• Journal of Digital Convergence
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• v.19 no.8
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• pp.219-224
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• 2021

The convergence of various industries has removed the boundaries of software application fields and reduced the restrictions on convergence fields. Software requirements are diversified and they want to reconfigure software requirements in a fast cycle. Since various changes in requirements have to be accepted technically, research on methodologies and standards to increase the efficiency of software productivity and methods for standardizing and producing software are needed. In this study, we studied how the reusability and complexity of the software asset reconfiguration system appeared according to the developer's characteristics and environment to utilize the assets optimized in previous studies. At this time, we measured how the change in complexity according to the usability and asset composition method that appears according to the developer's characteristics appears, but there is a limit to the collected data, so it is necessary to secure the quality of the measured value through continuous data collection. In addition, an intelligent system application plan is needed to supplement the problem of context classification in the use stage of complex assets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.117-124
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• 2021

This study is a study to recognize hand movements using a neural network for wrist rehabilitation. The rehabilitation of the hand aims to restore the function of the injured hand to the maximum and enable daily life, occupation, and hobby. It is common for a physical therapist, an occupational therapist, and a security tool maker to form a team and approach a doctor for a hand rehabilitation. However, it is very inefficient economically and temporally to find a place for treatment. In order to solve this problem, in this study, patients directly use smart devices to perform rehabilitation treatment. Using this will be very helpful in terms of cost and time. In this study, a wrist rehabilitation dataset was created by collecting data on 4 types of rehabilitation exercises from 10 persons. Hand gesture recognition was constructed using a neural network. As a result, the accuracy of 93% was obtained, and the usefulness of this system was verified.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1022-1029
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• 2020

We investigate the joint selection problem of the transmit power level and the best access point for multi-access points. We further reduce the transmit power by jointly optimizing the transmit power and the access point selection. Our aim is to minimize the total transmit power, while each terminal maintains minimum signal to interference ratio requirement. We observe that the optimum solution can be achieved through proposed iterative algorithm for both TA link and AT link. Simulation results show that proposed algorithm (joint optimization of transmit power level and access point) outperforms the algorithm which optimizes the transmit power only. We also observe that the duality between the TA link and AT link does not hold in multi-access points environment. Accordingly, the resulting power vectors and the access point vectors for TA link and AT link are different in general.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.50-56
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• 2020

With the rapid development of deep neural network theory and application research, the effect of face detection has been improved. However, due to the complexity of deep neural network calculation and the high complexity of the detection environment, how to detect face quickly and accurately becomes the main problem. This paper is based on the relatively simple model of the MTCNN model, using FDDB (Face Detection Dataset and Benchmark Homepage), LFW (Field Label Face) and FaceScrub public datasets as training samples. At the same time of sorting out and introducing MTCNN(Multi-Task Cascaded Convolutional Neural Network) model, it explores how to improve training speed and Increase performance at the same time. In this paper, the dynamic image pyramid technology is used to replace the traditional image pyramid technology to segment samples, and OHEM (the online hard example mine) function in MTCNN model is deleted in training, so as to improve the training speed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.5
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• pp.27-35
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• 2002

In this paper, we present the structure and interaction flow between IKE server and the other modules for our IPsec System's efficiency. Our IPsec systems have several components for IP-based end-to-end security services. They are IKE, SADB and SPDB and so on, not to speak of IPsec Protocol Engine. Therefore the efficient interaction structure between them has an much influence on total system efficiency. Especially, in case of IPsec engine integrated with kernel, it is very important how IPsec engine can refer to SPDB and SADB entries efficiently according to the location of the implementation of SPDB and SADB. To solve the above problem, we use the SPI generated by IKE. Finally, we propose the interaction structure between IKE server and the other modules according to the optimization for referring to SPDB and SADB entries.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.2
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• pp.53-58
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• 2021

In this paper, an alternative finite memory structure(FMS) smoothing filter is developed for discrete-time state-space model with a control input. To obtain the FMS smoothing filter, unbiasedness will be required beforehand in addition to a performance criteria of minimum variance. The FMS smoothing filter is obtained by directly solving an optimization problem with the unbiasedness constraint using only finite measurements and inputs on the most recent window. The proposed FMS smoothing filter is shown to have intrinsic good properties such as deadbeat and time-invariance. In addition, the proposed FMS smoothing filter is shown to be equivalent to existing FMS filters according to the delay length between the measurement and the availability of its estimate. Finally, to verify intrinsic robustness of the proposed FMS smoothing filter, computer simulations are performed for a temporary model uncertainty. Simulation results show that the proposed FMS smoothing filter can be better than the standard FMS filter and Kalman filter.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.211-216
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• 2021

Multiple UAV System has been used for various purposes such as reconnaissance, networking and aerial photography. In such systems, it is essential to form and maintain the formation of multiple UAVs. This paper proposes the algorithm that produces an autonomous distributed control for each vehicle for a flexible formation. This command is a repulsive force in the form of the second-order system by the nearest UAV or mission area. The algorithm uses the relative position/speed through sensing and communication for calculating the command without external intervention. The command allows each UAV to follow the reference distance and fill the mission area as densely as possible without overlapping. We determine the reference distance via optimization technique solving the packing problem. The mission area comprises the desired formation outline and can be set flexibly depending on the mission. Numerical simulation is carried out to verify the performance of the proposed algorithm under a complex and flexible environment. The formation is formed in 26.94 seconds and has a packing density of 71.91%.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.233-238
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• 2021

Recently, blockchain technology accumulates and stores all transactions. Therefore, in order to verify the contents of all transactions, the data itself is compressed, but the scalability is limited. In addition, since a separate verification algorithm is used for each type of transaction, the verification burden increases as the size of the transaction increases. Existing blockchain cannot participate in the network because it does not become a block sink by using a server with a low specification. Due to this problem, as the time passes, the data size of the blockchain network becomes larger and it becomes impossible to participate in the network except for users with abundant resources. Therefore, in this paper, we are improved transaction as studied the zero knowledge proof algorithm for general operation verification. In this system, the design of zero-knowledge circuit generator capable of general operation verification and optimization of verifier and prover were also conducted.

• The Journal of Korean Institute of Information Technology
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• v.17 no.10
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• pp.49-55
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• 2019

In this paper, we propose a simple precoding vector design scheme for multi-user multiple-input single-output (MISO) interference channel when there are multiple eavesdroppers. We aim to obtain a mathematical closed-form solution of the secrecy rate optimization problem. For this goal, we design the precoding vector based on the signal-to-leakage plus noise ratio (SLNR). More specifically, the proposed precoding vector is designed to completely eliminate a wiretap channel capacity for refraining the eavesdroppers from detecting the transmitted information, and to maximize the transmitter-receiver link achievable rate. We performed simulation for the performance investigation. Simulation results show that the proposed scheme has better secrecy rate than the conventional scheme over all signal-to-noise ratio (SNR) range even though the special condition among the numbers of transmit antennas, transmitter-receiver links, and eavesdroppers is not satisfied.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.58-65
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• 2021

Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.