• Archives of Craniofacial Surgery
• /
• v.25 no.3
• /
• pp.116-122
• /
• 2024

Background: Due to the importance of evidence-based research in plastic surgery, the authors of this study aimed to assess the accuracy of ChatGPT in generating novel systematic review ideas within the field of craniofacial surgery. Methods: ChatGPT was prompted to generate 20 novel systematic review ideas for 10 different subcategories within the field of craniofacial surgery. For each topic, the chatbot was told to give 10 "general" and 10 "specific" ideas that were related to the concept. In order to determine the accuracy of ChatGPT, a literature review was conducted using PubMed, CINAHL, Embase, and Cochrane. Results: In total, 200 total systematic review research ideas were generated by ChatGPT. We found that the algorithm had an overall 57.5% accuracy at identifying novel systematic review ideas. ChatGPT was found to be 39% accurate for general topics and 76% accurate for specific topics. Conclusion: Craniofacial surgeons should use ChatGPT as a tool. We found that ChatGPT provided more precise answers with specific research questions than with general questions and helped narrow down the search scope, leading to a more relevant and accurate response. Beyond research purposes, ChatGPT can augment patient consultations, improve healthcare equity, and assist in clinical decision-making. With rapid advancements in artificial intelligence (AI), it is important for plastic surgeons to consider using AI in their clinical practice to improve patient-centered outcomes.

• Convergence Security Journal
• /
• v.24 no.2
• /
• pp.71-78
• /
• 2024

As the rapid development of quantum computing compromises current public key encryption methods, the National Institute of Standards and Technology (NIST) in the United States has initiated the Post-Quantum Cryptography(PQC) project to develop new encryption standards that can withstand quantum computer attacks. This project involves reviewing and evaluating various cryptographic algorithms proposed by researchers worldwide. The initially selected quantum-resistant cryptographic algorithms were developed based on lattices and hash functions. Currently, algorithms offering diverse technical approaches, such as BIKE, Classic McEliece, and HQC, are under review in the fourth round. CRYSTALS-KYBER, CRYSTALS-Dilithium, FALCON, and SPHINCS+ were selected for standardization in the third round. In 2024, a final decision will be made regarding the algorithms selected in the fourth round and those currently under evaluation. Strengthening the security of public key cryptosystems in preparation for the quantum computing era is a crucial step expected to have a significant impact on protecting future digital communication systems from threats. This paper analyzes the security and efficiency of quantum-resistant cryptographic algorithms, presenting trends in this field.

• Tunnel and Underground Space
• /
• v.13 no.5
• /
• pp.373-388
• /
• 2003

The investigation on the rock discontinuity geometry has been usually undergone by direct measurement on the rock exposures. But this sort of field work has disadvantages, which we, for example, restriction of surveying areas and consuming excessive times and labors. To cover these kinds of disadvantages, image processing could be regarded as an altemative way, with additional advantages such as automatic and objective tools when used under adequate computerized algorithm. This study was focused on the recognition of the rock discontinuities captured in the image of rock exposure by digital camera and the production of the discontinuity map automatically. The whole process was written using macro commands builtin image analyzer, ImagePro Plus. ver 4.1(Media Cybernetic). The procedure of image processing developed in this research could be divided with three steps, which are enhancement, recognition and extraction of discontinuity traces from the digital image. Enhancement contains combining and applying several filters to remove and relieve various types of noises from the image of rock surface. For the next step, recognition of discontinuity traces was executed. It used local topographic features characterized by the differences of gray scales between discontinuity and rock. Such segments of discontinuity traces extracted from the image were reformulated using an algorithm of computer decision-making criteria and linked to form complete discontinuity traces. To verify the image processing algorithms and their sequences developed in this research, discontinuity traces digitally photographed on the rock slope were analyzed. The result showed about 75～80% of discontinuities could be detected. It is thought to be necessary that the algorithms and computer codes developed in this research need to be advanced further especially in combining digital filters to produce images to be more acceptable for extraction of discontinuity traces and setting seed pixels automatically when linking trace segments to make a complete discontinuity trace.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.9
• /
• pp.37-44
• /
• 2020

AI technology has developed in the form of decision support technology in law, patent, finance and national defense and is applied to disease diagnosis and legal judgment. To search real-time information with Deep Learning, Big data Analysis and Deep Learning Algorithm are required. In this paper, we try to predict the entrance rate to high-ranking universities using a Deep Learning model, RNN(Recurrent Neural Network). First, we analyzed the current status of private academies in administrative districts and the number of students by age in administrative districts, and established a socially accepted hypothesis that students residing in areas with a high educational fever have a high rate of enrollment in high-ranking universities. This is to verify based on the data analyzed using the predicted hypothesis and the government's public data. The predictive model uses data from 2015 to 2017 to learn to predict the top enrollment rate, and the trained model predicts the top enrollment rate in 2018. A prediction experiment was performed using RNN, a Deep Learning model, for the high-ranking enrollment rate in the special education zone. In this paper, we define the correlation between the high-ranking enrollment rate by analyzing the household income and the participation rate of private education about the current status of private institutes in regions with high education fever and the effect on the number of students by age.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.6
• /
• pp.88-95
• /
• 2011

An embedded mobile device mostly has lower computation power than a general purpose computer because of its relatively lower system specifications. Consequently, conventional face tracking and face detection methods, requiring complex algorithms for higher recognition rates, are unsuitable in a mobile environment aiming for real time detection. On the other hand, by applying a real-time tracking and detecting algorithm, we would be able to provide a two-way interactive multimedia service between an user and a mobile device thus providing a far better quality of service in comparison to a one-way service. Therefore it is necessary to develop a real-time face and eye tracking technique optimized to a mobile environment. For this reason, in this paper, we proposes a method of tracking horizontal face position of a user on a T-DMB device for enhancing the quality of 3D DMB content. The proposed method uses the orientation of edges to estimate the left and right boundary of the face, and by the color edge information, the horizontal position and size of face is determined finally to decide the horizontal face. The sobel gradient vector is projected vertically and candidates of face boundaries are selected, and we proposed a smoothing method and a peak-detection method for the precise decision. Because general face detection algorithms use multi-scale feature vectors, the detection time is too long on a mobile environment. However the proposed algorithm which uses the single-scale detection method can detect the face more faster than conventional face detection methods.

• Smart Structures and Systems
• /
• v.20 no.1
• /
• pp.61-74
• /
• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• Journal of Korea Water Resources Association
• /
• v.32 no.1
• /
• pp.71-81
• /
• 1999

The objective of this study is to develop a model which can design an optimal pipe network system of least cost while satisfying all the design constraints including hydraulic constraints using a genetic algorithm technique. Hydraulic constraints interfaced with the simulation program(KYPIPE) checked feasible solution region. Genetic algorithm(GA) technique is a relatively new optimization technique. The GA is known as a very powerful search and optimization technique especially when solving nonlinear programming problems. The model developed in this study selects optimal pipe diameters in the form of commercial discrete sizes using the pipe diameters and the pumping powers as decision variables. The model not only determines the optimal diameters and pumping powers of pipe network system but also satisfies the discharge and pressure requirements at demanding nodes. The model has been applied to an imaginary and an existing pipe network systems. One system is adopted from journal papers which has been used as an example network by many other researchers. Comparison of the results shows compatibility of the model developed in this study. The model is also applied to a system in Goyang city in order to check the model applicability to finding of optimal pumping powers. It has been found that the developed model can be successfully applied to optimal design of pipe network systems in a relatively simple manner.

• Journal of KIISE:Computer Systems and Theory
• /
• v.26 no.8
• /
• pp.918-929
• /
• 1999

동기식 스트림 암호통신 방식을 사용하는 암호통신에서는 암/복호화 과정 수행시 암호통신 과정에서 발생하는 사이클슬립으로 인해 키수열의 동기이탈 현상이 발생되고 이로 인해 오복호된 데이타를 얻게된다. 이러한 위험성을 감소하기 위한 방안으로 현재까지 암호문에 동기신호와 세션키를 주기적으로 삽입하여 동기를 이루는 주기적인 동기암호 통신방식을 사용하여 왔다. 본 논문에서는 CDMA(Cellular Division Multiple Access) 이동망에서 데이타서비스를 제공할 때 사용되는 점대점 프로토콜의 주소영역의 특성을 이용하여 단위 측정시간 동안 측정된 주소비트 정보와 플래그 패턴의 수신률을 이용하여 문턱 값보다 작은경우 동기신호와 세션키를 전송하는 비주기적인 동기방식을 사용하므로써 종래의 주기적인 동기방식으로 인한 전송효율성 저하와 주기적인 상이한 세션키 발생 및 다음 주기까지의 동기이탈 상태의 지속으로 인한 오류확산 등의 단점을 해결하였다. 제안된 알고리즘을 링크계층의 점대점 프로토콜(Point to Point Protocol)을 사용하는 CDMA 이동망에서 동기식 스트림 암호 통신방식에 적용시 동기이탈율 10-7의 환경에서 주기가 1sec인 주기적인 동기방식에서 요구되는 6.45x107비트에 비해 3.84x105비트가 소요됨으로써 전송율측면에서의 성능향상과 오복호율과 오복호 데이타 비트측면에서 성능향상을 얻었다. Abstract In the cipher system using the synchronous stream cipher system, encryption / decryption cause the synchronization loss (of key arrangement) by cycle slip, then it makes incorrect decrypted data. To lessen the risk, we have used a periodic synchronous cipher system which achieve synchronization at fixed timesteps by inserting synchronization signal and session key. In this paper, we solved the problem(fault) like the transfer efficiency drops by a periodic synchronous method, the periodic generations of different session key, and the incorrectness increases by continuing synchronization loss in next time step. They are achieved by the transfer of a non-periodic synchronous signal which carries synchronous signal and session key when it is less than the threshold value, analyzing the address field of point-to-point protocol, using the receiving rate of address bits information and flag patterns in the decision duration, in providing data services by CDMA mobile network. When the proposed algorithm is applied to the synchronous stream cipher system using point-to-point protocol, which is used data link level in CDMA mobile network, it has advanced the result in Rerror and Derror and in transmission rate, by the use of 3.84$\times$105bits, not 6.45$\times$107bits required in periodic synchronous method, having lsec time step, in slip rate 10-7.

• Journal of Service Research and Studies
• /
• v.3 no.2
• /
• pp.53-60
• /
• 2013

Datamining from the large data in the form of various techniques for obtaining information have been developed. In recent years one of the most sought areas of pattern recognition and machine learning method is created with most of existing learning algorithms based on categorical attributes to a rule or decision model. However, the real-world data, it may consist of numeric attributes in many cases. In addition it contains attributes with numerical values to the normal categorical attribute. In this case, therefore, it is required processes in order to use the data to learn an appropriate value for the type attribute. In this paper, the domain of the numeric attributes are divided into several segments using learning algorithm techniques of discritization. It is described Clustering with other data mining techniques. Large amount of first cluster with characteristics is similar records from the database into smaller groups that split multiple given finite patterns in the pattern space. It is close to each other of a set of patterns that together make up a bunch. Among the set without specifying a particular category in a given data by extracting a pattern. It will be described similar grouping of data clustering technique to classify the data.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.3C
• /
• pp.247-254
• /
• 2008

H.264 provides a good coding efficiency compared with existing video coding standards, H.263, MPEG-4, based on the use of multiple reference frame for variable block size motion estimation, quarter-pixel motion estimation and compensation, $4{\times}4$ integer DCT, rate-distortion optimization, and etc. However, many modules used to increase its performance also require H.264 to have increased complexity so that fast algorithms are to be implemented as practical approach. In this paper, among many approaches, fast mode decision algorithm by skipping variable block size motion estimation and spatial-predictive coding, which occupies most encoder complexity, is proposed. This approach takes advantages of temporal and spatial properties of fast mode selection techniques. Experimental results demonstrate that the proposed approach can save encoding time up to 65% compared with the H.264 standard while maintaining the visual perspectives.