Performance of dynamic texture segmentation using GPU

This work is focused on the assessment of the use of GPU computation in dynamic texture segmentation under the mixture of dynamic textures (MDT) model. In this generative video model, the observed texture is a time-varying process commanded by a hidden state process. The use of mixtures in this model allows simultaneously handling of different visual processes. Nowadays, the use of GPU computing is growing in high-performance applications, but the adaptation of existing algorithms in such a way as to obtain a benefit from its use is not an easy task. In this paper, we made two implementations, one in CPU and the other in GPU, of a known segmentation algorithm based on MDT. In the MDT algorithm, there is a matrix inversion process that is highly demanding in terms of computing power. We make a comparison between the gain in performance obtained by porting to GPU this matrix inversion process and the gain obtained by porting to GPU the whole MDT segmentation process. We also study real-time motion segmentation performance by separating the learning part of the algorithm from the segmentation part, leaving the learning stage as an off-line process and keeping the segmentation as an online process. The results of performance analyses allow us to decide the cases in which the full GPU implementation of the motion segmentation process is worthwhile.     

Real‐Time Isosurface Extraction With View‐Dependent Level of Detail and Applications

Volumetric scalar data sets are common in many scientific, engineering and medical applications where they originate from measurements or simulations. Furthermore, they can represent geometric scene content, e.g. as distance or density fields. Often isosurfaces are extracted, either for indirect volume visualization in the former category, or to simply obtain a polygonal representation in case of the latter. However, even moderately sized volume data sets can result in complex isosurfaces which are challenging to recompute in real time, e.g. when the user modifies the isovalue or when the data itself are dynamic. In this paper, we present a GPU‐friendly algorithm for the extraction of isosurfaces, which provides adaptive level of detail rendering with view‐dependent tessellation. It is based on a longest edge bisection scheme where the resulting tetrahedral cells are subdivided into four hexahedra, which then form the domain for the subsequent isosurface extraction step. Our algorithm generates meshes with good triangle quality even for highly non‐linear scalar data. In contrast to previous methods, it does not require any stitching between regions of different levels of detail. As all computation is performed at run time and no pre‐processing is required, the algorithm naturally supports dynamic data and allows us to change isovalues at any time.     

Industrial assay to assess the efficiency of vacuum pressure impregnation to eliminate the pinewood nematode from wood

An assay using the full-cell method in an industrial autoclave was performed to evaluate the efficiency of vacuum pressure impregnation treatment with a commercial wood preservative product to eliminate the pinewood nematode, Bursaphelenchus xylophilus, from infected Pinus pinaster wood trunks and sections. After treatment and wood incubation, no live nematodes were detected in the treated trunks and sections. This treatment revealed to be a good way to eliminate nematodes from wood and to reduce the risk of pinewood nematode dissemination.     

A 2.4 GHz high-performance CMOS differential quadrature relaxation oscillator

In this paper, the effects that limit the performance of practical implementations of RC relaxation oscillators are investigated. The insights gained are used to suggest a topology for high-frequency quadrature relaxation oscillators with closer-to-optimal performance. The proposed oscillator uses a modified latch to improve the switching speed without increasing the power consumption. Moreover, the new topology avoids static current sources, maximizes the voltage swing and has an active coupling structure without static power consumption that reduces the circuit phase-noise. Experimental results show that the oscillator operates in relaxation mode at 2.4 GHz and achieves a FoM of \(\mathrm {-162\,dBc/Hz}\), which is, as far as the authors know, the best FoM for relaxation oscillators operating in the GHz range.     

Satisfaction and switching intention in mobile services: Comparing lock-in and free contracts in the Spanish market

Switching costs are a relevant issue affecting market competition in the mobile services industry. However, customer switching costs have not disappeared, since numerous leading mobile services companies use lock-in strategies, such as obliged long-term contractual relationships. The present study provides and empirically test a conceptual model in order to analyze the creation of customer satisfaction and switching intention with mobile services, as well as to examine the differences between lock-in and free contracts in a South European mature market – Spain. For this purpose, drawing on a sample of 370 customers, we developed Structural Equation Modeling (SEM) through a multi-group analysis. Our findings suggest that service quality is one of the key determinants of satisfaction, while the availability of attractive alternatives is the main switching barrier. Moreover, some interesting differences were found between the two type of contracts analyzed. Consequently, we suggest shifting resources to customer retention through improved service quality for reducing customer churn rate.     

Optimizing a bi‐objective vehicle routing problem that appears in industrial enterprises

In this paper, a new solution method is implemented to solve a bi‐objective variant of the vehicle routing problem that appears in industry and environmental enterprises. The solution involves designing a set of routes for each day in a period, in which the service frequency is a decision variable. The proposed algorithm, a muti‐start multi‐objective local search algorithm (MSMLS), minimizes total emissions produced by all vehicles and maximizes the service quality measured as the number of times that a customer is visited by a vehicle in order to be served. The MSMLS is a neighbourhood‐based metaheuristic that obtains high‐quality solutions and that is capable of achieving better performance than other competitive algorithms. Furthermore, the proposed algorithm is able to perform rapid movements thanks to the easy representation of the solutions.     

Adaptive dialogue management using intent clustering and fuzzy rules

Conversational systems have become an element of everyday life for billions of users who use speech‐based interfaces to services, engage with personal digital assistants on smartphones, social media chatbots, or smart speakers. One of the most complex tasks in the development of these systems is to design the dialogue model, the logic that provided a user input selects the next answer. The dialogue model must also consider mechanisms to adapt the response of the system and the interaction style according to different groups and user profiles. Rule‐based systems are difficult to adapt to phenomena that were not taken into consideration at design‐time. However, many of the systems that are commercially available are based on rules, and so are the most widespread tools for the development of chatbots and speech interfaces. In this article, we present a proposal to: (a) automatically generate the dialogue rules from a dialogue corpus through the use of evolving algorithms, (b) adapt the rules according to the detected user intention. We have evaluated our proposal with several conversational systems of different application domains, from which our approach provided an efficient way for adapting a set of dialogue rules considering user utterance clusters.     

The 2D wavelet transform on emerging architectures: GPUs and multicores

Because of the computational power of today??s GPUs, they are starting to be harnessed more and more to help out CPUs on high-performance computing. In addition, an increasing number of today??s state-of-the-art supercomputers include commodity GPUs to bring us unprecedented levels of performance in terms of raw GFLOPS and GFLOPS/cost. In this work, we present a GPU implementation of an image processing application of growing popularity: The 2D fast wavelet transform (2D-FWT). Based on a pair of Quadrature Mirror Filters, a complete set of application-specific optimizations are developed from a CUDA perspective to achieve outstanding factor gains over a highly optimized version of 2D-FWT run in the CPU. An alternative approach based on the Lifting Scheme is also described in Franco et al. (Acceleration of the 2D wavelet transform for CUDA-enabled Devices, 2010). Then, we investigate hardware improvements like multicores on the CPU side, and exploit them at thread-level parallelism using the OpenMP API and pthreads . Overall, the GPU exhibits better scalability and parallel performance on large-scale images to become a solid alternative for computing the 2D-FWT versus those thread-level methods run on emerging multicore architectures.