Entropy-based feature extraction for electromagnetic discharges classification in high-voltage power generation

This work exploits four entropy measures known as Sample, Permutation, Weighted Permutation, and Dispersion Entropy to extract relevant information from Electromagnetic Interference (EMI) discharge signals that are useful in fault diagnosis of High-Voltage (HV) equipment. Multi-class classification algorithms are used to classify or distinguish between various discharge sources such as Partial Discharges (PD), Exciter, Arcing, micro Sparking and Random Noise. The signals were measured and recorded on different sites followed by EMI expert’s data analysis in order to identify and label the discharge source type contained within the signal. The classification was performed both within each site and across all sites. The system performs well for both cases with extremely high classification accuracy within site. This work demonstrates the ability to extract relevant entropy-based features from EMI discharge sources from time-resolved signals requiring minimal computation making the system ideal for a potential application to online condition monitoring based on EMI

Multimodal Content Analysis for Effective Advertisements on YouTube

The rapid advances in e-commerce and Web 2.0 technologies have greatly increased the impact of commercial advertisements on the general public. As a key enabling technology, a multitude of recommender systems exists which analyzes user features and browsing patterns to recommend appealing advertisements to users. In this work, we seek to study the characteristics or attributes that characterize an effective advertisement and recommend a useful set of features to aid the designing and production processes of commercial advertisements. We analyze the temporal patterns from multimedia content of advertisement videos including auditory, visual and textual components, and study their individual roles and synergies in the success of an advertisement. The objective of this work is then to measure the effectiveness of an advertisement, and to recommend a useful set of features to advertisement designers to make it more successful and approachable to users. Our proposed framework employs the signal processing technique of cross modality feature learning where data streams from different components are employed to train separate neural network models and are then fused together to learn a shared representation. Subsequently, a neural network model trained on this joint feature embedding representation is utilized as a classifier to predict advertisement effectiveness. We validate our approach using subjective ratings from a dedicated user study, the sentiment strength of online viewer comments, and a viewer opinion metric of the ratio of the Likes and Views received by each advertisement from an online platform.Comment: 11 pages, 5 figures, ICDM 201

Precision laser range finder system design for Advanced Technology Laboratory applications

Preliminary system design of a pulsed precision ruby laser rangefinder system is presented which has a potential range resolution of 0.4 cm when atmospheric effects are negligible. The system being proposed for flight testing on the advanced technology laboratory (ATL) consists of a modelocked ruby laser transmitter, course and vernier rangefinder receivers, optical beacon retroreflector tracking system, and a network of ATL tracking retroreflectors. Performance calculations indicate that spacecraft to ground ranging accuracies of 1 to 2 cm are possible

Wide area detection system: Conceptual design study

An integrated sensor for traffic surveillance on mainline sections of urban freeways is described. Applicable imaging and processor technology is surveyed and the functional requirements for the sensors and the conceptual design of the breadboard sensors are given. Parameters measured by the sensors include lane density, speed, and volume. The freeway image is also used for incident diagnosis

Mitigation of Radiation-Induced Bone Loss by Dried Plum

In recent years, much attention has been given to the effects of radiation on bone deterioration. Past research has demonstrated that radiation acts to alter the balance between osteoblasts and osteoclasts, promoting a net osteoclastic activity in the affected bone tissue, but specific molecular mechanisms remain unknown. Gene expression of many osteoclast markers is upregulated early in response to radiation, leading to bone resorption. This problem is especially prominent in space, as astronauts are regularly exposed to full body ionizing radiation that, over extended periods of time, may lead to significant bone loss. Research suggests that radiation leads to an inflammatory response in bone tissue, which leads to oxidative stress damage and increased osteoclast activity. Numerous natural compounds have been studied in vitro and have been observed to reduce the gene expression of bone resorption genes and their protein derivatives. We have attempted to take a closer look at the mechanisms by which radiation impairs bone health by examining the microarchitecture of mouse bones and the gene expression of osteoclast, osteoblast, and osteocyte markers. Much research has been devoted to studying osteoclastic activity because this is believed to play the most influential role in bone loss. Our gene expression findings show that radiation increases bone resorption and oxidative stress. Oxidative damage analysis indicated a higher level of malondialdehyde (MDA) in the irradiated, control diet samples compared to non-irradiated mice on the control diet and suggested that dried plum may protect bones by a systemic reduction in oxidative damage. Physical characterization results that we obtained from microCT demonstrate that a dried plum diet increased the bone mass compared to the control diet, but failed to show an effect from radiation on bone. The microCT data collected is not sufficient to confirm that dried plum has a radio-protective effect in vertebrae. Although at this stage, we have limited data to fully understand the mechanisms by which dried plum protects bone, we show that dried plum can increase bone mass in vertebrae and systemically reduces MDA levels in circulation. Our research increases the current medical and biological understanding of bone physiology in response to radiation and proposed dietary countermeasures, and is of relevance to astronauts in extended space missions, cancer patients, and patients with osteoporosis

An Overview of Multimodal Techniques for the Characterization of Sport Programmes

The problem of content characterization of sports videos is of great interest because sports video appeals to large audiences and its efficient distribution over various networks should contribute to widespread usage of multimedia services. In this paper we analyze several techniques proposed in literature for content characterization of sports videos. We focus this analysis on the typology of the signal (audio, video, text captions, ...) from which the low-level features are extracted. First we consider the techniques based on visual information, then the methods based on audio information, and finally the algorithms based on audio-visual cues, used in a multi-modal fashion. This analysis shows that each type of signal carries some peculiar information, and the multi-modal approach can fully exploit the multimedia information associated to the sports video. Moreover, we observe that the characterization is performed either considering what happens in a specific time segment, observing therefore the features in a "static" way, or trying to capture their "dynamic" evolution in time. The effectiveness of each approach depends mainly on the kind of sports it relates to, and the type of highlights we are focusing on