• Nuclear Engineering and Technology
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• 제52권1호
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• pp.101-108
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• 2020

In order to solve the contradiction between requirements of high sampling rate for acquiring accurate energy information of pulses and large amount of data to be processed timely, the method with an algorithm to correct errors caused by reducing the sampling rate is normally used in front-end read-out system, which is conductive to extract accurate energy information from digitized waveform of pulse. The functions and effects of algorithms, which mainly include polynomial fitting with different fitting times, double exponential function fitting under different sampling modes, and integral area algorithm, are analyzed and evaluated, and some meaningful results is presented in this paper. The algorithm described in the paper has been used preliminarily in a prototype system of Positron Emission Tomography (PET) for heavy-ion cancer therapy facility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1448-1463
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• 2021

With the continuous development of cloud storage, plenty of redundant data exists in cloud storage, especially multimedia data such as images and videos. Data deduplication is a data reduction technology that significantly reduces storage requirements and increases bandwidth efficiency. To ensure data security, users typically encrypt data before uploading it. However, there is a contradiction between data encryption and deduplication. Existing deduplication methods for regular files cannot be applied to image deduplication because images need to be detected based on visual content. In this paper, we propose a secure image deduplication scheme based on hashing and clustering, which combines a novel perceptual hash algorithm based on Local Binary Pattern. In this scheme, the hash value of the image is used as the fingerprint to perform deduplication, and the image is transmitted in an encrypted form. Images are clustered to reduce the time complexity of deduplication. The proposed scheme can ensure the security of images and improve deduplication accuracy. The comparison with other image deduplication schemes demonstrates that our scheme has somewhat better performance.

• International Journal of Internet, Broadcasting and Communication
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• 제13권1호
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• pp.37-46
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• 2021

Recently, social technologies have been created to solve problems from businesses for the establishment of generational solidarity ecosystem in terms of employment, residential space, network and social capital, age, cognitive and environmental aspects. This is senior-friendly healthcare business system aimed at meeting the senior needs for health life to enjoy active consumption culture life even after retirement, becoming a catalyst for minimizing generational conflicts, preventing the cognitive and physical deterioration of seniority in the areas of life healthcare, fitness and well-aging, and expanding into systems necessary for seniority self-reliance. We would like to draw up the development and requirements of the concept of the service platform for the study of collective characteristics for generation solidarity with senior class and the establishment of a customized senior health life system for generation solidarity. This system is characterized by a platform that can prevent the decline of seniors' cognitive and physical functions and enhance emotional stability. It is significant in providing feedback on the risk perception index, fall index, and prevention training index information to the child through the analysis and extraction of the senior health index for risk perception, fall probability, and fall prevention.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.406-412
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• 2022

Scene classification of very high-resolution (VHR) imagery can attribute semantics to land cover in a variety of domains. Real-world application requirements have not been addressed by conventional techniques for remote sensing image classification. Recent research has demonstrated that deep convolutional neural networks (CNNs) are effective at extracting features due to their strong feature extraction capabilities. In order to improve classification performance, these approaches rely primarily on semantic information. Since the abstract and global semantic information makes it difficult for the network to correctly classify scene images with similar structures and high interclass similarity, it achieves a low classification accuracy. We propose a VHR remote sensing image classification model that uses extracts the global feature from the original VHR image using an EfficientNet-V2L CNN pre-trained to detect similar classes. The image is then classified using a multilayer perceptron (MLP). This method was evaluated using two benchmark remote sensing datasets: the 21-class UC Merced, and the 38-class PatternNet. As compared to other state-of-the-art models, the proposed model significantly improves performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4476-4491
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• 2021

Video service providers tend to face user network problems in the process of transmitting video streams. They strive to provide user with superior video quality in a limited bitrate environment. It is necessary to accurately determine the target bitrate range of the video under different quality requirements. Recently, several schemes have been proposed to meet this requirement. However, they do not take the impact of visual influence into account. In this paper, we propose a new multi-category model to accurately predict the target bitrate range with target visual quality by machine learning. Firstly, a dataset is constructed to generate multi-category models by machine learning. The quality score ladders and the corresponding bitrate-interval categories are defined in the dataset. Secondly, several types of spatial-temporal features related to VMAF evaluation metrics and visual factors are extracted and processed statistically for classification. Finally, bitrate prediction models trained on the dataset by RandomForest classifier can be used to accurately predict the target bitrate of the input videos with target video quality. The classification prediction accuracy of the model reaches 0.705 and the encoded video which is compressed by the bitrate predicted by the model can achieve the target perceptual quality.

• 한국표면공학회지
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• 제34권6호
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• pp.553-567
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• 2001

Electrodeposition technology is widely used in industry for various kinds of coatings. Modifications in this technology led to several processes to meet various requirements. Electrolysis in ionic liquids has many advantages such as low energy consumption of energy, low pollutant emission and low operating costs. Although ionic liquids have already been used in liquid/liquid extraction processes, only recently their use in electrodeposition was exploited. Electrochemical deposition of composites is an expanding area. Coupled with the progress in the synthesis of nanometric powder, this research will open a large number of innovative materials. Pulse current plating is another electrodeposition technique which yields improved coatings. Although electrodeposition is now regarded as an environmental non-friendly process, it is economically viable and has many inherent advantages. For certain applications, alternatives to electrodeposition have not yet been fully implemented. Hence, continued research in this technology is warranted. This article reviews some recent advances in electrodeposition technology. Aspects of electrodeposition such as electrolysis in ionic liquids, electrodeposition of composites, pulse current plating techniques, metal and alloy deposition, compound deposition and effects of additives are discussed in this review.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2024년도 춘계학술발표대회
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• pp.490-493
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• 2024

현재 다양한 분야에서 AI 가 사용되고 있다. 최근에는 소프트웨어공학 관점에서 요구 사항 분석에 Chat GPT 와 같은 LLM 모델을 적용하고 있다. 하지만 1) 대부분의 생성형 AI 는 불투명한 공정을 통해 3D 이미지가 생성하고, 3D 이미지를 생성할 때마다 다른 이미지를 생성한다. 이에 따라 동일한 인물이나 사물을 사용하고 싶은 사용자들은 동일한 객체가 들어간 그림을 일관성 있게 생성할 수 없다. 2) 또한 LLM 과 이미지 생성 AI 와의 결합이 시도 되고 있지만 문장 의미 분석 성능이 부족하다. 이를 해결하기 위해, 자연어 요구사항을 언어학적 기법을 통해 분석하고, 분석 결과를 기반으로 UML 시퀀스 다이어그램 및 3D 객체 생성 메커니즘을 제안한다. 즉 언어학적 분석 기법을 통해, 요구사항의 정확한 의미와 속성을 추출한다. 그런 다음 추출된 정보를 시퀀스 다이어그램과 매핑하여 3D 객체 이미지를 생성한다. 제안하는 방법을 통해 3D 객체 생성의 소프트웨어 개발 공정 사용으로 생산성을 높여 시간과 비용을 단축할 수 있을 것으로 기대한다.

• Journal of Astronomy and Space Sciences
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• 제41권2호
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• pp.79-85
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• 2024

Nowadays, the trend in lunar exploration missions is shifting from prospecting lunar surface to utilizing in-situ resources and establishing sustainable bridgehead. In the past, experiments were mainly focused on rover maneuvers and equipment operations. But the current shift in trend requires more complex experiments that includes preparations for resource extraction, space construction and even space agriculture. To achieve that, the experiment requires a sophisticated simulation of the lunar environment, but we are not yet prepared for this. Particularly, in the case of lunar regolith simulants, precise physical and chemical composition with a rapid development speed rate that allows different terrains to be simulated is required. However, existing lunar regolith simulants, designed for 20th-century exploration paradigms, are not sufficient to meet the requirements of modern space exploration. In order to prepare for the latest trends in space exploration, it is necessary to innovate the methodology for producing simulants. In this study, the basic framework for lunar regolith simulant development was established to realize this goal. The framework not only has a sample database and a database of potential simulation target compositions, but also has a built-in function to automatically calculate the optimal material mixing ratio through the particle swarm optimization algorithm to reproduce the target simulation, enabling fast and accurate simulant development. Using this framework, we anticipate a more agile response to the evolving needs toward simulants for space exploration.

• 자원리싸이클링
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• 제31권4호
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• pp.56-65
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• 2022

구리는 우수한 특성, 특히 높은 전도성과 낮은 저항으로 인해 전기/전자 제조 산업에 널리 사용되는 비철금속 중 하나이다. 이러한 산업의 표면 처리 공정에서는 구리 함량이 높은 폐수가 발생하며, 직간접적으로 수계로 배출된다. 이는 심각한 환경 오염을 일으키고 또한 귀중한 유용금속의 손실을 초래한다. 이러한 문제를 극복하기 위하여, 효율적이고 저렴하며 친환경적인 흡착제를 찾기 위한 목적으로 흡착 분야에서 전 세계적으로 지속적인 연구개발이 진행되고 있다. 이러한 점을 고려하여, 본 연구에서는 위와 같은 폐수로부터 구리 흡착을 위한 바이오 흡착제로서 식물뿌리(Datura 뿌리 분말)의 성능을 합성 흡착제(Tulsion T-42)와 비교하였다. 실험은 흡착제 투여량, 접촉시간, pH, 주입액 농도 등의 변수들을 최적화하기 위하여 회분식으로 수행되었다. 초기구리농도가 100 ppm이고 pH가 4인 주입액에서, 0.2 g Datura 뿌리 분말을 15분간 접촉하였을 때 구리 흡착율은 95%이었으며, 0.1 g Tulsion T-42은 30분간 접촉에서 95%의 흡착율을 나타내었다. 두 흡착제의 흡착 데이터는 Freundlich 등온선과 잘 일치하였으며, 유사 2차 속도식을 따르는 것을 나타내었다. 전체 결과는 본 연구의 바이오 흡착제가 표면처리 공정의 폐액 또는 폐수로부터 금속 회수에 적용될 가능성을 보여주고 있다.

• 치위생과학회지
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• 제5권1호
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• pp.13-17
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• 2005

성남시 지역주민의 구강건강을 증진시키기 위한 장기 지역사회구강보건 개발의 일환으로 학교구강보건사업에 필요한 구강보건 정보를 수집 정리할 목적으로 성남시 12세 아동의 구강건강실태를 조사한 후 분석 검토하여 다음과 같은 결론을 얻었다. 1. 성남시 12세 아동의 영구치우식경험자율은 74.7%, 영구치우식유병자율은 36.2%, 우식경 험영구치지수는 2.75개이었다. 2. 우식영구치율은 전체 28.4%이었는데 수정구의 우식영구치율이 36.8%로 분당구의 19.8% 에 비해 2배 가까운 수치를 보여 지역적 불균형 현상을 나타냈다. 3. 영구치가료필요자율은 1치면 충전을 필요로 하는 비율이 26.6%, 2치면 이상이 13.3%, 인조치관 수복필요가 1.8%, 치수치료 등이 5.3%, 발치필요가 2.2%로 나타났으며 치면열 구전색자율은 27.1%에 불과하였다. 4. 성남시는 12세 아동을 대상으로 한 학교구강보건사업 뿐만 아니라 아동의 구강건강상태 의 경우 구별로 불균형을 보이므로 우식발생이 높은 아동이나 우식발생위험이 높은 지역의 아동을 위한 조기검진치료사업 및 치면열구전색과 같은 우식예방사업을 적극 검토할 필요가 있었다.