Article Type: Research Article
Abstract: With the continuous progress of data science, big data technology has been continuously integrated into human daily life. The application of big data technology in the field of education to improve the teaching and learning efficiency of teachers and students has become the focus of current scholars. With the popularization of the concept of the Internet of Everything, the Internet of Things technology has gradually become a hot spot for technology fans. It is widely used in home and body-worn devices. Applying the Internet of Things technology in the education field to obtain student status feedback data can make teachers …more accurately understand the goals of student learning. The continuous raging of the epidemic has led to the change of many courses from offline face-to-face teaching to home online teaching, which has brought about a huge change in the traditional offline face-to-face physical education teaching method. Therefore, in order to better protect against the epidemic and prevent the spread of the epidemic more effectively, X Academy responded to the country’s call to “suspend classes without teaching, and without stopping learning”, so that physical education courses other than other cultural courses will be conducted offline and face-to-face. Teaching has changed to online physical education. This paper firstly defines the concepts of big data, Internet of Things and online physical education teaching, and then conducts research on the current situation and countermeasures of online physical education teaching. Find optimized countermeasures, so that X College can get better teaching results when it conducts online physical education teaching again in the face of similar public health emergencies in the future, allowing students to exercise, improve physical fitness, enhance sports skills, and enhance their own resistance. power goal. The research method of this paper mainly adopts the data analysis method of questionnaire survey and statistics. Through the second survey, it is found that all aspects of online physical education teaching have been improved after adopting the improved strategy. Show more
Keywords: Online sports teaching, big data, Internet of Things
DOI: 10.3233/JCM-226589
Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 2, pp. 725-735, 2023
Authors: Tay, Francis Eng Hock | Cao, Li Juan
Article Type: Research Article
Abstract: Recently, support vector machine (SVM) has been receiving increasing attention in the field of regression estimation due to its remarkable characteristics such as good generalization performance, the absence of local minima and sparse representation of the solution. However, within the SVMs framework, there are very few established approaches for identifying important features. Selecting significant features from all candidate features is the first step in regression estimation, and this procedure can improve the network performance, reduce the network complexity, and speed up the training of the network. This paper investigates the use of saliency analysis (SA) and genetic algorithm (GA) in …SVMs for selecting important features in the context of regression estimation. The SA measures the importance of features by evaluating the sensitivity of the network output with respect to the feature input. The derivation of the sensitivity of the network output to the feature input in terms of the partial derivative in SVMs is presented, and a systematic approach to remove irrelevant features based on the sensitivity is developed. GA is an efficient search method based on the mechanics of natural selection and population genetics. A simple GA is used where all features are mapped into binary chromosomes with a bit “1” representing the inclusion of the feature and a bit of “0” representing the absence of the feature. The performances of SA and GA are tested using two simulated non-linear time series and five real financial time series. The experiments show that with the simulated data, GA and SA detect the same true feature set from the redundant feature set, and the method of SA is also insensitive to the kernel function selection. With the real financial data, GA and SA select different subsets of features. Both selected feature sets achieve higher generation performance in SVMs than that of the full feature set. In addition, the generation performance between the selected feature sets of GA and SA is similar. All the results demonstrate that that both SA and GA are effective in SVMs for identifying important features. Show more
Keywords: feature selection, support vector machines, structural risk minimization principle, saliency analysis, genetic algorithm
DOI: 10.3233/IDA-2001-5302
Citation: Intelligent Data Analysis, vol. 5, no. 3, pp. 191-209, 2001
Authors: Tay, Francis Eng Hock | Cao, Li Juan
Article Type: Research Article
Abstract: A two-stage neural network architecture constructed by combining Support Vector Machines (SVMs) with self-organizing feature map (SOM) is proposed for financial time series forecasting. In the first stage, SOM is used as a clustering algorithm to partition the whole input space into several disjoint regions. A tree-structured architecture is adopted in the partition to avoid the problem of predetermining the number of partitioned regions. Then, in the second stage, multiple SVMs, also called SVM experts, that best fit each partitioned region are constructed by finding the most appropriate kernel function and the optimal learning parameters of SVMs. The Santa Fe …exchange rate and five real futures contracts are used in the experiment. It is shown that the proposed method achieves both significantly higher prediction performance and faster convergence speed in comparison with a single SVM model. Show more
Keywords: financial time series forecasting, non-stationarity, support vector machines, self-organizing feature map
DOI: 10.3233/IDA-2001-5405
Citation: Intelligent Data Analysis, vol. 5, no. 4, pp. 339-354, 2001
Authors: Li, Xian Min | Cao, Li Li
Article Type: Research Article
Abstract: BACKGROUND: Metastatic gastric carcinoma (GC) is a typically incurable disease. The progression of anti-metastatic treatment is hampered because the underlying mechanisms regulating the metastasis of GC cell are not well illuminated. OBJECTIVE: Therefore, further elucidation of the molecular mechanism behind the metastatic traits of GC cells is needed for optimizing GC treatment. METHODS: The levels of GOLM1 and MMP13 in GC cells and tissues were measured by using qPCR assay. The growth of GC cells in vitro was detected using MTS and colony formation assays. The migration and invasion of GC cells was analyzed using wound healing test and Transwell …invasion assay. The level of MMP13 in GC cell was measured using immunoblotting and the level of GOLM1 was measured using immunofluorescence staining. The role of GOLM1 on the distant metastasis of GC SGC7910 cell was analyzed using experimental metastasis assay. Transplanted tumor model was constructed to analyze the influence of GOLM1 on GC cell growth in vivo . RESULTS: Here, we report that GOLM1 is over-expressed in GC and knockdown GOLM1 impairs the aggressive phenotypes of GC cell in vitro . Furthermore, downregulation of GOLM1 restrains the tumor growth of GC cell in nude mice. Nevertheless, upregulation of GOLM1 distinctly elevated the growth, migration ability and invasiveness of GC SGC7910 cell. Finally, GOLM1 increases the metastatic phenotypes of GC cell in a MMP13-dependent manner. CONCLUSIONS: Altogether, this investigation demonstrates the crucial function of GOLM1 in the progression of GC, which indicating GOLM1 as a potential target for GC treatment. Show more
Keywords: GOLM1, gastric carcinoma, MMP13, metastasis
DOI: 10.3233/CBM-190301
Citation: Cancer Biomarkers, vol. 26, no. 4, pp. 421-430, 2019
Authors: Xu, Wenjie | Lu, Rui | Hu, Yun | Cao, Li | Wang, Tao | Tan, Hao | Meng, Xuehuan | Ming, Ye | Zheng, Leilei
Article Type: Research Article
Abstract: OBJECTIVE: To assess reliability of cone-beam CT (CBCT) for nasolabial soft tissue measurements in patients with skeletal class III malocclusion based on 3-dimensional (3D) facial scanner results. METHODS: CBCT and 3D facial scan images of 20 orthognathic patients are used in this study. Eleven soft tissue landmarks and 15 linear and angular measurements are identified and performed. For qualitative evaluation, Shapiro-Wilk test and Bland-Altman plots are applied to analyze the equivalence of the measurements derived from these two kinds of images. To quantify specific deviation of CBCT measurements from facial scanner, the latter is set as a benchmark, and mean …absolute difference (MAD) and relative error magnitude (REM) for each variable are also calculated. RESULTS: Statistically significant differences are observed in regions of nasal base and lower lip vermilion between two methods. MAD value for all length measurements are less than 2 mm and for angular variables < 8°. The average MAD and REM for length measurements are 0.94 mm and 5.64%, and for angular measurements are 2.27° and 3.78%, respectively. CONCLUSIONS: The soft tissue results measured by CBCT show relatively good reliability and can be used for 3D measurement of soft tissue in the nasolabial region clinically. Show more
Keywords: Cone-beam CT, facial scanner, 3-dimensional cephalometry
DOI: 10.3233/XST-211018
Citation: Journal of X-Ray Science and Technology, vol. 30, no. 1, pp. 195-206, 2022
Authors: Cui, Pei-Jing | Zheng, Lan | Cao, Li | Wang, Ying | Deng, Yu-Lei | Wang, Gang | Xu, Wei | Tang, Hui-Dong | Ma, Jian-Fang | Zhang, Ting | Ding, Jian-Qing | Cheng, Qi | Chen, Sheng-Di
Article Type: Short Communication
Abstract: We conducted a case-control study to determine the prevalence of the CALHM1 P86L polymorphism (rs2986017) in patients with Alzheimer's disease (AD) in the Chinese population of mainland China, and also to clarify whether this polymorphism is a risk factor for AD. Fourteen heterozygous P86L carriers were identified among 198 AD patients. One control subject was also found to be a P86L heterozygous carrier. The allelic frequencies of the AD patients and control subjects were found to be significantly different. Our study indicates that the CALHM1-P86L polymorphism is associated with AD in the ethnic Chinese Han.
Keywords: Alzheimer's disease, CALHM1, P86L, polymorphism
DOI: 10.3233/JAD-2010-1207
Citation: Journal of Alzheimer's Disease, vol. 19, no. 1, pp. 31-35, 2010
Authors: Walker, Matthew D. | Volta, Mattia | Cataldi, Stefano | Dinelle, Katherine | Beccano-Kelly, Dayne | Munsie, Lise | Kornelsen, Rick | Mah, Chenoa | Chou, Patrick | Co, Kimberley | Khinda, Jaskaran | Mroczek, Marta | Bergeron, Sabrina | Yu, Katrina | Cao, Li Ping | Funk, Natalja | Ott, Thomas | Galter, Dagmar | Riess, Olaf | Biskup, Saskia | Milnerwood, Austen J. | Stoessl, A. Jon | Farrer, Matthew J. | Sossi, Vesna
Article Type: Research Article
Abstract: Background: A major risk-factor for developing Parkinson's disease (PD) is genetic variability in leucine-rich repeat kinase 2 (LRRK2), most notably the p.G2019S mutation. Examination of the effects of this mutation is necessary to determine the etiology of PD and to guide therapeutic development. Objective: Assess the behavioral consequences of LRRK2 p.G2019S overexpression in transgenic rats as they age and test the functional integrity of the nigro-striatal dopamine system. Conduct positron emission tomography (PET) neuroimaging to compare transgenic rats with previous data from human LRRK2 mutation carriers. Methods: Rats overexpressing human LRRK2 p.G2019S were generated by BAC transgenesis and compared to …non-transgenic (NT) littermates. Motor skill tests were performed at 3, 6 and 12 months-of-age. PET, performed at 12 months, assessed the density of dopamine and vesicular monoamine transporters (DAT and VMAT2, respectively) and measured dopamine synthesis, storage and availability. Brain tissue was assayed for D2, DAT, dopamine and cAMP-regulated phosphoprotein (DARPP32) and tyrosine hydroxylase (TH) expression by Western blot, and TH by immunohistochemistry. Results: Transgenic rats had no abnormalities in measures of striatal dopamine function at 12 months. A behavioral phenotype was present, with LRRK2 p.G2019S rats performing significantly worse on the rotarod than non-transgenic littermates (26% reduction in average running duration at 6 months), but with normal performance in other motor tests. Conclusions: Neuroimaging using dopaminergic PET did not recapitulate prior studies in human LRRK2 mutation carriers. Consistently, LRRK2 p.G2019S rats do not develop overt neurodegeneration; however, they do exhibit behavioral abnormalities. Show more
Keywords: Parkinson's disease, LRRK2 protein, human, dopaminergic neurons, transgenic rats, dopamine, brain imaging, positron-emission tomography
DOI: 10.3233/JPD-140344
Citation: Journal of Parkinson's Disease, vol. 4, no. 3, pp. 483-498, 2014
