High-Level Synthesis Based VLSI Architectures for Video Coding

High Efficiency Video Coding (HEVC) is state-of-the-art video coding standard. Emerging applications like free-viewpoint video, 360degree video, augmented reality, 3D movies etc. require standardized extensions of HEVC. The standardized extensions of HEVC include HEVC Scalable Video Coding (SHVC), HEVC Multiview Video Coding (MV-HEVC), MV-HEVC+ Depth (3D-HEVC) and HEVC Screen Content Coding. 3D-HEVC is used for applications like view synthesis generation, free-viewpoint video. Coding and transmission of depth maps in 3D-HEVC is used for the virtual view synthesis by the algorithms like Depth Image Based Rendering (DIBR). As first step, we performed the profiling of the 3D-HEVC standard. Computational intensive parts of the standard are identified for the efficient hardware implementation. One of the computational intensive part of the 3D-HEVC, HEVC and H.264/AVC is the Interpolation Filtering used for Fractional Motion Estimation (FME). The hardware implementation of the interpolation filtering is carried out using High-Level Synthesis (HLS) tools. Xilinx Vivado Design Suite is used for the HLS implementation of the interpolation filters of HEVC and H.264/AVC. The complexity of the digital systems is greatly increased. High-Level Synthesis is the methodology which offers great benefits such as late architectural or functional changes without time consuming in rewriting of RTL-code, algorithms can be tested and evaluated early in the design cycle and development of accurate models against which the final hardware can be verified

Thin-Wall Machining of Light Alloys: A Review of Models and Industrial Approaches

Thin-wall parts are common in the aeronautical sector. However, their machining presents serious challenges such as vibrations and part deflections. To deal with these challenges, di erent approaches have been followed in recent years. This work presents the state of the art of thin-wall light-alloy machining, analyzing the problems related to each type of thin-wall parts, exposing the causes of both instability and deformation through analytical models, summarizing the computational techniques used, and presenting the solutions proposed by di erent authors from an industrial point of view. Finally, some further research lines are proposed

Efficient Distortion-Free Neural Projector Deblurring in Dynamic Projection Mapping

Kageyama Y., Iwai D., Sato K.. Efficient Distortion-Free Neural Projector Deblurring in Dynamic Projection Mapping. IEEE Transactions on Visualization and Computer Graphics , (2024); https://doi.org/10.1109/TVCG.2024.3354957.Dynamic Projection Mapping (DPM) necessitates geometric compensation of the projection image based on the position and orientation of moving objects. Additionally, the projector's shallow depth of field results in pronounced defocus blur even with minimal object movement. Achieving delay-free DPM with high image quality requires real-time implementation of geometric compensation and projector deblurring. To meet this demand, we propose a framework comprising two neural components: one for geometric compensation and another for projector deblurring. The former component warps the image by detecting the optical flow of each pixel in both the projection and captured images. The latter component performs real-time sharpening as needed. Ideally, our network's parameters should be trained on data acquired in an actual environment. However, training the network from scratch while executing DPM, which demands real-time image generation, is impractical. Therefore, the network must undergo pre-training. Unfortunately, there are no publicly available large real datasets for DPM due to the diverse image quality degradation patterns. To address this challenge, we propose a realistic synthetic data generation method that numerically models geometric distortion and defocus blur in real-world DPM. Through exhaustive experiments, we have confirmed that the model trained on the proposed dataset achieves projector deblurring in the presence of geometric distortions with a quality comparable to state-of-the-art methods

Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria

Developing predictive models of multi-protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi-protein expression space across a > 10,000-fold range with tailored search parameters and well-predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram-positive and gram-negative bacterial hosts. We then combined the search algorithm with system-level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence-expression-activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate-limiting steps in metabolism. Creating sequence-expression-activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs

Microlens array grid estimation, light field decoding, and calibration

We quantitatively investigate multiple algorithms for microlens array grid estimation for microlens array-based light field cameras. Explicitly taking into account natural and mechanical vignetting effects, we propose a new method for microlens array grid estimation that outperforms the ones previously discussed in the literature. To quantify the performance of the algorithms, we propose an evaluation pipeline utilizing application-specific ray-traced white images with known microlens positions. Using a large dataset of synthesized white images, we thoroughly compare the performance of the different estimation algorithms. As an example, we apply our results to the decoding and calibration of light fields taken with a Lytro Illum camera. We observe that decoding as well as calibration benefit from a more accurate, vignetting-aware grid estimation, especially in peripheral subapertures of the light field.Comment: \copyright 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Microlens Array Grid Estimation, Light Field Decoding, and Calibration

We quantitatively investigate multiple algorithms for microlens array grid estimation for microlens array-based light field cameras. Explicitly taking into account natural and mechanical vignetting effects, we propose a new method for microlens array grid estimation that outperforms the ones previously discussed in the literature. To quantify the performance of the algorithms, we propose an evaluation pipeline utilizing application-specific raytraced white images with known microlens positions. Using a large dataset of synthesized white images, we thoroughly compare the performance of the different estimation algorithms. As an example, we apply our results to the decoding and calibration of light fields taken with a Lytro Illum camera. We observe that decoding as well as calibration benefit from a more accurate, vignetting-aware grid estimation, especially in peripheral subapertures of the light field

Modular Multilevel Cascaded Flying Capacitor STATCOM for Balanced and Unbalanced Load Compensation

Voltage and current unbalance are major problems in distribution networks, particularly with the integration of distributed generation systems. One way of mitigating these issues is by injecting negative sequence current into the distribution network using a Static Synchronous Compensator (STATCOM) which normally also regulates the voltage and power factor. The benefits of modularity and scalability offered by Modular Multilevel Cascaded Converters (MMCC) make them suitable for STATCOM application. A number of different types of MMCC may be used, classified according to the sub-module circuit topology used. Their performance features and operational ranges for unbalanced load compensation are evaluated and quantified in this research. This thesis investigates the use of both single star and single delta configured five-level Flying Capacitor (FC) converter MMCC based STATCOMs for unbalanced load compensation. A detailed study is carried out to compare this type of sub-module with several other types namely: half bridge, 3-L H-bridge and 3-L FC half bridge, and reveals the one best suited to STATCOM operation. With the choice of 5-L FC H-bridge as the sub-module for STATCOM operation, a detailed investigation is also performed to decide which pulse width modulation technique is the best. This was based on the assessment of total harmonic distortion, power loss, sub-module switch utilization and natural balancing of inner flying capacitors. Two new modulation techniques of swapped-carrier PWM (SC-PWM) along with phase disposed and phase shifted PWM (PS-PWM) are analyzed under these four performance metrics. A novel contribution of this research is the development of a new space vector modulation technique using an overlapping hexagon technique. This space vector strategy offers benefits of eliminating control complexity and improving waveform quality, unlike the case of multilevel space vector technique. The simulation and experimental results show that this method provides superior performance and is applicable for other MMCC sub-modules. Another contribution is the analysis and quantification of operating ranges of both single star and delta MMCCs in rating the cluster dc-link voltage (star) and current (delta) for unbalanced load compensation. A novel method of extending the operating capabilities of both configurations uses a third harmonic injection method. An experimental investigation validates the operating range extension compared to the pure sinusoidal zero sequence voltage and current injection. Also, the superiority of the single delta configured MMCC for unbalanced loading compensation is validated