• Journal of Multimedia Information System
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• 제9권1호
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• pp.33-42
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• 2022

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

• 한국전기전자재료학회논문지
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• 제35권5호
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• pp.509-515
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• 2022

As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2016년도 춘계학술대회
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• pp.62-63
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• 2016

여객선에는 다양한 종류의 센서와 장비가 설치되어 있다. 이러한 센서와 장비로부터 수집되는 데이터는 여객선의 안전운항 분석을 위해 육상 시스템과 연계가 필요하지만 선박이 LTE 통신을 이용하지 못하는 지역을 운항할 경우 AIS, 위성, MF/HF 등과 같이 다른 대체 통신망을 이용한 정보 전송이 필요하다. 본 논문은 AIS 통신을 이용한 센서정보 전송을 위해 여객선에서 수집되는 센서 데이터의 프로토콜과 종류를 조사하고 선박 센서보고용 ASM 메시지를 설계하였다.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• 산업경영시스템학회지
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• 제40권3호
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• pp.99-106
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• 2017

With the increased interest in the quality of life of modern people, the implementation of the five-day working week, the increase in traffic convenience, and the economic and social development, domestic and international travel is becoming commonplace. Furthermore, in the past, there were many cases of purchasing packaged goods of specialized travel agencies. However, as the development of the Internet improved the accessibility of information about the travel area, the tourist is changing the trend to plan the trip such as the choice of the destination. Web services have been introduced to recommend travel destinations and travel routes according to these needs of the customers. Therefore, after reviewing some of the most popular web services today, such as Stubby planner (http://www.stubbyplanner.com) and Earthtory (http://www.earthtory.com), they were supposed to be based on traditional Traveling Salesman Problems (TSPs), and the travel routes recommended by them included some practical limitations. That is, they were not considered important issues in the actual journey, such as the use of various transportation, travel expenses, the number of days, and lodging. Moreover, although to recommend travel destinations, there have been various studies such as using IoT (Internet of Things) technology and the analysis of cyberspatial Big Data on the web and SNS (Social Networking Service), there is little research to support travel routes considering the practical constraints. Therefore, this study proposes a new mathematical model for applying to travel route recommendation service, and it is verified by numerical experiments on travel to Jeju Island and trip to Europe including Germany, France and Czech Republic. It also expects to be able to provide more useful information to tourists in their travel plans through linkage with the services for recommending tourist attractions built in the Internet environment.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.749-759
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• 2020

Over the years, numerous Micro, Small, and Medium Enterprises (MSMEs) have been vigorously established across many countries. Even though the Internet of Things (IoT) has enabled companies to anchorage business returns, most Indonesian MSMEs are highly susceptible to failure and one of the main issues is the inability to manage their financials effectively. The literature on accounting points out that the success of MSMEs owing to the usage of cloud-based Accounting Information Systems (AIS) or Cloud Accounting (CA) could reduce the rate of failure by managing multiple accounting information at a low cost. Although many benefits exist, Indonesian MSMEs are not adopting these platforms in their daily business activities. This study investigates the factors that influence Indonesian MSMEs' intention to adopt CA. The study is directed by unstructured in-depth interviews with seven bestseller MSMEs where a thematic analysis technique was employed to identify them. The interview findings and prevailing literature on the influencing factors based on the TOE (technological, organizational, and environmental) framework to adopt CA in Indonesian MSMEs context are perceived benefits outweighing the cost, perceived compatibility, perceived complexity, owner-manager knowledge on accounting, organization size, competitive pressure, and informal network. The conceptual model further includes government intervention as a moderator in the model.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.201-202
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• 2018

자동차 부품산업은 자동차산업의 후방산업으로 완성차 메이커 제조산업의 조립용인 중간재 산업으로 부품의 품질에 따라 완성차의 성능이 좌우된다. 자동차 산업구조상 완성차에 종속적인 사업구조로 부품사의 독자 성장이 어렵고 수익성이 완성차업체에 종속 된다. 자동차부품사의 대형화 및 생산공정 자동화 변화로 기존의 수직계열화된 부품 공급 관계에도 변화가 예상되며, 완성차업체는 통합적인 시스템 부품을 생산할 수 있는 글로벌 대형 부품업체에 의존하는 상황이 전개될 수도 있다. 이와 같은 위기와 변화를 극복하기 위해 본 연구에서는 산업구조분석을 자동차 부품산업에 적용하여 자동차부품산업의 경쟁력제고 전략을 도출하고자 한다.

• 전기전자학회논문지
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• 제21권3호
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• pp.227-233
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• 2017

근래에 전 세계적으로 비전공자나 중등학생들에게도 코딩 교육이 폭넓게 이루어지고 있으며 파이썬(python)은 비전문가의 교육용으로도 널리 채택되고 있다. 그리고 아두이노(arduino)는 피지컬 컴퓨팅(physical computing)과 사물인터넷 용도로 사용되는 대중적인 하드웨어이지만 $C{^+^+}$ 언어로 제어되므로 비전문가가 초기에 진입하기에 어려움이 있다. 본 논문은 파이썬 언어와 I2C 통신으로 마스터(master) 기기에서 다수의 아두이노 기기들을 동시에 제어할 수 있는 무오류 프로토콜을 제안한다. 본 논문에서 구현된 프로토콜을 이용하면 다수의 아두이노를 파이썬으로 오류없이 제어할 수 있으므로 아두이노를 제어하는데 파이썬 프로그램의 장점을 활용할 수 있다.

• 통합자연과학논문집
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• 제11권1호
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• pp.44-50
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• 2018

In this paper, we propose a context-aware power management (CPM) scheme using beacons to reduce the power consumption of personal computers (PCs). In the proposed CPM scheme, the PC, smartphone, control server, and Internet of Things (IoT) device are necessary. PC users first log in the control server using their smartphones and select PCs to turn on. Then, the selected PCs automatically go into three different modes, i.e., sleep, shutdown, and standby power off modes, in order when the PC users leave the PCs without turning off them. Further, we develop a testbed with the proposed CPM scheme using the Arduino with Bluetooth low energy (BLE) and relay modules. Finally, it is shown that the proposed CPM scheme outperforms the conventional scheme in terms of the power consumption.