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View article: AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage
AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage Open
The AlphaFold Protein Structure Database (AFDB; https://alphafold.ebi.ac.uk), developed by EMBL–EBI and Google DeepMind, provides open access to hundreds of millions of high-accuracy protein structure predictions, transforming research in …
View article: AlphaFold Protein Structure Database and 3D-Beacons: New Data and Capabilities
AlphaFold Protein Structure Database and 3D-Beacons: New Data and Capabilities Open
The AlphaFold Protein Structure Database (https://alphafold.ebi.ac.uk/) has made significant strides in enhancing its utility and accessibility for the life science research community. The recent integration of AlphaMissense predictions en…
Early detection of small- and medium-sized drones in complex environments Open
Unmanned aerial vehicles, or drones, have become a weapon of choice on the modern battlefield. As military and civilian industries try to develop effective counter-drone systems, early detection of flying drones still poses multiple challe…
Fast online feature selection in streaming data Open
The challenge of getting big amounts of high-quality labeled data is compounded by the fact that data labeling is often subjective and requires significant human effort. In many cases, the quality of the labeled data depends entirely on th…
Leveraging peer-review aspects for extractive and abstractive summarization of scientific articles Open
This research introduces an innovative framework that supports the peer-review process by automatically extracting the following four key aspects of a scientific paper: contribution, motivation, claims, and claims support. Leveraging these…
Image segmentation and classification for fission track analysis for nuclear forensics using U-net model Open
This study introduces a novel methodology for the detection and classification of fission track (FT) clusters in microscope images, employing state-of-the-art deep learning techniques for segmentation and classification (Elgad in nuclear f…
Efficient Feature Ranking and Selection Using Statistical Moments Open
Unsupervised feature selection methods can be more efficient than supervised methods, which rely on the expensive and time-consuming data labeling process. The paper introduced skewness as a novel, unsupervised, and computationally efficie…
Mining Eye-Tracking Data for Text Summarization Open
In this study, we introduce and evaluate a novel extractive text summarization methodology, "SummarEyes," based on the visual interaction of the user with the text, using eye-tracking data, as opposed to the traditional approaches based on…
Towards the global equilibrium of COVID‐19: Statistical analysis of country‐level data Open
In our study, we explore the COVID‐19 dynamics to test whether the virus has reached its equilibrium point and to identify the main factors explaining the current R and case fatality rate (CFR) variability across countries. We present a re…
An Interactive Analysis of User-reported Long COVID Symptoms using Twitter Data Open
With millions of documented recoveries from COVID-19 worldwide, various long-term sequelae have been observed in a large group of survivors. This paper is aimed at systematically analyzing user-generated conversations on Twitter that are r…
Pattern Recognition in Vital Signs Using Spectrograms Open
Spectrograms visualize the frequency components of a given signal which may be an audio signal or even a time-series signal. Audio signals have higher sampling rate and high variability of frequency with time. Spectrograms can capture such…
Towards the global equilibrium of COVID-19: statistical analysis of country-level data Open
Objectives: In our study, we explore the COVID-19 dynamics to test whether the virus has reached its equilibrium point and to identify the main factors explaining R and CFR variability across countries. Design: A retrospective study of pub…
The first wave of COVID-19 in Israel—Initial analysis of publicly available data Open
The first case of COVID-19 was confirmed in Israel on February 21, 2020. Within approximately 30 days, the total number of confirmed cases climbed up to 1, 000, accompanied by a doubling period of less than 3 days. About one week later, af…
The First Wave of COVID-19 in Israel – Initial Analysis of Publicly Available Data Open
The first case of COVID-19 was confirmed in Israel on February 21, 2020. Within approximately 30 days, the total number of confirmed cases climbed up to 1,000, accompanied by a doubling period of less than 3 days. About one week later, aft…
Towards story-based classification of movie scenes Open
Humans are entertained and emotionally captivated by a good story. Artworks, such as operas, theatre plays, movies, TV series, cartoons, etc., contain implicit stories, which are conveyed visually (e.g., through scenes) and audially (e.g.,…
Parallel 3DPIFCM Algorithm for Noisy Brain MRI Images Open
In this paper we implemented the algorithm we developed in [1] called 3DPIFCM in a parallel environment by using CUDA on a GPU. In our previous work we introduced 3DPIFCM which performs segmentation of images in noisy conditions and uses p…
Twitter Data Augmentation for Monitoring Public Opinion on COVID-19 Intervention Measures Open
The COVID-19 outbreak is an ongoing worldwide pandemic that was announced as a global health crisis in March 2020. Due to the enormous challenges and high stakes of this pandemic, governments have implemented a wide range of policies aimed…
View article: Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases
Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases Open
The aim of this paper is to introduce an effective fuzzy clustering technique based kernel function to find appropriate subgroups in heterogeneous databases. This paper introduces the effective fuzzy clustering that incorporates weighted b…
View article: Effect of Kernel Learning in Unsupervised Learning for Clustering High Dimensional Databases
Effect of Kernel Learning in Unsupervised Learning for Clustering High Dimensional Databases Open
This paper reviews the effectiveness of kernel learning in unsupervised data analysis using clustering. Cluster analysis is an explorative data analysis tool that assists in discovering hidden patterns or natural grouping and has many effe…
Selecting a representative decision tree from an ensemble of decision-tree models for fast big data classification Open
The goal of this paper is to reduce the classification (inference) complexity of tree ensembles by choosing a single representative model out of ensemble of multiple decision-tree models. We compute the similarity between different models …
Using Graphs for Word Embedding with Enhanced Semantic Relations Open
Word embedding algorithms have become a common tool in the field of natural language processing. While some, like Word2Vec, are based on sequential text input, others are utilizing a graph representation of text. In this paper, we introduc…
Interpretable decision-tree induction in a big data parallel framework Open
When running data-mining algorithms on big data platforms, a parallel, distributed framework, such asMAPREDUCE, may be used. However, in a parallel framework, each individual model fits the data allocated to its own computing node without …
Additional file 1: of PCM-SABRE: a platform for benchmarking and comparing outcome prediction methods in precision cancer medicine Open
PCM-SABRE Library. PCM-SABRE KNIME workflow. (RAR 45850Â kb)
Predicting the Maximum Earthquake Magnitude from Seismic Data in Israel and Its Neighboring Countries Open
This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluat…