Search results for: artificial legal principles

Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Abbad

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The electronic and magnetic properties of the cubic praseodymium oxides perovskites PrMnO3 were calculated using the density functional theory (DFT) with both generalized gradient approximation (GGA) and GGA+U approaches, where U is on-site Coulomb interaction correction. The results show a half-metallic ferromagnetic ground state for PrMnO3 in GGA+U approached, while semi-metallic ferromagnetic character is observed in GGA. The results obtained, make the cubic PrMnO3 a promising candidate for application in spintronics.

Keywords: first-principles, electronic properties, transition metal, materials science

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Authors: Mikael Soini, Kari Björn

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Metropolia University of Applied Sciences (MUAS) Information and Communication Technology (ICT) Degree Programme provides full-time Bachelor-level undergraduate studies. ICT Degree Programme has seven different major options; this paper focuses on Health Technology. In Health Technology, a significant curriculum change in 2014 enabled transition from fragmented curriculum including dozens of courses to a new integrated curriculum built around three 30 ECTS themes. This paper focuses especially on the second theme called Customer Oriented Software Applications. From students’ point of view, the goal of this theme is to get familiar with existing health related ICT solutions and systems, understand business around health technology, recognize social and healthcare operating principles and services, and identify customers and users and their special needs and perspectives. This also acts as a background for health related web application development. Built web application is tested, developed and evaluated with real users utilizing versatile user centred development methods. This paper presents experiences obtained from the first implementation of Customer Oriented Software Applications theme. Student feedback was gathered with two questionnaires, one in the middle of the theme and other at the end of the theme. Questionnaires had qualitative and quantitative parts. Similar questionnaire was implemented in the first theme; this paper evaluates how the theme-based integrated curriculum has progressed in Health Technology major by comparing results between theme 1 and 2. In general, students were satisfied for the implementation, timing and synchronization of the courses, and the amount of work. However there is still room for development. Student feedback and teachers’ observations have been and will be used to develop the content and operating principles of the themes and whole curriculum.

Keywords: engineering education, integrated curriculum, learning and teaching methods, learning experience

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Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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Authors: K. Almi, S. Lakel, A. Benchabane, A. Kriker

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Several researches are focused on natural resources for the production of biomaterials intended for technical applications. Date palm wood present one of the world’s most important natural resource. Its use as insulating materials will help to solve the severe environmental and recycling problems which other artificial insulating materials caused. This paper reports the results of an experimental investigation on the thermal proprieties of date palm wood from Algeria. A study of physical, chemical, and mechanical properties is also carried out. The goal is to use this natural material in the manufacture of thermal insulation materials for buildings. The local natural resources used in this study are the date palm fibers from Biskra oasis in Algeria. The results have shown that there is no significant difference in the morphological proprieties of the four types of residues. Their chemical composition differed slightly; with the lowest amounts of cellulose and lignin content belong to Petiole. Water absorption study proved that Rachis has a low value of sorption whereas Petiole and Fibrillium have a high value of sorption what influenced their mechanical properties. It is seen that the Rachis and leaflets exhibit high tensile strength values compared to the other residue. On the other hand, the low value of the bulk density of Petiole and Fibrillium leads to a high value of specific tensile strength and young modulus. It was found that the specific young modulus of Petiole and Fibrillium was higher than that of Rachis and Leaflets and that of other natural fibers or even artificial fibers. Compared to the other materials date palm wood provide a good thermal proprieties thus, date palm wood will be a good candidate for the manufacturing efficient and safe insulating materials.

Keywords: composite materials, date palm fiber, natural fibers, tensile tests, thermal proprieties

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Authors: Susana Sousa Machado

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The debate on the use of religious symbols has been highlighted in modern societies, especially in the field of labour relationships. As litigiousness appears to be growing, the matter requires a careful study from a legal perspective. In this context, a description and critical analysis of the most recent case law is conducted regarding the use of symbols by the employee in the workplace, delivered both by the European Court of Human Rights and by the Court of Justice of the European Union. From this comparative analysis we highlight the most relevant aspects in order to seek a common core regarding the juridical-argumentative approach of case law.

Keywords: religion, religious symbols, workplace, discrimination

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Authors: Muhammad Farooq

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The present article explores the woman's consent as a paramount element in contracting a Muslim marriage. Also, whether permission of the wali (guardian) is a condition per se for a valid nikah (marriage deed) in the eye of law and Sharia. The researcher attempts to treat it through the related issues, inter alia; the marriage guardian, the women's legal capacity to give consent whether she is a virgin or nonvirgin and how that consent is to be given or may be understood. Does her laugh, tears or salience needs a legal interpretation as well as other female manifestations of emotion explained by the Muslim jurists? The silence of Muslim Family Law Ordinance 1961 (hereafter; MFLO 1961) in this regard and the likely reasons behind such silence is also inquired in brief. Germane to the theme, the various cases in which the true notion of woman's consent is interpreted by courts in Pakistan are also examined. In order to address the issue in hand, it is proposed to provide a brief overview of a few contemporary writers' opinions in which the real place of woman's consent in Muslim marriage is highlighted. Key to the idea of young Muslim woman's marriage, the doctrine of kafa'a (equality or suitability) between the man and woman is argued here to be grounded in the patriarchal and social norms. It is, therefore, concluded that such concept was the result of analogical reasoning and has less importance in the present time. As such it is not a valid factor in current scenarios to validate or invalidate marital bonds. A standard qualitative convention is used for this research. Among primary and secondary sources; for examples, Qur'an, Sunnah, Books, Scholarly articles, texts of law and case law is used to point out the researcher's view. In summation, the article is concluded with a bold statement that a young woman being a party to the contract, is absolutely entitled to 'full and free' consent for the Muslim marriage contract. It is the woman, an indispensable partaker and her consent (not the guardian' permission) that does validate or invalidate the said agreement in the eye of contemporary personal law and in Sharia.

Keywords: consent of woman, ejab (declaration), Nikah (marriage agreement), qabol (acceptance), sui juris (of age; independent), wali (guardian), wilayah (guardianship)

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Authors: Kyriaki G. Giota, George Kleftaras

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The purpose of this article is to briefly review the opportunities that social media presents to counselors and psychologists. Particular attention was given to understanding some of the more important common risks inherent in social media and the potential ethical dilemmas which may arise for counselors and psychologists who embrace them in their practice. Key considerations of issues pertinent to an online presence such as multiple relationships, visibility and privacy, maintaining ethical principles and professional boundaries are being discussed.

Keywords: social media, counseling, risks, ethics

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Authors: Valentina Dotto

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Climate change cases used to take the form of statutory disputes rather than constitutional or common law disputes. This changed in 2015, with the Urgenda Climate case in the Netherlands (Urgenda Foundation v. The State of the Netherlands, C/09/456689/HAZA 13-1396) and, the Juliana case in the U.S. (United States v. U.S. District Court for District of Oregon, 17-71692, 9th Cir.). The two cases represent a new type of climate litigation, the claims brought against the federal government were in fact grounded in constitutional rights. The complaints used the Doctrine of Public Trust as a cornerstone for the lawsuits asserting that government's actions against climate change failed to protect essential public trust resources; thus, violating a generation's constitutional rights to life, liberty, and property. The Public Trust Doctrine –a quintessentially American legal concept-, reserved to the States by virtue of the 9th and 10th amendment of the federal Constitution, gives them considerable jurisdiction over natural resources and has been refined by a number of Supreme Court rulings. The Juliana case exemplifies the Doctrine’s evolutionary nature because it attempts to apply it to the federal government, and establish a right to a climate system capable of sustaining human life as a fundamental right protected by a substantive due process. Furthermore, the flexibility of the Doctrine makes it permissible to be applied to a variety of different legal systems as in the Urgenda case. At the very heart of the lawsuits stands the question of who owns the Earth resources and, to what extent the general public can claim the services that the Earth provides as common property. By employing the widest possible definition of the Doctrine of Public Trust these lawsuits tried to redefine environmental resources as a collective right of all people. By doing case analysis, the paper explores how these cases can contribute to widening the public access to information and broadening the public voice in decision making as well as providing a precedent to equal access in seeking justice and redress from environmental failures.

Keywords: climate change, doctrine of public trust, environmental democracy, Juliana case, Urgenda climate case

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: Journey Whitfield

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This study investigates the United States' ongoing violation of Black Americans' fundamental human rights, as evidenced by mass incarceration, social injustice, and economic deprivation. It argues that the U.S. contravenes Article 9 of the International Covenant on Civil and Political Rights through policies that uphold systemic racism. The analysis dissects current practices within the criminal justice system, social welfare programs, and economic policy, uncovering the racially disparate impacts of seemingly race-neutral policies. This study establishes a clear lineage between past systems of oppression – slavery and Jim Crow – and present-day racial disparities, demonstrating their inextricable link. The thesis proposes that only a comprehensive reparations program for Black Americans can begin to redress these systemic injustices. This program must transcend mere financial compensation, demanding structural reforms within U.S. institutions to dismantle systemic racism and promote transformative justice. This study explores potential forms of reparations, drawing upon historical precedents, comparative case studies from other nations, and contemporary debates within political philosophy and legal studies. The research employs both qualitative and quantitative methods. Qualitative methods include historical analysis of legal frameworks and policy documents, as well as discourse analysis of political rhetoric. Quantitative methods involve statistical analysis of socioeconomic data and criminal justice outcomes to expose racial disparities. This study makes a significant contribution to the existing literature on reparations, human rights, and racial injustice in the United States. It offers a rigorous analysis of the enduring consequences of historical oppression and advocates for bold, justice-centered solutions.

Keywords: Black Americans, reparations, mass incarceration, racial injustice, human rights, united states

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Authors: Mohammad H. Yarmohammadian, Masoud Ferdosi, Abbas Haghshenas, Fatemeh Rezaei

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Surgical procedures aim at preserving human life and improving quality of their life. However, there are many potential risk sources that can cause serious harm to patients. For centuries, managers believed that technical competence of a surgeon is the only key to a successful surgery. But over the past decade, risks are considered in terms of process-based safety procedures, teamwork and inter departmental communication. Aims: This study aims to determine how the process- biased surgical risk management should be done in terms of project management tool named ABS (Activity Breakdown Structure). Settings and Design: This study was conducted in two stages. First, literature review and meeting with professors was done to determine principles and framework of surgical risk management. Next, responsible teams for surgical patient journey were involved in following meeting to develop the process- biased surgical risk management. Methods and Material: This study is a qualitative research in which focus groups with the inductive approach is used. Sampling was performed to achieve representativeness through intensity sampling biased on experience and seniority. Analysis Method used: context analysis of interviews and consensus themes extracted from FDG meetings discussion was the analysis tool. Results: we developed the patient journey process in 5 main phases, 24 activities and 108 tasks. Then, responsible teams, transposition and allocated places for performing determined. Some activities and tasks themes were repeated in each phases like patient identification and records review because of their importance. Conclusions: Risk management of surgical departments is significant as this facility is the hospital’s largest cost and revenue center. Good communication between surgical team and other clinical teams outside surgery department through process- biased perspective could improve safety of patient under this procedure.

Keywords: risk management, activity breakdown structure (ABS), surgical department, medical sciences

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Authors: Rima A. Ajlouni

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The discovery of quasi-periodic structures in material science is revealing an exciting new class of symmetries, which has never been explored before. Due to their unique structural and visual properties, these symmetries are drawing interest from many scientific and design disciplines. Especially, in art and architecture, these symmetries can provide a rich source of geometry for exploring new patterns, forms, systems, and structures. However, the structural systems of these complicated symmetries are still posing a perplexing challenge. While much of their local order has been explored, the global governing system is still unresolved. Understanding their unique global long-range order is essential to their generation and application. The recent discovery of dodecagonal quasi-periodic patterns in historical Islamic architecture is generating a renewed interest into understanding the mathematical principles of traditional Islamic geometry. Astonishingly, many centuries before its description in the modern science, ancient artists, by using the most primitive tools (a compass and a straight edge), were able to construct patterns with quasi-periodic formations. These ancient patterns can be found all over the ancient Islamic world, many of which exhibit formations with 5, 8, 10 and 12 quasi-periodic symmetries. Based on the examination of these historical patterns and derived from the generating principles of Islamic geometry, a global multi-level structural model is presented that is able to describe the global long-range order of dodecagonal quasi-periodic formations in Islamic Architecture. Furthermore, this method is used to construct new quasi-periodic tiling systems as well as generating their deflation and inflation rules. This method can be used as a general guiding principle for constructing infinite patches of dodecagon-based quasi-periodic formations, without the need for local strategies (tiling, matching, grid, substitution, etc.) or complicated mathematics; providing an easy tool for scientists, mathematicians, teachers, designers and artists, to generate and study a wide range of dodecagonal quasi-periodic formations.

Keywords: dodecagonal, Islamic architecture, long-range order, quasi-periodi

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Authors: Mohamed Basheer Abdul Atti Hassan

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This research paper will follow the main outlines of the Italian colonization in Libya in a historical geopolitical approach; before we reach the contemporary map. In this study, we are also concerned with following the chain's links, not as drama in time, but as a strategy in place, so that it draws to us a map of power and the distribution of political formations throughout this period within and around Libya. From the sum of these variable distributions and successive balances, we can come up with the basic principles that determined the Italian history in Libya and formed its political entity, which is a compass of guidance and an indication of the future.

Keywords: conflict, Mediterranean, colonization, political history

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Authors: Endalew Jibat, Feyera Senbeta, Tesfaye Zeleke, Fitsum Hagos

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Water governance considers multi-sector participation beyond the state; and for sustainable use of water resources, appropriate laws, policies, regulations, and institutions needs to be developed and put in place. Water policy, a critical and integral instrument of water governance, guided water use schemes and ensures equitable water distribution among users. The Ethiopian Central Rift Valley (CRV) is wealthy of water resources, but these water resources are currently under severe strain owing to an imbalance in human-water interactions. The main aim of the study was to examine the state of water resources governance in the CRV of Ethiopia, and the impact of the Ethiopian Water Resources Management Policy on water governance. Key informant interviews (KII), focused group discussions, and document reviews were used to gather data for the study. The NVivo 11 program was used to organize, code, and analyze the data. The results revealed that water resources governance practices such as water allocation and apportionment, comprehensive and integrated water management plans, water resources protection, and conservation activities were rarely implemented. Water resources management policy mechanisms were not fully put in place. Lack of coherence in water policy implementation, absence of clear roles and responsibilities of stakeholders, absence of transparency and accountability in irrigation water service delivery, and lack of meaningful participation of key actors in water governance decision-making were the primary shortcomings observed. Factors such as over-abstraction, deterioration of buffer zone, and chemical erosion from surrounding farming have contributed to the reduction in water volume and quality in the CRV. These challenges have influenced aquatic ecosystem services and threaten the livelihoods of the surrounding communities. Hence, reforms relating to policy coherence and enforcement, stakeholder involvement, water distribution strategies, and the application of water governance principles must be given more emphasis.

Keywords: water resources, irrigation, governance, water allocation, governance principles, stakeholders engagement, central rift valley

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Authors: N. Gopalakrishna Kini, Ranjana Paleppady, Akshata K. Naik

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Password authentication is one of the widely used methods to achieve authentication for legal users of computers and defense against attackers. There are many different ways to authenticate users of a system and there are many password cracking methods also developed. This paper is mainly to propose how best password cracking can be performed on a CPU-GPGPU based system. The main objective of this work is to project how quickly a password can be cracked with some knowledge about the computer security and password cracking if sufficient security is not incorporated to the system.

Keywords: GPGPU, password cracking, secret key, user authentication

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Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

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The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

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Authors: Joseph Falzon, Margaret Nelson

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Background: Regeneration and re-use of abandoned historic buildings present a continuous challenge for policy makers and stakeholders in the tourism and leisure industry. Obsolete historic buildings provide great potential for tourism and leisure accommodation, presenting unique heritage experiences to travellers and host communities. Contemporary demands in the hospitality industry continuously require higher standards, some of which are in conflict with heritage conservation principles. Objective: The aim of this research paper is to critically discuss regeneration policies with stakeholders of the tourism and leisure industry and to examine current practices in policy development and the resultant impact of policies on the Maltese tourism and leisure industry. Research Design: Six semi-structured interviews with stakeholders involved in the tourism and leisure industry participated in the research. A number of measures were taken to reduce bias and thus improve trustworthiness. Clear statements of the purpose of the research study were provided at the start of each interview to reduce expectancy bias. The interviews were semi-structured to minimise interviewer bias. Interviewees were allowed to expand and elaborate as necessary, with only necessary probing questions, to allow free expression of opinion and practices. Interview guide was submitted to participants at least two weeks before the interview to allow participants to prepare for the interview and prevent recall bias during the interview as much as possible. Interview questions and probes contained both positive and negative aspects to prevent interviewer bias. Policy documents were available during the interview to prevent recall bias. Interview recordings were transcribed ‘intelligent’ verbatim. Analysis was carried out using thematic analysis with the coding frame developed independently by two researchers. All phases of the study were governed by research ethics. Findings: Findings were grouped in main themes: financing of regeneration, governance, legislation and policies. Other key issues included value of historic buildings and approaches for regeneration. Whist regeneration of historic buildings was noted, participants discussed a number of barriers that hindered regeneration. Stakeholders identified gaps in policies and gaps at policy implementation stages. European Union funding policies facilitated regeneration initiatives but funding criteria based on economic deliverables presented the intangible heritage gap. Stakeholders identified niche markets for heritage tourism accommodation. Lack of research-based policies was also identified. Conclusion: Potential of regeneration is hindered by inadequate legal framework that supports contemporary needs of the tourism industry. Policies should be developed by active stakeholder participation. Adequate funding schemes have to support the tangible and intangible components of the built heritage.

Keywords: governance, historic buildings, policy, tourism

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Authors: Vanja Skoric

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The paper examines whether the impacts of artificial intelligence (AI) can be meaningfully addressed through the rights-based approach to AI design, investigating in particular how the inclusive, participatory process of assessing the AI impact would make this viable. There is a significant gap between envisioning rights-based AI systems and their practical application. Plausibly, internalizing human rights approach within AI design process might be achieved through identifying and assessing implications of AI features human rights, especially considering the case of vulnerable individuals and communities. However, there is no clarity or consensus on how such an instrument should be operationalised to usefully identify the impact, mitigate harms and meaningfully ensure relevant stakeholders’ participation. In practice, ensuring the meaningful inclusion of those individuals, groups, or entire communities who are affected by the use of the AI system is a prerequisite for a process seeking to assess human rights impacts and risks. Engagement in the entire process of the impact assessment should enable those affected and interested to access information and better understand the technology, product, or service and resulting impacts, but also to learn about their rights and the respective obligations and responsibilities of developers and deployers to protect and/or respect these rights. This paper will provide an overview of the study and practice of the participatory design process for AI, including inclusive impact assessment, its main elements, propose a framework, and discuss the lessons learned from the existing theory. In addition, it will explore pathways for enhancing and promoting individual and group rights through such engagement by discussing when, how, and whom to include, at which stage of the process, and what are the pre-requisites for meaningful and engaging. The overall aim is to ensure using the technology that works for the benefit of society, individuals, and particular (historically marginalised) groups.

Keywords: rights-based design, AI impact assessment, inclusion, harm mitigation

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Authors: Muthukuda Arachchige Dona Shiroma Jeeva Shirajanie Niriella

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The necessity of protection of the rights of victims of crime is a matter of concerns today. In the criminal justice system, child victims who are subjected to sexual abuse/violence are more vulnerable than the other crime victims. When they go to the police to lodge the complaint and until the end of the court proceedings, these victims are re-victimized in the criminal justice system. The rights of the suspects, accused and convicts are recognized and guaranteed by the constitution under fair trial norm, contemporary penal laws where crime is viewed as an offence against the State and existing criminal justice system in many jurisdictions including Sri Lanka. In this backdrop, a reasonable question arises as to whether the existing criminal justice system, especially which follow the adversarial mode of judicial trial protect the fair trial norm in the criminal justice process. Therefore, this paper intends to discuss the rights of the sexually abused child victims in the criminal justice system in order to restore imbalance between the rights of the wrongdoer and victim and suggest legal reforms to strengthen their rights in the criminal justice system which is essential to end secondary victimization. The paper considers Sri Lanka as a sample to discuss this issue. The paper looks at how the child victims are marginalized in the traditional adversarial model of the justice process, whether the contemporary penal laws adequately protect the right of these victims and whether the current laws set out the provisions to provide sufficient assistance and protection to them. The study further deals with the important principles adopted in international human rights law relating to the protection of the rights of the child victims in sexual offences cases. In this research paper, rights of the child victims in the investigation, trial and post-trial stages in the criminal justice process will be assessed. This research contains an extensive scrutiny of relevant international standards and local statutory provisions. Case law, books, journal articles, government publications such as commissions’ reports under this topic are rigorously reviewed as secondary resources. Further, randomly selected 25 child victims of sexual offences from the decided cases in last two years, police officers from 5 police divisions where the highest numbers of sexual offences were reported in last two years and the judicial officers both Magistrates and High Court Judges from the same judicial zones are interviewed. These data will be analyzed in order to find out the reasons for this specific sexual victimization, needs of these victims in various stages of the criminal justice system, relationship between victimization and offending and the difficulties and problems that these victims come across in criminal justice system. The author argues that the child victims are considerably neglected and their rights are not adequately protected in the adversarial model of the criminal justice process.

Keywords: child victims of sexual violence, criminal justice system, international standards, rights of child victims, Sri Lanka

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Andrey M. Norov, Denis A. Pagaleshkin, Pavel S. Fedotov, Viacheslav M. Kolpakov, Konstantin G. Gorbovskiy

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The article focuses on the latest research and developments (R&D) aimed at the development of plants for production of complex phosphorus-containing fertilizers which are in line with the principles of the best available techniques (BAT). The advantages of the implemented technical solutions are given. The paper describes developed options of flexible technologies for schemes with DGD (drum granulator dryer) and for schemes with AG-DD (ammoniator-granulator and dryer drum).

Keywords: ammoniator-granulator drier drum, phosphorus-containing fertilizer technology, PK, PKS and NPKS-fertilizers, WPA

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Authors: Monika Soni, Chandra Bhattacharya, Siraj Ahmed Ahmed, Prafulla Dutta

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Dengue is now a globally important arboviral disease. Extensive vector surveillance has already established A.aegypti as a primary vector, but A.albopictus is now accelerating the situation through gradual adaptation to human surroundings. Global destabilization and gradual climatic shift with rising in temperature have significantly expanded the geographic range of these species These versatile vectors also host Chikungunya, Zika, and yellow fever virus. Biggest challenge faced by endemic countries now is upsurge in co-infection reported with multiple serotypes and virus co-circulation. To foster vector control interventions and mitigate disease burden, there is surge for knowledge on vector susceptibility and viral tolerance in response to multiple infections. To address our understanding on transmission dynamics and reproductive fitness, both the vectors were exposed to single and dual combinations of all four dengue serotypes by artificial feeding and followed up to third generation. Artificial feeding observed significant difference in feeding rate for both the species where A.albopictus was poor artificial feeder (35-50%) compared to A.aegypti (95-97%) Robust sequential screening of viral antigen in mosquitoes was followed by Dengue NS1 ELISA, RT-PCR and Quantitative PCR. To observe viral dissemination in different mosquito tissues Indirect immunofluorescence assay was performed. Result showed that both the vectors were infected initially with all dengue(1-4)serotypes and its co-infection (D1 and D2, D1 and D3, D1 and D4, D2 and D4) combinations. In case of DENV-2 there was significant difference in the peak titer observed at 16th day post infection. But when exposed to dual infections A.aegypti supported all combinations of virus where A.albopictus only continued single infections in successive days. There was a significant negative effect on the fecundity and fertility of both the vectors compared to control (PANOVA < 0.001). In case of dengue 2 infected mosquito, fecundity in parent generation was significantly higher (PBonferroni < 0.001) for A.albopicus compare to A.aegypti but there was a complete loss of fecundity from second to third generation for A.albopictus. It was observed that A.aegypti becomes infected with multiple serotypes frequently even at low viral titres compared to A.albopictus. Possible reason for this could be the presence of wolbachia infection in A.albopictus or mosquito innate immune response, small RNA interference etc. Based on the observations it could be anticipated that transovarial transmission may not be an important phenomenon for clinical disease outcome, due to the absence of viral positivity by third generation. Also, Dengue NS1 ELISA can be used for preliminary viral detection in mosquitoes as more than 90% of the samples were found positive compared to RT-PCR and viral load estimation.

Keywords: co-infection, dengue, reproductive fitness, viral quantification

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Authors: Hitakshi Mahendru, Advait Tambe, Simran Chandok, Niharika Sanadhya

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After the Second World War had come to an end, the Founding Fathers of the United Nations recognized a need for a supreme peacekeeping mechanism to act as a mediator between nations and moderate disputes that might blow up, if left unchecked. It has been more than seven decades since the establishment of the International Court of Justice (ICJ). When it was created, there were certain aim and objectives that the ICJ was intended to achieve. However, in today’s world, with change in political dynamics and international relations between countries, the ICJ has not succeeded in achieving several of these objectives. The ICJ is the only body in the international scenario that has the authority to regulate disputes between countries. However, in recent times, with countries like China disregarding the importance of the ICJ, there is no hope for the ICJ to command respect from other nations, thereby sending ICJ on a slow, yet steady path towards redundancy. The authority of the judgements given by the International Court of Justice, which is one of the main pillars of the United Nations, is questionable due to the forthcoming reactions from various countries on public platforms. The ICJ’s principal role within the United Nations framework is to settle peacefully international/bilateral disputes between the states that come under its jurisdiction and in accordance with the principles laid down in international law. By shedding light on the public backlash from the Chinese Government to the recent South China Sea judgement, we see the decreasing relevance of the ICJ in the contemporary world scenario. Philippines and China have wrangled over territory in the South China Sea for centuries but after the recent judgement the tension has reached an all-time high with China threatening to prosecute anybody as trespassers while continuing to militarise the disputed area. This paper will deal with the South China Sea judgement and the manner in which it has been received by the Chinese Government. Also, it will look into the consequences of counter-back. The authors will also look into the Marshall Island matter and propose a model judgement, in accordance with the principles of international law that would be the most suited for the given situation. Also, the authors will propose amendments in the working of the Security Council to ensure that the Marshal Island judgement is passed and accepted by the countries without any contempt.

Keywords: International Court of Justice, international law, Marshall Islands, South China Sea, United Nations Charter

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Authors: Maryam Mohammadi, Mohammadjavad Mahdavinejad, Mojtaba Ansari

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The main driving force for increasing movement towards the design of High-Performance Buildings (HPB) are building codes and rating systems that address the various components of the building and their impact on the environment and energy conservation through various methods like prescriptive methods or simulation-based approaches. The methods and tools developed to meet these needs, which are often based on building performance simulation tools (BPST), have limitations in terms of compatibility with the integrated design process (IDP) and HPB design, as well as use by architects in the early stages of design (when the most important decisions are made). To overcome these limitations in recent years, efforts have been made to develop Design Decision Support Systems, which are often based on artificial intelligence. Numerous needs and steps for designing and developing a Decision Support System (DSS), which complies with the early stages of energy-efficient architecture design -consisting of combinations of different methods in an integrated package- have been listed in the literature. While various review studies have been conducted in connection with each of these techniques (such as optimizations, sensitivity and uncertainty analysis, etc.) and their integration of them with specific targets; this article is a critical and holistic review of the researches which leads to the development of applicable systems or introduction of a comprehensive framework for developing models complies with the IDP. Information resources such as Science Direct and Google Scholar are searched using specific keywords and the results are divided into two main categories: Simulation-based DSSs and Meta-simulation-based DSSs. The strengths and limitations of different models are highlighted, two general conceptual models are introduced for each category and the degree of compliance of these models with the IDP Framework is discussed. The research shows movement towards Multi-Level of Development (MOD) models, well combined with early stages of integrated design (schematic design stage and design development stage), which are heuristic, hybrid and Meta-simulation-based, relies on Big-real Data (like Building Energy Management Systems Data or Web data). Obtaining, using and combining of these data with simulation data to create models with higher uncertainty, more dynamic and more sensitive to context and culture models, as well as models that can generate economy-energy-efficient design scenarios using local data (to be more harmonized with circular economy principles), are important research areas in this field. The results of this study are a roadmap for researchers and developers of these tools.

Keywords: integrated design process, design decision support system, meta-simulation based, early stage, big data, energy efficiency

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Authors: Surendra Mund

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At the beginning, the physical entity force was defined mathematically by Sir Isaac Newton in his Principia Mathematica as F ⃗=(dp ⃗)/dt in form of his second law of motion. Newton also defines his Universal law of Gravitational force exist in same outstanding book, but at the end of 20th century and beginning of 21st century, we have tried a lot to specify and unify four or five Fundamental forces or Interaction exist in universe, but we failed every time. Usually, Gravity creates problems in this unification every single time, but in my previous papers and presentations, I defined and derived Field and force equations for Gravitational like Interactions for each and every kind of central systems. This force is named as Variational Force by me, and this force is generated by variation in the scalar field density around the body. In this particular paper, at first, I am specifying which type of Interactions are Fundamental in Universal sense (or in all type of central systems or bodies predicted by my N-time Inflationary Model of Universe) and then unify them in Universal framework (defined and derived by me as Universal Mechanics in a separate paper) as well. This will also be valid in Universal dynamical sense which includes inflations and deflations of universe, central system relativity, Universal relativity, ϕ-ψ transformation and transformation of spin, physical perception principle, Generalized Fundamental Dynamical Law and many other important Generalized Principles of Generalized Quantum Mechanics (GQM) and Central System Theory (CST). So, In this article, at first, I am Generalizing some Fundamental Principles, and then Unifying Variational Forces (General form of Gravitation like Interactions) and Flow Generated Force (General form of EM like Interactions), and then Unify all Fundamental Forces by specifying Weak and Strong Interactions in form of more basic terms - Variational, Flow Generated and Transformational Interactions.

Keywords: Central System Force, Disturbance Force, Flow Generated Forces, Generalized Nuclear Force, Generalized Weak Interactions, Generalized EM-Like Interactions, Imbalance Force, Spin Generated Forces, Transformation Generated Force, Unified Force, Universal Mechanics, Uniform And Non-Uniform Variational Interactions, Variational Interactions

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Eyasu Markos Woldesemayat, Paolo Vincenzo Genovese

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In recent years with an increase in the concentration of Green House Gases (GHG), Climate Change (CC) externalities are mounting, regardless of governments, are scrambling to implement mitigation and adaptation measures. With multiple social, economic and environmental benefits, Green Infrastructure (GI) has evolved as a highly valuable policy tool to promote sustainable development and smart growth by meeting multiple objectives towards quality of life. However, despite the wide range of benefits, it's uptake in African cities such as Addis Ababa is very low due to several constraining factors. This study, through content analysis and key informant interviews, examined barriers for the uptake of GI among spatial planners in Addis Ababa. Added to this, the study has revealed that the spatial planners had insufficient knowledge about GI planning principles such as multi-functionality, integration, and connectivity, and multiscale. The practice of implementing these holistic principles in urban spatial planning is phenomenally nonexistent. The findings also revealed 20 barriers categorized under four themes, i.e., institutional, socio-cultural, resource, and cognitive barriers. Similarly, it was identified that institutional barriers (0.756), socio-cultural barriers (0.730), cognitive barriers (0.700) and resource barriers (0.642), respectively, are the foremost impending factors for the promotion of GI in Addis Ababa. It was realized that resource barriers were the least constraining factor for enshrining the GI uptake in the city. Strategies to hasten the adoption of GI in the city mainly focus on improving political will, harmonization sectorial plans, improve spatial planning and implementation practice, prioritization of GI in all planning activities, enforcement of environmental laws, introducing collaborative GI governance, creating strong and stable institutions and raising awareness on the need to conserve environment and CC externalities through education and outreach mechanisms.

Keywords: Addis Ababa, climate change, green infrastructure, spatial planning, spatial planners

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Anushtha Saxena

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This paper examines the process of data monetisation bye-commerce companies operating in India. Data monetisation is collecting, storing, and analysing consumers’ data to use further the data that is generated for profits, revenue, etc. Data monetisation enables e-commerce companies to get better businesses opportunities, innovative products and services, a competitive edge over others to the consumers, and generate millions of revenues. This paper analyses the issues and challenges that are faced due to the process of data monetisation. Some of the issues highlighted in the paper pertain to the right to privacy, protection of data of e-commerce consumers. At the same time, data monetisation cannot be prohibited, but it can be regulated and monitored by stringent laws and regulations. The right to privacy isa fundamental right guaranteed to the citizens of India through Article 21 of The Constitution of India. The Supreme Court of India recognized the Right to Privacy as a fundamental right in the landmark judgment of Justice K.S. Puttaswamy (Retd) and Another v. Union of India . This paper highlights the legal issue of how e-commerce businesses violate individuals’ right to privacy by using the data collected, stored by them for economic gains and monetisation and protection of data. The researcher has mainly focused on e-commerce companies like online shopping websitesto analyse the legal issue of data monetisation. In the Internet of Things and the digital age, people have shifted to online shopping as it is convenient, easy, flexible, comfortable, time-consuming, etc. But at the same time, the e-commerce companies store the data of their consumers and use it by selling to the third party or generating more data from the data stored with them. This violatesindividuals’ right to privacy because the consumers do not know anything while giving their data online. Many times, data is collected without the consent of individuals also. Data can be structured, unstructured, etc., that is used by analytics to monetise. The Indian legislation like The Information Technology Act, 2000, etc., does not effectively protect the e-consumers concerning their data and how it is used by e-commerce businesses to monetise and generate revenues from that data. The paper also examines the draft Data Protection Bill, 2021, pending in the Parliament of India, and how this Bill can make a huge impact on data monetisation. This paper also aims to study the European Union General Data Protection Regulation and how this legislation can be helpful in the Indian scenarioconcerning e-commerce businesses with respect to data monetisation.

Keywords: data monetization, e-commerce companies, regulatory framework, GDPR

Procedia PDF Downloads 111