• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.532-540
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• 2005

In this paper, a sequential detection scheme is proposed as a combination of a novel weak-signal and a locally optimum(LO) detection schemes. In Part 1, we propose a novel sequential detection scheme for weak signals and show some interesting threshold properties and examples. In Part 2, the performance of the proposed sequential detection scheme is compared with that of the fixed sample size(FSS) test, sequential probability ratio test (SPRT), and truncated sequential probability ratio test(TSPRT).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.1027-1035
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• 2005

In this paper, the performance of the sequential detection scheme proposed in Part 1 is compared with that of the fixed sample size (FSS) test, sequential probability ratio test (SPRT), and truncated sequential probability ratio test (TSPRT). The proposed sequential detection scheme requires less complexity and, in most cases, smaller sample size than the SPRT. It is also observed that the proposed sequential detection scheme has always lower complexity and smaller sample size than the FSS test and TSPRT.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.122-133
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• 2009

As wireless spectrum resources become more scarce while some portions of frequency bands suffer from low utilization, the design of cognitive radio (CR) has recently been urged, which allows opportunistic usage of licensed bands for secondary users without interference with primary users. Spectrum sensing is fundamental for a secondary user to find a specific available spectrum hole. Cooperative spectrum sensing is more accurate and more widely used since it obtains helpful reports from nodes in different locations. However, if some nodes are compromised and report false sensing data to the fusion center on purpose, the accuracy of decisions made by the fusion center can be heavily impaired. Weighted sequential probability ratio test (WSPRT), based on a credit evaluation system to restrict damage caused by malicious nodes, was proposed to address such a spectrum sensing data falsification (SSDF) attack at the price of introducing four times more sampling numbers. In this paper, we propose two new schemes, named enhanced weighted sequential probability ratio test (EWSPRT) and enhanced weighted sequential zero/one test (EWSZOT), which are robust against SSDF attack. By incorporating a new weight module and a new test module, both schemes have much less sampling numbers than WSPRT. Simulation results show that when holding comparable error rates, the numbers of EWSPRT and EWSZOT are 40% and 75% lower than WSPRT, respectively. We also provide theoretical analysis models to support the performance improvement estimates of the new schemes.

• Phonetics and Speech Sciences
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• v.2 no.2
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• pp.63-68
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• 2010

A new version of sequential probability ratio test (SPRT) which has been investigated in utterance-length control is proposed to obtain uniform response results in speaker verification (SV). Although SPRTs can obtain fast responses in SV tests, differences in the performance may occur depending on the compositions of consonants and vowels in the sentences used. In this paper, a fast sequential probability ratio test (FSPRT) method that shows consistent performances at all times regardless of the compositions of vocalized sentences for SV will be proposed. In generating frames, the FSPRT will first conduct SV test processes with only generated frames without any overlapping and if the results do not satisfy discrimination criteria, the FSPRT will sequentially use frames applied with overlapping. With the progress of processes as such, the test will not be affected by the compositions of sentences for SV and thus fast response outcomes and even consistent performances can be obtained. Experimental results show that the FSPRT has better performance to the SPRT method while requiring less complexity with equal error rates (EER).

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.4
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• pp.1160-1171
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• 2015

The purpose of this study is to design and develop a computer based learning and test system, which supports not only testing learner's ability but also learning contents with giving feedback and hint. In order to design and develop a computer based learning and test system, Visual Basic dot Net software is used. The system works in three stages: sequential problem solving stage, randomized problem solving stage, and the challenge stage of pass/fail. The results of this study are as follows: (a) We propose the context of design for the computer based learning and test system. (b) We design and develop items display function with sequential and random algorithm in this system. (c) We design and develop pass/fail function by applying SPRT(Sequential Probability Ratio Testing) algorithm in the computer based learning and test system.

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.109-117
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• 1996

We introduce the more informative sequential probability ratio test(SPRT) than currently used SPRT. Though the proposed SPRT shares similar mathematical properties with the ordinary SPRT, it is less affected by the outliers and even it indicates possible existence of such outliers. Futhermore, it responds to the changes among observations more quickly than the ordinary SPRT.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.59-63
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• 2023

We create a malware detector classification method with using the Sequential Probability Ratio Test (SPRT) in IoT. More specifically, we adapt the SPRT to classify malware detectors into two categories of basic and advanced in line with malware detection capability. We perform evaluation of our scheme through simulation. Our simulation results show that the number of advanced detectors is changed in line with threshold for fraction of advanced malware information, which is used to judge advanced detectors in the SPRT.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.64-69
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• 2023

We devise a collaboration construction method based on the SPRT (Sequential Probability Ratio Test) for malware detection in IoT. In our method, high-end IoT nodes having capable of detecting malware and generating malware signatures harness the SPRT to give a reward of malware signatures to low-end IoT nodes providing useful data for malware detection in IoT. We evaluate our proposed method through simulation. Our simulation results indicate that the number of malware signatures provided for collaboration is varied in accordance with the threshold for fraction of useful data.

• Journal of Aerospace System Engineering
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• v.11 no.4
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• pp.22-29
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• 2017

A study is performed for the effective detection method of a fault which is occurred during operation in a small turbojet engine with non-linear characteristics used by unmanned air vehicle. For this study the non-linear dynamic model of the engine is derived from transient thermodynamic cycle analysis. Also for inducing real operation conditions the controller is developed associated with unscented Kalman filter to estimate noises. Sequential probability ratio test is introduced as a real time method to detect a fault which is manipulated for simulation as a malfunction of rotational speed sensor contaminated by large amount of noise. The method applied to the fault detection during operation verifies its effectiveness and high feasibility by showing good and definite decision performances of the fault.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.501-512
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• 2018

We propose Sequential Patient Recruitment Monitoring (SPRM), a new monitoring procedure for patient recruitment in a clinical trial. Based on the sequential probability ratio test using improved stopping boundaries by Woodroofe, the method allows for continuous monitoring of the rate of enrollment. It gives an early warning when the recruitment is unlikely to achieve the target enrollment. The packet data approach combined with the Central Limit Theorem makes the method robust to the distribution of the recruitment entry pattern. A straightforward application of the counting process framework can be used to estimate the probability to achieve the target enrollment under the assumption that the current trend continues. The required extension of the recruitment period can also be derived for a given confidence level. SPRM is a new, continuous patient recruitment monitoring tool that provides an opportunity for corrective action in a timely manner. It is suitable for the modern, centralized data management environment and requires minimal effort to maintain. We illustrate this method using real data from two well-known, multicenter, phase III clinical trials.