• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.114-130
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• 2006

This paper deals with complexity theory to describe amphibious warfare situation using EINSTein (Enhanced ISAAC Neural Simulation Tool) simulation model. EINSTein model is an agent-based artificial "laboratory" for exploring self-organized emergent behavior in land combat. Many studies have shown that existing Lanchester equations used in most war simulation models does not describe changes of combat. Future warfare will be information warfare with various weapon system and complex combat units. We have compared and tested combat results with Lanchester models and EINSTein model. Furthermore, the EINSTein model has been applied and analyzed to amphibious warfare model such as amphibious assault and amphibious sudden attack. The results show that the EINSTein model has a possibility to apply and analyze amphibious warfare more properly than Lanchester models.

• ETRI Journal
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• v.38 no.2
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• pp.326-336
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• 2016

We propose and describe new error control algorithms for redundant residue number systems (RRNSs) and residue number system product codes. These algorithms employ search techniques for obtaining error values from within a set of values (that contains all possible error values). For a given RRNS, the error control algorithms have a computational complexity of $t{\cdot}O(log_2\;n+log_2\;{\bar{m}})$ comparison operations, where t denotes the error correcting capability, n denotes the number of moduli, and ${\bar{m}}$ denotes the geometric average of moduli. These algorithms avoid most modular operations. We describe a refinement to the proposed algorithms that further avoids the modular operation required in their respective first steps, with an increase of ${\lceil}log_2\;n{\rceil}$ to their computational complexity. The new algorithms provide significant computational advantages over existing methods.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.1087-1094
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• 1987

In this paper, we describe about polygon resizing porblem where the given polygons are expanded or shrunk in two dimensional plane. First, the definition of polygon resizing and it's problems are given, then the enhanced XY method is proposed: the polygon resizing can be completed in one directional sweep of plane only, usisng enhanced plane sweep method. The time complexity is 0(n log n), and space complexity 0(\ulcorner), where n is the number of verties of polygons. The applications of polygon resizing to the mask artwork processing and layout verification are discussed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.1-13
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• 1993

In this paper, the problems of the conventional special-purpose array processor such as the deficiency of flexibility have been investigated. Then, a new modified methodology has been suggested and applied to obtain the common solution of the three typical App algorithms like SP(Shortest Path), TC(Transitive Closure), and MST(Minimun Spanning Tree) among the various APP algorithms using the similar method to obtain the solution. In the newly proposed APP parallel algorithm, real-time Processing is possible, without the structure enhancement and the functional restriction. In addition, we design 2-demensional bit-parallel low-triangular systolic array processor and the 1-PE in detail. For its evaluation, we consider its computational complexity according to bit-processing method and describe relationship of total chip size and execution time. Therefore, the proposed processor obtains, on which a large data inputs in real-time, 3n-4 execution time which is optimal o(n) time complexity, o(n$^{2}$) space complexity which is the number of total gate and pipeline period rate is one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1419-1426
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• 1997

A new SCEE(Syndrome Check Error Estimation) decoding method for convolutional code and concatenated SCEE/RS (Reed-Solomon) conding scheme are proposed. First, we describe the operation of the decoding steps in the proposed algorithm. Then deterministic values on the decoding operation are drived when some combination of predecoder-reencoder is used. Computer simulation results show that the compuatational complexity of the proposed SCEE decoder is significantly reduced compared to that of conventional Viterbi-decoder without degratation of the $P_{e}$ performance. Also, the concatenated SCEE/RS decoder has almost the same complexity of a RS decoder and its coding gain is higher than that of soft decision Viterbi or RS decoder respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1449-1454
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• 2003

For many industrial processes there are good static models used for process design and steady state operation. By using system identification techniques, it is possible to obtain black-box models with reasonable complexity that describe the system well in specific operating conditions [1]. But black-box models using inductive modeling(IM) is not suitable for model based control because they are only valid for specific operating conditions. Thus we need to use deductive modeling(DM) for a wide operating range. Furthermore, deductive modeling is several merits: First, the model is possible to be modularized. Second, we can increase and decrease the model complexity. Finally, we are able to use model for plant design. Power plant must be able to operate well at dramatic load change and consider safety and efficiency. This paper proposes a simplified nonlinear model of an industrial boiler, one of component parts of a power plant, by DM method and applies optimal control to the model.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.11 s.353
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• pp.95-117
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• 2006

In this paper, we describe the optimization of the link-level performance and the complexity of floating-point and fixed-point methods in IEEE 802.16e OFDMA/TDD mobile modem. In floating-point design, we propose the channel estimation methods for downlink traffic channel and select the optimized method using computer simulation. So we also propose efficent algorithms for time and frequency synchronization, Digital Front End and CINR estimation scheme to optimize the system performance. Furthermore, we describe fixed-point method of uplink traffic and control channels. The superiority of the proposed algorithm is validated using the performances of Detection, False Alarm, Missing Probability and Mean Acquisition Time, PER Curve, etc. For fixed-point design, we propose an efficient methodology for optimized fixed-point design from floating-point At last, we design fixed-point of traffic channel, time and frequency synchronization, DFE block in uplink and downlink. The tradeoff between performance and complexity are optimized through computer simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2497-2517
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• 2020

For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.68-70
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• 2004

In this paper we develop an adaptive interface between video compression and transission protocols to handle QoS fluctuations that are common to mobile communication systems. We consider various generic design alternatives for QoS adaptation and identify 'QoS negotiation' as the most promissing. This method gives the best possibilities to obtain system-wide efficiency. To handle the indued system complexity we apply a design philosophy (called ARC) that separates implementation dependencies by introducing QoS interfaces between system modules. In the ARC phlosophy the implementation details are hidden in the subsystems. To assure efficient adaptation, the QoS must be negotiated between modules. We select the QoS parameters that are both necessary and sufficient for efficient negotiation between the video encoder and protocol modules. We describe the relation between the QoS parameters at the interface and the internal parameters of common video coding methods and protocol elements. Furthermore, we describe a negotiation procedure that allows a system-wide optimum to emerge.