An MPEG‐4 Compliant Interactive Multimedia Streaming Platform Using Overlay Networks

This paper presents a multimedia streaming platform for efficiently transmitting MPEG‐4 content over IP networks. The platform includes an MPEG‐4 compliant streaming server and client, supporting object‐based representation of multimedia scenes, interactivity, and advanced encoding profiles defined by the ISO standard. For scalability purposes, we employ an application‐layer multicast scheme for media transmission using overlay networks. The overlay network, governed by the central entity of the network distribution manager, is dynamically deployed according to a set of pre‐defined criteria. The overlay network supports both broadcast delivery and video‐on‐demand content. The multimedia streaming platform is standards‐compliant and utilizes widespread multimedia protocols such as MPEG‐4, real‐time transport protocol, real‐time transport control protocol, and real‐time streaming protocol. The design of the overlay network was architected with the goal of transparency to both the streaming server and the client. As a result, many commercial implementations that use industry‐standard protocols can be plugged into the architecture relatively painlessly and can enjoy the benefits of the platform.     

Controllers with diagnostic capabilities. A neural network implementation

Designing controllers with diagnostic capabilities is important as in a feedback control system, detection and isolation of failures is generally affected by the particular control law used. Therefore, a common approach to control and failure diagnosis problems has significant merit. Controllers capable of performing failure diagnosis have additional diagnostic outputs to detect and isolate sensor and actuator faults. A linear such controller is usually called a four-parameter controller. Neural networks have proved to be a very powerful tool in the control systems area, where they have been used in the modelling and control of dynamical systems. In this paper, a neural network model of a controller with diagnostic capabilities (CDC) is presented for the first time. This nonlinear neural controller is trained to operate as a traditional controller, while at the same time it provides reproduction of the failure occurring either at the actuator or the sensor. The cases of actuator and sensor failure are studied independently. The validity of the results is verified by extensive simulations.A version of this paper under the title The Four-Parameter Controller. A Neural Network Implementation was presented at the IEEE Mediterranean Symposium on New Directions in Control Theory and Applications, Chania, Crete, Greece, June 21–23, 1993.     

Two heads better than one: pattern discovery in time-evolving multi-aspect data

Data stream values are often associated with multiple aspects. For example each value observed at a given time-stamp from environmental sensors may have an associated type (e.g., temperature, humidity, etc.) as well as location. Time-stamp, type and location are the three aspects, which can be modeled using a tensor (high-order array). However, the time aspect is special, with a natural ordering, and with successive time-ticks having usually correlated values. Standard multiway analysis ignores this structure. To capture it, we propose 2 Heads Tensor Analysis (2-heads), which provides a qualitatively different treatment on time. Unlike most existing approaches that use a PCA-like summarization scheme for all aspects, 2-heads treats the time aspect carefully. 2-heads combines the power of classic multilinear analysis with wavelets, leading to a powerful mining tool. Furthermore, 2-heads has several other advantages as well: (a) it can be computed incrementally in a streaming fashion, (b) it has a provable error guarantee and, (c) it achieves significant compression ratio against competitors. Finally, we show experiments on real datasets, and we illustrate how 2-heads reveals interesting trends in the data. This is an extended abstract of an article published in the Data Mining and Knowledge Discovery journal.     

Lie point symmetries and conservation laws in microstretch and micromorphic elasticity

In this paper, following Noether’s theorem we investigate Lie point symmetries of linear theories of microstretch elasticity and micromorphic elasticity. We restrict our consideration to isotropic, compatible and homogeneous materials. Conservation and balance laws are derived, thereby extending results from micropolar elasticity.     

Assessment of a modification to the Brinell method for determining solid wood hardness

Purpose of this study was to assess a modification to the hardness determination method in order to mitigate the effect of visual measurements on the consistency of Brinell method and accuracy of the results. The amendment has been previously proposed by other researchers and refers to the automated determination of indentation diameter and relies on the ability of modern testing machines to accurately measure indentation depth, through which the calculation of indentation diameter is possible. From the results of this study it was shown that the hardness values acquired by the proposed modification presented statistically significant difference compared to those acquired using the visual method described in EN1534 (Wood and parquet flooring—determination of resistance to indentation (Brinell)—test method, 2000). Moreover, compared to the standard methodology, the application of the proposed amendment led to hardness values which are better correlated to density as well as Janka hardness for the six different solid wood species tested. Furthermore, the proposed modification resulted to hardness values which seem to be less affected by the presence of varnish coatings.     

A methodology for the design of optimal traffic shapers incommunication networks

The authors consider the problem of optimally regulating the source traffic in a communication network to simultaneously satisfy a finite number of affine burstiness constraints. They prove that an optimal solution is a series connection of correspondingly dimensioned “leaky buckets.” They propose a simple “fork-join” implementation of the optimal solution and study extensions to the problem of optimally shaping the traffic flow to meet a burstiness constraint specified by a concave increasing function. A consequence of their optimality results is that permutations of leaky buckets in a series connection are input-output equivalent     

Theoretical and methodological implications of designing and implementing multiuser location-based games

Multiuser location-aware applications present a new form of mediated communication that takes place within a digital as well as a physical spatial context. The inherently hybrid character of locative media use necessitates that the designers of such applications take into account the way communication and social interaction is influenced by contextual elements. In this paper, an investigation into the communicational and social practices of users who participate in a location-based game is presented, with an emphasis on group formation and dynamics, interpersonal communication, and experienced sense of immersion. This investigation employs a methodological approach that is reliant on both qualitative and quantitative data analysis. A series of this user experience study’s results are presented and discussed.     

Pure red cell aplasia associated with true thymic hyperplasia

We reported unique magnetic resonance imaging (MRI) findings of a 57-year-old Japanese man who was diagnosed as Vogt-Koyanagi-Harada disease. This patient presented with complaints of a transient severe headache followed by a bilateral loss of visual acuity and truncal ataxia. Magnetic resonance imaging revealed abnormal contrast enhancement of both the uveas and the cerebellar vermis corresponding to his neurological abnormalities. The distribution and the nature of the resolution of this unusual pattern of contrast enhancement suggested that these MRI findings might illustrate transient destruction of the blood brain barrier or vascular extravasations. Such events might be representative of pathophysiology involving the central nervous system that occurred in patients with Vogt-Koyanagi-Harada disease.     

An efficient parallel algorithm for motion estimation in very low bit‐rate video coding systems

Motion estimation is widely used in video coding schemes in order to reduce the inherent temporal redundancy among the frames of a video stream. In particular, low and very low bit rate video coding schemes need sophisticated motion models which usually require a large number of arithmetic operations. In this paper we present a parallel algorithm for the most practical of these models. Specifically we implement the affine motion model on a hypercube‐based multiprocessor. This model covers the most usual kinds of motion and requires only a modest number of arithmetic operations. Also, the hypercube network can efficiently handle the non‐regular data flow resulting from the parallel implementation of this model. In addition, we assume that our multiprocessor is fine grained, in contrast to most programmable architectures used in video coding, where processors usually have large local memory. Apart from its practicality, the constraint of limited local memory makes the algorithm design more challenging and thus more theoretically interesting. Finally, with regard to other proposals in the literature, our scheme is more general: whereas our scheme covers all kinds of motion supported by the affine motion model, the rest of the proposals deal only with a subset of these kinds. Copyright © 2000 John Wiley & Sons, Ltd.