• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.12
• /
• pp.2820-2827
• /
• 2015

HSMS communication system using low-cost micro controller units(MCUs) is an essential technique for online semiconductor equipment system developments. It is intended as an alternative to SEMI E4 (SECS-I) for applications where higher speed communication is needed and the facilitated hardware setup is convenient. In this paper, an HSMS communication system using low-cost MCUS is designed and implemented. Using a MCU with a low price but high-performance as a main board, a module which processes HSMS communication is designed, and a circuit is designed to process BCR independently with a microminiature MCU. To convert tag data which is recognized from BCR into data based on HSMS communication protocol, SECS-II message is designed. Lastly, an HSMS communication system is implemented based on these designs. A low-cost HSMS communication module developed in this study can be applied in realtime monitoring and controlling system for semiconductor processes.

• The Journal of the Korea Contents Association
• /
• v.10 no.8
• /
• pp.451-460
• /
• 2010

The purpose of this paper is to present the effective operation method of cyber home learning system 2.0. Cyber home learning system 2.0 which plays an important role to produce and share data of internet users establishing user-centered internet environment is recently introduced as web 2.0 is beginning to appear. This research is based on the case of the operation on cyber home learning system, research literature of web 2.0 as well as expert consulting and performance test. After doing this research, cyber home learning system 2.0 can bring enormous educational effect when it has online education using web-based discussion tool and long distance consulting linking with off line school education. Redundant system configuration, the distributed processing also may be provided by the service was smooth. Moreover, it demands monitoring team consisting of student, parents and teacher in order to provide developmental service.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.6
• /
• pp.517-524
• /
• 2017

The objective of this research is to improve the efficiency of data collection from many machine components on smart factory floors using IoT(Internet of things) techniques and cloud platform, and to make it easy to update outdated diagnostic schemes through online deployment methods from cloud resources. The short-term analysis is implemented by a micro-controller, and it includes machine-learning algorithms for inferring snapshot information of the machine components. For long-term analysis, time-series and high-dimension data are used for root cause analysis by combining a cloud platform and multivariate analysis techniques. The diagnostic results are visualized in a web-based display dashboard for an unconstrained user access. The implementation is demonstrated to identify its performance in data acquisition and analysis for rotating machinery.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.2
• /
• pp.138-146
• /
• 2011

With the increased use of GPS in the field of various applications including surveying, the request for fast and precise positional information has increased. Several countries such as USA, Canada, and Australia have already been operating Internet-based automatic GPS data analysis system using e-mail and FTP. Expanding GPS market, it is necessary to establish automatic GPS baseline processing system that is accessible via Internet. The system developed in this study is operating on the web, and it allows the users to access easily regardless of time and place. The main processing engines are Bernese V5.0 and PAGES. They process user data with three GPS CORS(Continuously Operating Reference Station), and then send the report to the users through e-mail. This system allows users to process high accurate GPS data easily. It is expected that this system will be used for various GPS applications such as monitoring large-scale structures and providing spatial information services in private sector.

• Smart Structures and Systems
• /
• v.15 no.4
• /
• pp.1121-1137
• /
• 2015

This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.

• Structural Monitoring and Maintenance
• /
• v.5 no.2
• /
• pp.231-242
• /
• 2018

Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.

• Journal of Korean Society for Atmospheric Environment
• /
• v.31 no.4
• /
• pp.319-329
• /
• 2015

The characteristics of aerosol light extinction were investigated by comparing measured and calculated extinction coefficient to understand the contribution of air pollutants on visibility impairment for data during 4 months (Jan~ April), 2014. The integrated nephelometer and aethalometer system were installed to measure the scattering and absorption coefficients of aerosol as well as BAM 1020, MARGA, semi-continuous OCEC analyzer, and online-XRF to calculate the extinction coefficient. The IMPROVE_2005 equation was used to determine the contributions of different chemical components on visibility impairment in $PM_{2.5}$ and $PM_{10}$ due to highest correlation with measured data. Sulfate, nitrate, and organic mass by carbon (OMC) of fine aerosol were the major contributors affecting on visibility impairment. Total contributions to light extinction were calculated as $631.0Mm^{-1}$ for the worst-case and $64.4Mm^{-1}$ for the best-case. The concentrations of aerosol component for the worst-case were 38.4 times and 45.5 times larger than those of the best-case for $(NH_4)_2SO_4$ and $NH_4NO_3$, respectively. At lower visibility condition, in which extinction coefficient was higher than $400Mm^{-1}$, extinction coefficient varied according to the relative humidity variation regardless of $PM_{2.5}$.

• Journal of information and communication convergence engineering
• /
• v.12 no.3
• /
• pp.168-172
• /
• 2014

In this paper, we propose an algorithm that can efficiently detect and monitor multiple ships in real-time. The proposed algorithm uses morphological operations and edge information for detecting and tracking ships. We used smoothing filter with a $3{\times}3$ Gaussian window and luminance component instead of RGB components in the captured image. Additionally, we applied Sobel operator for edge detection and a threshold for binary images. Finally, object labeling with connectivity and morphological operation with open and erosion were used for ship detection. Compared with conventional methods, the proposed method is meant to be used mainly in coastal surveillance systems and monitoring systems of harbors. A system based on this method was tested for both stationary and non-stationary backgrounds, and the results of the detection and tracking rates were more than 97% on average. Thousands of image frames and 20 different video sequences in both online and offline modes were tested, and an overall detection rate of 97.6% was achieved.

• Journal of Advanced Navigation Technology
• /
• v.15 no.6
• /
• pp.1126-1131
• /
• 2011

As the recent paradigm of education changes to become learner-centered, there is an increasing interest in project based class as one of new teaching models. Universities are accepting this change and aiming at fostering human resources of next generations, who are able to create creative changes, and studies are being actively conducted to that end. This study suggested a learner-centered teaching model which minimizes intervention of teachers in conducting projects of main text contents in designed subjects. This study suggested support system for the suggested model project-based class, team organization method, various interaction methods of learners, and team work monitoring method of teachers. And the suggestions were designed and realized through project management applications using smart phones which are being used by a rapidly growing number of people recently.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.6
• /
• pp.1125-1136
• /
• 2010

Lately there exist increasing demands for online abnormality monitoring over trajectory stream, which are obtained from moving object tracking devices. This problem is challenging due to the requirement of high speed data processing within limited space cost. In this paper, we present a FADA (Fuzzy Anomaly Detection Algorithm) which constructs normal profile by computing mobility feature information from the GPS (Global Positioning System) logs of mobile devices in MANETs (Mobile Ad-hoc Networks), computes a fuzzy dissimilarity between the current mobility feature information of the mobile device and the mobility feature information in the normal profile, and detects effectively the anomaly behaviors of mobile devices on the basis of the computed fuzzy dissimilarity. The performance of proposed FADA is evaluated through simulation.