Breast cancer is the second most leading cause of women's death in America. To create an accurate prediction model and analyze remarkable risk factors, a data mining classification task that involves different methods has applied. Data been used to extract hidden knowledge domains such as business, medicine, science, engineering, etc. This research aims predict breast using anthropometric parameters are collected routine blood analysis. First, we found important attributes dataset can be...

In the market of cryptocurrency Bitcoins are first currency which has gain significant importance. To predict price and stability Bitcoin in Crypto-market, a machine learning based time series analysis been applied. Time-series can

About 26 million people worldwide experience its effects each year. Both cardiologists and surgeons have a tough time determining when heart failure will occur. Classification prediction models applied to medical data allow for enhanced insight. Improved projection is major goal of the research team using disease dataset. The probability predicted mined from database processed by machine learning methods. It has been shown, through use this study comparative analysis, that may be with high...

In the Internet of Things (IoT) era, mobile crowd sensing system (MCS) has become increasingly important. The Auto (IOTA) evolved rapidly in practically every technology field over last decade. IOTA-based is being developed this study using machine learning to detect and prevent users from engaging fake activities. It been determined through testing evaluation that our method effective for both quality estimation incentive allocation. Using IOTA Bottleneck dataset, multiple performance...

Predicting future sounds like magic, whether it be detecting, in advance, the intent of a potential customer to purchase company's products or figuring out where price stock is heading towards. If we can reliably predict something, then own massive advantage. Machine learning has served amplify this magic and uncover mystery. It also fields sports. Billions people around world are big fans Cricket wait for results eagerly. In paper, discuss 7 <sup...

The detection of lungs nodule cancer by Computer Aided Diagnosis (CAD) system, provide a great support to the medical experts and can lower death rate. In this research, CAD system is established for early cancer. First, contrast an input image enhanced applying Contrast Limited Adaptive Histogram Equalization (CLAHE). Otsu thresholding applied segmentation tumor followed morphological filters remove background other geometrical objects. resultant de-noised Discrete Wavelet Transform (DWT)....

The cell phone is assuming a crucial job in present day life. It offers types of assistance and applications, for example, location tracking, medical human activity examination. All android smartphones have motion sensors i.e. Accelerometer, gyroscope, order to detect user very precise way. In early conditions, committed were utilized acknowledgment. Different techniques are developed distinguishing normal or activities scenes the crowd by processing video an image. A novel KNN-SVM detection...

In the field of development, Internet things (IoT) plays a crucial role in providing solution to various situations. A lot research has been conducted recently model IoT based operating systems as standard UNIX, Windows and current real time are unable meet demand o

Quantifying atmospheric aerosols and their linkages to climatic repercussions is necessary understand the dynamics of climate forcing enhance our knowledge change. Because this reactivity precipitation, temperature, topography, human activity, boundary layer (ABL) one most dynamic regions: ABL have a big impact on evolution change’s radiative forcing, health, food security, and, eventually, local global economy. Continuous monitoring instrumental computational approaches are required for...

An important measurable indicator of urbanization and its environmental implications has been identified as the urban impervious surface. It presents a strategy based on three-dimensional convolutional neural networks (3D CNNs) for extracting from LiDAR datasets using deep learning technology. Various 3D CNN parameters are tested to see how they affect surface extraction. For delineation, this study investigates synergistic integration multiple remote sensing Azad Kashmir, State Pakistan,...

Facial recognition is now a days very emerging topic. The most challenging task for normal human being to follow the facial retrieval model correct match in least running time. Especially while dealing with moving or non-static environment like live video, webcam recording,

Anomaly in the crowds can create a threat to public security. Manual detection of abnormal crowd behavior CCTV footage by human operators is very difficult and time-consuming task. There need for automated events video. The proposed method based on Convolutional Autoencoder Generative Adversarial Network (GAN) model which are used extract features motion patterns videos. selected then classified using different classifiers such as Support Vector Machine (SVM), Naïve Bayes, Decision Tree,...

Osteoporosis is a bone issue which happens in light of low mass, debasement smaller scale design and high powerlessness to break. It critical prosperity stress over the world, especially more established people. In this paper significant learning model reliant on ResNet50 XGBoost Classifier has been used for predicting gouts or osteoporosis MURA V2 dataset by using RADTorch library order preprocess image X-rays identify defects easily. The randomly provided images were predicted it correctly...

This research depicts another artificial neural network (ANN) based digital differential protection scheme for generator stator winding protection. The incorporates two feedforward networks (FNNs). One ANN is utilized flaw recognition and the other inward deficiency

This novel method enlivened via cartographic maps in the geology area and this technique has been utilized to reintroduce visualization space lost data which non-linear mapping brings about. The diagnostic measurement of such a bending communicated as Magnification Factors, an

In modern age technology-based solution can help to maximize consistency of process in bounded discretion-sentencing regimes. Part Speech Tagging is an exceptionally natural applications. For example, speech processing, text mining, data extraction and mining techniques. The language handling Urdu a difficult task due its morphosynthetic uncertainty. individuals portray, the improvement novel tagging approach, utilizing Conditional Random Field (CRF). our work we have introduced (CRFs)...

Accurate stock market returns are quite difficult for the company because of unpredictable and non-linear nature financial markets. With development artificial intelligence increased computer power, programmed prediction approaches have demonstrated that

In order to meet the specific requirements of various industries and stringent demands 5G, control management 5G networks will heavily depend on integration Software Defined Networking, Network Function Virtualization, Machine Learning. learning can play a crucial role in addressing challenges such as slice type prediction, route optimization, resource management. To effectively evaluate use machine networks, suitable testing environment is necessary. This study proposes lightweight testbed...

The addition of distributed generation (DG) to an integrated delivery system has significantly increased the system's performance and efficiency. Researchers have proposed a number alternative approaches planning with DG insertion. In this article, multiobjective approach is introduced optimise both operator's owner's reciprocal benefits. reason behind multi-objective inconsistent relationship between MVA rating reduction device power losses reduction. To minimize active loss while also...

Intrahepatic cholangiocarcinoma is a form of cancer that forms in the cells bile ducts, both inside and outside liver. Cholangiocarcinoma duct are two words often used interchangeably to describe same disease. Therefore, we have proposed an intelligent Hepatoma detection system. So, main purpose this research develop implement automated method will help detect classify Liver Cancer disease by processing hepatomic images. We liver-tumor-segmentation dataset for testing our methodology, it...