• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4662-4679
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• 2015

Currently, the leakage of internal information has emerged as one of the most significant security concerns in enterprise computing environments. Especially, damage due to internal information leakage by insiders is more serious than that by outsiders because insiders have considerable knowledge of the system's identification and password (ID&P/W), the security system, and the main location of sensitive data. Therefore, many security companies are developing internal data leakage prevention techniques such as data leakage protection (DLP), digital right management (DRM), and system access control, etc. However, these techniques cannot effectively block the leakage of internal information by insiders who have a legitimate access authorization. The security system does not easily detect cases which a legitimate insider changes, deletes, and leaks data stored on the server. Therefore, we focused on the insider as the detection target to address this security weakness. In other words, we switched the detection target from objects (internal information) to subjects (insiders). We concentrated on biometrics signals change when an insider conducts abnormal behavior. When insiders attempt to leak internal information, they appear to display abnormal emotional conditions due to tension, agitation, and anxiety, etc. These conditions can be detected by the changes of biometrics signals such as pulse, temperature, and skin conductivity, etc. We carried out experiments in two ways in order to verify the effectiveness of the emotional recognition technology based on biometrics signals. We analyzed the possibility of internal information leakage detection using an emotional recognition technology based on biometrics signals through experiments.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.429-440
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• 2010

It is known that as many as 1 in 91 children are diagnosed with an autistic spectrum disorder, and the incidence rate of the autistic spectrum disorder is much higher than that of cancer in Korea. It is necessary to develop a novel technology to sense their emotional status and give proper psychological diagnosis and therapy, since the children with autistic spectrum disorder usually do not express their own emotional status. This article presents the state-of-the-arts on the affective computing technologies that include recognition of emotional status through bio-sensing and virtual affective agent modeling, and then proposes a novel system architecture for diagnosis and therapy of autistic spectrum disorder. The diagnosis and therapy system of autistic spectrum disorder is composed of bio-sensing module, virtual environment module with affective agents, and haptic interface module. The architecture proposed in this paper will enhance the objectivity to diagnose autism spectrum disorders, and enable continuous treatment in daily life.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.76-94
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• 2015

For different reasons, many viewers like to watch a summary of films without having to waste their time. Traditionally, video film was analyzed manually to provide a summary of it, but this costs an important amount of work time. Therefore, it has become urgent to propose a tool for the automatic video summarization job. The automatic video summarization aims at extracting all of the important moments in which viewers might be interested. All summarization criteria can differ from one video to another. This paper presents how the emotional dimensions issued from real viewers can be used as an important input for computing which part is the most interesting in the total time of a film. Our results, which are based on lab experiments that were carried out, are significant and promising.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.55-70
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• 2009

Vision-based Human computer interaction is an emerging field of science and industry to provide natural way to communicate with human and computer. In that sense, inferring the emotional state of the person based on the facial expression recognition is an important issue. In this paper, we present a novel approach to recognize facial expression from a sequence of input images using emotional specific HMM (Hidden Markov Model) and facial motion tracking based on optical flow. Conventionally, in the HMM which consists of basic emotional states, it is considered natural that transitions between emotions are imposed to pass through neutral state. However, in this work we propose an enhanced transition framework model which consists of transitions between each emotional state without passing through neutral state in addition to a traditional transition model. For the localization of facial features from video sequence we exploit template matching and optical flow. The facial feature displacements traced by the optical flow are used for input parameters to HMM for facial expression recognition. From the experiment, we can prove that the proposed framework can effectively recognize the facial expression in real time.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.475-488
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• 2001

With the increase of the number of Internet users, various methodologies have been proposed for the effective design of web page. However, the prior methodologies have focused only on the functional aspect of web page while ignoring the emotional aspects of web pages. This paper focuses on the emotional design of home pages and aims to provide a methodology to design a web page suitable for goal emotions. In order to achieve the main purpose, we have conducted three related studies. First, we have identified basic emotional dimensions representing various feeling users have from web pages as a pool of emotional adjectives. Second, we have identified key design elements related to the emotion by observing the design process of expert designers. Third, we examined the causal relation between the perceived emotion and designed elements. The results indicate that some design elements are more effective to produce certain feeling than others. This paper ends with limitations and implications of the study results.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.71-77
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• 2022

In this paper, a database is collected for extending the speech synthesis model to a model that synthesizes speech according to emotions and generating facial expressions. The database is divided into male and female data, and consists of emotional speech and facial expressions. Two professional actors of different genders speak sentences in Korean. Sentences are divided into four emotions: happiness, sadness, anger, and neutrality. Each actor plays about 3300 sentences per emotion. A total of 26468 sentences collected by filming this are not overlap and contain expression similar to the corresponding emotion. Since building a high-quality database is important for the performance of future research, the database is assessed on emotional category, intensity, and genuineness. In order to find out the accuracy according to the modality of data, the database is divided into audio-video data, audio data, and video data.

• International Journal of Human Ecology
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• v.9 no.1
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• pp.5-16
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• 2008

Development of technology in the $20^{th}$ century has made great contributions to women's lives. With the development of digital convergence, home network, and DMBs (Distance Method Bracings), the ubiquitous technology information era is expected to create a new progressive era for women. The purpose of this study is to investigate the lifestyle that Korean women would like to pursue, especially in regards to the sense of value within the personal and social life of each individual. As a method to suggest how the socio-cultural trends of women's lifestyle will change in the ubiquitous era, qualitative interviews have been conducted over 6 groups with 77 persons between the digital ages of 20s and 30s, living in Seoul. The majority had positive opinions regarding the economic, cultural, emotional, and physical prospects of the ubiquitous information environment. Results show high expectations evolved around freedom from household chores, the equality between the sexes (at home and in society), enhancing the working environment at home, an expansion of human relationships leading to creative knowledge, being able to maintain a single life without economic constraints, and the enjoyment that the internet provides. for suggestions to improve the quality of women's lifestyle through ubiquitous technology, issues such as individual based customization, time management, creating emotional hyperspaces, multi-media communication systems, and women as leaders were studied.

• Journal of Information Technology Applications and Management
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• v.15 no.4
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• pp.221-245
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• 2008

Recently, mobile internet technologies are enabling the possibility of radically new computing services which can share information and communicate with others on the move. In this situation, prior studies have attempted to identify of what factors make people use mobile internet. However, prior researches focused on investigating the factors affecting users' adoption to Mobile Internet. In order to offer beneficial materials to mobile internet companies, we investigated important factors to increase mobile users' value from the viewpoints of customer. In particular, this study was progressed how characteristics of mobile contents affect users' intrinsic attributes and how perceived users' network effects affect users' value in the mobile computing environments. To empirically test proposed hypotheses, we have analyzed 285 survey data gathering from mobile internet users and verified hypotheses by using SEM (structural equation modeling). Based on the results of this study, we found that content accessibility and content quality have significant impacts on users' intrinsic attributes such as perceived usefulness and perceived enjoyment. In addition, this study also revealed that perceived usefulness and perceived enjoyment were positively related to users' emotional value. Moreover, this study found that perceived users' network effects could affect users' monetary value by mediating expected benefits. Based on our findings, we can understand that this perspective can provide a deeper understanding of the mobile users' value adoption by bridging the gap between mobile internet studies and actual practice.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.376-386
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• 2015

Since affective computing has been introduced in 90s, affect recognition technology has achieved substantial progress recently. However, the application of user emotion recognition into software user interface is in its early stages. In this paper, we describe a new approach for developing mobile user interface which could react differently depending on user emotion states. First, an emotion reaction model is presented which determines user interface reactions for each emotional state. We introduce a pair of mappings from user states to different user interface versions. The reacting versions are implemented by a set of variations for a view. Further, we present an authoring framework to help developers/designers to create emotion-aware reactions based on the proposed emotion reaction model. The authoring framework is necessary to alleviate the burden of creating and handling multi versions for views at the development process. A prototype implementation is presented as an extension of the existing authoring tool DAT4UX. Moreover, a proof-of-concept application featuring an emotion-aware interface is developed using the tool.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.369-376
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• 2021

One of the most active areas of research in the field of affective computing and signal processing is emotion recognition. This paper proposes emotion recognition of low-resource (Sindhi) language. This work's uniqueness is that it examines the emotions of languages for which there is currently no publicly accessible dataset. The proposed effort has provided a dataset named MAVDESS (Mehran Audio-Visual Dataset Mehran Audio-Visual Database of Emotional Speech in Sindhi) for the academic community of a significant Sindhi language that is mainly spoken in Pakistan; however, no generic data for such languages is accessible in machine learning except few. Furthermore, the analysis of various emotions of Sindhi language in MAVDESS has been carried out to annotate the emotions using line features such as pitch, volume, and base, as well as toolkits such as OpenSmile, Scikit-Learn, and some important classification schemes such as LR, SVC, DT, and KNN, which will be further classified and computed to the machine via Python language for training a machine. Meanwhile, the dataset can be accessed in future via https://doi.org/10.5281/zenodo.5213073.