Due to the various performance requirements and data access restrictions of different types of real-time transactions, concurrency control protocols which had been designed for the systems with single type of transact...Due to the various performance requirements and data access restrictions of different types of real-time transactions, concurrency control protocols which had been designed for the systems with single type of transactions are not sufficient for mixed real-time database systems (MRTDBS), where different types of real-time transactions coexist in the systems concurrently. In this paper, a new concurrency control protocol MRTT_CC for mixed real-time transactions is proposed. The new strategy integrates with different concurrency control protocols to meet the deadline requirements of different types of real-time transactions. The data similarity concept is also explored in the new protocol to reduce the blocking time of soft real-time transactions, which increases their chances to meet the deadlines. Simulation experiments show that the new protocol has gained good performance.展开更多
Published:18 July 2025 The published article titled“Knockdown of REV7 Inhibits Breast Cancer Cell Migration and Invasion”has been retracted from Oncology Research,Vol.24,No.5,2016,pp.315–325.DOI:10.3727/096504016X1...Published:18 July 2025 The published article titled“Knockdown of REV7 Inhibits Breast Cancer Cell Migration and Invasion”has been retracted from Oncology Research,Vol.24,No.5,2016,pp.315–325.DOI:10.3727/096504016X14666990347590 URL:https://www.techscience.com/or/v24n5/56980.Following the publication,concerns have been raised about a number of figures in this article.An unexpected area of similarity was identified in terms of the cellular data,where the results from differently performed experiments were intended to have been shown,although the areas immediately surrounding this area featured comparatively different distributions of cells.In addition,the western blots in this article were presented with atypical,unusually shaped and possibly anomalous protein bands in many cases.展开更多
The published article titled“UCA1 Regulates the Growth and Metastasis of Pancreatic Cancer by Sponging miR-135a”has been retracted from Oncology Research,Vol.25,No.9,2017,pp.1529–1541.DOI:10.3727/096504017X14888987...The published article titled“UCA1 Regulates the Growth and Metastasis of Pancreatic Cancer by Sponging miR-135a”has been retracted from Oncology Research,Vol.25,No.9,2017,pp.1529–1541.DOI:10.3727/096504017X14888987683152 URL:https://www.techscience.com/or/v25n9/56938 Following the publication,concerns have been raised about a number of figures in this article.An unexpected area of similarity was identified in terms of the cellular data,where the results from differently performed experiments were intended to have been shown,although the areas immediately surrounding this area featured comparatively different distributions of cells.展开更多
In this paper, we target a similarity search among data supply chains, which plays an essential role in optimizing the supply chain and extending its value. This problem is very challenging for application-oriented da...In this paper, we target a similarity search among data supply chains, which plays an essential role in optimizing the supply chain and extending its value. This problem is very challenging for application-oriented data supply chains because the high complexity of the data supply chain makes the computation of similarity extremely complex and inefficient. In this paper, we propose a feature space representation model based on key points,which can extract the key features from the subsequences of the original data supply chain and simplify it into a feature vector form. Then, we formulate the similarity computation of the subsequences based on the multiscale features. Further, we propose an improved hierarchical clustering algorithm for a similarity search over the data supply chains. The main idea is to separate the subsequences into disjoint groups such that each group meets one specific clustering criteria; thus, the cluster containing the query object is the similarity search result. The experimental results show that the proposed approach is both effective and efficient for data supply chain retrieval.展开更多
Information on the population distribution at the building scale can help governments make supplemental decisions to address complex urban management issues.However,the discontinuity and strong spatial heterogeneity o...Information on the population distribution at the building scale can help governments make supplemental decisions to address complex urban management issues.However,the discontinuity and strong spatial heterogeneity of research units at the building scale make it challenging to fuse multi-source geographic data,which causes significant errors in population estimation.To address this problem,this study proposes a method for population estimation at the building scale based on Dual-Environment Feature Fusion(DEFF).The dual environments of buildings were constructed by splitting the physical boundaries and extracting features suitable for the dual-environment scale from multi-source geographic data to describe the complex environmental features of buildings.Meanwhile,Data Quality Weighting based Technique for Order of Preference by Similarity to Ideal Solution(DQW-TOPSIS)method was proposed to assign appropriate weights to the features of the external environment for better feature fusion.Finally,a regression model was established using dual-environment features for building-scale population estimation.The experimental areas chosen for this study were Jianghan and Wuchang Districts,both located in Wuhan City,China.The estimated results of the DEFF were compared with those of the ablation experiments,as well as three publicly accessible population datasets,specifically LandScan,WorldPop,and GHS-POP,at the community scale.The evaluation results showed that DEFF had an R2 of approximately 0.8,Mean Absolute Error(MAE)of approximately 1200,Root Mean Square Error(RMSE)of approximately 1700,and both Mean Absolute Percentage Error(MAPE)and Symmetric Mean Absolute Percentage Error(SMAPE)of approximately 26%,indicating an improved performance and verifying the validity of the proposed method for fine-scale population estimation.展开更多
Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data.However,data interlinking,which is the most valuable contribution of Linke...Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data.However,data interlinking,which is the most valuable contribution of Linked Data,remains incomplete and inaccurate.This study proposes a multidimensional and quantitative interlinking approach for Linked Data in the geospatial domain.According to the characteristics and roles of geospatial data in data discovery,eight elementary data characteristics are adopted as data interlinking types.These elementary characteristics are further combined to form compound and overall data interlinking types.Each data interlinking type possesses one specific predicate to indicate the actual relationship of Linked Data and uses data similarity to represent the correlation degree quantitatively.Therefore,geospatial data interlinking can be expressed by a directed edge associated with a relation predicate and a similarity value.The approach transforms existing simple and qualitative geospatial data interlinking into complete and quantitative interlinking and promotes the establishment of high-quality and trusted Linked Geospatial Data.The approach is applied to build data intra-links in the Chinese National Earth System Scientific Data Sharing Network(NSTI-GEO)and data-links in NSTI-GEO with the Chinese Meteorological Data Network and National Population and Health Scientific Data Sharing Platform.展开更多
Machine learning has been widely applied in well logging formation evaluation studies.However,several challenges negatively impacted the generalization capabilities of machine learning models in practical imple-mentat...Machine learning has been widely applied in well logging formation evaluation studies.However,several challenges negatively impacted the generalization capabilities of machine learning models in practical imple-mentations,such as the mismatch of data domain between training and testing datasets,imbalances among sample categories,and inadequate representation of data model.These issues have led to substantial insufficient identification for reservoir and significant deviations in subsequent evaluations.To improve the transferability of machine learning models within limited sample sets,this study proposes a weight transfer learning framework based on the similarity of the labels.The similarity weighting method includes both hard weights and soft weights.By evaluating the similarity between test and training sets of logging data,the similarity results are used to estimate the weights of training samples,thereby optimizing the model learning process.We develop a double experts’network and a bidirectional gated neural network based on hierarchical attention and multi-head attention(BiGRU-MHSA)for well logs reconstruction and lithofacies classification tasks.Oil field data results for the shale strata in the Gulong area of the Songliao Basin of China indicate that the double experts’network model performs well in curve reconstruction tasks.However,it may not be effective in lithofacies classification tasks,while BiGRU-MHSA performs well in that area.In the study of constructing large-scale well logging processing and formation interpretation models,it is maybe more beneficial by employing different expert models for combined evaluations.In addition,although the improvement is limited,hard or soft weighting methods is better than unweighted(i.e.,average-weighted)in significantly different adjacent wells.The code and data are open and available for subsequent studies on other lithofacies layers.展开更多
Clustering is perhaps one of the most widely used tools for microarray data analysis. Proposed roles for genes of unknown function are inferred from clusters of genes similarity expressed across many biological condit...Clustering is perhaps one of the most widely used tools for microarray data analysis. Proposed roles for genes of unknown function are inferred from clusters of genes similarity expressed across many biological conditions. However, whether function annotation by similarity metrics is reliable or not and to what extent the similarity in gene expression patterns is useful for annotation of gene functions, has not been evaluated. This paper made a comprehensive research on the correlation between the similarity of expression data and of gene functions using Gene Ontology. It has been found that although the similarity in expression patterns and the similarity in gene functions are significantly dependent on each other, this association is rather weak. In addition, among the three categories of Gene Ontology, the similarity of expression data is more useful for cellular component annotation than for biological process and molecular function. The results presented are interesting for the gene functions prediction research area.展开更多
文摘Due to the various performance requirements and data access restrictions of different types of real-time transactions, concurrency control protocols which had been designed for the systems with single type of transactions are not sufficient for mixed real-time database systems (MRTDBS), where different types of real-time transactions coexist in the systems concurrently. In this paper, a new concurrency control protocol MRTT_CC for mixed real-time transactions is proposed. The new strategy integrates with different concurrency control protocols to meet the deadline requirements of different types of real-time transactions. The data similarity concept is also explored in the new protocol to reduce the blocking time of soft real-time transactions, which increases their chances to meet the deadlines. Simulation experiments show that the new protocol has gained good performance.
文摘Published:18 July 2025 The published article titled“Knockdown of REV7 Inhibits Breast Cancer Cell Migration and Invasion”has been retracted from Oncology Research,Vol.24,No.5,2016,pp.315–325.DOI:10.3727/096504016X14666990347590 URL:https://www.techscience.com/or/v24n5/56980.Following the publication,concerns have been raised about a number of figures in this article.An unexpected area of similarity was identified in terms of the cellular data,where the results from differently performed experiments were intended to have been shown,although the areas immediately surrounding this area featured comparatively different distributions of cells.In addition,the western blots in this article were presented with atypical,unusually shaped and possibly anomalous protein bands in many cases.
文摘The published article titled“UCA1 Regulates the Growth and Metastasis of Pancreatic Cancer by Sponging miR-135a”has been retracted from Oncology Research,Vol.25,No.9,2017,pp.1529–1541.DOI:10.3727/096504017X14888987683152 URL:https://www.techscience.com/or/v25n9/56938 Following the publication,concerns have been raised about a number of figures in this article.An unexpected area of similarity was identified in terms of the cellular data,where the results from differently performed experiments were intended to have been shown,although the areas immediately surrounding this area featured comparatively different distributions of cells.
基金partly supported by the National Natural Science Foundation of China(Nos.61532012,61370196,and 61672109)
文摘In this paper, we target a similarity search among data supply chains, which plays an essential role in optimizing the supply chain and extending its value. This problem is very challenging for application-oriented data supply chains because the high complexity of the data supply chain makes the computation of similarity extremely complex and inefficient. In this paper, we propose a feature space representation model based on key points,which can extract the key features from the subsequences of the original data supply chain and simplify it into a feature vector form. Then, we formulate the similarity computation of the subsequences based on the multiscale features. Further, we propose an improved hierarchical clustering algorithm for a similarity search over the data supply chains. The main idea is to separate the subsequences into disjoint groups such that each group meets one specific clustering criteria; thus, the cluster containing the query object is the similarity search result. The experimental results show that the proposed approach is both effective and efficient for data supply chain retrieval.
基金supported by the National Natural Science Foundation of China[Grant numbers U20A2091,41930107]。
文摘Information on the population distribution at the building scale can help governments make supplemental decisions to address complex urban management issues.However,the discontinuity and strong spatial heterogeneity of research units at the building scale make it challenging to fuse multi-source geographic data,which causes significant errors in population estimation.To address this problem,this study proposes a method for population estimation at the building scale based on Dual-Environment Feature Fusion(DEFF).The dual environments of buildings were constructed by splitting the physical boundaries and extracting features suitable for the dual-environment scale from multi-source geographic data to describe the complex environmental features of buildings.Meanwhile,Data Quality Weighting based Technique for Order of Preference by Similarity to Ideal Solution(DQW-TOPSIS)method was proposed to assign appropriate weights to the features of the external environment for better feature fusion.Finally,a regression model was established using dual-environment features for building-scale population estimation.The experimental areas chosen for this study were Jianghan and Wuchang Districts,both located in Wuhan City,China.The estimated results of the DEFF were compared with those of the ablation experiments,as well as three publicly accessible population datasets,specifically LandScan,WorldPop,and GHS-POP,at the community scale.The evaluation results showed that DEFF had an R2 of approximately 0.8,Mean Absolute Error(MAE)of approximately 1200,Root Mean Square Error(RMSE)of approximately 1700,and both Mean Absolute Percentage Error(MAPE)and Symmetric Mean Absolute Percentage Error(SMAPE)of approximately 26%,indicating an improved performance and verifying the validity of the proposed method for fine-scale population estimation.
基金supported by the National Natural Science Foundation of China[grant number 41371381],[grant number 41431177]Natural Science Research Program of Jiangsu[grant number 14KJA170001]+4 种基金National Special Program on Basic Works for Science and Technology of China[grant number 2013FY110900]National Key Technology Innovation Project for Water Pollution Control and Remediation[grant number 2013ZX07103006]National Basic Research Program of China[grant number 2015CB954102]GuiZhou Welfare and Basic Geological Research Program of China[grant number 201423]China Scholarship Council[grant number 201504910358].
文摘Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data.However,data interlinking,which is the most valuable contribution of Linked Data,remains incomplete and inaccurate.This study proposes a multidimensional and quantitative interlinking approach for Linked Data in the geospatial domain.According to the characteristics and roles of geospatial data in data discovery,eight elementary data characteristics are adopted as data interlinking types.These elementary characteristics are further combined to form compound and overall data interlinking types.Each data interlinking type possesses one specific predicate to indicate the actual relationship of Linked Data and uses data similarity to represent the correlation degree quantitatively.Therefore,geospatial data interlinking can be expressed by a directed edge associated with a relation predicate and a similarity value.The approach transforms existing simple and qualitative geospatial data interlinking into complete and quantitative interlinking and promotes the establishment of high-quality and trusted Linked Geospatial Data.The approach is applied to build data intra-links in the Chinese National Earth System Scientific Data Sharing Network(NSTI-GEO)and data-links in NSTI-GEO with the Chinese Meteorological Data Network and National Population and Health Scientific Data Sharing Platform.
基金supported by the Strategic Cooperation Technology Projects of China National Petroleum Corporation(CNPC)and China University of Petroleum(Beijing)(CUPB)(ZLZX2020-03)National Key Research and Development Program,China(2019YFA0708301)+1 种基金National Key Research and Development Program,China(2023YFF0714102)Science and Technology Innovation Fund of China National Petroleum Corporation(CNPC)(2021DQ02-0403).
文摘Machine learning has been widely applied in well logging formation evaluation studies.However,several challenges negatively impacted the generalization capabilities of machine learning models in practical imple-mentations,such as the mismatch of data domain between training and testing datasets,imbalances among sample categories,and inadequate representation of data model.These issues have led to substantial insufficient identification for reservoir and significant deviations in subsequent evaluations.To improve the transferability of machine learning models within limited sample sets,this study proposes a weight transfer learning framework based on the similarity of the labels.The similarity weighting method includes both hard weights and soft weights.By evaluating the similarity between test and training sets of logging data,the similarity results are used to estimate the weights of training samples,thereby optimizing the model learning process.We develop a double experts’network and a bidirectional gated neural network based on hierarchical attention and multi-head attention(BiGRU-MHSA)for well logs reconstruction and lithofacies classification tasks.Oil field data results for the shale strata in the Gulong area of the Songliao Basin of China indicate that the double experts’network model performs well in curve reconstruction tasks.However,it may not be effective in lithofacies classification tasks,while BiGRU-MHSA performs well in that area.In the study of constructing large-scale well logging processing and formation interpretation models,it is maybe more beneficial by employing different expert models for combined evaluations.In addition,although the improvement is limited,hard or soft weighting methods is better than unweighted(i.e.,average-weighted)in significantly different adjacent wells.The code and data are open and available for subsequent studies on other lithofacies layers.
基金Project supported by the Key Program of Basic Research of Science ＆ Technology Commission of Shanghai Municipality （No. 04dz14004） and the Shanghai Natural Science Foundation （No. 03ZR14065）. Dedicated to Professor Xikui Jiang on the occasion of his 80th birthday.
文摘Clustering is perhaps one of the most widely used tools for microarray data analysis. Proposed roles for genes of unknown function are inferred from clusters of genes similarity expressed across many biological conditions. However, whether function annotation by similarity metrics is reliable or not and to what extent the similarity in gene expression patterns is useful for annotation of gene functions, has not been evaluated. This paper made a comprehensive research on the correlation between the similarity of expression data and of gene functions using Gene Ontology. It has been found that although the similarity in expression patterns and the similarity in gene functions are significantly dependent on each other, this association is rather weak. In addition, among the three categories of Gene Ontology, the similarity of expression data is more useful for cellular component annotation than for biological process and molecular function. The results presented are interesting for the gene functions prediction research area.
