• International journal of advanced smart convergence
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• v.13 no.3
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• pp.135-142
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• 2024

Recently, along with digital transformation, technologies such as cloud computing, big data, and artificial intelligence have been actively introduced. In a situation where these technological changes are progressing rapidly, it is often difficult to manage processes efficiently using existing simple workflow management methods. Companies providing current cloud services are adopting virtualization technologies, including virtual machines (VMs) and containers, in their distributed system infrastructure for automated application deployment. Accordingly, this paper proposes a process-based orchestration system for integrated execution of corporate process-oriented workloads by integrating the potential of big data and machine learning technologies. This system consists of four layers as components for performing workload processes. Additionally, a common information model is applied to the data to efficiently integrate and manage the various formats and uses of data generated during the process creation stage. Moreover, a standard metadata protocol is introduced to ensure smooth exchange between data. This proposed system utilizes various types of data storage to store process data, metadata, and analysis models. This enables flexible management and efficient processing of data.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9475-9478
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• 2014

Cancer is the third highest cause of premature mortality in Iran. We aimed to determine trend of common cancers in Khuzestan province, Iran. Methods: It was a hospital based survey on 4065 subjects from their hospital files, those had registered as cancer case in Shafa hospital which has known as a biggest center of cancer in khuzestan province, Iran during 2005-2011.All data has entered by SPSS (version 19), descriptive statistic and adjusted odds ratio of common cancers for age and sex were calculated from multiple logistic regression model. Results: From all subjects; (51% & 49%) were male and female respectively. The most frequent age group was 60-50 years and common cancers were breast 16%, colorectal 6.3%, blood 2%, lung 8% and stomach 8%. Conclusion: Prevalence of cancers has increased markedly with age in Khuzestan Providence. Therefore, it is essential to prevent through early prevention, using screening and identifying cases in initial stages.

• Korean Journal of Computational Design and Engineering
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• v.15 no.3
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• pp.212-221
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• 2010

Proposed in the paper is a methodology to generate kinematic template for 3D JIG models. Recently, according to increase of the rate of automatic facility in manufacturing system, the 3D manufacturing and verification research and development have been issued. So, unlike in the past, moving 3D facilities are very various like JIGs, turn table, AS/RS worked in the automated manufacturing industry. Because 3D mesh models are used in these kinds of 3D simulation, users have to define the kinematic information manually. This 3D mesh data doesn't have parametric information and design history of the 3D model unlike the design level data. So, it is lighter than 3D design level data and more efficient to render on the 3D virtual manufacturing environment. But, when user wants to find a common axis located between the links, the parameter information of the model has to reconstruct for defining kinematic construction. It takes a long time and very repetitive to define an axis and makes a joint using 3D mesh data and it is non-intuitive task for user. This paper proposed template model that provides kinematic information of the JIG. This model is kinds of a state diagram to describe a relation between links. So, this model can be used for a kinematic template to the JIG which has a same mechanism. The template model has to be registered in the template library to use in the future, after user made the model of the specific type of the 3D JIG model.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.74-81
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• 1995

Several non-manifold data structures have been compared, which are radial-edge data structure, partial-face data structure, vertex-based data structure, and Yamaguchi's data structrue. All the entities in the data structures are classified into common entities and special entities. The entities are also classified as model entities, primitive entities bounding entities, and coupling entities. The four data structures for nonmanifold solid modelers are compared in terms of accessing efficiency, storage requirements, and inclusion of circulation. The results of comparison will serve as the basis to develope a nonmanifold modeler.

• Smart Structures and Systems
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• v.23 no.6
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• pp.589-613
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• 2019

Cables are prone to vibration due to their low inherent damping characteristics. Recently, negative stiffness dampers have gained attentions, because of their promising energy dissipation ability. The viscous inertial mass damper (termed as VIMD hereinafter) can be viewed as one realization of the inerter. It is formed by paralleling an inertial mass part with a common energy dissipation element (e.g., viscous element) and able to provide pseudo-negative stiffness properties to flexible systems such as cables. A previous study examined the potential of IMD to enhance the damping of stay cables. Because there are already models for common energy dissipation elements, the key to establish a general model for IMD is to propose an analytical model of the rotary mass component. In this paper, the characteristics of the rotary mass and the proposed analytical model have been evaluated by the numerical and experimental tests. First, a series of harmonic tests are conducted to show the performance and properties of the IMD only having the rotary mass. Then, the mechanism of nonlinearities is analyzed, and an analytical model is introduced and validated by comparing with the experimental data. Finally, a real-time hybrid simulation test is conducted with a physical IMD specimen and cable numerical substructure under distributed sinusoidal excitation. The results show that the chosen model of the rotary mass part can provide better estimation on the damper's performance, and it is better to use it to form a general analytical model of IMD. On the other hand, the simplified damper model is accurate for the preliminary simulation of the cable responses.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.10
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• pp.497-503
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• 2017

In recent years, studies on the prediction of building load using Artificial Neural Network (ANN) models have been actively conducted in the field of building energy In general, building loads predicted by ANN models show a sharp deviation unless large data sets are used for learning. On the other hands, some of the input data are hard to be acquired by common measuring devices. In this work, we estimate daily building loads with a limited number of input data and fewer pastdatasets (3 to 10 days). The proposed model with fewer input data gave satisfactory results as regards to the ASHRAE Guide Line showing 21% in CVRMSE and -3.23% in MBE. However, the level of accuracy cannot be enhanced since data used for learning are insufficient and the typical ANN models cannot account for thermal capacity effects of the building. An attempt proposed in this work is that learning procersses are sequenced frequrently and past data are accumulated for performance improvement. As a result, the model met the guidelines provided by ASHRAE, DOE, and IPMVP with by 17%, -1.4% in CVRMSE and MBE, respectively.

• Korean Journal of Computational Design and Engineering
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• v.19 no.4
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• pp.434-442
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• 2014

Most manufacturing enterprises create CAD data as a result of the product/part design process; however, the CAD data is being utilized only for production activities. Besides the processes directly related to manufacturing such as design and production, the CAD data is an important resource that can be used in variety of services (e.g., catalog production and production manuals) for manufacturing enterprises. This study proposes a software platform that can support a wide range of services for manufacturing companies in an efficient and productive way. The software platform was designed based on the functions identified by requirement analysis. The platform consists of four layers: data model layer to manage relevant data; library layer and common function layer to configure services; and application layer to install and run the software. Finally, this study evaluates the validity of the proposed platform architecture by applying it to the digital catalog system.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.21-30
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• 2020

In this paper, we predicted the propagation loss for the air-to-ground (A2G) channel between the ground control system and the unmanned aerial vehicle (UAV) using the prediction model for the aircraft recommended by the International Telecommunication Union (ITU). We analyzed the network coverage of the aerial relay system based on the medium altitude UAVs by expanding it into the air-to-air (A2A) channel. Climate and geographic factors in Korea were used to predict propagation loss due to atmospheres. We used the measured data published by the Telecommunication Technology Association (TTA) for regional rainfall-rate and effective earth radius factors to increase accuracy. In addition, the aerial relay communication system used the key parameter of the common data link (CDL) system developed in Korea recently. Prediction results show that the network coverage of the aerial relay system broadens at higher altitude.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.22-30
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• 2007

Most real word systems such as world economy, stock market, and medical applications, contain a series of dynamic and complex phenomena. One of common methods to understand these systems is to build a model and analyze the behavior of the system. In this paper, we investigated methods for best clustering over time series data. As a first step for clustering, BIC (Bayesian Information Criterion) approximation is used to determine the number of clusters. A search technique to improve clustering efficiency is also suggested by analyzing the relationship between data size and BIC values. For clustering, two methods, model-based and similarity based methods, are analyzed and compared. A number of experiments have been performed to check its validity using real data(stock price). BIC approximation measure has been confirmed that it suggests best number of clusters through experiments provided that the number of data is relatively large. It is also confirmed that the model-based clustering produces more reliable clustering than similarity based ones.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.147-153
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• 2002

In this paper, a substrate network model to be used with BSIM3 MOSFET model for submicron MOSFETs in giga hertz frequencies and its direct parameter extraction with physically meaningful values are proposed. The proposed substrate network model includes a conventional resistance and single inductance originated from ring-type substrate contacts around active devices. Model parameters are extracted from S-parameter data measured from common-bulk configured MOS transistors with floating gate and use where needed without any optimization process. The proposed modeling technique has been applied to various-sized MOS transistors. The substrate model has been validated for frequency up to 300Hz.