• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.414-420
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• 2005

The ShortStack Micro Server enables any product that contains a microcontroller or microprocessor to quickly and inexpensively become a networked, Internet-accessible device. The ShortStack Micro Server provides a simple way to add LonWorks networking to new or existing smart devices. . It implements the LonTalk protocol and provides the physical interface with the LonWorks communication. The ShortStack host processor can be an 8, 16, or 32-bit microprocessor or microcontrollers. The ShortStack API and driver typically require about 4kbytes of program memory on the host processor and less than 200 bytes of RAM. The interface between host processor and the ShortStack Micro Server may be a Serial Communication Interface (SCI). The LonWorks control module with a high performance is developed, which is composed of the 8 bit PIC Microprocessor for host processor and the smart neuron chip for the ShortStack Micro Server. This intelligent control board is verified as proceeding the various function tests from experimental system with an boost pump and inverter driving systems. It is also confirmed that the developed control module provides stably 0-10VDC linear signal to the input signal of inverter driving system for varying the induction motor speed. Thus, the experimental results show that the fabricating intelligent board carried out very well the various functions in the wide operating ranges of boost pump system. This developed control module expect to apply to industrial fields to require the comparatively exact control and monitoring such as multi-motor driving system with inverter, variable air volume system and the boost pump water supply systems.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.6
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• pp.63-71
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• 1998

In this paper, we experiment the characteristics of coupling coefficient, gain, diffraction efficiency and dependence of time determined by TWM(Two-Wave Mixing), using Fe-LiNbO$_3$ crystal(doped with 0.015Wt.%). From these results, we proposed to apply for optical memory application. The highest coupling angle of 14。 and maximum coupling coefficient of 6.9$cm^{-1}$ / are obtained at 514.5nm wavelength. Also, maximum diffraction efficiency is 54.13% when intensity ratio and writing beam incident angle are 0.1 and 14o, respectively. After fixing process, diffraction efficiency is 21.4%. As an example, we demonstrated the writing and reconstruct optical data using spatial light modualtor and angular multiplexing in most optimal condition.

• Spatial Information Research
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• v.10 no.1
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• pp.61-76
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• 2002

Mobile map services using PDA are prevailing because of the rapid developments of techniques of the internet and handhold devices recently. While the volume of spatial data is tremendous and the spatial operations are time-intensive, the PDA has small size memory and a low performance processor. Therefore, the spatial index for PDA should be small size and efficiently filter out the candidate objects of spatial operation as well. This paper proposes a spatial index far PDA called MHF(Multilevel Hashing File). The MHF has simple structure for storage efficiency and uses a hashing technique, which is direct search method, for search efficiency. This paper also designs a compression technique for MBR. which occupies almost 80% of index data in the two dimensional case. We call it HMBR. Although the HMBR technique reduces the MB\ulcorner size to almost a third, it shows good filtering efficiency because of no information loss by quantization in case of small objects that occupy a major portion. Our experimental tests show that the proposed MHF index using HMBR technique is appropriate for PDA in terms of the size of index, the Number of MBR comparisons, the filtering efficiency and the execution time of spatial operations.

• Journal of Electrochemical Science and Technology
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• v.11 no.4
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• pp.384-391
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• 2020

Due to its characteristics of light weight, high energy density, good safety, long service life, no memory effect, and environmental friendliness, lithium-ion batteries (LIBs) are widely used in various portable electronic products. The capacity and performance of LIBs largely depend on the performance of electrode materials. Therefore, the development of better positive and negative materials is the focus of current research. The application of metal organic framework materials (MOFs) derivatives in energy storage has attracted much attention and research. Using MOFs as precursors, porous metal oxides and porous carbon materials with controllable structure can be obtained. In this paper, rod-shaped Co-MOF-74 was grown on Ni Foam (NF) by hydrothermal method, and then Co-MOF-74/NF precursor was heat-treated to obtain rodshaped Co₃O₄/NF. Ni Foam was skeleton structured, which effectively relieved. The change of internal stress changes and destroys the structural volume of the electrode material and reduces the capacity attenuation. Co₃O₄/NF composite material has a specific discharge capacity of up to 1858 mA h/g for the first time, and a reversible capacity of up to 902.4 mA h/g at a current density of 200 mA/g, and has excellent rate and impedance performance. The synthesis strategy reported in this article opens the way to design high-performance electrodes for energy storage and electrochemical catalysis.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.27-35
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• 2017

In near future, IoT data is expected to be a major portion of Big Data. Moreover, sensor data is expected to be major portion of IoT data, and its' research is actively carried out currently. However, processed results may not be trusted and used if outlier data is included in the processing of sensor data. Therefore, method for detection and deletion of those outlier data before processing is studied in this paper. Moreover, we used Spark which is memory based distributed processing environment for fast processing of big sensor data. The detection and deletion of outlier data consist of four stages, and each stage is implemented with Mapper and Reducer operation. The proposed method is compared in three different processing environments, and it is expected that the outlier detection and deletion performance is best in the distributed Spark environment as data volume is increasing.

• Advances in Computational Design
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• v.2 no.3
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• pp.123-141
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• 2017

Solving a system of linear or non-linear equations is required to analyze any kind of structures. There are many ways to solve a system of equations, and they can be classified as implicit and explicit techniques. The explicit methods eliminate round-off errors and use less memory. The dynamic relaxation method (DR) is one of the powerful and simple explicit processes. The important point is that the DR does not require to store the global stiffness matrix, for which it just uses the residual loads vector. In this paper, a new approach to the DR method is expressed. In this approach, the damping, mass and time steps are similar to those of the traditional method of dynamic relaxation. The difference of this proposed method is focused on the method of calculating the damping. The proposed method is expressed such that the time step is constant, damping is equal to zero except in steps with maximum energy and the concentrated damping can be applied to minimize the energy of system in this step. In this condition, the calculation of damping in all steps is not required. Then the volume of computation is reduced. The DR method for form-finding of membrane structures is employed in this paper. The form-finding of the three plans related to the membrane structures with different loading is considered to investigate the efficiency of the proposed method. The numerical results show that the convergence rate based on the proposed method increases in all cases than other methods.

• Journal of Biomedical Engineering Research
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• v.11 no.2
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• pp.305-314
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• 1990

In this paper we have implemented and tested TPN which is system to supply sufficent nutrition to nutritionally deficient patient by means of ES (expert system) a kind of A.1 (artificial intelligence) . This system affords to evaluation of nutritional state of patient which is essential to physi- cian. who performs TPN, decision of performing TPN and management of patient-data & calculation of information needing to making TPN fluid. The features were as follolv 1. we input data, take ideal weight of patient and 24hr's creatlnln In urine according to chart in system compare TSF (triceps skin fold), MAC (mid-arm circumference), AMC (arm muscle circumference) to 5th, 15th, 50th percentile and evaluate the nutritional state of patient. 2. Calculation of protein & nonprotein calorie needing to treament of patient can be made exactly by stress factor, activity factor and body temperature. 3. patient's personal recording needing to management of patient date name of chief doc- tor, name of department of admission, chart number, history can by taken very easily. 4. The way of system operating is pull-down Menu one, It can be processing very efficiently. 5. Date processing in system, we can manage memory volume of computer verlr efficiently using of dynamic allocation variables. 6. We can make it very easy to edit & revise the input data, processed data is saved to diskette in 2 files (TDF, THF) , these are semipermanent preservation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2885-2890
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• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.549-557
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• 2015

Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: Velocity, voracity, volume, and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platformand the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4Gbyte of storage size (87%of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.132-136
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• 1996

A Study is a experiment which is figure out to aptimum discharge cutting condition of the surfaceroughness, electric discharging speed and electro wear ratio with Ton Toff and V(voltage) as an input condition according to the current(Ip) in an electric spark machine ; 1)Electrode is utilized Cu(coper) and Graphite. 2)Work piece is used the material of carbon steel. The condition of experiment is; 1)Current is varied 0.7(A) to 50(A). 2)Pulse time(Ton) is varied 3($\mu$s) to 240($\mu$s) and also Toff is varied 7($\mu$s) to 20($\mu$s). 3)The time of electric discharging to work piece in each time is 30(min) to 60(min) 4)After the upper side of work piece was measured in radius (5${\mu}{\textrm}{m}$) of syulus analyzed the surface roughness to made the table and graph of Rmax by yielding data. 5)Electro wear ratio is; \circled1Coper was measured cx-machining and post machining but the electronic baiance. \circled2The ex-machining of graphite measured by it, the post-machining was found the data from volume specific gravity and analyzed to made its table and graph on ground the data 6)In order to keep the accuracy of voltage affected to the work piece was equipped with the A.V.R(Automatic Voltage Regulator). 7)The memory scope was sticked to the electric spark machine. 8)In order to preserve the precision of current, to get rid of the noise occured by internal resistance of electric spark machine and to force injecting for the discharge fluid, it made the fixed table for a work piece to minimize the work error by means of one's failure during the electric discharging According to above results, the surface roughness by the variation of electrodw and current was analyzed to compare KS(Korea Standards) It was decided the optimum condition of electric discharge cutting through analyzing the effect of electric discharge speed and electro wear ratio.