In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-ba...In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-based analytical model is presented.The model can be used to compute the expected single-command and dual-command travel time for a storage/retrieval(S/R)machine which can travel simultaneously horizontally and vertically as it moves along a storage aisle.The rack may be either square in time or non square in time.Additionally,the alternative layouts of the AS/RS and travel-time models are examined.Comparing with setting the I/O point at the left-lower corner of the rack,setting the I/O point at any point at the vertical edge can help enhance the efficiency of the AS/RS.展开更多
At present,the polymerase chain reaction(PCR)amplification-based file retrieval method is the mostcommonly used and effective means of DNA file retrieval.The number of orthogonal primers limitsthe number of files that...At present,the polymerase chain reaction(PCR)amplification-based file retrieval method is the mostcommonly used and effective means of DNA file retrieval.The number of orthogonal primers limitsthe number of files that can be accurately accessed,which in turn affects the density in a single oligo poolof digital DNA storage.In this paper,a multi-mode DNA sequence design method based on PCR file retrie-val in a single oligonucleotide pool is proposed for high-capacity DNA data storage.Firstly,by analyzingthe maximum number of orthogonal primers at each predicted primer length,it was found that the rela-tionship between primer length and the maximum available primer number does not increase linearly,and the maximum number of orthogonal primers is on the order of 10^(4).Next,this paper analyzes themaximum address space capacity of DNA sequences with different types of primer binding sites for filemapping.In the case where the capacity of the primer library is R(where R is even),the number ofaddress spaces that can be mapped by the single-primer DNA sequence design scheme proposed in thispaper is four times that of the previous one,and the two-level primer DNA sequence design scheme can reach [R/2·(R/2-1)]^(2)times.Finally,a multi-mode DNA sequence generation method is designed based onthe number of files to be stored in the oligonucleotide pool,in order to meet the requirements of the ran-dom retrieval of target files in an oligonucleotide pool with large-scale file numbers.The performance ofthe primers generated by the orthogonal primer library generator proposed in this paper is verified,andthe average Gibbs free energy of the most stable heterodimer formed between the orthogonal primersproduced is−1 kcal·(mol·L^(−1))^(−1)(1 kcal=4.184 kJ).At the same time,by selectively PCR-amplifying theDNA sequences of the two-level primer binding sites for random access,the target sequence can be accu-rately read with a minimum of 10^(3) reads,when the primer binding site sequences at different positionsare mutually different.This paper provides a pipeline for orthogonal primer library generation and multi-mode mapping schemes between files and primers,which can help achieve precise random access to filesin large-scale DNA oligo pools.展开更多
E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking d...E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.展开更多
The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment suc...The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.展开更多
Firstly, the definition, structure and working principles of storage batteries in automatic meteorological observation stations were stated simply, and then the daily maintenance of the storage batteries were introduc...Firstly, the definition, structure and working principles of storage batteries in automatic meteorological observation stations were stated simply, and then the daily maintenance of the storage batteries were introduced according to previous practical experience, finally typical faults of storage batteries were analyzed. Practical evidence shows that timely external maintenance and enough supply of electrolyte can greatly extend the lifespan of storage batteries.展开更多
Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the securi...Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the security of cloud data, how to increase data availability and how to improve user privacy perception are the key issues of cloud storage research, especially when the cloud service provider is not completely trusted. In this paper, a cloud storage ciphertext retrieval scheme based on AES and homomorphic encryption is presented. This ciphertext retrieval scheme will not only conceal the user retrieval information, but also prevent the cloud from obtaining user access pattern such as read-write mode, and access frequency, thereby ensuring the safety of the ciphertext retrieval and user privacy. The results of simulation analysis show that the performance of this ciphertext retrieval scheme requires less overhead than other schemes on the same security level.展开更多
In order to bridge the semantic gap exists in image retrieval, this paper propose an approach combining generative and discriminative learning to accomplish the task of automatic image annotation and retrieval. We fir...In order to bridge the semantic gap exists in image retrieval, this paper propose an approach combining generative and discriminative learning to accomplish the task of automatic image annotation and retrieval. We firstly present continuous probabilistic latent semantic analysis (PLSA) to model continuous quantity. Furthermore, we propose a hybrid framework which employs continuous PLSA to model visual features of images in generative learning stage and uses ensembles of classifier chains to classify the multi-label data in discriminative learning stage. Since the framework combines the advantages of generative and discriminative learning, it can predict semantic annotation precisely for unseen images. Finally, we conduct a series of experiments on a standard Corel dataset. The experiment results show that our approach outperforms many state-of-the-art approaches.展开更多
At present,the traditional blockchain for data storage and retrieval reflects the characteristics of slow data uploading speed,high cost,and transparency,and there are a lot of corresponding problems,such as not suppo...At present,the traditional blockchain for data storage and retrieval reflects the characteristics of slow data uploading speed,high cost,and transparency,and there are a lot of corresponding problems,such as not supporting private data storage,large data operation costs,and not supporting Data field query.This paper proposes a method of data encryption storage and retrieval based on the IOTA distributed ledger,combined with the fast transaction processing speed and zero-value transactions of the IOTA blockchain,through the Masked Authenticated Messaging technology,so that the data is encrypted in the data stream.The form is stored in the distributed ledger,quickly retrieved through the field index mechanism established by the data form,and the data operation is carried out on the chain.Experimental results show that this system has high storage,encryption and retrieval performance,and good practicability.展开更多
Objectives:The aim of this study was to investigate and develop a data storage and exchange format for the process of automatic systematic reviews(ASR)of traditional Chinese medicine(TCM).Methods:A lightweight and com...Objectives:The aim of this study was to investigate and develop a data storage and exchange format for the process of automatic systematic reviews(ASR)of traditional Chinese medicine(TCM).Methods:A lightweight and commonly used data format,namely,JavaScript Object Notation(JSON),was introduced in this study.We designed a fully described data structure to collect TCM clinical trial information based on the JSON syntax.Results:A smart and powerful data format,JSON-ASR,was developed.JSON-ASR uses a plain-text data format in the form of key/value pairs and consists of six sections and more than 80 preset pairs.JSON-ASR adopts extensible structured arrays to support the situations of multi-groups and multi-outcomes.Conclusion:JSON-ASR has the characteristics of light weight,flexibility,and good scalability,which is suitable for the complex data of clinical evidence.展开更多
Geothermal resources are efficient,renewable and clean energy sources,and their reservoirs are usually closely associated with high-temperature regions of the land surface.Current exploration methods primarily involve...Geothermal resources are efficient,renewable and clean energy sources,and their reservoirs are usually closely associated with high-temperature regions of the land surface.Current exploration methods primarily involve migrating traditional geological techniques,which fail to fully use the unique features of geothermal radiation characteristics.Thermal infrared remote-sensing imaging technology can capture and present areas with distinctive surface thermal radiation features,providing considerable significance as a guide for localization prior tofield exploration.In this study,we propose a deep learningebased method for intelligently identifying and segmenting geothermal radiation sources from thermal infrared remote-sensing images,including data preparation and model training.To improve the localization drift and anomalous interference caused by the high complexity of the Earth's surface environment,this study uses a surface temperature retrieval algorithm to calculate the land surface temperature in the research area.The retrieval results are used to train the semantic segmentation model.In addition,a pixel-level geothermal spatial segmentation network(PGSSNet)is proposed to suppress the diffuse thermal radiation and reduce the broad and blurred white areas of images to exact locations.Once the training is completed,the model directly segments and extracts the actual range of thermal radiation sources from subsequent thermal infrared remote-sensing images without temperature retrieval and/or manual calibration.展开更多
The vigorous development of grid side energy storage power generation has brought unprecedented development opportunities. However, with a large number of centralized and distributed energy storage power stations conn...The vigorous development of grid side energy storage power generation has brought unprecedented development opportunities. However, with a large number of centralized and distributed energy storage power stations connected to the power grid, it will also have certain impact on the stable operation of the power grid and the power quality. In order to meet the testing requirements of AGC control management system for grid side energy storage monitoring, an automatic testing system with flexible configuration, complete functions, simple use and convenient operation is proposed in this paper.展开更多
We propose a new approach to store and query XML data in an RDBMS basing on the idea of the numbering scheme and inverted list. O ur approach allows us to quickly determine the precedence, sibling and ancestor/ desc...We propose a new approach to store and query XML data in an RDBMS basing on the idea of the numbering scheme and inverted list. O ur approach allows us to quickly determine the precedence, sibling and ancestor/ descendant relationships between any pair of nodes in the hierarchy of XML, and utilize path index to speed up calculating of path expressions. Examples have de monstrated that our approach can effectively and efficiently support both XQuery queries and keyword searches. Our approach is also flexible enough to support X ML documents both with Schema and without Schema, and applications both retrieva l and update. We also present the architecture of middleware for application acc essing XML documents stored in relations, and an algorithm translating a given X ML document into relations effectively.展开更多
Ciphertext data retrieval in cloud databases suffers from some critical limitations,such as inadequate security measures,disorganized key management practices,and insufficient retrieval access control capabilities.To ...Ciphertext data retrieval in cloud databases suffers from some critical limitations,such as inadequate security measures,disorganized key management practices,and insufficient retrieval access control capabilities.To address these problems,this paper proposes an enhanced Fully Homomorphic Encryption(FHE)algorithm based on an improved DGHV algorithm,coupled with an optimized ciphertext retrieval scheme.Our specific contributions are outlined as follows:First,we employ an authorization code to verify the user’s retrieval authority and perform hierarchical access control on cloud storage data.Second,a triple-key encryption mechanism,which separates the data encryption key,retrieval authorization key,and retrieval key,is designed.Different keys are provided to different entities to run corresponding system functions.The key separation architecture proves particularly advantageous in multi-verifier coexistence scenarios,environments involving untrusted third-party retrieval services.Finally,the enhanced DGHV-based retrieval mechanism extends conventional functionality by enabling multi-keyword queries with similarity-ranked results,thereby significantly improving both the functionality and usability of the FHE system.展开更多
In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically ...In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically adjust the frequency regulation command based on the state of charge(SoC)of energy storage units,this paper proposes a secondary frequency regulation control strategy based on variable integral coefficients for multiple energy storage units.First,a power-uniform controller is designed to ensure that thermal power units gradually take on more regulation power during the frequency regulation process.Next,a control framework based on variable integral coefficients is proposed within the secondary frequency regulation model,along with an objective function that simultaneously considers both Automatic Generation Control(AGC)command tracking performance and SoC recovery requirements of energy storage units.Finally,a gradient descent optimization method is used to dynamically adjust the gain of the energy storage integral controller,allowingmultiple energy storage units to respond in real-time to AGC instructions and SoC variations.Simulation results confirmthe effectiveness of the proposedmethod.Compared to traditional strategies,the proposed approach takes into account the SoCdiscrepancies amongmultiple energy storage units and the duration of system net power imbalances.It successfully implements secondary frequency regulation while achieving dynamic power allocation among the units.展开更多
In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficie...In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficient and effective searching environment for users to query their images more easily. In this paper,a semi-supervised learning based probabilistic latent semantic analysis( PLSA) model for automatic image annotation is presenred. Since it's often hard to obtain or create labeled images in large quantities while unlabeled ones are easier to collect,a transductive support vector machine( TSVM) is exploited to enhance the quality of the training image data. Then,different image features with different magnitudes will result in different performance for automatic image annotation. To this end,a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible. Finally,a PLSA model with asymmetric modalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores. Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PLSA for the task of automatic image annotation.展开更多
A novel image auto-annotation method is presented based on probabilistic latent semantic analysis(PLSA) model and multiple Markov random fields(MRF).A PLSA model with asymmetric modalities is first constructed to esti...A novel image auto-annotation method is presented based on probabilistic latent semantic analysis(PLSA) model and multiple Markov random fields(MRF).A PLSA model with asymmetric modalities is first constructed to estimate the joint probability between images and semantic concepts,then a subgraph is extracted served as the corresponding structure of Markov random fields and inference over it is performed by the iterative conditional modes so as to capture the final annotation for the image.The novelty of our method mainly lies in two aspects:exploiting PLSA to estimate the joint probability between images and semantic concepts as well as multiple MRF to further explore the semantic context among keywords for accurate image annotation.To demonstrate the effectiveness of this approach,an experiment on the Corel5 k dataset is conducted and its results are compared favorably with the current state-of-the-art approaches.展开更多
In this paper, we propose a dynamic multi-descriptor fusion （DMDF） approach to improving the retrieval accuracy of 3-dimensional （3D） model retrieval systems. First, an independent retrieval list is generated by u...In this paper, we propose a dynamic multi-descriptor fusion （DMDF） approach to improving the retrieval accuracy of 3-dimensional （3D） model retrieval systems. First, an independent retrieval list is generated by using each individual descriptor. Second, we propose an automatic relevant/irrelevant models selection （ARMS） approach to selecting the relevant and irrelevant 3D models automatically without any user interaction. A weighted distance, in which the weight associated with each individual descriptor is learnt by using the selected relevant and irrelevant models, is used to measure the similarity between two 3D models. Furthermore, a descriptor-dependent adaptive query point movement （AQPM） approach is employed to update every feature vector. This set of new feature vectors is used to index 3D models in the next search process. Four 3D model databases are used to compare the retrieval accuracy of our proposed DMDF approach with several descriptors as well as some well-known information fusion methods. Experimental results have shown that our proposed DMDF approach provides a promising retrieval result and always yields the best retrieval accuracy.展开更多
The knowledge graph with relational abundant information has been widely used as the basic data support for the retrieval platforms.Image and text descriptions added to the knowledge graph enrich the node information,...The knowledge graph with relational abundant information has been widely used as the basic data support for the retrieval platforms.Image and text descriptions added to the knowledge graph enrich the node information,which accounts for the advantage of the multi-modal knowledge graph.In the field of cross-modal retrieval platforms,multi-modal knowledge graphs can help to improve retrieval accuracy and efficiency because of the abundant relational infor-mation provided by knowledge graphs.The representation learning method is sig-nificant to the application of multi-modal knowledge graphs.This paper proposes a distributed collaborative vector retrieval platform(DCRL-KG)using the multi-modal knowledge graph VisualSem as the foundation to achieve efficient and high-precision multimodal data retrieval.Firstly,use distributed technology to classify and store the data in the knowledge graph to improve retrieval efficiency.Secondly,this paper uses BabelNet to expand the knowledge graph through multi-ple filtering processes and increase the diversification of information.Finally,this paper builds a variety of retrieval models to achieve the fusion of retrieval results through linear combination methods to achieve high-precision language retrieval and image retrieval.The paper uses sentence retrieval and image retrieval experi-ments to prove that the platform can optimize the storage structure of the multi-modal knowledge graph and have good performance in multi-modal space.展开更多
This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Mul...This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Multiple input/output-points are located at the bottom of the racks. The stacker cranes transport bins between the input/output-points and cells on the racks to complete requests generated over time. Each request should be accomplished within its response time. The objective is to minimize the time by which all the generated requests are completed. Under a given physical layout, the authors study the complexity of the problem and design on-line algorithms for both one-stacker-crane model and two-stacker-crane model. The algorithms axe validated by instances and numerical simulations.展开更多
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-based analytical model is presented.The model can be used to compute the expected single-command and dual-command travel time for a storage/retrieval(S/R)machine which can travel simultaneously horizontally and vertically as it moves along a storage aisle.The rack may be either square in time or non square in time.Additionally,the alternative layouts of the AS/RS and travel-time models are examined.Comparing with setting the I/O point at the left-lower corner of the rack,setting the I/O point at any point at the vertical edge can help enhance the efficiency of the AS/RS.
基金supported by the fund from Tianjin Municipal Science and Technology Bureau(22JCYBJC01390).
文摘At present,the polymerase chain reaction(PCR)amplification-based file retrieval method is the mostcommonly used and effective means of DNA file retrieval.The number of orthogonal primers limitsthe number of files that can be accurately accessed,which in turn affects the density in a single oligo poolof digital DNA storage.In this paper,a multi-mode DNA sequence design method based on PCR file retrie-val in a single oligonucleotide pool is proposed for high-capacity DNA data storage.Firstly,by analyzingthe maximum number of orthogonal primers at each predicted primer length,it was found that the rela-tionship between primer length and the maximum available primer number does not increase linearly,and the maximum number of orthogonal primers is on the order of 10^(4).Next,this paper analyzes themaximum address space capacity of DNA sequences with different types of primer binding sites for filemapping.In the case where the capacity of the primer library is R(where R is even),the number ofaddress spaces that can be mapped by the single-primer DNA sequence design scheme proposed in thispaper is four times that of the previous one,and the two-level primer DNA sequence design scheme can reach [R/2·(R/2-1)]^(2)times.Finally,a multi-mode DNA sequence generation method is designed based onthe number of files to be stored in the oligonucleotide pool,in order to meet the requirements of the ran-dom retrieval of target files in an oligonucleotide pool with large-scale file numbers.The performance ofthe primers generated by the orthogonal primer library generator proposed in this paper is verified,andthe average Gibbs free energy of the most stable heterodimer formed between the orthogonal primersproduced is−1 kcal·(mol·L^(−1))^(−1)(1 kcal=4.184 kJ).At the same time,by selectively PCR-amplifying theDNA sequences of the two-level primer binding sites for random access,the target sequence can be accu-rately read with a minimum of 10^(3) reads,when the primer binding site sequences at different positionsare mutually different.This paper provides a pipeline for orthogonal primer library generation and multi-mode mapping schemes between files and primers,which can help achieve precise random access to filesin large-scale DNA oligo pools.
文摘E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.
基金supported by Theoretical study of power system synergistic dispatch National Science Foundation of China(51477091).
文摘The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.
文摘Firstly, the definition, structure and working principles of storage batteries in automatic meteorological observation stations were stated simply, and then the daily maintenance of the storage batteries were introduced according to previous practical experience, finally typical faults of storage batteries were analyzed. Practical evidence shows that timely external maintenance and enough supply of electrolyte can greatly extend the lifespan of storage batteries.
基金the National Natural Science Foundation of China under Grant，the Fundamental Research Funds for the Central Universities under Grant No.FRF-TP-14-046A2
文摘Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the security of cloud data, how to increase data availability and how to improve user privacy perception are the key issues of cloud storage research, especially when the cloud service provider is not completely trusted. In this paper, a cloud storage ciphertext retrieval scheme based on AES and homomorphic encryption is presented. This ciphertext retrieval scheme will not only conceal the user retrieval information, but also prevent the cloud from obtaining user access pattern such as read-write mode, and access frequency, thereby ensuring the safety of the ciphertext retrieval and user privacy. The results of simulation analysis show that the performance of this ciphertext retrieval scheme requires less overhead than other schemes on the same security level.
文摘In order to bridge the semantic gap exists in image retrieval, this paper propose an approach combining generative and discriminative learning to accomplish the task of automatic image annotation and retrieval. We firstly present continuous probabilistic latent semantic analysis (PLSA) to model continuous quantity. Furthermore, we propose a hybrid framework which employs continuous PLSA to model visual features of images in generative learning stage and uses ensembles of classifier chains to classify the multi-label data in discriminative learning stage. Since the framework combines the advantages of generative and discriminative learning, it can predict semantic annotation precisely for unseen images. Finally, we conduct a series of experiments on a standard Corel dataset. The experiment results show that our approach outperforms many state-of-the-art approaches.
基金supported by the National Key Research and Development Program“Biological Information Security and Efficient Transmission”Project,Project Letter No.2017YFC1201204.
文摘At present,the traditional blockchain for data storage and retrieval reflects the characteristics of slow data uploading speed,high cost,and transparency,and there are a lot of corresponding problems,such as not supporting private data storage,large data operation costs,and not supporting Data field query.This paper proposes a method of data encryption storage and retrieval based on the IOTA distributed ledger,combined with the fast transaction processing speed and zero-value transactions of the IOTA blockchain,through the Masked Authenticated Messaging technology,so that the data is encrypted in the data stream.The form is stored in the distributed ledger,quickly retrieved through the field index mechanism established by the data form,and the data operation is carried out on the chain.Experimental results show that this system has high storage,encryption and retrieval performance,and good practicability.
基金the National Key R&D Program of China(Grant no.2019YFC1709803)National Natural Science Foundation of China(Grant no.81873183).
文摘Objectives:The aim of this study was to investigate and develop a data storage and exchange format for the process of automatic systematic reviews(ASR)of traditional Chinese medicine(TCM).Methods:A lightweight and commonly used data format,namely,JavaScript Object Notation(JSON),was introduced in this study.We designed a fully described data structure to collect TCM clinical trial information based on the JSON syntax.Results:A smart and powerful data format,JSON-ASR,was developed.JSON-ASR uses a plain-text data format in the form of key/value pairs and consists of six sections and more than 80 preset pairs.JSON-ASR adopts extensible structured arrays to support the situations of multi-groups and multi-outcomes.Conclusion:JSON-ASR has the characteristics of light weight,flexibility,and good scalability,which is suitable for the complex data of clinical evidence.
基金supported by National Natural Science Foundation(NNSF)of China under Grant 41927801.
文摘Geothermal resources are efficient,renewable and clean energy sources,and their reservoirs are usually closely associated with high-temperature regions of the land surface.Current exploration methods primarily involve migrating traditional geological techniques,which fail to fully use the unique features of geothermal radiation characteristics.Thermal infrared remote-sensing imaging technology can capture and present areas with distinctive surface thermal radiation features,providing considerable significance as a guide for localization prior tofield exploration.In this study,we propose a deep learningebased method for intelligently identifying and segmenting geothermal radiation sources from thermal infrared remote-sensing images,including data preparation and model training.To improve the localization drift and anomalous interference caused by the high complexity of the Earth's surface environment,this study uses a surface temperature retrieval algorithm to calculate the land surface temperature in the research area.The retrieval results are used to train the semantic segmentation model.In addition,a pixel-level geothermal spatial segmentation network(PGSSNet)is proposed to suppress the diffuse thermal radiation and reduce the broad and blurred white areas of images to exact locations.Once the training is completed,the model directly segments and extracts the actual range of thermal radiation sources from subsequent thermal infrared remote-sensing images without temperature retrieval and/or manual calibration.
文摘The vigorous development of grid side energy storage power generation has brought unprecedented development opportunities. However, with a large number of centralized and distributed energy storage power stations connected to the power grid, it will also have certain impact on the stable operation of the power grid and the power quality. In order to meet the testing requirements of AGC control management system for grid side energy storage monitoring, an automatic testing system with flexible configuration, complete functions, simple use and convenient operation is proposed in this paper.
文摘We propose a new approach to store and query XML data in an RDBMS basing on the idea of the numbering scheme and inverted list. O ur approach allows us to quickly determine the precedence, sibling and ancestor/ descendant relationships between any pair of nodes in the hierarchy of XML, and utilize path index to speed up calculating of path expressions. Examples have de monstrated that our approach can effectively and efficiently support both XQuery queries and keyword searches. Our approach is also flexible enough to support X ML documents both with Schema and without Schema, and applications both retrieva l and update. We also present the architecture of middleware for application acc essing XML documents stored in relations, and an algorithm translating a given X ML document into relations effectively.
基金supported by the Innovation Program for Quantum Science and technology(2021ZD0301300)supported by the Fundamental Research Funds for the Central Universities(Nos.3282024046,3282024052,3282024058,3282023017).
文摘Ciphertext data retrieval in cloud databases suffers from some critical limitations,such as inadequate security measures,disorganized key management practices,and insufficient retrieval access control capabilities.To address these problems,this paper proposes an enhanced Fully Homomorphic Encryption(FHE)algorithm based on an improved DGHV algorithm,coupled with an optimized ciphertext retrieval scheme.Our specific contributions are outlined as follows:First,we employ an authorization code to verify the user’s retrieval authority and perform hierarchical access control on cloud storage data.Second,a triple-key encryption mechanism,which separates the data encryption key,retrieval authorization key,and retrieval key,is designed.Different keys are provided to different entities to run corresponding system functions.The key separation architecture proves particularly advantageous in multi-verifier coexistence scenarios,environments involving untrusted third-party retrieval services.Finally,the enhanced DGHV-based retrieval mechanism extends conventional functionality by enabling multi-keyword queries with similarity-ranked results,thereby significantly improving both the functionality and usability of the FHE system.
文摘In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically adjust the frequency regulation command based on the state of charge(SoC)of energy storage units,this paper proposes a secondary frequency regulation control strategy based on variable integral coefficients for multiple energy storage units.First,a power-uniform controller is designed to ensure that thermal power units gradually take on more regulation power during the frequency regulation process.Next,a control framework based on variable integral coefficients is proposed within the secondary frequency regulation model,along with an objective function that simultaneously considers both Automatic Generation Control(AGC)command tracking performance and SoC recovery requirements of energy storage units.Finally,a gradient descent optimization method is used to dynamically adjust the gain of the energy storage integral controller,allowingmultiple energy storage units to respond in real-time to AGC instructions and SoC variations.Simulation results confirmthe effectiveness of the proposedmethod.Compared to traditional strategies,the proposed approach takes into account the SoCdiscrepancies amongmultiple energy storage units and the duration of system net power imbalances.It successfully implements secondary frequency regulation while achieving dynamic power allocation among the units.
基金Supported by the National Program on Key Basic Research Project(No.2013CB329502)the National Natural Science Foundation of China(No.61202212)+1 种基金the Special Research Project of the Educational Department of Shaanxi Province of China(No.15JK1038)the Key Research Project of Baoji University of Arts and Sciences(No.ZK16047)
文摘In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficient and effective searching environment for users to query their images more easily. In this paper,a semi-supervised learning based probabilistic latent semantic analysis( PLSA) model for automatic image annotation is presenred. Since it's often hard to obtain or create labeled images in large quantities while unlabeled ones are easier to collect,a transductive support vector machine( TSVM) is exploited to enhance the quality of the training image data. Then,different image features with different magnitudes will result in different performance for automatic image annotation. To this end,a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible. Finally,a PLSA model with asymmetric modalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores. Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PLSA for the task of automatic image annotation.
基金Supported by the National Basic Research Priorities Program(No.2013CB329502)the National High-tech R&D Program of China(No.2012AA011003)+1 种基金National Natural Science Foundation of China(No.61035003,61072085,60933004,60903141)the National Scienceand Technology Support Program of China(No.2012BA107B02)
文摘A novel image auto-annotation method is presented based on probabilistic latent semantic analysis(PLSA) model and multiple Markov random fields(MRF).A PLSA model with asymmetric modalities is first constructed to estimate the joint probability between images and semantic concepts,then a subgraph is extracted served as the corresponding structure of Markov random fields and inference over it is performed by the iterative conditional modes so as to capture the final annotation for the image.The novelty of our method mainly lies in two aspects:exploiting PLSA to estimate the joint probability between images and semantic concepts as well as multiple MRF to further explore the semantic context among keywords for accurate image annotation.To demonstrate the effectiveness of this approach,an experiment on the Corel5 k dataset is conducted and its results are compared favorably with the current state-of-the-art approaches.
基金supported in part by“MOST”under Grants No.102-2632-E-216-001-MY3 and No.104-2221-E-216-010-MY2
文摘In this paper, we propose a dynamic multi-descriptor fusion （DMDF） approach to improving the retrieval accuracy of 3-dimensional （3D） model retrieval systems. First, an independent retrieval list is generated by using each individual descriptor. Second, we propose an automatic relevant/irrelevant models selection （ARMS） approach to selecting the relevant and irrelevant 3D models automatically without any user interaction. A weighted distance, in which the weight associated with each individual descriptor is learnt by using the selected relevant and irrelevant models, is used to measure the similarity between two 3D models. Furthermore, a descriptor-dependent adaptive query point movement （AQPM） approach is employed to update every feature vector. This set of new feature vectors is used to index 3D models in the next search process. Four 3D model databases are used to compare the retrieval accuracy of our proposed DMDF approach with several descriptors as well as some well-known information fusion methods. Experimental results have shown that our proposed DMDF approach provides a promising retrieval result and always yields the best retrieval accuracy.
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(2016DX GJMS15)+1 种基金Weihai Scientific Research and Innovation Fund(2020)Key Research and Development Program in Shandong Provincial(2017GGX90103).
文摘The knowledge graph with relational abundant information has been widely used as the basic data support for the retrieval platforms.Image and text descriptions added to the knowledge graph enrich the node information,which accounts for the advantage of the multi-modal knowledge graph.In the field of cross-modal retrieval platforms,multi-modal knowledge graphs can help to improve retrieval accuracy and efficiency because of the abundant relational infor-mation provided by knowledge graphs.The representation learning method is sig-nificant to the application of multi-modal knowledge graphs.This paper proposes a distributed collaborative vector retrieval platform(DCRL-KG)using the multi-modal knowledge graph VisualSem as the foundation to achieve efficient and high-precision multimodal data retrieval.Firstly,use distributed technology to classify and store the data in the knowledge graph to improve retrieval efficiency.Secondly,this paper uses BabelNet to expand the knowledge graph through multi-ple filtering processes and increase the diversification of information.Finally,this paper builds a variety of retrieval models to achieve the fusion of retrieval results through linear combination methods to achieve high-precision language retrieval and image retrieval.The paper uses sentence retrieval and image retrieval experi-ments to prove that the platform can optimize the storage structure of the multi-modal knowledge graph and have good performance in multi-modal space.
基金supported by the National Natural Science Foundation of China under Grant No.11371137Research Fund for the Doctoral Program of China under Grant No.20120074110021
文摘This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Multiple input/output-points are located at the bottom of the racks. The stacker cranes transport bins between the input/output-points and cells on the racks to complete requests generated over time. Each request should be accomplished within its response time. The objective is to minimize the time by which all the generated requests are completed. Under a given physical layout, the authors study the complexity of the problem and design on-line algorithms for both one-stacker-crane model and two-stacker-crane model. The algorithms axe validated by instances and numerical simulations.
