Volume 8, Issue 6
This issue presents a collection of fourteen research papers encompassing a wide array of domains including robotics, healthcare, machine learning, cloud computing, neuroscience, cybersecurity, and control systems. Each paper offers significant contributions to its respective field, introducing novel methodologies, insights, and solutions to tackle contemporary challenges. The research covers diverse topics such as designing control programs for autonomous mobile robots, predicting cardiovascular diseases using IoT and deep learning models, exploring ensemble methods in machine learning, summarizing social media texts with Transformer-based systems, assessing cloud IaaS services through consumer-centric ontologies, and analyzing mental stress levels via EEG feature extraction and classification. Additionally, studies delve into medical diagnostics, prosthetic hand design, underwater rescue devices, real-time object detection in surgical training, blockchain-powered medical history cards, cloud security frameworks, inverted pendulum control strategies, and network anomaly detection using advanced artificial intelligence models. These papers collectively highlight the ongoing pursuit of innovation, knowledge dissemination, and advancement within the dynamic realm of science and technology.
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Front Cover
Editorial Board
Editorial
Table of Contents
Control Program Generator for Vehicle Robot using Grammatical Evolution
A robot development has spread widely for various purposes. It is difficult to create a control program for an autonomous mobile robot manually. Therefore, an automatic design of the control program for an autonomous mobile robot is proposed in this research. The autonomous mobile robot is created with LEGO MINDSTORMS EV3, and the control program…
Read More IoT System and Deep Learning Model to Predict Cardiovascular Disease Based on ECG Signal
In this work, our contribution will intervene to reduce the impact of noises on the ECG signals. Various ECG denoising approaches were tested to see how efficient they were in removing dominant noises that add to pure ECG signals. Due to different causes such as interference, muscular noise, body movement related to breathing, and so…
Read More Tree-Based Ensemble Models, Algorithms and Performance Measures for Classification
An ensemble method is a Machine Learning (ML) algorithm that aggregates the predictions of multiple estimators or models. The purpose of an ensemble module is to provide better predictive performance than any single contributing model. This can be achieved by producing a predictive model with reduced variance using bagging, and bias using boosting. The Tree-Based…
Read More Social Media Text Summarization: A Survey Towards a Transformer-based System Design
Daily life is characterized by a great explosion of abundance of information available on the internet and social media. Smart technology has radically changed our lives, giving a leading role to social media for communication, advertising, information and exchange of opinions. Managing this huge amount of data by humans is an almost impossible task. Adequacy…
Read More Infrastructure-as-a-Service Ontology for Consumer-Centric Assessment
In the context of adopting cloud Infrastructure-as-a-Service (IaaS), prospective consumers need to consider a wide array of both business and technical factors associated with the service. The development of an intelligent tool to aid in the assessment of IaaS offerings is highly desirable. However, the creation of such a tool requires a robust foundation of…
Read More EEG Feature Extraction based on Fast Fourier Transform and Wavelet Analysis for Classification of Mental Stress Levels using Machine Learning
Mental stress assessment remains riddled with biases caused by subjective reports and individual differences across societal backgrounds. To objectively determine the presence or absence of mental stress, there is a need to move away from the traditional subjective methods of self-report questionnaires and interviews. Previously, it has been evidence that EEG Oscillations can discriminate mental…
Read More Comparative Study of J48 Decision Tree and CART Algorithm for Liver Cancer Symptom Analysis Using Data from Carnegie Mellon University
Liver cancer is a major contributor to cancer-related mortality both in the United States and worldwide. A range of liver diseases, such as chronic liver disease, liver cirrhosis, hepatitis, and liver cancer, play a role in this statistic. Hepatitis, in particular, is the main culprit behind liver cancer. As a consequence, it is decisive to…
Read More Design of Bio-Inspired Robot Hand Using Multiple Types of Actuators
Many prosthetic hands are focused on appearance and grip strength, however, gestures are also one of the performances that users need for communicating with others as body language to express their feeling and intention. For this paper, the initial prototype of the gesturing robotics hand is presented by using multiple types of actuators concept to…
Read More Implementation of a GAS Injection Type Prefabricated Lifting Device for Underwater Rescue Based on Location Tracking
In this paper, we have developed a gas injection-type prefabricated lifting device based on location tracking to efficiently lift the human body in the event of an accident that occurs underwater on the sea or land. The efficiency of the lifting system is very important to ensure the golden time of the rescue and the…
Read More Towards Real-Time Multi-Class Object Detection and Tracking for the FLS Pattern Cutting Task
The advent of laparoscopic surgery has increased the need to incorporate simulator-based training into traditional training programs to improve resident training and feedback. However, current training methods rely on expert surgeons to evaluate the dexterity of trainees, a time-consuming and subjective process. Through this research, we aim to extend the use of object detection in…
Read More A Secure Medical History Card Powered by Blockchain Technology
A reliable healthcare system ensures that the population has access to top-notch medical ser- vices, ultimately enhancing their overall health most efficiently. At times, data are not secured or handled appropriately. Addressing these concerns, blockchain technology is projected to bring about a substantial revolution in the medical industry by assuring the confidentiality of electronic health…
Read More Enhancing Cloud Security: A Comprehensive Framework for Real-Time Detection, Analysis and Cyber Threat Intelligence Sharing
Cloud computing has emerged as a pivotal component of contemporary IT systems, affording organizations the agility and scalability required to meet the ever-changing demands of business. However, this technological evolution has introduced a new era of cybersecurity challenges, as attackers employ increasingly sophisticated strategies to breach cloud networks. Such breaches can have far-reaching consequences, including…
Read More Dual Mode Control of an Inverted Pendulum: Design, Analysis and Experimental Evaluation
We present an inverted pendulum design using readily available V-slot rail components and 3D printing to construct custom parts. To enable the examination of different pendulum characteristics, we constructed three pendulum poles of different lengths. We implemented a brake mechanism to modify sliding friction resistance and built a paddle that can be attached to the…
Read More Optimizing the Performance of Network Anomaly Detection Using Bidirectional Long Short-Term Memory (Bi-LSTM) and Over-sampling for Imbalance Network Traffic Data
Cybercriminal exploits integrity, confidentiality, and availability of information resources. Cyberattacks are typically invisible to the naked eye, even though they target a wide range of our digital assets, such as internet-connected smart devices, computers, and networking devices. Implementing network anomaly detection proves to be an effective method for identifying these malicious activities. The traditional anomaly…
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