• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.77-84
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• 2019

Workflow management system is a system that manages the workflow model which defines the process of work in reality. We can define the workflow process by sequencing jobs which is performed by the performers. Using the workflow management system, we can also analyze the flow of the process and revise it more efficiently. Many researches are focused on how to make the workflow process model more efficiently and manage it more easily. Recently, many researches use the workflow log files which are the execution history of the workflow process model performed by the workflow management system. Ourresearch group has many interests in making useful knowledge from the workflow event logs. In this paper we use XES log files because there are many data using this format. This papersuggests what are the cardinalities of the temporal workcases and how to get them from the workflow event logs. Cardinalities of the temporal workcases are the occurrence pattern of critical elements in the workflow process. We discover instance cardinalities, activity cardinalities and organizational resource cardinalities from several XES-based workflow event logs and visualize them. The instance cardinality defines the occurrence of the workflow process instances, the activity cardinality defines the occurrence of the activities and the organizational cardinality defines the occurrence of the organizational resources. From them, we expect to get many useful knowledge such as a patterns of the control flow of the process, frequently executed events, frequently working performer and etc. In further, we even expect to predict the original process model by only using the workflow event logs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1702-1721
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• 2019

A workflow process (or business process) management system helps to define, execute, monitor and manage workflow models deployed on a workflow-supported enterprise, and the system is compartmentalized into a modeling subsystem and an enacting subsystem, in general. The modeling subsystem's functionality is to discover and analyze workflow models via a theoretical modeling methodology like ICN, to graphically define them via a graphical representation notation like BPMN, and to systematically deploy those graphically defined models onto the enacting subsystem by transforming into their textual models represented by a standardized workflow process definition language like XPDL. Before deploying those defined workflow models, it is very important to inspect its syntactical correctness as well as its structural properness to minimize the loss of effectiveness and the depreciation of efficiency in managing the corresponding workflow models. In this paper, we are particularly interested in verifying very large-scale and massively parallel workflow models, and so we need a sophisticated analyzer to automatically analyze those specialized and complex styles of workflow models. One of the sophisticated analyzers devised in this paper is able to analyze not only the structural complexity but also the data-sequence complexity, especially. The structural complexity is based upon combinational usages of those control-structure constructs such as subprocesses, exclusive-OR, parallel-AND and iterative-LOOP primitives with preserving matched pairing and proper nesting properties, whereas the data-sequence complexity is based upon combinational usages of those relevant data repositories such as data definition sequences and data use sequences. Through the devised and implemented analyzer in this paper, we are able eventually to achieve the systematic verifications of the syntactical correctness as well as the effective validation of the structural properness on those complicate and large-scale styles of workflow models. As an experimental study, we apply the implemented analyzer to an exemplary large-scale and massively parallel workflow process model, the Large Bank Transaction Workflow Process Model, and show the structural complexity analysis results via a series of operational screens captured from the implemented analyzer.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.83-89
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• 2018

In workflow process intelligence and systems, workflow process mining and analysis issues are becoming increasingly important. In order to improve the quality of workflow process intelligence, it is essential for an efficient and effective data center storing workflow enactment event logs to be provisioned in carrying out the workflow process mining and analytics. In this paper, we propose a three-dimensional process-aware datacube for organizing workflow enterprise data centers to efficiently as well as effectively store the workflow process enactment event logs in the XES format. As a validation step, we carry out an experimental process mining to show how much perfectly the process-aware datacubes are suitable for discovering workflow process patterns and its analytical knowledge, like enacted proportions and enacted work transferences, from the workflow process enactment event histories. Finally, we confirmed that it is feasible to discover the fundamental control-flow patterns of workflow processes through the implemented workflow process mining system based on the process-aware data cube.

• Archives of Plastic Surgery
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• v.48 no.3
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• pp.246-253
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• 2021

In order to provide a physiological solution for patients with breast cancer-related lymphedema (BCRL), the surgeon must understand where and how the pathology of lymphedema occurred. Based on each patient's pathology, the treatment plan should be carefully decided and individualized. At the authors' institution, the treatment plan is made individually based on each patient's symptoms and relative factors. Most early-stage patients first undergo decongestive therapy and then, depending on the efficacy of the treatment, a surgical approach is suggested. If the patient is indicated for surgery, all the points of lymphatic flow obstruction are carefully examined. Thus a BCRL patient can be considered for lymphaticovenous anastomosis (LVA), a lymph node flap, scar resection, or a combination thereof. LVA targets ectatic superficial collecting lymphatics, which are located within the deep fat layer, and preoperative mapping using ultrasonography is critical. If there is contracture on the axilla, axillary scar removal is indicated to relieve the vein pressure and allow better drainage. Furthermore, removing the scars and reconstructing the fat layer will allow a better chance for the lymphatics to regenerate. After complete removal of scar tissue, a regional fat flap or a superficial circumflex iliac artery perforator flap with lymph node transfer is performed. By deciding the surgical planning for BCRL based on each patient's pathophysiology, optimal outcomes can be achieved. Depending on each patient's pathophysiology, LVA, scar removal, vascularized lymph node transfer with a sufficient adipocutaneous flap, and simultaneous breast reconstruction should be planned.

• Archives of Plastic Surgery
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• v.50 no.3
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• pp.225-232
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• 2023

In retrospect, the irony of this story began with the first meeting of these co-authors-in of all places, Coimbatore, India, in 2008, at the 12th International Perforator Flap Course. Here the junior author [hereafter "jp"] demonstrated his unparalleled skills in networking, and soon thereafter journeyed some 11,073 km to Allentown, U.S. to peruse the operating room and clinics of the senior author [sic. ggh] in action. Within 2 years jp orchestrated the presentation of the 14th International Perforator Flap Course, so ggh with great anticipation flew only 6,830 miles to reach Seoul, Korea for his first time. But four years more elapsed before ggh returned again to Korea to be a visiting professor, all the while not quite sure why any Korean would want anything from a country doctor who resided in nowheresville Allentown, Pennsylvania. Yet, an extraordinary fact then was to be unveiled, about which ggh was totally ignorant. The pioneer of plastic surgery in Korea, the first Korean to have completed an accredited plastic surgery fellowship, by coincidence had accomplished all this in . . . . . Allentown. The collegial relationship that evolved between these co-authors, who met by chance, indeed had a precedent coincidence! Was this "by chance" alone or predestination? Amazingly, in a way similar, the origin of plastic surgery itself in Korea also had Allentown connections. As a tribute to Lew Jae-duk, this important story must be here told, so let us now retrace his past in Allentown so we can find how the future was to be not so far away.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.51-66
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• 2023

In this paper, we propose a new type of process discovery framework, which is named as control-path-driven process group discovery framework, to be used for process mining and process reengineering in supporting life-cycle management of business process models. In addition, we develop a process mining system based on the proposed framework and perform experimental verification through it. The process execution event logs applied to the experimental effectiveness and verification are specially defined as Process BIG-Logs, and we use it as the input datasets for the proposed discovery framework. As an eventual goal of this paper, we design and implement a control path-driven process group discovery algorithm and framework that is improved from the ρ-algorithm, and we try to verify the functional correctness of the proposed algorithm and framework by using the implemented system with a BIG-Log dataset. Note that all the process mining algorithm, framework, and system developed in this paper are based on the structural information control net process modeling methodology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3330-3344
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• 2023

This paper proposes an antenna performance prediction model in the autonomous driving radar manufacturing process. Our research work is based upon a challenge dataset, Driving Radar Manufacturing Process Dataset, and a typical AutoML machine learning workflow engine, Pycaret open-source Python library. Note that the dataset contains the total 70 data-items, out of which 54 used as input features and 16 used as output features, and the dataset is properly built into resolving the multi-output regression problem. During the data regression analysis and preprocessing phase, we identified several input features having similar correlations and so detached some of those input features, which may become a serious cause of the multicollinearity problem that affect the overall model performance. In the training phase, we train each of output-feature regression models by using the AutoML approach. Next, we selected the top 5 models showing the higher performances in the AutoML result reports and applied the ensemble method so as for the selected models' performances to be improved. In performing the experimental performance evaluation of the regression prediction model, we particularly used two metrics, MAE and RMSE, and the results of which were 0.6928 and 1.2065, respectively. Additionally, we carried out a series of experiments to verify the proposed model's performance by comparing with other existing models' performances. In conclusion, we enhance accuracy for safer autonomous vehicles, reduces manufacturing costs through AutoML-Pycaret and machine learning ensembled model, and prevents the production of faulty radar systems, conserving resources. Ultimately, the proposed model holds significant promise not only for antenna performance but also for improving manufacturing quality and advancing radar systems in autonomous vehicles.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.101-111
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• 2024

In this paper, we propose a concpetual architecture and its implementation approach for contextualizing unstructured CCTV-video frame data into structured XML-video textual data by using the deep-learning neural network models and frameworks. Conclusively, through the conceptual architecture and the implementation approach proposed in this paper, we can eventually realize and implement the so-called sharable working and experiencing knowledge management platforms to be adopted to smart factories in various industries.

• Archives of Plastic Surgery
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• v.51 no.2
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• pp.258-261
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• 2024

Career building can be challenging for young surgeons, especially when topics such as lifestyle, work-life balance and subspecialization arise. Suggestions and advice from senior colleagues is very valuable but many young surgeons do not have such opportunities or are limited to a few senior surgeons. The International Microsurgery Club (IMC), in collaboration with the World Society of Reconstructive Microsurgery, organized a combined webinar for this topic and invited world renownedmicrosurgery masters polled by the IMCmembers to join, including Prof. Peter Neligan (Emeritus from University of Washington, United States), Prof. Raja Sabapathy (Ganga Hospital, India), Dr. Gregory Buncke (The Buncke Clinic, United States), Prof. Isao Koshima (Hiroshima University Hospital, Japan), Prof. David Chwei-Chin Chuang (Chang Gung Memorial Hospital, Taiwan), and Prof. Eric Santamaria (Hospital General Dr. Manuel Gea Gonzalez, Mexico) on May 1, 2022. Prof. Joon-Pio Hong (Asan Medical Center, South Korea) and Prof. Fu-Chan Wei (Chang Gung Memorial Hospital, Taiwan) were also selected but unfortunately could not make it and were therefore invited to another event in April 2023, summarized in a recently published paper. There is ample literature reporting on different aspects of developing a microsurgical career but the goal of this session was to offer an opportunity for direct exchange with experienced mentors. Moreover, insights from experienced microsurgeons from different part of the world were more likely to offer different perspectives on aspects such as career building, failure management, and team culture. This webinar event was moderated by Dr. Jung-Ju Huang (Taiwan), Dr. Susana Heredero (Spain), and Dr. Wei F. Chen (United States).

• Archives of Plastic Surgery
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• v.42 no.1
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• pp.28-33
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• 2015

Background Topical anesthetics, such as eutectic mixture of local anesthetics (EMLA) cream, can be applied to reduce pain before minor procedure. This trial evaluated EMLA as pretreatment for facial lacerations and compared pain, discomfort and overall satisfaction. Methods This trial included consecutive emergency department patients ${\geq}16years$ of age who presented with simple facial lacerations. At triage, lacerations were allotted to either the routine processing group or EMLA pretreatment group according to date of admission. Initially, the emergency department doctors inspected each laceration, which were dressed with saline-soaked gauze. In the pretreatment group, EMLA cream was applied during wound inspection. The plastic surgeon then completed primary closure following the local injection of an anesthetic. After the procedure, all patients were given a questionnaire assessing pain using the 10-point visual analog scale (VAS) ("no pain" to "worst pain"). All questionnaires were collected by the emergency department nurse before discharge. Results Fifty patients were included in the routine processing group, and fifty patients were included in the EMLA pretreatment group. Median age was 39.9 years, 66% were male, and the average laceration was 2.67 cm in length. The EMLA pretreatment group reported lower pain scores in comparison with the routine processing group (2.4 vs. 4.5 on VAS, P<0.05), and lower discomfort scores during the procedure (2.0 vs. 3.3, P=0.60). Overall satisfaction was significantly higher in the EMLA pretreatment group (7.8 vs. 6.1, P<0.05). Conclusions Pretreating facial lacerations with EMLA topical cream aids patients by reducing pain and further enhancing overall satisfaction during laceration treatment.