• Journal of fish pathology
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• v.34 no.2
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• pp.243-248
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• 2021

Offshore wind power generation is an energy generation field that is rapidly developing owing to the increasing demand for clean energy. However, the physiological response of fish to the underwater noise generated during construction or operation of wind turbines is unclear. We confirmed the effects of sound pressures of 125, 135, 145, and 155 dB/µPa, including 140 dB/µPa (the standard sound pressure for noise damage recognition in South Korea), through serum analysis in rock bream (Oplegnathus fasciatus). High mortality induced by reduced immunity through artificial infection after stimulation was confirmed. These results suggest that rock bream is negatively affected by the noise generated during the construction of offshore wind power plants.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.59-64
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• 2020

Occasionally, MODEM test in satellite communication systems are needed. But Rx terminals in satellite communications are designed to obtain high SNR generally, therefore artificial bad conditions and environments are demanded for the test. One of the typical method is satellite output power reduction. Using noise generator can be another method. However, these costs a lot of money, time, and procedures in reality. In order to overcome these problems, this paper proposes an artificial noise generation method for MODEM test in satellite communication systems. First of all, SNR of a general heterodyne Rx terminal is calculated. Based on the calculation, a new model which is including variable attenuator is proposed to increase noise level. Simulation results illustrate the variable attenuator can control SNR, and these show that MODEM test in satellite communication systems be possible.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.90-95
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• 2023

With the rapid development of deep learning and artificial intelligence, generative models have achieved remarkable success in the field of image generation. By combining the stable diffusion method with Web UI technology, a novel solution is provided for the application of AI painting generation. The application prospects of this technology are very broad and can be applied to multiple fields, such as digital art, concept design, game development, and more. Furthermore, the platform based on Web UI facilitates user operations, making the technology more easily applicable to practical scenarios. This paper introduces the basic principles of Stable Diffusion Web UI technology. This technique utilizes the stability of diffusion processes to improve the output quality of generative models. By gradually introducing noise during the generation process, the model can generate smoother and more coherent images. Additionally, the analysis of different model types and applications within Stable Diffusion Web UI provides creators with a more comprehensive understanding, offering valuable insights for fields such as artistic creation and design.

• Journal of Industrial Convergence
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• v.16 no.1
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• pp.35-40
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• 2018

The procedural generation algorithm is an algorithm that automatically generates a content to be used in a game by repeatedly executing a series of rules. As the size of the game increases, the amount of content used in the game increases. Accordingly, artificial intelligence research is actively conducted to automatically generate game contents using game artificial intelligence such as procedural generation. In this paper, we propose an algorithm to create 3D game world using procedural generation. The proposed algorithm generates a two-dimensional contour in which the path is naturally connected using Perlin-Noise whose noise is gradually changed. A three-dimensional Height-Map is created based on the generated two-dimensional contour lines. The generated Height-Map show that the shape of the map is normal and that the player is able to move around all the sections as in the game world created by hand. In the future, we will improve the performance of algorithms and apply them to game.

• ETRI Journal
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• v.42 no.6
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• pp.951-964
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• 2020

This paper presents a lightweight true random number generator (TRNG) using beta radiation that is useful for Internet of Things (IoT) security. In general, a random number generator (RNG) is required for all secure communication devices because random numbers are needed to generate encryption keys. Most RNGs are computer algorithms and use physical noise as their seed. However, it is difficult to obtain physical noise in small IoT devices. Since IoT security functions are required in almost all countries, IoT devices must be equipped with security algorithms that can pass the cryptographic module validation programs of each country. In this regard, it is very cumbersome to embed security algorithms, random number generation algorithms, and even physical noise sources in small IoT devices. Therefore, this paper introduces a lightweight TRNG comprising a thin-film beta-radiation source and integrated circuits (ICs). Although the ICs are currently being designed, the IC design was functionally verified at the board level. Our random numbers are output from a verification board and tested according to National Institute of Standards and Technology standards.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.127-138
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• 2005

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.447-454
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• 1998

The paper describes the second half of the research for the development of Neural-Networks-based model for the generation of an Artificial earthquake and a Response Spectrum(NNARS). Based on the redefined traditional processes related to the generation of an earthquake acceleration response spectrum and design spectrum, four neural-networks-based models are proposed to substitute the traditional processes. RS_NN tries to directly generate acceleration response spectrum with basic data that are magnitude, epicentral distance, site conditions and focal depth. The test results of RS_NN are not good because of the characteristics of white noise, which is randomly generated. ARS_NN solve this problem by the introduction of the average concept. IARS_NN has a role to inverse the ARS_NN, so that is applied to generate a ground motion accelerogram compatible with the shape of a response spectrum. Additionally, DS_NN directly produces design spectrum with basic data. As these four neural networks are simulated as a step by step, the paper describes the methods to generate a response spectrum and a design spectrum using the neural networks.

• Journal of KSNVE
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• v.8 no.2
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• pp.239-250
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• 1998

Traditionally, intake noise from internal combustion engine has not recevied much attention compared to exhaust noise. But nowadays, intake noise is a major contributing factor to automotive passenger compartment noise levels. The main objective of this paper is to identify the mechanism of generation, propagation and radiation of the intake noise. With a simplest geometric model, one of the main noise sources for the intake stroke is found to be the pressure surge, which is generated after intake valve closing. The pressure surge, which has the nonlinear acoustic behavior, propagates and radiates with relatively large amplitude. In this paper, unsteady compressible Navier-Stokes equations are employed for the intake stroke of axisymmetric model having a single moving cylinder and a single moving intake valve. To simulate the periodic motion of the piston and the valve, unsteady deforming mesh algorithm is employed and Thompson's non-reflecting boundary condition is applied to the radiation field. In order to resolve the small amplitude waves at the radiation field, essentially non-oscillatory(ENO) schemes with an artificial compression method (ACM) are used.

• Journal of architectural history
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• v.31 no.1
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• pp.41-50
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• 2022

Traditional wooden buildings deform over time and are vulnerable to fire or earthquakes. Therefore, traditional wooden buildings require continuous management and repair, and securing architectural drawings is essential for repair and restoration. Unlike modernized CAD drawings, traditional wooden building drawings scan and store hand-drawn drawings, and in this process, many noise is included due to damage to the drawing itself. These drawings are digitized, but their utilization is poor due to noise. Difficulties in systematic management of traditional wooden buildings are increasing. Noise removal by existing algorithms has limited drawings that can be applied according to noise characteristics and the performance is not uniform. This study presents deep artificial neural network based noised reduction for architectural drawings. Front/side elevation drawings, floor plans, detail drawings of Korean wooden treasure buildings were considered. First, the noise properties of the architectural drawings were learned with both a cycle generative model and heuristic image fusion methods. Consequently, a noise reduction network was trained through supervised learning using training sets prepared using the noise models. The proposed method provided effective removal of noise without deteriorating fine lines in the architectural drawings and it showed good performance for various noise types.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.628-649
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• 2017

Security and resource-saving are both demands of the fifth generation (5G) wireless networks. In this paper, we study the secrecy spectrum efficiency (SSE) and secrecy energy efficiency (SEE) of a K-tier massive multiple-input multiple-output (MIMO) enabled heterogeneous cellular network (HetNet), in which artificial noise (AN) are employed for secrecy enhancement. Assuming (i) independent Poisson point process model for the locations of base stations (BSs) of each tier as well as that of eavesdroppers, (ii) zero-forcing precoding at the macrocell BSs (MBSs), and (iii) maximum average received power-based cell selection, the tractable lower bound expressions for SSE and SEE of massive MIMO enabled HetNets are derived. Then, the influences on secrecy oriented spectrum and energy efficiency performance caused by the power allocation for AN, transmit antenna number, number of users served by each MBS, and eavesdropper density are analyzed respectively. Moreover, the analysis accuracy is verified by Monte Carlo simulations.