A reduced memory bandwidth and high throughput HDTV motion compensation decoder for H.264/AVC High 4:2:2 profile

This article presents the HP422-MoCHA: optimized Motion Compensation hardware architecture for the High 4:2:2 profile of H.264/AVC video coding standard. The proposed design focuses on real-time decoding for HDTV 1080p (1,920 × 1,080 pixels) at 30 fps. It supports multiple sample bit-width (8, 9, or 10 bits) and multiple chroma sub-sampling formats (4:0:0, 4:2:0, and 4:2:2) to provide enhanced video quality experience. The architecture includes an optimized sample interpolator that processes luma and chroma samples in two parallel datapaths and features quarter sample accuracy, bi-prediction and weighted prediction. HP422-MoCHA also includes a hardwired Motion Vector Predictor, supporting temporal and spatial direct predictions. A novel memory hierarchy implemented as a 3-D Cache reduces the frame memory access, providing, on average, 62% of bandwidth and 80% of clock cycles reduction. The design was implemented in a Xilinx Virtex-II PRO FPGA, and also in an ASIC with a TSMC 0.18 μm standard cells technology. The ASIC implementation occupies 102 K equivalent gates and 56.5 KB of on-chip SRAM in a 3.8 × 3.4 mm² area. It presents a power consumption of 130 mW. Both implementations reach a maximum operation frequency of ~100 MHz, being able to motion compensate 37 bi-predictive frames or 69 predictive fps. The minimum required frequency to ensure the real-time decoding for HD1080p at 30 fps is 82 MHz. Since HP422-MoCHA is the first Motion Compensation architecture for the High 4:2:2 profile found in the literature, a Main profile MoCHA was used for comparison purposes, showing the highest throughput among all presented works. However, the HP422-MoCHA architecture also reaches the highest throughput when compared with the other published Main profile MC solutions, even considering the significantly higher complexity of the High 4:2:2 profile.     

A case study in computer-aided co-design of embedded controllers

We present an application of the methodology and of the various software tools embedded in the POLIS co-design system. The application is in the realm of automotive electronics: a shock absorber controller, whose specification comes from an actual product. All aspects of the design process are closely examined, including high level language specification and automatic hardware and software synthesis. We analyze different software implementation styles, compare the results, and outline the future developments of our work.This work was partially supported by SRC Contract DC-324-028 and by MURST Research Project VLSI Architectures.     

Power optimization for dynamic configuration in heterogeneous web server clusters

To reduce the environmental impact, it is essential to make data centers green, by turning off servers and tuning their speeds for the instantaneous load offered, that is, determining the dynamic configuration in web server clusters. We model the problem of selecting the servers that will be on and finding their speeds through mixed integer programming; we also show how to combine such solutions with control theory. For proof of concept, we implemented this dynamic configuration scheme in a web server cluster running Linux, with soft real-time requirements and QoS control, in order to guarantee both energy-efficiency and good user experience. In this paper, we show the performance of our scheme compared to other schemes, a comparison of a centralized and a distributed approach for QoS control, and a comparison of schemes for choosing speeds of servers.     

Environ: Integrating VR and CAD in Engineering Projects

A main objective of large industrial-engineering departments is implementing integrated information systems to manage their projects' life cycles. Environ is an application motivated by the demand to use Virtual Reality in large engineering models generated by CAD tools. Environ's main goal is to offer 3D visualization resources for CAD models with enough realism to serve as an integration tool for several engineering activities in the oil and gas industry.     

Comparing strategies for modeling students learning styles through reinforcement learning in adaptive and intelligent educational systems: An experimental analysis

A huge number of studies attest that learning is facilitated if teaching strategies are in accordance with students learning styles, making the learning process more effective and improving students performances. In this context, this paper presents an automatic, dynamic and probabilistic approach for modeling students learning styles based on reinforcement learning. Three different strategies for updating the student model are proposed and tested through experiments. The results obtained are analyzed, indicating the most effective strategy. Experiments have shown that our approach is able to automatically detect and precisely adjust students’ learning styles, based on the non-deterministic and non-stationary aspects of learning styles. Because of the probabilistic and dynamic aspects enclosed in automatic detection of learning styles, our approach gradually and constantly adjusts the student model, taking into account students’ performances, obtaining a fine-tuned student model.     

Assessing sentence scoring techniques for extractive text summarization

Text summarization is the process of automatically creating a shorter version of one or more text documents. It is an important way of finding relevant information in large text libraries or in the Internet. Essentially, text summarization techniques are classified as Extractive and Abstractive. Extractive techniques perform text summarization by selecting sentences of documents according to some criteria. Abstractive summaries attempt to improve the coherence among sentences by eliminating redundancies and clarifying the contest of sentences. In terms of extractive summarization, sentence scoring is the technique most used for extractive text summarization. This paper describes and performs a quantitative and qualitative assessment of 15 algorithms for sentence scoring available in the literature. Three different datasets (News, Blogs and Article contexts) were evaluated. In addition, directions to improve the sentence extraction results obtained are suggested.     

Safety assessment of a lithium target

This paper addresses the safety assessment of the lithium target of the International Fusion Materials Irradiation Facility (IFMIF) through evaluating the most important risk factors related to system operation and verifying the fulfillment of the safety criteria. The hazard assessment is based on using a well-structured Failure Mode and Effect Analysis (FMEA) procedure by detailing on a component-by-component basis all the possible failure modes and identifying their effects on the plant. Additionally, a systems analysis, applying the fault tree technique, is performed in order to evaluate, from a probabilistic standpoint, all the relevant and possible failures of each component required for safe system operation and assessing the unavailability of the lithium target system. The last task includes the thermal–hydraulic transient analysis of the target lithium loop, including operational and accident transients. A lithium target loop model is developed, using the RELAP5/Mod3.2 thermal–hydraulic code, which has been modified to include specific features of IFMIF itself. The main conclusions are that target safety is fulfilled, the hazards associated with lithium operation are confined within the IFMIF security boundaries, the environmental impact is negligible, and the plant responds to the simulated transients by being able to reach steady conditions in a safety situation.     

Probabilistic safety analysis of an accelerator—Lithium target based experimental facility

The international fusion materials irradiation facility (IFMIF) is aimed to provide an intense neutron source by a high current deuteron linear accelerator and a high-speed lithium flow target, for testing candidate materials for future fusion reactors.An activity aimed at the safety assessment of the IFMIF plant as a whole has been carried out applying the probabilistic risk assessment (PRA) approach to identify and quantify in terms of expected frequencies, the dominant accident sequences related to the plant operation, and define the reference accident scenarios to be further analyzed through deterministic transient analysis, in order to verify the fulfilment of the safety criteria.The accident sequences have been modeled through the event tree technique, which allows identifying all possible combinations of success or failure of the safety systems in responding to a selection of initiating events. The identification of accident initiators, provided by the failure mode and effect analysis (FMEA) procedure, is followed by the systems analysis based on fault tree technique, for the unavailability assessment of the safety systems: finally the accident sequence scenarios are assessed by RISK SPECTRUM software.The study has allowed for the development of all accident sequences resulting from selected initiators relative to IFMIF plant and their grouping within sequence families, denoted as plant damage states, on account of the plant response and expected consequences. The frequency assigned to each family sequence is the sum of the contributors relative to all sequences ending into that particular plant state.The outcome of the analysis shows that IFMIF plant is quite safe and presents no significant hazard to the environment: in fact all the sequences implying potential undesired effects as radioactive release to the outside, show very low frequencies, well below the limit for credible accident (1.0E−6/year). In addition, due to the novelty of the design and the large spreading assigned to the failure parameter probabilistic distributions (data utilized in the probabilistic analysis of this one of a kind plant are largely of a generic nature), an uncertainty analysis has been performed to add credit to the model quantification and to assess if the sequences have been correctly evaluated on the probability standpoint.     

Biological shape analysis by digital curvature

This paper reports the novel application of digital curvature as a feature for morphological characterization and classification of landmark shapes. By inheriting several unique features of the continuous curvature, the digital curvature provides invariance to translations, rotations, local shape deformations, and is easily made tolerant to scaling. In addition, the bending energy, a global shape feature, can be directly estimated from the curvature values. The application of these features to analyse patterns of cranial morphological geographic differentiation in the rodent species Thrichomys apereoides has led to encouraging results, indicating a close correspondence between the geographical and morphological distributions.