Application of Pedestrian Upstream Detection Strategy in a Mixed Flow Traffic Circumstance

Walking is an environment-friendly trip mode and can help ease the congestion caused by automobiles. Proper design of pedestrian facilities that promotes efficiency and safety can encourage more people to choose walking. Upstream detection (UD) strategy is proposed by previous studies to reduce pedestrian waiting time at mid-block crosswalk (MBC). This paper applied UD strategy to MBC under mixed traffic circumstance where the crosswalk serves both pedestrians and non-motor users. Traffic data was collected from an MBC in the city of Nanjing, China. Simulation models were developed by using the VISSIM software and its add-on module Vehicle Actuated Programming (VAP). The models were categorised by the volume and composition of pedestrians and non-motor users. Models were simulated according to different experimental schemes to explore the effectiveness of the UD strategy under mixed traffic circumstance. T-test and analysis of variance (ANOVA) were used to interpret the simulation results. The main conclusions of this paper are that the UD strategy is still effective at the MBC with a mixed traffic circumstance despite the proportion of non-motor users. However, as the proportion of non-motor users becomes higher, the average delay of pedestrians and non-motor users will increase compared to pure pedestrian flow

Temperature-Dependent Open-Circuit Voltage Measurements and Light-Soaking in Hydrogenated Amorphous Silcon Solar Cells

We present temperature-dependent measurements of the open-circuit voltage VOC(T) in hydrogenated amorphous silicon nip solar cells prepared at United Solar. At room-temperature and above, VOC measured using near-solar illumination intensity differs by as much as 0.04 V for the as-deposited and light-soaked states; the values of VOC for the two states converge below 250 K. Models for VOC based entirely on recombination through deep levels (dangling bonds) do not account for the convergence effect. The convergence is present in a model that assumes the recombination traffic in the as-deposited state involves only bandtails, but which splits the recombination traffic fairly evenly between bandtails and defects for the light-soaked state at room-temperature. Recombination mechanisms are important in understanding light-soaking, and the present results are inconsistent with at least one well-known model for defect generation

Hole Mobility Limit of Amorphous Silicon Solar Cells

We present temperature-dependent measurements and modeling for a thickness series of hydrogenated amorphous silicon nip solar cells. The comparison indicates that the maximum power density (PMAX) from the as-deposited cells has achieved the hole-mobility limit established by valence bandtail trapping, and PMAX is thus not significantly limited by intrinsic-layer dangling bonds or by the doped layers and interfaces. Measurements of the temperature-dependent properties of light-soaked cells show that the properties of as-deposited and light-soaked cells converge below 250 K; a model perturbing the valence band tail traps with a density of dangling bonds accounts adequately for the convergence effect

Hole Drift Mobility Measurements on a-Si:H using Surface and Uniformly Absorbed Illumination

The standard, time-of-flight method for measuring drift mobilities in semiconductors uses strongly absorbed illumination to create a sheet of photocarriers near an electrode interface. This method is problematic for solar cells deposited onto opaque substrates, and in particular cannot be used for hole photocarriers in hydrogenated amorphous silicon (a-Si:H) solar cells using stainless steel substrates. In this paper we report on the extension of the time-of-flight method that uses weakly absorbed illumination. We measured hole drift-mobilities on seven a-Si:H nip solar cells using strongly and weakly absorbed illumination incident through the n-layer. For thinner devices from two laboratories, the drift-mobilities agreed with each other to within a random error of about 15%. For thicker devices from United Solar, the driftmobilities were about twice as large when measured using strongly absorbed illumination. We propose that this effect is due to a mobility profile in the intrinsic absorber layer in which the mobility decreases for increasing distance from the substrate

Over-Sampling Strategy in Feature Space for Graphs based Class-imbalanced Bot Detection

The presence of a large number of bots in Online Social Networks (OSN) leads to undesirable social effects. Graph neural networks (GNNs) have achieved state-of-the-art performance in bot detection since they can effectively utilize user interaction. In most scenarios, the distribution of bots and humans is imbalanced, resulting in under-represent minority class samples and sub-optimal performance. However, previous GNN-based methods for bot detection seldom consider the impact of class-imbalanced issues. In this paper, we propose an over-sampling strategy for GNN (OS-GNN) that can mitigate the effect of class imbalance in bot detection. Compared with previous over-sampling methods for GNNs, OS-GNN does not call for edge synthesis, eliminating the noise inevitably introduced during the edge construction. Specifically, node features are first mapped to a feature space through neighborhood aggregation and then generated samples for the minority class in the feature space. Finally, the augmented features are fed into GNNs to train the classifiers. This framework is general and can be easily extended into different GNN architectures. The proposed framework is evaluated using three real-world bot detection benchmark datasets, and it consistently exhibits superiority over the baselines

MGTAB: A Multi-Relational Graph-Based Twitter Account Detection Benchmark

The development of social media user stance detection and bot detection methods rely heavily on large-scale and high-quality benchmarks. However, in addition to low annotation quality, existing benchmarks generally have incomplete user relationships, suppressing graph-based account detection research. To address these issues, we propose a Multi-Relational Graph-Based Twitter Account Detection Benchmark (MGTAB), the first standardized graph-based benchmark for account detection. To our knowledge, MGTAB was built based on the largest original data in the field, with over 1.55 million users and 130 million tweets. MGTAB contains 10,199 expert-annotated users and 7 types of relationships, ensuring high-quality annotation and diversified relations. In MGTAB, we extracted the 20 user property features with the greatest information gain and user tweet features as the user features. In addition, we performed a thorough evaluation of MGTAB and other public datasets. Our experiments found that graph-based approaches are generally more effective than feature-based approaches and perform better when introducing multiple relations. By analyzing experiment results, we identify effective approaches for account detection and provide potential future research directions in this field. Our benchmark and standardized evaluation procedures are freely available at: https://github.com/GraphDetec/MGTAB.Comment: 14 pages, 7 figure

Light-Soaking Effects on the Open-Circuit Voltage of a-Si:H Solar Cells

We present measurements on the decline of the open-circuit voltage VOC in a-Si:H solar cells during extended illumination (light-soaking) at 295 K. We used a near-infrared laser that was nearly uniformly absorbed in the intrinsic layer of the cell. At the highest photogeneration rate (about 2x1021 cm-3), a noticeable decline (0.01 V) occurred within about 10 minutes; VOC stabilized at 0.04 V below its initial value after about 200 hours. We found that both the kinetics and the magnitudes of VOC are reasonably consistent with the predictions of a calculation combining a bandtail+defect picture for recombination and a hydrogen-collision model for defect generation. The version of the hydrogen-collision model that we used assumes that only bandtail recombination drives the hydrogen collision processes. Within this picture, the crossover between bandtail and defect recombination occurs on the same timescale as the “light-induced annealing” process that accounts for stabilization of the optoelectronic properties for long lightsoaking times

Plasmonic Light-trapping and Quantum Efficiency Measurements on Nanocrystalline Silicon Solar Cells and Silicon-On-Insulator Devices

Quantum efficiency measurements in nanocrystalline silicon (nc-Si:H)solar cells deposited onto textured substrates indicate that these cells are close to the stochastic lighttrapping limit proposed by Yablonovitch in the 1980s. An interesting alternative to texturing is plasmonic light-trapping based on non-textured cells and using an overlayer of metallic nanoparticles to produce light-trapping. While this type of light-trapping has not yet been demonstrated for nc-Si:H solar cells, significant photocurrent enhancements have been reported on silicon-on-insulator devices with similar optical properties to nc-Si:H. Here we report our measurements of quantum efficiencies in nc-Si:H solar cells and normalized photoconductance spectra in SOI photodetectors with and without silver nanoparticle layers. As was done previously, the silver nanoparticles were created by thermal annealing of evaporated silver thin films. We observed enhancement in the normalized photoconductance spectra of SOI photodetectors at longer wavelengths with the silver nanoparticles. For nc-Si:H solar cells, we have not yet observed significant improvement of the quantum efficiency with the addition of annealed silver films