The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Washington Y Ochieng - One of the best experts on this subject based on the ideXlab platform.
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Integrated Solution for anomalous driving detection based on beidou gps imu measurements
Transportation Research Part C-emerging Technologies, 2016Co-Authors: Rui Sun, Washington Y Ochieng, Ke Han, Yanjun WangAbstract:Abstract There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, centimeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new Integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable Solution for performing these tasks.
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an Integrated Solution for lane level irregular driving detection on highways
Transportation Research Part C-emerging Technologies, 2015Co-Authors: Rui Sun, Washington Y Ochieng, Shaojun FengAbstract:Global Navigation Satellite Systems (GNSS) has been widely used in the provision of Intelligent Transportation System (ITS) services. Current meter level system availability can fulfill the road level applications, such as route guide, fleet management and traffic control. However, meter level of system performance is not sufficient for the advanced safety applications. These lane level safety applications requires centimeter/decimeter positioning accuracy, with high integrity, continuity and availability include lane control, collision avoidance and intelligent speed assistance, etc. Detecting lane level irregular driving behavior is the basic requirement for these safety related ITS applications. The two major issues involved in the lane level irregular driving identification are accessing to high accuracy positioning and vehicle dynamic parameters and extraction of erratic driving behaviour from this and other related information. This paper proposes an Integrated Solution for the lane level irregular driving detection. Access to high accuracy positioning is enabled by GNSS and Inertial Navigation System (INS) integration using filtering with precise vehicle motion models and lane information. The detection of different types of irregular driving behaviour is based on the application of a Fuzzy Inference System (FIS). The evaluation of the designed Integrated systems in the field test shows that 0.5 m accuracy positioning source is required for lane level irregular driving detection algorithm and the designed system can detect irregular driving styles.
Peng Zhang - One of the best experts on this subject based on the ideXlab platform.
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software infrastructure for enabling fpga based accelerations in data centers invited paper
International Symposium on Low Power Electronics and Design, 2016Co-Authors: Jason Cong, Peichen Pan, Muhuan Huang, Di Wu, Peng ZhangAbstract:This paper focuses on the development of an infrastructure to enable FPGA-based acceleration in data centers. We present an initial version of an Integrated Solution that includes automated compilation for accelerator generation, runtime accelerator resource scheduling and management, and acceleration libraries for FPGA-based customized computing for big data applications. The Solution can help overcome some of the main challenges with FPGA-based accelerated computing. It has the potential to bring significant performance and energy efficiency improvement for data center applications.
Sharad Singhal - One of the best experts on this subject based on the ideXlab platform.
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Integrated management of application performance, power and cooling in data centers
2010 IEEE Network Operations and Management Symposium - NOMS 2010, 2010Co-Authors: Yuan Chen, Chris Hyser, Cullen Bash, Christopher Hoover, Daniel Gmach, Zhikui Wang, Sharad SinghalAbstract:Data centers contain IT, power and cooling infrastructures, each of which is typically managed independently. In this paper, we propose a holistic approach that couples the management of IT, power and cooling infrastructures to improve the efficiency of data center operations. Our approach considers application performance management, dynamic workload migration/consolidation, and power and cooling control to “right-provision” computing, power and cooling resources for a given workload. We have implemented a prototype of this for virtualized environments and conducted experiments in a production data center. Our experimental results demonstrate that the Integrated Solution is practical and can reduce energy consumption of servers by 35% and cooling by 15%, without degrading application performance.
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1000 islands Integrated capacity and workload management for the next generation data center
International Conference on Autonomic Computing, 2008Co-Authors: Xiaoyun Zhu, Chris Hyser, Daniel Gmach, Sharad Singhal, Zhikui Wang, Don Young, Brian J Watson, Jerry Rolia, Bret Fort Collins Mckee, Robert C GardnerAbstract:Recent advances in hardware and software virtualization offer unprecedented management capabilities for the mapping of virtual resources to physical resources. It is highly desirable to further create a "service hosting abstraction" that allows application owners to focus on service level objectives (SLOs) for their applications. This calls for a resource management Solution that achieves the SLOs for many applications in response to changing data center conditions and hides the complexity from both application owners and data center operators. In this paper, we describe an automated capacity and workload management system that integrates multiple resource controllers at three different scopes and time scales. Simulation and experimental results confirm that such an Integrated Solution ensures efficient and effective use of data center resources while reducing service level violations for high priority applications.
Rui Sun - One of the best experts on this subject based on the ideXlab platform.
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Integrated Solution for anomalous driving detection based on beidou gps imu measurements
Transportation Research Part C-emerging Technologies, 2016Co-Authors: Rui Sun, Washington Y Ochieng, Ke Han, Yanjun WangAbstract:Abstract There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, centimeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new Integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable Solution for performing these tasks.
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an Integrated Solution for lane level irregular driving detection on highways
Transportation Research Part C-emerging Technologies, 2015Co-Authors: Rui Sun, Washington Y Ochieng, Shaojun FengAbstract:Global Navigation Satellite Systems (GNSS) has been widely used in the provision of Intelligent Transportation System (ITS) services. Current meter level system availability can fulfill the road level applications, such as route guide, fleet management and traffic control. However, meter level of system performance is not sufficient for the advanced safety applications. These lane level safety applications requires centimeter/decimeter positioning accuracy, with high integrity, continuity and availability include lane control, collision avoidance and intelligent speed assistance, etc. Detecting lane level irregular driving behavior is the basic requirement for these safety related ITS applications. The two major issues involved in the lane level irregular driving identification are accessing to high accuracy positioning and vehicle dynamic parameters and extraction of erratic driving behaviour from this and other related information. This paper proposes an Integrated Solution for the lane level irregular driving detection. Access to high accuracy positioning is enabled by GNSS and Inertial Navigation System (INS) integration using filtering with precise vehicle motion models and lane information. The detection of different types of irregular driving behaviour is based on the application of a Fuzzy Inference System (FIS). The evaluation of the designed Integrated systems in the field test shows that 0.5 m accuracy positioning source is required for lane level irregular driving detection algorithm and the designed system can detect irregular driving styles.
Kamel Bouallaga - One of the best experts on this subject based on the ideXlab platform.
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Fully Integrated FPGA-based controller for synchronous motor drive
IEEE Transactions on Industrial Electronics, 2009Co-Authors: Lahoucine Idkhajine, Antonio Prata, Mohamed Wissem Naouar, Eric Monmasson, Kamel BouallagaAbstract:The aim of this paper is to present a fully Integrated Solution for synchronous motor control. The implemented controller is based on Actel Fusion field-programmable gate array (FPGA). The objective of this paper is to evaluate the ability of the proposed fully Integrated Solution to ensure all the required performances in such applications, particularly in terms of control quality and time/area performances. To this purpose, a current control algorithm of a permanent-magnet synchronous machine has been implemented. This machine is associated with a resolver position sensor. In addition to the current control closed loop, all the necessary motor control tasks are implemented in the same device. The analog-to-digital conversion is ensured by the Integrated analog-to-digital converter (ADC), avoiding the use of external converters. The resolver processing unit, which computes the rotor position and speed from the resolver signals, is implemented in the FPGA matrix, avoiding the use of external resolver-to-digital converter (RDC). The sine patterns used for the Park transformation are stored in the Integrated flash memory blocks.
