Preferred Language
Articles
/
bxZnKYoBVTCNdQwCwZFW
Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease
...Show More Authors

Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have not obtained a formal early diagnosis, and this may provide them with a chance to access suitable healthcare facilities. An early diagnosis biomarker capable of measuring brain cell degeneration due to AD would be valuable. Potentially, electroencephalogram (EEG) can play a valuable role in the early diagnosis of AD. EEG is noninvasive and low cost, and provides valuable information about brain dynamics in AD. Thus, EEG-based biomarkers may be used as a first-line decision-support tool in AD diagnosis and could complement other AD biomarkers.

Crossref
View Publication
Publication Date
Fri Sep 23 2022
Journal Name
Specialusis Ugdymas
Intrusion Detection System Techniques A Review
...Show More Authors

With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.

Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Shared Congestion Detection: A Comparative Study
...Show More Authors

Most Internet-tomography problems such as shared congestion detection depend on network measurements. Usually, such measurements are carried out in multiple locations inside the network and relied on local clocks. These clocks usually skewed with time making these measurements unsynchronized and thereby degrading the performance of most techniques. Recently, shared congestion detection has become an important issue in many computer networked applications such as multimedia streaming and
peer-to-peer file sharing. One of the most powerful techniques that employed in literature is based on Discrete Wavelet Transform (DWT) with cross-correlation operation to determine the state of the congestion. Wavelet transform is used as a de-noisin

... Show More
View Publication Preview PDF
Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
edge detection using modification prewitt operators
...Show More Authors

in this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators

View Publication Preview PDF
Crossref
Publication Date
Thu Jul 01 2010
Journal Name
International Journal Of Advancements In Computing Technology
Implementation of digital chaotic signal generator based on reconfigurable LFSRs for multiple access communications
...Show More Authors

This paper describes the digital chaotic signal with ship map design. The robust digital implementation eliminates the variation tolerance and electronics noise problems common in analog chaotic circuits. Generation of good non-repeatable and nonpredictable random sequences is of increasing importance in security applications. The use of 1-D chaotic signal to mask useful information and to mask it unrecognizable by the receiver is a field of research in full expansion. The piece-wise 1-D map such as ship map is used for this paper. The main advantages of chaos are the increased security of the transmission and ease of generation of a great number of distinct sequences. As consequence, the number of users in the systems can be increased. Rec

... Show More
Scopus (3)
Scopus
Publication Date
Sun Oct 01 2017
Journal Name
Ieee Transactions On Neural Systems And Rehabilitation Engineering
A Framework of Temporal-Spatial Descriptors-Based Feature Extraction for Improved Myoelectric Pattern Recognition
...Show More Authors

View Publication
Scopus (126)
Crossref (126)
Scopus Clarivate Crossref
Publication Date
Mon Feb 01 2021
Journal Name
Environmental Monitoring And Assessment
GIS-based assessment of groundwater quality for drinking and irrigation purposes in central Iraq
...Show More Authors

View Publication
Scopus (41)
Crossref (35)
Scopus Clarivate Crossref
Publication Date
Sat Nov 05 2022
Journal Name
Sensors
Enhancement of the CAST Block Algorithm Based on Novel S-Box for Image Encryption
...Show More Authors

Background and Aim: due to the rapid growth of data communication and multimedia system applications, security becomes a critical issue in the communication and storage of images. This study aims to improve encryption and decryption for various types of images by decreasing time consumption and strengthening security. Methodology: An algorithm is proposed for encrypting images based on the Carlisle Adams and Stafford Tavares CAST block cipher algorithm with 3D and 2D logistic maps. A chaotic function that increases the randomness in the encrypted data and images, thereby breaking the relation sequence through the encryption procedure, is introduced. The time is decreased by using three secure and private S-Boxes rather than using si

... Show More
View Publication
Crossref (13)
Crossref
Publication Date
Thu Jan 13 2022
Journal Name
Medical & Biological Engineering & Computing
An integrated entropy-spatial framework for automatic gender recognition enhancement of emotion-based EEGs
...Show More Authors

View Publication
Scopus (12)
Crossref (13)
Scopus Clarivate Crossref
Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
...Show More Authors

View Publication
Crossref (1)
Clarivate Crossref
Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
...Show More Authors

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

... Show More
View Publication
Scopus (68)
Crossref (61)
Scopus Clarivate Crossref