To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on ...To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on the upper atmosphere has been developed by a Japanese inter-university project called the Inter-university Upper atmosphere Global Observation Network （1UGONET）. The objective of this paper is to describe the infrastructure and tools developed by IUGONET. We focus on the data analysis software. It is written in Interactive Data Language （IDL） and is a plug-in for the THEMIS Data Analysis Software suite （TDAS）, which is a set of IDL libraries used to visualize and analyze satellite- and ground-based data. We present plots of upper atmospheric data provided by IUGONET as examples of applications, and verify the usefulness of the software in the study of polar science. We discuss IUGONET＇s new and unique developments, i.e., an executable file of TDAS that can run on the IDL Virtual Machine, IDL routines to retrieve metadata from the IUGONET database, and an archive of 3-D simulation data that uses the Common Data Format so that it can easily be used with TDAS.展开更多
With the threshold for crop growth data collection having been markedly decreased by sensor miniaturization and cost reduction,unmanned aerial vehicle(UAV)-based low-altitude remote sensing has shown remarkable advant...With the threshold for crop growth data collection having been markedly decreased by sensor miniaturization and cost reduction,unmanned aerial vehicle(UAV)-based low-altitude remote sensing has shown remarkable advantages in field phenotyping experiments.However,the requirement of interdisciplinary knowledge and the complexity of the workflow have seriously hindered researchers from extracting plot-level phenotypic data from multisource and multitemporal UAV images.To address these challenges,we developed the Integrated High-Throughput Universal Phenotyping(IHUP)software as a data producer and study accelerator that included 4 functional modules:preprocessing,data extraction,data management,and data analysis.Data extraction and analysis requiring complex and multidisciplinary knowledge were simplified through integrated and automated processing.Within a graphical user interface,users can compute image feature information,structural traits,and vegetation indices(Vis),which are indicators of morphological and biochemical traits,in an integrated and high-throughput manner.To fulfill data requirements for different crops,extraction methods such as VI calculation formulae can be customized.To demonstrate and test the composition and performance of the software,we conducted case-related rice drought phenotype monitoring experiments.In combination with a rice leaf rolling score predictive model,leaf rolling score,plant height,VIs,fresh weight,and drought weight were efficiently extracted from multiphase continuous monitoring data.Despite the significant impact of image processing during plot clipping on processing efficiency,the software can extract traits from approximately 500 plots/min in most application cases.The software offers a user-friendly graphical user interface and interfaces for customizing or integrating various feature extraction algorithms,thereby significantly reducing barriers for nonexperts.It holds the promise of significantly accelerating data production in UAV phenotyping experiments.展开更多
For this special section on software systems special section, discuss important issues that will shape several research leaders in software systems, as guest editors for this this field＇s future directions. The essa...For this special section on software systems special section, discuss important issues that will shape several research leaders in software systems, as guest editors for this this field＇s future directions. The essays included in this roundtable article cover research opportunities and challenges for emerging software systems such as data processing programs （Xiangyu Zhang） and online services （Dongmei Zhang）, with new directions of technologies such as unifications in software testing （Yves Le Traon）, data-driven and evidence-based software engineering （Qing Wang）, and dynamic analysis of multiple traces （Lu Zhang）. Tao Xie, Leading Editor of Special Section on Softwaare Svstem.展开更多
Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a sof...Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a software development framework acting as compiler, cross-project linker and data fetcher, which allow hot-swaps in order to compare various versions of software under test. The flexibility fostered by IRIS allowed modular exchange of software libraries among developers, making it a powerful development tool. The IRIS platform used input data ROOT-ntuples [3];however a new data model is sought, in line with the facilities offered by IRIS. The schematic of a possible new data structuring—as a user implemented object oriented data base, is presented.展开更多
BETA-85 is the kernel of an integrated software engineering environment, hosted by UNIX operating system. It is general-purposed and open-ended, using programming language C as its base language and supporting a varie...BETA-85 is the kernel of an integrated software engineering environment, hosted by UNIX operating system. It is general-purposed and open-ended, using programming language C as its base language and supporting a variety of software development and maintenance methodologies.BETA-85 is organized as a hierarchical structure of environment work bench which, corresponds to a multi-base facility for organizing and managing information entities in the environment. A general-purposed interactive editing system is designed as its user interface. The technical and managerial supports at different levels are specially provided for programming in the small, in the large, and in the many. Therefore, the visibility and traceability of software engineering project are greatly increased, the software productivity is significantly raised, the quality of software products is effectively improved, and the cost of software development and maintenance is strictly controlled.展开更多
Search-based software engineering has mainly dealt with automated test data generation by metaheuristic search techniques. Similarly, we try to generate the test data (i.e., problem instances) which show the worst cas...Search-based software engineering has mainly dealt with automated test data generation by metaheuristic search techniques. Similarly, we try to generate the test data (i.e., problem instances) which show the worst case of algorithms by such a technique. In this paper, in terms of non-functional testing, we re-define the worst case of some algorithms, respectively. By using genetic algorithms (GAs), we illustrate the strategies corresponding to each type of instances. We here adopt three problems for examples;the sorting problem, the 0/1 knapsack problem (0/1KP), and the travelling salesperson problem (TSP). In some algorithms solving these problems, we could find the worst-case instances successfully;the successfulness of the result is based on a statistical approach and comparison to the results by using the random testing. Our tried examples introduce informative guidelines to the use of genetic algorithms in generating the worst-case instance, which is defined in the aspect of algorithm performance.展开更多
基金supported by the Special Edu-cational Research Budget(Research Promotion)[FY2009]the Special Budget(Project)[FY2010 and later years]from the Ministry of Education,Culture,Sports,Science and Technology(MEXT),Japansupported by the GRENE Arctic Climate Change Research Project,Japan
文摘To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on the upper atmosphere has been developed by a Japanese inter-university project called the Inter-university Upper atmosphere Global Observation Network （1UGONET）. The objective of this paper is to describe the infrastructure and tools developed by IUGONET. We focus on the data analysis software. It is written in Interactive Data Language （IDL） and is a plug-in for the THEMIS Data Analysis Software suite （TDAS）, which is a set of IDL libraries used to visualize and analyze satellite- and ground-based data. We present plots of upper atmospheric data provided by IUGONET as examples of applications, and verify the usefulness of the software in the study of polar science. We discuss IUGONET＇s new and unique developments, i.e., an executable file of TDAS that can run on the IDL Virtual Machine, IDL routines to retrieve metadata from the IUGONET database, and an archive of 3-D simulation data that uses the Common Data Format so that it can easily be used with TDAS.
基金supported by National Natural Science Foundation of China(grant nos.42171349 and 42271357)the Major Science and Technology Project of Yunnan Province(202402AE090022)the Major science and technology projects of Inner Mongolia Autonomous Region(2021ZD0046).
文摘With the threshold for crop growth data collection having been markedly decreased by sensor miniaturization and cost reduction,unmanned aerial vehicle(UAV)-based low-altitude remote sensing has shown remarkable advantages in field phenotyping experiments.However,the requirement of interdisciplinary knowledge and the complexity of the workflow have seriously hindered researchers from extracting plot-level phenotypic data from multisource and multitemporal UAV images.To address these challenges,we developed the Integrated High-Throughput Universal Phenotyping(IHUP)software as a data producer and study accelerator that included 4 functional modules:preprocessing,data extraction,data management,and data analysis.Data extraction and analysis requiring complex and multidisciplinary knowledge were simplified through integrated and automated processing.Within a graphical user interface,users can compute image feature information,structural traits,and vegetation indices(Vis),which are indicators of morphological and biochemical traits,in an integrated and high-throughput manner.To fulfill data requirements for different crops,extraction methods such as VI calculation formulae can be customized.To demonstrate and test the composition and performance of the software,we conducted case-related rice drought phenotype monitoring experiments.In combination with a rice leaf rolling score predictive model,leaf rolling score,plant height,VIs,fresh weight,and drought weight were efficiently extracted from multiphase continuous monitoring data.Despite the significant impact of image processing during plot clipping on processing efficiency,the software can extract traits from approximately 500 plots/min in most application cases.The software offers a user-friendly graphical user interface and interfaces for customizing or integrating various feature extraction algorithms,thereby significantly reducing barriers for nonexperts.It holds the promise of significantly accelerating data production in UAV phenotyping experiments.
文摘For this special section on software systems special section, discuss important issues that will shape several research leaders in software systems, as guest editors for this this field＇s future directions. The essays included in this roundtable article cover research opportunities and challenges for emerging software systems such as data processing programs （Xiangyu Zhang） and online services （Dongmei Zhang）, with new directions of technologies such as unifications in software testing （Yves Le Traon）, data-driven and evidence-based software engineering （Qing Wang）, and dynamic analysis of multiple traces （Lu Zhang）. Tao Xie, Leading Editor of Special Section on Softwaare Svstem.
文摘Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a software development framework acting as compiler, cross-project linker and data fetcher, which allow hot-swaps in order to compare various versions of software under test. The flexibility fostered by IRIS allowed modular exchange of software libraries among developers, making it a powerful development tool. The IRIS platform used input data ROOT-ntuples [3];however a new data model is sought, in line with the facilities offered by IRIS. The schematic of a possible new data structuring—as a user implemented object oriented data base, is presented.
文摘BETA-85 is the kernel of an integrated software engineering environment, hosted by UNIX operating system. It is general-purposed and open-ended, using programming language C as its base language and supporting a variety of software development and maintenance methodologies.BETA-85 is organized as a hierarchical structure of environment work bench which, corresponds to a multi-base facility for organizing and managing information entities in the environment. A general-purposed interactive editing system is designed as its user interface. The technical and managerial supports at different levels are specially provided for programming in the small, in the large, and in the many. Therefore, the visibility and traceability of software engineering project are greatly increased, the software productivity is significantly raised, the quality of software products is effectively improved, and the cost of software development and maintenance is strictly controlled.
文摘Search-based software engineering has mainly dealt with automated test data generation by metaheuristic search techniques. Similarly, we try to generate the test data (i.e., problem instances) which show the worst case of algorithms by such a technique. In this paper, in terms of non-functional testing, we re-define the worst case of some algorithms, respectively. By using genetic algorithms (GAs), we illustrate the strategies corresponding to each type of instances. We here adopt three problems for examples;the sorting problem, the 0/1 knapsack problem (0/1KP), and the travelling salesperson problem (TSP). In some algorithms solving these problems, we could find the worst-case instances successfully;the successfulness of the result is based on a statistical approach and comparison to the results by using the random testing. Our tried examples introduce informative guidelines to the use of genetic algorithms in generating the worst-case instance, which is defined in the aspect of algorithm performance.
