Article
Green & Sustainable Science & Technology
Samed Ozdemir, Ahmet Yavuzdogan, Burhan Baha Bilgilioglu, Zeynep Akbulut
Summary: Decentralized solar PhotoVoltaic (PV) is a promising energy source for energy self-sufficiency. This study proposes an efficient approach based on point cloud data for estimating the PV potential of roof surfaces, capable of processing various scales from single building to city scale.
Article
Computer Science, Theory & Methods
Hugo B. Lima, Carlos G. R. Dos Santos, Bianchi S. Meiguins
Summary: Music Information Research (MIR) involves modeling and understanding music through visualizations. Papers on music visualization are categorized based on input features, visualized aspects, InfoVis techniques, interaction provided, and user evaluations, offering opportunities for identifying trends and new research directions in the MIR and InfoVis community.
ACM COMPUTING SURVEYS
(2021)
Article
Environmental Sciences
Carlo Navarra, Katerina Vrotsou, Tomasz Opach, Almar Joling, Julie Wilk, Tina-Simone Neset
Summary: This paper describes the progressive development of three approaches with successively increasing analytic functionality for visually exploring and analyzing climate-related volunteered geographic information. The approaches include an initial map application, a visual analysis prototype, and a final custom-made visual analysis interface. These methods are evaluated using volunteered data collected in two campaigns held in Norrkoping, Sweden.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Computer Science, Software Engineering
Benedikt Mayer, Nastasja Steinhauer, Bernhard Preim, Monique Meuschke
Summary: Large-scale issues such as the COVID-19 pandemic, the war against Ukraine, and climate change have brought attention to visual storytelling with data in online journalism, confirming its effectiveness and relevance. However, there is limited research on interactive visual data stories with a spatio-temporal context. This study proposes a design space and analyzes 130 collected web-based visual data stories to understand common techniques used in conveying complex information in a comprehensible way.
COMPUTER GRAPHICS FORUM
(2023)
Article
Biochemical Research Methods
Christian Tischer, Ashis Ravindran, Sabine Reither, Nicolas Chiaruttini, Rainer Pepperkok, Nils Norlin
Summary: Modern bioimaging and related areas such as sensor technology have seen a tremendous development in recent years, resulting in large datasets with sizes reaching terabytes. To address the challenges of processing such large datasets, a Fiji plugin called BigDataProcessor2 was developed.
Article
Agronomy
Gustavo Willam Pereira, Domingos Sarvio Magalhaes Valente, Daniel Marcal de Queiroz, Andre Luiz de Freitas Coelho, Marcelo Marques Costa, Tony Grift
Summary: Machine learning algorithms have been used as an alternative to conventional methods in digital mapping of soil attributes, offering flexibility in using different layers of information. To address the difficulties faced by end users, a Smart-Map plugin was developed, incorporating Ordinary Kriging and Support Vector Machine algorithms, and selecting covariates based on spatial correlation. In a case study in Brazil, the performance of the Smart-Map plugin was evaluated using R-2 and RMSE, showing that Support Vector Machine outperformed Ordinary Kriging in predicting soil attributes.
Article
Public, Environmental & Occupational Health
Lisa Baxter, Jeremy Baynes, Anne Weaver, Anne Neale, Timothy Wade, Megan Mehaffey, Danelle Lobdell, Kelly Widener, Wayne Cascio
Summary: This study developed a tool to apply various COVID-19 re-opening guidelines to the facilities of the U.S. Environmental Protection Agency (EPA), and created a dashboard to display and analyze COVID-19 health data, providing relevant information for management and staff.
INTERNATIONAL JOURNAL OF PUBLIC HEALTH
(2022)
Article
Engineering, Civil
Nidzamuddin Md Yusof, Juffrizal Karjanto, Muhammad Zahir Hassan, Jacques Terken, Frank Delbressine, Matthias Rauterberg
Summary: This study explores the impact of peripheral visual and haptic information on drivers' situation awareness and mental workload. The results show that peripheral visual and haptic information significantly enhances situation awareness, but does not reduce mental workload.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Review
Chemistry, Analytical
Junwei Zhang, Huamin Feng, Biao Liu, Dongmei Zhao
Summary: Network security situation awareness (NSSA) is a crucial aspect of cybersecurity defense, providing macro perspective understanding to identify and assess network behavior, and predict the development trend of network security. This paper presents a state-of-the-art study on NSSA, aiming to bridge the gap between current research and future applications. It provides an introduction to NSSA, discusses recent research progress, explores classic use cases, and addresses challenges and potential research directions.
Article
Computer Science, Artificial Intelligence
Dominik Olszewski
Summary: The new adaptive version of NeRV maintains the advantages of the conventional method while proposing an improvement in calculating data samples' neighborhood widths. By adaptively computing the widths based on input data scattering, the proposed approach enhances the quality of data visualization effectively.
Article
Chemistry, Analytical
Irfan Baig Mirza, Dimitrios Georgakopoulos, Ali Yavari
Summary: This paper proposes novel, semantically based techniques for fusing social media and IoT sensor information spaces, and presents the design of semantic-based situation models for fusing sensor and social media information spaces. It also introduces a comprehensive, fully implemented system that utilizes these techniques and demonstrates improvements in situation awareness from fusing the IoT sensor and social media information spaces through experimental evaluation.
Article
Computer Science, Interdisciplinary Applications
Yiyi Ju, Masahiro Sugiyama, Diego Silva Herran, Jiayang Wang, Akimitsu Inoue
Summary: The mipplot tool is an open-source R package that visualizes data of long-term climate mitigation scenarios in multiple languages. It offers simple commands and a user-friendly interface suitable for both experts and non-experts, with greater flexibility and applicability due to its capability of specifying aggregation rules and different display languages.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Chemistry, Analytical
Thomas E. Lockwood, Mika T. Westerhausen, Philip A. Doble
Summary: Open-sourced software is crucial in the field of mass spectrometry imaging, and Pew2 is a specific and feature-rich open-source image processing software for LA-ICP-MS, designed to be fast, user-friendly, and in line with modern visualization philosophies.
ANALYTICAL CHEMISTRY
(2021)
Article
Chemistry, Medicinal
Raphael Robidas, Claude Y. Legault
Summary: CalcUS is an open-source platform that aims to streamline quantum chemistry studies, making it more accessible through a user-friendly interface.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Geosciences, Multidisciplinary
Lorenz M. Fischer, Christian Sommer, Kathryn E. Fitzsimmons
Summary: Future climate projections indicate an expansion of drylands and increased mobilization of desert sediments, making it important to investigate the formation of dryland landscapes such as dunefields. So far, investigations of erg-scale geomorphic patterns have been limited due to technological limitations. However, recent developments in open-source remote sensing datasets and GEOBIA software offer new opportunities for cartography and statistical analysis of dunefields. A study in central Australia used open-source GIS to characterize a diverse linear dunefield, providing insights into the interactions between dunes and other landforms.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Yapo Abole Serge Innocent Oboue, Yunfeng Chen, Sergey Fomel, Wei Zhong, Yangkang Chen
Summary: Strong noise can disrupt the recorded seismic waves and negatively impact subsequent seismological processes. To improve the signal-to-noise ratio (S/N) of seismological data, we introduce MATamf, an open-source MATLAB code package based on an advanced median filter (AMF) that simultaneously attenuates various types of noise and improves S/N. Experimental results demonstrate the usefulness and advantages of the proposed AMF workflow in enhancing the S/N of a wide range of seismological applications.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Upkar Singh, P. N. Vinayachandran, Vijay Natarajan
Summary: The Bay of Bengal maintains its salinity distribution due to the cyclic flow of high salinity water and the mixing with freshwater. This paper introduces an advection-based feature definition and algorithms to track the movement of high salinity water, validated through comparison with observed data.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Bijal Chudasama, Nikolas Ovaskainen, Jonne Tamminen, Nicklas Nordback, Jon Engstro, Ismo Aaltonen
Summary: This contribution presents a novel U-Net convolutional neural network (CNN)-based workflow for automated mapping of bedrock fracture traces from aerial photographs acquired by unmanned aerial vehicles (UAV). The workflow includes training a U-Net CNN using a small subset of photographs with manually traced fractures, semantic segmentation of input images, pixel-wise identification of fracture traces, ridge detection algorithm and vectorization. The results show the effectiveness and accuracy of the workflow in automated mapping of bedrock fracture traces.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Ruizhen Wang, Siyang Wan, Weitao Chen, Xuwen Qin, Guo Zhang, Lizhe Wang
Summary: This paper proposes a novel framework to generate a finer soil strength map based on RCI, which uses ensemble learning models to obtain USCS soil classification and predict soil moisture, in order to improve the resolution and reliability of existing soil strength maps.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhanlong Chen, Xiaochuan Ma, Houpu Li, Xuwei Xu, Xiaoyi Han
Summary: Simulated terrains are important for landform and terrain research, disaster prediction, rescue and disaster relief, and national security. This study proposes a deep learning method, IGPN, that integrates global information and pattern features of the local terrain to generate accurate simulated terrains quickly.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Daniele Secci, Vanessa A. Godoy, J. Jaime Gomez-Hernandez
Summary: Neural networks excel in various machine learning applications, but lack physical interpretability and constraints, limiting their accuracy and reliability in predicting complex physical systems' behavior. Physics-Informed Neural Networks (PINNs) integrate neural networks with physical laws, providing an effective tool for solving physical problems. This article explores recent developments in PINNs, emphasizing their application in solving unconfined groundwater flow, and discusses challenges and opportunities in this field.
COMPUTERS & GEOSCIENCES
(2024)
Article
Computer Science, Interdisciplinary Applications
Renguang Zuo, Ying Xu
Summary: This study proposes a hybrid deep learning model consisting of a one-dimensional convolutional neural network (1DCNN) and a graph convolutional network (GCN) to extract joint spectrum-spatial features from geochemical survey data for mineral exploration. The physically constrained hybrid model performs better in geochemical anomaly recognition compared to other models.
COMPUTERS & GEOSCIENCES
(2024)