File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most ...File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.展开更多
In the Big Data era,numerous sources and environments generate massive amounts of data.This enormous amount of data necessitates specialized advanced tools and procedures that effectively evaluate the information and ...In the Big Data era,numerous sources and environments generate massive amounts of data.This enormous amount of data necessitates specialized advanced tools and procedures that effectively evaluate the information and anticipate decisions for future changes.Hadoop is used to process this kind of data.It is known to handle vast volumes of data more efficiently than tiny amounts,which results in inefficiency in the framework.This study proposes a novel solution to the problem by applying the Enhanced Best Fit Merging algorithm(EBFM)that merges files depending on predefined parameters(type and size).Implementing this algorithm will ensure that the maximum amount of the block size and the generated file size will be in the same range.Its primary goal is to dynamically merge files with the stated criteria based on the file type to guarantee the efficacy and efficiency of the established system.This procedure takes place before the files are available for the Hadoop framework.Additionally,the files generated by the system are named with specific keywords to ensure there is no data loss(file overwrite).The proposed approach guarantees the generation of the fewest possible large files,which reduces the input/output memory burden and corresponds to the Hadoop framework’s effectiveness.The findings show that the proposed technique enhances the framework’s performance by approximately 64%while comparing all other potential performance-impairing variables.The proposed approach is implementable in any environment that uses the Hadoop framework,not limited to smart cities,real-time data analysis,etc.展开更多
Byte-addressable non-volatile memory(NVM),as a new participant in the storage hierarchy,gives extremely high performance in storage,which forces changes to be made on current filesystem designs.Page cache,once a signi...Byte-addressable non-volatile memory(NVM),as a new participant in the storage hierarchy,gives extremely high performance in storage,which forces changes to be made on current filesystem designs.Page cache,once a significant mechanism filling the performance gap between Dynamic Random Access Memory(DRAM)and block devices,is now a liability that heavily hinders the writing performance of NVM filesystems.Therefore state-of-the-art NVM filesystems leverage the direct access(DAX)technology to bypass the page cache entirely.However,the DRAM still provides higher bandwidth than NVM,which prevents skewed read workloads from benefiting from a higher bandwidth of the DRAM and leads to sub-optimal performance for the system.In this paper,we propose RCache,a readintensive workload-aware page cache for NVM filesystems.Different from traditional caching mechanisms where all reads go through DRAM,RCache uses a tiered page cache design,including assigning DRAM and NVM to hot and cold data separately,and reading data from both sides.To avoid copying data to DRAM in a critical path,RCache migrates data from NVM to DRAM in a background thread.Additionally,RCache manages data in DRAM in a lock-free manner for better latency and scalability.Evaluations on Intel Optane Data Center(DC)Persistent Memory Modules show that,compared with NOVA,RCache achieves 3 times higher bandwidth for read-intensive workloads and introduces little performance loss for write operations.展开更多
In distributed storage systems,file access efficiency has an important impact on the real-time nature of information forensics.As a popular approach to improve file accessing efficiency,prefetching model can fetches d...In distributed storage systems,file access efficiency has an important impact on the real-time nature of information forensics.As a popular approach to improve file accessing efficiency,prefetching model can fetches data before it is needed according to the file access pattern,which can reduce the I/O waiting time and increase the system concurrency.However,prefetching model needs to mine the degree of association between files to ensure the accuracy of prefetching.In the massive small file situation,the sheer volume of files poses a challenge to the efficiency and accuracy of relevance mining.In this paper,we propose a massive files prefetching model based on LSTM neural network with cache transaction strategy to improve file access efficiency.Firstly,we propose a file clustering algorithm based on temporal locality and spatial locality to reduce the computational complexity.Secondly,we propose a definition of cache transaction according to files occurrence in cache instead of time-offset distance based methods to extract file block feature accurately.Lastly,we innovatively propose a file access prediction algorithm based on LSTM neural network which predict the file that have high possibility to be accessed.Experiments show that compared with the traditional LRU and the plain grouping methods,the proposed model notably increase the cache hit rate and effectively reduces the I/O wait time.展开更多
In order to improve the management strategy for personnel files in colleges and universities,simplify the complex process of file management,and improve file management security and content preservation of the files.T...In order to improve the management strategy for personnel files in colleges and universities,simplify the complex process of file management,and improve file management security and content preservation of the files.This paper elaborates on the application of Artificial Intelligence(AI)technology in university personnel file management through theoretical analysis based on the understanding of Al technology.展开更多
To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution...To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.展开更多
The fast growing market of mobile device adoption and cloud computing has led to exploitation of mobile devices utilizing cloud services. One major chal-lenge facing the usage of mobile devices in the cloud environmen...The fast growing market of mobile device adoption and cloud computing has led to exploitation of mobile devices utilizing cloud services. One major chal-lenge facing the usage of mobile devices in the cloud environment is mobile synchronization to the cloud, e.g., synchronizing contacts, text messages, imag-es, and videos. Owing to the expected high volume of traffic and high time complexity required for synchronization, an appropriate synchronization algo-rithm needs to be developed. Delta synchronization is one method of synchro-nizing compressed files that requires uploading the whole file, even when no changes were made or if it was only partially changed. In the present study, we proposed an algorithm, based on Delta synchronization, to solve the problem of synchronizing compressed files under various forms of modification (e.g., not modified, partially modified, or completely modified). To measure the effi-ciency of our proposed algorithm, we compared it to the Dropbox application algorithm. The results demonstrated that our algorithm outperformed the regular Dropbox synchronization mechanism by reducing the synchronization time, cost, and traffic load between clients and the cloud service provider.展开更多
IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this...IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this paper.The new model provides an effective approach on choosing an optimal peer from several resource discovering results for the best file transfer.Compared with the traditional min-hops scheme that uses hops as the only selecting criterion,the proposed model uses FCM to investigate the complex relationships among various relative factors in wireless environments and gives an overall evaluation score on the candidate.It also has strong scalability for being independent of specified P2P resource discovering protocols.Furthermore,a complete implementation is explained in concrete modules.The simulation results show that the proposed model is effective and feasible compared with min-hops scheme,with the success transfer rate increased by at least 20% and transfer time improved as high as 34%.展开更多
In this paper, we analyze the complexity and entropy of different methods of data compression algorithms: LZW, Huffman, Fixed-length code (FLC), and Huffman after using Fixed-length code (HFLC). We test those algorith...In this paper, we analyze the complexity and entropy of different methods of data compression algorithms: LZW, Huffman, Fixed-length code (FLC), and Huffman after using Fixed-length code (HFLC). We test those algorithms on different files of different sizes and then conclude that: LZW is the best one in all compression scales that we tested especially on the large files, then Huffman, HFLC, and FLC, respectively. Data compression still is an important topic for research these days, and has many applications and uses needed. Therefore, we suggest continuing searching in this field and trying to combine two techniques in order to reach a best one, or use another source mapping (Hamming) like embedding a linear array into a Hypercube with other good techniques like Huffman and trying to reach good results.展开更多
Aim: the aim of this study was to investigate the shaping ability of thermomechanically treated files manufactured by twisting(Twisted files)and compare it to conventional rotary system (K3, Sybron Endo, Orange, CA) i...Aim: the aim of this study was to investigate the shaping ability of thermomechanically treated files manufactured by twisting(Twisted files)and compare it to conventional rotary system (K3, Sybron Endo, Orange, CA) in S-shaped canals, including formation of ledges, zipping, elbow, outer widening, danger zone, perforation and file deformation. Materials & Methods: Forty S-Shaped canals in resin blocks were randomly divided into 2 groups of 20 each. Pre-instrumentation images of the canals were taken via a digital camera and superimposed on images taken after preparation with TF and K3 systems to apical size of 25/06 and 30/06. Canal aberrations were measured from the superimposed image at five levels using AutoCAD system. Fisher exact test and Mann Whitney test were used for analysis of the data. Results: the incidence of zipping, elbow and apical transportation was significantly lower in the TF group (P = 0.04). Generally the incidence of aberration increased when the apical size increased to 30/0.06 regardless of the file system. Significant file deformation was evident in the TF after single use (P ? 0.001). Conclusion: Under the conditions of this study, TF manufactured by new technique performed better than K3 systems when used up to size 25/06 in simulated S-shaped canals. Clinical significance: The flexibility of thermomechanically treated files is beneficial in canals with multiple curvatures;however, attention should be paid to the instrument taper and final apical size of the preparation.展开更多
In public health emergencies, the collection of archival information in the area of public health emergencies is very important, which can provide a reference for the early warning and processing mechanism. At the pre...In public health emergencies, the collection of archival information in the area of public health emergencies is very important, which can provide a reference for the early warning and processing mechanism. At the present stage, the unlimited demand of archival users for resources and the convenience of obtaining resources have become the two driving forces to promote the “transformation” and “growth” of archives. Public health emergencies, the transformation of archives collection and service mode, social media has become an indispensable platform for user information exchange, sharing and transmission, which requires archives to change the mode of archives acquisition and storage. Archival users require more interactive, targeted and cutting-edge forms of access and archival services are also developing toward diversified functions and connotations. Archival information resource sharing is also an important link in this development trend. This paper attempts to analyze the collection methods of archives departments in public health emergencies, and then puts forward the corresponding measures for archives departments to play their functions, such as flexibly solving the needs of archives access, strengthening the development of information resources, doing a good job in the collection of relevant archives, and publicizing archives work in combination with hot spots. This paper discusses the completeness of archival data collection, the means of archival management, the scientific classification of archival data, the ways of archival data collection and so on.展开更多
The increase in issue width and instructions window size in modern processors demand an increase in the size of the register files, as well as an increase in the number of ports. Bigger register files implies an incre...The increase in issue width and instructions window size in modern processors demand an increase in the size of the register files, as well as an increase in the number of ports. Bigger register files implies an increase in power consumed by these units as well as longer access delays. Models that assist in estimating the size of the register file, and its timing early in the design cycle are critical to the time-budget allocated to a processor design and to its performance. In this work, we discuss a Radial Base Function (RBF) Artificial Neural Network (ANN) model for the prediction of time and area for standard cell register files designed using optimized Synopsys Design Ware components and an UMC130 nm library. The ANN model predictions were compared against experimental results (obtained using detailed simulation) and a nonlinear regression-based model, and it is observed that the ANN model is very accurate and outperformed the non-linear model in several statistical parameters. Using the trained ANN model, a parametric study was carried out to study the effect of the number of words in the file (D), the number of bit in one word (W) and the total number of Read and Write ports (P) on the latency and area of standard cell register files.展开更多
两次金卷轴奖获奖者Will Files是好莱坞的一位音效设计师和声音混录师,被好莱坞的记者称之为行业中"最杰出的最具才能的35岁以下的艺术家"他参与制作了许多好莱坞大片和卖座电影,包括Marvel漫画公司最新作品《神奇四侠》(Fant...两次金卷轴奖获奖者Will Files是好莱坞的一位音效设计师和声音混录师,被好莱坞的记者称之为行业中"最杰出的最具才能的35岁以下的艺术家"他参与制作了许多好莱坞大片和卖座电影,包括Marvel漫画公司最新作品《神奇四侠》(Fantastic Four),《猩球崛起:黎明之战》(Dawn of the Planet of the Apes)。展开更多
Stereolithographic(STL)files have been extensively used in rapid prototyping industries as well as many other fields as watermarking algorithms to secure intellectual property and protect three-dimensional models from...Stereolithographic(STL)files have been extensively used in rapid prototyping industries as well as many other fields as watermarking algorithms to secure intellectual property and protect three-dimensional models from theft.However,to the best of our knowledge,few studies have looked at how watermarking can resist attacks that involve vertex-reordering.Here,we present a lossless and robust watermarking scheme for STL files to protect against vertexreordering attacks.Specifically,we designed a novel error-correcting code(ECC)that can correct the error of any one-bit in a bitstream by inserting several check digits.In addition,ECC is designed to make use of redundant information according to the characteristics of STL files,which introduces further robustness for defense against attacks.No modifications are made to the geometric information of the three-dimensional model,which respects the requirements of a highprecision model.The experimental results show that the proposed watermarking scheme can survive numerous kinds of attack,including rotation,scaling and translation(RST),facet reordering,and vertex-reordering attacks.展开更多
文摘File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.
基金This research was supported by the Universiti Sains Malaysia(USM)and the ministry of Higher Education Malaysia through Fundamental Research Grant Scheme(FRGS-Grant No:FRGS/1/2020/TK0/USM/02/1).
文摘In the Big Data era,numerous sources and environments generate massive amounts of data.This enormous amount of data necessitates specialized advanced tools and procedures that effectively evaluate the information and anticipate decisions for future changes.Hadoop is used to process this kind of data.It is known to handle vast volumes of data more efficiently than tiny amounts,which results in inefficiency in the framework.This study proposes a novel solution to the problem by applying the Enhanced Best Fit Merging algorithm(EBFM)that merges files depending on predefined parameters(type and size).Implementing this algorithm will ensure that the maximum amount of the block size and the generated file size will be in the same range.Its primary goal is to dynamically merge files with the stated criteria based on the file type to guarantee the efficacy and efficiency of the established system.This procedure takes place before the files are available for the Hadoop framework.Additionally,the files generated by the system are named with specific keywords to ensure there is no data loss(file overwrite).The proposed approach guarantees the generation of the fewest possible large files,which reduces the input/output memory burden and corresponds to the Hadoop framework’s effectiveness.The findings show that the proposed technique enhances the framework’s performance by approximately 64%while comparing all other potential performance-impairing variables.The proposed approach is implementable in any environment that uses the Hadoop framework,not limited to smart cities,real-time data analysis,etc.
基金supported by ZTE Industry⁃University⁃Institute Coopera⁃tion Funds under Grant No.HC⁃CN⁃20181128026.
文摘Byte-addressable non-volatile memory(NVM),as a new participant in the storage hierarchy,gives extremely high performance in storage,which forces changes to be made on current filesystem designs.Page cache,once a significant mechanism filling the performance gap between Dynamic Random Access Memory(DRAM)and block devices,is now a liability that heavily hinders the writing performance of NVM filesystems.Therefore state-of-the-art NVM filesystems leverage the direct access(DAX)technology to bypass the page cache entirely.However,the DRAM still provides higher bandwidth than NVM,which prevents skewed read workloads from benefiting from a higher bandwidth of the DRAM and leads to sub-optimal performance for the system.In this paper,we propose RCache,a readintensive workload-aware page cache for NVM filesystems.Different from traditional caching mechanisms where all reads go through DRAM,RCache uses a tiered page cache design,including assigning DRAM and NVM to hot and cold data separately,and reading data from both sides.To avoid copying data to DRAM in a critical path,RCache migrates data from NVM to DRAM in a background thread.Additionally,RCache manages data in DRAM in a lock-free manner for better latency and scalability.Evaluations on Intel Optane Data Center(DC)Persistent Memory Modules show that,compared with NOVA,RCache achieves 3 times higher bandwidth for read-intensive workloads and introduces little performance loss for write operations.
基金This work is supported by‘The Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.201714)’‘Weihai Science and Technology Development Program(2016DXGJMS15)’‘Key Research and Development Program in Shandong Provincial(2017GGX90103)’.
文摘In distributed storage systems,file access efficiency has an important impact on the real-time nature of information forensics.As a popular approach to improve file accessing efficiency,prefetching model can fetches data before it is needed according to the file access pattern,which can reduce the I/O waiting time and increase the system concurrency.However,prefetching model needs to mine the degree of association between files to ensure the accuracy of prefetching.In the massive small file situation,the sheer volume of files poses a challenge to the efficiency and accuracy of relevance mining.In this paper,we propose a massive files prefetching model based on LSTM neural network with cache transaction strategy to improve file access efficiency.Firstly,we propose a file clustering algorithm based on temporal locality and spatial locality to reduce the computational complexity.Secondly,we propose a definition of cache transaction according to files occurrence in cache instead of time-offset distance based methods to extract file block feature accurately.Lastly,we innovatively propose a file access prediction algorithm based on LSTM neural network which predict the file that have high possibility to be accessed.Experiments show that compared with the traditional LRU and the plain grouping methods,the proposed model notably increase the cache hit rate and effectively reduces the I/O wait time.
文摘In order to improve the management strategy for personnel files in colleges and universities,simplify the complex process of file management,and improve file management security and content preservation of the files.This paper elaborates on the application of Artificial Intelligence(AI)technology in university personnel file management through theoretical analysis based on the understanding of Al technology.
文摘To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.
文摘The fast growing market of mobile device adoption and cloud computing has led to exploitation of mobile devices utilizing cloud services. One major chal-lenge facing the usage of mobile devices in the cloud environment is mobile synchronization to the cloud, e.g., synchronizing contacts, text messages, imag-es, and videos. Owing to the expected high volume of traffic and high time complexity required for synchronization, an appropriate synchronization algo-rithm needs to be developed. Delta synchronization is one method of synchro-nizing compressed files that requires uploading the whole file, even when no changes were made or if it was only partially changed. In the present study, we proposed an algorithm, based on Delta synchronization, to solve the problem of synchronizing compressed files under various forms of modification (e.g., not modified, partially modified, or completely modified). To measure the effi-ciency of our proposed algorithm, we compared it to the Dropbox application algorithm. The results demonstrated that our algorithm outperformed the regular Dropbox synchronization mechanism by reducing the synchronization time, cost, and traffic load between clients and the cloud service provider.
基金Sponsored by the National Natural Science Foundation of China(Grant No.60672124 and 60832009)Hi-Tech Research and Development Program(National 863 Program)(Grant No.2007AA01Z221)
文摘IIn order to improve the performance of wireless distributed peer-to-peer(P2P)files sharing systems,a general system architecture and a novel peer selecting model based on fuzzy cognitive maps(FCM)are proposed in this paper.The new model provides an effective approach on choosing an optimal peer from several resource discovering results for the best file transfer.Compared with the traditional min-hops scheme that uses hops as the only selecting criterion,the proposed model uses FCM to investigate the complex relationships among various relative factors in wireless environments and gives an overall evaluation score on the candidate.It also has strong scalability for being independent of specified P2P resource discovering protocols.Furthermore,a complete implementation is explained in concrete modules.The simulation results show that the proposed model is effective and feasible compared with min-hops scheme,with the success transfer rate increased by at least 20% and transfer time improved as high as 34%.
文摘In this paper, we analyze the complexity and entropy of different methods of data compression algorithms: LZW, Huffman, Fixed-length code (FLC), and Huffman after using Fixed-length code (HFLC). We test those algorithms on different files of different sizes and then conclude that: LZW is the best one in all compression scales that we tested especially on the large files, then Huffman, HFLC, and FLC, respectively. Data compression still is an important topic for research these days, and has many applications and uses needed. Therefore, we suggest continuing searching in this field and trying to combine two techniques in order to reach a best one, or use another source mapping (Hamming) like embedding a linear array into a Hypercube with other good techniques like Huffman and trying to reach good results.
文摘Aim: the aim of this study was to investigate the shaping ability of thermomechanically treated files manufactured by twisting(Twisted files)and compare it to conventional rotary system (K3, Sybron Endo, Orange, CA) in S-shaped canals, including formation of ledges, zipping, elbow, outer widening, danger zone, perforation and file deformation. Materials & Methods: Forty S-Shaped canals in resin blocks were randomly divided into 2 groups of 20 each. Pre-instrumentation images of the canals were taken via a digital camera and superimposed on images taken after preparation with TF and K3 systems to apical size of 25/06 and 30/06. Canal aberrations were measured from the superimposed image at five levels using AutoCAD system. Fisher exact test and Mann Whitney test were used for analysis of the data. Results: the incidence of zipping, elbow and apical transportation was significantly lower in the TF group (P = 0.04). Generally the incidence of aberration increased when the apical size increased to 30/0.06 regardless of the file system. Significant file deformation was evident in the TF after single use (P ? 0.001). Conclusion: Under the conditions of this study, TF manufactured by new technique performed better than K3 systems when used up to size 25/06 in simulated S-shaped canals. Clinical significance: The flexibility of thermomechanically treated files is beneficial in canals with multiple curvatures;however, attention should be paid to the instrument taper and final apical size of the preparation.
文摘In public health emergencies, the collection of archival information in the area of public health emergencies is very important, which can provide a reference for the early warning and processing mechanism. At the present stage, the unlimited demand of archival users for resources and the convenience of obtaining resources have become the two driving forces to promote the “transformation” and “growth” of archives. Public health emergencies, the transformation of archives collection and service mode, social media has become an indispensable platform for user information exchange, sharing and transmission, which requires archives to change the mode of archives acquisition and storage. Archival users require more interactive, targeted and cutting-edge forms of access and archival services are also developing toward diversified functions and connotations. Archival information resource sharing is also an important link in this development trend. This paper attempts to analyze the collection methods of archives departments in public health emergencies, and then puts forward the corresponding measures for archives departments to play their functions, such as flexibly solving the needs of archives access, strengthening the development of information resources, doing a good job in the collection of relevant archives, and publicizing archives work in combination with hot spots. This paper discusses the completeness of archival data collection, the means of archival management, the scientific classification of archival data, the ways of archival data collection and so on.
文摘The increase in issue width and instructions window size in modern processors demand an increase in the size of the register files, as well as an increase in the number of ports. Bigger register files implies an increase in power consumed by these units as well as longer access delays. Models that assist in estimating the size of the register file, and its timing early in the design cycle are critical to the time-budget allocated to a processor design and to its performance. In this work, we discuss a Radial Base Function (RBF) Artificial Neural Network (ANN) model for the prediction of time and area for standard cell register files designed using optimized Synopsys Design Ware components and an UMC130 nm library. The ANN model predictions were compared against experimental results (obtained using detailed simulation) and a nonlinear regression-based model, and it is observed that the ANN model is very accurate and outperformed the non-linear model in several statistical parameters. Using the trained ANN model, a parametric study was carried out to study the effect of the number of words in the file (D), the number of bit in one word (W) and the total number of Read and Write ports (P) on the latency and area of standard cell register files.
文摘两次金卷轴奖获奖者Will Files是好莱坞的一位音效设计师和声音混录师,被好莱坞的记者称之为行业中"最杰出的最具才能的35岁以下的艺术家"他参与制作了许多好莱坞大片和卖座电影,包括Marvel漫画公司最新作品《神奇四侠》(Fantastic Four),《猩球崛起:黎明之战》(Dawn of the Planet of the Apes)。
基金This work was supported in part by the National Science Foundation of China(No.61772539,6187212,61972405),STITSX(No.201705D131025),1331KITSX,and CiCi3D.
文摘Stereolithographic(STL)files have been extensively used in rapid prototyping industries as well as many other fields as watermarking algorithms to secure intellectual property and protect three-dimensional models from theft.However,to the best of our knowledge,few studies have looked at how watermarking can resist attacks that involve vertex-reordering.Here,we present a lossless and robust watermarking scheme for STL files to protect against vertexreordering attacks.Specifically,we designed a novel error-correcting code(ECC)that can correct the error of any one-bit in a bitstream by inserting several check digits.In addition,ECC is designed to make use of redundant information according to the characteristics of STL files,which introduces further robustness for defense against attacks.No modifications are made to the geometric information of the three-dimensional model,which respects the requirements of a highprecision model.The experimental results show that the proposed watermarking scheme can survive numerous kinds of attack,including rotation,scaling and translation(RST),facet reordering,and vertex-reordering attacks.