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Emotion recognition is rapidly advancing within the realm of artificial intelligence (AI), spurred by progress in deep learning, multimodal data handling, and broader availability of large datasets. This paper offers an in-depth overview of emotion recognition strategies, focusing on bio-metric signals (e.g., audio, visual, physiological, and brain signals), conventional machine learning methods, and the latest deep learning architectures, including Transformers, two-dimensional Con-volution Neural Networks (CNNs) 2D CNNs, and three-dimensional CNNs (3D CNNs). We further examine multimodal systems and the role of Large Language Models (LLMs) in merging textual, audio, and video information for more precise emotion assessments. Key challenges such as real-time implementation, data biases, and cultural diversity are also highlighted. Ethical issues related to privacy and the potential misuse of emotion recognition technologies receive attention, as does a discussion of emerging applications in healthcare, human-computer interaction (HCI), mental health monitoring, and education. In sum, this review aims to contribute to the scholarly conversa-tion around evolving emotion recognition methodologies and their applications in practical systems.

본 연구는 데이터 시각화 과정에서 사용자의 관심 뷰(View)를 관리하고, 공간적 맥락을 유지할 수 있도록 지원하는 새로운 탐색 보조 도구인 CSN(Contextual Stack Navigator)을 제안한다. 기존 스냅샷 기반 방법은 데이터 탐 색 과정에서 생성된 뷰 간의 관계를 효과적으로 파악하기 어렵고, 맥락 정보의 부족으로 인해 사용자의 인지적 부담 을 증가시키는 한계가 있었다. 이를 극복하기 위해 CSN은 탐색 과정에서 생성된 뷰를 계층적 구조로 저장하고, 시 각적 단서를 통해 사용자에게 명확한 맥락 정보를 제공한다. CSN은 데이터 표현 방식에 제한받지 않고 다양한 데 이터 분석에 적용 가능하며, 탐색 과정에서의 직관적 상호작용과 유연한 데이터 분석을 지원한다. 본 연구에서는 CSN의 유용성을 검증하기 위해 저수준 작업 분류(Low-level Task Taxonomies)에 기반한 사례 연구를 수행하 였으며, 이를 통해 CSN이 기존의 스냅샷 방식 대비 탐색 효율성과 맥락 유지 측면에서 효과적임을 입증하였다. 본 연구 결과는 복잡한 데이터 분석 환경에서 시각적 탐색과 인사이트 도출을 효과적으로 지원할 것으로 기대된다.

This study proposes a novel navigation aid tool called Contextual Stack Navigator (CSN), designed to manage users' views during data visualization and preserve spatial context. Traditional snapshot- based methods have limitations in effectively identifying relationships between views generated during data exploration, often increasing users' cognitive load due to the lack of contextual information. To address these challenges, CSN stores views generated during the exploration process in a hierarchical structure and provides users with clear contextual cues. CSN is not constrained by data representation types, making it applicable to a wide range of data analysis scenarios while supporting intuitive interactions and flexible data exploration. To validate the utility of CSN, we conducted case studies based on Low-level Task Taxonomies, demonstrating that CSN is more effective than traditional snapshot methods in terms of exploration efficiency and context retention. These findings suggest that CSN can effectively support visual exploration and insight generation in complex data analysis environments.

Oral and maxillofacial reconstructive surgery demands high levels of precision and expertise, requiring extensive practice. However, repeated practice is often constrained by various real-world limitations. This paper proposes the development of a simulator that leverages virtual reality technology to provide an immersive experience in oral and maxillofacial reconstructive surgery, reducing these constraints. The simulator replicates each step of the surgical procedure, creates 3D models of the reconstruction area, and implements interaction methods necessary for performing the surgery. The proposed solution utilizes virtual reality equipment, including a head-mounted display and controllers, enabling users to experience the surgery and generate 3D model guides applicable to reconstructive surgery. Future work will involve user evaluations and accuracy assessments of the generated 3D models to validate the effectiveness of the proposed approach.

2019년 말부터 전 세계 코로나19 여파로 관광업계 큰 타격을 당하고 있다. 아직은 코로나19가 얼마나 지속될지는 알 수 없지만 이번 사태는 관광시설을 보완하고 관광객의 관광체험을 향상시켜 관광사업에 경쟁력을 강화할 수 있는 좋은 기회이기도 하다. 외국인 관광객 실태 조사에서 언어, 교통, 정보 등의 장애 요소를 인해 외국인 관광객에게 큰 불편을 끼쳤다. 이를 해결하기 위한 방안으로 많이 보급되어 있는 DID를 설치한다. 특히 외국인 관광객을 타깃으로 스탠드형 DID가 외국인 관광객의 관광과정에서 중요한 역할을 한다. 모바일 능력, 센서 기술 및 통신 기술의 향상에 따라 HCI 기 술의 사용은 갈수록 완벽해지고 있다. 사인시스템은 광안리 해수욕장에서 담당하는 서비스와 체험 콘텐츠 역할이 점차 확장되고 있다. 새로운 기술이 가져온 서비스 경험 패턴은 사인시스템을 업그레이드하였다. 스탠드형 DID가 광안리해수 욕장에서의 역할을 탐색하여 어떻게 하면 외국인 관광객에게 더 좋은 관광 경험을 제공하여 외국인 관광객을 더욱 잘 유지할 수 있는지에 대한 방안을 도출해 낼 것이다.

Since the end of 2019, the tourism industry has been hit hard in the aftermath of COVID-19 around the world. It is not yet known how long COVID-19 will last, but this situation is also a good opportunity to strengthen competitiveness by supplementing tourism facilities and improving tourists' tourism experiences. In a survey of foreign tourists, language, transportation, and information obstacles caused great inconvenience to foreign tourists. As a way to solve this problem, DIDs, which are widely spread, especially stand-type DIDs targeting foreign tourists, play an important role in foreign tourists' tourism. With the improvement of mobile capability, sensor technology, and communication technology, the use of HCI technology is becoming increasingly perfect. The role of services and experience contents in charge of the beach's signature system is gradually expanding. The service experience pattern brought by the new technology has upgraded the sign system. Stand-type DID will explore the role of Gwangalli Beach and come up with ways to better maintain foreign tourists by providing better tourism experiences for foreign tourists.

Since Klaus Schwab mentioned the keyword of the fourth industrial revolution in the Davos Forum, revolutionary changes have occurred in all areas, ranging from information communication, manufacturing, transportation, finance, healthcare, education, and military. While these changes are anticipated to be a positive change in technological productivity and enhance the convenience of human life, there is also a significant downside to the anticipated problems of job insecurity and the dangers of military abuse. In particular, the innovative development of artificial intelligence due to deep-learning techniques implies serious social problems as they begin to replace much of human intelligence. In this paper, we discussed the role of the humanities in terms of both artificial intelligence and its social influence and its underlying trends, and discussed the role of humanities.

What does the revolutionary science and technology industry mean to us, which has already begun and is progressing at a much faster rate than it feels in our reality? This article examines the essential meaning of the Fourth Industrial Revolution and attempts to develop it further through the text. The difference between the 4th Industrial Revolution and the previous 3rd Industrial Revolution lies not in merely digitalization of information technology, but in the fact that innovative transformation based on technology combination and re-examination of business methods of existing socio-economic subjects are necessary. The future of the Fourth Industrial Revolution, reflects common goals and values of haman being's and depends on developing a comprehensive and shareable perspective. In this respect, our future must be human-centered, and technology must be changed; but direction must be maintained. The process of the Industrial Revolution is to innovate the future in the direction of changing the value of human life from the direction of pursuing industrialization or technological progress through physically and cognitively enhanced human beings. Ultimately, the future industry of intelligent information technology should prepare for the future, paying attention to the need to understand users who are the subjects of technology and to satisfy their needs. The socio-economic changes of future industrial society caused by the representative intelligence information technology of the 4th Industrial Revolution and the interaction between technology and human in it are important. In particular, the value of human experience, not technology itself, at the heart of automation, intelligence, and mechanization was emphasized. This emphasis is a key issue in 232 인문언어 제19권 제2호that human experience is more important than the simple change in technological progress, which leads to the qualitative innovation of the 4th Industrial Revolution to produce a revolutionary intelligent information technology industrial society.

In terms of development of intelligent information devices, the most important element is the function which is able to deliver the information user wants to input on the device without complexities. By using the mean such as our voice, expression, gesture and physical contact we use in our daily routine, we are able to interact with device easily and simply. In this paper, we are initiated to present interactive surface system, in which allows users to use their hand gesture as a function of mouse and keyboard free, to be interacted within the platform of management strategy simulation game we developed, ‘R-Day’.

In the ubiquitous computing environments, people usually carry multiple information technology devices with them. Personal device network (PDN) refers to the way how people connect multiple IT devices for their personal as well as professional purposes. Even though it has been quite popular to construct the PDN in ubiquitous computing context, not much research has been conducted on how people actually connected multiple devices and what influences their methods of connection. In this paper we conducted a content analysis on community bulletin boards of IT devices and a contextual inquiry with expert users of PDN for investigating the configurations with which users connect multiple IT devices. Base on the results of two related studies, we identified three major types of PDN configurations, and key factors that influence the configurations of PDN. We conclude this research with guidelines to design a set of devices for each of the three configuration types.

This research aims to examine the impact of human-computer interaction (HCI) on user happiness, with a specific focus on social media use, particularly TikTok, and its effects on users' mental health and overall well-being. The study aims to explore the relationship between TikTok use, users' mental health indicators, and subjective happiness levels. By employing a mixed-methods approach involving quantitative surveys and qualitative interviews, this research intends to gather comprehensive data on users' TikTok usage patterns, mental health status, and subjective well-being. The findings will provide valuable insights into the complex relationship between HCI, TikTok use, and users' mental health and well-being, contributing to a deeper understanding of the effects of social media on happiness.

사용자의 수요가 증가함으로 인하여 최근의 마커 기반 증강현실 기술은 제스처 기반 인간-컴 퓨터 상호작용 분야에서 주목을 받고 있다. 그러나 개체가 프레임에서 빠른 움직임을 보일 때 발 생하는 모션 블러 효과에 의하여 마커의 추적 및 감지의 한계점이 발생한다. 기존의 디블러링 기 술들에서 전체 프레임 중 특정 프레임을 추출하는 작업이 없다면 실시간 비디오에서 사용하기에 문제가 있다. 본 논문에서는 인간-컴퓨터 상호작용을 위하여 ArUco 마커를 사용한 특징점 기반 광학흐름 추적 방법을 제안하며, 마커를 이용한 자세 추정 방법을 설명한다. 이 방법은 ArUco 마 커를 감지하고 특수한 마커 추적 방법을 통해 마커 감지를 보완한다. 특히 마커 추적 방법은 FAST 알고리즘을 사용하여 특징점을 추출하고 루카스-카나데 방법을 사용하여 특징점의 움직임 을 분석하여 움직임 벡터를 계산한다. 또한 Perspective-n-Point 문제를 해결하여 마커 포즈 추정 을 구현했다. 제안된 시스템은 기존의 방법보다 높은 검출률을 보였으며, 마커를 포함한 비디오 에서 프레임 처리 속도가 약 37% 향상되었다. 또한 마커 포즈 추정을 그래픽으로 구현하였다. 이 연구는 실제 환경에서 카메라를 통한 제스처 기반 인간-컴퓨터 상호작용 분야와 또한 이동 로봇 분야에도 도움이 될 것이라 기대된다.

Recently, marker-based augmented reality technology has attracted attention in gesture based human-computer interaction due to the users' demand. However, the blur effect that occurs when the object shows fast motion in frames limits the marker detection and tracking. Conventional de-blurring techniques are not effective for real-time video without the task of extracting a specific frame from a full frame. In this paper, we proposed the algorithm which detects special marker first, and also tracks point features of markers based on optical flow method. Especially, marker tracking method extracts point features also using the FAST algorithm and calculates motion vectors by analyzing the motion of point features using Lucas-Kanade method. Also, we implemented a marker pose estimation by solving Perspective-n-Point problem. Our proposed system showed more improved results than conventional methods especially with the rate of 37% higher in the frame processing speed of marker tracking video. In addition, the marker pose estimation was graphically represented. It is expected that this research will be useful for gesture-based human-computer interaction field and mobile robot field through camera in real environment.

This article discusses unremarkable language user interface of human computer interaction areas. Growing demand for language performance in user interface design systems is creating new opportunities to use computer and all applications. Unless systems have proper user interface, there are more stringent constraints on cost and power consumption that lead to design for many applications. In terms of understanding basic challenges faced by user interface, we explore the challengers and goal of user interface. We show three case studies that there are guideline study of speech interface, experimental results on language interaction study, user study on new technology as wearable computer.

Aiming at solving problem of points’ redundancy caused by full automatically detecting points and the problem of large workload caused by picking all points manually, I advanced a new method of picking points which is based on Human-Computer Interaction in our 3D reconstruction platform after automatically detecting points. We first detected and matched points automatically and got the homograph matrix between two images, then projected points which were picked by hand on the one image to the other image, at last we would search the interesting feature points in the neighborhood of corresponding points in the two images. Experiments have shown that this method decreases the redundancy brought by large number of points and successfully finds the important feature points, so it lays a good foundation for 3D reconstruction.

In this paper, a real-time Human-Computer Interaction (HCI) based on the hand data glove and K-NN classifier for gesture recognition is proposed. HCI is moving more and more natural and intuitive way to be used. One of the important parts of our body is our hand which is most frequently used for the Interaction in Digital Environment and thus complexity and flexibility of motion of hands are the research topics. To recognize these hand gestures more accurately and successfully data glove is used. Here, gloves are used to capture current position of the hand and the angles between the joints and then these features are used to classify the gestures using K-NN classifier. The gestures classified are categorized as clicking, rotating, dragging, pointing and ideal position. Recognizing these gestures relevant actions are taken, such as air writing and 3D sketching by tracking the path helpful in virtual augmented reality (VAR). The results show that glove used for interaction is better than normal static keyboard and mouse as the interaction process is more accurate and natural in dynamic environment with no distance limitations. Also it enhances the user’s interaction and immersion feeling.

In contemporary concept design workflows, character design often relies on static visual forms, such as model sheets and orthographic views. These methods frequently make it challenging for team members, other than the original designer, to fully grasp the emotional and dynamic aspects of a character. Consequently, significant time is required in subsequent design stages to align the character’s feel and features across the team. To address this issue, this study introduces an improved workflow—Technical Concept Design—which leverages rapidly advancing generative AI technologies to provide AI-driven generative support for designers. Based on the typology of design knowledge and the concept of evolutionary creativity, this research provides project examples demonstrating the potential of generative AI in character design. We delves into the application of AI tools in technical concept design and proposes potential research opportunities. The study aims to optimize design workflows, enhance efficiency, and elevate creative outcomes. The results indicate that technical concept design has broad application prospects in fields such as video games, films and animation . Furthermore, it significantly improves human-computer interaction and team collaboration, offering both theoretical insights and practical guidance for the future of the design discipline.

We aimed to see if approach-avoidance visual experience would have different effects in the valence rating of emojis. Previous literature has shown that approach-avoidance tendencies have influences people’s emotional perceptions. Up until now, research on emojis have been heavily focused on static emojis, which gives room for exploration whether if movement added on to emoji would elicit different emotional responses. In the study, we examined the impact of approach-avoidance visual experience of emojis via mobile interface, categorized into 4 experimental conditions (positive approach, negative approach, positive avoid, and negative avoid), and conducted semi-structured interviews to identify users’ reasonings towards their valence ratings on specific emojis with approach or avoid movements. We found that positive approach emojis were the highest valence rating and preferred by the participants, while there were no differences between negative emoji approach or avoidance. Based on these findings, we conclude that positive emojis could be intensified to be more positive with approach motion, yet for negative emojis, individual differences or contextual differences may arise in its emotional ratings.

Alarm system performance is a critical aspect of safety. While existing research has extensively examined the influence of acoustic attributes on alarm performance, consonance’s impact remains largely uncharted territory. This study bridges this research gap by investigating the effect of consonance on alarm systems. We extend our investigation to encompass not only the sound characteristics of the alarm but also the acoustic qualities of the surrounding environment, recognizing their potential impact on alarm efficacy. Prior studies consistently link consonance to annoyance levels, resulting in a negative user experience. Thus, we explore the relationship between consonance and alarm system performance, with a particular focus on modulating annoyance as an explanatory factor. Utilizing an oddball paradigm, we categorized standard and oddball sounds into consonant and dissonant types, creating four sound combinations. Participants were asked to respond to the irregularly presented oddball sounds while ignoring the constantly presented standard sounds. Our results reveal significant differences between groups, with the Standard Consonant/Oddball Dissonant (SC/OD) group displaying notably slower response times than the Standard Dissonant/Oddball Consonant (SD/OC) group. This reaction time variation aligns with differences in annoyance levels, as the SC/OD group reports higher annoyance, suggesting that reaction time discrepancies may be linked to increased arousal due to heightened annoyance.

In this paper, an contemplate the direction for Usable Security in IT security and User Experience. To evaluate how the user interface is convenient to use, we examine the components such as the property, learnable property, memory simplicity, faults and satisfaction level. By considering for the security, we should bring positive effects on the user experience. By emphasizing usability and security at the same time, we should increase the satisfaction level of the user experience and then produce the valuable experience through participation, use and observation. The positive user experience is the important task for the software engineering, business administration and others., and this will result satisfaction of the users, brand trust, and success in the market. On the other hand, for the negative user experience, the users cannot achieve their desired goal and therefore, are unsatisfied due to emotional, rational and economic inconvenience. Due to this, we should try to maintain a certain level of usability and security of the system in IT security and User Experience.

In order to improve the problems of segmentation accuracy and real-time existing in dynamic hand gesture under complex backgrounds, this paper presents a kind of dynamic hand gesture segmentation method based on improved Kalman filter and weighted skin-color model. Firstly, improved Kalman filter is utilized to process hand gesture image of hand gesture video sequences and get rough hand gesture results. Secondly, weighted skin-color model is applied to process rough results of hand gesture segmentation and segment hand gesture. Finally, morphological method is utilized to deal with gesture segmentation result, getting rid of the holes in the hand gesture’s binary image to realize the segmentation of dynamic hand gesture. Experiments show that the proposed method can segment hand gesture from dynamic hand gesture video sequences with complex backgrounds effectively. And the accuracy of hand gesture segmentation is high.

Given that usability is one of the most important aspects of software quality, several methods have been developed in order to establish techniques capable of evaluating this attribute from early phases of the software development process. However, the choice of the most appropriate method for a particular scenario is still a difficult decision, due to the existence of a vast number of approaches that are described in the literature for this purpose. Therefore, a systematic mapping review was conducted in order to identify the most commonly used usability evaluation techniques in software developments. A total of 1169 studies were identified, of which only 215 studies were selected for this review. According to the analysis, most cases studies establish the use of usability questionnaires as assessment tool. In addition, health informatics and Web applications are the software domain and type of application that are frequently reported in these evaluations. This work has allowed to reach promising results in this area. It is intended to be a guide for specialists to support the choice of the most suitable method for a particular scenario.

In this paper, we propose a method to predict human emotion based on a multi-dimensional emotion model using sentimental similarity. The proposed framework predicts the user's level of emotional response to an emotional stimulus, based on a sensitivity database that consists of self-assessment manikin-based integer-scale data, rated on various object stimulations by many users. We experimented on 72 users, with 1,073 stimulation objects, based on the International Affective Picture System, and used Thayer's arousal-valence 2-dimensional emotion model to verify the proposed framework. As a result, we have confirmed that the proposed framework can predict user emotion using an arousal-valence model.