• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.76-86
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• 2021

Technologies for lithium secondary batteries are now increasingly expanding to simultaneously improve the safety and higher energy and power densities of large-scale battery systems, such as electric vehicles and smart-grid energy storage systems. Next-generation lithium batteries, such as lithium-sulfur (Li-S) and lithium-air (Li-O₂) batteries by adopting solid electrolytes and lithium metal anode, can be a solution for the requirements. In this analysis of battery technology trends, solid electrolytes, including polymer (organic), inorganic (oxides and sulfides), and their hybrid (composite) are focused to describe the electrochemical performance achievable by adopting optimal components and discussing the interfacial behaviors that occurred by the contact of different ingredients for safe and high-energy lithium secondary battery systems. As next-generation rechargeable lithium batteries, Li-S and Li-O₂ battery systems are briefly discussed coupling with the possible use of solid electrolytes. In addition, Electronics and Telecommunications Research Institutes achievements in the field of solid electrolytes for lithium rechargeable batteries are finally introduced.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.125-136
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• 2021

The development of systems that can generate automatically instructional material is a challenging goal for the e-learning community. These systems pave the way towards large scale e-learning deployment as they produce instruction on-demand for users requesting to learn about any topic, anywhere and anytime. However, realizing such systems is possible with the availability of vast repositories of web information in different formats that can be searched, reused and integrated into information-rich environments for interactive learning. This paradigm of learning relieves instructors from the tedious authoring task, making them focusing more on the design and quality of instruction. This paper presents a mobile learning system (Mole) that supports the generation of instructional material in M-Learning (Mobile Learning) contexts, by reusing and integrating heterogeneous hypermedia web resources. Mole uses open hypermedia repositories to build a Learning Web and to generate learning objects including various hypermedia resources that are adapted to the user context. Learning is delivered through a nice graphical user interface allowing the user to navigate conveniently while building their own learning path. A test case scenario illustrating Mole is presented along with a system evaluation which shows that in 90% of the cases Mole was able to generate learning objects that are related to the user query.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.792-812
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• 2022

Multi-agent systems often need to achieve the goal of learning more effectively for a task through coordination. Although the introduction of deep learning has addressed the state space problems, multi-agent learning remains infeasible because of the joint action spaces. Large-scale joint action spaces can be sparse according to implicit or explicit coordination structure, which can ensure reasonable coordination action through the coordination structure. In general, the multi-agent system is dynamic, which makes the relations among agents and the coordination structure are dynamic. Therefore, the explicit coordination structure can better represent the coordinative relationship among agents and achieve better coordination between agents. Inspired by the maximization of social group utility, we dynamically construct a factor graph as an explicit coordination structure to express the coordinative relationship according to the utility among agents and estimate the joint action values based on the local utility transfer among factor graphs. We present the application of such techniques in the scenario of multiple intelligent vehicle systems, where state space and action space are a problem and have too many interactions among agents. The results on the multiple intelligent vehicle systems demonstrate the efficiency and effectiveness of our proposed methods.

• Journal of Space Technology and Applications
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• v.4 no.1
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• pp.12-26
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• 2024

Attitude control of a satellite is very important to ensure proper for mission performance. Satellites launched in the past had simple missions. However, recently, with the advancement of technology, the tasks to be performed have become more complex. One example relies on a new technology that allows satellites quickly alter their attitude while orbiting in space. Currently, one of the most widely used technologies for satellite attitude control is the reaction wheel. However, the amount of torque generated by reaction wheels is too low to facilitate quick maneuvers by the satellite. One way to overcome this is to implement posture control logic using a control moment gyroscope (CMG). Various types of CMGs have been applied to space systems, and CMGs are currently mounted on large-scale satellites. However, although technological advancements have continued, the market for CMGs applicable to, small satellites remains in its early stages. An ultra-small CMG was developed for use with small satellites weighing less than 200 kg. The ultra-small CMG measured its target performance outcomes using a precision torque-measuring device. The target performance of the CMG, at 800 mNm, was set through an analysis. The final torque of the CMG produced through the design after the analysis was 821mNm, meaning that a target tolerance level of 10% was achieved.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1269-1289
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• 2014

With the sub-stepping technique, the numerical analysis in real-time dynamic hybrid testing is split into the response analysis and signal generation tasks. Two target computers that operate in real-time may be assigned to implement these two tasks, respectively, for fully extending the simulation scale of the numerical substructure. In this case, the integration time-step of solving the dynamic response of the numerical substructure can be dozens of times bigger than the sampling time-step of the controller. The time delay between the real and desired feedback forces becomes more striking, which challenges the well-developed delay compensation methods in real-time dynamic hybrid testing. This paper focuses on displacement prediction and force correction for delay compensation in the real-time dynamic hybrid testing with a large integration time-step. A new displacement prediction scheme is proposed based on recently-developed explicit integration algorithms and compared with several commonly-used prediction procedures. The evaluation of its prediction accuracy is carried out theoretically, numerically and experimentally. Results indicate that the accuracy and effectiveness of the proposed prediction method are of significance.

• Ocean Systems Engineering
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• v.4 no.3
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• pp.215-241
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• 2014

Steel catenary riser (SCR) is a popular/economical solution for the oil/gas production in deep and ultra-deep water. The behavioral characteristics of SCR have a high correlation with the motion of floating production facility at its survival and operational environments. When large motions of surface floaters occur, such as FPSO in 100-yr storm case, they can cause unacceptable negative tension on SCR near TDZ (touch down zone) and the corresponding elastic deflection can be large due to local dynamic buckling. The generation, propagation, and decay of the elastic wave are also affected by SCR and seabed soil interaction effects. The temporary local dynamic buckling vanishes with the recovery of tension on SCR with the upheaval motion of surface floater. Unlike larger-scale, an-order-of-magnitude longer period global buckling driven by heat and pressure variations in subsea pipelines, the sub-critical local dynamic buckling of SCR is motion-driven and short cycled, which, however, can lead to permanent structural damage when the resulting stress is greatly amplified beyond the elastic limit. The phenomenon is extensively investigated in this paper by using the vessel-mooring-riser coupled dynamic analysis program. It is found that the moment of large downward heave motion at the farthest-horizontal-offset position is the most dangerous for the local dynamic buckling.

• Journal of KIISE:Information Networking
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• v.31 no.5
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• pp.438-449
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• 2004

With the growing deployment of network and internet, the importance of security is also increased. But, recent intrusion detection systems which have an important position in security countermeasure can't provide proper analysis and effective defence mechanism. Instead, they have overwhelmed human operator by large volume of intrusion detection alerts. In this paper, we propose an efficient alert analysis system that can produce high level information by analyzing and processing the large volume of alerts and can detect large-scale attacks such as DDoS in early stage. And we have measured processing rate of each elementary module and carried out a scenario-based test in order to analyzing efficiency of our proposed system.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.278-288
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• 2021

Recently, IoT systems are cloud-based, so that continuous and large amounts of data collected from sensor nodes are processed in the data server through the cloud. However, in the centralized configuration of large-scale cloud computing, computational processing must be performed at a physical location where data collection and processing take place, and the need for edge computers to reduce the network load of the cloud system is gradually expanding. In this paper, a cluster system consisting of 6 inexpensive Raspberry Pi boards was constructed to perform fast data processing. And we propose "Kubernetes cluster system(KCS)" for processing large data collection and analysis by model distribution and data pipeline method. To compare the performance of this study, an ensemble model of deep learning was built, and the accuracy, processing performance, and processing time through the proposed KCS system and model distribution were compared and analyzed. As a result, the ensemble model was excellent in accuracy, but the KCS implemented as a data pipeline proved to be superior in processing speed..

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.204-213
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• 2022

Most of the prior studies on the servitization of manufacturing companies have been actively studied, focusing on the performance and cases of servitization at the single company level. According to the results, most of the servitization at the single company level has been expanded based on the relevance of the company's core products. However, the form of companies that form a large axis of the Korean economy is a large-scale business group, and these business groups incorporate service affiliates for various purposes, so they show different characteristics from that of a single corporate. In addition, since the purpose of forming a business group is different for each business group, the service relevance between affiliates within the business group is different. Therefore, this study aims to examine the effect of service relevance between affiliates within a business group on the management performance of each business group. To this end, an empirical analysis will be conducted using panel data for 10 years from 2011 to 2020 for a total of 98 affiliates listed on KOSPI and KOSDAQ of 9 domestic business groups. Based on these results, the direction for improving management performance and establishing future servitization strategies for large business groups in Korea will be expected to be made.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.