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The ever-growing threats of security and privacy loss from unauthorized access to mobile devices has led to the development of various biometric authentication methods for easier and safer data access. In this work we present a gait-based continuous authentication method using accelerometer and ground contact force data recorded from a pair of smart socks. Multi-modal learning and auto-encoders are...
Sparsity helps reducing the computation complexity of DNNs by skipping the multiplication with zeros. The granularity of sparsity affects the efficiency of hardware architecture and the prediction accuracy. In this paper we quantitatively measure the accuracy-sparsity relationship with different granularity. Coarse-grained sparsity brings more regular sparsity pattern, making it easier for hardware...
As our population ages, neurological impairments and degeneration of the musculoskeletal system yield gait abnormalities, which can significantly reduce quality of life. Gait rehabilitative therapy has been widely adopted to help patients maximize community participation and living independence. To further improve the precision and efficiency of rehabilitative therapy, more objective methods need...
A finite element model about SFL1-20000/35 type power transformer considering the power losses of fuel tank and clip was built utilizing FLUX 3D software from France in order to obtain the eddy current distribution in the fuel tank and clamp of transformer and estimate the related power losses. In this model, the hysteresis curve can be customized and other constraint conditions can be set. An agreement...
In order to improve the validity and accuracy of wind farm integrated power system dynamic analysis in high-altitude mountainous region, it is necessary to study on modeling of DFIG (Double-Fed Induction Generator) based wind farm considering non-uniformity of wind speed in mountainous region and its applicability analysis. Firstly, the wind speed characteristics of wind farm in high-altitude mountainous...
Convolutional neural networks (CNNs) have recently broken many performance records in image recognition and object detection problems. The success of CNNs, to a great extent, is enabled by the fast scaling-up of the networks that learn from a huge volume of data. The deployment of big CNN models can be both computation-intensive and memory-intensive, leaving severe challenges to hardware implementations...
We designed a crossdevice testing and reporting system, called cross-device testing and reporting system (CD-TRS), to facilitate the functional validation of protocol and application design in large-scale RTWNs. CD-TRS leverages the nice property of RTWNs that all devices in the network are fully synchronized. By specifying and retrieving events and device status from multiple devices in the runtime...
Real-time wireless networks (RTWNs) are fundamental to many Internet-of-Things (IoT) applications. Packet scheduling in an RTWN plays a critical role for achieving desired performance but is a challenging problem especially when the RTWN is large and subject to unexpected disturbances from the environment. Few solutions exist to tackle this challenge but they suffer serious limitations. This paper...
Conventional power converters control pulse width modulation (PWM) signals based on the directly sensed feedback signals or estimated state signals. Recently, information and communication technologies are beginning to integrate power converters into smart grid applications. This paper presents a Hardware-In-The-Loop Testbed using a WirelessHART network for smart home applications in a case study...
Real-time pedestrian detection and tracking are vital to many applications, such as the interaction between drones and human. However, the high complexity of Convolutional Neural Network (CNN) makes them rely on powerful servers, thus is hard for mobile platforms like drones. In this paper, we propose a CNN-based real-time pedestrian detection and tracking system, which can achieve 14.7 fps detection...
Access to sexual information has to be given some restricts on commercial search engine. Compared with filtering porn contents directly, we prefer to recognize porn queries and recommend appropriate ones considering several potential advantages. However, how to recognize them in an automatic way is not a trivial job due that its short length, in most scenarios, doesn’t allow enough information for...
For the problem of online thrust estimation difficulty in aero-engine direct control and health management, the aero-engine thrust estimation method is proposed based on the extreme learning machine. In order to reduce the online computation cost and ensure the sufficient accuracy, the correlation analysis method is used for selecting the input feature parameters. The number of neural network hidden...
This paper presents an improved quantitative index and its solving method for analyzing relative localness of electromechanical oscillation mode, which has the advantages of computational efficiency and practicality compared to the traditional indicator. At first the eigenvalue analysis may be implemented based on small-signal model. And the exponent parameter could be subsequently optimized in the...
Wireless sensing and networking technologies have taken a strong foothold in the process control industry. The focus has now shifted towards applying control with wireless technology. As such, the current industrial wireless sensor network architectures are under increased scrutiny about their real-time, reliability, and security performances. In this paper, we take a renewed look at network synchronization,...
This paper proposes an online calculation method of theoretical power losses for high-voltage(HV) distribution system based on rapid modeling and data quality analysis in order to improve the timeliness, accuracy and efficiency of the important task. At first the power grid structure model can be rapidly formed according to the basis data library transferred from the original PSD-BPA format file....
Real-time wireless sensor and actuator networks (WSANs) have experienced widespread adoption across many industries due to their great advantages of enhanced mobility, easier deployment as well as reduced configuration and maintenance costs. To compensate for the dynamic and unpredictable nature of wireless networks, extensive research efforts have been devoted on algorithm design for efficient network...
The neuromorphic visual processing framework mimicking the biological vision system offers an alternative process into applying computer vision in everyday environment. With the growing interest for an effective approach for making detection of vulnerable road users for the purpose of safety enhancement, the proposed neuromorphic visual processing was tested on vulnerable road users such as cyclists...
Convolutional Neural Network (CNN) has become a successful algorithm in the region of artificial intelligence and a strong candidate for many applications. However, for embedded platforms, CNN-based solutions are still too complex to be applied if only CPU is utilized for computation. Various dedicated hardware designs on FPGA and ASIC have been carried out to accelerate CNN, while few of them explore...
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