• Journal of Radiation Protection and Research
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• v.46 no.3
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• pp.143-150
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• 2021

Since its establishment in 2018, the Young Generation Network (YGN) has been dedicated, with support of the International Radiation Protection Association (IRPA), to a variety of activities to promote communication, collaboration and professional development of students and young professionals in the area of radiation protection and its allied fields. This article reports our recent activities from the middle of 2018 to the beginning of 2021, with highlights on some important events: "Joint JHPS-SRP-KARP Workshop of Young Generation Network" (December 2019 in Japan); contribution to "Nuclear Energy Agency Workshop on Optimization: Rethinking the Art of Reasonable" (January 2020 in Portugal); survey on the impact of coronavirus disease 2019 (COVID-19) on radiation protection among IRPA YGN members (March 2020); and contribution to IRPA15 (15^th International Congress of the IRPA; January-February 2021, online). The discussion and insight obtained from each activity are also summarized. The IRPA YGN will aim to achieve its on-going activities and continue to follow the ways paved in the Strategic Agenda and despite the challenges raised by the COVID-19 pandemic. Namely, running an international survey (for example, on the usage of social media in radiation protection, and on the long-term consequences of the COVID-19 pandemic), engaging national YGNs, extending the network, finding new relationships with networks with an interest in the young generation and participation in (remote) events will be aspired for.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.7-11
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• 2003

Nowadays, as digital technologies are rapidly developed and requirements for the various types of broadband multimedia services increases, the radio broadcasting is moving to digitalization. DAB(Digital Audio Broadcasting), as an alternation of existing analog radio broadcasting, is a new type of multimedia broadcasting system. DAB supports not only high-quality audio broadcasting but also various types of multimedia data services. In this paper, we investigate the performance optimization method of MOT Protocol, as the standard for additional services, to support the multimedia services in the DAB network. Because the performance of the MOT protocol is dependent on various parameters such as segment size, segment repetition and so on, we find those by simulation for performance optimization. According to simulation results, the suitable segment size is about 2Kbyte and segment repetition is 4 times for performance optimization.

• Journal of Advanced Navigation Technology
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• v.14 no.3
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• pp.358-366
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• 2010

In the wireless network the congestion and delay occurs mainly when there are too many packets for the network to process or the sender transmits more packets than the receiver can accept. The congestion and delay is the reason of packet loss which degrades the performance of multimedia streaming. This paper proposes a novel transmission rate monitoring-based optimization mechanism to optimize packet loss and to improve QoS. The proposed scheme is based on the trade-off relationship between transmission rate monitoring and overhead monitoring. For this purpose this paper processes a source rate control-based optimization which optimizes congestion and delay. Performance evaluated RED, TFRC, and the proposed mechanism. The simulation results show that the proposed mechanism is more efficient than REC(Random Early Detection) mechanism and TFRC(TCP-friendly Rate Control) mechanism in packet loss rate, throughput rate, and average response rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.89-96
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• 2016

In this paper, we study mobile data collector (MDC) based data-gathering schemes in wireless sensor networks. In Such networks, MDCs are used to collect data from the environment and transfer them to the sink. The majority of existing data-gathering schemes suffer from high data-gathering latency because they use only a single MDC. Although some schemes use multiple MDCs, they focus on maximizing network lifetime rather than minimizing packet delay. In order to address the limitations of existing schemes, this paper focuses on minimizing packet delay for given number of MDCs and minimizing the number of MDCs for a given delay bound of packets. To achieve the minimum packet delay and minimum number of MDCs, two optimization problems are formulated, and traveling distance and traveling time of MDCs are estimated. The interior-point algorithm is used to obtain the optimal solution for each optimization problem. Numerical results and analysis are presented to validate the proposed method.

• Journal of the Korea Concrete Institute
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• v.20 no.5
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• pp.627-634
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• 2008

This paper presents an optimum mixture design method for proportioning a concrete. In the proposed method, the search space is constrained as the domain defined by the minimal convex region of a database, instead of the available range of each component and the ratio composed of several components. The model for defining the search space which is expressed by the effective region is proposed. The effective region model evaluates whether a mix-proportion is effective on processing for optimization, yielding highly reliable results. Three concepts are adopted to realize the proposed methodology: A genetic algorithm for the optimization; an artificial neural network for predicting material properties; and a convex hull for evaluating the effective region. And then, it was applied to an optimization problem wherein the minimum cost should be obtained under a given strength requirement. Experimental test results show that the mix-proportion obtained from the proposed methodology using convex hulls is found to be more accurate and feasible than that obtained from a general optimum technique that does not consider this aspect.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1393-1400
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• 2006

This paper optimizes the access probabilities (APs) in a network resource allocation scheme based on access probabilities in order that the waiting time and the blocking probability are minimized under the given constraints, and obtains its performance. In order to optimize APs, an infinite number of balance equations is reduced to a finite number of balance equations by applying Neuts matrix geometric method. And the nonlinear programming problem is converted into a linear programming problem. As a numerical example, the performance measures of waiting time and blocking probability for optimal access probabilities and the maximum utilization under the given constraints are obtained. And it is shown that the scheme with optimal APs gives more performance build-up than the strategy without optimization.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.900-911
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• 2015

In this paper, 3D face recognition model is designed by using Polynomial based RBFNN(Radial Basis Function Neural Network) and PNN(Polynomial Neural Network). Also recognition rate is performed by this model. In existing 2D face recognition model, the degradation of recognition rate may occur in external environments such as face features using a brightness of the video. So 3D face recognition is performed by using 3D scanner for improving disadvantage of 2D face recognition. In the preprocessing part, obtained 3D face images for the variation of each pose are changed as front image by using pose compensation. The depth data of face image shape is extracted by using Multiple point signature. And whole area of face depth information is obtained by using the tip of a nose as a reference point. Parameter optimization is carried out with the aid of both ABC(Artificial Bee Colony) and PSO(Particle Swarm Optimization) for effective training and recognition. Experimental data for face recognition is built up by the face images of students and researchers in IC&CI Lab of Suwon University. By using the images of 3D face extracted in IC&CI Lab. the performance of 3D face recognition is evaluated and compared according to two types of models as well as point signature method based on two kinds of depth data information.

• Journal of IKEEE
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• v.23 no.4
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• pp.1314-1320
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• 2019

In this paper, we propose a new method for optimizing bit operations and applying them to DNN(Deep Neural Network) in software environment. As a method for this, we propose a packing function for bitwise optimization and a masking matrix multiplication operation for application to DNN. The packing function converts 32-bit real value to 2-bit quantization value through threshold comparison operation. When this sequence is over, four 32-bit real values are changed to one 8-bit value. The masking matrix multiplication operation consists of a special operation for multiplying the packed weight value with the normal input value. And each operation was then processed in parallel using a GPU accelerator. As a result of this experiment, memory saved about 16 times than 32-bit DNN Model. Nevertheless, the accuracy was within 1%, similar to the 32-bit model.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.3
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• pp.61-67
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• 2008

Proxy MIPv6 (PMIPv6) is that network-based mobility management protocol that network supports mobile node's mobility on behalf of the MN. In PMIPv6, when two MNs located within the same PMIPv6 domain want to communicate each other, sub-optimal path is established between the two MN. Route optimization method for PMIPv6 is proposed to resolve the problem. However, the method still suffer from the performance degradation due to out-of-sequence packet problem. In this paper, we propose the route optimization mechanism in PMIPv6 based on Flush message to resolve the out-of-sequence packet problem. The proposed mechanism is evaluated by performing simulations, and the simulation results show that the proposed one gives better performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1208-1222
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• 2014

Due to the low utilization and scarcity of frequency spectrum in current spectrum allocation methodology, cognitive radio networks (CRNs) have been proposed as a promising method to solve the problem, of which spectrum sensing is an important technology to utilize the precious spectrum resources. In order to protect the primary user from being interfered, most of the related works focus only on the restriction of the missed detection probability, which may causes over-protection of the primary user. Thus the interference probability is defined and the interference-aware sensing model is introduced in this paper. The interference-aware sensing model takes the spatial conditions into consideration, and can further improve the network performance with good spectrum reuse opportunity. Meanwhile, as so many fading factors affect the spectrum channel, errors are inevitably exist in the reporting channel in cooperative sensing, which is improper to be ignored. Motivated by the above, in this paper, we study the throughput tradeoff for interference-aware cognitive radio networks over imperfect reporting channel. For the cooperative spectrum sensing, the K-out-of-N fusion rule is used. By jointly optimizing the sensing time and the parameter K value, the maximum throughput can be achieved. Theoretical analysis is given to prove the feasibility of the optimization and computer simulations also shows that the maximum throughput can be achieved when the sensing time and the parameter of K value are both optimized.