• The Mathematical Education
• /
• v.63 no.2
• /
• pp.233-254
• /
• 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.

• Korean Journal of Radiology
• /
• v.25 no.6
• /
• pp.518-539
• /
• 2024

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.

• Clinical Endoscopy
• /
• v.56 no.5
• /
• pp.553-562
• /
• 2023

Colonoscopy plays an important role in reducing the incidence and mortality of colorectal cancer by detecting adenomas and other precancerous lesions. Image-enhanced endoscopy (IEE) increases lesion visibility by enhancing the microstructure, blood vessels, and mucosal surface color, resulting in the detection of colorectal lesions. In recent years, various IEE techniques have been used in clinical practice, each with its unique characteristics. Numerous studies have reported the effectiveness of IEE in the detection of colorectal lesions. IEEs can be divided into two broad categories according to the nature of the image: images constructed using narrow-band wavelength light, such as narrow-band imaging and blue laser imaging/blue light imaging, or color images based on white light, such as linked color imaging, texture and color enhancement imaging, and i-scan. Conversely, artificial intelligence (AI) systems, such as computer-aided diagnosis systems, have recently been developed to assist endoscopists in detecting colorectal lesions during colonoscopy. To gain a better understanding of the features of each IEE, this review presents the effectiveness of each type of IEE and their combination with AI for colorectal lesion detection by referencing the latest research data.

• Electronics and Telecommunications Trends
• /
• v.35 no.5
• /
• pp.123-133
• /
• 2020

With the development of artificial intelligence (AI) and 5G technology, an ecosystem of digital content is gradually becoming intelligent, immersive, and convergent. However, there is not enough ultra-realistic content for the ecosystem. For ultra-realistic content services, creative content technologies using AI are being developed. This paper introduces the trends in and prospects of creative content technologies such as 3D content creation, digital holography, image-based motion recognition, content analysis/understanding/searching, sport AI, and content distribution.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.5079-5099
• /
• 2018

Regarding to the huge number of connections and the large flow of data on the Internet, Intrusion Detection System (IDS) has a difficulty to detect attacks. Moreover, irrelevant and redundant features influence on the quality of IDS precisely on the detection rate and processing cost. Feature Selection (FS) is the important technique, which gives the issue for enhancing the performance of detection. There are different works have been proposed, but a map for understanding and constructing a state of the FS in IDS is still need more investigation. In this paper, we introduce a survey of feature selection algorithms for intrusion detection system. We describe the well-known approaches that have been proposed in FS for IDS. Furthermore, we provide a classification with a comparative study between different contribution according to their techniques and results. We identify a new taxonomy for future trends and existing challenges.

• Journal of the Society of Disaster Information
• /
• v.19 no.1
• /
• pp.76-83
• /
• 2023

Purpose: In emergency situations such as earthquakes, heavy rains, typhoons, or fires, when quick delivery of emergency alerts is crucial, the hearing impaired are the ones who are the most disadvantaged and vulnerable when alerts are only delivered through auditory or text alerts. They can't perceive auditory information, and many have difficulties in fast understanding text-based alerts. Method: An alert system that can deliver pictograms for specific disaster situations has been devised. Then, a novel approach based on artificial intelligence has been studied so that the pictograms for specific disaster situations can be chosen instantly once a disaster alert is issued in text. Result: A disaster alert system that delivers pictograms for specific disaster situations was developed and a novel method has been suggested for automatic delivery. Conclusion: A system to instantaneously deliver disaster alert information in pictograms has been developed to improve alert delivery to the populations vulnerable to disaster due to hearing impairment by the instantaneous understanding of disaster situations through visual information.

• Journal of Practical Engineering Education
• /
• v.16 no.1_spc
• /
• pp.65-70
• /
• 2024

As the interest in AI education grows, researchers have made efforts to implement AI education programs. However, research targeting pre-service teachers has been limited thus far. Therefore, this study was conducted to develop an AI literacy education program for preservice secondary teachers. The research results revealed that the weekly topics included the definition and applications of AI, analysis of intelligent agents, the importance of data, understanding machine learning, hands-on exercises on prediction and classification, hands-on exercises on clustering and classification, hands-on exercises on unstructured data, understanding deep learning, application of deep learning algorithms, fairness, transparency, accountability, safety, and social integration. Through this research, it is hoped that AI literacy education programs for preservice teachers will be expanded. In the future, it is anticipated that follow-up studies will be conducted to implement relevant education in teacher training institutions and analyze its effectiveness.

• Journal of Internet of Things and Convergence
• /
• v.8 no.6
• /
• pp.49-54
• /
• 2022

Rapid changes in modern society after the COVID-19 have highlighted artificial intelligence talent as a major influencing factor in determining national competitiveness. Accordingly, the Ministry of Education planned a large-scale SW·AI camp education project to develop the digital capabilities of 4th to 6th grade elementary school students and middle and high school students who are in a vacuum in artificial intelligence education. Therefore, this study aims to develop a camp-type SW·AI education program for students in grades 4-6 of elementary school so that students in grades 4-6 of elementary school can acquire basic knowledge in artificial intelligence. For this, the meaning of SW·AI education in elementary school is defined and SW·AI contents to be dealt with in elementary school are: understanding of SW AI, 'principle and application of SW AI', and 'social impact of SW AI' was set. In addition, an attempt was made to link the set elements of elementary school SW AI education and learning with related subjects and units of textbooks currently used in elementary schools. As for the program used for education, entry, a software coding learning tool based on block coding, is designed to strengthen software programming basic competency, and all programs are designed to be operated centered on experience and experience-oriented participants in consideration of the developmental characteristics of elementary school students. In order for SW·AI education to be organized and operated as a member of the regular curriculum, it is suggested that research based on the analysis of regular curriculum contents and in-depth analysis of SW·AI education contents is necessary.

• Journal of the Korean Society of Radiology
• /
• v.81 no.6
• /
• pp.1397-1411
• /
• 2020

Purpose To survey the perception, knowledge, wishes, and expectations of Korean radiology residents regarding artificial intelligence (AI) in radiology. Materials and Methods From June 4th to 7th, 2019, questionnaires comprising 19 questions related to AI were distributed to 113 radiology residents. Results were analyzed based on factors such as the year of residency and location and number of beds of the hospital. Results A total of 101 (89.4%) residents filled out the questionnaire. Fifty (49.5%) respondents had studied AI harder than the average while 68 (67.3%) had a similar or higher understanding of AI than the average. In addition, the self-evaluation and knowledge level of AI were significantly higher for radiology residents at hospitals located in Seoul and Gyeonggi-do compared to radiology residents at hospitals located in other regions. Furthermore, the self-evaluation and knowledge level of AI were significantly lower in junior residents than in residents in the 4th year of training. Of the 101 respondents, only 16 (15.8%) had experiences in AI-related study while 91 (90%) were willing to participate in AI-related study in the future. Conclusion Organizational efforts through a radiology society would be needed to meet the need of radiology trainees for AI education and to promote the role of radiologists more adequately in the era of medical AI.

• Journal of Digital Convergence
• /
• v.19 no.4
• /
• pp.435-441
• /
• 2021

This study was performed to investigate the relations on nursing professionalism, consciousness of biomedical ethics and intrapersonal intelligence of nursing students. The study included 159 nursing students. Data collection period was from December 3, 2018 to December 7 (5 days). Nursing professionalism was 3.97 with low social awareness and consciousness of biomedical ethics was 2.95 with high right to life of newborn and organ transplantation but low artificial abortion and euthanasia. Intrapersonal intelligence was 3.79, which showed high self reflection and self-understanding but low self-planning. There was significant positive correlation between nursing professionalism and consciousness of biomedical ethics (r=.31, p<.001) and nursing professionalism and intrapersonal intelligence(r=.39, p<.001). Nursing professionalism showed a positive correlation with biomedical ethics and intrapersonal intelligence. As a result, the nursing education strategy for positive establishment of nursing professionalism of nursing college students needs to be provided with education to improve intrapersonal intelligence that can improve self-development and education that deals with the foundation of Nursing professionalism.