• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.5
• /
• pp.1167-1177
• /
• 2019

In this paper, the improved security operation model based on the vulnerability database is studied. The proposed model consists of information protection equipment, vulnerability database, and a dashboard that visualizes and provides the results of interworking with detected logs. The evaluation of the model is analyzed by setting up a simulated attack scenario in a virtual infrastructure. In contrast to the traditional method, it is possible to respond quickly to threats of attacks specific to the security vulnerabilities that the asset has, and to find redundancy between detection rules with a secure agent, thereby creating an optimal detection rule.

• Geomechanics and Engineering
• /
• v.9 no.6
• /
• pp.729-742
• /
• 2015

The aim of the present work was the study of instability in a loose sand from Les Dunes beach in Ain Beninan, Algeria, where the Boumerdes earthquake occurred in 2003. This earthquake caused significant structural damages and claimed the lives of many people. Damages caused to infrastructures were strongly related to phenomena of liquefaction. The study was based on the results of two drained and six undrained triaxial tests over a local sand collected in a region where liquefaction occurred. All the tests hereby analyzed followed compression stress-paths in monotonic conditions and the specimens were isotropically consolidated, since the objective was to study the instability due to static loading as part of a more general project, which also included cyclic studies. The instability was modeled with the second-order work increment criterion. The definition of the instability line for Les Dunes sand and its relation with yield surfaces allowed the identification of the region of potential instability and helped in the evaluation of the susceptibility of soils to liquefy under undrained conditions and its modeling. The dilatancy rate was studied in the points where instability began. Some mixed tests were also simulated, starting with drained conditions and then changing to undrained conditions at different time steps.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.4
• /
• pp.129-143
• /
• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• Archives of Craniofacial Surgery
• /
• v.20 no.1
• /
• pp.62-65
• /
• 2019

Odontoma is an asymptomatic slow-growing odontogenic tumor. It is usually found by chance in the maxilla or mandible on radiography, or when it deforms the adjacent teeth. It is commonly found in patients who are 30 years of age or younger. We report our encounter with an odontoma within a dentigerous cyst found incidentally in a 56-year-old man. He presented with abnormal fullness in the right infraorbital area of the cheek. During the evaluation of the mass, we incidentally detected the odontogenic tumor within a dentigerous cyst in the patient's maxilla. Under general anesthesia, complete surgical drainage of the infraorbital cystic mass was performed. Enucleation of the odontogenic tumor and a bone grafting from the iliac bone were also performed. The final diagnosis was odontoma. After 2 years of follow-up, there was no sign of recurrence of the tumor. In case of odontogenic tumors, even in old patients, it is important to suspect an odontoma. When odontoma accompanies a dentigerous cyst, surgical excisional biopsy should be performed to rule out malignancy. In case of a large bony defect after enucleation, autogenous bone grafting is essential for reconstruction.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.2012-2030
• /
• 2021

Named Entity Recognition (NER) is used to identify entity nouns in the corpus such as Location, Person and Organization, etc. NER is also an important basic of research in various natural language fields. The processing of Chinese NER has some unique difficulties, for example, there is no obvious segmentation boundary between each Chinese character in a Chinese sentence. The Chinese NER task is often combined with Chinese word segmentation, and so on. In response to these problems, we summarize the recognition methods of Chinese NER. In this review, we first introduce the sequence labeling system and evaluation metrics of NER. Then, we divide Chinese NER methods into rule-based methods, statistics-based machine learning methods and deep learning-based methods. Subsequently, we analyze in detail the model framework based on deep learning and the typical Chinese NER methods. Finally, we put forward the current challenges and future research directions of Chinese NER technology.

• International Journal of Computer Science & Network Security
• /
• v.21 no.1
• /
• pp.97-106
• /
• 2021

Social networking platforms have become a smart way for people to interact and meet on internet. It provides a way to keep in touch with friends, families, colleagues, business partners, and many more. Among the various social networking sites, Twitter is one of the fastest-growing sites where users can read the news, share ideas, discuss issues etc. Due to its vast popularity, the accounts of legitimate users are vulnerable to the large number of threats. Spam and Malware are some of the most affecting threats found on Twitter. Therefore, in order to enjoy seamless services it is required to secure Twitter against malicious users by fixing them in advance. Various researches have used many Machine Learning (ML) based approaches to detect spammers on Twitter. This research aims to devise a secure system based on Hybrid Similarity Cosine and Soft Cosine measured in combination with Genetic Algorithm (GA) and Artificial Neural Network (ANN) to secure Twitter network against spammers. The similarity among tweets is determined using Cosine with Soft Cosine which has been applied on the Twitter dataset. GA has been utilized to enhance training with minimum training error by selecting the best suitable features according to the designed fitness function. The tweets have been classified as spammer and non-spammer based on ANN structure along with the voting rule. The True Positive Rate (TPR), False Positive Rate (FPR) and Classification Accuracy are considered as the evaluation parameter to evaluate the performance of system designed in this research. The simulation results reveals that our proposed model outperform the existing state-of-arts.

• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.177-184
• /
• 2021

All over the world, people are affected by many chronic diseases and medical practitioners are working hard to find out the symptoms and remedies for the diseases. Many researchers focus on the feature detection of the disease and trying to get a better health recommendation system. It is necessary to detect the features automatically to provide the most relevant solution for the disease. This research gives the framework of Health Recommendation System (HRS) for identification of relevant and non-redundant features in the dataset for prediction and recommendation of diseases. This system consists of three phases such as Pre-processing, Feature Selection and Performance evaluation. It supports for handling of missing and noisy data using the proposed Imputation of missing data and noise detection based Pre-processing algorithm (IMDNDP). The selection of features from the pre-processed dataset is performed by proposed ensemble-based feature selection using an expert's knowledge (EFS-EK). It is very difficult to detect and monitor the diseases manually and also needs the expertise in the field so that process becomes time consuming. Finally, the prediction and recommendation can be done using Support Vector Machine (SVM) and rule-based approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.11
• /
• pp.3680-3693
• /
• 2022

The handover procedure of IEEE 802.11 wireless local area networks (WLANs) introduces significant delay, which can degrade the quality of service (QoS) especially for delay-sensitive applications. Although studies have been conducted to support handover in SDN-based WLAN, there is no research to reduce the channel scanning procedure that takes up the most delay time in the handover process. The channel scanning procedure is essential to determine the appropriate access point (AP). To mitigate this problem, this paper proposes a SWITCH: SDN-WLAN integrated handover scheme for QoS-Guaranteed mobile service. In SWITCH, each AP periodically broadcasts beacon frames through different channels in a predetermined order that includes the operating channel information of the AP. This allows mobile stations (MSs) to receive the beacon frames of nearby APs, and therefore they can determine the appropriate APs for handover without the channel scanning procedure. By reporting the information of the newly moved AP to the SDN controller, a flow rule is installed in advance to provide fast handover, and packet loss is reduced by buffering data destined for MS. In addition, the proposed scheme can adaptively operate SWITCH to consider the user location and QoS requirement of flow to save radio resource overhead. Performance evaluation results demonstrate that SWITCH can reduce the handover delays, flow table utilization ratio and radio resource overhead while improving the network throughput.

• The Journal of KAIRB
• /
• v.5 no.1
• /
• pp.1-13
• /
• 2023

In the United States (US), due to the Common Rule, completely revised in 2017, single Institutional Review Board (IRB) review has become mandatory for government-sponsored multi-institutional research since 2020 regardless of the number of participating institutions. The goal of these changes is to reduce redundant reviews by the IRB at each institution and better protect research participants. In this paper, single IRB and Human Research Protection Program (HRPP) in the US and Korea were compared and considered, and their implications were discussed. A comparison of the HRPP evaluation and certification systems of the US and Korea includes that of SMART IRB in the US and Korea Central IRB, aiming at single IRB review for efficient review with support from the country and building a more efficient national human subject research network in the future. Its comparison and analysis will be helpful in deriving future tasks and development directions of single IRB and HRPP in Korea.

• Journal of Korean Port Research
• /
• v.1 no.1
• /
• pp.21-47
• /
• 1987

Nowaday all the countries of the world have studied the various problems caused in operating their own ports efficiently. Ship delay in the port is attributal to the inefficient operation in the navigation aids, the cargo handling, the storage and transfer facilities, and to the inefficient allocation of gangs or to a bad service for ships. Among these elements the allocation of gangs is the predominating factor in minimizing ship's turn round time. At present, in the case of Pusan Port. the labour union and stevedoring companies allocate gangs in every hatches of ships by a rule of thumb, just placing emphasis on minimizing ship's turn round time, without applying the principle of allocation during the cargo handling. Owing to this the efficiency of the cargo handling could not be expected to be maximized and this unsystematic operation result in supplying human resources of much unnecessary surplus gangs. Therefore in this paper the optimal size and allocation of gangs for minimizing the ship's turn round time is studied and formularized. For the determination of the priority for allocation the evaluation function, namely $F=PHi^{n}{\times}(W+H)$, can be obtained; where, PHI : Principal Hatch Index W : Total Cargo Weight represented in Gang-Shifts H : Total Number of Ship's hatches and also for the optimal size of gangs the average number of gang allocated per shift (Ng), namely Ng=W/PHI, is used. The proposed algorithm is applied to Pusan Port and its validity is verified.