Virtual Digital Retarders System

This work presents a digital inhibitor system for vehicles speed control using Global Positioning System (GPS).In this work the vehicle will reduce its speed by applying the brake out of driver control, programmed coordination points will cause receiving a GPS signal using GPS receiver to an imbedded system, which appears on the LCD screen, to inform the driver that he has entered in the target area. It is found that this system may help in reducing  the huge number of accidents on roads, controlling the inappropriate behavior of reckless drivers, saving time and effort to police departments by decreasing the number of patrols (fixed and moving) spread on the roads. The GPS is used in this project because it’s fixed simply inside the automobile without need of operational cost, and because of the wide coverage for satellite system; the GPS reaches any point on the Earth without need for large numbers even huge numbers of workers without affording additional costs, so the money and manpower can be saved without abandoning the desired goals. This system has many advantages; it can be used in wide range and also can be fitted in any vehicle. Keywords: Road retarders, GPS, Automobile, Deceleration, Digital inhibitor, Virtual retarders

Enhance Linux Security Server Misconfigurations and hardening Methods

The calamity begins if an attacker successfully compromises a system and gains access to high-level privileges. This paper presents and addresses a vulnerable Linux server with typical flaws and configuration errors. This paper aims to show how these widespread vulnerabilities might be used by an attacker to compromise the server. In order to prevent building and setting up a Linux server with risks and low security, as well as to guarantee the integrity and confidentiality of user and customer information, this paper instructs aspiring system administrators and developers on how to avoid making such errors in their initial configuration for this servers set of examples

Performance of Retrieval Information System For Medical Images

Problem statement : In this article the principles of building knowledge and retrieval information system will be applied to medical images in some studied hospital. Since there is a huge number of medical images this system will organizes and manages the operation of retrieving and displaying such images to the persons who need such images in short time and in high quality services. Approach : From relevance assessments we can compute measures of retrieval performance such as: Recall (R), discrimination DC, and Precision. Results: both recall and precision of the system are linearly depend on relevant items correctly retrieved. Conclusion : Number of retrieved images from huge total number of medical images in some hospital determine the systems' recall, discrimination, and precision of the retrieval information system

Distribution Systems Efficiency

This paper constructing a measurement system for determining the efficiency of the distributed system. This efficiency depends on many parameters like number of terminals, number of customers and kind of information, number of nodes, and number of messages. It is found that the efficiency depends strongly on number of messages sent or received inside the distributed system, as the number of messages increased the efficiency decreased. Keywords: distributed system, terminals, efficiency

Measuring the Latency of Semantic Message Oriented Middleware System

Abstract This paper presents an investigation and analysis of the performance of services in publish-subscribe middleware working in the networks. The publish/subscribe paradigm of Message Oriented Middleware provides a loosely coupled communication model between distributed applications. Traditional publish/subscribe middleware uses keywords to match advertisements and subscriptions and does not support deep semantic matching. In this paper the message latency is measured as a relation with message interval for both methods of messaging: Message Oriented Middleware (MOM), and Java Message Service (JMS). It is found that the message latency have an inverse non-linear relationship with message interval. Keywords: publish-subscribe, middleware, semantic matching I Introduction Many large-scale distributed systems today need to connect thousands of systems that are widely distributed and change frequently throughout their lifetime. This challenge motivates the demand for middleware that can provide loosely coupled communication models for distributed systems, allowing each component to evolve independently. While traditional point-to-point and synchronous communication models are popular in rigid and static applications, MessageOriented Middleware (MOM), provides a versatile middleware system to loosely integrate distributed system

A Proposed Arabic Handwritten Text Normalization Method

Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and characters recognition. In the present article, a new method for text baseline detection, straightening, and slant correction for Arabic handwritten texts is proposed. The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direction features of the skeletons are extracted, and the candidate baseline regions are determined. After that, selection of the correct baseline region is done, and finally, the baselines of all components are aligned with the writing line.  The experiments are conducted on IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance

Combining Artificial Intelligence and Image Processing for Diagnosing Diabetic Retinopathy in Retinal Fundus Images

Retinopathy is an eye disease caused by diabetes, and early detection and treatment can potentially reduce the risk of blindness in diabetic retinopathy sufferers. Using retinal Fundus images, diabetic retinopathy can be diagnosed, recognized, and treated. In the current state of the art, sensitivity and specificity are lacking. However, there are still a number of problems to be solved in state-of-the-art techniques like performance, accuracy, and being able to identify DR disease effectively with greater accuracy. In this paper, we have developed a new approach based on a combination of image processing and artificial intelligence that will meet the performance criteria for the detection of disease-causing diabetes retinopathy in Fundus images. Automatic detection of diabetic retinopathy has been proposed and has been carried out in several stages. The analysis was carried out in MATLAB using software-based simulation, and the results were then compared with those of expert ophthalmologists to verify their accuracy. Different types of diabetic retinopathy are represented in the experimental evaluation, including exudates, micro-aneurysms, and retinal hemorrhages. The detection accuracies shown by the experiments are greater than 98.80 percent

Swin Transformer-Based Segmentation and Multi-Scale Feature Pyramid Fusion Module for Alzheimer’s Disease with Machine Learning

Alzheimer Disease (AD) is the ordinary type of dementia which does not have any proper and efficient medication. Accurate classification and detection of AD helps to diagnose AD in an earlier stage, for that purpose machine learning and deep learning techniques are used in AD detection which observers both normal and abnormal brain and accurately detect AD in an early. For accurate detection of AD, we proposed a novel approach for detecting AD using MRI images. The proposed work includes three processes such as tri-level pre-processing, swin transfer based segmentation, and multi-scale feature pyramid fusion module-based AD detection.In pre-processing, noises are removed from the MRI images using Hybrid Kuan Filter and Improved Frost Filter (HKIF) algorithm, skull stripping is performed by Geodesic Active Contour (GAC) algorithm which removes the non-brain tissues that increases detection accuracy. Here, bias field correction is performed by Expectation-Maximization (EM) algorithm which removes the intensity non-uniformity. After completed pre-processing, we initiate segmentation process using Swin Transformer based Segmentation using Modified U-Net and Generative Adversarial Network (ST-MUNet) algorithm which segments the gray matter, white matter, and cerebrospinal fluid from the brain images by considering cortical thickness, color, texture, and boundary information which increases segmentation accuracy. After that, multi-scale feature extraction is performed by Multi-Scale Feature Pyramid Fusion Module using VGG16 (MSFP-VGG16) which extract the features in multi-scale which increases the detection and classification accuracy, based on the extracted features the brain image is classified into three classes such as Alzheimer Disease (AD), Mild Cognitive Impairment, and Normal. The simulation of this research is conducted by Matlab R2020a simulation tool, and the performance of this research is evaluated by ADNI dataset in terms of accuracy, specificity, sensitivity, confusion matrix, and positive predictive value.

Review and Measuring the Efficiency of SQL Injection Method in Preventing E-Mail Hacking

E-mail hackers use many methods in their work, in this article, most of such efficient methods are demonstrated and compared. Different methods and stages of such methods are listed here, in order to reveal such methods and to take care of them but the most common discussed method in this paper is SQL method. SQL injection is a type of security exploit in which the attacker adds SQL statements through a web application’s input fields or hidden parameters to gain access to resources or make changes to data. It is found that the SQL is an efficient way in preventing E-mail hacking and its efficiency reaches about 80%. The method of SQL injection can be considered as an efficient way comparing with other methods