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- 2019
- low-temperature electronics
- class AB operation
- optimization of analog electronic circuit
- operational amplifier
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- Don State Technical University
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Brain Storm Optimization Graph Theory (BSOGT) and Energy Resource Aware Virtual Network Mapping (ERVNM) for Medical Image System in Cloud
摘要： With the development of Internet and the make use of Internet for medical information, the demand for huge scale and reliable managing medical information has brought out the huge scale Internet data centers. This work that has been presented here highlights the structural lay out and formulation of the medical information model. The aim of presenting this to aid medical departments as well as workers to exchange information and integrate available resources that help facilitate the analysis to be conducted on the given information. Software here comprises of medical information and offers a comprehensive service structure that benefits medical data centers. VNM or Virtual Network Mapping (VNM) essentially relates to substrate network that involves the installation and structuring of on demand virtual machines. These however are subjective to certain limitations that are applicable in relation to latency, capacity as well as bandwidth. Data centers need to dynamically handle cloud workloads effectively and efficiently. Simultaneously, since the mapping of virtual and physical networks with several providers’ consumes more time along with energy. In order to resolve this issue, VNM has been mapped by making use of Graph Theory (GT) matching, a well-studied database topic. (i) Brain Storm Optimization Graph Theory (BSOGT) is introduced for modeling a virtual network request in the form of a GT with different resource constraints, and the substrate networks here is considered being a graph. For this graph the nodes and edges comprise of attributes that indicate their constraints. (ii) The algorithm that has been recently introduced executes graph decomposition into several topology patterns. Thereafter the BSOGT is executed to solve any issues that pertain to mapping. (iii) The model that has been presented here, ERVNM and the BSOGT are used with a specific mapping energy computation function.(iv) Issues pertaining to these are categorized as being those related to virtual network mapping as the ACGT and optimal solution are drawn by using effective integer linear programming. ACGT, pragmatic approach, as well as the precise and two-stage algorithms performance is evaluated by means of cloud Simulator environment. The results obtained from simulation indicate that the BSOGT algorithm attains the objectives of cloud service providers with respect to Acceptance ratio, mapping percentage, processing time as well as Convergence Time.
关键词： Virtual Network Mapping (VNM),Distributed cloud computing and optimization,Virtualization quality of services (Qos),Brain Storm Optimization Graph Theory (BSOGT)
更新于2025-09-23 15:22:29
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Hybrid Beamforming for Millimeter Wave Systems Using the MMSE Criterion
摘要： Hybrid analog and digital beamforming (HBF) has recently emerged as an attractive technique for millimeter-wave (mmWave) communication systems. It well balances the demand for sufficient beamforming gains to overcome the propagation loss and the desire to reduce the hardware cost and power consumption. In this paper, the mean square error (MSE) is chosen as the performance metric to characterize the transmission reliability. Using the minimum sum-MSE criterion, we investigate the HBF design for broadband mmWave transmissions. To overcome the difficulty of solving the multi-variable design problem, the alternating minimization method is adopted to optimize the hybrid transmit and receive beamformers alternatively. Specifically, a manifold optimization based HBF algorithm is firstly proposed, which directly handles the constant modulus constraint of the analog component. Its convergence is then proved. To reduce the computational complexity, we then propose a low-complexity general eigenvalue decomposition based HBF algorithm in the narrowband scenario and three algorithms via the eigenvalue decomposition and orthogonal matching pursuit methods in the broadband scenario. A particular innovation in our proposed alternating minimization algorithms is a carefully designed initialization method, which leads to faster convergence. Furthermore, we extend the sum-MSE based design to that with weighted sum-MSE, which is then connected to the spectral efficiency based design. Simulation results show that the proposed HBF algorithms achieve significant performance improvement over existing ones, and perform close to full-digital beamforming.
关键词： Minimum mean square error (MMSE),Alternating optimization,Manifold optimization (MO),Hybrid analog and digital beamforming (HBF),Millimeter-wave (mmWave) communications
更新于2025-09-23 15:22:29
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[IEEE 2018 International Conference and Exposition on Electrical And Power Engineering (EPE) - Iasi (2018.10.18-2018.10.19)] 2018 International Conference and Exposition on Electrical And Power Engineering (EPE) - Metaheuristic Algorithms based Multi-objective Optimization for Image Segmentation
摘要： In this paper a multi-threshold image segmentation procedure based on nature-inspired multi-objective optimization is proposed. The Particle Swarm Optimization, Black Hole and Gravitational Search algorithms were adapted for multi-objective optimization. The Root Mean Square Error and the number of segmented regions were used as optimization criteria. The three procedures were applied for human silhouettes detection in video sequences and the obtained results are compared. Concerning the algorithms performances, the experiments revealed that the results of multi-objective Black Hole algorithm based segmentation are better than those of the other two algorithms, at least for the test images used in this experiment.
关键词： nature-inspired algorithms,human locomotion,video processing,multi-objective optimization
更新于2025-09-23 15:22:29
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - An Interior Point Method for Nonnegative Sparse Signal Reconstruction
摘要： We present a primal-dual interior point method (IPM) with a novel preconditioner to solve the (cid:96)1-norm regularized least square problem for nonnegative sparse signal reconstruction. IPM is a second-order method that uses both gradient and Hessian information to compute effective search directions and achieve super-linear convergence rates. It therefore requires many fewer iterations than first-order methods such as iterative shrinkage/thresholding algorithms (ISTA) that only achieve sub-linear convergence rates. However, each iteration of IPM is more expensive than in ISTA because it needs to evaluate an inverse of a Hessian matrix to compute the Newton direction. We propose to approximate each Hessian matrix by a diagonal matrix plus a rank-one matrix. This approximation matrix is easily invertible using the Sherman-Morrison formula, and is used as a novel preconditioner in a preconditioned conjugate gradient method to compute a truncated Newton direction. We demonstrate the efficiency of our algorithm in compressive 3D volumetric image reconstruction. Numerical experiments show favorable results of our method in comparison with previous interior point based and iterative shrinkage/thresholding based algorithms.
关键词： nonnegative sparse,3d volumetric image reconstruction,primal-dual preconditioned interior point method,(cid:96)1-norm regularized optimization,compressive sensing
更新于2025-09-23 15:22:29
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Design of a distributed compliant mechanism using spring-lever model and topology optimization for piezoelectrically actuated flapping wings
摘要： We present a distributed compliant mechanism, which acts like a transmission between a flapping wing of a micro air vehicle and a laminated piezoelectric actuator. The piezoelectric bimorph actuator is connected in cantilever configuration with the compliant mechanism at its free end. The mechanism takes translational deflection at its input from the piezoelectric actuator to provide angular deflection at its output, which causes flapping. We used spring-lever model and topology optimization to obtain the design of the mechanism. The design of the mechanism has been finalized by analyzing the design considering beam model with geometric nonlinearity. The final mechanism is a planar structure of 1 mm thickness and 40 mm × 24 mm in-plane footprint. The input stiffness of the compliant mechanism is 711 N/m and the output torsional stiffness is 0.014 Nm/rad. The compliant mechanism is tested with a piezoelectric bimorph actuator. The mechanism takes ±1 mm deflection with ±0.2 N block force at 30 Hz as an input and produces ±6° flap angle at 30 Hz as an output. The first fundamental frequency of the mechanism is 391 Hz, which is almost 13 times greater than our assumed wing flapping frequency 30 Hz. The final mechanism is prototyped with a 3D printer using VeroWhitePlus RGD835 material and tested with a piezoelectric bimorph actuator using a bench-top experimental set-up.
关键词： Mechanism,flapping,piezo-actuated flapping mechanism,flapping wing micro air vehicle,spring-lever model,distributed compliant mechanism,topology optimization
更新于2025-09-23 15:22:29
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[IEEE 2018 International Conference on Microwave and Millimeter Wave Technology (ICMMT) - Chengdu, China (2018.5.7-2018.5.11)] 2018 International Conference on Microwave and Millimeter Wave Technology (ICMMT) - Grating Lobe Suppression of Planar Array with Large Inter-Element Spacing by Using Genetic Algorithm
摘要： In this paper, a method using genetic algorithm to suppress the grating lobe of a wideband planar array is presented. With the alteration of operating frequency point, the electrical size of distance between two adjacent elements will change thereupon. This approach achieves the suppression of grating lobe at high operating frequency point, whose highest sidelobe level is around -10 dB, with little influence to array’s radiation characteristic of lower frequency point. For this approach’s practicability, simple dipole antenna is adopted as the array’s element to check out whether the approach keeps validity by simulation.
关键词： Grating lobe suppression,distance optimization,sparse array,genetic algorithm
更新于2025-09-23 15:22:29
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[IEEE 2018 20th International Conference on Transparent Optical Networks (ICTON) - Bucharest (2018.7.1-2018.7.5)] 2018 20th International Conference on Transparent Optical Networks (ICTON) - Supporting Low-Latency Applications through Hybrid Cost-Optimised Cloudlet Placement
摘要： Low-latency applications such as augmented reality, cognitive assistance, and context-aware computation are better supported by augmenting cloud networks with cloudlet enabled edge computing solution. This overcomes the high-transmission latency arising from the edge devices in the access segment to cloud servers located in the core. In this talk, we will review our recently proposed hybrid cost-optimization framework for optimal cloudlet placement over existing passive optical access networks, subject to capacity and latency constraints. In our work, we formulate a mixed-integer non-linear program to identify ideal locations (either at the central office (CO), remote node (RN), or in the field) for cloudlet placement over three deployment areas of differing population densities. Our results point to the fact that the installation of more RN and CO-located cloudlets will yield an improved cost optimal solution than the installation of field cloudlets alone, and that the percentage of the incremental energy budget arising from the installation of cloudlets are low.
关键词： non-linear mixed-integer programming,passive optical access network,cloud computing,low-latency,Tactile Internet,cloudlets,cost-optimization
更新于2025-09-23 15:22:29
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[IEEE 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC) - Hangzhou (2018.8.25-2018.8.26)] 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC) - SAR and Optical Image Registration Method Based on Quantum Particle Swarm Optimization
摘要： Abstract: In the most important step of GIS and optical image fusion, in order to improve the registration accuracy and efficiency of the strategic target, a new image registration method based on quantum particle swarm optimization (QPSO) with independent optical selection is presented. The proposed method consists of three steps: first, it decomposes the optical image into different frequency components with the wavelet transform; second, it extracts the feature corner points with the Harris corner detector; and finally, it constructs the similarity measure by combining the mutual information and the spatial distance, and uses the QPSO algorithm to search the optimal transformation parameters. The experimental results show that the proposed method is effective and feasible, it can achieve high accuracy and robustness for the low-frequency component of the optical image.
关键词： GIS Image,Image Registration,Independent Optical Selection,Quantum Particle Swarm Optimization,Optical Image
更新于2025-09-23 15:22:29
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A methodology for topology optimization based on level set method and its application to piezoelectric energy harvester design
摘要： Compared to a density based procedure, the level set method can acquire a clear boundary without any intermediate density elements, and has become a topical issue in topology optimization studies. In this method, the material properties of the discretized elements are usually defined as the design variables, giving rise to the so called discrete or sawtooth topologies. In this paper, a topology optimization methodology based on level-set method (LSM) and radial basis function (RBF) is proposed. To enhance the performance of the LSM, an improved material interpolation model is proposed. The RBF based post-processor is proposed to smooth the preliminary optimized topology. The proposed method is applied to the topology design of a piezoelectric energy harvester. The effect of different penalization factors is compared and analyzed. The numerical results validate the feasibility and effectiveness of the proposed method.
关键词： Coupled problems,topology optimization,level set method
更新于2025-09-23 15:22:29
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Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model
摘要： Accurate global solar radiation prediction is highly essential for related research on renewable energy sources. The cost implication and measurement expertise of global solar radiation emphasize that intelligence prediction models need to be applied. On the basis of long-term measured daily solar radiation data, this study uses a novel regularized online sequential extreme learning machine, integrated with variable forgetting factor (FOS-ELM), to predict global solar radiation at Bur Dedougou, in the Burkina Faso region. Bayesian Information Criterion (BIC) is applied to build the seven input combinations based on speed (Wspeed), maximum and minimum temperature (Tmax and Tmin), maximum and minimum humidity (Hmax and Hmin), evaporation (Eo) and vapor pressure deficiency (VPD). For the difference input parameters magnitudes, seven models were developed and evaluated for the optimal input combination. Various statistical indicators were computed for the prediction accuracy examination. The experimental results of the applied FOS-ELM model demonstrated a reliable prediction accuracy against the classical extreme learning machine (ELM) model for daily global solar radiation simulation. In fact, compared to classical ELM, the FOS-ELM model reported an enhancement in the root mean square error (RMSE) and mean absolute error (MAE) by (68.8–79.8%). In summary, the results clearly confirm the effectiveness of the FOS-ELM model, owing to the fixed internal tuning parameters.
关键词： global solar radiation,West Africa region,energy harvesting,FOS-ELM model,input optimization
更新于2025-09-23 15:22:29