• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2321-2326
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• 2011

Cervical vertebrae are a complex structure and an important part of human body connecting the head and the trunk. In this paper, we propose a method to extract sternocleidomastoid muscle from ultrasonography images of cervical vertabrae automatically. In our method, Region of Interests(ROI) is extracted first from an ultrasonography image after removing unnecessary auxiliary information such as metrics. Then we apply Ends-in search stretching algorithm in order to enhance the contrast of brightness. Average binarization is then applied to those pixels which its brightness is sufficiently large. The noise part is removed by image processing algorithms. After extracting fascia encloses sternocleidomastoid muscle, target muscle object is extracted using the location information of fascia according to the number of objects in the fascia. When only one object is to be extracted, we search downward first to extract the target muscle area and then search from right to left to extract the area and merge them. If there are two target objects, we extract first from the upper-bound of higher object to the lower-bound of lower object and then remove the fascia of the target object area. Smearing technique is used to restore possible loss of the fat area in the process. The thickness of sternocleidomastoid muscle is then calculated as the maximum thickness of those extracted objects. In this experiment with 30 real world ultrasonography images, the proposed method verified its efficacy and accuracy by health professionals.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.256-264
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• 2020

Industrial Wireless Sensor Networks (IWSNs) is exploited to achieve various objectives such as improving productivity and reducing cost in the diversity of industrial application, and it has requirements such as low-delay and high reliability packet transmission. To accomplish the requirement, the network manager performs graph construction and resource allocation about network topology, and determines the transmission cycle and path of each node in advance. However, this network management scheme cannot treat mobile devices that cause continuous topology changes because graph reconstruction and resource reallocation should be performed as network topology changes. That is, despite the growing need of mobile devices in many industries, existing scheme cannot adequately respond to path failure caused by movement of mobile device and packet loss in the process of path recovery. To solve this problem, a network management scheme is required to prevent packet loss caused by mobile devices. Thus, we analyse the location and movement cycle of mobile devices over time using machine learning for predicting the mobility pattern. In the proposed scheme, the network manager could prevent the problems caused by mobile devices through performing graph construction and resource allocation for the predicted network topology based on the movement pattern. Performance evaluation results show a prediction rate of about 86% compared with actual movement pattern, and a higher packet delivery ratio and a lower resource share compared to existing scheme.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.10
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• pp.239-246
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• 2020

In the medical field where artificial intelligence technology is introduced, research related to clinical decision support system(CDSS) in relation to diagnosis and prediction is actively being conducted. In particular, medical imaging-based disease diagnosis area applied AI technologies at various products. However, medical imaging data consists of inconsistent data, and it is a reality that it takes considerable time to prepare and use it for research. This paper describes a one-stop AI learning platform for converting to medical image standard R_CDM(Radiology Common Data Model) and supporting AI algorithm development research based on the dataset. To this, the focus is on linking with the existing CDM(common data model) and model the system, including the schema of the medical imaging standard model and report information for multi-center research based on DICOM(Digital Imaging and Communications in Medicine) tag information. And also, we show the execution results based on generated datasets through the AI learning platform. As a proposed platform, it is expected to be used for various image-based artificial intelligence researches.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.51-58
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• 2002

The conventional code division multiple access(CDMA) detector shows severe degradation in communication quality as the number of users increases due to multiple access interferences(MAI). This problem thus restricts the user capacity. Various multiuser detection algorithms have been proposed to overcome the MAI problem. The existing detectors can be generally classified into one of the two categories : linear multiuser detection and subtractive interference cancellation detectors. In the linear multiuser detection, a linear transform is applied to the soft outputs of the conventional detector. In the subtractive interference cancellation detection, estimates of the interference are generated and subtracted out from the received signal. There has been great interest in the family of the subtractive interference cancellation detection because the linear multiuser detection exhibits the disadvantage of taking matrix inversion operations. The successive interference cancellation (SIC) and the parallel interference cancellation (PIC) are the two most popular structures in the subtractive interference cancellation detector. The SIC structure is very simple in hardware complexity, but has the disadvantage of increased processing delay time, while the PIC structure is good in performance, but shows the disadvantage of increased hardware complexity. In this paper we propose a mixed structure form of SIC and PIC in order to achieve good performance as well as simple hardware complexity. A performance analysis of the proposed scheme has been made, and the superior characteristics of the mixed structure are demonstrated by extensive computer simulations. 

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.225-234
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• 2015

Nowadays a Virtual Power Plant (VPP) represents an aggregation of distributed energy resource such as Distributed Generation (DG), Combined Heat and Power generation (CHP), Energy Storage Systems (ESS) and load in order to operate as a single power plant by using Information and Communication Technologies, ICT. The VPP has been developed and verified based on a single virtual plant platform which is connected with a number of various distributed energy resources. As the VPP's distributed energy resources increase, so does the number of data from distributed energy. Moreover, it is obviously inefficient in the aspects of technique and cost that a virtual plant platform operates in a centralized manner over widespread region. In this paper the concept of the large-scale VPP which can reduce a error probability of system's load and increase the robustness of data exchange among distributed energy resources will be proposed. In addition, it can directly control and supervise energy resource by making small size's virtual platform which can make a optimal resource scheduling to consider of variable and sensitive load in the large-scale VPP. It makes certain the result is verified by simulation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.2
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• pp.6-14
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• 2007

In this paper, we propose and observe the Adaptive Modulation system with optimal Turbo Coded V-BLAST (Vertical-Bell-lab Layered Space-Time) technique that is applied the extrinsic information from MAP (Maximum A Posteriori) Decoder in decoding Algorithm of V-BLAST: ordering and slicing. The extrinsic information is used by a priori probability and the system decoding process is composed of the Main Iteration and the Sub Iteration. And comparing the proposed system with the Adaptive Modulation system using conventional Turbo Coded V-BLAST technique that is simply combined V-BLAST with Turbo Coding scheme, we observe how much throughput performance has been improved. In addition, we observe the proposed system using STD (Selection Transmit Diversity) scheme. As a result of simulation, Comparing with the conventional Turbo Coded V-BLAST technique with the Adaptive Modulation systems, the optimal Turbo Coded V-BLAST technique with the Adaptive Modulation systems has better throughput gain that is about 350 Kbps in 11 dB SNR range. Especially, comparing with the conventional Turbo Coded V-BLAST technique using 2 transmit and 2 receive antennas, the proposed system with STD (Selection Transmit Diversity) scheme show that the improvement of maximum throughput is about 1.77 Mbps in the same SNR range.

• The Journal of the Acoustical Society of Korea
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• v.21 no.6
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• pp.566-575
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• 2002

Low-titrate audio coding enables a number of Internet and mobile multimedia streaming service more efficiently. For the help of next-generation mobile telephone technologies and digital audio/video compression algorithm, we can enjoy the real-time multimedia contents on our mobile devices (cellular phone, PDA notebook, etc). But the limited available bandwidth of mobile communication network prohibits transmitting high-qualify AV contents. In addition, most bandwidth is assigned to transmit video contents. In this paper, we design a novel and simple method for reproducing high frequency components. The spectrum of high frequency components, which are lost by down-sampling, are modeled by the energy rate with low frequency band in Bark scale, and these values are multiplexed with conventional coded bitstream. At the decoder side, the high frequency components are reconstructed by duplicating with low frequency band spectrum at a rate of decoded energy rates. As a result of segmental SNR and MOS test, we convinced that our proposed method enhances the subjective sound quality only 10%∼20% additional bits. In addition, this proposed method can apply all kinds of frequency domain audio compression algorithms, such as MPEG-1/2, AAC, AC-3, and etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.45-52
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• 2004

There are many cities installing ITS(Intelligent Transportation Systems) and running TMC(Trafnc Management Center) to improve mobility and safety of roadway transportation by providing roadway information to drivers. There are many devices in ITS which collect real-time traffic data. We can obtain many valuable traffic data from the devices. But it's impossible to avoid missing traffic data for many reasons such as roadway condition, adversary weather, communication shutdown and problems of the devices itself. We couldn't do any secondary process such as travel time forecasting and other transportation related research due to the missing data. If we use the traffic data to produce AADT and DHV, essential data in roadway planning and design, We might get skewed data that could make big loss. Therefore, He study have explored some imputation techniques such as heuristic methods, regression model, EM algorithm and time-series analysis for the missing traffic volume data using some evaluating indices such as MAPE, RMSE, and Inequality coefficient. We could get the best result from time-series model generating 5.0$\%$, 0.03 and 110 as MAPE, Inequality coefficient and RMSE, respectively. Other techniques produce a little different results, but the results were very encouraging.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.38-51
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• 2020

A bottleneck and congestion occur when a freeway is closed due to maintenance and construction activities on the freeway. Although various traffic managements have been developed to improve the traffic efficiency at freeway work zones, such as merge control, there is a limit to those controls with human drivers. On the other hand, the wireless communication of connected and automated vehicles (CAVs) enables the operation of advanced traffic management. This study developed a traffic control strategy that integrates Dynamic Merge Control (DMC) and Lane Change Control (LCC) in a CAV environment. DMC operates as an either early or late merge based on the occupancy rate of upstream of the work zone. The LCC algorithm determines the number of vehicles that need to change their lane to balance the traffic volume on open lanes. The simulation results showed that integrated control improves the cumulative vehicle count, average speed upstream, and average network travel time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1083-1091
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• 2017

This paper describes a design of cryptographic processor supporting 224-bit elliptic curves over prime field defined by NIST. Scalar point multiplication that is a core arithmetic function in elliptic curve cryptography(ECC) was implemented by adopting the modified Montgomery ladder algorithm. In order to eliminate division operations that have high computational complexity, projective coordinate was used to implement point addition and point doubling operations, which uses addition, subtraction, multiplication and squaring operations over GF(p). The final result of the scalar point multiplication is converted to affine coordinate and the inverse operation is implemented using Fermat's little theorem. The ECC processor was verified by FPGA implementation using Virtex5 device. The ECC processor synthesized using a 0.18 um CMOS cell library occupies 2.7-Kbit RAM and 27,739 gate equivalents (GEs), and the estimated maximum clock frequency is 71 MHz. One scalar point multiplication takes 1,326,985 clock cycles resulting in the computation time of 18.7 msec at the maximum clock frequency.