suffers from a lack of legal basis and political will to implement it. Or better said, it is being selectively used by the hegemon’s power to achieve its political will. In doing so, the origin and development shall be explained. Furthermore, it will be submitted that R2P has failed to achieve its purpose due to the unresolved Security Council’s deadlock. Lastly, the concept of legal morality entailed in R2P and its use in real life cases since 2005 will be examined.

Keywords: responsibility to protect, humanitarian intervention, United Nations, legitimacy, legality

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Authors: Tikumporn Rodkhunmuang

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The importance of ‘international law of governance’ is the means and end to deal with international affairs. This research paper seeks to first study the historical development of international law of governance from the classical period of the international legal framework of global governance until the contemporary period of its framework. Second, the international law of governance is extremely turning into the crucial point in its long history because of the changing of China's foreign policies towards ‘One Belt One Road Initiative’. Third, the proposing model of the existing international law of governance within Chinese characteristics will be the new rules and modalities of modern diplomacy and governed international affairs. Methodologically speaking, this research paper is conducting under mixed methods research, which are also included numerical analysis and theoretical considerations. As a result, this research paper is the critical point of the international legal framework of global governance that changing the diplomatic paradigm as well as turning China into a great-power in international politics. So, this research paper is useful for international legal scholars and diplomats for slightly changing their understanding of the rapidly changing their norms from western norms to the eastern norms of international law. Therefore, the outcome of the research is the modern model of China to make a diplomatic relationship with other countries in the global society.

Keywords: global governance, international law, landscape, one belt one road

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Authors: Bashayer Al-Enezi, Budoor Al-Sabti, Eman Al-Durai, Fatmah Kalban, Meshael Ahmed

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Production planning and control principles are concerned with planning, controlling and balancing all aspects of manufacturing including raw materials, finished goods, production schedules, and equipment requirements. Hence, an effective production planning and control system is very critical to the success of any factory. This project will focus on the application of production planning and control principles on “The National Canned Food Production and Trading Company (NCFP)” factory to find problems or areas for improvement.

Keywords: production planning, operations improvement, inventory management, National Canned Food Production and Trading Company (NCFP)

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Authors: Andrea Trimarchi

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This paper is designed to provide a comprehensive overview on the EU Regulation No. 868/2004 concerning protection against subsidisation and unfair pricing practices regarding non-EU carriers and causing injury to Community air carriers. The analysis will focus, at first, on the exegetical scrutiny of the legal categories encompassed by the Regulation. In addition to that, while considering the peculiarities of such legal instrument, the attention will be addressed on the assessment on its effectiveness. The Regulation, indeed, having received lots of criticism, is in need of a profound revision. In this context, the present work will try to take into account the policy alternatives. In light of the failure of Regulation 868, which is to be seen as the expression of a unilateral and regional approach, there would seem to be the necessity for the aviation sector to reconsider the topic of subsidisation and unfair pricing practices in a more international oriented manner.

Keywords: non-EU airlines, aviation, subisidisation, unfair

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Authors: Huseyin Sinan Gunesli

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Process Safety Management is a disciplined framework for managing the integrity of systems and processes that handle hazardous substances. It relies on good design principles, well-implemented automation systems, and operating and maintenance practices. Alarm Management Systems play a critically important role in the safe and efficient operation of modern industrial plants. In that respect, Alarm Management is one of the critical factors feeding the safe operations of the plants in the manner of applying effective process safety principles. Trans Anatolian Natural Gas Pipeline (TANAP) is part of the Southern Gas Corridor, which extends from the Caspian Sea to Italy. TANAP transports Natural Gas from the Shah Deniz gas field of Azerbaijan, and possibly from other neighboring countries, to Turkey and through Trans Adriatic Pipeline (TAP) Pipeline to Europe. TANAP plays a crucial role in maintaining Energy Security for the region and Europe. In that respect, the application of Process Safety principles is vital to deliver safe, reliable and efficient Natural Gas delivery to Shippers both in the region and Europe. Effective Alarm Management is one of those Process Safety principles which feeds safe operations of the TANAP pipeline. Alarm Philosophy was designed and implemented in TANAP Pipeline according to the relevant standards. However, it is essential to manage the alarms received in the control room effectively to maintain safe operations. In that respect, TANAP has commenced Alarm Management & Rationalization program as of February 2022 after transferring to Plateau Regime, reaching the design parameters. While Alarm Rationalization started, there were more than circa 2300 alarms received per hour from one of the compressor stations. After applying alarm management principles such as reviewing and removal of bad actors, standing, stale, chattering, fleeting alarms, comprehensive review and revision of alarm set points through a change management principle, conducting alarm audits/design verification and etc., it has been achieved to reduce down to circa 40 alarms per hour. After the successful implementation of alarm management principles as specified above, the number of alarms has been reduced to industry standards. That significantly improved operator vigilance to focus on mainly important and critical alarms to avoid any excursion beyond safe operating limits leading to any potential process safety events. Following the ‟What Gets Measured, Gets Managed” principle, TANAP has identified key Performance Indicators (KPIs) to manage Process Safety principles effectively, where Alarm Management has formed one of the key parameters of those KPIs. However, review and analysis of the alarms were performed manually. Without utilizing Alarm Management Software, achieving full compliance with international standards is almost infeasible. In that respect, TANAP has started using one of the industry-wide known Alarm Management Applications to maintain full review and analysis of alarms and define actions as required. That actually significantly empowered TANAP’s process safety principles in terms of Alarm Management.

Keywords: process safety principles, energy security, natural gas pipeline operations, alarm rationalization, alarm management, alarm management application

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Authors: Sharad Shrivastava, Arun Jalan

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In this study tensile testing was performed on randomly oriented short glass fiber/epoxy resin composite specimens which were prepared using hand lay-up method. Samples were tested over a wide range of strain rate/loading rate from 2mm/min to 40mm/min to see the effect on ultimate tensile strength of the composite. A multi layered 'back propagation artificial neural network of supervised learning type' was used to analyze and predict the tensile properties with strain rate and temperature as given input and output as UTS to predict. Various network structures were designed and investigated with varying parameters and network sizes, and an optimized network structure was proposed to predict the UTS of short glass fiber/epoxy resin composite specimens with reasonably good accuracy.

Keywords: glass fiber composite, mechanical properties, strain rate, artificial neural network

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Authors: Hassan Naseh, Javad Roozgard

Abstract:

This paper represents the methodology based on Artificial Intelligent (AI) applied to Liquid Propellant Engine (LPE) optimization. The AI methodology utilized from Adaptive neural Fuzzy Inference System (ANFIS). In this methodology, the optimum objective function means to achieve maximum performance (specific impulse). The independent design variables in ANFIS modeling are combustion chamber pressure and temperature and oxidizer to fuel ratio and output of this modeling are specific impulse that can be applied with other objective functions in LPE design optimization. To this end, the LPE’s parameter has been modeled in ANFIS methodology based on generating fuzzy inference system structure by using grid partitioning, subtractive clustering and Fuzzy C-Means (FCM) clustering for both inferences (Mamdani and Sugeno) and various types of membership functions. The final comparing optimization results shown accuracy and processing run time of the Gaussian ANFIS Methodology between all methods.

Keywords: ANFIS methodology, artificial intelligent, liquid propellant engine, optimization

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Authors: Gerald Steyn

Abstract:

Despite the huge number of identical, tiny, boxy, freestanding houses built by the South African government after the advent of democracy in 1994, squatter camps continue to mushroom, and there is no evidence that the backlog is being reduced. Not only is the wasteful low-density detached-unit approach of the past being perpetuated, but the social, spatial, and economic marginalization is worse than before 1994. The situation is precarious since squatters are vulnerable to fires and flooding. At the same time, the occupants of the housing schemes are trapped far from employment opportunities or any public amenities. Despite these insecurities, the architectural, urban design, and city planning professions are puzzlingly quiet. Design projects address these issues only at the universities, albeit inevitably with somewhat Utopian notions. Geoffrey Payne, the renowned urban housing and urban development consultant and researcher focusing on issues in the Global South, once proclaimed that “we do not have a housing problem – we have a settlement problem.” This dictum was used as the guiding philosophy to conceptualize urban design and architectural principles that foreground the needs of low-income households and allow them to be fully integrated into the larger conurbation. Information was derived from intensive research over two decades, involving frequent visits to informal settlements, historic Black townships, and rural villages. Observations, measured site surveys, and interviews resulted in several scholarly articles from which a set of desirable urban and architectural criteria could be extracted. To formulate culturally appropriate design principles, existing vernacular and informal patterns were analyzed, reconciled with contemporary designs that align with the requirements for the envisaged settlement attributes, and reimagined as residential design principles. Five interrelated design principles are proposed, ranging in scale from (1) Integrating informal settlements into the city, (2) linear neighborhoods, (3) market streets as wards, (4) linear neighborhoods, and (5) typologies and densities for clustered and aggregated patios and courtyards. Each design principle is described, first in terms of its context and associated issues of concern, followed by a discussion of the patterns available to inform a possible solution, and finally, an explanation and graphic illustration of the proposed design. The approach is predominantly bottom-up since each of the five principles is unfolded from existing informal and vernacular practices studied in situ. They are, however, articulated and represented in terms of contemporary design language. Contrary to an idealized vision of housing for South Africa’s low-income urban households, this study proposes actual principles for critical assessment by peers in the tradition of architectural research in design.

Keywords: culturally appropriate design principles, informal settlements, South Africa’s housing backlog, squatter camps

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