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With the increasing scale and complexity of the network, how to maintain a level of network performance and robustness for network operators to satisfy customers becomes more and more challenging. Network anomaly detection and localization are critical for ensuring network performance. In this paper, a novel framework for detecting and localizing network anomalies using active measurements is presented...
We conduct a detailed analysis of cellular communication patterns using (voice/text based) call detail records (CDR) dataset from a nationwide cellular network. We analyze a 5-month large dataset containing over hundreds of millions of CDRs with a user population of over 5 million to dissect meaningful communication patterns, with the goal to understand their impact on - and better manage - cellular...
Android is currently the most popular Operating System (OS) which is widespreadly installed on mobile phones, smart TVs and other wearable devices. Due to its overwhelming market share, Android attracts the attentions from many attackers. Reverse Engineering technology plays an important role in the field of Android security, such as cracking applications, malware analysis, software protection, etc...
Parkinson's disease (PD) and essential tremor (ET) are two kinds of tremor disorders which always confusing doctors in clinical diagnosis. Early experiments on structural MRI have already shown that Parkinson's disease can cause pathological changes in the brain region named Caudate_R (a part of Basal ganglia) while essential tremor cannot. Although there are many research work on the classification...
In order to recover high resolution image from their corresponding low-resolution counterparts for MR Images, this paper has proposed a super resolution reconstruction method to recover the low-resolution MR images based on convolution neural network. Based on the proposed network, the convolution operation and non-linear mapping are employed to adapt MR images naturally and leaning the end-to-end...
For Massive MIMO system with hundreds of antennas at the base station and serve a lot of users, regularized zero forcing (RZF) precoding can achieve the high performance, but suffer from high complexity due to the required matrix inversion of large size. To solve this question, we propose a precoding based on weighted symmetric successive over relaxation (WSSOR) method to approximate the matrix inversion...
This paper develops a large-scale classification algorithm for cargo X-ray images using ensemble of exemplar-SVMs. Large-scale or fine-grained classification is very helpful for customs to improve the inspection efficiency and liberate their inspectors. However, big intra-class variation accompanied with small inter-class variation of cargo images makes it almost impossible to classify them using...
In this paper, we propose a new template selection based superpixel earth mover's distance (TS-SP-EMD) algorithm for hand gesture recognition. In the original SP-EMD, template matching is utilized as the classification method. Therefore, the quality and quantity of templates are closely related to the recognition accuracy and computational speed. To address this issue, we propose a Ä-medoids based...
In this paper, the problem of economic transformation of supply chain enterprises based on collaborative innovation is studied, and the corresponding index evaluation model is put forward to determine the strategy and scheme to solve the problem. The results show that in order to solve the problems of knowledge, technology security, belonging, benefit distribution, need to put forward the suitable...
Considering the traffic safety in the scenario of arterial road with on-ramp, this study proposes a time-to-collision (TTC) based vehicular collision warning algorithm under connected environment. In particular, the information of vehicles of interest, i.e., position, traveling direction and velocity, is assumed to be collected by the roadside device via the vehicle-to-infrastructure (V2I) communications...
We tackle the challenging problem of hand gesture tracking with 2D webcams, which is a promising enabler for human computer interaction. Recent studies have proposed many methods for object tracking. However, unlike the other ob-jects, the particularities of hand make it difficult to be represented by common-used feature descriptors. In this paper, we analyze the key points in hand tracking and take...
Generation schedule must not only meet the forecasting load, but also be capable of coping with uncertainty. Traditionally, the ability to provide adequacy generation under uncertainty is just required in each period, namely certain reliability criteria must be satisfied. However, because the inner period variability and uncertainty brought by renewable generation such as wind power increase greatly,...
To deal with the uncertainty rising with high wind penetration, it is technically and economically important to consider reserve provision by wind generation (WG). Storage could mitigate the WG volatility, so reserve provision by combination of WG and storage could be more competitive in reserve market. This paper presents a new unit commitment (UC) model, in which both WG reserve opportunity cost...
The two-layer dual-Circular Polarization (CP) reflectarray antenna has been designed in this paper. The upper element structure is based on CP selective surfaces (CPSS) for LCP and the second layer adopts reactively loaded ring slots for RCP. Finally, a 20-cm two-layer reflectarray antenna has been designed and simulated for verification. A good agreement with the corresponding single layer demonstrates...
This paper presents a simulation study on the implementation of the Single Star Flying Capacitor Converter Modular Multi-level Cascaded Converter (MMCC-SSFCC) as a STATCOM operating under voltage sag condition. This paper proposes a cluster balancing control, using a zero sequence voltage injection technique for the SSFCC-STATCOM operating either as a reactive compensator under Low Voltage Ride Through...
Inefficient utilization of electricity business expanding data in State Grid Companies related departments still exist. It is because of their excessive attention on the speed of electricity supply and the quality of service, but ignores the potential useful information of the data implied in the future electricity sale market. With this regard, this paper proposes a novel analysis and forecast method...
Spatial load forecasting is a significant basis for power system planning and construction. With the development of renewable energy generation and the continuing deterioration of the environment, energy alternatives is becoming a new growth point of load. The methods present cannot take energy alternative into consideration appropriately. To solve it, this paper analyzes the temporal and spatial...
The goal of this paper is to acquire the energy response functions precisely with enough accuracy for spectral restoration and reconstruction. In this work we estimate the response functions of the XCounter Flite X1 detector by measuring the spectrum of the X-ray fluorescence. The incident spectrum and the deposited spectrum are simulated by the Monte Carlo method using Geant4. The broadening of deposition...
To reduce patient's dose, few-view CT reconstruction promises to be a good attempt. The key to better reconstruction is the sparse view artifacts. In recent years, DL(deep learing) has attracted a lot of attention because its outstanding performance in image processing. We propose a deep learning method for few-view CT reconstuction. Our method directly learns an end-to-end mapping between the full-view/few-view...
With the two fold aim of analyzing the energy dispersive X-ray diffraction (EDXRD) system for illicit materials detection and of selecting optimal configurations prior to experimental tests, a simulation method for modelling the response of EDXRD system has been proposed. The simulation is done based on two orthogonal planes of the system: the diffraction plane (H-Plane) and its vertical plane (V-Plane)...
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