The use of FPGAs in the design of wireless sensor networks can improve the processing system performance so as to develop sensor nodes with powerful embedded processor. In fact, FPGA has a super-parallel processing ca...
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The use of FPGAs in the design of wireless sensor networks can improve the processing system performance so as to develop sensor nodes with powerful embedded processor. In fact, FPGA has a super-parallel processing capacity in data processing and its use and configuration is flexible. This allows intensive digital signal processing tasks like Fast Fourier Transforms to be implemented on the sensor node and this can even support intelligent applications and new security algorithms. This paper presents a wireless sensor network system that monitors and visualizes periodically the environment temperature. The proposed system consists of a base station node based on an FPGA DE2-70 and five sensor nodes having the architecture of the System-on-Chip CC2430.
Cloth is a flexible thin material with low stretch. Although large stiffness can reduce stretch to some extent, it degrades numerical computing stability. Introducing effective constraints into the system is another c...
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Cloth is a flexible thin material with low stretch. Although large stiffness can reduce stretch to some extent, it degrades numerical computing stability. Introducing effective constraints into the system is another common method to reduce stretch. In this paper, a novel constraint method is deduced and implemented. The bending deformation of cloth is firstly analyzed from micro-mesh view, based on which, constraint method is deduced. Then, constraint is combined with dynamic equation to simulate cloth. Overstretch of cloth is controlled at the same time realistic wrinkles and folds are maintained. Finally, based on this method, some experiments are conducted and the analysis and evaluation are given.
Supervisory control reconfiguration can handle the uncertainties including resource failures and task changes in discrete event systems. It was not addressed to exploit the robustness of closed-loop systems to accommo...
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Cognitive diagnosis models (CDMs) are of growing interest in test development and in the measurement of human performance. The DINA (deterministic input, noisy, and gate) model has been widely used in cognitive diagno...
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Cognitive diagnosis models (CDMs) are of growing interest in test development and in the measurement of human performance. The DINA (deterministic input, noisy, and gate) model has been widely used in cognitive diagnosis tests and in the process of test development. Central to many such models, the well-known Q-matrix [1], which specifies the item-attribute relationships and two noise parameters in DINA model related to item response functions are termed as slip and guessing. Slip parameter indicates a student with mastery of all of the attributes that an item requires fails to answer the item correctly. In contrast, guessing parameter indicates a student lacks the attributes that are required by an item but succeeds to answer the item correctly. In this paper, we developed a new method and presented an alternate recursive algorithm to learn Q-matrix and uncertainty variables slip and guessing based on Boolean Matrix Factorization (BMF) and Maximum Likelihood Estimation (MLE) respectively for DINA model of CDM. In particularly, we spontaneously transferred the deterministic Q-matrix learning problem into BMF problem. Because BMF is an NP-hard problem [2], we proposed an alternate recursive method to find approximate solution by adding one dimension in attribute latent space in each step. On the other hand, we analytically estimated the slip and guessing parameters through the maximum likelihood of uncertainty variables. The optimum process is alternate recursive between latent attribute space and uncertainty variable space. Simulation results show that the MLE Q-matrix learning algorithm has fast convergence to the optimal solution under suitable initial values of Q init and A init . This is extremely important and applicable when the method is extended to big data.
The paper proposes a look-ahead cruise control method considering both energy efficiency and the safety of vehicle motion. Based on the curve radius of the road, a method is proposed for the calculation of the safe co...
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ISBN:
(纸本)9781479947287
The paper proposes a look-ahead cruise control method considering both energy efficiency and the safety of vehicle motion. Based on the curve radius of the road, a method is proposed for the calculation of the safe cornering velocity, which is used in the look-ahead control design process. If the speed limit is in conflict with the calculated safe cornering velocity, the latter is applied in the energy optimization process of the look-ahead control algorithm. Thus, the designed velocity is coherent with the terrain characteristics, the speed limits and the geometry of the road as well, enabling the vehicle to travel safely and energy efficiently along the path. The main novelty of the paper is the consideration of the safe cornering velocity in the look-ahead design, improving energy efficiency and the safety of the vehicle during various maneuvers.
This paper studies the delay robustness of a class of periodically edge-event driven synchronous consensus protocols in time-invariant networks. These protocols have the benefits of improved performance at reduced com...
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This paper studies the delay robustness of a class of periodically edge-event driven synchronous consensus protocols in time-invariant networks. These protocols have the benefits of improved performance at reduced communication and computation costs. Under the assumption that all information links share a common time-varying transmission delay, we give non-conservative estimates of the maximum allowable time-delay and event-detecting period for solving the average consensus problem in terms of the algebraic structure of interaction topologies. Furthermore, rigorous stability analysis shows that the proposed technique is also applicable to the asynchronous consensus with multiple time-delays.
Background: Next Generation Sequencing (NGS) machines extract from a biological sample a large number of short DNA fragments (reads). These reads are then used for several applications, e.g., sequence reconstruction, ...
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This paper considers the problem of synthesizing output-feedback control laws for a class of discrete-time hybrid systems in order for the trajectories of the system to satisfy certain high-level specifications expres...
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ISBN:
(纸本)9781479932757
This paper considers the problem of synthesizing output-feedback control laws for a class of discrete-time hybrid systems in order for the trajectories of the system to satisfy certain high-level specifications expressed in linear temporal logic. By leveraging ideas from robust interpretation of temporal logic formulas and bounded-error estimation, we identify a subclass of systems for which it is possible to reduce the problem to a state-feedback form. In particular, we use locally superstable hybrid observers to resolve the partial information at the continuous level. This allows us to use recent results in temporal logic planning to synthesize the desired controllers based on two-player perfect-information games. The overall control architecture consists of a hybrid observer, a high-level switching protocol and a low-level continuous controller. We demonstrate the proposed framework in a case study on designing control protocols for an aircraft air management system.
Heterogeneous many-cores can deliver high performance or energy efficiency. There are two orthogonal ways to improve performance: 1) scale-out by exploiting thread-level parallelism, and 2) scale-up by enabling core h...
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Heterogeneous many-cores can deliver high performance or energy efficiency. There are two orthogonal ways to improve performance: 1) scale-out by exploiting thread-level parallelism, and 2) scale-up by enabling core heterogeneity. Predicting the performance of such architecture is increasingly challenging. We propose a comprehensive performance model Amphisbaena, or Φ, built from two orthogonal functions α and β. Function α describes the scale-out speedup and function β handles the scale-up speedup. The Φ model can clearly tell not only the overall speedup of a given multithreading and core mapping strategy, but also how to improve the multithreading and core mapping, hence should be a promising performance predictor for future heterogenous many-cores. The results show that Φ model's error rate is within 12%, which is lower than state-of-the-art methods. We demonstrate the application of Φ model by introducing a heuristic scheduling algorithm, which outperforms the baselines by 13% on average.
Ensuring the security of control systems against integrity attacks is a major challenge. Due to the events of Stuxnet, replay attacks in particular have been considered by the research community. Replaying previous me...
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ISBN:
(纸本)9781467360890
Ensuring the security of control systems against integrity attacks is a major challenge. Due to the events of Stuxnet, replay attacks in particular have been considered by the research community. Replaying previous measurements of a system in steady state allows an adversary to generate statistically correct virtual outputs which can bypass traditional detectors. The adversary can then inject destabilizing inputs to cause damage to the plant. The method of injecting secret noisy control inputs, or physical watermarking, has recently been proposed to detect replay attacks. However, the proposed watermarking design methods assume that the adversary does not use his potential access to real time communication channels to create stealthy virtual outputs to send to the defender. In this paper, we formulate an attack model for an adversary who uses knowledge of the system as well as access to a subset of real time control inputs and sensor outputs to construct stealthy virtual outputs. A robust physical watermark and detector to counter such an adversary is proposed.
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