scholarly journals A Survey on Situational Awareness of Ransomware Attacks—Detection and Prevention Parameters

2019 ◽  
Vol 11 (10) ◽  
pp. 1168 ◽  
Author(s):  
Juan A. Herrera Silva ◽  
Lorena Isabel Barona López ◽  
Ángel Leonardo Valdivieso Caraguay ◽  
Myriam Hernández-Álvarez
Keyword(s):  
Operating System ◽  
Current Literature ◽  
Situational Awareness ◽  
Early Stage ◽  
Rapid Identification ◽  
Current Situation ◽  
Research Field ◽  
Future Challenges ◽  
Network Communications

In recent years, cybercrime activities have grown significantly, compromising device security and jeopardizing the normal activities of enterprises. The profits obtained through intimidation and the limitations for tracking down the illegal transactions have created a lucrative business based on the hijacking of users’ files. In this context, ransomware takes advantage of cryptography to compromise the user information or deny access to the operating system. Then, the attacker extorts the victim to pay a ransom in order to regain access, recover the data, or keep the information private. Nowadays, the adoption of Situational Awareness (SA) and cognitive approaches can facilitate the rapid identification of ransomware threats. SA allows knowing what is happening in compromised devices and network communications through monitoring, aggregation, correlation, and analysis tasks. The current literature provides some parameters that are monitored and analyzed in order to prevent these kinds of attacks at an early stage. However, there is no complete list of them. To the best of our knowledge, this paper is the first proposal that summarizes the parameters evaluated in this research field and considers the SA concept. Furthermore, there are several articles that tackle ransomware problems. However, there are few surveys that summarize the current situation in the area, not only regarding its evolution but also its issues and future challenges. This survey also provides a classification of ransomware articles based on detection and prevention approaches.

scholarly journals Unconventional Materials Processing Using Spark Plasma Sintering

Ceramics ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 20-40
Author(s):  
Ambreen Nisar ◽  
Cheng Zhang ◽  
Benjamin Boesl ◽  
Arvind Agarwal
Keyword(s):  
Spark Plasma Sintering ◽  
Real Life ◽  
Functional Materials ◽  
Research Field ◽  
Advanced Materials ◽  
Plasma Sintering ◽  
Challenges And Opportunities ◽  
Future Challenges ◽  
Gas Quenching ◽  
Spark Plasma

Spark plasma sintering (SPS) has gained recognition in the last 20 years for its rapid densification of hard-to-sinter conventional and advanced materials, including metals, ceramics, polymers, and composites. Herein, we describe the unconventional usages of the SPS technique developed in the field. The potential of various new modifications in the SPS technique, from pressureless to the integration of a novel gas quenching system to extrusion, has led to SPS’ evolution into a completely new manufacturing tool. The SPS technique’s modifications have broadened its usability from merely a densification tool to the fabrication of complex-shaped components, advanced functional materials, functionally gradient materials, interconnected materials, and porous filter materials for real-life applications. The broader application achieved by modification of the SPS technique can provide an alternative to conventional powder metallurgy methods as a scalable manufacturing process. The future challenges and opportunities in this emerging research field have also been identified and presented.

scholarly journals The Clinical Assessment of MicroRNA Diagnostic, Prognostic, and Theranostic Value in Colorectal Cancer

Cancers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2916
Author(s):  
Hussein Al-Akhrass ◽  
Niki Christou
Keyword(s):  
Colorectal Cancer ◽  
Current Literature ◽  
Clinical Assessment ◽  
Prospective Studies ◽  
Healthcare Management ◽  
Colorectal Cancers ◽  
Liquid Biopsies ◽  
Future Challenges

MiRNAs have recently become a subject of great interest within cancers and especially colorectal cancers in diagnosis, prognosis, and therapy decisions; herein we review the current literature focusing on miRNAs in colorectal cancers, and we discuss future challenges to use this tool on a daily clinical basis. In liquid biopsies, miRNAs seem easily accessible and can give important information toward each step of the management of colorectal cancers. However, it is now necessary to highlight the most sensitive and specific miRNAs for each goal thanks to multicentric prospective studies. Conclusions: by their diversity and the feasibility of their use, miRNAs are getting part of the armamentarium of healthcare management of colorectal cancers.

scholarly journals Detection and Severity Classification of COVID-19 in CT Images Using Deep Learning

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 893
Author(s):  
Yazan Qiblawey ◽  
Anas Tahir ◽  
Muhammad E. H. Chowdhury ◽  
Amith Khandakar ◽  
Serkan Kiranyaz ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Neural Networks ◽  
Early Stage ◽  
Similarity Coefficient ◽  
Dice Similarity Coefficient ◽  
Lung Region ◽  
Computed Tomography Images ◽  
Feature Pyramid ◽  
Severity Levels

Detecting COVID-19 at an early stage is essential to reduce the mortality risk of the patients. In this study, a cascaded system is proposed to segment the lung, detect, localize, and quantify COVID-19 infections from computed tomography images. An extensive set of experiments were performed using Encoder–Decoder Convolutional Neural Networks (ED-CNNs), UNet, and Feature Pyramid Network (FPN), with different backbone (encoder) structures using the variants of DenseNet and ResNet. The conducted experiments for lung region segmentation showed a Dice Similarity Coefficient (DSC) of 97.19% and Intersection over Union (IoU) of 95.10% using U-Net model with the DenseNet 161 encoder. Furthermore, the proposed system achieved an elegant performance for COVID-19 infection segmentation with a DSC of 94.13% and IoU of 91.85% using the FPN with DenseNet201 encoder. The proposed system can reliably localize infections of various shapes and sizes, especially small infection regions, which are rarely considered in recent studies. Moreover, the proposed system achieved high COVID-19 detection performance with 99.64% sensitivity and 98.72% specificity. Finally, the system was able to discriminate between different severity levels of COVID-19 infection over a dataset of 1110 subjects with sensitivity values of 98.3%, 71.2%, 77.8%, and 100% for mild, moderate, severe, and critical, respectively.

scholarly journals Cross-evaluation of social mining for classification of depressed online personas

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Alina Trifan ◽  
José Luis Oliveira
Keyword(s):  
Transfer Learning ◽  
Early Stage ◽  
Post Partum ◽  
Evaluation Study ◽  
Continuous Increase ◽  
Digital Phenotyping ◽  
Public Datasets ◽  
The Impact ◽  
Social Mining

Abstract With the continuous increase in the use of social networks, social mining is steadily becoming a powerful component of digital phenotyping. In this paper we explore social mining for the classification of self-diagnosed depressed users of Reddit as social network. We conduct a cross evaluation study based on two public datasets in order to understand the impact of transfer learning when the data source is virtually the same. We further complement these results with an experiment of transfer learning in post-partum depression classification, using a corpus we have collected for the matter. Our findings show that transfer learning in social mining might still be at an early stage in computational research and we thoroughly discuss its implications.

Lack of agreement in experts’ classification of patients with early-stage knee osteoarthritis

2021 ◽  
Vol 29 ◽  
pp. S299-S300
Author(s):  
A. Mahmoudian ◽  
S. Lohmander ◽  
M. Englund ◽  
P. Hansen ◽  
F. Luyten
Keyword(s):  
Knee Osteoarthritis ◽  
Early Stage

Machine Learning Arrives in Archaeology

2021 ◽  
Vol 9 (2) ◽  
pp. 186-191
Author(s):  
Simon H. Bickler
Keyword(s):  
Machine Learning ◽  
Rapid Development ◽  
Rapid Identification ◽  
First Century ◽  
Traditional Methods ◽  
Archaeological Practice ◽  
The World ◽  
Archaeological Work ◽  
Archaeological Analysis

OverviewMachine learning (ML) is rapidly being adopted by archaeologists interested in analyzing a range of geospatial, material cultural, textual, natural, and artistic data. The algorithms are particularly suited toward rapid identification and classification of archaeological features and objects. The results of these new studies include identification of many new sites around the world and improved classification of large archaeological datasets. ML fits well with more traditional methods used in archaeological analysis, and it remains subject to both the benefits and difficulties of those approaches. Small datasets associated with archaeological work make ML vulnerable to hidden complexity, systemic bias, and high validation costs if not managed appropriately. ML's scalability, flexibility, and rapid development, however, make it an essential part of twenty-first-century archaeological practice. This review briefly describes what ML is, how it is being used in archaeology today, and where it might be used in the future for archaeological purposes.

Latviešu metālmūzikas albumu nosaukumi

2021 ◽  
pp. 361-369
Author(s):  
Ingars Gusāns
Keyword(s):  
Current Situation ◽  
Creative Work ◽  
Distinctive Character ◽  
Literary Works ◽  
The Third ◽  
Metal Music ◽  
Local Character ◽  
The Subject ◽  
The Common

The aim of the study is to describe the titles of Latvian metal music albums, from the perspective of content, by identifying the common and distinctive character of the metallic music tradition, and perhaps even the local one. Of 241 album titles (data on Dec. 31, 2019), most are in English, some in French, Latin, Russian, some consisting of digits, and 69 titles in Latvian. These titles are the subject of the research. The main source is Encyclopaedia Metallum (www.metal-archives.com), which still does not reflect the current situation concerning Latvian metal music. Album titles in this study are viewed separately from album designs and song titles and are analysed from the perspective of content. The album title is an important part of the work that has been issued because it is an element that makes the audience/buyer pay attention to the album because it must not be forgotten that today the album is also an item that you want to sell. In general, it can be concluded that Latvian metal musicians, with their album titles in Latvian, are mostly following world trends, as evidenced by the integration in the researcher Deena Weinstein’s classification of Dionysian discourse and discourse on chaos. Most titles are more relevant to the discourse on chaos because the thematic circle of chaos is wider. Latvian mythology, along with history, is an up-to-date source for the creative work of bands that is responsible for the local feeling of the titles. A large enough number are titles that are difficult to fit in the Weinstein’s division and form the third group with philosophical titles and simply all sorts of titles. If the philosophical titles follow the world’s trends, the simple titles include the names of the events, tributes, and the titles of literary works, which give them a local character.

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