• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1079-1082
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• 1996

Automatic control systems for warehouse composed of unmanned crane system and vision system. Unmanned crane system is introduced to reject oscillations of a load suspended from a trolley at a moment of its arrival at its target position. And vision system is applied to find out the coordinates of coils on trucks using image processing.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.9-9
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• 2000

Accurate counting and packaging pills is one of the most fundamental works of the pharmaceutical industry. But it is so labor consuming and very hard to be automated. As the pharmaceutical industry is growing bigger, the need of counting and packaging automation is increasing to obtain effective mass production. Precise and quick sensing is required in the counting and processing of quickly dropping pills to improve the productivity. There are many trials for this automation and automatic machine. But the performance of the existing counting machine varies with the size, shape and the dispersion degree of pills In this research, authors design the counting and packing machine of medicinal pills that is more accurate and highly trustworthy After getting analog signal from optical sensor, pill passage is discriminated from chosen characteristic feature using microprocessor.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1105-1110
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• 2013

In this paper, a robot arm capable of recognizing and drawing various line thicknesses is developed. Conventional line drawing robots are not capable of adjusting the thickness of lines. However, to draw faster and to enrich the expression of line drawing robots, it is necessary to adjust line thickness using a brush pen. Simple images are acquired and various line thicknesses are recognized by image processing. Trajectories of lines are generated with distance sorting using thinning and corner point detections for each label. Information on line thickness and trajectory is sent to the controller of a robot arm taking into consideration 2D inverse kinematics. Through this process, the robot arm can draw various lines thicknesses along 2D trajectories with 3 motors. Robot arm for detailed drawing will be studied in the future.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4695-4702
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• 2023

Nuclear power plants play a pivotal role in the global energy infrastructure, fulfilling a substantial share of the world's energy requirements in a sustainable way. The management of these facilities, especially the handling of spent nuclear fuel (SNF), necessitates meticulous inspections to guarantee operational safety and efficiency. However, the prevailing inspection methodologies lean heavily on human operators, which presents challenges due to the potential hazards of the SNF environment. This study introduces the design of a novel Pre-Batched Inspection Strategy (PBIS) that integrates robotic automation and image processing techniques to bolster the inspection process. This methodology deploys robotics to undertake tasks that could be perilous or time-intensive for humans, while image processing techniques are used for precise identification of SNF targets and regulating the robotic system. The implementation of PBIS holds considerable promise in minimizing inspection time and enhancing worker safety. This paper elaborates on the structure, capabilities, and application of PBIS, underlining its potential implications for the future of nuclear energy inspections.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.164-171
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• 2010

We have studied the port-automation system which is requested by the steep increment of cost and complexity for processing the freight. This paper will introduce a new algorithm for navigating and controlling the autonomous Guided Vehicle (AGV). The camera has the optical distortion in nature and is sensitive to the external ray, the weather, and the shadow, but it is very cheap and flexible to make and construct the automation system for the port. So we tried to apply to the AGV for detecting and tracking the lane using the CCD camera. In order to make the error stable and exact, this paper proposes new concept and algorithm for obtaining the error is generated by the Virtual Photo-Sensor Array (VPSA). VPSAs are implemented by programming and very easy to use for the various autonomous systems. Because the load of the computation is light, the AGV utilizes the maximal performance of the CCD camera and enables the CPU to take multi-tasks. We experimented on the proposed algorithm using the mobile robot and confirmed the stable and exact performance for tracking the lane.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.108-117
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• 2024

The selection and recommendation of a suitable job applicant from the pool of thousands of applications are often daunting jobs for an employer. The recommendation and selection process significantly increases the workload of the concerned department of an employer. Thus, Resume Classification System using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process and ease the job of an employer. Moreover, the automation of this process can significantly expedite and transparent the applicants' selection process with mere human involvement. Nevertheless, various Machine Learning approaches have been proposed to develop Resume Classification Systems. However, this study presents an automated NLP and ML-based system that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of Resume Classification Systems and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP & ML techniques for processing & classification of Resumes, the extracted features were tested on nine machine learning models Support Vector Machine - SVM (Linear, SGD, SVC & NuSVC), Naïve Bayes (Bernoulli, Multinomial & Gaussian), K-Nearest Neighbor (KNN) and Logistic Regression (LR). The Term-Frequency Inverse Document (TF-IDF) feature representation scheme proven suitable for Resume Classification Task. The developed models were evaluated using F-Score_M, Recall_M, Precission_M, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume Classification task, the SVM class of Machine Learning algorithms performed better on the study dataset with over 96% overall accuracy. The promising results suggest that NLP & ML techniques employed in this study could be used for the Resume Classification task.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.116-116
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• 2000

This paper describes an experimental embedded tiny web server system that monitors the processing of manufacture using the Internet. The object of this study is developing of an embedded tiny web server that connects the stand-alone machines in factory to the Internet. Using the World Wide Web (WWW), we proffer user-friendly environments to users. Anyone with a web browser may easily access the processing of manufacture in the factory. Through connecting different network system, our web server extends the private networks to the Internet, the global networks. Our embedded tiny web server is ideal for process control, building and facility management system, factory automation and even home automation.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.160-163
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• 1993

In this paper, design of an automatic grinding robot system for car brazing bead is introduced. Car roof and side panels are joined using brazing, and then the brazing bead is processed so that the bead is invisible after painting. Up to now the grinding process is accomplished manually. The difficulties in automation of the grinding process are induced by variation of position and shape of the bead and non-uniformity of the grinding area due to surface deformation. For each car, the grinding area including the brazing bead is sensed and then modeled using a 2-D optical sensor system. Using these model data, the position and the direction of discrete points on the car, body surface are obtained to produce grinding path for a 6 degrees of freedom grinding robot. During the process, it is necessary to sense the reaction forces continuously to prepare for the unexpected circumstances. In addition, to meet the line cycle time it is necessary to reduce the required time in sensing, signal processing, modeling, path planning and data transfer by utilizing real-time communication of the information. The key technique in the communication and integration of the complex information is obtaining in-field reliability. This automatic grinding robot system may be regarded as a jump in the intelligent robot processing technique.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.707-711
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• 2007

An observer-based fault tolerant control (FTC) method is proposed for constrained switched systems (CSS) with input constraints. A family of Lyapunov-based bounded controllers are designed to ensure that, whenever actuator faults occur at the dwell time period of each continuous mode, the mode is always within its corresponding stability region. A set of switching laws are designed to guarantee the asymptotic stability of the overall CSS. The fixed stability regions on which the FTC method is based are also relaxed by the proposed variable stability regions. An example of CPU processing illustrates the effectiveness of proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.923-928
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• 1990

This paper describes the design and implementation of a real-time, high-precision vision system and its application to SMT(surface mounting technology) automation. The vision system employs a 32 bit MC68030 as a main processor, and consists of image acquisition unit. DSP56001 DSP based vision processor, and several algorithmically dedicated hardware modules. The image acquisition unit provides 512*480*8 bit image for high-precision vision tasks. The DSP vision processor and hardware modules, such as histogram extractor and feature extractor, are designed for a real-time excution of vision algorithms. Especially, the implementation of multi-processing architecture based on DSP vision processors allows us to employ more sophisticated and flexible vision algorithms for real-time operation. The developed vision system is combined with an Adept Robot system to form a complete SMD system. It has been found that the vision guided SMD assembly system is able to provide a satisfactory performance for SND automation.