• Journal of the Korean Chemical Society
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• v.35 no.4
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• pp.397-404
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• 1991

Nonchromophore compounds such as aliphatic acids, alcohols and tetraalkylammonium salts could be detected by indirect photometric detection on the revered-phase liquid chromatography. Benzyltriethylammonium bromide(BTEAB) was used as a detection reagent. Also, the retention mechanism and response of samples were investigated to the several factors such as pH, temperature, and concentration of MeOH as well as concentration of detection reagents in mobile phase. And some mixture of samples were able to be separated under optimum condition.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2086-2098
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• 2018

Security plays a vital role and is the key challenge in Mobile Ad-hoc Networks (MANET). Infrastructure-less nature of MANET makes it arduous to envisage the genre of topology. Due to its inexhaustible access, information disseminated by roaming nodes to other nodes is susceptible to many hazardous attacks. Intrusion Detection and Prevention System (IDPS) is undoubtedly a defense structure to address threats in MANET. Many IDPS methods have been developed to ascertain the exceptional behavior in these networks. Key issue in such IDPS is lack of fast self-organized learning engine that facilitates comprehensive situation awareness for optimum decision making. Proposed "Intelligent Behavioral Hybridized Intrusion Detection and Prevention System (IBH_IDPS)" is built with computational intelligence to detect complex multistage attacks making the system robust and reliable. The System comprises of an Intelligent Client Agent and a Smart Server empowered with fuzzy inference rule-based service engine to ensure confidentiality and integrity of network. Distributed Intelligent Client Agents incorporated with centralized Smart Server makes it capable of analyzing and categorizing unethical incidents appropriately through unsupervised learning mechanism. Experimental analysis proves the proposed model is highly attack resistant, reliable and secure on devices and shows promising gains with assured delivery ratio, low end-to-end delay compared to existing approach.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.682-684
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• 2003

With the explosive rapid expansion of computer using during the past few years, security has become a crucial issue for modem computer systems. Today, there are many intrusion detection systems (IDS) on the Internet. A variety of intrusion detection techniques and tools exist in the computer security community such as enterprise security management system (ESM) and system integrity checking tools. However, there is a potential problem involved with intrusion detection systems that are installed locally on the machines to be monitored. If the system being monitored is compromised, it is quite likely that the intruder will after the system logs and the intrusion logs while the intrusion remains undetected. In this project KIT-I, we adopt remote logging server (RLS) mechanism, which is used to backup the log files to the server. Taking into account security, we make use of the function of SSL of Java and certificate authority (CA) based key management. Furthermore, Support Vector Machine (SVM) is applied in our project to detect the intrusion activities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.737-743
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• 2008

I compare my parameter estimation methodoloay with existing method, considering both of testing effort and fault detecting rate simultaneously in software reliability modeling. Generally speaking, fault detection/removal mechanism depends on how apply previous fault detection/removal and testing effort of S/W. The fault removal efficiency makes large influence to the reliability growth, testing and removal cost in developing stage S/W. This is very useful measure during all the developing stages and much helpful for the developer to estimate debugging efficiency, and furthermore, to anticipate additional working amount.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2027-2031
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• 2007

Recently the diffusion of the advancement of mobile communication technique and mobile terminal increased, The users were demanded seamless services when carrying and moving. It proposed the FMIPv6(Fast Handoff for Mobile IPv6) from the IETF like this meeting this requirement. The handover procedure of the FMIPv6 causes to defecate with movement detection, new CoA configuration and binding update. But, the delay occurs from each process, when the DAD(Duplicate Address Detection) of the CoA executing, the big delay occurs. This paper proposes a scheme of delay reduction, it omits DAD process and stores in the AR(Access Router) relates in the CoA of the mobile terminal information.

• Current Applied Physics
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• v.18 no.11
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• pp.1255-1260
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• 2018

In this work, a green and simple one-pot route was developed for the synthesis of highly fluorescent aminofunctionalized graphene quantum dots (a-GQDs) via hydrothermal process without any further modification or surface passivation. We synthesized the a-GQDs using glucose as the carbon source and ammonium as a functionalizing agent without the use of a strong acid, oxidant, or other toxic chemical reagent. The as-obtained aGQDs have a uniform size of 3-4 nm, high contents of amino groups, and show a bright green emission with high quantum yield of 32.8%. Furthermore, the a-GQDs show effective fluorescence quenching for $Cu^{2+}$ ions which can serve as effective fluorescent probe for the detection of $Cu^{2+}$. The fluorescent probe using the obtained aGQDs exhibits high sensitivity and selectivity toward $Cu^{2+}$ with the limit of detection as low as 5.6 nM. The mechanism of the $Cu^{2+}$ induced fluorescence quenching of a-GQDs can be attributed to the electron transfer by the formation of metal complex between $Cu^{2+}$ and the amino groups on the surface of a-GQDs. These results suggest great potential for the simple and green synthesis of functionalized GQDs and a practical sensing platform for $Cu^{2+}$ detection in environmental and biological applications.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1026-1034
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• 2021

Tire wear and defect are important factors for safe driving condition. These defects are generally inspected by some specialized experts or very expensive equipments such as stereo depth camera and depth gauge. In this paper, we propose tire safety vision inspector based on deep neural network (DNN). The status of tire wear is categorized into three: 'safety', 'warning', and 'danger' based on depth of tire tread. We propose an attention mechanism for emphasizing the feature of tread area. The attention-based feature is concatenated to output feature maps of the last convolution layer of ResNet-101 to extract more robust feature. Through experiments, the proposed tire wear classification model improves 1.8% of accuracy compared to the existing ResNet-101 model. For detecting the tire defections, the developed tire defect detection model shows up-to 91% of accuracy using the Mask R-CNN model. From these results, we can see that the suggested models are useful for checking on the safety condition of working tire in real environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.80-96
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• 2022

Nowadays, artificial intelligence promotes the rapid development of skin cancer detection technology, and the federated skin cancer detection model (FSDM) and dual generative adversarial network model (DGANM) solves the fragmentation and privacy of data to a certain extent. To overcome the problem that the many-objective evolutionary algorithm (MaOEA) cannot guarantee the convergence and diversity of the population when solving the above models, a many-objective evolutionary algorithm based on integrated strategy (MaOEA-IS) is proposed. First, the idea of federated learning is introduced into population mutation, the new parents are generated through sub-populations employs different mating selection operators. Then, the distance between each solution to the ideal point (SID) and the Achievement Scalarizing Function (ASF) value of each solution are considered comprehensively for environment selection, meanwhile, the elimination mechanism is used to carry out the select offspring operation. Eventually, the FSDM and DGANM are solved through MaOEA-IS. The experimental results show that the MaOEA-IS has better convergence and diversity, and it has superior performance in solving the FSDM and DGANM. The proposed MaOEA-IS provides more reasonable solutions scheme for many scholars of skin cancer detection and promotes the progress of intelligent medicine.

• The Journal of the Acoustical Society of Korea
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• v.39 no.1
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• pp.24-31
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• 2020

In this paper, the deep convolutional neural network for sound event detection is studied. Especially, the end-to-end neural network, which generates the detection results from the input audio waveform, is studied for weakly supervised problem that includes weakly-labeled and unlabeled dataset. The proposed system is based on the network structure that consists of deeply-stacked 1-dimensional convolutional neural networks, and enhanced by the skip connection and gating mechanism. Additionally, the proposed system is enhanced by the sound event detection and post processings, and the training step using the mean-teacher model is added to deal with the weakly supervised data. The proposed system was evaluated by the Detection and Classification of Acoustic Scenes and Events (DCASE) 2019 Task 4 dataset, and the result shows that the proposed system has F₁-scores of 54 % (segment-based) and 32 % (event-based).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.155-160
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• 2003

This paper presents a multiple face detector based on a robust pupil detection technique. The pupil detector uses active illumination that exploits the retro-reflectivity property of eyes to facilitate detection. The detection range of this method is appropriate for interactive desktop and kiosk applications. Once the location of the pupil candidates are computed, the candidates are filtered and grouped into pairs that correspond to faces using heuristic rules. To demonstrate the robustness of the face detection technique, a dual mode face tracker was developed, which is initialized with the most salient detected face. Recursive estimators are used to guarantee the stability of the process and combine the measurements from the multi-face detector and a feature correlation tracker. The estimated position of the face is used to control a pan-tilt servo mechanism in real-time, that moves the camera to keep the tracked face always centered in the image.