Scale periodicity and its sampling theorem

The scalar transform is a new representation for signals, offering a perspective that is different from the Fourier transform. We introduce the notion of a scalar periodic function. These functions are then represented through the discrete scale series. We also define the notion of a strictly scale-limited signal. Analogous to the Shannon interpolation formula, we show that such signals can be exactly reconstructed from exponentially spaced samples of the signal in the time domain. As an interesting, practical application, we show how properties unique to the scale transform make it very useful in computing depth maps of a scene     

Field experience with momentary fast turbine valving and otherspecial stability controls employed at AEP's Rockport plant

Several special stability controls, including fast turbine valving are in service at AEP's Rockport generating plant to enhance the plant's transient and voltage stability performance. An account of how these supplementary controls evolved over time to meet changing system needs is provided. An overview of field tests, maintenance practices and operating history of the fast turbine valving equipment is presented. Finally, one of the successful Rockport fast valving events is analyzed in detail, with respect to valve stroke characteristics and electrical response of the Rockport units. This paper emphasizes the lessons learned from the operating experience, which include a need to constantly monitor the adequacy of the special stability control equipment, through regular maintenance and analysis of actual operations     

Hodgkin's disease: impact on childbearing

Although Hodgkin's disease is considered one of the "curable" cancers, the high cure rates associated with this disease are not accomplished without risk of potentially severe, immediate, and late side effects. Because the predominant histologic subtype of Hodgkin's disease found in the United States generally affects the 15- to 25-year-old age group, the disease, its treatment, and the side effects of treatment will affect many women of childbearing age. The treatment and its effects on the patient and offspring, including posttreatment fertility, are key issues for perinatal nurses.     

What is "special" about face perception?

There is growing evidence that face recognition is "special" but less certainty concerning the way in which it is special. The authors review and compare previous proposals and their own more recent hypothesis, that faces are recognized "holistically" (i.e., using relatively less part decomposition than other types of objects). This hypothesis, which can account for a variety of data from experiments on face memory, was tested with 4 new experiments on face perception. A selective attention paradigm and a masking paradigm were used to compare the perception of faces with the perception of inverted faces, words, and houses. Evidence was found of relatively less part-based shape representation for faces. The literatures on machine vision and single unit recording in monkey temporal cortex are also reviewed for converging evidence on face representation. The neuropsychological literature is reviewed for-evidence on the question of whether face representation differs in degree or kind from the representation of other types of objects.     

PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation

Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a finite collection of data, are the most popular approach in small-area spatial statistical modelling. In this context, they are used to encode correlation structures over space and can generalize well in interpolation tasks. Despite their flexibility, off-the-shelf GPs present serious computational challenges which limit their scalability and practical usefulness in applied settings. Here, we propose a novel, deep generative modelling approach to tackle this challenge, termed PriorVAE: for a particular spatial setting, we approximate a class of GP priors through prior sampling and subsequent fitting of a variational autoencoder (VAE). Given a trained VAE, the resultant decoder allows spatial inference to become incredibly efficient due to the low dimensional, independently distributed latent Gaussian space representation of the VAE. Once trained, inference using the VAE decoder replaces the GP within a Bayesian sampling framework. This approach provides tractable and easy-to-implement means of approximately encoding spatial priors and facilitates efficient statistical inference. We demonstrate the utility of our VAE two-stage approach on Bayesian, small-area estimation tasks.     

ADYTIA: Adaptive and Dynamic TCP Interface Architecture for heterogeneous networks

Due to the widespread popularity and usage of Internet of things (IoT)‐enabled devices, there is an exponential increase in the data traffic generated from these IoT devices. Most of these devices communicate with each other using heterogeneous links having constraints such as latency, throughput, and interference from concurrent transmissions. This results in an extra burden on the underlying communication infrastructure to manage the traffic within these constraints between source and destination. However, most of the existing applications use different Transmission Control Protocol (TCP) variants for traffic management between these devices and are dependent on the stage of the sender, irrespective of the application types and link characteristics. Each operating system (OS) has different TCP variant for all applications, irrespective of path characteristics. Hence, a single TCP variant cannot select the best suitable link, which results in degradation in throughput compared to the existing default. Moreover, it cannot use the full capacity of the available link for different applications and network links, especially in heterogeneous network such as IoT. To cope up with these challenges, in this paper, we propose an Adaptive and Dynamic TCP Interface Architecture (ADYTIA). ADYTIA allows the usage of different TCP variants based on application and link characteristics, irrespective of the physical links of the entire path. It allows the usage of different TCP variants based on their design principle across heterogeneous technologies, platforms, and applications. ADYTIA is implemented on NS‐2 and Linux kernel for real testbed experiments. Its ability to select the best suitable TCP variant results in 20% to 80% improvement in throughput compared with the existing default and single TCP variant on Linux and Windows.     

Spatial and Temporal Resolution of Conjugate Conduction-Convection Thermal Resistance

A transient, 3-D solution to the heat conduction equation with a small square heat source on an adiabatic surface and Newtonian convection on the opposite side was obtained using Green's functions. The geometry conservatively models conduction spreading resistance encountered by small, concentrated heat sources such as light-emitting diodes and integrated circuits in general, mounted to larger substrates such as the base of a heat sink experiencing Newtonian convection. The solution is presented for a range of nondimensional parameters. Superposition techniques can also be used to extend the applicability of the current solution to the temperature prediction of arbitrary heat flux patterns in certain cases. This technique only holds for applications where the heat transfer coefficient is not a function of temperature, such as thermal management strategies designed to rely on forced convection with air.     

Assimilation of altimeter significant wave height into a third-generation global spectral wave model

Data from three different altimeters (Topex/Poseidon, Jason-1, and European Remote Sensing Satellite 2) have been assimilated in a third-generation global spectral wave model forced by winds observed by scatterometer onboard QuikSCAT. Two different approaches of assimilation have been discussed. In the first approach, a simple scaling has been used to generate wave spectrum from altimeter-derived significant wave heights for assimilation in the model. In the second approach, the influence of altimeter observation has been spread to nearby grid points. Assimilation has been carried out every 6 h for five days. After the expiry of the assimilation phase, the model has been run in pure hindcast mode. Assimilation experiments have been carried out for the months of September and December 2002. Impact of assimilation has been found to be quite high in the Indian Ocean. It has been also found that the model is able to retain the memory of assimilation for a period of two and a half days as far as global ocean is concerned. This memory is more for the Indian Ocean. The wave spectrum generated by the model in the hindcast mode has been validated against the buoy-observed wave spectrum in the high sea conditions. The more significant impact has been seen in the case of altimeter track in the vicinity of the buoy.     

Self-esteem in alcoholics and nonalcoholics

Alcoholics scored lower on a test of self-esteem than did nonalcoholics, Alcoholics with lower self-esteem were found to be more willing to seek treatment than those with higher self-esteem.