• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.73-81
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• 2024

Recently, mobile manipulators have been utilized in agriculture industry for weed removal and harvest automation. This paper proposes a domain adaptive fruit detection method for harvest automation, by utilizing OWL-ViT model which is an open-vocabulary object detection model. The vision-language model can detect objects based on text prompt, and therefore, it can be extended to detect objects of undefined categories. In the development of deep learning models for real-world problems, constructing a large-scale labeled dataset is a time-consuming task and heavily relies on human effort. To reduce the labor-intensive workload, we utilized a large-scale public dataset as a source domain data and employed a domain adaptation method. Adversarial learning was conducted between a domain discriminator and feature extractor to reduce the gap between the distribution of feature vectors from the source domain and our target domain data. We collected a target domain dataset in a real-like environment and conducted experiments to demonstrate the effectiveness of the proposed method. In experiments, the domain adaptation method improved the AP50 metric from 38.88% to 78.59% for detecting objects within the range of 2m, and we achieved 81.7% of manipulation success rate.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.167-176
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• 2024

Lip-reading is the task of inferring the speaker's utterance from silent video based on learning of lip movements. It is very challenging due to the inherent ambiguities present in the lip movement such as different characters that produce the same lip appearances. Recent advances in deep learning models such as Transformer and Temporal Convolutional Network have led to improve the performance of lip-reading. However, most previous works deal with English lip-reading which has limitations in directly applying to Korean lip-reading, and moreover, there is no a large scale Korean lip-reading dataset. In this paper, we introduce the first large-scale Korean lip-reading dataset with more than 120 k utterances collected from TV broadcasts containing news, documentary and drama. We also present a preprocessing method which uniformly extracts a facial region of interest and propose a transformer-based model based on grapheme unit for sentence-level Korean lip-reading. We demonstrate that our dataset and model are appropriate for Korean lip-reading through statistics of the dataset and experimental results.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.58-65
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• 2006

Accurate and efficient monitoring of dynamically changing environments is one of the most important requirements for ubiquitous network environments. Ubiquitous computing provides intelligent environments which are aware of spatial conditions and can provide timely and useful information to users or devices. Also, the growth of embedded systems and wireless communication technology has made it possible for sensor network environments to develop on a large scale and at low-cost. In this paper, we present the design and implementation of a monitoring system that collects, analyzes, and controls the status information of each sensor, following sensor data extracted from each sensor node. The monitoring system adopts Web technology for the implementation of a simple but efficient user interface that allows an operator to visualize any of the processes, elements, or related information in a convenient graphic form.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.10-14
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• 2013

High precision machining technology has become one of the important parts in the development of a precision machine. Such a machine requires high precision positioning as well as high speed on a large workspace. For machining systems having a high precision positioning with a long stroke, it is necessary to examine the repeatability of reference position decision. Though ball-screw driven linear stages equipped linear scale have high precision feed drivers and a long stroke, they have some limitations for reference position decision if they have not equipped the accurate home sensor. This study is performed to experimentally examine the repeatability for home position decision of a magnetic sensor as a home switch of ball-screw driven linear stage by using capacitance probe.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• Asia pacific journal of information systems
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• v.4 no.2
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• pp.83-130
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• 1994

Software development of large scale program such as Operating System or University Total Information System is lengthy and costly process. In order to reduce cost, time and risk, there is currentry general acceptance of the need for Software Reuse System during the whole development cycles. In this paper, (from a practical point of view), the problem of existing reuse system methodology is analyzed and an implement method of software reuse system is presented. Also using this method Application Program Reuse System(APRS) which supports all phase of software life cycles is designed and implemented. This application program reuse system which is based on common language is considerably shown to reduce communication Error of requirement specification between systems analyst and end-user.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.398-404
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• 2012

A fault detection process is necessary for high integrity systems like satellites, missiles and aircrafts. Especially, the satellite has to be expected to detect faults autonomously because it cannot be fixed by an expert in the space. Faults can cause critical errors to the entire system and the satellite does not have sufficient computation power to operate a large scale fault management system. Thus, a fault detection method, which has less computational burden, is required. In this paper, we proposed a modified PCA (Principal Component Analysis) as a powerful fault detection method of redundant IMU (Inertial Measurement Unit). The proposed method combines PCA with the parity space approach and it is much more efficient than the others. The proposed fault detection algorithm, modified PCA, is shown to outperform fault detection through a simulation example.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.15-20
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• 2005

We developed a database system to enable efficient and high-throughput transposon analyses in rice. We grow large-scale mutant series of rice by taking advantage of an active MITE transposon mPing, and apply the transposon display method to them to study correlation between genotypes and phenotypes. But the analytical phase, in which we find mutation spots from waveform data called fragment profiles, involves several problems from a viewpoint of labor amount, data management, and reliability of the result. As a solution, our database system manages all the analytical data throughout the experiments, and provides several functions and well designed web interfaces to perform overall analyses reliably and efficiently.

• IE interfaces
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• v.15 no.4
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• pp.460-473
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• 2002

The objective of this paper is to design a Goal Alternatives Disposition System having three main subsystems for setting, evaluating and selecting goal alternatives. For setting of goal alternatives, System Alternatives Tree(SAT) structure will be developed, which has a computation algorithm for setting decision alternatives by the concept of System Priority Number(SPN). For evaluating and selecting of goal alternatives; First, Normative and Exploratory Priority Indices which consider technical performance to the goal, cost and feasibility are developed respectively. Second, Integrated Priority Index is built up to determine the total priority of the Goal Alternatives Disposition(GAD) system. For the design and verification of the GAD system, technological forecasting structure theory, systems engineering methodology will be used.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.323-326
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• 1995

During a fast decade, an automatic control technology makes an aggressive improvement with the developments of computer and communication technology. In large scale and complicated systems, an autonomous decentralized control system is required in which the sub-systems must have some ability such that the self-judgement and self-performance functions. In this paper, we propose an algorithm to realized these functions using micro mobile robot which is applied to a control of a werehouse. The proposed algorithm is based on performance index, and the selecting rules of the task between the sub-systems are induced by the index. Also, it is effected by weighting function which is determined by environment and kind of works. To verify the effectiveness of this algorithm, we develop the simulator to implement the autonomous decentralized control and apply to the micro mobile robot on the PC machine.