• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.207-216
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• 2024

As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.

• ETRI Journal
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• v.35 no.6
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• pp.1058-1067
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• 2013

An approach for game bot detection in massively multiplayer online role-playing games (MMORPGs) based on the analysis of game playing behavior is proposed. Since MMORPGs are large-scale games, users can play in various ways. This variety in playing behavior makes it hard to detect game bots based on play behaviors. To cope with this problem, the proposed approach observes game playing behaviors of users and groups them by their behavioral similarities. Then, it develops a local bot detection model for each player group. Since the locally optimized models can more accurately detect game bots within each player group, the combination of those models brings about overall improvement. Behavioral features are selected and developed to accurately detect game bots with the low resolution data, considering common aspects of MMORPG playing. Through the experiment with the real data from a game currently in service, it is shown that the proposed local model approach yields more accurate results.

• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.49-56
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• 2024

There have been emerging many use-cases applying recommendation systems especially in online platform. Although the performance of recommendation systems is affected by a variety of factors, selecting appropriate features is difficult since most of recommendation systems have sparse data. Conventional matrix factorization (MF) method is a basic way to handle with problems in the recommendation systems. However, the MF based scheme cannot reflect non-linearity characteristics well. As deep learning technology has been attracted widely, a deep neural network (DNN) framework based collaborative filtering (CF) was introduced to complement the non-linearity issue. However, there is still a problem related to feature embedding for use as input to the DNN. In this paper, we propose an effective method using singular value decomposition (SVD) based feature embedding for improving the DNN performance of recommendation algorithms. We evaluate the performance of recommendation systems using MovieLens dataset and show the proposed scheme outperforms the existing methods. Moreover, we analyze the performance according to the number of latent features in the proposed algorithm. We expect that the proposed scheme can be applied to the generalized recommendation systems.

• Journal of KIISE
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• v.41 no.12
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• pp.1110-1116
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• 2014

Nowadays, social networking sites (SNSs), such as Twitter, LinkedIn, and Tumblr, are coming into the forefront, due to the growth in the number of users. While users voluntarily provide their information in SNSs, privacy leakages resulting from the use of SNSs is becoming a problem owing to the evolution of large data processing techniques and the raising awareness of privacy. In order to solve this problem, the studies on protecting privacy on SNSs, based on graph and machine learning, have been conducted. However, examples of privacy leakages resulting from the advent of a new SNS are consistently being uncovered. In this paper, we propose a technique enabling a user to detect privacy leakages beforehand in the case where the service provider or third-party application developer threatens the SNS user's privacy maliciously.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.3
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• pp.195-201
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• 2015

In this study, IT education contents have been developed based on the u-Learning approach for people with hearing impairment, focusing on allowing the user to learn from anywhere and anytime. Specifically, this study applies HTML5 to implementing IT education contents(JSP, Oracle) for the deaf because HTML5 enables the learner to access the contents through both web and mobile device on various platforms including android, Mac OS, and PC etc. The results of this study are as follows: First, the online computer courses are mostly supposed to be compatible with diverse types of mobile devices. However, some of the contents could not be run on applications residing in web and mobile devices because the contents tend to be developed using FLASH. HTML5 is the effective way to overcome the compatibility problem. Second, FLASH and HTML5 contents authoring tools have been compared in terms of their strong and weak points by applying the developed contents to those tools. The study also suggests that the future work would be needed in order to implement wide variety of event functions with HTML5. Lastly, design strategies enabling access through web and mobile devices have been analyzed in accordance with u-Learning design guidelines for the deaf and mobile application accessibility guidelines. However, in the latter case, the future work regarding design guidelines needs to be conducted to improve the educational accessibility depending on the level of impairment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.134-139
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• 2022

Recently, interest in programming and artificial intelligence is continuously increasing, and software education is being implemented as a mandatory education from elementary school. For efficient programming education, it is basically necessary to build a lab environment suitable for students and teachers, but there are performance problems due to the inadequacy of old computers and network equipment. Therefore, in this paper, we propose a web page-based online practice environment and algorithm competition scoring system using React and Spring boot to solve the problem of the programming practice environment. Through this, it is thought that programming learning can be carried out using only a web browser even on low-spec computers. In addition, since various programming languages can be learned irrespective of the language to be learned, it is considered that the time cost for establishing a practice environment can be reduced.

• Journal of the Korean earth science society
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• v.21 no.6
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• pp.655-662
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• 2000

According to the development of internet with Web, WBI has greatly influence on the present educational society. However, it is difficutly to design the web of the dynamic motions of graphics or animation using general programming technique based on high or low level language. Recently, Mecromedia Company supported a tool that is called Authoware which is the leading visual rich-media authoring solution for creating Web and online learning applications, to solve the problem easily. In the paper, using the the Authoware we tried to develop a web page about tidal variations due to sea level change and intertidal zone variations using the Authorware 5.1. To do this, we used the ocean survey data of Iho beach and the tidal level data based on Tidal Tables of Cheju harbor. The results showed that the Authorware was very useful to construct the simulation of tidal phenomena on web. Therefore, the Authorware can be applied to the simulation related with animation and dynamic motions for the other WBI objective.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.651-658
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• 2020

The basic medical subjects are essential for the understanding of the major in the department of health science and are very important. Anatomy is one of the fundamental areas of medical education. On the other hand, the application of new teaching method is being attempted in various fields. Station rotation model, one of the blended learning, is also one of the popular teaching method. Station rotation model allows students to rotate through stations on a fixed schedule, where at least one of the stations is an online learning station. This study investigate the satisfaction of students when applying station rotation model to anatomy class. Each station in the station rotation model consisted of VR application learning, online problem solving, model observation and oral test. After applying station rotation model (2 weeks) to the 'Functional anatomy and Practice' course taken by 37 students of the'Department of Occupational Therapy'at H University, this study conducted a satisfaction survey compare with lecture class for students taking the course. At the result, station rotation model was significantly higher than lecture class in both understanding, interest, concentration and diversity degree. Based on these results, I suggest applying the station rotation model to the anatomy class because it also showed high satisfaction in that.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.170-171
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• 2013

In aspect of HCI(Human Computer Interaction) gameplay is the procedure to solve the problem that gamers encounter in order to generate or discover a new rule to achieve gamers' goal. The goal of this research is to investigate the structure and understand the gameplay in aspect of affordance from ecological psychology rather than the traditional problem solving theory. This research selects 'World of Warcraft' as MMORPG(Massively Multiplayer Online Role Playing Game). Five expert gamers participated in this experiment. We record all gameplay using audio and video device. We conducted protocol analysis as qualitative method based on the verbal report and action protocol during game playing. As result, gameplay based on affordance includes selection and relation. We found that subjects selected one thing at once with attention. Moreover, we found that there were two behaviors : exploratory action and performatory action. We believe that learning, utilization, and transformation for affordance appear. The result of this research imply to suggest design guideline for game design methodology when designers develop game.