• The KIPS Transactions:PartD
• /
• v.13D no.5 s.108
• /
• pp.671-682
• /
• 2006

Until now, a variety of the standard and research activities are progressed in the business process management. However, since the common standard of the collaboration process language has not been determined, the research activities could not be well-systemized. We would present the guide-line to select and use the collaboration process language straightly through comparing different collaboration process languages (BPEL4WS, BPML, WSCI, WS-CDL, BPSS, etc). In this regard, we define the implicit and the explicit collaboration as the collaboration method in advance and present the result acquired according to compare and analyze the features of the collaboration process languages. First, the necessary elements the collaboration process languages have are extracted through the framework of the inter-organizational workflow proposed by Bernauer and the collaboration process modeling procedure(CPMP). Second, we analyze the properties of the collaboration process language based the essential elements. Finally, we show the complete example that the collaboration business process really reflects the characteristics of the collaboration business process languages

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.38 no.4
• /
• pp.168-176
• /
• 2015

Trends of integrating products and services lead to the emergence of Product-Service System (PSS). To implement and embody a PSS solution in new product development, a comprehensive design framework is allowed designers to facilitate the design factors of the PSS in complex business environments. A physical product, containing functionalities for services, is the role of medium between customers and a manufactures. Customers can access those metaphysical interfaces to utilize the product fully or expand its performances. The PSS is aiming to prolong its lifecycle while maintaining its expected quality. Since the quality can be represented as a measure which belongs to user's perspective, guaranteeing certain level of quality can be interpreted to sustaining customer satisfaction. The objective of this paper is to propose a PSS design framework to identify design factors for developing products and services by integrating object-oriented concepts and blueprinting in context of a business ecosystem. The proposed model is developed based on relationship products and services matching with their design factors. The products and the services are then brought together to form a PSS. Functions and processes can be categorized to identify the design factors in different levels using the object-oriented concepts. Objected-oriented concepts provide PSS analysis tools for describing a business process or a workflow process in the PSS. The blueprint is used to identify the relationships between the products functions and the service processes that are offered as part of a job. To demonstrate of the effectiveness of the proposed model, we use a case study involving a smart phone.

• Journal of Fashion Business
• /
• v.27 no.4
• /
• pp.141-162
• /
• 2023

With the prospect that integrating creative AI in the fashion design field will become more visible, this study considered the case of creative fashion design development through Human-AI Co-creation (HAIC). Methodologically, this research encompasses a literature review and empirical investigations. In the literature review, the fashion design and creative HAIC processes, and the possibilities of integrating AI in fashion design were considered. In the empirical study, based on the case analysis of generating fashion design through HAIC, the HAIC type according to the role and interaction method, and characteristics of humans and AI was considered, and the HAIC process for fashion design was derived. The results of this study are summarized as follows. First, HAIC types in fashion design are divided into four types: AI-driven passive HAIC, human-driven passive HAIC, flexible interaction-based HAIC, and integrated interaction-based value creation HAIC. Second, the stages of the HAIC process for creative fashion design can be broadly divided into semantic data integration, visual ideation, design creation and expansion, design presentation, and design/manufacturing solution and UX platform creation. Third, in fashion design, HAIC contributes to human ability, enhancement of creativity, achievement of efficient workflow, and creation of new values. This research suggests that HAIC has the potential to revolutionize the fashion design industry by facilitating collaboration between humans and AI; consequently, enhancing creativity, and improving the efficiency of the design process. It also offers a framework for understanding the different types of HAIC and the stages involved in the creative fashion design process.

• Journal of Trauma and Injury
• /
• v.36 no.3
• /
• pp.231-241
• /
• 2023

Purpose: Overtriage and undertriage rates are critical metrics in trauma, influenced by both trauma team activation (TTA) criteria and compliance with these criteria. Analysis of undertriaged patients at a level I trauma center revealed suboptimal compliance with existing criteria. This study assessed triage patterns after implementing compliance-focused process interventions. Methods: A physician-driven, free-text alert system was modified to a nonphysician, hospital dispatcher-guided system. The latter employed dropdown menus to maximize compliance with criteria. The preintervention period included patients who presented between May 12, 2020, and December 31, 2020. The postintervention period incorporated patients who presented from May 12, 2021, through December 31, 2021. We evaluated appropriate triage, overtriage, and undertriage using the Standardized Trauma Assessment Tool. Statistical analyses were conducted with an α level of 0.05. Results: The new system was associated with improved compliance with existing TTA criteria (from 70.3% to 79.3%, P=0.023) and decreased undertriage (from 6.0% to 3.2%, P=0.002) at the expense of increasing overtriage (from 46.6% to 57.4%, P<0.001), ultimately decreasing the appropriate triage rate (from 78.4% to 74.6%, P=0.007). Conclusions: This study assessed a workflow change designed to improve compliance with TTA criteria. Improved compliance decreased undertriage to below the target threshold of 5%, albeit at the expense of increased overtriage. The decrease in appropriate triage despite compliance improvements suggests that the current criteria at this institution are not adequately tailored to optimally balance the minimization of undertriage and overtriage. This finding underscores the importance of improved compliance in evaluating the efficacy of TTA criteria.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.12
• /
• pp.3330-3344
• /
• 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 Korean Society on Water Environment
• /
• v.40 no.1
• /
• pp.19-35
• /
• 2024

The global pandemic, coronavirus disease caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the implementation of wastewater surveillance as a means to monitor the spread of SARS-CoV-2 prevalence in the community. The challenging aspect of establishing wastewater surveillance requires a well-equipped laboratory for wastewater sample analysis. According to previous studies, RT-PCR-based molecular tests are the most widely used and popular detection method worldwide. However, this approach for the detection or quantification of SARS-CoV-2 from wastewater demands a specialized laboratory, skilled personnel, expensive instruments, and a workflow that typically takes 6 to 8 hours to provide results for a few samples. Rapid and reliable alternative detection methods are needed to enable less-well-qualified practitioners to set up and provide sensitive detection of SARS-CoV-2 within wastewater at regional laboratories. In some cases, the structural and molecular characteristics of SARS-CoV-2 are unknown, and various strategies for the correct diagnosis of COVID-19 have been proposed by research laboratories. The ongoing research and development of alternative and rapid technologies, namely RT-LAMP, ELISA, Biosensors, and GeneXpert, offer a wide range of potential options not only for SARS-CoV-2 detection but also for other viruses. This study aims to discuss the effective regional rapid detection and quantification methods in community wastewater.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.1
• /
• pp.115-123
• /
• 2024

The purpose of this study is to contribute to how the advantages of artificial intelligence (AI) services and the associated limitations can be simultaneously overcome, using the keywords AI and risk management. To achieve this, two cases were introduced: (1) presenting a risk monitoring process utilizing AI and (2) introducing an operational toolkit to minimize the emerging limitations in the development and operation of AI services. Through case analysis, the following implications are proposed. First, as AI services deeply influence our lives, the process are needed to minimize the emerging limitations. Second, for effective risk management monitoring using AI, priority should be given to obtaining suitable and reliable data. Third, to overcome the limitations arising in the development and operation of AI services, the application of a risk management process at each stage of the workflow, requiring continuous monitoring, is essential. This study is a research effort on approaches to minimize limitations provided by advancing artificial intelligence (AI). It can contribute to research on risk management in the future growth and development of the related market, examining ways to mitigate limitations posed by evolving AI technologies.

• KIISE Transactions on Computing Practices
• /
• v.20 no.9
• /
• pp.513-518
• /
• 2014

It has become possible for small scale laboratories to interpret large scale genomic DNA, thanks to the reduction of the sequencing cost by the development of next generation sequencing (NGS). De novo assembly is a method which creates a putative original sequence by reconstructing reads without using a reference sequence. There have been various study results on de novo assembly, however, it is still difficult to get the desired results even by using the same assembly procedures and the analysis tools which were suggested in the studies reported. This is mainly because there are no specific guidelines for the assembly procedures or know-hows for the use of such analysis tools. In this study, to resolve these problems, we introduce steps to finding whole genome of an unknown DNA via NGS technology and de novo assembly, while providing the pros and cons of the various analysis tools used in each step. We used 350Mbp of Toxocara canis DNA as an application case for the detailed explanations of each stated step. We also extend our works for prediction of protein-coding genes and their functions from the draft genome sequence by comparing its homology with reference sequences of other nematodes.

• Journal of the Geological Society of Korea
• /
• v.54 no.6
• /
• pp.615-630
• /
• 2018

Basin analysis is a research field to understand the formation and evolution of sedimentary basins. This task requires various geoscientific datasets as well as numerical and graphical modelling techniques to synthesize results dimensionally in time and space. For basin analysis and modelling in a comprehensive workflow, BasinVis 1.0 was released as a MATLAB-based program in 2016, and recently the software has been extended to BasinVis 2.0, with new functions and revised user-interface. As a case study, this work analyses the southern Vienna Basin and visualizes the sedimentation setting and subsidence evolution to introduce the basin modelling functions of BasinVis 2.0. This is a preliminary study for a basin-scale modelling of the Vienna Basin, together with our previous studies using BasinVis 1.0. In the study area, during the late Early Miocene, sedimentation and subsidence are significant along strike-slip and en-echelon listric normal faults. From the Middle Miocene onwards, however, subsidence decreases abruptly over the area and this situation continues until the Late Miocene. This is related to the development of the pull-apart system and corresponds to the episodic tectonic subsidence in strike-slip basins. The subsidence of the Middle Miocene is confined mainly to areas along the strike-slip faults, while, from the late Middle Miocene, the depocenter shifts to a depression along the N-S trending listric normal faults. This corresponds to the regional paleostress regime transitioning from NE-SW trending transtension to E-W trending extension. This study applies various functions and techniques to this case study, and the modelled results demonstrate that BasinVis 2.0 is effective and applicable to the basin modelling.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.7
• /
• pp.1-7
• /
• 2022

Recently, as the use of applications such as big data programs and machine learning programs that are driven while generating large amounts of data in the program itself becomes common, the existing main memory alone lacks memory, making it difficult to execute the program quickly. In particular, the need to derive results more quickly has emerged in a situation where it is necessary to analyze whether the entire sequence is genetically altered due to the outbreak of the coronavirus. As a result of measuring performance by applying large-capacity data to a computing system equipped with a self-developed memory pool MOCA host adapter instead of processing large-capacity data from an existing SSD, performance improved by 16% compared to the existing SSD system. In addition, in various other benchmark tests, IO performance was 92.8%, 80.6%, and 32.8% faster than SSD in computing systems equipped with memory pool MOCA host adapters such as SortSampleBam, ApplyBQSR, and GatherBamFiles by task of workflow. When analyzing large amounts of data, such as electrical dielectric pipeline analysis, it is judged that the measurement delay occurring at runtime can be reduced in the computing system equipped with the memory pool MOCA host adapter developed in this research.