• The Research Journal of the Costume Culture
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• v.23 no.6
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• pp.1097-1115
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• 2015

ICT in the IOT era is the core basis of modern society. This study investigated and analyzed the recent commercialization trends of smart fashion products internationally and domestically, to utilize them as the basis of data for developing user-friendly smart fashion products that can meet the needs of consumers. Keyword research using the most representative search engines, Google and Naver was conducted for searching for various wearable items commercialized actively since 2010. The final 78 products were classified by the physical area, and the key features and benefits were analyzed. Smart fashion products were classified as four physical types for the head and face, torso, arms and hands, and ankles and feet. Smart fashion products for each body part were developed in various ways, such as hats, glasses, lenses, virtual screens, earphones, headsets, clothing, watches, wrist bands, gloves, rings, wallets, bags, anklets, shoes, socks, and insoles. The main features were music playback, bluetooth, a camera based on NFC, virtual effects, health and safety protection through measuring heartbeat and momentum, and social network sharing of all kinds of information, based on inter-working with a smartphone. These functions represent the physical, social, and emotional interactions among users and their surroundings, as well as the users, themselves. The research results are expected to be used in future studies on planning user-friendly and marketable products through in-depth analysis of the design characteristics of smart fashion products as well as consumer responses.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.27-39
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• 2017

To grasp the current status of smart campus and look for future directions, this study investigated the usage rate and perceived usefulness of digital devices and services by conducting online survey of 580 university students. The main results are as follows. First, smartphones have the highest ownership rate, followed by laptops, desktops, and digital cameras. Purchase intention of virtual reality devices is highest followed by smart watches/bands, and tablets. Second, mobilization in campus life is almost realized, however the usage of desktops is still high in education and administration context. Digital devices have been perceived particularly useful when searching and sharing information. Third, students use digital services such as search engines, messengers, and online libraries in their learning, and they use messengers, music and video services in their lives. Service usage rate and perceived usefulness are not proportional.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.5-23
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• 2016

It has been shown that in the modern society, teenagers do not read a lot of books. As basic research in order to attract teenagers to reading activities, the effectiveness of booktrailers in affecting reading motivation of teenagers has been studied. As such, 121 middle school and high school students were surveyed with respect to their (1) basic awareness of reading and booktrailers, (2) awareness thereof after watching booktrailers, and (3) reader behaviour reaction applied to AIDMA & AISAS sub-elements. Results show booktrailers to be much more effective in reading motivation than printed media such as book reviews. The preferred booktrailer type is the storyline type. The preferred elements of booktrailers are the storyline, background music, video effects, with their preference in descending order. Also, in terms of the reader behaviour reaction of the teenagers, very positive responses appear across all areas including attention and interest in the book, memories of the book, desire to read the book, search for information, and production of booktrailers. These results indicate that booktrailers can be utilized very effectively in providing reading motivation and in reading expression activities.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.223-230
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• 2003

Feature-based similarity retrieval has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects (e 'g', documents, images, video, music score, etc.). For example, images are represented by their color histograms, texture vectors, and shape descriptors, and are usually high-dimensional data. The performance of conventional multidimensional data structures(e'g', R- Tree family, K-D-B tree, grid file, TV-tree) tends to deteriorate as the number of dimensions of feature vectors increases. The R＊-tree is the most successful variant of the R-tree. In this paper, we propose a SOM-based R＊-tree as a new indexing method for high-dimensional feature vectors.The SOM-based R＊-tree combines SOM and R＊-tree to achieve search performance more scalable to high dimensionalities. Self-Organizing Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two dimensional space. The mapping preserves the topology of the feature vectors. The map is called a topological of the feature map, and preserves the mutual relationship (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. A best-matching-image-list. (BMIL) holds similar images that are closest to each codebook vector. In a topological feature map, there are empty nodes in which no image is classified. When we build an R＊-tree, we use codebook vectors of topological feature map which eliminates the empty nodes that cause unnecessary disk access and degrade retrieval performance. We experimentally compare the retrieval time cost of a SOM-based R＊-tree with that of an SOM and an R＊-tree using color feature vectors extracted from 40, 000 images. The result show that the SOM-based R＊-tree outperforms both the SOM and R＊-tree due to the reduction of the number of nodes required to build R＊-tree and retrieval time cost.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.393-398
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• 2002

The conventional bit allocation scheme for MPEG-1 audio encoding searches the subband with minimum MNR(mask-to-noise ratio) repetitively until its operation is completed, which occupies most of its total computational complexity. In this paper, as a computationally efficient approximation of it, we propose a new bit allocation scheme with a simple subband search and compare it with the existing schemes[1][2] in terms of the computational complexity and sound quality. For the performance comparison, we used the pop music signal contained in SQAM(sound quality assess material) CD from EBU. Simulation results show that the computational complexity of the proposed method is about 42% of that of the existing one in [1] and the sound quality difference in terms of MNR between the two schemes is within the 0.2 ㏈, for the case of using the layer II at the bit rate of 128 kbps.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.534-546
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• 2009

Query by humming is an effective and intuitive querying mechanism when a user wants to find a song without knowing lyrics. The query by humming system takes a user-hummed melody as input, compares it with melodies in a music database, and returns top-k similar melodies to the input. In this paper, we propose a novel algebra for query by humming, and design and implement a real query by humming system called HummingBase by exploiting the algebra. By analyzing existing similarity search techniques, we derive 10 core operators for the algebra. By using the well-defined algebra, we can easily implement such a system in a extensible and modular way. With two case studies, we show that the proposed algebra can easily represent the query processing processes of existing query-by-humming systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.388-393
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• 2010

Cultural Content Technology(CT, Culture Technology) for the development of cultural industry and the commercialization of technology, cultural contents, media, mount, pass the value chain process and increase the added value of cultural products that are good for all forms of intangible technology. In the field of Culture Technology, Music by analyzing the characteristics of the development of a variety of applications has been studied. Associated with EEG measures and the results of their research in response to musical stimuli are used to detect and study is getting attention. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP (Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG.

• Perspectives in Nursing Science
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• v.16 no.1
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• pp.45-54
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• 2019

Purpose: The purposes of this study was to review the literature on intervention for treating anxiety and depression among unmarried mothers living in facilities, and to understand core that could promote the development of more effective interventions. Methods: Key words in English and Korean were used to search through eight electronic databases-PubMed, Cochrane Library, EMBASE, CINAHL, RISS, DBpia, NDSL, and the National Assembly Library. Results: Ten studies were ultimately selected for the integrative review and were evaluated in terms of contextual and methodological quality. The studies consisted of seven quasi-experimental studies and three case report studies. The selected studies utilized music, art, forest therapy, dancing, education, and play programs to change mothers' perceptions, emotions, and behavior and to improve their relationships with their babies or others. Conclusion: It is important to consider mothers' self-awareness and emotional expression, and to improve their relationships with their babies or others as core elements when developing intervention programs for anxiety and/or depression among unmarried mothers living in residential facilities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1523-1537
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• 2018

The AI speaker is a simple operation that provides users with useful functions such as music playback, online search, and so the AI speaker market is growing at a very fast pace. However, AI speakers always wait for the user's voice, which can cause serious problems such as eavesdropping and personal information exposure if exposed to security threats. Therefore, in order to provide overall improved security of all AI speakers, it is necessary to identify potential security threats and analyze them systematically. In this paper, security threat modeling is performed by selecting four products with high market share. Data Flow Diagram, STRIDE and LINDDUN Threat modeling was used to derive a systematic and objective checklist for vulnerability checks. Finally, we proposed a method to improve the security of AI speaker by comparing the vulnerability analysis results and the vulnerability of each product.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.