• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.525-534
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• 2023

Gas leak detection system is a key to minimize the loss of life due to the explosiveness and toxicity of gas. Most of the leak detection systems detect by gas sensors or thermal imaging cameras. To improve the performance of gas leak detection system using single-modal methods, the paper propose multimodal approach to gas sensor data and thermal camera data in developing a gas type identification model. MultimodalGasData, a multimodal open-dataset, is used to compare the performance of the four models developed through multimodal approach to gas sensors and thermal cameras with existing models. As a result, 1D CNN and GasNet models show the highest performance of 96.3% and 96.4%. The performance of the combined early fusion model of 1D CNN and GasNet reached 99.3%, 3.3% higher than the existing model. We hoped that further damage caused by gas leaks can be minimized through the gas leak detection system proposed in the study.

• Smart Media Journal
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• v.13 no.1
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• pp.9-17
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• 2024

This study aims to develop an integrated agricultural distribution network management system to improve the quality, profit, and decision-making efficiency of agricultural products. We adopt two key techniques: crop maturity detection based on the YOLOX target detection algorithm and market price prediction based on the Prophet model. By training the target detection model, it was possible to accurately identify crops of various maturity stages, thereby optimizing the shipment timing. At the same time, by collecting historical market price data and predicting prices using the Prophet model, we provided reliable price trend information to shipping decision makers. According to the results of the study, it was found that the performance of the model considering the holiday factor was significantly superior to that of the model that did not, proving that the effect of the holiday on the price was strong. The system provides strong tools and decision support to farmers and agricultural distribution managers, helping them make smart decisions during various seasons and holidays. In addition, it is possible to optimize the distribution network of agricultural products and improve the quality and profit of agricultural products.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.169-185
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• 2024

Due to levitate and rapid growth of E-Commerce, most of the organizations are moving towards cashless transaction Unfortunately, the cashless transactions are not only used by legitimate users but also it is used by illegitimate users and which results in trouncing of billions of dollars each year worldwide. Fraud prevention and Fraud Detection are two methods used by the financial institutions to protect against these frauds. Fraud prevention systems (FPSs) are not sufficient enough to provide fully security to the E-Commerce systems. However, with the combined effect of Fraud Detection Systems (FDS) and FPS might protect the frauds. However, there still exist so many issues and challenges that degrade the performances of FDSs, such as overlapping of data, noisy data, misclassification of data, etc. This paper presents a comprehensive survey on financial fraud detection system using such data mining techniques. Over seventy research papers have been reviewed, mainly within the period 2002-2015, were analyzed in this study. The data mining approaches employed in this research includes Neural Network, Logistic Regression, Bayesian Belief Network, Support Vector Machine (SVM), Self Organizing Map(SOM), K-Nearest Neighbor(K-NN), Random Forest and Genetic Algorithm. The algorithms that have achieved high success rate in detecting credit card fraud are Logistic Regression (99.2%), SVM (99.6%) and Random Forests (99.6%). But, the most suitable approach is SOM because it has achieved perfect accuracy of 100%. But the algorithms implemented for financial statement fraud have shown a large difference in accuracy from CDA at 71.4% to a probabilistic neural network with 98.1%. In this paper, we have identified the research gap and specified the performance achieved by different algorithms based on parameters like, accuracy, sensitivity and specificity. Some of the key issues and challenges associated with the FDS have also been identified.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.641-651
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• 2006

거대한 웹 컨텐츠 안에는 수많은 링크들로 인한 순환들이 존재하게 된다. 그 순환들은 강하게 뭉쳐있는 실타래 처럼, 강하게 결합한 순환들의 덩어리 형태로 존재하게 된다. 웹 컨텐츠는 흔히 방향그래프로 표현되는데, 즉 웹 컨텐츠에서 나타나는 수많은 링크둘을 방향그래프에서 강결합요소를 이용하면 모든 순환을 효율적으로 발견할 수 있다. 본 논문에서는 강결합요소를 이용하여 거대한 그래프에서 보다 효율적으로 모든 순환을 찾아낼 수 있는 방법을 제시하였다.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1227-1230
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• 2007

This paper describes recent advances in the R&D work achieved at Fraunhofer HHI (Germany) that are believed to provide key technologies for the development of future human-machine interfaces. The paper focus on the area of vision based interaction technologies that will be one essential component in future three-dimensional display systems.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.07a
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• pp.279-282
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• 2003

Mobile Ad hoc망의 경우 단말기에서 무선접속 인터페이스만 있으면 침입자로 하여금 쉽게 접속이 가능하게 하며, SSID와 WEP Key를 쉽게 취득하여 네트워크의 일원으로 참여할 수 있는 보안상의 취약성이 존재한다. 보안 취약성을 극복하기 위해서는 한정된 에너지 자원과 프로세서를 가진 무선 단말기로 침입탐지를 수행하기에는 문제점들이 존재한다. 따라서 본 논문에서는 프로세스 부하를 줄이는 IEEE802.11 Frame헤더의 Sequence Number 분석방법과 효과적으로 침입을 탐지할 수 있는 RF Monitoring을 이용하여 Mobile Ad hoc 환경에 적합한 칩입탐지 시스템을 제안한다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.315-317
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• 1998

많은 양의 비디오 데이터가 디지털화 되면서 사용자가 쉽게 자신이 원하는 비디오 데이터를 검색할 수 있는 내용 기반 검색이 필요하게 되었다. 내용 기반 검색을 위해서는 비디오 데이터를 연속된 카메라 모션으로 구성된 셧으로 나누고, 셧의 내용을 대표 할 수 있는 대표 프레임을 찾아야 한다. 대표 프레임은 비디오 데이터의 요약과 색인의 중요한 수단이다. 본 논문에서는 셧의 내용 기반으로 대표 프레임을 찾기 위해서 프레임에 존재하는 영역 정보를 바탕으로 셧의 내용을 알 수 있는 핵심 정보인 카메라 모션을 검출 하고, 이를 기반으로 대표 프레임을 선택하는 방법을 제안한다.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2000.10a
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• pp.60.2-60
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• 2000

• Mass Spectrometry Letters
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• v.11 no.2
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• pp.17-24
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• 2020

Metabolomics has become an important research field with many areas of applications ranging from disease biomarker discovery to global biology systems study. A key step in metabolomics is to perform metabolome analysis to obtain quantitative information on metabolic changes among comparative samples. Mass spectrometry (MS) is widely used for highly sensitive detection of many different types of metabolites. In this review, we highlight some of the more commonly used MS techniques for metabolome analysis.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.154.2-154.2
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• 2003

Mammalian cell cycles are tightly regulated by cyclins, cyclin dependent kinase (CDK), Retinoblatoma (Rb) protein, and cellular CDK inhibitors (CDKI). Cyelin dependent kinases (CDK) are key enzymes regulating eukaryotic cell cycle. And also it is recognized that the abnormal increase of CDK activities is one of the common events in human cancer and CDK inhibitors have therapeutic values in cancer treatment. Until now it is known that over 10 different CKDs participate in cell cycle regulation. (omitted)