A literature review of using machine learning in software development life cycle stages
The software engineering community is rapidly adopting machine learning for transitioning
modern-day software towards highly intelligent and self-learning systems. However, the …
modern-day software towards highly intelligent and self-learning systems. However, the …
A novel LSTM–CNN–grid search-based deep neural network for sentiment analysis
I Priyadarshini, C Cotton - The Journal of Supercomputing, 2021 - Springer
As the number of users getting acquainted with the Internet is escalating rapidly, there is
more user-generated content on the web. Comprehending hidden opinions, sentiments, and …
more user-generated content on the web. Comprehending hidden opinions, sentiments, and …
Performance evaluation of Botnet DDoS attack detection using machine learning
Botnet is regarded as one of the most sophisticated vulnerability threats nowadays. A large
portion of network traffic is dominated by Botnets. Botnets are conglomeration of trade PCs …
portion of network traffic is dominated by Botnets. Botnets are conglomeration of trade PCs …
Exploring the intersection between software maintenance and machine learning—a systematic mapping study
While some areas of software engineering knowledge present great advances with respect
to the automation of processes, tools, and practices, areas such as software maintenance …
to the automation of processes, tools, and practices, areas such as software maintenance …
Energy efficient scheme for better connectivity in sustainable mobile wireless sensor networks
The extreme issues related to energy consumption and connectivity within the network in
mobile wireless sensor network indulges so many researchers to find out the optimal …
mobile wireless sensor network indulges so many researchers to find out the optimal …
Energy efficient optimized rate based congestion control routing in wireless sensor network
V Srivastava, S Tripathi, K Singh, LH Son - Journal of Ambient Intelligence …, 2020 - Springer
A wireless sensor network is designed to facilitate various real time applications, constituting
a wide range of sensor nodes. In order to provide energy efficient transmissions, a novel …
a wide range of sensor nodes. In order to provide energy efficient transmissions, a novel …
Identifying cyber insecurities in trustworthy space and energy sector for smart grids
Energy is critical infrastructure, and addressing cybersecurity issues in the energy sector is
challenging. Cloud computing has advanced from being a data storage solution to a …
challenging. Cloud computing has advanced from being a data storage solution to a …
[PDF][PDF] Dealing with the class imbalance problem in the detection of fake job descriptions
In recent years, the detection of fake job descriptions has become increasingly necessary
because social networking has changed the way people access burgeoning information in …
because social networking has changed the way people access burgeoning information in …
A machine-learning ensemble model for predicting energy consumption in smart homes
Smart homes incorporate several devices that automate tasks and make our lives easy.
These devices can be useful for many things, like security access, lighting, temperature, etc …
These devices can be useful for many things, like security access, lighting, temperature, etc …
Prediction of Air Pollution Index in Kuala Lumpur using fuzzy time series and statistical models
JW Koo, SW Wong, G Selvachandran, HV Long… - Air Quality, Atmosphere …, 2020 - Springer
Air pollutants can cause multifaceted harm to the human body. Respiratory diseases and
immunology dysfunction are some of its main manifestations. Forecasting the air quality of a …
immunology dysfunction are some of its main manifestations. Forecasting the air quality of a …