Material Identification of Loose Particles in Sealed Electronic Devices Using PCA and SVM

The existence of loose particles left inside the sealed electronic devices is one of the main factors affecting the reliability of the whole system. It is important to identify the particle material for analyzing their source. The conventional material identification algorithms mainly rely on time, frequency and wavelet domain features. However, these features are usually overlapped and redundant, resulting in unsatisfactory material identification accuracy. The main objective of this paper is to improve the accuracy of material identification. First, the principal component analysis (PCA) is employed to reselect the nine features extracted from time and frequency domains, leading to six less correlated principal components. And then the reselected principal components are used for material identification using a support vector machine (SVM). Finally, the experimental results show that this new method can effectively distinguish the type of materials including wire, aluminum and tin particles.

Long-Term Economic Model for Allocation of FACTS Devices in Restructured Power System Integrated Wind Generation

This study proposes an approach to optimally allocate multiple types of flexible AC transmission system (FACTS) devices in market-based power systems with wind generation. The main objective is to maximise profit by minimising device investment cost, and the system's operating cost considering both normal conditions and possible contingencies. The proposed method accurately evaluates the long-term costs and benefits gained by FACTS devices (FDs) installation to solve a large-scale optimisation problem. The objective implies maximising social welfare as well as minimising compensations paid for generation re-scheduling and load shedding. Many technical operation constraints and uncertainties are included in problem formulation. The overall problem is solved using both particle swarm optimisations for attaining optimal FDs allocation as main problem and optimal power flow as sub-optimisation problem. The effectiveness of the proposed approach is demonstrated on modified IEEE 14-bus test system and IEEE 118-bus test system.

Validity of model devices used to assess canine temperament in behavioral tests

Temperament tests are widely accepted as instruments for profiling behavioral variability in dogs, and they are applied in numerous areas of investigation (e.g. suitability for adoption or for breeding). During testing, to elicit a dog's reaction toward novel stimuli and predict its behavior in everyday life, model devices such as a child-like doll, or a fake dog, are often employed. However, the reliability of these devices to accurately stimulate dogs' reactions to children or dogs, is unknown and perhaps overestimated. This may be a particular concern in the case of aggressive behavior toward humans, a significant public health issue. The aim of this study was to: (1) evaluate the correlation between dogs' reactions to these devices, and owners' reports of their dog's aggression history (using the C-BARQ ??); (2) compare reactions toward the devices of dogs with and without histories of aggression. Subjects were selected among those visiting for behavioral consultation at the Veterinary Hospital of the University of Pennsylvania, and previously categorized as aggressive toward unfamiliar children, conspecifics, or as non-aggressive dogs (control). The test consisted of different components: an unfamiliar female tester approaching the dog; the presentation of a child-like doll, an ambiguous object, and a fake plastic dog. All tests were videotaped and durations of behaviors were later analyzed on the basis of a specified ethogram. Dogs' reactions were compared to C-BARQ scores, and interesting correlations emerged for 'dog-directed aggression/fear' (R = 0.48, P = 0.004), and 'stranger-directed aggression' (R = 0.58, P <0.001) factors. Dogs differed in their reactions toward the devices: the child-like doll and the fake dog elicited more social behaviors than the ambiguous object used as a control stimulus. Issues concerning the reliability of these tools to assess canine temperament are discussed. ?? 2012 Elsevier B.V. All rights reserved.

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.

Assessing the Potential for Saving Energy by Impersonating Idle Networked Devices

The idea of proxying network connectivity has been proposed as an efficient mechanism to maintain network presence on behalf of idle devices, so that they can “sleep”. The concept has been around for many years; alternative architectural solutions have been proposed to implement it, which lead to different considerations about capability, effectiveness and energy efficiency. However, there is neither a clear understanding of the potential for energy saving nor a detailed performance comparison among the different proxy architectures. In this paper, we estimate the potential energy saving achievable by different architectural solutions for proxying network connectivity. Our work considers the trade-off between the saving achievable by putting idle devices to sleep and the additional power consumption to run the proxy. Our analysis encompasses a broad range of alternatives, taking into consideration both implementations already available in the market and prototypes built for research purposes. We remark that the main value of our work is the estimation under realistic conditions, taking into consideration power measurements, usage profiles and proxying capabilities.