• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.8-19
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• 2021

The air pollution problem caused by industrialization in recent years is attracting great attention to both the country and the people. Domestic wide-area air pollution information is provided to the public through public data nationally, but regional air pollution information with different environmental variables is very insufficient. Therefore, in this study, we design and implement an air pollution analysis and prediction system based on regional environmental variables that can more accurately analyze and predict regional air pollution phenomena. In particular, the proposed system accurately analyzes and provides regional atmospheric information based on environmental data measured locally and public big data, and predicts and presents future regional atmospheric information using artificial intelligence algorithms. Furthermore, through the proposed system, it is expected that local air pollution can be prevented by accurately identifying the cause of regional air pollution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1609-1617
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• 2019

Described in this paper is a design of hardware accelerator for implementing public-key cryptographic protocols (PKCPs) based on Elliptic Curve Cryptography (ECC) and RSA. It supports five elliptic curves (ECs) over GF(p) and three key lengths of RSA that are defined by NIST standard. It was designed to support four point operations over ECs and six modular arithmetic operations, making it suitable for hardware implementation of ECC- and RSA-based PKCPs. In order to achieve small-area implementation, a finite field arithmetic circuit was designed with 32-bit data-path, and it adopted word-based Montgomery multiplication algorithm, the Jacobian coordinate system for EC point operations, and the Fermat's little theorem for modular multiplicative inverse. The hardware operation was verified with FPGA device by implementing EC-DH key exchange protocol and RSA operations. It occupied 20,800 gate equivalents and 28 kbits of RAM at 50 MHz clock frequency with 180-nm CMOS cell library, and 1,503 slices and 2 BRAMs in Virtex-5 FPGA device.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.44-49
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• 2020

Recently, one of the major issues of shipbuilding and marine is the reduction of air and marine pollution emission to ships. In response, the International Maritime Organization (IMO) has concluded an international convention (MARPOL) to prevent pollution from ships. A Annex Six of The Convention restricts and regulates air and marine pollution of ship from exhausting gases. To this end, it is required to apply EEDI (Energy Efficiency Design Indicators) to the construction of new ships, and to minimize the emission of environmental pollutants by recommending the application of EEOI (Energy Efficiency Operation Indicators) to operational ships. Therefore, in this study, we propose to calculate the grade of operating efficiency (EG) of ships based on actual operational data for transport ships and to provide energy-efficient optimal path search information through analysis of marine environment data.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.145-153
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• 2020

Recently, keyword extraction from social big data has been widely used for the purpose of extracting opinions or complaints from the user's perspective. Regarding this, our previous work suggested a method to improve accuracy of keyword extraction based on the notion of cohesion scoring, but its accuracy can be degraded when the number of input reviews is relatively small. This paper presents a method to resolve this issue by applying simplified morphological analysis as a postprocessing step to extracted keywords generated from the algorithm discussed in the previous work. The proposed method enables to add analysis rules necessary to process input data incrementally whenever new data arrives, which leads to reduction of a dictionary size and improvement of analysis efficiency. In addition, an interactive rule adder is provided to minimize efforts to add new rules. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that error ratio was reduced from 10% to 1% by applying our method and it took 450 milliseconds to process 5,000 reviews, which means that keyword extraction can be performed in a timely manner in the proposed method.

• Structural Engineering and Mechanics
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• v.77 no.2
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• pp.167-177
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• 2021

Due to various benefits such as unlimited degrees of freedom, environment adaptability, and safety for humans, engineers have used soft materials with hyperelastic behavior in various industrial, medical, rescue, and other sectors. One of the applications of these materials in the fabrication of bending soft actuators (SA) is that they have eliminated many problems in the actuators such as production cost, mechanical complexity, and design algorithm. However, SA has complexities, such as predicting and monitoring behavior despite the many benefits. The first part of this paper deals with the prediction of SA behavior through mathematical models such as Ogden and Darijani, and its comparison with the results of experiments. At first, by examining different geometric models, the cubic structure was selected as the optimal structure in the investigated models. This geometrical structure at the same pressure showed the most significant bending in the simulation. The simulation results were then compared with experimental, and the final gripper model was designed and manufactured using a 3D printer with silicone rubber as for the polymer part. This geometrical structure is capable of bending up to a 90-degree angle at 70 kPa in less than 2 seconds. The second section is dedicated to monitoring the bending behavior created by the strain sensors with different sensitivity and stretchability. In the fabrication of the sensors, silicon is used as a soft material with hyperelastic behavior and carbon fiber as a conductive material in the soft material substrate. The SA designed in this paper is capable of deforming up to 1000 cycles without changing its characteristics and capable of moving objects weigh up to 1200 g. This SA has the capability of being used in soft robots and artificial hand making for high-speed objects harvesting.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.178-186
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• 2021

COVID-19 occurred in China in December 2019 and spread to the world. Untact culture becoming commonplace due to the spread of COVID-19, is accelerating digital transformation across society. The government is increasing government fund to overcome national crisis situations such as COVID-19. In order to efficiently execute these government funds, the government and policy financial institutions need to come up with two measures. One is to establish a transparent government fund execution process, and the other is to secure the objectivity of the review process. In this paper, to solve this problem, we designed the execution process of government funds from the government to end users with Consortium Blockchain, and designed a machine learning algorithm for internal review of policy financial institutions. The research data proposed in this paper will be helpful in setting the future government policy direction for government fund execution.

• The Journal of Information Systems
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• v.30 no.4
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• pp.1-20
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• 2021

Purpose Nowadays, Autonomous Sensory Meridian Response (ASMR) is rapidly growing in popularity and increasingly appearing in marketing. Not even in TV commercial advertisement, ASMR also fast growing in one-person media communication, many brands and social media influencers used ASMR for their marketing contents. The purpose of this study is to measure consumers' perceptions about the products in ASMR marketing content and compare the differences in communication effect of ASMR content creator between product review and how-to in the same Macro tier influencer - the YouTuber that has 10,000-100,000 subscribers. Design/methodology/approach The research methods selected ASMRtist that do product review content and how-to content, Text comments data was collected from 200 videos of tech-device review videos and beauty-fashion videos. A total of 52,833 text comments were analyzed by applying the LDA topic modeling algorithm and social network analysis. Findings Through the result, we can know that ASMR is good at taking attention of viewers with ASMR triggers. In the Tech device reviews field, ASMR viewers also focus on the product like product's performance and purchase. However, there are many topics related to reaction of ASMR sound, trigger, relaxation. In the Beauty-fashion field, viewers' topics mainly focus on the reaction of the ASMR trigger, response to ASMRtist and other topics are talking about makeup - fashion, product, purchase. From LDA result, many ASMR viewers comment that they feel more comfortable when watching the marketing content that uses ASMR. This result has shown that ASMR marketing contents have a good performance in terms of user watching experience, so applying ASMR can take more consumer intention. And the result of social network analysis showed that product review ASMRtist have a higher communication effectiveness than how-to ASMRtist in the same tier. As an influencer marketing strategy, this study provides information to establish an efficient advertising strategy by using influencers that create ASMR content.

• The Journal of Information Systems
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• v.31 no.1
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• pp.289-304
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• 2022

Purpose The development of the network and mobile industries has induced companies to invest in information systems, leading a new industrial revolution. The Journal of Information Systems, which developed the information system field into a theoretical and practical study in the 1990s, retains a 30-year history of information systems. This study aims to identify academic values and research trends of JIS by analyzing the trends. Design/methodology/approach This study aims to analyze the trend of JIS by compounding various methods, named as TLS mining analysis. TLS mining analysis consists of a series of analysis including Term Frequency-Inverse Document Frequency (TF-IDF) weight model, Latent Dirichlet Allocation (LDA) topic modeling, and a text mining with Semantic Network Analysis. Firstly, keywords are extracted from the research data using the TF-IDF weight model, and after that, topic modeling is performed using the Latent Dirichlet Allocation (LDA) algorithm to identify issue keywords. Findings The current study used the summery service of the published research paper provided by Korea Citation Index to analyze JIS. 714 papers that were published from 2002 to 2012 were divided into two periods: 2002-2011 and 2012-2021. In the first period (2002-2011), the research trend in the information system field had focused on E-business strategies as most of the companies adopted online business models. In the second period (2012-2021), data-based information technology and new industrial revolution technologies such as artificial intelligence, SNS, and mobile had been the main research issues in the information system field. In addition, keywords for improving the JIS citation index were presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.850-858
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• 2022

To deploy Gate Recurrent Units (GRU) on resource-constrained embedded devices, this paper presents a reconfigurable FPGA-based GRU accelerator that enables structured compression. Firstly, a dense GRU model is significantly reduced in size by hybrid quantization and structured top-k pruning. Secondly, the energy consumption on external memory access is greatly reduced by the proposed reuse computing pattern. Finally, the accelerator can handle a structured sparse model that benefits from the algorithm-hardware co-design workflows. Moreover, inference tasks can be flexibly performed using all functional dimensions, sequence length, and number of layers. Implemented on the Intel DE1-SoC FPGA, the proposed accelerator achieves 45.01 GOPs in a structured sparse GRU network without batching. Compared to the implementation of CPU and GPU, low-cost FPGA accelerator achieves 57 and 30x improvements in latency, 300 and 23.44x improvements in energy efficiency, respectively. Thus, the proposed accelerator is utilized as an early study of real-time embedded applications, demonstrating the potential for further development in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.396-402
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• 2022

User interactions are being developed in various forms, and in particular, interactions using human gestures are being actively studied. Among them, hand gesture recognition is used as a human interface in the field of realistic media based on the 3D Hand Model. The use of interfaces based on hand gesture recognition helps users access media media more easily and conveniently. User interaction using hand gesture recognition should be able to view images by applying fast and accurate hand gesture recognition technology without restrictions on the computer environment. This paper developed a fast and accurate user hand gesture recognition algorithm using the open source media pipe framework and machine learning's k-NN (K-Nearest Neighbor). In addition, in order to minimize the restriction of the computer environment, a stereoscopic image control system based on user hand gesture recognition was designed and implemented using a web service environment capable of Internet service and a docker container, a virtual environment.