Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of Alzheimer's disease. The system employs MRI and feature extraction methods to categorize images. This paper adopts the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset includes functional MRI and Positron-Version Tomography scans for Alzheimer's patient identification, which were produced for people with Alzheimer's as well as typical individuals. The proposed technique uses MRI brain scans to discover and categorize traits utilizing the Histogram Features Extraction (HFE) technique to be combined with the Canny edge to representing the input image of the Convolutional Neural Networks (CNN) classification. This strategy keeps track of their instances of gradient orientation in an image. The experimental result provided an accuracy of 97.7% for classifying ADNI images.
The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t
... Show MoreThe aim of advancements in technologies is to increase scientific development and get the overall human satisfaction and comfortability. One of the active research area in recent years that addresses the above mentioned issues, is the integration of radio frequency identification (RFID) technology into network-based systems. Even though, RFID is considered as a promising technology, it has some bleeding points. This paper identifies seven intertwined deficiencies, namely: remote setting, scalability, power saving, remote and concurrent tracking, reusability, automation, and continuity in work. This paper proposes the construction of a general purpose infrastructure for RFID-based applications (IRFID) to tackle these deficiencies. Finally
... Show MoreToday many people suffering from health problems like dysfunction in lungs and cardiac. These problems often require surveillance and follow up to save a patient's health, besides control diseases before progression. For that, this work has been proposed to design and developed a remote patient surveillance system, which deals with 4 medical signs (temperature, SPO2, heart rate, and Electrocardiogram ECG. An adaptive filter has been used to remove any noise from the signal, also, a simple and fast search algorithm has been designed to find the features of ECG signal such as Q,R,S, and T waves. The system performs analysis for medical signs that are used to detected abnormal values. Besides, it sends data to the Base-Stati
... Show MoreImage databases are increasing exponentially because of rapid developments in social networking and digital technologies. To search these databases, an efficient search technique is required. CBIR is considered one of these techniques. This paper presents a multistage CBIR to address the computational cost issues while reasonably preserving accuracy. In the presented work, the first stage acts as a filter that passes images to the next stage based on SKTP, which is the first time used in the CBIR domain. While in the second stage, LBP and Canny edge detectors are employed for extracting texture and shape features from the query image and images in the newly constructed database. The p
In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the
... Show MoreFace recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima
... Show MoreAny software application can be divided into four distinct interconnected domains namely, problem domain, usage domain, development domain and system domain. A methodology for assistive technology software development is presented here that seeks to provide a framework for requirements elicitation studies together with their subsequent mapping implementing use-case driven object-oriented analysis for component based software architectures. Early feedback on user interface components effectiveness is adopted through process usability evaluation. A model is suggested that consists of the three environments; problem, conceptual, and representational environments or worlds. This model aims to emphasize on the relationship between the objects
... Show MoreThe cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.