• Title/Summary/Keyword: Time-interval information

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A Structured Overlay Network Scheme Based on Multiple Different Time Intervals

  • Kawakami, Tomoya
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1447-1458
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    • 2020
  • This paper describes a structured overlay network scheme based on multiple different time intervals. Many types of data (e.g., sensor data) can be requested at specific time intervals that depend on the user and the system. These queries are referred to as "interval queries." A method for constructing an overlay network that efficiently processes interval queries based on multiple different time intervals is proposed herein. The proposed method assumes a ring topology and assigns nodes to a keyspace based on one-dimensional time information. To reduce the number of forwarded messages for queries, each node constructs shortcut links for each interval that users tend to request. This study confirmed that the proposed method reduces the number of messages needed to process interval queries. The contributions of this study include the clarification of interval queries with specific time intervals; establishment of a structured overlay network scheme based on multiple different time intervals; and experimental verification of the scheme in terms of communication load, delay, and maintenance cost.

Model-Free Interval Prediction in a Class of Time Series with Varying Coefficients

  • Park, Sang-Woo;Cho, Sin-Sup;Lee, Sang-Yeol;Hwang, Sun-Y.
    • Journal of the Korean Data and Information Science Society
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    • v.11 no.2
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    • pp.173-179
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    • 2000
  • Interval prediction based on the empirical distribution function for the class of time series with time varying coefficients is discussed. To this end, strong mixing property of the model is shown and results due to Fotopoulos et. al.(1994) are employed. A simulation study is presented to assess the accuracy of the proposed interval predictor.

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Optimal Time-Interval for Time-based Location Update in Mobile Communications

  • Lee, Yong;Lee, Goo-Yeon
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.169-173
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    • 2003
  • In this paper, we analyze a time-based update method in location management and calculate the optimal time-interval. We obtain the probability that an MT is j rings away from the center cell. And using these values, an exact analysis is made for the time-based location management cost. From the result, when the time-based method is applied to location update, we can get the optimal time-interval which minimizes the location management cost.

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Effects of comparison interval and order on subjective evaluation test of loudness

  • Yonshida, Junji;Hasegawa, Hiroshi;Kasuga, Masao
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1792-1795
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    • 2002
  • In this paper we investigated effects of the presentation time interval on a subjective evaluation test of loudness. We carried out paired comparison experiments of pure tones loudness with changing the time interval of the comparison. As the results, two characteristic effects were obtained. The difference limen of the loudness was almost proportional to the time interval in below 10 s and was almost the same value of 1.5 dB in above 10 s. On the other hand, the effect of the presentation order was smallest at the time interval of about 5 s.

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Machine Learning Based Malware Detection Using API Call Time Interval (API Call Time Interval을 활용한 머신러닝 기반의 악성코드 탐지)

  • Cho, Young Min;Kwon, Hun Yeong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.1
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    • pp.51-58
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    • 2020
  • The use of malware in cyber threats continues to be used in all ages, and will continue to be a major attack method even if IT technology advances. Therefore, researches for detecting such malicious codes are constantly tried in various ways. Recently, with the development of AI-related technology, many researches related to machine learning have been conducted to detect malware. In this paper, we propose a method to detect malware using machine learning. For machine learning detection, we create a feature around each call interval, ie Time Interval, in which API calls occur among dynamic analysis data, and then apply the result to machine learning techniques.

Efficient Anomaly Detection Through Confidence Interval Estimation Based on Time Series Analysis

  • Kim, Yeong-Ju;Jeong, Min-A
    • International journal of advanced smart convergence
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    • v.4 no.2
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    • pp.46-53
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    • 2015
  • This paper suggests a method of real time confidence interval estimation to detect abnormal states of sensor data. For real time confidence interval estimation, the mean square errors of the exponential smoothing method and moving average method, two of the time series analysis method, were compared, and the moving average method with less errors was applied. When the sensor data passes the bounds of the confidence interval estimation, the administrator is notified through alarms. As the suggested method is for real time anomaly detection in a ship, an Android terminal was adopted for better communication between the wireless sensor network and users. For safe navigation, an administrator can make decisions promptly and accurately upon emergency situation in a ship by referring to the anomaly detection information through real time confidence interval estimation.

An iterative hybrid random-interval structural reliability analysis

  • Fang, Yongfeng;Xiong, Jianbin;Tee, Kong Fah
    • Earthquakes and Structures
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    • v.7 no.6
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    • pp.1061-1070
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    • 2014
  • An iterative hybrid structural dynamic reliability prediction model has been developed under multiple-time interval loads with and without consideration of stochastic structural strength degradation. Firstly, multiple-time interval loads have been substituted by the equivalent interval load. The equivalent interval load and structural strength are assumed as random variables. For structural reliability problem with random and interval variables, the interval variables can be converted to uniformly distributed random variables. Secondly, structural reliability with interval and stochastic variables is computed iteratively using the first order second moment method according to the stress-strength interference theory. Finally, the proposed method is verified by three examples which show that the method is practicable, rational and gives accurate prediction.

Analytic Model for Optimal Checkpoints in Mobile Real-time Systems

  • Lim, Sung-Hwa;Lee, Byoung-Hoon;Kim, Jai-Hoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.8
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    • pp.3689-3700
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    • 2016
  • It is not practically feasible to apply hardware-based fault-tolerant schemes, such as hardware replication, in mobile devices. Therefore, software-based fault-tolerance techniques, such as checkpoint and rollback schemes, are required. In checkpoint and rollback schemes, the optimal checkpoint interval should be applied to obtain the best performance. Most previous studies focused on minimizing the expected execution time or response time for completing a given task. Currently, most mobile applications run in real-time environments. Therefore, it is extremely essential for mobile devices to employ optimal checkpoint intervals as determined by the real-time constraints of tasks. In this study, we tackle the problem of determining the optimal inter-checkpoint interval of checkpoint and rollback schemes to maximize the deadline meet ratio in real-time systems and to build a probabilistic cost model. From this cost model, we can numerically find the optimal checkpoint interval using mathematical tools. The performance of the proposed solution is evaluated using analytical estimates.

A Dynamic Discount Approach to the Poisson Process

  • Shim, Joo-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.2
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    • pp.271-276
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    • 1997
  • A dynamic discount approach is proposed for the estimation of the Poisson parameter and the forecasting of the Poisson random variable, where the parameter of the Poisson distribution varies over time intervals. The recursive estimation procedure of the Poisson parameter is provided. Also the forecasted distribution of the Poisson random variable in the next time interval based on the information gathered until the current time interval is provided.

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Discount Survival Models

  • Shim, Joo-Y.;Sohn, Joong-K.
    • Journal of the Korean Data and Information Science Society
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    • v.7 no.2
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    • pp.227-234
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    • 1996
  • The discount survival model is proposed for the application of the Cox model on the analysis of survival data with time-varying effects of covariates. Algorithms for the recursive estimation of the parameter vector and the retrospective estimation of the survival function are suggested. Also the algorithm of forecasting of the survival function of individuals of specific covariates in the next time interval based on the information gathered until the end of a certain time interval is suggested.

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