scholarly journals Analyzing Network Protocols of Application Layer Using Hidden Semi-Markov Model

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Jun Cai ◽  
Jian-Zhen Luo ◽  
Fangyuan Lei
Keyword(s):  
Markov Model ◽  
Reverse Engineering ◽  
Rapid Development ◽  
Mobile Internet ◽  
High Rate ◽  
Propagation Mechanism ◽  
Internet Protocols ◽  
Novel Approach ◽  
Protocol Reverse Engineering ◽  
New Applications

With the rapid development of Internet, especially the mobile Internet, the new applications or network attacks emerge in a high rate in recent years. More and more traffic becomes unknown due to the lack of protocol specifications about the newly emerging applications. Automatic protocol reverse engineering is a promising solution for understanding this unknown traffic and recovering its protocol specification. One challenge of protocol reverse engineering is to determine the length of protocol keywords and message fields. Existing algorithms are designed to select the longest substrings as protocol keywords, which is an empirical way to decide the length of protocol keywords. In this paper, we propose a novel approach to determine the optimal length of protocol keywords and recover message formats of Internet protocols by maximizing the likelihood probability of message segmentation and keyword selection. A hidden semi-Markov model is presented to model the protocol message format. An affinity propagation mechanism based clustering technique is introduced to determine the message type. The proposed method is applied to identify network traffic and compare the results with existing algorithm.

scholarly journals Mapping the Sharing Economy in China

2020 ◽  
Vol 12 (16) ◽  
pp. 6333
Author(s):  
Chan Liu ◽  
Raymond K. H. Chan ◽  
Maofu Wang ◽  
Zhe Yang
Keyword(s):  
Global Economy ◽  
Rapid Development ◽  
Sharing Economy ◽  
Essential Elements ◽  
Mobile Internet ◽  
Internet Technology ◽  
Short Term ◽  
Bona Fide ◽  
The Government ◽  
Idle Capacity

Harnessing the rapid development of mobile internet technology, the sharing economy has experienced unprecedented growth in the global economy, especially in China. Likely due to its increasing popularity, more and more businesses have adopted this label in China. There is a concern as to the essential meaning of the sharing economy. As it is difficult to have a universally accepted definition, we aim to map the sharing economy and demystify the use of it in China in this paper. We propose seven organizing essential elements of the sharing economy: access use rights instead of ownership, idle capacity, short term, peer-to-peer, Internet platforms mediated, for monetary profit, and shared value orientation. By satisfying all or only parts of these elements, we propose one typology of sharing economy, and to differentiate bona fide sharing economy from quasi- and pseudo-sharing economy. Finally, there are still many problems that need to be solved urgently in the real sharing economy from the perspective of the government, companies and individuals.

scholarly journals High-Rate Transition Metal-based Cathode Materials for Battery-Supercapacitor Hybrid Devices

2021 ◽  
Author(s):  
Cong Wang ◽  
Zehao Song ◽  
Pei Shi ◽  
Lin Lv ◽  
Houzhao Wan ◽  
...  
Keyword(s):  
Large Scale ◽  
Rapid Development ◽  
Electronic Devices ◽  
High Rate ◽  
Specific Power ◽  
Energy Storage Devices ◽  
Storage Devices ◽  
Electrochemical Devices ◽  
Hybrid Devices ◽  
Scale Grid

With the rapid development of portable electronic devices, electric vehicles and large-scale grid energy storage devices, it needs to reinforce specific energy and specific power of related electrochemical devices meeting...

scholarly journals Accurate Instance-Based Segmentation for Boundary Detection in Robot Grasping Application

2021 ◽  
Vol 11 (9) ◽  
pp. 4248
Author(s):  
Hong Hai Hoang ◽  
Bao Long Tran
Keyword(s):  
Object Segmentation ◽  
State Of The Art ◽  
Rapid Development ◽  
Spatial Relationship ◽  
Learning Technologies ◽  
Average Precision ◽  
Novel Approach ◽  
3D Camera ◽  
Robot Grasping ◽  
Instance Segmentation

With the rapid development of cameras and deep learning technologies, computer vision tasks such as object detection, object segmentation and object tracking are being widely applied in many fields of life. For robot grasping tasks, object segmentation aims to classify and localize objects, which helps robots to be able to pick objects accurately. The state-of-the-art instance segmentation network framework, Mask Region-Convolution Neural Network (Mask R-CNN), does not always perform an excellent accurate segmentation at the edge or border of objects. The approach using 3D camera, however, is able to extract the entire (foreground) objects easily but can be difficult or require a large amount of computation effort to classify it. We propose a novel approach, in which we combine Mask R-CNN with 3D algorithms by adding a 3D process branch for instance segmentation. Both outcomes of two branches are contemporaneously used to classify the pixels at the edge objects by dealing with the spatial relationship between edge region and mask region. We analyze the effectiveness of the method by testing with harsh cases of object positions, for example, objects are closed, overlapped or obscured by each other to focus on edge and border segmentation. Our proposed method is about 4 to 7% higher and more stable in IoU (intersection of union). This leads to a reach of 46% of mAP (mean Average Precision), which is a higher accuracy than its counterpart. The feasibility experiment shows that our method could be a remarkable promoting for the research of the grasping robot.

scholarly journals Enhancing Wind Turbine Power Forecast via Convolutional Neural Network

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 261
Author(s):  
Tianyang Liu ◽  
Zunkai Huang ◽  
Li Tian ◽  
Yongxin Zhu ◽  
Hui Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Rapid Development ◽  
Superior Performance ◽  
Learning Platform ◽  
Novel Approach ◽  
Wind Power Forecast ◽  
Transformation Methods

The rapid development in wind power comes with new technical challenges. Reliable and accurate wind power forecast is of considerable significance to the electricity system’s daily dispatching and production. Traditional forecast methods usually utilize wind speed and turbine parameters as the model inputs. However, they are not sufficient to account for complex weather variability and the various wind turbine features in the real world. Inspired by the excellent performance of convolutional neural networks (CNN) in computer vision, we propose a novel approach to predicting short-term wind power by converting time series into images and exploit a CNN to analyze them. In our approach, we first propose two transformation methods to map wind speed and precipitation data time series into image matrices. After integrating multi-dimensional information and extracting features, we design a novel CNN framework to forecast 24-h wind turbine power. Our method is implemented on the Keras deep learning platform and tested on 10 sets of 3-year wind turbine data from Hangzhou, China. The superior performance of the proposed method is demonstrated through comparisons using state-of-the-art techniques in wind turbine power forecasting.

scholarly journals Design of Short, High-Rate DVB-S2-Like Semi-Regular LDPC Codes

2008 ◽  
Vol 2008 ◽  
pp. 1-4
Author(s):  
Luca Barletta ◽  
Arnaldo Spalvieri
Keyword(s):  
Coded Modulation ◽  
High Rate ◽  
Parity Check ◽  
Code Length ◽  
Carrier Recovery ◽  
Low Density Parity Check ◽  
Novel Approach ◽  
Parity Check Codes ◽  
Moderate Length

This work focuses on high-rate () moderate-length () low-density parity-check codes. High-rate codes allow to maintain good quality of the preliminary decisions that are used in carrier recovery, while a moderate code length allows to keep the latency low. The interleaver of the LDPC matrix that we consider is inspired to the DVB-S2 standard one. A novel approach for avoiding short cycles is analyzed. A modified BP decoding algorithm is applied in order to deal with longer cycles. Simulations and results for the AWGN channel are presented, both for BPSK signalling and for coded modulation based on the partition .

scholarly journals Investigating the Temporal Effect of User Preferences with Application in Movie Recommendation

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Wen-Jun Li ◽  
Qiang Dong ◽  
Yan Fu
Keyword(s):  
Rapid Development ◽  
User Preferences ◽  
Mobile Internet ◽  
Smart Devices ◽  
Data Sets ◽  
Rating Data ◽  
Temporal Effect ◽  
Proposed Model ◽  
Target User ◽  
The Difference

As the rapid development of mobile Internet and smart devices, more and more online content providers begin to collect the preferences of their customers through various apps on mobile devices. These preferences could be largely reflected by the ratings on the online items with explicit scores. Both of positive and negative ratings are helpful for recommender systems to provide relevant items to a target user. Based on the empirical analysis of three real-world movie-rating data sets, we observe that users’ rating criterions change over time, and past positive and negative ratings have different influences on users’ future preferences. Given this, we propose a recommendation model on a session-based temporal graph, considering the difference of long- and short-term preferences, and the different temporal effect of positive and negative ratings. The extensive experiment results validate the significant accuracy improvement of our proposed model compared with the state-of-the-art methods.

scholarly journals Research on Sentiment Tendency and Evolution of Public Opinions in Social Networks of Smart City

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yanni Liu ◽  
Dongsheng Liu ◽  
Yuwei Chen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sentiment Analysis ◽  
Smart City ◽  
Topic Model ◽  
Rapid Development ◽  
Mobile Internet ◽  
Time Curve ◽  
Public Opinions ◽  
The Social

With the rapid development of mobile Internet, the social network has become an important platform for users to receive, release, and disseminate information. In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. In view of social networks’ characteristics such as short text, rich topics, diverse sentiments, and timeliness, this paper conducts text modeling with words co-occurrence based on the topic model. Besides, the sentiment computing and the time factor are incorporated to construct the dynamic topic-sentiment mixture model (TSTS). Then, four hot events were randomly selected from the microblog as datasets to evaluate the TSTS model in terms of topic feature extraction, sentiment analysis, and time change. The results show that the TSTS model is better than the traditional models in topic extraction and sentiment analysis. Meanwhile, by fitting the time curve of hot events, the change rules of comments in the social network is obtained.

scholarly journals eBook Service in Shanghai Library

2016 ◽  
Vol 1 (1) ◽  
pp. 66 ◽  
Author(s):  
Qing Zhou
Keyword(s):  
New Media ◽  
Rapid Development ◽  
Public Library ◽  
Mobile Internet ◽  
Digital Reading ◽  
Reading Habits ◽  
Digital Resources ◽  
Tablet Pcs ◽  
One Stop ◽  
Further Development

In the 21st century, with the rapid development of mobile Internet, people's reading habits have started shifting from the traditional paper-based media, to completely new media such as cell phones, eBook readers, tablet PCs and so on. "Shanghai Library’s Urban Digital Reading Service Platform" integrates all types of collections of digital resources to support eBook readers, tablet PCs, smart phones and other types ofmobiledevices. Thisplatformprovidesaconvenient,low-costandfriendlylearninginterfacetoonline users, providing one of the best reading experiences. This also creates a one-stop public library reading platform, and meets the reader’s need for reading on the go. By investigating and researching libraries’ experiences and requirements for digital reading platforms and its internationalization service, this paper will discuss its further development.

scholarly journals Use of Reverse Engineering and Additive Printing in the Reconstruction of Gears

2020 ◽  
Vol 3 (1) ◽  
pp. 274-284
Author(s):  
Dorota Palka
Keyword(s):  
3D Printing ◽  
Reverse Engineering ◽  
Fused Deposition Modeling ◽  
Rapid Development ◽  
Spare Parts ◽  
Common Element ◽  
Practical Application ◽  
Computer Aided Manufacturing ◽  
Fused Deposition ◽  
Computer Aided

AbstractDespite the very rapid technological development, the general concept of mechanical devices has not changed. Still, the most common element of these devices are gears, whose range of use is very wide. There are both technological and historical considerations for the reconstruction of gears and other elements. In particular, this applies to spare parts for technical facilities that are not available on the market or service costs are too high. Contemporary reconstruction is called Reverse Engineering, which offers tools that allow transformation of an existing object through a virtual model into the final real product. Modern production engineering is based on innovative CAD – Computer Aided Designed design methods and computer-aided manufacturing technologies, CAM – Computer Aided Manufacturing. The rapid development of 3D CAD systems has led to the development of solutions to obtain the designed object, already at the development stage. Such a solution is the Rapid Prototyping method, designed for fast, precise and repeatable production of machine components. Widespread use and growing interest in the use of additive printing influenced the development of this technology. The purpose of the article is to present the practical application of the Reverse Engineering method and 3D printing in the reconstruction of gears. The object of research is the real gear, which has been reconstructed using Reverse Engineering and 3D printing. The article presents the basic assumptions of the methods used and the methodology for conducting reconstruction work. FDM (Fused Deposition Modeling) technology was used for the research. The results obtained are a real example of the practical application of the presented methods. At the same time, they create great opportunities for their wider use.

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