Improving the Quality of Technology-Enhanced Learning for Computer Programming Courses

Teaching computing courses is a major challenge for the majority of lecturers in Libyan higher learning institutions. These courses contain numerous abstract concepts that cannot be easily explained using traditional educational methods. This paper describes the rationale, design, development and implementation stages of an e-learning package (including multimedia resources such as simulations, animations, and videos) using the ASSURE model. This training package can be used by students before they attend practical computer lab sessions, preparing them by developing technical skills and applying concepts and theories presented in lecture through supplementary study and exercises

Towards the Application of Classification Techniques to Test and Identify Faults in Multimedia Systems

The advances in computer and graphic technologies have led to the popular use of multimedia for information exchange. However, multimedia systems are difficult to test. A major reason is that these systems generally exhibit fuzziness in their temporal behaviors. The fuzziness may be caused by the existence of non-deterministic factors in their runtime environments, such as system load and network traffic. It complicates the analysis of test results. The problem is aggravated when a test involves the synchronization of different multimedia streams as well as variations in system loading.\ud \ud In this paper, we conduct an empirical study on the testing and fault-identification of multimedia systems by treating the issue as a classification problem. Typical classification techniques, including Bayesian networks, k-nearest neighbor, and neural networks, are experimented with the use of X-Smiles, an open sourced multimedia authoring tool supporting the Synchronized Multimedia Integration Language (SMIL). From these experiments, we make a few interesting observations and give plausible explanations based on the geometrical properties of the test results

Design and Validation of a Software Defined Radio Testbed for DVB-T Transmission

This paper describes the design and validation of a Software Defined Radio (SDR) testbed, which can be used for Digital Television transmission using the Digital Video Broadcasting - Terrestrial (DVB-T) standard. In order to generate a DVB-T-compliant signal with low computational complexity, we design an SDR architecture that uses the C/C++ language and exploits multithreading and vectorized instructions. Then, we transmit the generated DVB-T signal in real time, using a common PC equipped with multicore central processing units (CPUs) and a commercially available SDR modem board. The proposed SDR architecture has been validated using fixed TV sets, and portable receivers. Our results show that the proposed SDR architecture for DVB-T transmission is a low-cost low-complexity solution that, in the worst case, only requires less than 22% of CPU load and less than 170 MB of memory usage, on a 3.0 GHz Core i7 processor. In addition, using the same SDR modem board, we design an off-line software receiver that also performs time synchronization and carrier frequency offset estimation and compensation

Quality of Service Controlled Multimedia Transport Protocol

PhDThis research looks at the design of an open transport protocol that supports a range of services including multimedia over low data-rate networks. Low data-rate multimedia applications require a system that provides quality of service (QoS) assurance and flexibility. One promising field is the area of content-based coding. Content-based systems use an array of protocols to select the optimum set of coding algorithms. A content-based transport protocol integrates a content-based application to a transmission network. General transport protocols form a bottleneck in low data-rate multimedia communicationbsy limiting throughpuot r by not maintainingt iming requirementsT. his work presents an original model of a transport protocol that eliminates the bottleneck by introducing a flexible yet efficient algorithm that uses an open approach to flexibility and holistic architectureto promoteQ oS.T he flexibility andt ransparenccyo mesi n the form of a fixed syntaxt hat providesa seto f transportp rotocols emanticsT. he mediaQ oSi s maintained by defining a generic descriptor. Overall, the structure of the protocol is based on a single adaptablea lgorithm that supportsa pplication independencen, etwork independencea nd quality of service. The transportp rotocol was evaluatedth rougha set of assessmentos:f f-line; off-line for a specific application; and on-line for a specific application. Application contexts used MPEG-4 test material where the on-line assessmenuts eda modified MPEG-4 pl; yer. The performanceo f the QoSc ontrolledt ransportp rotocoli s often bettert hano thers chemews hen appropriateQ oS controlledm anagemenatl gorithmsa re selectedT. his is shownf irst for an off-line assessmenwt here the performancei s compared between the QoS controlled multiplexer,a n emulatedM PEG-4F lexMux multiplexers chemea, ndt he targetr equirements. The performanceis also shownt o be better in a real environmentw hen the QoS controlled multiplexeri s comparedw ith the real MPEG-4F lexMux scheme

3D high definition video coding on a GPU-based heterogeneous system

H.264/MVC is a standard for supporting the sensation of 3D, based on coding from 2 (stereo) to N views. H.264/MVC adopts many coding options inherited from single view H.264/AVC, and thus its complexity is even higher, mainly because the number of processing views is higher. In this manuscript, we aim at an efficient parallelization of the most computationally intensive video encoding module for stereo sequences. In particular, inter prediction and its collaborative execution on a heterogeneous platform. The proposal is based on an efficient dynamic load balancing algorithm and on breaking encoding dependencies. Experimental results demonstrate the proposed algorithm's ability to reduce the encoding time for different stereo high definition sequences. Speed-up values of up to 90× were obtained when compared with the reference encoder on the same platform. Moreover, the proposed algorithm also provides a more energy-efficient approach and hence requires less energy than the sequential reference algorith

On the quality of VoIP with DCCP for satellite communications

We present experimental results for the performance of selected voice codecs using DCCP with CCID4 congestion control over a satellite link. We evaluate the performance of both constant and variable data rate speech codecs for a number of simultaneous calls using the ITU E-model. We analyse the sources of packet losses and additionally analyse the effect of jitter which is one of the crucial parameters contributing to VoIP quality and has, to the best of our knowledge, not been considered previously in the published DCCP performance results. We propose modifications to the CCID4 algorithm and demonstrate how these improve the VoIP performance, without the need for additional link information other than what is already monitored by CCID4. We also demonstrate the fairness of the proposed modifications to other flows. Although the recently adopted changes to TFRC specification alleviate some of the performance issues for VoIP on satellite links, we argue that the characteristics of commercial satellite links necessitate consideration of further improvements. We identify the additional benefit of DCCP when used in VoIP admission control mechanisms and draw conclusions about the advantages and disadvantages of the proposed DCCP/CCID4 congestion control mechanism for use with VoIP applications

Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles

The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking received support from the European Union’s Horizon 2020 research and innovation programme and Germany, Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy, Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL Joint Undertaking under grant agreement No. 692455-2

Strategies for Searching Video Content with Text Queries or Video Examples

The large number of user-generated videos uploaded on to the Internet everyday has led to many commercial video search engines, which mainly rely on text metadata for search. However, metadata is often lacking for user-generated videos, thus these videos are unsearchable by current search engines. Therefore, content-based video retrieval (CBVR) tackles this metadata-scarcity problem by directly analyzing the visual and audio streams of each video. CBVR encompasses multiple research topics, including low-level feature design, feature fusion, semantic detector training and video search/reranking. We present novel strategies in these topics to enhance CBVR in both accuracy and speed under different query inputs, including pure textual queries and query by video examples. Our proposed strategies have been incorporated into our submission for the TRECVID 2014 Multimedia Event Detection evaluation, where our system outperformed other submissions in both text queries and video example queries, thus demonstrating the effectiveness of our proposed approaches