• Title/Summary/Keyword: intelligent control system

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Engine of computational Emotion model for emotional interaction with human (인간과 감정적 상호작용을 위한 '감정 엔진')

  • Lee, Yeon Gon
    • Science of Emotion and Sensibility
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    • v.15 no.4
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    • pp.503-516
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    • 2012
  • According to the researches of robot and software agent until now, computational emotion model is dependent on system, so it is hard task that emotion models is separated from existing systems and then recycled into new systems. Therefore, I introduce the Engine of computational Emotion model (shall hereafter appear as EE) to integrate with any robots or agents. This is the engine, ie a software for independent form from inputs and outputs, so the EE is Emotion Generation to control only generation and processing of emotions without both phases of Inputs(Perception) and Outputs(Expression). The EE can be interfaced with any inputs and outputs, and produce emotions from not only emotion itself but also personality and emotions of person. In addition, the EE can be existed in any robot or agent by a kind of software library, or be used as a separate system to communicate. In EE, emotions is the Primary Emotions, ie Joy, Surprise, Disgust, Fear, Sadness, and Anger. It is vector that consist of string and coefficient about emotion, and EE receives this vectors from input interface and then sends its to output interface. In EE, each emotions are connected to lists of emotional experiences, and the lists consisted of string and coefficient of each emotional experiences are used to generate and process emotional states. The emotional experiences are consisted of emotion vocabulary understanding various emotional experiences of human. This study EE is available to use to make interaction products to response the appropriate reaction of human emotions. The significance of the study is on development of a system to induce that person feel that product has your sympathy. Therefore, the EE can help give an efficient service of emotional sympathy to products of HRI, HCI area.

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Study on the Standardization of Management Form through Integrated Management of CCTV (CCTV 통합관리를 위한 관리대장 표준화 연구)

  • PARK, Jeong-Woo;LEE, Seong-Ho;NAM, Kwang-Woo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.2
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    • pp.63-72
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    • 2016
  • Closed-circuit television(CCTV) is a facility that forms the backbone of the ubiquitous services provided by the Integrated Management Center of the Ministry of Land, Infrastructure and Transport and the Integrated Control Center of the Ministry of the Interior. However, it is installed and managed according to different laws, as it is operated and managed by each department. Moreover, because there are no regulatory grounds for unified management of CCTV, each municipality responsible for the actual management manages it based on the individual standards of each department. Thus, the purpose of this study is to develop a standardized management form to establish an integrated management plan. The author inspected the existing situation by examining the legal system and public data and through hands-on worker interviews, and discovered the managed element by reviewing the specifications of the bidding system. The management form for integrated management comprises the above requirements along with the management histories and linkage of intelligent facilities. A uniform management form for integrated management containing specifications of the CCTVs installed by various departments is created, and is easily searched for facilities to check requirements for joint use. The result of this study can contribute to building the database of facility management system for integrated management of facilities at the integrated management center as well as for a detailed simulation of the selection of location of CCTV depending on the CCTV's specifications.

Flexible Intelligent Exit Sign Management of Cloud-Connected Buildings

  • Lee, Minwoo;Mariappan, Vinayagam;Lee, Junghoon;Cho, Juphil;Cha, Jaesang
    • International Journal of Advanced Culture Technology
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    • v.5 no.1
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    • pp.58-63
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    • 2017
  • Emergencies and disasters can happen any time without any warning, and things can change and escalate very quickly, and often it is swift and decisive actions that make all the difference. It is a responsibility of the building facility management to ensure that a proven evacuation plan in place to cover various worst scenario to handled automatically inside the facility. To mapping out optimal safe escape routes is a straightforward undertaking, but does not necessarily guarantee residents the highest level of protection. The emergency evacuation navigation approach is a state-of-the-art that designed to evacuate human livings during an emergencies based on real-time decisions using live sensory data with pre-defined optimum path finding algorithm. The poor decision on causalities and guidance may apparently end the evacuation process and cannot then be remedied. This paper propose a cloud connected emergency evacuation system model to react dynamically to changes in the environment in emergency for safest emergency evacuation using IoT based emergency exit sign system. In the previous researches shows that the performance of optimal routing algorithms for evacuation purposes are more sensitive to the initial distribution of evacuees, the occupancy levels, and the type and level of emergency situations. The heuristic-based evacuees routing algorithms have a problem with the choice of certain parameters which causes evacuation process in real-time. Therefore, this paper proposes an evacuee routing algorithm that optimizes evacuation by making using high computational power of cloud servers. The proposed algorithm is evaluated via a cloud-based simulator with different "simulated casualties" are then re-routed using a Dijkstra's algorithm to obtain new safe emergency evacuation paths against guiding evacuees with a predetermined routing algorithm for them to emergency exits. The performance of proposed approach can be iterated as long as corrective action is still possible and give safe evacuation paths and dynamically configure the emergency exit signs to react for real-time instantaneous safe evacuation guidance.

GIS-based Market Analysis and Sales Management System : The Case of a Telecommunication Company (시장분석 및 영업관리 역량 강화를 위한 통신사의 GIS 적용 사례)

  • Chang, Nam-Sik
    • Journal of Intelligence and Information Systems
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    • v.17 no.2
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    • pp.61-75
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    • 2011
  • A Geographic Information System(GIS) is a system that captures, stores, analyzes, manages and presents data with reference to geographic location data. In the later 1990s and earlier 2000s it was limitedly used in government sectors such as public utility management, urban planning, landscape architecture, and environmental contamination control. However, a growing number of open-source packages running on a range of operating systems enabled many private enterprises to explore the concept of viewing GIS-based sales and customer data over their own computer monitors. K telecommunication company has dominated the Korean telecommunication market by providing diverse services, such as high-speed internet, PSTN(Public Switched Telephone Network), VOLP (Voice Over Internet Protocol), and IPTV(Internet Protocol Television). Even though the telecommunication market in Korea is huge, the competition between major services providers is growing more fierce than ever before. Service providers struggled to acquire as many new customers as possible, attempted to cross sell more products to their regular customers, and made more efforts on retaining the best customers by offering unprecedented benefits. Most service providers including K telecommunication company tried to adopt the concept of customer relationship management(CRM), and analyze customer's demographic and transactional data statistically in order to understand their customer's behavior. However, managing customer information has still remained at the basic level, and the quality and the quantity of customer data were not enough not only to understand the customers but also to design a strategy for marketing and sales. For example, the currently used 3,074 legal regional divisions, which are originally defined by the government, were too broad to calculate sub-regional customer's service subscription and cancellation ratio. Additional external data such as house size, house price, and household demographics are also needed to measure sales potential. Furthermore, making tables and reports were time consuming and they were insufficient to make a clear judgment about the market situation. In 2009, this company needed a dramatic shift in the way marketing and sales activities, and finally developed a dedicated GIS_based market analysis and sales management system. This system made huge improvement in the efficiency with which the company was able to manage and organize all customer and sales related information, and access to those information easily and visually. After the GIS information system was developed, and applied to marketing and sales activities at the corporate level, the company was reported to increase sales and market share substantially. This was due to the fact that by analyzing past market and sales initiatives, creating sales potential, and targeting key markets, the system could make suggestions and enable the company to focus its resources on the demographics most likely to respond to the promotion. This paper reviews subjective and unclear marketing and sales activities that K telecommunication company operated, and introduces the whole process of developing the GIS information system. The process consists of the following 5 modules : (1) Customer profile cleansing and standardization, (2) Internal/External DB enrichment, (3) Segmentation of 3,074 legal regions into 46,590 sub_regions called blocks, (4) GIS data mart design, and (5) GIS system construction. The objective of this case study is to emphasize the need of GIS system and how it works in the private enterprises by reviewing the development process of the K company's market analysis and sales management system. We hope that this paper suggest valuable guideline to companies that consider introducing or constructing a GIS information system.

LED driver IC design for BLU with current compensation and protection function (전류보상 및 보호 기능을 갖는 BLU용 LED Driver IC설계)

  • Lee, Seung-Woo;Lee, Jung-Gi;Kim, Sun-Yeob
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.10
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    • pp.1-7
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    • 2020
  • In recent years, as LED display systems are actively spread, study on effective control methods for an LED driver for driving the systems has been in progress. The most representative among them is the uniform brightness control method for the LED driver channel. In this paper, we propose an LED driver IC for BLU with current compensation and system protection functions to minimize channel luminance deviation. It is designed for current accuracy within ±3% between channels and a channel current of 150 mA. In order to satisfy the design specifications, the channel amplifier offset was canceled out by a chopping operation using a channel-driving PWM signal. Also, a pre-charge function was implemented to minimize the fast operation speed and luminance deviation between channels. LED error (open, short), switch TR short detection, and operating temperature protection circuits were designed to protect the IC and BLU systems. The proposed IC was fabricated using a Magnachip 0.35-um CMOS process and verified using Cadence and Synopsys' Design Tool. The fabricated LED driver IC has current accuracy within ±1.5% between channels and 150-mA channel output characteristics. The error detection circuits were verified by a test board.

A Study on Design of Smart Home Service Robot McBot II (스마트 홈 서비스 로봇 맥봇II의 설계에 관한 연구)

  • Kim, Seung-Woo;Kim, Hi-Jun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.4
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    • pp.1824-1832
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    • 2011
  • In this paper, a smart home service robot McBot II is newly developed in much more practical and intelligent system than McBot I which we had developed a few years ago. Thus far, vacuum-cleaners have lightened the burden of household chores but the operational labor that vacuum-cleaners entail has been very severe. Recently, a cleaning robot was commercialized to solve but it also was not successful because it still had the problem of mess-cleanup, which pertained to the clean-up of large trash and the arrangement of newspapers, clothes, etc. Hence, we develop a new home mess-cleanup robot McBot II to completely overcome this problem on real environments. The mechanical design and the basic control of McBot II, which performs mess-cleanup function etc. in house, is actually focused in this paper. McBot II is mechanically modeled in the same method that the human works in door by using the waist and the hands. The big-ranged vertical lift and the shoulder joints to be able to forward move are mechanically designed for the operating function as the human's waist when the robot works. The mobility of McBot II is designed in the holonomic mobile robot for the collision avoidance of obstacle and the high speed navigation on the small area in door. Finally, good performance of McBot II, which has been optimally desinged, is confirmed through the experimental results for the control of the robotic body, mobility, arms and hands in this paper.

Learning Material Bookmarking Service based on Collective Intelligence (집단지성 기반 학습자료 북마킹 서비스 시스템)

  • Jang, Jincheul;Jung, Sukhwan;Lee, Seulki;Jung, Chihoon;Yoon, Wan Chul;Yi, Mun Yong
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.179-192
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    • 2014
  • Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

Application for Measurement of Curing Temperature of Concrete in a Construction Site using a Wireless Sensor Network (무선센서네트워크에 의한 콘크리트 양생온도 계측에 관한 현장 적용성 연구)

  • Lee, Sung-Bok;Bae, Kee-Sun;Lee, Do-Heon
    • Journal of the Korea Institute of Building Construction
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    • v.11 no.3
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    • pp.283-291
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    • 2011
  • As the construction industry has recently been transformed by the emergence of ubiquitous and intelligent technology, there have been major changes in the management methods employed. Specifically, next-generation construction management systems have been developed that collect and analyze many pieces of information in real time by using various wireless sensors and networks. The purpose of this study is to understand the current status of Ubiquitous Sensor Networks (USN) in the construction sector, and to gain fundamental data for a system of measuring concrete curing temperature in a construction site that employs a USN. By investigating the application status of USN, it was confirmed that USN has mainly been applied to the maintenance of facilities, safety management, and quality control. In addition, a field experiment in which the curing temperature of concrete was measured using a USN was carried out to evaluate two systems with wireless sensor networks, and the applicability of these systems on site was confirmed. However, it is estimated that the embedded wireless sensor type is affected by metal equipment on site, internal battery of sensor and concrete depth, and studies to provide more stable system by USN are thus required.

Collision Avoidance and Deadlock Resolution for AGVs in an Automated Container Terminal (자동화 컨테이너 터미널에서의 AGV 충돌 방지 및 교착 해결 방안)

  • Kang, Jae-Ho;Choi, Lee;Kang, Byoung-Ho;Ryu, Kwang-Ryel;Kim, Kap-Hwan
    • Journal of Intelligence and Information Systems
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    • v.11 no.3
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    • pp.25-43
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    • 2005
  • In modern automated container terminals, automated guided vehicle (AGV) systems are considered a viable option for the horizontal tansportation of containers between the stacking yard and the quayside cranes. AGVs in a container terminal move rather freely and do not follow fixed guide paths. For an efficient operation of such AGVs, however, a sophisticated traffic management system is required. Although the flexible routing scheme allows us to find the shortest possible routes for each of the AGVs, it may incur many coincidental encounters and path intersections of the AGVs, leading to collisions or deadlocks. However, the computational cost of perfect prediction and avoidance of deadlocks is prohibitively expensive for a real time application. In this paper, we propose a traffic control method that predicts and avoids some simple, but at the same time the most frequently occurring, cases of deadlocks between two AGVs. More complicated deadlock situations are not predicted ahead of time but detected and resolved after they occur. Our method is computationally cheap and readily applicable to real time applications. The efficiency and effectiveness of our proposed methods have been validated by simulation.

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Building an Analytical Platform of Big Data for Quality Inspection in the Dairy Industry: A Machine Learning Approach (유제품 산업의 품질검사를 위한 빅데이터 플랫폼 개발: 머신러닝 접근법)

  • Hwang, Hyunseok;Lee, Sangil;Kim, Sunghyun;Lee, Sangwon
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.125-140
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    • 2018
  • As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.