• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.433-439
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• 2010

This paper proposes a beacon color code scheduling algorithm for the localization of multiple robots in a multi-block workspace. With the developments of intelligent robotics and ubiquitous technology, service robots are applicable for the wide area such as airports and train stations where multiple indoor GPS systems are required for the localization of the mobile robots. Indoor localization schemes using ultrasonic sensors have been widely studied due to its cheap price and high accuracy. However, ultrasonic sensors have some shortages of short transmission range and interferences with other ultrasonic signals. In order to use multiple robots in wide workspace concurrently, it is necessary to resolve the interference problem among the multiple robots in the localization process. This paper proposes an indoor localization system for concurrent multiple robots localization in a wide service area which is divided into multi-block for the reliable sensor operation. The beacon color code scheduling algorithm is developed to avoid the signal interferences and to achieve efficient localization with high accuracy and short sampling time. The performance of the proposed localization system is verified through the simulations and the real experiments.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.31-39
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• 2019

A robot usually adopts ANN (artificial neural network)-based object detection and instance segmentation algorithms to recognize objects but creating datasets for these algorithms requires high labeling costs because the dataset should be manually labeled. In order to lower the labeling cost, a new scheme is proposed that can automatically generate a training images and label them for specific objects. This scheme uses an instance segmentation algorithm trained to give the masks of unknown objects, so that they can be obtained in a simple environment. The RGB images of objects can be obtained by using these masks, and it is necessary to label the classes of objects through a human supervision. After obtaining object images, they are synthesized with various background images to create new images. Labeling the synthesized images is performed automatically using the masks and previously input object classes. In addition, human intervention is further reduced by using the robot arm to collect object images. The experiments show that the performance of instance segmentation trained through the proposed method is equivalent to that of the real dataset and that the time required to generate the dataset can be significantly reduced.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1281-1286
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• 2018

The sea cucumber, which is distributed over 1,500 species worldwide, is a highly value-added variety that has been considered an important source of marine resources in many countries for a long period of time. Most of the research on sea cucumbers involves the effectiveness of food and its extractions; however, there was no research on the extraction of sea cucumbers. In response, this research suggested a boundary detection algorithm to extract the special spot of sea cucumbers Therefore, in order to capture a large quantity of high value-added in sea cucumbers and we believe that they will be a great help to the sea cucumber recognition program in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.117-128
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• 2008

Compared with the existing bar code system, RFID system has lots of advantages such as it identifies automatically massive objects. We might anticipate RFID technology will be a substitution for an optical bar code system in the near future. However, their feature that uses radio waves may cause various security problems. Many kinds of solutions have been researched to overcome these security problems. In this paper, we analyze the previous proposed protocols. And then, we categorize RFID authentication into two types according to the synchronization requirement between a Back-end Database and a Tag. In addition, we introduce the previous proposed approaches to tag search problem in RFID authentication. And we propose an efficient method which provides fast tag search by using membership test algorithm, a Bloom filter.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.461-466
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• 2021

본 연구에서는 DECO(Dictionnaire Electronique du COreen) 한국어 전자사전과 LGG(Local-Grammar Graph)에 기반한 반자동 언어데이터 증강(Semi-automatic Symbolic Propagation: SSP) 방식에 입각하여, 핀테크 분야의 CS(Customer Service) 챗봇 NLU(Natural Language Understanding)을 위한 주석 학습 데이터를 효과적으로 생성하고, 이를 기반으로 RASA 오픈 소스에서 제공하는 DIET(Dual Intent and Entity Transformer) 아키텍처를 활용하여 핀테크 CS 챗봇 NLU 시스템을 구현하였다. 실 데이터을 통해 확인된 핀테크 분야의 32가지의 토픽 유형 및 38가지의 핵심 이벤트와 10가지 담화소 구성에 따라, DECO-LGG 데이터 생성 모듈은 질의 및 불만 화행에 대한 양질의 주석 학습 데이터를 효과적으로 생성하며, 이를 의도 분류 및 Slot-filling을 위한 개체명 인식을 종합적으로 처리하는 End to End 방식의 멀티태스크 트랜스포머 모델 DIET로 학습함으로써 DIET-only F1-score 0.931(Intent)/0.865(Slot/Entity), DIET+KoBERT F1-score 0.951(Intent)/0.901(Slot/Entity)의 성능을 확인하였으며, DECO-LGG 기반의 SSP 생성 데이터의 학습 데이터로서의 효과성과 함께 KoBERT에 기반한 DIET 모델 성능의 우수성을 입증하였다.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2022.09a
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• pp.59-59
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• 2022

Vulpia octoflora (Walter) Rydb.가 경기도 여주시 강천리 일대에서 발견되었다. 본 종은 북아메리카 원산으로 알려져 있으며, 최근 호주와 일본, 우크라이나에서 침입외래식물로 보고된 바 있다. V. octoflora는 주로 건조한 건조한 모래나 자갈 모래밭에 자라는 잡초성 식물로, 도로변을 따라 개방된 지역이나 인위적 교란 지역에서 빈번하게 발견된다. 학자에 따라 북아메리카 지역에 분포하는 개체들의 지리적 분포와 형태 변이를 근거로 종하분류군으로 세분화하기도 하지만, 형태 변이의 일관성 부족으로 인해 종내 변이로 인식하여 통합하여 처리하는 것이 타당하게 여겨진다. 본 종은 최근에 국내에 보고된 침입외래식물인 들묵새아재비와 유사하나, 소수당 달리는 소화의 수가 더 많고, 호영 정단부의 까락의 길이가 짧은 것으로 명확히 구분된다. 좀들묵새에 대한 생태계 위해성 연구는 진행된 바 없으나, 최초 발견지인 여주시 강천섬 일대는 멸종위기 2등급종인 단양쑥부쟁이의 자생지이기 때문에, 새롭게 유입된 외래식물의 잠재적 생태 교란에 따른 위해성 평가 및 확산 방지를 위한 모니터링이 필요할 것으로 여겨진다. 본 연구에서는 주요 형질에 대한 기재와, 지리적 분포, 도해도, 화상자료와 국내에 분포하는 동속 분류군과의 검색표를 제공하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.19-29
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• 2006

As the security of personal information is becoming more important in mobile phones, we are starting to apply iris recognition technology to these devices. In conventional iris recognition, magnified iris images are required. For that, it has been necessary to use large magnified zoom & focus lens camera to capture images, but due to the requirement about low size and cost of mobile phones, the zoom & focus lens are difficult to be used. However, with rapid developments and multimedia convergence trends in mobile phones, more and more companies have built mega-pixel cameras into their mobile phones. These devices make it possible to capture a magnified iris image without zoom & focus lens. Although facial images are captured far away from the user using a mega-pixel camera, the captured iris region possesses sufficient pixel information for iris recognition. However, in this case, the eye region should be detected for accurate iris recognition in facial images. So, we propose a new fast iris detection method, which is appropriate for mobile phones based on corneal specular reflection. To detect specular reflection robustly, we propose the theoretical background of estimating the size and brightness of specular reflection based on eye, camera and illuminator models. In addition, we use the successive On/Off scheme of the illuminator to detect the optical/motion blurring and sunlight effect on input image. Experimental results show that total processing time(detecting iris region) is on average 65ms on a Samsung SCH-S2300 (with 150MHz ARM 9 CPU) mobile phone. The rate of correct iris detection is 99% (about indoor images) and 98.5% (about outdoor images).

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.51-55
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• 2017

In this paper, we designed a LBS-based smart platform for Lifelog service that can utilize the other's lifelog information. The conventional Lifelog service means that the system records the daily activities of the smart device user so the user can retrieve the early-recorded information later. The proposed Lifelog service platform uses the GPS/UFID location information and the various information extracted from the image as the lifelog data. Further, the proposed Lifelog platform using DB can provide the user with the Lifelog data recorded by the other service user. The system usually provide the other's Lifelog data within the 500m distance from the user and the range of distance can be adjustable. The proposed smart platform based on image recognition for Lifelog can acquire the image from the smart device directly and perform the various image recognition processing to produce the useful image attributes. And it can store the location information, image data, image attributes and the relevant web informations on the database that can be retrieved by the other use's request. The attributes stored and managed in the image information database consist of the followings: Object ID, the image type, the capture time and the image GPS coordinates. The image type attribute has the following values: the mountain, the sea, the street, the front of building, the inside of building and the portrait. The captured image can be classified into the above image type by the pattern matching image processing techniques and the user's direct selection as well. In case of the portrait-attribute, we can choose the multiple sub-attribute values from the shirt, pant, dress and accessory sub-attributes. Managing the Lifelog data in the database, the system can provide the user with the useful additional services like a path finding to the location of the other service user's Lifelog data and information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.750-762
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• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.

• Korean Journal of Plant Taxonomy
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• v.34 no.3
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• pp.221-244
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• 2004

Prunus sargentii complex of subgenus Cerasus is an Eastem Asiatic plant group that exhibits a broad range of morphological variation and includes P. takesimensis, P. yedosensis, P. verecunda, and P. sargentii. In this study, a morphological analysis was undertaken to determine whether the observed morphological variation was primarily attributable to morphological discontinuities among the taxa. P. sargentii, which distributed eastem area in Korea, northern area in Japan and far east Russia had umbel like inflorescence and additionally was characterized by sticky bud and leaf twigs, compared with P. serrulata complex. Also, P. verecunda in Korea and Japan was characterized by umbel like inflorescence and presence of hair in leaf, petiole and pedicel, and was treated as a variety of P. sargentii. Evidence obtained from multivariate morphometric analyses indicated that the entity of P. takesimensis formed a cohesive group somewhat distinct from P. sargenti.. Especially, P. takesimensis was characterized by relatively small flowers (26-32mm in diameter) and many flowers [(2)3-5] per umbel inflorescence, compared with P. sargentii (34-48mm and 2(3) per inflorescence) and should be recognized as an independent and endeImic taxon in Korea. Additionally, P. yedosensis, which was known to have umbel inflorescence (short peduncle type) with pubescent style based on the type specimen, was comprised of corymb inflorescence (long peduncle type) as well. The morphological differentiation between these two types of P. yedosensis was not considered sufficient to warrant recognition of specific status because of the putative hybrid origin, no distinctive geographical distribution pattern, and existence of various peduncle length on Island Jeju-do of Korea.