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Sensor Pillow and Bed Sheet System: Unconstrained Monitoring of Respiration Rate and Posture Movements During Sleep

Sensor Pillow and Bed Sheet System: Unconstrained Monitoring...

引用

IEEE International Conference on Systems, Man, and Cybernetics

作者： Shongpun Lokavee Theeraporn Puntheeranurak Teerakiat Kerdcharoen Natthapol Watthanwisuth Adisorn Tuantranont Materials Science and Engineering Programme Faculty of Science Mahidol University Nanoelectronic and MEMS Lab National Electronic and Computer Technology Center

ISBN: (纸本)9781467317139

In this paper, we have developed a low-cost sleep monitoring system for patient based on polysomnography which will be useful for patient communication with healthcare personals and/or relatives. In particular, we have presented the sensor pillow and bed sheet system that employs wireless networks based on low-cost ZigBee technology and a sensor array of force sensitive resistors (FSR) based on polymer thick film (PTF) device, for classifying and specifically verifying the respiration rate during sleep. This paper also proposes a simple motion model that explains the change of head and body pressure distribution. In addition, we can detect some physiological parameters during the sleep stages and wakefulness as well as record respiration rate as related to different physiological factors. The integration of this sensor system and wireless technology with computer software could make this healthcare monitoring system a commercial product valuable for point-of-care applications.

关键词： Polysomnography Healthcare monitoring Wireless sensor networks Respiratory Rate Coverlets Sleep Stages Sleep Sensor arrays Polysomnography Sensor systems pillow Wireless Technology Wakefulness computer software

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A Hybrid Context Model for Pervasive Healthcare System

A Hybrid Context Model for Pervasive Healthcare System

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2011 International Conference on Advanced Materials and computer science(ICAMCS 2011)

作者： Shouming Ma Ruchuan Wang Ning Ye School of Computer Science and Technology Nangjing University of Posts and Telecommunications Department of Information Science Nanjing College for Population Programme Management

Pervasive computing applications aim to provide appropriate services that respond directly to their users and environments,with greatly reduced explicit human guidanceThese applications usually adapt to changing failure-prone context information which was acquired from various sources that differ in quality and formatTo efficiently acquire,share,correlate,and reason over raw existing context data,they must be modeled in a homogenous fashionIn this paper,we propose a hybrid context modelling approach,which attempt to integrate the advantages of object-oriented model and ontology-based model for their distributed context handling and efficient context reasoning respectivelyWe have applied this model to the development of a context management middleware which providing an extensible application framework for monitoring and assisting the elderly at home environments

关键词： pervasive computing context-awareness context modelling hybrid model ontology.

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K- Nearest Neighbour-Based Chronic Kidney Disease Prediction System: A Case of Toxic Metals in Urine

K- Nearest Neighbour-Based Chronic Kidney Disease Prediction...

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science, Engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Adebusola Tope-Oke Bukola Badeji-Ajisafe Abiodun Oguntimilehin Martin Victor Inyang Opani Aweh Oluwatoyin Abiola Department of Mathematical and Physical Sciences (Computer Science Programme) Afe Babalola University Ado-Ekiti Nigeria

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

Loss of renal function is a symptom of chronic kidney disease (CKD). Numerous lives are lost each year as a result of the disease, which frequently has symptoms that are not obvious. Since kidney disease is a progressive condition, it spreads quickly and eventually causes a decline in kidney function. Using factors like age, bacteria, diabetes mellitus, and white blood cell count to name a few, previous studies predicted kidney illness, but they did not incorporate toxic metals in urine. Using machine learning methods, CKD may be predicted with a high degree of accuracy in medical investigations. Thus, this study uses three of the supervised classification methods learning algorithms, which include, Decision tree, Random Forest, and K Nearest Neighbor (KNN) algorithms for the prediction of CKD. A raw dataset of hazardous metals in urine that was gathered from two Nigerian hospitals was used to analyze the performance of the algorithms' predictions. Copper (Cu), Zinc (Zn), Iron (Fe), Lead (Pb), Magnesium (Mg), Chromium (Cr), Cadmium (Cd), and Selenium (Se) are some of these metals. Based on how accurate the results were, a performance analysis was carried out. According to the comparison of the algorithms, the KNN method, which has the highest accuracy, is ideal for predicting chronic renal disease. This work created a system to predict CKD along five classifications using the KNN algorithm.

关键词： Accuracy Machine learning algorithms Nearest neighbor methods Lead Prediction algorithms Chronic kidney disease Classification algorithms

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Performance of APN guidance law in a two dimensional aerial engagement scenario

Performance of APN guidance law in a two dimensional aerial ...

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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： K.N. Swamy I.G. Sarma Advanced Technology Programme I.G.Sarma Professor of Computer Science and Automation Indian Institute of Science Bangalore India

In the available literature, the main advantage claimed for APN (augmented proportional navigation) is that it demands a progressively decreasing missile acceleration in the constant target maneuver situation, as opposed to an increasing missile acceleration for the more conventional PN guidance. This inference is mainly based on studies with one-dimensional models. Based on a two-dimensional model, the authors not only incorporate a more realistic target maneuver, but also consider the effect of target glint characterized by correlated noise. The missile acceleration and the miss-distance induced by target maneuver and glint are the two features of performance investigated. In a deterministic study, with target maneuver initiation occurring at various points in time, the acceleration profiles resemble the ones obtained from a linear quadratic tracking formulation of the guidance problem. The results indicate that there is a considerable improvement in the miss distance performance over PN, for maneuvers which are initiated when the relative separation is small.< >

关键词： Acceleration Missiles Navigation White noise Delay estimation computer science Automation Target tracking Low pass filters Filtering

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Heterogeneous 360 Degree Videos in Metaverse: Differentiated Reinforcement Learning Approaches

Heterogeneous 360 Degree Videos in Metaverse: Differentiated...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Wenhan Yu Jun Zhao Interdisciplinary Graduate Programme Nanyang Technological University School of Computer Science & Engineering Nanyang Technological University

Advanced video technologies are driving the development of the futuristic Metaverse, which aims to connect users from anywhere and anytime. As such, the use cases for users will be much more diverse, leading to a mix of 360-degree videos with two types: non-VR and VR 360° videos. This paper presents a novel Quality of Service model for heterogeneous 360° videos with different requirements for frame rates and cybersickness. We propose a frame-slotted structure and conduct frame-wise optimization using self-designed differentiated deep reinforcement learning algorithms. Specifically, we design two structures, Separate Input Differentiated Output (SIDO) and Merged Input Differentiated Output (MIDO), for this heterogeneous scenario. We also conduct comprehensive experiments to demonstrate their effectiveness.

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Learning on paper: Diagrams and discovery in game playing 2

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2nd International Conference on Diagrammatic Representation and Inference, Diagrams 2002

作者： Epstein, Susan L. Keibel, J.-Holger Department of Computer Science Hunter College Graduate School of the City University of New York New York NY 10021 United States Germanics Department Graduate Programme in Human and Machine Intelligence University of Freiburg 79098 Freiburg Germany

ISBN: (纸本)3540435611

Diagrams play an important role in human problem solving. In response to a challenging assignment, three students produced diagrams and subsequent verbal protocols that offer insight into human cognition. The diversity and richness of their response, and their ability to address the task via diagrams, provide an incisive look at the role diagrams play in the development of expertise. This paper recounts how their diagrams led and misled them, and how the diagrams both explained and drove explanation. It also considers how this process might be adapted for a computer program. © Springer-Verlag 2002.

关键词： Adversarial machine learning

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Virtual Reality in Metaverse Over Wireless Networks with User-Centered Deep Reinforcement Learning

Virtual Reality in Metaverse Over Wireless Networks with Use...

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IEEE International Conference on Communications (ICC)

作者： Wenhan Yu Terence Jie Chua Jun Zhao Interdisciplinary Graduate Programme Nanyang Technological University School of Computer Science & Engineering Nanyang Technological University

The Metaverse and its promises are fast becoming reality as maturing technologies are empowering the different facets. One of the highlights of the Metaverse is that it offers the possibility for highly immersive and interactive socialization. Virtual reality (VR) technologies are the backbone for the virtual universe within the Metaverse as they enable a hyper-realistic and immersive experience, and especially so in the context of socialization. As the virtual world 3D scenes to be rendered are of high resolution and frame rate, these scenes will be offloaded to an edge server for computation. Besides, the metaverse is user-center by design, and human users are always the core. In this work, we introduce a multi-user VR computation offloading over wireless communication scenario. In addition, we devised a novel user-centered deep reinforcement learning approach to find a near-optimal solution. Extensive experiments demonstrate that our approach can lead to remarkable results under various requirements and constraints.

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In-class use of the nu-case mobile telehealth system in a medical school

In-class use of the nu-case mobile telehealth system in a me...

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作者： Carloni, Marcelo Ballaben Cesario, Manuel Cesario, Raquel Rangel Luz, Saturnino Margarido, Edson Masoodian, Masood Pires, Daniel Facciolo Medical School University of Franca São Paulo Brazil Graduate Programme on Health Promotion University of Franca São Paulo Brazil Uni-FACEF São Paulo Brazil School of Computer Science and Statistics Trinity College Dublin Dublin Ireland Department of Computer Science University of Waikato Hamilton New Zealand

As telehealth systems are increasingly being adopted by healthcare providers, a growing number of medical practitioners need to learn to use such systems. Despite this, however, most medical schools do not currently include telehealth-related content in their curriculum. In this paper we demonstrate, through examples from our own experience, how the Problem Based Learning method can be used to incorporate telehealth systems in medical science education. We also present a survey of medical students and faculty, conducted at a university in Brazil, to gain the participants' opinions on the nu-case mobile telehealth system. The results of the survey show that nu-case provides support for a range of tasks that a telehealth system needs to cater for in the context of our application area. © 2013 IEEE.

关键词： Surveys

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Time-based Geographical Mapping of Communicable Diseases

Time-based Geographical Mapping of Communicable Diseases

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International Conference on Information Visualisation (IV)

作者： Manuel Cesario Matthew Jervis Saturnino Luz Masood Masoodian Bill Rogers Graduate Programme on Health Promotion University of Franca Brazil Department of Computer Science University of Waikato New Zealand School of Computer Science and Statistics Trinity College Dublin Ireland

Information visualisation methods can potentially be employed to assist the work of epidemiologists and other health care professionals in mapping the spread of communicable diseases in remote areas, where the task of disease surveillance encompasses temporal elements such as changes in climate, land use and population movements. This paper presents an investigation into the use of time-based visualisation techniques coupled with geographical maps and support for distributed mobile collection of patient data. This study has focused on the development of an information visualisation prototype designed for use by epidemiology researchers on mobile platforms (tablets and smart phones). The prototyping activity has involved the participation of prospective users working in the Amazon region. Initial results are presented and discussed.

关键词： Diseases Data visualization Surveillance Prototypes Sociology Statistics

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Computation-Efficient Model Predictive Control of a Multilevel Current Source Converter 49

Computation-Efficient Model Predictive Control of a Multilev...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Chen, Muyu Yuan, Zhige Ghias, Amer M. Y. M. Nicholas, Vun Chan Hua School of Electrical and Electronic Engineering Collab. Initiative Interdisciplinary Graduate Programme Nanyang Technological University Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9798350331820

This paper presents a modified finite control set model predictive control (FCS-MPC) that can significantly reduce computation time and maintain good quality of output voltage. The switching states of a three-phase five-level current source converter (5L-CSC) are sorted according to the corresponding output converter current level. The influences of every switching state on the converter inductor current are analyzed. Then the optimal switching state can be anchored based on the converter current level that minimizes the cost function and converter inductor current conditions. The proposed method eliminates the need for the discrete-time model establishment for the converter. It avoids the ergodic search through all switching states, easing the controller's computation burden. Besides, this algorithm achieves multiple control goals without assigning different weighting factors to various control objectives. The simulated output voltage total harmonics distortion (THD), the inductor current ripple, and the execution time of the modified model predictive control and traditional model predictive control are compared to validate the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Model predictive control

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