A Real-time Faint Space Debris Detector With Learning-based LCM

With the development of aerospace technology, the increasing population of space debris has posed a great threat to the safety of spacecraft. However, the low intensity of reflected light and high angular velocity of space debris impede the extraction. Besides, due to the limitations of the ground observation methods, small space debris can hardly be detected, making it necessary to enhance the spacecraft's capacity for space situational awareness (SSA). Considering that traditional methods have some defects in low-SNR target detection, such as low effectiveness and large time consumption, this paper proposes a method for low-SNR streak extraction based on local contrast and maximum likelihood estimation (MLE), which can detect space objects with SNR 2.0 efficiently. In the proposed algorithm, local contrast will be applied for crude classifications, which will return connected components as preliminary results, and then MLE will be performed to reconstruct the connected components of targets via orientated growth, further improving the precision. The algorithm has been verified with both simulated streaks and real star tracker images, and the average centroid error of the proposed algorithm is close to the state-of-the-art method like ODCC. At the same time, the algorithm in this paper has significant advantages in efficiency compared with ODCC. In conclusion, the algorithm in this paper is of high speed and precision, which guarantees its promising applications in the extraction of high dynamic targets.Comment: 13 pages, 28 figures, normal articl

The Wing Pavilion:A Participatory Action Approach to Bamboo Architectural Research in Chinese Universities

The application of bamboo construction techniques in Chinese architecture remains behind its potential. Chinese universities began conducting participatory action research on bamboo as a building material. Students from the Huazhong University of Science and Technology designed the wing pavilion: a temporary bamboo structure built in six days inside the Nan Sha Bird Eco-Park, Guangzhou. The process combined handcraft and digital techniques within five steps: pre-design, formulation, successive answers, project, and conclusion of the theory. Eight bamboo arches interconnected to create a six-meter span roof. Each arch was pre-fabricated with two layers of split bamboo and one slender bamboo culm as reinforcement. The cartesian plane technique was utilised to overcome the indeterminacy of bamboo. Details could be fuller, and the roof lacked enough strength. More important than a perfect result, the principles of bamboo architecture transferred to students, and a range of scales can replicate the methodology. The technical solution reflected a Western functionality with an Asian essence. Many of the now underprivileged people will benefit from it since bamboo is abundant in China. Keywords: Bamboo architecture, participatory action research, green building, architectural education. DOI: 10.7176/ISDE/10-5-03 Publication date:June 30th 201

Image Cluster Berdasarkan Warna Untuk Identifikasi Kematangan Buah Tomat Dengan Metode Valley Tracing

Ciri yang digunakan dalam identifikasi kematangan buah adalah ciri warna (fitur R, G, dan B). Selanjutnya dilakukan clustering dengan metode Single Linkage Hierarchical Method (SLHM) terhadap ciri warna yang diperoleh. Dalam clustering, umumnya harus dilakukan inisialisasi jumlah cluster yang diinginkan terlebih dahulu, padahal pada beberapa kasus clustering, user bahkan tidak tahu berapa banyak cluster yang bisa dibangun. Untuk itu, dalam penelitian ini diaplikasikan metode Valley Tracing. Metode ini merupakan constraint yang akan melakukan identifikasi terhadap pergerakan variance dari tiap tahap pembentukan cluster, dan menganalisa polanya untuk membentuk suatu cluster secara otomatis (automatic clustering). Jumlah cluster yang diperoleh menunjukkan jumlah buah yang diidentifikasi, kemudian nama buah dan jenis kematangan masing-masing buah diperoleh dengan membandingkan nilai centroid tiap cluster dengan nilai centroid data training yang sebelumnya telah disimpan dalam database dan mempunyai label nama buah

Improving the Predictability of Severe Convective Weather Processes by Using Wind Vectors and Potential Temperature Changes: A Case Study of a Severe Thunderstorm

Strong, local convective weather events are capable of causing extensive damage, but weather observation systems with limited resolution and radar monitoring can typically provide only a few minutes to hours of prior warning time. This paper presents a comprehensive case study of the cumulative evolution of several characteristic quantities during one extremely severe convective weather process. The research results indicate that the main feature of strong convective weather is the uneven distribution of thermal energy in the atmosphere, and the structure of this heat distribution determines the level of instability in the atmosphere. A vertical “clockwise rolling current” occurs in the wind field structure at the beginning of the process, and this is accompanied by a rapid drop in temperature at the top of the troposphere. When these signs occurred in the case study, radar technology was used to refine the precipitation region and spatial characteristics of the approaching storm. The height and vertical evolution of radar echoes were indicative of the characteristics of the system’s movement through space. Such findings may be useful for improving the forecasting times for strong convective weather

How does capability reconfiguration impact the innovation performance of Chinese manufacturing firms?

This study explores the relationship between capability reconfiguration and firm innovation performance by analyzing a sample of 375 manufacturing firms in China. The results suggest that the relationship between capability reconfiguration and innovation performance is affected by both the catch-up stage and the mode of capability reconfiguration (evolution or substitution). The catch-up stage of enterprises significantly impacts the moderating effects of innovation magnitude on the relationship between capability substitution and firm innovation performance, however, it has no obvious effects on the moderation of innovation magnitude on the relationship between capability evolution and innovation performance. This study contributes to the theory of dynamic capability and catch-up by revealing how innovation magnitude affects capability reconfiguration and subsequent innovation performance in different catch-up stages. The implication of this study is to remind managers to take full account of the innovation magnitude and catch-up stage in their decision-making

The impact of income level on skeletal muscle health in rural Chinese older residents: a study of mediating effects based on dietary knowledge

China’s rural residents have basically solved the problem of subsistence, but due to aging, the prevalence of sarcopenia (abbreviated as sarcopenia) has been increasing year by year, especially the skeletal muscle health of the rural older residents has not been sufficiently paid attention to, so analyses of the impact of income level on the skeletal muscle health of the older people in rural areas of China are of great practical significance. Based on the annual data of the China Health and Nutrition Survey (CHNS) in 2006, 2009, and 2011, we introduced the mediator variable of dietary knowledge and used the Probit model regression, mediation effect model, and instrumental variable regression to assess the skeletal muscle health status of the rural older people in China and explore the mechanism of the influence of the income level on the skeletal muscle health of the rural older residents in China. The primary objectives of this study were to evaluate the impact of income level on the skeletal muscle health status of older adults living in rural areas of China and to investigate the underlying mechanisms. By analyzing the findings of this study, our aim is to establish a correlation between the economic status and skeletal muscle health of older adults in rural communities, as well as elucidate the influence of income level and dietary knowledge on their skeletal muscle health. Through the attainment of these objectives, we hope to provide valuable insights and recommendations for enhancing skeletal muscle health among the rural older population in China. Based on our research findings, it can be inferred that there was a significant association between the financial status of rural older adults and their skeletal muscle health. Additionally, the prevalence of sarcopenia was lower among individuals with higher income levels, and there was a negative correlation between the prevalence of sarcopenia and the level of dietary knowledge among rural older individuals. The knowledge of dietary knowledge level of rural older people plays a mediating role in the income level and the prevalence of sarcopenia. Moreover, with the change in income level and the increase in age, the change in skeletal muscle health status showed obvious heterogeneity, in which the effect on the relatively younger (65–70 years old) samples was greater. Therefore, sustained income growth remains an effective way to improve the skeletal muscle health of older rural residents. At the same time, improving dietary knowledge and dietary quality among the older people is important in preventing a decline in muscle strength and physical function and in preventing the onset of sarcopenia

New Image Restoration Method Based on Multiple Aperture Defocus Images for Microscopic Images

Abstract: Image deconvolution is an effective image restoration technique to improve the quality of digital microscopic images resulting from out-of-focus blur. To solve the severely ill-posed problem of traditional Richardson-Lucy method, considering the point spread difference of various directions, a new microscope image restoration method based on multiple defocused images of different aperture is proposed. The maximumlikelihood estimation is used to suppress the ringing artifacts and noises sensitivity of microscope image. Experimental results show that the proposed algorithm performs better than Richardson-Lucy method and improve peak-signal-to-noise-rate about 4 dB

Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research

The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction