Hypervisor-Level Ransomware Detection in Cloud Using Machine Learning

Ransomware attack incidences have been on the rise for a few years. The attacks have evolved over the years. The severity of these attacks has only increased in the cloud era. This article discusses the evolution of ransomware attacks targeting cloud storage and explores existing ransomware detection solutions. It also presents a methodology for generating a dataset for detecting ransomware in the cloud and discusses the results, including feature selection and normalization. The article proposes a system for detecting attacks in virtualized environments using machine learning models and evaluates the performance of different classification models. The proposed system is shown to have high accuracy of 96.6% in detecting ransomware attacks in virtualized environments at the hypervisor level

Brain Tumour Detection Using Resnet 50 and Mobilenet

The scientific community defines a brain tumour as  a mass or growth of abnormal cells in the brain. A brain tumour is a development of abnormal cells, some of which may develop  into cancer. MRI scans are the most common way to find brain  tumours and are used to detect brain cancer. There are different  types of tumours exist. They are cancerous(malignant)and non- cancerous(benign) in the brain identification of unchecked tissue growth in MRI may help us diagnose brain cancer. Machine Learning and Deep Learning algorithms are used to identify this tissue growth. When these algorithms are applied to MRI scans, a faster prediction of brain tumours is made, and   a better degree of accuracy aids in treating patients. MRI scans   allow us to perform rapid analysis and identify the exact location of unwanted tissue growth. Various uses include image   recognition and identifying objects, image classification, segmentation, neural network and data processing. The proposed model successfully classified the MRI image into four   classes: glioma, meningioma, and pituitary tumour and no tumour, indicating that the given brain MRI has no tumour. In  this paper the proposed models are MobileNet and Resnet50 and gives accuracy of 0.98. These models classifies the type of tumour very accurately

An Overview of Inflammatory Spondylitis for Biomedical Imaging Using Deep Neural Networks

Ankylosing Spondylitis (AS) is an axial spine inflammatory illness and also chronic that might present with a range of clinical symptoms and indicators. The illness is most frequently characterized by increasing spinal stiffness and persistent back discomfort. The affect of the sacroiliac joints, spine, peripheral joints, entheses and digits are the main cause of the illness. AS symptoms include reduced spinal mobility, aberrant posture, hip and dactylitis, enthesitis, peripheral arthritis, and buttock pain. With their exceptional picture classification ability, the diagnosis of AS illness has been transformed by deep learning techniques in artificial intelligence (AI). Despite the excellent results, these processes are still being widely used in clinical practice at a moderate rate. Due to security and health concerns, medical imaging applications utilizing deep learning must be viewed with caution. False instances, whether good or negative, have far-reaching effects on the well-being of patients and these are to be considered. These are extracted from the fact of the state-of-the-art of deep learning (DL) algorithms lack internal workings comprehension and have complicated interconnected structure, huge millions of parameters, and also a "black box" aspect compared to conventional machine learning (ML) algorithms. XAI (Explainable AI) approaches make it easier to comprehend model predictions, which promotes system reliability, speeds up the diagnosis of the AS disease, and complies with legal requirements

Digital tanlock loop architecture with no delay

This article proposes a new architecture for a digital tanlock loop which eliminates the time-delay block. The �=2 (rad) phase shift relationship between the two channels, which is generated by the delay block in the conventional timedelay digital tanlock loop (TDTL), is preserved using two quadrature sampling signals for the loop channels. The proposed system outperformed the original TDTL architecture, when both systems were tested with frequency shift keying input signal. The new system demonstrated better linearity and acquisition speed as well as improved noise performance compared with the original TDTL architecture. Furthermore, the removal of the time-delay block enables all processing to be digitally performed, which reduces the implementation complexity. Both the original TDTL and the new architecture without the delay block were modelled and simulated using ATLAB/Simulink. Implementation issues, including complexity and relation to simulation of both architectures, are also addressed

Assessing the impact of velocity dip and wake coefficients on velocity prediction for open channel flows

The aim of the present study is to assess the impact of the velocity-dip and wake strength on the velocity prediction using the dip modified laws. The dip modified laws, particularly the dip modified log wake law (DMLW-law), are preferred over the traditional wall laws in the narrow open channels. This is mainly because these analytical-based laws basically rely on parameters for the velocity dip (α) caused by secondary flow and for the wake strength (Π) due to the turbulence and boundary walls. In this study, comprehensive expressions for estimating these two key parameters were proposed and tested for smooth and rough flows. The results indicated that the proposed expressions can noticeably improve the application of the DMLW-law model to both smooth and rough flow

Assessing the leanness in product design: a model for planned design reuse

Shrinking product lifecycles, tough international competition, swiftly changing technologies, ever increasing customer quality expectation and demanding high variety options are some of the forces that drive next generation of development processes. To overcome these challenges, design cost and development time of product has to be reduced as well as quality to be improved. Design reuse is considered one of the lean strategies to win the race in this competitive environment. design reuse can reduce the product development time, product development cost as well as number of defects which will ultimately influence the product performance in cost, time and quality. However, it has been found that no or little work has been carried out for quantifying the effectiveness of design reuse in product development performance such as design cost, development time and quality. Therefore, in this study we propose a systematic design reuse based product design framework and developed a design leanness index (DLI) as a measure of effectiveness of design reuse. The DLI is a representative measure of reuse effectiveness in cost, development time and quality. Through this index, a clear relationship between reuse measure and product development performance metrics has been established. Finally, a cost based model has been developed to maximise the design leanness index for a product within the given set of constraints achieving leanness in design process

Continuous Improvement Practices in Manufacturing Companies in the Sultanate of Oman

Purpose The aims of this study were to identify Continuous Improvement (CI) practices prevailing in the manufacturing companies with regards to Visual Management, Employee Engagement, Leadership and Risk Management; to identify continuous improvement tools that have been adopted by the manufacturing companies; and to analyse the critical success factors for implementing CI practices in manufacturing companies. Design/methodology/approach For this study, a survey questionnaire was used to collect the CI practices information from manufacturing companies in Oman.  146 samples were collected from 75 manufacturing units selected at random from the Public Establishment for Industrial Estate database. The data was analysed for reliability, robustness, ranking tests using Statistical Package for Social Statistics (SPSS). Findings The majority of the manufacturing firms were using only the CI program for the past five years. However, there was not substantial cost savings for these businesses. The overall sales increased, while the average processing time had declined and the product recalls also had increased. The most important factors identified for the effective implementation of CI in industrial firms were effective communication, top management encouragement, and employee involvement and conducive organization atmosphere. Social Implications Sultanate of Oman like any other GCC countries is undergoing a critical phase in economy because of the oil price plunge combined with ongoing COVID-19 pandemic. The paper will be of use to academics, researchers and continuous improvement practitioners. Originality/value So far, very few studies have been conducted in analysing the factors correlated to CI in the Omani context and no study was carried out before in exploring the CI application in the Sultanate of Oman.  &nbsp

Factorial Analysis of the Critical Success Factors of Continuous Improvement (CI) Techniques in the Companies from Sohar Industrial Estate, Oman

Purpose: The research objectives was to analyze the role of continuous improvement (CI) techniques in manufacturing in Oman in the CI process and to investigate the crucial factors of CI and the application techniques of CI that has been implemented by the manufacturing companies during the CI process. Design/methodology/approach: A survey questionnaire was developed with the baseline of CI practices used by manufacturing companies in Oman and convenient sampling method was used to collect the data.  146 completely filled in questionnaires were collected from 75 manufacturing units out of the entire Public Establishment database. The data was tabulated, compiled. The robustness was tested along with the ranking tests and the factor analysis using SPSS and AMOS. Findings: The results reveal that the Omani manufacturing companies using structured CI programs had lesser product recalls, lead to increased overall sales, decrease in processing time. Further, it is also revealed that the CI culture and Employee Performance Measurement and Review are instrumental in translating into company savings. Research limitations/implications: This research was limited to Sohar Industrial estate only. As there are nine industrial estates in Oman, the research can be undertaken to study the CI practices adoption in all the other industrial estates as well. Social implications: Countries from all over the world are facing numerous challenges due to COVID-19. The paper will help the manufacturing companies in decision making towards the process improvement. Originality/Value: There is not many studies on continuous improvement practices within the Omani manufacturing industry and this paper examines the status of CI implementation in manufacturing companies in Oman