Search
459 articles for “Detection Algorithm”
-
Hybrid Machine Learning and Finite Element Framework for Predicting Damage Behavior in Fiber-Reinforced Polymer Composites
Abstract: Fiber Reinforced Polymer (FRP) composites have broad spread use in aerospace, automotive, marine and structural applications due to its high specific strength, stiffness and corrosion resistance. The various damage mechanisms such as matrix cracking, fiber breakage, delamination and interfacial failure, however, make the forecasting of damage particularly complex. In this work, a hybrid machine learning (ML) and finite element (FE) system is proposed for predicting the damage behavior of FRP …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Electronic Circuitry and Material Integration for Enhanced Gas Detection Windows
Abstract: Liquefied Petroleum Gas (LPG) and propane, being flammable mixtures of hydrocarbon gases, are widely used as fuel in various applications such as homes, hostels, and industries. Our main objective for this project is to design and fabricate a gas sensing window that will autonomously open upon detecting any leakage of gases like LPG, CO2, alcohol, propane, etc. The heart of our system is the MQ-9 gas sensor, known for its …
Published in Journal of Microelectronics and Solid State Devices · Vol. 11, Issue 3, 2024 · pp. 14–24 Read article
-
ML Associated DoS and DDoS Attack Observation in Protection
Abstract: DoS and DDoS assaults are significant risks to the availability and integrity of online services and networks. Attack traffic might come from a variety of geographical regions, making it difficult to filter and neutralize the attack. DDoS attacks are far more sophisticated and powerful than DoS attacks. They use a network of compromised devices, known as a botnet, to launch a coordinated attack on a target. Monitoring and evaluating the …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 18–26 Read article
-
Developing a Comprehensive Framework for User and Entity Behavior Analytics (UEBA): Integrating Advanced Machine Learning and Contextual Insights
Abstract: User and Entity Behavior Analytics (UEBA) has emerged as a crucial approach in modern cybersecurity for detecting and mitigating insider threats, compromised accounts, and other malicious activities within organizational networks. However, existing UEBA frameworks often face challenges in scalability, detection accuracy, and response effectiveness. This research work proposes a novel framework for UEBA that aims to address these limitations and enhance threat detection and response capabilities. The framework integrates advanced …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 20–32 Read article
-
Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 Read article
-
Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article
-
Machine Learning Innovations for Effective Spam Comment Filtering in Social Networks
Abstract: The increasing prevalence of social media platforms has revolutionized communication, fostering unparalleled levels of connectivity and data exchange. However, the widespread increase in spam comments presents a serious threat to the integrity of online discussions, potentially undermining the quality of interactions. To confront this issue, our proposed model utilizes machine learning techniques to bolster spam comment detection across various social media platforms. This endeavor involves a thorough investigation encompassing data …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 19–24 Read article
-
Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
-
Self-Driving Cars and Computer Vision: Enhancing Computer Vision for Autonomous Vehicle Navigation
Abstract: Autonomous vehicles, commonly known as self-driving cars, are transforming the transportation sector by aiming to enhance road safety, ease traffic congestion, and boost overall efficiency. Central to the operation of these vehicles is computer vision, which enables them to perceive and understand their environment. This paper examines how computer vision contributes to the navigation of autonomous vehicles and highlights its continuous developments. Specifically, it examines key challenges such as real-time …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 1–10 Read article
-
The Role of AI in Modern Circuit Design and Simulation
Abstract: The integration of artificial intelligence (AI) in circuit design and simulation is revolutionizing the electronics industry by enabling faster, more efficient, and innovative design processes. This article explores the transformative role of AI in automating tasks traditionally reliant on manual expertise, such as schematic generation, component optimization, and fault detection. It highlights how machine learning algorithms and generative AI tools are improving design accuracy, reducing time-to-market, and enabling cost-effective prototyping. …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 9–14 Read article
-
Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
-
A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
-
Smart Weather Monitoring System Using ESP32 and IoT
Abstract: The increasing unpredictability of climate conditions necessitates an efficient and real-time weather monitoring system. The following paper describes an IoT weather monitoring system using the ESP32 microcontroller, connected to various environmental sensors to gather and process atmospheric information. The system uses a DHT11 sensor to measure temperature and humidity, an MQ135 gas sensor for measuring air quality, and a PM2.5 sensor to measure the level of particulate matter. The ESP32 …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 2, 2025 · pp. 25–36 Read article
-
Artificial Intelligence and IoT Integration for Real-Time Violence Monitoring
Abstract: The peace and tranquility of any place can be affected greatly by the insurgence of violence and violent attacks that are perpetrated by individuals with malicious and nefarious intentions. These individuals terrorize the areas and can cause a lot of harm and damage to people and public property. The incidences of violence are undesirable and can be problematic to handle by the law enforcement agencies, as these acts are committed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 39–45 Read article
-
A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 25–34 Read article
-
Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1207–1231 Read article
-
Stationary Wavelet and Recursive Least Square Filtering Based Fetal ECG Data Extraction from Composite Abdominal Signal
Abstract: This paper introduces a fast methodology for fetal ECG extraction based on stationary wavelet and noise canceler adaptive filter with the recursive least square filter. Firstly, signals are preprocessed by moving averaging filter for removing baseline wander. The stationary wavelet and the recursive least square filter is applied on preprocessed signal that effectively separates the maternal ECG and extracts fetal ECG (fECG) from the abdominal ECG. Finally, fetal ECG(fECG) is …
Published in Current Trends in Signal Processing · Vol. 7, Issue 2, 2017 · pp. 46–58 Read article
-
Real-time Criminal Detection Using Face Recognition
Abstract: The objective of this project is to create a criminal face detection system that utilizes machine learning algorithms like TensorFlow and Scikit-learn, implemented in the Python programming language. To handle image processing, OpenCV will be utilized, while SQL will manage the current criminal database. The high-resolution pictures in the database will be split into various components and utilized for training the model, which can identify specific features to recognize the …
Published in Journal Of Network security · Vol. 11, Issue 1, 2023 · pp. 1–7 Read article
-
Smart CCTV for Daycare
Abstract: In the modern world, security has been the most crucial issue. Closed Circuit Television (CCTV) is used to monitor, and identify the specific surrounding for surveillance and security purpose. The device warns of the presence of any individual in the vicinity and adds security by documenting the person's actions. In day-care, the footage captured by surveillance camera is critical for crime prevention and investigation. A motion detection, video capturing, and …
Published in Journal Of Network security · Vol. 11, Issue 1, 2023 · pp. 44–47 Read article
-
Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article