• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.11-16
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• 2019

This paper suggests an algorithm for detecting fault of longitudinal controller in autonomous vehicles. Guaranteeing safety in fault situation is essential because electronic devices in vehicle are dependent each other. Several methods like alarm to driver, ceding control to driver, and emergency stop are considered to cope with fault. This research investigates the fault monitoring process in fail-safe system, for controller which is responsible for accelerating and decelerating control in vehicle. Residual is computed using desired acceleration control command and actual acceleration, and detection of its abnormal increase leads to the decision that system has fault. Before computing residual for controller, health monitoring process of acceleration signal is performed using hardware and analytic redundancy. In fault monitoring process for controller, a process model which is fitted using driving data is considered to improve the performance. This algorithm is simulated via MATLAB tool to verify performance.

• The KIPS Transactions:PartA
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• v.12A no.1 s.91
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• pp.53-58
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• 2005

The use of computers for control and monitoring of industrial process has expanded greatly in recent years. The computer used in such applications is shared between a certain number of time-critical control and monitor function and non time-critical batch processing job stream. Embedded systems encompass a variety of hardware and software components which perform specific function in host computer. Many embedded system must respond to external events under certain timing constraints. Failure to respond to certain events on time may either seriously degrade system performance or even result in a catastrophe. In the design of real-time embedded system, decisions made at the architectural design phase greatly affect the final implementation and performance of the system. Flexibility indicates how well a particular system architecture can tolerate with respect to satisfying real-time requirements. The degree of flexibility of real-time system architecture indicates the capability of the system to tolerate perturbations in timing related specifications. Given degree of flexibility, one may compare and rank different implementations. A system with a higher degree of flexibility is more desirable. Flexibility is also an important factor in the trade-off studies between cost and performance. In this paper, it is identified the need for flexibility function and shows that the existing real-time analysis result can be effective. This paper motivated the need for a flexibility for the efficient analysis of potential design candidates in the architectural design exploration or real time embedded system.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.87-96
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• 2019

In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.34-43
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• 2000

Replicated data that is used for fault tolerant distributed system requires replica control protocol to maintain data consistency. The one of replica control protocols is quorum consensus method which accesses replicated data by getting majority approval. If site failure or communication link failure occurs and any one can't get quorum consensus, it degrades the availability of data managed by quorum consensus protocol. So it needs for ghost to replace the failed site. Because ghost is not full replica but process which has state information using meta data, it is important to simplify meta data. In order to maintain availability and simplify meta data, we propose a method to use cohort set as ghost's meta data. The proposed method makes it possible to organize meta data in 2N+logN bits and to have higher availability than quorum consensus only with cohort set and dynamic linear voting protocol. Using Markov model we calculate proposed method's availability to analyze availability and compare it with existing protocols.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of logarithmic hazard learning effects property.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.980-984
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• 2010

Exploring microRNA (miRNA) and mRNA regulatory interactions may give new insights into diverse biological phenomena. Recently, miRNAs have been discovered as important regulators that play a major role in various cellular processes. Therefore, it is essential to identify functional interactions between miRNAs and mRNAs for understanding the context- dependent activities of miRNAs in complex biological systems. While elucidating complex miRNA-mRNA interactions has been studied with experimental and computational approaches, it is still difficult to infer miRNA-mRNA regulatory modules. Here we present a novel method, termed layered hypernetworks (LHNs), for identifying functional miRNA-mRNA interactions from heterogeneous expression data. In experiments, we apply the LHN model to miRNA and mRNA expression profiles on multiple cancers. The proposed method identifies cancer-specific miRNA-mRNA interactions. We show the biological significance of the discovered miRNA- mRNA interactions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.72-77
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• 2017

This paper focuses on the development of a supporting S/W tool for the automated design of an automotive press trim die. To define the die design process based on automation, we analyze the press die design process of the current industry and group repetitive works in the 3D modeling process. The proposed system consists of two modules, namely the template models of the trim steel parts and UI function for their auto-positioning. Four kinds of template models are developed to adapt to various situations and the rules of the interaction formula which are used for checking and correcting the directions of the datum point, datum curve, datum plane are implemented to eliminate errors. The system was developed using CATIA Knowledgeware, CAA(CATIA SDK) and Visual C++, in order for it to function as a plug-in module of CATIA V5, which is one of the major 3D CAD systems in the manufacturing industry. The developed system was tested by applying it to various panels of current automobiles and the results showed that it reduces the time-cost by 74% compared to the traditional method.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.129-136
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• 2020

Recognizing finger movements have been used as a intuitive way of human-computer interaction. In this study, we implement an wearable device for finger motion recognition and evaluate the accuracy of several ML (Machine learning) techniques. Not only HMM (Hidden markov model) and DTW (Dynamic time warping) techniques that have been traditionally used as time series data analysis, but also NN (Neural network) technique are applied to compare and analyze the accuracy of each technique. In order to minimize the computational requirement, we also apply the pre-processing to each ML techniques. Our extensive evaluations demonstrate that the NN-based gesture recognition system achieves 99.1% recognition accuracy while the HMM and DTW achieve 96.6% and 95.9% recognition accuracy, respectively.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.1-7
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• 2019

As the cloud environment has become more prevalent among large companies, small and medium-sized companies are also trying to utilize various technologies (IoT, blockchain, etc.) that use cloud services as a way to coexist with large companies. In this paper, a blockchain-based IoT information collection model is proposed to efficiently handle large volumes of IoT data produced by small businesses in order to improve information efficiency of SMEs. The proposed model allowe d small businesses to improve their production efficiency by independently creating groups of the same information so that data that could be generated at the endpoints of small businesses can be block-chained and forwarded to the data center for analysis. In addition, the proposed model's performance assessment was assumed to handle the production throughput of data processed in IoT for small and medium businesses, not large enterprises, so the link between large volumes of data processed in the proposed model could be maintained evenly. One of the biggest features of the proposed model is the ability to expand processes to efficiently control the information of prod ucts produced, as well as the productivity of small and medium enterprises.

• Korean Journal of Construction Engineering and Management
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• v.15 no.3
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• pp.47-57
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• 2014

LNG plant projects tend to be implemented in overseas owing to its characteristics, so their project management scheme is somewhat different from those of general projects. Value chain in a LNG plant project includes exploration/production of gases, physical liquefaction/chemical conversion processes, transportation and storage. Key factors in the chain include liquefaction process (including ultra-low temperature liquefaction) to convert natural gas into liquid materials or fuel, and Front End Engineering Design (FEED) package, as well as Engineering, Procurement and Construction (EPC) technology comprising control, operation and construction. Success of a complex LNG plant project implemented in overseas depends on decision-making process in project management. Accordingly, to develop a decision-making model in of plant construction, the study extracted none factors in project management by EPC stage and assessed importance of each factor. The result showed that items in both project management and project risk management are important. Especially, the study developed a decision-making model in the construction stage of a LNG plant project based on the project management factors and importance assessment. The developed decision-making model would lay groundwork in building a decision-making system in construction stage of project management.