Search results for: artificial legal principles
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5227

Search results for: artificial legal principles

4027 Alternator Fault Detection Using Wigner-Ville Distribution

Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

Abstract:

This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

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4026 The Influence of Advertising in the Respect of the Right to Adequate Food: Some Notes regarding the Portuguese Legal Framework

Authors: Susana Almeida

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The right to adequate food is a human right protected under several international human rights treaties of universal or regional application. In addition, this social right is – as we intend to demonstrate – guaranteed under the Portuguese Constitution. Therefore, in order to assure the protection of this right, the Portuguese State must not only abstain from interfering with this human right (negative obligation) but also take action to secure the human right to adequate food (positive obligation). In this context, the Portuguese State has developed several governmental policies, such as taxing sugary drinks, setting the maximum amount of salt in the bread or creating the National Program for the Promotion of Healthy Food. Nevertheless, we intend to demonstrate that special attention should be given to advertising, as advertisements have an extreme influence on the consumers' decisions and hence on the food decisions. In this paper, besides explaining the cross construction of the human right to adequate food, we aim to examine the Advertising Portuguese Code and to study the several provisions that could be held by the Portuguese consumer to challenge some advertisements due to the violation of the right to health and the right to adequate food. Moreover, having in mind the influence of advertising on the food decisions and the serious problems that unhealthy food may bring (e.g., child obesity), one should ask if this legal framework should not be reviewed in order to lay out some restrictions on advertising, namely setting advices like in alcohol advertisements.

Keywords: advertising code, consumer law, right to adequate food, social human right

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4025 Applications of Artificial Intelligence (AI) in Cardiac imaging

Authors: Angelis P. Barlampas

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The purpose of this study is to inform the reader, about the various applications of artificial intelligence (AI), in cardiac imaging. AI grows fast and its role is crucial in medical specialties, which use large amounts of digital data, that are very difficult or even impossible to be managed by human beings and especially doctors.Artificial intelligence (AI) refers to the ability of computers to mimic human cognitive function, performing tasks such as learning, problem-solving, and autonomous decision making based on digital data. Whereas AI describes the concept of using computers to mimic human cognitive tasks, machine learning (ML) describes the category of algorithms that enable most current applications described as AI. Some of the current applications of AI in cardiac imaging are the follows: Ultrasound: Automated segmentation of cardiac chambers across five common views and consequently quantify chamber volumes/mass, ascertain ejection fraction and determine longitudinal strain through speckle tracking. Determine the severity of mitral regurgitation (accuracy > 99% for every degree of severity). Identify myocardial infarction. Distinguish between Athlete’s heart and hypertrophic cardiomyopathy, as well as restrictive cardiomyopathy and constrictive pericarditis. Predict all-cause mortality. CT Reduce radiation doses. Calculate the calcium score. Diagnose coronary artery disease (CAD). Predict all-cause 5-year mortality. Predict major cardiovascular events in patients with suspected CAD. MRI Segment of cardiac structures and infarct tissue. Calculate cardiac mass and function parameters. Distinguish between patients with myocardial infarction and control subjects. It could potentially reduce costs since it would preclude the need for gadolinium-enhanced CMR. Predict 4-year survival in patients with pulmonary hypertension. Nuclear Imaging Classify normal and abnormal myocardium in CAD. Detect locations with abnormal myocardium. Predict cardiac death. ML was comparable to or better than two experienced readers in predicting the need for revascularization. AI emerge as a helpful tool in cardiac imaging and for the doctors who can not manage the overall increasing demand, in examinations such as ultrasound, computed tomography, MRI, or nuclear imaging studies.

Keywords: artificial intelligence, cardiac imaging, ultrasound, MRI, CT, nuclear medicine

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4024 The Promotion of AI Technology to Financial Development in China

Authors: Li Yong

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Using the data of 135 financial institutions in China from 2018 to 2022, this paper deeply analyzes the underlying theoretical mechanism of artificial intelligence (AI) technology promoting financial development and examines the impact of AI technology on the digital transformation performance of financial enterprises. It is found that the level of AI technology has a significant positive impact on the development of finance. Compared with the impact on the expansion of financial scale, AI technology plays a greater role in improving the performance of financial institutions, reflecting the trend characteristics of the current AI technology to promote the evolution of financial structure. By investigating the intermediary transmission effects, we found that AI technology plays a positive role in promoting the performance of financial institutions by reducing operating costs and improving customer satisfaction, but its function in innovating financial products and mitigating financial risks is relatively limited. In addition, the promotion of AI technology in financial development has significant heterogeneity in terms of the type, scale, and attributes of financial institutions.

Keywords: artificial intelligence technology, financial development, China, heterogeneity

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4023 The Impact of Generative AI Illustrations on Aesthetic Symbol Consumption among Consumers: A Case Study of Japanese Anime Style

Authors: Han-Yu Cheng

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This study aims to explore the impact of AI-generated illustration works on the aesthetic symbol consumption of consumers in Taiwan. The advancement of artificial intelligence drawing has lowered the barriers to entry, enabling more individuals to easily enter the field of illustration. Using Japanese anime style as an example, with the development of Generative Artificial Intelligence (Generative AI), an increasing number of illustration works are being generated by machines, sparking discussions about aesthetics and art consumption. Through surveys and the analysis of consumer perspectives, this research investigates how this influences consumers' aesthetic experiences and the resulting changes in the traditional art market and among creators. The study reveals that among consumers in Taiwan, particularly those interested in Japanese anime style, there is a pronounced interest and curiosity surrounding the emergence of Generative AI. This curiosity is particularly notable among individuals interested in this style but lacking the technical skills required for creating such artworks. These works, rooted in elements of Japanese anime style, find ready acceptance among enthusiasts of this style due to their stylistic alignment. Consequently, they have garnered a substantial following. Furthermore, with the reduction in entry barriers, more individuals interested in this style but lacking traditional drawing skills have been able to participate in producing such works. Against the backdrop of ongoing debates about artistic value since the advent of artificial intelligence (AI), Generative AI-generated illustration works, while not entirely displacing traditional art, to a certain extent, fulfill the aesthetic demands of this consumer group, providing a similar or analogous aesthetic consumption experience. Additionally, this research underscores the advantages and limitations of Generative AI-generated illustration works within this consumption environment.

Keywords: generative AI, anime aesthetics, Japanese anime illustration, art consumption

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4022 Foreign Artificial Intelligence Investments and National Security Exceptions in International Investment Law

Authors: Ying Zhu

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Recent years have witnessed a boom of foreign investments in the field of artificial intelligence (AI). Foreign investments provide critical capital for AI development but also trigger national security concerns of host states. A notable example is an increasing number of cases in which the Committee on Foreign Investment in the United States (CFIUS) has denied Chinese acquisitions of US technology companies on national security grounds. On July 19, 2018, the Congress has reached a deal on the final draft of a new provision to strengthen CFIUS’s authority to review overseas transactions involving sensitive US technology. The question is: how to reconcile the emerging tension between, on the one hand, foreign AI investors’ expectations of a predictable investment environment, and on the other hand, host states’ regulatory power on national security? This paper provides a methodology to reconcile this tension under international investment law. Based on an examination, the national security exception clauses in international investment treaties and the application of national security justification in investor-state arbitration jurisprudence, the paper argues that a traditional interpretation of the national security exception, based on the necessity concept in customary international law, fails to take into account new risks faced by countries, including security concerns over strategic industries such as AI. To overcome this shortage, the paper proposes to incorporate an integrated national security clause in international investment treaties, which includes a two-tier test: a ‘self-judging’ test in the pre-establishment period and a ‘proportionality’ test in the post-establishment period. At the end, the paper drafts a model national security clause for future treaty-drafting practice.

Keywords: foreign investment, artificial intelligence, international investment law, national security exception

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4021 Redefining Infrastructure as Code Orchestration Using AI

Authors: Georges Bou Ghantous

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This research delves into the transformative impact of Artificial Intelligence (AI) on Infrastructure as Code (IaaC) practices, specifically focusing on the redefinition of infrastructure orchestration. By harnessing AI technologies such as machine learning algorithms and predictive analytics, organizations can achieve unprecedented levels of efficiency and optimization in managing their infrastructure resources. AI-driven IaaC introduces proactive decision-making through predictive insights, enabling organizations to anticipate and address potential issues before they arise. Dynamic resource scaling, facilitated by AI, ensures that infrastructure resources can seamlessly adapt to fluctuating workloads and changing business requirements. Through case studies and best practices, this paper sheds light on the tangible benefits and challenges associated with AI-driven IaaC transformation, providing valuable insights for organizations navigating the evolving landscape of digital infrastructure management.

Keywords: artificial intelligence, infrastructure as code, efficiency optimization, predictive insights, dynamic resource scaling, proactive decision-making

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4020 India’s Deterrence Program: Defense or Development

Authors: Aneri Mehta, Krunal Mehta

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A doctrine, any doctrine, incorporates a set of beliefs or principles held by a body of persons. A national nuclear doctrine represents, therefore, the collective set of beliefs or principles held by the nation in regard to the utility of its nuclear weapons. India’s foreign policy has been profoundly affected by the nuclear explosions conducted in May 1998. The departure from the professed peaceful nuclear policies has had several implications for India’s defense and foreign policies. The explosions in Pokhran have aggravated tensions in south Asia by disrupting diplomatic initiatives with Pak and China. Diplomacy has been reduced to damage control. The object of India’s nuclear deterrence is to persuade an adversary that the costs to him of seeking a military solution to his political problems with India will far outweigh the benefits. The paper focuses on India’s guidelines governing nuclear policy, development of nuclear materials for effective deterrence as well as civil development purpose. The paper finds that security concerns and technological capabilities are important determinants of whether India develops a nuclear weapons programs, while security concerns, economic capabilities, and domestic politics help to explain the possession of nuclear weapons.

Keywords: foreign policy, nuclear deterrence, nuclear policy, development

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4019 Europe's War on Refugees: The Increased Need for International Protection and Promotion of Migrant Rights

Authors: Rai Friedman

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The recent migrant crisis has revealed an unmet demand for increased international protection and promotion of migrant rights. Europe has found itself at the centre of the migration crisis, being the recipient to the largest number of asylum-seekers since the conclusion of the second World War. Rather than impart a unified humanitarian lens of offering legal protections, the Schengen territory is devising new, preventative measures to confront the influx of asylum-seekers. This paper will focus on the refugee crisis in Europe as it relates to the Central Mediterranean route. To do so, it will outline the increased need for international protection for migrant rights through analyzing historic human rights treaties and conventions; the formation of the current composition of the Schengen area; the evolutionary changes in policies and legal landscapes throughout Europe and the Central Mediterranean route; the vernacular transformation surrounding refugees, migrants, and asylum-seekers; and expose the gaps in international protection. It will also discuss Europe’s critical position, both geographically and conceptually, critiquing the notion of European victimization. Lastly, it will discuss the increased harm of preventative border measures and argue for tangible sustainability solutions through economic programming models in highly vulnerable countries. To do so, this paper will observe a case study in Algeria that has conceded to an economic programming model for forced migrants. In 2017 amid worker shortages, Algeria announced it would grant African migrants’ legal status to become agriculturalists and construction workers. Algeria is one of the few countries along the Central Mediterranean route that has adopted a law to govern foreign nationals’ conditions of entry, stay and circulation. Thereafter, it will provide recommendations for solutions for forced migration along the Central Mediterranean route and advocate for strengthened protections under international law.

Keywords: refugees, migrants, human rights, middle east, Africa, mediterranean, international humanitarian law, policy

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4018 Gandhi and the Judicial Discourse on Moral Rights

Authors: Sunayana Basu Mallik, Shishira Prakash

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The inclusion of Rights of Author (Moral and Personal Rights) resonate the century long battle of rights of authors, composers, performers across developed and developing countries (whether following civil law or common law systems). But, the juxtaposition of author’s special, moral, personal rights within the legislative framework of Copyright statutes (Indian Copyright Act, 1957, applicable statutes) underscores the foundational role of the right which goes to the root of the constitutional structure of India and philosophies of political and literary leaders like Mahatma Gandhi and Gurudeb Rabindranath Tagore. In the pre-independence era when the concept of moral rights was unknown to both England and India’s statutory laws, the strategic deployment method of Gandhi, his ideologies and thoughts scripted the concept of moral rights for authors/composers. The preservation of Rabindric Style (Characteristic Tagore’s vocal renditions) by Vishwabharati University (successor in interest for Tagore’s literary and musical compositions) prior to the Copyright Amendment of 1999 recognizing Author’s Special Rights in line with 6bis of Berne Convention invigorates the fact that the right existed intrinsically prior to the legislative amendment. The paper would in addition to the academic probe carry out an empirical enquiry of the institution’s (Navjivan Trust and Vishwa Bharati University’s) reasoning on the same. The judicial discourse and transforming constitutional ideals between 1950s till date in India alludes Moral Rights to be an essential legal right which have been reasoned by Indian Courts based on the underlying philosophies in culture, customs, religion wherein composers and literary figures have played key roles in enlightening and encouraging the members of society through their literary, musical and artistic work during pre-independence renaissance of India. The discourses have been influenced by the philosophies reflected in the preamble of the Indian constitution, ‘socialist, secular, democratic republic’ and laws of other civil law countries. Lastly, the paper would analyze the adjudication process and witness involvement in ascertaining violations of moral rights and further summarize the indigenous and country specific economic thoughts that often chisel decisions on moral rights of authors, composers, performers which sometimes intersect with author’s right of privacy and against defamation. The exclusivity contracts or other arrangements between authors, composers and publishing companies not only have an erosive effect on each thread of moral rights but irreparably dents factors that promote creativity. The paper would also be review these arrangements in view of the principles of unjust enrichment, unfair trade practices, anti-competitive behavior and breach of Section 27 (Restrain of Trade) of Indian Contract Act, 1857. The paper will thus lay down the three pillars on which author’s rights in India should namely rest, (a) political and judicial discourse evolving principles supporting moral rights of authors; (b) amendment and insertion of Section 57 of the Copyright Act, 1957; (c) overall constitutional framework supporting author’s rights.

Keywords: copyright, moral rights, performer’s rights, personal rights

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4017 Medical Diagnosis of Retinal Diseases Using Artificial Intelligence Deep Learning Models

Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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4016 Maximising the Therapeutic Value of the Mental Capacity Act of Singapore for People Who Lack Legal Capacity

Authors: Kenji Gwee

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The Mental Capacity Act is a new legislation that allows for lasting powers of attorney and court-appointed deputies, in respect of people who lack legal capacity. While the UK Act, after which the Singapore Act is modeled, has been shown to be therapeutic to donors, the Singapore Act differs from its UK counterpart and it is unclear if the Singapore Act can be beneficial to donors as purported. The purpose of this study was to determine what the perceptions of three groups of stakeholders (patients, caregivers and psychiatrists) are about the aspects of the Mental Capacity Act that are therapeutic to donors. In addition, ways to increase the therapeutic value of the Act to donors are sought. A qualitative methodology was used and the research was guided by two theoretical frameworks: therapeutic jurisprudence and an interpretive constructive framework. Interviews with 12 psychiatrists, and focus groups with twenty three patients and seven caregivers showed agreement that, allowing donors to nominate more than one decision- maker, and whistle-blowing mechanisms for recourse for abuse, were therapeutic to donors. To further increase the therapeutic value of the Act, 2 suggestions were made: the Act should provide for (i) advanced healthcare directives- allowing donors to make advance decisions to refuse treatment, or cease existing treatment, and (ii) independent advocacy services- to have a case worker to represent people who have no family or friends and are thus unable to find suitable donees.

Keywords: Mental Capacity Act, therapeutic jurisprudence, qualitative methodology, the UK Act

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4015 Metareasoning Image Optimization Q-Learning

Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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4014 Policy Initiatives That Increase Mass-Market Participation of Fuel Cell Electric Vehicles

Authors: Usman Asif, Klaus Schmidt

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In recent years, the development of alternate fuel vehicles has helped to reduce carbon emissions worldwide. As the number of vehicles will continue to increase in the future, the energy demand will also increase. Therefore, we must consider automotive technologies that are efficient and less harmful to the environment in the long run. Battery Electric Vehicles (BEVs) have gained popularity in recent years because of their lower maintenance, lower fuel costs, and lower carbon emissions. Nevertheless, BEVs show several disadvantages, such as slow charging times and lower range than traditional combustion-powered vehicles. These factors keep many people from switching to BEVs. The authors of this research believe that these limitations can be overcome by using fuel cell technology. Fuel cell technology converts chemical energy into electrical energy from hydrogen power and therefore serves as fuel to power the motor and thus replacing heavy lithium batteries that are expensive and hard to recycle. Also, in contrast to battery-powered electric vehicle technology, Fuel Cell Electric Vehicles (FCEVs) offer higher ranges and lower fuel-up times and therefore are more competitive with electric vehicles. However, FCEVs have not gained the same popularity as electric vehicles due to stringent legal frameworks, underdeveloped infrastructure, high fuel transport, and storage costs plus the expense of fuel cell technology itself. This research will focus on the legal frameworks for hydrogen-powered vehicles, and how a change in these policies may affect and improve hydrogen fueling infrastructure and lower hydrogen transport and storage costs. These policies may also facilitate reductions in fuel cell technology costs. In order to attain a better framework, a number of countries have developed conceptual roadmaps. These roadmaps have set out a series of objectives to increase the access of FCEVs to their respective markets. This research will specifically focus on policies in Japan, Europe, and the USA in their attempt to shape the automotive industry of the future. The researchers also suggest additional policies that may help to accelerate the advancement of FCEVs to mass-markets. The approach was to provide a solid literature review using resources from around the globe. After a subsequent analysis and synthesis of this review, the authors concluded that in spite of existing legal challenges that have hindered the advancement of fuel-cell technology in the automobile industry in the past, new initiatives that enhance and advance the very same technology in the future are underway.

Keywords: fuel cell electric vehicles, fuel cell technology, legal frameworks, policies and regulations

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4013 From Biosensors towards Artificial Intelligence: A New Era in Toxoplasmosis Diagnostics and Therapeutics

Authors: Gehan Labib Abuelenain, Azza Fahmi, Salma Awad Mahmoud

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Toxoplasmosis is a global parasitic disease caused by the protozoan Toxoplasma gondii (T. gondii), with a high infection rate that affects one third of the human population and results in severe implications in pregnant women, neonates, and immunocompromised patients. Anti-parasitic treatments and schemes available against toxoplasmosis have barely evolved over the last two decades. The available T. gondii therapeutics cannot completely eradicate tissue cysts produced by the parasite and are not well-tolerated by immunocompromised patients. This work aims to highlight new trends in Toxoplasma gondii diagnosis by providing a comprehensive overview of the field, summarizing recent findings, and discussing the new technological advancements in toxoplasma diagnosis and treatment. Advancements in therapeutics utilizing trends in molecular biophysics, such as biosensors, epigenetics, and artificial intelligence (AI), might provide solutions for disease management and prevention. These insights will provide tools to identify research gaps and proffer planning options for disease control.

Keywords: toxoplamosis, diagnosis, therapeutics, biosensors, AI

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4012 Managing Gender Based Violence in Nigeria: A Legal Conundrum

Authors: Foluke Dada

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The Prevalence of gender-based violence in Nigeria is of such concern and magnitude that the government has intervened by ratifying international instruments such as the convention on the elimination of all forms of discrimination against women, the declaration on the elimination of violence against women; the protocol to the African charter on human and people’s rights on the rights of women, etc. By promulgating domestic laws that sought to prevent the perpetration of Gender-based violence and also protect victims from future occurrences. Nigeria principally has two legal codes creating criminal offenses and punishments for breach of those offenses, the Criminal Code Law, applying to most states in Southern Nigeria and the Penal Code applying to states in Northern Nigeria. Individual State laws such as the Ekiti State and Lagos State Gender-Based Violence laws are also discussed. This paper addresses Gender-Based Violence in Nigeria and exposes the inadequacies in the laws and their application. The paper postulates that there is a need for more workable public policy that strengthens the social structure fortified by the law in order to engender the necessary changes and provide the opportunity for government to embark on grassroots-based advocacy that engage the victims and sensitize them of their rights and how they can enjoy some of the protections afforded by the laws.

Keywords: gender, violence, human rights, law and policy

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4011 First-Principles Calculations and Thermo-Calc Study of the Elastic and Thermodynamic Properties of Ti-Nb-ZR-Ta Alloy for Biomedical Applications

Authors: M. Madigoe, R. Modiba

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High alloyed beta (β) phase-stabilized titanium alloys are known to have a low elastic modulus comparable to that of the human bone (≈30 GPa). The β phase in titanium alloys exhibits an elastic Young’s modulus of about 60-80 GPa, which is nearly half that of α-phase (100-120 GPa). In this work, a theoretical investigation of structural stability and thermodynamic stability, as well as the elastic properties of a quaternary Ti-Nb-Ta-Zr alloy, will be presented with an attempt to lower Young’s modulus. The structural stability and elastic properties of the alloy were evaluated using the first-principles approach within the density functional theory (DFT) framework implemented in the CASTEP code. The elastic properties include bulk modulus B, elastic Young’s modulus E, shear modulus cʹ and Poisson’s ratio v. Thermodynamic stability, as well as the fraction of β phase in the alloy, was evaluated using the Thermo-Calc software package. Thermodynamic properties such as Gibbs free energy (Δ?⁰?) and enthalpy of formation will be presented in addition to phase proportion diagrams. The stoichiometric compositions of the alloy is Ti-Nbx-Ta5-Zr5 (x = 5, 10, 20, 30, 40 at.%). An optimum alloy composition must satisfy the Born stability criteria and also possess low elastic Young’s modulus. In addition, the alloy must be thermodynamically stable, i.e., Δ?⁰? < 0.

Keywords: elastic modulus, phase proportion diagram, thermo-calc, titanium alloys

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4010 Identifying Confirmed Resemblances in Problem-Solving Engineering, Both in the Past and Present

Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Philippe Blanchard, Simon Richir

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Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

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4009 Nonlinear Aerodynamic Parameter Estimation of a Supersonic Air to Air Missile by Using Artificial Neural Networks

Authors: Tugba Bayoglu

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Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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4008 Design and Characterization of Ecological Materials Based on Demolition and Concrete Waste, Casablanca (Morocco)

Authors: Mourad Morsli, Mohamed Tahiri, Azzedine Samdi

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The Cities are the urbanized territories most favorable to the consumption of resources (materials, energy). In Morocco, the economic capital Casablanca is one of them, with its 4M inhabitants and its 60% share in the economic and industrial activity of the kingdom. In the absence of legal status in force, urban development has favored the generation of millions of tons of demolition and construction waste scattered in open spaces causing a significant nuisance to the environment and citizens. Hence the main objective of our work is to valorize concrete waste. The representative wastes are mainly concrete, concrete, and fired clay bricks, ceramic tiles, marble panels, gypsum, and scrap metal. The work carried out includes: geolocation with a combination of artificial intelligence, GIS, and Google Earth, which allowed the estimation of the quantity of these wastes per site; then the sorting, crushing, grinding, and physicochemical characterization of the collected samples allowed the definition of the exploitation ways for each extracted fraction for integrated management of the said wastes. In the present work, we proceeded to the exploitation of the fractions obtained after sieving the representative samples to incorporate them in the manufacture of new ecological materials for construction. These formulations prepared studies have been tested and characterized: physical criteria (specific surface, resistance to flexion and compression) and appearance (cracks, deformation). We will present in detail the main results of our research work and also describe the specific properties of each material developed.

Keywords: demolition and construction waste, GIS combination software, inert waste recovery, ecological materials, Casablanca, Morocco

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4007 Artificial Neural Network-Based Prediction of Effluent Quality of Wastewater Treatment Plant Employing Data Preprocessing Approaches

Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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4006 [Keynote Speech]: Determination of Naturally Occurring and Artificial Radionuclide Activity Concentrations in Marine Sediments in Western Marmara, Turkey

Authors: Erol Kam, Z. U. Yümün

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Natural and artificial radionuclides cause radioactive contamination in environments, just as the other non-biodegradable pollutants (heavy metals, etc.) sink to the sea floor and accumulate in sediments. Especially the habitat of benthic foraminifera living on the surface of sediments or in sediments at the seafloor are affected by radioactive pollution in the marine environment. Thus, it is important for pollution analysis to determine the radionuclides. Radioactive pollution accumulates in the lowest level of the food chain and reaches humans at the highest level. The more the accumulation, the more the environment is endangered. This study used gamma spectrometry to investigate the natural and artificial radionuclide distribution of sediment samples taken from living benthic foraminifera habitats in the Western Marmara Sea. The radionuclides, K-40, Cs-137, Ra-226, Mn 54, Zr-95+ and Th-232, were identified in the sediment samples. For this purpose, 18 core samples were taken from depths of about 25-30 meters in the Marmara Sea in 2016. The locations of the core samples were specifically selected exclusively from discharge points for domestic and industrial areas, port locations, and so forth to represent pollution in the study area. Gamma spectrometric analysis was used to determine the radioactive properties of sediments. The radionuclide concentration activity values in the sediment samples obtained were Cs-137=0.9-9.4 Bq/kg, Th-232=18.9-86 Bq/kg, Ra-226=10-50 Bq/kg, K-40=24.4–670 Bq/kg, Mn 54=0.71–0.9 Bq/kg and Zr-95+=0.18–0.19 Bq/kg. These values were compared with the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) data, and an environmental analysis was carried out. The Ra-226 series, the Th-232 series, and the K-40 radionuclides accumulate naturally and are increasing every day due to anthropogenic pollution. Although the Ra-226 values obtained in the study areas remained within normal limits according to the UNSCEAR values, the K-40, and Th-232 series values were found to be high in almost all the locations.

Keywords: Ra-226, Th-232, K-40, Cs-137, Mn 54, Zr-95+, radionuclides, Western Marmara Sea

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4005 Programmatic Actions of Social Welfare State in Service to Justice: Law, Society and the Third Sector

Authors: Bruno Valverde Chahaira, Matheus Jeronimo Low Lopes, Marta Beatriz Tanaka Ferdinandi

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This paper proposes to dissect the meanings and / or directions of the State, in order, to present the State models to elaborate a conceptual framework about its function in the legal scope. To do so, it points out the possible contracts established between the State and the Society, since the general principles immanent in them can guide the models of society in force. From this orientation arise the contracts, whose purpose is by the effect to modify the status (the being and / or the opinion) of each of the subjects in presence - State and Society. In this logic, this paper announces the fiduciary contracts and “veredicção”(portuguese word) contracts, from the perspective of semiotics discourse (or greimasian). Therefore, studies focus on the issue of manifest language in unilateral and bilateral or reciprocal relations between the State and Society. Thus, under the biases of the model of the communicative situation and discourse, the guidelines of these contractual relations will be analyzed in order to see if there is a pragmatic sanction: positive when the contract is signed between the subjects (reward), or negative when the contract between they are broken (punishment). In this way, a third path emerges which, in this specific case, passes through the subject-third sector. In other words, the proposal, which is systemic in nature, is to analyze whether, since the contract of the welfare state is not carried out in the constitutional program on fundamental rights: education, health, housing, an others. Therefore, in the structure of the exchange demanded by the society according to its contractual obligations (others), the third way (Third Sector) advances in the empty space left by the State. In this line, it presents the modalities of action of the third sector in the social scope. Finally, the normative communication organization of these three subjects is sought in the pragmatic model of discourse, namely: State, Society and Third Sector, in an attempt to understand the constant dynamics in the Law and in the language of the relations established between them.

Keywords: access to justice, state, social rights, third sector

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4004 Application of Artificial Neural Network for Prediction of Retention Times of Some Secoestrane Derivatives

Authors: Nataša Kalajdžija, Strahinja Kovačević, Davor Lončar, Sanja Podunavac Kuzmanović, Lidija Jevrić

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In order to investigate the relationship between retention and structure, a quantitative Structure Retention Relationships (QSRRs) study was applied for the prediction of retention times of a set of 23 secoestrane derivatives in a reversed-phase thin-layer chromatography. After the calculation of molecular descriptors, a suitable set of molecular descriptors was selected by using step-wise multiple linear regressions. Artificial Neural Network (ANN) method was employed to model the nonlinear structure-activity relationships. The ANN technique resulted in 5-6-1 ANN model with the correlation coefficient of 0.98. We found that the following descriptors: Critical pressure, total energy, protease inhibition, distribution coefficient (LogD) and parameter of lipophilicity (miLogP) have a significant effect on the retention times. The prediction results are in very good agreement with the experimental ones. This approach provided a new and effective method for predicting the chromatographic retention index for the secoestrane derivatives investigated.

Keywords: lipophilicity, QSRR, RP TLC retention, secoestranes

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4003 Evaluation of the Conditions of Managed Aquifer Recharge in the West African Basement Area

Authors: Palingba Aimé Marie Doilkom, Mahamadou Koïta, Jean-michel Vouillamoz, Angelbert Biaou

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Most African populations rely on groundwater in rural areas for their consumption. Indeed, in the face of climate change and strong demographic growth, groundwater, particularly in the basement, is increasingly in demand. The question of the sustainability of water resources in this type of environment is therefore becoming a major issue. Groundwater recharge can be natural or artificial. Unlike natural recharge, which often results from the natural infiltration of surface water (e.g. a share of rainfall), artificial recharge consists of causing water infiltration through appropriate developments to artificially replenish the water stock of an aquifer. Artificial recharge is, therefore, one of the measures that can be implemented to secure water supply, combat the effects of climate change, and, more generally, contribute to improving the quantitative status of groundwater bodies. It is in this context that the present research is conducted with the aim of developing artificial recharge in order to contribute to the sustainability of basement aquifers in a context of climatic variability and constantly increasing water needs of populations. In order to achieve the expected results, it is therefore important to determine the characteristics of the infiltration basins and to identify the areas suitable for their implementation. The geometry of the aquifer was reproduced, and the hydraulic properties of the aquifer were collected and characterized, including boundary conditions, hydraulic conductivity, effective porosity, recharge, Van Genuchten parameters, and saturation indices. The aquifer of the Sanon experimental site is made up of three layers, namely the saprolite, the fissured horizon, and the healthy basement. Indeed, the saprolite and the fissured medium were considered for the simulations. The first results with FEFLOW model show that the water table reacts continuously for the first 100 days before stabilizing. The hydraulic charge increases by an average of 1 m. The further away from the basin, the less the water table reacts. However, if a variable hydraulic head is imposed on the basins, it can be seen that the response of the water table is not uniform over time. The lower the basin hydraulic head, the less it affects the water table. These simulations must be continued by improving the characteristics of the basins in order to obtain the appropriate characteristics for a good recharge.

Keywords: basement area, FEFLOW, infiltration basin, MAR

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4002 Implementation of Gender Policy in the Georgian National Defence: Key Issues and Challenges

Authors: Vephkhvia Grigalashvili

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The defense of Georgia is every citizen’s duty. The present article reviews the principles and standards of gender policy in the Georgian national defense sector. In addition, it looks at mechanisms for ensuring gender equality, going through the relevant Georgian legislation. Furthermore, this work aims to conduct a comparative analysis of defense models of Georgia, Finland, and the Baltic States in order to identify core institutional challenges. The study produced the following findings:(a) The national defense planning is based on the Total Defense approach, which implies a wide involvement of the country`s population in state defense. (b) This political act does not specify gender equality aspects of the Total Defense strategy; (c) According to the Constitution of Georgia, irrespective of gender factors, every citizen of Georgia is legally obliged to participate in state security activities. However, the state has an authority (power of choice) to decide which gender group (male or/and female citizen) must fulfill above mentioned their constitutional commitment. For instance, completion of compulsory military and reserve military services is a male citizen’s duty, whereas professional military service is equally accessible to both genders. The study concludes that effective implementation of the Total Defense concept largely depends on how Georgia uses its capabilities and human resources. Based on the statistical fact that more than 50% of the country’s population are women, Georgia has to elaborate on relevant institutional mechanisms for implementation of gender equality in the national defense organization. In this regard, it would be advisable: (i) to give the legal opportunity to women to serve in compulsory military service, and (ii) to develop labor reserve service as a part of the anti-crisis management system of Georgia.

Keywords: gender in defense organisation, gender mechanisms, gender in defense policy, gender policy

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4001 A Comprehensive Theory of Communication with Biological and Non-Biological Intelligence for a 21st Century Curriculum

Authors: Thomas Schalow

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It is commonly recognized that our present curriculum is not preparing students to function in the 21st century. This is particularly true in regard to communication needs across cultures - both human and non-human. In this paper, a comprehensive theory of communication-based on communication with non-human cultures and intelligences is presented to meet the following three imminent contingencies: communicating with sentient biological intelligences, communicating with extraterrestrial intelligences, and communicating with artificial super-intelligences. The paper begins with the argument that we need to become much more serious about communicating with the non-human, intelligent life forms that already exists around us here on Earth. We need to broaden our definition of communication and reach out to other sentient life forms in order to provide humanity with a better perspective of its place within our ecosystem. The paper next examines the science and philosophy behind CETI (communication with extraterrestrial intelligences) and how it could prove useful even in the absence of contact with alien life. However, CETI’s assumptions and methodology need to be revised in accordance with the communication theory being proposed in this paper if we are truly serious about finding and communicating with life beyond Earth. The final theme explored in this paper is communication with non-biological super-intelligences. Humanity has never been truly compelled to converse with other species, and our failure to seriously consider such intercourse has left us largely unprepared to deal with communication in a future that will be mediated and controlled by computer algorithms. Fortunately, our experience dealing with other cultures can provide us with a framework for this communication. The basic concepts behind intercultural communication can be applied to the three types of communication envisioned in this paper if we are willing to recognize that we are in fact dealing with other cultures when we interact with other species, alien life, and artificial super-intelligence. The ideas considered in this paper will require a new mindset for humanity, but a new disposition will yield substantial gains. A curriculum that is truly ready for the 21st century needs to be aligned with this new theory of communication.

Keywords: artificial intelligence, CETI, communication, language

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4000 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques

Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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3999 The AI Arena: A Framework for Distributed Multi-Agent Reinforcement Learning

Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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3998 The Role of Religion in the Foundation of State [Pakistan]

Authors: Hafiz Atif Iqbal

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It is a confirmed historical fact that Pakistan is an ideological state, and religion has played a very important and vital role in the establishment of Pakistan. This is the reason why the slogan "What does Pakistan mean is "la ilaha illa Allah" is embedded in the heart of every Muslim. This slogan became so popular in the dimensions of India that Movement of Pakistan and this slogan became inseparable, and that is why Quaid-e-Azam said: "Twenty-five percent share in Movement of Pakistan belongs to the creator of this slogan, Asghar Soudai Sialkoti." This slogan later formed the basis of the two-nation theory, whereby the Hindus and Muslims of the sub-continent were declared to be two separate and complete nations, completely different from each other in terms of their religion, affairs, dress, lifestyle, and values. In this regard, on March 23, 1940, at the historic meeting of the Muslim League in Lahore, in which the Lahore Resolution was passed, Quaid-e-Azam said: Islam and Hinduism are not just religions, but actually two different social systems. Therefore, this desire should be called a dream and a dream that Hindus and Muslims will be able to create a common nationality together. These people do not marry each other, nor do they eat at the same table. I say in a nutshell that they belong to two different civilizations, and these civilizations are based on concepts and facts that contradict each other and are against each other. Quaid-e-Azam, while addressing Peshawar in January 1948, said: "We did not demand Pakistan just to get a separate piece of land, but we wanted to get a laboratory where we can test the principles of Islam. The distinction of the concept of Islamic government should be kept in mind that the authority of obedience and loyalty in it is God Almighty, whose practical means of compliance are the rules and principles of the Holy Quran. Only the rules of the Holy Quran can determine the limits of our freedom and restrictions in the state and society. In other words, the Islamic government is the government of Quranic principles and rules. All these facts make it clear that religion has played a fundamental and important role in the establishment of Pakistan.

Keywords: la ilaha illa allah, asghar soudai sialkoti, lahore resolution, quaid-e-azam

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