• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.45-53
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• 2015

Adaptive support-weight based algorithm can produce better disparity map compared to generic area-based algorithms and also can be implemented as a realtime system. In this paper, we propose a realtime system based on geodesic support-weight which performs better segmentation of objects in the window. The data scheduling is analyzed for efficient hardware design and better performance and the parallel architecture for weight update which takes the longest delay is proposed. The exponential function is efficiently designed using a simple step function by careful error analysis. The proposed architecture is designed with verilogHDL and synthesized using Donbu Hitek 0.18um standard cell library. The proposed system shows 2.22% of error rate and can run up to 260Mhz (25fps) operation frequency with 182K gates.

• Archives of Plastic Surgery
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• v.42 no.5
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• pp.532-543
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• 2015

Capsular contracture is the most common complication following implant based breast surgery and is one of the most common reasons for reoperation. Therefore, it is important to try and understand why this happens, and what can be done to reduce its incidence. A literature search using the MEDLINE database was conducted including search terms 'capsular contracture breast augmentation', 'capsular contracture pathogenesis', 'capsular contracture incidence', and 'capsular contracture management', which yielded 82 results which met inclusion criteria. Capsular contracture is caused by an excessive fibrotic reaction to a foreign body (the implant) and has an overall incidence of 10.6%. Risk factors that were identified included the use of smooth (vs. textured) implants, a subglandular (vs. submuscular) placement, use of a silicone (vs. saline) filled implant and previous radiotherapy to the breast. The standard management of capsular contracture is surgical via a capsulectomy or capsulotomy. Medical treatment using the off-label leukotriene receptor antagonist Zafirlukast has been reported to reduce severity and help prevent capsular contracture from forming, as has the use of acellular dermal matrices, botox and neopocket formation. However, nearly all therapeutic approaches are associated with a significant rate of recurrence. Capsular contracture is a multifactorial fibrotic process the precise cause of which is still unknown. The incidence of contracture developing is lower with the use of textured implants, submuscular placement and the use of polyurethane coated implants. Symptomatic capsular contracture is usually managed surgically, however recent research has focussed on preventing capsular contracture from occurring, or treating it with autologous fat transfer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.330-335
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• 2002

In the direct sequence code division multiple access system, the problem of multiple access interference due to multiple access is generated. A interference cancelling receiver is used to solve this problem. The conventional interference cancelling receiver is structure of successive interference canceller using antenna array. In this structure, the difference of between method I and method II depends on updating weight vector. In this paper, the adaptive blind CMA array interference cancelling receiver using cost function of constant modulus algorithms is proposed to update weight vector at conventional structure. The simulation compared the proposed interference cancelling receiver with two conventional interference cancelling receivers by signal to interference ratio and bit error rate curve under additive white Gaussian noise environment. The simulation results show that the proposed receiver has about the gain of SIR of 1.5[dB] more than method I which is conventional receiver at SIR curve, and about the gain of SIR of 0.5(dB) more than method II. In BER curve, the proposed IC receiver about the gain of SNR of 2[dB] more than method I and about the gain of SNR of 0.5[dB] more than method If, Thus, the proposed interference cancelling receiver has the higher performance than conventional interference cancelling receivers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5248-5255
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• 2014

Because of the rapid growth of smart phone market, the number of mobile applications has increased exponentially. As mobile applications are developing at a rapid rate, many of them are being developed without considering a systematic development process or quality factors, such as reusability, extensibility, etc.. As a result, they have many faults internally, they are being underrated in satisfaction or reliability from customers, and finally customers do not update or repeat the purchase. Therefore, a meta-model of development process for mobile applications was designed to improve the continuous usability of mobile applications as well as the satisfaction and reliability from users. Applying development process based on a meta-model to mobile application development is expected to improve development productivity and quality of mobile applications.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.42-46
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• 2018

Adaptive signal processing is quite important in various signal and communication environments. In adaptive signal processing methods since the least mean square(LMS) algorithm is simple and robust, it is used everywhere. As the step is varied in the variable step(VS) LMS algorithm, the fast convergence speed and the small excess mean square error can be obtained. Various variable step LMS algorithms are researched for better performances. But in some of variable step LMS algorithms the computational complexity is quite large for better performances. The fixed step LMS algorithm with a low computational complexity merit and the variable step LMS algorithm with a fast convergence merit are combined in the proposed sporadic step algorithm. As the step is sporadically updated, the performances of the variable step LMS algorithm can be maintained in the low update rate using Fibonacci sequence. The performances of the proposed variable step LMS algorithm are proved in the adaptive equalizer.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.37 no.2
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• pp.97-108
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• 2011

Cancer stem cells have stem cell-like features, such as the ability for self-renewal and differentiation but show unlimited growth because they have the lost normal regulation of cell growth. Cancer stem cells and normal stem cells have similar features. They show high motility, diversity of progeny, robust proliferative potential, association with blood vessels, immature expression profiles, nestin expression, epidermal growth factor (EGF)-receptor expression, phosphatase and tensin homolog (PTEN) expression, hedgehog pathway activity, telomerase activity, and Wnt pathway activity. On the other hand, with cancer cells, some of these signaling pathways are abnormally modified. In 1875, Cohnheim suggested the concept of cancer stem cells. Recently, evidence for the existence of cancer stem cells was identified. In 1994, the cancer stem cells' specific cell surface marker for leukemia was identified. Since then, other specific cell surface markers for cancer stem cells in solid tumors (e.g. breast and colon cancer) have been identified. In oral cancer, studies on cancer stem cells have been performed mainly with squamous cell carcinomas. Oral cancer specific cell surface markers, which are genes strongly expressed in oral cancer and cancer stem cell specific side populations, have been identified. Cancer stem cells are resistant to radiotherapy and chemotherapy. Therefore, to eliminate malignant tumors efficiently and reduce the recurrence rate, therapy targeting cancer stem cells needs to be performed. Currently, studies targeting the cancer stem cells' specific signaling pathways, telomerase and tumor vasculatures are being done.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1958-1968
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• 2015

Things intelligence communication (M2M or IoT) service activation and global company of OneM2M-related business on aggressive investing and has led to the acceleration of change in the ICT market. But a variety of hacking security technology because of the possibility of secure communication (data exposure, theft, modification, deletion, etc.) has been issued as an important requirement. In this paper, we propose a mutual authentication protocol for secure communications chameleon hash based on the M2M environment. The results of performance analysis efficiency is encryption and decryption an average of 0.7%, calculated rate showed good results as compared to the target algorithm, equivalent to a 3%(Average 0.003 seconds) difference, mutual authentication and encryption region by using the key update advantage of ECC(Elliptic Curve Cryptography)based Chameleon hash function is signed of the operational efficiency, using a collision message verifiable properties demonstrated strong security of the communication section.

• The KIPS Transactions:PartC
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• v.16C no.1
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• pp.13-20
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• 2009

Recently, as traffic flooding attacks such as DoS/DDoS and Internet Worm have posed devastating threats to network services, rapid detection and proper response mechanisms are the major concern for secure and reliable network services. However, most of the current Intrusion Detection Systems (IDSs) focus on detail analysis of packet data, which results in late detection and a high system burden to cope with high-speed network traffic. In this paper we propose an SNMP-based lightweight and fast detection algorithm for traffic flooding attacks, which minimizes the processing and network overhead of the detection system, minimizes the detection time, and provides high detection rate. The attack detection algorithm consists of three consecutive stages. The first stage determines the detection timing using the update interval of SNMP MIB. The second stage analyzes attack symptoms based on correlations of MIB data. The third stage determines whether an attack occurs or not and figure out the attack type in case of attack.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.98-107
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• 2011

In this paper, we propose the location determination system of an agent mobile device using the information provided by the WLAN(Wireless LAN) infrastructure. This system is configured as a typical ESS(Extended Service Set)-type WLAN structure with real-time location positioning engine and thru AP(Access Point) controller. The positioning engine collects the information of agent devices using SNMP(Small Network Management Protocol) thru AP controller and utilize those information as Cell ID. for LBS(Location Based Service). In the result of a real office environment implementation, the average success rate of inter-AP roaming is measured to 62.5% and the duration time of the device information update within the AP is average of 11 second of time, which means this system is adaptable to the location based service of above average accuracy but somewhat less urgency.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.