Current Issue : January - March Volume : 2021 Issue Number : 1 Articles : 5 Articles
Optical burst switching (OBS) networks are frequently compromised by attackers who can flood the networks with burst header\npackets (BHPs), causing a denial of service (DoS) attack, also known as a BHP flooding attack. Nowadays, a set of machine\nlearning (ML) methods have been embedded into OBS core switches to detect these BHP flooding attacks. However, due to the\nredundant features of BHP data and the limited capability of OBS core switches, the existing technology still requires major\nimprovements to work effectively and efficiently. In this paper, an efficient and effective ML-based security approach is proposed\nfor detecting BHP flooding attacks. The proposed approach consists of a feature selection phase and a classification phase. The\nfeature selection phase uses the information gain (IG) method to select the most important features, enhancing the efficiency of\ndetection. For the classification phase, a decision tree (DT) classifier is used to build the model based on the selected features of\nBHPs, reducing the overfitting problem and improving the accuracy of detection. A set of experiments are conducted on a public\ndataset of OBS networks using 10-fold cross-validation and holdout techniques. Experimental results show that the proposed\napproach achieved the highest possible classification accuracy of 100% by using only three features....
A plastic filament of poly (methyl methacrylate) (PMMA) was fabricated by extrusion.\nThe mode confinement was simulated using numerical software. The idea is to study how the light\nintensity changes inside the plastic optical fiber (POF) when a bending in multiple directions is\napplied. The results obtained from the simulation were compared to the experimental observations.\nThe non-circular shape of the POF allows sensing a rotation applied as well. The angle of rotation was\nobtained processing two images of the end facet of the fiber (one with the fiber in a reference position\nand one with the rotated fiber), using an intensity-based automatic image registration....
In the MEMS optical switch assembly, the collision is likely to happen between the optical fiber and the U-groove of the chip due to\nthe uncontrollable assembly errors. However, these errors can hardly be completely eliminated by the active control using high\nprecision sensors and actuators. It will cause the large acting force and part damage, which further leads to the assembly failure. To\nsolve this question, this paper presents a novel low-cost three-degree-of-freedom (three-DOF) passive flexure system to adaptively\neliminate the planar assembly errors. The flexure system adopts three parallel kinematic chains with a novel 3-RPR structure and\nhas a compact size with a diameter of 125mmand thickness of 12 mm. A novel eddy current damper with the structure of Halbach\narray permanent magnets (PMs) is utilized to suppress the adverse mechanical vibration of the assembly system from the\nbackground disturbances. Analytical models are established to analyze the kinematic, static, and dynamic performances of the\nsystem in detail. Finally, finite element analysis is adopted to verify the established models for optimum design....
Quantitative analysis of the flow field is an effective method to study hydrodynamics. As a flow field measurement technology, the\nBackground Oriented Schlieren (BOS) is widely used. However, it is difficult to measure the complex transparent flow field (flow\nfield with large refractive index gradient) using the BOS experiment. In order to overcome this difficulty and improve the accuracy\nof the BOS experiment, this paper presents a hybrid adaptive wavelet-based optical flow algorithm for the BOS. The current\nalgorithm is a combination of the traditional optical flow algorithm and the wavelet-based optical flow algorithm. By adding the\ninitial value constraints, the adaptive scale constraints, and the adaptive regularization constraints, the algorithm can effectively\novercome the above-mentioned difficulty and also improve its accuracy. To further illustrate the feasibility of the proposed\nmethod, this paper uses the simulation data, the data of the DNS datasets, and the data of the BOS experiment to verify the\nperformance of the algorithm. The experiment of comparing the proposed algorithm with the existing ones is carried out on the\nDNS datasets and the data of the BOS experiment. Finally, the proposed method is verified by a practical BOS experiment. The\nresults show that the proposed algorithm can effectively improve the measurement accuracy of displacements....
In this study, nano ferrite materials were produced to replace costive industrial\nmaterials [1]. Ferrite nanoparticles are the interesting material due to\ntheir rich and unique physical and chemical properties. They find applications\nin catalysis, bio-processing, medicine, magnetic recording, adsorption,\ndevices etc..........................
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