Gait Analysis. An Introduction

Biometric Recognition - Security and Privacy Concerns.

Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future

digital video and hdtv algorithms and interfaces is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the digital video and hdtv algorithms and interfaces is universally compatible with any devices to read.

Digital Video And Hdtv Algorithms And Interfaces

The interest in using drones in various applications has grown significantly in recent years. The reasons are related to the continuous advances in technology, especially the advent of fast microprocessors, which support intelligent autonomous control of several systems. Photography, construction, and monitoring and surveillance are only some of the areas in which the use of drones is becoming common. Among these, last-mile delivery is one of the most promising areas. In this work we focus on routing problems with drones, mostly in the context of parcel delivery. We survey and classify the existing works and we provide perspectives for future research.

Drone-aided routing: A literature review

Highly developed drone technology enables the use of drones in a wide variety of areas. However, those drones are mainly used in the unmanned aerial vehicles. We believe that underwater drones will become a big research topic and find a market in the near future. We developed an underwater drone with a 360° panoramic camera acting as the “eye” of the drone. The designs are based on the open-source hardware and will be shared as an open-source for contributing to the innovation of manufacturing including drone. The function of the 360° panoramic camera is generated by correcting the images taken by two fisheye lenses. The underwater drone was designed by extending the Raspberry Pi compute module, the frame was designed by OpenSCAD, and the printed circuit board was designed by MakePro. As for the application of the underwater drone, we focused on fish recognition for investigating fish species in a natural lake to help protect the original environment. Fish recognition is based on deep learning, which is the biggest topic in the artificial intelligence research field today. Experimental results show that the function of the underwater drone achieved at diving in the leak automatically. The 360° panoramic images were generated correctly. Fish recognition achieved 87% accuracy by deep learning.

Underwater-Drone With Panoramic Camera for Automatic Fish Recognition Based on Deep Learning

As a promising new paradigm, Vehicular Edge Computing (VEC) can improve the QoS of vehicular applications by computation offloading. However, with more and more computation-intensive vehicular applications, VEC servers face the challenges of limited resources. In this paper, we study how to effectively and economically utilize the idle resources in volunteer vehicles to handle the overloaded tasks in VEC servers. First, we present a model of volunteer assisted vehicular edge computing, in which the cost and utility functions are defined for requesting vehicles and VEC servers, and volunteer vehicles are encouraged to assist the overloaded VEC servers via obtaining rewards from VEC servers. Then, based on Stackelberg game, we analyze the interactions between requesting vehicles and VEC servers, and find the optimal strategies for them. Furthermore, we prove theoretically that the Stackelberg game between requesting vehicles and VEC servers has a unique Stackelberg equilibrium, and propose a fast searching algorithm based on genetic algorithm to find the best pricing strategy for the VEC server. In addition, to maximize the reward of volunteer vehicles, we propose the volunteer task assignment algorithm for optimal mapping between the tasks and volunteer alliances. Finally, the effectiveness of the proposed scheme is demonstrated through a large number of simulations. Compared with other schemes, the proposed scheme can reduce the offloading cost of vehicles and improve the utility of VEC servers.

Volunteer Assisted Collaborative Offloading and Resource Allocation in Vehicular Edge Computing

A HOG-SVM Based Fall Detection IoT System for Elderly Persons Using Deep Sensor

Recent research regards the electroencephalogram (EEG) as a promising method to study real-time brain dynamic changes in patients with Parkinson's disease (PD), but a deeper understanding is needed to discern coincident pathophysiology, patterns of changes, and diagnosis. This review summarized recent research on EEG characterization related to the cognitive and motor functions in PD patients and discussed its potential to be used as diagnostic biomarkers. Thirty papers out of 220 published from 2010 to 2020 were reviewed. Movement abnormalities and cognitive decline are related to changes in EEG spectrum and event-related potentials (ERPs) during typical oddball paradigms and/or combined motor tasks. Abnormalities in β and δ frequency bands are, respectively the main manifestation of dyskinesia and cognitive decline in PD. The review showed that PD patients have noteworthy changes in specific EEG characterizations, however, the underlying mechanism of the interrelation between gait and cognitive is still unclear. Understanding the specific nature of the relationship is essential for development of novel invasive clinical diagnostic and therapeutic methods.

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Lin Meng

Papers

Underwater-Drone With Panoramic Camera for Automatic Fish Recognition Based on Deep Learning

Volunteer Assisted Collaborative Offloading and Resource Allocation in Vehicular Edge Computing

A HOG-SVM Based Fall Detection IoT System for Elderly Persons Using Deep Sensor

Characterization of EEG Data Revealing Relationships With Cognitive and Motor Symptoms in Parkinson's Disease: A Systematic Review.

Machine learning based real-time visible fatigue crack growth detection