• Journal of Industrial Technology
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• v.30 no.A
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• pp.111-117
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• 2010

To improve the performance of the prediction system, the system should reflect well the uncertainty of nonlinear data. Thus, this paper presents multiple prediction systems based on Type-2 fuzzy sets. To construct each prediction system, an Interval Type-2 TSK Fuzzy Logic System and difference data were used, because, in general, it has been known that the Type-2 Fuzzy Logic System can deal with the uncertainty of nonlinear data better than the Type-1 Fuzzy Logic System, and the difference data can provide more steady information than that of original data. Also, to improve each rule base of the fuzzy prediction systems, the HCBKA (Hierarchical Correlation Based K-means clustering Algorithm) was applied because it can consider correlationship and statistical characteristics between data at a time. Subsequently, to alleviate complexity of the proposed prediction system, a system selection method was used. Finally, this paper analyzed and compared the performances between the Type-1 prediction system and the Interval Type-2 prediction system using simulations of three typical time series examples.

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.389-402
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• 2023

Multivariate or clustered failure time data often occur in many medical, epidemiological, and socio-economic studies when survival data are collected from several research centers. If the data are periodically observed as in a longitudinal study, survival times are often subject to various types of interval-censoring, creating multivariate interval-censored data. Then, the event times of interest may be correlated among individuals who come from the same cluster. In this article, we propose a unified linear regression method for analyzing multivariate interval-censored data. We consider a semiparametric multivariate accelerated failure time model as a statistical analysis tool and develop a generalized Buckley-James method to make inferences by imputing interval-censored observations with their conditional mean values. Since the study population consists of several heterogeneous clusters, where the subjects in the same cluster may be related, we propose a generalized estimating equations approach to accommodate potential dependence in clusters. Our simulation results confirm that the proposed estimator is robust to misspecification of working covariance matrix and statistical efficiency can increase when the working covariance structure is close to the truth. The proposed method is applied to the dataset from a diabetic retinopathy study.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.12
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• pp.70-78
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• 2000

A novel capacitance deviation-to-time interval converter based on ramp-integration is presented. It consists of two current mirrors, two schmitt triggers, and control digital circuits by the upper and lower sides, symmetrically. Total circuit has been with discrete components. The results show that the proposed converter has a linearity error of less than 1% at the time interval(pulse width) over a capacitance deviation from 295 pF to 375 pF. A capacitance deviation of 40pF and time interval of 0.2 ms was measured for sensor capacitance of 335 pF. Therefore, the high-resolution can be known by counting the fast and stable clock pulses gated into a counter for time interval. The application of a novel capacitance deviation-to time interval converter to a digital humidity controller is also presented. The presented circuit is insensitive to the capacitance difference in disregard of voltage source or temperature deviation. Besides the accuracy, it features the small MOS device count integrable onto a small chip area. The circuit is thus particularly suitable for the on-chip interface.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.551-556
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• 2021

In this paper, we deal with the stability condition of linear interval discrete systems with time-varying delays and unstructured uncertainty. For the interval discrete system which has interval matrix as its system matrices, time-varying delay time within some interval value and unstructured uncertainty which can include non-linearity and be expressed by only its magnitude, the stability condition is proposed. Compared with the previous result derived by using a upper bound solution of the Lyapunov equation, the new results are derived by the form of simple inequality based on Lyapunov stability condition and have the advantage of being more effective in stability application. Furthermore, the proposed stable conditions are very comprehensive and powerful, including the previously published stable conditions of various linear discrete systems. The superiority of the new condition is proven in the derivation process, and the utility and superiority of the proposed condition are examined through numerical example.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.185-190
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• 2009

The event sequence of the same type from a set of events having time property can be summarized in one event. But if the event sequence having an interval, It is reasonable to be summarized more than one in independent sub event sequence of each other. In this paper, we suggest a method of temporal data mining that summarizes the interval events based on Allen's interval algebra and finds out interval event association rule from interval events. It provides better knowledge than others by using concept of an independent sub sequence and finding interval event association rules.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.397-402
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• 2013

Time variation is the essential component of the context awareness. It is a beneficial way not only including time lapse but also clustering time interval for the context inference using the information from sensor mote. In this study, we proposed a novel way of clustering based multi-sensor data fusion for the context inference. In the time interval, we fused the sensed signal of each time slot, and fused again with the results of th first fusion. We could reach the enhanced context inference with assessing the segmented signal according to the time interval at the Dempster-Shafer evidence theory based multi-sensor data fusion.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.464-471
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• 2013

With the advance of wireless sensor networks, WMSN(Wireless Multimedia Sensor Networks) researches to transfers multimedia data have been studied actively. First of all, three basic protocols, End-to-end, Hop-by-hop, and Unreliable transmission method, are compared to transfer multimedia data using simulations. This paper presents an efficient protocol to transfer multimedia data by overhearing messages of nodes and by transmitting next packets during the unused time interval. The proposed method is verified its performance by simulations and experiments. The results shows that the transmission rate of the proposed method 22% higher than that of End-to-end protocol with half of transmission time. Also the performance of the proposed method is compared with that of PIGAB(Packet Interval Gap based on Adaptive Backoff).

• Journal of the Chungcheong Mathematical Society
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• v.29 no.1
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• pp.109-115
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• 2016

In this paper we introduce the interval-valued Henstock-Stieltjes integral on time scales and investigate some properties of these integrals.

• Journal of the Chungcheong Mathematical Society
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• v.27 no.4
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• pp.745-751
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• 2014

In this paper we introduce the interval-valued Henstock integral on time scales and investigate some properties of these integrals.

• 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.