An architecture for stereo image matching

Calcium signals have been implicated in the regulation of many diverse cellular processes. The problem of how information from extracellular signals is delivered with specificity and fidelity using fluctuations in cytosolic Ca2+ concentration remains unresolved. The capacity of cells to generate Ca2+ signals of sufficient spatial and temporal complexity is the primary constraint on their ability to effectively encode information through Ca2+. Over the past decade, a large body of literature has dealt with some basic features of Ca2+-handling in cells, as well as the multiplicity and functional diversity of intracellular Ca2+ stores and extracellular Ca2+ influx pathways. In principle, physiologists now have the necessary information to attack the problem of function- and agonist-specificity in Ca2+ signal transduction. This review explores the data indicating that Ca2+ release from diverse sources, including many types of intracellular stores, generates Ca2+ signals with sufficient complexity to regulate the vast number of cellular functions that have been reported as Ca2+-dependent. Some examples where such complexity may relate to neuroendocrine regulation of hormone secretion/synthesis are discussed. We show that the functional and spatial heterogeneity of Ca2+ stores generates Ca2+ signals with sufficient spatiotemporal complexity to simultaneously control multiple Ca2+-dependent cellular functions in neuroendocrine systems.

Calcium signals have been implicated in the regulation of many diverse cellular processes. The problem of how information from extracellular signals is delivered with specificity and fidelity using fluctuations in cytosolic Ca2+ concentration remains unresolved. The capacity of cells to generate Ca2+ signals of sufficient spatial and temporal complexity is the primary constraint on their ability to effectively encode information through Ca2+. Over the past decade, a large body of literature has dealt with some basic features of Ca2+-handling in cells, as well as the multiplicity and functional diversity of intracellular Ca2+ stores and extracellular Ca2+ influx pathways. In principle, physiologists now have the necessary information to attack the problem of function- and agonist-specificity in Ca2+ signal transduction. This review explores the data indicating that Ca2+ release from diverse sources, including many types of intracellular stores, generates Ca2+ signals with sufficient complexity to regulate the vast number of cellular functions that have been reported as Ca2+-dependent. Some examples where such complexity may relate to neuroendocrine regulation of hormone secretion/synthesis are discussed. We show that the functional and spatial heterogeneity of Ca2+ stores generates Ca2+ signals with sufficient spatiotemporal complexity to simultaneously control multiple Ca2+-dependent cellular functions in neuroendocrine systems.

Since the definition of attribute reduction based on classic discernibility matrix is different from the definition of attribute reduction based on positive region, simplified discernibility matrix and the corresponding definition of attribute reduction are proposed. At the same time, it is proved that the proposed definition of attribute reduction is identical to the definition of attribution reduction based on positive region. For computing simplified discernibility matrix, IND(C) should usually be calculated at first, so a new algorithm for computing IND(C) is designed, whose temporal complexity is cut down to O(|C||U|). Furthermore, an efficient attribute reduction algorithm is proposed, whose temporal complexity and spatial complexity are cut down to \(\max(O(|C|^2|U'_{pos}||U'|, O(|U||C|))\) and max (O(|C||U′ pos ||U′|, O(|U|)) respectively. At last, an example is used to illustrate the efficiency of the new algorithms.KeywordsRough setdiscernibility matrixsimplified discernibility matrixattribute reductioncomplexity

Geographic and temporal patterns in white spruce climate–growth relationships in Yukon, Canada

Multimedia content consumption is very popular nowadays. However, not every content can be consumed in its original format: the combination of content, transport and access networks, consumption device and usage environment characteristics may all pose restrictions to that purpose. One way to provide the best possible quality to the user is to adapt the content according to these restrictions as well as user preferences. This adaptation stage can be best executed if knowledge about the content is known a-priori. In order to provide this knowledge we classify the content based on metrics to define its temporal and spatial complexity. The temporal complexity classification is based on the Motion Vectors of the predictive encoded frames and on the difference between frames. The spatial complexity classification is based on different implementations of an edge detection algorithm and an image activity measure.

The increasing demand for high-quality and low-cost video streaming services calls for the prediction of video encoding complexity. The prior prediction of video encoding complexity including encoding time and bitrate predictions are used to allocate resources and set optimized parameters for video encoding effectively. In this paper, a light-weight video encoding complexity prediction (VECP) scheme that predicts the encoding bitrate and the encoding time of video with high accuracy is proposed. Firstly, low-complexity Discrete Cosine Transform (DCT)-energy-based features, namely spatial complexity, temporal complexity, and brightness of videos are extracted, which can efficiently represent the encoding complexity of videos. The latent vectors are also extracted from a Convolutional Neural Network (CNN) with MobileNet as the backend to obtain additional features from representative frames of each video to assist the prediction process. The extreme gradient boosting (XGBoost) regression algorithm is deployed to predict video encoding complexity using the extracted features. The experimental results demonstrate that VECP predicts the encoding bitrate with an error percentage of up to 3.47% and encoding time with an error percentage of up to 2.89%, but with a significantly low overall latency of 3.5 milliseconds per frame which makes it suitable for both Video on Demand (VoD) and live streaming applications.

This article addresses the problem of finding the shortest route for Automated Guided Vehicles (AGVs) in a production environment with constrained battery state-of-charge (SoC) and time-dependent operating conditions. The route map is divided into a uniform grid containing stationary obstacles and two types of dynamic obstacles: human, for which AGV transportation is prohibited, and inanimate (moving objects), which impose a penalty function. A key contribution of the proposed methodology is the introduction of a battery residual charge matrix, which embeds cell-level energy feasibility into the environment representation by determining minimum admissible SoC constraints and accounting for transition-dependent energy costs. This matrix directly restricts the set of traversable cells under low-energy conditions. The proposed approach is based on the A* and D* Lite algorithms, providing shortest-path construction that explicitly integrates battery SoC into the spatio-temporal cost function. To avoid collisions in a multi-agent environment during routing, a simplified hybrid scheme with M* elements performs local coordination and adaptive trajectory replanning. The effectiveness of the proposed methodology was assessed using travel time, temporal complexity, and spatial complexity metrics. Simulation results on a 10×10 grid showed that agents with sufficient battery completed routes of 8 and 11 cells with travel times of 7.2 to 10.7 conventional units. A critically low-energy agent was initially unable to move, but after adjusting the minimum SoC constraint, all agents completed their routes with travel times up to 11.4 conventional units, demonstrating the direct impact of energy constraints on system performance.

We introduce the concept of spatial and temporal complexity with emphasis on how its fractal characterization for 1D, 2D or 3D hemodynamic brain signals can be carried out. Using high-resolution experimental data sets acquired in animal and human brain by noninvasive methods - such as laser Doppler flowmetry, laser speckle, near infrared, or functional magnetic resonance imaging - the spatiotemporal complexity of cerebral hemodynamics is demonstrated. It is characterized by spontaneous, seemingly random (that is disorderly) fluctuation of the hemodynamic signals. Fractal analysis, however, proved that these fluctuations are correlated according to the special order of self-similarity. The degree of correlation can be assessed quantitatively either in the temporal or the frequency domain respectively by the Hurst exponent (H) and the spectral index (beta). The values of H for parenchymal regions of white and gray matter of the rat brain cortex are distinctly different. In human studies, the values of beta were instrumental in identifying age-related stiffening of cerebral vasculature and their potential vulnerability in watershed areas of the brain cortex such as in borderline regions between frontal and temporal lobes. Biological complexity seems to be present within a restricted range of H or beta values which may have medical significance because outlying values can indicate a state of pathology.

This paper is dedicated to the analysis of the existing approaches to video codecs comparisons. It includes the revealed drawbacks of popular comparison methods and proposes new techniques. The performed analysis of user-generated videos collection showed that two of the most popular open video collections from media.xiph.org which are widely used for video-codecs analysis and development do not cover real-life videos complexity distribution. A method for creating representative video sets covering all segments of user videos the spatial and temporal complexity is also proposed. One of the sections discusses video quality estimation algorithms used for video codec comparisons and shows the disadvantages of popular methods VMAF and NIQE. Also, the paper describes the drawbacks of the BD-rate – generally used method for video codecs final ranking during comparisons. A new ranking method called BSQ-rate which considers the identified issues is proposed. The results of this investigation were obtained during the series of research conducted as part of the annual video-codecs comparisons organized by video group of computer graphics and multimedia laboratory at Moscow State University.

SUMMARY We present new dedicated core surface field models spanning the decade from 2000.0 to 2010.0. These models, called gufm-sat, are based on CHAMP, Orsted and SAC-C satellite observations along with annual differences of processed observatory monthly means. A spatial parametrization of spherical harmonics up to degree and order 24 and a temporal parametrization of sixth-order B-splines with 0.25 yr knot spacing is employed. Models were constructed by minimizing an absolute deviation measure of misfit along with measures of spatial and temporal complexity at the core surface. We investigate traditional quadratic or maximum entropy regularization in space, and second or third time derivative regularization in time. Entropy regularization allows the construction of models with approximately constant spectral slope at the core surface, avoiding both the divergence characteristic of the crustal field and the unrealistic rapid decay typical of quadratic regularization at degrees above 12. We describe in detail aspects of the models that are relevant to core dynamics. Secular variation and secular acceleration are found to be of lower amplitude under the Pacific hemisphere where the core field is weaker. Rapid field evolution is observed under the eastern Indian Ocean associated with the growth and drift of an intense low latitude flux patch. We also find that the present axial dipole decay arises from a combination of subtle changes in the southern hemisphere field morphology.

Kootenay Lake is a large (over 392 km2) fjord-type lake, part of the upper Columbia River Basin, which has undergone significant limnological changes due to a range of human activities over the past half century. We analyzed the limnological conditions of the lake during the mid 1960s, prior to major dam construction on its main tributaries. At that time, large volumes (25.4 km3 yr−1) of highly turbid (up to 180 JTU) but anthropogenically phosphate-enriched water entered the south end via the Kootenay River. This interacted with smaller volumes of less turbid and much lower nutrient waters entering from the Duncan River in the north and lateral lake drainages (15.6 and 9.8 km3 yr−1 respectively) to produce complex spatial and temporal differences in physical and chemical features (temperature, light penetration, ionic composition, pH, dissolved oxygen and nutrients) as well as in phytoplankton biomass, productivity and taxonomic composition. In the southern part of the lake, phytoplankton biomass, cell density and 14C uptake rates were severely depressed during late spring and summer by light limitation from incoming silt turbidity, in spite of high phosphate concentrations. In contrast, phytoplankton stock and production was elevated in the middle to northern parts where transparency was high. Experimental algal bioassays using filtered lake waters demonstrated that through this period nutrient (primarily phosphorus) limitation occurred in the northern but not in the southern parts of Kootenay Lake. Watershed impoundments during the 1970s homogenized and simplified this ecosystem. On-going efforts to rebuild fisheries through restoration of the pre-dam nutrient loading may not return Kootenay Lake to the spatial and temporal complexity that once existed.

For health and human services, fraud detection and other security services, identity resolution is a core requirement for understanding big data in the cloud. Due to the lack of a globally unique identifier and captured typographic differences for the same identity, identity resolution has high spatial and temporal complexities. We propose a filter and verify method to substantially increase the speed of approximate string matching using edit distance. This method has been found to be almost 80 times faster (130 times when combined with other optimizations) than Damerau-Levenshtein edit distance and preserves all approximate matches. Our method creates compressed signatures for data fields and uses Boolean operations and an enhanced bit counter to quickly compare the distance between the fields. This method is intended to be applied to data records whose fields contain relatively short-length strings, such as those found in most demographic data. Without loss of accuracy, the proposed Fast Bitwise Filter will provide substantial performance gain to approximate string comparison in database, record linkage and deduplication data processing systems.

For applications involving video streaming, full decoding is usually not acceptable for quality assessment. To address the inherent challenges, an efficient method for coding distortion assessment is proposed in this paper. Building on empirical analysis, the proposed method employs a linear model to assess the coding distortion using the quantization scale. Furthermore, the characteristics of the human visual system are exploited by taking into account the spatial and temporal masking. To estimate the required spatial and temporal complexities in absence of sufficient information, a rate-distortion model is theoretically derived to formulate their relationship with the coding bit-rate. Extensive experimental results have demonstrated the effectiveness of the proposed method for quality assessment with respect to perceived coding distortion.

In this paper we present several schemes for solving the inverse problem in Optical Tomography. We first set the context of Optical Tomography and discuss alternative photon transport models and measurement schemes. We develop the inverse problem as the optimisation of an objective functions and develop three classes of algorithms fors its solution: Newton methods, linearised methods, and gradient methods. We concentrate on the use numerical methods based on Finite Elements, and discuss how efficient methods may be developed using adjoint solutions. A taxonomy of algorithms is given, with an analysis of their spatial and temporal complexity.

The cortical network subserving language processing is likely to exhibit a high spatial and temporal complexity. Studies using brain imaging methods, like fMRI or PET, succeeded in identifying a number of brain structures that seem to contribute to the processing of syntactic structures, while their dynamic interaction remains unclear due to the low temporal resolution of the methods. On the other hand, ERP studies have revealed a great deal of the temporal dimension of language processing without being able to provide more than very coarse information on the localisation of the underlying generators. MEG has a temporal resolution similar to EEG combined with a better spatial resolution. In this paper, Brain Surface Current Density (BSCD) mapping in a standard brain model was used to identify statistically significant differences between the activity of certain brain regions due to syntactically correct and incorrect auditory language input. The results show that the activity in the first 600 ms after violation onset is mainly concentrated in the temporal cortex and the adjacent frontal and parietal areas of both hemispheres. The statistical analysis reveals significantly different activity mainly in both frontal and temporal cortices. For longer latencies above 250 ms, the differential activity is more prominent in the right hemisphere. These findings confirm other recent results that suggest right hemisphere involvement in auditory language processing. One interpretation might be that right hemisphere regions play an important role in repair and re-analysis processes in order to free the specialised left hemisphere language areas for processing further input.