Cervical cancer is one of the leading causes premature mortality among women worldwide and more than 85% these deaths are in developing countries. There several risk factors associated with cervical cancer. In this paper, we developed a predictive model for predicting outcome patients cancer, given patterns from individual medical records preliminary screening. This work presents decision tree (DT) classification algorithm to analyze Recursive feature elimination (RFE) least absolute...

Breast cancer is a prevalent disease that affects mostly women, and early diagnosis will expedite the treatment of this ailment. Recently, machine learning (ML) techniques have been employed in biomedical informatics to help fight breast cancer. Extracting information from data support clinical tedious time-consuming task. The use feature extraction has significantly changed whole process diagnosis. This research work proposed model for classification To achieve this, vector (SVM) was...

A series of alkylsulfonyl 1H-benzo[d]imidazole derivatives were synthesized and evaluated for anticancer activity against human breast cancer cells, MCF-7 in vitro. The cytotoxic potential was determined using the xCELLigence real-time cell analysis, expression levels genes related to microtubule organization, tumor suppression, apoptosis, cycle, proliferation examined by quantitative polymerase chain reaction. Molecular docking Bcl-2 carried out AutoDock Vina, while ADME studies performed...

Accuracy improvement has been one of the most outstanding issues in recommender systems research community. Recently, multi-criteria that use multiple criteria ratings to estimate overall rating have receiving considerable attention within domain. This paper proposes a neural network model for improving prediction accuracy systems. The was trained using simulated annealing algorithms and integrated with two samples single-rating presents experimental results each techniques together their...

Background:Interactive learning tools are emerging as effective educational materials in the area of computer science and engineering. It is a research domain that rapidly expanding because its positive impacts on motivating improving students’ performance during process.Material methods:Taking into account style index preferences engineering learners, work uses software techniques to develop interactive environment. also Java Technology implantation part.Results:This paper introduces an...

We often make decisions on the things we like, dislike, or even don't care about.However, taking right becomes relatively difficult from a variety of items different sources.Recommender systems are intelligent decision support software tools that help users to discover might be interest them.Various techniques and approaches have been applied design implement such generate credible recommendations users.A multi-criteria recommendation technique is an extended approach for modeling user's...

Recommender systems are powerful online tools that help to overcome problems of information overload. They make personalized recommendations users using various data mining and filtering techniques. However, most the existing recommender use a single rating represent preference user on an item. These techniques have several limitations as towards items may depend attributes items. Multi-criteria extend recommendation incorporate multiple criteria ratings for improving accuracy. modeling in...

Recommender systems (RSs) are increasingly recognized as intelligent software for predicting users’ opinions on specific items. Various RSs have been developed in different domains, such e-commerce, e-government, e-resource services, e-business, e-library, e-tourism, and e-learning, to make excellent user recommendations. In e-learning technology, designed support improve the learning practices of a student or an organization. This survey aims examine works literature that corroborate...

Recent advances in computing allows researchers to propose the automation of hydroponic systems boost efficiency and reduce manpower demands, hence increasing agricultural produce profit. A completely automated system should be equipped with tools capable detecting plant diseases real-time. Despite availability deep-learning-based disease detection models, existing models are not designed for an embedded environment, cannot realistically deployed on resource-constrained IoT devices such as...

Modern technologies have been greatly employed to support teachers and learners for facilitating teaching learning processes. Recommender systems (RSs) technology-enhanced (TEL) are among those new that researched extensively within the past few years. This is because RSs TEL intelligent decision assist internet users in finding suitable objects might match their preferences on kinds of materials they could require enhanced activities. However, most existing used traditional techniques...

With advances in social network sites and easy access to internet services, many learners depend on suggestions from other people the for very essential information concerning learning materials, also collaborate with each order exchange ideas. Current recommender systems focus recommending a sequence of materials based similarities or between new objects ones user is already familiar past. Many prefer collaborative than their own classroom, but major difficulty engaging an online how get...

With the advent of new technologies in medical field, huge amounts cancerous data have been collected and are readily accessible to research community. Over years, researchers employed advanced mining machine learning techniques develop better models that can analyze datasets extract conceived patterns, ideas, hidden knowledge. The mined information be used as a support decision making for diagnostic processes. These techniques, while being able predict future outcomes certain diseases...

Cervical cancer is one of the leading causes premature mortality among women worldwide and more than 85% these deaths are in developing countries. There several risk factors associated with cervical cancer. In this research, aim to develop a predictive model for predicting outcome patient's results, given patterns from individual medical records preliminary screening. This work presents machine learning method using Decision Tree (DT) algorithm analyze Recursive Feature Elimination (RFE)...

To achieve meaningful learning goals, both pedagogues and tutees need frequent supports on how to obtain relevant materials. Recommendation systems have been proved as important tools that assist learners in getting useful objects. Nowadays, various recommendation techniques are used build a system can find suggests objects learners. This paper proposed use multi-criteria technique aggregation function approach for modeling user preferences improve the quality of recommendations given by...

Accuracy improvement is among the primary key research focuses in area of recommender systems. Traditionally, systems work on two sets entities, Users and Items, to estimate a single rating that represents user’s acceptance an item. This technique was later extended multi-criteria use overall from ratings degree by users for items. The concern still open community find suitable optimization algorithms can explore relationships between multiple compute rating. One approaches doing this assume...

Recently, researchers proposed automation of hydroponic systems to improve efficiency and minimize manpower requirements. Thus increasing profit farm produce. However, a fully automated system should be able identify cases such as plant diseases, lack nutrients, inadequate water supply. Failure detect these issues can lead damage crops loss capital. This paper presents an Internet Things-based machine learning for disease detection using Deep Convolutional Neural Network (DCNN). The model...

Many factors can hinder learning process especially in the classroom, but greatest among all is student's preferences. This research work implemented a fuzzy-like mobile-based system that be used to determine preferences of engineering students based on their responses answering 55 questions with multiple choice answers system's questionnaire. The will automatically categorizes between Active-Reflective, Sensory-Intuitive, Visual-Verbal, Sequential-Global, and Social-Emotional learners....

With the recent advances in clinical technologies, a huge amount of data has been accumulated for breast cancer diagnosis. Extracting information from to support diagnosis is tedious and time-consuming task. The use machine learning mining techniques significantly changed whole process In this research, prediction model developed using features extracted individual medical screening tests. To overcome problem overfitting obtain good accuracy, Linear Discriminant Analysis (LDA) applied...