The Booming Field of Epitranscriptomics and its Role in Human Disease

2021 ◽  
Author(s):  
Spring Libray
Keyword(s):  
Human Disease ◽  
Detection Methods ◽  
Sequencing Analysis ◽  
Chemical Modifications ◽  
Detection Techniques

Currently, the detection techniques used for transcriptome-wide identification of chemical modifications mainly depend on chemical and antibody-based detection methods followed by sequencing analysis.

scholarly journals Indirectly Supervised Anomaly Detection of Clinically Meaningful Health Events from Smart Home Data

2021 ◽  
Vol 12 (2) ◽  
pp. 1-18
Author(s):  
Jessamyn Dahmen ◽  
Diane J. Cook
Keyword(s):  
Anomaly Detection ◽  
Time Series Data ◽  
Bayesian Optimization ◽  
Detection Methods ◽  
Series Data ◽  
Detection Techniques ◽  
Health Events ◽  
Warm Start ◽  
Health Related ◽  
Unsupervised Algorithms

Anomaly detection techniques can extract a wealth of information about unusual events. Unfortunately, these methods yield an abundance of findings that are not of interest, obscuring relevant anomalies. In this work, we improve upon traditional anomaly detection methods by introducing Isudra, an Indirectly Supervised Detector of Relevant Anomalies from time series data. Isudra employs Bayesian optimization to select time scales, features, base detector algorithms, and algorithm hyperparameters that increase true positive and decrease false positive detection. This optimization is driven by a small amount of example anomalies, driving an indirectly supervised approach to anomaly detection. Additionally, we enhance the approach by introducing a warm-start method that reduces optimization time between similar problems. We validate the feasibility of Isudra to detect clinically relevant behavior anomalies from over 2M sensor readings collected in five smart homes, reflecting 26 health events. Results indicate that indirectly supervised anomaly detection outperforms both supervised and unsupervised algorithms at detecting instances of health-related anomalies such as falls, nocturia, depression, and weakness.

scholarly journals Evaluating effects of focal length and viewing angle in a comparison of recent face landmark and alignment methods

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xiang Li ◽  
Jianzheng Liu ◽  
Jessica Baron ◽  
Khoa Luu ◽  
Eric Patterson
Keyword(s):  
Focal Length ◽  
Ground Truth ◽  
Detection Methods ◽  
Viewing Angle ◽  
Deep Convolutional Neural Networks ◽  
Landmark Detection ◽  
High Performing ◽  
Detection Techniques ◽  
And Performance ◽  
Lens Focal Length

AbstractRecent attention to facial alignment and landmark detection methods, particularly with application of deep convolutional neural networks, have yielded notable improvements. Neither these neural-network nor more traditional methods, though, have been tested directly regarding performance differences due to camera-lens focal length nor camera viewing angle of subjects systematically across the viewing hemisphere. This work uses photo-realistic, synthesized facial images with varying parameters and corresponding ground-truth landmarks to enable comparison of alignment and landmark detection techniques relative to general performance, performance across focal length, and performance across viewing angle. Recently published high-performing methods along with traditional techniques are compared in regards to these aspects.

scholarly journals Standalone Behaviour-Based Attack Detection Techniques for Distributed Software Systems via Blockchain

2021 ◽  
Vol 11 (12) ◽  
pp. 5685
Author(s):  
Hosam Aljihani ◽  
Fathy Eassa ◽  
Khalid Almarhabi ◽  
Abdullah Algarni ◽  
Abdulaziz Attaallah
Keyword(s):  
Attack Detection ◽  
Detection Methods ◽  
Software Systems ◽  
Distributed Software ◽  
Detection Techniques ◽  
Detection Systems ◽  
Novel Approach ◽  
Validation Experiment ◽  
Critical Issues ◽  
Concrete Solution

With the rapid increase of cyberattacks that presently affect distributed software systems, cyberattacks and their consequences have become critical issues and have attracted the interest of research communities and companies to address them. Therefore, developing and improving attack detection techniques are prominent methods to defend against cyberattacks. One of the promising attack detection methods is behaviour-based attack detection methods. Practically, attack detection techniques are widely applied in distributed software systems that utilise network environments. However, there are some other challenges facing attack detection techniques, such as the immutability and reliability of the detection systems. These challenges can be overcome with promising technologies such as blockchain. Blockchain offers a concrete solution for ensuring data integrity against unauthorised modification. Hence, it improves the immutability for detection systems’ data and thus the reliability for the target systems. In this paper, we propose a design for standalone behaviour-based attack detection techniques that utilise blockchain’s functionalities to overcome the above-mentioned challenges. Additionally, we provide a validation experiment to prove our proposal in term of achieving its objectives. We argue that our proposal introduces a novel approach to develop and improve behaviour-based attack detection techniques to become more reliable for distributed software systems.

State of Research on Negative Pressure Techniques Applied to Leak Detection in Liquid Pipelines

2004 ◽  
Author(s):  
Wei Liang ◽  
Lai-bin Zhang ◽  
Zhao-hui Wang
Keyword(s):  
Pressure Wave ◽  
Analytical Techniques ◽  
Leak Detection ◽  
Point Of View ◽  
Detection Methods ◽  
Propagation Mechanism ◽  
Detection Techniques ◽  
Wave Detection ◽  
State Of Research ◽  
Signal Processing Methods

In China, the rarefaction-pressure wave techniques are widely used to diagnose the leakage fault for liquid pipelines. Many leaking propagating assumptions, such as stable single-phased flow hypothesis and none rarefaction wave front hypothesis, are often uncertain in the process of leak detection, which can easily result in some errors. Thus the rarefaction-pressure wave techniques should be integrated with other analytical techniques to compute a more accurate leak location. Additionally, the development trends of rarefaction-pressure wave techniques lie in three aspects. First, rarefaction-pressure wave detection techniques will be integrated with other compatible detection techniques and modern signal processing methods to solve the complex problems encountered in leak detection. Second, studies of rarefaction-pressure wave techniques have advanced to a new stage. The deductions on propagation mechanism of rarefaction-pressure wave have been successfully applied to determine leaks qualitatively. Third, analysis on rarefaction-pressure wave detection techniques will be made from a quantitative point of view. The quantitative data have been used to deduce leak amounts and location. The purpose of this paper is to present the recent achievements in the study of improved rarefaction-pressure wave detection techniques. The rarefaction-pressure wave detection methods, effects of incomplete information conditions, the improvements of rarefaction-pressure wave detection techniques with modified factors and propagation mechanisms are comprehensively investigated. The disfigurements of rarefaction-pressure wave are analyzed. The corresponding methods for resolving such problems as ill diagnostic information and weak amplitude values are put forward. Several methods for stronger small leakage detection ability, higher leakage positioning precision, lower false alarm rates are proposed. The application of rarefaction-pressure wave detection techniques to safety protection of liquid pipelines is also introduced. Finally, the prospect of rarefaction-pressure wave detection techniques is predicted.

Deepfake videos: synthesis and detection techniques –a survey

2021 ◽  
pp. 1-21
Author(s):  
Shahela Saif ◽  
Samabia Tehseen
Keyword(s):  
Social Systems ◽  
Generative Models ◽  
Detection Methods ◽  
Future Research ◽  
Fake News ◽  
Research Directions ◽  
Detection Techniques ◽  
Future Research Directions ◽  
Video Creation ◽  
The One

Deep learning has been used in computer vision to accomplish many tasks that were previously considered too complex or resource-intensive to be feasible. One remarkable application is the creation of deepfakes. Deepfake images change or manipulate a person’s face to give a different expression or identity by using generative models. Deepfakes applied to videos can change the facial expressions in a manner to associate a different speech with a person than the one originally given. Deepfake videos pose a serious threat to legal, political, and social systems as they can destroy the integrity of a person. Research solutions are being designed for the detection of such deepfake content to preserve privacy and combat fake news. This study details the existing deepfake video creation techniques and provides an overview of the deepfake datasets that are publicly available. More importantly, we provide an overview of the deepfake detection methods, along with a discussion on the issues, challenges, and future research directions. The study aims to present an all-inclusive overview of deepfakes by providing insights into the deepfake creation techniques and the latest detection methods, facilitating the development of a robust and effective deepfake detection solution.

Partial Discharge Detection Using Acoustic and Optical Methods in High Voltage Power Equipments: A Review

2013 ◽  
Vol 845 ◽  
pp. 283-286 ◽  
Author(s):  
Malik Abdul Razzaq Al Saedi ◽  
Mohd Muhridza Yaacob
Keyword(s):  
Acoustic Emission ◽  
High Voltage ◽  
Power Transformer ◽  
Partial Discharge ◽  
Optical Detection ◽  
Detection Threshold ◽  
Optical Methods ◽  
Detection Methods ◽  
Detection Techniques ◽  
Advantages And Disadvantages

There is a high risk of insulation system dielectric instability when partial discharge (PD) occurs. Therefore, measurement and monitoring of PD is an important preventive tool to safeguard high-voltage equipment from wanton damage. PD can be detected using optical method to increase the detection threshold and to improve the performance of on-line measurement of PD in noise environment. The PD emitted energy as acoustic emission. We can use this emitted energy to detect PD signal. The best method to detect PD in power transformer is by using acoustic emission. Optical sensor has some advantages such as; high sensitivity, more accuracy small size. Furthermore, in on-site measurements and laboratory experiments, it isoptical methodthat gives very moderate signal attenuations. This paper reviews the available PD detection methods (involving high voltage equipment) such as; acoustic detection and optical detection. The advantages and disadvantages of each method have been explored and compared. The review suggests that optical detection techniques provide many advantages from the consideration of accuracy and suitability for the applications when compared to other techniques.

A Study on Different Edge Detection Techniques in Digital Image Processing

2017 ◽  
pp. 100-122 ◽  
Author(s):  
Shouvik Chakraborty ◽  
Mousomi Roy ◽  
Sirshendu Hore
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Basic Feature ◽  
Detection Methods ◽  
Natural Image ◽  
Detection Techniques ◽  
Image Edges

Image segmentation is one of the fundamental problems in image processing. In digital image processing, there are many image segmentation techniques. One of the most important techniques is Edge detection techniques for natural image segmentation. Edge is a one of the basic feature of an image. Edge detection can be used as a fundamental tool for image segmentation. Edge detection methods transform original images into edge images benefits from the changes of grey tones in the image. The image edges include a good number of rich information that is very significant for obtaining the image characteristic by object recognition and analyzing the image. In a gray scale image, the edge is a local feature that, within a neighborhood, separates two regions, in each of which the gray level is more or less uniform with different values on the two sides of the edge. In this paper, the main objective is to study the theory of edge detection for image segmentation using various computing approaches.

The Detection of Crime

2019 ◽  
pp. 91-112
Author(s):  
Brian H. Bornstein ◽  
Jeffrey S. Neuschatz
Keyword(s):  
Deception Detection ◽  
Lie Detection ◽  
The Body ◽  
Detection Methods ◽  
Major Focus ◽  
The Unconscious ◽  
Detection Techniques ◽  
Psychology And Law ◽  
Physiologically Based ◽  
Better Than

The deception detection method Münsterberg advocates is grounded on principles of association. Although this approach derives partially from a Freudian view of the unconscious, it is not terribly dissimilar to more modern, physiologically based lie detection methods. In recent years, deception detection has become a major focus within psychology and law. Research shows that humans’ ability to detect deception is limited but, summarizing across the body of studies, slightly better than chance. However, most police investigators believe they can detect when suspects are lying. This chapter covers the reliability of modern deception detection techniques with the exception of the polygraph, which is covered in the next chapter.

scholarly journals Polymeric Nanowires for Diagnostic Applications

Micromachines ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 225 ◽  
Author(s):  
Hendrik Hubbe ◽  
Eduardo Mendes ◽  
Pouyan Boukany
Keyword(s):  
Electrical Signal ◽  
Considerable Progress ◽  
Detection Methods ◽  
Chemical Modifications ◽  
Single Wire ◽  
Related Research ◽  
Disordered Structures ◽  
Functional Part ◽  
Diagnostic Applications ◽  
Polymer Nanowires

Polymer nanowire-related research has shown considerable progress over the last decade. The wide variety of materials and the multitude of well-established chemical modifications have made polymer nanowires interesting as a functional part of a diagnostic biosensing device. This review provides an overview of relevant publications addressing the needs for a nanowire-based sensor for biomolecules. Working our way towards the detection methods itself, we review different nanowire fabrication methods and materials. Especially for an electrical signal read-out, the nanowire should persist in a single-wire configuration with well-defined positioning. Thus, the possibility of the alignment of nanowires is discussed. While some fabrication methods immanently yield an aligned single wire, other methods result in disordered structures and have to be manipulated into the desired configuration.

scholarly journals It’s the Little Things (in Viral RNA)

mBio ◽  
2020 ◽  
Vol 11 (5) ◽  
Author(s):  
Jiří František Potužník ◽  
Hana Cahová
Keyword(s):  
Mass Spectrometry ◽  
Viral Rna ◽  
Detection Methods ◽  
Scientific Methodology ◽  
Rna Modifications ◽  
Chemical Modifications ◽  
Viral Protein Synthesis ◽  
Antibody Assays ◽  
Rna Export ◽  
Generation Sequencing

ABSTRACT Chemical modifications of viral RNA are an integral part of the viral life cycle and are present in most classes of viruses. To date, more than 170 RNA modifications have been discovered in all types of cellular RNA. Only a few, however, have been found in viral RNA, and the function of most of these has yet to be elucidated. Those few we have discovered and whose functions we understand have a varied effect on each virus. They facilitate RNA export from the nucleus, aid in viral protein synthesis, recruit host enzymes, and even interact with the host immune machinery. The most common methods for their study are mass spectrometry and antibody assays linked to next-generation sequencing. However, given that the actual amount of modified RNA can be very small, it is important to pair meticulous scientific methodology with the appropriate detection methods and to interpret the results with a grain of salt. Once discovered, RNA modifications enhance our understanding of viruses and present a potential target in combating them. This review provides a summary of the currently known chemical modifications of viral RNA, the effects they have on viral machinery, and the methods used to detect them.

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