• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.127-132
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• 1992

To relize the future intelligent robot the development of a special-purpose processor for a coordinate transformation is evidently challenging task. In this case the complexity of a hardware architecture strongly depends on the adopted algorithm. In this paper we have used an inverse kinemetics algorithm based on incremental unit computation method. This method considers the 3-axis articulated robot as the combination of two types of a 2-axis robot: polar robot and 2-axis planar articulated one. For each robot incremental units in the joint and Cartesian spaces are defined. With this approach the calculation of the inverse Jacobian matrix can be realized through a simple combinational logic gate. Futhermore, the incremental computation of the DDA integrator can be used to solve the direct kinematics. We have also designed a hardware architecture to implement the proposed algorithm. The architecture consists of serveral simple unitsl. The operative unit comprises several basic operators and simple data path with a small bit-length. The hardware architecture is realized byusing the EPLD. For the straight-line motion of the KAIST arm we have obtained maximum end effector's speed of 12.6 m/sec by adopting system clock of 8 MHz.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.7
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• pp.20-29
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• 1998

As the packing density of ICs in recent submicron IC design increases, interconnects gain importance. Because interconnects directly affect on two major components of circuit performance, power dissipation and operating speed, circuit engineers are concerned with the optimal design of interconnects and the aid tool to design them. When circuit models of interconnects are given (including geometry and material information), the analysis process for the given structure is not an easy task, but conversely, it is much more difficult to design an interconnect structure with given circuit characteristics. This paper focuses on the latter process that has not been foucsed on much till now due to the complexity of the problem, and prsents a design aid tool(DATOIS) to synthesize interconnects. this tool stroes the circuit performance parameters for normalized interconnect geometries, and has two oeprational modes:analysis mode and synthesis mode. In the analysis mode, circuit performance parameters are obtained by searching the internal database for a given geometry and interpolates results if necessary . In thesynthesis mode, when a given circuit performance parameter satisfies a set of geometry condition in the database, those geometry structures are printed out.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.2
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• pp.103-110
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• 2010

Due to the increasing amount of electronic control system in a vehicle, the automotive software is increasingly sophisticated and complicated. Therefore it may be faced a time critical problem caused by its complexity. In order to solve such problems, the automotive electronic system can use a real-time scheduling mechanism based on predictability. We first consider the standard specification of the AUTOSAR OS and uC/OS-II such as its scheduling theory with time determinism. In this paper, we propose the scheduling algorithm to be conformable to a conformance class of OSEK/VDX specification. Algorithm analysis shows that our scheduling algorithm outperforms an existing Trampoline OS by intuition.

• Asia pacific journal of information systems
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• v.9 no.2
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• pp.117-132
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• 1999

Common system deployment is one of the global information systems strategies of a multinational corporation for large-scale development that can provide economies of scale and optimal use of scarce technical expertise. But while the same (headquarter) team implements the same system, the resulting efficiencies of those projects differ widely among the subsidiaries. This paper focuses on the differences between the efficiencies of these implementation projects. Eight prepropositions about the factors causing the differences have been developed from the previous research. These prepropositions are explored through a case study on the twelve overseas subsidiaries of a multinational electronic corporation headquartered in Korea. We found that three factors(autonomy of subsidiary, complexity of task, experience level of users) have strong relevant relationships and two factors(level of subsidiary country, level of process formality) have partial relevant relationships with the implementation outcome.

• Journal of Computing Science and Engineering
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• v.12 no.1
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• pp.1-11
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• 2018

Human activities recognition is a challenging task due to its complexity of human movements and the variety performed by different subjects for the same action. This paper presents a recognition algorithm by using skeleton information generated from depth maps. Concatenating motion features and temporal constraint feature produces feature vector. Reducing dictionary scale proposes an improved fast classifier based on sparse representation. The developed method is shown to be effective by recognizing different activities on the UTD-MHAD dataset. Comparison results indicate superior performance of our method over some existing methods.

• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.39-48
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• 2020

Information-security management systems (ISMSs) are becoming very important, even for micro, small, and medium enterprises (MSMEs). However, implementing an ISMS is not an easy task. Many obstacles must be overcome, e.g., complexity, document tracking, competency management, and even changing cultures. The objective of our study is to provide ISMS application tools, based on ISO 27001:2013 ISM frameworks. The application was developed on the Odoo Open Enterprise Resource Planning platform. To validate its feasibility for future improvement, the application was implemented by an MSME company. For this implementation, information-security-related users gave their feedback through a questionnaire. The distributed feedback questionnaire consists of nine assessment parameters, covering topics from the application's technical aspects to users' experiences. Based on the questionnaire feedback, all users of the application were satisfied with its performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3096-3117
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• 2013

To execute the performance driven Grid applications, an effective and scalable workflow scheduling is seen as an essential. To optimize cost & makespan, in this paper, we propose a Scalable Cost-Time Trade-off (SCTT) model for scheduling workflow tasks. We have developed a heuristic algorithm known as Scalable Cost-Time Trade-off Scheduling (SCTTS) with a lower runtime complexity based on the proposed SCTT model. We have compared the performance of our proposed approach with other heuristic and meta-heuristic based scheduling strategies using simulations. The results show that the proposed approach improves performance and scalability with different workflow sizes, task parallelism and heterogeneous resources. This method, therefore, outperforms other methods.

• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.753-772
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• 2014

The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.13-23
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• 2006

The present study has investigated the patterns and the causes of safety -accidents on the accident-data in semiconductor Industries through near miss report the cases in the advanced companies. The ratio of incomplete actions to incomplete state was 4 to 6 as the cases of accidents in semiconductor industries in the respect of Human-ware, Hard- ware, Environment-ware and System-ware. The ratio of Human to machine in the attributes of semiconductor accident was 4 to 1. The study also investigated correlation among the system related to production, accident, losses and time. In semiconductor industry, we found that pattern of safety-accident analysis is organized potential, interaction, complexity, medium. Therefore, this study find out that semiconductor model consists of organization, individual, task, machine, environment and system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.209-215
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• 2014

Sequence tagging is the task of predicting frame-wise labels for a given input sequence and has important applications to diverse domains. Conventional methods such as maximum likelihood (ML) learning matches global features in empirical and model distributions, rather than local features, which directly translates into frame-wise prediction errors. Recent probabilistic sequence models such as conditional random fields (CRFs) have achieved great success in a variety of situations. In this paper, we introduce a novel discriminative CRF learning algorithm to minimize local feature mismatches. Unlike overall data fitting originating from global feature matching in ML learning, our approach reduces the total error over all frames in a sequence. We also provide an efficient gradient-based learning method via gradient forward-backward recursion, which requires the same computational complexity as ML learning. For several real-world sequence tagging problems, we empirically demonstrate that the proposed learning algorithm achieves significantly more accurate prediction performance than standard estimators.