• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.161-170
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• 2019

Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.39-47
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• 2020

In this paper, we proposed a deep learning-based detection method using Saliency Attention to detect salient objects in images. The salient object detection separates the object where the human eye is focused from the background, and determines the highly relevant part of the image. It is usefully used in various fields such as object tracking, detection, and recognition. Existing deep learning-based methods are mostly Autoencoder structures, and many feature losses occur in encoders that compress and extract features and decoders that decompress and extend the extracted features. These losses cause the salient object area to be lost or detect the background as an object. In the proposed method, Saliency Attention is proposed to reduce the feature loss and suppress the background region in the Autoencoder structure. The influence of the feature values was determined using the ELU activation function, and Attention was performed on the feature values in the normalized negative and positive regions, respectively. Through this Attention method, the background area was suppressed and the projected object area was emphasized. Experimental results showed improved detection results compared to existing deep learning methods.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.73-80
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• 2023

The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.119-126
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• 2009

This paper describes the non-stringed guitar composed of laser strings, frets, sound synthesis algorithm and a processor. The laser strings that can depict stroke and playing arpeggios comprise laser modules and photo diodes. Frets are implemented by voltage divider. The guitar body does not need to implement physically because commuted waveguide synthesis is used. The proposed frets enable; players to represent all of chords by the chord glove as well as guitar solo. Sliding, hammering-on and pulling-off sounds are synthesized by using parameters from the voltage divider. Because the pitch shifting corresponds to the time-varying propagation speed in the digital waveguide model, the proposed model can synthesize vibrato as well. After transformation of signals from the laser strings and frets into parameters for synthesis algorithm, the digital signal processor, TMS320F2812, performs the real-time synthesis algorithm and communicates with the DAC. The demonstration movieclip available via the Internet shows one to play a song, 'Arirang', synthesized by proposed algorithm and interfaces in real-time. Consequently, we can conclude that the proposed synthesis algorithm is efficient in guitar solo and there is no problem to play the non-stringed guitar in real-time.

• The Korean Journal of Nuclear Medicine
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• v.38 no.4
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• pp.294-299
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• 2004

Purpose: Both human NIS and mutant $D_2R$ transgenes are proposed as reporting system in transplanted cell tracking. Using hepatoma cell lines, we constructed a dual reporter system containing human sodium-iodide symporter (hNIS) and dopamine 2 receptor ($D_2R$) and compared its characteristics. Materials and Methods: The recombinant plasmid ($pIRES-hNIS/D_2R$) was constructed with IRES (internal ribosome entry site) under control of the CMV promoter $pIRES-hNIS/D_2R$ was transfected to human hepatoma SK-Hep1 cell line with lipofectamine. HEP-ND ($SK-Hep1-hNIS/D_2R$) cells stably expressing hNIS and $D_2R$ was established by selection with G418 for two weeks. RT-PCR was performed to investigate the expression of both hNIS and $D_2R$ genes. The expressions of hNIS and $D_2R$ were measured by $^{125}I$ uptake assays and receptor binding assays. Specific binding of $D_2R$ to $[^3H]spiperone$ was verified by Scatchard plot with (+) butaclamol as a specific inhibitor. $K_d\;and\;B_{max}$ values were estimated. The correlation between hNIS and $D_2R$ expression was compared by using each clone. Results: Similar quantities of hNIS and $D_2R$ genes were expressed on HEP-ND as RT-PCR assays. HEP-ND cells showed 30 to 40 fold higher radioiodine uptakes than those of parental SK-Hep1 cells. $^{125}I$ uptake in HEP-ND cells was completely inhibited by $KClO_4$, a NIS inhibitor Specific binding to HEP-ND cells was saturable and the $K_d\;and\;B_{max}$ values for HEP-ND cells were 2.92 nM, 745.25 fmol/mg protein and 2.91nM, 1323 fmole/mg protein in two clones, respectively. The radioiodine uptake by hNIS activity and $D_2R$ binding was highly correlated. Conclusion: We developed a dual positron and gamma imaging reporter system of hNIS and $D_2R$ in a stably transfected cell line. We expect that $D_2R$ and hNIS genes can complement mutually as a nuclear reporting system or that $D_2R$ can be used as reporter gene when hNIS gene were used as a treatment gene.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.45-58
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• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.3
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• pp.60-68
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• 2009

This work proposes a 10b 200MS/s 65nm CMOS ADC for high-definition video systems such as HDTV requiring high resolution and fast operating speed simultaneously. The proposed ADC employs a four-step pipeline architecture to minimize power consumption and chip area. The input SHA based on four capacitors reduces the output signal range from $1.4V_{p-p}$ to $1.0V_{p-p}$ considering high input signal levels at a low supply voltage of 1.2V. The proposed three-stage amplifiers in the input SHA and MDAC1 overcome the low output resistance problem as commonly observed in a 65nm CMOS process. The proposed multipath frequency-compensation technique enables the conventional RNMC based three-stage amplifiers to achieve a stable operation at a high sampling rate of 200MS/s. The conventional switched-bias power-reduction technique in the sub-ranging flash ADCs further reduces power consumption while the reference generator integrated on chip with optional off-chip reference voltages allows versatile system a locations. The prototype ADC in a 65nm CMOS technology demonstrates a measured DNL and INL within 0.19LSB and 0.61LSB, respectively. The ADC shows a maximum SNDR of 54.BdB and 52.4dB and a maximum SFDR of 72.9dB and 64.8dB at 150MS/S and 200MS/s, respectively. The proposed ADC occupies an active die area of $0.76mm^2$ and consumes 75.6mW at a 1.2V supply voltage.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.1
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• pp.51-60
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• 2014

In this study, ICT medical service provider's level of knowledge fire fighting safety and methods on coping with fires in the regions of Gwangju and Jeonam Province of Korea were investigated to determine the elements affecting such levels and provide basic information on the manuals for educating how to cope with the fire fighting safety in medical facilities. The data were analyzed using SPSS Win 14.0. The scores of level of knowledge fire fighting safety of ICT medical service provider's were 7.06(10 point scale), and the scores of level of recognizing how to cope with fire fighting safety were 6.61(11 point scale). level of recognizing how to cope with fire fighting safety were significantly different according to gender(t=4.12, p<.001), age(${\chi}^2$=17.24, p<.001), length of career(${\chi}^2$=22.76, p<.001), experience with fire fighting safety education(t=6.10, p<.001), level of subjective knowledge on fire fighting safety(${\chi}^2$=53.83, p<.001). In order to enhance the level of understanding of fire fighting safety and methods of coping by the ICT medical service providers it is found that: self-directed learning through avoiding the education just conveying knowledge by lecture tailored learning for individuals fire fighting education focused on experiencing actual work by developing various contents emphasizing cooperative learning deploying patients by classification systems using simulations and a study on the implementation of digital anti-fire monitoring system with multipoint communication protocol, a design and development of the smoke detection system using infra-red laser for fire detection in the wide space, video based fire detection algorithm using gaussian mixture mode developing an education manual for coping with fire fighting safety through multi learning approach at the medical facilities are required.