Ito and Stratonovich integrals for delta-correlated processes

In this paper the generalization of the Itd and Stratonovich integrals for the case of non-linear systems excited by parametric delta-correlated processes is presented. This generalization gives a new light on the corrective coefficients in the stochastic differential equations driven by parametric delta-correlated processes. The full significance of these corrective terms is evidenced by means of some examples.     

Quantitative phase contrast imaging of arborescent graft polystyrene by off-axis transmission electron holography

Imaging nanoscale polymer objects in the Transmission Electron Microscope is difficult, because small polymeric objects interact only weakly with intermediate-energy electrons. Heavy element staining can induce significant amplitude contrast, but stains can introduce artifacts that complicate the structure determination at nanometer length scales. This paper explores transmission electron holography for phase contrast imaging of unstained arborescent graft polystyrene nanoparticles. Holography is able to recover significant phase contrast from these particles despite the fact that there is negligible amplitude contrast. Comparative imaging experiments show that off-axis holography provides substantially higher contrast than that generated by the traditional method of transferring phase information to amplitude information via defocus. This effect is a consequence of different lens contrast-transfer behavior in each of these two imaging approaches. Under kinematical conditions when the appropriate mean inner potential is known, the specimen's projected thickness can be directly mapped from the holographic phase image to give a measure of the specimen's three-dimensional shape. Such quantitative imaging shows that individual arborescent graft polystyrene nanoparticles, which are spherical in a good solvent, adopt a flattened shape when deposited on a carbon substrate and allowed to dry.     

Improvement of Data Rate Performance of Wireless Local Area Networks through the Use of Orthogonal Code Division Multiplexing (OCDM), Multipath Diversity,and Parallel Concatenated Channel Encoding

The widespread use of Wireless Local Area Networks (WLAN) and the desire for such products from different vendors to operate together has generated a movement towards standardization. Over the last few years, several organizations worldwide have researched and developed WLAN standards like IEEE 802.11/15, HIPERLAN, multimedia mobile access communication (MMAC), etc., to name a few. One of the important considerations in designing and marketing WLAN products is the data rate supported by them. This paper deals with the development of a modification of the Direct Sequence (DS) physical layer standard in IEEE 802.11b to allow reliable higher data rates beyond the 1–2 Mb/s supported by the standard. More precisely, this paper proposes the usage of Orthogonal Code Division Multiplexing (OCDM), a form of Code Division Multiple Access (CDMA), diversity via a rake receiver, and parallel concatenated channel encoding, in order to improve the data rate performance in a multipath Rayleigh fading environment. The proposed transceiver design is described in detail and its performance is assessed via digital computer simulation of the corresponding mathematical model.     

Normal people working in normal organizations with normal equipment: System safety and cognition in a mid-air collision

A fundamental challenge in improving the safety of complex systems is to understand how accidents emerge in normal working situations, with equipment functioning normally in normally structured organizations. We present a field study of the en route mid-air collision between a commercial carrier and an executive jet, in the clear afternoon Amazon sky in which 154 people lost their lives, that illustrates one response to this challenge. Our focus was on how and why the several safety barriers of a well structured air traffic system melted down enabling the occurrence of this tragedy, without any catastrophic component failure, and in a situation where everything was functioning normally. We identify strong consistencies and feedbacks regarding factors of system day-to-day functioning that made monitoring and awareness difficult, and the cognitive strategies that operators have developed to deal with overall system behavior. These findings emphasize the active problem-solving behavior needed in air traffic control work, and highlight how the day-to-day functioning of the system can jeopardize such behavior. An immediate consequence is that safety managers and engineers should review their traditional safety approach and accident models based on equipment failure probability, linear combinations of failures, rules and procedures, and human errors, to deal with complex patterns of coincidence possibilities, unexpected links, resonance among system functions and activities, and system cognition.     

Editorial

Ohne Zusammenfassung     

Mobeyes: smart mobs for urban monitoring with a vehicular sensor network

Vehicular sensor networks are emerging as a new network paradigm of primary relevance, especially for proactively gathering monitoring information in urban environments. Vehicles typically have no strict constraints on processing power and storage capabilities. They can sense events (e.g., imaging from streets), process sensed data (e.g., recognizing license plates), and route messages to other vehicles (e.g., diffusing relevant notification to drivers or police agents). In this novel and challenging mobile environment, sensors can generate a sheer amount of data, and traditional sensor network approaches for data reporting become unfeasible. This article proposes MobEyes, an efficient lightweight support for proactive urban monitoring based on the primary idea of exploiting vehicle mobility to opportunistically diffuse summaries about sensed data. The reported experimental/analytic results show that MobEyes can harvest summaries and build a low-cost distributed index with reasonable completeness, good scalability, and limited overhead     

Learning Nonoverlapping Perceptron Networks from Examples and Membership Queries

We investigate, within the PAC learning model, the problem of learning nonoverlapping perceptron networks (also known as read-once formulas over a weighted threshold basis). These are loop-free neural nets in which each node has only one outgoing weight. We give a polynomial time algorithm that PAC learns any nonoverlapping perceptron network using examples and membership queries. The algorithm is able to identify both the architecture and the weight values necessary to represent the function to be learned. Our results shed some light on the effect of the overlap on the complexity of learning in neural networks.     

A multi-failure additive dependability model for transit system effectiveness analysis

Dependability has been recognized in the transportation reliability literature as an effective measure of transit system service quality. Dependability models link system dependability with reliability and maintainability characteristics of subsystems, incorporating special operating characteristics and recovery policy from failure of each particular transit system. In this paper a new transit system dependability model is proposed, which considers the possibility that a passenger may be delayed by the occurrence of more than one failure in a trip. The mathematical difficulties associated with the algebra of random variables are overcome by using the Monte Carlo method. The results of the proposed model are compared with those relative to different modelling approaches in the literature, by applying the model to a common test scenario.