• 제목/요약/키워드: Mathematical Computing

검색결과 342건 처리시간 0.02초

Microblog User Geolocation by Extracting Local Words Based on Word Clustering and Wrapper Feature Selection

  • Tian, Hechan;Liu, Fenlin;Luo, Xiangyang;Zhang, Fan;Qiao, Yaqiong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권10호
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    • pp.3972-3988
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    • 2020
  • Existing methods always rely on statistical features to extract local words for microblog user geolocation. There are many non-local words in extracted words, which makes geolocation accuracy lower. Considering the statistical and semantic features of local words, this paper proposes a microblog user geolocation method by extracting local words based on word clustering and wrapper feature selection. First, ordinary words without positional indications are initially filtered based on statistical features. Second, a word clustering algorithm based on word vectors is proposed. The remaining semantically similar words are clustered together based on the distance of word vectors with semantic meanings. Next, a wrapper feature selection algorithm based on sequential backward subset search is proposed. The cluster subset with the best geolocation effect is selected. Words in selected cluster subset are extracted as local words. Finally, the Naive Bayes classifier is trained based on local words to geolocate the microblog user. The proposed method is validated based on two different types of microblog data - Twitter and Weibo. The results show that the proposed method outperforms existing two typical methods based on statistical features in terms of accuracy, precision, recall, and F1-score.

Paper Recommendation Using SPECTER with Low-Rank and Sparse Matrix Factorization

  • Panpan Guo;Gang Zhou;Jicang Lu;Zhufeng Li;Taojie Zhu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권5호
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    • pp.1163-1185
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    • 2024
  • With the sharp increase in the volume of literature data, researchers must spend considerable time and energy locating desired papers. A paper recommendation is the means necessary to solve this problem. Unfortunately, the large amount of data combined with sparsity makes personalizing papers challenging. Traditional matrix decomposition models have cold-start issues. Most overlook the importance of information and fail to consider the introduction of noise when using side information, resulting in unsatisfactory recommendations. This study proposes a paper recommendation method (PR-SLSMF) using document-level representation learning with citation-informed transformers (SPECTER) and low-rank and sparse matrix factorization; it uses SPECTER to learn paper content representation. The model calculates the similarity between papers and constructs a weighted heterogeneous information network (HIN), including citation and content similarity information. This method combines the LSMF method with HIN, effectively alleviating data sparsity and cold-start issues and avoiding topic drift. We validated the effectiveness of this method on two real datasets and the necessity of adding side information.

BIFURCATION ANALYSIS OF A DELAYED PREDATOR-PREY MODEL OF PREY MIGRATION AND PREDATOR SWITCHING

  • Xu, Changjin;Tang, Xianhua;Liao, Maoxin
    • 대한수학회보
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    • 제50권2호
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    • pp.353-373
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    • 2013
  • In this paper, a class of delayed predator-prey models of prey migration and predator switching is considered. By analyzing the associated characteristic transcendental equation, its linear stability is investigated and Hopf bifurcation is demonstrated. Some explicit formulae for determining the stability and the direction of the Hopf bifurcation periodic solutions bifurcating from Hopf bifurcations are obtained by using the normal form theory and center manifold theory. Some numerical simulations for justifying the theoretical analysis are also provided. Finally, biological explanations and main conclusions are given.

모바일 클라우드 컴퓨팅의 작업 실행 시간에 대한 연구 (Study on the Job Execution Time of Mobile Cloud Computing)

  • 정성민;김태경
    • 디지털산업정보학회논문지
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    • 제8권1호
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    • pp.99-105
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    • 2012
  • Given the numbers of smartphones, tablets and other mobile devices shipped every day, more and more users are relying on the cloud as the main driver for satisfying their computing needs, whether it is data storage, applications or infrastructure. Mobile cloud computing is simply cloud computing in which at least some of the devices involved are mobile. Each node is owned by a different user and is likely to be mobile. Using mobile hardware for cloud computing has advantages over using traditional hardware. These advantage include computational access to multimedia and sensor data without the need for large network transfer, more efficient access to data stored on other mobile devices and distributed ownership and maintenance of hardware. It is important to predict job execution time in mobile cloud computing because there are many mobile nodes with different capabilities. This paper analyzes the job execution time for mobile cloud computing in terms of network environment and heterogeneous mobile nodes using a mathematical model.

소형컴퓨터의 수학교육에의 이용의 가능성 (Possibility of Micro Computer Uses in Mathematics Education)

  • 식촌철랑
    • 한국수학교육학회지시리즈A:수학교육
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    • 제24권2호
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    • pp.35-47
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    • 1986
  • As computer is diffused in society widely, it is desired that we investigate on computer uses in school education. In this paper, Possibility of Micro computer uses in mathematics education is investigated. Educational computing is classified roughly three categories they are CAI CMI and Computer iteracy education. CAI is discussed at this place. Firstly, programs of mathematics educational computing is introduced and they are classified into Practicing, Tutoring, Simulating, Gaming, Demonstration, Informing. Next, the problems that we must notice in mathematics educational computing are indicated. They are computer language, development of soft ware, effectiveness of CAI etc...

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EPfuzzer: Improving Hybrid Fuzzing with Hardest-to-reach Branch Prioritization

  • Wang, Yunchao;Wu, Zehui;Wei, Qiang;Wang, Qingxian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권9호
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    • pp.3885-3906
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    • 2020
  • Hybrid fuzzing which combines fuzzing and concolic execution, has proved its ability to achieve higher code coverage and therefore find more bugs. However, current hybrid fuzzers usually suffer from inefficiency and poor scalability when applied to complex, real-world program testing. We observed that the performance bottleneck is the inefficient cooperation between the fuzzer and concolic executor and the slow symbolic emulation. In this paper, we propose a novel solution named EPfuzzer to improve hybrid fuzzing. EPfuzzer implements two key ideas: 1) only the hardest-to-reach branch will be prioritized for concolic execution to avoid generating uninteresting inputs; and 2) only input bytes relevant to the target branch to be flipped will be symbolized to reduce the overhead of the symbolic emulation. With these optimizations, EPfuzzer can be efficiently targeted to the hardest-to-reach branch. We evaluated EPfuzzer with three sets of programs: five real-world applications and two popular benchmarks (LAVA-M and the Google Fuzzer Test Suite). The evaluation results showed that EPfuzzer was much more efficient and scalable than the state-of-the-art concolic execution engine (QSYM). EPfuzzer was able to find more bugs and achieve better code coverage. In addition, we discovered seven previously unknown security bugs in five real-world programs and reported them to the vendors.

An OpenFlow User-Switch Remapping Approach for DDoS Defense

  • Wei, Qiang;Wu, Zehui;Ren, Kalei;Wang, Qingxian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권9호
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    • pp.4529-4548
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    • 2016
  • DDoS attacks have had a devastating effect on the Internet, which can cause millions of dollars of damage within hours or even minutes. In this paper we propose a practical dynamic defense approach that overcomes the shortage of static defense mechanisms. Our approach employs a group of SDN-based proxy switches to relay data flow between users and servers. By substituting backup proxy switches for attacked ones and reassigning suspect users onto the new proxy switches, innocent users are isolated and saved from malicious attackers through a sequence of remapping process. In order to improve the speed of attacker segregation, we have designed and implemented an efficient greedy algorithm which has been demonstrated to have little influence on legitimate traffic. Simulations, which were then performed with the open source controller Ryu, show that our approach is effective in alleviating DDoS attacks and quarantining the attackers by numerable remapping process. The simulations also demonstrate that our dynamic defense imposes little effect on legitimate users, and the overhead introduced by remapping procedure is acceptable.

A Dynamic Defense Using Client Puzzle for Identity-Forgery Attack on the South-Bound of Software Defined Networks

  • Wu, Zehui;Wei, Qiang;Ren, Kailei;Wang, Qingxian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권2호
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    • pp.846-864
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    • 2017
  • Software Defined Network (SDN) realizes management and control over the underlying forwarding device, along with acquisition and analysis of network topology and flow characters through south bridge protocol. Data path Identification (DPID) is the unique identity for managing the underlying device, so forged DPID can be used to attack the link of underlying forwarding devices, as well as carry out DoS over the upper-level controller. This paper proposes a dynamic defense method based on Client-Puzzle model, in which the controller achieves dynamic management over requests from forwarding devices through generating questions with multi-level difficulty. This method can rapidly reduce network load, and at the same time separate attack flow from legal flow, enabling the controller to provide continuous service for legal visit. We conduct experiments on open-source SDN controllers like Fluid and Ryu, the result of which verifies feasibility of this defense method. The experimental result also shows that when cost of controller and forwarding device increases by about 2%-5%, the cost of attacker's CPU increases by near 90%, which greatly raises the attack difficulty for attackers.

SOCMTD: Selecting Optimal Countermeasure for Moving Target Defense Using Dynamic Game

  • Hu, Hao;Liu, Jing;Tan, Jinglei;Liu, Jiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권10호
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    • pp.4157-4175
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    • 2020
  • Moving target defense, as a 'game-changing' security technique for network warfare, realizes proactive defense by increasing network dynamics, uncertainty and redundancy. How to select the best countermeasure from the candidate countermeasures to maximize defense payoff becomes one of the core issues. In order to improve the dynamic analysis for existing decision-making, a novel approach of selecting the optimal countermeasure using game theory is proposed. Based on the signal game theory, a multi-stage adversary model for dynamic defense is established. Afterwards, the payoffs of candidate attack-defense strategies are quantified from the viewpoint of attack surface transfer. Then the perfect Bayesian equilibrium is calculated. The inference of attacker type is presented through signal reception and recognition. Finally the countermeasure for selecting optimal defense strategy is designed on the tradeoff between defense cost and benefit for dynamic network. A case study of attack-defense confrontation in small-scale LAN shows that the proposed approach is correct and efficient.