• Journal of Music and Human Behavior
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• v.15 no.2
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• pp.1-22
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• 2018

The purpose of this analysis was to classify music therapy studies published in KCI journals to understand the type of research being conducted and trends in the research. This study analyzed 472 music therapy articles published in KCI journals from 2005 to October 31, 2017. The study analyzed the overall characteristics of the included studies, trends in each research field, study subjects, research types, and commonalities and differences between research fields. It was confirmed that the number of music therapy studies published in KCI journals steadily increased from 2005. The results also confirmed that the research subjects and types of music therapy research became more diverse. For example, earlier studies focused on participants with disabilities, but populations without disabilities were increasingly the focus of more recent studies. Similarly, earlier studies were mostly experimental or descriptive, but more recent research included historical, philosophical, and program development studies. The results of analysis confirm that music therapy research is evolving and being conducted in cooperation with many other fields. This article provides a snapshot of the current state of music therapy research and offers implications for the future of music therapy research with multidisciplinary characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.813-826
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• 2022

AI-based image processing technologies in various fields have been widely studied. However, the lighter the board, the more difficult it is to reduce the weight of image processing algorithm due to a lot of computation. In this paper, we propose a method using deep learning for object recognition algorithm in lightweight embedded boards. We can determine the area using a deep neural network architecture algorithm that processes semantic segmentation with a relatively small amount of computation. After masking the area, by using more accurate deep learning algorithm we could operate object detection with improved accuracy for efficient neural network (ENet) and You Only Look Once (YOLO) toward executing object recognition in real time for lightweighted embedded boards. This research is expected to be used for autonomous driving applications, which have to be much lighter and cheaper than the existing approaches used for object recognition.

• Korean Journal of Optics and Photonics
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• v.34 no.6
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• pp.261-268
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• 2023

We propose a compact differential interference contrast microscopic module, which enables snapshot measurements for quantitative phase imaging. The proposed module adopts the lateral shearing interferometric principle, which can obtain self-interference without a reference. Due to the absence of the reference, the system is more stable than the typical interferometric systems. It uses a polarization grating to generate two laterally shifted wavefronts based on its birefringence and polarizing beam-splitting characteristics. Furthermore, the use of a polarization camera does not require sequential measurements for the phase extraction. In the experiments, we observe and measure the timely varying changes of various specimens to verify the system performance with the bright field images and phase contrast images. Because the proposed microscopic module also has the merit of being adaptable to typical microscopy instead of using an imaging camera, it can conveniently replace conventional contrast microscopy.

• Journal of the Korea Safety Management & Science
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• v.25 no.4
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• pp.141-151
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational safety and reliability of the parcel loading system, a predictive maintenance platform was implemented based on the Naive Bayes-LSTM(Long Short Term Memory) model. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on a RabbitMQ, loading data in an InMemory method using a Redis, and managing snapshot DB in real time. Also, in this paper, as a verification of the Naive Bayes-LSTM predictive maintenance platform, the function of measuring the time for data collection/storage/processing and determining outliers/normal values was confirmed. The predictive maintenance platform can contribute to securing reliability and safety by identifying potential failures and defects that may occur in the operation of the parcel loading system in the future.

• Bioinformatics and Biosystems
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• v.1 no.2
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• pp.99-102
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• 2006

The Basic Local Alignment Search Tool (BLAST) is one of the most established software in bioinformatics research and it compares a query sequence against the libraries of known sequences in order to investigate sequence similarity. Expressed Sequence Tags (ESTs) are single-pass sequence reads from mRNA (or cDNA) and represent the expression for a given cDNA library and the snapshot of genes expressed in a given tissue and/or at a given developmental stage. Therefore, ESTs can be very valuable information for functional genomics and bioinformatics researches. Although major bio database (DB) websites including NCBI are providing BLAST services and EST data, local DB and search system is demanding for better performance and security issue. Here we present animal EST DBs and local BLAST search system. The animal ESTs DB in NCBI Genbank were divided by animal species using the Perl script we developed. and we also built the new extended DB search systems fur the new data (Local Animal BLAST Search System: http://bioinfo.kohost.net), which was constructed on the high-capacity PC Cluster system fur the best performance. The new local DB contains 650,046 sequences for Bos taurus(cattle), 368,120 sequences for Sus scrofa (pig), 693,005 sequences for Gallus gallus (fowl), respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.895-904
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• 2007

This paper proposes a robust sub-optimal smart antenna in Code Division Multiple Access (CDMA) basestation. It makes use of the property of the Least Mean Square (LMS) algorithm and the Conjugate Gradient Method (CGM) algorithm for beamforming processes. The weight update takes place at symbol level which follows the PN correlators of receiver module under the assumption that the post correlation desired signal power is far larger than the power of each of the interfering signals. The proposed algorithm is simple and has as low computational load as five times of the number of antenna elements(O(5N)) as a whole per each snapshot. The output Signal to Interference plus Noise Ratio (SINR) of the proposed smart antenna system when the weight vector reaches the steady state has been examined. It has been observed in computer simulations that proposed beamforming algorithm improves the SINR significantly compared to the single antenna case. The convergence property of the weight vector has also been investigated to show that the proposed hybrid algorithm performs better than CGM and LMS during the initial stage of the weight update iteration. The Bit Error Rate (BER) characteristics of the proposed array has also been shown as the processor input Signal to Noise Ratio (SNR) varies.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.118-128
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• 2015

Recently BIM technology has been expanded for using in construction project. Due to the high-cost of BIM infrastructure development, lack of regulations, lack of process and so forth, usage of BIM has been delayed than initial expectations. In design phase, especially, collaboration based on BIM system has been a key factor for successful next generation building project. Through the analysis of current research trends about IT technologies, virtualization and BIM service, data exchange such as drawings, 3D model, object data, properties using cloud computing and virtual server system is defined as a most successful solution. The purpose of this study is to enable the cloud computing BIM server to provide several main functions such as editing models, 3D model viewing and checking, mark-up and snapshot in high-performance quality by proper design of VDI system. Concurrent client connection performance is a main technical index of VDI. Through testing of test-bed server client, developed VDI system's multi-connect control is evaluated. Performance-test result of BIM server VDI effect to development direction of cloud computing BIM service for commercialization.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.5
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• pp.406-418
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• 2004

Last days, various kinds of applications and system were individually introduced into specific groups or enterprises by different objective without considering interoperability among those. However, the environment for data processing is changing rapidly in these days. And now the necessity is growing to integrate and couple applications and system in the process dimension for more flexible and quicker data processing on these application programs and system. When integrating these application programs or system, an integration based on XML is recommended as it is one of good methods which will the additional cost and satisfy the requirements of the integration. This is because the XML is not only device-independent data type which can be used any platform, but also it uses XSLT, the document conversion standard established by W3C, which allows easy data conversion from one to another type on occasion of demands. This paper studies a design and implementation of system to convert XML structure. This system shows the structure of source- side providing data and destination-side processing data with using XML schema that defines structural information of a XML document. And this system defines the structure relationship of desired form as mapping structural information and data. This system creates the XSLT document that defines conversion rule between two structures based information which is defined. The XSLT document which is created as described above will convert data to be appropriate to the structure of the destination- side. By implementing this system, it is able to apply a document into various kinds of structure without considering specific system or platform and it is able to construct XSLT document to which meaning of desired form can be given. This paper aims to offer a process conversion between documents and to improve interoperability and scalability, so that we can contribute to build XML document processing environment

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.280-291
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• 2009

Skyline Query processing is important to wireless sensor applications in order to process multi-dimensional data efficiently. Most skyline researches about sensor network focus on minimizing the energy consumption due to the battery powered constraints. In order to reduce energy consumption, Filtering Method is proposed. Most existing researches have assumed a snapshot skyline query processing and do not consider continuous queries and use data generated in ancestor node. In this paper, we propose an energy efficient method called Bottom up filtering tuple selection for continuous skyline query processing. Past skyline data generated in child nodes are stored in each sensor node and is used when choosing filtering tuple. We also extend the algorithms, called Support filtering tuple(SFT) that is used when we choose the additional filtering tuple. There is a temporal correlation between previous sensing data and recent sensing data. Thus, Based on past data, we estimate current data. By considering this point, we reduce the unnecessary communication cost. The experimental results show that our method outperforms the existing methods in terms of both data reduction rate(DRR) and total communication cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2594-2603
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• 1997

A novel method of adaptive beam forming is presented in this paper. The proposed technique provides for a suboptimal beam pattern that increases the Signal to Noise/Interference Ratio (SNR/SIR), thus, eventually increases the capacity of the communication channel, under an assumption that the desired signal is dominant compared to each component of interferences at the receiver, which is precoditionally achieved in Code Division Multiple Access (CDMA) mobile communications by the chip correlator. The main advantages of the new technique are:(1)The procedure requires neither reference signals nor training period, (2)The signal interchoerency does not affect the performance or complexity of the entire procedure, (3)The number of antennas does not have to be greater than that of the signals of distinct arrival angles, (4)The entire procedure is iterative such that a new suboptimal beam pattern be generated upon the arrival of each new data of which the arrival angle keeps changing due tot he mobility of the signal source, (5)The total amount of computation is tremendously reduced compared to that of most conventional beam forming techniques such that the suboptimal beam pattern be produced at vevery snapshot on a real-time basis. The total computational load for generating a new set of weitht including the update of an N-by-N(N is the number of antenna elements) autocovariance matrix is $0(3N^2 + 12N)$. It can further be reduced down to O(11N) by approximating the matrix with the instantaneous signal vector.