Game economy design significantly shapes the player experience and progression speed. Modern game economies are becoming increasingly complex and can be very sensitive to even minor numerical adjustments, which may ha...
详细信息
Low Power Wide Area Networks (LPWANs) plat-forms (LoRa, NB-IoT, Sigfox) came to add a missing piece to the Internet of Things (IoT) ecosystem, namely long range communication in low power. LPWAN platforms are characte...
详细信息
This study investigates clinicians' perceptions and attitudes toward an assistive artificial intelligence (AI) system that employs a speech-based explainable ML algorithm for detecting depression. The AI system de...
详细信息
Meta Automated Machine Learning (Meta AutoML) allows effective ML models to be generated automatically. This is accomplished by leveraging multiple AutoML solutions and searching for their best model in parallel. Whil...
详细信息
In today’s fast-paced world,many elderly individuals struggle to adhere to their medication schedules,especially those with memory-related conditions like Alzheimer’s disease,leading to serious health risks,hospital...
详细信息
In today’s fast-paced world,many elderly individuals struggle to adhere to their medication schedules,especially those with memory-related conditions like Alzheimer’s disease,leading to serious health risks,hospital-izations,and increased healthcare *** reminder systems often fail due to a lack of personalization and real-time *** address this critical challenge,we introduce MediServe,an advanced IoT-enabled medication management system that seamlessly integrates deep learning techniques to provide a personalized,secure,and adaptive *** features a smart medication box equipped with biometric authentication,such as fingerprint recognition,ensuring authorized access to prescribed medication while preventing misuse.A user-friendly mobile application complements the system,offering real-time notifications,adherence tracking,and emergency alerts for caregivers and healthcare *** system employs predictive deep learning models,achieving an impressive classification accuracy of 98%,to analyze user behavior,detect anomalies in medication adherence,and optimize scheduling based on an individual’s habits and health ***,MediServe enhances accessibility by employing natural language processing(NLP)models for voice-activated interactions and text-to-speech capabilities,making it especially beneficial for visually impaired users and those with cognitive ***-based data analytics and wireless connectivity facilitate remote monitoring,ensuring that caregivers receive instant alerts in case of missed doses or medication ***,machine learning-based clustering and anomaly detection refine medication reminders by adapting to users’changing health *** combining IoT,deep learning,and advanced security protocols,MediServe delivers a comprehensive,intelligent,and inclusive solution for medication *** innovative approach not only improves the quality of life for elderly
Over the past two decades, there has been a tremendous increase in the growth of representation learning methods for graphs, with numerous applications across various fields, including bioinformatics, chemistry, and t...
详细信息
Medical research using Artificial Intelligence (AI) is a growing field and, as such, requires large amounts of data to train AI models. A data-trustee infrastructure (DTI) can enable secure data sharing between data p...
详细信息
Latent space geometry provides a rigorous and empirically valuable framework for interacting with the latent variables of deep generative models. This approach reinterprets Euclidean latent spaces as Riemannian throug...
详细信息
Latent space geometry provides a rigorous and empirically valuable framework for interacting with the latent variables of deep generative models. This approach reinterprets Euclidean latent spaces as Riemannian through a pull-back metric, allowing for a standard differential geometric analysis of the latent space. Unfortunately, data manifolds are generally compact and easily disconnected or filled with holes, suggesting a topological mismatch to the Euclidean latent space. The most established solution to this mismatch is to let uncertainty be a proxy for topology, but in neural network models, this is often realized through crude heuristics that lack principle and generally do not scale to high-dimensional representations. We propose using ensembles of decoders to capture model uncertainty and show how to easily compute geodesics on the associated expected manifold. Empirically, we find this simple and reliable, thereby coming one step closer to easy-to-use latent geometries. Copyright 2024 by the author(s).
作者：
Ratanavilisagul, Chiabwoot
Faculty Of Applied Science Department Of Computer And Information Sciences Bangkok Thailand
The task of Handwriting Digits Recognition represents a classification challenge involving the interpretation of handwritten digits sourced from diverse mediums such as paper, photos, touch screens, and other devices....
详细信息
The topic of the current research deals with the early detection of hotspots in photovoltaic (PV) panels using image classification deep learning (DL) techniques. It is an interesting field of research. The author pro...
详细信息
暂无评论