Search results for: law enforcement intelligence

Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

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Authors: Veronika Pivkina, Alla Kim, Khon Nataliya

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Actuality of the present study is defined first of all the role of subjective well-being problem in modern psychology and the comprehending of subjective well-being by current students. Purpose of this research is to educe peculiarities of comprehending of subjective well-being by students with various levels of emotional intelligent. Methods of research are adapted Russian-Language questionnaire of K. Riff 'The scales of psychological well-being'; emotional intelligent questionnaire of D. V. Lusin. The research involved 72 student from different universities and disciplines aged between 18 and 24. Analyzing the results of the studies, it can be concluded that the understanding of happiness in different groups of students with high and low levels of overall emotional intelligence is different, as well as differentiated by gender. Students with higher level of happiness possess more capacity and higher need to control their emotions, to cause and maintain the desired emotions and control something undesirable.

Keywords: subjective well-being, emotional intelligent, psychology of comprehending, students

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Authors: Danilo López, Edwin Rivas, Fernando Pedraza

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Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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Authors: Ayanda P. Deliwe, Storm B. Watson

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The COVID-19 pandemic has disrupted the established practices of higher education institutions (HEIs). Most higher education institutions worldwide had to shift from traditional face-to-face to online learning. The online environment and new online tools are disrupting the way in which higher education is presented. Furthermore, the structures of higher education institutions have been impacted by rapid advancements in information and communication technologies. Emerging technologies should not be viewed in a negative light because, as opposed to the traditional curriculum that worked to create productive and efficient researchers, emerging technologies encourage creativity and innovation. Therefore, using technology together with traditional means will enhance teaching and learning. Emerging technologies in higher education not only change the experience of students, lecturers, and the content, but it is also influencing the attraction and retention of students. Higher education institutions are under immense pressure because not only are they competing locally and nationally, but emerging technologies also expand the competition internationally. Emerging technologies have eliminated border barriers, allowing students to study in the country of their choice regardless of where they are in the world. Higher education institutions are becoming indifferent as technology is finding its way into the lecture room day by day. Academics need to utilise technology at their disposal if they want to get through to their students. Academics are now competing for students' attention with social media platforms such as WhatsApp, Snapchat, Instagram, Facebook, TikTok, and others. This is posing a significant challenge to higher education institutions. It is, therefore, critical to pay attention to emerging technologies in order to see how they can be incorporated into the classroom in order to improve educational quality while remaining relevant in the work industry. This study aims to understand how emerging technologies have been utilised at Nelson Mandela University in presenting teaching and learning activities since April 2020. The primary objective of this study is to analyse how academics are incorporating emerging technologies in their teaching and learning activities. This primary objective was achieved by conducting a literature review on clarifying and conceptualising the emerging technologies being utilised by higher education institutions, reviewing and analysing the use of emerging technologies, and will further be investigated through an empirical analysis of the use of emerging technologies at Nelson Mandela University. Findings from the literature review revealed that emerging technology is impacting several key areas in higher education institutions, such as the attraction and retention of students, enhancement of teaching and learning, increase in global competition, elimination of border barriers, and highlighting the digital divide. The literature review further identified that learning management systems, open educational resources, learning analytics, and artificial intelligence are the most prevalent emerging technologies being used in higher education institutions. The identified emerging technologies will be further analysed through an empirical analysis to identify how they are being utilised at Nelson Mandela University.

Keywords: artificial intelligence, emerging technologies, learning analytics, learner management systems, open educational resources

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Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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Authors: Libia Jiménez Chávez

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This is a study of freedom riders and their courageous journey for civil rights, but the year was not 1961. It was 2003. This paper chronicles the emergence of a new civil rights movement for immigrant rights through an oral history of the 2003 U.S. Immigrant Workers Freedom Ride (IWFR). During the height of the post-9/11 immigrant repression, a bloc of organizations inspired by the Civil Rights Movement of the 1960s mobilized 900 multinational immigrants and their allies in the fight for legal status, labor protections, family reunification, and civil rights. The activists visited over 100 U.S. cities, met with Congressional leaders in the nation’s capital, and led a rally of over 50,000 people in New York City. This unified effort set the groundwork for the national May Day immigration protests of 2006. Movements can be characterized in two distinct ways: physical movement and social movements. In the past, historians have considered immigrants both as people and as participants in social movements. In contrast, studies of recent migrants tend to say little about their involvement in immigrant political mobilizations. The dominant literature on immigration portrays immigrants as objects of exclusion, border enforcement, detention, and deportation instead of strategic political actors. This paper aims to change this perception. It considers the Freedom Riders both as immigrants who were literally on the move and as participants in a social movement. Through interviews with participants and archival video footage housed at the University of California Los Angeles, it is possible to study this mobile protest as a movement. This contemporary immigrant struggle is an opportunity to explore the makeup and development of a heterogenous immigrant coalition and consider the relationship between population movements and social justice. In addition to oral histories and archival research, the study will utilize social movement literature, U.S. immigration and labor history, and Undocumented Critical Theory to expand the historiography of immigrant social movements in America.

Keywords: civil rights, immigrant social movements, undocumented communities, undocumented critical theory

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Authors: Lana Dalawr Jalal

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This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: obstacle avoidance, particle swarm optimization, three-dimensional path planning unmanned aerial vehicles

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Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

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This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among the people living in Malaysia using Particle Swarm Optimized Artificial. With the skyrocketing prevalence of Type 2 diabetes in Malaysia, the system can be used to encourage affected people to seek further medical attention to prevent the onset of diabetes or start managing it early enough to avoid the associated complications. The study sought to find out the best predictive variables of Type 2 Diabetes Mellitus, developed a system to diagnose diabetes from the variables using Artificial Neural Networks and tested the system on accuracy to find out the patent generated from diabetes diagnosis result in machine learning algorithms even at primary or advanced stages.

Keywords: diabetes diagnosis, Artificial Neural Networks, artificial intelligence, soft computing, medical diagnosis

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Authors: Noura Al-Ajmi, Mohammed A. Almulla

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With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.

Keywords: headache diagnosis system, prescription recommender system, expert system, backward rule-based system

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Authors: Navdeep Singh Randhawa, Shally Sharma

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Wireless Sensor Network is an autonomous technology emanating in the current scenario at a fast pace. This technology faces a number of defiance’s and energy management is one of them, which has a huge impact on the network lifetime. To sustain energy the different types of routing protocols have been flourished. The classical routing protocols are no more compatible to perform in complicated environments. Hence, in the field of routing the intelligent algorithms based on nature systems is a turning point in Wireless Sensor Network. These nature-based algorithms are quite efficient to handle the challenges of the WSN as they are capable of achieving local and global best optimization solutions for the complex environments. So, the main attention of this paper is to develop a routing algorithm based on some swarm intelligent technique to enhance the performance of Wireless Sensor Network.

Keywords: wireless sensor network, routing, swarm intelligence, MPRSO

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Authors: Ismene Ithai Bras-Ruiz

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Learning Analytics (LA) is employed by universities not only as a tool but as a specialized ground to enhance students and professors. However, not all the academic programs apply LA with the same goal and use the same tools. In fact, LA is formed by five main fields of study (academic analytics, action research, educational data mining, recommender systems, and personalized systems). These fields can help not just to inform academic authorities about the situation of the program, but also can detect risk students, professors with needs, or general problems. The highest level applies Artificial Intelligence techniques to support learning practices. LA has adopted different techniques: statistics, ethnography, data visualization, machine learning, natural language process, and data mining. Is expected that any academic program decided what field wants to utilize on the basis of his academic interest but also his capacities related to professors, administrators, systems, logistics, data analyst, and the academic goals. The Open and Distance University System (SUAYED in Spanish) of the University National Autonomous of Mexico (UNAM), has been working for forty years as an alternative to traditional programs; one of their main supports has been the employ of new information and communications technologies (ICT). Today, UNAM has one of the largest network higher education programs, twenty-six academic programs in different faculties. This situation means that every faculty works with heterogeneous populations and academic problems. In this sense, every program has developed its own Learning Analytic techniques to improve academic issues. In this context, an investigation was carried out to know the situation of the application of LA in all the academic programs in the different faculties. The premise of the study it was that not all the faculties have utilized advanced LA techniques and it is probable that they do not know what field of study is closer to their program goals. In consequence, not all the programs know about LA but, this does not mean they do not work with LA in a veiled or, less clear sense. It is very important to know the grade of knowledge about LA for two reasons: 1) This allows to appreciate the work of the administration to improve the quality of the teaching and, 2) if it is possible to improve others LA techniques. For this purpose, it was designed three instruments to determinate the experience and knowledge in LA. These were applied to ten faculty coordinators and his personnel; thirty members were consulted (academic secretary, systems manager, or data analyst, and coordinator of the program). The final report allowed to understand that almost all the programs work with basic statistics tools and techniques, this helps the administration only to know what is happening inside de academic program, but they are not ready to move up to the next level, this means applying Artificial Intelligence or Recommender Systems to reach a personalized learning system. This situation is not related to the knowledge of LA, but the clarity of the long-term goals.

Keywords: academic improvements, analytical techniques, learning analytics, personnel expertise

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Authors: Kolade Olawande Owoeye, George R. S. Weir

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The widespread of terrorism and extremism activities on the internet has become a major threat to the government and national securities due to their potential dangers which have necessitated the need for intelligence gathering via web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult or time-consuming. In response to this challenge, an automated classification system called composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a web. We implemented the framework on a set of extremist webpages dataset that has been subjected to the manual classification process. Therein, we developed a classification model on the data using J48 decision algorithm, this is to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of arts, indicated a 96% success rate in classifying overall webpages when matched against the manual classification.

Keywords: extremist, web pages, classification, semantics, posit

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Authors: Sara Fayez Fawzy Mikhael

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Inclusive education services for students with autism are still developing in Thailand. Although many more children with intellectual disabilities have been attending school since the Thai government enacted the Education for Persons with Disabilities Act in 2008, facilities for students with disabilities and their families are generally inadequate. This comprehensive study used the Attitudes and Preparedness for Teaching Students with Autism Scale (APTSAS) to examine the attitudes and preparedness of 110, elementary teachers in teaching students with autism in the general education setting. Descriptive statistical analyzes showed that the most important factor in the formation of a negative image of teachers with autism is student attitudes. Most teachers also stated that their pre-service training did not prepare them to meet the needs of children with special needs who cannot speak. The study is important and provides directions for improving non-formal teacher education in Thailand.

Keywords: attitude, autism, teachers, thailandsports activates, movement skills, motor skills

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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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: Jana Ismail, Layla Fallatah, Maha Alshmaisi

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ChatGPT, a cutting-edge language model built on the GPT-3.5 architecture, has garnered attention for its profound natural language processing capabilities, holding promise for transformative applications in customer service and content creation. This study delves into ChatGPT's architecture, aiming to comprehensively understand its strengths and potential limitations. Through systematic experiments across diverse domains, such as general knowledge and creative writing, we evaluated the model's coherence, context retention, and task-specific accuracy. While ChatGPT excels in generating human-like responses and demonstrates adaptability, occasional inaccuracies and sensitivity to input phrasing were observed. The study emphasizes the impact of prompt design on output quality, providing valuable insights for the nuanced deployment of ChatGPT in conversational AI and contributing to the ongoing discourse on the evolving landscape of natural language processing in artificial intelligence.

Keywords: artificial Inelegance, chatGPT, open AI, NLP

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Authors: Karen Fang

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Investigative genetic genealogy has attracted much interest in both the field of ethics and the public eye due to its global application in criminal cases. Arguments have been made regarding privacy and informed consent, especially with law enforcement using consumer genetic testing results to convict individuals. In the case of public interest, DNA databases have the strong potential to significantly reduce crime, which in turn leads to safer communities and better futures. With the advancement of genetic technologies, the integration of a universal forensic DNA database in violent crimes, crimes against children, and missing person cases is expected to deter crime while protecting one’s privacy. Rather than collecting whole genomes from the whole population, STR profiles can be used to identify unrelated individuals without compromising personal information such as physical appearance, disease risk, and geographical origin, and additionally, reduce cost and storage space. STR DNA profiling is already used in the forensic science field and going a step further benefits several areas, including the reduction in recidivism, improved criminal court case turnaround time, and just punishment. Furthermore, adding individuals to the database as early as possible prevents young offenders and first-time offenders from participating in criminal activity. It is important to highlight that DNA databases should be inclusive and tightly governed, and the misconception on the use of DNA based on crime television series and other media sources should be addressed. Nonetheless, deterrent effects have been observed in countries like the US and Denmark with DNA databases that consist of serious violent offenders. Fewer crimes were reported, and fewer people were convicted of those crimes- a favorable outcome, not even the death penalty could provide. Currently, there is no better alternative than a universal forensic DNA database made up of STR profiles. It can open doors for investigative genetic genealogy and fostering better communities. Expanding the appropriate use of DNA databases is ethically acceptable and positively impacts the public.

Keywords: bioethics, deterrent effects, DNA database, investigative genetic genealogy, privacy, public interest

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Authors: Saeid Jalilzadeh

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PID controllers are widely used to control the industrial plants because of their robustness and simple structures. Tuning of the controller's parameters to get a desired response is difficult and time consuming. With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameters tuning methods of PID controller have emerged in endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfect as to be expected. Honey Bee algorithm (HBA) and genetic algorithm (GA) are extensively used for real parameter optimization in diverse fields of study. This paper describes an application of HBA and GA to the problem of designing a PID controller whose parameters comprise proportionality constant, integral constant and derivative constant. Presence of three parameters to optimize makes the task of designing a PID controller more challenging than conventional P, PI, and PD controllers design. The suitability of the proposed approach has been demonstrated through computer simulation using MATLAB/SIMULINK.

Keywords: controller, GA, optimization, PID, PSO

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Authors: Tarek Aboueldahab, Hanan Farag

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Cost minimization of Multiple Vehicle Routing Problem becomes a critical issue in the field of transportation because it is NP-hard optimization problem and the search space is complex. Many researches use the hybridization of artificial intelligence (AI) models to solve this problem; however, it can not guarantee to reach the best solution due to the difficulty of searching the whole search space. To overcome this problem, we introduce the hybrid model of Discrete Particle Swarm Optimization (DPSO) with a passive congregation which enable searching the whole search space to compromise between both local and global search. The practical experiment shows that our model obviously outperforms other hybrid models in cost minimization.

Keywords: cost minimization, multi-vehicle routing problem, passive congregation, discrete swarm, passive congregation

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Authors: Sameh Sarwat Melek Mikheal

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The relationship between development and human rights has long been the subject of academic debate. To understand the dynamics between these two concepts, various principles are adopted, from the right to development to development-based human rights. Despite the initiatives taken, the relationship between development and human rights remains unclear. However, the overlap between these two views and the idea that efforts should be made in the field of human rights have increased in recent years. It is then evaluated whether the right to sustainable development is acceptable or not. This article concludes that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, and this is a good answer to the question posed above. This book therefore cites regional and international human rights agreements such as , as well as the jurisprudence and interpretative guidelines of human rights institutions, to prove this hypothesis.

Keywords: balance, counter-terrorism, cyber-terrorism, human rights, security, violation sustainable development, 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: Shenouda Farag Aziz Ibrahim

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The relationship between terrorism and human rights has become an important issue in the fight against terrorism worldwide. This is based on the fact that terrorism and human rights are closely linked, so that when the former begins, the latter suffers. This direct link was recognized in the Vienna Declaration and Program of Action adopted by the International Conference on Human Rights held in Vienna on 25 June 1993, which recognized that terrorist acts aim to violate human rights in all their forms and manifestations. . Therefore, terrorism represents an attack on fundamental human rights. For this purpose, the first part of this article focuses on the relationship between terrorism and human rights and aims to show the relationship between these two concepts. In the second part, the concept of cyber threat and its manifestations are discussed. An analysis of the fight against terrorism in the context of human rights was also made..

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: Nur Syahidatul Idany Abdul Ghani, Rahizar Ramli, Jamilah Mohamad, Ahmad Saifizul, Mohamed Rehan Karim

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Increasing fatalities in road accidents in Malaysia over the last 10 years are quite alarming. Based on Malaysian Institute of Road Safety Research (Miros) latest research ‘Predicting Malaysian Road Fatalities for year 2020; it is predicted that road fatalities in Malaysia for 2015 is 8,780 and 10,716 for the year 2020 which 30 percent of fatalities were caused by accidents involving commercial vehicles. Government, related agencies and NGOs have continuously and persistently work to reduce the statistics through enforcement, educating the public, training to drivers, road safety campaigns, advertisements etc. However, the trend of casualties does not show encouraging pattern but instead, steadily growing. Thus, this comparative study reviews the literature pertaining on method of measurement used to evaluate commercial drivers competency. In several studies driving competency has been assessed with different assessment based on the license procedures and requirements according to the country regulation. The assessment criteria that has been establish for commercial drivers generally focus on driving tasks and assessment e.g. theory test, medical test and road assessment rather than driving competency test or physical test. Realizing the importance of specific assessment test for drivers competency this comparative study reviews the most discussed literature related to competency assessment method to identify competency of the drivers include (1. judgement and reaction, 2. skill of drivers, 3. experiences and fatigue). The concluding analysis of this paper is a comparative table for assessment methodology to access driver’s competency. A comparative study is a further discussion reviewing past literature to provide an overview on existing assessment test and potential subject matters that can be identified for further studies to increase awareness of the drivers, passengers as well as the authorities about the importance of competent drivers in order to improve safety in commercial vehicles.

Keywords: commercial vehicles, driver’s competency, specific assessment

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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: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Sumanta Meher, Gaurav Shukla

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The torments of the victims of terrorism have not only confined to loss of life and limp but also includes the physiological trauma to the innocent victims. The physical wounds may heal, but the trauma remains in the mind and heart of the victims and their loved ones; however, one should not deny that these terrorist activities affect to a major extent to their livelihood. To protect their human rights and restore the shattered lives of the victims of terrorism all the Nations beyond their differences have to show solidarity and frame a comprehensive restorative policy with an effective implementing mechanism. The General Assembly of United Nations, through its several resolutions, has appealed Nations to show solidarity and also committed to helping the Members State to frame the law and policy to support the victims of terrorism. To achieve the objectives of the resolutions adopted by the United Nations, the Indian legislators in 2008 amended the Code of Criminal Procedure, 1973 and incorporated Section 357A to provide financial assistance to the victims of terrorism. In India, the contemporary developments in the victims’ oriented studies have increased the dimension of the traditional criminal justice systems to protect the rights of the victims. In this regard, the paper has ascertained the Indian legal framework in respect to the restorative justice to the victims of terrorism and also addressed the question as to whether the statutory provisions and enforcement mechanisms are efficient enough to protect the human rights of the victims of terrorism. For that purpose, the paper has analyzed the International instruments and the reports with regard to the compensation to the victims of terrorist attacks, with that, the article also evaluates the initiatives of United Nations to help Members State to frame the law and policies to support the victims of terrorism. The study also made an attempt to critically analyze the legal provisions of compensation and rehabilitation of the victims of terrorist attacks in India and whether they are in alignment with the International standards. While concluding, the paper has made an endeavor for a robust legal framework towards the restorative justice for the victims of terrorism in India.

Keywords: victims of terrorism, restorative justice, human rights, criminal justice system of India

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Authors: Avi Shrivastava

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In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

Procedia PDF Downloads 56

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

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

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

Procedia PDF Downloads 43

Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

Procedia PDF Downloads 53

Authors: Joshefina Bengoechea Fernandez, Alex Bell

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In its 2021 guidance for policy makers, the UNESCO has proposed 4 areas where AI can be applied in educational settings: These are: 1) Education management and delivery; 2) Learning and assessment; 3) Empowering teachers and facilitating teaching, and 4) Providing lifelong learning possibilities (UNESCO, 2021). Like with wblockchain technologies, AI will automate the management of educational institutions. These include, but are not limited to admissions, timetables, attendance, and homework monitoring. Furthermore, AI will be used to select relevant learning content across learning platforms for each student, based on his or her personalized needs. A problem educators face is the “one-size-fits-all” approach that does not work with a diverse student population. The purpose of this paper is to illustrate if the implementation of Technology is the solution to the Problems faced in Higher Education. The paper builds upon a constructivist approach, combining a literature review and research on key publications and academic reports.

Keywords: artificial intelligence, learning platforms, students personalised needs, life- long learning, privacy, ethics

Procedia PDF Downloads 82

Authors: Enya Autumn Trenholm-Jensen, Hjalte Hviid Mikkelsen

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This study was done in the pursuit of nuancing the discussion surrounding what it means to be human in a time of unparalleled technological development. Subjectivity was deemed to be an accessible example of humanity to study, and art was a fitting medium through which to probe subjectivity. Upon careful theoretical consideration, abstract art was found to fit the parameters of the study with the added bonus of being, as of yet, uninterpretable from an AI perspective. It was hypothesised that dissimilar appraisals of the art stimuli would be found through sentiment and terminology. Opinion data was collected through survey responses and analysed using Valence Aware Dictionary for sEntiment Reasoning (VADER) sentiment analysis. The results reflected the enigmatic nature of subjectivity through erratic ratings of the art stimuli. However, significant themes were found in the terminology used in the responses. The implications of the findings are discussed in relation to the uniqueness, or lack thereof, of human subjectivity, and directions for future research are provided.

Keywords: abstract art, artificial intelligence, cognition, sentiment, subjectivity

Procedia PDF Downloads 103