We present a method for unsupervised learning of event classes from videos in which multiple actions might occur simultaneously. It is assumed that all such activities are produced an underlying set class generators. The task then to recover this generative process visual data. A derived the most likely decomposition tracks into labelled events involving subsets interacting tracks. Interactions between modelled as relational graph structure captures qualitative spatio-temporal relationships...

In our increasingly interconnected world, Cyber-Physical Systems (CPS) play a crucial role in industries like healthcare, transportation, and manufacturing by combining physical processes with computing power. These systems, however, face many challenges, especially regarding security system faults. Anomalies CPS may indicate unexpected problems, from sensor malfunctions to cyber-attacks, must be detected prevent failures that can cause harm or disrupt services. This paper provides an...

Diabetes is a long-term metabolic condition. This study describes an expert system for predicting diabetes and insulin dosage. A deep learning approach used in the proposed to predict machine algorithm dosage based on several characteristics like blood sugar levels, body mass, age, insulin, diabetic pedigree function. was trained PIMA Indian dataset& related properties create system. To improve model parameters, using Convolutional Neural Network (CNN) technique. Once trained, can accurately...

Road scenes can be naturally interpreted in terms of a hierarchical structure consisting parts and sub-parts, which captures different degrees abstraction at levels the hierarchy. We introduce Latent Hierarchical Part based Models (LHPMs), provide promising framework for interpreting an image using tree structure, case when root filter non-leaf nodes may not available. While HPMs have been developed context object detection pose estimation, their application to scene understanding is...

Software technology based on reuse is identified as a process of designing software for the purpose. The in which existing used to build new software. A metric quantitative indicator an attribute item/thing. Reusability likelihood segment source code that can be again add functionalities with slight or no modification. lot research has been projected using reusability reducing code, domain, requirements, design etc., but very little work reported medical domain. An attempt made bridge gap...

Coronary delivery path coronary disease is caused in corridors by atherosclerosis which results heart failure and respiratory failure. Angiography, an exorbitantly tedious deeply specialized intrusive technique, used to conclude CAD (Coronary Artery Disease). Thus, experts are triggered elective approaches, for example, AI calculations that will use non-intrusive scientific knowledge assess measure the severity of cardiovascular condition. In this report, we present another way deal with...

Software reuse is the process of building software applications that make use formerly developed components. In this paper, we explain benefits can be obtained from using statistical procedures for prescribing medicines, especially in rural areas, which have limited resources available on hand. It should noted although expert systems were successful research, they never dominated market when actual patient treatment was considered. The proposed methodology compared with categorical...


 In the present living environment, transportation plays an important role, which includes movement of small things to very large equipment. Now a day, green in becoming significant part considering this situation, using bicycle seems be cheaper and greener. Also, with physical exercise would more useful for end users. It enables user along moderate exercise. project, attempt has been made design fabricate treadmill bicycle. Design calculations CAD modelling have carried out Based on...

Modern industrial infrastructures rely heavily on Cyber-Physical Systems (CPS), but these are vulnerable to cyber-attacks with potentially catastrophic effects. To reduce risks, anomaly detection methods based physical invariants have been developed. However, often require domain-specific expertise manually define invariants, making them costly and difficult scale. address this limitation, we propose a novel approach extract from CPS testbeds for detection. Our insight is that design...

This paper presents a novel approach to incorporate multiple contextual factors into tracking process, for the purpose of reducing false positive detections. While much previous work has focused on improving object detection static images using context, these have not been integrated process. Our hypothesis is that significant improvement can result from use context in dynamically influencing linking detections, during To verify this hypothesis, we augment state art dynamic programming based...

This paper proposes a novel method for jointly estimating the track of moving object and events in which it participates. The is intended dealing with generic objects that are hard to localise performance current detection algorithms - our focus on involving carried objects. tracks other target interacts (e.g. carrying person) assumed be given. posed as maximisation posterior probability defined over event sequences temporally-disjoint subsets tracklets from an earlier tracking process....

As one of the consequences COVID-19 pandemic, a lot new technologies are developing in fast-track pace clinical practices. The main idea our project is to design contactless technology for support patients who suffer from blood pressure disorders and coronary heart diseases using machine learning approach. This may intend people monitor their rate, pulse respiratory life oxygen saturation levels at an ease. orientation this paper considering facial changes movements video get rid cuff-based...

A series of improvements in a hybrid architecture for multilayer networks is presented. This incorporates the incoming connection strengths and neurons each layer into one stage by multiplexing scheme, hence reducing complexity interstage wiring. An analysis performance this performed and, based on its results, authors propose number improvements. Also, three-layer network has been implemented double metal, single polysilicon p-well CMOS technology proposed The improved version analyzed...

Detection and Prediction of Frequent Diseases in India through Association Technique using Apriori Algorithm Random Forest Regression - written by M. Bhanu Sridhar , P. Aiswarya L. Kavitha published on 2020/03/28 download full article with reference data citations