Foreground detection is an essential preprocessing step for many image processingapplications such as object tracking, human action recognition, pose estimation and occupancy mapping. Many existing techniques only pe...
详细信息
Two-dimensional image correlation using optical computation is proposed as a fast and flexible technique for tracking target images in automated biomedical systems. A robotic laser delivery system can use the correlat...
详细信息
Two-dimensional image correlation using optical computation is proposed as a fast and flexible technique for tracking target images in automated biomedical systems. A robotic laser delivery system can use the correlation technique to fixate the laser beam on a moving background. A small magnification change, which normally smears the profile of the output of digital correlators, can be adjusted in an optical correlator. The use of optical computing in highly computationally-oriented applications is crucial due to the inherently fast parallelprocessing nature of optical systems. The optical correlator is described, and the compensation process is discussed.
distributed online social networks (DOSN) have emerged recently. Nevertheless, recommending friends in the distributed social networks has not been exploited fully. We propose BCE (Bloom Filter based Common-Friend Est...
详细信息
The recent development on semiconductor process and design technologies enables multi-core processors to become a dominant market trend in desk-top PCs as well as high end mobile devices. At the same time, the increas...
详细信息
Quality assurance of multitier application is still a challenge. Especially difficult is testing big, distributedapplications written by several programmers, with the use of components from different sources. Due to ...
详细信息
ISBN:
(纸本)0387393870
Quality assurance of multitier application is still a challenge. Especially difficult is testing big, distributedapplications written by several programmers, with the use of components from different sources. Due to multi threaded and distributed architecture, their ability to be observed and their profiling are extremely difficult. J2eeprof is a new tool developed for testing and profiling multitier applications that run in the J2EE environment. The tool is based on the paradigm of aspect insertion. The main goal of j2eeprof is to help in fixing of integration errors and efficiency errors. This paper presents the concept of j2eeprof and gives some insides of j2eeprof development. On the beginning we give some introduction to the methods of software profiling, and a brief characteristic of existing profilers, i.e., JFluid, Iron Track Sql, Optimizelt Server Trace and JXInsight. Next we present the architecture of j2eeprof, and we describe how it collects data, what protocols it uses, and what kind of analysis it supports. On the end we demonstrate how j2eeprof works in practice. In conclusions we list the strong and weak points of this tool, which is still in a beta version. J2eeprof is planned to be offered as an open source for the programmer community.
The increase in global energy demand with a growing dynamic power system has made today's electrical network a complex infrastructure where increased faults and grid violations are being reported at higher rates. ...
详细信息
ISBN:
(纸本)9798350377385;9798350377378
The increase in global energy demand with a growing dynamic power system has made today's electrical network a complex infrastructure where increased faults and grid violations are being reported at higher rates. Also, with an increased penetration of intermittent distributed Energy Resource (DER), the detection of transient events occurring in a large network is becoming challenging and therefore encouraging potential areas of research in this field. Furthermore, the deployment of high-resolution devices such as PMU gives access to vast amounts of data and carries vital information to ensure grid safety and protection. This paper analyzes a methodology to detect and predict power system disturbances and fault location in electrical power network (distribution & transmission) using data-driven & machine learning techniques. It uses signal processingtechniques based on multi-level discrete wavelet transforms, with wavelet spectral energy/entropy-based feature extraction stage to train ANN (Artificial Neural Network) classifiers to predict and classify faults in power system applications. Machine learning classification techniques are used based on a dataset which is generated with single measurement point in simulation environment where grid model is used with varying fault conditions such as alternating phase & neutral impedance, inception angle & distance. A comparative analysis is performed with ANN and other potential classifiers to identify potential limitation & improvements in feature extraction stage to better classify faults and location. Furthermore, PQ events such as voltage sag, voltage swell, and transient event have been analyzed and the propagating effect of faults in the network, medium voltage to low voltage network are also discussed.
To thwart the detection of malware through traditional and emerging approaches, malware development has seen a paradigm of embedding the malware into benign applications. This calls for a localized feature extraction ...
详细信息
ISBN:
(纸本)9781450369251
To thwart the detection of malware through traditional and emerging approaches, malware development has seen a paradigm of embedding the malware into benign applications. This calls for a localized feature extraction scheme for detecting stealthy malware with more robustness. To address this challenge, we introduce a hybrid approach which utilizes the microarchitectural traces obtained through on-chip embedded hardware performance counters (HPCs) and the application binary for malware detection. The obtained HPCs are fed to multi-stage machine learning (ML) classifier for detecting and classifying the malware. To overcome the challenge of detecting the stealthy malware, image processing based approach is applied in parallel. In this approach, the malware binaries are converted into images, which is further converted into sequences and fed to recurrent neural networks to recognize patterns of stealthy malware. Based on the localized patterns, sequence classification is further applied to perform binary classification and further discover the variation of the identified malware family. Our proposed framework exhibits high resilience to popular obfuscation techniques such as code relocation.
The paper presents an important aspect of cloud computing technology, namely migrating enterprise level workloads to a cloud environment, without re-architecting or re-engineering the existing applications. How readil...
详细信息
ISBN:
(纸本)9781467323703
The paper presents an important aspect of cloud computing technology, namely migrating enterprise level workloads to a cloud environment, without re-architecting or re-engineering the existing applications. How readily an application can be lifted and shifted onto a cloud platform depends on factors like nature of the application, the type of cloud etc. In this respect, the paper explores the methodology of migrations along with the challenges and issues that usually acts as a barrier for organizations trying to pursue this goal. An effort is also made to see how the cloud migration framework maps to the cloud Computing Reference Architecture model. Finally, a set of migration patterns which span the continuum from legacy IT environment to the cloud are included as a common framework for aligning the various migration approaches developed in support of using cloud as a delivery paradigm.
With today's new battery technology and power hungry devices that may need many hours of emergency battery backup, there is the danger of short circuit currents reaching more than 100kA and exceeding the short cir...
详细信息
ISBN:
(纸本)9781479931040
With today's new battery technology and power hungry devices that may need many hours of emergency battery backup, there is the danger of short circuit currents reaching more than 100kA and exceeding the short circuit current ratings of existing DC fuses. Until manufacturers design, test and certify DC fuses with higher short circuit current rating, excessive short circuit currents pose a danger to both personnel and property. This paper discusses solutions to manage short circuit currents and make a system safe using available current limiting devices and techniques. An energy storage system project was deployed which consists of 3 sites with a total of 1MW hours of distributed lithium-ion batteries. These batteries provide stored energy to be used for uninterruptable power supply (UPS) back up and peak shaving (PS) applications. The biggest site, of the3, contains a distributed energy storage system with 64 lithium-ion batteries, rated at 416 kWh, installed in parallel, with a potential of 384kA of short circuit current and this is almost 4 times more current than a 100kA rated fuse can handle. In circuit measurements were used to determine the inductance and resistance of the system. Computer simulations were used to verify the rise times, RMS, and peak current levels required to safely interrupting the current in the fuses. Increasing the Impedance (resistance and inductance), along with proper fusing, were used to limit the short circuit current in a system. Using this combined approach, the required protection to limit the potential short circuit current, flowing through any fuse, could be shown to be reduced to fewer than 100kA.
We introduce a novel method for the consolidation of unorganized point clouds with noise, outliers, non-uniformities as well as sharp features. This method is feature preserving, in the sense that given an initial est...
详细信息
暂无评论