• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.96-103
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• 2023

This paper presents a robust position tracking controller for a motor used in semiconductor equipment, utilizing the motor angle measurement. Precise position control is challenging due to the presence of uncertainties in various motor applications. The proposed controller consists of a PD (Proportional-Derivative) controller and a PIO (Proportional-Integral Observer) to estimate the system's state and equivalent disturbance compensating for the uncertainties. Since the stability alternates as the observer gain increases, we have investigated it through the closedloop root locus under the system parameters change. The analysis has showed that the inertia of the motor is the main parameter that affects it, and by adjusting the control gain appropriately, the system can be rendered to be stable even when the inertia of the motor changes. The effectiveness of the proposed control algorithm is validated through computer simulations, followed by a comparison of its performance with the results of a previous study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2316-2332
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• 2024

In this paper, we introduce a web-based system that leverages the capabilities of the ρ(rho)-algorithm, which is a Structure Information Control Net (SICN)-oriented process mining algorithm, with open-source platforms, including Django, Graphviz, and Cytoscape, to facilitate the rediscovery and visualization of business process models. Our approach involves discovering SICN-oriented process models from process instances from the IEEE XESformatted process enactment event logs dataset. This discovering process is facilitated by the ρ-algorithm, and visualization output is transformed into either a JSON or DOT formatted file, catering to the compatibility requirements of Cytoscape or Graphviz, respectively. The proposed system utilizes the robust Django platform, which enables the creation of a userfriendly web interface. This interface offers a clear, concise, modern, and interactive visualization of the rediscovered business processes, fostering an intuitive exploration experience. The experiment conducted on our proposed web-based process discovery system demonstrates its ability and efficiency showing that the system is a valuable tool for discovering business process models from process event logs. Its development not only contributes to the advancement of process mining but also serves as an educational resource. Readers, students, and practitioners interested in process mining can leverage this system as a completely free process miner to gain hands-on experience in rediscovering and visualizing process models from event logs.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.377-387
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• 2014

The purpose of this study is to suggest improvement ways of outpatient process via a simulation model and to improve operational efficiency. Three experimentation scenarios were implemented into the simulation model to determine which proposed scenario provides better improvement in terms of the following performance measures: LOS(Length of Stay), patient waiting time, patient travel time, and staff utilization. The hospital medical data collection and statistical tools used to analyze the process mining tools. And the PIOS simulation tool was used and the validity of the model was verified by using t-test. The simulation results demonstrated that oupatient process of center type is most efficient. Simulation approach is a powerful technique that supports efficient decision-making compared to traditional healthcare management approach based on past experience, feelings, and intuition. Therefore, the proposed experimentation model has wide applicability in healthcare systems.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.47-53
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• 2016

A type of workflow affiliation network is one of the specialized social network types, which represents the associative relation between actors and activities. There are many methods on a workflow affiliation network measuring centralities such as degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In particular, we are interested in the closeness centrality measurements on a workflow affiliation network discovered from enterprise workflow models, and we know that the time complexity problem is raised according to increasing the size of the workflow affiliation network. This paper proposes an estimated ranking algorithm and analyzes the accuracy and average computation time of the proposed algorithm. As a result, we show that the accuracy improves 47.5%, 29.44% in the sizes of network and the rates of samples, respectively. Also the estimated ranking algorithm's average computation time improves more than 82.40%, comparison with the original algorithm, when the network size is 2400, sampling rate is 30%.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.69-77
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• 2016

Recently, the importance of visual analytics has been recognized in the field of business intelligence. From the view of business intelligence, visual analytics aims for acquiring valuable insights for decision making by interactively visualizing a variety of business information. In this paper, we propose a treemap-based method for visualizing work-sharing relationships among business process performers. A work-sharing relationship is established between two performers who jointly participate in a specific activity of a business process and is an important factor for understanding organizational structures and behaviors in a process-centric organization. To this end, we design and implement a treemap-based visualization tool for representing work-sharing relationships as well as basic hierarchical information in business processes. Finally, we evaluate usefulness of the proposed visualization tool through an operational example using XPDL (XML Process Definition Language) process models.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.83-92
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• 2020

Recently, many companies and organizations are interested in predictive process monitoring for the efficient operation of business process models. Traditional process monitoring focused on the elapsed execution state of a particular process instance. On the other hand, predictive process monitoring focuses on predicting the future execution status of a particular process instance. In this paper, we implement the function of the business process remaining time prediction, which is one of the predictive process monitoring functions. In order to effectively model the remaining time, normalization by activity is proposed and applied to the predictive model by taking into account the difference in the distribution of time feature values according to the properties of each activity. In order to demonstrate the superiority of the predictive performance of the proposed model in this paper, it is compared with previous studies through event log data of actual companies provided by 4TU.Centre for Research Data.

• Archives of Plastic Surgery
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• v.45 no.5
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• pp.466-469
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• 2018

The highly contoured nature of the nose and the abundant free margin makes it especially difficult to reconstruct. In this report, we describe the use of a new helical rim free flap technique for the reconstruction of full-thickness nasal alar defects via supermicrosurgery. Briefly, after a wide excision with a margin of 0.7 cm, an alar defect with a size of $1{\times}1{\times}0.5cm$ was obtained, which included the full thickness of the skin, mucosa, and lower lateral cartilage. Vessel dissection was performed in a straightforward manner, starting from the incision margin for flap harvest, without any further dissection for reach the greater trunk of the superficial temporal artery. The flap was inset in order to match the contour of the contralateral ala. We closed the donor site via rotation and advancement. No donor site morbidity was observed, despite the presence of a small scar that could easily be covered with hair. The alar contour was satisfactory, and the patient was satisfied with the results. The supermicrosurgical technique did not require further dissection to identify the vessels for anastomosis, leading to better cosmetic outcomes and a reduced operating time.

• Archives of Plastic Surgery
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• v.33 no.6
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• pp.737-741
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• 2006

Purpose: This study was to evaluate the expression pattern of CD 18(leukocyte adhesion glycoprotein) in ischemia-reperfusion injury of TRAM flap of rats. Through this study, we can obtain more information about ischemia-reperfusion injury. We want to develop specific medicine to improve the survival rate of TRAM flap in the future. Methods: A TRAM flap supplied by a single pedicle superior epigastric artery and vein was elevated on 60 Sprauge-Dawley rats. The rats were divide into 6 groups (each group n=10); Group O: sham, no ischemia-reperfusion injury, Group I: 2 hour reperfusion after 4 hour ischemia, Group II: 4 hour reperfusion after 4 hour ischemia, Group III: 8 hour reperfusion after 4 hour ischemia, Group IV: 12 hour reperfusion after 4 hour ischemia, and Group V: 24 hour reperfusion after 4 hour ischemia. This study consisted of gross examination for flap survival and flow cytometry study of CD18 on neutrophils. Results: The gross measurement of the flap showed different survival rate in group I(71%), II(68%), III(37%), IV(34%) and V(34%). All experimental groups showed an increase in the expression of CD18 compared to group O. The expression of CD18 was rapidly increased in ascending order in group I, II and III. But, the expression of CD18 was maintained in group IV and V. Conclusion: The results can be implemented in the study to develop drugs which are capable of reducing ischemia-reperfusion injury in microsurgical breast reconstruction.

• Archives of Plastic Surgery
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• v.33 no.5
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• pp.621-626
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• 2006

Purpose: Erythropoietin is traditionally known to regulate erythropoiesis, but recently its protective effect against ischemia-reperfusion injury has been studied mainly in cardiovascular and neuronal systems. This study was planned to investigate the effects of recombinant human erythropoietin on ischemia-reperfusion injury in rat TRAM flap model. Methods: Superiorly based TRAM flap was elevated and ischemic insult was given for four hours. Thirty minutes before reperfusion, single dose recombinant human Erythropoietin(5000IU/kg) was injected via intraperitoneal route in the treatment group. At 24 hours postoperatively, systemic neutrophil count, tissue myeloperoxidase activity, malonyldialdehyde amount, nitric oxide content, tissue water content and histologic finding of inflammation was evaluated. On 10 days postoperatively, flap survival rate, angiogenesis and change in hematocrit level was evaluated. Results: Tissue nitric oxide level was significantly higher and myeloperoxidase activity was significantly lower in the treatment group 24 hours after reperfusion. Tissue water content was significantly lower in the treatment group. Perivascular neutrophil infiltration and intravascular adhesion was marked in the control group. Mean flap survival after ten days was 69% in the treatment group, and 47% in the control group, demonstrating a significant difference. Neovascularization in the treatment group also outnumbered the control group. No significant hematocrit rise was noted ten days after erythropoietin administration. Conclusion: Recombinant human Erythropoietin improved flap survival in ischemia-reperfusion injured rat TRAM flaps, at least partially owing to suppressed inflammation, increased nitric oxide, and enhanced angiogenesis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1454-1466
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• 2016

This paper implements an estimated ranking algorithm of closeness centrality measures in large-scale workflow-supported social networks. The traditional ranking algorithms for large-scale networks have suffered from the time complexity problem. The larger the network size is, the bigger dramatically the computation time becomes. To solve the problem on calculating ranks of closeness centrality measures in a large-scale workflow-supported social network, this paper takes an estimation-driven ranking approach, in which the ranking algorithm calculates the estimated closeness centrality measures by applying the approximation method, and then pick out a candidate set of top k actors based on their ranks of the estimated closeness centrality measures. Ultimately, the exact ranking result of the candidate set is obtained by the pure closeness centrality algorithm [1] computing the exact closeness centrality measures. The ranking algorithm of the estimation-driven ranking approach especially developed for workflow-supported social networks is named as RankCCWSSN (Rank Closeness Centrality Workflow-supported Social Network) algorithm. Based upon the algorithm, we conduct the performance evaluations, and compare the outcomes with the results from the pure algorithm. Additionally we extend the algorithm so as to be applied into weighted workflow-supported social networks that are represented by weighted matrices. After all, we confirmed that the time efficiency of the estimation-driven approach with our ranking algorithm is much higher (about 50% improvement) than the traditional approach.