Building self-optimized communication systems based on applicative cross-layer information

This article proposes the Implicit Packet Meta Header(IPMH) as a standard method to compute and represent common QoS properties of the Application Data Units (ADU) of multimedia streams using legacy and proprietary streams’ headers (e.g. Real-time Transport Protocol headers). The use of IPMH by mechanisms located at different layers of the communication architecture will allow implementing fine per-packet selfoptimization of communication services regarding the actual application requirements. A case study showing how IPMH is used by error control mechanisms in the context of wireless networks is presented in order to demonstrate the feasibility and advantages of this approach

Information-theoretic analysis of content based identification for correlated data

A number of different multimedia fingerprinting algorithms and identification techniques were proposed and analyzed recently. This paper presents a content identification setup for a class of multimedia data that can be modeled by the Gauss-Markov process. We advocate a constrained order statistics decoding scheme based on digital fingerprints extracted from correlated data to identify contents. Finally, we investigate the fundamental limits of the proposed setup by deriving bounds on the miss and false acceptance probabilities

A Tutorial on Clique Problems in Communications and Signal Processing

Since its first use by Euler on the problem of the seven bridges of K\"onigsberg, graph theory has shown excellent abilities in solving and unveiling the properties of multiple discrete optimization problems. The study of the structure of some integer programs reveals equivalence with graph theory problems making a large body of the literature readily available for solving and characterizing the complexity of these problems. This tutorial presents a framework for utilizing a particular graph theory problem, known as the clique problem, for solving communications and signal processing problems. In particular, the paper aims to illustrate the structural properties of integer programs that can be formulated as clique problems through multiple examples in communications and signal processing. To that end, the first part of the tutorial provides various optimal and heuristic solutions for the maximum clique, maximum weight clique, and $k$-clique problems. The tutorial, further, illustrates the use of the clique formulation through numerous contemporary examples in communications and signal processing, mainly in maximum access for non-orthogonal multiple access networks, throughput maximization using index and instantly decodable network coding, collision-free radio frequency identification networks, and resource allocation in cloud-radio access networks. Finally, the tutorial sheds light on the recent advances of such applications, and provides technical insights on ways of dealing with mixed discrete-continuous optimization problems

Lip Reading Sentences in the Wild

The goal of this work is to recognise phrases and sentences being spoken by a talking face, with or without the audio. Unlike previous works that have focussed on recognising a limited number of words or phrases, we tackle lip reading as an open-world problem - unconstrained natural language sentences, and in the wild videos. Our key contributions are: (1) a 'Watch, Listen, Attend and Spell' (WLAS) network that learns to transcribe videos of mouth motion to characters; (2) a curriculum learning strategy to accelerate training and to reduce overfitting; (3) a 'Lip Reading Sentences' (LRS) dataset for visual speech recognition, consisting of over 100,000 natural sentences from British television. The WLAS model trained on the LRS dataset surpasses the performance of all previous work on standard lip reading benchmark datasets, often by a significant margin. This lip reading performance beats a professional lip reader on videos from BBC television, and we also demonstrate that visual information helps to improve speech recognition performance even when the audio is available

Putting the Horse Before the Cart: Utilizing What Assessment Data Reveal About Struggling Young Adolescent Readers to Inform Policy and Instruction

In recent years, increased attention has been paid to accelerating the development of struggling young adolescents’ reading skills (Franzak, 2006). It has been widely acknowledged that these students require intensive instruction in reading in order to meet changing societal demands (Allington, 2002; Afflerbach, 2004; Alvermann, 2001; Biancarosa & Snow, 2004). Score reporting from the National Assessment of Educational Progress (NAEP) may demonstrate a dichotomy amongst our young adolescent readers, but the scores do not tell us about the specific needs of individual students. In other words, these levels essentially create two groups: those who can read and those who cannot. Further, instructional decisions are being made based on the limited proficiency scores of state mandated standardized assessments. This method of reporting scores creates a notion of homogeneity amongst the reading skills of young adolescents. The purpose of this multivariate correlational study was to determine the patterns of reading abilities amongst struggling young adolescent readers in an attempt to demonstrate the heterogeneous nature of these students and the variability of reading skills they bring to middle school classrooms (grades 6-8), in an effort to influence both policy and instruction at this level. Data were collected during the 2005-2006 academic year. Each student participant (n=94) was administered five assessments that measured alphabetics (phonemic awareness and phonics), fluency, vocabulary, and comprehension, which were representative of both the highly and less constrained skills (Paris, 2005) presented as essential components of reading instruction by the National Reading Panel (NRP, 2000). Independent samples t-tests were used to compare the assessment means of several subgroups, students who qualified for special education, free and reduced price lunch, and English Language Learner services, and those who did not qualify for these services. Results indicated all of these students scored below grade level on the assessments administered. However, all of the students represented varying abilities and needs that required further analysis. Factor analysis was then utilized to determine which reading skills assessed were most directly related to student performance on TCAP. Three factors emerged, meaning, decoding, and rate and accuracy. Finally, cluster analysis presented four distinct clusters of struggling young adolescents, which represented heterogeneous abilities in various reading skills. Results indicated one-size-fits-all approaches to policy and instruction relating to struggling young adolescent readers do not meet the heterogeneous needs of this population of students. Rather, in-depth assessment and diagnoses are necessary to determine the most appropriate instructional tools for individual students. Further, by suggesting the use of state mandated standardized assessment scores be the sole indicator of student placement in remedial reading courses, policy fails to address the multifaceted process of reading and the differing trajectories of young adolescent reading development