標(biāo)題: Titlebook: Big-Data-Analytics in Astronomy, Science, and Engineering; 9th International Co Shelly Sachdeva,Yutaka Watanobe,Subhash Bhalla Conference p [打印本頁] 作者: 難免 時(shí)間: 2025-3-21 17:26
書目名稱Big-Data-Analytics in Astronomy, Science, and Engineering影響因子(影響力)
書目名稱Big-Data-Analytics in Astronomy, Science, and Engineering影響因子(影響力)學(xué)科排名
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書目名稱Big-Data-Analytics in Astronomy, Science, and Engineering被引頻次
書目名稱Big-Data-Analytics in Astronomy, Science, and Engineering被引頻次學(xué)科排名
書目名稱Big-Data-Analytics in Astronomy, Science, and Engineering年度引用
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書目名稱Big-Data-Analytics in Astronomy, Science, and Engineering讀者反饋
書目名稱Big-Data-Analytics in Astronomy, Science, and Engineering讀者反饋學(xué)科排名
作者: Lipoprotein 時(shí)間: 2025-3-21 22:31 作者: 攀登 時(shí)間: 2025-3-22 02:40
https://doi.org/10.1007/978-94-009-3153-4ova light-curves given the goal of minimizing SALT2 parameter uncertainties. We find a median improvement of 2–6% for SALT2 parameters and 3–11% for photometric redshift with 2–7 additional data points in ., . and/or . compared to random augmentation. The augmentations are automatically strategized 作者: 窒息 時(shí)間: 2025-3-22 06:33 作者: Habituate 時(shí)間: 2025-3-22 11:29 作者: 全等 時(shí)間: 2025-3-22 14:42 作者: Hearten 時(shí)間: 2025-3-22 20:15 作者: 安裝 時(shí)間: 2025-3-22 23:02 作者: 緯線 時(shí)間: 2025-3-23 02:31
Autonomous Real-Time Science-Driven Follow-up of Survey Transientsova light-curves given the goal of minimizing SALT2 parameter uncertainties. We find a median improvement of 2–6% for SALT2 parameters and 3–11% for photometric redshift with 2–7 additional data points in ., . and/or . compared to random augmentation. The augmentations are automatically strategized 作者: 停止償付 時(shí)間: 2025-3-23 09:17
Journey of Database Migration from RDBMS to NoSQL Data Storesf denormalization and selection of columns for denormalization. The assessment of various techniques (based on space or time costs) is presented. The key challenge is to pick a particular datastore on which to apply a specific technique. d) The paper also describes current market-driven migration to作者: Directed 時(shí)間: 2025-3-23 13:01
Cascaded Anomaly Detection with Coarse Sampling in Distributed Systemsects of limiting the number of parameters and the sampling rate reduction on the detection performance of selected classic ML algorithms. Moreover, an example of microservice architecture for coarse network anomaly detection for a network node is presented.作者: octogenarian 時(shí)間: 2025-3-23 14:51
Big Data Management for Policy Support in Sustainable Development requires a holistic perspective of several dimensions of human society and addressing them together. With the increasing proliferation of Big Data, Machine Learning, and Artificial Intelligence, there is increasing interest in designing Policy Support Systems (PSS) for supporting policy formulation作者: 關(guān)節(jié)炎 時(shí)間: 2025-3-23 19:04 作者: 柱廊 時(shí)間: 2025-3-24 01:07
Symbolic Regression for?Interpretable Scientific Discoverytly from data. The combination of SR with deep learning (e.g. Graph Neural Network and Autoencoders) provides a powerful toolkit for scientists to push the frontiers of scientific discovery in a data-driven manner. We briefly overview SR, autoencoders and GNN and highlight examples where they have b作者: 他姓手中拿著 時(shí)間: 2025-3-24 03:49
A Front-End Framework Selection Assistance System with Customizable Quantification Indicators Based evolution and big variety. Prior research has revealed several indicators that developers consider important when selecting a framework. In this study, we propose and develop a system that assists developers in the selection process of a front-end framework, which collects data from repository and 作者: 閑聊 時(shí)間: 2025-3-24 09:00
Autonomous Real-Time Science-Driven Follow-up of Survey Transientses for years to come. However, their data throughput has overwhelmed the ability to manually synthesize alerts for devising and coordinating necessary follow-up with limited resources. The advent of Rubin Observatory, with alert volumes an order of magnitude higher at otherwise sparse cadence, prese作者: opprobrious 時(shí)間: 2025-3-24 12:38
Deep Learning Application for?Reconstruction of?Large-Scale Structure of?the?Universerging method to measure large-scale intensity fluctuations of spectral lines emitted from galaxies and intergalactic medium. Observing their large-scale distributions enables us to study cosmology and galaxy formation and evolution. One of the problems with the LIM is observational noises and line i作者: Fracture 時(shí)間: 2025-3-24 15:06
Identification of Distinctive Behavior Patterns of Bots and Human Teams in Soccert to examine whether is possible to assess similarity of play styles between different human teams and artificial teams in soccer. We rely on “behavior fingerprints” based on heat maps and their comparison using dot product. Our method shows no distinctive differences between the fingerprints of hum作者: achlorhydria 時(shí)間: 2025-3-24 19:12 作者: Foam-Cells 時(shí)間: 2025-3-25 03:10 作者: Commonplace 時(shí)間: 2025-3-25 03:30 作者: homocysteine 時(shí)間: 2025-3-25 09:21 作者: 哺乳動(dòng)物 時(shí)間: 2025-3-25 14:25 作者: 津貼 時(shí)間: 2025-3-25 18:00
Cascaded Anomaly Detection with Coarse Sampling in Distributed Systemstion, is considered. Use of statistical analysis, or machine learning (ML), can result in high computational complexity and requirement to transfer large amount of data from the monitored system’s elements. This enforces monitoring of only major components (e.g., access link, key machine components,作者: 刪除 時(shí)間: 2025-3-25 23:35
Video Indexing System Based on?Multimodal Information Extraction Using Combination of?ASR and?OCRe one of the most popular media. The COVID-19 pandemic has further pushed the envelope, forcing learners to turn to E-Learning platforms. In the absence of relevant descriptions of these videos, it becomes imperative to generate metadata based on the content of the video. In the current paper, an at作者: BANAL 時(shí)間: 2025-3-26 01:21 作者: 妨礙 時(shí)間: 2025-3-26 06:26
Skin Cancer Recognition for Low Resolution Imagese taken by mobile phones, where quality of image is reduced. The aim of this contribution is report on skin cancer recognition when applying machine learning to “l(fā)ow resolution” images. Experiments have been performed on the dataset from the ISIC 2018 Challenge.作者: 小教堂 時(shí)間: 2025-3-26 11:45 作者: instulate 時(shí)間: 2025-3-26 13:01 作者: 河潭 時(shí)間: 2025-3-26 17:57 作者: 玩笑 時(shí)間: 2025-3-26 21:16 作者: 神圣不可 時(shí)間: 2025-3-27 03:10 作者: MUT 時(shí)間: 2025-3-27 05:55
Introduction to Optimization Methodstly from data. The combination of SR with deep learning (e.g. Graph Neural Network and Autoencoders) provides a powerful toolkit for scientists to push the frontiers of scientific discovery in a data-driven manner. We briefly overview SR, autoencoders and GNN and highlight examples where they have b作者: 追逐 時(shí)間: 2025-3-27 13:15
https://doi.org/10.1007/978-94-009-5705-3 evolution and big variety. Prior research has revealed several indicators that developers consider important when selecting a framework. In this study, we propose and develop a system that assists developers in the selection process of a front-end framework, which collects data from repository and 作者: resuscitation 時(shí)間: 2025-3-27 13:52
https://doi.org/10.1007/978-94-009-3153-4es for years to come. However, their data throughput has overwhelmed the ability to manually synthesize alerts for devising and coordinating necessary follow-up with limited resources. The advent of Rubin Observatory, with alert volumes an order of magnitude higher at otherwise sparse cadence, prese作者: Extricate 時(shí)間: 2025-3-27 19:20
Functions, Transformations, Operators,rging method to measure large-scale intensity fluctuations of spectral lines emitted from galaxies and intergalactic medium. Observing their large-scale distributions enables us to study cosmology and galaxy formation and evolution. One of the problems with the LIM is observational noises and line i作者: 大笑 時(shí)間: 2025-3-27 23:07 作者: 大包裹 時(shí)間: 2025-3-28 02:25
Introduction to Optimization of Structuresaging and spectroscopic data is technically challenging, and producing scientific outputs from the big data will remain a key task in the next decade. We develop novel methods based on modern machine learning and deep learning to analyze data from Subaru Hyper Suprime-Cam. In this contribution, we f作者: 寬大 時(shí)間: 2025-3-28 09:24 作者: 凝視 時(shí)間: 2025-3-28 11:50 作者: 加花粗鄙人 時(shí)間: 2025-3-28 18:07
https://doi.org/10.1007/978-1-4612-0511-1sing the environment. Air pollution is one of the negative impacts that come from these developments. An indexing system has been developed for quantitative analysis of air quality, known as Air quality index. AQI’s value depends on various pollutant values such as PM (Particulate matter), CO, NH., 作者: 寬度 時(shí)間: 2025-3-28 20:00
Gopinath Kallianpur,Rajeeva L. Karandikarsformation, migration of data, complex query support, and indexing. This paper presents a) Journey on existing migration techniques from RDBMS (SQL) to NoSQL databases. Schema migration and Data migration are two main aspects while migrating from relational to NoSQL database. b) The various existing作者: 強(qiáng)制令 時(shí)間: 2025-3-29 01:45 作者: 葡萄糖 時(shí)間: 2025-3-29 03:35
Organic Electrochemical Transistor,e one of the most popular media. The COVID-19 pandemic has further pushed the envelope, forcing learners to turn to E-Learning platforms. In the absence of relevant descriptions of these videos, it becomes imperative to generate metadata based on the content of the video. In the current paper, an at作者: genuine 時(shí)間: 2025-3-29 10:36 作者: mettlesome 時(shí)間: 2025-3-29 11:35 作者: 太空 時(shí)間: 2025-3-29 18:21 作者: Harass 時(shí)間: 2025-3-29 23:12 作者: Exploit 時(shí)間: 2025-3-30 03:50 作者: 關(guān)節(jié)炎 時(shí)間: 2025-3-30 04:28
0302-9743 organized in topical sections as follows: Data science: systems; data science: architectures; big data analytics in healthcare support systems, information interchange of web data resources; and business analytics..978-3-030-96599-0978-3-030-96600-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 噴出 時(shí)間: 2025-3-30 11:40
Functions, Transformations, Operators,an teams, however, clearly indicates the difference between human teams and artificial teams. This approach is aimed to assist the design of human-like soccer teams but can also be useful in the domain of sports analytics.作者: Dungeon 時(shí)間: 2025-3-30 13:01 作者: Glaci冰 時(shí)間: 2025-3-30 19:13
Introduction to Optimization of Structuresreconstruct the density field in full three dimensions. Statistical analysis of cosmic structure enables accurate determination of a few fundamental quantities called cosmological parameters that describe the contents and the evolution of the Universe.作者: Peak-Bone-Mass 時(shí)間: 2025-3-30 22:02 作者: 剝削 時(shí)間: 2025-3-31 03:20 作者: 粗語 時(shí)間: 2025-3-31 07:27
Organic Electrochemical Transistor,and ASR generated texts are combined to obtain the final description of the respective video. The dataset contains 400 videos spread across 4 genres. To quantify the accuracy of our descriptions, clustering is performed using the video description to discern between the genres of video.
