MPP: A Novel Algorithm for Estimating Vehicle Space Headways from a Single Image

Vehicle space headway, also called spacing, is an important and basic traffic parameter. Traditional space headway calculation methods are facing the problems of large errors and high costs. This paper presents a novel algorithm based on measurement point pairs (MPPs) to estimate the real-time microcosmic vehicle space headway from single images in existing traffic surveillance videos and images without any additional equipment. First, the camera is calibrated with road markings to obtain the relationship between the image coordinates and the world coordinates. Second, vehicle pairs of two successive vehicles in the image are established, measurement points on each vehicle are selected by video intelligence analysis technologies, and their world coordinates are calculated by camera calibration results. Finally, the measurement points of the preceding and following vehicles are matched to obtain the MPPs, followed by the calculation of the weighted space headway. By using the measurement point information, one of the most difficult problems in image distance measurement, the lack of height information, is solved. The main factors causing estimation errors are fully addressed and the range and trend of errors under certain conditions are given by virtual simulation. Two real-world experiments are used to prove the accuracy and usability of the MPP in common video scenes: the simulation experiment indicates that the MPP algorithm achieves a high accuracy with estimation error less than ±0.1 m and the relative error within 1.1%; the application experiment shows that the MPP-based calculation is more accurate and stable than the state-of-the-art distance measurement algorithm and that the convenience of the proposed MPP algorithm is higher than that of traditional methods of space headway estimation. Document type: Articl

Object Re-Identification Based on Deep Learning

With the explosive growth of video data and the rapid development of computer vision technology, more and more relevant technologies are applied in our real life, one of which is object re-identification (Re-ID) technology. Object Re-ID is currently concentrated in the field of person Re-ID and vehicle Re-ID, which is mainly used to realize the cross-vision tracking of person/vehicle and trajectory prediction. This chapter combines theory and practice to explain why the deep network can re-identify the object. To introduce the main technical route of object Re-ID, the examples of person/vehicle Re-ID are given, and the improvement points of existing object Re-ID research are described separately

Helping Beginning Vloggers to Overcome Cold Start: the Perspective of Identity Construction

Beginning vloggers’ low enthusiasm for Vlog creation has garnered little consideration, even though a social media platform can highly improve user stickiness and user activity by engaging users to generate content. This paper investigates the effects of extrinsic and intrinsic motivations on Vlog creative behavior mediated by cognition and emotion based on social cognitive theory and self-discrepancy theory. The analysis of 342 questionnaire surveys shows that intrinsic motivation (social interaction and social cues presentation) positively affects identity construction and positive emotions. In contrast, extrinsic motivation (community incentives and social norms) only positively affects identity construction and does not significantly influence positive emotions. Identity construction and positive emotions further significantly affect the creative behavior of beginning vloggers. The results reveal the process of Vlog creative behavior and have important practical implications for enhancing the platform performance

A Traffic State Detection Tool for Freeway Video Surveillance System

AbstractTraffic state is one of the most important traffic flow parameters to both the traffic management center and the traveler. It's difficult to extract traffic data using surveillance cameras because of the wider field, panning and zooming of the surveillance cameras. To leverage the existing surveillance camera infrastructure, a surveillance video based traffic state detection system is proposed. The proposed system can estimate traffic flow speed and road space occupancy, and recognize three typical traffic states (congested, slow, and smooth). Experimental results show that the system had good adaptation and high accuracy in daytime

Observation of Hybrid-Order Topological Pump in a Kekule-Textured Graphene Lattice

Thouless charge pumping protocol provides an effective route for realizing topological particle transport. To date, the first-order and higher-order topological pumps, exhibiting transitions of edge-bulk-edge and corner-bulk-corner states, respectively, are observed in a variety of experimental platforms. Here, we propose a concept of hybrid-order topological pump, which involves a transition of bulk, edge, and corner states simultaneously. More specifically, we consider a Kekul\'e-textured graphene lattice that features a tunable phase parameter. The finite sample of zigzag boundaries, where the corner configuration is abnormal and inaccessible by repeating unit cells, hosts topological responses at both the edges and corners. The former is protected by a nonzero winding number, while the latter can be explained by a nontrivial vector Chern number. Using our skillful acoustic experiments, we verify those nontrivial boundary landmarks and visualize the consequent hybrid-order topological pump process directly. This work deepens our understanding to higher-order topological phases and broadens the scope of topological pumps.Comment: 5 figure

APOC1 predicts a worse prognosis for esophageal squamous cell carcinoma and is associated with tumor immune infiltration during tumorigenesis

Background: Esophageal carcinoma (ESCA), a common malignant tumor of the digestive tract with insidious onset, is a serious threat to human health. Despite multiple treatment modalities for patients with ESCA, the overall prognosis remains poor. Apolipoprotein C1 (APOC1) is involved in tumorigenesis as an inflammation-related molecule, and its role in esophageal cancer is still unknown.Methods: We downloaded documents and clinical data using The Cancer Genome Atlas (TCGA)and Gene Expression Omnibus (GEO) databases. We also conducted bioinformatics studies on the diagnostic value, prognostic value, and correlation between APOC1 and immune infiltrating cells in ESCA through STRING (https://cn.string-db.org/), the TISIDB (http://cis.hku.hk/TISIDB/) website, and various other analysis tools.Results: In patients with ESCA, APOC1 was significantly more highly expressed in tumor tissues than in normal tissues (p < 0.001). APOC1 could diagnose ESCA more accurately and determine the TNM stage and disease classification with high accuracy (area under the curve, AUC≥0.807). The results of the Kaplan–Meier curve analysis showed that APOC1 has prognostic value for esophageal squamous carcinoma (ESCC) (p = 0.043). Univariate analysis showed that high APOC1 expression in ESCC was significantly associated with worse overall survival (OS) (p = 0.043), and multivariate analysis shows that high APOC1 expression was an independent risk factor for the OS of patients with ESCC (p = 0.030). In addition, the GO (gene ontology)/KEGG (Kyoto encyclopedia of genes and genomes) analysis showed a concentration of gene enrichment in the regulation of T-cell activation, cornification, cytolysis, external side of the plasma membrane, MHC protein complex, MHC class II protein complex, serine-type peptidase activity, serine-type endopeptidase activity, Staphylococcus aureus infection, antigen processing and presentation, and graft-versus-host disease (all p < 0.001). GSEA (gene set enrichment analysis) showed that enrichment pathways such as immunoregulatory-interactions between a lymphoid and non-lymphoid cell (NES = 1.493, p. adj = 0.023, FDR = 0.017) and FCERI-mediated NF-KB activation (NES = 1.437, p. adj = 0.023, FDR = 0.017) were significantly enriched in APOC1-related phenotypes. In addition, APOC1 was significantly associated with tumor immune infiltrating cells and immune chemokines.Conclusion: APOC1 can be used as a prognostic biomarker for esophageal cancer. Furthermore, as a novel prognostic marker for patients with ESCC, it may have potential value for further investigation regarding the diagnosis and treatment of this group of patients

Multiple evaluations, risk assessment, and source identification of heavy metals in surface water and sediment of the Golmud River, northeastern Qinghai-Tibet Plateau, China

The water quality of the Golmud River is essential for environmental preservation and economic growth of Golmud city and Qarhan Salt Lake in China. Thirty-four samples of surface water and sediment from seventeen places in the Golmud River and thirty-two dustfall samples in the Qaidam Basin were collected. The concentrations of heavy metals (HMs) were measured; water quality, risk assessment, and multiple source analysis were applied. Concentrations of HMs in water were Zn > Cu > Ni > As > Pb > Cd > Hg, and in sediment were Ni > Zn > Pb > As > Cu > Cd > Hg. In water, the Nemerow pollution index (NP) values indicated that most of the sampling points seemly were seriously polluted; other water quality assessment results suggested no pollution. In sediment, the concentrations of 27% HMs exceeded the background values of soil in Qinghai; 48% exceeded the Earth crust background values, which were As, Hg, and Cd. The single factor index method (Pi), geological accumulation index (Igeo), and contamination factor (CF) revealed that As pollution is serious, followed by Hg and Cd; the pollution load index (PLI) and modified pollution index (mCd) values indicated that 64% and 57% of samples were polluted. NP values are shown serious pollution. The ecological risk results demonstrated a low risk in water and a medium risk in sediment. The average total hazard quotient values in sediment and water for adults and children revealed low non-carcinogenic risks. Carcinogenic risk indicated Ni in water and sediment, and As in sediment may be involved in cancer risk. Multivariate statistics showed that the HMs mainly came from nature, and human activities will also impact them. The upper continental crust values indicated that As and Hg have high background values. The saline dust storm was one of the essential sources of HMs, especially Hg. Various provenances constituted the material cycling of HMs in the surface environment