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The study makes several contributions to not only the adoption literature by examining the influence of Emotional Intelligence (EI) and Big-Five traits on adoption of Augmented Reality (AR) but also given its utility in both industry and research, it contributes to the interesting inter-disciplinary domain of psychology, information systems, and human behaviour. A quantitative based approach using a sample of 275 respondents was undertaken. It is found that emotional intelligence influence both perceived ease-of-use and perceived usefulness. They in turn influence intention to use. Another important observation is that personality traits (openness and agreeableness) have a significant moderating effect on the relation between attitude and intention to use AR. This research will help academicians and executives working on the adoption of AR in various sectors ranging from retail industry to the education sector. The originality of this study is that it explores the impact of EI on the acceptance of AR and helps in extending the literature in interdisciplinary research.

인공지능윤리에 대한 다양한 연구가 활발하게 진행되고 있지만, 정보윤리, 컴퓨터윤리, 인터넷윤리, 사이버윤리, 로봇윤리에 대한 용어와 개념에 대한 고찰은 상대적으로 미흡하다. 이 논문에서는 이 윤리들을 아우르는 플랫폼 기반 정보윤리체계를 정리하였다. 동일한 개념으로 인식되는 컴퓨터윤리와 인터넷윤리는 인터넷에 연결된 소프트 웨어에 대한 사용자의 규범으로, 사이버윤리는 가상공간에서 사용자간의 규범으로, 로봇윤리는 물리적 공간에서 인간과 로봇의 규범으로 보았다. 또한 교사들의 관련 윤리 용어의 개념적 차이에 대한 인식을 조사하고, 이에 대 한 교사연수 요구를 알아보았다. 그리고 정보윤리체제 안에서 인간컴퓨터상호작용에 기반한 세 가지 정보기술환경 (커뮤니케이션 플랫폼, 소프트봇, 로봇)에 대하여 8가지 윤리기준(중독·예방, 보안·프라이버시, 넷티켓·공공선, 행복, 데이터공정성, 인간존엄성, 투명성, 안전성) 사례에 대한 교사들의 중요도 인식을 조사하였다.

Various studies on artificial intelligence ethics are being actively conducted, but considerations on terms and concepts of information ethics, computer ethics, Internet ethics, cyber ethics, and robot ethics are relatively insufficient. In this paper, we reviewed the concept of an information ethics framework that encompasses the ethics mentioned based on the platforms. Computer ethics and Internet ethics, recognized as the same concept, are the user's norms for Internet-connected software, cyber ethics are the norms between users in virtual space, and robot ethics are the norms of humans and robots in physical space. Additionally, teachers' perceptions of conceptual differences in related ethical terms were investigated based on the information ethics framework, and teacher training needs were investigated. In addition, teachers' perception of the importance of eight ethical standards (addiction, prevention, security, privacy, net ticket, public good, happiness, data fairness, human dignity, transparency, and safety) was investigated for cases based on human computer interaction in three information technology environments (communication platform, softbot, and robot).

This paper presents a novel friendly and interactive Chinese character (Kanji in Japanese) learning system to enable elementary school students and foreign people living in Japan and to learn Kanji by an interesting and efficient way. By interacting with the network between the client application for students and the server application for teachers, teachers can grasp circumstances of education of all students in real-time. When students select and input characters they want to learn, the client application checks whether each stroke is unbalanced or not, and it is corrected if unbalanced. If there are no unbalanced strokes, a “Hanamaru” is displayed. On the other hand, the server application has two kinds of display modes, to display circumstances of all students and to display detail circumstances of each student, and teachers can switch them anytime. At the same time, the server takes statistics of points where each student is easy to make mistakes and saves them. So teachers can grasp circumstances and trend of all students. Moreover, pen speed and segment division are introduced in order to extract and correct local features, such as “tome”, “hane”, and “harai”, which were a weak point of previous system in spite of the important point in Kanji education. Segment division is a method that refraction points of each stroke are extracted and each stroke is subdivided by these points and is used to correct “hane” and to distinguish between “ore” and “mage”. For both of them, the correction of local features can be realized and the close correction is enabled. Finally, by using the system actually, this system is evaluated whether it is useful to be able to write and memorize Kanji correctly and the interface is really friendly for learners. As a result, since many students feel interesting and useful to learn Kanji, it is clear that this system is useful for Kanji education. And the interface is also a high appraisal.

Haptics, the science and physiology of the sense of touch, has been investigated in the field of engineering and HCI to provide better computing environments for users. Previous haptic technology being focused was mainly on the PC environments; however, beginning with the i- Phone of Apple recent haptic technology has entered our daily lives. Despite its popularization, the business opportunities the technology will bring have not yet been investigated thoroughly. This research forecasts the application of haptic technology on mobile devices and the consequential business opportunity. Also, the direction of future research in the field of MIS will be proposed.

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.

The face describes the personality of humans and has adequate importance in the identification and verification process. The human face provides, information as age, gender, face expression and ethnicity. Research has been carried out in the area of face detection, identification, verification, and gender classification to correctly identify humans. The focus of this paper is on gender classification, for which various methods have been formulated based on the measurements of face features. An efficient technique of gender classification helps in accurate identification of a person as male or female and also enhances the performance of other applications like Computer-User Interface, Investigation, Monitoring, Business Profiling and Human Computer Interaction (HCI). In this paper, the most prominent gender classification techniques have been evaluated in terms of their strengths and limitations.

With the evolution of HCI (Human-Computer Interaction), the computer vision systems are playing an important role in our lives. Some of the prime areas of computer vision applications include gender detection, face recognition, body tracking and ethnicity identification etc. Automated data analyses techniques help discover regularities and hidden associations in larger volumes of datasets. Classification being a data mining technique is largely used to group categorical data as well as a blend of continuous numeric values and categorical data. A number of classification techniques like decision trees, support vector machine (SVM), nearest neighbors and neural networks etc. have gained popularity in numerous areas of data mining practices. Among these classification techniques, decision trees offer an added advantage of producing easily interpretable rules and logic statements along with generating the classification tree for the given dataset. This study offers a distinct method for gender classification of facial images. We have used a variant of the decision tree algorithm for gender classification of frontal images due to its distinctive features. Our technique demonstrates robustness and relative scale invariance for gender classification. Details of the experimental design and the results are reported herein.

As touch-screen mobile phones pour into the market, demands for reusing existing mobile applications by adding a touch-screen UI are increasing. In order to service an existing application without a touch-screen UI to touch phones, an on-screen keyboard that implements a virtual keyboard on the touch screen is needed. On-screen keyboards are particularly convenient to use on small mobile phone screens because they reduce the number of keys and consequently increase the size of each. Previous on-screen keyboard generation methods generate fixed keyboard layouts that include every key defined by a system, resulting in smaller and inconvenient keys. Further, the recently studied dynamic analysis method analyzes keys used in source codes during run-time to generate on-screen keyboards optimized for applications but it generates too much overhead to control. In this study, we proposed the touch-screen UI generating technique based on content's source code by static analysis. To generate the UI automatically, we adopt the notion of key set graphs that store the UI status information of applications to identify UI states by referencing the graphs and generating optimized on-screen keyboards. This method uses effective graph data structures to effectively circumvent the overhead issues featured in the dynamic analysis method.

일상생활의 상황을 이해하고 다양한 전자매체들과 지능적으로 의사소통할 수 있는 착용형 컴퓨터가 유비쿼터스 환경에서 사용자를 위한 에이전트로서 매우 유용할 것이다. 본 논문에서는 유비쿼터스 컴퓨팅 환경에서 사용자가 다양한 정보 에이전트들과 상호작용할 수 있는 새로운 형태의 컴퓨팅 시스템으로서 착용형 도움 슈트를 제안한다. 개발된 시스템은 사용자가 사용하거나 통신하기를 원하는 상호작용형 전자매체를 자동으로 감지할 수 있다. 이러한 상호작용 능력을 활용하여 사용자와 각각의 매체들을 중재하고 이 시스템을 착용하고 있는 사용자에게 친숙한 인터페이스를 제공한다. 또한 유비쿼터스 환경에서 상호작용형 전자매체들과 상호작용하는 모습을 연출함으로써 제안된 시스템의 사용법을 설명한다.

The wearable computer that can understand the context of human life and intelligently communicate with various electronic media in ubiquitous computing environment would be very useful as an assistant for humans. In this paper we introduce an intelligent wearable assistance suite. The proposed wearable suite can interact with both humans and electronic media in ubiquitous computing environment. The developed system can sense the interactive electronic media that a user wants to use and also communicate with it. By utilizing these interaction capabilities, it intermediates between each media and the user and offers a friendlier interface to the user who wears this system. We also show the usages of the proposed system by demonstrating its interaction with the interactive electronic media in ubiquitous computing environment.

주거환경에서의 사용자 요구사항은 매우 다양하고 복잡한 연계관계를 갖고 있다. 근 미래의 u-Home시스템은 기존 사용자들의 요구 수용뿐만 아니라 U-home관련 신기술의 요구사항도 접목해야 한다. 본 연구에서는 이러한 사용자의 요구사항을 보다 효율적으로 시스템에 반영하기위해 사용자의 행위 데이터를 기반으로 요구유형을 분류하고 시스템 개발에 활용할 수 있도록 사용자 행위분석모형UBAF(User Behavior Analysis Framework)을 제안 하고자한다. UBAF는 SE에서의 시스템 모델링 방법과 HCI 관점의 사용자 모델링 방법을 접목한 개발 프레임워크이다. 이를 통해 u-Home에서 정형화된 방법으로 사용자들의 핵심행위를 시스템 개발에 적용할 수 있었다. 적용사례로 u-Home의 실내온도 조절 시나리오를 분석하여 시스템 모델링과 사용자 행위를 지식화 하였다.

User needs in residential environment have very complicated and variety connection with others. u-home system for the near future is need to be combined acceptance of exist user needs as well as needs on new technology relating with u-Home. The study proposes a User Behavior Analysis Framework – UBAF for applying the user needs to the system more efficiently and developing the system by classifying patterns for the needs based on date of user behavior analysis. UBAF is a developing framework getting the basic idea of combining system modeling methods on SE and user modeling methods considering on HCI. It will be applicable to develop the system with core user behaviors by applying a standard way on u-Home. For example, the study transforms information into knowledge the system modeling and user modeling with analyzing a scenario for indoor temperature controlling on u-Home.

Among the various hand gestures, pointing gesture is highly intuitive, and does not require any priori assumptions. A major problem for pointing gesture recognition is the difficulty of pointing fingertip tracking and the unreliability of the direction estimation. A novel real-time method is developed for pointing gesture recognition using Kinect based depth image and skeletal points tracking. An adaptive virtual touch screen is constructed instead of estimating pointing direction. When a user stands in a certain distance from a large screen to perform pointing behaviors, he interacts with the virtual touch screen as if it is just right in front of him. The proposed method is suitable for both large and small pointing gestures, and it’s not subject to users’ characteristics and environmental changes. Experiments have highlighted that the proposed approach is robust and efficient to realize human-computer interaction based on pointing gesture recognition by comparisons.

Human-computer interaction (HCI) has great interactive applications in many fields. A novel eye-hand coordination based HCI approach has been proposed. According to the fact that the eye gazing starts prior to the hand movement and reaches the target in advance, an eye-hand coordination model in a non-contact way is constructed by facial orientation and skeletal joints of hand. Both temporal median filtering and moving average filter strategies are developed to overcome some fluctuation influences during HCI. The diversity of interactive habits among multiple users is considered in an ordinary hardware from a crowded scene without any hypothesis for the scenario contents in advance. Comparative comparisons with state-of-the-arts have highlighted the superior performance of the proposed approach.

In this paper, we present a face and gesture based human computer interaction (HCI) system. We combine head pose and hand gesture to control the system. We can identify the positions of the eyes and mouth, and use the face center to estimate the pose of the head. Moreover, we introduce a technique for automatic gesture area segmentation and orientation normalization of the hand gesture. The user does not need to keep gestures in upright position and the system segments and normalizes the gestures automatically. The experimental results show that the proposed approach is accurate with gesture recognition rate of 93.6%. Also, the user can control multiple devices, including robots simultaneously through a wireless network.

Human-computer interaction (HCI) has great potential for applications in many fields. A HCI method has been developed based on audio-visual perceptive features and dynamic interactive pooling. A mode analysis based fusion strategy is proposed to fuse the interactive responses from audio-visual modalities especially for the case there are deviations from the modalities at the same time. The developed approach can be applied with a better performance even in single modal with multiple interactive users in the scenario. The users in the scenario are endowed with a fair chance to perform HCI by their interactive priorities no matter how many modalities used, and the interactive authority and priority are updated dynamically according to the variation of HCI content. The scenario and multiple users altogether are regarded as a dynamic HCI pooling. The diversity of interactive habits among multiple users is considered in an ordinary hardware from a crowded scene without any hypothesis for the scenario contents in advance. The pooling is updated dynamically to meet the user demands with the most intentions preferentially. Comparative study with state-of-the-arts has indicated the superior performance of the proposed method.

This paper develops the Adaptive Multisensory Integration Framework (AMIF), explaining how artificial intelligence coordinates sensory modalities to enhance human-computer interaction. Synthesizing cognitive neuroscience, AI, and HCI theories, AMIF identifies five cyclically-operating components governing multisensory integration. Critical analysis reveals fundamental limitations in temporal prediction, computational efficiency, and individual variability. Four case studies demonstrate the framework's explanatory power, showing both successes and persistent challenges in real-world systems. The framework generates testable hypotheses and design principles grounded in theoretical understanding.