• Advances in Computational Design
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• v.5 no.4
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• pp.445-465
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• 2020

This paper presents a study conducted with the aim of developing a model of tendering based on a technique of artificial intelligence by managing and controlling the factors of success or failure of construction projects through the evaluation of the process of invitation to tender. Aiming to solve this problem, analysis of the current environment based on SWOT (Strengths, Weaknesses, Opportunities, and Threats) is first carried out. Analysis was evaluated through a case study of the construction projects in Algeria, to bring about the internal and external factors which affect the process of invitation to tender related to the construction projects. This paper aims to develop a mean to identify threats-opportunities and strength-weaknesses related to the environment of various national construction projects, leading to the decision on whether to continue the project or not. Following a SWOT analysis, novel artificial intelligence models in forecasting the project status are proposed. The basic principal consists in interconnecting the different factors to model this phenomenon. An artificial neural network model is first proposed, followed by a model based on fuzzy logic. A third model resulting from the combination of the two previous ones is developed as a hybrid model. A simulation study is carried out to assess performance of the three models showing that the hybrid model is better suited in forecasting the construction project status than RNN (recurrent neural network) and FL (fuzzy logic) models.

• Korean System Dynamics Review
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• v.12 no.4
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• pp.125-156
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• 2011

The information service management models developed thus far have put their focuses mostly on technical dimensions of information systems (IS), finding their rationale from the goods-dominant logic (GDL) that IS as goods has value in itself. Information systems, however, is nothing more than a mechanism by which value is delivered to the users. According to the service-dominant logic (SDL), value is created and determined not at the time serve is made by the providers but at the time it is consumed by the users. The users therefore should be regarded as active value creators not as passive consumers of the value delivered by the providers. Based on the service-dominant logic, DISQM (Dynamic Information Service Quality Model) is developed. DISQM's backbone is designed in causal loop diagrams referring to and reinterpreting in systems thinking the 'Parasuraman, Zeithaml & Berry's GAP Model' and 'SERVQUAL' as an operational tool for the GAP Model, and the main IS success constructs are mapped onto the model exploiting the 'DeLone & MacLean's IS Success Model'. With VENSIM simulation software, this paper also shows how DISQM works in computer-simulation settings. After confirming DISQM's validity with the base simulation run, two scenarios are developed for the exemplary purpose and tested in terms of IS quality, service quality, and net benefits from the service for the public information service. Implications from the simulation runs are also discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.34-44
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• 1997

The Belgian Nuclear Research Centre(SCK${\cdot}$CEN) has been a pioneer of the peaceful uses of nuclear energy after over forty years of existence. Recently, SCK${\cdot}$CEN's financial support of doctoral and postdoctoral research in close collaboration with universities has been a vital ingredient for securing a quality profile committed to the pursuit of execllence. FLINS, Fuzzy Logic and Intelligent technologies in Nuclear Science, was initially built within one of the postdoctoral research project at SCK${\cdot}$CEN. Among SCK${\cdot}$CEN's activities which will have an important impact on its scientific future, the application of fuzzy logic and intelligent technologies in nuclear science and engineering opens new domains in radiation protection, safety assessment, human reliability, nuclear reactor control, waste and disposal, etc. In this paper, we review the available literature on fuzzy logic in nuclear applications. We then present the initiative of R&D on fuzzy logic applications at SCK${\cdot}$CEN, namely, (1) safety control for a nuclear reactor, and (2) a safety evaluation model for nuclear transmission lines. By these two examples of nuclear applications, we illustrate the potential use of fuzzy logic in nuclear safety issues.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.5
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• pp.180-187
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• 1996

This paper describes a post-layout simulation method using VHDL and C for verifying the architecture of antifuse-based FPGAs and the dedicated CAD system. An antifuse-based FPGA consists of programming circuitry including decoding logic, logic modules, segmented tracks, antifuses and I/O pads. The VHDL model which includes all these elements is used for logic verification and programming verification of the implemented circuit by reconstructing the logic circuit from the bit-stream generated from layout tool. The implemented circuit comprises of logic modules and routing networks. Since the routing delay of the complex networks is comparable to the delay of the logic module in the FPGA, the accurate post-layout simulation is essential to the FPGA system. In this paper, the C program calculates the delay of the routing netowrks using SPICE, elmore or horowitz delay models and the results feedback to the VHDL simulation. Critical path anc be found from this post-layout simulation results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.74-82
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• 2015

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.1
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• pp.48-55
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• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. In additionally, this algorithm adjusts the driving torque for restraining re-slip. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy, These procedures are implemented using a Pioneer 2-DXE wheeled robot parameter.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.225-228
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• 2002

When the fuzzy logic controller (FLC), which is designed based on the plant model, is applied to the real control system, satisfactory control performance may not be attained due to modeling errors from the plant model. In such cases, the control parameters of the controller must be adjusted to enhance control performance. Until now, the trial and error method has been used, consuming much time and effort. To resolve such problem, response surface methodology (RSM), a new method of adjusting the control parameters of the controller, is suggested. This method is more systematic than the previous trial and error method, and thus optimal solutions can be provided with less tuning. First, the initial values of the control parameters were determined through the plant model and the optimization algorithm. Then, designed experiments were performed in the region around the initial values, determining the optimal values of the control parameters which satisfy both the rise time and overshoot simultaneously.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.30-32
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• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy.

• Transactions of Materials Processing
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• v.8 no.2
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• pp.208-215
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• 1999

To increase rolling yields by minimizing trimming losses of hot-rolled plate, optimization logic for the edger model has been developed. The logic to determine optimum edging amount model has been formulated on the basis of actual production rolling data. In case of broadside rolling, the fish tail shape at the sides of plate was better for reducing the crop loss and this could be achieved when the edging amount of broadside rolling was increased. At a given broadside rolling ratio, methodology to determine optimum edging amount for the finish rolling which could minimize the width deviation of plate were systematically derived. Therefore, for a given broadside rolling condition and the permissible tolerance in width deviation of plate, it was possible to optimize the edging amount in finish rolling to maximize rolling yields. The application of optimization logic in this study increased rolling yields from approximately 10% to 30% at various longitudinal eding raitos.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.273-281
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• 2022

In this paper, we propose a robot sound recognition system that detects various sound events. The proposed system is designed to detect various sound events in real-time by using a microphone on a robot. To get real-time performance, we use a VGG11 model which includes several convolutional neural networks with real-time normalization scheme. The VGG11 model is trained on augmented DB through 24 kinds of various environments (12 reverberation times and 2 signal to noise ratios). Additionally, based on random forest algorithm, a decision logic is also designed to generate event signals for robot applications. This logic can be used for specific classes of acoustic events with better performance than just using outputs of network model. With some experimental results, the performance of proposed sound recognition system is shown on real-time device for robots.