Multiresolution analysis as an approach for tool path planning in NC machining

Wavelets permit multiresolution analysis of curves and surfaces. A complex curve can be decomposed using wavelet theory into lower resolution curves. The low-resolution (coarse) curves are similar to rough-cuts and high-resolution (fine) curves to finish-cuts in numerical controlled (NC) machining.;In this project, we investigate the applicability of multiresolution analysis using B-spline wavelets to NC machining of contoured 2D objects. High-resolution curves are used close to the object boundary similar to conventional offsetting, while lower resolution curves, straight lines and circular arcs are used farther away from the object boundary.;Experimental results indicate that wavelet-based multiresolution tool path planning improves machining efficiency. Tool path length is reduced, sharp corners are smoothed out thereby reducing uncut areas and larger tools can be selected for rough-cuts

RGB2LIDAR: Towards Solving Large-Scale Cross-Modal Visual Localization

We study an important, yet largely unexplored problem of large-scale cross-modal visual localization by matching ground RGB images to a geo-referenced aerial LIDAR 3D point cloud (rendered as depth images). Prior works were demonstrated on small datasets and did not lend themselves to scaling up for large-scale applications. To enable large-scale evaluation, we introduce a new dataset containing over 550K pairs (covering 143 km^2 area) of RGB and aerial LIDAR depth images. We propose a novel joint embedding based method that effectively combines the appearance and semantic cues from both modalities to handle drastic cross-modal variations. Experiments on the proposed dataset show that our model achieves a strong result of a median rank of 5 in matching across a large test set of 50K location pairs collected from a 14km^2 area. This represents a significant advancement over prior works in performance and scale. We conclude with qualitative results to highlight the challenging nature of this task and the benefits of the proposed model. Our work provides a foundation for further research in cross-modal visual localization.Comment: ACM Multimedia 202

Huangqi Injection (a Traditional Chinese Patent Medicine) for Chronic Heart Failure: A Systematic Review

Chronic heart failure (CHF) is a global public health problem. Therefore, novel and effective drugs that show few side-effects are needed. Early literature studies indicated that Huangqi injection is one of the most commonly used traditional Chinese patent medicines for CHF in China. As a large number of clinical studies has been carried out and published, it is essential to evaluate the effectiveness and safety of Huangqi injection. Therefore, we carried out this systematic review under the support of the framework of the Joint Sino-Italian Laboratory (JoSIL).To evaluate the efficacy and safety of Huangqi injection for CHF according to the available scientific knowledge.An extensive search including PubMed, EMBASE, CBM, the Cochrane Library and Chinese literature databases was performed up to July 2008. Clinical trials regarding Huangqi injection for the treatment of CHF were searched for, irrespective of languages. The quality of each trial was assessed according to the Cochrane Reviewers' Handbook 5.0, and RevMan 5.0 provided by the Cochrane Collaboration and STATA 9.2 were used for data analysis.After selection of 1,205 articles, 62 RCTs and quasi-RCTs conducted in China and published in Chinese journals were included in the review. The methodological quality of the trials was low. In most trials inclusion and exclusion criteria were not specified. Furthermore, only one study evaluated the outcomes for drug efficacy after an adequate period of time. For these reasons and because of the different baseline characteristics we did not conduct a meta-analysis.Although available studies are not adequate to draw a conclusion on the efficacy and safety of Huangqi injection (a traditional Chinese patent medicine), we hope that our work could provide useful experience on further studies on Huangqi injections. The overall level of TCM clinical research needs to be improved so that the efficacy of TCM can be evaluated by the international community and possibly some TCM can enter into the international market

Multiresolution analysis as an approach for tool path planning in NC machining

Wavelets permit multiresolution analysis of curves and surfaces. A complex curve can be decomposed using wavelet theory into lower resolution curves. The low-resolution (coarse) curves are similar to rough-cuts and high-resolution (fine) curves to finish-cuts in numerical controlled (NC) machining.;In this project, we investigate the applicability of multiresolution analysis using B-spline wavelets to NC machining of contoured 2D objects. High-resolution curves are used close to the object boundary similar to conventional offsetting, while lower resolution curves, straight lines and circular arcs are used farther away from the object boundary.;Experimental results indicate that wavelet-based multiresolution tool path planning improves machining efficiency. Tool path length is reduced, sharp corners are smoothed out thereby reducing uncut areas and larger tools can be selected for rough-cuts.</p

Tongue Coating Grading Identification Using Deep Learning for Hyperspectral Imaging Data

Tongue diagnosis is one of the four diagnostic methods of traditional Chinese medicine (TCM), which has important value in clinical disease diagnosis and efficacy evaluation. The change in tongue coating is a comprehensive cause of multi-dimensional changes such as color, texture, and substance. However, the color tongue image contains less spectral information, which may lead to the lack of key information in tongue diagnosis. Hyperspectral images can obtain reflection information of tongue images in hundreds of spectral bands. Unlike traditional color images, the rich spectral information can more accurately and sensitively describe and classify tongue coating, and has been widely applied in biomedical images. In this paper, we conducted feature extraction and analysis on hyperspectral images of different tongue coatings, and proposed a spectral-spatial feature deep learning framework to classification and quantitative recognition the tongue coating based on hyperspectral image features. Firstly, 360 hyperspectral images of tongue body were collected, and clinicians were identify all tongue coatings and divided them into 6 different grades. The hyperspectral features of each tongue coating area were extracted respectively. In order to reduce noise interference, singular spectrum analysis was used to preprocess the hyperspectral curve features. Considering the actual situation of tongue coating, a depth learning model was established to analyze the spectral and spatial feature of the hyperspectral tongue image to identified the grading of tongue coating. The experimental results showed that tongue coating with different quantization levels had different hyperspectral features, and the recognition rate of tongue coating quantization level can reach 87.21&#x0025; using the spatial-spectral features

Intelligent Control in the Application of a Rotary Dryer for Reduction in the Over-Drying of Cut Tobacco

The drying process is fundamental for cut tobacco processing. However, there are some problems related to the drying process such as overheating, or inconsistent control of moisture content. This paper shows how an intelligent controller is designed for an industrial rotary drying system. This controller is applied to a tobacco production unit to reduce overdried cut tobacco and improve the overall unit performance. The proposed control system aims to keep the content of moisture at the dryer outlet as close as possible to the optimal value and improve the homogeneity of the product without any operator intervention. The study shows that, if a reduction of humidity in the cut tobacco drying process is achieved using AI, the quality of the final product improves. In particular, if compared to regulatory control, the proposed method constantly monitors and adjusts the moisture content level in order to reduce the amount of overdried product. The findings of this paper indicate that the suggested process can save at least 222.2 kg of cut tobacco for each batch in the first stage of the drying process

Relative Quantitative Comparison between Lipotoxicity and Glucotoxicity Affecting the PARP-NAD-SIRT1 Pathway in Hepatocytes

Background/Aims: Insulin resistance in type 2 diabetes results from a combination of hyperglycemia and elevated free fatty acid (FFA) concentrations. However, the individual effects of glucotoxicity and lipotoxicity on cell function have not been determined. Methods: To compare the effects of increased FFAs and glucose levels on the PARP-NAD-SIRT1 pathway, which modulates insulin sensitivity, we cultured HepG2 hepatocytes with 300 or 500 µM oleic acid (OA) or 30 mM glucose for 1-4 days. PARP activity, NAD level, SIRT1 expression and insulin receptor phosphorylation were determined. Results: PARP activity was higher while NAD level and SIRT1 expression were lower in OA-treated cells than in control cells. Insulin receptor phosphorylation in response to insulin stimulation was attenuated under OA stimulation. Compared to glucose, OA produced a more rapid effect on the PARP-NAD-SIRT1 pathway in HepG2 cells. The reduction in SIRT1 expression and insulin receptor phosphorylation was similar in cells treated with 500 μM OA for 1 day and those treated with 30 mM glucose for 4 days. In addition to PARP activation, the LXRα activator T0901317 also affected SIRT1 expression. Conclusion: FFAs modulated cellular function through multiple ways, and induced more rapid and more potent cytotoxicity than glucose