The purpose of this study was to describe the 3-D nano-scaled surface texture of the Nickel–Carbon(Ni–C) nanocomposite thin films composed of Ni nanoparticles with different average sizes embedded in amorphous hydro...
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The purpose of this study was to describe the 3-D nano-scaled surface texture of the Nickel–Carbon(Ni–C) nanocomposite thin films composed of Ni nanoparticles with different average sizes embedded in amorphous hydrogenated carbon using stereometric analysis. The 3-D nanoscaled surface texture was studied by atomic force microscopy(AFM) and stereometric analysis. In a wider context, we also discuss our findings with regard to manufacture of the Nickel-Carbon composite thin films with desired surface characteristics.
This article focuses on modeling of different options of antenna system including and in particular an antenna for the capsule endoscope (transmitter antenna) of the capsule endoscopic complex "Landish". A h...
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This article focuses on modeling of different options of antenna system including and in particular an antenna for the capsule endoscope (transmitter antenna) of the capsule endoscopic complex "Landish". A helical antenna is reviewed for the transmitter, as well as a patch antenna on a curved substrate, and a quarter-wave monopole vibrator and a ceramic antenna. An experiment was conducted in order to compare the gain of the antennas at a fixed position in the space of the transmitting antennas, and the impact of the human body on the features of antennas. Recommendations on the choice of antenna systems in accordance with the simulation results are provided.
A highly efficient design project on embedded system for Internet of Things (IOT) is presented for materials margin management system. As the key instruments of IOT, the acquisition and transmission of weight system d...
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ISBN:
(纸本)9789811026638;9789811026621
A highly efficient design project on embedded system for Internet of Things (IOT) is presented for materials margin management system. As the key instruments of IOT, the acquisition and transmission of weight system data is based on embedded STC15W201S. RS485 bus and Ethernet are used to link microcontroller and PC which make a complete materials margin for real-time dynamic management system. Communication between host computer and instruments and software of host computer are provided to implement of weighting system. As the key technologies, communication between PC and Ethernet, weighting calibration and data filtering are discussed. Test results show that this embedded system can satisfy the design purpose to materials management for Internet of Things.
Wireless capsule endoscopy (WCE) can painlessly capture a large number of images inside the intestine. However, only a small portion of these WCE images contain hemorrhage. It is thus critical to develop automated hem...
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ISBN:
(纸本)9781509060689
Wireless capsule endoscopy (WCE) can painlessly capture a large number of images inside the intestine. However, only a small portion of these WCE images contain hemorrhage. It is thus critical to develop automated hemorrhage detection method to facilitate the diagnosis of intestinal diseases. However, automated hemorrhage detection is complicated by 1) the extreme imbalance between the amount of hemorrhage images and that of normal images; and 2) the variety of the appearance, texture, and luminance inside the intestine. In this paper, we proposed to learn a robust intestinal hemorrhage detection model via Convolutional Neural Networks (CNNs), because of CNNs' extraordinary performance in solving various image understanding tasks. Specially, we explored different CNN architectures and data augmentation methods. Besides, we investigated the correlation between hemorrhage detection accuracy and image quality. Across about 1.3k hemorrhage images and 40k normal images, the learned CNN model achieves an F-measure of 98.87%.
The proceedings contain 6 papers. The topics discussed include: stack size estimation on machine-independent intermediate code for OpenCL kernels;predictive modeling methodology for compiler phase-ordering;flexible re...
ISBN:
(纸本)9781450340526
The proceedings contain 6 papers. The topics discussed include: stack size estimation on machine-independent intermediate code for OpenCL kernels;predictive modeling methodology for compiler phase-ordering;flexible resource allocation and management for application graphs on ReN MPSoC;low communication overhead dynamic mapping of multiple HEVC Video stream decoding on NOCs;deploying and monitoring hadoop MapReduce analytics on single-chip cloud computer;and runtime resource management for embedded and HPC systems.
The path towards Industrie 4.0, requires that factory automation problems cope with the cyber-physical system complexity and its challenges. Some practical experiences and literature in the field testify that the role...
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The path towards Industrie 4.0, requires that factory automation problems cope with the cyber-physical system complexity and its challenges. Some practical experiences and literature in the field testify that the role of the database management systems is becoming central for control and automation technology in the new industrial scenario. This article proposes database-centric technology and architectures that seamlessly integrate networking, artificial intelligence and real-time control issues into a unified model of computing. The proposed methodology is also viable for the development of simulation and rapid prototyping tools for smart and advanced industrial automation. (C) 2016, IFAC (Informational rederation of Automatic Control) Hosting Elsevier Ltd. All rights reserved.
Performing a tsunami or storm surge simulation in real time on low power computation devices is a highly challenging research topic with a big impact on the lives of many people. In order to advance this topic further...
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ISBN:
(数字)9783319312958
ISBN:
(纸本)9783319312958;9783319312941
Performing a tsunami or storm surge simulation in real time on low power computation devices is a highly challenging research topic with a big impact on the lives of many people. In order to advance this topic further a tight collaboration between mathematics and computer science is needed. Mathematical models must be combined with numerical methods which, in turn, directly determine the computational performance and efficiency of the solution. Also, code parallelization is required in order to obtain accurate and fast simulation results. Traditional approaches in high performance computing require a lot of computational power and significant amounts of electrical energy;they are also highly dependent on uninterrupted access to a reliable network and power supply. We present a concept how to develop solutions for suitable low power hardware architectures for tsunami and storm surge simulations based on cooperative software and hardware simulation. The main goal is to enable in situ simulations on potentially battery-powered device on site. Flood warning systems in regions with weak or unreliable power, network and computing infrastructure could largely benefit from our approach as it would significantly decrease the risk of network or power failure during the computation.
Constantly increasing number of information items (i.e. published or digital subjects) set the necessary goal to develop new approaches for filtering and structuring data. This paper describes agent-based approach tha...
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Constantly increasing number of information items (i.e. published or digital subjects) set the necessary goal to develop new approaches for filtering and structuring data. This paper describes agent-based approach that is used in Multi-agent information and analytical system (MIAS) developed at the National Research Nuclear University "MEPhI" in order to form a dynamic profile of the Human Brain Project, which includes general information, identification of funding, interrelation of subprojects and new technologies that are being developed in the course of the project. The MIAS support of object-oriented approach and international standards of linked data contributes to the development of future information systems that will enable forecasting on specific scientific field.
embeddedsystems are subject to timing and power constraints. To support both, software currently must integrate multiple tools, resulting in additional complexity. We address this problem with a unified, portable fra...
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ISBN:
(纸本)9781509030774
embeddedsystems are subject to timing and power constraints. To support both, software currently must integrate multiple tools, resulting in additional complexity. We address this problem with a unified, portable framework called Bard which uses control theory to meet the primary constraint and linear programming to optimize the other. We evaluate Bard on two embedded platforms that exhibit different performance and power/energy characteristics and show that it achieves less than 2% error in meeting power constraints while maintaining nearly 95% of optimal performance. Additionally, Bard supports changing the primary constraint type at runtime while still achieving similar results.
Deep neural network algorithms show very high performance, however increased amounts of arithmetic and memory accesses hinder their adoption to embeddedsystems. This paper explores a programmable neural network proce...
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ISBN:
(纸本)9781509030774
Deep neural network algorithms show very high performance, however increased amounts of arithmetic and memory accesses hinder their adoption to embeddedsystems. This paper explores a programmable neural network processing architecture that can efficiently execute feed-forward, recurrent, and convolutional deep neural networks. The neural network algorithms are transformed to matrix-vector multiplication operations, which are then executed using a very wide SIMD (Single Instruction Multiple Data) functional unit. Especially, the functional and the data-level parallelism are compared for this architecture exploration, and an auxiliary hardware support for data rearrangement is added. The simulation results show that the architecture with a 128-wide SIMD functional unit can execute deep neural network algorithms for voice command, gesture, and handwritten digit recognition in real-time.
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