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3rd IEEE International Conference on Communications, Information System and Computer Engineering, CISCE 2021

作者： Wang, Weili Cao, Yongchun Lin, Qiang Man, Zhengxing Li, Tongtong Key Laboratory of China's Ethnic Languages and Information Technology Ministry of Education Northwest Minzu University Gansu Lanzhou730000 China School of Mathematics and Computer Sciece Northwest Minzu University Gansu Lanzhou730030 China Key Laboratory of Streaming Data Computing and Applications Northwest Minzu University Gansu Lanzhou730030 China

ISBN: (纸本)9780738112152

SPECT bone imaging is an effective method for early diagnosis of bone metastases from malignant tumors. In addition to bone metastases, arthritis and other diseases will also appear as abnormal metabolic distribution areas in SPECT images. Early diagnosis of arthritis based on SPECT bone imaging is of great significance for the treatment of patients. This article takes SPECT bone imaging as the object to study and construct an arthritis disease classifier based on convolutional neural network. Firstly, data preprocessing is carried out to deal with the impact of small amount of medical image data and individual differences between imaging data on the classification effect of deep learning model. Secondly, a classifier suitable for low resolution and large-scale SPECT images is constructed based on VGGNet. Finally, based on a set of real SPECT bone imaging data sets to compare the arthritis diagnosis results of different depth classification models. The experimental results show that the classifier constructed in this paper can effectively detect arthritis diseases, and the accuracy, recall and F-1 values are 0.9309, 0.9511 and 0.9284, respectively. © 2021 IEEE.

关键词： Diseases

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CNN-Based Classifier for Diagnosing SPECT Bone Images 3

CNN-Based Classifier for Diagnosing SPECT Bone Images

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3rd IEEE International Conference on Communications, Information System and Computer Engineering, CISCE 2021

作者： Guo, Yanru Chen, Xiaoyan Zheng, Ziwen Lin, Qiang School of Mathematics and Computer Sciece Northwest Minzu University Gansu Lanzhou730030 China Key Laboratory of Chinese National Language and Information Technology Ministry of Education Northwest Minzu University Gansu Lanzhou730030 China Key Laboratory of Streaming Data Computing and Applications Northwest Minzu University Gansu Lanzhou730030 China

ISBN: (纸本)9780738112152

To assist nuclear medicine doctors for quickly and accurately identifying bone metastases, in this work, we develop a convolutional neural network to automatically classify whole-body SPECT bone scans. First, the original data of SPECT bone scans are augmented by using geometric transformation. Second, two deep model VGG5 and VGG7 are developed by following the famous VGG model, where a 2\times 1 maximum pooling is introduced before the first layer convolution. Experimental evaluation conducted on real-world SPECT images shows that the developed models are workable to classify SPECT images into categories of concern. © 2021 IEEE.

关键词： Convolutional neural networks

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The acyclic coloring of the Corona product and Edge corona product of special graphs

The acyclic coloring of the Corona product and Edge corona p...

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2020 International Conference on Computer Science and Management Technology, ICCSMT 2020

作者： Lu, Qiqi Tian, Shuangliang Peng, Lizhen Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University School of Mathematics and Computer Science Lanzhou China

ISBN: (纸本)9781728186689

An acyclic coloring of a graph is a proper vertex coloring such that there are no bichromatic cycles. The acyclic chromatic number of G, denoted a(G), is the minimum number of colors required for acyclic coloring of a graph G. We study the acyclic coloring of the corona product, edge corona product of paths or circles and any simple graph, and the corresponding acyclic chromatic number are determined. © 2020 IEEE.

关键词： Coloring

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Adjacent vertex distinguishing incidence coloring of semi-strong product of paths

Adjacent vertex distinguishing incidence coloring of semi-st...

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2020 International Conference on Computer Science and Management Technology, ICCSMT 2020

作者： Peng, Lizhen Tian, Shuangliang Lu, Qiqi Northwest Minzu University School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Lanzhou China

ISBN: (纸本)9781728186689

Adjacent vertex distinguishing incidence coloring of graph G is an incidence coloring that satisfies that adjacent vertices have different color sets, and the minimum color number is called the adjacent vertex distinguishing incidence coloring number of graph G, which is denoted as χai (G). In this paper, we study the adjacent vertex distinguishing incidence coloring of semi-strong products and strong products of paths of different orders, and obtain the exact values of the corresponding coloring numbers. © 2020 IEEE.

关键词： Coloring

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Automated classification of textual SPECT diagnostic reports with TextCNN model

Automated classification of textual SPECT diagnostic reports...

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2020 International Conference on Communications, Information System and Software Engineering, CISSE 2020

作者： Han, Chengcheng Lin, Qiang Man, Zhengxing Cao, Yongchun Wang, Haijun School of Mathematics and Computer Science Northwest Minzu University No. 1 Xibei Xincun Rd Lanzhou city Gansu Province730030 China Key Laboratory of Streaming Computing and Applications Northwest Minzu University China Department of Nuclear Medicine Gansu Provincial Hospital No. 204 Donggang Xilu Rd. Lanzhou city Gansu Province730000 China

The SPECT diagnostic text contains several aspects of the patient’s personal information, image description, and suggested results. In order to construct a diagnostic model of nuclear medical text, a classification method of nuclear medical text based on deep learning was proposed. TextCNN was applied to propose the classification method of diseases. A set of real nuclear medical text data was used to verify the proposed method, the experimental results show that the proposed method has a good classification effect. © 2021 Journal of Physics: Conference Series.

关键词： Deep learning

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On Star Coloring of Mycielski's Graphs for Special Graphs

On Star Coloring of Mycielski's Graphs for Special Graphs

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Computer Science and Management Technology (ICCSMT), International Conference on

作者： Cai Jin Shuangliang Tian Zhuomo An School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou China

ISBN: (纸本)9781728186696

Let G be a simple graph with vertex set V (G) and edge set E (G). A vertex coloring of G is called a star coloring of G if any path of 4 order is bicolored. The minimum number of colors required for a star coloring of G is denoted by χ s (G). Let G is a simple graph with vertex set V (G) = V and edge set E (G) = E, if the vertex set is V ∪ V' ∪ {w} where V' = {X' : x ∈ V} and the edge set is EU{xy' : xy∈V} U {y'w : y'∈V'}, then G is a Mycielski's graph. This paper mainly studies star coloring of Mycielski's graph for some special graphs, the specific results are as follows: if n = 2,3 , then χ s (M (P n )) = 4, otherwise, χ s (M (P n )) = 6 ; if n = 5, then χ s (M(C n )) = 8, otherwise, χ s (M(C n )) = 6 ; χ s (M(S n )) = 4 ; χ s (M (K n )) = n + 2.

关键词： Computer science Color

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The acyclic coloring of the Corona product and Edge corona product of special graphs

The acyclic coloring of the Corona product and Edge corona p...

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Computer Science and Management Technology (ICCSMT), International Conference on

作者： Qiqi Lu Shuangliang Tian Lizhen Peng School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou China

关键词： Computer science Color Corona

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Adjacent vertex distinguishing incidence coloring of semi-strong product of paths

Adjacent vertex distinguishing incidence coloring of semi-st...

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Computer Science and Management Technology (ICCSMT), International Conference on

作者： Lizhen Peng Shuangliang Tian Qiqi Lu School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou China

ISBN: (纸本)9781728186696

Adjacent vertex distinguishing incidence coloring of graph G is an incidence coloring that satisfies that adjacent vertices have different color sets, and the minimum color number is called the adjacent vertex distinguishing incidence coloring number of graph G, which is denoted as χ ai (G). In this paper, we study the adjacent vertex distinguishing incidence coloring of semi-strong products and strong products of paths of different orders, and obtain the exact values of the corresponding coloring numbers.

关键词： Computer science Color

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Research on the Recognition of Abnormal Behaviors in the Elderly Based on Wi-Fi Signals

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Journal of Physics: Conference Series 2021年第1期1848卷

作者： YiFan Li YongChun Cao Qiang Lin WeiQiong Wang School of Mathematics and Computer Science Northwest Minzu University Lanzhou Gansu 730030 China Key Laboratory of Streaming Computing and Applications Northwest Minzu University Lanzhou Gansu 730030 China

Wandering behaviour is an important diagnostic indicator for patients with Alzheimer's disease, and falls are the main threat to the health of the elderly. Effective detection of these two types of abnormal behaviours of the elderly and timely intervention are important for improving the quality of life of patients with Alzheimer's disease and related diseases significance. This study proposes and studies a method for detecting and identifying abnormal behaviours of the elderly based on Wi-Fi signals. First, the correlation between Wi-Fi signal changes and abnormal behaviours of the elderly was analyzed; secondly, this study applied general Wi-Fi equipment to obtain the status data of the abnormal behaviours of the elderly and preprocess the data through Hampel filtering; then, the effective features of the CSI sequence fragments were designed and extracted, a data set of 2243 samples including 7 types of abnormal behaviours of the elderly was constructed; finally, a BiLSTM-Based abnormal behaviour recognition model for the elderly was constructed, and the average classification accuracy reached 95.95%, which proved this experiment is feasible and effective.

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On Star Coloring of Several Corona Graphs

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Journal of Physics: Conference Series 2021年第1期1738卷

作者： Jin Cai Shuangliang Tian Zhuomo An School of Mathematics and Computer Science Northwest for Minzu University Lanzhou 730030 China Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou 730030 China

Let G be a simple graph with vertex set V(G) and edge set E(G). A vertex coloring of G is called a star coloring of G if any of the paths of 4 order are bicolored. The minimum number of colors required for a star coloring of G is denoted by χs(G). The corona product of simple graphs G of order m and H of order n is graph G ∘ H with vertex set V(G ∘ H) = {vi|i = 1,2,⋯m}∪{vij|i = 1,2,⋯m, j = 1,2,⋯n}, in which vi is adjacent to every vertex of Hi if and only if, vi ∈ V(G), vij ∈ V(Hi). According to the existing graph dyeing literature, it has become a very important technical means to study the graph dyeing problem by using the graph structure operation. Therefore, it is of great significance to study the star coloring of graphs for studying the acyclic coloring and distance coloring of graphs, the study has strong application background and great theoretical value for computing graphs. In this paper, we find the upper bound of χs(G ∘ H) and the exact values of χs(G ∘ H) of the corona product G ∘ H of two graphs G and H as: χs(G ∘ H) ≤ χs(G) + χs(H); χs(Pm ∘ H) = χs(H) + 2; χs(K1,m ∘ H) = χs(H) + 2; χs(Cn ∘ H) = χs(H) + 2, where n ≠ 5.

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