Design and Implementation of an Open Network Security Management Platform

In order to manage all kinds of network security devices and software systems efficiently, and make them collaborate with each other, the model for an open network security management platform is presented. The feasibility and key implementing technology of the model are expatiated. A prototype system is implemented to validate it.

ZTE Rolls Out New Unified Open Environment Platform

ZTE Corporation (ZTE),a leading global provider of telecommunications equipment and network solutions,on February 12,2009,released a unique Unified Open Environment (UOE) platform that will make it easier fortelecom operators

Shaped Offset Quadrature Phase Shift Keying Based Waveform for Fifth Generation Communication

Fifth generation(5G)wireless networks must meet the needs of emerging technologies like the Internet of Things(IoT),Vehicle-to-everything(V2X),Video on Demand(VoD)services,Device to Device communication(D2D)and many other bandwidth-hungry multimedia applications that connect a huge number of devices.5G wireless networks demand better bandwidth efficiency,high data rates,low latency,and reduced spectral leakage.To meet these requirements,a suitable 5G waveform must be designed.In this work,a waveform namely Shaped Offset Quadrature Phase Shift Keying based Orthogonal Frequency Division Multiplexing(SOQPSK-OFDM)is proposed for 5G to provide bandwidth efficiency,reduced spectral leakage,and Bit Error Rate(BER).The proposed work is evaluated using a real-time Software Defined Radio(SDR)testbed-Wireless open Access Research Platform(WARP).Experimental and simulation results show that the proposed 5G waveform exhibits better BER performance and reduced Out of Band(OOB)radia-tion when compared with other waveforms like Offset Quadrature Phase Shift Key-ing(OQPSK)and Quadrature Phase Shift Keying(QPSK)based OFDM and a 5G waveform candidate Generalized Frequency Division Multiplexing(GFDM).BER analysis shows that the proposed SOQPSK-OFDM waveform attains a Signal to Noise Ratio(SNR)gain of 7.2 dB at a BER of 10�3,when compared with GFDM in a real-time indoor environment.An SNR gain of 8 and 6 dB is achieved by the proposed work for a BER of 10�4 when compared with QPSK-OFDM and OQPSK-OFDM signals,respectively.A significant reduction in OOB of nearly 15 dB is achieved by the proposed work SOQPSK-OFDM when compared to 16 Quadrature Amplitude Modulation(QAM)mapped OFDM.

Investigation of the effects of platform motion on the aerodynamics of a floating offshore wind turbine

Along with the flourishing of the wind energy industry, floating offshore wind turbines have aroused much interest among the academia as well as enterprises. In this paper, the effects of the supporting platform motion on the aerodynamics of a floating wind turbine are studied using the open source CFD framework Open FOAM. The platform motion responses, including surge, heave and pitch, are superimposed onto the rotation of the wind turbine. Thrust and torque on the wind turbine are compared and analysed for the cases of different platform motion patterns together with the flow field. It is shown that the movement of the supporting platform can have large influences on a floating offshore wind turbine and thus needs to be considered carefully during the design process.

RESEARCH ON STABILITY OF OPEN BOTTOM STORAGE PLATFORM

In this paper, we present a new type of offshore structure, open bottomstorage platform, and its theoretical and experimental studies of its stability. In order tooptimize the design of column length and storage tank of the open bottom storage platform, we discuss the effect of air chamber length and storage on the stability of open bottom storage platform.

A Study on Idea Adoption Prediction Model Based on SMOTE-AdaBoost:Taking Salesforce Platform as an Example

In the context of information overload,companies often struggle to effectively identify valuable ideas on their open innovation platforms.In this article,we propose an idea adoption strategy based on machine learning.We used data from a well-known open innovation platform,Salesforce,and extracted characteristic variables using the Information Adoption Model.Four classification models were then constructed based on AdaBoost,Random Forest,SVM and Logistic Regression models.Due to significant differences in the number of positive and negative samples in the OIP,we used the SMOTE method to address the problem of data imbalance.The results of the study showed that the ensemble learning models were more accurate in identifying valuable ideas than the individual machine learning models.When comparing the two ensemble learning models,AdaBoost outperformed Random Forest in predicting both positive and negative class samples.The SMOTE-AdaBoost model achieved a recall of 0.93,a precision of 0.92 and an impressive AUC of 0.98 in identifying adopted ideas,which could well identify valuable ideas and has implications for improving the efficiency and quality of idea adoption in OIP.The shortcoming of this work is that it only investigated a single platform.In the future,we will consider extending this method to different platforms and multiple classification problems.

Inaugural Editorial - Digital Twin [version 1;peer review: not peer reviewed]

Professor Fei Tao from Beihang University initiated Digital Twin (ISSN 2752-5783), the first open research publishing platform dedicated to digital twin technologies and applications. It is published by F1000, part of the Taylor & Francis Group and sponsored by Beihang University. Digital Twin has been set up to accommodate the outputs of scientific research and engineering applications that are related to digital twin.