The paper considers stages of the development of studies in computing optimization in Ukraine (in particular, at the V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine) related to el...
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The paper considers stages of the development of studies in computing optimization in Ukraine (in particular, at the V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine) related to elements of error theory, computational algorithms that are optimal in accuracy and time, high-tech computer technologies for solving problems in computational and applied mathematics with given values of quality characteristics.
Content Aware Soft Real Time Media Broadcast (CASoRT) is a new solution for information service of cellular network. As the similar distribution of users interest, the data of same content may be accessed and retransm...
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ISBN:
(纸本)9781467309905;9781467309882
Content Aware Soft Real Time Media Broadcast (CASoRT) is a new solution for information service of cellular network. As the similar distribution of users interest, the data of same content may be accessed and retransmitted frequently in cellular network during certain period of time, which caused the dissipation of both energy and spectrum efficiency. With the development of Data Mining, the CASoRT system could discovers the users common interests and broadcast such content to users who may be interested in. With those users accessing the content locally, the potential retransmission could be avoided and thus it could save energy from carriers view while providing the same real time experience to the users. In this paper, we propose a set of algorithm for the optimization of broadcasting scheme for the CASoRT system to achieve more energy efficiency.
This paper provides algorithms for the optimization of autonomous hybrid systems based on the geometrical properties of switching manifolds. The first and second sections of the paper introduce optimal hybrid control ...
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ISBN:
(纸本)9781467320665
This paper provides algorithms for the optimization of autonomous hybrid systems based on the geometrical properties of switching manifolds. The first and second sections of the paper introduce optimal hybrid control systems and the third section presents the Newton-Geodesic-Hybrid Minimum Principle (HMP) which is an extension of the Gradient Geodesic-HMP algorithm in [4]. In the fourth section, we extend the analysis yielding the Newton-Geodesic-HMP algorithm to relate the difference of the curvatures of the ambient and switching manifolds to second order variations of the hybrid value function. Finally an example is given to illustrate the results.
Transcranial electrical stimulation refers to the transmission of weak electrical currents to the brain through scalp electrodes to induce neuromodulatory effects. Current usually passes through two large electrodes, ...
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ISBN:
(纸本)9798350388084;9798350388077
Transcranial electrical stimulation refers to the transmission of weak electrical currents to the brain through scalp electrodes to induce neuromodulatory effects. Current usually passes through two large electrodes, generating a diffusion electric field. In this article, we propose a new paradigm where multiple small electrodes with independent current control are systematically optimized to generate targeted and effective stimuli under safety constraints. We used finite element method combined with a model based on human head magnetic resonance imaging to develop a linear system that correlates the applied scalp current with the generated electric field. Then apply optimization techniques to derive yield increasing parameters that maximize intensity or focus at the target location. The results indicate that the optimal electrode structure is closely related to the required electric field orientation and optimization criteria. The two optimization methods used have achieved good results.
In this paper, we optimized PSO by quantum behavior and optimized KH by simulated annealing, so a new hybrid algorithm, named Annealing Krill Quantum Particle Swarm optimizationalgorithm (AKQPSO), is proposed, and it...
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In this paper, we optimized PSO by quantum behavior and optimized KH by simulated annealing, so a new hybrid algorithm, named Annealing Krill Quantum Particle Swarm optimizationalgorithm (AKQPSO), is proposed, and it is based on annealing krill herd algorithm (AKH) and quantum particle swarm optimizationalgorithm (QPSO). QPSO has better performance in exploitation and AKH has better performance in exploration, so AKQPSO proposed on this basis increases the diversity of population individuals, and shows better performance in both exploitation and exploration. In addition, the quantum behavior increased the diversity of the population, and the simulated annealing strategy made the algorithm avoid falling into the local optimal value, which made the algorithm obtain better performance. The test set used in this paper is a classic 100 -Digit Challenge problem, which is proposed at 2019 IEEE Congress on Evolutionary Computation (CEC 2019), and AKQPSO has achieved better performance on the benchmark problems.
The computational method of unconstrained optimization problem is an important research topic in the field of numerical computation. It is of great significance to solve the problem of unconstrained optimization. Ther...
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ISBN:
(纸本)9781467382663
The computational method of unconstrained optimization problem is an important research topic in the field of numerical computation. It is of great significance to solve the problem of unconstrained optimization. There are many ways that are applied to settle these questions, so we need to choose a method which owns much fast er and less complex trait. Furthermore, in order to solve this rubs, this paper presents a comparative study of the common algorithms and our approach which are used to handle some concrete unconstrained optimization problems.
With the introduction of many new features of 5g and the gradual promotion of 5g test and pre commercial plan, the 5g oriented bearer network architecture and technical solution have become the focus of the industry. ...
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ISBN:
(数字)9781665458641
ISBN:
(纸本)9781665458641
With the introduction of many new features of 5g and the gradual promotion of 5g test and pre commercial plan, the 5g oriented bearer network architecture and technical solution have become the focus of the industry. Correspondingly, the management and control technology of the bearer network has also appeared many new features. 5g network involves wireless, core network and bearer network, and supports a variety of network application scenarios at the same time. It is the basic demand of 5g bearer network collaborative management and control to realize end-to-end network and business collaboration through SDN architecture and improve the automatic opening and deployment of services and intelligent operation and maintenance capabilities. This paper proposes a multi-path routing optimizationalgorithm based on 5g + Sdn. Compared with traditional algorithms, the optimizationalgorithm has obvious improvement in cost, energy consumption awareness and load balancing.
This paper implements the self-collision detection optimization during the clothes simulation, including the high-level and low-level tailoring optimization. During the high-level tailoring stage, this paper firstly i...
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ISBN:
(数字)9789811026669
ISBN:
(纸本)9789811026669;9789811026652
This paper implements the self-collision detection optimization during the clothes simulation, including the high-level and low-level tailoring optimization. During the high-level tailoring stage, this paper firstly implements the basic high-level tailoring in combination with the hierarchical bounding box algorithm and continuous normal vector cone information. On this basis, this paper implements the high-level tailoring optimization based on the radiation angle. Finally, this paper implements the high-level tailoring optimization based on the isolated set. During the low-level tailoring stage, this paper firstly implements the low-level tailoring optimization based on the characteristic distribution. In addition, this paper also implements the low-level tailoring optimization based on the non-coplanar filter. Experiment result shows that the two level tailoring optimization method in this paper can effectively cut off the redundant and non-collision primitive pair and further improve the efficiency of self-collision detection.
Myoelectric control refers to the use of processed Electromyogram (EMG) signals in the operation of devices external to the human body. It finds numerous applications requiring good precision, quick response, design f...
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ISBN:
(纸本)0780382781
Myoelectric control refers to the use of processed Electromyogram (EMG) signals in the operation of devices external to the human body. It finds numerous applications requiring good precision, quick response, design flexibility and ease in control. A variety of myoelectric controller algorithms exist, but there is immense scope for optimization. This paper proposes an intelligent system which is capable of optimizing the system speed and the number of actions that can be selected. Such an optimization involves rigorous mathematical analysis of the characteristics and the inter-dependence of these two parameters. The intelligent systems employ a technique to continuously monitor the actions that are performed. Accordingly, they allocate the least selection duration to those actions that are executed the most number of times. This process has been termed as self-preferential time allocation and is achieved by a combination of spatial and temporal coding. Here, the temporal priorities are reassigned preferentially to spatially coded signals. Such systems that employ self-preferential time allocation eliminate the need for constant re-programming and the design of individually programmed myoelectric controllers. The introduction of a scaling factor also induces intelligence to the system, resulting in fast, flexible and self-regulating myoelectric controllers.
Investigation of hash join algorithm on multicore and many-core platforms showed that carefully tuned hash join implementations could outperform simple hash joins on most multi-core servers. However, hardware-obliviou...
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ISBN:
(纸本)9781728143972
Investigation of hash join algorithm on multicore and many-core platforms showed that carefully tuned hash join implementations could outperform simple hash joins on most multi-core servers. However, hardware-oblivious hash join has shown competitive performance on many-core platforms. Knights Landing (KNL) has received attention in the field of parallel computing for its massively data-parallel nature and high memory bandwidth, but both hardware-oblivious and hardware-conscious hash join algorithms have not been systematically discussed and evaluated for KNL's characteristics (high bandwidth, cluster mode, etc.). In this paper, we present the design and implementation of the state-of-the-art hardware-oblivious and hardware-conscious hash joins that are tuned to exploit various KNL hardware characteristics. Using a thorough evaluation, we show that:1) Memory allocation strategies based on KNL's architecture are effective for both hardware-oblivious and hardware-conscious hash join algorithms;2) In order to improve the efficiency of the hash join algorithms, hardware architecture features are still non-negligible factors.
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