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AI Methods for Personalized Suggestions on Smart Glasses Based on Human Activity Recognition

AI Methods for Personalized Suggestions on Smart Glasses Bas...

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4th ieee-EMBS international conference on Wearable and Implantable Body sensor Networks (BSN) / 18th ieee-EMBS international conference on Biomedical and Health Informatics (BHI)

作者： Boucharas, Dimitrios G. Androutsos, Christos Tachos, Nikolaos S. Tripoliti, Evanthia E. Manousos, Dimitrios Skaramagkas, Vasileios Ktistakis, Emmanouil Marias, Kostas Tsiknakis, Manolis Fotiadis, Dimitrios I. FORTH Biomed Res Inst Ioannina Greece Univ Ioannina Dept Mat Sci & Engn Unit Med Technol & Intelligent Informat Syst Ioannina Greece FORTH Inst Comp Sci Iraklion Crete Greece Hellen Mediterranean Univ Dept Elect & Comp Engn Iraklion Crete Greece FORTH Dept Biomed Res Ioannina Greece

ISBN: (数字)9781665487917

ISBN: (纸本)9781665487917

Smart wearables are becoming an irreplaceable part of daily living by supporting their users to maintain or adopt healthier lifestyles and monitor their current status. While the trend is increasing, little has been accomplished in the field of personalized solutions. In the present study, two models derived from distinct conceptual themes were developed, and the performance was evaluated utilizing a wearable prototype in the form of smart glasses. A statistical and a reinforcement learning approach were adopted to construct a personalization layer in terms of a predefined system reaction upon specific user behavior. the settings of the present study involve the user behavior derived from Artificial Intelligence (AI) based human activity recognition, among others, and the system reaction being a supportive Augmented Reality (AR) based functionality. Each approach yielding different benefits and drawbacks, imminently leads to a comparative analysis based on the efficiency offered by assessing the inference, update, and trend handling time. Both models are built upon the user's previous data, resulting in a data driven approach that is entirely different for each user and tailored to the user preferences. the results derived from the comparative analysis indicate that both approaches offer the personalization seeked, with the reinforcement learning approach to adapt faster.

关键词： Smart glasses sensor systems Bayes methods Q-learning

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CSS: Built-In Channel State Scrambling for Secure Wi-Fi Based Sensing

CSS: Built-In Channel State Scrambling for Secure Wi-Fi Base...

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international conference on distributed computing systems

作者： Xiao Deng Dongyu Xia Xun Wang Shuyu Shi Wei Wang State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (数字)9798350386059

ISBN: (纸本)9798350386066

this paper proposes CSS, a built-in channel state scrambling scheme to provide always-on protection for channel state information. CSS uses randomly generated scrambling vectors to emulate human activities, preventing eavesdroppers from recovering human physical activity from the channel state. By carefully designing the scrambling scheme based on physical channel models, we ensure that legacy receivers can successfully decode the frames and all frames transmitted over the air are scrambled. Furthermore, legitimate Wi-Fi sensors can still recover the true activity with a pre-shared secret key. Implementation on a real communication system shows that CSS can retain the same frame-error rate for commercial wireless receivers while misleading eavesdroppers with a success rate of over 95%.

关键词： Wireless communication Wireless sensor networks Receivers Vectors sensor systems OFDM modulation sensors

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A Prototype of IoT-based Real-time Respiratory Rate Monitoring Using an Accelerometer sensor 4

A Prototype of IoT-based Real-time Respiratory Rate Monitori...

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4th international conference on Biomedical Engineering, IBIOMED 2022

作者： Andarevi, Muhammad Hanif Iskandar, Aulia Arif Swiss German University Biomedical Engineering Department Tangerang Indonesia

ISBN: (数字)9781665460798

ISBN: (纸本)9781665460798

the emergence of the internet of things (IoT) has provided a dynamic change of healthcare system that enables interoperability and secure data transmission for a more effective healthcare delivery. this paper extends the implementation of IoT in combining medical devices and sensors with an IoT platform. Among various fundamental vital signs, respiratory rate is one of the most sensitive indicators of physiological conditions. Although it is deemed as a prognostic parameter that can predict miscellaneous diseases, respiratory rate monitoring remains frequently omitted and considered as time-consuming using manual counting methods. To address this problem, this paper presents a prototype of a respiratory rate monitoring device based on IoT and real-time systems. the device is equipped with an accelerometer sensor to measure abdominal movement generated by the inhale-exhale process. Butterworth filter and peak detection algorithm are applied to the signal to detect respiratory cycles. the proposed system uses the message queuing telemetry transport (MQTT) protocol that implements publish-subscribe systems. Respiratory rate results are featured on the Node-RED dashboard with motion and peak signals plotted during the test. Monitoring was carried out on five participants and the results were analyzed using paired t-test. Good performance was demonstrated by having no significant difference in respiratory rate using the proposed method compared to the actual values (p>0.05). Hence, this work provides a convenient technique for respiratory rate estimation and may further allow for the improvement of the effectiveness of remote patient monitoring. © 2022 ieee.

关键词： Accelerometers

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Malware Detection By distributed systems with Partial Centralization

Malware Detection By Distributed Systems with Partial Centra...

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ieee international Workshop on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications

作者： Bohdan Savenko Antonina Kashtalian Sergii Lysenko Oleg Savenko Khmelnytskyi National University Khmelnytskyi Ukraine

the paper proposes approach to use new tools for malware detection in corporate networks, which are distributed systems with partial centralization. To make decision about malware presence, the components which includes specified decision-making for the system's center are defined as a decentralized subsystem. To determine the states of the system components, characteristic indicators are proposed, and generalized analytical expressions for their calculation are developed. Such calculations make it possible to assess the state of the components in the system in order to determine its further steps. As a result, the system is the basis for usage of different malware detection methods in combination with the system components as an integral sensor. To test the system, a worm-virus detection method was implemented and experiments were conducted. the results of experimental studies approved the efficiency of the proposed solution.

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Intelligent Space Robots Integrated with Enhanced Information Technology and Development Activities 4

Intelligent Space Robots Integrated with Enhanced Informatio...

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4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Venice, J. Arockia thoti, Kiran Kumar Henrietta, H. Mary Elangovan, Muniyandy Anusha, D.J. Zhakupova, Aliya DMI-ST. Eugene University India Universiti Malaysia Kelantan Department of Mgseb & Fkp Kelantan Malaysia College Saveetha Engineering College Department Mathematics India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Mechanical Engineering India School of Engineering & Technology Sri Padmavati MahilaVisvavidyalayam Department of Computer Science & Engineering India International Education Corporation Department of Linguistics Kazakhstan

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

this work presents the most recent research in Intelligent Intervals, which combines modern information technology and advanced robotics. Researchers use robots outfitted with various sensors and instruments on the surface of other planets, in orbit, or as aides to astronauts. the ability of space robots to move, work, and intelligently explore without needing to be touched on a frequent basis or relying heavily on human operators is important to their use. this necessitates the ability to comprehend the chaotic or unfamiliar environment in which people find themselves. In such a scenery, intellectual thinking about perception is required to carry out actions in a meaningful and consistent manner. As a result, the effectiveness of robotics and automated space systems in space exploration is intimately related to robot intelligence or autonomy. the Smart Space initiative has evolved in scope and complexity since its inception in 1996. the core of a smart space is a ubiquitous sensor network integrated into the human living environment that can track a large number of people and other objects in space. With the help of intelligent space, mobile robots operate in human living areas and provide a variety of services, such as human direction. Robots are becoming more capable of solving tough space resources and planetary surfaces with autonomy and prowess as space agencies throughout the world improve their robotic missions, proving their value and usefulness in every mission. the demand for this capability is increasing as international space agencies need humans and intelligent robots. © 2022 ieee.

关键词： Intelligent robots

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thoughts on Non-IID Data Impact in Healthcare with Federated Learning Medical Blockchain 4

Thoughts on Non-IID Data Impact in Healthcare with Federated...

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ieee 4th international conference on Cognitive Machine Intelligence (CogMI)

作者： Shae, Zon-Yin Chen, Kun-Yi Chang, Chi-Yu Tsai, Yuan-Yu Chou, Che-Yi Baskett, William I. Shyu, Chi-Ren Tsai, Jeffrey J. P. Asia Univ Dept Comp Sci & Informat Engn Taichung Taiwan Asia Univ Dept M Commerce & Multimedia Applicat Taichung Taiwan Asia Univ Hosp Div Nephrol Taichung Taiwan Univ Missouri Inst Data Sci & Informat Columbia MO USA Asia Univ Dept Bioinformat & Med Engn Taichung Taiwan

ISBN: (纸本)9781665474061

We share the common hypothesis/belief that the more aggregated good quality training data, the better the performance that can be attained by the resulting Artificial Intelligence (AI) model. However, this common belief, in general, is not true in the medical area, since healthcare data sets sourced from different hospitals are often not identically distributed (NonIID). this imposes severe technical challenges for effectively aggregating the individual hospital data sets together. In this vision paper, instead of offering complete solutions, we will discuss some questions and food for thought with the goal of aiding effective data aggregation and improving federated learning (FL) AI model performance: (1) benchmark and measure the Non-IID degree of medical data sets. (2) include the Non-IID degree metrics in the FL data aggregation mechanism. (3) search for the optimal global model creation strategy among a group of many medical data sets. (4) investigate FL performance better than the centralized learning. this paper will discuss these questions by outlining a visionary approach for exploring a medical blockchain FL mechanism to effectively aggregate medical data across multiple healthcare systems to serve large populations with broad demographics.

关键词： Medical blockchain non-iid health data privacy medical data set aggregation distributed federated medical data lake AI federated learning

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A Deep Learning-Based Human Action Recognition Based on Depth Maps, Skeletons, and sensor Images 4

A Deep Learning-Based Human Action Recognition Based on Dept...

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4th international conference on Emerging Research in Electronics, Computer Science and Technology, ICERECT 2022

作者： Rajput, Gaurav Kumar Lal Yadav, Ram Teerthanker Mahaveer University Department of Computing Science and IT Moradabad India Jaipur National University Department of Computer Sciences Jaipur India

ISBN: (纸本)9781665456357

this study describes a method for identifying human behavior based on depth motion maps. A depth video array projects each depth outline onto three symmetric Cartesian planes. A comprehensive depth video group forming a depth motion map, under each projection view he captures the unique differences between two successive projection maps. A 12-regularized joint representation classifier with a distance-weighted Tikhonov lattice is then applied for action detection. the developed method has been proven to be computationally efficient and capable of stepwise manipulation. Detection results using the Microsoft Exploration Action3D dataset show that our strategy performs more effectively than existing methods. Convolutional neural networks are used in this paper to offer a solution for human action recognition based on depth images and posture data (CNN). Both a depth motion image (DMI) and a proposed moving joint descriptor (MJD) are used as inputs for the purpose of action representation. © 2022 ieee.

关键词： Convolutional neural networks

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Hierarchical Clustering Detection Based Secure Fusion Filtering for Multiple False Data Injection Attacks 4

Hierarchical Clustering Detection Based Secure Fusion Filter...

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4th ieee international conference on Industrial Cyber-Physical systems (ICPS)

作者： Feng, Xiaoliang Yan, Jingjing Zheng, Jian Guo, Yaguang Shanghai Dianji Univ Sch Elect Engn Shanghai Peoples R China Henan Univ Technol Coll Elect Engn Zhengzhou Peoples R China Shanghai Maritime Univ Coll Transport & Commun Shanghai Peoples R China

ISBN: (纸本)9781728162072

this paper concerns the secure fusion filtering under multiple false data injection attack scenarios. A hierarchical clustering based secure fusion filtering approach is proposed for the remote-measuring system with a known secure node. the fusion filtering approach includes two parts. In the local filtering part, the remote measurement is utilized to estimate the system sate locally, after detected by Chi-square detector. In the distributed fusion part, a novel hierarchical clustering detection based distributed fusion method is provided to obtain the final fusion filtering results. the simulation results are presented to illustrate the effectiveness of the proposed approach.

关键词： Cyber physical system secure fusion filtering hierarchical clustering detection distributed fusion

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Fast distributed Stochastic Scheduling for A Multi-Energy Industrial Park 4

Fast Distributed Stochastic Scheduling for A Multi-Energy In...

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4th ieee international conference on Industrial Cyber-Physical systems (ICPS)

作者： Zhu, Dafeng Yang, Bo Wang, Zhaojian Ma, Chengbin Ma, Kai Zhu, Shanying Shanghai Jiao Tong Univ Dept Automat Shanghai Peoples R China Shanghai Jiao Tong Univ Univ Michigan Shanghai Jiao Tong Univ Joint Inst Shanghai Peoples R China Yanshan Univ Sch Elect Engn Qinhuangdao Hebei Peoples R China

ISBN: (纸本)9781728162072

the multi-energy management framework of industrial parks advocates energy conversion and scheduling, which takes full advantage of the compensation and temporal availability of multiple energy. However, how to exploit elastic loads and compensate inelastic loads to match multiple generators and storage is still a key problem under the uncertainty of demand and supply. To solve the issue, the energy management problem is constructed as a stochastic optimization problem. the optimization aims are to minimize the time-averaged energy cost and improve the energy efficiency while respecting the energy constraints. To achieve the distributed implementation in real time without knowing any priori knowledge of underlying stochastic process, a distributed stochastic gradient algorithm based on dual decomposition and a fast scheme are proposed. the numerical results based on real data show that the industrial park, by adopting the proposed algorithm, can achieve social welfare maximization asymptotically.

关键词： Multi-energy management framework industrial park distributed implementation stochastic gradient algorithm

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Sample-based Event-triggered Control of thermostatically Controlled Loads for Demand Side Management

Sample-based Event-triggered Control of Thermostatically Con...

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4th ieee international conference on Cyborg and Bionic systems (CBS)

作者： Xu, Chenguan Xu, Jing Wang, Kui Zhu, Liangliang Yu, Meng Jiang, Cheng Rao, Yao Nan Grp Corp State Grid Elect Power Res Inst Nanjing 210000 Peoples R China State Grid Elect Power Res Inst Wuhan Efficiency Wuhan Peoples R China

ISBN: (纸本)9781665490283

In this paper, a distributed sample-based event-triggered method is proposed to coordinate the thermostatically controlled loads (TCLs) such that the photovoltaic and load variations can be alleviated from demand side. Firstly, a sample-based event-triggered control scheme, where each TCL communicates with its neighbor TCLs only when the event-triggered condition is satisfied, and thus reducing redundant communication to save the limited communication network resources. then, an initial power state updating scheme of each TCL is designed based on the output of PVs and loads such that the supply and demand balance can be satisfied from demand side. Under the designed control scheme, the resident's comfort temperature range requirement can be met. Furthermore, the challenge problem Zeno behavior that often occurs in event-triggered control is automatically excluded. Finally, by employing Lyapunov stability theory, the sufficient criteria is rigidly derived.

关键词： Demand side management distributed control event-triggered communication thermostatically controlled loads

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