Will mobile video become the killer application for 3G? - an empirical model for media convergence

Mobile carriers have continually rolled out 3G mobile video applications to increase their revenue and profits. The presumption is that video is superior to the already successful SMS, ringtones, and pictures, and can create greater value to users. However, recent market surveys revealed contradicting results. Motivated by this discrepancy, we propose in this paper a parsimonious model for user acceptance of mobile entertainment as digital convergence. Integrating research on Information Systems, Flow, and Media Psychology, we take a unique approach to user acceptance of digital convergence - platform migration. Our key proposition is that the interaction between media types and the platform-specific constraints is the key determinant of user evaluation. Particularly, users' involvement in the media is determined by both the entertaining time span on the original platform and the attentional constraint of the new platform. The mismatch between the two spans can result in lower level involvement, which in turn cause no or even negative user emotional responses. The model was tested with empirical data. We discuss the theoretical contributions, strategic and design implications, and future research directions derived from this theoretical framewor

Hierarchical Matrices in the See-Saw Mechanism, large Neutrino Mixing and Leptogenesis

We consider the see-saw mechanism for hierarchical Dirac and Majorana neutrino mass matrices m_D and M_R, including the CP violating phases. Simple arguments about the structure of the neutrino mass matrix and the requirement of successful leptogenesis lead to the situation that one of the right-handed Majorana neutrinos is much heavier than the other two, which in turn display a rather mild hierarchy. It is investigated how for the neutrino mixing one small and two large angles are generated. The mixing matrix element |U_{e3}|^2 is larger than 10^{-3} and a characteristic ratio between the branching ratios of lepton flavor violating charged lepton decays \ell_j -> \ell_i \gamma is found. Successful leptogenesis implies sizable CP violation in oscillation experiments. As in the original minimal see-saw model, the signs of the baryon asymmetry of the universe and of the CP asymmetry in neutrino oscillations are equal and there is no connection between the leptogenesis phase and the effective mass as measurable in neutrinoless double beta decay.Comment: 16 + 3 pages, 2 figures. To appear in Eur.Phys.J.

Old Wine in New Bottles? An Overview of Two Centuries of Free Trade between the United States and Canada

On February 5, 2003 the Maine International Trade Center and University of Maine Canadian American Center co-sponsored a day-long forum on the challenges and opportunities of free trade between Canada and the United States. This article presents the edited remarks of Scott See who gave audience members a whirlwind overview of the history of Canadian-American free trade from the Revolutionary War era up to passage of the Free Trade Agreement in 1989

Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognition

Facial micro-expression (ME) recognition has posed a huge challenge to researchers for its subtlety in motion and limited databases. Recently, handcrafted techniques have achieved superior performance in micro-expression recognition but at the cost of domain specificity and cumbersome parametric tunings. In this paper, we propose an Enriched Long-term Recurrent Convolutional Network (ELRCN) that first encodes each micro-expression frame into a feature vector through CNN module(s), then predicts the micro-expression by passing the feature vector through a Long Short-term Memory (LSTM) module. The framework contains two different network variants: (1) Channel-wise stacking of input data for spatial enrichment, (2) Feature-wise stacking of features for temporal enrichment. We demonstrate that the proposed approach is able to achieve reasonably good performance, without data augmentation. In addition, we also present ablation studies conducted on the framework and visualizations of what CNN "sees" when predicting the micro-expression classes.Comment: Published in Micro-Expression Grand Challenge 2018, Workshop of 13th IEEE Facial & Gesture 201

A new class of two-channel biorthogonal filter banks and wavelet bases

We propose a novel framework for a new class of two-channel biorthogonal filter banks. The framework covers two useful subclasses: i) causal stable IIR filter banks. ii) linear phase FIR filter banks. There exists a very efficient structurally perfect reconstruction implementation for such a class. Filter banks of high frequency selectivity can be achieved by using the proposed framework with low complexity. The properties of such a class are discussed in detail. The design of the analysis/synthesis systems reduces to the design of a single transfer function. Very simple design methods are given both for FIR and IIR cases. Zeros of arbitrary multiplicity at aliasing frequency can be easily imposed, for the purpose of generating wavelets with regularity property. In the IIR case, two new classes of IIR maximally flat filters different from Butterworth filters are introduced. The filter coefficients are given in closed form. The wavelet bases corresponding to the biorthogonal systems are generated. the authors also provide a novel mapping of the proposed 1-D framework into 2-D. The mapping preserves the following: i) perfect reconstruction; ii) stability in the IIR case; iii) linear phase in the FIR case; iv) zeros at aliasing frequency; v) frequency characteristic of the filters

Less is More: Micro-expression Recognition from Video using Apex Frame

Despite recent interest and advances in facial micro-expression research, there is still plenty room for improvement in terms of micro-expression recognition. Conventional feature extraction approaches for micro-expression video consider either the whole video sequence or a part of it, for representation. However, with the high-speed video capture of micro-expressions (100-200 fps), are all frames necessary to provide a sufficiently meaningful representation? Is the luxury of data a bane to accurate recognition? A novel proposition is presented in this paper, whereby we utilize only two images per video: the apex frame and the onset frame. The apex frame of a video contains the highest intensity of expression changes among all frames, while the onset is the perfect choice of a reference frame with neutral expression. A new feature extractor, Bi-Weighted Oriented Optical Flow (Bi-WOOF) is proposed to encode essential expressiveness of the apex frame. We evaluated the proposed method on five micro-expression databases: CAS(ME)$^2$, CASME II, SMIC-HS, SMIC-NIR and SMIC-VIS. Our experiments lend credence to our hypothesis, with our proposed technique achieving a state-of-the-art F1-score recognition performance of 61% and 62% in the high frame rate CASME II and SMIC-HS databases respectively.Comment: 14 pages double-column, author affiliations updated, acknowledgment of grant support adde

ASEAN-EU university network programme on EMC and SI education

This paper reports about a project for the creation of an innovative university course devoted to the preparation of future electronic designers to the challenges imposed by the assurance of the electrical performance of high-speed electronic systems. The target groups are future university teaching staff and future electronic systems designers. Activities are developed by means of sharing research results, seminars, experience exchange and the development of demonstrators to be used for teaching. The partnership is composed by Technical University of Turin (Italy), University of Hannover (Germany), University of Nottingham (UK), Nanyang Technological University (Singapore) and King Monguts Institute of Technology Lad-krabang, Bangkok (Thailand). The program is partially funded by the European Commission under the ASEAN-EU University Network Programme (AUNP) and its duration is 24 months