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At present, machine learning is widely used for classification, such as automatic speech recognition, image identification, text classification and numbers of researches for fault diagnosis besides. Generally, most of the models used for fault diagnosis are based on the same data distribution, while the applications of the equipment in actual production and operation are mostly under unstable conditions,...
Infrared (IR) imaging for rotating machinery monitoring and fault diagnosis has gained noticeable attention in recent years since it enables non-contact, on-intrusive and singlesensor based temperature measurements. However, the IR image for fault identification requires the process of artificial feature extraction, which is influenced by personal experience. And the sensitivity of the infrared image...
Shopping of the same or similar types of products as shown in the online TV programs has been highly desired by many people, especially the youth. To meet this eminent market need, we develop a prototype system to enable effortless TV-to-Online (T2O) experience. A key component of this system is the product search that maps specific items embedded in the video into a list of online merchants. The...
Logging is a common programming practice of practical importance to collect system runtime information for postmortem analysis. Strategic logging placement is desired to cover necessary runtime information without incurring unintended consequences (e.g., Performance overhead, trivial logs). However, in current practice, there is a lack of rigorous specifications for developers to govern their logging...
In this paper, we investigate offloading policy for energy efficient mobile cloud computing. To minimize the energy consumption on the mobile device and the cloud, we propose a general optimization framework based on the characteristic of applications. Particularly, for delay-sensitive applications, we formulate a delay-constrained optimization problem, in order to reduce the energy consumption on...
Understanding the behaviors of a software system is very important for performing daily system maintenance tasks. In practice, one way to gain knowledge about the runtime behavior of a system is to manually analyze system logs collected during the system executions. With the increasing scale and complexity of software systems, it has become challenging for system operators to manually analyze system...
Target turning maneuvering is always accompanied with the rapid attitude variations, which are helpful to achieve high cross-range resolution for pulsed coherent radar. Thus, it is feasible to detect target turning maneuver using the high resolution Doppler profile (HRDP). The preliminaries concerning the HRDP are first introduced, including its formulation, extraction requirements, and procedure...
Detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. Execution anomalies include both work flow errors and low performance problems. People often use system logs produced by distributed systems for troubleshooting and problem diagnosis. However, manually inspecting system logs to detect anomalies is unfeasible...
When solving the problem in computer assisted detection by the approach of pattern recognition, the lesion data always exhibited high-dimensional and inhomogeneous, which makes most of the traditional classifiers can not performance very well. In this paper, a novel approach based on the dynamic feature subset selection and the EM algorithm with Naive Bayesian classifier integration algorithm (DSFS+EMNB)...
Automatic target recognition (ATR) performance evaluation has become an important subject in ATR theory community since the last two decades. The extended operation condition (EOC) and system cost are two key aspects in ATR performance evaluation. For the situation of air-to-ground (A-G) ATR using high range resolution (HRR) data, this paper analyzes the influence of target type number on ATR system...
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