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检索条件"任意字段=IEEE Information Visualization Conference/IEEE Visualization Conference"

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Learning Analytics and MOOLs: there is much more than equipment usage logs

Learning Analytics and MOOLs: there is much more than equipm...

引用

ieee conference on Learning with MOOCS (LWMOOCS) - The 4th Industrial Revolution - From the Pandemic to the Remote World

作者： Zappatore, Marco Univ Salento Lecce Dept Engn Innovat Lecce Italy

ISBN: (数字)9781665424868

ISBN: (纸本)9781665424868

When dealing with online laboratories (either remote or virtual), it is crucial to monitor experiment activities and their outcomes closely, as well as to control how students access to these labs. A similar need also exists for evaluating student learning patterns and results, at both the individual and group level, so that customized study paths and contents can be proposed. To such aim, the research in the field of Learning Analytics has been very prolific in the recent decade, especially in the STEM area. This scenario becomes more challenging when online labs are offered as Massive Open Online Laboratories (MOOLs), large-scale and cloud-based infrastructure allowing students to access catalogs of online experiments on several topics as normally happens with traditional courses accessible via Massive Open Online Courses (MOOCs). This paper aims at focusing on the most relevant aspects of LA for MOOLs in terms of data requirements and data-related challenges, by examining four aspects that are tightly related to LA: data models and catalogs, data quality and scope, data privacy and ethics, and data visualizations. The resulting considerations can be used as a set of guidelines to take into account when designing a MOOL.

关键词： MOOL Learning Analytics Online Laboratories Data Quality Data visualization

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Improving placement of CSA-nets

Improving placement of CSA-nets

引用

2023 International conference on Smart Computing and Application, ICSCA 2023

作者： Alahmadi, Mohammed Koutny, MacIej School of Computing Newcastle University Newcastle upon TyneNE4 5TG United Kingdom

ISBN: (纸本)9798350347050

Communication structured acyclic nets (CSA-nets) are a Petri net-based formalism for representing interactions between subsystems of complex evolving systems (CES). CSA-nets, made up of sets of acyclic-nets, are suitable tools for modelling and visualising event-based systems' execution behaviour. Each subsystem is represented using a separate acyclic net and is linked with other acyclic nets through a set of buffer places. These buffer places link different acyclic nets and depict their interactions. Analysis and visualising CES is a complex task. The hurdle is that a huge number of subsystems resulting from alternative and concurrent scenarios of CESs results in a huge number of buffer places, increasing the number of crossings arcs. One way to mitigate this problem is to filter out some system components. However, this results in information loss. This paper focuses on improving the visualisation of CSA-nets by rearranging their component acyclic nets to minimise the number of crossing arcs. To this end, this paper takes inspiration from the main ideas behind three well-known sorting algorithms, viz. bubble sort, insertion sort and selection sort, and integrates them with formulas to compute crossing. Experimental comparisons are carried out to compare the improvements resulting from following each of the three approaches. The outcomes point to the high effectiveness of the selection sort-inspired approach. © 2023 ieee.

关键词： visualization

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Deep Learning Model to Improve Teaching-Learning Process using Sentiment Analysis 14

Deep Learning Model to Improve Teaching-Learning Process usi...

引用

14th International conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Chauhan, Ganpat Singh Garg, Neeraj Nahta, Ravi Meena, Yogesh Kumar Manipal University Department of Information Technology Jaipur India Skit Department of Computer Engineering Jaipur India Nirma University Department of Computer Engineering India Mnit Computer Science & Engineering Jaipur India

ISBN: (纸本)9798350335095

The integration of teacher capabilities and teaching quality has become a crucial concern in today's Outcome-Based Education (OBE) in higher educational institutes. In addition, there is a requirement to utilize the vast amounts of textual qualitative data obtained through stakeholder's input, primarily the responses to open-ended inquiries, which pose a significant problem to academics and institutions alike. The present research assesses instructors' interpersonal abilities using sentiment analysis techniques. We evaluated certain skills using aspect-based sentiment severity of the over 4,000 inputs left by Stakeholders for higher learning. The latest deep learning models and visualization frameworks were used to carry out the sentiment assessment system. According to the research presented, certain abilities are brought to light using aspect-driven sentiment analysis by the course's structure, teacher's teaching, and student's learning. Additionally, the results show that stakeholders have an equally monolithic and converging perspective, supporting the legitimacy of their opinions and their significant involvement towards the tracking of the teaching environment generally concerning the ultimate aim of improving learning of the students. © 2023 ieee.

关键词： Sentiment analysis

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Force-Sensor Integrated Touch-Feeling Sensor Capable of Acquiring Subtle Texture Changes Caused by Contact Force

Force-Sensor Integrated Touch-Feeling Sensor Capable of Acqu...

引用

ieee International conference on Micro Electro Mechanical Systems

作者： Ryo Akiyama Nachi Mise Kyohei Terao Hidekuni Takao Kagawa University Japan Faculty of Engineering and Design Kagawa University Takamatsu Japan

ISBN: (数字)9798331508890

ISBN: (纸本)9798331508906

In this study, we have realized the first MEMS tactile device that can simultaneously acquire both a fingertip-level acute force sensing function and a micro-scale tactile texture. By simultaneously acquiring the contact force to the object, we demonstrated that it is possible to acquire accurate and stereoscopic information of microshape, frictional force, temperature, and hardness textures that represent surface tactile texture on flexible materials with large contact force dependence.

关键词： Micromechanical devices Temperature sensors Performance evaluation visualization Temperature dependence Shape Stereo image processing Force Tactile sensors Surface texture

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A Controlled Experiment on the Usability of Automated Reflexion Mapping Suggestions Integrated in Code Cities

A Controlled Experiment on the Usability of Automated Reflex...

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ieee International conference on Software Architecture Workshops (ICSAW)

作者： Leon Ehrhardt Rainer Koschke University of Bremen Germany

ISBN: (数字)9798331533366

ISBN: (纸本)9798331533373

Reflexion modeling allows developers to reconstruct and verify their software architecture against its implementation. One step of this method is the mapping of implementation components onto architecture components. Researchers have tried to automate the process of recommending suggestions where to map implementation components. This paper describes how such techniques can be integrated in an interactive approach that is based on software visualization using the code-city metaphor and evaluates the usability of this approach through a controlled experiment. During our user study, effects of reduced cognitive effort and time savings were measured when automated suggestions were available during reflexion modeling, although no statistical significance of the observed differences could be established.

关键词： visualization Codes Software architecture Urban areas Computer architecture Time measurement Software Software reliability Software measurement Usability

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Big Data Based Analysis of Key Parameters of Airbus A321 Flight Trajectory 3

Big Data Based Analysis of Key Parameters of Airbus A321 Fli...

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3rd ieee International conference on Civil Aviation Safety and information Technology, ICCASIT 2021

作者： Zhao, Haimeng Deng, Junwen Zhang, Huimin Pan, Jinjin Sun, Shanlin Guangxi Engineering Research Center for Small UAV System and Application Guilin University of Aerospace Technology Guilin China Information Engineering College Capital Normal University Beijing China

ISBN: (纸本)9781665425186

With the continuous innovation of aviation technology and computer technology, the analysis of flight data has a new direction. When computer simulation technology is combined with flight data, flight data can be presented in the form of images. At present, most of the data visualization is planar trajectory line display, and the trajectory is single, which cannot achieve multi-trajectory comparison. In order to solve the problem of singletrack display and poor contrast, this paper designs a file conversion method to realize the synchronous display of track in multiple periods on Google Earth platform. This paper uses PyCharm, Anaconda, Google Earth software, takes Airbus A321 data as the research object, carries out preprocessing, Comma Separated Values (CSV) file conversion Keyhole Markup Language (KML) file and data visualization function design, realizes the conversion of Airbus A321 data file to visualization file, so that the flight data is presented in the form of three-dimensional images on Google Earth, which visually shows the characteristics of the data. © 2021 ieee

关键词： Data visualization

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Star-ECG: visualization of Electrocardiograms for Arrhythmia and Heart Rate Variability 43

Star-ECG: Visualization of Electrocardiograms for Arrhythmia...

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43rd Annual International conference of the ieee Engineering in Medicine and Biology Society, EMBC 2021

作者： Hsu, Po-Ya Hsu, Po-Han Liu, Hsin-Li Lin, Chi-Te Chou, Hung-Tao Tseng, Yu-Fang Lee, Tsung-Han University of California Department of Computer Science and Engineering San Diego United States Department of Nursing Central Taiwan University of Science and Technology Taiwan Division of Cardiovascular Surgery Department of Surgery Lin Shin Hospital Taiwan

ISBN: (纸本)9781728111797

Conventional electrocardiograms (ECG) are displayed in one dimension. Reading one-dimensional ECG waveform becomes challenging when one wants to visualize the heart rate variability with naked eye. Some ECG visualization techniques have been proposed. However, they rely on domain knowledge to comprehend the heart rate variability. To improve the readability for patients and non-experts, we introduce Star-ECG, a novel ECG visualization approach. Such approach projects ECG waveforms onto a two-dimensional plane in a circular form. We demonstrate that Star-ECG offers not only easily deciphered visualization of cardiac abnormalities and heart rate variability, but also the application of state-of-the-art arrhythmia classification with integrated deep neural networks. We also report positive user feedback from both experts and non-experts that Star-ECG can provide readable and helpful information to monitor cardiac activities. © 2021 ieee.

关键词： Deep learning visualization Electrocardiography Biology Heart rate variability Biomedical monitoring Monitoring

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Spatio-temporal predictive tasks for abnormal event detection in videos 18

Spatio-temporal predictive tasks for abnormal event detectio...

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18th ieee International conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Naji, Yassine Setkov, Aleksandr Loesch, Angelique Gouiffes, Michele Audigier, Romaric Univ Paris Saclay CEA List F-91120 Palaiseau France Univ Paris Saclay CNRS LISN F-91400 Orsay France

ISBN: (纸本)9781665463829

Abnormal event detection in videos is a challenging problem, partly due to the multiplicity of abnormal patterns and the lack of their corresponding annotations. In this paper, we propose new constrained pretext tasks to learn object level normality patterns. Our approach consists in learning a mapping between down-scaled visual queries and their corresponding normal appearance and motion characteristics at the original resolution. The proposed tasks are more challenging than reconstruction and future frame prediction tasks which are widely used in the literature, since our model learns to jointly predict spatial and temporal features rather than reconstructing them. We believe that more constrained pretext tasks induce a better learning of normality patterns. Experiments on several benchmark datasets demonstrate the effectiveness of our approach to localize and track anomalies as it outperforms or reaches the current state-of-the-art on spatio-temporal evaluation metrics.

关键词： Measurement visualization Event detection Tracking Surveillance Benchmark testing Predictive models

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visualization Method of Emotional EEG Features Based on Convolutional Neural Networks

Visualization Method of Emotional EEG Features Based on Conv...

引用

System Simulation Technology and its Application (CCSSTA), ieee China conference on

作者： Lin Lu Dongyue Wu Chao Chen Zhonghuan Information College Tianjin University of Technology Tianjin China School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

In recent years, deep learning models have been increasingly applied in emotional brain computer interfaces. Unlike traditional emotional brain computer interfaces, they perform end-to-end learning on raw EEG signals and use Convolutional Neural Networks (CNN) to analyze emotional EEG signals, which has become a commonly used method in this field. However, due to the fact that CNN is a black box model, the decision-making process between them is not visible, and the decoding process of the model cannot be understood, resulting in poor interpretability of the model and difficulty in convincing the predicted results. Based on the above issues, three different architectures of CNN models were designed, named shallow CNN, middle CNN, and deep CNN according to the depth of the convolutional layers, and three visualization methods were used to improve the interpretability of the CNN model. Visualizing the features learned in the five EEG frequency bands of the midlevel CNN using spectral power difference, it was found that the Delta, Beta, and Gamma EEG frequency bands may be closely related to emotions, with active areas mainly appearing in the frontal, temporal, and occipital regions of the brain. By studying the maximum activation method, the output feature maps of the shallow CNN with the lowest classification performance and the middle CNN with the highest classification performance were visualized. The results showed that the middle CNN had a higher degree of activation and was more sensitive to capturing emotional information.

关键词： visualization Emotion recognition Convolution Computational modeling Predictive models Brain modeling Electroencephalography Brain-computer interfaces Decoding Convolutional neural networks

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Web Scraping for Data Analytics: A BeautifulSoup Implementation 6

Web Scraping for Data Analytics: A BeautifulSoup Implementat...

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6th International conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2023

作者： Abodayeh, Ayat Hejazi, Reem Najjar, Ward Shihadeh, Leena Latif, Rabia Prince Sultan University College of Computer and Information Sciences Riyadh Saudi Arabia

ISBN: (纸本)9781665477239

Web scraping is an essential tool for automating the data-gathering process for big data applications. There are many implementations for web scraping, but barely any of them is based on Python's BeautifulSoup library. Therefore, this paper aims at creating a web scraper that gathers data from any website and then analyzes the data accordingly. For results and analysis, the web scraper has been implemented on the Amazon website which collects a product's name, price, number of reviews, rate, and link. We further highlighted the web scraper's capabilities by assimilating the results into an interface that integrates data visualization techniques to analyze the results gathered. The web scraper proved to be efficient upon execution, in which it scraped five pages and analyzed them, and visualized the information in approximately ten seconds. The limitations as a result of this implementation mainly revolved around applying it to specific product names rather than generic ones and extracting specific information that we wanted from the resulting products. Moreover, BeautifulSoup cannot extract all the data available to not compromise on speed. Further studies can be done by researchers who wish to reuse this implementation and modify it according to the data they want to extract, the analysis they wish to perform, and the website they wish to scrape. The implementation can be helpful, thus, to developers who are novices in the web scraping field or to researchers that wish to reuse the code for small data analytics projects. © 2023 ieee.

关键词： Websites

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