• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.143-149
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• 2016

Recent accidents caused by toxic chemicals and the social problems caused by frequent. As of 2010, there are more than 100,000 types of deadly toxic chemicals being distributed throughout Korea, and severely intoxicated patients along with an enormous number of patients can be induced at the time of an accident involving deadly toxic chemicals. Internationally, the seriousness of large-scale disasters due to a NBC disaster (nuclear, biologic and chemical disaster) is being highlighted as well. So, we obtain the information of the RFID tag attached to a glass bottle with containing the toxic chemical to transfer the data to the smart device has been studied a system that can monitor the status of the toxic chemical in real time. The proposed system is the information was sent to the main system using a zigbee communication by recognizing the tag vial containing the toxic chemical with the 13.56MHz bandwidths good permeability. User may check the information in real time by utilizing the smart device. However, the error of the system for managing the toxic chemical generates a result that can not be predicted. Failure of the system was detecting the error by using a comparator as this can cause an error. And the detected error proposed a duplex system so that they do not affect the overall system.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.635-641
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• 2016

In order to drive a hybrid propulsion device which combines an engine and an electric propulsion unit, battery packs that contain dozens of unit cells consisting of a lithium-based battery are used to maintain the power source. Therefore, it is necessary to more strictly manage a number of battery cells at any given time. In order to manage battery cells, generally voltage, current, and temperature data under load condition are monitored from a personal computer. Other important elements required to analyze the condition of the battery are the internal resistances that are used to judge its state-of-health (SOH) and the open-circuit voltage (OCV) that is used to check the battery charging state. However, in principle, the internal resistances cannot be measured during operation because the parallel equivalent circuit is composed of internal loss resistances and capacitance. In most energy storage systems, battery management system (BMS) operations are carried out by using data such as voltage, current, and temperature. However, during operation, in the case of unexpected battery cell failure, the output voltage of the power supply can be changed and propulsion of the hybrid vehicle and vessel can be difficult. This paper covers the implementation of a high safety battery management system (HSBMS) that can estimate the OCV while the device is being driven. If a battery cell fails unexpectedly, a DC power supply with lithium iron phosphate can keep providing the load with a constant output voltage using the remainder of the batteries, and it is also possible to estimate the internal resistance.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.489-496
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• 2002

This study proposes a new polling algorithm allowing dynamic change in polling period based on line utilization prediction. Polling is the most important function in network monitoring, but excessive polling data causes rather serious congestion conditions of network when network is In congestion. Therefore, existing multiple polling algorithms decided network congestion or load of agent with previously performed polling Round Trip Time or line utilization, chanced polling period, and controlled polling traffic. But, this algorithm is to change the polling period based on the previous polling and does not reflect network conditions in the current time to be polled. A algorithm proposed in this study is to predict whether polling traffic exceeds threshold of line utilization on polling path based on the past data and to change the polling period with the prediction. In this study, utilization of each line configuring network was predicted with AR model and violation of threshold was presented in probability. In addition, suitability was evaluated by applying the proposed dynamic polling algorithm based on line utilization prediction to the actual network, reasonable level of threshold for line utilization and the violation probability of threshold were decided by experiment. Performance of this algorithm was maximized with these processes.

• Journal of Wetlands Research
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• v.22 no.4
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• pp.312-320
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• 2020

Various LIDs with natural water circulation function are applied to reduce urban environmental problems and environmental impact of development projects. However, excessive Infiltration and evaporation of LID facilities dry the LID internal soil, thus reducing plant and microbial activity and reducing environmental re duction ability. The purpose of this study was to develop a real-time measurement system with complex sensors to derive the management plan of LID facilities. The test of measurable sensors and Internet of Things (IoT) application was conducted in artificial wetlands shaped in acrylic boxes. The applied sensors were intended to be built at a low cost considering the distributed LID and were based on Arduino and Raspberry Pi, which are relatively inexpensive and commercialized. In addition, the goal was to develop complex sensor measurements to analyze the current state o f LID facilities and the effects of maintenance and abnormal weather conditions. Sensors are required to measure wind direction, wind speed, rainfall, carbon dioxide, Micro-dust, temperature and humidity, acidity, and location information in real time. Data collection devices, storage server programs, and operation programs for PC and mobile devices were developed to collect, transmit and check the results of measured data from applied sensors. The measurements obtained through each sensor are passed through the Wifi module to the management server and stored on the database server in real time. Analysis of the four-month measurement result values conducted in this study confirmed the stability and applicability of ICT technology application to LID facilities. Real-time measured values are found to be able to utilize big data to evaluate the functions of LID facilities and derive maintenance measures.

• Proceedings of the CALSEC Conference
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• 1999.11a
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• pp.159-168
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• 1999

오늘날 우리 나라가 당면한 최우선 경제과제중 하나는 물류부문의 혁신을 통한 국가경쟁력 강화라고 할 수 있으며, 이를 위해 정부도 1993년 물류체계 개선을 위한 장기구상으로 ‘화물유통체계 개선 10개년 기본계획’을 수립하여 적극 추진 중에 있다. 그러나 이러한 노력에도 불구하고 PORT-MIS사용자를 상대로 한 설문조사에서는 선박입출항 업무 관련 서류의 40%, 항만시설 사용 업무와 관련된 서류의 31%, 하역업무 관련 서류의 10%만이 EDI를 활용하고 있었다. EDI 활용이 저조한 사유로는 전송시간이 많이 걸리며, EDI 소프트웨어가 작동되지 않으며, 수신확인이 되지 않기 때문이라 응답을 하였다. 이처럼 오늘날 항만물류산업이 겪고 있는 물류 데이타 흐름의 단절적 현상은 시간이 흐를수록 해결될 기미가 보이고 있지 않다. 따라서 본 논문에서는 우리 나라가 겪고 있는 물류관련 업무를 한번의 데이터 입력으로 해결할 수 있는 원스톱 서비스 시스템개발을 목표로 우선 PORT-MIS EDI 업무를 처리할 수 있는 시스템을 구축하였다. 이는 향후 화주, 운송사, 선사, 포워더, 창고업자, 하역회사, 철도청, 화물터미널, 컨테이너 터미널, 해양수산청, 관세청, 출입국관리사무소, 검역소 사이에 서로 교환되는 적하목록, Booking List, 컨테이너 Pick up정보, 위험물 정보, COPINO 정보를 비롯하여 대 관세청 신고 등 수출컨테이너 화물업무의 전반적인 영역으로까지 쉽게 확대할 수 있을 것이다. 본 연구결과 구축된 시스템은 원천정보를 중앙의 통합데이터베이스에 저장하여 이를 사용자의 요구에 의해 인터넷을 통해 전달하는 FTP와 웹 EDI 방식을 결합한 하이브리드 형태이다.인터넷으로 주문처리하고, 신속 안전한 배달을 기대한다. 더불어 고객은 현재 자신의 물건이 배달되는 경로를 알고싶어 한다. 웹을 통해 물건을 주문한 고객이 자신이 물건의 배달 상황을 웹에서 모니터링 한다면 기업은 고객으로 공간적인 제약으로 인한 불신을 불식시키는 신뢰감을 주게 된다. 이러한 고객서비스 향상과 물류비용 절감은 사이버 쇼핑몰이 전국 어디서나 우리의 안방에서 자연스럽게 점할 수 있는 상황을 만들 것이다.SP가 도입되어, 설계업무를 지원하기위한 기본적인 시스템 구조를 구상하게 된다. 이와 함께 IT Model을 구성하게 되는데, 객체지향적 접근 방법으로 Model을 생성하고 UML(Unified Modeling Language)을 Tool로 사용한다. 단계 4)는 Software Engineering 관점으로 접근한다. 이는 최종산물이라고 볼 수 있는 설계업무 지원 시스템을 Design하는 과정으로, 시스템에 사용될 데이터를 Design하는 과정과, 데이터를 기반으로 한 기능을 Design하는 과정으로 나눈다. 이를 통해 생성된 Model에 따라 최종적으로 Coding을 통하여 실제 시스템을 구축하게 된다.the making. program and policy decision making, The objectives of the study are to develop the methodology of modeling the socioeconomic evaluation, and build up the practical socioeconomic evaluation model of the HAN projects including scientific and technologica

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1318-1327
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• 2012

With the recent increased risk of livestock disease spread and human infection, livestock disease control has become very important. Consequently, there has been an increased attention on an implantable real-time monitoring and traceability system for individual cattle. Therefore, we have developed a robust monitoring and traceability system based on an implantable MFAN/RFID sensor tag. Our design combines the MFAN technology that is capable of robust wireless communication within cattle sheds and the 900MHz RFID technology that is capable of wireless communication without battery. In MFAN/RFID implantable sensor tag monitoring system, UHF sensor tag is implanted under the skin and accurately monitors the body temperature and biological changes without being affected by external environment. In order to acquire power needed by the tag, we install a MFAN/RFID tranceiver on the neck of cattle. The MFAN coordinator passes through the MFAN node and the RFID-reader-combined MFAN/RFID transceiver and transmits/receives the data and power for the sensor tag. The data stored in the MFAN coordinator is transmitted via the internet to the livestock history monitoring system, where it is stored and managed. By developing this system, we hope to alleviate the problems related to livestock disease control.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.457-464
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• 2019

The weight of pig is one of the main factors in determining the health and growth state of pigs, their shipment, the breeding environment, and the ration of feed, and thus measuring the pig's weight is an important issue in productivity perspective. In order to estimate the pig's weight by using the number of pig's pixels from images, acquired from a Top-view camera, the posture determining and the head removal from images are necessary to measure the accurate number of pixels. In this research, we propose the fast and accurate method to determine the pig's posture by using a fast image processing technique, find the head location by using a fast deep learning technique, and remove pig's head by using light weighted image processing technique. First, we determine the pig's posture by comparing the length from the center of the pig's body to the outline of the pig in the binary image. Then, we train the location of pig's head, body, and hip in images using YOLO(one of the fast deep learning based object detector), and then we obtain the location of pig's head and remove an outside area of head by using head location. Finally, we find the boundary of head and body by using Convex-hull, and we remove pig's head. In the Experiment result, we confirmed that the pig's posture was determined with an accuracy of 0.98 and a processing speed of 250.00fps, and the pig's head was removed with an accuracy of 0.96 and a processing speed of 48.97fps.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.654-661
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• 2021

Air pollution caused by industrial development has become a level that can seriously threaten human health. In general, indoor air pollution is considered to be lower than outdoors, but modern people live indoors most of the time, thus it is essential to keep the indoor air quality comfortable in order to take care of one's own health and improve the quality of life. Therefore, the development of an indoor environment management platform using Internet of Things and data processing technology, which is currently drawing attention, is considered a very meaningful study. In this paper, we designed an IoT-based management platform that can remotely monitor and control indoor environments. In addition, the functions of the IoT terminal, gateway, and data server constituting the platform were implemented using open source and open libraries, and all functional operations were also verified. In particular, the IoT terminal and the gateway in this paper exchange data using BLE communication, so they can operate with relatively low power and since the gateway uses the BLE Advertising mode, it has the advantage of automatically recognizing IoT terminals that have not been previously configured.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.