Arrhythmias pose a significant challenge for early diagnosis and treatment, necessitating advanced detection techniques. This paper introduces the Secure and PrivacyPreserving IoT-Based Arrhythmia Detection (SPIoT-AD)...
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Cryogenics amplifiers feature very low noise injection and low power consumption, and therefore, they are of highly demand in RF imaging, space communications, medical applications, and quantum computing. Unconditiona...
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ISBN:
(数字)9798350338782
ISBN:
(纸本)9798350338799
Cryogenics amplifiers feature very low noise injection and low power consumption, and therefore, they are of highly demand in RF imaging, space communications, medical applications, and quantum computing. Unconditional stability with high gain also feature these applications. The band gaps of these devices are independent from temperature, suggesting their suitability for cryogenics applications. Furthermore, the nanometer scale lengths of these devices lead to ballistic transport with no scattering or diffusion, resulting in high-speed, low-power, and low noise capabilities within Extremely High Frequency (EHF) operating range that may extend into the THz. This study addresses these parameter issues within the range of 90K to 300K, assuming liquid nitrogen coolant medium, and further shows its stability above the room temperature as well. An appropriate model for the device that incorporates complex parasitics was investigated within this temperature range. The device with its estimated parameters, has been integrated into a simulated three-stage amplifier system. A low-noise gain between 16.9-18.9 dB with estimated noise figure of 2.97 dB and a bandwidth of 269 GHz bandwidth were predicted, with a high Stern stability factor suggesting unconditional stability over the bandwidth.
The rapid digitalization of communication necessitates continuous skill updates to keep pace with evolving technology. Network management involves multiple functionalities that play a crucial role in optimizing networ...
The rapid digitalization of communication necessitates continuous skill updates to keep pace with evolving technology. Network management involves multiple functionalities that play a crucial role in optimizing network performance and ensuring continuous availability. It is very important to ensure a proper network management system for a university that has multiple branches to effectively manage and monitor their network infrastructure. A proper network management system provides centralized control and visibility over the entire network infrastructure, allowing administrators to efficiently manage and monitor network devices, configurations, and performance from a single interface. this research has developed a network management system that facilitates real-time network monitoring and troubleshooting, enabling proactive identification and resolution of issues to ensure smooth operations across all branches. It simplifies configuration management, ensuring consistency and compliance in network settings and updates. Resource optimization is achieved through insights into network utilization and performance metrics, allowing administrators to allocate resources efficiently and plan for future expansion. Security and compliance measures can be enforced, protecting sensitive data and ensuring adherence to regulatory requirements. This study utilized GNS3 to create a network layout for a university with multiple branches, along with essential security configurations for the network design. A diverse range of protocols was implemented to safeguard and cater to the users of the secure university network. Furthermore, Switches, Data Routers, firewalls, and BGP Routers were incorporated into the network to enhance communication efficiency and streamline operations.
Object detection is an important task in computer vision. In earlier studies, object detection mostly works on single-modal. But recently, in order to improve detection efficiency, researchers start adding more modals...
Object detection is an important task in computer vision. In earlier studies, object detection mostly works on single-modal. But recently, in order to improve detection efficiency, researchers start adding more modals for improving the robustness of detection result. In this paper, we assume that all input modals which can convert to image style are able to complete object detection task through a unified model. We choose YOLOv7 as our baseline model and use RGB and infrared images from the public dataset Camel to test our hypothesis. Based on our experiment results, training RGB and IR images together obtains better performance than training individually, which shows that all image style modalities are possibly handled by a unified model and even achieve better results.
One of the most popularly used features on smart-phones is WhatsApp. It is a free messaging app available for An-droid, IOS, and all other smartphones. A WhatsApp vulnerability is a hole or a weakness in the app, whic...
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One of the most popularly used features on smart-phones is WhatsApp. It is a free messaging app available for An-droid, IOS, and all other smartphones. A WhatsApp vulnerability is a hole or a weakness in the app, which can be a design flaw or an implementation bug. Through bug, an attacker can enter into the app and cause harm to the database of an application. A database contains private information like backup files, chatting information, contacts, etc. The most dangerous vulnerability in WhatsApp are Authentication, Account Hijacking, and Message Manipulation. In these vulnerabilities, an attacker can manip-ulate the message but not hijack the entire account. There are some basic requirements for a secure and privacy-preserving chat service, database backup, encrypted database, etc. The awareness about the vulnerability of WhatsApp and its security settings in new versions of WhatsApp. Use WhatsApp security features and secure the services of the application. This paper aims to be aware of the risks and vulnerabilities of WhatsApp and use the Threat modeling method to mitigate its vulnerability. It used threat Modelling steps to help organizations to quantify risks and vulnerabilities, ensuring those that need the most attention and resources do so to minimize their attack surface in a purposeful way.
Cardio Vascular Diseases (CVDs) are the prime reason of death globally. Particularly, the cases of coronary artery disease (CAD) have been rising in the post Covid era, especially amongst middle-aged people. Thus, the...
Cardio Vascular Diseases (CVDs) are the prime reason of death globally. Particularly, the cases of coronary artery disease (CAD) have been rising in the post Covid era, especially amongst middle-aged people. Thus, the before time detection of the disease might evade the growing number of fatalities and morbidities. Two most common and accurate methods used to detect CAD are angiography and electrocardiography (ECG). While the former is invasive and a risky procedure, the latter one although non-invasive lacks correctness. Over a decade, non-invasive Machine Learning (ML) as well as Deep Learning (DL) methods have shaped the healthcare scenario by facilitating early diagnosis of the diseases through the application of various computer based algorithmic models over clinical data and images. A hybrid Convolutional- Extreme Gradient Boosting (Convolutional XGBoost) model has been proposed to accurately detect CAD by outperforming some of the existing methods.
Our proposed work is a research project that does quantitative analysis of various basic image manipulation techniques as processes for augmentation of image type data on the accuracy of deep learning task of hand-wri...
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This study aims to present a feasible LFC (Load Frequency Control) model that integrates physical security limitations, namely GRC, GDB, and TD. The presence of this characteristic guarantees that the design is not on...
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A small size printed patch antenna to cover applications of X and Ku band is suggested in this paper. The suggested antenna consists of an arrow shaped patch on front view of FR 4 substrate and a partial ground on the...
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In accordance with the Sustainable Development Goals, the exponential expansion of machine learning (ML) and artificial intelligence (AI) presents an excellent chance to build more effective tools and solutions and ge...
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