• Journal of Information Processing Systems
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• v.17 no.3
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• pp.537-555
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• 2021

Many researchers have carried out studies related to programming languages since the beginning of computer science. Besides programming with traditional programming languages (i.e., procedural, object-oriented, functional programming language, etc.), a new paradigm of programming is being carried out. It is programming with natural language. By programming with natural language, we expect that it will free our expressiveness in contrast to programming languages which have strong constraints in syntax. This paper surveys the approaches that generate source code automatically from a natural language description. We also categorize the approaches by their forms of input and output. Finally, we analyze the current trend of approaches and suggest the future direction of this research domain to improve automatic code generation with natural language. From the analysis, we state that researchers should work on customizing language models in the domain of source code and explore better representations of source code such as embedding techniques and pre-trained models which have been proved to work well on natural language processing tasks.

• Journal of Ship and Ocean Technology
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• v.12 no.4
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• pp.7-19
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• 2008

In preliminary ship design, a parametric study is a more realistic way to explore design space and analyze design problem than an optimization technique due to time-consuming computational work or a difficulty in incorporating all constraints into the optimization formulation. In the parametric study, feasible alternatives are examined in various aspects; the best one can be selected. Among the aspects, the strength assessment by FE analysis is an essential process in the ship design. This paper proposes a system to facilitate a parametric study for FE model based on design of experiment (DOE). It works on a FE pre-processor environment and assists a user to define a parametric study by interacting with FE model. It also provides an interface module with a FE solver in order to control the input file and extract predefined FE results from the output file. Based on the proposed system, a better understating and a better design are expected to be achieved.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.79-84
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• 1996

The robust controller for the nuclear reactor power control system is designed. The reactor model is set up by use of the point kinetics equations and the singly lumped energy balance equations. Since the model is different from the actual plant, the controller which makes the system robust is necessary. The perturbation of the actual plant is investigated with respect to several possible sources of uncertainty. Then the overall system is configured into the two port model and the $H_{\infty}$ controller is designed. The loop shaping and the permissible control rod speed are considered as the design constraints. The designed $H_{\infty}$ controller provides the sufficient margins for the robustness, and the system output as well as the control input satisfy their relevant requirements.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.209-212
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• 2003

In this paper, we proposed new speech feature parameter through parts-based feature extraction of speech spectrum using Non-Negative Matrix Factorization (NMF). NMF can effectively reduce dimension for multi-dimensional data through matrix factorization under the non-negativity constraints, and dimensionally reduced data should be presented parts-based features of input data. For speech feature extraction, we applied Mel-scaled filter bank outputs to inputs of NMF, than used outputs of NMF for inputs of speech recognizer. From recognition experiment result, we could confirm that proposed feature parameter is superior in recognition performance than mel frequency cepstral coefficient (MFCC) that is used generally.

• Elastomers and Composites
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• v.57 no.4
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• pp.147-156
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• 2022

In this study, we chose a flat die to optimize a general die geometry. The optimization was aimed at obtaining a uniform velocity distribution across the exit of the die. For the optimization, the input and output design parameters were randomly computed, and response surfaces were generated to obtain statistical data for the minimum and maximum sensitivities computed during optimization. Subsequently, object functions with constraints were numerically computed to obtain the minimum errors in the velocity difference (i.e., variable "Outp" in this study). Finally, we obtained the candidate optimized dataset. Note that the current numerical computations were simultaneously conducted for an entire extruder, i.e., screw plus die. The numerical outlet velocity distributions in the modified die geometry tended to be much more uniform than the conventional distributions in the current optimization processes for this specific flat die.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.562-567
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• 2006

Model Predictive Control(MPC) system uses the current input which minimizes the difference between the desired output and the estimated output in the receding horizon scheme. In many cases (for example, system with constraints or nonlinear system), however, it is not easy to find the optimal solution to the above problem. In this paper, we show that real number coding genetic algorithm can be used to solve the optimal problem for MPC effectively. Also, we show by simulation that the real coding algorithm is mote natural and advantageous than the digital coding one.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.768-770
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• 1996

This paper propose neural network which is one of self-organizing techniques. It is composed neural network controller as input signal is error and change of error which is optimal output, and is learned system by using a error back-propagation learning algorithm is one of error mimizing learning methods. In order to achieve practical real time control reduce on learning time, it is applied to load-frequency control of nonlinear power system with using a moment learning method. It is described in such a case considering constraints for a rate of increace generation-rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.5
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• pp.443-450
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• 2013

We consider user pairing and resource allocation for the uplink of cellular systems employing virtual multiple input multiple output (MIMO). As a multiple access scheme, discrete Fourier transform spread orthogonal frequency division multiple access (DFTS-OFDMA) is adopted for more flexible resource allocation than single carrier (SC)-OFDMA adopted in the Long Term Evolution (LTE) system. We formulate the optimization problems of user pairing and resource allocation to maximize the throughput of the DFTS-OFDMA system under different constraints. The DFTS-OFDMA allowing non-contiguous subcarrier allocation and redundant user assignment provides a better throughput than the SC-FDMA at lower complexity in finding the optimal solution but at the cost of the increased control information indicating the allocated resources.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1108-1121
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• 2019

The non-inverting buck-boost converter (NIBB) is a step-up and step-down DC-DC converter suitable for wide-input-voltage-range applications. However, when the input voltage is close to the output voltage, the NIBB needs to operate in the buck-boost mode, causing a significant efficiency reduction since all four switches operates in the PWM mode. Considering both the current stress limitation and the efficiency optimization, a novel design methodology for the optimal phase-shift modulation of a NIBB in the buck-boost mode is proposed in this paper. Since the four switches in the NIBB form two bridges, the shifted phase between the two bridges can serve as an extra degree of freedom for performance optimization. With general phase-shift modulation, the analytic current expressions for every duty ratio, shifted phase and input voltage are derived. Then with the two key factors in the NIBB, the converter efficiency and the switch current stress, taken into account, an objective function with constraints is derived. By optimizing the derived objective function over the full input voltage range, an offline design methodology for the optimal modulation scheme is proposed for efficiency optimization on the premise of current stress limitation. Finally, the designed optimal modulation scheme is implemented on a DSPs and the design methodology is verified with experimental results on a 300V-1.5kW NIBB prototype.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.299-306
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• 2003

This paper formulates a problem of embedded real-time system re-engineering, and presents its solution approach. Embedded system re-engineering is defined as a development task of meeting performance requirements newly imposed on a system after its hardware and software have been fully implemented. The performance requirements nay include a real-time throughput and an input-to-output latency. The proposed solution approach is based on a bottleneck analysis and nonlinear optimization. The inputs to the approach include a system design specified with a process network and a set of task graphs, task allocation and scheduling, and a new real-time throughput requirement specified as a system's period constraint. The solution approach works in two steps. In the first step, it determines bottleneck precesses in the process network via estimation of process latencies. In the second step, it derives a system of constraints with performance scaling factors of processing elements being variables. It then solves the constraints for the performance staling factors with an objective of minimizing the total hardware cost of the resultant system. These scaling factors suggest the minimal cost hardware upgrade to meet the new performance requirement. Since this approach does not modify carefully designed software structures, it helps reduce the re-engineering cycle.