• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.1
• /
• pp.363-375
• /
• 2013

Today, a shortage of the skilled operator has been intensified gradually and the necessity of an earthwork in extreme environment operators are difficult to access is increasing for the purpose of resource development and new living space creation. For this reason, an effort to develop an unmanned excavation robot for fully automated earthwork system is continuing globally. In Korea, a research consortium called 'Intelligent Excavation System' has been formed since 2006 as a part of Construction Technology Innovation Program of Ministry of Land, Transport and Maritime Affairs of Korea. Among detailed technologies of the Task Planning System is one of the core technologies of IES, this paper explains research and development process of the Local Area Design Module, which provides informatization unit to create automated excavators' work command information at operation level such as location, range, target, and sequence for excavation work. Designing of Local Area should be considered various influential factors such as excavator's specification, working mechanism, heuristics, and structural stability to create work plan guaranteed safety and effectiveness. For this research, conceptual and detail design of the Local Area is performed for analyzing design element and variable, and quantization method of design specification corresponding with heuristics and structural safety is generated. Finally, module is developed through constructed algorithm and developed module is verified.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.831-838
• /
• 2022

Machine Learning is a process of using computer algorithms to extract information from raw data to solve complex problems in a data-rich environment. It has been used in the construction industry by both academics and practitioners for multiple applications to improve the construction process. The Construction Industry Institute, a leading construction research organization has twenty-five years of experience in benchmarking capital projects in the industry. The organization is at an advantage to develop useful machine learning applications because it possesses enormous real construction data. Its benchmarking programs have been actively used by owner and contractor companies today to assess their capital projects' performance. A credible benchmarking program requires statistically valid data without subjective interference in the program administration. In developing the next-generation benchmarking program, the Data Warehouse, the organization aims to use machine learning algorithms to minimize human effort and to enable rapid data ingestion from diverse sources with data validity and reliability. This research effort uses a focus group comprised of practitioners from the construction industry and data scientists from a variety of disciplines. The group collaborated to identify the machine learning requirements and potential applications in the program. Technical and domain experts worked to select appropriate algorithms to support the business objectives. This paper presents initial steps in a chain of what is expected to be numerous learning algorithms to support high-performance computing, a fully automated performance benchmarking system.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.14 no.2
• /
• pp.104-109
• /
• 2010

Purpose: $[^{18}F]$Fallypride plays an effective radiotracer for the study of dopamine $D_2/D_3$ receptor occupancy, neuropsychiatric disorders and aging in humans. This tracer has the potential for clinical use, but automated labeling efficiency showed low radiochemical yields about 5~20% with relatively long labelling time of fluorine-18. In present study, we describe an improved automatic synthesis of [$^{18}F$]Fallypride using different base concentration for routine clinical use. Materials and Methods: Fully automated synthetic process of [$^{18}F$]Fallypride was perform using the TracerLab $FX_{FN}$ synthesizer under various labeling conditions and tosyl-fallypride was used as a precursor. [$^{18}F$]Fluoride was extracted with various concentration of $K_{2.2.2.}/K_2CO_3$ from $^{18}O$-enriched water trapped on the ion exchange cartridge. After azeotropic drying, the labeling reaction proceeded in $CH_3CN$ at $100^{\circ}C$ for 10 or 30 min. The reaction mixture was purified by reverse phase HPLC and collected organic solution was exchanged by tc-18 Sep-Pak for the clinically available solution. Results: The optimal labeling condition of [$^{18}F$]Fallypride in the automatic production was that 2 mg of tosyl-fallypride in acetonitrile (1 mL) was incubated at $100^{\circ}C$ for 10 min with $K_{2.2.2.}/K_2CO_3$ (11/0.8 mg). [$^{18}F$]Fallypride was obtained with high radiochemical yield about $66{\pm}1.4%$ (decay-corrected, n=28) within $51{\pm}1.2$ min including HPLC purification and solid-phase purification for the final formulation. Conclusion: [$^{18}F$]Fallypride was prepared with a significantly improved radiochemical yield with high specific activity and shorten synthetic time. In addition, this automated procedure provides the high reproducibility with no synthesis failures (n=28).

• The Korean Journal of Blood Transfusion
• /
• v.23 no.2
• /
• pp.127-135
• /
• 2012

Background: Despite modern advances in laboratory automated medicine, work-process in the blood bank is still handled manually. Several automated immunohematological instruments have been developed and are available in the market. The IH-1000 (Bio-Rad Laboratories, Hercules, CA, USA), a fully automated instrument for immunohematology, was recently introduced. In this study, we evaluated the performance of the IH-1000 for ABO/Rh typing and irregular antibody screening. Methods: In October 2011, a total of 373 blood samples for ABO/Rh typing and 303 cases for unexpected antibody screening were collected. The IH-1000 was compared to the manual tube and slide methods for ABO/Rh typing and to the microcolumn agglutination method (DiaMed-ID system) for antibody screening. Results: For ABO/Rh typing, concordance rate was 100%. For unexpected antibody screening, positive results for both column agglutination and IH-1000 were observed in 10 cases (four cases of anti-E and c, three of anti-E, one of anti-D, one of anti-M, and one of anti-Xg) and negative results for both were observed in 289 cases. The concordance rate between IH-1000 and column agglutination was 98.7%. Sensitivity and specificity were 90.9% and 99.3%, respectively. Conclusion: The automated IH-1000 showed good correlation with the manual tube and slide methods and the microcolumn agglutination method for ABO-RhD typing and irregular antibody screening. The IH-1000 can be used for routine pre-transfusion testing in the blood bank.

• Journal of Bio-Environment Control
• /
• v.7 no.2
• /
• pp.91-108
• /
• 1998

This study was carried out to survey basic information of swine farms on the machine holdings. facility type. management of manure by farm scale and operation, and then to develop the mechanization model. Manual feeding was common for sows and nursing sows. but automation feeding was normally furnished for weaners. growing pigs and castrated male pigs. Water supplies was completely automated for all of the surveyed swine farms. Fully mechanized and automated system would not be feasible and affordable for the small scale farms breeding less than 500 heads. Because the environmental control for the nursing sows and weaner was important, some swine houses were constructed with the windowless type. However, the furnished rates ranged from 22.2% to 44.4% of the surveyed nursing sow and weaner houses at the farm scales. In the future, a computerized ventilation system would be commended for the efficient use of heat energy and to maintain the desirable temperature of swine buildings. Over-investment for large scale farm and over-crowded pigpen of small farm would cause wasting construction expenses and spreading epidermic diseases Hence, the size of swine building should follow the recommended scale. The fermentation drier was recommended for the manure management. Urine could be recycled or discharged after treating by the activated sludge process.

• Korean Journal of Radiology
• /
• v.21 no.8
• /
• pp.987-997
• /
• 2020

Objective: Measurement of the liver and spleen volumes has clinical implications. Although computed tomography (CT) volumetry is considered to be the most reliable noninvasive method for liver and spleen volume measurement, it has limited application in clinical practice due to its time-consuming segmentation process. We aimed to develop and validate a deep learning algorithm (DLA) for fully automated liver and spleen segmentation using portal venous phase CT images in various liver conditions. Materials and Methods: A DLA for liver and spleen segmentation was trained using a development dataset of portal venous CT images from 813 patients. Performance of the DLA was evaluated in two separate test datasets: dataset-1 which included 150 CT examinations in patients with various liver conditions (i.e., healthy liver, fatty liver, chronic liver disease, cirrhosis, and post-hepatectomy) and dataset-2 which included 50 pairs of CT examinations performed at ours and other institutions. The performance of the DLA was evaluated using the dice similarity score (DSS) for segmentation and Bland-Altman 95% limits of agreement (LOA) for measurement of the volumetric indices, which was compared with that of ground truth manual segmentation. Results: In test dataset-1, the DLA achieved a mean DSS of 0.973 and 0.974 for liver and spleen segmentation, respectively, with no significant difference in DSS across different liver conditions (p = 0.60 and 0.26 for the liver and spleen, respectively). For the measurement of volumetric indices, the Bland-Altman 95% LOA was -0.17 ± 3.07% for liver volume and -0.56 ± 3.78% for spleen volume. In test dataset-2, DLA performance using CT images obtained at outside institutions and our institution was comparable for liver (DSS, 0.982 vs. 0.983; p = 0.28) and spleen (DSS, 0.969 vs. 0.968; p = 0.41) segmentation. Conclusion: The DLA enabled highly accurate segmentation and volume measurement of the liver and spleen using portal venous phase CT images of patients with various liver conditions.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.7 no.2
• /
• pp.41-50
• /
• 1993

This paper describes an effort to develop a microcomputer-based parameter identification system for three phase and two phase brushless DC motor. Back EMF equation is derived from back EMF waveform of three phase and two phase brushless DC motor. In this paper, a new identification algorithm for the brushless DC motor parameters by Pasek's technique is developed. It is found that Pasek's equation is valid for the brushless DC motor, too. The results obtained clearly shows that it is possible to implement the identification system for the determination of the brushless DC motor parameters. To minimize errors due to the ripple component in the measured armature current, digital averaging firis employed. The whole identification process of signal generation, measuring, parameter determination is fully automated. The use of the propod method in the parameter identifition system shows that the averaged current curve is in excellent agreement with the estimated current curve. Therefore, this close agreement confirms the validity of this technique.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.21 no.3
• /
• pp.215-228
• /
• 2003

National Geography Institute(NGI, National mapping agency) has been producing national basemap in automated process since middle of 1980's toward the systematic and efficient management of national land. In 1995, Korean government initiated a full-scale implementation of the National Geographic Information System(NGIS) Development Plan. Under the NGIS Development Plan, NGI began to produce digital maps in the scales of 1:1,000, 1:5,000, 1:25,000. However, digital maps of 1:250,000 scale, which are currently used for national land planning, were not included in NCIS Development Plan. Also, the existing laws and specifications related to digital maps of 1:250,000 scale are not clearly defined. It is fully appreciated that data dictionary will be a key element for users and generators of digital maps to rectify the existing problems in digital maps as well as to maximize the application of digital maps. There(ore this study proposed a feature classification system, which defines features that should be represented in digital map of 1:250,000 scale, and data dictionary as well.

• Journal of KIISE
• /
• v.43 no.2
• /
• pp.196-203
• /
• 2016

Due to the limitations of budget, resources, and time invested in a project, software requirements should be prioritized and be implemented in order of importance. Existing approaches to prioritizing requirements mostly depend on human decisions. The manual prioritization process is based on intensive interactions with the stakeholders, thus raising the issues of scalability and biased prioritization. To solve these problems, we propose a fully automated requirements prioritization approach, ToMSN (Topic Modeling Stakeholder Needs for requirements prioritization), by topic modeling the stakeholder needs-artifacts earned in the requirements elicitation phase. The requirements dataset of a 30,000-user system was utilized for the performance evaluation. ToMSN showed competitive prioritizing accuracy with existing approaches without human aids, therefore solving scalability and biased prioritization issues.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.10
• /
• pp.171-178
• /
• 2023

In this paper, we propose a smart automated warehouse to maximize space utilization. Previous elevator-type automatic warehouses were designed with a maximum payload of 100kg on trays, which has the problem of extremely limiting the number of pallets that can be loaded within the space. In this paper, we design a smart warehouse that can maximize space utilization with a maximum vertical stiffness of 300kg. As a result of the performance evaluation of the implemented warehouse, the maximum payload was 500.6kg, which satisfied the original design and requirements, the lifting speed was 0.5m/s, the operating noise of the device was 67.1dB, the receiving and forwarding time of the pallet was 36.92sec, the deflection amount was 4mm, and excellent performance was confirmed in all evaluation items. In addition, the PLC control method, which designs the control UI and control panel separately, was integrated into the PC system to improve interoperability and maintainability with various process management systems. In the future, we plan to develop it into a fully automatic smart warehouse by linking IoT sensor-based logistics robots.