Search results for: legal artificial intelligence

Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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Authors: Aya Salama

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Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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Authors: Muhammad Fathurridho

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Grammar as a rule used by every language to be understood by everyone is always related to syntax and morphology. Arabic grammar is different with another languages’ grammars. It has more rules and difficulties. This paper aims to investigate and describe the English grammatical errors of machine translation systems in translating Arabic sentences, including declarative, exclamation, imperative, and interrogative sentences, specifically in year 2018 which can be supported with artificial intelligence’s role. The Arabic sample sentences which are divided into two; verbal and nominal sentence of several Arabic published texts will be examined as the source language samples. The translated sentences done by several popular online machine translation systems, including Google Translate, Microsoft Bing, Babylon, Facebook, Hellotalk, Worldlingo, Yandex Translate, and Tradukka Translate are the material objects of this research. Descriptive method that will be taken to finish this research will show the grammatical errors of English target language, and classify them. The conclusion of this paper has showed that the grammatical errors of machine translation results are varied and generally classified into morphological, syntactical, and semantic errors in all type of Arabic words (Noun, Verb, and Particle), and it will be one of the evaluations for machine translation’s providers to correct them in order to improve their understandable results.

Keywords: Arabic, Arabic-English translation, machine translation, grammatical errors

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Muller Salah Zaky Toudry

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The complexity arises in defining the development great due to its notion, based on inherent market situations and their requirements, the diverse stakeholders itself and their desired output. An quantitative survey based totally approach was adopted in this optimistic examine. A questionnaire-primarily based survey was performed for the assessment of production fine belief and expectations within the context of excellent development technique. The survey feedback of experts of the leading creation corporations/companies of Pakistan production industry have been analyzed. The monetary ability, organizational shape, and production revel in of the construction companies shaped basis for their selection. The great belief become located to be venture-scope-orientated and taken into consideration as an extra cost for a production assignment. Any excellent improvement technique changed into expected to maximize the profit for the employer, via enhancing the productiveness in a creation project. The look at is beneficial for the construction specialists to evaluate the prevailing creation great perception and the expectations from implementation of any pleasant improvement approach in production projects.

Keywords: correlation analysis, lean construction tools, lean construction, logistic regression analysis, risk management, safety construction quality, expectation, improvement, perception client loyalty, NPS, pre-construction, schedule reduction

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Authors: Dalia Rimawi, Walid Salameh, Amal Al-Omari, Hadeel AbdelKhaleq

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Predication of Survival time of patients with cancer, is a core factor that influences oncologist decisions in different aspects; such as offered treatment plans, patients’ quality of life and medications development. For a long time proportional hazards Cox regression (ph. Cox) was and still the most well-known statistical method to predict survival outcome. But due to the revolution of data sciences; new predication models were employed and proved to be more flexible and provided higher accuracy in that type of studies. Artificial neural network is one of those models that is suitable to handle time to event predication. In this study we aim to compare ph Cox regression with artificial neural network method according to data handling and Accuracy of each model.

Keywords: Cox regression, neural networks, survival, cancer.

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Authors: Hae-Won Seo, Yong-Gu Lee

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Recent progress in the next generation of automobile technology is geared towards incorporating information technology into cars. Collectively called smart cars are bringing intelligence to cars that provides comfort, convenience and safety. A branch of smart cars is connected-car system. The key concept in connected-cars is the sharing of driving information among cars through decentralized manner enabling collective intelligence. This paper proposes a foundation of the information model that is necessary to define the driving information for smart-cars. Road conditions are modeled through a unique data structure that unambiguously represent the time variant traffics in the streets. Additionally, the modeled data structure is exemplified in a navigational scenario and usage using UML. Optimal driving route searching is also discussed using the proposed data structure in a dynamically changing road conditions.

Keywords: connected-car, data modeling, route planning, navigation system

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Authors: Sumeyra Yakar

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The idea of this research had its genesis from the writer's interest in Shi'i school and religio-political atmosphere in contemporary Iran. The research aims to identify how the past dynamics between political and legal figures and their relationship between each other affect contemporary relationship between political and religious authorities at the local and global level. It attempts to explore religio-politic Shi'i figures and their relationship with the official jurisprudence from the 15th century to the contemporary period. The mutual interaction between the opinion and acts of political figures and jurisprudential institutions enlightens the role of religious values to control the mass population. After the collapse of the Safawīd Dynasty, Shi'i believers lost their political guardian and legal independence, and the situation gave them the inspiration to create unique ideologies or political approaches to solve the governance crisis. The analysis of authoritative political figures and their scholastic contributions elucidate the connection between political powers and religious doctrines under the protection of sectarian oriented theocratic governments. Additionally, understanding the incremental influence of political (historical) Shi'i figures into religious doctrines shed lights on the chronological development of peculiar government style and authoritative hierarchy in contemporary Shi’i communities. The research as being interdisciplinary one offers to create an academic awareness between legal and political factors in Shi’i school of thought and encompasses political, religious, social, financial and cultural atmospheres of the countries in which the political figures lived. The Iranian regime enshrines the principle of vilāyāt-i faqīh (guardianship of the jurist) which enables jurists to solve the conflict between law as an ideal system, in theory, and law in practice. The paper aims to show how the religious, educational system works in harmony with the governmental authorities with the concept of vilāyāt-i faqīh in Iran and contributes to the creation of religious custom in the society. Contemporary relationship between the political figures and religious authorities in Iran will be explained by religio-legal dimensions. The methodology that will be applied by the study has been chosen in order to acquire information and deduce conclusions from the opinions of the scholars. Thus, the research method is mainly descriptive and qualitative. Three lines of description are pursued throughout the study; the explanation of political ideas belonging to the religio-political figures theoretically depending on written texts; the description of approaches adopted by contemporary Iranian and Saudi scholars relating to the legal systems (theoretically); and the explanation of the responses of governmental authorities.

Keywords: clergy (‘ulamā), guardianship of the jurist (vilāyāt-i faqīh), Iran, Shi’i figures

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Authors: Ahmed Krobba, Meriem Touzene, Mohamed Debeyche

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The wireless communications system (5G) will provide more diverse applications and higher quality services for users compared to the long-term evolution 4G (LTE). 5G uses a higher carrier frequency, which suffers from information loss in 5G coverage. Most 5G users often cannot obtain high-quality communications due to transmission channel noise and channel complexity. Physical Uplink Control Channel (PUCCH-NR: Physical Uplink Control Channel New Radio) plays a crucial role in 5G NR telecommunication technology, which is mainly used to transmit link control information uplink (UCI: Uplink Control Information. This study based of evaluating the performance of channel physical uplink control PUCCH-NR under low Signal-to-Noise Ratios with various antenna numbers reception. We propose the artificial intelligence approach based on deep neural networks (Deep Learning) to estimate the PUCCH-NR channel in comparison with this approach with different conventional methods such as least-square (LS) and minimum-mean-square-error (MMSE). To evaluate the channel performance we use the block error rate (BLER) as an evaluation criterion of the communication system. The results show that the deep neural networks method gives best performance compared with MMSE and LS

Keywords: 5G network, uplink (Uplink), PUCCH channel, NR-PUCCH channel, deep learning

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Authors: Abrar Abuzaid, Maha Alaaeddine, Haya Alesayi

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This project is centered around understanding the usage and impact of Alexa, Amazon's popular virtual assistant, in everyday life. Alexa, known for its integration into devices like Amazon Echo, offers functionalities such as voice interaction, media control, providing real-time information, and managing smart home devices. Our primary focus is to conduct a straightforward survey aimed at uncovering how people use Alexa in their daily routines. We plan to reach out to a wide range of individuals to get a diverse perspective on how Alexa is being utilized for various tasks, the frequency and context of its use, and the overall user experience. The survey will explore the most common uses of Alexa, its impact on daily life, features that users find most beneficial, and improvements they are looking for. This project is not just about collecting data but also about understanding the real-world applications of a technology like Alexa and how it fits into different lifestyles. By examining the responses, we aim to gain a practical understanding of Alexa's role in homes and possibly in workplaces. This project will provide insights into user satisfaction and areas where Alexa could be enhanced to meet the evolving needs of its users. It’s a step towards connecting technology with everyday life, making it more accessible and user-friendly

Keywords: Amazon Alexa, artificial intelligence, smart speaker, natural language processing

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Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

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Authors: Ana Lambelho

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In an economic crisis such as the one that shook (and still shake) Europe, one does not question the importance of the measures that encourage the hiring and integration of young people into the labour market. In the mentioned context, enterprises tend to reduce the cost of labour and to seek flexible contracting instruments. The professional internships allow innovation and creativity at low cost, because, as they are not labour contracts, the enterprises do not have to respect the minimum standards related to wages, working time duration and so on. In Portugal, we observe a widespread existence of training contracts in which the trainee worked several hours without salary or was paid below the legally prescribed for the function and the work period. For this reason, under the tripartite agreement for a new system of regulation of labour relations, employment policies and social protection, between the Government and the social partners, in June 2008, foresaw a prohibition of professional internships unpaid and the legal regulation of the mandatory internships for access to an activity. The first Act about private internship contracts, i.e., internships without public funding was embodied in the Decree-Law N. 66/2011, of 1^st June. This work is dedicated to the study of the legal regime of the internship contract in Portugal, by analysing the problems brought by the new set of rules and especially those which remains unresolved. In fact, we can conclude that the number of situations covered by the Act is much lower than what was expected, because of the exclusion of the mandatory internship for access to a profession when the activity is developed autonomously. Since the majority of the activities can be developed both autonomously or subordinated, it is quite easy to out of the Act requirements and, so, out of the protection that it confers to the intern. In order to complete this study, we considered not only the mentioned legal Act, but also the few doctrine and jurisprudence about the theme.

Keywords: intern, internship contact, labour law, Portugal

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Gabriel S. Adesina, Ruixue Cheng, Geetika Aggarwal, Michael Short

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With the global shift towards sustainability and technological advancements, electric Hybrid vehicles (EHVs) are increasingly being seen as viable alternatives to traditional internal combustion (IC) engine vehicles, which also require efficient cooling systems. The electric Automotive Water Pump (AWP) has been introduced as an alternative to IC engine belt-driven pump systems. However, current control methods for AWPs typically employ fixed gain settings, which are not ideal for the varying conditions of dynamic vehicle environments, potentially leading to overheating issues. To overcome the limitations of fixed gain control, this paper proposes implementing an artificial neural network (ANN) for managing the AWP in EHVs. The proposed ANN provides an intelligent, adaptive control strategy that enhances the AWP's performance, supported through MATLAB simulation work illustrated in this paper. Comparative analysis demonstrates that the ANN-based controller surpasses conventional PID and fuzzy logic-based controllers (FLC), exhibiting no overshoot, 0.1secs rapid response, and 0.0696 IAE performance. Consequently, the findings suggest that ANNs can be effectively utilized in EHVs.

Keywords: automotive water pump, cooling system, electric hybrid vehicles, artificial neural networks, PID control, fuzzy logic control, IAE, MATLAB

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Authors: Xavier Ruiz Del Portal

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This paper incorporates mobility between the legal and black economies into a model of tax evasion with endogenous labor supply in which underreporting is possible in one sector but impossible in the other. We have found that the results of the effects along the extensive margin (number of evaders) become more robust and conclusive than those along the intensive margin (hours of illegal work) usually considered by the literature. In particular, it is shown that the following policies reduce the number of evaders: (a) larger and more progressive evasion penalties; (b) higher detection probabilities; (c) an increase in the legal sector wage rate; (d) a decrease in the moonlighting wage rate; (e) higher costs for creating opportunities to evade; (f) lower opportunities to evade, and (g) greater psychological costs of tax evasion. When tax concealment and illegal work also are taken into account, the effects do not vary significantly under the assumptions in Cowell (1985), except for the fact that policies (a) and (b) only hold as regards low- and middle-income groups and policies (e) and (f) as regards high-income groups.

Keywords: income taxation, tax evasion, extensive margin responses, the penalty system

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Authors: Shinoy Vengaramkode Bhaskaran, Kaushik Sathupadi, Sandesh Achar

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Human locomotion recognition is important in a variety of sectors, such as robotics, security, healthcare, fitness tracking and cloud computing. With the increasing pervasiveness of peripheral devices, particularly Inertial Measurement Units (IMUs) sensors, researchers have attempted to exploit these advancements in order to precisely and efficiently identify and categorize human activities. This research paper introduces a state-of-the-art methodology for the recognition of human locomotion patterns in a cloud environment. The methodology is based on a publicly available benchmark dataset. The investigation implements a denoising and windowing strategy to deal with the unprocessed data. Next, feature extraction is adopted to abstract the main cues from the data. The SelectKBest strategy is used to abstract optimal features from the data. Furthermore, state-of-the-art ML classifiers are used to evaluate the performance of the system, including logistic regression, random forest, gradient boosting and SVM have been investigated to accomplish precise locomotion classification. Finally, a detailed comparative analysis of results is presented to reveal the performance of recognition models.

Keywords: artificial intelligence, cloud computing, IoT, human locomotion, gradient boosting, random forest, neural networks, body-worn sensors

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Authors: Karam Aziz Hamdy Fahmy

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Although human rights protection in the industrial sector has increased, human rights violations continue to occur. Although the government has passed human rights laws, labor laws, and an international treaty ratified by the United States, human rights crimes continue to occur and go undetected. The growing number of textile companies in Bekasi is also leading to an increase in human rights violations as the government has no obligation to protect them. The United States government and business leaders should respect, protect and defend the human rights of workers. The article discusses the human rights violations faced by garment factory workers in the context of the law, as well as ideas for improving the protection of workers' rights. The connection between development and human rights has long been the subject of academic debate. Therefore, to understand the dynamics between these two concepts, a number of principles have been adopted, ranging from the right to development to a human rights-based approach to development. Despite these attempts, the precise connection between development and human rights is not yet fully understood. However, the inherent interdependence between these two concepts and the idea that development efforts must respect human rights guarantees has gained momentum in recent years. It will then be examined whether the right to sustainable development is recognized.

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

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Authors: A. Fahim, Mutahira N. Naseem

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SPAM is any unwanted electronic message or material in any form posted to many people. As the world is growing as global world, social networking sites play an important role in making world global providing people from different parts of the world a platform to meet and express their views. Among different social networking sites facebook become the leading one. With increase in usage different users start abusive use of facebook by posting or creating ways to post spam. This paper highlights the potential spam types nowadays facebook users faces. This paper also provide the reason how user become victim to spam attack. A methodology is proposed in the end discusses how to handle different types of spam.

Keywords: artificial neural networks, facebook spam, social networking sites, spam filter

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Authors: Abanoub Rady Shaker Saleb

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Nowadays, design and architecture are being affected and underwent change with the rapid advancements in technology, economics, politics, society and culture. Architecture has been transforming with the latest developments after the inclusion of computers into design. Integration of design into the computational environment has revolutionized the architecture and new perspectives in architecture have been gained. The history of architecture shows the various technological developments and changes in which the architecture has transformed with time. Therefore, the analysis of integration between technology and the history of the architectural process makes it possible to build a consensus on the idea of how architecture is to proceed. In this study, each period that occurs with the integration of technology into architecture is addressed within historical process. At the same time, changes in architecture via technology are identified as important milestones and predictions with regards to the future of architecture have been determined. Developments and changes in technology and the use of technology in architecture within years are analyzed in charts and graphs comparatively. The historical process of architecture and its transformation via technology are supported with detailed literature review and they are consolidated with the examination of focal points of 20th-century architecture under the titles; parametric design, genetic architecture, simulation, and biomimicry. It is concluded that with the historical research between past and present; the developments in architecture cannot keep up with the advancements in technology and recent developments in technology overshadow the architecture, even the technology decides the direction of architecture. As a result, a scenario is presented with regards to the reach of technology in the future of architecture and the role of the architect.

Keywords: design and development the information technology architecture, enterprise architecture, enterprise architecture design result, TOGAF architecture development method (ADM)

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Authors: Juanita Morris

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The purpose of this study will examine the mediating relationships between the theories of intelligence, mathematics anxiety, gender stereotype threat, meta-cognition and math performance through the use of eye tracking technology, affecting student perception and problem-solving abilities. The participants will consist of (N=80) female graduate students. Test administered were the Abbreviated Math Anxiety Scale, Tobii Eye Tracking software, gender stereotype threat through Google images, and they will be asked to describe their problem-solving approach allowed to measure metacognition. Participants will be administered mathematics problems while having gender stereotype threat shown to them through online images while being directed to look at the eye tracking software Tobii. We will explore this by asking ‘Is mathematics anxiety associated with the theories of intelligence and gender stereotype threat and how does metacognition and math performance place a role in mediating those perspectives?’. It is hypothesized that math-anxious students are more likely affected by the gender stereotype threat and that may play a role in their performance? Furthermore, we also want to explore whether math anxious students are more likely to be an entity theorist than incremental theorist and whether those who are math anxious will be more likely to be fixated on variables associated with coefficients? Path analysis and independent samples t-test will be used to generate results for this study. We hope to conclude that both the theories of intelligence and metacognition mediate the relationship between mathematics anxiety and gender stereotype threat.

Keywords: math anxiety, emotions, affective domains fo learning, cognitive underlinings

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Authors: Faiz Bakhsh, Tahira Yasmeen

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The Afghan refugee children in Pakistan are considered as the most vulnerable persons in danger of being abused and treated badly as compared to the minimum criteria of the protection of refugee children under 1951 refugee convention. This paper explores the impact of the 1951 refugee convention on the protection of refugee children, affected by the armed conflict in Afghanistan, residing in refugee camps in Pakistan. Despite, protection available under Refugee Convention, there exist millions of refugees in the world, including a huge portion of women and children, that remain unprotected, and their protection remains a challenging task for the world community. This study investigates the status and number of refugees in Pakistan, especially children; protection and assistance of refugees under Refugee Convention; protection of the rights of refugee children in Pakistan; and implementation of the rules of Refugee Convention relating refugee children in Pakistan and measures for the protection of refugee children in Pakistan. This socio-legal study utilizes a qualitative research approach and applies mixed methods of data collection. The primary data is collected through the interpretation of the legal framework available for the protection of refugees as well as domestic laws of Pakistan. The secondary data is collected through previous studies available on the same topic. The result of this study indicates that lack of proper implementation of the rules, of the Refugee Convention, relating protection of refugee children cause sufferings to refugee children including the provision of basic health, nutrition, family life, education and protection from child abuse. Pakistan needs a comprehensive domestic legal framework for the protection of refugees, especially refugee children. Moreover, the government of Pakistan with the help of the United Nations High Commissioner for Refugees (UNHCR) must prioritize the protection of Afghan refugee children as per standard criteria provided by the refugee convention 1951.

Keywords: refugee children, refugee convention, armed conflict, Pakistan

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Authors: Amira M. Othman

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Despite the massive array of literature that engages with the Egyptian legislative system on a theoretical level, very little attention has been dedicated to the comparison between the legislative clauses on the one hand, and the (absence of their) real-world implementation on the other. This paper starts with this discrepancy, focusing on the legal proceedings in some recent cases dubbed ‘political,’ in which defendants received death sentences. Then, it sheds light on the trend of practical disregard of the law on behalf of the criminal justice apparatuses (whether security forces, public prosecution offices, lawyers, judges, prison wardens, and executioners) through the examination of case files and the conduction of interviews with some defense lawyers in the cases in question. It also identifies the resultant state of confusion among prison staff, as manifest in their treatment of defendants even before the death sentences against them is pronounced; in other words, the application of some aspects of the law in certain cases, and their simultaneous disregard of others. Then, the paper explores the effects of such execution of the law on the death row inmates, as it identifies the different strategies through which defendants who are sentenced to death appropriate a number of legal clauses to their benefit, thereby embarrassing - or highly irritating - the judges that pronounce their death sentences. In addition to appropriation, other strategies include the contestation of the law and their presence before the courts in general, as well as the complete disregard and dismissal of the legal system altogether. Finally, the paper investigates the consequent conceptual effect on the first degree families of death row inmates, namely how their daily encounters with the Egyptian legislative system - particularly its emphasis on the absence of the otherwise binding local legislation - continue to shape their conceptions of the ‘law,’ of ‘justice,’ and their trust in the ‘state.’

Keywords: death penalty, Egyptian law absence, justice, political cases

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: Tesfaye Mengistu

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This thesis aims to investigate the effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management solutions. The study explores the potential of Model Free RL approaches, such as Monte Carlo RL and Q-learning, to improve energy management by autonomously adjusting energy management strategies to maximize efficiency. The research investigates the implementation of RL algorithms for optimizing energy consumption in a single-agent environment. The focus is on developing a framework for the implementation of RL algorithms, highlighting the importance of RL for enabling autonomous systems to adapt quickly to changing conditions and make decisions based on previous experiences. Moreover, the paper proposes RL as a novel energy management solution to address nations' CO2 emission goals. Reinforcement learning algorithms are well-suited to solving problems with sequential decision-making patterns and can provide accurate and immediate outputs to ease the planning and decision-making process. This research provides insights into the challenges and opportunities of using RL for energy management solutions and recommends further studies to explore its full potential. In conclusion, this study provides valuable insights into how RL can be used to improve the efficiency of energy management systems and supports the use of RL as a promising approach for developing autonomous energy management solutions in residential buildings.

Keywords: artificial intelligence, reinforcement learning, monte carlo, energy management, CO2 emission

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Authors: Catalina Oana Dumitrescu, Andreea L. Drugau-constantin

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In the digital age, public administration is facing profound change, fueled by technological advances and the growing demands of citizens for efficient, accessible and transparent services. This paper explores how new digital technologies – including artificial intelligence, blockchain, big data and e-governance solutions – are reshaping the functioning of public administrations globally. In addition to the obvious opportunities to streamline and optimize processes, digital transformation brings with it major challenges, such as cyber security, personal data protection, resistance to change and the need to develop new skills for employees. The paper aims to provide a discussion platform for public administration experts, policy makers and technology innovators to consider how governments can balance the benefits and risks of digital transformation. Topics such as the reconfiguration of administrative processes, the creation of interoperable government systems, the involvement of citizens in public decisions through digital platforms, and solutions for reducing the digital gap between developed and developing regions will be addressed. In conclusion, the digital transformation of public administration is not only an opportunity for modernization, but also a necessity to respond to the new demands and challenges of contemporary society. This paper will provide new insights into the role of technology in improving the quality of governance and public services.

Keywords: public administration, digital ERA, technology, government systems, global

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Authors: Ronli Sifris

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The last Australian Parliamentary inquiry into surrogacy took place in 2016. Since then, a number of countries have reviewed their surrogacy laws, including countries such as New Zealand and the United Kingdom, which traditionally have invoked similar legal approaches to Australia on a broad range of issues. The time is ripe to reform Australia’s surrogacy laws with a view to putting in place a system that best protects the rights of all parties to a surrogacy arrangement, and especially the rights of the child. There are two specific, linked issues which tend to be particularly contentious in the surrogacy context. The first relates to legal parentage. There are questions around whether the surrogate or the intended parents should be deemed the legal parents of a child born through surrogacy and what should be the process for any transfer of parentage. The second key issue relates to compensation and whether a surrogate should be compensated for the reproductive labour inherent in conceiving, gestating, and birthing a child. This paper will invoke a comparative analysis with a view to considering how different countries are regulating surrogacy and which approach best protects the rights all parties involved in the surrogacy arrangement, especially the rights of the children born through surrogacy. The specific countries to be considered are Australia, Canada, and California (United States). I have selected these countries for the following reasons: Australia is the jurisdiction where the author is based, it is, therefore, the jurisdiction with which she has the most familiarity. It allows altruistic surrogacy only and post-birth parentage orders in favour of the intended parents of children born through altruistic surrogacy California, as a jurisdiction allowing for compensated surrogacy and pre-birth parentage orders in favour of the intended parents, sits at the other end of the spectrum to Australia thereby providing an interesting point of comparison. Canada sits somewhere in the middle; it ostensibly allows only altruistic surrogacy, but in practice, many aspects of the Canadian process resemble compensated surrogacy. In addition to conducting a comparative analysis with other countries, the paper will also consider international human rights law as its overarching framework for determining the approach that best protects the rights of a child born through surrogacy. Particular attention will be paid to the United Nations Convention on the Rights of the Child as the key children’s rights treaty. The European Court of Human Rights will also be extensively considered as it has decided a number of cases relating to the rights of children born through surrogacy.

Keywords: surrogacy, children’s rights, australia, compensation, parentage

Procedia PDF Downloads 132

Authors: Joud Basyouni, Rama Zagzoog, Mashael Al Faleh, Jana Alireza

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AI is changing many fields and speeding up tasks that used to take a long time. It used to take too long to edit photos. However, many AI-powered apps make photo editing, automatic effects, and animations much easier than other manual editing apps with no AI. The mobile app Photoleap edits photos and creates digital art using AI. Editing photos with text prompts is also becoming a standard these days with the help of apps like Photoleap. Now, users can change backgrounds, add animations, turn text into images, and create scenes with AI. This project report discusses the photo editing app's history and popularity. Photoleap resembles Photoshop, Canva, Photos, and Pixlr. The report includes survey questions to assess Photoleap user satisfaction. The report describes Photoleap's features and functions with screenshots. Photoleap uses AI well. Charts and graphs show Photoleap user ratings and comments from the survey. This project found that most Photoleap users liked how well it worked, was made, and was easy to use. People liked changing photos and adding backgrounds. Users can create stunning photo animations. A few users dislike the app's animations, AI art, and photo effects. The project report discusses the app's pros and cons and offers improvements.

Keywords: artificial intelligence, photoleap, images, background, photo editing

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Authors: Edlira Kalemi, Sule Yildirim-Yayilgan

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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.

Keywords: criminal digital evidence, social media, ontologies, reasoning

Procedia PDF Downloads 390

Authors: Catherine McWhorter

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Robotics is a fast-evolving field lacking comprehensive and harm-mitigating regulation; it also lacks critical data on how human-robot interaction (HRI) may affect human psychology. As most anthropomorphic robots are intended as substitutes for humans, this paper asserts that the commercial robotics industry should be preemptively regulated at the federal level such that robots capable of embodying a victim role in criminal scenarios (“vicbots”) are prohibited until clinical studies determine their effects on the user and society. The results of these studies should then inform more permanent legislation that strives to mitigate risks of harm without infringing upon fundamental rights or stifling innovation. This paper explores these concepts through the lens of the sex robot industry. The sexbot industry offers some of the most realistic, interactive, and customizable robots for sale today. From approximately 2010 until 2017, some sex robot producers, such as True Companion, actively promoted ‘vicbot’ culture with personalities like “Frigid Farrah” and “Young Yoko” but received significant public backlash for fetishizing rape and pedophilia. Today, “Frigid Farrah” and “Young Yoko” appear to have vanished. Sexbot producers have replaced preprogrammed vicbot personalities in favor of one generic, customizable personality. According to the manufacturer ainidoll.com, when asked, there is only one thing the user won’t be able to program the sexbot to do – “…give you drama”. The ability to customize vicbot personas is possible with today’s generic personality sexbots and may undermine the intent of some current legislative efforts. Current debate on the effects of vicbots indicates a lack of consensus. Some scholars suggest vicbots may reduce the rate of actual sex crimes, and some suggest that vicbots will, in fact, create sex criminals, while others cite their potential for rehabilitation. Vicbots may have value in some instances when prescribed by medical professionals, but the overall uncertainty and lack of data further underscore the need for preemptive regulation and clinical research. Existing literature on exposure to media violence and its effects on prosocial behavior, human aggression, and addiction may serve as launch points for specific studies into the hyperrealism of vicbots. Of course, the customization, anthropomorphism and artificial intelligence of sexbots, and therefore more mainstream robots, will continue to evolve. The existing sexbot industry offers an opportunity to preemptively regulate and to research answers to these and many more questions before this type of technology becomes even more advanced and mainstream. Robots pose complicated moral, ethical, and legal challenges, most of which are beyond the scope of this paper. By examining the possibility for custom vicbots via the sexbots industry, reviewing existing literature on regulation, media violence, and vicbot user effects, this paper strives to underscore the need for preemptive federal regulation prohibiting vicbot capabilities in robots while advocating for further research into the potential for the user and societal harm by the same.

Keywords: human-robot interaction effects, regulation, research, robots

Procedia PDF Downloads 207