• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.49-55
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• 2017

Recently, for safety of people, there are proposed so many technologies which detect density of people at the specific place or space. The representative technology for crowd density estimation was using image analysis method from CCTV images. However, this method had a weakness which could not be used and which's accuracy was lower at the dark or smog space. Therefore, in this paper, to solve this problem, we proposed a user density estimation system at closed space using high frequency and smart device. The system send inaudible high frequencies to smart devices and it count the smart devices which detect the high frequencies on the space. We tested real-time user density with the proposed system and ten smart devices to evaluate performance. According to the testing results, we confirmed that the proposed system's accuracy was 95% and it was very useful. Thus, because the proposed system could estimate about user density at specific space exactly, it could be useful technology for safety of people and measurement of space use state at indoor space.

• Convergence Security Journal
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• v.19 no.3
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• pp.29-36
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• 2019

The convergence of traditional industry and ICT is a combination of security threats and vulnerabilities in ICT and specific industry-specific problems of existing industries, and new security threats and vulnerabilities are emerging. In particular, in the medical ICT convergence industry, various problems regarding user authentication are derived from the medical information system, which is being used for abuse and security weaknesses. According, this study designed and implemented a user authentication system for secure user management in medical ICT convergence environment. Specifically, we design and implement measures to solve the abuse and security weaknesses of ID sharing and to solve the inconvenience of individual ID / PW authentication by performing user authentication using personalized devices based on medical information systems.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.97-117
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• 2012

Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.193-200
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• 2016

This paper introduces an algorithm to middle-low price drone's autonomous navigation flight system using computer vision and GPS. Existing drone operative system mainly contains using methods such as, by inputting course of the path to the installed software of the particular drone in advance of the flight or following the signal that is transmitted from the controller. However, this paper introduces new algorithm that allows autonomous navigation flight system to locate specific place, specific shape of the place and specific space in an area that the user wishes to discover. Technology developed for military industry purpose was implemented on a lower-quality hobby drones without changing its hardware, and used this paper's algorithm to maximize the performance. Camera mounted on middle-low price drone will process the image which meets user's needs will look through and search for specific area of interest when the user inputs certain image of places it wishes to find. By using this algorithm, middle-low price drone's autonomous navigation flight system expect to be apply to a variety of industries.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.161-170
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• 2010

This paper provides a novel approach for a user oriented system for face detection system for application developers. Even though there are many open source or commercial libraries to solve the problem of face detection, they are still hard to use because they require specific knowledge on detail algorithmic techniques. The purpose of this paper is to come up with a high-level system for face detection with which users can develop systems easily and even without specific knowledge on face detection theories and algorithms. Important conditions are firstly considered to categorize the large problem space of face detection. The conditions identified here are then represented as expressions so that application developers can use them to express various problems. Once the conditions are expressed by developers, the interpreter proposed take the role to interpret the conditions, find and organize the optimal algorithms to solve the represented problem with corresponding conditions. A proof-of-concept is implemented and some example problems are tested and analyzed to show the ease of use and usability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.66
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• pp.27-35
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• 2001

The Gateway Server Authorization System(GSAS) presented in this thesis is a database authorization system. GSAS is responsible for user\`s authorization, and privilege management, audit service. Only users that are filtered in GSAS can access the DBMS(Data Base Management System) through middleware. GSAS is located at the DBMS and already contains an authorization record for user accessing a specific DBMS. GSAS on consists of several components, namely an authorization manager, a privilege manager, and an audit manager. As an authorization manager and a privilege manager can only approve a pass at the same time, a user can get accessibility for DBMS.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.217-223
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• 2017

With the development of sensor networks and Internet of Things (IoT) technology, personalized context information has been collected and customized services can be provided to related users. Currently, the context information system is at the level of analyzing and recognizing user specific behavioral characteristics and generating events.In the IoT environment, IoT products themselves should provide the required services with minimal user intervention, rather than acting for a specific purpose. In this paper, to minimize the user intervention in the IoT environment, we implemented an automatic attendance recognition system using context information from the ECG based on beacon. Environment of provided specific Context information, we compared and analyzed the degree of user intervention among the authentication method using ECG sensor in this paper and the existing authentication method. As a result of the analysis, we confirmed that the system implemented in this paper minimizes user intervention.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.64-78
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• 2024

Sentiment analysis is one of the promising approaches for developing a point of interest (POI) recommendation system. It uses natural language processing techniques that deploy expert insights from user-generated content such as reviews and feedback. By applying sentiment polarities (positive, negative, or neutral) associated with each POI, the recommendation system can suggest the most suitable POIs for specific users. The proposed study combines two models for POI recommendation. The first model uses bidirectional long short-term memory (BiLSTM) to predict sentiments and is trained on an election dataset. It is observed that the proposed model outperforms existing models in terms of accuracy (99.52%), precision (99.53%), recall (99.51%), and F1-score (99.52%). Then, this model is used on the Foursquare dataset to predict the class labels. Following this, user and POI embeddings are generated. The next model recommends the top POIs and corresponding coordinates to the user using the LSTM model. Filtered user interest and locations are used to recommend POIs from the Foursquare dataset. The results of our proposed model for the POI recommendation system using sentiment analysis are compared to several state-of-the-art approaches and are found quite affirmative regarding recall (48.5%) and precision (85%). The proposed system can be used for trip advice, group recommendations, and interesting place recommendations to specific users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1237-1252
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• 2010

This paper proposes an intelligent technique for data sharing and event transition among personal devices including smart phones, laptops, and desktops. We implemented the PES (Personal Event Service) system that proactively executes appropriate tasks across multiple devices without explicit user requests by sharing the data used by the user and recognizing user intention based on the observed actions of the user for specific devices. The client module of PES installed on each device monitors the user actions and recognizes the intention of the user. The server provides data sharing and maintenance for clients. The connection between client and server is established by Java RMI (Remote Method Invocation). A series of experiments were performed to evaluate user satisfaction and system accuracy, and the results showed that the PES system can proactively provide appropriate, personalized services with a high degree of satisfaction to the user in an effective and efficient manner.

• Asia pacific journal of information systems
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• v.9 no.2
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• pp.1-17
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• 1999

A feedback echo is a structured restatement of the user's query and informs the user what the system intends to do for the query. This provides backtracking of the user's query so that the user knows how the system has interpreted the query. This study scrutinizes whether the feedback echo, as currently available in the INTELLECT commercial system, can improve the performance of a casual user using a restricted natural language database interface. This study concludes that the particular type of feedback echo available in this commercial system was not effective in terms of overall performance for casual users. It is worth mentioning, however, that the feedback echo was effective for the specific type of error: using wrong conditions for data retrieval.