• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.135-148
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• 2023

The Code of Ethics for Newspaper Advertising in Korea, first implemented in 1976 and subsequently revised in 1976, 1996, and 2021, is a critical regulatory instrument for the country's advertising sector. However, the specialized domain of "advertising ethics," particularly the "code of advertising ethics," remains under-explored. This research addresses this scholarly gap, providing an empirical analysis of the 2021 amendment's revision trajectory. This study employs a robust methodological approach, integrating expert interviews and small-group AHP-based surveys. This approach allows for a comprehensive understanding of the revision needs, referencing existing ethical codes studies, and comparing similar ethics codes nationally and internationally. The research further investigates key challenges such as personal data protection and copyright issues in the rapidly evolving digital media landscape, while preserving the existing code's inherent value. The findings are expected to significantly contribute to the emerging field of advertising ethics in Korea, offering practical implications for future code revisions.

• Korean journal of aerospace and environmental medicine
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• v.29 no.2
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• pp.59-66
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• 2019

Artificial Intelligence (AI) born in 1956 is a general term that implies the use of a computer to make intelligent machines with minimal human intervention. AI is a topic dominating diverse discussions on the future of professional employment, change in the social standard and economic performance. In this paper, I describe fundamental concepts underlying AI and their significance to various fields including aviation and medicine. I highlight issues involved and describe the potential impacts and challenges to the industrial fields. While many benefits are expected in human life with AI integration, problems are needed to be identified and discussed with respect to ethical issues and the future roles of professionals and specialists for their wider application of AI.

• Women's Health Nursing
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• v.29 no.3
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• pp.239-242
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• 2023

Artificial intelligence (AI) has tremendous potential to change the way we train future health professionals. Although AI can provide improved realism, engagement, and personalization in nursing simulations, it is also important to address any issues associated with the technology, teaching methods, and ethical considerations of AI. In nursing simulation education, AI does not replace the valuable role of nurse educators but can enhance the educational effectiveness of simulation by promoting interdisciplinary collaboration, faculty development, and learner self-direction. We should continue to explore, innovate, and adapt our teaching methods to provide nursing students with the best possible education.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.318-325
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• 2024

The rapid advancement of drone technology has led to the emergence of drone swarms, a game-changing concept in modern warfare. This study explores the military applications, countermeasures, and strategic implications of drone swarms. By examining the current trends in drone swarm development and deployment, this research highlights the potential of this technology to revolutionize the battlefield. The study also investigates the challenges and vulnerabilities associated with drone swarms, emphasizing the need for effective countermeasures. Through an analysis of multi-sensor fusion, directed energy weapons, and artificial intelligence, this research proposes comprehensive strategies to counter the threats posed by drone swarms. Furthermore, the study delves into the ethical and legal issues surrounding the use of autonomous drone swarms, underscoring the necessity for international norms and regulations. The findings of this research contribute to the understanding of the transformative impact of drone swarms on military strategy and national security, while providing valuable insights for policymakers, military strategists, and researchers in the field.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.211-218
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• 2023

Background: Traditional wildlife monitoring has often relied on invasive techniques posing risks to species and demanding substantial resources. To address this, camera traps emerged as non-invasive alternatives, albeit primarily tailored for larger mammals, posing limitations for small mammal research. Thus, the Mostela, an innovative tool designed to overcome these challenges, was introduced to monitor small mammals in South Korea. Results: The Mostela was deployed at two study sites in South Korea, yielding compelling evidence of its efficiency in capturing small mammal species. By analyzing the collected data, we calculated the relative abundance of each species and elucidated their activity patterns. Conclusions: In summary, the Mostela system demonstrates substantial potential for advancing small mammal monitoring, offering valuable insights into diversity, community dynamics, activity patterns, and habitat preferences. Its application extends to the detection of endangered and rare species, further contributing to wildlife conservation efforts in South Korea. Consequently, the Mostela system stands as a valuable addition to the toolkit of conservationists and researchers, fostering ethical and non-invasive research practices while advancing our understanding of small mammal populations and ecosystems.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.9
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• pp.4961-4964
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• 2013

Greater use of mobile phone devices seems inevitable because the health industry and cancer care are facing challenges such as resource constraints, rising care costs, the need for immediate access to healthcare data of types such as audio video texts for early detection and treatment of patients and increasing remote aids in telemedicine. Physicians, in order to study the causes of cancer, detect cancer earlier, act in prevention measures, determine the effectiveness of treatment and specify the reasons for the treatment ineffectiveness, need to access accurate, comprehensive and timely cancer data. Mobile devices provide opportunities and can play an important role in consulting, diagnosis, treatment, and quick access to health information. There easy carriage make them perfect tools for healthcare providers in cancer care management. Key factors in cancer care management systems through a mobile phone health approach must be considered such as human resources, confidentiality and privacy, legal and ethical issues, appropriate ICT and provider infrastructure and costs in general aspects and interoperability, human relationships, types of mobile devices and telecommunication related points in specific aspects. The successful implementation of mobile-based systems in cancer care management will constantly face many challenges. Hence, in applying mobile cancer care, involvement of users and considering their needs in all phases of project, providing adequate bandwidth, preparation of standard tools that provide maximum mobility and flexibility for users, decreasing obstacles to interrupt network communications, and using suitable communication protocols are essential. It is obvious that identifying and reducing barriers and strengthening the positive points will have a significant role in appropriate planning and promoting the achievements of mobile cancer care systems. The aim of this article is to explain key points which should be considered in designing appropriate mobile health systems in cancer care as an approach for improving cancer care management.

• Journal of Animal Science and Technology
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• v.63 no.4
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• pp.693-724
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• 2021

The in-vitro meat is a novel concept in food biotechnology comprising field of tissue engineering and cellular agriculture. It involves production of edible biomass by in-vitro culture of stem cells harvested from the muscle of live animals by self-organizing or scaffolding methodology. It is considered as efficient, environmental friendly, better ensuring public safety and nutritional security, as well as ethical way of producing meat. Source of stem cells, media ingredients, supply of large size bioreactors, skilled manpower, sanitary requirements, production of products with similar sensory and textural attributes as of conventional meat, consumer acceptance, and proper set up of regulatory framework are challenges faced in commercialization and consumer acceptance of in-vitro meat. To realize any perceivable change in various socio-economic and environmental spheres, the technology should be commercialized and should be cost-effective as conventional meat and widely accepted among consumers. The new challenges of increasing demand of meat with the increasing population could be fulfill by the establishment of in-vitro meat production at large scale and its popularization. The adoption of in-vitro meat production at an industrial scale will lead to self-sufficiency in the developed world.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Journal of Korean Neurosurgical Society
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• v.67 no.5
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• pp.493-509
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• 2024

In neurointensive care units (NICUs), particularly in cases involving traumatic brain injury (TBI), swift and accurate decision-making is critical because of rapidly changing patient conditions and the risk of secondary brain injury. The use of artificial intelligence (AI) in NICU can enhance clinical decision support and provide valuable assistance in these complex scenarios. This article aims to provide a comprehensive review of the current status and future prospects of AI utilization in the NICU, along with the challenges that must be overcome to realize this. Presently, the primary application of AI in NICU is outcome prediction through the analysis of preadmission and high-resolution data during admission. Recent applications include augmented neuromonitoring via signal quality control and real-time event prediction. In addition, AI can integrate data gathered from various measures and support minimally invasive neuromonitoring to increase patient safety. However, despite the recent surge in AI adoption within the NICU, the majority of AI applications have been limited to simple classification tasks, thus leaving the true potential of AI largely untapped. Emerging AI technologies, such as generalist medical AI and digital twins, harbor immense potential for enhancing advanced neurocritical care through broader AI applications. If challenges such as acquiring high-quality data and ethical issues are overcome, these new AI technologies can be clinically utilized in the actual NICU environment. Emphasizing the need for continuous research and development to maximize the potential of AI in the NICU, we anticipate that this will further enhance the efficiency and accuracy of TBI treatment within the NICU.

• Analyses & Alternatives
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• v.8 no.3
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• pp.125-150
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• 2024

This paper explores the integration of artificial intelligence and causal inference in social science research, focusing on causal deep learning. We examine key theories including Pearl's Structural Causal Model, Rubin's Potential Outcomes Framework, and Schölkopf's Causal Representation Learning. Methodologies such as structural causal models with deep learning, counterfactual reasoning, and causal discovery algorithms are discussed. The paper presents applications in social media analysis, economic policy, public health, and education, demonstrating how causal deep learning enables nuanced understanding of complex social phenomena. Key challenges addressed include model complexity, causal identification, interpretability, and ethical considerations like fairness and privacy. Future research directions include developing new AI architectures, real-time causal inference, and multi-domain generalization. While limitations exist, causal deep learning shows significant potential for enhancing social science research and informing evidence-based policy-making, contributing to addressing complex social challenges globally.