Identify a Specified Fish species by the Co-occurrence and Confusion Matrix

Nowadays, invasive species threaten native species has become a global problem. Invasive species might be carrying pathogenic microorganisms, reduce biological species and even threat to human health. Therefore, in this study, we proposed a method of co-occurrence matrix to texture analysis of three species of fish. We catch the body pattern, and make a judgment based on confusion matrix. Simulation results show that three species of fish can be classified from each other reasonable.The 3rd International Conference on Industrial Application Engineering 2015, March 28-31, 2015, Kitakyushu International Conference Center, Kitakyushu, Japa

Study on Image Segmentation in CT Metal Artifacts

Computed Tomography (CT) is one of the most important means of medical diagnosis and the quality of CT image can be seriously affected by metal artifacts. How to use CT image segmentation to extract the focused region is a classical difficult problem in this research field. According to the principle of CT reconstruction, after the medical image segmentation, projection of the metal part by compensation can improve the image quality. This paper first introduces the causes of the metal artifacts as well as the principle of CT image reconstruction. Then，it mainly discusses the simple and iterative threshold segmentation to solve metal artifacts. Corresponding comparison shows that the proposed method in this study has better segmentation effect based on the experimental results. Finally, the prospect of medical image segmentation is predicted to indicate future research work.The 2nd International Conference on Intelligent Systems and Image Processing 2014 (ICISIP2014), September 26-29, 2014, Nishinippon Institute of Technology, Kitakyushu, Japa

An Analysis of the Principles in Formulation and Implementation of University Constitution from the Perspective of the Spirit of Law

Under the background of university constitution construction,the formulation and implementation of the university constitution need to be divided into three parts, the legal effect,the regulatory mechanism,the power inside and outside of the university and the legal relationship, these three areas need further improvement. This paper will analyze the principles of university constitution from three aspects: constitution formulation, rights and interests protection and procedure implementation conditions

When Online Auction Meets Virtual Reality: An Empirical Investigation

The online auction is becoming increasingly popular in e-commerce, which allows to sell a product to the buyer with the highest bid. However, the lack of authentic product details for a thorough evaluation still poses challenges to its success. Recently, virtual reality (VR) is introduced to online auctions. We employ a unique dataset to investigate the effects of VR on auction outcomes and bidding activities. Results show that VR enhances buyers’ bidding competition, which in turn increases auction success and price, resulting in a competitive effect. Additionally, we find VR boosts buyers’ strategic responses to the bidding war, leading to a late-bidding effect. Findings contribute to both the theory and practice of VR and online auctions in selling houses

Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction

Low-rank tensor decomposition and completion have attracted significant interest from academia given the ubiquity of tensor data. However, the low-rank structure is a global property, which will not be fulfilled when the data presents complex and weak dependencies given specific graph structures. One particular application that motivates this study is the spatiotemporal data analysis. As shown in the preliminary study, weakly dependencies can worsen the low-rank tensor completion performance. In this paper, we propose a novel low-rank CANDECOMP / PARAFAC (CP) tensor decomposition and completion framework by introducing the $L_{1}$-norm penalty and Graph Laplacian penalty to model the weakly dependency on graph. We further propose an efficient optimization algorithm based on the Block Coordinate Descent for efficient estimation. A case study based on the metro passenger flow data in Hong Kong is conducted to demonstrate improved performance over the regular tensor completion methods.Comment: Accepted at AAAI 202

Choose A Table: Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering

Passenger clustering based on trajectory records is essential for transportation operators. However, existing methods cannot easily cluster the passengers due to the hierarchical structure of the passenger trip information, including multiple trips within each passenger and multi-dimensional information about each trip. Furthermore, existing approaches rely on an accurate specification of the clustering number to start. Finally, existing methods do not consider spatial semantic graphs such as geographical proximity and functional similarity between the locations. In this paper, we propose a novel tensor Dirichlet Process Multinomial Mixture model with graphs, which can preserve the hierarchical structure of the multi-dimensional trip information and cluster them in a unified one-step manner with the ability to determine the number of clusters automatically. The spatial graphs are utilized in community detection to link the semantic neighbors. We further propose a tensor version of Collapsed Gibbs Sampling method with a minimum cluster size requirement. A case study based on Hong Kong metro passenger data is conducted to demonstrate the automatic process of cluster amount evolution and better cluster quality measured by within-cluster compactness and cross-cluster separateness. The code is available at https://github.com/bonaldli/TensorDPMM-G.Comment: Accepted in ACM SIGSPATIAL 2023. arXiv admin note: substantial text overlap with arXiv:2306.1379

Curricular Object Manipulation in LiDAR-based Object Detection

This paper explores the potential of curriculum learning in LiDAR-based 3D object detection by proposing a curricular object manipulation (COM) framework. The framework embeds the curricular training strategy into both the loss design and the augmentation process. For the loss design, we propose the COMLoss to dynamically predict object-level difficulties and emphasize objects of different difficulties based on training stages. On top of the widely-used augmentation technique called GT-Aug in LiDAR detection tasks, we propose a novel COMAug strategy which first clusters objects in ground-truth database based on well-designed heuristics. Group-level difficulties rather than individual ones are then predicted and updated during training for stable results. Model performance and generalization capabilities can be improved by sampling and augmenting progressively more difficult objects into the training samples. Extensive experiments and ablation studies reveal the superior and generality of the proposed framework. The code is available at https://github.com/ZZY816/COM.Comment: Accepted by CVPR 2023. The code is available at https://github.com/ZZY816/CO

CircUBXN7 promotes macrophage infiltration and renal fibrosis associated with the IGF2BP2-dependent SP1 mRNA stability in diabetic kidney disease

IntroductionInflammatory cell infiltration is a novel hallmark of diabetic kidney disease (DKD), in part, by activated macrophages. Macrophage-to-tubular epithelial cell communication may play an important role in renal fibrosis. Circular RNAs (circRNAs) have been reported in the pathogenesis of various human diseases involving macrophages activation, including DKD. However, the exact mechanism of circRNAs in macrophage infiltration and renal fibrosis of DKD remains obscure.MethodsIn our study, a novel circRNA circUBXN7 was identified in DKD patients using microarray. The function of circUBXN7 in vitro and in vivo was investigated by qRT-PCR, western blot, and immunofluorescence. Finally, a dual-luciferase reporter assay, ChIP, RNA pull-down, RNA immunoprecipitation and rescue experiments were performed to investigate the mechanism of circUBXN7.ResultsWe demonstrated that the expression of circUBXN7 was significantly upregulated in the plasma of DKD patients and correlated with renal function, which might serve as an independent biomarker for DKD patients. According to investigations, ectopic expression of circUBXN7 promoted macrophage activation, EMT and fibrosis in vitro, and increased macrophage infiltration, EMT, fibrosis and proteinuria in vivo. Mechanistically, circUBXN7 was transcriptionally upregulated by transcription factor SP1 and could reciprocally promote SP1 mRNA stability and activation via directly binding to the m6A-reader IGF2BP2 in DKD.ConclusionCircUBXN7 is highly expressed in DKD patients may provide the potential biomarker and therapeutic target for DKD

Facilitating Self-monitored Physical Rehabilitation with Virtual Reality and Haptic feedback

Physical rehabilitation is essential to recovery from joint replacement operations. As a representation, total knee arthroplasty (TKA) requires patients to conduct intensive physical exercises to regain the knee's range of motion and muscle strength. However, current joint replacement physical rehabilitation methods rely highly on therapists for supervision, and existing computer-assisted systems lack consideration for enabling self-monitoring, making at-home physical rehabilitation difficult. In this paper, we investigated design recommendations that would enable self-monitored rehabilitation through clinical observations and focus group interviews with doctors and therapists. With this knowledge, we further explored Virtual Reality(VR)-based visual presentation and supplemental haptic motion guidance features in our implementation VReHab, a self-monitored and multimodal physical rehabilitation system with VR and vibrotactile and pneumatic feedback in a TKA rehabilitation context. We found that the third point of view real-time reconstructed motion on a virtual avatar overlaid with the target pose effectively provides motion awareness and guidance while haptic feedback helps enhance users' motion accuracy and stability. Finally, we implemented \systemname to facilitate self-monitored post-operative exercises and validated its effectiveness through a clinical study with 10 patients