• Bulletin of the Korean Chemical Society
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• v.28 no.3
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• pp.373-378
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• 2007

A micro organism Agrobacterium tumifacient as an immobilized cell on a solid support was presented as a new biosorbent in a simple and sensitive spectrophotometry determination of Ni(II) in various samples using 4-hydroxy benzaldehyde-4-bromophenyl hydrazone as a color developing agent (λmax 497 nm) at pH 4.0 ± 0.2. Beer's law was obeyed over the range of 0.01-0.1 μg L-1. The molar absorptivity and Sandell's sensitivity were 1.285 × 105 L mol-1cm-1 and 0.007245 μg cm-2 respectively. Under these conditions, the preconcentration factor obtained was 82, and the detection limit achieved was 0.05 μg L-1. The detailed study of various interfering ions made the method more sensitive and selective. The recovery of Ni(II) from various samples range from 97.75 to 99.35%. The present method was successfully applied for the determination of Ni(II) in spiked, natural water and alloy samples. The proposed method was compared with reported methods in terms of Student's ‘t'-test and Variance ratio ‘f'-test which indicates that there is no significant difference between proposed and literature method at 95% confidence level.

• Journal of Environmental Science International
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• v.18 no.10
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• pp.1079-1088
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• 2009

The statistics of monitoring on soil quality is a report statistics which is made on the basis of Article 15, Environment Strategy Basic Law and Article 5, Soil Environment Conservation Law. This study was conducted according to quality assessment of Korea National Statistical Office. The assessment of quality infrastructure advised that the authority bring up and increase completely responsible officer and secure the budget. The assessment of user satisfaction and reflection of request propose that the statistics is focused on soil background concentration, decrease soil sampling points and extend survey period. The assessment of error management system per processes of detailed preparation suggest change of the statistics objective, a reduction of sampling points and improvement of survey period and soil measurement properties. Accuracy assessment of data proposed cuts of sampling points, accessibility increment and build up of management system linking subordinates and Ministry of Environment. The substantiality assessment of data service demonstrated information environment improvement for users including reference expression and records of statistics table and figure contents.

• Water for future
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• v.29 no.2
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• pp.167-178
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• 1996

In designing automatic water quality monitoring networks for a river basin, determination of measurement locations and items is critical to the effectiveness of the total system. In this paper we studied how to decide these two design factors when a monitoring network is designed for the purposse of water quality surveillance and emergency alarm. For measurement locations, candidate sites are chosen based on the intake amount for water supply and the point sources of contamination. Then, detailed locations are decided according to the contaminant flow distance. As for measurement items, characteristics and the accident history of water pollution in the basin must be taken into account. Considering economic aspects, we proposed a two-stage measurement plan: basic components for all locations and selective ones variable for different locations. Proposed methodology is demonstrated through a case study for Nak-dong River Basin.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.403-409
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• 2012

This paper proposes an energy efficient ECG monitoring system by putting some intelligence on the sensor node to reduce the number of transmissions. The sensor node is mostly put into the processing mode and just connects the base station when necessary. Therefore, the transmission energy is greatly reduced while the energy for processing is increased a little bit. Our proposed ECG analysis method classifies ECG cycles by computing the Euclidean distance between the sensed ECG cycle and the reference ECG cycle. This work is a detailed and full explanation of our former work. Extended experimental results show that the proposed trade is very effective in saving energy and the Euclidean distance based classification method is accurate. Furthermore, the PowerTOSSIM energy simulation method is also demonstrated as very accurate in evaluating the energy consumption of the sensor node in our application scenario.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.56-60
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• 2008

In this paper, we design and implement the web-based property management system using RFID. There are many properties in the organizations such as companies, schools and so on. Many users share these properties. Thus, these fields require efficient management systems for monitoring a variety of information such as the locations and the detailed information of the properties for the monitoring and lending services. We attach RFID tags to every property and monitor their information with our web-based management system. Our management system provides the monitoring service and the lending service for properties and users.

• Design & Manufacturing
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• v.15 no.1
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• pp.14-20
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• 2021

The objective of this study is to introduce the new possibility of sensing technology based on inductive displacement sensors to monitor the status of wheel position in the hot forging process. In order to validate effectiveness of proposed sensing technology, the indirect forging force measurement with displacement sensor was applied into a typical closed hot forging die-set used for the manufacturing of flange bolts. The locations to implement the displacement sensor were selected carefully by simulating forming process and static structural. From the measurement results of the forging force change during one hot forging cycle, it was found that the proposed monitoring system can provide useful information to understand the detailed behaviors of die-set in the closed hot forging process.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.920-927
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• 2009

Many schedule delays and cost overruns in interior construction are caused by a lack of understanding in detailed and complicated interior works. To minimize these potential impacts in interior construction, a systematic approach for project managers to detect discrepancies at early stages and take corrective action through use of visualized data is required. This systematic implementation is still challenging: monitoring is time-consuming due to the significant amount of as-built data that needs to be collected and evaluated; and current interior construction progress reports have visual limitations in providing spatial context and in representing the complexities of interior components. To overcome these issues, this research focuses on visualization and computer vision techniques representing interior construction progress with photographs. The as-planned 3D models and as-built photographs are visualized in a 3D walk-through model. Within such an environment, the as-built interior construction elements are detected through computer vision techniques to automatically extract the progress data linked with Building Information Modeling (BIM). This allows a comparison between the as-planned model and as-built elements to be used for the representation of interior construction progress by superimposing over a 3D environment. This paper presents the process of representing and detecting interior construction components and the results for an ongoing construction project. This paper discusses implementation and future potential enhancement of these techniques in construction.

• Ocean and Polar Research
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• v.45 no.2
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• pp.33-42
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• 2023

Dissolved oxygen (DO) is a crucial parameter for assessing environmental conditions in aquatic ecosystems. However, commercial in situ dataloggers for oxygen optodes can be relatively expensive and limited in their specifications. In this paper, we present a novel design for a DO datalogger system based on the control boards family with RP2040 MCU chipset. Our design includes two types of dataloggers: a simple logging system and a programmable system for sampling rates via magnetic switches underwater for divers. We provide detailed descriptions of the system, including the MicroPython source code and drawings to aid in construction. We also discuss the various applications of our DO datalogger system in monitoring dissolved oxygen concentration in coastal waters and assessing the benthic metabolism of aquatic ecosystems. Our DO datalogger system provides an affordable and flexible option for researchers to accurately monitor DO concentrations in aquatic environments, and thereby improve our understanding of these complex ecosystems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• Journal of Ecology and Environment
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• v.48 no.3
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• pp.395-404
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• 2024

Background: In this study, citizen scientists gathered survey data by monitoring inland wetlands, recognized as carbon sinks, and verified the accuracy of the data for incorporation into ecosystem management policies. Results: In October 2022, citizen scientists conducted surveys on three taxonomical groups (plants, mammals, terrestrial insects) in three wetland protection areas. After capturing photographs with location information, these images were uploaded to a national ecological information bank (EcoBank) managed in Korea. The information collected by citizen scientists underwent cross-validation through two expert methods, involving ecology field experts. First, experts conducted a survey of invasive alien plants in the designated areas and compared their findings with those of citizen scientists. The choice of survey locations by citizen scientists was influenced by their proximity to their residences. Second, an expert scrutinized the accuracy of species names collected and uploaded to EcoBank by citizen scientists, presenting their findings. The classification accuracy for species names was 98.8% for vegetation (n = 83), 21.6% for terrestrial insects (n = 21), and 66.7% for mammals (n = 8). These results indicate that citizen scientists may lack detailed classification ability at the species level. Conclusions: Moving forward, it will be imperative to offer diverse forms of education to strengthen the capabilities of the citizen scientists, including sharing wetland survey results to enhance expertise in species identification, creating and distributing educational materials, and providing on-site education through professional surveyors.