This study aims to develop a multichannel stimulation system integrating electrocardiogram (ECG)-based heart rate and heart rate variability (HRV) measurement capabilities within a non-invasive vagus nerve stimulator ...
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Cardiovascular disease continues to be a predominant cause of mortality globally, requiring precise and effective strategies for early identification. This work examines the application of clinical datasets to explore...
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As the file system that must be mounted before the operating system starts, the root file system (rootfs) is crucial to ensure the normal running of the operating system and is closely related to application security....
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In today’s information-rich digital age, the volume of web content available to users has become overwhelming, making it challenging for individuals to find relevant and personalized content. Recommendation systems h...
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ISBN:
(纸本)9789819747108
In today’s information-rich digital age, the volume of web content available to users has become overwhelming, making it challenging for individuals to find relevant and personalized content. Recommendation systems have emerged as a transformative solution, catering to individual users by offering customized suggestions aligned with their unique interests. This research explores a novel approach that utilizes topic modeling techniques on web content titles for recommendation purposes. Topic modeling, a subfield of natural language processing (NLP) is utilized to automatically identify latent topics within a large corpus of text. The proposed work begins by collecting a diverse dataset of web content titles across the domains. It employs a combination of other state-of-the-art topic modeling algorithms like BERTopic modeling and statistical model to uncover the underlying topics in the titles. By leveraging this approach on web content titles, aim to extract meaningful themes and categorize the content efficiently. Then preprocess the data to remove irrelevant information, ensuring that the subsequent topic modeling process yields accurate and meaningful results. This approach not only expedites the recommendation process but also conserves computational resource. Once the topics are identified, associate them with appropriate metadata, such as user preferences, and content types. This step forms the foundation of our content-based recommendation approach. Then maps the user’s interests to the most relevant topics, enabling us to present a tailored list of web content titles. By recommending content based on underlying themes rather than just keywords, this approach surpasses traditional methods, ensuring more accurate and diverse suggestions for users. The results demonstrate the system’s ability to provide highly personalized recommendations, enhancing user satisfaction and engagement. By delving into the semantic structure of content rather than relying solely on
Stock market forecasting and analysis through Deep Learning (DL) methods is the objective of this study, which aims to address the complexity of financial data through the use of advanced predictive modeling. The curr...
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Depression is a prevalent mental health condition affecting millions globally, often going undiagnosed due to social stigma and limited accessibility to healthcare. This study presents an innovative AI-enhanced system...
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This study introduces a smart education management system designed to enhance the accreditation processes mandated by the National Commission for Academic Accreditation & Assessment (NCAAA) for postgraduate progra...
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Clever system that can look at pictures of fruits and figure out what kind of fruit each picture shows. AI algorithms like deep learning, which is like giving the Machine learning model a crash course in fruit recogni...
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With the number of low Earth orbit satellites and the expansion of application demands, satellite trajectory prediction is crucial for efficiently operating satellite systems. Traditional trajectory prediction methods...
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The proceedings contain 32 papers. The special focus in this conference is on Futuristic Advancements in Materials, Manufacturing, and Thermal Sciences,. The topics include: Design and Development of Welding Fixture o...
ISBN:
(纸本)9789819756209
The proceedings contain 32 papers. The special focus in this conference is on Futuristic Advancements in Materials, Manufacturing, and Thermal Sciences,. The topics include: Design and Development of Welding Fixture on Release Welding Machine;advancements in Design of Semi-Active Suspension Control system During Pre- and Post-Covid-19—A Review of Research;Design of Flexural Bearings in Experimental Analysis and PID Control of a Voice Coil Actuator;design and Optimization of Railway Power Axle system for Structural Safety;design and Analysis of Rotary Slag Skimmer Machine;developing and Implementing Vision-Based Production Lines for Detecting and Removing Defective Components;designing a Piezo-Actuated Four-Bar Motion Amplification Mechanism for Enhanced Compliance;geometrical Aspects of Snow Sinkage for Robotic application;finite Element Analysis of a Cable-Driven Robotic Hand Exoskeleton;envisioning the Future of Robotics Sensors: Innovations and Prospects;Home Automation system with Multiple Control Access Using IoT and RTC Module;dynamic Analysis of Underactuated Soft Robotic Gripper for Space applications;EMG-Controlled Upper Arm Exoskeleton Powered by Pneumatic Artificial Muscle;self-Operated Optimized Design of an Automated Seed-Sowing Robot;Fault Diagnosis in a Centrifugal Pump Using MODWPT and SVMA;methodology for Wall Thickness Validation with Stress Analysis of ClO2 Generator Piping system;A Comparative Study of Live Load for Bridge Deck with Custom Fighter Aircraft Loading and IRC Standard Loading for Design of Elevated Taxiway;modeling and Simulation of Self-stabilizing Platform for Industrial application;enhancing the Thermal Performance of a Solar Air Heater by Incorporating Artificial Roughness to the Absorber Plate;topology Optimization of Wind Turbine Structural Components.
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