• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.482-482
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• 2000

The essential requirements of neural network for human skill transfer are fast convergence, high storage capacity, and strong noise immunity. Bidirectional associative memory(BAM) suffering from low storage capacity and abundance of spurious memories is rarely used for skill transfer application though it has fast and wide association characteristics for visual data. This paper suggests generalization of classical BAM structure and new learning algorithm which uses supervised learning to guarantee perfect recall starting with correlation matrix. The generalization is validated to accelerate convergence speed, to increase storage capacity, to lessen spurious memories, to enhance noise immunity, and to enable multiple association using simulation work.

• 제어로봇시스템학회논문지
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• 제7권1호
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• pp.1211-1217
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• 2001

This paper presnts a controller for the heat capacity of thermal storage systems using off-peak electricity which is composed of an identifier using neural networks and a storage time adjuster in order to store exactly the required thermal energy without loss. Since thermal storage systems have nonlinear characteristics and large time constant, even if we predict the heating load accurately, it is very difficult to store exactly the required thermal energy. Thus, in the neural network for the identifier, the adaptive learning rate for high learning speed and bit inputs based on state changes of thermal storage power source are used. Also a hardware for the controller using a microprocessor is developed. The performance of the proposed controller is shown by experiment.

• Journal of international Conference on Electrical Machines and Systems
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• 제1권2호
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• pp.111-115
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• 2012

In this paper, a solar energy powered bicycle linked to a wireless sensor network (WSN) which monitors the transfer of solar energy to an electrical energy storage unit and an analysis of its effectiveness is proposed. In order to achieve this goal, a solar-powered bicycle with an attached ZigBee and a far-end wireless network supervisory system is setup. Experimental results prove that our prototype, solar energy powered bicycle, can achieve enough solar energy for charging a two lead-acid battery pack. As a result, the user, through use of a wireless network in the parking period can be kept aware of the data on the amount of immediate solar radiation, the degree of illumination, the ambient temperature, and electrical energy storage capacity information of the bicycle through an internet interface.

• 대한임베디드공학회논문지
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• 제5권4호
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• pp.175-184
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• 2010

This paper designs a virtual USB drive for mobile devices which gives an illusion of a traditional USB flash memory drive and provides capacity-free storage space over IP network. The virtual USB drive operating with a S3C2410 hardware platform and embedded linux consists of USB device driver, an iSCSI-enabled network stack, and a seamless USB/iSCSI tunneling module. For performance enhancement, it additionally provides a kernel-level seamless USB/iSCSI tunneling module and data sharing with symbol references among kernel modules. Experiments reveal that the kernel-level implementation can improve the I/O performance up to 8 percentage, as compared with the user-level implementation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.202-204
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• 1993

Appropriate control of real and reactive power flowing in and out from system can lead to considerable benefits : network stabilization, load leveling, voltage regulation etc. This paper presents how to control real and reactive power flow between an flywheel energy storage system and a power three phase network. The system compensating real and reactive power consists of control system and cycloconverter operating in the four quadrant modes.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.89-100
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• 2022

With the advancement in the Internet of things Technology (IoT) cloud computing, billions of physical devices have been interconnected for sharing and collecting data in different applications. Despite many advancements, some latency - specific application in the real world is not feasible due to existing constraints of IoT devices and distance between cloud and IoT devices. In order to address issues of latency sensitive applications, fog computing has been developed that involves the availability of computing and storage resources at the edge of the network near the IoT devices. However, fog computing suffers from many limitations such as heterogeneity, storage capabilities, processing capability, memory limitations etc. Therefore, it requires an adequate task scheduling method for utilizing computing resources optimally at the fog layer. This work presents a comprehensive review of different task scheduling methods in fog computing. It analyses different task scheduling methods developed for a fog computing environment in multiple dimensions and compares them to highlight the advantages and disadvantages of methods. Finally, it presents promising research directions for fellow researchers in the fog computing environment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2652-2654
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• 2005

A vacuum chamber temperature control system of Pohang Accelerator Laboratory (PAL) storage ring is a subsystem upgraded PAL control system, which is based upon Experimental Physics and Industrial Control System (EPICS) [1]. There are two control components, data acquisition system (SA120 data logger), development control system IOC (Input/Output Controller) at the storage ring of PAL. There are 240 vacuum chamber at the storage ring. It was a very important problem to solve how to monitor such a large number of vacuum chamber temperature distributed around the ring. The IOC connect MODBUS/JBUS field network to asynchronous serial ports for communication with serial device. It can simultaneously control up to 4 data acquisition systems. Upon receiving a command from a IOC running under Windows2k through the network, the IOC communicate through the slave serial interface ports to SA120. We added some software components on the top of EPICS toolkit. The design of the vacuum control system is discussed. This paper describes the development vacuum chamber temperature control system and how the design of this system.

• 한국화재소방학회논문지
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• 제34권1호
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• pp.26-36
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• 2020

랙크식 창고 화재의 경우 랙크에 적재된 가연성물품사이의 송기공간을 통한 급격한 화재확산으로 인해 화재진압이 매우 어렵다. 현재 국내 랙크식 창고의 소방시스템은 많은 문제점이 있으며, 이를 해결하기 위하여 새로운 소방시스템을 설계되고 개발되었다. 극 초기감지와 화재발생위치정보를 얻기 위하여 감지기 네트워크와 인공지능을 활용한 지능형 시스템을 설계되었다. 극초기에 화재 위치 인근에서 살수가 가능하도록 수직 일제살수 배관과 습식배관, 그리고 전자밸브를 사용하여 시스템을 구성하였다. 설계 결과를 기반으로 실제 시스템의 설치 및 실대형 시험을 진행하였으며, 성공적으로 시험이 완료되었다.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.196-202
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• 2021

DNA sequencing provides fundamental data in genomics, bioinformatics, biology and many other research areas. With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Those large volumes of data also require a fast transmission, effective storage, superior functionality and provision of quick access to any record. Data storage costs have a considerable proportion of total cost in the formation and analysis of DNA sequences. In particular, there is a need of highly control of disk storage capacity of DNA sequences but the standard compression techniques unsuccessful to compress these sequences. Several specialized techniques were introduced for this purpose. Therefore, to overcome all these above challenges, lossless compression techniques have become necessary. In this paper, it is described a new DNA compression mechanism of pattern matching extended Compression algorithm that read the input sequence as segments and find the matching pattern and store it in a permanent or temporary table based on number of bases. The remaining unmatched sequence is been converted into the binary form and then it is been grouped into binary bits i.e. of seven bits and gain these bits are been converted into an ASCII form. Finally, the proposed algorithm dynamically calculates the compression ratio. Thus the results show that pattern matching extended Compression algorithm outperforms cutting-edge compressors and proves its efficiency in terms of compression ratio regardless of the file size of the data.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.