This paper presents a project aimed at developing a trilingual visual dictionary for aircraft maintenance professionals and students.The project addresses the growing demand for accurate communication and technical te...This paper presents a project aimed at developing a trilingual visual dictionary for aircraft maintenance professionals and students.The project addresses the growing demand for accurate communication and technical terminology in the aviation industry,particularly in Brazil and China.The study employs a corpus-driven approach,analyzing a large corpus of aircraft maintenance manuals to extract key technical terms and their collocates.Using specialized subcorpora and a comparative analysis,this paper demonstrates challenges and solutions into the identification of high-frequency keywords and explores their contextual use in aviation documentation,emphasizing the need for clear and accurate technical communication.By incorporating these findings into a trilingual visual dictionary,the project aims to enhance the understanding and usage of aviation terminology.展开更多
Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabli...Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabling updates and retrievals of ciphertext on untrusted cloud server while ensuring data privacy.However,previous research on DSSE mostly focused on single keyword search,which limits its practical application in cloud-based IoT systems.Recently,Patranabis(NDSS 2021)[1]proposed a groundbreaking DSSE scheme for conjunctive keyword search.However,this scheme fails to effectively handle deletion operations in certain circumstances,resulting in inaccurate query results.Additionally,the scheme introduces unnecessary search overhead.To overcome these problems,we present CKSE,an efficient conjunctive keyword DSSE scheme.Our scheme improves the oblivious shared computation protocol used in the scheme of Patranabis,thus enabling a more comprehensive deletion functionality.Furthermore,we introduce a state chain structure to reduce the search overhead.Through security analysis and experimental evaluation,we demonstrate that our CKSE achieves more comprehensive deletion functionality while maintaining comparable search performance and security,compared to the oblivious dynamic cross-tags protocol of Patranabis.The combination of comprehensive functionality,high efficiency,and security makes our CKSE an ideal choice for deployment in cloud-based IoT systems.展开更多
International Journal of Minerals,Metallurgy and Materials is dedicated to the publication and the dissemination of original research articles (and occasional invited reviews) in the fields of Minerals,Metallurgy and ...International Journal of Minerals,Metallurgy and Materials is dedicated to the publication and the dissemination of original research articles (and occasional invited reviews) in the fields of Minerals,Metallurgy and Materials.It is covered by EI Compendex,SCI Expanded,Chemical Abstract,etc.Manuscript preparation The following components are required for a complete manuscript:Title,Author(s),Author affiliation(s),Abstract,Keywords,Main text,Acknowledgements and References.展开更多
As a fundamental and effective tool for document understanding and organization, multi-document summarization enables better information services by creating concise and informative reports for large collections of do...As a fundamental and effective tool for document understanding and organization, multi-document summarization enables better information services by creating concise and informative reports for large collections of documents. In this paper, we propose a sentence-word two layer graph algorithm combining with keyword density to generate the multi-document summarization, known as Graph ＆ Keywordp. The traditional graph methods of multi-document summarization only consider the influence of sentence and word in all documents rather than individual documents. Therefore, we construct multiple word graph and extract right keywords in each document to modify the sentence graph and to improve the significance and richness of the summary. Meanwhile, because of the differences in the words importance in documents, we propose to use keyword density for the summaries to provide rich content while using a small number of words. The experiment results show that the Graph ＆ Keywordp method outperforms the state of the art systems when tested on the Duc2004 data set. Key words： multi-document, graph algorithm, keyword density, Graph ＆ Keywordp, Due2004展开更多
The education and quality of life of children with intellectual disabilities(ID)have received increasing attention in China due to the evolving diagnostic standards and educational policies.This study analyzes researc...The education and quality of life of children with intellectual disabilities(ID)have received increasing attention in China due to the evolving diagnostic standards and educational policies.This study analyzes research trends on support for children with ID in China from 2004 to 2023.Using bibliometric analysis and keyword clustering methods,384 research papers published in the China National Knowledge Infrastructure(CNKI)database were examined.The results are as follows.First,research on support for children with ID in China has gradually increased since 2004,with a significant surge observed after 2016.Second,keyword analysis identified key research themes,including“social support,”“inclusive education,”“special schools,”“group work,”and“case studies.”Third,the research frontier analysis revealed that studies on ID support in China have primarily developed in three key domains:social support systems,family and community support,and school-based support.This paper aims to serve as a foundational reference for future research and policy development.展开更多
Background: Peripheral nerve regeneration is a critical research area with significant implications for neurology,neurosurgery,and regenerative medicine.A bibliometric analysis was conducted to provide a structured ov...Background: Peripheral nerve regeneration is a critical research area with significant implications for neurology,neurosurgery,and regenerative medicine.A bibliometric analysis was conducted to provide a structured overview of research trends,intellectual impact,and evolving themes in peripheral nerve regeneration.This study aimed to identify the most influential research articles on peripheral nerve regeneration;analyze keyword trends,thematic evolution,and co-word structures;assess the contributions of top authors,universities,and countries;and examine collaboration networks and research dynamics.Methods: A systematic bibliometric approach was employed using two search strategies.The first strategy involved searching within the title,abstract,and keyword fields,yielding 15 317 papers,whereas the second strategy was restricted to searching titles only,retrieving 3 531 papers.From these,the 100 most cited papers were selected for analysis.A thematic analysis was conducted using co-word clustering.The leading contributors were ranked according to the number of publications,citations,h-index,g-index,and m-index.Results: The bibliometric analysis provided several key insights.Keyword analysis using bi-and tri-gram techniques revealed the dominant research themes within the field.The top contributors,including authors,universities,and countries,were ranked based on their productivity and citation impact.Collaboration networks were mapped at the author,institutional,and country levels,highlighting key partnerships and global research interactions.Thematic analysis classified research into seven major domains: neural regeneration and repair;cellular and molecular biology;biomaterials and tissue engineering;experimental studies and statistical analyses;functional and therapeutic aspects;neuropathic pain and peripheral nerve disorders;and Schwann cell and cellular responses.Additionally,the ten most influential papers were reviewed in detail to understand their contributions to the field.Conclusion: This study provides a comprehensive and structured overview of peripheral nerve regeneration research.These findings offer valuable insights into the intellectual foundation of the field by identifying key contributors,research trends,and collaboration patterns.The results serve as a guide for future research,helping researchers to navigate the evolving landscape of peripheral nerve regeneration.展开更多
1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography,natural resources,environmental sciences,geographic inform...1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography,natural resources,environmental sciences,geographic information sciences,remote sensing and cartography.Manuscripts come from different parts of the world.2 Format and style Contributions should be typed on A4 paper using Times New Roman typeface in Word format,normally not exceeding 20,000 words.3 Abstract and keywords The text should be preceded by an abstract of 200-300 words,which should be followed by 3-7keywords on a separate line.展开更多
1 Preparation of manuscripts The manuscript should be prepared with a major word processing program and the file also submitted as a PDF(to clearly indicate all fonts).Please provide the author’s affiliation(address ...1 Preparation of manuscripts The manuscript should be prepared with a major word processing program and the file also submitted as a PDF(to clearly indicate all fonts).Please provide the author’s affiliation(address and email),an abstract of 150–300 words presenting the main arguments of the paper,4–8 keywords,high-resolution figures(with permissions),acknowledgments and references.“Documentation II:Author-Date References”in The Chicago Manual of Style and a back issue of the journal can be used as guides to prepare the manuscript.展开更多
The authors employed inappropriate search keywords and strategies in their published bibliometric papers within volume 29 of the World Journal of Gastroenterology.The comment highlights the identified issues,provides ...The authors employed inappropriate search keywords and strategies in their published bibliometric papers within volume 29 of the World Journal of Gastroenterology.The comment highlights the identified issues,provides evidence,and suggests improved study methodologies.Subsequent results with more appro-priate search strategies were presented to address the shortcomings.展开更多
As mobile edge computing continues to develop,the demand for resource-intensive applications is steadily increasing,placing a significant strain on edge nodes.These nodes are normally subject to various constraints,fo...As mobile edge computing continues to develop,the demand for resource-intensive applications is steadily increasing,placing a significant strain on edge nodes.These nodes are normally subject to various constraints,for instance,limited processing capability,a few energy sources,and erratic availability being some of the common ones.Correspondingly,these problems require an effective task allocation algorithmto optimize the resources through continued high system performance and dependability in dynamic environments.This paper proposes an improved Particle Swarm Optimization technique,known as IPSO,for multi-objective optimization in edge computing to overcome these issues.To this end,the IPSO algorithm tries to make a trade-off between two important objectives,which are energy consumption minimization and task execution time reduction.Because of global optimal position mutation and dynamic adjustment to inertia weight,the proposed optimization algorithm can effectively distribute tasks among edge nodes.As a result,it reduces the execution time of tasks and energy consumption.In comparative assessments carried out by IPSO with benchmark methods such as Energy-aware Double-fitness Particle Swarm Optimization(EADPSO)and ICBA,IPSO provides better results than these algorithms.For the maximum task size,when compared with the benchmark methods,IPSO reduces the execution time by 17.1%and energy consumption by 31.58%.These results allow the conclusion that IPSO is an efficient and scalable technique for task allocation at the edge environment.It provides peak efficiency while handling scarce resources and variable workloads.展开更多
Keyword extraction is an important research topic of information retrieval. This paper gave the specification of keywords in Chinese news documents based on analyzing linguistic characteristics of news documents and t...Keyword extraction is an important research topic of information retrieval. This paper gave the specification of keywords in Chinese news documents based on analyzing linguistic characteristics of news documents and then proposed a new keyword extraction method based on tf/idf with multi-strategies. The approach selected candidate keywords of uni-, hi- and tri-grams, and then defines the features according to their morphological characters and context information. Moreover, the paper proposed several strategies to amend the incomplete words gotten from the word segmentation and found unknown potential keywords in news documents. Experimental results show that our proposed method can significantly outperform the baseline method. We also applied it to retrospective event detection. Experimental results show that the accuracy and efficiency of news retrospective event detection can be significantly improved.展开更多
Public Key Encryption with Keyword Search （PEKS）, an indispensable part of searchable encryption, is stock-in- trade for both protecting data and providing operability of encrypted data. So far most of PEKS schemes ...Public Key Encryption with Keyword Search （PEKS）, an indispensable part of searchable encryption, is stock-in- trade for both protecting data and providing operability of encrypted data. So far most of PEKS schemes have been established on Identity-Based Cryptography （IBC） with key escrow problem inherently. Such problem severely restricts the promotion of IBC-based Public Key Infrastructure including PEKS component. Hence, Certificateless Public Key Cryptography （CLPKC） is efficient to remove such problem. CLPKC is introduced into PEKS, and a general model of Certificateless PEKS （CLPEKS） is formalized. In addition, a practical CLPEKS scheme is constructed with security and efficiency analyses. The proposal is secure channel free, and semantically secure against adaptive chosen keyword attack and keyword guessing attack. To illustrate the superiority, massive experiments are conducted on Enron Email dataset which is famous in information retrieval field. Compared with existed constructions, CLPEKS improves the efficiency in theory and removes the key escrow problem.展开更多
Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to enc...Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to encrypted data retrieval in cryptographic cloud storage. Certificateless public key cryptography (CLPKC) is a novel cryptographic primitive that has many merits. It overcomes the key escrow problem in identity-based cryptography (IBC) and the cumbersome certificate problem in conventional public key cryptography (PKC). Motivated by the appealing features of CLPKC, several certificateless encryption with keyword search (CLEKS) schemes have been presented in the literature. But, our cryptanalysis demonstrates that the previously proposed CLEKS frameworks suffer from the security vulnerability caused by the keyword guessing attack. To remedy the security weakness in the previous frameworks and provide resistance against both inside and outside keyword guessing attacks, we propose a new CLEKS framework. Under the new framework, we design a concrete CLEKS scheme and formally prove its security in the random oracle model. Compared with previous two CLEKS schemes, the proposed scheme has better overall performance while offering stronger security guarantee as it withstands the existing known types of keyword guessing attacks.展开更多
The user data stored in an untrusted server, such as the centralized data center or cloud computing server, may be dangerous of eavesdropping if the data format is a plaintext. However, the general ciphertext is diffi...The user data stored in an untrusted server, such as the centralized data center or cloud computing server, may be dangerous of eavesdropping if the data format is a plaintext. However, the general ciphertext is difficult to search and thus limited for practical usage. The keyword search encryption is a helpful mechanism that provides a searchable ciphertext for some predefined keywords. The previous studies failed to consider the attack from the data storage server to guess the keyword. This kind of attack may cause some critical information revealed to the untrusted server. This paper proposes a new keyword search encryption model that can effectively resist the keyword-guessing attack performed by the untrusted data storage(testing) server. The testing(query)secret is divided into multiple shares so that the security can be guaranteed if the servers cannot conspire with each other to retrieve all shares of the secret.展开更多
To save the local storage,users store the data on the cloud server who offers convenient internet services.To guarantee the data privacy,users encrypt the data before uploading them into the cloud server.Since encrypt...To save the local storage,users store the data on the cloud server who offers convenient internet services.To guarantee the data privacy,users encrypt the data before uploading them into the cloud server.Since encryption can reduce the data availability,public-key encryption with keyword search(PEKS)is developed to achieve the retrieval of the encrypted data without decrypting them.However,most PEKS schemes cannot resist quantum computing attack,because the corresponding hardness assumptions are some number theory problems that can be solved efficiently under quantum computers.Besides,the traditional PEKS schemes have an inherent security issue that they cannot resist inside keywords guessing attack(KGA).In this attack,a malicious server can guess the keywords encapsulated in the search token by computing the ciphertext of keywords exhaustively and performing the test between the token and the ciphertext of keywords.In the paper,we propose a lattice-based PEKS scheme that can resist quantum computing attacks.To resist inside KGA,this scheme adopts a lattice-based signature technique into the encryption of keywords to prevent the malicious server from forging a valid ciphertext.Finally,some simulation experiments are conducted to demonstrate the performance of the proposed scheme and some comparison results are further shown with respect to other searchable schemes.展开更多
With recent significant development in the portable device market, cloud computing is getting more and more utilized. Many sensitive data are stored in cloud central servers. To ensure privacy, these data are usually ...With recent significant development in the portable device market, cloud computing is getting more and more utilized. Many sensitive data are stored in cloud central servers. To ensure privacy, these data are usually encrypted before being uploaded—making file searching complicated. Although previous cloud computing searchable encryption schemes allow users to search encrypted data by keywords securely, these techniques only support exact keyword search and will fail if there are some spelling errors or if some morphological variants of words are used. In this paper, we provide the solution for fuzzy keyword search over encrypted cloud data. K-grams is used to produce fuzzy results. For security reasons, we use two separate servers that cannot communicate with each other. Our experiment result shows that our system is effective and scalable to handle large number of encrypted files.展开更多
may incur significant bandwidth for executing more com- plicated search queries such as multiple-attribute queries. In order to reduce query overhead, KSS (keyword-set search) by Gnawali partitions the index by a set ...may incur significant bandwidth for executing more com- plicated search queries such as multiple-attribute queries. In order to reduce query overhead, KSS (keyword-set search) by Gnawali partitions the index by a set of keywords. However, a KSS index is considerably larger than a standard inverted index, since there are more word sets than there are individual words. And the insert overhead and storage overhead are obviously un- acceptable for full-text search on a collection of documents even if KSS uses the distance window technology. In this paper, we extract the relationship information between query keywords from websites’ queries logs to improve performance of KSS system. Experiments results clearly demonstrated that the improved keyword-set search system based on keywords relationship (KRBKSS) is more efficient than KSS index in insert overhead and storage overhead, and a standard inverted index in terms of communication costs for query.展开更多
In this paper, an improved algorithm, web-based keyword weight algorithm （WKWA）, is presented to weight keywords in web documents. WKWA takes into account representation features of web documents and advantages of t...In this paper, an improved algorithm, web-based keyword weight algorithm （WKWA）, is presented to weight keywords in web documents. WKWA takes into account representation features of web documents and advantages of the TF＊IDF, TFC and ITC algorithms in order to make it more appropriate for web documents. Meanwhile, the presented algorithm is applied to improved vector space model （IVSM）. A real system has been implemented for calculating semantic similarities of web documents. Four experiments have been carried out. They are keyword weight calculation, feature item selection, semantic similarity calculation, and WKWA time performance. The results demonstrate accuracy of keyword weight, and semantic similarity is improved.展开更多
Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their...Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.展开更多
In this paper,we study the problem of privacy-preserving top-k keyword similarity search over outsourced cloud data.Taking edit distance as a measure of similarity,we first build up the similarity keyword sets for all...In this paper,we study the problem of privacy-preserving top-k keyword similarity search over outsourced cloud data.Taking edit distance as a measure of similarity,we first build up the similarity keyword sets for all the keywords in the data collection.We then calculate the relevance scores of the elements in the similarity keyword sets by the widely used tf-idf theory.Leveraging both the similarity keyword sets and the relevance scores,we present a new secure and efficient treebased index structure for privacy-preserving top-k keyword similarity search.To prevent potential statistical attacks,we also introduce a two-server model to separate the association between the index structure and the data collection in cloud servers.Thorough analysis is given on the validity of search functionality and formal security proofs are presented for the privacy guarantee of our solution.Experimental results on real-world data sets further demonstrate the availability and efficiency of our solution.展开更多
文摘This paper presents a project aimed at developing a trilingual visual dictionary for aircraft maintenance professionals and students.The project addresses the growing demand for accurate communication and technical terminology in the aviation industry,particularly in Brazil and China.The study employs a corpus-driven approach,analyzing a large corpus of aircraft maintenance manuals to extract key technical terms and their collocates.Using specialized subcorpora and a comparative analysis,this paper demonstrates challenges and solutions into the identification of high-frequency keywords and explores their contextual use in aviation documentation,emphasizing the need for clear and accurate technical communication.By incorporating these findings into a trilingual visual dictionary,the project aims to enhance the understanding and usage of aviation terminology.
基金supported in part by the Major Science and Technology Projects in Yunnan Province(202202AD080013)King Khalid University for funding this work through Large Group Project under grant number RGP.2/373/45.
文摘Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabling updates and retrievals of ciphertext on untrusted cloud server while ensuring data privacy.However,previous research on DSSE mostly focused on single keyword search,which limits its practical application in cloud-based IoT systems.Recently,Patranabis(NDSS 2021)[1]proposed a groundbreaking DSSE scheme for conjunctive keyword search.However,this scheme fails to effectively handle deletion operations in certain circumstances,resulting in inaccurate query results.Additionally,the scheme introduces unnecessary search overhead.To overcome these problems,we present CKSE,an efficient conjunctive keyword DSSE scheme.Our scheme improves the oblivious shared computation protocol used in the scheme of Patranabis,thus enabling a more comprehensive deletion functionality.Furthermore,we introduce a state chain structure to reduce the search overhead.Through security analysis and experimental evaluation,we demonstrate that our CKSE achieves more comprehensive deletion functionality while maintaining comparable search performance and security,compared to the oblivious dynamic cross-tags protocol of Patranabis.The combination of comprehensive functionality,high efficiency,and security makes our CKSE an ideal choice for deployment in cloud-based IoT systems.
文摘International Journal of Minerals,Metallurgy and Materials is dedicated to the publication and the dissemination of original research articles (and occasional invited reviews) in the fields of Minerals,Metallurgy and Materials.It is covered by EI Compendex,SCI Expanded,Chemical Abstract,etc.Manuscript preparation The following components are required for a complete manuscript:Title,Author(s),Author affiliation(s),Abstract,Keywords,Main text,Acknowledgements and References.
文摘As a fundamental and effective tool for document understanding and organization, multi-document summarization enables better information services by creating concise and informative reports for large collections of documents. In this paper, we propose a sentence-word two layer graph algorithm combining with keyword density to generate the multi-document summarization, known as Graph ＆ Keywordp. The traditional graph methods of multi-document summarization only consider the influence of sentence and word in all documents rather than individual documents. Therefore, we construct multiple word graph and extract right keywords in each document to modify the sentence graph and to improve the significance and richness of the summary. Meanwhile, because of the differences in the words importance in documents, we propose to use keyword density for the summaries to provide rich content while using a small number of words. The experiment results show that the Graph ＆ Keywordp method outperforms the state of the art systems when tested on the Duc2004 data set. Key words： multi-document, graph algorithm, keyword density, Graph ＆ Keywordp, Due2004
文摘The education and quality of life of children with intellectual disabilities(ID)have received increasing attention in China due to the evolving diagnostic standards and educational policies.This study analyzes research trends on support for children with ID in China from 2004 to 2023.Using bibliometric analysis and keyword clustering methods,384 research papers published in the China National Knowledge Infrastructure(CNKI)database were examined.The results are as follows.First,research on support for children with ID in China has gradually increased since 2004,with a significant surge observed after 2016.Second,keyword analysis identified key research themes,including“social support,”“inclusive education,”“special schools,”“group work,”and“case studies.”Third,the research frontier analysis revealed that studies on ID support in China have primarily developed in three key domains:social support systems,family and community support,and school-based support.This paper aims to serve as a foundational reference for future research and policy development.
文摘Background: Peripheral nerve regeneration is a critical research area with significant implications for neurology,neurosurgery,and regenerative medicine.A bibliometric analysis was conducted to provide a structured overview of research trends,intellectual impact,and evolving themes in peripheral nerve regeneration.This study aimed to identify the most influential research articles on peripheral nerve regeneration;analyze keyword trends,thematic evolution,and co-word structures;assess the contributions of top authors,universities,and countries;and examine collaboration networks and research dynamics.Methods: A systematic bibliometric approach was employed using two search strategies.The first strategy involved searching within the title,abstract,and keyword fields,yielding 15 317 papers,whereas the second strategy was restricted to searching titles only,retrieving 3 531 papers.From these,the 100 most cited papers were selected for analysis.A thematic analysis was conducted using co-word clustering.The leading contributors were ranked according to the number of publications,citations,h-index,g-index,and m-index.Results: The bibliometric analysis provided several key insights.Keyword analysis using bi-and tri-gram techniques revealed the dominant research themes within the field.The top contributors,including authors,universities,and countries,were ranked based on their productivity and citation impact.Collaboration networks were mapped at the author,institutional,and country levels,highlighting key partnerships and global research interactions.Thematic analysis classified research into seven major domains: neural regeneration and repair;cellular and molecular biology;biomaterials and tissue engineering;experimental studies and statistical analyses;functional and therapeutic aspects;neuropathic pain and peripheral nerve disorders;and Schwann cell and cellular responses.Additionally,the ten most influential papers were reviewed in detail to understand their contributions to the field.Conclusion: This study provides a comprehensive and structured overview of peripheral nerve regeneration research.These findings offer valuable insights into the intellectual foundation of the field by identifying key contributors,research trends,and collaboration patterns.The results serve as a guide for future research,helping researchers to navigate the evolving landscape of peripheral nerve regeneration.
文摘1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography,natural resources,environmental sciences,geographic information sciences,remote sensing and cartography.Manuscripts come from different parts of the world.2 Format and style Contributions should be typed on A4 paper using Times New Roman typeface in Word format,normally not exceeding 20,000 words.3 Abstract and keywords The text should be preceded by an abstract of 200-300 words,which should be followed by 3-7keywords on a separate line.
文摘1 Preparation of manuscripts The manuscript should be prepared with a major word processing program and the file also submitted as a PDF(to clearly indicate all fonts).Please provide the author’s affiliation(address and email),an abstract of 150–300 words presenting the main arguments of the paper,4–8 keywords,high-resolution figures(with permissions),acknowledgments and references.“Documentation II:Author-Date References”in The Chicago Manual of Style and a back issue of the journal can be used as guides to prepare the manuscript.
文摘The authors employed inappropriate search keywords and strategies in their published bibliometric papers within volume 29 of the World Journal of Gastroenterology.The comment highlights the identified issues,provides evidence,and suggests improved study methodologies.Subsequent results with more appro-priate search strategies were presented to address the shortcomings.
基金supported by the University Putra Malaysia and the Ministry of Higher Education Malaysia under grantNumber:(FRGS/1/2023/ICT11/UPM/02/3).
文摘As mobile edge computing continues to develop,the demand for resource-intensive applications is steadily increasing,placing a significant strain on edge nodes.These nodes are normally subject to various constraints,for instance,limited processing capability,a few energy sources,and erratic availability being some of the common ones.Correspondingly,these problems require an effective task allocation algorithmto optimize the resources through continued high system performance and dependability in dynamic environments.This paper proposes an improved Particle Swarm Optimization technique,known as IPSO,for multi-objective optimization in edge computing to overcome these issues.To this end,the IPSO algorithm tries to make a trade-off between two important objectives,which are energy consumption minimization and task execution time reduction.Because of global optimal position mutation and dynamic adjustment to inertia weight,the proposed optimization algorithm can effectively distribute tasks among edge nodes.As a result,it reduces the execution time of tasks and energy consumption.In comparative assessments carried out by IPSO with benchmark methods such as Energy-aware Double-fitness Particle Swarm Optimization(EADPSO)and ICBA,IPSO provides better results than these algorithms.For the maximum task size,when compared with the benchmark methods,IPSO reduces the execution time by 17.1%and energy consumption by 31.58%.These results allow the conclusion that IPSO is an efficient and scalable technique for task allocation at the edge environment.It provides peak efficiency while handling scarce resources and variable workloads.
基金Supported by the National Natural Science Foundation of China (90604025)
文摘Keyword extraction is an important research topic of information retrieval. This paper gave the specification of keywords in Chinese news documents based on analyzing linguistic characteristics of news documents and then proposed a new keyword extraction method based on tf/idf with multi-strategies. The approach selected candidate keywords of uni-, hi- and tri-grams, and then defines the features according to their morphological characters and context information. Moreover, the paper proposed several strategies to amend the incomplete words gotten from the word segmentation and found unknown potential keywords in news documents. Experimental results show that our proposed method can significantly outperform the baseline method. We also applied it to retrospective event detection. Experimental results show that the accuracy and efficiency of news retrospective event detection can be significantly improved.
基金This research was supported by the National Science Foundation of China for Funding Projects （61173089,61472298） and National Statistical Science Program of China（2013LZ46）.
文摘Public Key Encryption with Keyword Search （PEKS）, an indispensable part of searchable encryption, is stock-in- trade for both protecting data and providing operability of encrypted data. So far most of PEKS schemes have been established on Identity-Based Cryptography （IBC） with key escrow problem inherently. Such problem severely restricts the promotion of IBC-based Public Key Infrastructure including PEKS component. Hence, Certificateless Public Key Cryptography （CLPKC） is efficient to remove such problem. CLPKC is introduced into PEKS, and a general model of Certificateless PEKS （CLPEKS） is formalized. In addition, a practical CLPEKS scheme is constructed with security and efficiency analyses. The proposal is secure channel free, and semantically secure against adaptive chosen keyword attack and keyword guessing attack. To illustrate the superiority, massive experiments are conducted on Enron Email dataset which is famous in information retrieval field. Compared with existed constructions, CLPEKS improves the efficiency in theory and removes the key escrow problem.
基金supported by the National Natural Science Foundation of China under Grant Nos. 61772009 and U1736112the Natural Science Foundation of Jiangsu Province under Grant Nos. BK20161511 and BK20181304
文摘Searchable public key encryption is a useful cryptographic paradigm that enables an untrustworthy server to retrieve the encrypted data without revealing the contents of the data. It offers a promising solution to encrypted data retrieval in cryptographic cloud storage. Certificateless public key cryptography (CLPKC) is a novel cryptographic primitive that has many merits. It overcomes the key escrow problem in identity-based cryptography (IBC) and the cumbersome certificate problem in conventional public key cryptography (PKC). Motivated by the appealing features of CLPKC, several certificateless encryption with keyword search (CLEKS) schemes have been presented in the literature. But, our cryptanalysis demonstrates that the previously proposed CLEKS frameworks suffer from the security vulnerability caused by the keyword guessing attack. To remedy the security weakness in the previous frameworks and provide resistance against both inside and outside keyword guessing attacks, we propose a new CLEKS framework. Under the new framework, we design a concrete CLEKS scheme and formally prove its security in the random oracle model. Compared with previous two CLEKS schemes, the proposed scheme has better overall performance while offering stronger security guarantee as it withstands the existing known types of keyword guessing attacks.
文摘The user data stored in an untrusted server, such as the centralized data center or cloud computing server, may be dangerous of eavesdropping if the data format is a plaintext. However, the general ciphertext is difficult to search and thus limited for practical usage. The keyword search encryption is a helpful mechanism that provides a searchable ciphertext for some predefined keywords. The previous studies failed to consider the attack from the data storage server to guess the keyword. This kind of attack may cause some critical information revealed to the untrusted server. This paper proposes a new keyword search encryption model that can effectively resist the keyword-guessing attack performed by the untrusted data storage(testing) server. The testing(query)secret is divided into multiple shares so that the security can be guaranteed if the servers cannot conspire with each other to retrieve all shares of the secret.
基金The authors would like to thank the support from Fundamental Research Funds for the Central Universities(No.30918012204)The authors also gratefully acknowledge the helpful comments and suggestions of other researchers,which has improved the presentation.
文摘To save the local storage,users store the data on the cloud server who offers convenient internet services.To guarantee the data privacy,users encrypt the data before uploading them into the cloud server.Since encryption can reduce the data availability,public-key encryption with keyword search(PEKS)is developed to achieve the retrieval of the encrypted data without decrypting them.However,most PEKS schemes cannot resist quantum computing attack,because the corresponding hardness assumptions are some number theory problems that can be solved efficiently under quantum computers.Besides,the traditional PEKS schemes have an inherent security issue that they cannot resist inside keywords guessing attack(KGA).In this attack,a malicious server can guess the keywords encapsulated in the search token by computing the ciphertext of keywords exhaustively and performing the test between the token and the ciphertext of keywords.In the paper,we propose a lattice-based PEKS scheme that can resist quantum computing attacks.To resist inside KGA,this scheme adopts a lattice-based signature technique into the encryption of keywords to prevent the malicious server from forging a valid ciphertext.Finally,some simulation experiments are conducted to demonstrate the performance of the proposed scheme and some comparison results are further shown with respect to other searchable schemes.
文摘With recent significant development in the portable device market, cloud computing is getting more and more utilized. Many sensitive data are stored in cloud central servers. To ensure privacy, these data are usually encrypted before being uploaded—making file searching complicated. Although previous cloud computing searchable encryption schemes allow users to search encrypted data by keywords securely, these techniques only support exact keyword search and will fail if there are some spelling errors or if some morphological variants of words are used. In this paper, we provide the solution for fuzzy keyword search over encrypted cloud data. K-grams is used to produce fuzzy results. For security reasons, we use two separate servers that cannot communicate with each other. Our experiment result shows that our system is effective and scalable to handle large number of encrypted files.
基金Project supported by the National Natural Science Foundation of China (No. 60221120145) and Science & Technology Committee of Shanghai Municipality Key Project (No. 02DJ14045), China
文摘may incur significant bandwidth for executing more com- plicated search queries such as multiple-attribute queries. In order to reduce query overhead, KSS (keyword-set search) by Gnawali partitions the index by a set of keywords. However, a KSS index is considerably larger than a standard inverted index, since there are more word sets than there are individual words. And the insert overhead and storage overhead are obviously un- acceptable for full-text search on a collection of documents even if KSS uses the distance window technology. In this paper, we extract the relationship information between query keywords from websites’ queries logs to improve performance of KSS system. Experiments results clearly demonstrated that the improved keyword-set search system based on keywords relationship (KRBKSS) is more efficient than KSS index in insert overhead and storage overhead, and a standard inverted index in terms of communication costs for query.
基金Project supported by the Science Foundation of Shanghai Municipal Commission of Science and Technology （Grant No.055115001）
文摘In this paper, an improved algorithm, web-based keyword weight algorithm （WKWA）, is presented to weight keywords in web documents. WKWA takes into account representation features of web documents and advantages of the TF＊IDF, TFC and ITC algorithms in order to make it more appropriate for web documents. Meanwhile, the presented algorithm is applied to improved vector space model （IVSM）. A real system has been implemented for calculating semantic similarities of web documents. Four experiments have been carried out. They are keyword weight calculation, feature item selection, semantic similarity calculation, and WKWA time performance. The results demonstrate accuracy of keyword weight, and semantic similarity is improved.
基金the National Natural Science Foundation of China Grant 71673131 for financial support
文摘Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.
基金supported partly by the following funding agencies:the National Natural Science Foundation(No.61170274)the Innovative Research Groups of the National Natural Science Foundation(No.61121061)+1 种基金the National Key Basic Research Program of China (No.2011CB302506)Youth Scientific Research and Innovation Plan of Beijing University of Posts and Telecommunications(No. 2013RC1101)
文摘In this paper,we study the problem of privacy-preserving top-k keyword similarity search over outsourced cloud data.Taking edit distance as a measure of similarity,we first build up the similarity keyword sets for all the keywords in the data collection.We then calculate the relevance scores of the elements in the similarity keyword sets by the widely used tf-idf theory.Leveraging both the similarity keyword sets and the relevance scores,we present a new secure and efficient treebased index structure for privacy-preserving top-k keyword similarity search.To prevent potential statistical attacks,we also introduce a two-server model to separate the association between the index structure and the data collection in cloud servers.Thorough analysis is given on the validity of search functionality and formal security proofs are presented for the privacy guarantee of our solution.Experimental results on real-world data sets further demonstrate the availability and efficiency of our solution.
