Aiming at the problem that the most existing fault diagnosis methods could not effectively recognize the early faults in the rotating machinery, the empirical mode decomposition, fuzzy information entropy, improved particle swarm optimization algorithm and least squares support vector machines are introduced into the fault diagnosis to propose a novel intelligent diagnosis method, which is applied to diagnose the faults of the motor bearing in this paper. In the proposed method, the vibration signal is decomposed into a set of intrinsic mode functions (IMFs) by using empirical mode decomposition method. The fuzzy information entropy values of IMFs are calculated to reveal the intrinsic characteristics of the vibration signal and considered as feature vectors. Then the diversity mutation strategy, neighborhood mutation strategy, learning factor strategy and inertia weight strategy for basic particle swarm optimization (PSO) algorithm are used to propose an improved PSO algorithm. The improved PSO algorithm is used to optimize the parameters of least squares support vector machines (LS-SVM) in order to construct an optimal LS-SVM classifier, which is used to classify the fault. Finally, the proposed fault diagnosis method is fully evaluated by experiments and comparative studies for motor bearing. The experiment results indicate that the fuzzy information entropy can accurately and more completely extract the characteristics of the vibration signal. The improved PSO algorithm can effectively improve the classification accuracy of LS-SVM, and the proposed fault diagnosis method outperforms the other mentioned methods in this paper and published in the literature. It provides a new method for fault diagnosis of rotating machinery.

A novel intelligent diagnosis method using optimal LS-SVM with improved PSO algorithm

Energy crisis and carbon emission have become two seriously concerned issues universally. As a feasible solution, Energy Internet (EI) has aroused global concern once proposed. EI is a new power generation developing a vision of evolution of smart grids into the Internet. The communication infrastructure is an essential component to the implementation of EI. A scalable and permanent communication infrastructure is crucial in both construction and operation of EI. In this paper, we present an introduction and the motivation to the evolution from smart grid to EI. We also introduce a representative EI architecture, i.e., the future renewable electric energy delivery and management system. Four critical EI features are emphasized. Then, we summarize the essential requirements that EI systems have to meet. With several key supporting technologies, EI shall realize the optimal utilization of highly scalable and distributed green energy resources, so that the situation of severe energy source crisis and carbon emission can be efficiently relieved. Since an EI system might have extensively distributed consumers and devices, the guarantee of its reliability and security is extremely significant. The further specific exploration for challenges, including reliability and security, will be stated in this paper.

A Survey on Energy Internet: Architecture, Approach, and Emerging Technologies

With the rapid development of cloud computing, cloud storage has been accepted by an increasing number of organizations and individuals, therein serving as a convenient and on-demand outsourcing application However, upon losing local control of data, it becomes an urgent need for users to verify whether cloud service providers have stored their data securely Hence, many researchers have devoted themselves to the design of auditing protocols directed at outsourced data In this paper, we propose an efficient public auditing protocol with global and sampling blockless verification as well as batch auditing, where data dynamics are substantially more efficiently supported than is the case with the state of the art Note that, the novel dynamic structure in our protocol consists of a doubly linked info table and a location array  Moreover, with such a structure, computational and communication overheads can be reduced substantially Security analysis indicates that our protocol can achieve the desired properties Moreover, numerical analysis and real-world experimental results demonstrate that the proposed protocol achieves a given efficiency in practice

An Efficient Public Auditing Protocol With Novel Dynamic Structure for Cloud Data

The new development trends including Internet of Things (IoT), smart city, enterprises digital transformation and world's digital economy are at the top of the tide. The continuous growth of data storage pressure drives the rapid development of the entire storage market on account of massive data generated. By providing data storage and management, cloud storage system becomes an indispensable part of the new era. Currently, the governments, enterprises and individual users are actively migrating their data to the cloud. Such a huge amount of data can create magnanimous wealth. However, this increases the possible risk, for instance, unauthorized access, data leakage, sensitive information disclosure and privacy disclosure. Although there are some studies on data security and privacy protection, there is still a lack of systematic surveys on the subject in cloud storage system. In this paper, we make a comprehensive review of the literatures on data security and privacy issues, data encryption technology, and applicable countermeasures in cloud storage system. Specifically, we first make an overview of cloud storage, including definition, classification, architecture and applications. Secondly, we give a detailed analysis on challenges and requirements of data security and privacy protection in cloud storage system. Thirdly, data encryption technologies and protection methods are summarized. Finally, we discuss several open research topics of data security for cloud storage.

/pdf/data-security-and-privacy-protection-for-cloud-storage-a-51q9ennl7z.pdf

Data Security and Privacy Protection for Cloud Storage: A Survey

Display Omitted An improved adaptive PSO based on Alpha-stable distribution and dynamic fractional calculus is studied.A new multi-objective optimization model of gate assignment problem is proposed.The actual data are used to demonstrate the effectiveness of the proposed method. Gate is a key resource in the airport, which can realize rapid and safe docking, ensure the effective connection between flights and improve the capacity and service efficiency of airport. The minimum walking distances of passengers, the minimum idle time variance of each gate, the minimum number of flights at parking apron and the most reasonable utilization of large gates are selected as the optimization objectives, then an efficient multi-objective optimization model of gate assignment problem is proposed in this paper. Then an improved adaptive particle swarm optimization(DOADAPO) algorithm based on making full use of the advantages of Alpha-stable distribution and dynamic fractional calculus is deeply studied. The dynamic fractional calculus with memory characteristic is used to reflect the trajectory information of particle updating in order to improve the convergence speed. The Alpha-stable distribution theory is used to replace the uniform distribution in order to escape from the local minima in a certain probability and improve the global search ability. Next, the DOADAPO algorithm is used to solve the constructed multi-objective optimization model of gate assignment in order to fast and effectively assign the gates to different flights in different time. Finally, the actual flight data in one domestic airport is used to verify the effectiveness of the proposed method. The experiment results show that the DOADAPO algorithm can improve the convergence speed and enhance the local search ability and global search ability, and the multi-objective optimization model of gate assignment can improve the comprehensive service of gate assignment. It can effectively provide a valuable reference for assigning the gates in hub airport.

Study on an improved adaptive PSO algorithm for solving multi-objective gate assignment

Keyword-based search over encrypted outsourced data has become an important tool in the current cloud computing scenario. The majority of the existing techniques are focusing on multi-keyword exact match or single keyword fuzzy search. However, those existing techniques find less practical significance in real-world applications compared with the multi-keyword fuzzy search technique over encrypted data. The first attempt to construct such a multi-keyword fuzzy search scheme was reported by Wang et al. , who used locality-sensitive hashing functions and Bloom filtering to meet the goal of multi-keyword fuzzy search. Nevertheless, Wang’s scheme was only effective for a one letter mistake in keyword but was not effective for other common spelling mistakes. Moreover, Wang’s scheme was vulnerable to server out-of-order problems during the ranking process and did not consider the keyword weight. In this paper, based on Wang et al. ’s scheme, we propose an efficient multi-keyword fuzzy ranked search scheme based on Wang et al. ’s scheme that is able to address the aforementioned problems. First, we develop a new method of keyword transformation based on the uni-gram, which will simultaneously improve the accuracy and creates the ability to handle other spelling mistakes. In addition, keywords with the same root can be queried using the stemming algorithm. Furthermore, we consider the keyword weight when selecting an adequate matching file set. Experiments using real-world data show that our scheme is practically efficient and achieve high accuracy.

Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement

In practice, search keywords have quite different importance when users take search operations. In addition, such keywords may have a certain grammatical relationship among them, which reflect the importance of keywords from the user’s perspective intuitively. However, the existing search techniques regard the search keywords as independent and unrelated. In this paper, for the first time, we take the relation among query keywords into consideration and design a keyword weighting algorithm to show the importance of the distinction among them. By introducing the keyword weight to the search protocol design, the search results will be more in line with the user’s demand. On top of this, we further design a novel central keyword semantic extension ranked scheme. By extending the central query keyword instead of all keywords, our scheme makes a good tradeoff between the search functionality and efficiency. To better express the relevance between queries and files, we further introduce the TF-IDF rule when building trapdoors and the index. In particular, our scheme supports both data set and keywords updates by using the sub-matrix technique. Our work first gives a basic idea for the design of the central keyword semantic extension ranked scheme, and then presents two secure searchable encryption schemes to meet different privacy requirements under two different threat models. Experiments on the real-world data set show that our proposed schemes are efficient, effective, and secure.

Enabling Central Keyword-Based Semantic Extension Search Over Encrypted Outsourced Data

Text-based search over encrypted cloud data is a hot topic today. Many researchers have made many efforts in this field and designed a series of efficient search schemes over encrypted cloud data. We think it's time to investigate and overview these papers. So in this paper, we survey these searchable encryption schemes and analyze individual contributions respectively. We hope our work can support researchers and practitioner sadness the security problems they may meet in the future.

Text-Based Searchable Encryption in Cloud: A Survey

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Xinle Wu

Author Tools

Chat about Author

Papers

Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement

Enabling Central Keyword-Based Semantic Extension Search Over Encrypted Outsourced Data

Text-Based Searchable Encryption in Cloud: A Survey