• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.41-56
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• 2019

Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

• Journal of IKEEE
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• v.24 no.2
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• pp.426-434
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• 2020

FMI is being researched as a standard for linking large-scale simulation of CPS. In order to guarantee the reliability of the results in large-scale simulations using FMI, event handling through time management techniques is required. This paper aims to guarantee real-time performance and accuracy in large-scale co-simulation environments such as CPS. Synchronize the wallclock time and simulation time to ensure real time. Also, to ensure the accuracy, before the simulation, the event is checked and the simulation is performed with the smallest step size while maintaining the real time until the event occurrence time. As a result, the events occurring in the co-simulation environment are processed immediately and sequentially, ensuring the real-time performance and minimizing the numerical integration error by maximizing the simulation resolution. In the experiment, the proposed method was processed immediately, and it was confirmed that the numerical integration error is reduced by about 1/5 unlike the existing time management method which does not guarantee the resolution.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.181-188
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• 2014

Heterogeneous physical systems and computational devices are incorporated on a large-scale in a CPS (cyber-physical system) environment. Simulations can be useful for the reliable behaviors of CPSs. Time synchronization is one of major technical issues for the simulations. In the CPS, distributed systems control themselves by interacting with each other during runtime. When some simulation models have high complexity, wrong control commands as well as incorrect data can be exchanged due to the time error. We propose a time synchronization algorithm for the hybrid model that has characteristics of both continuous time systems and discrete event systems. In addition, we develop a CPS simulator based on our algorithm. For the verification of the algorithm and the execution of the simulator, we develop an example hybrid model and simulate considering user controls as well as interactions among the distributed systems.

• Journal of IKEEE
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• v.22 no.1
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• pp.6-13
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• 2018

To develop highly dependable CPS, M&S(modeling and simulation) is very important. It is not easy to model any CPS whole system in a single simulation tool because each simulation tool is optimized for modeling each different part of the CPS. The FMI is the standard for M&S between different simulation tools. The DDS is a communication middleware suitable for large-scale real-time data transmission. In this paper, we proposed FMI based CPS real-time distributed simulaton framework using DDS. To evaluate the performance of the proposed framework, we performed distributed simulation using IEEE HLA/RTI and OMG DDS middleware and measured and compared the execution time of the entire simulation. From the simulation results, we can confirm that the simulation execution time using DDS is at least 1.14 times faster compared to execution time using HLA/RTI.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.2
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• pp.1-10
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• 2016

In this paper, we consider the algorithms and numerical analysis for real-time integrated control system and resource management of large-scale manufacturing smart factory system. There various data transmitted on Cyber-Physical-System (CPS) is necessary to control in real time, as well as the terminal and the platform with respective system service. This will be a true smart manufacturing which consisting of existing research results, and a numerical analysis by the parameter-specific information. In this paper, Jacoby calculation to reflect the optimization algorithms that are newly proposed. It also presents a behavior that optimal operational algorithm on CPS which is adapted to the sensing data. In addition, we also verify the excellence of the real-time integrated control system through experimentation, by comparison with the existing research results.

• Journal of Microbiology and Biotechnology
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• v.31 no.11
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• pp.1545-1551
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• 2021

Exopolysaccharides (EPSs) such as capsular polysaccharide (CPS) are important bioactive carbohydrate compounds and are often used as bioenrichment agents and bioabsorbers to remove environmental pollutants like di-n-butyl phthalate (DBP). Among the EPS-producing bacteria, lactic acid bacteria (LAB) have gained the most attention. As generally recognized as safe (GRAS) microorganisms, LAB can produce EPSs having many different structures and no health risks. However, EPS production by LAB does not meet the needs of large-scale application on an industrial scale. Here, the capA gene (encoding CPS biosynthesis protein) was overexpressed in Lactobacillus plantarum P1 to improve the production of EPSs and further enhance the DBP adsorption capability. Compared with P1, the CPS production in capA overexpressed strain was increased by 11.3 mg/l, and the EPS thickness was increased from 0.0786 ± 0.0224 ㎛ in P1 to 0.1160 ± 0.0480 ㎛ in P1-capA. These increases caused the DBP adsorption ratio of P1-capA to be doubled. Overall, the findings in this study provide a safe method for the adsorption and removal of DBP.

• Journal of Korean Academy of Nursing
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• v.34 no.2
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• pp.372-378
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• 2004

Purpose: The purpose of this study was to measure the functional status of stroke patients cared for in different long-term care settings. Method: We assessed all stroke patients in two home health care agencies, four nursing homes and one geriatric hospital in Korea (n=171) using the Resident Assessment Instrument (RAI), which comprises Activity of Daily Living (ADL), urine incontinence, bowel incontinence, a Cognitive Performance Scale (CPS),and being understood and understanding others. Data was collected by face-to-face surveys with patients. Results: The mean ADL score, urine incontinence score, bowel incontinence score, CPS, and being understood score and understanding others score were lowest for the patients receiving home health care, and highest for the patients in nursing homes. Low scores described poor and high scores good functional status. The results showed significant differences in physical and cognitive function scores between the three groups of patients. Conclusion: This study suggests that there may be large differences between the patients in these three types of long-term care settings. These findings can be used to help develop and implement efficient long-term care programs.

• Journal of Microbiology and Biotechnology
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• v.22 no.12
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• pp.1776-1781
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• 2012

Multiple viruses such as Lily symptomless virus (LSV), Lily mottle virus (LMoV), and cucumber mosaic virus (CMV) are the most prevalent viruses infecting lilies in Korea. Leaf samples and bulbs showing characteristic symptoms of virus infection were collected from Gangwon, Chungnam, and Jeju provinces of Korea in 2008-2011. Coat protein (CP) genes of LSV and LMoV were amplified from collected samples by reverse transcription-polymerase chain reaction (RT-PCR) and cloned into a pET21d(+) expression vector to generate recombinant CPs. The resulting carboxy-terminal His-tagged CPs were expressed in Escherichia coli strain BL21(DE3) by isopropyl-1-thio-${\beta}$-D-galactoside induction. The recombinant proteins were purified using Ni-NTA agarose beads, and the purified proteins were used as an immunogen to produce polyclonal antibodies in rabbits. The resulting polyclonal antisera recognized specifically LSV and LMoV from infected plant tissues in Western blotting assays. Indirect enzymelinked immunosorbent assay and immunocapture RT-PCR using these polyclonal antisera were developed for the sensitive, efficient, economic, and rapid detection of Lily viruses. These results suggest that large-scale bulb tests and economic detection of Lily viruses in epidemiological studies can be performed routinely using these polyclonal antisera.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1532-1534
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• 2008

Aquesous carbon nanotubes (CNTs) solutions were prepared using SDS (sodium dodecyl sulfonate) and NADDBS (sodium dodecylbenzene sulfonate). Our inks are found to have the viscosity of 1-2 cps. In addition, the surface tension of inks inversely decreased with increasing surfactant concentration and then saturated at critical micelle concentration (CMC). The low surface tension at CMC gave rise to lower contact angles on Indium layers, resulting in larger printable feature sizes. In the fabrication of cold cathode, jet-printing is feasible to modify and scale up the cathode structures. These feasibilities could contribute jet-printing method to be more adaptable for making large-area cold cathodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2257-2285
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• 2022

Cyber-physical systems (CPS) have been growing exponentially due to improved cloud-datacenter infrastructure-as-a-service (CDIaaS). Incremental expandability (scalability), Quality of Service (QoS) performance, and reliability are currently the automation focus on healthy Tier 4 CDIaaS. However, stable QoS is yet to be fully addressed in Cyber-physical data centers (CP-DCS). Also, balanced agility and flexibility for the application workloads need urgent attention. There is a need for a resilient and fault-tolerance scheme in terms of CPS routing service including Pod cluster reliability analytics that meets QoS requirements. Motivated by these concerns, our contributions are fourfold. First, a Distributed Non-Recursive Cloud Model (DNRCM) is proposed to support cyber-physical workloads for remote lab activities. Second, an efficient QoS stability model with Routh-Hurwitz criteria is established. Third, an evaluation of the CDIaaS DCN topology is validated for handling large-scale, traffic workloads. Network Function Virtualization (NFV) with Floodlight SDN controllers was adopted for the implementation of DNRCM with embedded rule-base in Open vSwitch engines. Fourth, QoS evaluation is carried out experimentally. Considering the non-recursive queuing delays with SDN isolation (logical), a lower queuing delay (19.65%) is observed. Without logical isolation, the average queuing delay is 80.34%. Without logical resource isolation, the fault tolerance yields 33.55%, while with logical isolation, it yields 66.44%. In terms of throughput, DNRCM, recursive BCube, and DCell offered 38.30%, 36.37%, and 25.53% respectively. Similarly, the DNRCM had an improved incremental scalability profile of 40.00%, while BCube and Recursive DCell had 33.33%, and 26.67% respectively. In terms of service availability, the DNRCM offered 52.10% compared with recursive BCube and DCell which yielded 34.72% and 13.18% respectively. The average delays obtained for DNRCM, recursive BCube, and DCell are 32.81%, 33.44%, and 33.75% respectively. Finally, workload utilization for DNRCM, recursive BCube, and DCell yielded 50.28%, 27.93%, and 21.79% respectively.