• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.5
• /
• pp.544-549
• /
• 2006

This research is to introduce about Judgment System for Intelligent Movement(JSIM) that can perform assistance work of human brain. JSIM can order autonomous command and also it can be directly controlled by user. This research assumes that control object is limited to Mobile Robot(MR) Mobile robot offers image and ultrasonic sensor information to user carrying JSIM and it performs guide to user. JSIM having PDA and Sensor-box controls velocity and direction of the mobile robot by soft-computing method that inputs user's command and information that is obtained to mobile robot. Also it controls mobile robot to achieve various movement. This paper introduces wearable JSIM that communicates with around devices and that can do intelligent judgment. To verify the possibility of the proposed system, in real environment, the simulation of control and application problem lot mobile robot will be introduced. Intelligent algorithm in the proposed system is generated by mixed hierarchical fuzzy and neural network.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.4
• /
• pp.9-21
• /
• 2018

In South Korea, Jeju Island has a role as a test bed for electric vehicles (EVs). All conventional cars on the island are supposed to be replaced with EVs by 2030. Accordingly, how to effectively set up EV charging stations (EVCSs) that can charge EVs is an urgent research issue. In this paper, we present a case study on planning the locations of EVCS for Jeju Island, South Korea. The objective is to determine where EVCSs to be installed so as to balance the load of EVCSs while satisfying demands. For a public service with EVCSs by some government or non-profit organization, load balancing between EVCS locations may be one of major measures to evaluate or publicize the associated service network. Nevertheless, this measure has not been receiving much attention in the related literature. Thus, we consider the measure as a constraint and an objective in a mixed integer programming model. The model also considers the maximum allowed distance that drivers would detour to recharge their EV instead of using the shortest path to their destination. To solve the problem effectively, we develop a heuristic algorithm. With the proposed heuristic algorithm, a variety of numerical analysis is conducted to identify effects of the maximum allowed detour distance and the tightness of budget for installing EVCSs. From the analysis, we discuss the effects and draw practical implications.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.7
• /
• pp.2496-2512
• /
• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• Korean Journal of Metals and Materials
• /
• v.46 no.5
• /
• pp.289-295
• /
• 2008

The effect of the alloy elements(Si/Mn) ratio on the coating quality including wettabilty with molten zinc, galvannealing kinetics and crater has been investigated in interstitial-free high strength steel(IFHSS) containing Si and Mn. When the Si/Mn ratio was below 0.75, IF-HSS exhibited a good wettability leading to a good galvannealed coating quality after annealing at $800^{\circ}C$ for 40s in $15%H_2-N_2$ mixed gas with dew point $-60^{\circ}C$. In contrast, the wettability and galvannealed coating quality were deteriorated in the Si/ Mn ratio above 0.75. It is shown that they have relevance to oxides forms by selective oxidation on the steel surface. The oxide particles dispersed on the steel surface with a surface coverage of below 40% resulted in good wettability and galvannealed coating quality. The oxide particle is mainly consisted of $Mn_2SiO_4$ with low contact angle in molten zinc. On the other hand, the continuous oxide layer on the steel surface, such as network- and film-type,caused to poor wettability and galvannealed coating quality. The coverage of oxide layer was above 80%, and its chemical species was $SiO_2$ with high contact angle in molten zinc. Consequently, the Si/Mn alloy ratio played an importance role in galvannealed coating quality of IF-HSS.

• Korean Journal of Metals and Materials
• /
• v.46 no.7
• /
• pp.427-436
• /
• 2008

The effect of dewpoints on annealing behavior and coating characteristics such as wettability and galvannealing kinetics was studied by annealing 0.3wt%Si - 0.1~0.4wt% Mn added interstitial-free high strength steels(IF-HSS). The 0.3wt%Si-0.1wt%Mn steel exhibited good wettability with molten zinc and galvannealing kinetics after annealing when the dewpoint of $H_2-N_2$ mixed gas was above $-20^{\circ}C$. It is shown that the wettability and galvannealing kinetics are directly related to the coverage of the external(surface) oxide formed by selective oxidation during annealing. At $N_2-15%H_2$ annealing atmosphere, the increase of dewpoint results in a gradual transition from external to internal selective oxidation. The decrease of external oxidation of alloying elements with a concurrent increase of their subsurface enrichment in the substrate, showing a larger surface area that was free of oxide particles, contributed to the improved wettability and galvannealing kinetics. On the other hand, the corresponding wettability and galvannealing kinetics were deteriorated with the dewpoints below $-20^{\circ}C$. The continuous oxide layer of network and/or film type was formed on the steel surface, leading to the poor wettability and galvannealing kinetics. It causes a high contact angle between annealed surface and molten zinc and plays an interrupting role in interdiffusion of Zn and Fe during galvannealing process.

• Convergence Security Journal
• /
• v.20 no.4
• /
• pp.71-80
• /
• 2020

In order to provide realistic traffic to the cyber warfare training system, it is necessary to prepare a traffic distribution plan in advance and to create a training data set using normal/threat data sets. This paper presents the design and implementation results of a method for creating a traffic distribution plan and a training data set to provide background traffic like a real environment to a cyber warfare training system. We propose a method of a traffic distribution plan by using the network topology of the training environment to distribute traffic and the traffic attribute information collected in real and simulated environments. We propose a method of generating a training data set according to a traffic distribution plan using a unit traffic and a mixed traffic method using the ratio of the protocol. Using the implemented tool, a traffic distribution plan was created, and the training data set creation result according to the distribution plan was confirmed.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.3
• /
• pp.571-576
• /
• 2021

This study was carried out to overcome the problems of the existing fitness business and to build a fitness system that can meet the increased demand in the Corona situation. As a platform technology for non-face-to-face fitness edutainment service, it is a next-generation fitness exercise device that can use various body parts and synchronize network-type information. By synchronizing the exercise information of the fitness equipment, it was composed of learning contents through MR-based avatars. A quantified result was derived from examining the applicability of the customized evaluation system through momentum analysis with A.I analysis applying the LSTM-based algorithm according to the cumulative exercise effect of the user. It is a motion capture and 3D visualization fitness program for the application of systematic exercise techniques through academic experts, and it is judged that it will contribute to the improvement of the user's fitness knowledge and exercise ability.

• Journal of Convergence for Information Technology
• /
• v.12 no.1
• /
• pp.31-38
• /
• 2022

This paper applies an expert independent unsupervised neural network learning-based multivariate time series data analysis model, MSCRED(Multi-Scale Convolutional Recurrent Encoder-Decoder), and to overcome the limitation, because the MCRED is based on Auto-encoder model, that train data must not to be contaminated, by using learning data sampling technique, called Subset Sampling Validation. By using the vibration data of power plant equipment that has been labeled, the classification performance of MSCRED is evaluated with the Anomaly Score in many cases, 1) the abnormal data is mixed with the training data 2) when the abnormal data is removed from the training data in case 1. Through this, this paper presents an expert-independent anomaly diagnosis framework that is strong against error data, and presents a concise and accurate solution in various fields of multivariate time series data.

• Molecules and Cells
• /
• v.45 no.4
• /
• pp.202-215
• /
• 2022

The androgen receptor (AR) is an important therapeutic target for treating prostate cancer (PCa). Moreover, there is an increasing need for understanding the AR-independent progression of tumor cells such as neuroendocrine prostate cancer (NEPC). Menin, which is encoded by multiple endocrine neoplasia type 1 (MEN1), serves as a direct link between AR and the mixed-lineage leukemia (MLL) complex in PCa development by activating AR target genes through histone H3 lysine 4 methylation. Although menin is a critical component of AR signaling, its tumorigenic role in AR-independent PCa cells remains unknown. Here, we compared the role of menin in AR-positive and AR-negative PCa cells via RNAi-mediated or pharmacological inhibition of menin. We demonstrated that menin was involved in tumor cell growth and metastasis in PCa cells with low or deficient levels of AR. The inhibition of menin significantly diminished the growth of PCa cells and induced apoptosis, regardless of the presence of AR. Additionally, transcriptome analysis showed that the expression of many metastasis-associated genes was perturbed by menin inhibition in AR-negative DU145 cells. Furthermore, wound-healing assay results showed that menin promoted cell migration in AR-independent cellular contexts. Overall, these findings suggest a critical function of menin in tumorigenesis and provide a rationale for drug development against menin toward targeting high-risk metastatic PCa, especially those independent of AR.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.9
• /
• pp.9-15
• /
• 2023

Metaverse is a modern new technology that is advancing quickly. The goal of this study is to investigate this technique from the perspective of computer vision as well as general perspective. A thorough analysis of computer vision related Metaverse topics has been done in this study. Its history, method, architecture, benefits, and drawbacks are all covered. The Metaverse's future and the steps that must be taken to adapt to this technology are described. The concepts of Mixed Reality (MR), Augmented Reality (AR), Extended Reality (XR) and Virtual Reality (VR) are briefly discussed. The role of computer vision and its application, advantages and disadvantages and the future research areas are discussed.