• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.13-20
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• 2020

One of the major issues surrounding big data is the availability of massive time-based or telemetry data. Now, the appearance of low cost capture and storage devices has become possible to get very detailed time data to be used for further analysis. Thus, we can use these time data to get more knowledge about the underlying system or to predict future events with higher accuracy. In particular, it is very important to define custom tailored contract offers for many households and businesses having smart meter records and predict the future electricity usage to protect the electricity companies from power shortage or power surplus. It is required to identify a few groups with common electricity behavior to make it worth the creation of customized contract offers. This study suggests big data transformation as a side effect and clustering technique to understand the electricity usage pattern by using the open data related to smart meter and KNIME which is an open source platform for data analytics, providing a user-friendly graphical workbench for the entire analysis process. While the big data components are not open source, they are also available for a trial if required. After importing, cleaning and transforming the smart meter big data, it is possible to interpret each meter data in terms of electricity usage behavior through a dynamic time warping method.

• Journal of KIISE:Information Networking
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• v.32 no.5
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• pp.615-624
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• 2005

In Mobile IP, several types of messages - binding update, binding request and binding acknowledgement - are used to support user mobility. It is necessary to exchange those messages frequently for seamless mobility but it incurs both the increase of network overhead and poor usage of mobile node battery power Thus, we need a mechanism that the server detects users location and also copes with the problems effectively, which is our main concern in this paper Each user records all moving logs locally and periodically makes out profile based on them in HMIPv6. By using profile, estimated resident time can be computed whenever he enters an area and the time is set up as the binding update message lifetime. Of course, the more correct lifetime nay be obtained IP arrival time as well as average resident time Is considered in profile. Through extensive experiments, we measure the bandwidth usage for binding update messages by comparing the proposed schemes with that in HMIPv6. From the results, Gain gets over $80\%$ when mobile node stays more than 13 minutes in a subnet. Namely, we come to know that our schemes improve network usage and energy usage in mobile node by decreasing the number of messages while they also manage users locations like that in HMIPv6.

• ETRI Journal
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• v.37 no.2
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• pp.348-358
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• 2015

Mobile devices have been widespread and become very popular with connectivity to the Internet, and a lot of desktop PC applications are now aggressively ported to them. Unfortunately, mobile devices are often vulnerable to malicious attacks due to their common usage and connectivity to the Internet. Therefore, the demands on the development of mobile security systems increase in accordance with advances in mobile computing. However, it is very hard to run a security program on a mobile device all of the time due the device's limited computational power and battery life. To overcome these problems, we propose a novel mobile security scheme that migrates heavy computations on mobile devices to cloud servers. An efficient data transmission scheme for reducing data traffic between devices and servers over networks is introduced. We have evaluated the proposed scheme with a mobile device in a cloud environment, whereby it achieved a maximum speedup of 13.4 compared to a traditional algorithm.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.47
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• pp.25-48
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• 2010

The principle of parties' autonomy is one of general and dominant principles in an international trade contract. When we consider the determinants of negotiation outcomes, the negotiation is affected its result by their culture and custom. A negotiation has extensively been used a lot as a business process. As we negotiate with our clients, we have to check a lot of factors like strategies, their behaviors, culture shock and custom. That why most people have their different life and circumstance. The same words which are used its contract have several meaning. Because the words are influenced by culture and own custom. Also most people abide by their social pattern. Each culture in the world follows its own customs and traditions. Therefore, when we have the negotiation of trade contract, we have to think these factors. Then the negotiation is leaded very successful This dissertation examines the effects of the negotiators' personality and different culture and custom. On the point of a negotiating power, contracting parties are affected a lot by their usage. The culture which is influenced by contracting parties is possible to apply as a key point. So, this study will be analyzed these factors.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.12
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• pp.683-695
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• 2007

NAND flash memory-based file systems cannot store their system-related information in the file system due to wear-leveling of NAND flash memory. This forces NAND flash memory-based file systems to scan the whole flash memory during their mounts. The mount time usually increases linearly according to the size of and the usage pattern of the flash memory. NAND flash memory has been widely used as the storage medium of mobile devices. Due to the fact that mobile devices have unstable power supply, the file system for NAND flash memory requires stable recovery mechanism from power failure. In this paper, we present design and implementation of a new NAND flash memory-based file system that provides fast mount and enhanced stability. Our file system mounts 19 times faster than JFFS2's and 2 times faster than YAFFS's. The stability of our file system is also shown to be equivalent to that of JFFS2.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.176-183
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• 2009

Distributed generation(DG) of combined cooling, heat, and power(CCHP)has been gaining momentum in recent year as efficient, secure alternative for meeting increasing energy demands. This paper presents the energy performance of microturbine CCHP system equipped with an absorption chiller by modelling it in hospital building. The orders of study were as following. 1)The list and schedule of energy consumption equipment in hospital were examined such as heating and cooling machine, light etc. 2) Annual report of energy usage and monitoring data were examined as heating, cooling, DHW, lighting, etc. 3) The weather data in 2007 was used for simulation and was arranged by meteorological office data in Daejeon. 4) Reference simulation model was built by comparison of real energy consumption and simulation result by TRNSYS and ESP-r. The energy consumption pattern of building were analyzed by simulation model and energy reduction rate were calculated over the cogeneration. As a result of this study, power generation efficiency of turbine was about 30[%] after installing micro gas turbine and lighting energy as well as total electricity consumption can be reduced by 40[%]. If electricity energy and waste heat in turbine are used, 56[%] of heating energy and 67[%] of cooling energy can be reduced respectively, and total system efficiency can be increased up to 70[%].

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.17-28
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• 2024

As listed as one of the most important requirements for Post-Quantum Cryptography standardization process by National Institute of Standards and Technology, the resistance to various side-channel attacks is considered very critical in deploying cryptosystems in practice. In fact, cryptosystems can easily be broken by side-channel attacks, even though they are considered to be secure in the mathematical point of view. The timing attack(TA) and the simple power analysis attack(SPA) are such side-channel attack methods which can reveal sensitive information by analyzing the timing behavior or the power consumption pattern of cryptographic operations. Thus, appropriate measures against such attacks must carefully be considered in the early stage of cryptosystem's implementation process. The Montgomery multiplier is a commonly used and classical gadget in implementing big-number-based cryptosystems including RSA and ECC. And, as recently proposed as an alternative of building blocks for implementing post quantum cryptography such as lattice-based cryptography, the big-number multiplier including the Montgomery multiplier still plays a role in modern cryptography. However, in spite of its effectiveness and wide-adoption, the multiplier is known to be vulnerable to TA and SPA. And this paper proposes a new countermeasure for the Montgomery multiplier against TA and SPA. Briefly speaking, the new measure first represents a multiplication operand without 0 digits, so the resulting multiplication operation behaves in a very regular manner. Also, the new algorithm removes the extra final reduction (which is intrinsic to the modular multiplication) to make the resulting multiplier more timing-independent. Consequently, the resulting multiplier operates in constant time so that it totally removes any TA and SPA vulnerabilities. Since the proposed method can process multi bits at a time, implementers can also trade-off the performance with the resource usage to get desirable implementation characteristics.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.133-140
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• 2023

The performance of lithium ion batteries depends on the usage environment and the combination ratio of cathode materials. In order to develop a high-performance lithium-ion battery, it is necessary to manufacture the battery and measure its performance while varying the cathode material ratio. However, it takes a lot of time and money to directly develop batteries and measure their performance for all combinations of variables. Therefore, research to predict the performance of a battery using an artificial intelligence model has been actively conducted. However, since measurement experiments were conducted with the same battery in the existing published battery data, the cathode material combination ratio was fixed and was not included as a data attribute. In this paper, we define a training data model required to develop an artificial intelligence model that can predict battery performance according to the combination ratio of cathode materials. We analyzed the factors that can affect the performance of lithium-ion batteries and defined the mass of each cathode material and battery usage environment (cycle, current, temperature, time) as input data and the battery power and capacity as target data. In the battery data in different experimental environments, each battery data maintained a unique pattern, and the battery classification model showed that each battery was classified with an error of about 2%.

• Economic and Environmental Geology
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• v.35 no.4
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• pp.317-323
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• 2002

Mineral medicines are single or mixtures of minerals and rocks which have been used to treat disease. Recently, their application has been increased by emphasizing the physical properies of the medicines, in addition to their chemical properies. In this study, mineralogical, chemical, spectroscopic and magnetic properties were measured using X-ray diffraction analysis, X-ray fluorescence spectrometry, Ff-Infrared spectroscopy, nuclear magnetic resonance spectroscopy, mass magnetic susceptibility. Experiments were done using these properties to evaluate application of traditional mineral medicines such as Yanggiseok, Yeonok and Eumgiseok. Mineralogical study proves that Yanggiseok, generally known as tremolite, consists of actinolite. Yeonok for medical usage mostly consists of fine grained tremolite. Eumgiseok is mainly composed of vermiculite and minor kaolinite and halloysite. Yeonok and Yanggiseok, belong to the amphibole group among inosilicates and both have similar emission power properties. The intensity of emission power, calculated from FT-IR measurements, follows in the order of Yeonok, Yanggiseok and Eumgiseok at 40$^{\circ}$C and Yanggiseok, Yeonok and Eumgiseok in such order at 150$^{\circ}$C. As a result of NMR analysis after 20 days in distilled water, the three mineral medicines decreased in the following order; Eumgiseok, Yanggiseok and Yeonok. However, the same minerals decreased in the order of Eumgiseok, Yeonok and Yanggiseok after 80 days. In response temperature, magnetic susceptibility of Yanggiseok and Eumgiseok systematically increased by heating to 25$^{\circ}$C, 100$^{\circ}$C and 700$^{\circ}$C. Magnetic susceptibility of Yeonok shows a decreasing pattern due to heating.