• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.389-393
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• 2000

Ethnography, a major research method in Anthropology, has been recently applied in human-centered design research. Since ethnography has empirical, naturalistic, holistic and eclectic characteristics, it is needed a guideline to apply ethnography into design research in accordance with a characteristic of project. Design project in which ethnography is applied can be categorized by two criteria; degree of newness of project goal(existing user-potential user) and limitedness of worksite(site-oriented-work-oriented). Among work-site activities, technology in use, and user group culture, it should be decided which content to content to focus more than others and thus what kinds of research techniques to apply in the ethnographic research.Case study was to design an interior of a Korean express train. This project is site-oriented and has an existing-potential users. Therefore, video ethnography was effectively applied to obtain chronological data of activity potential users. Therefore, video ethnography was effectively applied to obtain chronological data of activity flow, and participant observation was applied to obtain statistical data of synchronous activities. Case study shows a concrete process example of how to apply ethnography into design research.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.506-513
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• 2014

In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.154-155
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• 2013

This paper presents a user authentication scheme for healthcare application using wireless sensor networks, where wireless sensors are used for patients monitoring. These medical sensors' sense the patient body data and transmit it to the professionals. Since, the data of an individual are highly vulnerable; it must ensures that patients medical vital signs are secure, and are not exposed to an unauthorized person. In this regards, we propose a user authentication scheme for healthcare application using medical sensor networks. The proposed scheme includes: a novel two-factor user authentication, where the healthcare professionals are authenticated before access the patient's body data; a secure session key is establish between the patient sensor node and the professional at the end of user authentication. Furthermore, the analysis shows that the proposed scheme is safeguard to various practical attacks and achieves efficiency at low computation cost.

• ETRI Journal
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• v.43 no.1
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• pp.95-108
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• 2021

Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers. It exploits numeric app ratings provided by users as training data and returns authentic mobile app ratings by analyzing user reviews. An ensemble learning model is proposed for this purpose that considers term frequency/inverse document frequency (TF/IDF) features. Three TF/IDF features, including unigrams, bigrams, and trigrams, were used. The dataset was scraped from the Google Play store, extracting data from 14 different app categories. Biased and unbiased user ratings were discriminated using TextBlob analysis to formulate the ground truth, from which the classifier prediction accuracy was then evaluated. The results demonstrate the high potential for machine learning-based classifiers to predict authentic numeric ratings based on actual user reviews.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.767-777
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• 2023

In modern society, user privacy is emerging as an important issue as closed-circuit television (CCTV) systems increase rapidly in various public and private spaces. If CCTV cameras monitor sensitive areas or personal spaces, they can infringe on personal privacy. Someone's behavior patterns, sensitive information, residence, etc. can be exposed, and if the image data collected from CCTV is not properly protected, there can be a risk of data leakage by hackers or illegal accessors. This paper presents an innovative approach to "machine learning based reversible chaotic masking method for user privacy protection in CCTV environment." The proposed method was developed to protect an individual's identity within CCTV images while maintaining the usefulness of the data for surveillance and analysis purposes. This method utilizes a two-step process for user privacy. First, machine learning models are trained to accurately detect and locate human subjects within the CCTV frame. This model is designed to identify individuals accurately and robustly by leveraging state-of-the-art object detection techniques. When an individual is detected, reversible chaos masking technology is applied. This masking technique uses chaos maps to create complex patterns to hide individual facial features and identifiable characteristics. Above all, the generated mask can be reversibly applied and removed, allowing authorized users to access the original unmasking image.

• Journal of Service Research and Studies
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• v.10 no.1
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• pp.85-96
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• 2020

In Asia, where the aging population is growing rapidly, as the funeral service industry develops and the market grows. The economic value and interest of funeral services is increasing. However, Korea's funeral services are being developed in a biased direction, focusing only on funeral services, after death. Compared to the case of advanced funeral services in the United States, the United Kingdom, and Japan, not only the funeral but also the care of the deceased's family and acquaintances around us are developing. It is appropriate to use a method based on ethnography and User eXperience. For this purpose, the method of collecting and analyzing the ethnography and user experience data of actual resident and visitor was deduced in persona method in the next ten years, and funeral service centered on resident and visitor. In this study, qualitative data centered on the future direction of funeral services, focusing on the resident (family) and the guest who are the principals of services from the perspective of service science. It is difficult to derive meaningful results from the process of collecting, processing, and interpreting big data in general, and in this case, the data analysis method is based on ethnography and user eXperience.) Is appropriate. For this purpose, the method of collecting and analyzing the ethnography and user experience data of the actual resident and the visitor was deduced in the persona method in detail after 10 years. In addition, the future direction of funeral services centered on residence and visitor was presented.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.4
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• pp.745-754
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• 2019

As GeoWeb 2.0 technologies are widely used, various kinds of services that mashup spatial data and user data are being developed. In particular, various spatial information platforms such as Google Maps, OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld based on GeoWeb 2.0 technologies support mashup service. The mashup service which is supported through the Open APIs of the platforms, provides various kinds of spatial data such as 2D map, 3D map, and aerial image. Also, application fields using the mashup service are greatly expanded. Recently, as user data for mashup have been greatly increased, there was a problem in mashup performance. However, the research on the mashup performance improvement is currently insufficient, even the research on the mashup performance comparison of various platforms has not been performed. In this paper, we perform comparative analysis of the mashup performance for large amounts of user data and spatial data using various spatial information platforms available in Korea. Specifically, we propose two performance analysis indexes of mashup time and user interaction time in order to analyze the mashup performance efficiently. Also, we implement a system for the performance analysis. Finally, from the performance analysis result, we propose a spatial information platform that can be efficiently applied to cases when user data increases greatly and user interaction occurs frequently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1364-1370
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• 2017

This paper proposes a method that automatically sets profile schedule context-based mobile phone by collecting the user's external situation based on the GPS sensor and accelerometer built into the smartphone and interacting with the data in the user's schedule to minimize the user's handset handling. However, real-time data collection in mobile phones causes energy shortage in the device due to battery consumption. In other words, a service control method is explained in a way that can efficiently handle resource consumption because accessing a measurement device such as GPS and other sensors may increase power consumption of the portable device. Therefore, effective data sharing for context awareness to reduce weekly schedules and smartphone mode has improved energy efficiency in sensing for data collection. The user can use the context more effectively by providing environmental adaptability for various situations such as the end user's local context and smartphone force control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4136-4156
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• 2020

Recently, data can be safely shared or stored using the infrastructure of cloud computing in various fields. However, issues such as data security and privacy affect cloud environments. Thus, a variety of security technologies are required, one of them is security technology using CP-ABE. Research into the CP-ABE scheme is currently ongoing, but the existing CP-ABE schemes can pose security threats and are inefficient. In terms of security, the CP-ABE approach should be secure against user collusion attacks and masquerade attacks. In addition, in a dynamic cloud environment where users are frequently added or removed, they must eliminate user access when they leave, and so users will not be able to access the cloud after removal. A user who has left should not be able to access the cloud with the existing attributes, secret key that had been granted. In addition, the existing CP-ABE scheme increases the size of the ciphertext according to the number of attributes specified by the data owner. This leads to inefficient use of cloud storage space and increases the amount of operations carried out by the user, which becomes excessive when the number of attributes is large. In this paper, CP-ABE access control is proposed to block access of withdrawn users in dynamic cloud environments. This proposed scheme focuses on the revocation of the attributes of the withdrawn users and the output of a ciphertext of a constant-size, and improves the efficiency of the user decryption operation through outsourcing.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.3
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• pp.41-69
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• 2020

The purpose of this study is to design and develop a alternative material recommendation system using automatic classification, based on user preference. Details of usage data by users from DREAM was analysed in order to develop the way of a method on selecting proper alternative material, and then the data by user preference were allocated under each category of 10 KDC categories. The keyword, selected from the title of users' usage data from a certain period of time, were divided into 10 subject categories and ranked by the order of frequency of appearance. Books including high frequency of the keyword in title can be selected as a preferred target for producing alternative materials. Lastly, a dynamic linkage for sharing usage data among National Library for the Disabled and other libraries is proposed to produce more proper alternative materials, based on user preference.