- 标题
- 摘要
- 关键词
- 实验方案
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Impact of Dynamic Shading in cSi PV Modules and Systems for Novel Applications
摘要： With the dense deployment of small cells in the next generation of mobile networks, the users from different tiers suffer from high downlink interferences. In this paper, we propose a game theoretic approach for joint co-tier and cross-tier collaboration in heterogeneous networks and analyze the relevance of the proposed scheme. First, we propose a coalition structure game with a weighted Owen value as imputation, where the small-cell base stations (SBSs) and their connecting macrocell user equipments (MUEs) form a priori union. We prove that the proposed framework optimizes the users profit. As an additional global benefit, the SBSs are encouraged to host the harmed public users in their vicinity. Second, we propose a canonical game with a weighted solidarity value as imputation to allow cooperation among SBSs and MUEs when they fail to connect to nearby SBSs. We prove that the weak players are protected in this scheme and that a high degree of fairness is provided in the game. We compare through extensive simulations the proposed frameworks with state-of-the-art resource allocation solutions, access modes, and legacy game-theoretic approaches. We show that the proposed framework obtains the best performances for the MUEs and small-cells user equipments in terms of throughput and fairness. Throughput gain is in order of 40% even reaching 50% for both types of users.
关键词： game theory,interference mitigation,resource allocation,heterogeneous networks,cooperative games,Small-cells
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Citizens on the driving seat of Photovoltaics
摘要： Reliable data congestion analytics in crowdsourced eHealth networks becomes particularly important, especially in big data era, because of wide adaption of ubiquitous crowdsourced healthcare participants. Since a crowdsourced eHealth network has intermittent connectivity to its remote healthcare provider, researchers usually use some well-studied networks to model the novel network, but data congestion analytics is still a big problem in most intermittent connecting networks. In most cases, data congestion analytics may be realized by ?xing the number of forwarded copies, but sometimes, it cannot suit the changing network environments well. This problem could be solved by modifying packet forwarding conditions dynamically through detecting real-time network environment. Based on this idea, in this paper, an optimized routing algorithm named RSW (reduced variable neighborhood search-based spray and wait) is proposed. In the algorithm, nodes will exchange and store each other’s buffer status during their communication, based on which, current network environments will be evaluated and quanti?ed as a real-time threshold. Then, spray and wait adapts the threshold for data congestion control. Simulation shows that the proposed algorithm increases data packet delivery probability, and optimize the overhead ratio dramatically, which can be up to ten times lower than that of standard algorithm.
关键词： congestion control,optimization,Data analytics,crowdsourced eHealth networks
更新于2025-09-23 15:21:01
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[IEEE 2018 International Symposium on Micro-NanoMechatronics and Human Science (MHS) - Nagoya, Japan (2018.12.9-2018.12.12)] 2018 International Symposium on Micro-NanoMechatronics and Human Science (MHS) - Laser Lift-Off Process for Additive Micropatterning of Functional Particles and Films
摘要： While visual or tactile image data have been conventionally processed via filters or perceptron-like learning machines, the recent advances of computational topology may make it possible to successfully extract the global features from the local pixelwise data. In fact, some inventive algorithms have succeeded in computing the topological invariants, such as the number of objects or holes and irrespective of the shapes and positions of the touches. However, they are mostly offline algorithms aiming at big data. A real-time algorithm for computing topology is also needed for interactive applications such as touch sensors. Here, we propose a fast algorithm to compute the Euler characteristics of touch shapes by using the Poincare–Hopf index for each pixel. We demonstrate that our simple algorithm, implemented solely as logical operations in Arduino, correctly returns and updates the topological invariants of touches in real time.
关键词： invariance,sensor networks,touch counter,Poincare-Hopf index,topology
更新于2025-09-23 15:21:01
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A Scalable Soft-Switching Photovoltaic Inverter with Full-Range ZVS and Galvanic Isolation
摘要： The introduction of heterogeneous wireless mesh technologies provides an opportunity for higher network capacity, wider coverage, and higher quality of service (QoS). Each wireless device utilizes different standards, data formats, protocols, and access technologies. However, the diversity and complexity of such technologies create challenges for traditional control and management systems. This paper proposes a heterogeneous metropolitan area network architecture that combines an IEEE 802.11 wireless mesh network (WMN) with a long-term evolution (LTE) network. In addition, a new heterogeneous routing protocol and a routing algorithm based on reinforcement learning called cognitive heterogeneous routing are proposed to select the appropriate transmission technology based on parameters from each network. The proposed heterogeneous network overcomes the problems of sending packets over long paths, island nodes, and interference in WMNs and increases the overall capacity of the combined network by utilizing unlicensed frequency bands instead of buying more license frequency bands for LTE. The work is validated through extensive simulations that indicate that the proposed heterogeneous WMN outperforms the LTE and Wi-Fi networks when used individually. The simulation results show that the proposed network achieves an increase of up to 200% in throughput compared with Wi-Fi-only networks or LTE-only networks.
关键词： routing protocol,long-term evolution (LTE),reinforcement learning,next-generation network,Heterogeneous networks,wireless mesh network (WMN)
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL) - Sozopol, Bulgaria (2019.9.6-2019.9.8)] 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL) - Measurement Uncertainty as a Test Model Assessment Tool
摘要： We developed and successfully applied data-driven models that heavily rely on readily available remote sensing datasets to investigate probabilities of algal bloom occurrences in Kuwait Bay. An artificial neural network (ANN) model, a multivariate regression (MR) model, and a spatiotemporal hybrid model were constructed, optimized, and validated. Temporal and spatial submodels were coupled in a hybrid modeling framework to improve on the predictive powers of conventional ANN and MR generic models. Sixteen variables (sea surface temperature [SST], chlorophyll a OC3M, chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel-Maritorena (GSM), precipitation, CDOM, turbidity index, PAR, euphotic depth, Secchi depth, wind direction, wind speed, bathymetry, distance to nearest river outlet, distance to shore, and distance to aquaculture) were used as inputs for the spatial submodel; all of these, with the exception of bathymetry, distance to nearest river outlet, distance to shore, and distance to aquaculture were used for the temporal submodel as well. Findings include: 1) the ANN model performance exceeded that of the MR model and 2) the hybrid models improved the model performance significantly; 3) the temporal variables most indicative of the timing of bloom propagation are sea surface temperature, Secchi disk depth, wind direction, chlorophyll a (OC3M), and wind speed; and 4) the spatial variables most indicative of algal bloom distribution are the ocean chlorophyll from OC3M, GSM, and the GIOP products; distance to shore; and SST. The adopted methodologies are reliable, cost-effective and could be used to forecast algal bloom occurrences in data-scarce regions.
关键词： remote sensing,Coupled spatiotemporal algal bloom model,data mining,Kuwait bay,neural networks
更新于2025-09-23 15:21:01
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Highly Efficient All-Small-Molecule Organic Solar Cells with Appropriate Active Layer Morphology by Side Chain Engineering of Donor Molecules and Thermal Annealing
摘要： It is very important to fine-tune the nanoscale morphology of donor:acceptor blend active layers for improving the photovoltaic performance of all-small-molecule organic solar cells (SM-OSCs). In this work, two new small molecule donor materials are synthesized with different substituents on their thiophene conjugated side chains, including SM1-S with alkylthio and SM1-F with fluorine and alkyl substituents, and the previously reported donor molecule SM1 with an alkyl substituent, for investigating the effect of different conjugated side chains on the molecular aggregation and the photophysical, and photovoltaic properties of the donor molecules. As a result, an SM1-F-based SM-OSC with Y6 as the acceptor, and with thermal annealing (TA) at 120 °C for 10 min, demonstrates the highest power conversion efficiency value of 14.07%, which is one of the best values for SM-OSCs reported so far. Besides, these results also reveal that different side chains of the small molecules can distinctly influence the crystallinity characteristics and aggregation features, and TA treatment can effectively fine-tune the phase separation to form suitable donor–acceptor interpenetrating networks, which is beneficial for exciton dissociation and charge transportation, leading to highly efficient photovoltaic performance.
关键词： small molecule donor materials,all-small-molecule organic solar cells,interpenetrating networks,side-chain engineering,thermal annealing
更新于2025-09-23 15:21:01
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Fluorescent Properties of Gd-Doped Zno Nanonporous Networks & Its Application in Optical Biosensing
摘要： This research presents a study of the fluorescent properties of new materials based on gadolinium-doped zinc oxide nanoporous networks obtained by sol gel method on the surface of microcrystalline silicon. The effect of co-doping of different concentrations of Gd ions on the emission properties of ZnO nanoparticles has been investigated. Emissions of such biomolecules as protein, amino acids and porphyrin and its detection limits were studied for the purpose of practical application of Gd-doped ZnO nanonporous networks as an element of an optical biosensor technology.
关键词： sol-gel method,nanoporous networks,optical biosensing,fluorescent properties,Gd-doped ZnO
更新于2025-09-23 15:21:01
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Neural networks for trajectory evaluation in direct laser writing
摘要： Material shrinkage commonly occurs in additive manufacturing and compromises the fabrication quality by causing unwanted distortions or residual stresses in fabricated parts. Even though it is known that the resulting deformations and stresses are highly dependent on the writing trajectory, no effective strategy for choosing suitable trajectories has been reported to date. Here, we present a path to achieve this goal in direct laser writing, an additive manufacturing method based on photopolymerization that commonly suffers from strong shrinkage-induced effects. First, we introduce a method for measuring the shrinkage of distinct direct laser written lines. We then introduce a semi-empirical numerical model to capture the interplay of sequentially polymerized material and the resulting macroscopic effects. Finally, we implement an artificial neural network to evaluate given laser trajectories in terms of the resulting part quality. The presented approach proves feasibility of using artificial neural networks to assess the quality of 3D printing trajectories and thereby demonstrates a potential route for reducing the impact of material shrinkage on 3D printed parts.
关键词： Advanced manufacturing,Residual stresses,Artificial neural networks,Direct laser writing
更新于2025-09-23 15:21:01
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Analysis of the reflectivity in meteorological radars using data mining and neural networks
摘要： The aim of this work is show the analysis of the data measured by weather radar used in data mining and fuzzy logic. A decoding of the data measured by the meteorological radar was made, which was encrypted, then an analysis of this data was made using neural networks that are trained with 10 and 20 neurons, in each case the effectiveness of each one is checked. The results showed that neural networks are an excellent tool that allows eliminate erroneous information and then normalize it to the scale used according to the standard. This knowledge is essential for the aviation industry to operate properly and without risks for passengers, crew and aircraft, it is also important to anticipate and/or avoid, if possible, catastrophes generated by weather events related to rainfall.
关键词： Polarimetric Variables,Reflectivity,Weather Radar,Neural Networks,Data Mining
更新于2025-09-23 15:21:01
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Automated Tuning of Double Quantum Dots into Specific Charge States Using Neural Networks
摘要： While quantum dots are at the forefront of quantum-device technology, the tuning of multidot systems requires a lengthy experimental process as multiple parameters need to be accurately controlled. This process becomes increasingly time-consuming and difficult to perform manually as the devices become more complex and the number of tuning parameters grows. In this work, we present a crucial step toward automated tuning of quantum-dot qubits. We introduce an algorithm driven by machine learning that uses a small number of coarse-grained measurements as its input and tunes the quantum-dot system into a preselected charge state. We train and test our algorithm on a GaAs double-quantum-dot device and we consistently arrive at the desired state or its immediate neighborhood.
关键词： neural networks,automated tuning,charge states,machine learning,quantum dots
更新于2025-09-23 15:21:01