The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters.Machine learning techniques now days used to automatically filter the spam in very successful rate.In this paper we review some most popular machine methods (Bayesian classification, k-NN, ANNs, SVMs, Artificial immune system and Rough sets) their applicability problem Email classification.Descriptions algorithms are presented, comparison performance on SpamAssassin...

Abstract To address the public health issue of renal failure and global shortage nephrologists, an AI-based system has been developed to automatically identify kidney diseases. Recent advancements in machine learning, deep learning (DL), artificial intelligence (AI) have unlocked new possibilities healthcare. By harnessing these technologies, we can analyze data gain insights into symptoms patterns, ultimately facilitating remote patient care. create diagnosis for disease, this paper focused...

Ensuring reliable and easily accessible charging infrastructure becomes crucial as more people adopt electric vehicles. This study introduces a recommendation system designed to assist vehicle users in finding convenient stations, enhancing the experience, reducing range anxiety. The employs advanced data analysis techniques offer personalized suggestions based on users' preferences. Real-time factors like station availability, individual preferences, past usage patterns are collected...

Abstract One of the most common cancers among women worldwide is breast cancer (BC), and early diagnosis can save lives. Early detection BC increases likelihood a successful outcome by enabling treatment to start sooner. Even in areas without access specialist physician, machine learning (ML) aids detection. The medical imaging community becoming more interested using ML, deep (DL) increase accuracy screening. Many disease-related data are sparse. However, for DL models perform well, large...

The need for cloud storage grows day after due to its reliable and scalable nature. maintenance of user data at a remote location are severe issues the difficulty ensuring privacy confidentiality. Some security within current systems managed by third party (CTP), who may turn into an untrustworthy insider part. This paper presents automated Encryption/Decryption System Cloud Data Storage (AEDS) based on hybrid cryptography algorithms improve ensure confidentiality without interference from...

Mortality from breast cancer (BC) is among the top causes of death in women. BC can be effectively treated when diagnosed early, improving likelihood that a patient will survive. masses and calcification clusters must identified by mammography order to prevent disease effects commence therapy at an early stage. A misinterpretation may result unnecessary biopsy false-positive results, lowering patient's odds survival. This study intends improve mass detection identification provide better...

Abstract Reliance on deep learning techniques has become an important trend in several science domains including biological science, due to its proven efficiency manipulating big data that are often characterized by their non-linear processes and complicated relationships. In this study, Convolutional Neural Networks (CNN) been recruited, as one of the techniques, be used classifying predicting activities essential oil-producing plant/s through chemical compositions. The model is established...

The accuracy of fingerprint recognition model is extremely important due to its usage in forensic and security fields. Any system has particular network architecture whereas many other networks achieve higher accuracy. To solve this problem a unified model, paper proposes that can automatically specify itself. So, it called an automatic deep neural (ADNN). Our algorithm the appropriate used some significant parameters network. These are number filters, epochs, iterations. It guarantees...

DNA sequence classification is considered a significant challenge for biological researchers to scientifically analyze the enormous volumes of data and discover different features. In genomic research, classifying sequences may help learn new functions protein. Insulin an example protein that human body produces regulate glucose levels. Any mutations in insulin gene would result diabetes mellitus. Diabetes one widely spread chronic diseases, leading severe effects longer term if diagnosis...

Medical image classification (IC) is a method for categorizing images according to the appropriate pathological stage. It crucial stage in computer-aided diagnosis (CAD) systems, which were created help radiologists with reading and analyzing medical as well early detection of tumors other disorders. The use convolutional neural network (CNN) models industry has recently increased, they achieve great results at IC, particularly terms high performance robustness. proposed uses pre-trained...

MicroRNAs (miRNA) are small, non-coding regulatory molecules whose effective alteration might result in abnormal gene manifestation the downstream pathway of their target. miRNA variants can impact transcription, maturation, or target selectivity, impairing usefulness plant growth and stress responses. Simple Sequence Repeat (SSR) based on is a newly introduced functional marker that has recently been used breeding. MicroRNA long RNA (lncRNA) two examples (ncRNA) play vital role controlling...

Deep learning (DL) plays a critical role in processing and converting data into knowledge decisions.DL technologies have been applied variety of applications, including image, video, genome sequence analysis.In deep the most widely utilized architecture is Convolutional Neural Networks (CNN) are taught discriminatory traits supervised environment.In comparison to other classic neural networks, CNN makes use limited number artificial neurons, therefore it ideal for recognition wheat gene...

Water is a prime necessity for the survival and sustenance of all living beings. Thus, it very important to maintain water quality balance. Otherwise, would seriously damage health humans severely affect ecological balance among other species. an factor consider, whether ecosystem needs or contamination levels that directly impact health, hygiene, food, economy. In this study, we have utilized Artificial Intelligence as efficient technique predict without resorting traditional analysis...

In this paper we use machine learning algorithms like SVM, KNN and GIS to perform a behavior comparison on the web pages classifications problem, from experiment see in SVM with small number of negative documents build centroids has smallest storage requirement least line test computation cost.But almost all different nearest neighbors have an even higher cost than KNN.This suggests that some future work should be done try reduce list GIS.

Improving the performance of e-learning services to provide a scalable and effective system is big challenge for educational organizations. The faces many challenges in pedagogical (e.g. learning design content problems), technical resource provisioning financial cost). This article presents an environment based on cloud computing (PCLE) attempt enhance services' by customizing contents course's material depending students' knowledge, experiences, requirements. Also, focuses supporting...

Throughout the years Machine Learning (ML) has increased a lot of consideration on ordinary products as search, filters, recognition and recently genomics. Various strategies incorporate sophisticated artificial neural system designs are all known applications Deep (DL). These days, deep learning could be current fortifying field machine learning. models have fair been shown prepared for both enhancing data encoding simplicity prescient design execution over elective methodologies. Also...

The rapid spread of using Cloud services has become a source attraction for many business owners due to its multiple potential benefits flexibility and efficiency with variant pricing plans that can be suited all types users. However, there are some vulnerabilities have important influential impact on the Computing efficiency, specially ability achieve availability security customers. In this paper we try find way assessing public frameworks E-learning application from two points view;...

Real-time systems are intensively used nowadays. Scheduling algorithms very important to manage the scheduling of tasks in real-time systems. In this paper we give an overview on techniques for uniprocessors and multiprocessors, then present a comparison between multiprocessor which classified into partitioning global algorithms. The results achieved from have showed that parameters such as makespan, waiting time, missed deadlines task preemptions better performance when using partitioned...

Day after day, the importance of relying on nature in many fields such as food, medical, pharmaceutical industries, and others is increasing. Essential oils (EOs) are considered one most significant natural products for use antimicrobials, antioxidants, antitumorals, anti-inflammatories. Optimizing usage EOs a big challenge faced by scientific researchers because complexity chemical composition every EO, addition to difficulties determine best inhibiting bacterial activity. The goal this...