• 스마트미디어저널
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• 제13권2호
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• pp.44-51
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• 2024

스트레스 측정용 데이터셋의 구축은 건강, 의료분야, 심리향동, 교육분야 등 현대의 다양한 응용 분야에서 핵심적인 역할을 수행하교 있다. 특히, 스트레스 측정용 인공지능 모델의 효율적인 훈련을 위해서는 다양한 편향성을 제거하고 품질 관리된 데이터셋을 구축하는 것이 중요하다. 본 논문에서는 다양한 편향성 제거를 통한 품질의 관리된 스트레스 측정용 데이터셋 구축에 관하여 제안하였다. 이를 위해 스트레스 정의 및 측정도구 소개, 스트레스 인공지능 데이터 셋 구축과정, 품질향상을 위한 편향성 극복 전략 그리고 스트레스 데이터 수집시 고려사항을 제시하였다. 특히, 데이터셋 품질을 관리하기 위해 데이터셋 구축시 고려사항과, 발생할 수 있는 선택편향, 측정편향, 인과관계편향, 확증편향, 인공지능편향과 같은 다양한 편향서에 대해 검토하였다. 본 논문을 통해 스트레스 데이터 수집시 고려사항과 스트레스 데이터셋의 구축에서 발생할 수 있는 다양한 편향성을 체계적으로 이해하고, 이를 극복하여 품질이 보장된 데이터셋을 구축하는데 기여할 것으로 기대된다.

• 한국인공지능학회지
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• 제11권1호
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• pp.9-15
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• 2023

As mobile devices such as smartphones, tablets, and kiosks become increasingly prevalent, there is growing interest in developing alternative input systems in addition to traditional tools such as keyboards and mouses. Many people use their own bodies as a pointer to enter simple information on a mobile device. However, methods using the body have limitations due to psychological factors that make the contact method unstable, especially during a pandemic, and the risk of shoulder surfing attacks. To overcome these limitations, we propose a simple information input system that utilizes gaze-tracking technology to input passwords and control web surfing using only non-contact gaze. Our proposed system is designed to recognize information input when the user stares at a specific location on the screen in real-time, using intelligent gaze-tracking technology. We present an analysis of the relationship between the gaze input box, gaze time, and average input time, and report experimental results on the effects of varying the size of the gaze input box and gaze time required to achieve 100% accuracy in inputting information. Through this paper, we demonstrate the effectiveness of our system in mitigating the challenges of contact-based input methods, and providing a non-contact alternative that is both secure and convenient.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.229-238
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• 2022

Due to digitization, data has become a tsunami in almost every data-driven business sector. The information wave has been greatly boosted by man-to-machine (M2M) digital data management. An explosion in the use of ICT for farm management has pushed technical solutions into rural areas and benefited farmers and customers alike. This study discusses the benefits and possible pitfalls of using information and communication technology (ICT) in conventional farming. Information technology (IT), the Internet of Things (IoT), and robotics are discussed, along with the roles of Machine learning (ML), Artificial intelligence (AI), and sensors in farming. Drones are also being studied for crop surveillance and yield optimization management. Global and state-of-the-art Internet of Things (IoT) agricultural platforms are emphasized when relevant. This article analyse the most current publications pertaining to precision agriculture using ML and AI techniques. This study further details about current and future developments in AI and identify existing and prospective research concerns in AI for agriculture based on this thorough extensive literature evaluation.

• 4차산업연구
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• 제2권1호
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• pp.19-32
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• 2022

Purpose - As new technologies that have led the 4th industrial revolution spread after the COVID-19 pandemic, the business crisis of existing financial institutions and the threat of employee jobs are growing, especially in the financial sector. The purpose of this study is to propose a human-technology convergence curriculum for creating high value-added in financial institutions and upskilling financial manpower. Research design, data, and methodology - In this study, a curriculum was designed to strengthen job competency for Private Bankers, high-quality employees of a bank dealing with high-net-worth owners. The focus of the design is that learners acquire skills to use robo-advisors as a tool and supplement artificial intelligence ethics. Result - The curriculum is organized into a total of 16 classes, and the main contents are changes in the financial environment and financial consumers, the core technology of robo-advisors and AI ethics, and establishment and evaluation of hyper-personalized asset management strategies using robo-advisors. To achieve the educational goal, two evaluations are performed to derive individual tasks and team project results. Conclusion - Human-centered upskilling convergence education will contribute to improving employee value and expanding corporate high value-added business areas by utilizing new technologies as tools. It is expected that the development and application of convergence curriculum in various fields will continue to be advanced in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권5호
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• pp.1466-1488
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• 2022

Recently, the importance and necessity of artificial intelligence (AI), especially machine learning, has been emphasized. In fact, studies are actively underway to solve complex and challenging problems through the use of AI systems, such as intelligent CCTVs, intelligent AI security systems, and AI surgical robots. Information security that involves analysis and response to security vulnerabilities of software is no exception to this and is recognized as one of the fields wherein significant results are expected when AI is applied. This is because the frequency of malware incidents is gradually increasing, and the available security technologies are limited with regard to the use of software security experts or source code analysis tools. We conducted a study on MalDC, a technique that converts malware into images using machine learning, MalDC showed good performance and was able to analyze and classify different types of malware. MalDC applies a preprocessing step to minimize the noise generated in the image conversion process and employs an image augmentation technique to reinforce the insufficient dataset, thus improving the accuracy of the malware classification. To verify the feasibility of our method, we tested the malware classification technique used by MalDC on a dataset provided by Microsoft and malware data collected by the Korea Internet & Security Agency (KISA). Consequently, an accuracy of 97% was achieved.

• 청정기술
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• 제29권2호
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• pp.145-150
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• 2023

Tele-metering systems have been useful tools for managing domestic wastewater treatment plants (WWTP) over the last decade. They mostly generate water quality data for discharged water to ensure that it complies with mandatory regulations and they may be able to produce every operation parameter and additional measurements in the near future. A sub-big data group, comprised of about 150,000 data points from four domestic WWTPs, was ready to be classified and also analyzed to optimize the WWTP process. We used the Statistical Product and Service Solutions (SPSS) 25 package in order to statistically treat the data with linear regression and correlation analysis. The major independent variables for analysis were water temperature, sludge recycle rate, electricity used, and water quality of the influent while the dependent variables representing the water quality of the effluent included the total nitrogen, which is the most emphasized index for discharged flow in plants. The water temperature and consumed electricity showed a strong correlation with the total nitrogen but the other indices' mutual correlations with other variables were found to be fuzzy due to the large errors involved. In addition, a multilayer perceptron analysis method was applied to TMS data along with root mean square error (RMSE) analysis. This study showed that the RMSE in the SS, T-N, and TOC predictions were in the range of 10% to 20%.

• 문화기술의 융합
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• 제9권4호
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• pp.659-666
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• 2023

생성형 인공지능 기술을 기반으로 한 도구 중 하나로 ChatGPT에 대한 활용 가능성이 모색되고 있다. 하지만 이를 교육적으로 활용할 때, 어떠한 요소를 고려해야 하는지를 학습자의 실제적인 인식을 기반으로 확인한 연구는 미흡하다. 본 연구는 교육 현장에서 ChatGPT를 활용할 때, 고려해야 하는 요소가 무엇인지를 질적 연구를 통해 도출하고자 하였다. 연구 결과, 교육에 있어서 ChatGPT를 효과적으로 활용하기 위해서는 생성된 정보에 대한 비판적 사고, 학습을 지원하는 한 가지 도구로서 인식하여 의존적인 활용 지양, 올바른 윤리적 활용에 대한 사전 교육 실시, 명확하고 적절한 질문 생성, 답변에 대한 재검토와 종합화 총 다섯 가지의 핵심 고려 요소를 확인하였다. 향후 이상의 요소를 종합적으로 구성한 교수설계 모형 개발이 이루어질 필요가 있다.

• Tuberculosis and Respiratory Diseases
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• 제86권4호
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• pp.251-263
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• 2023

The stethoscope has long been used for the examination of patients, but the importance of auscultation has declined due to its several limitations and the development of other diagnostic tools. However, auscultation is still recognized as a primary diagnostic device because it is non-invasive and provides valuable information in real-time. To supplement the limitations of existing stethoscopes, digital stethoscopes with machine learning (ML) algorithms have been developed. Thus, now we can record and share respiratory sounds and artificial intelligence (AI)-assisted auscultation using ML algorithms distinguishes the type of sounds. Recently, the demands for remote care and non-face-to-face treatment diseases requiring isolation such as coronavirus disease 2019 (COVID-19) infection increased. To address these problems, wireless and wearable stethoscopes are being developed with the advances in battery technology and integrated sensors. This review provides the history of the stethoscope and classification of respiratory sounds, describes ML algorithms, and introduces new auscultation methods based on AI-assisted analysis and wireless or wearable stethoscopes.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2024년도 춘계학술발표대회
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• pp.891-894
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• 2024

The quest for reliability in Artificial Intelligence (AI) is progressively urgent, especially in the field of next generation wireless networks. Future Beyond 5G (B5G)/6G networks will connect a huge number of devices and will offer innovative services invested with AI and Machine Learning tools. Wireless communications, in general, and medium access control (MAC) techniques were among the fields that were heavily affected by this improvement. This study presents the applications and services of future communication networks. This study details the Medium Access Control (MAC) scheduler of Beyond-5G/6G from 3^rd Generation Partnership (3GPP) and highlights the current open research issues which are yet to be optimized. This study provides an overview of how AI plays an important role in improving next generation communication by solving MAC-layer issues such as resource scheduling and queueing. We will select C-V2X as our use case to implement our proposed MAC scheduling model.

• 한국수학교육학회지시리즈A:수학교육
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• 제63권2호
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• pp.233-254
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• 2024

This paper delves into the symbiotic integration of coding and mathematics education, aimed at cultivating computational thinking and enriching mathematical problem-solving proficiencies. We have identified a corpus of scholarly articles (n=38) disseminated within the preceding two decades, subsequently culling a portion thereof, ultimately engendering a contemplative analysis of the extant remnants. In a swiftly evolving society driven by the Fourth Industrial Revolution and the ascendancy of Artificial Intelligence (AI), understanding the synergy between these domains has become paramount. Mathematics education stands at the crossroads of this transformation, witnessing a profound influence of AI. This paper explores the evolving landscape of mathematical cognition propelled by AI, accentuating how AI empowers advanced analytical and problem-solving capabilities, particularly in the realm of big data-driven scenarios. Given this shifting paradigm, it becomes imperative to investigate and assess AI's impact on mathematics education, a pivotal endeavor in forging an education system aligned with the future. The symbiosis of AI and human cognition doesn't merely amplify AI-centric thinking but also fosters personalized cognitive processes by facilitating interaction with AI and encouraging critical contemplation of AI's algorithmic underpinnings. This necessitates a broader conception of educational tools, encompassing AI as a catalyst for mathematical cognition, transcending conventional linguistic and symbolic instruments.