The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform

Benxiong Huang - One of the best experts on this subject based on the ideXlab platform.

  • DASC - Password Recovery for RAR Files Using CUDA
    2009 Eighth IEEE International Conference on Dependable Autonomic and Secure Computing, 2009
    Co-Authors: Guang Hu, Jianhua Ma, Benxiong Huang
    Abstract:

    Driven by the Insatiable Demand of real-time graphics, especially from the market of computer games, Graphics Processing Unit (GPU) is becoming a major computing horsepower during recent years since the performance of GPU is surpassing that of the contemporary CPU. This paper presents our study on how to efficiently recover the passwords for encrypted RAR files. Our research focus is on the AES key generation processing, which is the most time consuming stage in the whole RAR encryption/decryption process. The design and implementation of the password recovery are based on NVIDIA's CUDA (Computer Unified Device Architecture). A CPU-based version is also implemented as a reference and the performance comparison with that of the GPU-based version. In addition, a modified model is proposed to estimate the performance by static analysis of code for and then further assist program optimization.

  • Password Recovery for RAR Files Using CUDA
    2009 Eighth IEEE International Conference on Dependable Autonomic and Secure Computing, 2009
    Co-Authors: Guang Hu, Benxiong Huang
    Abstract:

    Driven by the Insatiable Demand of real-time graphics, especially from the market of computer games, graphics processing unit (GPU) is becoming a major computing horsepower during recent years since the performance of GPU is surpassing that of the contemporary CPU. This paper presents our study on how to efficiently recover the passwords for encrypted RAR files. Our research focus is on the AES key generation processing, which is the most time consuming stage in the whole RAR encryption/decryption process. The design and implementation of the password recovery are based on NVIDIA's CUDA (computer unified device architecture). A CPU-based version is also implemented as a reference and the performance comparison with that of the GPU-based version. In addition, a modified model is proposed to estimate the performance by static analysis of code for and then further assist program optimization.

Ronald Freund - One of the best experts on this subject based on the ideXlab platform.

  • Coexistence of WiFi and LiFi toward 5G: Concepts, opportunities, and challenges
    IEEE Communications Magazine, 2016
    Co-Authors: Moussa Ayyash, Michael B. Rahaim, Jonas Hilt, Thomas Little, Volker Jungnickel, Thomas D.c. Little, Dominic Schulz, Rudolf Freund, Sihua Shao, Abdallah Khreishah, Hany Elgala, Ronald Freund
    Abstract:

    Smart phones, tablets, and the rise of the Internet of Things are driving an Insatiable Demand for wireless capacity. This Demand requires networking and Internet infrastructures to evolve to meet the needs of current and future multimedia applications. Wireless HetNets will play an important role toward the goal of using a diverse spectrum to provide high quality-of-ser- vice, especially in indoor environments where most data are consumed. An additional tier in the wireless HetNets concept is envisioned using indoor gigabit small-cells to offer additional wire- less capacity where it is needed the most. The use of light as a new mobile access medium is considered promising. In this article, we describe the general characteristics of WiFi and VLC (or LiFi) and demonstrate a practical framework for both technologies to coexist. We explore the existing research activity in this area and articu- late current and future research challenges based on our experience in building a proof-of-concept prototype VLC HetNet.

Timothy Tsui - One of the best experts on this subject based on the ideXlab platform.

  • ACCV (1) - An FPGA-based smart camera for gesture recognition in HCI applications
    Computer Vision – ACCV 2007, 2007
    Co-Authors: Timothy Tsui
    Abstract:

    Smart camera is a camera that can not only see but also think and act. A smart camera is an embedded vision system which captures and processes image to extract application-specific information in real time. The brain of a smart camera is a special processing module that performs application specific information processing. The design of a smart camera as an embedded system is challenging because video processing has Insatiable Demand for performance and power, but at the same time embedded systems place considerable constraints on the design. We present our work to develop GestureCam, an FPGA-based smart camera built from scratch that can recognize simple hand gestures. The first completed version of GestureCam has shown promising real-time performance and is being tested in several desktop HCI (Human Computer Interface) applications.

  • An FPGA-Based Smart Camera for Gesture Recognition in HCI Applications
    Computer Vision – ACCV 2007, 2007
    Co-Authors: Yu Shi, Timothy Tsui
    Abstract:

    Smart camera is a camera that can not only see but also think and act. A smart camera is an embedded vision system which captures and processes image to extract application-specific information in real time. The brain of a smart camera is a special processing module that performs application specific information processing. The design of a smart camera as an embedded system is challenging because video processing has Insatiable Demand for performance and power, but at the same time embedded systems place considerable constraints on the design. We present our work to develop GestureCam, an FPGA-based smart camera built from scratch that can recognize simple hand gestures. The first completed version of GestureCam has shown promising realtime performance and is being tested in several desktop HCI (Human Computer Interface) applications. © Springer-Verlag Berlin Heidelberg 2007.

Guang Hu - One of the best experts on this subject based on the ideXlab platform.

  • DASC - Password Recovery for RAR Files Using CUDA
    2009 Eighth IEEE International Conference on Dependable Autonomic and Secure Computing, 2009
    Co-Authors: Guang Hu, Jianhua Ma, Benxiong Huang
    Abstract:

    Driven by the Insatiable Demand of real-time graphics, especially from the market of computer games, Graphics Processing Unit (GPU) is becoming a major computing horsepower during recent years since the performance of GPU is surpassing that of the contemporary CPU. This paper presents our study on how to efficiently recover the passwords for encrypted RAR files. Our research focus is on the AES key generation processing, which is the most time consuming stage in the whole RAR encryption/decryption process. The design and implementation of the password recovery are based on NVIDIA's CUDA (Computer Unified Device Architecture). A CPU-based version is also implemented as a reference and the performance comparison with that of the GPU-based version. In addition, a modified model is proposed to estimate the performance by static analysis of code for and then further assist program optimization.

  • Password Recovery for RAR Files Using CUDA
    2009 Eighth IEEE International Conference on Dependable Autonomic and Secure Computing, 2009
    Co-Authors: Guang Hu, Benxiong Huang
    Abstract:

    Driven by the Insatiable Demand of real-time graphics, especially from the market of computer games, graphics processing unit (GPU) is becoming a major computing horsepower during recent years since the performance of GPU is surpassing that of the contemporary CPU. This paper presents our study on how to efficiently recover the passwords for encrypted RAR files. Our research focus is on the AES key generation processing, which is the most time consuming stage in the whole RAR encryption/decryption process. The design and implementation of the password recovery are based on NVIDIA's CUDA (computer unified device architecture). A CPU-based version is also implemented as a reference and the performance comparison with that of the GPU-based version. In addition, a modified model is proposed to estimate the performance by static analysis of code for and then further assist program optimization.

Sheikh S. Muhammad - One of the best experts on this subject based on the ideXlab platform.

  • Achievable capacity region of a Gaussian optical wireless relay channel
    IEEE OSA Journal of Optical Communications and Networking, 2015
    Co-Authors: A. D. Raza, Sheikh S. Muhammad
    Abstract:

    Congested and expensive radio spectrum coupled with an Insatiable Demand for higher throughput in the last mile makes optical wireless an attractive alternative. The limitation of coverage area of optical wireless links is compensated by their ultrahigh bandwidth and unregulated spectrum. Cooperative relay strategies can further enhance the capacity and availability of optical wireless. A number of researchers have studied how the capacity of an optical relay channel is effected by fading processes. However, the capacity of an optical wireless relay channel (OWRC) has received little attention. This paper attempts to delineate the achievable capacity region of a Gaussian OWRC. Decode and forward, compress and forward, and amplify and forward relay strategies are used to determine the capacity bounds that constitute the achievable region. High and low signal asymptotes of the bounds are developed. The probability of outage under fading induced by turbulence and pointing error is also discussed. The results presented in this paper will facilitate the design of optical wireless relay networks in terms of choice of relaying strategy and input distribution.