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"title": "2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)",
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"article": {
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"doi": "10.1145/3510003.3510226",
"title": "SAPIENTML: Synthesizing Machine Learning Pipelines by Learning from Human-Written Solutions",
"normalizedTitle": "SAPIENTML: Synthesizing Machine Learning Pipelines by Learning from Human-Written Solutions",
"abstract": "Automatic machine learning, or AutoML, holds the promise of truly democratizing the use of machine learning (ML), by substantially automating the work of data scientists. However, the huge combinatorial search space of candidate pipelines means that current AutoML techniques, generate sub-optimal pipelines, or none at all, especially on large, complex datasets. In this work we propose an AutoML technique SapientML, that can learn from a corpus of existing datasets and their human-written pipelines, and efficiently generate a high-quality pipeline for a predictive task on a new dataset. To combat the search space explosion of AutoML, SapientML employs a novel divide-and-conquer strategy realized as a three-stage program synthesis approach, that reasons on successively smaller search spaces. The first stage uses meta-learning to predict a set of plausible ML components to constitute a pipeline. In the second stage, this is then refined into a small pool of viable concrete pipelines using a pipeline dataflow model derived from the corpus. Dynamically evaluating these few pipelines, in the third stage, provides the best solution. We instantiate SapientML as part of a fully automated tool-chain that creates a cleaned, labeled learning corpus by mining Kaggle, learns from it, and uses the learned models to then synthesize pipelines for new predictive tasks. We have created a training corpus of 1,094 pipelines spanning 170 datasets, and evaluated SapientML on a set of 41 benchmark datasets, including 10 new, large, real-world datasets from Kaggle, and against 3 state-of-the-art AutoML tools and 4 baselines. Our evaluation shows that SapientML produces the best or comparable accuracy on 27 of the benchmarks while the second best tool fails to even produce a pipeline on 9 of the instances. This difference is amplified on the 10 most challenging benchmarks, where SapientML wins on 9 instances with the other tools failing to produce pipelines on 4 or more benchmarks.",
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"content": "Automatic machine learning, or AutoML, holds the promise of truly democratizing the use of machine learning (ML), by substantially automating the work of data scientists. However, the huge combinatorial search space of candidate pipelines means that current AutoML techniques, generate sub-optimal pipelines, or none at all, especially on large, complex datasets. In this work we propose an AutoML technique SapientML, that can learn from a corpus of existing datasets and their human-written pipelines, and efficiently generate a high-quality pipeline for a predictive task on a new dataset. To combat the search space explosion of AutoML, SapientML employs a novel divide-and-conquer strategy realized as a three-stage program synthesis approach, that reasons on successively smaller search spaces. The first stage uses meta-learning to predict a set of plausible ML components to constitute a pipeline. In the second stage, this is then refined into a small pool of viable concrete pipelines using a pipeline dataflow model derived from the corpus. Dynamically evaluating these few pipelines, in the third stage, provides the best solution. We instantiate SapientML as part of a fully automated tool-chain that creates a cleaned, labeled learning corpus by mining Kaggle, learns from it, and uses the learned models to then synthesize pipelines for new predictive tasks. We have created a training corpus of 1,094 pipelines spanning 170 datasets, and evaluated SapientML on a set of 41 benchmark datasets, including 10 new, large, real-world datasets from Kaggle, and against 3 state-of-the-art AutoML tools and 4 baselines. Our evaluation shows that SapientML produces the best or comparable accuracy on 27 of the benchmarks while the second best tool fails to even produce a pipeline on 9 of the instances. This difference is amplified on the 10 most challenging benchmarks, where SapientML wins on 9 instances with the other tools failing to produce pipelines on 4 or more benchmarks.",
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"normalizedAbstract": "Automatic machine learning, or AutoML, holds the promise of truly democratizing the use of machine learning (ML), by substantially automating the work of data scientists. However, the huge combinatorial search space of candidate pipelines means that current AutoML techniques, generate sub-optimal pipelines, or none at all, especially on large, complex datasets. In this work we propose an AutoML technique SapientML, that can learn from a corpus of existing datasets and their human-written pipelines, and efficiently generate a high-quality pipeline for a predictive task on a new dataset. To combat the search space explosion of AutoML, SapientML employs a novel divide-and-conquer strategy realized as a three-stage program synthesis approach, that reasons on successively smaller search spaces. The first stage uses meta-learning to predict a set of plausible ML components to constitute a pipeline. In the second stage, this is then refined into a small pool of viable concrete pipelines using a pipeline dataflow model derived from the corpus. Dynamically evaluating these few pipelines, in the third stage, provides the best solution. We instantiate SapientML as part of a fully automated tool-chain that creates a cleaned, labeled learning corpus by mining Kaggle, learns from it, and uses the learned models to then synthesize pipelines for new predictive tasks. We have created a training corpus of 1,094 pipelines spanning 170 datasets, and evaluated SapientML on a set of 41 benchmark datasets, including 10 new, large, real-world datasets from Kaggle, and against 3 state-of-the-art AutoML tools and 4 baselines. Our evaluation shows that SapientML produces the best or comparable accuracy on 27 of the benchmarks while the second best tool fails to even produce a pipeline on 9 of the instances. This difference is amplified on the 10 most challenging benchmarks, where SapientML wins on 9 instances with the other tools failing to produce pipelines on 4 or more benchmarks.",
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"fullName": "Ripon K. Saha",
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{
"affiliation": "The University of Texas at Austin",
"fullName": "Chenguang Zhu",
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"surname": "Zhu",
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{
"affiliation": "University of Illinois at Urbana-Champaign",
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{
"affiliation": "The University of Texas at Austin",
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"affiliation": "The University of Texas at Austin",
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"fullName": "Mukul R. Prasad",
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"abstract": "The objective of this research work is to design and construct RFID tag for fish identification using RFID antennas. By logging on the identified data in PIC, it is more secure than other RFID devices. And also it is easily programmable and reliable method. In this work, tag's data for fish identification are created in MS access database engine. ActiveX Comport is built on top of serial interface driver with Visual Basic programming language for communication from EEPROM of tag circuit to PC. PIC16F628 is used for commissioning identified tag's data into EEPROM and modulating the tag's data in EEPROM with 135 kHz carrier from the reader. PIC program is written in Assembly language. The best reading angle of fish identification data between the antennas of RFID tag and reader is measured by spectra analyzer. The experimental result shows that the minimum attenuation can be obtained at the reading angle of (0deg) and(90deg) than any other reading angles at the maximum readable distance of 30 cm.",
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"content": "The objective of this research work is to design and construct RFID tag for fish identification using RFID antennas. By logging on the identified data in PIC, it is more secure than other RFID devices. And also it is easily programmable and reliable method. In this work, tag's data for fish identification are created in MS access database engine. ActiveX Comport is built on top of serial interface driver with Visual Basic programming language for communication from EEPROM of tag circuit to PC. PIC16F628 is used for commissioning identified tag's data into EEPROM and modulating the tag's data in EEPROM with 135 kHz carrier from the reader. PIC program is written in Assembly language. The best reading angle of fish identification data between the antennas of RFID tag and reader is measured by spectra analyzer. The experimental result shows that the minimum attenuation can be obtained at the reading angle of (0deg) and(90deg) than any other reading angles at the maximum readable distance of 30 cm.",
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"title": "2017 21st International Conference Information Visualisation (IV)",
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"title": "Visual Analytics Solutions as ‘off-the-Shelf’ Libraries",
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"abstract": "Visual Analytics has brought forward many solutions to different tasks such as exploring topics, understanding user and customer behavior, comparing genomes, or detecting anomalies. Many of these solutions, if not most, are standalone applications with technological contributions which cannot be easily taken for: reuse in other domains, further improvement, benchmarking, or integration and deployment alongside other solutions. The latter can prove specially helpful for exploratory data analysis. This often leads researchers to re-implement solutions and thus to a suboptimal use of skills and resources. This paper discusses further the lack of off-the-shelf libraries for Visual Analytics, and proposes the creation of pluggable libraries on top of existing technologies such as Spark and Zeppelin. We provide an illustrative example of a pluggable, Visual Analytics library using these technologies.",
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"abstract": "The thermal properties of concrete and steel were concerned. Specific heat, thermal conductivity, density and thermal contact conductance at the steel-concrete interface were compared from different researchers. Different ways of calculation method of heat transfer were summarized. A finite element method (FEM) procedure was suggested to calculate temperature distribution of concrete filled steel tube reinforced concrete (CFSTRC) column with suitable thermal properties of concrete and steel. The results showed that different models of thermal properties of concrete and steel dispersed widely. The dispersion of thermal properties of steel was smaller than that of concrete. Moisture and aggregate type had some influence on specific heat of concrete, and aggregate type had some influence on thermal conductivity of concrete. Thermal conductivity of reinforcing steel and stainless steel showed a reverse trend with temperature increasing. The influence of temperature on density of concrete and steel was slightly. Cross-sectional type had some influence on thermal contact conductance at the steel-concrete interface in some models, but constant values have been used extensively by different researchers. According to experimental validation, the FEM procedure was capable of predicting temperature distribution of CFSTRC columns with an accuracy that was sufficient for design purposes.",
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"content": "The thermal properties of concrete and steel were concerned. Specific heat, thermal conductivity, density and thermal contact conductance at the steel-concrete interface were compared from different researchers. Different ways of calculation method of heat transfer were summarized. A finite element method (FEM) procedure was suggested to calculate temperature distribution of concrete filled steel tube reinforced concrete (CFSTRC) column with suitable thermal properties of concrete and steel. The results showed that different models of thermal properties of concrete and steel dispersed widely. The dispersion of thermal properties of steel was smaller than that of concrete. Moisture and aggregate type had some influence on specific heat of concrete, and aggregate type had some influence on thermal conductivity of concrete. Thermal conductivity of reinforcing steel and stainless steel showed a reverse trend with temperature increasing. The influence of temperature on density of concrete and steel was slightly. Cross-sectional type had some influence on thermal contact conductance at the steel-concrete interface in some models, but constant values have been used extensively by different researchers. According to experimental validation, the FEM procedure was capable of predicting temperature distribution of CFSTRC columns with an accuracy that was sufficient for design purposes.",
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"normalizedAbstract": "The thermal properties of concrete and steel were concerned. Specific heat, thermal conductivity, density and thermal contact conductance at the steel-concrete interface were compared from different researchers. Different ways of calculation method of heat transfer were summarized. A finite element method (FEM) procedure was suggested to calculate temperature distribution of concrete filled steel tube reinforced concrete (CFSTRC) column with suitable thermal properties of concrete and steel. The results showed that different models of thermal properties of concrete and steel dispersed widely. The dispersion of thermal properties of steel was smaller than that of concrete. Moisture and aggregate type had some influence on specific heat of concrete, and aggregate type had some influence on thermal conductivity of concrete. Thermal conductivity of reinforcing steel and stainless steel showed a reverse trend with temperature increasing. The influence of temperature on density of concrete and steel was slightly. Cross-sectional type had some influence on thermal contact conductance at the steel-concrete interface in some models, but constant values have been used extensively by different researchers. According to experimental validation, the FEM procedure was capable of predicting temperature distribution of CFSTRC columns with an accuracy that was sufficient for design purposes.",
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"keywords": [
"Concrete",
"Steel",
"Thermal Conductivity",
"Heating",
"Conductivity",
"Electron Tubes",
"Fires",
"Thermal Properties",
"Fire Exposure",
"Heat Transfer",
"Temperature Distribution"
],
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"fullName": "Kai Xiang",
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"surname": "Xiang",
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"fullName": "Guo-Hui Wang",
"givenName": "Guo-Hui",
"surname": "Wang",
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"affiliation": null,
"fullName": "Yan-Chong Pan",
"givenName": "Yan-Chong",
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"doi": "10.1109/ICCMS.2010.205",
"title": "Finite Element Analysis of Shear Behaviors for Steel Fiber Reinforced Concrete Corbels by ANSYS",
"normalizedTitle": "Finite Element Analysis of Shear Behaviors for Steel Fiber Reinforced Concrete Corbels by ANSYS",
"abstract": "Based on the experimental results of 12 steel fiber reinforced concrete corbels, the numerical simulation by nonlinear finite element method was adopted to analyze their behaviors and to explore the influence of steel fiber volume ratio, the shear span to depth ratio and the strength of concrete on the shear behaviors, crack and deformation of concrete corbels. The results indicate that the shear behaviors increases with the increase of the volume ratio of steel fibers or steel fiber concrete strength. The shear behaviors decreases with the increase of shear span ratio. Steel fiber enhances the cracking-resistance capacity of the steel fiber reinforced concrete corbels, decreases the width of the crack and restricts lateral deformation of concrete. Furthermore, the results of the numerical simulation and the results of the relevant experiments coincide well, and it proves the rationality of unit type and material stress-strain relations and failure criteria used in the infinite element analysis model.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Based on the experimental results of 12 steel fiber reinforced concrete corbels, the numerical simulation by nonlinear finite element method was adopted to analyze their behaviors and to explore the influence of steel fiber volume ratio, the shear span to depth ratio and the strength of concrete on the shear behaviors, crack and deformation of concrete corbels. The results indicate that the shear behaviors increases with the increase of the volume ratio of steel fibers or steel fiber concrete strength. The shear behaviors decreases with the increase of shear span ratio. Steel fiber enhances the cracking-resistance capacity of the steel fiber reinforced concrete corbels, decreases the width of the crack and restricts lateral deformation of concrete. Furthermore, the results of the numerical simulation and the results of the relevant experiments coincide well, and it proves the rationality of unit type and material stress-strain relations and failure criteria used in the infinite element analysis model.",
"__typename": "ArticleAbstractType"
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],
"normalizedAbstract": "Based on the experimental results of 12 steel fiber reinforced concrete corbels, the numerical simulation by nonlinear finite element method was adopted to analyze their behaviors and to explore the influence of steel fiber volume ratio, the shear span to depth ratio and the strength of concrete on the shear behaviors, crack and deformation of concrete corbels. The results indicate that the shear behaviors increases with the increase of the volume ratio of steel fibers or steel fiber concrete strength. The shear behaviors decreases with the increase of shear span ratio. Steel fiber enhances the cracking-resistance capacity of the steel fiber reinforced concrete corbels, decreases the width of the crack and restricts lateral deformation of concrete. Furthermore, the results of the numerical simulation and the results of the relevant experiments coincide well, and it proves the rationality of unit type and material stress-strain relations and failure criteria used in the infinite element analysis model.",
"fno": "3941d303",
"keywords": [
"Cracks",
"Deformation",
"Fibre Reinforced Composites",
"Finite Element Analysis",
"Mechanical Engineering Computing",
"Reinforced Concrete",
"Stress Strain Relations",
"Finite Element Analysis",
"Shear Behaviors",
"Steel Fiber Reinforced Concrete Corbels",
"ANSYS",
"Numerical Simulation",
"Nonlinear Finite Element Method",
"Steel Fiber Volume Ratio",
"Cracks",
"Deformations",
"Steel Fiber Concrete Strength",
"Stress Strain Relations",
"Finite Element Methods",
"Steel",
"Concrete",
"Optical Fiber Testing",
"Tensile Stress",
"Building Materials",
"Shearing",
"Numerical Simulation",
"Surface Cracks",
"Surface Resistance",
"Steel Fiber Reinforced Concrete",
"Corbel",
"Shear Behaviors",
"Numerical Simulation"
],
"authors": [
{
"affiliation": "Res. Center of New Style Building Mater. & Struct., Zhengzhou Univ., Zhengzhou, China",
"fullName": "Daoying Gao",
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"affiliation": "Res. Center of New Style Building Mater. & Struct., Zhengzhou Univ., Zhengzhou, China",
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"proceeding": {
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"doi": "10.1109/CSIE.2009.119",
"title": "Numerical Experiment on Flexural Properties of Steel Fiber Reinforced Concrete Beam",
"normalizedTitle": "Numerical Experiment on Flexural Properties of Steel Fiber Reinforced Concrete Beam",
"abstract": "Based on the laboratory experiment of steel fiber reinforced concrete (SFRC), a total of 10 specimens have been designed according to the aggregate interface condition, steel fiber ratios and different-strength concrete. These specimens were computed by MFPA2D in micro-structure level. Comparing the result of SFRC with plain concrete beams, this paper validated the positive effect of steel fiber in crack-resistant and the flexural strength improvement of SFRC beam, analyzed the sensitivity of steel fiber to concrete with different strength, and provided the stress field and elastic modulus images. The numerical results gave the whole failure process of crack initiation, propagation, and interpenetrated. These results provide useful information toward understanding the flexural behavior of SFRC and have great significance to comprehend the flexural failure process of SFRC beam.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Based on the laboratory experiment of steel fiber reinforced concrete (SFRC), a total of 10 specimens have been designed according to the aggregate interface condition, steel fiber ratios and different-strength concrete. These specimens were computed by MFPA2D in micro-structure level. Comparing the result of SFRC with plain concrete beams, this paper validated the positive effect of steel fiber in crack-resistant and the flexural strength improvement of SFRC beam, analyzed the sensitivity of steel fiber to concrete with different strength, and provided the stress field and elastic modulus images. The numerical results gave the whole failure process of crack initiation, propagation, and interpenetrated. These results provide useful information toward understanding the flexural behavior of SFRC and have great significance to comprehend the flexural failure process of SFRC beam.",
"__typename": "ArticleAbstractType"
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],
"normalizedAbstract": "Based on the laboratory experiment of steel fiber reinforced concrete (SFRC), a total of 10 specimens have been designed according to the aggregate interface condition, steel fiber ratios and different-strength concrete. These specimens were computed by MFPA2D in micro-structure level. Comparing the result of SFRC with plain concrete beams, this paper validated the positive effect of steel fiber in crack-resistant and the flexural strength improvement of SFRC beam, analyzed the sensitivity of steel fiber to concrete with different strength, and provided the stress field and elastic modulus images. The numerical results gave the whole failure process of crack initiation, propagation, and interpenetrated. These results provide useful information toward understanding the flexural behavior of SFRC and have great significance to comprehend the flexural failure process of SFRC beam.",
"fno": "3507g755",
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"affiliation": null,
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"abstract": "This paper presents the full-field displacement and strain measurements in the debonding tests of steel stranded wire mesh and polymer mortar (SMPM) laminates bonded to concrete, in which the electronic speckle pattern interferometry (ESPI) with four-phase shifting technique is used. The in-plane displacements of SMPM laminates are obtained by measuring the changes in phase patterns due to deformation. Derivation of displacements resulted in strains. The propagation of interference fringes and the characteristic of strain distributions are recorded and analyzed. It is concluded that the ESPI, being a whole-field non-contacting optical method, is suitable for the study of debonding mechanism of composites. However, the rigid body motions of test specimens should be strictly restrained. The strain distribution on the surface of SMPM laminates is different from that of the well-used fiber reinforced polymer (FRP) laminates, and the position of transversal stranded wires has a significant influence on the strain distribution and the debonding load. Results of this study can be used for developing the interfacial bond-slip relationship of SMPM laminates bonded to concrete.",
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"abstract": "Reinforced concrete (RC) can work normally in actual engineering, which depends on well interfacial bond strength between reinforcing steel bar and concrete. Interfacial debonding is one of the main damage forms for RC and its structure. Relative sliding or interfacial debonding may occur under external loading, especially cyclic loading. Cyclic loading exists in many projects, for example, ocean platform and crane girder. Finite element model for interfacial debonding investigation of RC under cyclic loading is designed as basis of ADINA. The friction between reinforcing steel bar and concrete is defined, and bond stress-slippage relationship between concrete and reinforcing steel bar is established. According to the calculating result, effects of reinforcing steel bar type and anchor depth on interfacial fatigue are analyzed. It can provide effective numerical ideal and method for investigation of RC lasting quality.",
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"content": "Reinforced concrete (RC) can work normally in actual engineering, which depends on well interfacial bond strength between reinforcing steel bar and concrete. Interfacial debonding is one of the main damage forms for RC and its structure. Relative sliding or interfacial debonding may occur under external loading, especially cyclic loading. Cyclic loading exists in many projects, for example, ocean platform and crane girder. Finite element model for interfacial debonding investigation of RC under cyclic loading is designed as basis of ADINA. The friction between reinforcing steel bar and concrete is defined, and bond stress-slippage relationship between concrete and reinforcing steel bar is established. According to the calculating result, effects of reinforcing steel bar type and anchor depth on interfacial fatigue are analyzed. It can provide effective numerical ideal and method for investigation of RC lasting quality.",
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"title": "2021 International Conference of Social Computing and Digital Economy (ICSCDE)",
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"title": "Extraction of optimum ratio parameters of steel fiber reinforced concrete based on BP neural network",
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"abstract": "In order to overcome the problems of low precision in the traditional extraction method of steel fiber reinforced concrete optimum ratio parameters, a new extraction method of steel fiber reinforced concrete optimum ratio parameters based on BP neural network is proposed in this paper. Based on the analysis of suspension state, virtual accumulation state and actual accumulation state of concrete solid particles, combined with the characteristic particle sizes of large particles and small particles, the packing density and constraint conditions of concrete solid particles are calculated. Based on the structure of BP neural network, the input of hidden layer is calculated, and the output of hidden layer is calculated according to s function. By comparing the expected output with the actual output, the threshold and weight of BP neural network are modified to construct the optimal ratio parameters of steel fiber reinforced concrete. The experimental results show that under the same experimental environment, the flexural strength of concrete is the best under the ratio parameters extracted by this method, and the extraction accuracy of the best ratio parameters is the highest, so this method can improve the rationality of the ratio of steel fiber reinforced concrete.",
"abstracts": [
{
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"content": "In order to overcome the problems of low precision in the traditional extraction method of steel fiber reinforced concrete optimum ratio parameters, a new extraction method of steel fiber reinforced concrete optimum ratio parameters based on BP neural network is proposed in this paper. Based on the analysis of suspension state, virtual accumulation state and actual accumulation state of concrete solid particles, combined with the characteristic particle sizes of large particles and small particles, the packing density and constraint conditions of concrete solid particles are calculated. Based on the structure of BP neural network, the input of hidden layer is calculated, and the output of hidden layer is calculated according to s function. By comparing the expected output with the actual output, the threshold and weight of BP neural network are modified to construct the optimal ratio parameters of steel fiber reinforced concrete. The experimental results show that under the same experimental environment, the flexural strength of concrete is the best under the ratio parameters extracted by this method, and the extraction accuracy of the best ratio parameters is the highest, so this method can improve the rationality of the ratio of steel fiber reinforced concrete.",
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"affiliation": "Anhui Higher Education Institutes (Anhui Xinhua University),Key Laboratory of Building Structure,Anhui Hefei,China,230088",
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"abstract": "Recent global climate changes have affected vegetation coverage in the Tibetan Plateau. Based on the remote sensing images and the meteorological data from 1986 to 2000, using the model of extracting vegetation coverage, the spatiotemporal changes of vegetation coverage and its responses to global climate changes in the Tibetan Plateau during 1986-2000 were studied. The results showed that from 1986 to 2000 vegetation coverage increased 0.011 as a whole, except some small regions degradation in the Tibetan Plateau. Global climate changes have contributed to an increase of vegetation coverage in the Tibetan Plateau, and the vegetation coverage change was positively correlated with the changes of precipitation and temperature. The regions with decreasing vegetation coverage were mainly distributed in the southeast where the recent warming trends contribute to humid weather and favorable conditions for vegetation growth, while increasing vegetation coverage were in the northwest where higher temperature have led to arid conditions and insufficient rainfall of the Tibetan Plateau. The responses of vegetation coverage to climate changes varied with different vegetation types.",
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"title": "Information Visualization in Climate Research",
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"abstract": "Much of the work conducted in climate research involves large and heterogeneous datasets with spatial and temporal references. This makes climate research an interesting application area for visualization. However, the application of interactive visual methods to assist in gaining insight into climate data is still hampered for climate research scientists, who are usually not visualization experts. In this paper, we report on a survey that we conducted to evaluate the application of interactive visualization methods and to identify the problems related to establishing such methods in scientific practice. The feedback from 76 participants shows clearly that state-of-the-art techniques are rarely applied and that integrating existing solutions smoothly into the scientists workflow is problematic. We have begun to change this and present first results that illustrate how interactive visualization tools can be successfully applied to accomplish climate research tasks. As a concrete example, we describe the visualization of climate networks and its benefits for climate impact research.",
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"content": "Much of the work conducted in climate research involves large and heterogeneous datasets with spatial and temporal references. This makes climate research an interesting application area for visualization. However, the application of interactive visual methods to assist in gaining insight into climate data is still hampered for climate research scientists, who are usually not visualization experts. In this paper, we report on a survey that we conducted to evaluate the application of interactive visualization methods and to identify the problems related to establishing such methods in scientific practice. The feedback from 76 participants shows clearly that state-of-the-art techniques are rarely applied and that integrating existing solutions smoothly into the scientists workflow is problematic. We have begun to change this and present first results that illustrate how interactive visualization tools can be successfully applied to accomplish climate research tasks. As a concrete example, we describe the visualization of climate networks and its benefits for climate impact research.",
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"abstract": "The occurrence of El Nino / Lanina event will cause climate change, which has an important effect on garlic production. As the main garlic producing area of China, Jinxiang County, the study of its climate and garlic yield can provide guidance for garlic farmers and garlic merchants and provide decision-making suggestions for the government. The effects of El nino/la Nina event on climate and garlic yield were studied by collecting and sorting out the annual data of yield per unit area of garlic, annual precipitation and annual average temperature in Jinxiang County and the occurrence of El Nino / La Nina event. The results showed that: (f) when La Nina occurred in the year, the garlic yield per unit in Jinxiang County would be 6.2% lower than that of normal year. (2) When El Nino occurs, the annual precipitation of Jinxiang County is 28% higher than that of normal year; When La Nina happened, the annual precipitation of Jinxiang County was 4% lower than that of normal year and the annual average temperature was 2% lower than that of normal year. (3) In the next two years, the per mu output of garlic in Jinxiang County will remain at a high level.",
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"abstract": "The Polymer has become a popular research topic in the field of soft matter, gaining attention from both chemistry and physics community. Polymer brush is an architecture which has been intensively researched in recent years, ranging from theoretical development to its synthesis. The variety of polymer brushes resulted by the architecture of polymers (linear, bottle-brush, star-like, etc.) attached to the substrate surface and the geometry of grafting surface (planar, cylindrical and spherical) leads to the diverseness of conformations of polymer brushes. Molecular dynamics simulation is an important tool to provide a calculation of statistical properties of the system and verify the prediction of theories. This review article would focus on works of molecular dynamics simulation related to linear polymer brush and bottle-brush polymer. Three research works on linear polymer brush are discussed, focusing on the linear brush in a good solvent, in varying solvent quality and polar linear brush respectively. For bottle-brush polymer, cases of stiff backbone and flexible backbone are introduced.",
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"content": "The Polymer has become a popular research topic in the field of soft matter, gaining attention from both chemistry and physics community. Polymer brush is an architecture which has been intensively researched in recent years, ranging from theoretical development to its synthesis. The variety of polymer brushes resulted by the architecture of polymers (linear, bottle-brush, star-like, etc.) attached to the substrate surface and the geometry of grafting surface (planar, cylindrical and spherical) leads to the diverseness of conformations of polymer brushes. Molecular dynamics simulation is an important tool to provide a calculation of statistical properties of the system and verify the prediction of theories. This review article would focus on works of molecular dynamics simulation related to linear polymer brush and bottle-brush polymer. Three research works on linear polymer brush are discussed, focusing on the linear brush in a good solvent, in varying solvent quality and polar linear brush respectively. For bottle-brush polymer, cases of stiff backbone and flexible backbone are introduced.",
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"abstract": "Cochlear implant is a sort of equipment which is used to restore normal hearing to the profoundly deaf by electrical stimulation of the auditory nerve. And it is an imitation of normal hearing function. However ,the speech signal coding methods used in the cochlear implant at present consider only about the conversion from speech signal to electrical signal, without the function of human cochlear’s temporal encoding pattern. So the effect of the cochlear implant is not very perfect. This paper combined the mechanism of hearing physiology, presented a new solution which generated stimulating pulsatile series by a “Amplitude-Time-Frequency” method. The coding method is converting the speech signal’s amplitude into stimulating pulsatile series’s amplitude time and frequency. We named it as “ATF coding method”. ATF coding method can solve the problem that stimulating pulsatile series’s dynamic configuration used in the auditory neural center. ATF can keep the temporal correlation and coherence of speech remained in stimulating pulsatile series.",
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"abstract": "This paper selects a native speaker of Shigatse dialect in the Wei Zang dialect area as the research object to study the parameters of airflow when the nasal sound of Shigatse dialect is used as the initial consonant.Three parameters of nasal obstruction were collected for comparison, including the duration of articulation, average air velocity and airflow. The results show that the three parameters follow the rule of pronunciation duration, average air velocity and airflow is ད[ŋa]>ཉ[ɳa]>མ[ma]>ན[na]. The reference values of acoustic and airflow parameters obtained in this paper can provide theoretical basis and technical support for throat diseases, dysphonic diseases and postoperative evaluation of Tibetan native speakers.",
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"abstract": "Recently, breast MR images have been used more frequently for diagnosis of that area. Several methods have been proposed for segmenting these MR images, however, these methods are not dedicated to segmenting the pectoral muscle. Therefore, in this paper, we propose a practical and general-purpose approach for detecting segmenting in the pectoral muscle boundary based on the structure tensor. The segmentation work flow comprises four key steps: preprocessing, detection of the region of interest (ROI) within the breast region, segmenting the pectoral muscle and finally extracting and refining the pectoral muscle boundary. From experimental results we show that the proposed method can segment the pectoral muscle exactly. In addition, the proposed method will allow the application of the CAD and registration for various breast images.",
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"abstract": "Fiber tracking is a technique that determines the location of fiber bundles in a human brain. Sequential implementations of fiber tracking usually require a large execution time, which hinders both the interactivity currently experienced by physicians and its applications to large collections of data sets. In this paper we present the design and implementation of fiber tracking applications in two different parallel environments, GPUs and PC clusters. The performance results obtained in our experiments show that both HPC configurations are suitable for fiber tracking: GPUs for interactive applications targeted at physicians and PC clusters for batch processing by fiber tracking researchers.",
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"abstract": "Diffusion weighted magnetic resonance imaging (dMRI) together with tractography algorithms allow to probe for principal white matter tracts in the living human brain. Specifically, probabilistic tractography quantifies the existence of physical connections to a given seed region as a 3D scalar map of confidence scores. Fiber-Stippling is a visualization for probabilistic tracts that effectively communicates the diffusion pattern, connectivity score, and anatomical context. Unfortunately, it cannot handle multiple diffusion orientations per voxel, which exist in high angular resolution diffusion imaging (HARDI) data. Such data is needed to resolve tracts in complex configurations, such as crossings. In this work, we suggest a visualization based on Fiber-Stippling but sensible to multiple diffusion orientations from HARDI-based diffusion models. With such a technique, it is now possible to visualize probabilistic tracts from HARDI-based tractography algorithms. This implies that tract crossings may now be visualized as crossing stipples, which is an essential step towards an accurate visualization of the neuroanatomy, as crossing tracts are widespread phenomena in the brain.",
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"abstract": "Confocal microscopy is an important tool for visualizing 3D datasets of fluorescent specimens, and has been used to investigate the structure of biological specimens. However, such images are affected by the noise introduced during the specimen preparation and image acquisition processes. Anisotropic diffusion is a non-linear filter that can significantly improve image quality while removing noise without blurring edges. This study investigates the application of anisotropic diffusion in confocal microscopy images by exploring different models for parameters' calculation. Our data consists of several slices of extrahepatic bile ducts containing a network of small vessels named Peribiliary Vascular Plexus (PVP), which are affected by several sources of noise. Experimental results show that anisotropic diffusion improved the volumetric visualization of the PVP. We validated the results using MSE and PSNR quantitative approaches and qualitative description by an expert user.",
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"content": "Confocal microscopy is an important tool for visualizing 3D datasets of fluorescent specimens, and has been used to investigate the structure of biological specimens. However, such images are affected by the noise introduced during the specimen preparation and image acquisition processes. Anisotropic diffusion is a non-linear filter that can significantly improve image quality while removing noise without blurring edges. This study investigates the application of anisotropic diffusion in confocal microscopy images by exploring different models for parameters' calculation. Our data consists of several slices of extrahepatic bile ducts containing a network of small vessels named Peribiliary Vascular Plexus (PVP), which are affected by several sources of noise. Experimental results show that anisotropic diffusion improved the volumetric visualization of the PVP. We validated the results using MSE and PSNR quantitative approaches and qualitative description by an expert user.",
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"abstract": "We present a cell cycle analysis that aims towards improving our previous work by adding another channel and using one more dimension. The data we use is a set of 3D images of mouse cells captured with a spinning disk confocal microscope. All images are available in two channels showing the chromocenters and the fluorescently marked protein PCNA, respectively. In the present paper, we will describe our recent colocalization study in which we use Hessian-based blob detectors in combination with radial features to measure the degree of overlap between both channels. We show that colocalization performed in such a way provides additional discriminative power and allows us to distinguish between phases that we were not able to distinguish with a single 2D channel.",
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"normalizedAbstract": "For cancers such as glioblastoma multiforme, there is an increasing interest in defining \"biological target volumes\" (BTV), high tumour-burden regions which may be targeted with dose boosts in radiotherapy. The definition of a BTV requires insight into tumour characteristics going beyond conventionally defined radiological abnormalities and anatomical features. Molecular and biochemical imaging techniques, like positron emission tomography, the use of Magnetic Resonance (MR) Imaging contrast agents or MR Spectroscopy deliver this information and support BTV delineation. MR Spectroscopy Imaging (MRSI) is the only non-invasive technique in this list. Studies with MRSI have shown that voxels with certain metabolic signatures are more susceptible to predict the site of relapse. Nevertheless, the discovery of complex relationships between a high number of different metabolites, anatomical, molecular and functional features is an ongoing topic of research — still lacking appropriate tools supporting a smooth workflow by providing data integration and fusion of MRSI data with other imaging modalities. We present a solution bridging this gap which gives fast and flexible access to all data at once. By integrating a customized visualization of the multi-modal and multi-variate image data with a highly flexible visual analytics (VA) framework, it is for the first time possible to interactively fuse, visualize and explore user defined metabolite relations derived from MRSI in combination with markers delivered by other imaging modalities. Real-world medical cases demonstrate the utility of our solution. By making MRSI data available both in a VA tool and in a multi-modal visualization renderer we can combine insights from each side to arrive at a superior BTV delineation. We also report feedback from domain experts indicating significant positive impact in how this work can improve the understanding of MRSI data and its integration into radiotherapy planning.",
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"title": "2008 IEEE International Conference on Data Mining Workshops",
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"title": "Mining Temporal Patterns with Quantitative Intervals",
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"abstract": "In this paper we consider the problem of discovering frequent temporal patterns in a database of temporal sequences, where a temporal sequence is a set of items with associated dates and durations. Since the quantitative temporal information appears to be fundamental in many contexts, it is taken into account in the mining processes and returned as part of the extracted knowledge. To this end, we have adapted the classical APriori framework to propose an efficient algorithm based on a hyper-cube representation of temporal sequences. The extraction of quantitative temporal information is performed using a density estimation of the distribution of event intervals from the temporal sequences. An evaluation on synthetic data sets shows that the proposed algorithm can robustly extract frequent temporal patterns with quantitative temporal extents.",
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"fno": "3503a218",
"keywords": [
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"Temporal Sequence",
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"Intervalsdistribution",
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"fullName": "Thomas Guyet",
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"abstract": "We describe a method that recovers an estimate of surface shape and of the irradiance field for a textured surface. The method assumes the surface is viewed in scaled orthography, and we demonstrate the appropriateness of this assumption. Our method uses interest points to obtain the locations of putative texton instances, clusters the textons into types, and then uses an autocalibration method to recover the frontal appearance of each texton model. This yields (a) a dense set of normal estimates, each up to a two-fold ambiguity, (b) a dense set of irradiance estimates and (c) whether each instance is, in fact, an instance of the relevant texton. Because we are able to obtain a very large number of instances of a large number of different textons, this information is obtained at sites very closely spaced in the image. As a result, we need only a simple smoothness constraint to reconstruct a surface model, using EM to resolve the normal ambiguity. We show results on images of real scenes, comparing our reconstructions with those obtained using other methods and demonstrating the accuracy of both the recovered shape and the irradiance estimate.",
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"abstract": "A Category Sequence Traversal Query (CSTQ) is a new type of category based query that determines the minimum-cost path with a predefined origin-destination pair, traversing at least a single selection from each of a set of categories in a specified order. CSTQ has distinct applications in transportation trip planning and other potential applications whenever a workflow exists to traverse a set of categories of interest. This paper proposes bivariate best first searches to process CSTQ in a transportation network. Specifically, this paper 1) proposes a general multivariate best first search framework, L#, to process multiple points/categories of interest in a graph; 2) presents a developed bivariate best first search algorithm, C*, to process CSTQ in a general graph; and 3) provides C*-P and C*-Dijkstra, two bivariate best-first-search instances of C*, to retrieve optimal solutions for CSTQ processing in a transportation network. The performance of C*-P and C*-Dijkstra are analyzed with a set of experiments in a large urban dense transportation network, and the results show that on average, C*-Dijkstra is 5.9~8.8 times slower and expands 4.3~5.0 times more states than C*-P, with number of categories up to 7 and number of objects in each category up to 3800.",
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"abstract": "Color and texture are visual cues of different nature, their integration in a useful visual descriptor is not an obvious step. One way to combine both features is to compute texture descriptors independently on each color channel. A second way is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress in the last years in object recognition has provided the bag-of-words framework that again deals with the problem of feature combination through the definition of vocabularies of visual words. Inspired in this framework, here we present perceptual textons that will allow to fuse color and texture at the level of p-blobs, which is our feature detection step. Feature representation is based on two uniform spaces representing the attributes of the p-blobs. The low-dimensionality of these text on spaces will allow to bypass the usual problems of previous approaches. Firstly, no need for normalization between cues; and secondly, vocabularies are directly obtained from the perceptual properties of text on spaces without any learning step. Our proposal improve current state-of-art of color-texture descriptors in an image retrieval experiment over a highly diverse texture dataset from Corel.",
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"abstract": "Predicting the quantum resources for potential applications such as quantum chemistry plays a key role in the future development of quantum computers, and a systematic approach based on a reliable metric is needed for efficient resource estimation. In this work, we developed a Python software package QRE (Quantum Resource Estimator) for estimating quantum resources required to compute the properties of molecules. We define the key requirements for the quantum phase estimation (QPE) algorithm for molecules with different basis sets. We estimated the number of ancilla qubits, circuit depth, and time to solution. The input for QRE is the information about a molecule such as atom types, molecular geometries, charges, basis set, and level of theory. Also, we consider an error analysis scheme for QPE algorithm to calculate the number of ancilla qubits. As a part of the estimation, we calculate the number of rotation and CNOT gates for one Trotter step. Based on these results, the QRE program calculates costs for full QPE algorithms for the given gate time, fidelities of CNOT gates, and target success probability. It is expected that our work will contribute to a better understanding of the limitations of current and future quantum computers for quantum chemistry applications.",
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