Development of communication technologies and e-commerce has made the credit card as most common technique payment for both online regular purchases. So, security in this system is highly expected to prevent fraud transactions. Fraud transactions data transaction are increasing each year. In direction, researchers also trying novel techniques detect such frauds. However, there always a need some that should precisely efficiently these This paper proposes scheme detecting frauds which uses...

Wireless sensor networks (WSN) became very popular in last few years. They are deployed distributed manner for collecting variety of data. There a lot research issues and challenges WSN viz; energy efficiency, security, localization etc. Outlier or anomaly detection is one such area to prevent malicious attacks reducing the errors noisy data millions wireless networks. models should not compromise with quality We have identify anomalies offline mode online accuracy, better performance intake...

IoT solutions improve the quality of patient care in healthcare system by allowing patients to connect devices that monitor and evaluate essential health data. However, massive amounts data generated carry serious security threats, which are self-inflicted detecting abnormal behaviours can indicate a possible breach or failure. Usually, anomaly detection is done employing heuristic algorithms on labeled datasets. real-world applications, several privacy barriers dump hinder obtaining This...

IoT solutions improve the quality of patient care in healthcare system by allowing patients to connect devices that monitor and evaluate essential health data. However, massive amounts data generated carry serious security threats, which are self-inflicted detecting abnormal behaviours can indicate a possible breach or failure. Usually, anomaly detection is done employing heuristic algorithms on labeled datasets. real-world applications, several privacy barriers dump hinder obtaining This...

This study looks at how corporate governance is being impacted by artificial intelligence (AI). The feasibility, acceptability, along with the obligation to automate board-level collective decision making are assessed from viewpoints of business, technology, and society. Five possibilities for AI suggested in article: aided, enhanced, amplified, autonomous, autopoietic intelligence. We evaluate strengths weaknesses both human machine learning, we examine consequences future governance. ends...

Now-a-days, Internet of Things (IoT) based systems are developing very fast which have various type wireless sensor networks (WSN) behind it. These applications viz., healthcare, agricultural, industrial and military applications. Anomaly or outlier detection is one the important research problems in such where a huge amount data collected. helps to find out defective, erroneous, noisy nodes. There many techniques used detect anomalies. Machine learning algorithm (MLA) approaches much useful...

A portable parameter monitoring and analysis system for physiological studies assisting patient-centric health care management is developed. The uses the network approach to acquire data from sensors transmit them a server through wireless propagation means. automates acquisition of parameters by continuous display on monitor screen. Programming done using industry strength software trends in real time standard PC. measured accurate lives up standards industry.

Machine learning algorithms have found several applications in the field of robotics and control systems. The systems community has started to show interest towards machine from sub-domains such as supervised learning, imitation reinforcement achieve autonomous intelligent decision making. Amongst many complex problems, stable bipedal walking been most challenging problem. In this paper, we present an architecture design simulate a planar robot(BWR) using realistic simulator, Gazebo. robot...

Temporal autocorrelation present in functional magnetic resonance image (fMRI) data poses challenges to its analysis. The existing approaches handling fMRI time-series often presume a specific model of such as an auto-regressive model. main limitation here is that the correlation structure voxels generally unknown and varies different brain regions because levels neurogenic noises pulsatile effects. Enforcing universal on all leads bias loss efficiency In this paper, we propose mixed...

A telemetric system that can measure physiological parameters in an unobtrusive way and transmit it for remote monitoring prove to be quite useful providing the ambulatory patients with freedom of mobility while their health is being monitored continuously. Such a equally monitor vital signs service personnel e.g. firefighters working hazardous environment during course duty. In this paper similar system, has been designed & developed continuous monitoring, described. The uses RF GSM...

A portable parameter monitoring and analysis system for physiological studies assisting patient-centric health care management is developed. The uses network approach to acquire the data from sensors transmit on a server through wireless means. automates acquisition of parameters by continuous display monitor screen. programming done using software traces in real time standard PC.

The vast majority of recommender systems model preferences as static or slowly changing due to observable user experience. However, spontaneous changes in are ubiquitous many domains like media consumption and key factors that drive not directly observable. These latent sources preference change pose new challenges. When do track adapt users' tastes, users lose confidence trust, increasing the risk churn. We meet these challenges by developing a novelty learns tracks tastes. combine three...

Animal behavior is not driven simply by its current observations, but strongly influenced internal states. Estimating the structure of these states crucial for understanding neural basis behavior. In principle, can be estimated inverting models, as in inverse model-based Reinforcement Learning. However, this requires careful parameterization and risks model-mismatch to animal. Here we take a data-driven approach infer latent directly from observations behavior, using partially observable...

Abstract Deep learning models have become state of the art in many language modelling tasks. Among such tasks, source code auto-completion is one important areas research. This paper presents various methodologies for using different Learning Python and CSharp Programming Languages. In a resource-limited environment, it paramount to reduce overheads: way achieving that use sequences train evaluate rather than other structures as semantics. compares deep architectures like CodeGPT [1] from...

Modern computer vision technologies have served to bridge the gap between contemporary scientific analysis and machine learning assisted digital processing. Within field of biomechanics, applied strategies incorporating both conventional means shown great success in augmenting observations electromyogram graphical sensors; albeit within constraints specialized, multiple-source arrays. The ongoing study represents an endeavor utilize several distinct achieve similar results with application a...