Frame synchronization for pulsed jammed satellite telecommand links

A new issue of the satellite telecommand synchronization and channel coding sublayer protocol includes LDPC‐coded communication link transmission units (CLTUs) that contain a 64‐bit start sequence. The novel data structures allow operation at lower signal‐to‐noise ratios than before and offer improved protection against jamming attacks. This paper considers the corresponding CLTU frame synchronization process. We derive practical algorithms to locate the start sequence in the presence of high noise levels and pulsed jamming. The different algorithms are compared in terms of implementation complexity and performance under various jamming conditions. It is shown that among the considered frame synchronizers, those involving a full search over the entire observation window provide the desired accuracy, ie, they guarantee a frame synchronization error probability that is significantly smaller than the codeword error rate, for codeword error rates near a target value of 10^?4. Among these synchronizers, the full‐search hard‐decision–directed correlation‐based algorithm has the lowest complexity.     

Associating and Tuning Sodium and Oxygen Mixed‐Ion Conduction in Niobium‐Based Perovskites

Pure ionic conductors as solid‐state electrolytes are of high interest in electrochemical energy storage and conversion devices. They systematically involve only one ion as the charge carrier. The association of two mobile ionic species, one positively and the other negatively charged, in a specific network should strongly influence the total ion conduction. Nb⁵⁺‐ (4d⁰) and Ti⁴⁺‐based (3d⁰) derived‐perovskite frameworks containing Na⁺ and O^2? as mobile species are investigated as mixed ion conductors by electrochemical impedance spectroscopy. The design of Na⁺ blocking layers via sandwiched pellet sintered by spark plasma sintering at high temperatures leads to quantified transport number of both ionic charge carriers t_Na+ and t_O2?. In the 350–700 °C temperature range, ionic conductivity can be tuned from major Na⁺ contribution (t_Na+ = 88%) for NaNbO₃ to pure O^2? transport in NaNb_0.9Ti_0.1O_2.95 phase. Such a Ti‐substitution is accompanied with a ≈100‐fold increase in the oxygen conductivity, approaching the best values for pure oxygen conductors in this temperature range. Besides the demonstration of tunable mixed ion conduction with quantifiable cationic and anionic contributions in a single solid‐state structure, a strategy is established from structural analysis to develop other architectures with improved mixed ionic conductivity.     

Data-driven and tool-supported elicitation of quality requirements in agile companies

Software Quality Journal - Quality requirements (QRs) are a key artifact needed to ensure the quality and success of a software system. Despite their importance, QRs rarely get the same degree of...     

Efficient Computation of Smoothed Exponential Maps

Many applications in geometry processing require the computation of local parameterizations on a surface mesh at interactive rates. A popular approach is to compute local exponential maps, i.e. parameterizations that preserve distance and angle to the origin of the map. We extend the computation of geodesic distance by heat diffusion to also determine angular information for the geodesic curves. This approach has two important benefits compared to fast approximate as well as exact forward tracing of the distance function: First, it allows generating smoother maps, avoiding discontinuities. Second, exploiting the factorization of the global Laplace–Beltrami operator of the mesh and using recent localized solution techniques, the computation is more efficient even compared to fast approximate solutions based on Dijkstra's algorithm.     

Does syntax highlighting help programming novices?

Program comprehension is an important skill for programmers – extending and debugging existing source code is part of the daily routine. Syntax highlighting is one of the most common tools used to support developers in understanding algorithms. However, most research in this area originates from a time when programmers used a completely different tool chain. We examined the influence of syntax highlighting on novices’ ability to comprehend source code. Additional analyses cover the influence of task type and programming experience on the code comprehension ability itself and its relation to syntax highlighting. We conducted a controlled experiment with 390 undergraduate students in an introductory Java programming course. We measured the correctness with which they solved small coding tasks. Each test subject received some tasks with syntax highlighting and some without. The data provided no evidence that syntax highlighting improves novices’ ability to comprehend source code. There are very few similar experiments and it is unclear as of yet which factors impact the effectiveness of syntax highlighting. One major limitation may be the types of tasks chosen for this experiment. The results suggest that syntax highlighting squanders a feedback channel from the IDE to the programmer that can be used more effectively.     

Software engineering practices and Simulink: bridging the gap

International Journal on Software Tools for Technology Transfer - Although widely used in embedded systems design, Matlab/Simulink is not considered a state-of-the-art design environment by the...     

Tree Branch Level of Detail Models for Forest Navigation

We present a level of detail (LOD) method designed for tree branches. It can be combined with methods for processing tree foliage to facilitate navigation through large virtual forests. Starting from a skeletal representation of a tree, we fit polygon meshes of various densities to the skeleton while the mesh density is adjusted according to the required visual fidelity. For distant models, these branch meshes are gradually replaced with semi‐transparent lines until the tree recedes to a few lines. Construction of these complete LOD models is guided by error metrics to ensure smooth transitions between adjacent LOD models. We then present an instancing technique for discrete LOD branch models, consisting of polygon meshes plus semi‐transparent lines. Line models with different transparencies are instanced on the GPU by merging multiple tree samples into a single model. Our technique reduces the number of draw calls in GPU and increases rendering performance. Our experiments demonstrate that large‐scale forest scenes can be rendered with excellent detail and shadows in real time.     

A user parameter-free approach for mining robust sequential classification rules

Recent years have witnessed extensive studies of graph classification due to the rapid increase in applications involving structural data and complex relationships. To support graph classification, all existing methods require that training graphs should be relevant (or belong) to the target class, but cannot integrate graphs irrelevant to the class of interest into the learning process. In this paper, we study a new universum graph classification framework which leverages additional “non-example” graphs to help improve the graph classification accuracy. We argue that although universum graphs do not belong to the target class, they may contain meaningful structure patterns to help enrich the feature space for graph representation and classification. To support universum graph classification, we propose a mathematical programming algorithm, ugBoost, which integrates discriminative subgraph selection and margin maximization into a unified framework to fully exploit the universum. Because informative subgraph exploration in a universum setting requires the search of a large space, we derive an upper bound discriminative score for each subgraph and employ a branch-and-bound scheme to prune the search space. By using the explored subgraphs, our graph classification model intends to maximize the margin between positive and negative graphs and minimize the loss on the universum graph examples simultaneously. The subgraph exploration and the learning are integrated and performed iteratively so that each can be beneficial to the other. Experimental results and comparisons on real-world dataset demonstrate the performance of our algorithm.     

Performance and energy effects on task-based parallelized applications

Heterogeneity, parallelization and vectorization are key techniques to improve the performance and energy efficiency of modern computing systems. However, programming and maintaining code for these architectures poses a huge challenge due to the ever-increasing architecture complexity. Task-based environments hide most of this complexity, improving scalability and usage of the available resources. In these environments, while there has been a lot of effort to ease parallelization and improve the usage of heterogeneous resources, vectorization has been considered a secondary objective. Furthermore, there has been a swift and unstoppable burst of vector architectures at all market segments, from embedded to HPC. Vectorization can no longer be ignored, but manual vectorization is tedious, error-prone and not practical for the average programmer. This work evaluates the feasibility of user-directed vectorization in task-based applications. Our evaluation is based on the OmpSs programming model, extended to support user-directed vectorization for different SIMD architectures (i.e., SSE, AVX2, AVX512). Results show that user-directed codes achieve manually optimized code performance and energy efficiency with minimal code modifications, favoring portability across different SIMD architectures.     

A Survey on Data‐driven Dictionary‐based Methods for 3D Modeling

Dictionaries are very useful objects for data analysis, as they enable a compact representation of large sets of objects through the combination of atoms. Dictionary‐based techniques have also particularly benefited from the recent advances in machine learning, which has allowed for data‐driven algorithms to take advantage of the redundancy in the input dataset and discover relations between objects without human supervision or hard‐coded rules. Despite the success of dictionary‐based techniques on a wide range of tasks in geometric modeling and geometry processing, the literature is missing a principled state‐of‐the‐art of the current knowledge in this field. To fill this gap, we provide in this survey an overview of data‐driven dictionary‐based methods in geometric modeling. We structure our discussion by application domain: surface reconstruction, compression, and synthesis. Contrary to previous surveys, we place special emphasis on dictionary‐based methods suitable for 3D data synthesis, with applications in geometric modeling and design. Our ultimate goal is to enlight the fact that these techniques can be used to combine the data‐driven paradigm with design intent to synthesize new plausible objects with minimal human intervention. This is the main motivation to restrict the scope of the present survey to techniques handling point clouds and meshes, making use of dictionaries whose definition depends on the input data, and enabling shape reconstruction or synthesis through the combination of atoms.