• Title/Summary/Keyword: Dynamically Weighted Method

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A study of the load distributing algorithm on the heterogeneously clustered web system (이기종 웹 클러스터 시스템에 대한 부하분산 알고리즘의 연구)

  • Rhee, Young
    • The KIPS Transactions:PartA
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    • v.10A no.3
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    • pp.225-230
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    • 2003
  • In this paper, we develope algorithms that distribute the load on the heterogeneously clustered web system, The response time based on the concurrent user is examined for the suggested algorithms. Simulation experience shows that the response time using the dynamically weighted methods seems to have a good results compare to that with the fixed weighted methods. And, also the effectiveness of clustered system becomes better as long as the number of concurrent user increases.

Dynamically weighted loss based domain adversarial training for children's speech recognition (어린이 음성인식을 위한 동적 가중 손실 기반 도메인 적대적 훈련)

  • Seunghee, Ma
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.6
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    • pp.647-654
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    • 2022
  • Although the fields in which is utilized children's speech recognition is on the rise, the lack of quality data is an obstacle to improving children's speech recognition performance. This paper proposes a new method for improving children's speech recognition performance by additionally using adult speech data. The proposed method is a transformer based domain adversarial training using dynamically weighted loss to effectively address the data imbalance gap between age that grows as the amount of adult training data increases. Specifically, the degree of class imbalance in the mini-batch during training was quantified, and the loss function was defined and used so that the smaller the data, the greater the weight. Experiments validate the utility of proposed domain adversarial training following asymmetry between adults and children training data. Experiments show that the proposed method has higher children's speech recognition performance than traditional domain adversarial training method under all conditions in which asymmetry between age occurs in the training data.

Dynamic Adaptive Model for WebMedia Educational Systems based on Discrete Probability Techniques (이산 확률 기법에 기반한 웹미디어 교육 시스템을 위한 동적 적응 모델)

  • Lee, Yoon-Soo
    • Journal of the Korea Computer Industry Society
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    • v.5 no.9
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    • pp.921-928
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    • 2004
  • This paper proposed dynamic adaptive model based on discrete probability distribution function and user profile in web based HyperMedia educational systems. This modelsrepresents application domain to weighted direction graph of dynamic adaptive objects andmodeling user actions using dynamically approach method structured on discrete probability function. Proposed probabilitic analysis can use that presenting potential attribute to useractions that are tracing search actions of user in WebMedia structure. This approach methodscan allocate dynamically appropriate profiles to user.

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Algorithm of GTS Time Slots Allocation Based on Weighted Fair Queuing in Environments of WBAN (WBAN 환경에서 Weighted Fair Queuing 기반의 GTS 타임 슬롯 할당 알고리즘)

  • Kim, Kyoung-Mok;Jung, Won-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.11
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    • pp.45-56
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    • 2011
  • WBAN is short range wireless communication technology which is consists of several small devices close to, attached to or implanted into the human body. WBAN is classified into between medical and non-medical by applications based on technology and medical data with periodic characteristics is used the GTS method for transmitting data to guarantee the QoS. In this paper we proposed algorithm that resolve lack of GTSs while data transmit GTS method in superframe structure of WBAN. Coordinator dynamically allocates GTSs according to the data rate of devices and make devices share GTSs when lack of GTSs. We compared delay bounds, throughput for performance evaluation of the proposed algorithm. In other words, we proposed algorithm adaptive WFQ scheduling that GTS allocation support differential data rate in environments of WBAN. The experiment results show the throughput increased and the maximum delay decreased compared with Round Robin scheduling.

Machine Learning-Based Malicious URL Detection Technique (머신러닝 기반 악성 URL 탐지 기법)

  • Han, Chae-rim;Yun, Su-hyun;Han, Myeong-jin;Lee, Il-Gu
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.3
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    • pp.555-564
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    • 2022
  • Recently, cyberattacks are using hacking techniques utilizing intelligent and advanced malicious codes for non-face-to-face environments such as telecommuting, telemedicine, and automatic industrial facilities, and the damage is increasing. Traditional information protection systems, such as anti-virus, are a method of detecting known malicious URLs based on signature patterns, so unknown malicious URLs cannot be detected. In addition, the conventional static analysis-based malicious URL detection method is vulnerable to dynamic loading and cryptographic attacks. This study proposes a technique for efficiently detecting malicious URLs by dynamically learning malicious URL data. In the proposed detection technique, malicious codes are classified using machine learning-based feature selection algorithms, and the accuracy is improved by removing obfuscation elements after preprocessing using Weighted Euclidean Distance(WED). According to the experimental results, the proposed machine learning-based malicious URL detection technique shows an accuracy of 89.17%, which is improved by 2.82% compared to the conventional method.

RadioCycle: Deep Dual Learning based Radio Map Estimation

  • Zheng, Yi;Zhang, Tianqian;Liao, Cunyi;Wang, Ji;Liu, Shouyin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.11
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    • pp.3780-3797
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    • 2022
  • The estimation of radio map (RM) is a fundamental and critical task for the network planning and optimization performance of mobile communication. In this paper, a RM estimation method is proposed based on a deep dual learning structure. This method can simultaneously and accurately reconstruct the urban building map (UBM) and estimate the RM of the whole cell by only part of the measured reference signal receiving power (RSRP). Our proposed method implements UBM reconstruction task and RM estimation task by constructing a dual U-Net-based structure, which is named RadioCycle. RadioCycle jointly trains two symmetric generators of the dual structure. Further, to solve the problem of interference negative transfer in generators trained jointly for two different tasks, RadioCycle introduces a dynamic weighted averaging method to dynamically balance the learning rate of these two generators in the joint training. Eventually, the experiments demonstrate that on the UBM reconstruction task, RadioCycle achieves an F1 score of 0.950, and on the RM estimation task, RadioCycle achieves a root mean square error of 0.069. Therefore, RadioCycle can estimate both the RM and the UBM in a cell with measured RSRP for only 20% of the whole cell.

Optimization of settlement layout based on parametric generation

  • Song, Jinghua;Xie, Xinqin;Yu, Yang
    • Advances in Computational Design
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    • v.3 no.1
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    • pp.35-47
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    • 2018
  • Design of settlement space is a complicated process while reasonable spatial layout bears great significance on the development and resource allocation of a settlement. The study proposes a weighted L-system generation algorithm based on CA (Cellular Automation) model which tags the spatial attributes of cells through changes in their state during the evolution of CA and thus identifies the spatial growth mode of a settlement. The entrance area of the Caidian Botanical and Animal Garden is used a case study for the model. A design method is proposed which starts from the internal logics of spatial generation, explores possibility of spatial rules and realizes the quantitative analysis and dynamic control of the design process. Taking a top-down approach, the design method takes into account the site information, studies the spatial generation mechanism of settlements and further presents a engine for the generation of multiple layout proposals based on different rules. A optimal solution is acquired using GA (Genetic Algorithm) which generates a settlement spatial layout carrying site information and dynamically linked to the surround environment. The study aims to propose a design method to optimize the spatial layout of the complex settlement system based on parametric generation.

Ontology based Educational Systems using Discrete Probability Techniques (이산 확률 기법을 이용한 온톨로지 기반 교육 시스템)

  • Lee, Yoon-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.1 s.45
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    • pp.17-24
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    • 2007
  • Critical practicality problems are cause to search the presentation and contents according to user request and purpose in previous internet system. Recently, there are a lot of researches about dynamic adaptable ontology based system. We designed ontology based educational system which uses discrete probability and user profile. This system provided advanced usability of contents by ontology and dynamic adaptive model based on discrete probability distribution function and user profile in ontology educational systems. This models represents application domain to weighted direction graph of dynamic adaptive objects and modeling user actions using dynamically approach method structured on discrete probability function. Proposed probability analysis can use that presenting potential attribute to user actions that are tracing search actions of user in ontology structure. This approach methods can allocate dynamically appropriate profiles to user.

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Policy-based Dynamic Channel Selection Architecture for Cognitive Radio Network (무선인지 기술 기반의 정책에 따른 동적 채널 선택 구조)

  • Na, Do-Hyun;Yoo, Sang-Jo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.6B
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    • pp.358-366
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    • 2007
  • Recently, FCC(Federal Communications Commission) has considered for that unlicensed device leases licensed devices' channel to overcome shortage of communication channels. Therefore, IEEE 802.22 WRAN(Wireless Regional Area Networks) working group progresses CR (Cognitive Radio) technique that is able to sense and adopt void channels that are not being occupied by the licensed devices. Channel selection is of the utmost importance because it can affect the whole system performance in CR network. Thus, we propose a policy-based dynamic channel selection architecture for cognitive radio network to achieve an efficient communication. We propose three kinds of method for channel selection; the first one is weighted channel selection, the second one is sequential channel selection, and the last one is combined channel selection. We can obtain the optimum channel list and allocates channels dynamically using the proposed protocol.

A Base Station Clustering Method Based on Sequential Selection Approach (순차적 선택 기반의 전송 기지국 클러스터 형성 방법)

  • Yoo, Hyung-Gil;Sung, Won-Jin
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.48 no.9
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    • pp.1-9
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    • 2011
  • In this paper, we propose an efficient method to create clusters of geographically distributed base stations which cooperatively transmit signals in cellular mobile communication systems. The proposed method utilizes a sequential selection approach to choose candidate base stations which can provide maximum weighted sum-rate gain when they participate in the cooperative transmission with the existing cluster. In particular, the proposed method limits the maximum number of base stations in a cluster by considering the system operational and implementation complexities. Moreover, the combinations of clusters dynamically change along with variations of channel environments. Through computer simulations, performance of the proposed method is verified by comparing with the non-cooperative transmission method and the static clustering method. Numerical result shows that the proposed sequential selection based clustering method is especially advantageous for the performance improvement of lower percentile users in terms of average throughput, and thus the proposed method can effectively improve the fairness among users.