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Topic Review
Missing-Digit Sum
Missing-digit sums are integer numbers that are equal to the sum of numbers created by deleting one or more digits at a time from the original number. For example, the OEIS lists these two integers as missing-digit sums in base ten: Missing-digit sums are therefore a subset of narcissistic numbers, when these are defined as numbers that are equal to some manipulation of their own digits (for example, 153 and 132 are narcissistic numbers in base ten because 153 = 13 + 53 + 33 and 132 = 13 + 32 + 12 + 31 + 23 + 21).
  • 399
  • 27 Oct 2022
Topic Review
Measure of Presortedness
In computer science, a measure of presortedness of a sequence represents how much work is required to sort the sequence. If the sequence is pre-sorted, sorting the sequence entirely require little work, hence it is expected to have a small measure of presortedness. In particular, the measure of a sorted sequence is 0. Some sorting algorithms are more efficient on pre-sorted list, as they can use this pre-work into account to avoid duplicate work. The measure of presortedness allows to formalize the notion that an algorithm is optimal for a certain measure.
  • 399
  • 07 Nov 2022
Topic Review
Forensic Methods for Image Inpainting
The rapid development of digital image inpainting technology is causing serious hidden danger to the security of multimedia information. Efforts have been devoted to developing forensic methods for image inpainting. They can be roughly divided into the following two categories: conventional inpainting forensics methods and deep learning-based inpainting forensics methods.
  • 399
  • 26 Jun 2023
Topic Review
Patent Analysis and Tools
Patent analysis is a field that concerns the analysis of patent records, for the purpose of extracting insights and trends, and it is widely used in various fields. Despite the abundance of proprietary software employed for this purpose, there is currently a lack of easy-to-use and publicly available software that can offer simple and intuitive visualizations, while advocating for open science and scientific software development.
  • 399
  • 25 Dec 2023
Topic Review
Medical Case-Based Multiple-Choice Questions
Moving from old-style multiple-choice questions (MCQs) to ones that are more related to real clinical situations is really important. It helps in growing critical thinking and practical use, especially since MCQs are still the primary method for testing knowledge in medicine.
  • 399
  • 15 Jan 2024
Topic Review
Tensorsketch
User:RMCD bot/subject notice In statistics, machine learning and algorithms, a tensor sketch is a type of dimensionality reduction that is particularly efficient when applied to vectors that have tensor structure. Such a sketch can be used to speed up explicit kernel methods, bilinear pooling in neural networks and is a cornerstone in many numerical linear algebra algorithms.
  • 398
  • 30 Sep 2022
Topic Review
Coordination Center for TLD RU
The Coordination Center for TLD RU (the acronym - the Coordination Center for domains .RU/.РФ; the full name - ANO “The Coordination Center for TLD RU”) — is the administrator of Top Level National Domains .RU and .PФ. It serves as the national registry.
  • 398
  • 07 Nov 2022
Topic Review
Deep Learning for Protein-Protein Interaction
Deep learning is steadily leaving its transformative imprint across multiple disciplines. Within computational biology, it is expediting progress in the understanding of Protein–Protein Interactions (PPIs), key components governing a wide array of biological functionalities.
  • 398
  • 04 Jul 2023
Topic Review
Deep-Learning-Based Approach to Keystroke-Injection Payload Generation
USB-based keystroke-injection attacks involve manipulating USB devices to inject malicious keystrokes into the target system. These attacks exploit the trust of USB devices and can bypass traditional security measures if they are taken into account and adapted to the systems designed to prevent such attacks. By impersonating a keyboard or using programmable USB devices, attackers can execute unauthorized commands or gain unauthorized access to sensitive information mimicking legitimate user keystrokes. Different attack vectors, such as BadUSB and rogue device attacks, have drawn attention to the potential risks and ramifications involved in these types of attacks. However, the emergence of advanced attack methods necessitates the development of more sophisticated countermeasures. These attacks pose a significant security risk and highlight the importance of implementing strong defenses to mitigate the potential impact of such exploits, especially those that can bypass keystroke dynamics systems using rogue USB devices with implants.
  • 398
  • 17 Jul 2023
Topic Review
Self-Supervised Transfer Learning for Fine-Grained Image Recognition
Fine-grained image recognition aims to classify fine subcategories belonging to the same parent category, such as vehicle model or bird species classification. This is an inherently challenging task because a classifier must capture subtle interclass differences under large intraclass variances. Most previous approaches are based on supervised learning, which requires a large-scale labeled dataset. However, such large-scale annotated datasets for fine-grained image recognition are difficult to collect because they generally require domain expertise during the labeling process. Researchers propose a self-supervised transfer learning method based on Vision Transformer (ViT) to learn finer representations without human annotations. Interestingly, it is observed that existing self-supervised learning methods using ViT (e.g., DINO) show poor patch-level semantic consistency, which may be detrimental to learning finer representations. Motivated by this observation, researchers propose a consistency loss function that encourages patch embeddings of the overlapping area between two augmented views to be similar to each other during self-supervised learning on fine-grained datasets.
  • 398
  • 07 Oct 2023
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