• 재활복지
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• v.20 no.1
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• pp.131-150
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• 2016

This study aims to compare global policies on ICT accessibility and to suggest possible solutions that help to enhance ICT accessibility for socially disadvantaged groups. The results indicated that related laws and standards in Korea are relatively well established than Asian countries' whereas they need improvements when compared to the US or the UK. Particularly, in spite of rapid development in information communication technology industry, incorporating the definition of newly developed technologies into existing laws related to ICT accessibility seemed slow that caused reluctancy of related parties to address accessibility issues the new technologies create. In addition, Korean government seems less effortful to develop policies and standards apart from web and mobile application accessibility. In order to resolve the problems, firstly, the period or process of enacting and amending laws can be shorten. Next, a government affiliated research institute can be established to do research and develop ICT accessibility related to user scenarios so that effective policies and standards could be readily provided. Even though other possible solutions can be suggested, what is more important than that is that any interested parties should sustainably make efforts to provide equal opportunities for the underserved populations.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.15-26
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• 2021

Recently, as the introduction of cloud, mobile, and IoT has become active, there is a growing need for technology development that can supplement the limitations of traditional security solutions based on fixed perimeters such as firewalls and Network Access Control (NAC). In response to this, SDP (Software Defined Perimeter) has recently emerged as a new base technology. Unlike existing security technologies, SDP can sets security boundaries (install Gateway S/W) regardless of the location of the protected resources (servers, IoT gateways, etc.) and neutralize most of the network-based hacking attacks that are becoming increasingly sofiscated. In particular, SDP is regarded as a security technology suitable for the cloud and IoT fields. In this study, a new access control system was proposed by combining SDP and hash tree-based large-scale data high-speed signature technology. Through the process authentication function using large-scale data high-speed signature technology, it prevents the threat of unknown malware intruding into the endpoint in advance, and implements a kernel-level security technology that makes it impossible for user-level attacks during the backup and recovery of major data. As a result, endpoint security, which is a weak part of SDP, has been strengthened. The proposed system was developed as a prototype, and the performance test was completed through a test of an authorized testing agency (TTA V&V Test). The SDP-based access control solution is a technology with high potential that can be used in smart car security.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.281-290
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• 2020

With the spread of smartphones, services that want to use personalized data are increasing. In particular, healthcare-related services deal with a variety of data, and data visualization techniques are used to effectively show this. As data visualization techniques are used, interactions in visualization are also naturally emphasized. In the PC environment, since the interaction for data visualization is performed with a mouse, various filtering for data is provided. On the other hand, in the case of interaction in a mobile environment, the screen size is small and it is difficult to recognize whether or not the interaction is possible, so that only limited visualization provided by the app can be provided through a button touch method. In order to overcome the limitation of interaction in such a mobile environment, we intend to enable data visualization interactions through conversations with chatbots so that users can check individual data through various visualizations. To do this, it is necessary to convert the user's query into a query and retrieve the result data through the converted query in the database that is storing data periodically. There are many studies currently being done to convert natural language into queries, but research on converting user queries into queries based on visualization has not been done yet. Therefore, in this paper, we will focus on query generation in a situation where a data visualization technique has been determined in advance. Supported interactions are filtering on task x-axis values and comparison between two groups. The test scenario utilized data on the number of steps, and filtering for the x-axis period was shown as a bar graph, and a comparison between the two groups was shown as a line graph. In order to develop a natural language processing model that can receive requested information through visualization, about 15,800 training data were collected through a survey of 1,000 people. As a result of algorithm development and performance evaluation, about 89% accuracy in classification model and 99% accuracy in query generation model was obtained.

• Korea Science and Art Forum
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• v.21
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• pp.105-116
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• 2015

This study intended to give helps in planning a specialized exhibition by carrying out a survey objecting to KOREA PACK 2015 attendees including visitors who possessed mobile coupons after finishing advance registration through on-line, and then investigating, analyzing satisfactions of attendees together with effects of the specialized exhibition using IT technology. As a lot of relevant preceeding researches have been made by focussing on exhibition organizer and exhibitors, the viewpoints of attendees at the specialized exhibition using IT conversing technology such as mobile and etc. were to be investigated and analyzed. Thus, this research tried to do an empirical identification on effects of the exhibition by analyzing relations between its watching forms and satisfactions including a survey on the on-line PR route utility of IT technology in addition to visiting motives of attendees who watched the exhibition. A summarization of the current study is followed: First, in case of attending in the exhibition for specific purposes, they searched related information positively, and were shown as doing information gathering behaviors and also high possibility on purchases was confirmed. Second, it was confirmed that positive attendees had decision-making on purchases. This finding means that attendees who watch the specialized exhibition have authority and responsibility of being able to purchase in many cases, so methods of improving sales by effectively doing PR on own products and technical competitiveness in the exhibition are necessary to exhibitors. Third, attendees who have specific purposes showed higher satisfactions on the exhibition than general visitors, but satisfactions on consultation, staff attitudes, and facility were turn out to be higher than providing related information on products or technology. Accordingly, the necessity of improving this outcome was confirmed. Therefore, exhibitors have to endeavor in providing more advanced services to attendees of the exhibition by grasping technical trends in advance as well as cultivating professional staff who can promote products well.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.637-651
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• 2017

In order for a financial company to collect personal information, it explicitly notifies consumers of the contents stipulated by law and gets consent beforehand. As a result, as financial products became more complicated and diverse, and the contents of 'Consent form for providing personal information' became more complicated and more. In particular, in the case of internet or mobile, the letter became smaller as the screen size limit, making it more difficult to understand. This is because almost all companies that collecting personal information are in a similar situation, In the position of consumers who use services are, contradictions arise that habitually agree without understanding the consent contents. In this research, in order to present a consent policy establishment decision-making model to rationally collect and use personal information through the Internet website of financial companies, consider the domestic and foreign legal system Then, derive a problem To present improvement measures. In addition, the evaluation factors selected through the research are verified by presenting decision making models and formulas using AHP (Analytic Hierarchy Process) method.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.57-68
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• 2018

A system to prevent disasters by collecting and analyzing environmental information such as road surface sedimentation, sinkholes, collapse risk of bridges, temperature and humidity around tram station is continuously monitored by monitoring the condition of road surface when constructing tram which is one of the urban railways. In this paper, we propose a wireless network security management system for tram roads based on LPWA that can recognize risk factors of road surface, bridge and tram station of tram in advance and prevent risk. The proposed system consists of a sensor node that detects the state of the tram road surface, a gateway that collects sensor information, and a safety management system that monitors the safety and environmental conditions of the tram road surface, and applies the low power long distance communication technology. As a result of comparing the proposed system with the LTE system in the field test, it was confirmed that there is no significant difference between the sensor information value and the critical alarm level in the monitoring system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.195-200
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• 2021

With the development of transportation and mobiles demand for tourism travel is increasing and related industries are also developing significantly. The combination of augmented reality and tourism contents one of the areas of digital media technology, is also actively being studied, and artificial intelligence is already combined with the tourism industry in various directions, enriching tourists' travel experiences. In this paper, we propose a system that scans miniature models produced by reducing tourist areas, finds the relevant tourist sites based on models learned using deep learning in advance, and provides relevant information and 3D models as AR services. Because model learning and object detection are carried out using YOLOv3 neural networks, one of various deep learning neural networks, object detection can be performed at a fast rate to provide real-time service.

• Smart Media Journal
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• v.11 no.5
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• pp.48-55
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• 2022

Tomato crops are easy to expose to disease and spread in a short period of time, so late measures against disease are directly related to production and sales, which can cause damage. Therefore, there is a need for a service that enables early prevention by simply and accurately diagnosing tomato diseases in the field. In this paper, we construct a system that applies a deep learning-based model in which ImageNet transition is learned in advance to classify and serve nine classes of tomatoes for disease and normal cases. We use the input of MobileNet, ResNet, with a deep learning-based CNN structure that builds a lighter neural network using a composite product for the image set of leaves classifying tomato disease and normal from the Plant Village dataset. Through the learning of two proposed models, it is possible to provide fast and convenient services using MobileNet with high accuracy and learning speed.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.415-424
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• 2022

This study is a user experience research on the current usage of TV multiview and evaluating the usability. From traditional TV viewing to connecting laptop or mobile devices, the scope of using TV has expanded and evolved to multipurpose. Utilizing the multiview feature offers new TV experiences, but research on its usability has not been actively conducted yet. In this research, a case study and survey were held prior to usability testing to identify user needs and behavior of TV multiview. After reviewing the results, we ran a task-based usability testing and in-depth interview. As a result, users preferred different ways of accessing and using multiview based on their situation, and the current user interface needed improvement for easier, intuitive use. This study is expected to contribute to the development of improving user experience in TV multiview.