A machine learning-based framework for preventing video freezes in HTTP adaptive streaming

HTTP Adaptive Streaming (HAS) represents the dominant technology to deliver videos over the Internet, due to its ability to adapt the video quality to the available bandwidth. Despite that, HAS clients can still suffer from freezes in the video playout, the main factor influencing users' Quality of Experience (QoE). To reduce video freezes, we propose a network-based framework, where a network controller prioritizes the delivery of particular video segments to prevent freezes at the clients. This framework is based on OpenFlow, a widely adopted protocol to implement the software-defined networking principle. The main element of the controller is a Machine Learning (ML) engine based on the random undersampling boosting algorithm and fuzzy logic, which can detect when a client is close to a freeze and drive the network prioritization to avoid it. This decision is based on measurements collected from the network nodes only, without any knowledge on the streamed videos or on the clients' characteristics. In this paper, we detail the design of the proposed ML-based framework and compare its performance with other benchmarking HAS solutions, under various video streaming scenarios. Particularly, we show through extensive experimentation that the proposed approach can reduce video freezes and freeze time with about 65% and 45% respectively, when compared to benchmarking algorithms. These results represent a major improvement for the QoE of the users watching multimedia content online

Study on the Mechanical Cumulative Damage Model of Slope Fault Fracture Zone under the Cumulative Effect of Blasting Vibration

As for the slope with fault fracture zone, the fault fracture zone is the main sliding surface, whose shear strength parameter is the main calculation parameter of landslide occurrence. In this paper, shaking table model tests and damage theory were used to study the change of shear strength and mechanical cumulative damage model of fault fracture zone under the blasting vibration cyclic load. At first, the slope of Daye Iron Mine is selected as a case to study the shear strength weakening law of fault fracture zone by the similarity theory and the principle of the orthogonal test, in which the influence of the characteristics of vibration loading on the shear strength parameters of fault fracture zone with different thicknesses was studied. Secondly, by the assumption of Lemaitre strain equivalence and according to the extreme value characteristics of the normal stress-shear stress curve, the damage theory model of the fault fracture zone was reconstructed, and the microelement of fault was selected for analysis and divided into two parts, including damaged and undamaged materials. Finally, the results of the shaking table model tests were compared with the results of the shear cumulative damage model to verify the rationality of the theoretical model. Moreover, the predicted results of the theoretical model can better reflect the degradation trend of the fault fracture zone with the loading amplitude, normal stress, and loading times. It can be used as a reference for slope stability prediction under the action of cumulative static and dynamic loads

A novel solid-state electrochemiluminescence sensor for the determination of hydrogen peroxide based on an Au nanocluster–silica nanoparticle nanocomposite

the National Nature Scientic Foundation of China (no. 21175112), the National Basic Research Program of China (2010CB732402) and NFFTBS (J1210014

A novel solid-state electrochemiluminescence sensor for the determination of hydrogen peroxide based on an Au nanocluster-silica nanoparticle nanocomposite

National Nature Scientific Foundation of China [21175112]; National Basic Research Program of China [2010CB732402]; NFFTBS [J1210014]A gold nanocluster@bovine serum albumin-silica nanoparticle composite has been synthesized and used for the solid-state electrochemiluminescence (ECL) sensing of hydrogen peroxide. The ECL characteristics have also been studied

Feature Selection in Speech and Speaker Recognition (Kenmerken selectie in spraak en spreker herkenning)

Wu T., ''Feature selection in speech and speaker recognition'', Proefschrift voorgedragen tot het behalen van het doctoraat in de ingenieurswetenschappen, K.U.Leuven, June 2009, Leuven, Belgium.status: publishe

A Message Passing-Assisted Iterative Noise Cancellation Method for Clipped OTFS-BFDM Systems

Compared with orthogonal frequency division multiplexing (OFDM) systems, orthogonal time frequency space systems based on bi-orthogonal frequency division multiplexing (OTFS-BFDM) have lower out-of-band emission (OOBE) and better robustness to high-mobility scenarios, but suffer from a higher peak-to-average ratio (PAPR) in large data packets. In this paper, one-iteration clipping and filtering (OCF) is adopted to reduce the PAPR of OTFS-BFDM signals. However, the extra noise introduced by the clipping process, i.e., clipping noise, will distort the desired signal and increase the bit error rate (BER). We propose a message passing (MP)-assisted iterative cancellation (MP-AIC) method to cancel the clipping noise based on the traditional MP decoding at the receiver, which incorporates with the (OCF) at the transmitter to keep the sparsity of the effective channel matrix. The main idea of MP-AIC is to extract the residual signal fed to the MP detector by iteratively constructing reference clipping noise at the receiver. During each iteration, the variance of residual signal and channel noise are taken as input parameters of MP decoding to improve the BER. Moreover, the convergence probability of the modulation alphabet after MP decoding in the current iteration is used as the initial probability of MP decoding in the next iteration to accelerate the convergence rate of MP decoding. Simulation results show that the proposed MP-AIC method significantly improves MP-decoding accuracy while accelerating the BER convergence in the clipped OTFS-BFDM system. In the clipped OTFS-BFDM system with rectangular pulse shaping, the BER of MP-AIC with two iterations can be reduced by 72% more than that without clipping noise cancellation