The rising number of malicious threats on computer networks and Internet services owing to a large attacks makes the network security be at incessant risk. One predominant that poses distressing are brute force attacks. A attack uses trial error algorithm decode encrypted data such as passwords or Data Encryption Standard keys, through exhaustive effort (using force) rather than using intellectual strategies. Brute resemble legitimate traffic, making it difficult defend an organization rely...

Network Intrusion Detection Systems (NIDSs) have become standard security solutions that endeavours to discover unauthorized access an organizational computer network by scrutinizing incoming and outgoing traffic for signs of malicious activity. In recent years, deep learning based NIDSs emerged as active area research in cybersecurity several surveys been done on these systems. Although a plethora exists covering this burgeoning body research, there lacks the literature empirical analysis...

U-Net convolutional neural networks have become a cornerstone in medical image processing, particularly for complex segmentation tasks. However, with the proliferation of various variants, it is imperative to evaluate their performance across diverse datasets determine most suitable architecture specific applications. This study presents comprehensive empirical analysis six variants namely; U-Net, U-Net++, ResU-Net, TransU-Net, V-Net, and 3+, focusing on effectiveness segmentation. The...

The deep learning model for crop diseases and pest classification research examined how might improve farming methods, particularly the purpose of accurately classifying pests illnesses that affect crops. importance to world food security was highlighted in introduction, along with need new approaches, such as models, accuracy effectiveness disease control farming. In order evaluate accuracy, secondary datasets obtained from kaggle website were used train test various one which being...

Increasing interest and advancement of internet communication technologies have made network security rise as a vibrant research domain. Network intrusion detection systems (NIDSs) developed indispensable defense mechanisms in cybersecurity that are employed discovery prevention malicious activities. In the recent years, researchers proposed deep learning approaches development NIDSs owing to their ability extract better representations from large corpus data. literature, convolutional...

Regression testing is carried out to ensure that software modifications do not introduce new potential bugs the existing software. Existing test cases are applied in testing, such can run into thousands, and there much time execute all of them. Test Case Prioritization (TCP) a technique order so potentially revealing more faults performed first. With TCP being deemed an optimization problem, several metaheuristic nature-inspired algorithms as Bat, Genetic, Ant colony, Firefly have been...

Deep learning has proven to be a landmark computing approach the computer vision domain. Hence, it been widely applied solve complex cognitive tasks like detection of anomalies in surveillance videos. Anomaly this case is identification abnormal events videos which can deemed as security incidents or threats. solutions for anomaly outperformed other traditional machine solutions. This review attempts provide holistic benchmarking published deep since 2016. The paper identifies, technique,...

Object-Oriented Programming (OOP) has been promoted as a way to produce high-quality software while increasing developer productivity through code reuse. Software systems and underlying designs get more extensive complicated maintaining high degree of quality. One the widely accepted standards for describing architectures is UML Sequence Diagram. A sequence diagram depicts interaction two-dimensional chart players by showing messages delivered received between them. This research aims...

Dimensionality reduction is an essential ingredient of machine learning modelling that seeks to improve the performance such models by extracting better quality features from data while removing irrelevant and redundant ones.The technique aids reduce computational load, avoiding over-fitting, increasing model interpretability.Recent studies have revealed dimensionality can benefit labeled information, through joint approximation predictors target variables a low-rank representation.A...

This paper outlines the guidelines and requirements for students undertaking a computing project as part of their academic program. The is critical component most undergraduate programs designed to provide with opportunity apply theoretical knowledge practical scenarios, demonstrating ability plan, execute, present complex piece work. Unfortunately, there currently lack clear helpful guidance on how conduct elementary research at this level, differentiate from other types projects, report it...

Software complexity refers to the factors that determine level of a software project. High is caused by many attributes used in system and complex logic relationships among these features. The increased undesirable affects maintenance. Over years, Engineering scholars recommended several metrics like Halstead metric, cyclomatic complexity, line code deal with complexity. With increasing as time goes by, there need for better can evaluate more effectively. This research aims develop model...

The paper presents feature extraction methods and classification algorithms used to classify maize leaf disease images. From images, features are extracted passed the machine learning algorithm identify possible based on detected using method. images include of common rust, spot, northern blight healthy An evaluation was done for method see which performs best with image algorithms. Based evaluation, outcomes revealed Histogram Oriented Gradients performed classifiers compared KAZE FAST...

Computer vision has gained momentum in medical imaging tasks. Deep learning and Transfer are some of the approaches used computer vision. The aim this research was to do a comparative study deep transfer detection diabetic retinopathy. To achieve objective, experiments were conducted that involved training four state-of-the-art neural network architectures namely; EfficientNetB0, DenseNet169, VGG16, ResNet50. from scratch. using which pre-trained ImageNet dataset then fine-tuning them solve...

The paper presents feature extraction methods and classification algorithms used to classify maize leaf disease images. From images, features are extracted passed the machine learning algorithm identify possible based on detected using method. images include of common rust, spot, northern blight healthy An evaluation was done for method see which performs best with image algorithms. Based evaluation, outcomes revealed Histogram Oriented Gradients performed classifiers compared KAZE FAST...

In response to the increased demand for more effective authentication methods, usage of biometric secure systems against unwanted access has grown. Because recent COVID-19 pandemic outbreak, any direct physical contact with system should be avoided. Furthermore, current lack necessary security features, making them vulnerable cyber risks such as forgery by unethical employees and unauthorized users. The goal this paper is investigate existing propose best models overcome weaknesses...

Software project management includes a substantial area for estimating software maintenance effort. Estimation of effort improves the overall performance and efficiency software. The Constructive Cost Model (COCOMO) other estimation models are mentioned in literature but inappropriate Python programming language. This research aimed to modify (COCOMO II) by considering range influencing factors get estimations incorporated size complexity metrics estimate A within-subjects experimental...

The purpose of this article sought to design a secure framework that can be used in M-Health systems development. researcher the integrated information theory as for enforcing system security holistic approach. To actualize study, objectives were meant guide carrying out research were: evaluate significance Confidentiality, Integrity and availability on M-health develop integration systems. University Nairobi Hospital because ease accessibility financial resources available conduct research....

This paper provides an Extended Client Based Technique (ECBT) that performs classification on emails using the Bayessian classifier attain in-depth defense by performing textual analysis email messages and attachment extensions to detect flag snooping emails. The technique was implemented python 3.6 in a jupyter notebook. An experimental research method personal computer used validate developed different metrics. validation results produced high acceptable percentage rate based four...