Graph pattern matching(GPM)can be used to mine the key information in graphs.Exact GPM is one of the most commonly used methods among all the GPM-related methods,which aims to exactly find all subgraphs for a given qu...Graph pattern matching(GPM)can be used to mine the key information in graphs.Exact GPM is one of the most commonly used methods among all the GPM-related methods,which aims to exactly find all subgraphs for a given query graph in a data graph.The exact GPM has been widely used in biological data analyses,social network analyses and other fields.In this paper,the applications of the exact GPM were first introduced,and the research progress of the exact GPM was summarized.Then,the related algorithms were introduced in detail,and the experiments on the state-of-the-art exact GPM algorithms were conducted to compare their performance.Based on the experimental results,the applicable scenarios of the algorithms were pointed out.New research opportunities in this area were proposed.展开更多
Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Chan...Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Changing Consecutive Characters (PMCCC) to make the searching pro- cess of the algorithm faster. PMCCC enhances the shift process that determines how the pattern moves in case of the occurrence of the mismatch between the pattern and the text. It enhances the Berry Ravindran (BR) shift function by using m consecutive characters where m is the pattern length. The formal basis and the algorithms are presented. The experimental results show that PMCCC made enhancements in searching process by reducing the number of comparisons and the number of attempts. Comparing the results of PMCCC with other related algorithms has shown significant enhancements in average number of comparisons and average number of attempts.展开更多
Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topologi...Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.展开更多
Modern applications require large databases to be searched for regions that are similar to a given pattern. The DNA sequence analysis, speech and text recognition, artificial intelligence, Internet of Things, and many...Modern applications require large databases to be searched for regions that are similar to a given pattern. The DNA sequence analysis, speech and text recognition, artificial intelligence, Internet of Things, and many other applications highly depend on pattern matching or similarity searches. In this paper, we discuss some of the string matching solutions developed in the past. Then, we present a novel mathematical model to search for a given pattern and it’s near approximates in the text.展开更多
The research on graph pattern matching(GPM) has attracted a lot of attention. However, most of the research has focused on complex networks, and there are few researches on GPM in the medical field. Hence, with GPM th...The research on graph pattern matching(GPM) has attracted a lot of attention. However, most of the research has focused on complex networks, and there are few researches on GPM in the medical field. Hence, with GPM this paper is to make a breast cancer-oriented diagnosis before the surgery. Technically, this paper has firstly made a new definition of GPM, aiming to explore the GPM in the medical field, especially in Medical Knowledge Graphs(MKGs). Then, in the specific matching process, this paper introduces fuzzy calculation, and proposes a multi-threaded bidirectional routing exploration(M-TBRE) algorithm based on depth first search and a two-way routing matching algorithm based on multi-threading. In addition, fuzzy constraints are introduced in the M-TBRE algorithm, which leads to the Fuzzy-M-TBRE algorithm. The experimental results on the two datasets show that compared with existing algorithms, our proposed algorithm is more efficient and effective.展开更多
In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine environment.The autonomous drivi...In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine environment.The autonomous driving robot continuously detects the wall of the tunnel in the horizontal direction using the light detection and ranging(Li DAR)sensor and performs pattern matching by recognizing the shape of the tunnel wall.The proposed method was designed to measure the heading of the robot by fusion with the inertial measurement units sensor according to the pattern matching accuracy;it is combined with the encoder sensor to estimate the location of the robot.In addition,when the robot is driving,the vertical direction of the underground mine is scanned through the vertical Li DAR sensor and stacked to create a 3D map of the underground mine.The performance of the proposed method was superior to that of previous studies;the mean absolute error achieved was 0.08 m for the X-Y axes.A root mean square error of 0.05 m^(2)was achieved by comparing the tunnel section maps that were created by the autonomous driving robot to those of manual surveying.展开更多
String matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that...String matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that is created and kept by modern computational devices influences researchers to obtain even more powerful methods for coping with this problem. In this research, the Quick Search string matching algorithm are adopted to be implemented under the multi-core environment using OpenMP directive which can be employed to reduce the overall execution time of the program. English text, Proteins and DNA data types are utilized to examine the effect of parallelization and implementation of Quick Search string matching algorithm on multi-core based environment. Experimental outcomes reveal that the overall performance of the mentioned string matching algorithm has been improved, and the improvement in the execution time which has been obtained is considerable enough to recommend the multi-core environment as the suitable platform for parallelizing the Quick Search string matching algorithm.展开更多
Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal...Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal graph association rules(TGARs)that extend traditional graph-pattern association rules in a static graph by incorporating the unique temporal information and constraints.We introduce quality measures(e.g.,support,confidence,and diversification)to characterize meaningful TGARs that are useful and diversified.In addition,the proposed support metric is an upper bound for alternative metrics,allowing us to guarantee a superset of patterns.We extend conventional confidence measures in terms of maximal occurrences of TGARs.The diversification score strikes a balance between interestingness and diversity.Although the problem is NP-hard,we develop an effective discovery algorithm for TGARs that integrates TGARs generation and TGARs selection and shows that mining TGARs is feasible over a temporal graph.We propose pruning strategies to filter TGARs that have low support or cannot make top-k as early as possible.Moreover,we design an auxiliary data structure to prune the TGARs that do not meet the constraints during the TGARs generation process to avoid conducting repeated subgraph matching for each extension in the search space.We experimentally verify the effectiveness,efficiency,and scalability of our algorithms in discovering diversified top-k TGARs from temporal graphs in real-life applications.展开更多
Deep Packet Inspection(DPI)at the core of many monitoring appliances,such as NIDS,NIPS,plays a major role.DPI is beneficial to content providers and censorship to monitor network traffic.However,the surge of network t...Deep Packet Inspection(DPI)at the core of many monitoring appliances,such as NIDS,NIPS,plays a major role.DPI is beneficial to content providers and censorship to monitor network traffic.However,the surge of network traffic has put tremendous pressure on the performance of DPI.In fact,the sensitive content being monitored is only a minority of network traffic,that is to say,most is undesired.A close look at the network traffic,we found that it contains many undesired high frequency content(UHC)that are not monitored.As everyone knows,the key to improve DPI performance is to skip as many useless characters as possible.Nevertheless,researchers generally study the algorithm of skipping useless characters through sensitive content,ignoring the high-frequency non-sensitive content.To fill this gap,in this literature,we design a model,named Fast AC Model with Skipping(FAMS),to quickly skip UHC while scanning traffic.The model consists of a standard AC automaton,where the input traffic is scanned byte-by-byte,and an additional sub-model,which includes a mapping set and UHC matching model.The mapping set is a bridge between the state node of AC and UHC matching model,while the latter is to select a matching function from hash and fingerprint functions.Our experiments show promising results that we achieve a throughput gain of 1.3-2.6 times the original throughput and 1.1-1.3 times Barr’s double path method.展开更多
To precisely meet the nutritional requirements of sows during the stages of pregnancy and lactation,a precision feeding system was developed by using the intelligent sow feeder combined with a rule-based expert system...To precisely meet the nutritional requirements of sows during the stages of pregnancy and lactation,a precision feeding system was developed by using the intelligent sow feeder combined with a rule-based expert system and the Internet of Things(IoTs).The model of uncertain knowledge representation was established for inference by using the certainty factor.The daily feeding amount of each sow was calculated by the expert system.An improved pattern matching algorithm Reused Degree Model-RETE(RDM-RETE)was proposed for the decision of daily feeding amount,which sped up inference by optimizing the RETE network topology.A prediction model of daily feeding amount was established by a rule-based expert system and the precision feeding was achieved by an accurate control technology of variable volume.The experimental results demonstrated that the HASH-RDM-RETE algorithm could effectively reduce the network complexity and improve the inference efficiency.The feeding amount decided by the expert system was a logarithmic model,which was consistent with the feeding law of lactating sows.The inferential feeding amount was adopted as the predicted feed intake and the coefficient of correlation between predicted feed intake and actual feed intake was greater than or equal to 0.99.Each sow was fed at different feeding intervals and different feed amounts for each meal in a day.The feed intake was 26.84% higher than that of artificial feeding during lactation days(p<0.05).The piglets weaned per sow per year(PSY)can be increased by 1.51 compared with that of relatively high levels in domestic pig farms.This system is stable in feeding and lowers the breeding cost that can be applied in precision feeding in swine production.展开更多
Objectives:Genomic signatures like k-mers have become one of the most prominent approaches to describe genomic data.As a result,myriad real-world applications,such as the construction of de Bruijn graphs in genome ass...Objectives:Genomic signatures like k-mers have become one of the most prominent approaches to describe genomic data.As a result,myriad real-world applications,such as the construction of de Bruijn graphs in genome assembly,have been benefited by recognizing genomic signatures.In other words,an efficient approachof genomic signatureprofiling is an essential need for tackling high-throughput sequencing reads.However,most of the existing approaches only recognize fixed-size k-merswhile many research studies have shown the importance of considering variable-length k-mers.Methods:In this paper,we present a novel genomic signature profiling approach,TahcoRoll,by extending the Aho–Corasick algorithm(AC)for the task of profiling variable-length k-mers.We first group nucleotides into two clusters and represent each cluster with a bit.The rolling hash technique is further utilized to encode signatures and read patterns for efficient matching.Results:In extensive experiments,TahcoRoll significantly outperforms the most state-of-the-art k-mer counters and has the capability of processing reads across different sequencing platforms on a budget desktop computer.Conclusions:The single-thread version of TahcoRoll is as efficient as the eight-thread version of the state-of-the-art,JellyFish,while the eight-thread TahcoRoll outperforms the eight-thread JellyFish by at least four times.展开更多
Packet analysis is very important in our digital life. But what protocol analyzers can do is limited because they can only process data in determined format. This paper puts forward a solution to decode raw data in an...Packet analysis is very important in our digital life. But what protocol analyzers can do is limited because they can only process data in determined format. This paper puts forward a solution to decode raw data in an unknown format. It is certain that data can be cut into packets because there are usually characteristic bit sequences in packet headers. The key to solve the problem is how to find out those characteristic sequences. We present an efficient way of bit sequence enumeration. Both Aho-Corasick (AC) algorithm and data mining method are used to reduce the cost of the process.展开更多
We propose an efficient, specific method for estimating camera parameters from a single starry night image. Such an image consists of a collection of disks representing stars, so traditional estimation methods for com...We propose an efficient, specific method for estimating camera parameters from a single starry night image. Such an image consists of a collection of disks representing stars, so traditional estimation methods for common pictures do not work. Our method uses a database, a star catalog, that stores the positions of stars on the celestial sphere. Our method computes magnitudes(i.e., brightnesses) of stars in the input image and uses them to find the corresponding stars in the star catalog. Camera parameters can then be estimated by a simple geometric calculation. Our method is over ten times faster and more accurate than a previous method.展开更多
Purpose–Over the past decade,the cost of product development has increased drastically,and this is due to the inability of most enterprises to locate suitable and optimal collaborators for knowledge sharing.Neverthel...Purpose–Over the past decade,the cost of product development has increased drastically,and this is due to the inability of most enterprises to locate suitable and optimal collaborators for knowledge sharing.Nevertheless,knowledge sharing is a mechanism that helps people find the best collaborators with relevant knowledge.Hence,a new approach for locating optimal collaborators with relevant knowledge is needed,which couldhelp enterprisein reducingcost andtime ina knowledge-sharingenvironment.Thepaper aimsto discuss these issues.Design/methodology/approach–One unique challenge in the domain of knowledge sharing is that collaborators do not possess the same number of events resident in the knowledge available for sharing.In this paper,the authors present a new approach for locating optimal collaborators in knowledge-sharing environment using the combinatorial algorithm(CA-KSE).Findings–The proposed pattern-matching approach implemented in Java is considered efficient for solving the issue peculiar to collaboration in knowledge-sharing domain.The authors benchmarked the proposed approach with its semi-global pairwise alignment and global alignment counterparts through scores comparison and the receiver operating characteristic curve.The results obtained from the comparisons showedthat CA-KSEis a perfect test havinganarea undercurveof 0.9659,comparedto the other approaches.Research limitations/implications–The paper has proposed an efficient algorithm,which is considered better than related methods,for matching several collaborators(more than two)in KS environment.The method could be deployed in medical field for gene analysis,software organizations for distributed development and academics for knowledge sharing.Originality/value–One sign of strength of this approach,compared to most sequence alignment approaches that can only match two collaborators at a time,is that it can match several collaborators at a faster rate.展开更多
文摘Graph pattern matching(GPM)can be used to mine the key information in graphs.Exact GPM is one of the most commonly used methods among all the GPM-related methods,which aims to exactly find all subgraphs for a given query graph in a data graph.The exact GPM has been widely used in biological data analyses,social network analyses and other fields.In this paper,the applications of the exact GPM were first introduced,and the research progress of the exact GPM was summarized.Then,the related algorithms were introduced in detail,and the experiments on the state-of-the-art exact GPM algorithms were conducted to compare their performance.Based on the experimental results,the applicable scenarios of the algorithms were pointed out.New research opportunities in this area were proposed.
文摘Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Changing Consecutive Characters (PMCCC) to make the searching pro- cess of the algorithm faster. PMCCC enhances the shift process that determines how the pattern moves in case of the occurrence of the mismatch between the pattern and the text. It enhances the Berry Ravindran (BR) shift function by using m consecutive characters where m is the pattern length. The formal basis and the algorithms are presented. The experimental results show that PMCCC made enhancements in searching process by reducing the number of comparisons and the number of attempts. Comparing the results of PMCCC with other related algorithms has shown significant enhancements in average number of comparisons and average number of attempts.
文摘Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.
文摘Modern applications require large databases to be searched for regions that are similar to a given pattern. The DNA sequence analysis, speech and text recognition, artificial intelligence, Internet of Things, and many other applications highly depend on pattern matching or similarity searches. In this paper, we discuss some of the string matching solutions developed in the past. Then, we present a novel mathematical model to search for a given pattern and it’s near approximates in the text.
基金supported by the National Natural Science Foundation of China under grants 62076087&61906059the Program for Changjiang Scholars and Innovative Research Team in University(PCSIRT)of the Ministry of Education of China under grant IRT17R32
文摘The research on graph pattern matching(GPM) has attracted a lot of attention. However, most of the research has focused on complex networks, and there are few researches on GPM in the medical field. Hence, with GPM this paper is to make a breast cancer-oriented diagnosis before the surgery. Technically, this paper has firstly made a new definition of GPM, aiming to explore the GPM in the medical field, especially in Medical Knowledge Graphs(MKGs). Then, in the specific matching process, this paper introduces fuzzy calculation, and proposes a multi-threaded bidirectional routing exploration(M-TBRE) algorithm based on depth first search and a two-way routing matching algorithm based on multi-threading. In addition, fuzzy constraints are introduced in the M-TBRE algorithm, which leads to the Fuzzy-M-TBRE algorithm. The experimental results on the two datasets show that compared with existing algorithms, our proposed algorithm is more efficient and effective.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2021R1A2C1011216)。
文摘In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine environment.The autonomous driving robot continuously detects the wall of the tunnel in the horizontal direction using the light detection and ranging(Li DAR)sensor and performs pattern matching by recognizing the shape of the tunnel wall.The proposed method was designed to measure the heading of the robot by fusion with the inertial measurement units sensor according to the pattern matching accuracy;it is combined with the encoder sensor to estimate the location of the robot.In addition,when the robot is driving,the vertical direction of the underground mine is scanned through the vertical Li DAR sensor and stacked to create a 3D map of the underground mine.The performance of the proposed method was superior to that of previous studies;the mean absolute error achieved was 0.08 m for the X-Y axes.A root mean square error of 0.05 m^(2)was achieved by comparing the tunnel section maps that were created by the autonomous driving robot to those of manual surveying.
文摘String matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that is created and kept by modern computational devices influences researchers to obtain even more powerful methods for coping with this problem. In this research, the Quick Search string matching algorithm are adopted to be implemented under the multi-core environment using OpenMP directive which can be employed to reduce the overall execution time of the program. English text, Proteins and DNA data types are utilized to examine the effect of parallelization and implementation of Quick Search string matching algorithm on multi-core based environment. Experimental outcomes reveal that the overall performance of the mentioned string matching algorithm has been improved, and the improvement in the execution time which has been obtained is considerable enough to recommend the multi-core environment as the suitable platform for parallelizing the Quick Search string matching algorithm.
基金This work was partially supported by the National Key Research and Development Program(No.2018YFB1800203)National Natural Science Foundation of China(No.U19B2024)Postgraduate Scientific Research Innovation Project of Hunan Province(No.CX20210038).
文摘Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal graph association rules(TGARs)that extend traditional graph-pattern association rules in a static graph by incorporating the unique temporal information and constraints.We introduce quality measures(e.g.,support,confidence,and diversification)to characterize meaningful TGARs that are useful and diversified.In addition,the proposed support metric is an upper bound for alternative metrics,allowing us to guarantee a superset of patterns.We extend conventional confidence measures in terms of maximal occurrences of TGARs.The diversification score strikes a balance between interestingness and diversity.Although the problem is NP-hard,we develop an effective discovery algorithm for TGARs that integrates TGARs generation and TGARs selection and shows that mining TGARs is feasible over a temporal graph.We propose pruning strategies to filter TGARs that have low support or cannot make top-k as early as possible.Moreover,we design an auxiliary data structure to prune the TGARs that do not meet the constraints during the TGARs generation process to avoid conducting repeated subgraph matching for each extension in the search space.We experimentally verify the effectiveness,efficiency,and scalability of our algorithms in discovering diversified top-k TGARs from temporal graphs in real-life applications.
基金This work was supported by National Natural Science Foundation of China under Grant(Nos.61771166,61771166,61402137)National Key Research&Development Plan of China under Grant 2016QY05X1000。
文摘Deep Packet Inspection(DPI)at the core of many monitoring appliances,such as NIDS,NIPS,plays a major role.DPI is beneficial to content providers and censorship to monitor network traffic.However,the surge of network traffic has put tremendous pressure on the performance of DPI.In fact,the sensitive content being monitored is only a minority of network traffic,that is to say,most is undesired.A close look at the network traffic,we found that it contains many undesired high frequency content(UHC)that are not monitored.As everyone knows,the key to improve DPI performance is to skip as many useless characters as possible.Nevertheless,researchers generally study the algorithm of skipping useless characters through sensitive content,ignoring the high-frequency non-sensitive content.To fill this gap,in this literature,we design a model,named Fast AC Model with Skipping(FAMS),to quickly skip UHC while scanning traffic.The model consists of a standard AC automaton,where the input traffic is scanned byte-by-byte,and an additional sub-model,which includes a mapping set and UHC matching model.The mapping set is a bridge between the state node of AC and UHC matching model,while the latter is to select a matching function from hash and fingerprint functions.Our experiments show promising results that we achieve a throughput gain of 1.3-2.6 times the original throughput and 1.1-1.3 times Barr’s double path method.
基金financially supported by the National Natural Science Foundation of China(Grant No.31172243)Agricultural Science and Technology Independent Innovation Fund Project[CX(16)1006]of Jiangsu Province,China.
文摘To precisely meet the nutritional requirements of sows during the stages of pregnancy and lactation,a precision feeding system was developed by using the intelligent sow feeder combined with a rule-based expert system and the Internet of Things(IoTs).The model of uncertain knowledge representation was established for inference by using the certainty factor.The daily feeding amount of each sow was calculated by the expert system.An improved pattern matching algorithm Reused Degree Model-RETE(RDM-RETE)was proposed for the decision of daily feeding amount,which sped up inference by optimizing the RETE network topology.A prediction model of daily feeding amount was established by a rule-based expert system and the precision feeding was achieved by an accurate control technology of variable volume.The experimental results demonstrated that the HASH-RDM-RETE algorithm could effectively reduce the network complexity and improve the inference efficiency.The feeding amount decided by the expert system was a logarithmic model,which was consistent with the feeding law of lactating sows.The inferential feeding amount was adopted as the predicted feed intake and the coefficient of correlation between predicted feed intake and actual feed intake was greater than or equal to 0.99.Each sow was fed at different feeding intervals and different feed amounts for each meal in a day.The feed intake was 26.84% higher than that of artificial feeding during lactation days(p<0.05).The piglets weaned per sow per year(PSY)can be increased by 1.51 compared with that of relatively high levels in domestic pig farms.This system is stable in feeding and lowers the breeding cost that can be applied in precision feeding in swine production.
文摘Objectives:Genomic signatures like k-mers have become one of the most prominent approaches to describe genomic data.As a result,myriad real-world applications,such as the construction of de Bruijn graphs in genome assembly,have been benefited by recognizing genomic signatures.In other words,an efficient approachof genomic signatureprofiling is an essential need for tackling high-throughput sequencing reads.However,most of the existing approaches only recognize fixed-size k-merswhile many research studies have shown the importance of considering variable-length k-mers.Methods:In this paper,we present a novel genomic signature profiling approach,TahcoRoll,by extending the Aho–Corasick algorithm(AC)for the task of profiling variable-length k-mers.We first group nucleotides into two clusters and represent each cluster with a bit.The rolling hash technique is further utilized to encode signatures and read patterns for efficient matching.Results:In extensive experiments,TahcoRoll significantly outperforms the most state-of-the-art k-mer counters and has the capability of processing reads across different sequencing platforms on a budget desktop computer.Conclusions:The single-thread version of TahcoRoll is as efficient as the eight-thread version of the state-of-the-art,JellyFish,while the eight-thread TahcoRoll outperforms the eight-thread JellyFish by at least four times.
文摘Packet analysis is very important in our digital life. But what protocol analyzers can do is limited because they can only process data in determined format. This paper puts forward a solution to decode raw data in an unknown format. It is certain that data can be cut into packets because there are usually characteristic bit sequences in packet headers. The key to solve the problem is how to find out those characteristic sequences. We present an efficient way of bit sequence enumeration. Both Aho-Corasick (AC) algorithm and data mining method are used to reduce the cost of the process.
文摘We propose an efficient, specific method for estimating camera parameters from a single starry night image. Such an image consists of a collection of disks representing stars, so traditional estimation methods for common pictures do not work. Our method uses a database, a star catalog, that stores the positions of stars on the celestial sphere. Our method computes magnitudes(i.e., brightnesses) of stars in the input image and uses them to find the corresponding stars in the star catalog. Camera parameters can then be estimated by a simple geometric calculation. Our method is over ten times faster and more accurate than a previous method.
文摘Purpose–Over the past decade,the cost of product development has increased drastically,and this is due to the inability of most enterprises to locate suitable and optimal collaborators for knowledge sharing.Nevertheless,knowledge sharing is a mechanism that helps people find the best collaborators with relevant knowledge.Hence,a new approach for locating optimal collaborators with relevant knowledge is needed,which couldhelp enterprisein reducingcost andtime ina knowledge-sharingenvironment.Thepaper aimsto discuss these issues.Design/methodology/approach–One unique challenge in the domain of knowledge sharing is that collaborators do not possess the same number of events resident in the knowledge available for sharing.In this paper,the authors present a new approach for locating optimal collaborators in knowledge-sharing environment using the combinatorial algorithm(CA-KSE).Findings–The proposed pattern-matching approach implemented in Java is considered efficient for solving the issue peculiar to collaboration in knowledge-sharing domain.The authors benchmarked the proposed approach with its semi-global pairwise alignment and global alignment counterparts through scores comparison and the receiver operating characteristic curve.The results obtained from the comparisons showedthat CA-KSEis a perfect test havinganarea undercurveof 0.9659,comparedto the other approaches.Research limitations/implications–The paper has proposed an efficient algorithm,which is considered better than related methods,for matching several collaborators(more than two)in KS environment.The method could be deployed in medical field for gene analysis,software organizations for distributed development and academics for knowledge sharing.Originality/value–One sign of strength of this approach,compared to most sequence alignment approaches that can only match two collaborators at a time,is that it can match several collaborators at a faster rate.
