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By employing a light pulse storage and retrieval process based on the electromagnetically induced transparency effect, first-order subwavelength interference fringe with an effective wavelength equal to λ/n was proposed and experimentally demonstrated with n=2 and a visibility ∼80%.
In this paper, a series of BaTiO3-SiO2 composites were fabricated by using a combined process of SiO2 wet chemical coating and conventional ceramic process, and the effects of SiO2 coating on microstructures, dielectric and ferroelectric properties were investigated. XRD diffraction patterns illustrated a typical perovskite structure of the SiO2 coated BaTiO3 particles, which confirmed an amorphous...
AdaBoost has attracted much attention in the machine learning community because of its excellent performance in combining weak classifiers into strong classifiers. However, AdaBoost tends to overfit to the noisy data in many applications. Accordingly, improving the antinoise ability of AdaBoost plays an important role in many applications. The sensitiveness to the noisy data of AdaBoost stems from...
Among a variety of techniques for broadband access, the infrastructure based on Passive Optical Network (PON) is one of the most viable solutions. In 10- and 40-Gigabit capable PON, the downstream wavelength in optical line terminals (OLTs) has been set in L-band. The electroabsorption modulated laser (EML) is a popular lasing source in such PONs due to its low chirp and high modulation speed. However,...
Rapid growth in the number of users (largely sensor nodes) of most Internet-of-Things (IoT) applications is widely expected in recent years. 3G or 4G protocols are designed for regular Human-to-Human communication purposes instead of low-rate, Machine-to-Machine (M2M) communication, which is the basis of IoT. Comparatively, traditional spread-spectrum protocols such as Code-Division Multiple Access...
Nowadays, machine learning based methods are among the most popular ones for malware detection. However, most of the previous works use a single type of features, dynamic or static, and take them to build a binary classification model. These methods have limited ability to depict characteristic malware behaviors and suffer from insufficiently sampled benign samples and extremely imbalanced training...
Capturing behavior of malware is one of the essential prerequisites for dynamic malware analysis. In this paper, we study and design a system called Osiris, which makes use of virtual machine technique to capture malware behavior. In particularly, we monitor Windows API calls invoked by the process under analysis (or target program) to rebuild its behaviors. The monitor is implemented at the virtual...
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