Internet cross-media retrieval based on deep learning

With the development of Internet, multimedia information such as image and video is widely used. Therefore, how to find the required multimedia data quickly and accurately in a large number of resources , has become a research focus in the field of information process. In this paper, we propose a real time internet cross-media retrieval method based on deep learning. As an innovation, we have made full improvement in feature extracting and distance detection. After getting a large amount of image feature vectors, we sort the elements in the vector according to their contribution and then eliminate unnecessary features. Experiments show that our method can achieve high precision in image-text cross media retrieval, using less retrieval time. This method has a great application space in the field of cross media retrieval

Knowledge Discovery and Machine Learning: Research in Gingivitis Detection

Gingivitis is a high-risk condition that causes dietary issues in older people. The study of gingivitis is more difficult in the realm of medical image analysis due to the absence and complexity of dental image analysis. As traditional clinical diagnosis takes time and money and necessitates a lot of physical effort on the part of competent clinicians. In contrast, deep learning allows for automated medicine via picture analysis. However, several obstacles remain in medicine, such as poor machine model performance, inadequate training data, and expensive labeling costs, to name a few. These difficulties encourage the development of data- and knowledge-aware deep learning approaches that can be used for a variety of medical activities without requiring considerable human labeling and that incorporate domain-specific information throughout the learning process. This paper reviews and analyses research in computer-aided diagnosis and medical image deep learning, with a focus on the challenges in the field of gingivitis image detection, and proposes model performance achieved by combining different image extraction methods and different classification methods. At the same time, some traditional feature extraction methods and standard computer-aided diagnosis methods are introduced. In this paper, a feature extraction model based on fractional Fourier entropy and wavelet energy entropy is proposed for gingival image segmentation, and various classification and optimization techniques are combined. By evaluating the reintegrated medical images, the experimental results of the gingivitis detection model based on fractional Fourier entropy feature extraction combined with particle swarm optimization neural network show that the detection method significantly reduces the detection space and the complexity of image information. The improved algorithm can cluster the sample data efficiently and accurately, and the accuracy is higher than that of advanced gingival image diagnosis technology.</p

Relevant constants for the CSTR dynamic model.

<p>Relevant constants for the CSTR dynamic model.</p

Robust shrinking ellipsoid model predictive control for linear parameter varying system

<div><p>In this paper, a new off-line model predictive control strategy is presented for a kind of linear parameter varying system with polytopic uncertainty. A nest of shrinking ellipsoids is constructed by solving linear matrix inequality. By splitting the objective function into two parts, the proposed strategy moves most computations off-line. The on-line computation is only calculating the current control to assure the system shrinking into the smaller ellipsoid. With the proposed formulation, the stability of the closed system is proved, followed with two numerical examples to demonstrate the proposed method’s effectiveness in the end.</p></div

Table_1_Case report: Visual snow as the presenting symptom in multiple evanescent white dot syndrome. Two case reports and literature review.docx

PurposeMultiple evanescent white dot syndrome (MEWDS) usually manifests as photopsia, enlarged blind spots, scotomas, and blurred vision, which can be classified into positive and negative visual phenomena. Visual snow and chromatopsia were rarely reported in these patients. Herein, we described two Chinese female patients with MEWDS who initially presented with visual snow, and one of them also had yellow-tinged vision.MethodsFirst, we performed the chart review of two patients. Second, we reviewed the English literature for all cases of MEWDS through PubMed until December 2021, using the terms “MEWDS” or “multiple evanescent white dot syndrome.” We concluded on all the reported patients' demographic features and symptoms. The visual acuity of patients with/without positive or negative visual phenomena was compared through one-way ANOVA.ResultsPatient 1: A 27-year-old Chinese woman experienced continuous visual snow and yellow-tinged vision in the right eye for a week. She noticed tiny white and black dots involving the entire visual field and shimmering light inferiorly. Patient 2: A 22-year-old Chinese woman complained of a gray area with continuous visual snow in the temporal visual field of the left eye for 5 days. The ocular examinations, including fundus autofluorescence (FAF), optical coherence tomography (OCT), and indocyanine green angiography (ICGA), confirmed the diagnosis of MEWDS. Their symptoms resolved spontaneously without treatment. We found 60 MEWDS case reports (147 cases) in PubMed. The mean age was 31.2 years old. The mean LogMAR best-corrected visual acuity was 0.35 ± 0.39 at the first visit and 0.01 ± 0.16 at the last visit. The most common symptoms included blurred vision (72.8%), enlarged blind spot (42.2%), photopsia (37.4%), and scotoma (33.3%). We found the patients with only positive visual phenomena had significantly worse visual acuity at the first and last visit than patients with only negative visual phenomena (p = 0.008) or the patients with both positive and negative visual phenomena (p = 0.026). Four cases similar to visual snow were discovered. Compared to the MEWDS patients without visual snow, the patients with visual snow tend to have a larger proportion of females (p = 0.005) and a better visual acuity at the first visit (p = 0.007).ConclusionHerein, we expand upon the clinical manifestations of MEWDS with visual snow, and the symptoms attributable to visual snow could precede the onset of MEWDS. Neurologists and ophthalmologists should carefully rule out occult chorioretinopathy before diagnosing visual snow syndrome.</p

States of the closed-loop system of example 1.

<p>States of the closed-loop system of example 1.</p

On-line numerical burdens in example 1.

<p>On-line numerical burdens in example 1.</p

Additional file 1: of Prospective associations between pulse pressure and cognitive performance in Chinese middle-aged and older population across a 5-year study period

Final dataset. (XLSX 2360 kb

Factors associated with the number of overweight and obese pregnant women based on panel data model between 2005 and 2013.

<p>Factors associated with the number of overweight and obese pregnant women based on panel data model between 2005 and 2013.</p

Estimated global overweight and obesity burden in pregnant women based on panel data model

<div><p>Objective</p><p>To estimate the global and country-level burden of overweight and obesity among pregnant women from 2005 to 2014.</p><p>Methods</p><p>Publicly accessible country-level data were collected from <i>the World Health Organization</i>, <i>the World Bank</i> and <i>the Food</i> and <i>Agricultural Organization</i>. We estimated the number of overweight and obese pregnant women among 184 countries and determined the time-related trend from 2005 to 2014. Based on panel data model, we determined the effects of food energy supply, urbanization, gross national income and female employment on the number of overweight and obese pregnant women.</p><p>Results</p><p>We estimated that 38.9 million overweight and obese pregnant women and 14.6 million obese pregnant women existed globally in 2014. In upper middle income countries and lower middle income countries, there were sharp increases in the number of overweight and obese pregnant women. In 2014, the percentage of female with overweight and obesity in India was 21.7%, and India had the largest number of overweight and obese pregnant women (4.3 million), which accounted for 11.1% in the world. In the United States of America, a third of women were obese, and the number of obese pregnant women was 1.1 million. In high income countries, caloric supply and urbanization were positively associated with the number of overweight and obese pregnant women. The percentage of employment in agriculture was inversely associated with the number of overweight and obese pregnant women, but only in upper middle income countries and lower middle income countries.</p><p>Conclusion</p><p>The number of overweight and obese pregnant women has increased in high income and middle income countries. Environmental changes could lead to increased caloric supply and decreased energy expenditure among women. National and local governments should work together to create a healthy food environment.</p></div