Comparative Study on Engineering Education in China and USA

The project, Comparative Study on Engineering Education in China and USA, studied the industrial need of professionals and engineering education in China and USA respectively in BJTU and WPI. The study evaluated the industrial need and the current engineering education practice including curriculums and methods of assessment. Based on the data analysis, we provided constructive perspectives on the changes of engineering education

Predicting Policyholder Behavior and Benefit Utilization: An Analysis on Long-Term Care Insurance

In order to better serve their customers, a project to create a methodology for identifying variables that could indicate future long-term care insurance usage was commissioned by Ability Resources, Inc. As a basis for constructing a predictive model, tools such as SAS and Excel were implemented. A k-means clustering algorithm in SAS was utilized to group policyholders with similar characteristics, and a performance evaluation was executed in Excel. Together, these processes created a tool that determined the impact each characteristic had on policyholder benefit utilization. The validity of the process was assessed by applying it to supplemental data generated by the team. After several trials, the Variable Identification Procedure proved accurate

GPU Accelerated Color Correction and Frame Warping for Real-time Video Stitching

Traditional image stitching focuses on a single panorama frame without considering the spatial-temporal consistency in videos. The straightforward image stitching approach will cause temporal flicking and color inconstancy when it is applied to the video stitching task. Besides, inaccurate camera parameters will cause artifacts in the image warping. In this paper, we propose a real-time system to stitch multiple video sequences into a panoramic video, which is based on GPU accelerated color correction and frame warping without accurate camera parameters. We extend the traditional 2D-Matrix (2D-M) color correction approach and a present spatio-temporal 3D-Matrix (3D-M) color correction method for the overlap local regions with online color balancing using a piecewise function on global frames. Furthermore, we use pairwise homography matrices given by coarse camera calibration for global warping followed by accurate local warping based on the optical flow. Experimental results show that our system can generate highquality panorama videos in real time

STCA-SNN: self-attention-based temporal-channel joint attention for spiking neural networks

Spiking Neural Networks (SNNs) have shown great promise in processing spatio-temporal information compared to Artificial Neural Networks (ANNs). However, there remains a performance gap between SNNs and ANNs, which impedes the practical application of SNNs. With intrinsic event-triggered property and temporal dynamics, SNNs have the potential to effectively extract spatio-temporal features from event streams. To leverage the temporal potential of SNNs, we propose a self-attention-based temporal-channel joint attention SNN (STCA-SNN) with end-to-end training, which infers attention weights along both temporal and channel dimensions concurrently. It models global temporal and channel information correlations with self-attention, enabling the network to learn ‘what’ and ‘when’ to attend simultaneously. Our experimental results show that STCA-SNNs achieve better performance on N-MNIST (99.67%), CIFAR10-DVS (81.6%), and N-Caltech 101 (80.88%) compared with the state-of-the-art SNNs. Meanwhile, our ablation study demonstrates that STCA-SNNs improve the accuracy of event stream classification tasks

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Case Study Research in Tesla (China) Marketing Strategy Application During Covid-19

Background: In the past two years, the outbreak of the coronavirus has had a major impact on the world economy, and has a considerable negative impact on the performance and sales of the automobile manufacturing industry. Enterprises need to sum up their experience. Tesla's successful case can be used as a reference for analysis. . Purpose: In response to the substantial increase in sales performance of Tesla's Chinese market during the epidemic, relevant market strategy analysis was made, and the researchers tried to summarize relevant experience to provide reference for the automotive industry. Method: The researchers used a relatively flexible and exploratory qualitative approach, conducting semi-structured interviews with seven current Tesla employees and using secondary sources to aid in proving the veracity and viability of the information. Conclusion: The results show that most of the targeted strategies implemented by Tesla during the epidemic are effective, and the application of various strategies is related to changes in sales performance. The researchers collected raw data through interviews, analyzed why Tesla used these strategies, and evaluated the application effects of the main strategies. At the same time, the researchers also put forward our own views and opinions

Assembly and phylogenetic analysis of the complete chloroplast genome of Citrus aurantium (Rutaceae)

Citrus aurantium (C. aurantium), belonging to the family Rutaceae, is usually utilized as a flavoring and acidifying agent for food. This study assembled and characterized the complete chloroplast (cp) genome of C. aurantium. The cp genome was 160,140 bp in length, containing a pair of inverted repeats (IRs, 26,996 bp each), which is separated by a large single-copy (LSC, 87,763 bp) region and a small single copy (SSC, 18,385 bp) region. The cp genome has overall GC content of 38.48% and 135 genes, composing of 90 protein-coding genes, 37 tRNA genes and 8 rRNA genes. Phylogenetic analysis based on 25 cp genomes highly supported that C. aurantium was evolutionarily close to Cirtus sinensis (C. sinensis)

Case Study Research in Tesla (China) Marketing Strategy Application During Covid-19

Background: In the past two years, the outbreak of the coronavirus has had a major impact on the world economy, and has a considerable negative impact on the performance and sales of the automobile manufacturing industry. Enterprises need to sum up their experience. Tesla's successful case can be used as a reference for analysis. . Purpose: In response to the substantial increase in sales performance of Tesla's Chinese market during the epidemic, relevant market strategy analysis was made, and the researchers tried to summarize relevant experience to provide reference for the automotive industry. Method: The researchers used a relatively flexible and exploratory qualitative approach, conducting semi-structured interviews with seven current Tesla employees and using secondary sources to aid in proving the veracity and viability of the information. Conclusion: The results show that most of the targeted strategies implemented by Tesla during the epidemic are effective, and the application of various strategies is related to changes in sales performance. The researchers collected raw data through interviews, analyzed why Tesla used these strategies, and evaluated the application effects of the main strategies. At the same time, the researchers also put forward our own views and opinions