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Comparison of Anomaly Detection Performance Based on GRU Model Applying Various Data Preprocessing Techniques and Data Oversampling (다양한 데이터 전처리 기법과 데이터 오버샘플링을 적용한 GRU 모델 기반 이상 탐지 성능 비교)

  • Yoo, Seung-Tae;Kim, Kangseok
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.2
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    • pp.201-211
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    • 2022
  • According to the recent change in the cybersecurity paradigm, research on anomaly detection methods using machine learning and deep learning techniques, which are AI implementation technologies, is increasing. In this study, a comparative study on data preprocessing techniques that can improve the anomaly detection performance of a GRU (Gated Recurrent Unit) neural network-based intrusion detection model using NGIDS-DS (Next Generation IDS Dataset), an open dataset, was conducted. In addition, in order to solve the class imbalance problem according to the ratio of normal data and attack data, the detection performance according to the oversampling ratio was compared and analyzed using the oversampling technique applied with DCGAN (Deep Convolutional Generative Adversarial Networks). As a result of the experiment, the method preprocessed using the Doc2Vec algorithm for system call feature and process execution path feature showed good performance, and in the case of oversampling performance, when DCGAN was used, improved detection performance was shown.

Anterior Cranial Base Reconstruction in Complex Craniomaxillofacial Trauma: An Algorithmic Approach and Single-Surgeon's Experience

  • Shakir, Sameer;Card, Elizabeth B.;Kimia, Rotem;Greives, Matthew R.;Nguyen, Phuong D.
    • Archives of Plastic Surgery
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    • v.49 no.2
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    • pp.174-183
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    • 2022
  • Management of traumatic skull base fractures and associated complications pose a unique reconstructive challenge. The goals of skull base reconstruction include structural support for the brain and orbit, separation of the central nervous system from the aerodigestive tract, volume to decrease dead space, and restoration of the three-dimensional appearance of the face and cranium with bone and soft tissues. An open bicoronal approach is the most commonly used technique for craniofacial disassembly of the bifrontal region, with evacuation of intracranial hemorrhage and dural repair performed prior to reconstruction. Depending on the defect size and underlying patient and operative factors, reconstruction may involve bony reconstruction using autografts, allografts, or prosthetics in addition to soft tissue reconstruction using vascularized local or distant tissues. The vast majority of traumatic anterior cranial fossa (ACF) injuries resulting in smaller defects of the cranial base itself can be successfully reconstructed using local pedicled pericranial or galeal flaps. Compared with historical nonvascularized ACF reconstructive options, vascularized reconstruction using pericranial and/or galeal flaps has decreased the rate of cerebrospinal fluid (CSF) leak from 25 to 6.5%. We review the existing literature on this uncommon entity and present our case series of n = 6 patients undergoing traumatic reconstruction of the ACF at an urban Level 1 trauma center from 2016 to 2018. There were no postoperative CSF leaks, mucoceles, episodes of meningitis, or deaths during the study follow-up period. In conclusion, use of pericranial, galeal, and free flaps, as indicated, can provide reliable and durable reconstruction of a wide variety of injuries.

Conventional and digital impressions for complete-arch implant-supported fixed prostheses: time, implant quantity effect and patient satisfaction

  • Pereira, Ana Larisse Carneiro;Medeiros, Vitoria Ramos;Campos, Maria de Fatima Trindade Pinto;Medeiros, Annie Karoline Bezerra de;Yilmaz, Burak;Carreiro, Adriana da Fonte Porto
    • The Journal of Advanced Prosthodontics
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    • v.14 no.4
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    • pp.212-222
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    • 2022
  • PURPOSE. To evaluate and compare the effect of impression type (conventional vs digital) and the number of implants on the time from the impressions to the generation of working casts of mandibular implant-supported fixed completearch frameworks, as well as on patient satisfaction. MATERIALS AND METHODS. 17 participants, 3 or 4 implants, received 2 types of digital impression methods (DI) and conventional (CI). In DI, two techniques were performed: scanning with the scan bodies (SC) and scanning with a device attached to the scan bodies (SD) (BR 10 2019 026265 6). In CI, the making of a solid index (SI) and open-tray impression (OT) were used. The outcomes were used to evaluate the time and the participant satisfaction with conventional and digital impressions. The time was evaluated through the timing of the time obtained in the workflow in the conventional and digital impression. The effect of the number of implants on time was also assessed. Satisfaction was assessed through a questionnaire based on seven. The Wilcoxon test used to identify the statistical difference between the groups in terms of time. The Mann-Whitney test was used to analyze the relationship between the time and the number of implants. Fisher's test was used to assess the patient satisfaction (P<.05). RESULTS. The time with DI was shorter than with CI (DI, $\tilde{x}=02:58$; CI, $\tilde{x}=31:48$) (P<.0001). The arches rehabilitated with 3 implants required shorter digital impression time (3: $\tilde{x}=05:36$; 4: $\tilde{x}=09:16$) (P<.0001). Regarding satisfaction, the DI was more comfortable and pain-free than the CI (P<.005). CONCLUSION. Digital impressions required shorter chair time and had higher patient acceptance than conventional impressions.

Minimize Web Applications Vulnerabilities through the Early Detection of CRLF Injection

  • Md. Mijanur Rahman;Md. Asibul Hasan
    • International Journal of Computer Science & Network Security
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    • v.23 no.2
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    • pp.199-202
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    • 2023
  • Carriage return (CR) and line feed (LF), also known as CRLF injection is a type of vulnerability that allows a hacker to enter special characters into a web application, altering its operation or confusing the administrator. Log poisoning and HTTP response splitting are two prominent harmful uses of this technique. Additionally, CRLF injection can be used by an attacker to exploit other vulnerabilities, such as cross-site scripting (XSS). Email injection, also known as email header injection, is another way that can be used to modify the behavior of emails. The Open Web Application Security Project (OWASP) is an organization that studies vulnerabilities and ranks them based on their level of risk. According to OWASP, CRLF vulnerabilities are among the top 10 vulnerabilities and are a type of injection attack. Automated testing can help to quickly identify CRLF vulnerabilities, and is particularly useful for companies to test their applications before releasing them. However, CRLF vulnerabilities can also lead to the discovery of other high-risk vulnerabilities, and it fosters a better approach to mitigate CRLF vulnerabilities in the early stage and help secure applications against known vulnerabilities. Although there has been a significant amount of research on other types of injection attacks, such as Structure Query Language Injection (SQL Injection). There has been less research on CRLF vulnerabilities and how to detect them with automated testing. There is room for further research to be done on this subject matter in order to develop creative solutions to problems. It will also help to reduce false positive alerts by checking the header response of each request. Security automation is an important issue for companies trying to protect themselves against security threats. Automated alerts from security systems can provide a quicker and more accurate understanding of potential vulnerabilities and can help to reduce false positive alerts. Despite the extensive research on various types of vulnerabilities in web applications, CRLF vulnerabilities have only recently been included in the research. Utilizing automated testing as a recurring task can assist companies in receiving consistent updates about their systems and enhance their security.

Experimental Study on Hydrodynamic Characteristics of Dam Break Flow for Estimation of Green Water Loading (청수현상 추정을 위한 댐 붕괴 흐름의 유체동역학적 특성에 관한 실험적 연구)

  • Hyung Joon Kim;Jong Mu Kim;Jae Hong Kim;Kwang Hyo Jung;Gang Nam Lee
    • Journal of the Society of Naval Architects of Korea
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    • v.60 no.2
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    • pp.120-134
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    • 2023
  • In this study, hydrodynamic characteristics of dam break flow were investigated by a series of experiments. The experiments were performed in a 2-D rectangular flume with obtaining instantaneous images of dam break flow to capture the free surface elevation, and pressure distributions on vertical wall and bottom of the flume. The initial water depth of the dam break flow was changed into 3 different heights, and the gate opening speed was changed during the experiments to study the effect of the gate speed in the dam break flow. Generation of dam break phenomena could be classified into three stages, i.e., very initial, relatively stable, and wall impact stages. The wall impact stage could be separated into 4 generation phases of wall impinge, run-up, overturning, and touchdown phases based on the deformation of the free surface. The free surface elevation were investigated with various initial water depth and compared with the analytic solutions by Ritter (1892). The pressures acting on the vertical wall and bottom were provided for the whole period of dam break flow varying the initial water depth and gate open speed. The measurement results of the dam break flow was compared with the hydrodynamic characteristics of green water phenomena, and it showed that the dam break flow could overestimate the green water loading based on the estimation suggested by Buchner (2002).

A Study on Classification Models for Predicting Bankruptcy Based on XAI (XAI 기반 기업부도예측 분류모델 연구)

  • Jihong Kim;Nammee Moon
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.8
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    • pp.333-340
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    • 2023
  • Efficient prediction of corporate bankruptcy is an important part of making appropriate lending decisions for financial institutions and reducing loan default rates. In many studies, classification models using artificial intelligence technology have been used. In the financial industry, even if the performance of the new predictive models is excellent, it should be accompanied by an intuitive explanation of the basis on which the result was determined. Recently, the US, EU, and South Korea have commonly presented the right to request explanations of algorithms, so transparency in the use of AI in the financial sector must be secured. In this paper, an artificial intelligence-based interpretable classification prediction model was proposed using corporate bankruptcy data that was open to the outside world. First, data preprocessing, 5-fold cross-validation, etc. were performed, and classification performance was compared through optimization of 10 supervised learning classification models such as logistic regression, SVM, XGBoost, and LightGBM. As a result, LightGBM was confirmed as the best performance model, and SHAP, an explainable artificial intelligence technique, was applied to provide a post-explanation of the bankruptcy prediction process.

A Study on Image Creation and Modification Techniques Using Generative Adversarial Neural Networks (생성적 적대 신경망을 활용한 부분 위변조 이미지 생성에 관한 연구)

  • Song, Seong-Heon;Choi, Bong-Jun;Moon, M-Ikyeong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.2
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    • pp.291-298
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    • 2022
  • A generative adversarial network (GAN) is a network in which two internal neural networks (generative network and discriminant network) learn while competing with each other. The generator creates an image close to reality, and the delimiter is programmed to better discriminate the image of the constructor. This technology is being used in various ways to create, transform, and restore the entire image X into another image Y. This paper describes a method that can be forged into another object naturally, after extracting only a partial image from the original image. First, a new image is created through the previously trained DCGAN model, after extracting only a partial image from the original image. The original image goes through a process of naturally combining with, after re-styling it to match the texture and size of the original image using the overall style transfer technique. Through this study, the user can naturally add/transform the desired object image to a specific part of the original image, so it can be used as another field of application for creating fake images.

Prediction Model of Real Estate Transaction Price with the LSTM Model based on AI and Bigdata

  • Lee, Jeong-hyun;Kim, Hoo-bin;Shim, Gyo-eon
    • International Journal of Advanced Culture Technology
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    • v.10 no.1
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    • pp.274-283
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    • 2022
  • Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

A refined quasi-3D theory for stability and dynamic investigation of cross-ply laminated composite plates on Winkler-Pasternak foundation

  • Nasrine Belbachir;Fouad Bourada;Abdelmoumen Anis Bousahla;Abdelouahed Tounsi;Mohamed A. Al-Osta;Mofareh Hassan Ghazwani;Ali Alnujaie;Abdeldjebbar Tounsi
    • Structural Engineering and Mechanics
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    • v.85 no.4
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    • pp.433-443
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    • 2023
  • The current paper discusses the dynamic and stability responses of cross-ply composite laminated plates by employing a refined quasi-3D trigonometric shear deformation theory. The proposed theory takes into consideration shear deformation and thickness stretching by a trigonometric variation of in-plane and transverse displacements through the plate thickness and assures the vanished shear stresses conditions on the upper and lower surfaces of the plate. The strong point of the new formulation is that the displacements field contains only 4 unknowns, which is less than the other shear deformation theories. In addition, the present model considers the thickness extension effects (εz≠0). The presence of the Winkler-Pasternak elastic base is included in the mathematical formulation. The Hamilton's principle is utilized in order to derive the four differentials' equations of motion, which are solved via Navier's technique of simply supported structures. The accuracy of the present 3-D theory is demonstrated by comparing fundamental frequencies and critical buckling loads numerical results with those provided using other models available in the open literature.

Correlation between different methodologies used to evaluate the marginal adaptation of proximal dentin gingival margins elevated using a glass hybrid

  • Hoda S. Ismail;Brian R. Morrow;Ashraf I. Ali;Rabab El. Mehesen;Franklin Garcia-Godoy;Salah H. Mahmoud
    • Restorative Dentistry and Endodontics
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    • v.47 no.4
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    • pp.36.1-36.17
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    • 2022
  • Objectives: This study aimed to evaluate the effect of aging on the marginal quality of glass hybrid (GH) material used to elevate dentin gingival margins, and to analyze the consistency of the results obtained by 3 in vitro methods. Materials and Methods: Ten teeth received compound class II cavities with subgingival margins. The dentin gingival margins were elevated with GH, followed by resin composite. The GH/gingival dentin interfaces were examined through digital microscopy, scanning electron microscopy (SEM) using resin replicas, and according to the World Dental Federation (FDI) criteria. After initial evaluations, all teeth were subjected to 10,000 thermal cycles, followed by repeating the same marginal evaluations and energy dispersive spectroscopy (EDS) analysis for the interfacial zone of 2 specimens. Marginal quality was expressed as the percentage of continuous margin at ×200 for microscopic techniques and as the frequency of each score for FDI ranking. Data were analyzed using the paired sample t-test, Wilcoxon signed-rank test, and Pearson and Spearmen correlation coefficients. Results: None of the testing techniques proved the significance of the aging factor. Moderate and strong significant correlations were found between the testing techniques. The EDS results suggested the presence of an ion-exchange layer along the GH/gingival dentin interface of aged specimens. Conclusions: The marginal quality of the GH/dentin gingival interface defied aging by thermocycling. The replica SEM and FDI ranking results had stronger correlations with each other than either showed with the digital microscopy results.