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2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023

作者： Lee, Hyungro Guo, Luanzheng Tang, Meng Firoz, Jesun Tallent, Nathan Kougkas, Anthony Sun, Xian-He Pacific Northwest National Laboratory Richland United States Illinois Institute of Technology Chicago United States

ISBN: (纸本)9798400701092

A critical performance challenge in distributed scientific workflows is coordinating tasks and data flows on distributed resources. To guide these decisions, this paper introduces data flow lifecycle analysis. Workflows are commonly represented using directed acyclic graphs (DAGs). data flow lifecycles (DFL) enrich task DAGs with data objects and properties that describe data flow and how tasks interact with that flow. Lifecycles enable analysis from several important perspectives: task, data, and data flow. We describe representation, measurement, analysis, visualization, and opportunity identification for DFLs. Our measurement is both distributed and scalable, using space that is constant per data file. We use lifecycles and opportunity analysis to reason about improved task placement and reduced data movement for five scientific workflows with different characteristics. Case studies show improvements of 15×, 1.9×, and 10 - 30×. Our work is implemented in the dataLife tool. © 2023 ACM.

关键词： Digital storage

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Information system for flood monitoring based on IoT and AI 2

Information system for flood monitoring based on IoT and AI

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2nd International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2023

作者： Wilson, Allan J Pon Bharathi, A. Anoop, M. Angelin Jeba Malar, J. Amrita College of Engineering and Technology Department of Electronics and Communication Engineering Nagercoil India Alpha Arts and Science College Department of Computer Applications Chennai India A.M.Jain College Department of Computer Science Chennai India

ISBN: (纸本)9798350348002

One of the most significant areas where realistic solutions have been put into place to minimise harm is flood management. In this research project, we are creating an IoTenabled adaptive AI technique for effective fluid management. Floods in Kerala, India, have recently seriously damaged the environment, infrastructure, and population. Various IoT devices gathered information on temperature, precipitation rates, and other variables. This study uses a real-time flood visualisation technology to provide an information system for flood monitoring. A system is constructed by first creating two systems: a client system comprised of hardware for detecting floods and a server system comprised of software for monitoring floods and distributing the collected data. All of the information on the flood in Kerala is compiled and split in halves, with the first set serving as training data and the second as test data. The suggested hybrid model is trained using six different machine learning models, and it achieves a maximum accuracy of 99.64%. We were able to prevent losses because to the system's seamless design. Research reveals that the client of the flood detection system may deliver real-time data on flood levels, weather conditions, and temperatures. Additionally, data from client systems can be collected by flood monitoring information systems and stored in MySQL. © 2023 ieee.

关键词： visualization

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Research on the path of integrating the excellent traditional culture into the Ideological and political precision teaching in colleges and universities driven by artificial intelligence 8

Research on the path of integrating the excellent traditiona...

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8th International Conference on Information Systems Engineering, ICISE 2023

作者： Ding, Hengyue Zhang, Bo WTU College of International Business and Economics Ideological and Political Science Department Wuhan430000 China Wuhan Donghu University School of Computer Science Wuhan430000 China

ISBN: (纸本)9798350307009

At present, the precision teaching supported by intelligent technology has some shortcomings in practice, such as single technology bias, lack of thinking of educational cognitive logic, and weakening of teachers' role status. One of the reasons lies in the lack of theoretical perspective on the academic logic of technology-enabled precision teaching. From the perspective of educational cognition, on the basis of clarifying the concept connotation of precision teaching, the research analyzes the existing practical difficulties in the process of its development, such as goal setting, diagnostic evaluation and activity development. Based on the function analysis of intelligent technology, the realization logic of intelligent technology-enabled precision teaching goal, evaluation and activity accurate development is discussed: With the help of group analysis, individual needs diagnosis, mapping relationship analysis to achieve accurate target setting;With the help of data acquisition, analysis mining and visualization technologies, the automatic implementation and intelligent analysis of evaluation are realized to facilitate the hierarchical and precise intervention of the application of evaluation results. With the help of resource recommendation and tool assistance, it can help the accurate design and practice of multiple learning activities, and provide support for the process intervention and real-time feedback of learning activities. © 2023 ieee.

关键词： data visualization

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CPAConv-POCO:a Continuous Position Adaptive Convolution based POCO for lung nodule 3D Reconstruction

CPAConv-POCO:a Continuous Position Adaptive Convolution base...

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2023 ieee International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Jiang, Ao Liu, Feng Zhang, Yun Kong, Ruoshan Luo, Fei Huang, Wen Cai Ni Zou, Jia Wuhan University School of Computer Science Wuhan China General Hospital of Central Theater Command of the PLA Department of Radiology Wuhan China

ISBN: (纸本)9798350337488

The development of CT technology has played a crucial role in assisting doctors in the diagnosis of lung nodules. However, due to their three-dimensional morphology and complex structure, two-dimensional medical images are insufficient for intuitive visualization and analysis of lung nodules, making three-dimensional reconstruction necessary to address this issue. In this study, we propose a novel three-dimensional reconstruction framework called CPAConv-POCO, which is based on point convolution. This framework employs continuous convolution instead of discrete convolution commonly used in traditional image processing tasks to handle unstructured data such as point cloud. Additionally, we introduce a new convolution kernel construction method called Position Adaptive Convolution (PAConv). PAConv dynamically assembles convolution kernels by combining basic weight matrices stored in Weight Bank. The coefficients of these weight matrices are adaptively learned from the positions of points using ScoreNet. This data-driven construction of kernels provides the flexibility of PAConv, allowing it to better handle irregular and unordered point cloud data. The convolution module obtained by combining these two components is named Continuous Position Adaptive Convolution (CPAConv). In our experiments, we extensively evaluated our method on the publicly available LUNA16 and LNDb datasets. In terms of reconstruction accuracy, the Intersection over Union(IoU) of CPAConv-POCO's lung nodule reconstruction reaches 85.70%, which is 1.51% higher than POCO. On the LNDb dataset, the IoU of our method reaches 71.33%, which is 3.33% higher than POCO. We also evaluated the performance of our model on lung nodules of different diameters. On the LUNA16 dataset, the IoU of our method reaches 90.19% on lung nodules with a diameter smaller than 5mm, demonstrating superior reconstruction performance for small lung nodules. © 2023 ieee.

关键词： 3D Reconstruction Continuous Convolution lung nodule Position Adaptive Convolution

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A smart chicken farming platform for chicken behavior identification and feed residual estimation

A smart chicken farming platform for chicken behavior identi...

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2023 ieee International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Yang, Jiezhi Gao, Jun Li, Yanyan Zhou, Antong Qu, Chaochao Zhao, Kuo Wei, Linjing Zhang, Le Liu, Zirong Jiang, Ning Tao, Wenjing Ma, Kangzhe Lu, Quan Zheng, Huiru Mashang Consumer Finance Co. Ltd Chongqing401121 China Sichuan University College of Computer Science Chengdu610065 China Sichuan University School of Mechanical Engineering Coleraine United Kingdom Sichuan University Mashang Consumer Finance Co. Ltd College of Computer Science Chengdu610065 China Gansu Agriculture University School of Computer Science and Technology Lanzhou730070 China William Marsh Rice University Mashang Consumer Finance Co. Ltd HoustonTX77005 United States Key Laboratory of Aquatic Science of Chongqing School of Life Sciences Chongqing400715 China Ulster University BelfastUlsterColeraine School of Computing United Kingdom

ISBN: (纸本)9798350337488

It is very potential to develop digital villages for promoting smart agriculture. As one of the important research fields of smart agriculture, smart chicken farms encounter management problems such as difficulties in quickly and accurately warning of sick and dead chickens and estimating feed residuals. Therefore, this study not only respectively proposed CKTrack and FRCM to detect sick and dead chickens and estimate feed residuals, but also developed a smart chicken farming platform for automagical management. Our main results include (1) the proposed CKTrack method can effectively identify sick and dead chickens under the condition of limited data volume and computing capacity;(2) the proposed FRCM method can accurately estimate the feed residuals;and (3) the smart chicken farming platform developed can provide farmers with functions such as early warning of sick and dead chickens, visualization of the chicken quantity inventory, and feed residual estimation. © 2023 ieee.

关键词： computational biology computer vision instance segmentation object tracking smart chicken farming

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CitadelPolice: An Interactive visualization Environment for Scenario Testing on Criminal Networks

CitadelPolice: An Interactive Visualization Environment for ...

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25th Eurographics Conference on visualization, EuroVis 2023

作者： Roelofsen, Liza A.S. Oetker, Frederike van der Lely, Miles Belleman, Robert G. Quax, Rick Computational Science Lab. University of Amsterdam Netherlands

ISBN: (纸本)9783038682202

Criminal networks have proven to be highly resilient against law enforcement interventions. This resiliency has driven researchers to investigate these networks further. However, the obtained insights reaching law enforcement agencies are generally highly case-dependent or extremely general. Therefore, CitadelPolice aims to provide an environment for visualizing criminal network models on a comprehensive and interactive dashboard. The main advantage of CitadelPolice is that it allows law enforcement to independently test specific scenarios and discover the most effective disruption strategy before deploying it. To achieve this, we used a computational network model based on collaboration with and data from the Dutch Police Force, named the Criminal Cocaine Replacement Model and implemented this on a web-based graph visualization and simulation tool named Citadel. Using this, we can interactively visualize the network while running simulations. To test the effectiveness of the network visualization and implementation of the model, we performed sequential usability testing and compared the results over time. © 2023 The Authors.

关键词： visualization

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SIGFusion: Semantic Information-Guided Infrared and Visible Image Fusion

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ieee TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2024年 73卷

作者： Lv, Guohua Sima, Chaoqun Gao, Yongbiao Dong, Aimei Ma, Guangxiao Cheng, Jinyong Qilu Univ Technol Shandong Acad Sci Shandong Comp Sci Ctr Natl Supercomp Ctr JinanMinist EducKey Lab Comp Jinan 250316 Peoples R China Qilu Univ Technol Shandong Acad Sci Fac Comp Sci & Technol Jinan 250316 Peoples R China Shandong Fundamental Res Ctr Comp Sci Serv Comp Shandong Prov Key Lab Comp Power Internet Jinan 250000 Peoples R China Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China

In the field of image fusion, the fusion of infrared and visible images emerges as a crucial work, retaining the inherent characteristics of each source image for the creation of high-quality fusion images. However, existing fusion algorithms primarily prioritize the visual performance and statistical metrics, often neglecting the requisites of high-level vision tasks. To bridge this gap, this article proposes SIGFusion, an end-to-end method for infrared and visible image fusion. SIGFusion not only considers the visual performance and statistical metrics of the fused image but also focuses on meeting the demands of subsequent high-level vision tasks, thereby enhancing performance in fusion and high-level vision tasks. Concretely, we define significant semantic information as salient targets presenting in both infrared and visible images. By utilizing targets, our fusion network is guided to enhance these salient targets. In contrast to the isolated employ of either infrared or visible images, our target-based method comprehensively utilizes the semantic information within the image. In addition, the utilization of target-based self-attention loss enhances the extraction of vital information from the source image. It is worth noting that masks are only necessary during the training stage and are automatically generated through detection algorithms. We conduct experiments in both image fusion and high-level vision tasks. Experimental results demonstrate the effectiveness of SIGFusion in both infrared and visible image fusion tasks, as well as in subsequent high-level vision tasks. The source code is available at: https://***/poison-pig/SIGFusion.

关键词： Image fusion Semantics visualization Training data mining Computer science Object detection Deep learning high-level vision task image fusion infrared image mask self-attention visible image

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Transformer-based spectro-temporal fusion for Sentinel-2 super-resolution 30

Transformer-based spectro-temporal fusion for Sentinel-2 sup...

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30th International Conference on Systems, Signals and Image Processing, IWSSIP 2023

作者： Pogodzinski, Bartlomiej Tarasiewicz, Tomasz Kawulok, Michal Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland

ISBN: (纸本)9798350337297

Multi-image super-resolution consists in fusing multiple images of the same scene to generate an image of higher spatial resolution. Recently, it has been demonstrated that for remotely sensed multispectral Sentine1-2 images, fusion performed in both spectral and temporal dimensions improves the reconstruction quality. However, the deep networks elaborated for this purpose are quite large and influence of the input data is difficult to interpret. In this paper, we show how to exploit transformer-based image fusion to reduce the number of trainable parameters by 30% and allow for increased interpretability with means of attention rollout. The reported experimental results performed over simulated and real-world data indicate that this does not affect the reconstruction quality, while at the same time the visualization tools may help in developing techniques for input data selection and preprocessing. © 2023 ieee.

关键词： Image fusion

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Comparison of MIMIC-III and MIMIC-IV for big data analytics of health informatics

Comparison of MIMIC-III and MIMIC-IV for big data analytics ...

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2023 ieee International Conference on Big data, Bigdata 2023

作者： Chrimes, Dillon Kim, Chanhee University of Victoria School of Health Information Science Victoria Canada

ISBN: (纸本)9798350324457

The use of a health big data via Medical Information Mart for Intensive Care (MIMIC) data sets has significant advancements in health informatics and clinical research of electronic health records (EHRs) in hospital systems. MIMIC-III and MIMIC-IV data sets are the two latest publicly available iterations of data from electronic records that possess distinct features, variables, and structures in two separate large relational databases. This study aimed to provide big data analytics comparisons of MIMIC-III and MIMIC-IV for experiential learning of health informatics from *** data sets were quantitatively and qualitatively evaluated based on dataset properties (data, list of tables, timeline, patient encounters, software, system), data mining and visual categories (i.e., data size, data structure and schema, features/variables, data quality and completeness, clinical focus, access and use, dashboards, and visualization types), data usability heuristics and utilization (i.e., usability, complexity, granularity, applicability, and capacity). Results showed significant difference of 100 patients across 26 tables for MIMIC-III compared to 2,520 patients across 31 tables for MIMIC-IV data sets, respectively. There were 1716 diagnoses (ICD-9) and 503 procedures (ICD-9) for MIMIC-III. There were 262 diseases categories with >1000 disease instances and >2000 treatments for MIMIC-IV with no ICD codes. Moreover, these data sets contained large (big data) charting events in MIMIC-III of 758,356 rows, and MIMIC-IV eICU with charting events of 1,477,163 for nursing, and respiratory of 176,089 rows, respectively. The results suggest that MIMIC-III provided detailed information for retrospective clinical studies and operations in critical care with high data granularity in terms of re-admission (calculated fields from its admission table), length of stay, prescriptions, caregivers, and diagnosis and procedure (ICD-9). However, it lacked clinical capacity because of no diagno

关键词： dataset health big data health informatics intensive care unit

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An Imperial Analysis of Large Language Models for Automated Tweet Sentiment Prediction

An Imperial Analysis of Large Language Models for Automated ...

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2023 International Conference on Sustainable Communication Networks and Application, ICSCNA 2023

作者： Akhouri, Shivam Ajbani, Vidhi Lakshminarayanan, Ritika Pandey, Trilok Nath Nigam, Meher Shrishti Patra, Sudhansu Shekhar Vellore Institute of Technology School of Computer Science and Engineering Chennai India Kiit Deemed to Be University School of Computer Applications Bhubaneswar India

ISBN: (纸本)9798350313987

Company' s brand perception majorly depends on customer experience and the reviews which follow that. A customer is capable of influencing many more people just on the basis of reviews given by him/her. Google released Pathways Language Model (PaLM) which is a major advancement in Artificial Intelligence (AI). It has been trained with the Pathways System, which allows it to generalize tasks in various domains. In this work, a trustworthy platform is provided for the examination of millions of people's continually moving and changing perspectives. Twitter data is captured, and effective sentiment and data analysis is used to generate trustworthy and helpful info graphics reflecting public opinion. Product sales, stock returns, election outcomes, and other commercial and social events may all be predicted and explained using the information found in tweets. Brands, product manufacturers, and other companies may utilise the information derived from data analysis to better understand their brand image, expand their market share by targeting the relevant demographics at the right moments, and enhance their offerings in terms of both quality and customer service. © 2023 ieee.

关键词： Attention Units data visualization Masks Sentiment Analysis Tokenization

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