In order to assist the process of questions answering on CQA (Community Question Answering) websites, this paper proposes an improved methodology of batch recommendation of answerers (experts) to questions called BESF (BERT Expert Recommendation using Multi-Objective Sailfish Algorithm with Genetic Algorithm). First, experts and questions modeling is done using BERT Topic modeling technique, which creates […]
In recent years, Software Defined Networking (SDN) has emerged as a pivotal element in various networks. The prominent feature of software-defined networking is the separation of two planes that were tightly coupled in traditional networks that is the forwarding and control planes. Forwarding plane’s basic functionalities are packet forwarding while control plane issues control command […]
GPU kernels have come to the forefront of computing due to their utility in varied fields, from high-performance computing to machine learning. A typical GPU compute kernel is invoked millions, if not billions of times in a typical application, which makes their performance highly critical. Due to the unknown nature of the optimization surface, an […]
Now a days everyone is using the smart phones, there is a need of various applications to be installed on the smart phones. So, there are 3.48 million apps on google play store. Apps demand is increasing day by day. Apps developers want to make their app in top of the leader board so that […]
Deep learning is the foundation for various applications, including decision support, fraud detection, text categorization, machine translation, market research, and customer segmentation. Despite their widespread use, deep learning algorithms are frequently vulnerable to adversarial instances, in which legal inputs are manipulated in subtle and often invisible ways. Even the most complicated models may be tricked […]
Reinforcement learning generates policies based on reward functions, hyper-parameters. Slight changes in these can significantly affect results. The lack of documentation and reproducibility in Reinforcement learning research makes it difficult to replicate once-deduced strategies. While previous research has identified strategies using grounded maneuver, there is limited work in the more complex environments. The agents in […]
The immeasurable amount of data in network traffic has increased its vulnerability. Therefore, monitoring and analyzing traffic for threat hunting is inevitable. Analyzing and capturing realtime network traffic is challenging due to privacy and space concerns. However, many simulated datasets are available. Machine-learning based intrusion detection systems are trained on these datasets for attack detection. […]
This study introduces a novel deep learning hybrid approach using various models like Vector autoregression(VAR), Long Short-Term Memory (LSTM) neural network, hybrid VAR-LSTM, ARIMA and various other classifiers for the three distinct regional locations namely SanJuan, Ahmedabad and Iquitos.
Spatio-temporal data mining techniques are used for crime analysis for their knowledge oriented and meaningful visual representation of crime incidents. Visual representation of crime patterns assist analysts with in-depth understanding of crime behavior with time and location. The representation can be made more knowledgeable and perceptible by incorporating details of socio-economic factor and areafis geographical […]
Descriptive and Predictive Analysis of infectious diseases