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Given the significant industrial growth of demand for virtual reality (VR), 360º video streaming is one of the most important VR applications that require cost-optimal solutions to achieve widespread proliferation of VR technology. Because of its inherent variability of data-intensive content types and its tiled-based encoding and streaming, 360º video requires new encoding ladders in adaptive streaming...
With the recent proliferation of the Internet-of-Things (IoT) devices, coupled with the expected massive growth in the deployment of such devices, the 3GPP Specifications continued to evolve to address the performance needs and the cost/complexity reduction requirements of these IoT devices, achieved through the introduction of new features and new User Equipment (UE) categories. These features will...
Evolution-in-materio is a form of unconventional computing combining materials' training and evolutionary search algorithms. In previous work, a mixture of single-walled-carbon-nanotubes (SWCNTs) dispersed in a liquid crystal (LC) was trained so that its morphology and electrical properties were gradually changed to perform a computational task. Material-based computation is treated as an optimisation...
We develop several efficient algorithms for the classical Matrix Scaling} problem, which is used in many diverse areas, from preconditioning linear systems to approximation of the permanent. On an input n× n matrix A, this problem asks to find diagonal (scaling) matrices X and Y (if they exist), so that X A Y ε-approximates a doubly stochastic matrix, or more generally a matrix...
Object tracking configuration is a tedious task for users due to an overwhelming amount of parameters while solving a multicriterial optimisation problem for a black box. With increasing complexity of the algorithms and fast changing situations due to the upcoming fourth industrial revolution, even experts will find themselves struggling with this topic. For this reason we present a concept for an...
In order to reduce the effect of pilot contamination and maximize the system sum rate while guaranteeing the fairness among users, an efficient and fair pilot allocation scheme is proposed for multi-cell massive MIMO systems in this work. The pilot allocation optimization problem is formulated to maximize the sum rate of the system while guaranteeing the fairness among users. A heuristic algorithm,...
Exponential increase and global access to read/write memory states in quantum computing simulation limit both the number of qubits and quantum transformations that can be currently simulated. Although quantum computing simulation is parallel by nature, spatial and temporal complexity are major performance hazards, making this an important application for HPC. A new methodology employing reduction...
As the emerging development of IoT circumstance, on-line detections or observations of a system states become easier by facilitating its corresponding multi-sensory responses, and thus the description of a system behavior becomes clearer. Abundant on-line multi-channel information from the embedded sensors would be advantageous to the understanding of the system. Though having the information, it...
In this paper a Markov decision process (MDP) model for virtualized content delivery networks is proposed. We use stochastic optimization to assign cloud site resources to each user group. We propose how quality of experience (QoE) can be included in the modeling and optimization. We then present an optimal solution for a constraint-free version of the problem, and show the improvement in accumulated...
Empowering a person automatically leads to the need for decision-making or, in other words, the need to optimize their activities — to exclude mistakes in decision-making, or at least to minimize them. At present, the process of optimization itself is bringing the system to the optimal (best) or, profitable solution. Synthesis of methods of system analysis and optimization is one of the best ways...
This paper mainly presents a design of optimized (15, 4) parallel counter. When testing the design with 15 rows of inputs, synthesis report of our design performs better in respect of delay, area and power consumption than other two existing design. This result shows that processes such as partial product reduction in a multiplier or column-addition in a matrix could be more efficient, especially...
Discriminative clustering has been successfully applied to a number of weakly supervised learning tasks. Such applications include person and action recognition, text-to-video alignment, object co-segmentation and co-localization in videos and images. One drawback of discriminative clustering, however, is its limited scalability. We address this issue and propose an online optimization algorithm based...
In the area of applied optimisation, heuristics are a popular means to address computational problems of high complexity. Modelling the problem and mapping all variations of its solution into a so-called solution space are integral parts of this process. Representing solutions as graphs is common and, for a special type of graph, Prüfer Code (PC) offers a computationally efficient mapping (algorithms...
Increased complexity of computer hardware makes close to impossible to rely on hand-coding at the-level of HDLs for digital hardware design. High-level synthesis can be employed instead, in order to automatically obtain HDL codes from highlevel language functional descriptions. With high-level synthesis it becomes easier to design coprocessors, accelerators, and other special-purpose hardware. Nonetheless,...
Various methods of identifying cellular automaton models and their state transition functions, in particular, have been proposed. Among these, a method that uses ℓ1-norm optimization can be applied to multi-valued cellular automaton models. When solving this optimization problem, it is important to reduce the computational cost as the size of the problem increases. In this paper, we present a method...
In this paper a circuit-oriented approximate solution to an explicit nonlinear Model Predictive Control (NMPC) problem is proposed, based on piecewise-affine functions defined over simplicial domain partitions. The resulting controller is suitable for circuit implementation in programmable devices, such as microcontrollers or FPGA, enabling the application of NMPC to systems with low sampling times...
A novel projection twin support vector machine (PTSVM), termed as NPTSVM, is presented in this paper for binary classification. Although this method determines two projection vectors using the same way as PTSVM, it has more advantages than existing PTSVMs. First, NPTSVM does not have to calculate inverse matrices during the learning process, which makes the training speed of NPTSVM be much faster...
This paper investigates the problem of visual analysis of complex plans, schemes and maps for solving of difficult formalized tasks. It is analyzed the dependence of the level of perception upon the visualization complexity. It is introduced the concept of the utility of the visual image, it is described by the behavior of the empirical utility function. We propose an optimization model of the utility,...
The widespread use of graphs to model large scale real-world data brings with it the need for fast graph analytics. In this paper, we explore the problem of triangle counting, a fundamental graph-analytic operation, on shared-memory platforms. Existing triangle counting implementations do not effectively utilize the key characteristics of large sparse graphs for tuning their algorithms for performance...
The complexity and diversity of today's computer architectures are requiring more attention from the software developers in order to harness all the computing power available. Furthermore, each different modern architecture requires a potentially non-overlapping set of optimizations to attain a higher fraction of its nominal peak speed. This leads to challenges about performance portability and code...
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