• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.59-66
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• 2015

A stochastic modeling approach as a mathematical method for workflow intelligence is widely used for analyzing and simulating workflow models in the literature. In particular, as a resource-centric modeling approach, this paper proposes a stochastic model to represent work-handover relationships between performers in a workflow-supported social network. Calculating probabilities for the work-handover relationships are determined by two types of probabilities. One is the work-transition probability between activities, and the other is the task assignment probability between activities and performers. In this paper, we describe formal definitions of stochastic workflow models and stochastic work-handover relationship models, as well. Then, we propose an algorithm for extracting a stochastic work-handover relationship model from a stochastic workflow model. As a consequence, the proposed model ought to be useful in performing resource-centric workflow simulations and model-log comparison analyses.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.19-27
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• 2022

In this study, we propose a language and platform to describe and manage the MLOps(Machine Learning Operations) workflow for time series data anomaly detection. Time series data is collected in many fields, such as IoT sensors, system performance indicators, and user access. In addition, it is used in many applications such as system monitoring and anomaly detection. In order to perform prediction and anomaly detection of time series data, the MLOps platform that can quickly and flexibly apply the analyzed model to the production environment is required. Thus, we developed Python-based AI/ML Modeling Language (AMML) to easily configure and execute MLOps workflows. Python is widely used in data analysis. The proposed MLOps platform can extract and preprocess time series data from various data sources (R-DB, NoSql DB, Log File, etc.) using AMML and predict it through a deep learning model. To verify the applicability of AMML, the workflow for generating a transformer oil temperature prediction deep learning model was configured with AMML and it was confirmed that the training was performed normally.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.460-469
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• 2008

Process mining aims at mining valuable information from process execution results (called "event logs"). Even though process mining techniques have proven to be a valuable tool, the mining results from real process logs are usually too complex to interpret. The main cause that leads to complex models is the diversity of process logs. To address this issue, this paper proposes a trace clustering approach that splits a process log into homogeneous subsets and applies existing process mining techniques to each subset. Based on log profiles from a process log, the approach uses existing clustering techniques to derive clusters. Our approach are implemented in ProM framework. To illustrate this, a real-life case study is also presented.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.113-129
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• 2009

Abstract Corporate activities are composed of numerous working processes and during the working flow, various business processes are being created and completed simultaneously. Enterprise Resources Planning (ERP) makes the working process simple, yet creates more complicated work structure and therefore, there is an absolute need of efficient management for business processes. The workflow literature has been looking for efficient and effective ways of rediscovering and mining workflow intelligence and knowledge from their enactment histories and event logs. As part of studies to analyze and improve the process, the concepts of 'Process Mining', 'Process re-discovery', 'BPR (Business Process Reengineering)' have appeared and the studies for practical implementation are proactively being done. However, these studies normally follow the approach throughout data warehousing for log data of process instances. It is very hard for these approaches to reflect user's intention to the rediscovering and mining activities. The process instances designed based on the consideration of analysis can make groupings effectively and when the analysis demand of user changes within the analysis domain can also reduce the cost of analysis. Therefore, the thesis proposes a special type of workflow model, which is called a colored workflow model, that is extended from the ICN (information control net) modeling methodology by reinforcing the concept of colored token. The colored tokens represent the conceptual types of constraints and criteria that can be used to classifying and grouping the workflow intelligence and knowledge extracted from the corresponding workflow models' enactment histories and event logs. Through the runtime information of process instances, it makes possible to analyze proactive and user-oriented process with the goal of deriving business knowledge from the beginning of process definition.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.63-73
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• 2018

These days, VR contents are created in three ways: CG based method, game engine based method, and live action shooting method. The most universal method is live action shooting. So far, most live actions are shot with action cams. Therefore, this method is different from professional image production method for movies and TV dramas. This study tries to point out the difference between professional image production method and action cam based shooting method, and proposes an alternative. The proposed method is log shooting based HDR filming and editing. As the result of test shooting and editing, the proposed method was able to obtain more color information than conventional action cam based shooting method and thereby to implement high-definition images which are hard in an action cam.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.49-55
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• 2019

Organizations design and operate business process models to achieve their goals efficiently and systematically. With the advancement of IT technology, the number of items that computer systems can participate in and the process becomes huge and complicated. This phenomenon created a more complex and subdivide flow of business process.The process instances that contain workcase and events are larger and have more data. This is an essential resource for process mining and is used directly in model discovery, analysis, and improvement of processes. This event log is getting bigger and broader, which leads to problems such as capacity management and I / O load in management of existing row level program or management through a relational database. In this paper, as the event log becomes big data, we have found the problem of management limit based on the existing original file or relational database. Design and apply schemes to archive and analyze large event logs through Hadoop, an open source distributed file system, and HBase, a NoSQL database system.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.191-203
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• 2013

Today, information technologies have been applied to operations in container terminals, and it is possible to collect operational log data due to development of equipment and operations technology. Terminal operators are collecting event log data and try to figure out the way of resolving operations problems. Operators want to analyze event logs to determine the causes of the operation problems, but it can hardly be done manually. In this paper, we suggest a formal framework to evaluate performance measures using the collected log data of operations in container terminals. The proposed formal framework supports different container terminal layout, operational processes, and equipment. Our formal framework is composed of specification of terminal layout, log data, workflow, statistics, and report, based on the concept of container handling objects. For validation of our framework, we have implemented a terminal performance analysis system based on the proposed framework.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.32-36
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• 2002

본 논문에서는 워크플로우 시스템의 관리에 유용한 잠재 규clr을 도출하기 위한 프레임워크를 제안한다. 워크플로우 시스템의 전반적인 수행과정 관리에는 워크플로우 시스템의 모니터링 기능이 이용된다. 그러나 기존의 모니터링 기능은 시스템 수행과정에 대만 관리가 해당 시점에 한정된다는 문제점과, 모니터링 툴이 제공하는 이력 정보는 가공되지 않은 단순한 데이터베이스 필드 수준이라는 문제점이 있다. 따라서 본 연구에서는 워크플로우 시스템에 데이터 마이닝 기법을 이용해 누적된 데이터로부터 얻을 수 잇는 공통의 잠재 규칙에 대한 정보를 제공함으로써 기존의 모니터링 기능을 보완한다. 제안된 방법론은 분석 데이터 추출. 전처리. 연관관계 분석등의 단계를 거치며. 이러한 과정을 통해 워크플로우 시스템 관리에 유용한 잠재 규칙이 도출된다. 도출된 잠재 규칙은 추후 워크플로우 시스템에서 BPR(Business Process Reengineering)의 근거로 사용될 수 있다.

• Progress in Medical Physics
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• v.30 no.2
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• pp.59-63
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• 2019

Purpose: To manage radiation measurement equipment, a web-based management program has been developed in this study. Materials and Methods: This program is based on a web service and Java Server Pages (JSP) and employs compatibility and accessibility. Results: The first step in the workflow has been designed to create accounts for each user or organization and to log in. The program consists of two parts: fields for listed instruments, and measurement information. The instruments for measuring radiation listed in this program are as follows: ionization chambers, survey meters, thermometers, barometers, electrometers, and phantoms. Instrument properties can be put in the recording fields and browsing for associated instruments can be performed. The main part of the program is the cross-calibration for each ion chamber. For instance, the ionization chamber to be used as a relative dosimeter can be registered by cross-calibration data with a reference chamber calibrated by an accredited laboratory. This program supports methods using the central axis transfer theory for cross-calibration for the ionization chambers. The reference and field ionization chambers were placed in a solid water phantom along the beam central axis at two different depths, and then the positions were switched. Each measured value was used for calculating the cross-calibration factor. Conclusions: Because many instruments are used and managed in radiation oncology departments, systematic, traceable recording is very important. The web-based program developed in this study is expected to be used effectively in the maintenance of radiation measurement instruments.

• Safety and Health at Work
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• v.12 no.4
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• pp.462-470
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• 2021

Background: Fatigue is pervasive, under-reported, and potentially deadly where flight operations are concerned. The aviation industry appears to lack a standardized, practical, and easily replicable protocol for fatigue risk assessment which can be consistently applied across operators. Aim: Our paper sought to present a framework, supported by real-world data with subjective and objective parameters, to monitor aircrew fatigue and performance, and to determine the safe crew configuration for commercial airline operations. Methods: Our protocol identified risk factors for fatigue-induced performance degradation as triggers for fatigue risk and performance assessment. Using both subjective and objective measurements of sleep, fatigue, and performance in the form of instruments such as the Karolinska Sleepiness Scale, Samn-Perelli Crew Status Check, Psychomotor Vigilance Task, sleep logs, and a wearable actigraph for sleep log correlation and sleep duration and quality charting, a workflow flagging fatigue-prone flight operations for risk mitigation was developed and trialed. Results: In an operational study aimed at occupational assessment of fatigue and performance in airline pilots on a three-men crew versus a four-men crew for a long-haul flight, we affirmed the technical feasibility of our proposed framework and approach, the validity of the battery of assessment instruments, and the meaningful interpretation of fatigue and work performance indicators to enable the formulation of safe work recommendations. Conclusion: A standardized occupational assessment protocol like ours is useful to achieve consistency and objectivity in the occupational assessment of fatigue and work performance.