• Quality Improvement in Health Care
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• v.20 no.1
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• pp.28-40
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• 2014

Objectives: Prescriptions for Parkinson's can be dispensed at the outpatient pharmacy. In general, the treatment of Parkinson's disease requires a multitude of drugs, sometimes taken 4 to 6 times a day at specific times as prescribed by the medical practitioner. Said "time-specific therapy" is one of the major reasons of dispensing delay observed at the outpatient pharmacy. Because our establishment lacked a computerized system to support time-specific prescriptions, they were not recognized electronically. They had to be issued and dispensed manually, which required a greater amount of time than the automated process. To solve the problem, a new sig code was developed to handle time-specific prescriptions with a comprehensive automated dispensing system to support it. This study aims to create electronic programs and streamline the process to increase dispensing performance. And thus, ensure greater patient safety and dispensing accuracy within a shorter dispensing time and also increase employee satisfaction through a decreased workload. Methods: After identifying the problems caused by non-electronic prescriptions an automated system that allowed the issuance of time-specific prescriptions was developed. A new sig code was created that could be recognized by the Pharmacy electronic medical program, the label printer to group medications by administration times and the Automatic Tablet Counter(ATC) to count the grouped drugs accordingly. Result: With the new sig code, the practitioner became able to electronically select the times of drug administration while issuing the prescription. This 'time-specific prescription' can now be recognized by the pharmacy electronic medical program, the label printer and the ATC like any other prescription. Conclusion: The developed program started operating on September 2013. Although not all Parkinson's patients have been issued with the new electronic 'time-specific prescription', the overall dispensing process has become more streamlined and accurate. As the medical team continues to integrate the new system in their practice an additional decrease of the dispensing time is predicted. Future program upgrades and other new time-saving approaches are scheduled, which are expected to further increase the service quality of our outpatient pharmacy.

• The Journal of Information Technology
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• v.6 no.4
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• pp.163-175
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• 2003

SURF is a compliance engine, checking document content against detail in an established agreement. It provides a single vehicle for handling documentary trade settlement, regardless of the risk profile and financing requirements of the parties involved. That is, SURF, a Value Added Service connected to the Core Messaging Platform, is a documentary trade settlement service. It offers users of the system automated document compliance checking and a tool to manage the workflow in connection with documentary trade settlement. The Service supports varying degrees of risk transfer between buyer, sellers and banks and supports transactions from open account to more complex Letters of Credit.

• IE interfaces
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• v.10 no.3
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• pp.1-10
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• 1997

CALS, being widely adopted by industry, is a strategy to share integrated digital product data through a set of standards to achieve effieciencies and competition in business. For CALS implemetation, creating a shared information system is necessary and CITIS is proposed for that. CITIS shall provide on-line access and automated exchange of all the technical information between contractor and service provider, and the function of CITIS is difined in MIL-STD-974. In this paper, regarding CITIS as a infrastructure of information for CALS, we proposed CITIS server system which comprise global data sharing software, global data management system, workflow manager, and configuration management maneger.

• IE interfaces
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• v.13 no.4
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• pp.680-687
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• 2000

The objectives of this research are to establish the operation scheduling and the preventive maintenance system in order to optimize the operation of mailing center. For the optimal operation scheduling of mailing process, the existing workflow of mailing process and that of required time are investigated prior to simulation modeling. The simulation experiments are conducted to increase the nextday delivery rate. The best alternative whose nextday delivery rate up to 100% is selected based the AHP(Analytic Hierarchy Process) method. The optimal work scheduling of all mailing centers are also presented. In addition, the CMMS(Computerized Maintenance Management System) for preventive maintenance is introduced for efficient operation of highly automated facilities of mailing center.

• Proceedings of Korean Society of Archives and Records Management
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• 2019.05a
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• pp.69-74
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• 2019

In the digital environment, electronic records are explosively increasing, but there are little concerns on how to effectively manage and service. On-Nara 2.0 and record management system, the information system of records production and management stage, are being developed and distributed on the cloud base. Archives management system requires the acquisition of new record management techniques because they need to acquire and manage various types of private records as well as public records. In this paper, we will discuss automation and intelligent technologies for archives management.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.135-142
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• 2024

Recently, along with digital transformation, technologies such as cloud computing, big data, and artificial intelligence have been actively introduced. In a situation where these technological changes are progressing rapidly, it is often difficult to manage processes efficiently using existing simple workflow management methods. Companies providing current cloud services are adopting virtualization technologies, including virtual machines (VMs) and containers, in their distributed system infrastructure for automated application deployment. Accordingly, this paper proposes a process-based orchestration system for integrated execution of corporate process-oriented workloads by integrating the potential of big data and machine learning technologies. This system consists of four layers as components for performing workload processes. Additionally, a common information model is applied to the data to efficiently integrate and manage the various formats and uses of data generated during the process creation stage. Moreover, a standard metadata protocol is introduced to ensure smooth exchange between data. This proposed system utilizes various types of data storage to store process data, metadata, and analysis models. This enables flexible management and efficient processing of data.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.5
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• pp.1061-1068
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• 2024

In this paper, anomaly detection methods for a collaborative robot during the chemical drum assembly process in the semiconductor industry are presented. The manual assembly of chemical drums has been automated using robots to prevent industrial accidents. However, the automation may increase downtime due to anomalies or failures in the robot manipulator tasks. To prevent this issue in advance, the methods to diagnose anomalous behaviors and conditions in the robotic automation workflow and subsequently resume tasks are proposed. To detect and diagnose anomalies in the tasks, the Random Forest classification method was utilized. Using this Random Forest classification, the collaborative robot anomaly detection model achieved an accuracy of 98.91%, successfully detecting all anomalies in the assembly process.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.95-102
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• 2007

This paper presents the core technology of Construction Business Process Automation to model and automate construction business processes. Business Process Reengineering (BPR) and Automation (BPA) have been recognized as one of the important aspects in construction business management. However, BPR requires a lot of efforts to identify, document, implement, execute, maintain, and keep track thousands of business processes to deliver a project. Moreover, existing BPA technologies used in existing Enterprise Resource Planning (ERP) systems do not lend themselves to effective scalability for construction business process management. Application of Workflow and Object Technologies would be quite effective in implementing a scalable enterprise application for construction business processes by addressing how: 1) Automated construction management tasks are developed as software components, 2) The process modeling is facilitated by dragging-and dropping task components in a network, 3) Raising business requests and instantiating corresponding process instances are delivered, and 4) Business process instances are executed by using workflow technology based on real-time simulation engine. This paper presents how the construction business process automation is achieved by using equipment reservation and cancellation processes simplified intentionally.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.161-167
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• 2021

Laboratory Information Management System(LIMS) is a centralized database for storing, processing, retrieving, and analyzing laboratory data, and refers to a computer system or system specially designed for laboratories performing inspection, analysis, and testing tasks. In particular, LIMS is equipped with a function to support the operation of the laboratory, and it requires workflow management or data tracking support. In this paper, we collect data on websites and various channels using crawling technology, one of the automated big data collection technologies for the operation of the laboratory. Among the collected test methods and contents, useful test methods and contents useful that the tester can utilize are recommended. In addition, we implement a complementary LIMS platform capable of verifying the collection channel by managing the feedback.

• Smart Structures and Systems
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• v.30 no.5
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• pp.501-511
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• 2022

Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.