Co-supervised learning paradigm with conditional generative adversarial networks for sample-efficient classification

Classification using supervised learning requires annotating a large amount of classes-balanced data for model training and testing. This has practically limited the scope of applications with supervised learning, in particular deep learning. To address the issues associated with limited and imbalanced data, this paper introduces a sample-efficient co-supervised learning paradigm (SEC-CGAN), in which a conditional generative adversarial network (CGAN) is trained alongside the classifier and supplements semantics-conditioned, confidence-aware synthesized examples to the annotated data during the training process. In this setting, the CGAN not only serves as a co-supervisor but also provides complementary quality examples to aid the classifier training in an end-to-end fashion. Experiments demonstrate that the proposed SEC-CGAN outperforms the external classifier GAN (EC-GAN) and a baseline ResNet-18 classifier. For the comparison, all classifiers in above methods adopt the ResNet-18 architecture as the backbone. Particularly, for the Street View House Numbers dataset, using the 5% of training data, a test accuracy of 90.26% is achieved by SEC-CGAN as opposed to 88.59% by EC-GAN and 87.17% by the baseline classifier; for the highway image dataset, using the 10% of training data, a test accuracy of 98.27% is achieved by SEC-CGAN, compared to 97.84% by EC-GAN and 95.52% by the baseline classifier.Comment: 14 pages, 5 figure

Semantic Communication for Cooperative Perception based on Importance Map

Cooperative perception, which has a broader perception field than single-vehicle perception, has played an increasingly important role in autonomous driving to conduct 3D object detection. Through vehicle-to-vehicle (V2V) communication technology, various connected automated vehicles (CAVs) can share their sensory information (LiDAR point clouds) for cooperative perception. We employ an importance map to extract significant semantic information and propose a novel cooperative perception semantic communication scheme with intermediate fusion. Meanwhile, our proposed architecture can be extended to the challenging time-varying multipath fading channel. To alleviate the distortion caused by the time-varying multipath fading, we adopt explicit orthogonal frequency-division multiplexing (OFDM) blocks combined with channel estimation and channel equalization. Simulation results demonstrate that our proposed model outperforms the traditional separate source-channel coding over various channel models. Moreover, a robustness study indicates that only part of semantic information is key to cooperative perception. Although our proposed model has only been trained over one specific channel, it has the ability to learn robust coded representations of semantic information that remain resilient to various channel models, demonstrating its generality and robustness.Comment: 13 pages,22 figures;journal;submitted for possible publicatio

A review of the spider genus Chthonopes (Araneae, Theridiosomatidae), with descriptions of two new species from China

The genus Chthonopes Wunderlich, 2011 is reviewed in this paper. The type species Chthonopes jaegeri Wunderlich, 2011 was illustrated based on new material from the type locality and the new distribution records (Bolikhamsay and Ban Kouanphavang Khammouane, Laos). Two new species are described from Yunnan, China: C. bifidum Yu & Lin, sp. nov. (♂♀) and C. jimudeng Yu & Lin, sp. nov. (♀). A key is provided for the genus, as well as species diagnoses, and a distribution map for all five species of Chthonopes

Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data

Time-Series Forecasting based on Cumulative Data (TSFCD) is a crucial problem in decision-making across various industrial scenarios. However, existing time-series forecasting methods often overlook two important characteristics of cumulative data, namely monotonicity and irregularity, which limit their practical applicability. To address this limitation, we propose a principled approach called Monotonic neural Ordinary Differential Equation (MODE) within the framework of neural ordinary differential equations. By leveraging MODE, we are able to effectively capture and represent the monotonicity and irregularity in practical cumulative data. Through extensive experiments conducted in a bonus allocation scenario, we demonstrate that MODE outperforms state-of-the-art methods, showcasing its ability to handle both monotonicity and irregularity in cumulative data and delivering superior forecasting performance.Comment: Accepted as CIKM'23 Applied Research Trac

Research on Design Method of Long-life Asphalt Pavement

In recent years, the problem of early damage of asphalt pavement has been basically solved, and the service performance has been improved, but there are still some deficiencies in design life and service life. This paper investigates the long-life asphalt pavement structure, analyzes the design method of asphalt mixture, and summarizes the pavement design theory and related software. The long-life asphalt pavement with semi-rigid base, flexible base and combined base structure has been designed by four method, including typical load, Per-Road, D50-2006 and D50-2017. Four methods were compared by designing long-life pavements with semi-rigid base and flexible base. The results show that the proposed asphalt pavement structure can meet the requirements of Per-Road, typical load design and D50-2006. However, D50-2017 has higher requirements for the bending and tensile fatigue life of the base layer and requires a thicker base layer. When d50-2017 is used to design flexible base pavement, the fatigue life of asphalt layer should be the main control index, and the fatigue life of sub base course should be the main control index in other pavement de-sign. It remains to be seen whether the proposed highway structure can achieve the design goal of long-life asphalt pavement

Research on Design Method of Long-life Asphalt Pavement

In recent years, the problem of early damage of asphalt pavement has been basically solved, and the service performance has been improved, but there are still some deficiencies in design life and service life. This paper investigates the long-life asphalt pavement structure, analyzes the design method of asphalt mixture, and summarizes the pavement design theory and related software. The long-life asphalt pavement with semi-rigid base, flexible base and combined base structure has been designed by four method, including typical load, Per-Road, D50-2006 and D50-2017. Four methods were compared by designing long-life pavements with semi-rigid base and flexible base. The results show that the proposed asphalt pavement structure can meet the requirements of Per-Road, typical load design and D50-2006. However, D50-2017 has higher requirements for the bending and tensile fatigue life of the base layer and requires a thicker base layer. When d50-2017 is used to design flexible base pavement, the fatigue life of asphalt layer should be the main control index, and the fatigue life of sub base course should be the main control index in other pavement de-sign. It remains to be seen whether the proposed highway structure can achieve the design goal of long-life asphalt pavement

FePt nanodot arrays with perpendicular easy axis, large coercivity, and extremely high density

Ordered FePt nanodot arrays with extremely high density have been developed by physical vapor deposition using porous alumina templates as evaporation masks. Nanodot diameter of 18 nm and periodicity of 25 nm have been achieved, resulting in an areal density exceeding 1 x1012 dots/in2. Rapid thermal annealing converts the disordered fcc to L10 phase, resulting in (001)-oriented FePt nanodot arrays with perpendicular anisotropy and large coercivity, without the need of epitaxy. High anisotropy and coercivity, perpendicular easy axis orientation and extremely high density are desirable features for future magnetic data storage media applications

A review of the spider genus Sinoalaria (Araneae, Theridiosomatidae), with the descriptions of four new species and two new combinations

The spider genus Sinoalaria Zhao & Li, 2014 is redefined and reviewed. A total of ten species are studied, including four new species: S. chi Yu & Lin, sp. nov. (♂♀), S. shenhei Yu & Lin, sp. nov. (♀), S. shuidi Yu & Lin, sp. nov. (♀), S. xiaotu Yu & Lin, sp. nov. (♂♀). Two new combinations are proposed: Sinoalaria nitida (Zhao & Li, 2012), comb. nov. and S. prolata (Zhao & Li, 2012), comb. nov., both transferred from Karstia Chen, 2010. The material of six known species were re-examined and photographed, including the type species, S. chengguanensis (Zhao & Li, 2012). A key is provided for all species of the genus, as well as diagnoses, illustrations, and a distribution map

Analysis of mechanical properties, permeability and fracturing mechanism of coal samples at different fracturing time of liquid nitrogen

In order to study the influence of liquid nitrogen cracking time on mechanical properties and permeability of coal samples, the independently developed WYS-800 triaxial gas seepage test device and acoustic emission detection system were used to conduct triaxial mechanical seepage tests on four groups of coal samples treated with different cracking time and collect acoustic emission signals. The mechanical properties and permeability of coal samples in triaxial mechanical seepage experiment were analyzed, and the characteristics of acoustic emission signals were described. Based on boiling heat transfer theory, one-dimensional cylinder heat conduction theory and thermal stress theory, the cracking mechanism was analyzed, and the thermal stress under different cracking time was calculated. The relationship between average temperature drop, average thermal stress, initial permeability and cracking time was revealed by data fitting. The results show that: ① Liquid nitrogen fracturing time have different influence on the mechanical properties of coal samples, the compressive strength and elastic modulus with the increase of the crack time shows the tendency of increase with the decrease of the first, the poisson's ratio are increased after the first decreases, coal sample triaxial loading when the axial stress and axial strain curve of the periodic evolution has obvious difference, associated with the change of mechanical parameters. ② The permeability of coal samples with different cracking time changes in u-shape during the triaxial loading process. The initial permeability, minimum permeability and maximum permeability increase with the increase of cracking time, and the increase rate is 119.05%, 437.5% and 146.49% when the cracking time is 30min. Acoustic emission signals are not active in compaction and elastic stages, and are mainly generated in yield and failure stages. The peak value of acoustic emission ringing count of coal samples after cracking is generated near the failure point, which is more than 20000 times. ③ The film boiling heat transfer coefficient between the coal sample and liquid nitrogen is 570.4 W/(m2·K). The average temperature drop of the coal sample is related to the cracking time, and the average thermal stress and initial permeability play a leading role. The average temperature drop of the coal sample can reach 213.63 K and the average thermal stress can reach 5.85 MPa after 30 min of cracking. ④ There is a linear relationship between initial permeability and average temperature drop, and a negative exponential relationship between initial permeability and cracking time of coal samples after liquid nitrogen treatment. Changing the parameter value can be extended to other similar coal samples or actual production evaluation