• Progress in Medical Physics
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• v.29 no.4
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• pp.106-114
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• 2018

This study aimed to compare the performance of previous optimization algorithms against new a photon optimizer (PO) algorithm for intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) plans for prostate cancer. Eighteen patients with prostate cancer were retrospectively selected and planned to receive 78 Gy in 39 fractions of the planning target volume (PTV). All plans for each patient optimized with the dose volume optimizer (DVO) and progressive resolution optimizer (PRO) algorithms for IMRT and VMAT were compared against plans optimized with the PO within Eclipse version 13.7. No interactive action was performed during optimization. Dosimetric and radiobiological indices for the PTV and organs at risk were analyzed. The monitor units (MU) per plan were recorded. Based on the plan quality for the target coverage, prostate IMRT and VMAT plans using the PO showed an improvement over DVO and PRO. In addition, the PO generally showed improvement in the tumor control probability for the PTV and normal tissue control probability for the rectum. From a technical perspective, the PO generated IMRT treatment plans with fewer MUs than DVO, whereas it produced slightly more MUs in the VMAT plan, compared with PRO. The PO showed over potentiality of DVO and PRO whenever available, although it led to more MUs in VMAT than PRO. Therefore, the PO has become the preferred choice for planning prostate IMRT and VMAT at our institution.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.502-509
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• 2023

This study presents a satellite constellation method that achieves optimal revisit performance by utilizing genetic algorithm techniques. The Walker method is a global coverage concept, and there are limitations to target-centered constellation considering the strategic environment of the Korean Peninsula. To overcome these limitations, targets are set in major areas of interest in North Korea, orbit elements with optimal revisit performance for each target are searched, and based on this, the number of satellites optimized for each target is derived using a genetic algorithm. The results of this study demonstrate the performance of the optimized constellation by applying phasing rules to achieve the desired revisit performance.

• Radiation Oncology Journal
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• v.28 no.4
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• pp.238-248
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• 2010

Purpose: To compare the dose distributions between three-dimensional (3D) and four-dimensional (4D) radiation treatment plans calculated by Ray-tracing or the Monte Carlo algorithm, and to highlight the difference of dose calculation between two algorithms for lung heterogeneity correction in lung cancers. Materials and Methods: Prospectively gated 4D CTs in seven patients were obtained with a Brilliance CT64-Channel scanner along with a respiratory bellows gating device. After 4D treatment planning with the Ray Tracing algorithm in Multiplan 3.5.1, a CyberKnife stereotactic radiotherapy planning system, 3D Ray Tracing, 3D and 4D Monte Carlo dose calculations were performed under the same beam conditions (same number, directions, monitor units of beams). The 3D plan was performed in a primary CT image setting corresponding to middle phase expiration (50%). Relative dose coverage, D95 of gross tumor volume and planning target volume, maximum doses of tumor, and the spinal cord were compared for each plan, taking into consideration the tumor location. Results: According to the Monte Carlo calculations, mean tumor volume coverage of the 4D plans was 4.4% higher than the 3D plans when tumors were located in the lower lobes of the lung, but were 4.6% lower when tumors were located in the upper lobes of the lung. Similarly, the D95 of 4D plans was 4.8% higher than 3D plans when tumors were located in the lower lobes of lung, but was 1.7% lower when tumors were located in the upper lobes of lung. This tendency was also observed at the maximum dose of the spinal cord. Lastly, a 30% reduction in the PTV volume coverage was observed for the Monte Carlo calculation compared with the Ray-tracing calculation. Conclusion: 3D and 4D robotic radiotherapy treatment plans for lung cancers were compared according to a dosimetric viewpoint for a tumor and the spinal cord. The difference of tumor dose distributions between 3D and 4D treatment plans was only significant when large tumor movement and deformation was suspected. Therefore, 4D treatment planning is only necessary for large tumor motion and deformation. However, a Monte Carlo calculation is always necessary, independent of tumor motion in the lung.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.653-662
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• 2016

This paper describes a test case generation algorithm for Simulink/Stateflow models based on the Rapidly exploring Random Tree (RRT) algorithm that has been successfully applied to path finding. An important factor influencing the performance of the RRT algorithm is the metric used for calculating the distance between the nodes in the RRT space. Since a test case for a Simulink/Stateflow (SL/SF) model is an input sequence to check a specific condition (called a test target in this paper) at a specific status of the model, it is necessary to drive the model to the status before checking the condition. A status maps to a node of the RRT. It is usually necessary to check various conditions at a specific status. For example, when the specific status represents an SL/SF model state from which multiple transitions are made, we must check multiple conditions to measure the transition coverage. We propose a unique distance calculation metric, based on the observation that the test targets are gathered around some specific status such as an SL/SF state, named key nodes in this paper. The proposed metric increases the probability that an RRT is extended from key nodes by imposing penalties to non-key nodes. A test case generation algorithm utilizing the proposed metric is proposed. Three models of Electrical Control Units (ECUs) embedded in a commercial vehicle are used for the performance evaluation. The performances are evaluated in terms of penalties and compared with those of the algorithm using a typical RRT algorithm.

• The KIPS Transactions:PartA
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• v.13A no.4 s.101
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• pp.335-342
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• 2006

As PRC linear interpolation algorithm is applied after analysed and verified in this paper, the unknown location of a user can be identified by using PRC information of multi-DGPS reference station. The PRC information of each GPS satellite is not varying rapidly, which makes it possible to assume that PRC information of each GPS satellite varies linearly. So, the PRC regeneration algorithm with linear interpolation can be applied to improve the accuracy of finding a user's location by using the various PRC information obtained from multi-DGPS reference station. The desirable PRC is made by the linear combination with the known position of multi-DGPS reference station and PRC values of a satellite using signals from multi-DGPS reference station. The RTK-GPS result was used as the reference. To test the performance of the linearly interpolated PRC regeneration algorithm, multi-channel DGPS beacon receiver was built to get a user's position more exactly by using PRC data of maritime DGPS reference station in RTCM format. At the end of this paper, the result of the quantitative analysis of the developed navigation algorithm performance is presented.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.11
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• pp.393-402
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• 2014

We have experienced an explosive increase of the IoT(Internet of Things) technology based devices including smart phones and the wireless communications. Also the growing power consumption in IEEE 802.11 WLANs(Wireless LANs) driven by these dramatic increases in not only mobile users and but also wireless APs(Access Points). To reduce the power consumption, this paper proposes a wireless AP power saving algorithm, which minimizes the transmission power without decrease the transmission and carrier sense ranges. A wireless AP which is use in our algorithm checks its own original coverage periodically for whether there is a new STA(Station) or not when its transmission power is decreased. Moreover, if there are no signaling message to connect the wireless AP, it changes its operation mode Wake-up to sleep. A Result shows that the proposed AP algorithm can reduce the total power consumption of the wireless AP approximated 18% and 35% compared to the conventional wireless AP with and without the existing power saving algorithm, respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.12
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• pp.79-90
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• 2005

In this paper, we propose a new clustered reconfigurable interconnect network (CRIN) BIST to improve the embedding probabilities of random-pattern-resistant-patterns. The proposed method uses a scan-cell reordering technique based on the signal probabilities of given test cubes and specific hardware blocks that increases the embedding probabilities of care bit clustered scan chain test cubes. We have developed a simulated annealing based algorithm that maximizes the embedding probabilities of scan chain test cubes to reorder scan cells, and an iterative algorithm for synthesizing the CRIN hardware. Experimental results demonstrate that the proposed CRIN BIST technique achieves complete fault coverage with lower storage requirement and shorter testing time in comparison with the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.548-556
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• 2014

To cope with recently increasing demand for data traffics, heterogeneous networks have been actively studied, where small cells are deployed within a macro cell coverage with the same frequency band. To mitigate the interference from the macro cell to small cells, an enhanced Inter-cell Interference Coordination (eICIC) technique has been proposed, where ABS (Almost Blank Subframe) is used in time domain. However, there is a waste of resource since no data is transmitted in a macro-cell in ABS. In this paper, we propose a new interference management method by using a 3D sector beam based on Active Antenna System (AAS), where Genetic Algorithm (GA) is applied to reduce the antenna gain toward a small-cell. With the proposed scheme, the macro-cell and small cells can transmit data at the same time with the AAS antenna pattern generating reduced interference to small cells. The performance of the proposed scheme is evaluated by using an LTE-Advanced system level simulator.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.114-121
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• 2013

As the weight of embedded memory within Systems-On-Chips(SoC) rapidly increases to 80-90% of the number of total transistors, the importance of testing embedded memory in SoC increases. This paper proposes IEEE std. 1500 wrapper based Programmable Memory Built-In Self-Test(PMBIST) architecture which can support various kinds of test algorithm. The proposed PMBIST guarantees high flexibility, programmability and fault coverage using not only March algorithms but also non-March algorithms such as Walking and Galloping. The PMBIST has an optimal hardware overhead by an optimum program instruction set and a smaller program memory. Furthermore, the proposed fault information processing scheme guarantees improvement of the memory yield by effectively supporting three types of the diagnostic methods for repair and diagnosis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.709-730
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• 2017

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.