Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition

In most previous research on distributional semantics, Vector Space Models (VSMs) of words are built either from topical information (e.g., documents in which a word is present), or from syntactic/semantic types of words (e.g., dependency parse links of a word in sentences), but not both. In this paper, we explore the utility of combining these two representations to build VSM for the task of semantic composition of adjective-noun phrases. Through extensive experiments on benchmark datasets, we find that even though a type-based VSM is effective for semantic composition, it is often outperformed by a VSM built using a combination of topic- and type-based statistics. We also introduce a new evaluation task wherein we predict the composed vector representation of a phrase from the brain activity of a human subject reading that phrase. We exploit a large syntactically parsed corpus of 16 billion tokens to build our VSMs, with vectors for both phrases and words, and make them publicly available.

Channel Time Allocation PSO for Gigabit Multimedia Wireless Networks

This article introduces a resource allocation solution capable of handling mixed media applications within the constraints of a 60 GHz wireless network. The challenges of multimedia wireless transmission include high bandwidth requirements, delay intolerance and wireless channel availability. A new Channel Time Allocation Particle Swarm Optimization (CTA-PSO) is proposed to solve the network utility maximization (NUM) resource allocation problem. CTA-PSO optimizes the time allocated to each device in the network in order to maximize the Quality of Service (QoS) experienced by each user. CTA-PSO introduces network-linked swarm size, an increased diversity function and a learning method based on the personal best, Pbest, results of the swarm. These additional developments to the PSO produce improved convergence speed with respect to Adaptive PSO while maintaining the QoS improvement of the NUM. Specifically, CTA-PSO supports applications described by both convex and non-convex utility functions. The multimedia resource allocation solution presented in this article provides a practical solution for real-time wireless networks.

Next generation femtocells: An enabler for high efficiency multimedia transmission

The first generation of femtocells is evolving to the next generation with many more capabilities in terms of better utilisation of radio resources and support of high data rates. It is thus logical to conjecture that with these abilities and their inherent suitability for home environment, they stand out as an ideal enabler for delivery of high efficiency multimedia services. This paper presents a comprehensive vision towards this objective and extends the concept of femtocells from indoor to outdoor environments, and strongly couples femtocells to emergency and safety services. It also presents and identifies relevant issues and challenges that have to be overcome in realization of this vision.

Multimedia psycho-educational interventions to support patient self-care in degenerative conditions: a realist review

Objective: Multimedia interventions are increasingly used to deliver information in order to promote self-care among patients with degenerative conditions. We carried out a realist review of the literature to investigate how the characteristics of multimedia psychoeducational interventions combine with the contexts in which they are introduced to help or hinder their effectiveness in supporting self-care for patients with degenerative conditions.

Method: Electronic databases (Medline, Science Direct, PSYCHinfo, EBSCO, and Embase) were searched in order to identify papers containing information on multimedia psychoeducational interventions. Using a realist review approach, we reviewed all relevant studies to identify theories that explained how the interventions work.

Results: Ten papers were included in the review. All interventions sought to promote self-care behaviors among participants. We examined the development and content of the multimedia interventions and the impact of patient motivation and of the organizational context of implementation. We judged seven studies to be methodologically weak. All completed studies showed small effects in favor of the intervention.

Significance of Results: Multimedia interventions may provide high-quality information in an accessible format, with the potential to promote self-care among patients with degenerative conditions, if the patient perceives the information as important and develops confidence about self-care. The evidence base is weak, so that research is needed to investigate effective modes of delivery at different resource levels. We recommend that developers consider how an intervention will reduce uncertainty and increase confidence in self-care, as well as the impact of the context in which it will be employed.

Green Media: The Future of Wireless Multimedia Networks:Guest Editorial

By 2015, with the proliferation of wireless multimedia applications and services (e.g., mobile TV, video on demand, online video repositories, immersive video interaction, peer to peer video streaming, and interactive video gaming), and any-time anywhere communication, the number of smartphones and tablets will exceed 6.5 billion as the most common web access devices. Data volumes in wireless multimedia data-intensive applications and mobile web services are projected to increase by a factor of 10 every five years, associated with a 20 percent increase in energy consumption, 80 percent of which is multimedia traffic related. In turn, multimedia energy consumption is rising at 16 percent per year, doubling every six years. It is estimated that energy costs alone account for as much as half of the annual operating expenditure. This has prompted concerted efforts by major operators to drastically reduce carbon emissions by up to 50 percent over the next 10 years. Clearly, there is an urgent need for new disruptive paradigms of green media to bridge the gap between wireless technologies and multimedia applications.

A Cross-Layer Optimized Scheme and Its Application in Mobile Multimedia Networks with QoS Provision

To cope with the rapid growth of multimedia applications that requires dynamic levels of quality of service (QoS), cross-layer (CL) design, where multiple protocol layers are jointly combined, has been considered to provide diverse QoS provisions for mobile multimedia networks. However, there is a lack of a general mathematical framework to model such CL scheme in wireless networks with different types of multimedia classes. In this paper, to overcome this shortcoming, we therefore propose a novel CL design for integrated real-time/non-real-time traffic with strict preemptive priority via a finite-state Markov chain. The main strategy of the CL scheme is to design a Markov model by explicitly including adaptive modulation and coding at the physical layer, queuing at the data link layer, and the bursty nature of multimedia traffic classes at the application layer. Utilizing this Markov model, several important performance metrics in terms of packet loss rate, delay, and throughput are examined. In addition, our proposed framework is exploited in various multimedia applications, for example, the end-to-end real-time video streaming and CL optimization, which require the priority-based QoS adaptation for different applications. More importantly, the CL framework reveals important guidelines as to optimize the network performance

Multimedia Resource Allocation in mmWave 5G Networks

The 5G network infrastructure is driven by the evolution of today's most demanding applications. Already, multimedia applications such as on-demand HD video and IPTV require gigabit- per-second throughput and low delay, while future technologies include ultra HDTV and machine-to-machine communication. Mm-Wave technologies such as IEEE 802.15.3c and IEEE 802.11ad are ideal candidates to deliver high throughput to multiple users demanding differentiated QoS. Optimization is often used as a methodology to meet throughput and delay constraints. However, traditional optimization techniques are not suited to a mixed set of multimedia applications. Particle swarm optimization (PSO) is shown as a promising technique in this context. Channel-time allocation PSO (CTA-PSO) is successfully shown here to allocate resource even in scenarios where blockage of the 60 GHz signal poses significant challenges.

Two-part Segmentation of Text Documents

We consider the problem of segmenting text documents that have a
two-part structure such as a problem part and a solution part. Documents
of this genre include incident reports that typically involve
description of events relating to a problem followed by those pertaining
to the solution that was tried. Segmenting such documents
into the component two parts would render them usable in knowledge
reuse frameworks such as Case-Based Reasoning. This segmentation
problem presents a hard case for traditional text segmentation
due to the lexical inter-relatedness of the segments. We develop
a two-part segmentation technique that can harness a corpus
of similar documents to model the behavior of the two segments
and their inter-relatedness using language models and translation
models respectively. In particular, we use separate language models
for the problem and solution segment types, whereas the interrelatedness
between segment types is modeled using an IBM Model
1 translation model. We model documents as being generated starting
from the problem part that comprises of words sampled from
the problem language model, followed by the solution part whose
words are sampled either from the solution language model or from
a translation model conditioned on the words already chosen in the
problem part. We show, through an extensive set of experiments on
real-world data, that our approach outperforms the state-of-the-art
text segmentation algorithms in the accuracy of segmentation, and
that such improved accuracy translates well to improved usability
in Case-based Reasoning systems. We also analyze the robustness
of our technique to varying amounts and types of noise and empirically
illustrate that our technique is quite noise tolerant, and
degrades gracefully with increasing amounts of noise