• 한국정보과학회논문지:정보통신
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• 제31권1호
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• pp.20-26
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• 2004

I-TCP의 이동성 지원 라우터(MSR)의 버퍼가 넘치는 현상을 방지하기 위한 혼잡제어 알고리즘을 제안한다. 무선망 환경에서의 높은 비트 오류율와 잦은 핸드오프로 인해 유ㆍ무선이 혼재된 네트워크에서의 TCP Reno의 혼잡제어 방식은 유선으로만 이루어진 네트워크에서 보다 낮은 전송률을 보인다. 이를 해결하기 위해 하나의 TCP 연결을 유선과 무선부분 각각 두개의 TCP 연결로 나누어 처리하는 I-TCP가 제안되었다. 그러나 무선망의 비트 오류가 과다하게 발생하거나 핸드오프가 빈번하면 이동성 지원 라우터의 버퍼가 넘치는 현상이 발생할 수 있다. 이것은 MSR이 송신자에게 해달 ack를 보낸 패킷(MSR 버퍼에 있는)들이 수신자에게 전송되지 못하는 결과를 초래하여 TCP의 end-to-end semantic를 위반하게 된다. 본 논문에서는 송신자와 MSR 사이에 “흐름 제어” 기법을 도입하여 이동성 지원 라우터의 버퍼가 넘치는 현상을 방지하였다. 송신자와 MSR 사이의 advertised window를 MSR 버퍼의 남은 공간과 연동하여 MSR의 버퍼가 넘치기 전에 MSR로 전송되는 패킷의 양을 조절할 수 있다.

• 한국정보처리학회논문지
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• 제6권6호
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• pp.1493-1501
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• 1999

다양한 통신망에서의 멀티미디어 회의 서비스와 관련하여 국제표준화 작업이 H 시리즈 및 T 시리즈로 이루어지고 있다. 다양한 망에서의 다지점 데이터 회의를 위하여 T.120으로 표준화되어 구현되고 있으며, 단점으로는 영상과 음성이 지원되지 않는다는 점이다. 또한 각종 망에서의 영상회의는 H.32X 시리즈로 망마다 고유의 표준화가 진행되고 있으며, 이로 인하여 혼합 망에서 운용될 경우 일관성 있고 전체적인 관리가 어렵다는 점이 단점으로 지적되고 있다. 이 두 문제를 해결하기 위하여 H.32X와 T.120을 통합하여 이용하고 있으나 내부 제어의 일관성 문제 때문에 많은 어려움이 있다. 이를 해결하고, 다양한 망에서의 멀티미디어 회의시스템을 위하여 국제표준기구 및 컨소시엄에서 T.130, T.131, T.132로 현재 표준화가 진행되고 있으며, 본 논문에서 이들을 분석하고 LAN에서 구현하였다. 구현된 시스템에 망에 종속된 하부구조들을 추가하면 혼합망에서 운용되는 멀티미디어 회의 시스템으로 확장할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2774-2796
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• 2015

Quality-of-service (QoS) provisioning for a cognitive mesh network (CMN) with heterogeneous services has become a challenging area of research in recent days. Considering both real-time (RT) and non-real-time (NRT) traffic in a multihop CMN, [1] studied cross-layer resource management, including joint access control, route selection, and resource allocation. Due to the complexity of the formulated resource allocation problems, which are mixed-integer non-linear programming, a low-complexity yet efficient algorithm was proposed there to approximately solve the formulated optimization problems. In contrast, in this work, we present an application of genetic algorithm (GA) to re-address the hard resource allocation problems studied in [1]. Novel initialization, selection, crossover, and mutation operations are designed such that solutions with enough randomness can be generated and converge with as less number of attempts as possible, thus improving the efficiency of the algorithm effectively. Simulation results show the effectiveness of the newly proposed GA-based algorithm. Furthermore, by comparing the performance of the newly proposed algorithm with the one proposed in [1], more insights have been obtained in terms of the tradeoff among QoS provisioning for RT traffic, throughput maximization for NRT traffic, and time complexity of an algorithm for resource allocation in a multihop network such as CMN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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• pp.3876-3895
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• 2014

Recently, Heterogeneous Network (HetNet) with Coordinated Multi-Point (CoMP) scheme is introduced into Long Term Evolution-Advanced (LTE-A) systems to improve digital services for User Equipments (UEs), especially for cell-edge UEs. However, Radio Resource Management (RRM), including Resource Block (RB) scheduling and Power Allocation (PA), in this scenario becomes challenging, due to the intercell cooperation. In this paper, we investigate the RRM problem for downlink transmission of HetNet system with Joint Processing (JP) CoMP (both joint transmission and dynamic cell selection schemes), aiming at maximizing weighted sum data rate under the constraints of both transmission power and backhaul capacity. First, joint RB scheduling and PA problem is formulated as a constrained Mixed Integer Programming (MIP) which is NP-hard. To simplify the formulation problem, we decompose it into two problems of RB scheduling and PA. For RB scheduling, we propose an algorithm with less computational complexity to achieve a suboptimal solution. Then, according to the obtained scheduling results, we present an iterative Karush-Kuhn-Tucker (KKT) method to solve the PA problem. Extensive simulations are conducted to verify the effectiveness and efficiency of the proposed algorithms. Two kinds of JP CoMP schemes are compared with a non-CoMP greedy scheme (max capacity scheme). Simulation results prove that the CoMP schemes with the proposed RRM algorithms dramatically enhance data rate of cell-edge UEs, thereby improving UEs' fairness of data rate. Also, it is shown that the proposed PA algorithms can decrease power consumption of transmission antennas without loss of transmission performance.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제6권3호
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• pp.135-142
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• 2017

DDoS (Distributed Denial of Service)는 대량의 좀비 PC를 이용하여 공격 대상 서버에 접근하여 자원을 고갈시켜 정상적인 사용자가 서버를 이용하지 못하게 하는 공격이다. DDoS 공격발생 사례가 꾸준히 증가하고 있고, 주요 공격대상은 IT 서비스, 금융권, 정부기관이기 때문에 DDoS를 탐지하는 것이 중요한 이슈로 떠오르고 있다. 본 논문에서는 DNS 서버를 이용하여 패킷을 증폭시키는 DNS DDoS 공격 즉, DNS Amplification 공격(이하 DNS 증폭 공격)을 Deep Learning (이하 딥 러닝)을 활용해 실시간으로 탐지하는 방법에 대해 소개한다. 기존 연구들의 한계점을 극복하기 위하여 실험망 환경의 데이터가 아닌 실 환경 데이터를 혼합하여 탐지 시스템을 학습하였다. 또한 이미지 인식에 주로 사용되는 Convolutional Neural Network (이하 CNN)을 이용하여 딥 러닝 모델을 구축하였다.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.175-182
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• 2022

In our daily life, we come across different types of information, for example in the format of multimedia and text. We all need different types of information for our common routines as watching/reading the news, listening to the radio, and watching different types of videos. However, sometimes we could run into problems when a certain type of information is required. For example, someone is listening to the radio and wants to listen to jazz, and unfortunately, all the radio channels play pop music mixed with advertisements. The listener gets stuck with pop music and gives up searching for jazz. So, the above example can be solved with an automatic audio classification system. Deep Learning (DL) models could make human life easy by using audio classifications, but it is expensive and difficult to deploy such models at edge devices like nano BLE sense raspberry pi, because these models require huge computational power like graphics processing unit (G.P.U), to solve the problem, we proposed DL model. In our proposed work, we had gone for a low complexity model for Audio Event Detection (AED), we extracted Mel-spectrograms of dimension 128×431×1 from audio signals and applied normalization. A total of 3 data augmentation methods were applied as follows: frequency masking, time masking, and mixup. In addition, we designed Convolutional Neural Network (CNN) with spatial dropout, batch normalization, and separable 2D inspired by VGGnet [1]. In addition, we reduced the model size by using model quantization of float16 to the trained model. Experiments were conducted on the updated dataset provided by the Detection and Classification of Acoustic Events and Scenes (DCASE) 2020 challenge. We confirm that our model achieved a val_loss of 0.33 and an accuracy of 90.34% within the 132.50KB model size.

• Advances in materials Research
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• 제13권1호
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• pp.63-86
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• 2024

Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.

• Animal Bioscience
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• 제36권1호
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• pp.10-18
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• 2023

Objective: In this study, we aimed to position the Hungarian Merino among other Merinoderived sheep breeds, explore the characteristics of our sampled animals' genetic similarity network within the breed, and highlight single nucleotide polymorphisms (SNPs) associated with daily weight-gain. Methods: Hungarian Merino (n = 138) was genotyped on Ovine SNP50 Bead Chip (Illumina, San Diego, CA, USA) and positioned among 30 Merino and Merino-derived breeds (n = 555). Population characteristics were obtained via PLINK, SVS, Admixture, and Treemix software, within-breed network was analysed with python networkx 2.3 library. Daily weight gain of Hungarian Merino was standardised to 60 days and was collected from the database of the Association of Hungarian Sheep and Goat Breeders. For the identification of loci associated with daily weight gain, a multi-locus mixed-model was used. Results: Supporting the breed's written history, the closest breeds to Hungarian Merino were Estremadura and Rambouillet (pairwise F_ST values are 0.035 and 0.036, respectively). Among Hungarian Merino, a highly centralised connectedness has been revealed by network analysis of pairwise values of identity-by-state, where the animal in the central node had a betweenness centrality value equal to 0.936. Probing of daily weight gain against the SNP data of Hungarian Merinos revealed five associated loci. Two of them, OAR8_17854216.1 and s42441.1 on chromosome 8 and 9 (-log₁₀P>22, false discovery rate<5.5e-20) and one locus on chromosome 20, s28948.1 (-log₁₀P = 13.46, false discovery rate = 4.1e-11), were close to the markers reported in other breeds concerning daily weight gain, six-month weight, and post-weaning gain. Conclusion: The position of Hungarian Merino among other Merino breeds has been determined. We have described the similarity network of the individuals to be applied in breeding practices and highlighted several markers useful for elevating the daily weight gain of Hungarian Merino.

• International Journal of CAD/CAM
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• 제4권1호
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• pp.1-10
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• 2004

Through reviewing and comparing the current virtual shopping malls web sites integrated VR into E-commerce, this paper analyzed both the advantages and disadvantages of two kinds of methods for product presentation: 2D image based and 3D model based presentation method. Using the virtual shopping mall (EasyMall) as a showcase, we presented the architecture of the system and the development technologies, especially those in the mixed presentation method. The presentation and customization methods in the two related modules, including the PhoneShow for mobile phone and EasyShow for textile products, were discussed. It indicated that the integration of E-commerce with VR could provide consumers with virtual experience and intelligent service for business activities. Furthermore, the product presentation methods can be made available for use in different cases.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1758-1761
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• 1997

The problem of long range capacity expansion planing for chemical processing network under uncertain demand forecast secnarios is addressed. This optimization problem involves capactiy expansion timing and sizing of each chemical processing unit to maximize the expected net present value considering the deviation of net present values and the excess capacity over a given time horizon. A multiperiod mixed integer nonlinear programming optimization model that is both solution and modle robust for any realization of demand scenarios is developed using the two-stage stochastic programming algorithm. Two example problems are considered to illustrate the effectiveness of the model.