As the usage of Android mobile devices has increased rapidly, so has the occurrence of Android malware. To mitigate the risk posed by Android malware, it is important to develop effective detection techniques. In this ...

Recent work by Tramer et al. [6] highlighted online models’ vulnerability to theft by exploiting prediction APIs through repetitive querying. Since then, numerous studies have emphasized the increasing significance of model ...

Federated learning (FL) is a popular framework for training a model in a distributed setting, where the data is spread over a network of devices. In traditional FL, the devices communicate with a central server to share ...

Creating software that supports the similarities and facilities offered by Cad tools for semiconductors, photoelectric cells, and other devices Primarily, making a cost effective software that could give similar results ...

Wireless devices, including mobile phones, laptops, autonomous driving, UAT, etc., generate an enormous amount of local data, which could be employed to train machine learning models for decision-making and improve prediction ...

Millimeter wave (mmWave) massive multiple input multiple output (mMIMO) systems are at the core of fifth-generation (5G) and beyond-fifth-generation (B5G) technologies due to their ability to support error-free communication ...

Gastrointestinal (GI)-tract associated cancers remain a significant global health concern due to their high incidence and mortality rates. These complex diseases arise from intricate interactions between genetic factors ...

In this study, we build upon the Image-Based Visual Servoing (IBVS) technique by Yogesh Kumar and Bassam Pervez Shamsi to develop an advanced kinematic controller for quadrotor tracking. Our approach enhances the tracking ...

The primary goal of this project is to identify and develop a system to monitor Key Performance Indicators (KPIs) that can enhance the efficiency of Public Bus Services in Delhi. By meticulously analyzing various aspects ...

Resource allocation is a problem that requires complex decision making. Our focus is to solve this problem in the healthcare sector using Reinforcement Learning. We propose an RL pipeline that starts with a sequential ...