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What Are the Trends in Eco-Design Research When We Talk about Digital Technology? - A Five Year Analytical Dive into Research data

What Are the Trends in Eco-Design Research When We Talk abou...

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2023 International Symposium on World Ecological Design, ISWED 2023

作者： Zhuang, Nan Ma, Yanni Zhai, Shuo Zhao, Xin Weng, Shitong Ma, Zhenyuan Shi, Shang Ying, Fangtian School of Software Technology Zhejiang University China College of Computer Science and Technology Zhejiang University China Polytechnic Institute Zhejiang University China

ISBN: (纸本)9781643685069

The convergence of digital technology with eco-design offers an integrative approach, merging environmental sustainability with technological innovation in design. In the realm of eco-design, there is a growing emphasis on the application of digital technology. However, the focal areas and trends of eco-design studies utilizing digital technology remain underexplored. This leads to a deficiency in our deep understanding and prediction of the evolution and transformation of this domain. To comprehend the progression in this domain, we curated and scrutinized a dataset of 1,359 papers related to digital technology and eco-design presented at the CHI conference over the past five years. Through keywords analysis from the past half-decade, we pinpointed prevailing research areas in eco-design utilizing digital technology, such as virtual reality, sustainability, health, and human-computer interaction. We also gathered essential information about the papers for descriptive statistical analysis, including the count, authors' nationalities and gender distribution, and the scale of the authorship teams. Coupled by the visual insights from keyword clouds, we discerned trends in eco-design research in the backdrop of digital technology. Our findings underscore that the eco-design domain, when integrated with digital technology, persistently captivates academic interest, with comparatively smaller teams often embarking on projects in this research sphere. Predominantly, researchers from the United States and male participants lead these endeavors. Moreover, there's an escalating emphasis on people-centered design, striving to engineer solutions that harmonize environmental interactions with health promotions. This study's outcomes furnish insights for a more profound exploration in the realm of digital technology and eco-design, offering recommendations to further propel sustainable progress and innovative design. © 2024 The Authors.

关键词： Ecodesign

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Interactive visual analysis of COVID-19

Interactive Visual Analysis of COVID-19

引用

International conference on Information visualisation (iv)

作者： Margaret Varga Adelica Ndoni Susan Traeber-Burdin April Rose Panganiban Valérie Lavigne Department of Biology University of Oxford Oxford United Kingdom NATO Communication and Information Agency (NCIA) The Hague Netherlands Human Machine Systems Fraunhofer FKIE Bonn Germany Air Force Reserch Laboratory Dayton USA Defence Research and Development Canada Valcartierr Canada

ISBN: (数字)9798350380163

ISBN: (纸本)9798350380170

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. It was first detected in China in December 2019. It spreads between people in close contact. On the 11 th March 2020 the WHO declared the outbreak of the virus as a pandemic, which signaled a significant acceleration in the global response to the COVID-19 outbreak, and recognized the widespread transmission of the virus across multiple countries and continents. data regarding COVID-19 was gathered and made available for open access. These data sources offer invaluable information for tracking, raising awareness and understanding of COVID-19, recognizing its impact, as well as informing the general public, health authorities, policy makers, situation managers and decision makers. However, COVID-19 data in its raw form is complex and difficult to understand and analyze. The application of visualization together with human factor design principles in a complex systems framework provides an effective means for exploiting these big and complex datasets. These techniques can transform such inherently non-visual data into intuitive visual forms that enable users to gain insight into, and understanding of, information contained within the data. This paper discusses the application of visualization and development of interactive dashboards, set in a complex systems framework, to provide an effective means for the users to explore, analyze and gain awareness of the situation, thus enabling informed decision making.

关键词： COVID-19 visualization Analytical models Pandemics Decision making User centered design data visualization Transforms Complexity theory Complex systems

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45th European conference on Information Retrieval, ECIR 2023

45th European Conference on Information Retrieval, ECIR 2023

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45th European conference on Information Retrieval, ECIR 2023

ISBN: (纸本)9783031282409

The proceedings contain 45 papers. The special focus in this conference is on Information Retrieval. The topics include: Towards Detecting Interesting Ideas Expressed in Text;towards Linguistically Informed Multi-objective Transformer Pre-training for Natural Language Inference;dirichlet-Survival Process: Scalable Inference of Topic-Dependent Diffusion Networks;consumer Health Question Answering Using Off-the-Shelf Components;MOO-CMDS+NER: Named Entity Recognition-Based Extractive Comment-Oriented Multi-document Summarization;fragmented visual Attention in Web Browsing: Weibull analysis of Item Visit Times;don’t Raise Your Voice, Improve Your Argument: Learning to Retrieve Convincing Arguments;learning Query-Space Document Representations for High-Recall Retrieval;investigating Conversational Search Behavior for Domain exploration;evaluating Humorous Response Generation to Playful Shopping Requests;joint Span Segmentation and Rhetorical Role Labeling with data Augmentation for Legal Documents;trigger or not Trigger: Dynamic Thresholding for Few Shot Event Detection;The Impact of a Popularity Punishing Hyperparameter on ItemKNN Recommendation Performance;neural Ad-Hoc Retrieval Meets Open Information Extraction;augmenting Graph Convolutional Networks with Textual data for Recommendations;utilising Twitter Metadata for Hate Classification;topic-Enhanced Personalized Retrieval-Based Chatbot;evolution of Filter Bubbles and Polarization in News Recommendation;capturing Cross-Platform Interaction for Identifying Coordinated Accounts of Misinformation Campaigns;improving the Generalizability of the Dense Passage Retriever Using Generated datasets;segmentCodeList: Unsupervised Representation Learning for Human Skeleton data Retrieval;knowing What and How: A Multi-modal Aspect-Based Framework for Complaint Detection;preface;Extractive Summarization of Financial Earnings Call Transcripts: Or: When GREP Beat BERT;what Is Your Cause for Concern? Towards Interpretable Complaint

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45th European conference on Information Retrieval, ECIR 2023

45th European Conference on Information Retrieval, ECIR 2023

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45th European conference on Information Retrieval, ECIR 2023

ISBN: (纸本)9783031282430

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International conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2022

International Conference on Medical Imaging and Computer-Aid...

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International conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2022

ISBN: (纸本)9789811667749

The proceedings contain 47 papers. The special focus in this conference is on Medical Imaging and Computer-Aided Diagnosis. The topics include: Non-pooling Network for Medical Image Segmentation;Lung CT analysis Using 3D Disparity-Regularised Block Matching for Stereotactic Ablative Body Radiotherapy;Identification of Melanoma Diseases from Multispectral Dermatological Images Using a Novel BSS Approach;2.5D Lightweight Network Integrating Multi-scale Semantic Features for Liver Tumor Segmentation;registration of Medical Image Sequences Using Auto-differentiation;Small Animal Imaging: Iterative Algorithms Combined with Regularization Schemes, an Application to a Dual-Head Small Animal PET;Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Networks (DSMS-CNN);a Change Detection with Machine Learning Approach for Medical Image analysis;u-Net##: A Powerful Novel Architecture for Medical Image Segmentation;exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation;optimising Chest X-Rays for Image analysis by Identifying and Removing Confounding Factors;3D-3D Rigid Registration: A Comparative analysis Study on Femoral Bone Scans;fully Automatic Axial Vertebral Rotation Measurement of Children with Scoliosis Using Convolutional Neural Networks;diagnostic Accuracy and Reliability of Deep Learning-Based Human Papillomavirus Status Prediction in Oropharyngeal Cancer;optimizing the Illumination of a Surgical Site in New Autonomous Module-based Surgical Lighting Systems;an Eye-Tracking Based Machine Learning Model Towards the Prediction of visual Expertise for Electrocardiogram Interpretation;Synthetic data as a Tool to Combat Racial Bias in Medical AI: Utilizing Generative Models for Optimizing Early Detection of Melanoma in Fitzpatrick Skin Types iv–VI;BD-Transformer: A Transformer-Based Approach for Bipolar Disorder Classification Using Audio;establishment and analysis of a Combined Diagnostic Model of Acute Myocard

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An Intelligent visual Big data Analytics Framework for Supporting Interactive exploration and visualization of Big OLAP Cubes 24

An Intelligent Visual Big Data Analytics Framework for Suppo...

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24th International conference Information visualisation (iv)

作者： Ordonez, Carlos Chen, Zhibo Cuzzocrea, Alfredo Garcia-Garcia, Javier Univ Houston Houston TX 77004 USA Haliburton Houston TX USA LORIA Villers Les Nancy France Univ Calabria Commenda Di Rende Italy Univ Nacl Autonoma Mexico C3 Mexico City DF Mexico

ISBN: (纸本)9781728191348

visual big data analytics aims at supporting big data analytics via visual metaphors, with a plethora of applications in modern settings and scenarios. In all these domains, visual big data analytics paradigms offer several advantages, among which some noticeable ones are: (i) fast knowledge understanding from big data sets;(ii) pattern and trend discovery from big data sets;(iii) entity and model discovery from big data sets;(iv) sharing insights among organizations. Among several proposals, OLAP-based visual big data analytics methodologies and tools represents a successful case of visual big data analytics frameworks, which is entirely based on OLAP analysis. In this context, an OLAP cube is typically explored with multiple aggregations selecting different subsets of cube dimensions to analyze trends or to discover unexpected results. Unfortunately, such analytic process is generally manual and fails to statistically explain results. On the basis of these considerations, in this paper we propose an innovative OLAP-shaped visual big data analytics framework that incorporates a state-of-the-art statistical technique for supporting exploration and visualization of OLAP data cubes. An experimental evaluation with a medical data set presents statistically significant results and interactive visualizations, which link risk factors and degree of disease.

关键词： OLAP Cubes visual Big data Analytics Big data analysis Intelligent Big data Systems

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45th European conference on Information Retrieval, ECIR 2023

45th European Conference on Information Retrieval, ECIR 2023

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45th European conference on Information Retrieval, ECIR 2023

ISBN: (纸本)9783031282379

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Towards a Task-based Guidance in Exploratory visual Analytics 54

Towards a Task-based Guidance in Exploratory Visual Analytic...

引用

54th Annual Hawaii International conference on System Sciences

作者： Mutlu, Belgin Gashi, Milot Sabol, Vedran Pro2Future GmbH Linz Austria Graz Univ Technol Graz Austria Know Ctr GmbH Graz Austria

ISBN: (纸本)9780998133140

Exploring large datasets and identifying meaningful information is still an active topic in many application fields. Dealing with large datasets is currently not only a matter of simply collecting and structuring data for retrieval, but sometimes it also requires the provision of adequate means for guiding the user through the exploration process. visualizations have shown to be an effective method in this context, the reason being that since they are grounded on visual cognition, people understand them and can naturally perform visual operations such as clustering, filtering and comparing quantities. However, systems which help us to create visualizations often require specific knowledge in data analysis, which ordinary users typically do not possess. To address this gap, we propose a system that guides the user in the data analysis process. To achieve this, the system observes current user behavior, tries to infer the task of the user and recommends the next analysis steps to help her to carry out the task.

关键词： Large dataset

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KRAKEN: A Knowledge-Based Recommender System for Analysts, to Kick exploration up a Notch 1

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14th International conference on Innovative Security Solutions for Information Technology and Communications, SecITC 2021

作者： Brisse, Romain Boche, Simon Majorczyk, Frédéric Lalande, Jean-Francois Malizen Rennes France CentraleSupélec Inria Univ. Rennes 1 CNRS IRISA Rennes France Direction Générale de l’Armement-Maîtrise de l’Information Bruz France

ISBN: (数字)9783031175107

ISBN: (纸本)9783031175091

During a computer security investigation, a security analyst has to explore the logs available to understand what happened in the compromised system. For such tasks, visual analysis tools have been developed to help with log exploration. They provide visualisations of aggregated logs, and help navigate data efficiently. However, even using visualisation tools, the task can still be difficult and tiresome. The amount and the numerous dimensions of the logs to analyse, the potential stealthiness and complexity of the attack may end with the analyst missing some parts of an attack. We offer to help the analyst finding the logs where her expertise is needed rapidly and efficiently. We design a recommender system called KRAKEN that links knowledge coming from advanced attack descriptions into a visual analysis tool to suggest exploration paths. KRAKEN confronts real world adversary knowledge with the investigated logs to dynamically provide relevant parts of the dataset to explore. To evaluate KRAKEN we conducted a user study with seven security analysts. Using our system, they investigated a dataset from the DARPA containing different Advanced Persistent Threat attacks. The results and comments of the security analysts show the usability and usefulness of the recommender system. © 2022, Springer Nature Switzerland AG.

关键词： Digital forensics

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exploration of Electronic Structure and Optical Properties Hafnium (iv) Oxide and Its 12% Si, Ge and Sn with Material data analysis by Computational Methods 4th

Exploration of Electronic Structure and Optical Properties H...

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International conference on 4th Industrial Revolution and Beyond, IC4IR 2021

作者： Chakma, Unesco Kumer, Ajoy Hossain, Tomal Sayed Hossain, Md. Monsur Alam, Md. Khandakar, Nusrat Jahan Shariful Islam, Md. Shaikh, Rubel Hazrat Ali, Md. Department of Electrical and Electronics Engineering European University of Bangladesh Gabtoli Dhaka1216 Bangladesh Laboratory of Computational Research for Drug Design and Material Science Department of Chemistry European University of Bangladesh Gabtoli Dhaka1216 Bangladesh Department of Chemistry Bangladesh University of Engineering Technology Dhaka1000 Bangladesh Center for Research Reactor Bangladesh Atomic Energy Commission Dhaka Bangladesh Department of Civil Engineering European University of Bangladesh Gabtoli Dhaka1216 Bangladesh European University of Bangladesh Gabtoli Dhaka1216 Bangladesh

ISBN: (纸本)9789811980312

This research work conveys the computational analysis of hafnium (iv) oxide and its doped crystal by Si, Ge and Sn replacing on the oxygen atom in HfO2, as hafnium (iv) oxide has been used in power-electronics devices of MOSFETs and electronics as RRAM due to wide band gap which makes a vast problems creating high resistances. Regarding this case, the hafnium (iv) oxide has selected inputs how the band gap has decreased later than doping by the large surface area atoms, such as Si, Ge and Sn. The first principle method in view of density functional theory (DFT) expresses the structural geometry, electronic structure and optical properties utilizing conformist calculations pertaining to HfO2 executing the computational avenue of the CASTAP regulation from material studio 8.0. The band gap was found in 4.340 eV, 2.033 eV, 1.686 eV and 3.210 eV for HfO2, Hf0.88Si0.12O2 Hf0.88Ge0.12O2 and Hf0.88Sn0.12O2 crystals through the Generalized Gradient Approximation (GGA) with Perdew Burke Ernzerhof (PBE), and the DFT and PDOS were simulated for evaluating the nature of 6s2, 5p6, 4f14, 5d2 orbital for a Hf atom, 3s2, 2p6 orbital for Si atom, 4s2,3p6, 3d10 orbital for Ge atom, 4d10, 5s2, 5p2 for Sn atom, 2s and 2p orbital for O atom of Hf0.88Ge0.12O2 and Hf0.88Sn0.12O2 crystals. The optical properties, for instance, absorption, reflection, refractive index, conductivity, dielectric function and loss function, were calculated. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Energy gap

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