Video streaming applications have been gaining interest rapidly in various perspectives from entertainment to e-learning. Practically, these applications suffer from inevitable loss in the transmission channels. Hence it is a challenging task to improve the quality of video streaming over the error prone channels. Multiple Description Coding (MDC) is a promising error resilient coding scheme wh...

Data from 14 crossbred (Landreace x Large white) boars aged 10-12 months were used to investigate specific germ cells and to what extent Sertoli cells are prone to sub-clinical infection with strain Y58/98 Trypanosome brucei brucei and effects on spermatogenesis. Boars were divided into three groups, A, B and C of 5, 5 and 4 animals, respectively. Groups A and B were infected intraperitoneally ...

Sign languages (SLs) are visuo-gestural representations used by deaf communities. Recognition of SLs usually requires manual annotations, which are expert dependent, prone to errors and time consuming. This work introduces a method to support SL annotations based on a motion descriptor that characterizes dynamic gestures in videos. The proposed approach starts by computing local kinematic cues,...

With emerging standards like JPEG2000 focusing on scalable encoding of images, there is an immediate need for robust schemes to transmit progressive source streams over error-prone fading channels. In this work, we explore one possibility for this framework, where we use multilevel codes with Low Density Parity Check (LDPC) component codes and an 8-PSK constellation. We match the channel code r...

This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dynamic programming. The deep neural network (DNN) concept has recently emerged as a very effective tool for processing vision sensor signals. A patch-...

There is an ongoing global movement for the entrenchment of occupational mental health as an integral part of occupational health and safety schemes. Aside from being a fundamental human right issue, this move has been demonstrated to be of cost-benefit in terms of workplace productivity and general economic growth. Despite being among the regions most prone to the human and economic repercussi...

Data-Oriented Translation (DOT), based on DataOriented Parsing (DOP), is a language-independent MT engine which exploits parsed, aligned bitexts to produce very high quality translations. However, data acquisition constitutes a serious bottleneck as DOT requires parsed sentences aligned at both sentential and sub-structural levels. Manual substructural alignment is time-consuming, error-prone a...

Data-driven approaches to machine translation (MT) achieve state-of-the-art results. Many syntax-aware approaches, such as ExampleBased MT and Data-Oriented Translation, make use of tree pairs aligned at sub-sentential level. Obtaining sub-sentential alignments manually is time-consuming and error-prone, and requires expert knowledge of both source and target languages. We propose a novel, lang...