• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.377-383
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• 2021

Recently, in accordance with the 4th industrial revolution, The use of autonomous mobile robots for flexible logistics transfer is increasing in factories, the warehouses and the service areas, etc. In large factories, many manual work is required to use Simultaneous Localization and Mapping(SLAM), so the need for the improved mobile robot autonomous driving is emerging. Accordingly, in this paper, an algorithm for mapless navigation that travels in an optimal path avoiding fixed or moving obstacles is proposed. For mapless navigation, the robot is trained to avoid fixed or moving obstacles through Deep Q Network (DQN) and accuracy 90% and 93% are obtained for two types of obstacle avoidance, respectively. In addition, DQN requires a lot of learning time to meet the required performance before use. To shorten this, the target size change algorithm is proposed and confirmed the reduced learning time and performance of obstacle avoidance through simulation.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.430-435
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• 2022

In this paper, we consider the non-orthogonal multiple access (NOMA) technique in the heterogeneous network (HetNET) consisting of a single macro base station (BS) and multiple small BSs, where the perfect successive interference cancellation is assumed for the NOMA signals. In this paper, we propose a deep learning-based user association and power allocation scheme to maximize the data rate in the NOMA-based HetNET. In particular, the proposed scheme includes the deep neural network (DNN)-based user association process for load balancing and the DNN-based power allocation process for data-rate maximization. Through the simulation assuming path loss and Rayleigh fading channels between BSs and users, the performance of the proposed scheme is evaluated, and it is compared with the conventional maximum signal-to-interference-plus-noise ratio (Max-SINR) scheme. Through the performance comparison, we show that the proposed scheme provides better sum rate performance than the conventional Max-SINR scheme.

• Journal of Electrochemical Science and Technology
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• v.12 no.4
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• pp.458-464
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• 2021

Lithium ion batteries (LIBs) is a kind of rechargeable secondary battery, developed from lithium battery, lithium ions move between the positive and negative electrodes to realize the charging and discharging of external circuits. Zeolitic imidazolate frameworks (ZIFs) are porous crystalline materials in which organic imidazole esters are cross-linked to transition metals to form a framework structure. In this article, ZIF-67 is used as a sacrificial template to prepare nano porous carbon (NPC) coated cobalt nanoparticles. The final product Co/NPC composites with complete structure, regular morphology and uniform size were obtained by this method. The conductive network of cobalt and nitrogen doped carbon can shorten the lithium ion transport path and present high conductivity. In addition, amorphous carbon has more pores that can be fully in contact with the electrolyte during charging and discharging. At the same time, it also reduces the volume expansion during the cycle and slows down the rate of capacity attenuation caused by structure collapse. Co/NPC composites first discharge specific capacity up to 3115 mA h/g, under the current density of 200 mA/g, circular 200 reversible capacity as high as 751.1 mA h/g, and the excellent rate and resistance performance. The experimental results show that the Co/NPC composite material improves the electrical conductivity and electrochemical properties of the electrode. The cobalt based ZIF-67 as the precursor has opened the way for the design of highly performance electrodes for energy storage and electrochemical catalysis.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.463-476
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• 2021

This study examined significant differences in the impact of workplace bullying on emotional depletion and organizational commitment, and used 400 questionnaires to examine whether there would be significant differences depending on social support. As an analysis method, we used SPSS 24 for sample characteristics, SmartPLS 3 statistical programs for verifiable factor analysis, reliability and validity, path analysis, and structural equation models. Studies have shown that bullying in the workplace affects significant positive (+) for emotional depletion, and that emotional depletion affects significant negative (-) for tissue commitment. The influence relationship between workplace bullying and tissue commitment was partially mediated in the direction of wealth (-), and the effect of emotional depletion on tissue immersion was shown to be significant differences in the control of social support. Implications are that bullying in the workplace affects emotional depletion, so corporate efforts to prevent bullying are urgently needed, suggesting that employees can improve their organizational commitment, by using a system or community that can promote communication with their bosses.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.261-268
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• 2022

Recently, the number of elderly living alone suffering from loneliness and depression is also increasing significantly due to the rapid aging of the population and nuclear families. In this paper, we propose a smart aging system that increases life satisfaction by providing the elderly with the optimal service tailored to the elderly with the help of IT according to their residential environment and health status. It is possible to provide an advanced customized support system for the elderly by fully utilizing IoT, AI, and Metaverse techniques not only for the elderly who want to live an active life in society but also for the elderly who need care in a nursing hospital. The proposed system provides human satisfaction by providing social connection in real space and virtual space in accordance with the residential environment and health status to the elderly suffering from loneliness in hospital (hospital care) facilities and at home. This paper proposes a new path for future-oriented welfare policy for the elderly by providing a user-customized smart aging system by combining AI and Metaverse technology with a rapidly changing social environment.

• Fashion & Textile Research Journal
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• v.24 no.1
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• pp.29-41
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• 2022

With the outbreak of the COVID-19 pandemic, global fashion brands have been hosting online fashion shows instead of offline ones. In light of the current pandemic scenario, this research conducted a study on digital fashion shows held online, specifically focusing on two types of shows: fashion films and games. This study examined the characteristics of changes in digital fashion shows as well as their limitations. The case studies analyzed fashion shows from January 2020 to July 2021, with a focus on the 2021 S/S and 2021 F/W seasons, and 26 fashion shows from 23 brands. The results of this study were as follows: First, digital fashion shows transcended physical limitations through virtualization and non-face-to-face communication, breaking free of the limits of space and time in reality. Second, the entertainment role of fashion shows was strengthened. However, online fashion shows had limitations as they lacked a sense of reality and distracted viewers' attention from fashion products. This study has practical implications as it proposes a path for the development of digitalized fashion shows by addressing its current limitations. Overcoming these shortcomings, post-pandemic fashion shows would be more diverse, flexible, and creative. Consequently, following the pandemic period, we look forward to new types of fashion shows using digital imaging technologies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1040-1046
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• 2022

In this paper, we consider a system with massive user equipments (UEs) in a cell and assume path loss and Rayleigh fading channels between the base station (BS) and UEs. In addition, it is assumed that the system bandwidth consists of multiple identical frequency subchannels. Under such assumptions, we propose a channel state information (CSI) feedback scheme and a resource allocation scheme for non-orthogonal multiple access (NOMA) transmission in order to reduce the feedback overhead of CSI generated by massive UEs and to reduce the complexity of resource allocation. In particular, for the proposed schemes, we analyze the sum data rate achievable by massive UEs in a cell and the outage probability with which the UEs in a cell do not meet the target data rate. Through the simulation results, we show that the proposed schemes can provide the superior outage probability, although it degrades the average sum data rate.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.61-71
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• 2009

The server redirection system replicates contents on replica servers in the distributed network environment. When users make a request for contents, the system can provide the contents much faster than the client-server network system. In the server redirection system, it is the most important to select the optimal replica server with user's information because many replica servers are geographically distributed. And, the system can serve contents to users flexibly if a redirector is well constructed. In this paper, the redirector makes a list of candidates suitable for user conditions by the decision tree method and calculates the availability of each replica server. And, the redirector selects the replica server with the highest availability. This paper also proposes an availability-based server redirection system that predicts the availability of each replica server in order to reduce the workload of replica servers and the repetitive communication messages between a redirector and replica servers. If a user accesses the network path for the replica server selected and noticed by the proposed system, the user can get contents effectively and efficiently.