The development of a sound viewer for an open hypermedia system

Abstract

While rich support for a wide variety of media such as text, video and image is common among contemporary hypermedia systems, so too is the inadequate support for audio. The primary reason that audio has not attracted as much attention as other media can be attributed to its obvious lack of visual identity. The main focus of this work was to identify a generic and meaningful visual representation of audio within a hypermedia context, and significantly promote hypermedia support for audio through the provision of a sound viewer.

This paper describes the inherent difficulties in providing a consistent interface to audio, and discusses in some depth the issues raised during the development process. The sound viewer is then introduced and the associated concepts described. The creation and traversal of links to and from audio are facilitated by the sound viewer across formats including WAV (proprietary digital sound file format from Microsoft), CD (Compact Disc) Audio and MIDI (Musical Instrument Digital Interface). The resultant viewer provides a unified and extensible framework for interacting with audio from within an open hypermedia environment. The open hypermedia system Microcosm was used as the development platform for this work. Microcosm can be augmented to supply a hypermedia link service to additional media with minimal overhead.     

Clustering high dimensional data: A graph-based relaxed optimization approach

There is no doubt that clustering is one of the most studied data mining tasks. Nevertheless, it remains a challenging problem to solve despite the many proposed clustering approaches. Graph-based approaches solve the clustering task as a global optimization problem, while many other works are based on local methods. In this paper, we propose a novel graph-based algorithm “GBR” that relaxes some well-defined method even as improving the accuracy whilst keeping it simple. The primary motivation of our relaxation of the objective is to allow the reformulated objective to find well distributed cluster indicators for complicated data instances. This relaxation results in an analytical solution that avoids the approximated iterative methods that have been adopted in many other graph-based approaches. The experiments on synthetic and real data sets show that our relaxation accomplishes excellent clustering results. Our key contributions are: (1) we provide an analytical solution to solve the global clustering task as opposed to approximated iterative approaches; (2) a very simple implementation using existing optimization packages; (3) an algorithm with relatively less computation time over the number of data instances to cluster than other well defined methods in the literature.     

Applications of wavelet data reduction in a recommender system

Memory-based collaborative filtering (CF) recommender systems have emerged as an effective technique for information filtering. CF recommenders are being widely adopted for e-commerce applications to assist users in finding and selecting items of interest. As a result, the scalability of CF recommenders presents a significant challenge; one that is particularly resilient because the volume of data these systems utilize will continue to increase over time. This paper examines the impact of discrete wavelet transformation (DWT) as an approach to enhance the scalability of memory-based collaborative filtering recommender systems. In particular, a wavelet transformation methodology is proposed and applied to both synthetic and real-world recommender ratings. For experimental purposes, the DWT methodology’s effect on predictive accuracy and calculation speed is evaluated to compare recommendation quality and performance.     

Air damping of high performance resonating micro-mirrors with angular vertical comb-drive actuators

Microsystem Technologies - The maximum scan angle amplitude of resonating micro-mirrors, intended for micro-projection display applications is limited by air damping. Three-dimensional transient...     

Efficient and 1,8-diiodooctane-free ternary organic solar cells fabricated via nanoscale morphology tuning using small-molecule dye additive

The ternary strategy for incorporating multiple photon-sensitive components into a single junction has emerged as an effective method for optimizing the nanoscale morphology and improving the device performance of organic solar cells (OSCs).In this study,efficient and stable ternary OSCs were achieved by introducing the small-molecule dye (5E,5'E)-5,5'-(4',4″-(1,2-diphenylethene-1,2-diyl)bis(biphenyl-4',4-diyl))bis(methan-1-yl-1-ylidene)bis(3-ethyl-2-thioxothia zolidin-4-one) (BTPERn) into poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b']dithiopheneco-3-fluorothieno[3,4-b]thiophene-2-carboxylate] (PTB7-Th):[6,6]-phenyl C71 butyric acid methyl ester (PC71BM) blend films processed using a 1,8-diiodooctane (DIO)-free solvent.The incorporation of BTPE-Rn enhanced the short-circuit current density and fill factor of the ternary OSCs compared with those of binary OSCs.An investigation of the optical,electronic,and morphological properties of the ternary blends indicated that the third component of BTPE-Rn not only promoted the photon utilization of blends through the energy-transfer process but also improved the electron mobility of the blends owing to the fullerene-rich nanophase optimization.More importantly,this ternary strategy of utilizing a small-molecule dye to replace the photounstable DIO additive enhanced the operational stability of the OSCs.