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The Sequential Probability Ratio Test (SPRT) is a classical detector for problems with an unfixed sample size. Though it is optimal under some conditions, SPRT can be directly used only for a binary hypothesis with exactly known distributions. In this paper, sequential detection problem with an uncertain hypothesis distribution is considered, in which the uncertain distribution is formulated in a...
fault injection is an effective technique in software testing. By introducing faults to software under test, fault injection can improve the coverage of a test, as the same time, the fault injected in software contributes significantly to find true fault related to fault injected. In this paper we propose a software testing method based on fault injection. In this method, we first use neural network...
Power-hardware-in-the-loop (PHIL) is a simulation tool that can support electrical systems engineers in the development and experimental validation of novel, advanced control schemes that ensure the robustness and resiliency of electrical grids that have high penetrations of low-inertia variable renewable resources. With PHIL, the impact of the device under test on a generation or distribution system...
Implementing higher voltages in vehicles like 48V mild hybrid or full-hybrid enables CO2 reduction and weight savings. However, the increase in the voltage demands an accurate and robust protection system again potential fault conditions. Series arc is one of the fault conditions which needs to be detected and addressed before the benefits of using higher voltages in vehicle can be fully realized...
Given a networked evolutionary game (NEG), if there is a positive integer T such that the trajectory from any initial profile becomes constant after the time step T, then each profile of each trajectory after the time step T is called a stationary stable profile (SSP). For finite-player NEGs, an equivalent condition for the existence of SSPs is given in [D. Cheng, F. He, H. Qi, and T. Xu. Modeling,...
Fault localization defines information models from raw runtime information as the input, depicting program behaviors for supporting localization algorithms. It is natural that an elaborate information model is desirable and likely to improve the effectiveness of fault localization, because it typically depicts subtle and more program runtime behaviors. In fact, much work on fault localization assumes...
In this paper, we introduce a new dataset, Kimia Path24, for image classification and retrieval in digital pathology. We use the whole scan images of 24 different tissue textures to generate 1,325 test patches of size 1000x1000 (0.5mm x 0.5mm). Training data can be generated according to preferences of algorithm designer and can range from approximately 27,000 to over 50,000 patches if the preset...
In order to satisfy the higher precision of indoor location-based service (ILBS), scholars have explored a great deal of algorithms based on Wi-Fi, ultrasonic, RFID or infrared, but all of which need additional device settings for transmitting and receiving signals before implementing location recognition. This paper proposed an idea that how to conveniently find the optimal feature or composite features...
In this paper we address three open questions regarding randomness test: the probability of false acceptance, the number of minimum sample size to achieve a given probability error and tests independence. We shall point out statistical testing assumptions, source of errors, sample constructions and a computational method for determining the probability of false acceptance and estimating the correlation...
Despite the popularity of Fingerprinting Localization Algorithms (FPS), general theoretical frameworks for their performance studies have rarely been discussed in the literature. In this work, after setting up an abstract model for the FPS, we show that a fingerprinting-based localization problem can be cast as a Hypothesis Testing (HT) problem and therefore various results from the HT literature...
This paper addresses the problem of the development, implementation and testing of a Lane Change Decision Aid System on a motorcycle, by using a short range radar sensor and a set of LEDs to interface with the driver. First, a feasibility analysis for such application is performed, then the algorithm is described, and finally the results of on-road tests are presented to illustrate and validate the...
All the pre-processing algorithms are being improved constantly. The biggest challenge for the multitemporal analysis is to deal with errors caused directly by the chain of pre-processing of raw Sentinel-2 data to the level L1C - misregistration of pixels. Another problem to overcome while aggregating a series of classifications is the incorrect mask of clouds over artificial structures resulting...
We consider the online and nonparametric detection of abrupt and persistent anomalies, such as a change in the regular system dynamics at a time instance due to an anomalous event (e.g., a failure, a malicious activity). Combining the simplicity of the nonparametric Geometric Entropy Minimization (GEM) method with the timely detection capability of the Cumulative Sum (CUSUM) algorithm we propose a...
More and more on-line experiments have been done in E-Commerce in order to understand the behavior of users or customers and then apply the data analysis technique to provide business guidance. One of the techniques is A/B testing. However, there is not clear guidance on the sample size in order for us to have valuable, trustable discovery. The purpose of this work is to find out a way to group customers...
The problem of quickest change detection (QCD) under transient dynamics is studied, in which the change from the initial distribution to the final persistent distribution does not happen instantaneously, but after a series of cascading transient phases. It is assumed that the durations of the transient phases are deterministic but unknown. The goal is to detect the change as quickly as possible subject...
This paper presents a comparative study on the impact of the erase algorithm on flash memory lifetime, to demonstrate how the reduction of overall stress, suffered by memories, will increase their lifetime, thanks to a smart management of erase operations. To this purpose a fixed erase voltage, equal to the maximum value and the maximum time-window, was taken as the reference test; while an algorithm...
Swarm robotic systems are often considered to be dependable. However, there is little empirical evidence or theoretical analysis showing that dependability is an inherent property of all swarm robotic system. Recent literature has identified potential issues with respect to dependability within certain types of swarm robotic algorithms. There appears to be a dearth of literature relating to the testing...
Determination of source-destination connectivity in networks has long been a fundamental problem, where most existing works are based on deterministic graphs that overlook the inherent uncertainty in network links. To overcome such limitation, this paper models the network as an uncertain graph where each edge e exists independently with some probability p(e). The problem examined is that of determining...
Statistical Machine Translation (SMT) is one of the research areas in computer science. The research of Statistical Machine Translation shows a momentous output in the denary of years. Primarily, the research focuses on how to translate from one language to another language and vice versa. It rarely discusses the searching process of Statistical Machine Translation. The objectives of this paper are...
Aim to multiclass text categorization problem, a classification algorithm based on multiconlitron and 1-a-r method is presented. 1-a-r method is used to convert a multiclass categorization problem to several binary problems. Multiconlitron is constructed for each binary problem in input space. For the text to be classified, its class is decided by multiconlitrons. The classification experiments are...
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