• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.55-62
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• 2024

International exchange implementing the Internet began inevitably due to the pandemic, but it provided Digital Nomads with new experiences in their lives using the Internet. This study the possibility and challenge of international exchange implementing the Internet identified. To this end, we explored its strengths and weaknesses through interviews and descriptions of students who participated in international exchange. As a result, we identified that students were positive in the diverse aspects of communication tools and ways, whereas they were negative because they felt difficulties in the physical environment, inaccessible physical conditions especially. They were also negative in the emotional exchange, an ice-breaking which needed much more time than offline exchange. Therefore, we identified in the case of designing or conducting student activities implementing the Internet, including international exchange, the possibility of activities implementing the Internet could be much more extended if their developer various programs considered in the introduction step.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2767-2780
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• 2016

Video-based human-activity recognition has become increasingly popular due to the prominent corresponding applications in a variety of fields such as computer vision, image processing, smart-home healthcare, and human-computer interactions. The essential goals of a video-based activity-recognition system include the provision of behavior-based information to enable functionality that proactively assists a person with his/her tasks. The target of this work is the development of a novel approach for human-activity recognition, whereby human-body-joint features that are extracted from depth videos are used. From silhouette images taken at every depth, the direction and magnitude features are first obtained from each connected body-joint pair so that they can be augmented later with motion direction, as well as with the magnitude features of each joint in the next frame. A generalized discriminant analysis (GDA) is applied to make the spatiotemporal features more robust, followed by the feeding of the time-sequence features into a Hidden Markov Model (HMM) for the training of each activity. Lastly, all of the trained-activity HMMs are used for depth-video activity recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.219-234
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• 2009

This paper presents a novel approach for extracting simultaneously human daily activity patterns and discovering the temporal relations of these activity patterns. It is necessary to resolve the services conflict and to satisfy a user who wants to use multiple services. To extract the simultaneous activity patterns, context has been collected from physical sensors and electronic devices. In addition, a context model is organized by the proposed incremental statistical method to determine conflicts and to infer user intentions through analyzing the daily human activity patterns. The context model is represented by the sets of the simultaneous activity patterns and the temporal relations between the sets. To evaluate the method, experiments are carried out on a test-bed called the Ubiquitous Smart Space. Furthermore, the user-intention simulator based on the simultaneous activity patterns and the temporal relations from the results of the inferred intention is demonstrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1118-1133
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• 2017

Computer vision-based human activity recognition (HAR) has become very famous these days due to its applications in various fields such as smart home healthcare for elderly people. A video-based activity recognition system basically has many goals such as to react based on people's behavior that allows the systems to proactively assist them with their tasks. A novel approach is proposed in this work for depth video based human activity recognition using joint-based motion features of depth body shapes and Deep Belief Network (DBN). From depth video, different body parts of human activities are segmented first by means of a trained random forest. The motion features representing the magnitude and direction of each joint in next frame are extracted. Finally, the features are applied for training a DBN to be used for recognition later. The proposed HAR approach showed superior performance over conventional approaches on private and public datasets, indicating a prominent approach for practical applications in smartly controlled environments.

• International Journal of Quality Innovation
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• v.6 no.2
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• pp.17-30
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• 2005

The Internet can provide benefits obtained from changing the structure of a business, such as emphasizing the importance of different types of personnel. In addition, the Internet alters the process for business activity, both within and outside the organization. Using structural equation modeling, I empirically test a number of hypothesized relationship based on a sample of 126 Internet Community users. The results are as follows: loyalty is significantly influenced by trust and relationship, repeat purchase is significantly influenced bye-loyalty. In addition, word of mouth is significantly influenced by e-loyalty.

• Journal of Family Resource Management and Policy Review
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• v.6 no.1
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• pp.149-165
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• 2002

This study is to understand consumer's information search activity and satisfaction. When they buy the elderly related goods through internet market and to get some ideas for silver industry on internet shopping. The 382 subjects by online banner formatted Questionnaires were analyzed by frequency, percentage, standard deviation, Person's relation and regression analysis by SPSS PC program. The major findings are summarized as follows. (1) The most respondents were young and well-educated. In terms of psychological variables, the degree of the consumer's perception for internet usefulness and using capability were relatively high. (2) Information search amount of the group who have experienced purchasing elderly related goods through internet shopping and had low perception of internet risk is higher than other group. (3) The variables influenced mostly on consumer satisfaction were the age, the sex, the purchasing experience from Internet shopping, the Internet using capacity and the perception of internee usefulness as well as of the perception of internet risk.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2016-2034
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• 2011

Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

• The Research Journal of the Costume Culture
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• v.22 no.1
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• pp.112-125
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• 2014

The purpose of this study was to compare the effects of internet fashion advertisement (Ad) formats according to university students' online lifestyle. Static banner, rich media, floating, shopping, and target advertisement were selected as stimuli and a self-administered questionnaire was used for data collection. SPSS PC (Ver. 16.0) was used for factor analysis, ANOVA, and Chi-square test. Factors of online lifestyle were economy, early adaption, cyberspace activity, sociability, innovation, and entertainment, and subjects were segmented into online activity (OA) retard group, OA mania group, hedonic early adapter group, and OA intermediate group. OA retard group was positive to a static banner Ad with intimacy, and OA mania group and OA intermediate group were positive to a static banner Ad with confidence, attention, and intimacy and rich media Ad and floating Ad with confidence and attention. Hedonic early adapter group was positive to a target Ad with attention and intimacy. Internet shopping mall managers should select internet Ad format after segmenting their customers according to OA lifestyle.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.99-104
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• 2016

The walking exercise can alleviate stress and also it can improve health fortheir lifetime. Recent development in Information and Communication Technologies (ICT) has laid the foundation for Internet of Things (IoT) to become the future technology. IoT has many applications in industry automation, security, smart homes and cities, education, health etc. In personal health-care domain, IoT is mainly used for monitoring fitness condition by observing current activity of individual. In this paper, we have proposed a novel IoT based personal wellness care system. Proposed system not only keep track of current fitness level but also provide future activity prediction based on history data along with standard recommendations. Predicted activity helps in motivating the individual to achieve the desired fitness level. Initially, we consider only walking activity for testing purpose and later, other types of activities/exercise will be captured for improved health care support.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.