• Journal of Information Processing Systems
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• 제19권3호
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• pp.302-309
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• 2023

Artificial intelligence (AI) plays a crucial role in the intelligent development of China's power system. It is also an important part of the digital development of the power grid. The development of AI determines whether the digital transformation of China's power system can be successfully implemented. Therefore, this paper discusses the digital transformation of the power grid based on AI technologies. The author has established a digital evaluation index system to reflect the development of the power grid in one province. Both qualitative and quantitative methods have been adopted in the analysis, which delves into the economic effectiveness, quality, and coordination of power grid development in the province in a comprehensive way. Results show that, to meet the needs of the power grid's digital transformation, the correlation coefficient between the power grid's development and the province's overall coordination has been increasing in recent years.

• 한국항공운항학회지
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• 제31권3호
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• pp.172-177
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• 2023

The main purpose of the research was to review the global trends of airport's smart security technologies. Moreover, using the case studies of airport using smart security, this paper tried to propose the implication how the findings through the case studies may be important for airport policy and will impact the future research of airport operation. It is expected in the future the aviation security technology with biometric information evolves from single identification to multiple identification technology which has combined application of iris, vein and others. Facing post COVID-19 era, the number of passengers traveling through airports continues increase dramatically and the risks as well, the role of AI becomes even more crucial. With AI based automated security robotics airport operators could effectively handle the growing passenger and cargo volume and address the associated issues Smart CCTV analysis with A.I. and IoT applying solutions could also provide significant support for airport security.

• 연구논문집
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• 통권28호
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• pp.13-20
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• 1998

The power steering pump bracket for a passenger car which is mounted on the engine block plays a role to support the inertia forces of the pump and the reaction forces of the belt assembly. The existing bracket which is made of FCD material has some demerits such as heavy weight, lower productivity and lower reliability. Recently, AI alloy bracket has been investigated to overcome these demerits. In this study, Stress analysis and modal analysis for a existing FCD bracket and two type of AI alloy brackets were performed, and strength and natural frequency of them were estimated by using finite element method to accomplish the weight reduction. As a result, the modified shape of AI alloy bracket is proposed, and it has achieved the 45% weight reduction and the improvement of its strength and vibration characteristics.

• 로봇학회논문지
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• 제1권2호
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• pp.203-211
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• 2006

In this research, a comprehensive study is performed upon the design of a quadruped walking robot. In advance, the walking posture and skeletal configuration of the vertebrate are analyzed to understand quadrupedal locomotion, and the roles of limbs during walking are investigated. From these, it is known that the forelimbs just play the role of supporting their body and help vault forward, while most of the propulsive force is generated by hind limbs. In addition, with the study of the stances on walking and energy efficiency, design criteria and control method for a quadruped walking robot are derived. The proposed controller, though it is simple, provides a useful framework for controlling a quadruped walking robot. In particular, introduciton of a new rhythmic pattern generator relieves the heavy computational burden because it does not need any computation on kinematics. Finally, the proposed method is validated via dynamic simulations and implementing in a quadruped walking robot, called AiDIN(Artificial Digitigrade for Natural Environment).

• International journal of advanced smart convergence
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• 제13권2호
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• pp.25-34
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• 2024

The paper investigates how the semiconductor and electric vehicle industries are addressing safety and security concerns in the era of autonomous driving, emphasizing the prioritization of safety over security for market competitiveness. Collaboration between these sectors is deemed essential for maintaining competitiveness and value. The research suggests solutions such as advanced autonomous driving technologies and enhanced battery safety measures, with the integration of AI chips playing a pivotal role. However, challenges persist, including the limitations of big data and potential errors in semiconductor-related issues. Legacy automotive manufacturers are transitioning towards software-driven cars, leveraging artificial intelligence to mitigate risks associated with safety and security. Conflicting safety expectations and security concerns can lead to accidents, underscoring the continuous need for safety improvements. We analyzed the expansion of electric vehicles as a means to enhance safety within a framework of converging security concerns, with AI chips being instrumental in this process. Ultimately, the paper advocates for informed safety and security decisions to drive technological advancements in electric vehicles, ensuring significant strides in safety innovation.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2024년도 춘계학술발표대회
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• pp.337-340
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• 2024

Pretrained language models (PLMs) are extensively utilized to enhance the performance of log anomaly detection systems. Their effectiveness lies in their capacity to extract valuable semantic information from logs, thereby strengthening the detection performance. Nonetheless, challenges arise due to discrepancies in the distribution of log messages, hindering the development of robust and generalizable detection systems. This study investigates the structural and distributional variation across various log message datasets, underscoring the crucial role of domain-specific PLMs in overcoming the said challenge and devising robust and generalizable solutions.

• 동의생리병리학회지
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• 제35권1호
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• pp.22-27
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• 2021

This study conducted a questionnaire for students of Pusan National University Graduate School of Korean Medicine who practiced using the Oriental Medicine Diagnosis System (ODS). From the questionnaire, this study investigated current state of application and perception of AI in Korean Medicine and explored the direction of ODS improvement and utilization. The survey questions consisted of six questions examining the satisfaction of the diagnostic expert system, five questions evaluating the availability of the diagnostic expert system, and six questions to predict the impact of AI on the Korean medicine community. The survey analysis showed high satisfaction with practice using ODS. On the other hand, the possibility of using ODS, especially in clinical use, was evaluated as relatively low compared to the satisfaction of the practice. Therefore, the overall impact of AI on the Korean medical community is not expected to be large. Although there are difficulties in standardization of clinical data due to the academic characteristics of Korean medicine, it is necessary to continue attempts to apply AI. By actively introducing educational tools using the latest AI techniques to the diagnosis experience and doctor-patient role in a practice, students will be able to increase their satisfaction with their practice and respond appropriately to the state-of-the-art medical environment.

• Journal of Korean Neurosurgical Society
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• 제66권6호
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• pp.632-641
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• 2023

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI's role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O'Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient's prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

• 문화기술의 융합
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• 제10권1호
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• pp.121-128
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• 2024

최근 AI기반 온라인 번역 도구의 활용도가 높아짐에 따라 이에 대한 교육적 활용 방안 및 효과에 대한 관심이 높아지고 있다. 본 연구에서는 초등 예비교사를 30명을 대상으로 AI기반 온라인 번역도구를 활용한 영작문 과업을 수행하고 영어 글쓰기 능력에 미치는 영향과 실제적 경험을 기반으로 AI번역도구에 대한 활용 가능성, 교육적 활용도 및 장단점 등에 대한 인식을 살펴보았다. 작문시험, 설문조사와 인터뷰를 통해 수집된 자료를 바탕으로 분석한 결과, 영어 글쓰기의 완성도 및 충실도에 있어서 유의미한 증가를 보였으며, 학습자들의 인식에서도 번역도구의 사용은 학습에 대한 즉각적인 지원과 편의성을 제공, 효과적인 도구활용을 위한 교육적 전략의 필요성에 대한 긍정적 인식도 나타났으나, 번역의 완성도나 정확성을 높이기 위한 방법, 도구 활용에 대한 과용과 의존성에 대한 우려도 제기되었다. 번역도구의 효과적 활용을 위해서 교육적 전략이나 교사의 역할의 중요한 것으로 나타났다.

• 전자통신동향분석
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• 제39권4호
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• pp.32-41
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• 2024

Building energy management plays a crucial role in improving energy efficiency and optimizing energy usage. To achieve this, it is important to monitor and analyze energy-related data from buildings in real time using sensors to understand energy consumption patterns and establish optimal operational strategies. Because of the uncertainties in building energy-related data, there are challenges in analyzing these data and formulating operational strategies based on them. Artificial intelligence (AI) technology can help overcome these challenges. This paper investigates past and current research trends in AI technology and examines its future prospects for building energy management. By performing prediction and analysis based on energy consumption or supply data, the future energy demands of buildings can be forecasted and energy consumption can be optimized. Additionally, data related to the surrounding environment, occupancy, and other building energy-related factors can be collected and analyzed using sensors to establish operational strategies aimed at further reducing energy consumption and increasing efficiency. These technologies will contribute to cost savings and help minimize environmental impacts for building owners and operators, ultimately facilitating sustainable building operations.