The diagnosis of a rolling bearing for monitoring its status is critical in maintaining industrial equipment while using bearings. traditional method diagnosing faults the has low identification accuracy, which needs artificial feature extraction order to enhance accuracy. one-dimensional convolution neural network (1D-CNN) can not only diagnose accurately, but also overcome shortcomings methods. Different from machine learning and other deep models, 1D-CNN does need pre-processing data...

Electronically controlled pneumatic (ECP) brake is widely used in heavy-haul train. Although the latest data-driven fault diagnosis can exploit collection data from braking system, it still has challenges for effective model because of industrial noise and insufficient samples. This article proposes a based on multidimensional feature fusion ensemble learning system train (MFF-GBFD). First, features are extracted. By principal component analysis fusion, redundant eliminated. Then, trained...

Data sparsity poses a significant challenge for recommendation systems, prompting the research of cross-domain ( CDR ). aims to leverage more user-item interaction information from source domains improve performance in target domain. However, major is identification transferable features. Traditional methods struggle distinguish between various features users, including domain-invariant that are effective feature transfer and domain-specific detrimental transfer. In this paper, we aim...

In cloud computing, the system should avoid wasting resources as a result of under-utilization and lengthy response times over-utilization. Recent research has focused on globally optimal solution in virtualized data centers. However, makes lot unnecessary migrations cannot work large-scale computing environment. this paper, we propose new model for distributed load balancing allocation virtual machine center using TOPSIS method. Results show that our can achieve better environment with less...

Vulnerable code reuse in open source software is a serious threat to security. However, the existing high-efficiency methods for vulnerable clone detection have large number of false-negatives when modified, which results limited application scenarios. In this paper, we present an innovative fingerprint model describe vulnerability and propose VFDETECT, efficient system detect clones based on fingerprints. Firstly, constructed by applying hash function appropriate blocks diff are...

In rail trains, the prognostics and health management system will make use of data from sensors deployed in key components. These are typically non-stationary multi-variable time series with abrupt variations. The challenges multivariate forecasting include how to identify interactions between various variables, assess influence historical on present data. This paper presents nature air brake its physical models. By analyzing observed obtained freight train system, a Memory network-based...

Recently, XOR based network coding has been applied to the loss recovery of reliable broadcast transmission in wireless networks, where source can multiple lost packets with distinct receivers together into one packet and transmits this combined retransmission, resulting a significant improvement on efficiency. The problem finding optimal set that minimizes overall number transmissions for proved be NP-hard. In paper, we propose an efficient heuristic algorithm vertex coloring giving...

The condition of train brake system directly affects the performance and safety train. In view low accuracy inefficiency fault diagnosis, a new diagnosis method for based on multi-dimension feature fusion GBDT enhanced classification is proposed. Firstly, initial features data are extracted from four dimensions, including time domain, frequency wavelet packet decomposition correlation. Secondly, features, which have great contributions to model, screened out by ReliefF algorithm,...

Information-Centric Networking(ICN) is a paradigm shift from traditional TCP/IP's host-centric approaches, which relies on self-certifiable content, built-in pervasive in-network caching and flexible request routing to provide native support for efficient scalable content distribution the architectural layer. Caching in ICN diverts Web due its arbitrary network topology requirement line-rate operation, makes cache coordination crucial task. However, most of schemes proposed date use uniform...

Information-Centric Networking(ICN) is a paradigm shift from traditional TCP/IP's host-centric approaches, which relies on self-certifiable content, built-in pervasive in-network caching and flexible request routing to provide native support for efficient scalable content distribution the architectural layer. Caching in ICN diverts Web due its arbitrary network topology requirement line-rate operation, makes cache coordination crucial task. However, most of schemes proposed date use uniform...

As convolutional neural network (CNN) has been used more and widely, such as in areas of images classifications face recognition, the traditional CPU or GPU platforms have insufficient to support efficient operation increasingly complex CNN. Therefore, heterogeneous computing platform is accelerate CNN, which contains a host one devices, FPGA, etc.

In the problem of VMs consolidation for cloud energy saving, workload characteristics should be considered to make a more reasonable solution VM placement. Different works in varied CPU utilization during its work time according task characteristics. However, there are many that evaluate consumption have basic assumption on 100% full load. this paper, we theoretically verified will frequency best suited certain can minimum consumption. According deduction, We put forward scaling algorithm...

High energy consumption becomes an urgent problem in cloud datacenters. Based on virtualization tech- nologies, the pay-as-you-go resource provision paradigm has become a trend. Specifically, Virtual Machine (VM) is basic unit data center for migration and provisioning. Many researches have been devoted to improve datacenter utilization reduce power by VM placement. As most important resource, CPU fluctuant frequency range. scaling, new approach VMs placement proposed. The realized two...

A joint jobs scheduling and routing algorithm is proposed for geographically-distributed micro datacenters over EON. Simulation results show that the can reduce jobs' average completion time bandwidth consumption.

In the problem of VMs consolidation for cloud energy saving, different workloads will ask resources. Thus, considering workload characteristic, VM placement solution be more reasonable. real world, works in a varied CPU utilization during its work time according to task characteristics. That means consumption related both and frequency. Therefore, only using model frequency evaluate is insufficient. This paper theoretically verified that there best suit certain order obtain minimum...

Purpose: Improve work efficiency of logistics park department, and drive the economy its surrounding areas. Design/methodology/approach: Analyze information development situation existent questions current national park, design proper scheme to meet demand port park. Findings: Proposed an construction implementation plan using technology Internet things which can be applied Designed a for explained system's strategy steps. Practical implications: The proposed program is particularly suitable...