• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.107-118
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• 2024

With the seamless growth of the technology, network usage requirements are expanding day by day. The majority of electronic devices are capable of communication, which strongly requires a secure and reliable network. Network-based intrusion detection systems (NIDS) is a new method for preventing and alerting computers and networks from attacks. Machine Learning is an emerging field that provides a variety of ways to implement effective network intrusion detection systems (NIDS). Bagging and Boosting are two ensemble ML techniques, renowned for better performance in the learning and classification process. In this paper, the study provides a detailed literature review of the past work done and proposed a novel ensemble approach to develop a NIDS system based on the voting method using bagging and boosting ensemble techniques. The test results demonstrate that the ensemble of bagging and boosting through voting exhibits the highest classification accuracy of 99.98% and a minimum false positive rate (FPR) on both datasets. Although the model building time is average which can be a tradeoff by processor speed.

• Korean Journal of Radiology
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• 제24권2호
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• pp.95-108
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• 2023

Recent advances in lymphatic imaging have provided novel insights into the lymphatic system. Interventional radiology has played a significant role in the development of lymphatic imaging techniques and modalities. Radiologists should be familiar with the basic physiology and anatomy of the lymphatic system to understand the imaging features of lymphatic disorders, which reflect their pathophysiology. This study comprehensively reviews the physiological and anatomical aspects of the human lymphatic system as well as the latest lymphatic imaging techniques.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2024년도 춘계학술발표대회
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• pp.294-297
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• 2024

Malware detection has become increasingly critical with the proliferation of end devices. To improve detection rates and efficiency, the research focus in malware detection has shifted towards leveraging machine learning and deep learning approaches. This shift is particularly relevant in the context of the widespread adoption of end devices, including smartphones, Internet of Things devices, and personal computers. Machine learning techniques are employed to train models on extensive datasets and evaluate various features, while deep learning algorithms have been extensively utilized to achieve these objectives. In this research, we introduce TabNet, a novel architecture designed for deep learning with tabular data, specifically tailored for enhancing malware detection techniques. Furthermore, the Synthetic Minority Over-Sampling Technique is utilized in this work to counteract the challenges posed by imbalanced datasets in machine learning. SMOTE efficiently balances class distributions, thereby improving model performance and classification accuracy. Our study demonstrates that SMOTE can effectively neutralize class imbalance bias, resulting in more dependable and precise machine learning models.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 전력전자학술대회 논문집
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• pp.185-186
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• 2016

Maximum power point tracking (MPPT) techniques play a big role in improving the efficiency of photovoltaic (PV) system. Among various schemes, the incremental conductance (INC) method is mostly discussed in literature because of its fast response to the rapid irradiation changes and high tracking accuracy. However, the existing INC algorithm has trade-offs between fast dynamic response and steady state stability. This study proposes a novel INC method to meet high efficiency and fast tracking performance at the same time.

• 전기학회논문지
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• 제67권10호
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• pp.1303-1307
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• 2018

A improving sensorless compensator for the IPMSM(Interior Permanent Magnet Synchronous Motor) drive system is proposed. Generally, the motor drive system is required the robust parameter variation and disturbance. The speed estimation methods of the conventional IRP(Instantaneous Reactive Power) compensator is improved by the speed estimation techniques of the current model observer with the proposed instantaneous reactive power compensator. Performance evaluations of the novel speed error compensator and sensorless control system are carried out by the experiments.

• 한국고분자학회:학술대회논문집
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• 한국고분자학회 2006년도 IUPAC International Symposium on Advanced Polymers for Emerging Technologies
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• pp.200-200
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• 2006

Several polynorbornene or poly(norbornene-7-oxide) based functional block copolymers were synthesized by ring opening metathesis polymerization (ROMP) with good molecular weight and polydispersity control. Some representative functional groups in these polymers are a nitrobenzoyl group or ferrocene. These polymers were subjected to various chemical modification reactions to give other block copolymers that contain novel functionality such as amine, diazonium salt, and diazo groups. The resulting polymers were characterized by various techniques such as GPC, NMR, UV-VIS, AFM, and cyclovotammography (CV).

• 전자공학회논문지B
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• 제32B권1호
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• pp.1-10
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• 1995

A graphic user interface for effectively browsing object-oriented databases in complex applications is designed and implemented. The rationale behind our design lies in enabling the users of various levels and needs to investigate the database according to their respective interests and desired depths. A novel idea in our design is the introduction of zooming techniques from a logical view, which vidualize the backbone abstraction concepts of the object-oriented data model. These objectives are verified by evaluating the results of its implementation.

• 한국세라믹학회:학술대회논문집
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• 한국세라믹학회 2004년도 춘계총회 및 연구발표회 초록집
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• pp.42.2-42.2
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• 2004

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.409-412
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• 1997

In this paper, we propose a novel synthesis method of GBSB(Generalized BSB)-based neural autoassociative memories in which we analyze qualitative properties of GBSB model, recast a design problem of an associative memory to LMIP(Linear Matrix Inequality Problem), and optimize the LMIP using LMI techniques. The obtained memory satisfies many of the required properties of associative memories and has some peculiar properties. Comparing experimental results with those of others, we show its correctness and effectiveness.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.675-679
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• 1999

A single-phase PWM current source rectifier with a neutral leg is presented and throughly analyzed in this paper. This novel topology is implemented by adding an extra leg a step-down single phase PWM space vector modulation method to reduce the dc output voltage harmonics is proposed. The PWM pattern generation need a digital system. As compared with a conventional single-phase PWM rectifier, over 20% improvement of the total harmonics distortion in the output voltage can be obtained. Different SVM techniques are analyzed for this PWM rectifier and simulation result are presented.