Recent Advances in Computer Science and Communications - Volume 17, Issue 1, 2024

The special issue contains research papers elaborating advancements in computational intelligence. Computational intelligence mimics the extraordinary capacity of the human intellect to assert and understand in an environment of uncertainty and imprecision. Computational intelligence is new-age multidisciplinary artificial intelligence. The main goal of computational intelligence is to develop intelligent system Read More

There has been an exponential increase in discussions about bias in Artificial Intelligence (AI) systems. Bias in AI has typically been defined as a divergence from standard statistical patterns in the output of an AI model, which could be due to a biased dataset or biased assumptions. While the bias in artificially taught models is attributed able to bias in the dataset provided by humans, there is still room for advancement in term Read More

Chatbots use artificial intelligence (AI) and natural language processing (NLP) algorithms to construct a clever system. By copying human connections in the most helpful way possible, chatbots emulate individuals and serve as virtual assistants. They easily interface and respond to customers' requests. In the modern technical environment, these conversation agents or chatbots are considered the next-generation i Read More

Background: Text mining derives information and patterns from textual data. Online social media platforms, which have recently acquired great interest, generate vast text data about human behaviors based on their interactions. This data is generally ambiguous and unstructured. The data includes typing errors and errors in grammar that cause lexical, syntactic, and semantic uncertainties. This results in incorrect pattern d Read More

Aim: Load forecasting for efficient power system management. Background: Short-term energy load forecasting (STELF) is a valuable tool for utility companies and energy providers because it allows them to predict and plan for changes in energy. Method: 1D CNN BI-LSTM model incorporating convolutional layers. Result: The results provide the Root Mean Square Error of 0.952. The results shows that the proposed model outper Read More

Introduction: Crack is the main bridge disease. The monitoring of the crack width is the key for determining whether the bridge needs to be maintained. The systematic and automatic detection of bridge cracks can be realized using the crack images, which are captured using unmanned aerial vehicles (UAV). Methods: Cracks in the image with a complex background and low contrast ratio are difficult to detect. In order to Read More

Background: Data quality is crucial to the success of big data analytics. However, the presence of outliers affects data quality and data analysis. Employing effective outlier detection techniques to eliminate dirty data can improve data quality and garner more accurate analytical insights. Data uncertainty presents a significant challenge for outlier detection methods and warrants further refinement in the era of big data. Objecti Read More

Background: The healthcare sector faces numerous issues, such as insurance fraud, electronic medical record management, interoperability, insecure dissemination of information, etc. The novel Blockchain technology holds tremendous potential to transform the healthcare sector by addressing these rising challenges in the industry. It provides a secure platform for storing, disseminating, and retrieving sensitive patien Read More

One of the most promising fields of research in recent years is Mobile Ad Hoc Networks (MANET). The well-known advantages of the internet for specific types of applications lead to the fact that it is a wireless ad-hoc network. As a result, such networks can be utilized in circumstances where no other wireless communication infrastructure is present. A MANET is a network of wireless devices without any centralized control. A d Read More