Search Results - Wireless & Networking

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  1. Pervasive Brain-Mobile Interfacing (BMoI) is a new trend that has significantly increased within this decade through the creation of wearable dry contact electroencephalogram (EEG) sensors. Unfortunately, current commercially wearable brain sensors have low accuracy, power limitations and computational restraint based from mobile devices. These lim...
    Published: 11/22/2017
  2. In the most recent decades, material characterization has evolved into the microscopic scanning field. Modern sensors are capable of applying electromagnetic radiation to obtain characterization data on set materials. However, current technologies require rotating sensors or sample adjustments. This causes problems in measurements because it risks ...
    Published: 10/26/2017
  3. Devices that continuously monitor cardiac activity in free living conditions are being integrated into everyday life. Cardiac sensors are an essential advancement for disease diagnostics and evaluation of post-operative progress. Also, these observations are useful for overall physical health and well-being. With today’s technology, smartpho...
    Published: 9/18/2017
  4. Brain Computer Interfaces (BCI) have gained increased attention over the last four decades because they offer intuitive control in an abundance of applications where other interfaces are insufficient or impractical. Current technologies require lengthy training sessions until users achieve an acceptable level of control. Otherwise, users only have ...
    Published: 8/21/2017
  5. Convolutional Neural Networks (CNNs) have gained popularity in many computer vision applications. For example, they are able to train and classify images, video, and speech at high accuracy. However, the multiple layers of convolution and pooling operations necessary for CNNs create redundancy. This makes it difficult to perform real-time classific...
    Published: 8/9/2017
    Inventor(s): Jae-sun Seo, Minkyu Kim
  6. The immense growth of social media has shifted online platforms into effective resources for determining and categorizing potential customers. Relational learning (RL) adopts network connectivity and social media content to establish predictions about users. It uses the influences of social network structures and user content to model a supervised ...
    Published: 6/28/2017
    Inventor(s): Liang Wu, Xia (Ben) Hu, Huan Liu
    Keywords(s):  
  7. Recent breakthroughs in deep neural networks (DNNs) have led to improvements in state-of-the-art speech applications. Conventional DNNs have hundreds or thousands of neurons in each layer, which require a large amount of memory to store the connections between neurons. Implementing these networks in hardware requires a large memory and high computa...
    Published: 3/16/2017
    Keywords(s):  
  8. A lack of a secure caller ID scheme in today's telephone network system leaves users susceptible to voice and voicemail spam used to gain access to sensitive personal information. Additionally, caller ID masking prevents law enforcement agents from tracing a call and tracking down a criminal. Current caller ID authentication systems are computation...
    Published: 12/16/2016
    Category(s): Wireless & Networking
  9. Artificial neural networks have countless applications with their ability for adaptive learning, recognition, and classification. When implemented in software, the artificial neural network algorithms often use a double-precision format. This can result in large area and power requirements for the hardware. Other approaches can be used to determine...
    Published: 12/8/2016
    Inventor(s): Jae-sun Seo
  10. Traffic signal control systems are inefficient for simulating traffic and constrain both research and development. Proposed traffic control systems require high computing power or physical replacement of hardware, which results in high manufacturing costs. Therefore, there is a need for a centralized traffic control system that quickly simulates tr...
    Published: 10/20/2016

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