Search results for: law enforcement intelligence

Authors: Odoh Ben Uruchi

Abstract:

Access to Justice implies access to social and distributive Justice. Access to social justice in Nigeria remains an illusion where cases last in courts for unduly long period of time, as is currently the situation in the country. As the popular saying goes– justice delayed is justice denied. It is, however, important to underscore the point that these perspectives are not necessarily disconnected since the extent to which one can have distributive justice in any system is largely determined by the level and effectiveness of social justice in the country. Generally, Alternative Dispute Resolution (ADR) Processes are increasingly being accepted in Nigeria as appropriate mechanisms for resolving disputes. While some jurisdictions have institutionalized ADR through the concept of a Multidoor Courthouse, many other are at different stages of doing same. With these developments, it is obvious that stakeholders in the administration of justice in Nigeria, can no longer be indifferent about understanding and fully mainstreaming ADR into their various activities and professional practice. Any framework for promoting social justice in Nigeria should therefore of necessity include provision of avenues for use of ADR in the protection and enforcement of citizen’s rights. The constitutional and other legal provisions that guarantee various rights of citizens cannot of itself ensure the enjoyment of the rights in the absence of an effective framework for dispute resolution. Excessive reliance on litigation and other adversarial approaches will also fail to ensure a sound regime of social justice. There should be structured mainstreaming of alternative dispute resolution mechanisms in justice delivery if the society must provide and guarantee social justice to the citizens. This paper seeks to address some of the fundamental issues affecting the perception, knowledge and skills of ADR in the provision of social justice. In doing this, the paper proposes to unlock the full enormous potentials of Alternative Dispute Resolution (ADR) in promoting access to justice in Nigeria.

Keywords: aspects, dimensions, alternative dispute resolution, social justice

Procedia PDF Downloads 412

Authors: Ramesh Kumar Behera, Md. Izhar Hassan

Abstract:

Accident investigation and analysis are useful to identify deficiencies in plant, process, and management practices and formulate preventive strategies for injury elimination. In India and other parts of the world, industrial accidents are investigated to know the causes and also to fulfill legal compliances. However, findings of investigation are seldom used appropriately to strengthen Occupational Safety and Health (OSH) in expected lines. The mineral rich state of Odisha in eastern coast of India; known as a hub for Iron and Steel industries, witnessed frequent accidents during 2005-2009. This article based on study of 982 fatal ‘factory-accidents’ occurred in Odisha during the period 2001-2016, discusses the ‘turnaround-story’ resulting in reduction of fatal accident from 122 in 2009 to 45 in 2016. This paper examines various factors causing incidents; accident pattern in steel and chemical sector; role of climate and harsh weather conditions on accident causation. Software such as R, SQL, MS-Excel and Tableau were used for analysis of data. It is found that maximum fatality is caused due to ‘fall from height’ (24%); steel industries are relatively more accident prone; harsh weather conditions of summer increase chances of accident by 20%. Further, the study suggests that enforcement of partial work-restriction around lunch time during peak summer, screening and training of employees reduce accidents due to fall from height. The study indicates that learning from accident investigation and analysis can be used as a method to reduce work related accidents in the journey towards ‘Vision Zero’.

Keywords: accident investigation and analysis, fatal accidents in India, fall from height, vision zero

Procedia PDF Downloads 135

Authors: Muhammad Naziru Yahaya, Mustapha Bashir Ayinde

Abstract:

Noise has been recognized as a major source of pollution in many urban and semi-urban settlements. Noise pollution causes by vehicular movement in urban cities has reaches an alarming proportion due to continuous increases in vehicles and industrialization. This research aim to determine the geo-physical characteristics of the study area and to determine the level of noise generation and volume intensity in areas where noise levels are high within the metropolis and compare with NESREA and WHO standards. This study identified the various sources of noise, compared noise levels in various parts of the study area with recommended standards and determined the geo-physical characteristic of noise generated. A sound level meter Gm 1352, was used for the noise measurements. The study showed that the noise pollution levels measured in minimum noise level of 63.75 dBA and average maximum of 95.175 dBA, at some locations in Birnin Kebbi metropolis the noise level have exceeded the standard limits set by the World Health Organization (WHO), Federal Environment Protection Agency (FEPA). Results revealed that there was a considerable increase in noise pollution in First Bank roundabout and Haliru Abdu roundabout, attribute to high numbers of vehicular movement and road congestion within Birnin Kebbi. The study therefore concluded that there should be an enforcement and adherence to the regulation regarding noise pollution limit. The minimum average day noise level recorded was 67.225 dBA, and average maximum of 96.6 dBA is an indication that the noise level of Birnin Kebbi metropolis was highly unsatisfactory. Based on this, it is suggested that taking adequate measures and following the laid-down recommendations will reduce traffic noise to the barest minimum.

Keywords: decibel, noise level, pollution, sound level, traffic, highway

Procedia PDF Downloads 61

Authors: Zheng Yuxun

Abstract:

This review critically assesses the advancements and prospective developments in defect detection methodologies within the semiconductor industry, an essential domain that significantly affects the operational efficiency and reliability of electronic components. As semiconductor devices continue to decrease in size and increase in complexity, the precision and efficacy of defect detection strategies become increasingly critical. Tracing the evolution from traditional manual inspections to the adoption of advanced technologies employing automated vision systems, artificial intelligence (AI), and machine learning (ML), the paper highlights the significance of precise defect detection in semiconductor manufacturing by discussing various defect types, such as crystallographic errors, surface anomalies, and chemical impurities, which profoundly influence the functionality and durability of semiconductor devices, underscoring the necessity for their precise identification. The narrative transitions to the technological evolution in defect detection, depicting a shift from rudimentary methods like optical microscopy and basic electronic tests to more sophisticated techniques including electron microscopy, X-ray imaging, and infrared spectroscopy. The incorporation of AI and ML marks a pivotal advancement towards more adaptive, accurate, and expedited defect detection mechanisms. The paper addresses current challenges, particularly the constraints imposed by the diminutive scale of contemporary semiconductor devices, the elevated costs associated with advanced imaging technologies, and the demand for rapid processing that aligns with mass production standards. A critical gap is identified between the capabilities of existing technologies and the industry's requirements, especially concerning scalability and processing velocities. Future research directions are proposed to bridge these gaps, suggesting enhancements in the computational efficiency of AI algorithms, the development of novel materials to improve imaging contrast in defect detection, and the seamless integration of these systems into semiconductor production lines. By offering a synthesis of existing technologies and forecasting upcoming trends, this review aims to foster the dialogue and development of more effective defect detection methods, thereby facilitating the production of more dependable and robust semiconductor devices. This thorough analysis not only elucidates the current technological landscape but also paves the way for forthcoming innovations in semiconductor defect detection.

Keywords: semiconductor defect detection, artificial intelligence in semiconductor manufacturing, machine learning applications, technological evolution in defect analysis

Procedia PDF Downloads 18

Authors: R. Kerbachi, S. Chikhi, M. Boughedaoui

Abstract:

The study presents an analysis of the Algerian vehicle fleet and resultant emissions. The emission measurement of air pollutants emitted by road transportation (CO, THC, NOX and CO2) was conducted on 17 light duty vehicles in real traffic. This sample is representative of the Algerian light vehicles in terms of fuel quality (gasoline, diesel and liquefied petroleum gas) and the technology quality (injection system and emission control). The experimental measurement methodology of unit emission of vehicles in real traffic situation is based on the use of the mini-Constant Volume Sampler for gas sampling and a set of gas analyzers for CO2, CO, NOx and THC, with an instrumentation to measure kinematics, gas temperature and pressure. The apparatus is also equipped with data logging instrument and data transfer. The results were compared with the database of the European light vehicles (Artemis). It was shown that the technological injection liquefied petroleum gas (LPG) has significant impact on air pollutants emission. Therefore, with the exception of nitrogen oxide compounds, uncatalyzed LPG vehicles are more effective in reducing emissions unit of air pollutants compared to uncatalyzed gasoline vehicles. LPG performance seems to be lower under real driving conditions than expected on chassis dynamometer. On the other hand, the results show that uncatalyzed gasoline vehicles emit high levels of carbon monoxide, and nitrogen oxides. Overall, and in the absence of standards in Algeria, unit emissions are much higher than Euro 3. The enforcement of pollutant emission standard in developing countries is an important step towards introducing cleaner technology and reducing vehicular emissions.

Keywords: on-board measurements of unit emissions of CO, HC, NOx and CO2, light vehicles, mini-CVS, LPG-fuel, artemis, Algeria

Procedia PDF Downloads 263

Authors: Linda Frazer

Abstract:

A pluralistic methodology focuses on promoting an understanding that an alternative juridical framework for the regulation of transnational business negotiations (TBN) between private business parties is fundamentally required. This paper deals with the evolving assessment of the doctoral research of the author which demonstrated that due to insufficient juridical tools, negotiations are commonly misunderstood within the complexity of pluralistic and conflicting legal regimes. This inadequacy causes uncertainty in the enforcement of legal remedies, leaving business parties surprised. Consequently, parties cannot sufficiently anticipate when and how legal rights and obligations are created, often counting on oral or incomplete agreements which may lead to the misinterpretation of the extent of their legal rights and obligations. This uncertainty causes threats to business parties for fear of creating unintended legal obligations or, conversely, that law will not enforce intended agreements for failure to pass the tests of contractual validity. A need to find a manner to set default standards of communications and standards of conduct to monitor our evolving global trade would aid law to provide the security, predictability and foreseeability during alternative dispute resolution required by TBN parties. The conclusion of this study includes a proposal of new trade mechanisms, termed 'Bills of Negotiations' (BON) to enhance party autonomy and promote the ability for TBN parties to self-regulate within the boundaries of law. BON will be guided by a secure juridical institutionalized setting that caters to guiding communications during TBN and resolving disputes that arise along the negotiation processes on a fast track basis.

Keywords: alternative resolution disputes, ADR, good faith, good faith, juridical security, legal regulation, trade mechanisms, transnational business negotiations

Procedia PDF Downloads 128

Authors: Sandhra M. Pillai

Abstract:

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

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

Procedia PDF Downloads 48

Authors: Mayar Almasri, Rosa Helmi, Rayana Enany

Abstract:

This report describes the features of AutoCAD software released by Adobe. It explains how the program makes it easier for engineers and designers and reduces their time and effort spent using AutoCAD. Moreover, it highlights how AutoCAD works, how some of the commands used in it, such as Shortcut, make it easy to use, and features that make it accurate in measurements. The results of the report show that most users of this program are designers and engineers, but few people know about it and find it easy to use. They prefer to use it because it is easy to use, and the shortcut commands shorten a lot of time for them. The feature got a high rate and some suggestions for improving AutoCAD in Aperture, but it was a small percentage, and the highest percentage was that they didn't need to improve the program, and it was good.

Keywords: artificial intelligence, design, planning, commands, autodesk, dimensions

Procedia PDF Downloads 112

Authors: Vickie Knox

Abstract:

Since the ‘urgent humanitarian crisis’ of the arrival of tens of thousands of Central American minors at the Mexico-US border in early 2014, the USA has increasingly externalised migration controls to Mexico. Although the resulting policy ‘Plan Frontera Sur’ claimed to protect migrants’ human rights, it has manifested as harshly delivered in-country controls and an alarming increase in deportations, particularly of minors. This is of particular concern given the ongoing situation of forced migration caused by criminal violence in Central America because these deportations do not all comply with Mexico’s international obligations and with its own legal framework for international protection that allows inter alia verbal asylum claims and grants minors additional protection against deportation. Notably, the volume of deportations, the speed with which they are carried out and the lack of adequate screening indicate non-compliance with the principle of non-refoulement and the right to claim asylum or other forms of protection. Based on qualitative data gathered in fieldwork in 2015 and quantitative data covering the period 2014-2016, this research details three types of adverse outcome resulting from these externalised controls: human rights violations perpetrated in order to deliver the policy–namely, deportations that may not comply with the principle of non-refoulement or the protection of minors; human rights violations perpetrated in the execution of policy–such as violations by state actors during apprehension and detention; and adverse consequences of the policy – such as increased risk during transit. This research has particular resonance as the Trump era brings tighter enforcement in the region, and has broader relevance for the study of externalisation tools on a global level.

Keywords: deportation, externalisation, forced migration, non-refoulement

Procedia PDF Downloads 135

Authors: Jansen Ang, Andrew Neo, Dawn Chia

Abstract:

Border Security is unlike mainstream policing in that officers are essentially in static deployment, working round the clock every day and every hour of the year looking for illegitimate entry of persons and goods. In Singapore, Border Security officers perform multiple functions to ensure the nation’s safety and security. They are responsible for safeguarding the borders of Singapore to prevent threats from entering the country. Being the first line of defence in ensuring the nation’s border security officers are entrusted with the responsibility of screening travellers inbound and outbound of Singapore daily. They examined 99 million arrivals and departures at the various checkpoints in 2014, which is a considerable volume compared to most immigration agencies. The officers’ work scopes also include cargo clearance, protective and security functions of checkpoints. The officers work in very demanding environment which can range from the smog at the land checkpoints to the harshness of the ports at the sea checkpoints. In addition, all immigration checkpoints are located at the boundaries, posing commuting challenges for officers. At the land checkpoints, festive seasons and school breaks are peak periods as given the surge of inbound and outbound travellers at the various checkpoints. Such work provides unique challenges in comparison to other law enforcement duties. This paper assesses the current stressors faced by officers of a border security agency through the conduct of ground observations as well as a perceived stress survey as well as recommendations in combating stressors faced by border security officers. The findings from the field observations and surveys indicate organisational and operational stressors that are unique to border security and recommends interventions in managing these stressors. Understanding these stressors would better inform border security agencies on the interventions needed to enhance the resilience of border security officers.

Keywords: border security, Singapore, stress, operations

Procedia PDF Downloads 308

Authors: Eglė Bilevičiūtė, Vidmantas Egidijus Kurapka, Snieguolė Matulienė, Sigutė Stankevičiūtė

Abstract:

The Council of European Union (EU Council) has stressed on several occasions the need for a concerted, comprehensive and effective solution to delinquency problems in EU communities. In the context of establishing a European Forensic Science Area and the development of forensic science infrastructure in Europe, EU Council believes that forensic science can significantly contribute to the efficiency of law enforcement, crime prevention and combating crimes. Lithuanian scientists have consolidated to implement a project named “Conception of the vision for European Forensic Science 2020 implementation in Lithuania” (the project is funded for the period of 1 March 2014 - 31 December 2016) with the objective to create a conception of implementation of the vision for European Forensic Science 2020 in Lithuania by 1) evaluating the current status of Lithuania’s forensic system and opportunities for its improvement; 2) analysing achievements and knowledge in investigation of crimes listed in conclusions of EU Council on the vision for European Forensic Science 2020 including creation of a European Forensic Science Area and the development of forensic science infrastructure in Europe: trafficking in human beings, organised crime and terrorism; 3) analysing conceptions of criminalistics, which differ in different EU member states due to the variety of forensic schools, and finding means for their harmonization. Apart from the conception of implementation of the vision for European Forensic Science 2020 in Lithuania, the project is expected to suggest provisions that will be relevant to other EU countries as well. Consequently, the presented conception of implementation of vision for European Forensic Science 2020 in Lithuania could initiate a project for a common vision of European Forensic Science and contribute to the development of the EU as an area of freedom, security and justice. The article presents main ideas of the project of the conception of the vision for European Forensic Science 2020 of EU Council and analyses its legal background, as well as prospects of and challenges for its implementation in Lithuania and the EU.

Keywords: EUROVIFOR, standardization, vision for European Forensic Science 2020, Lithuania

Procedia PDF Downloads 386

Authors: Mohsen Shakerinejad

Abstract:

Due to the growing momentum of technology, the present age is called age of communication and information. And With Astounding progress of Communication and information tools, current world Is likened to the "global village". That a message can be sent from one point to another point of the world in a Time scale Less than a minute. However, one of the new sociologists -Alain Touraine- in describing the destructive effects of new changes arising from the development of information appliances refers to the "new fields for undemocratic social control And the incidence of acute and unrest social and political tensions", Yet, in this era That With the advancement of the industry, the life of people has been industrial too, quickly and accurately Data Transfer, Causes Blowing new life in the Body of Society And according to the features of each society and the progress of science and technology, Various tools should be used. One of these communication tools is Mobile. Cellular phone As Communication and telecommunication revolution in recent years, Has had a great influence on the individual and collective life of societies. This powerful communication tool Have had an Undeniable effect, On all aspects of life, including social, economic, cultural, scientific, etc. so that Ignoring It in Design, Implementation and enforcement of any system is not wise. Nowadays knowledge and information are one of the most important aspects of human life. Therefore, in this article, it has been tried to introduce mobile potentials in receive and transmit News and Information. As it follows, among the numerous capabilities of current mobile phones features such as sending text, photography, sound recording, filming, and Internet connectivity could indicate the potential of this medium of communication in the process of sending and receiving information. So that nowadays, mobile journalism as an important component of citizen journalism Has a unique role in information dissemination.

Keywords: mobile, informing, receiving information, mobile journalism, citizen journalism

Procedia PDF Downloads 386

Authors: Muhammad Bilal Shaikh

Abstract:

Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 51

Authors: Foluke Abimbola

Abstract:

There are two separate groups of a recognised body of human rights. These are known as Civil and Political Rights, and Economic and Social Rights. There is however an impression that civil and political rights are enforceable in courts while socio-economic rights are not. Nigeria is an example of one of such countries whose constitution has social, economic and cultural rights’ provisions as well as civil and political rights. However, the socio-economic rights provided in the Nigerian constitution are not justiciable or are unenforceable in a court of law. On the other hand, a comparative examination of the socio-economic right provisions in the South African constitution and judgments of the constitutional court of South Africa reveals that socio-economic rights may be enforceable. This position may ensure the protection of the socio-economic rights of the poor and vulnerable groups. These rights include the rights to food, adequate shelter, health, and education. Moreover, the African Charter on Human and Peoples’ Rights (African Charter) which incorporates similar socio-economic right provisions, has been recognized as a domestic law in Nigeria and its provisions are enforceable by the domestic courts by virtue of the African Charter on Human and People’s Rights (Ratification and Enforcement) Act Cap A9 Laws of the Federation of Nigeria 2004. It is not only a regional treaty signed and adopted by Nigeria but has been passed into law by the National Assembly and can be enforced like any other local law. This paper will propose that in view of the provisions of the African Charter and mechanisms for implementation as well as other international conventions and national constitutional provisions on human rights, domestic courts may be able to assess state responsibilities in the light of socio-economic rights. Cases decided by South African courts and other jurisdictions will be discussed in order to lend weight to the notion that socio-economic rights can be enforced in jurisdictions such as Nigeria even though the constitution provides otherwise.

Keywords: african charter, constitutional court of south africa, nigerian constitution, socio-economic rights, south african constitution

Procedia PDF Downloads 132

Authors: Ashutosh Mishra, Nikhil Goyal

Abstract:

A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

Procedia PDF Downloads 204

Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

Abstract:

Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

Procedia PDF Downloads 106

Authors: Lucy Tsado

Abstract:

As cybercrime and cyberattacks continue to increase, the need to respond will follow suit. When cybercrimes occur, the duty to respond sometimes falls on law enforcement. However, criminal justice students are not taught concepts in cybersecurity and digital forensics. There is, therefore, an urgent need for many more institutions to begin teaching cybersecurity and related courses to social science students especially criminal justice students. However, many faculty in universities, colleges, and high schools are not equipped to teach these courses or do not have the knowledge and resources to teach important concepts in cybersecurity or digital forensics to criminal justice students. This research intends to develop curricula and training programs to equip faculty with the skills to meet this need. There is a current call to involve non-technical fields to fill the cybersecurity skills gap, according to experts. There is a general belief among non-technical fields that cybersecurity education is only attainable within computer science and technologically oriented fields. As seen from current calls, this is not entirely the case. Transitioning into the field is possible through curriculum development, training, certifications, internships and apprenticeships, and competitions. There is a need to identify how a cybersecurity eco-system can be created at a university to encourage/start programs that will lead to an interest in cybersecurity education as well as attract potential students. A short-term strategy can address this problem through curricula development, while a long-term strategy will address developing training faculty to teach cybersecurity and digital forensics. Therefore this research project addresses this overall problem in two parts, through curricula development for the criminal justice discipline; and training of faculty in criminal justice to teaching the important concepts of cybersecurity and digital forensics.

Keywords: cybersecurity education, criminal justice, curricula development, nontechnical cybersecurity, cybersecurity, digital forensics

Procedia PDF Downloads 82

Authors: Bodhayan Nandi, Shubhajit Roy Chowdhury

Abstract:

This paper presents the development of a portable blood glucose monitoring device based on Near-Infrared Spectroscopy. The system supports Internet connectivity through WiFi and uploads the time series data of glucose concentration of patients to a server. In addition, the server is given sufficient intelligence to predict the future pathophysiological state of a patient given the current and past pathophysiological data. This will enable to prognosticate the approaching critical condition of the patient much before the critical condition actually occurs.The server hosts web applications to allow authorized users to monitor the data remotely.

Keywords: non invasive, blood glucose concentration, microcontroller, IoT, application server, database server

Procedia PDF Downloads 198

Authors: Nur Inayah Ismaniar, Sukri Palutturi, Ansariadi, Atjo Wahyu

Abstract:

Background: In various countries in the world, the problem of smoking is now considered something serious because of the effects of smoking which can not only lead to addiction but also have the potential to harm health. Public health authorities have concluded that one solution that can be done to protect the public from active smokers is to issue a policy that requires public facilities to be completely smoke-free. The hospital is one of the public facilities that has been designated as a smoke-free area. However, the implementation and maintenance of a successful program based on a smoke-free hospital are still considered an ongoing challenge worldwide due to the very low level of adherence. The low level of compliance with this smoke-free policy is also seen in other public facilities. The purpose of the literature review is to review the level of compliance with the application of the Non-Smoking Area policy, how this policy has succeeded in reducing smoking activity in hospitals, and what factors lead to such compliance in each country in the world. Methods: A literature review of articles was carried out on all types of research methods, both qualitative and quantitative. The sample is all subjects who are in the research location, which includes patients, staff and hospital visitors. Results: Various variations in the level of compliance were found in various kinds of literature. The literature with the highest level of compliance is 88.4%. Furthermore, several determinants that are known to affect the compliance of the Non-Smoking Area policies in hospitals include communication, information, knowledge, perceptions, interventions, attitudes and support. Obstacles to its enforcement are the absence of sanctions against violators of the Non-Smoking Area policy, the ineffectiveness of the function of policymakers in hospitals, and negative perceptions of smoking related to mental health. Conclusion: Violations of the Non-Smoking Area policy are often committed by the hospital staff themselves, which makes it difficult for this policy to be fully enforced at various points in the hospital.

Keywords: health policy, non-smoking area, hospital, implementation

Procedia PDF Downloads 71

Authors: Julio Vega

Abstract:

Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

Procedia PDF Downloads 105

Authors: Aliya Ashraf, Mehreen Sirshar, Fatima Akhtar, Farwa Kazmi, Jawaria Wazir

Abstract:

Vision, the basis for performing navigational tasks, is absent or greatly reduced in visually impaired people due to which they face many hurdles. For increasing the navigational capabilities of visually impaired people a desktop application ODAPTA is presented in this paper. The application uses camera to capture video from surroundings, apply various image processing algorithms to get information about path and obstacles, tracks them and delivers that information to user through voice commands. Experimental results show that the application works effectively for straight paths in daylight.

Keywords: visually impaired, ODAPTA, Region of Interest (ROI), driver fatigue, face detection, expression recognition, CCD camera, artificial intelligence

Procedia PDF Downloads 528

Authors: Gilberto Goracci, Fabio Curti

Abstract:

This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

Procedia PDF Downloads 85

Authors: Pritam Kumar Ghosh

Abstract:

The phenomenon of inter-country parental child removal and the protection of children against removal from lawful custody by their own parents has been a major issue over the last five decades. This occurs when parents take away their children during pending divorce and custody proceedings or in violation of pre-existing foreign or Indian custody orders through which they may have obtained visitation rights only after divorce but not permanent custody. Even though considerable efforts have been made by the Indian judiciary to resolve the issue, a lot is still left to be desired. A study of the spate of judicial decisions on the issue since 1970 reveals that judges have attempted to resolve the issue mainly through the application of the existing personal law regime and the principle of the best interest of the child. This has made the position of law extremely confusing. The existing precedential jurisprudence contains a wide variety of custody orders in the name of enforcement of the paramount consideration of the best interest and welfare of children. The problem is aggravated by the fact that India has decided not to accede to the Hague Abduction Convention of 1980, which is the main international instrument combating the issue. In this context, the paper discusses the reasons behind the rising instances of inter-country parental child removals. It then goes on to analyze the existing jurisprudence of international child custody disputes in India, which have come before courts post-removal of children from lawful custody. The paper concludes by suggesting essential reforms in the existing Indian legal framework governing the issue. In the process, the paper proposes new legislation for India governing inter-country parental child removals and subsequent custody disputes. The possible structure and content of this new law shall also be outlined as a part of the paper.

Keywords: custody, dispute, child removal, Hague convention

Procedia PDF Downloads 54

Authors: Molly Meadows

Abstract:

Following the presidency of Donald J. Trump, Americans have become hyperaware of ethnocentrisms that plague the culture. The president's egoist ethics encouraged a divide between what the citizens of the US identified as just or unjust. In the race for global supremacy and leading ideology, fears have arisen, exacerbated by the ethnocentricity of the country's leader, pointing to the possible harmful ethical standards of competing nations. Due to the concept of ethical absolutism, an international code of ethics would not be possible, and the changes needed to eliminate the stigma surrounding other cultures of thought would need to come from the governing body of the US. As the current leading global ideology, the US would need its government to embody a transformational leadership style in order to unite the motivations of the citizens and encourage intercultural tolerance.

Keywords: ethics, transformational leadership, American politics, egoism, cultural intelligence, ethical relativism

Procedia PDF Downloads 74

Authors: Menglu Yang, Ani Beybutyan, Rocio Pina, Miguel Angel Soria

Abstract:

Domestic violence against women is one of the most serious social problems in the world. Attitudes toward domestic violence against women play an important role in the perpetration of violence against women, the way that victims respond to the violence, and how the community responds to violence against women. China and Spain are countries which have been influenced by the culture which males hold power and dominance over the female for a long time. However, as more connected with other European countries, the legal enforcement related to domestic violence against women developed earlier in Spain, and consequently, social awareness of violence against women evolved differently in two countries. The present study aimed to explore and compare the attitudes toward domestic violence against women across China and Spain, and their influence factors, such as gender equality attitudes and coercive control. Totally 506 participants, 255 from China and 251 from Spain completed questionnaires, including attitudes toward domestic violence against women, definition of violence behavior, justification for violence, gender equity attitudes, and coercive control. Results demonstrated that Chinese participants were less aware of domestic violence against women issue but more agreed that such issue was a crime than Spanish participants. In addition to cultural difference, gender equality attitudes, coercive control, gender, and age also affected attitudes toward domestic violence against women. Our findings imply attitudes toward domestic violence against women differ from countries along with the difference in gender equity attitudes and coercive control; such a difference may arise from cultural, traditional belief and current justice system influence. Despite the developed justice system, male dominance culture may lead to maintain the belief that domestic violence is domestic and private issue which police and justice force may not get involved.

Keywords: cross-cultural differences, domestic violence, public attitudes, violence against women

Procedia PDF Downloads 254

Authors: P. W. Tsai, W. L. Hong, C. W. Chen, C. Y. Chen

Abstract:

In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.

Keywords: Lyapunov stability, parallel particle swarm optimization, linear differential inclusion, artificial intelligence

Procedia PDF Downloads 634

Authors: Sarah Mohammed, Huda Allagany, Ayah Barakat, Muna Elyas

Abstract:

This paper delves into the history and development of ChatGPT, tracing its evolution from its inception by OpenAI to its current state, and emphasizing its design improvements and strategic partnerships. It also explores the performance and applicability of ChatGPT versions 3.5 and 4 in various contexts, examining its capabilities and limitations in producing accurate and relevant responses. Utilizing a quantitative approach, user satisfaction, speed of response, learning capabilities, and overall utility in academic performance were assessed through surveys and analysis tools. Findings indicate that while ChatGPT generally delivers high accuracy and speed in responses, the need for clarification and more specific user instructions persists. The study highlights the tool's increasing integration across different sectors, showcasing its potential in educational and professional settings.

Keywords: artificial intelligence, chat GPT, analysis, education

Procedia PDF Downloads 24

Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

Abstract:

Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

Procedia PDF Downloads 444

Authors: Aron Witkowski, Andrzej Wodecki

Abstract:

Purpose: This study aims to explore the feasibility and effectiveness of utilizing Generative Artificial Intelligence (GenAI) agents as product managers within the manufacturing sector. It seeks to evaluate whether current GenAI capabilities can fulfill the complex requirements of product management and deliver comparable outcomes to human counterparts. Study Design/Methodology/Approach: This research involved the creation of a support application for product managers, utilizing high-quality sources on product management and generative AI technologies. The application was designed to assist in various aspects of product management tasks. To evaluate its effectiveness, a study was conducted involving 10 experienced product managers from the manufacturing sector. These professionals were tasked with using the application and providing feedback on the tool's responses to common questions and challenges they encounter in their daily work. The study employed a mixed-methods approach, combining quantitative assessments of the tool's performance with qualitative interviews to gather detailed insights into the user experience and perceived value of the application. Findings: The findings reveal that GenAI-based product management agents exhibit significant potential in handling routine tasks, data analysis, and predictive modeling. However, there are notable limitations in areas requiring nuanced decision-making, creativity, and complex stakeholder interactions. The case study demonstrates that while GenAI can augment human capabilities, it is not yet fully equipped to independently manage the holistic responsibilities of a product manager in the manufacturing sector. Originality/Value: This research provides an analysis of GenAI's role in product management within the manufacturing industry, contributing to the limited body of literature on the application of GenAI agents in this domain. It offers practical insights into the current capabilities and limitations of GenAI, helping organizations make informed decisions about integrating AI into their product management strategies. Implications for Academic and Practical Fields: For academia, the study suggests new avenues for research in AI-human collaboration and the development of advanced AI systems capable of higher-level managerial functions. Practically, it provides industry professionals with a nuanced understanding of how GenAI can be leveraged to enhance product management, guiding investments in AI technologies and training programs to bridge identified gaps.

Keywords: generative artificial intelligence, GenAI, NPD, new product development, product management, manufacturing

Procedia PDF Downloads 28

Authors: Aydin Azizi, Aburrahman Tanira

Abstract:

The main source of energy used in this modern age is fossil fuels. There is a myriad of problems that come with the use of fossil fuels, out of which the issues with the greatest impact are its scarcity and the cost it imposes on the planet. Fossil fuels are the only plausible option for many vital functions and processes; the most important of these is transportation. Thus, using this source of energy wisely and as efficiently as possible is a must. The aim of this work was to explore utilising mathematical modelling and artificial intelligence techniques to enhance fuel consumption in passenger cars by focusing on the speed at which cars are driven. An artificial neural network with an error less than 0.05 was developed to be applied practically as to predict the rate of fuel consumption in vehicles.

Keywords: mathematical modeling, neural networks, fuel consumption, fossil fuel

Procedia PDF Downloads 384