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Security Operations Centers (SOCs) require intrusion detection systems that achieve high detection accuracy while maintaining a low false-positive rate and robustness to evolving attack patterns. However, most existing machine learning-based approaches primarily focus on detecting known threats and often overlook distribution shifts and the reliability of generated alerts. In this paper, we propose TL-SOC, a…

The rapid growth of Internet of things (IoT) devices have heightened the need for effective Intrusion Detection System (IDS) to combat evolving cyber threats. The IoT networks has the security challenges due to the heterogeneous and high-dimensional nature of network traffic data, redundant features, and class imbalance which hinder detection accuracy and efficiency. Effective IDS…

Service-oriented architecture has attracted attention in automotive development. The Automotive Open System Architecture (AUTOSAR) specifies Scalable Service-Oriented Middleware over IP (SOME/IP) as a key middleware for service-oriented communication in-vehicles. However, SOME/IP-based networks are vulnerable to server spoofing during the service discovery phase, enabling attackers to cause man-in-the-middle attacks by impersonating legitimate services. This paper proposes…

Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…

Persistent anomalies in modern photovoltaic (PV) systems present a formidable challenge, impeding optimal power output and system resilience. Artificial Intelligence (AI) has surfaced as a game-changing solution, yet existing research has merely scratched the surface of solar panel prognosis, leaving a critical void in leveraging AI’s explainable nature and active learning capabilities. This pioneering study…

A lightning detection system based on a large-diameter Rogowski coil and an analog integrator was developed for wind turbine applications and is presented in this paper. To accurately detect lightning current, the Rogowski coil was designed with a lower cutoff frequency of 0.1 Hz. The analog integrator, comprising an inverting active integrator, and an amplifier,…

This study addresses the need for improved prognostics in switch-mode power supplies (SMPS) that incorporate electromagnetic interference (EMI) filters, with a focus on aluminum electrolytic capacitors, which are critical for the reliability of these systems. The primary aim is to develop a robust model-based approach that can accurately predict the degradation and operational lifetime of…

The proliferation of internet economies has given the corporate world manifold advantages to businesses, as they can now incorporate the latest innovations into their operations, thereby enhancing ease of doing business. For instance, financial institutions have leveraged credit card usage on the aforesaid proliferation. However, this exposes clients to cybercrime, as fraudsters always find ways…

The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability. Network anomaly detection is crucial for ensuring the security of information resources. Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in…

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…

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…

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…

The article presents a simulation of obstacle detection based on noise-free optical flow images for motion control of mobile robots. The detection of hazardous areas in optical flow images is accomplished by dividing multiple layers of optical flow vectors into equal parts. Based on the results of calculating the average magnitude of the vectors in…

In this paper, an automatic method for detection of olive trees in RGB images acquired by an unmanned aerial vehicle (UAV) is developed. Presented approach is based on the implementation of RetinaNet model and DeepForest Phyton package. Due to fact that original (pretrained) model used in DeepForest package has been built on images of various…

The Activity and Event Network (AEN) is a new dynamic knowledge graph that models different network entities and the relationships between them. The graph is generated by processing various network security logs, such as network packets, system logs, and intrusion detection alerts, which allows the graph to capture security-relevant activity and events in the network.…

Globally, road transportation has become one of the most reliable means of moving goods and services from one place to the other. It has contributed immensely to the standard of living and modern civilization. However, this means of transportation is characterised by some issues which are poised to be harmful to the human population if…

Corn is one of the most important agricultural products in the world. However, climate change greatly threatens corn yield, further increasing already prevalent diseases. Northern corn leaf blight (NLB) and Gray Leaf Spot are two major corn diseases with lesion symptoms that look very similar to each other, and can lead to devastating loss if…

Alzheimer’s disease has proven to be the major cause of dementia in adults, making its early detection an important research goal. We have used Ensemble ELMs (Extreme Learning Models) on the OASIS (Open Access Series of Imaging Studies) data set for Alzheimer’s detection. We have explored various single layered light-weight ELM networks. This is an…

Emotion is the most important component of being human, and very essential for everyday activities, such as the interaction between people, decision making, and learning. In order to adapt to the COVID-19 pandemic situation, most of the academic institutions relied on online video conferencing platforms to continue educational activities. Due to low bandwidth in many…

Electroencephalography (EEG) is one of the most common and benign methods for analyzing and identifying abnormalities in the human brain. EEG is an incessant measure of the activities of the human brain. In contrast, when the measurement of EEG is bounded by time and the EEG is synchronized to an exterior stimulus, is known as…

This paper builds on the realization that since mobile devices have become a common tool for researchers to collect, process, and analyze large quantities of data, we are now entering a generation where the creation of solutions to difficult real-world problems will mostly come in the form of mobile device apps. One such relevant real-life…

In this paper, we investigate the utilization of three effective detection methods to identify potential threats of insects in date palm trees. The detection techniques presented here are the application of infrared radiation, microwave antennas and metamaterials based sensors. Experimental trials using IR radiation took place in a local farm. Moreover, the second sensing system…

Owing to the recent development of AI technology, various studies on computer-aided diagnosis systems for CT image interpretation are being conducted. In particular, studies on the detection of lung cancer which is leading the death rate are being conducted in image processing and artificial intelligence fields. In this study, to improve the anatomical interpretation ability…

Building detection in aerial or satellite imagery is one of the most challenging tasks due to the variety of shapes, sizes, colors, and textures of man-made objects. To this end, in this paper, we propose a novel approach to extracting buildings in high-resolution images based on prior knowledge of the shadow position. Firstly, the image…

The main purpose in this work is to explore the fact that chaos, as a biological characteristic in the brain, should be used in an Artificial Neural Network (ANN) system. In fact, as long as chaos is present in brain functionalities, its properties need empirical investigations to show their potential to enhance accuracies in artificial…