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2024 8th International Conference on Mechanics, Mathematics and Applied Physics, ICMMAP 2024

作者： Zhao, Wenying Tian, Shuangliang School of Mathematics and Computer Science Northwest for Minzu University Lanzhou730030 China Key Laboratory of Streaming Data Computing Technologies and Applications Northwest for Minzu University Lanzhou730030 China

The injective chromatic number χi(G) of a graph G is the minimum number of colors needed to color the vertices of G such that different vertices with the same neighbor are colored differently. In this here, we get some exact values of the injective chromatic number of the edge corona product of some graphs. © Published under licence by IOP Publishing Ltd.

关键词： Graph theory

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Acyclic coloring of two operations of graphs 8

Acyclic coloring of two operations of graphs

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2024 8th International Conference on Mechanics, Mathematics and Applied Physics, ICMMAP 2024

作者： Jin, Xinze Tian, Shuangliang School of Mathematics and Computer Science Northwest for Minzu University Lanzhou730030 China Key Laboratory of Streaming Data Computing Technologies and Applications Northwest for Minzu University Lanzhou730030 China

The coloring theory of graphs is a very important direction in graph theory. The graph coloring problem has a strong application background. Many practical problems such as timetabling problems, frequency allocation problems, traffic arrangements, circuit design, and storage problems can be transformed into graph coloring problems. A substantial amount of scholarly work has been dedicated to the exploration of acyclic coloring, resulting in a plethora of significant findings that significantly contribute to the theoretical framework of vertex coloring in graphs. An acyclic coloring of a graph G refers to a proper vertex coloring where the subgraph resulting from any pair of color classes does not encompass any cycles. We analyze acyclic coloring in splitting graphs and Cartesian products of paths and cycles by using the method of structural coloring, reductive proof, and mathematical induction. Moreover, we present the precise acyclic chromatic numbers for splitting graphs of cycles and Cartesian products of paths and cycles. © Published under licence by IOP Publishing Ltd.

关键词： Integrated circuit design

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Wi-Fi based non-invasive detection of indoor wandering using LSTM model

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Frontiers of Computer Science 2021年第6期15卷 109-119页

作者： Qiang LIN Yusheng HAO Caihong LIU School of mathematics and computer science Northwest Minzu UniversityLanzhou 730030China Key Laboratory of Streaming Data Computing and Application Northwest Minzu UniversityLanzhou 730124China

Wandering is a significant indicator in the clinical diagnosis of dementia and other related diseases for *** monitoring of long-term continuous movement in indoor setting for detection of wandering movement is challenging because most elders are prone to forget to carry or wear sensors that collect motion information daily due to their declining ***-Fi as an emerging sensing modality has been widely used to monitor human indoor movement in a noninvasive *** order to continuously monitor individuals’indoor motion and reliably identify wandering movement in a non-invasive manner,in this work,we develop a LSTMbased deep classification method that is able to differentiate the wandering-causedWi-Fi signal change from the ***,we first use the off-the-shelf Wi-Fi devices to capture a resident’s indoor motion information,enabling to collect a group ofWi-Fi signal streams,which will be split into variablesize ***,the deep network LSTM is adopted to develop wandering detection method that is able to classify every variable-size segment of Wi-Fi signals into categories according to the well-known wandering spatiotemporal ***,experimental evaluation conducted on a group of realworld Wi-Fi signal streams shows that our proposed LSTMbased detection method is workable and effective to identify indoor wandering behavior,obtaining an average value of 0.9286,0.9618,0.9634 and 0.9619 for accuracy,precision,recall and F-1 score,respectively.

关键词： wandering detection assisting living Wi-Fi signal deep learning LSTM

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Existence and Non-Existence of Solutions to Some Degenerate Coercivity Quasilinear Elliptic Equations with Measure data

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Journal of Mathematical Research with applications 2022年第2期42卷 173-188页

作者： Maoji RI Xiangrui LI Qiaoyu TIAN Shuibo HUANG School of Mathematics and Computer Science Northwest Minzu University Key Laboratory of Streaming Data Computing Technologies and Application Northwest Minzu University

In this article,we study the existence and non-existence of weak solutions to the following quasilinear elliptic problem with principal part having degenerate coercivity and nonlinear term involving gradie,■where??RN... 详细信息

关键词： elliptic equation degenerate coercivity measures data existence non-existence

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Automatic Segmentation of Metastasis Lesions in SPECT Bone Scan Images

Automatic Segmentation of Metastasis Lesions in SPECT Bone S...

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2020 International Conference on Intelligent computing, Automation and Systems, ICICAS 2020

作者： Gao, Ruiting Lin, Qiang Luo, Mingyang Man, Zhengxing Cao, Yongchun Wang, Haijun Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education Key Laboratory of Streaming Data Computing Technologies and Application Northwest Minzu University Lanzhou China Key Laboratory of Streaming Data Computing Technologies and Application Northwest Minzu University Lanzhou China Gansu Provincial People's Hospital Department of Nuclear Medicine Lanzhou China

ISBN: (纸本)9781728191461

SPECT bone imaging is among the main nuclear medicine functional imaging modalities, which has the potential of early diagnosis of various serious diseases such as cancers. However, the low resolution and contrast of SPECT bone images bring huge challenges to performance on segmenting hotspots or lesions in SPECT bone scan images. In this work, three different algorithms including K-means clustering method, region growth method and C-V model are introduced to segment lesions in SPECT bone scan images by fine-tuning parameters, focusing on the bone metastatic lesions area in SPECT imaging. Specifically, each of the original 256×1024 whole body images is cropped into a 256×256 thoracic region including ribs and spine, followed by the data normalization. Then, different parameters are experimentally determined for the above three algorithms, leading to three different segmentation algorithms. Last, experimental evaluation conducted on a group of real-world samples of SPECT bone scan images reveals that our methods are workable for segmenting lesions with SPECT imaging, obtaining a value of 0.7307, 0.7768 and 0.8076 for Tanimoto similarity coefficient metric by the three methods, respectively. Particularly, the C-V model based segmentation method is able to provide more assistive information for oncologists on diagnose of tumors and other related diseases. © 2020 IEEE.

关键词： Image segmentation

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An intelligent system for heart disease prediction using adaptive neuro-fuzzy inference systems and genetic algorithm 4

An intelligent system for heart disease prediction using ada...

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2021 4th International Conference on Computer Information Science and application Technology, CISAT 2021

作者： Feng, Jindong Wang, Qian Li, Na Northwest Minzu University Lanzhou China Key Laboratory of Streaming Data Computing and Application Northwest Minzu University Lanzhou China

Cardiovascular disease remains the leading cause of death worldwide over the past two decades. Because of a large number of clinical data and the complexity of the disease, it is often challenging to diagnose and make the proper treatment. Over the past decade, as a soft computing method, fuzzy expert systems have been applied in disease diagnosis by many researches because of its superiority in dealing with uncertain and ambiguous problems. This study proposes an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to diagnose heart disease. Parameters related to membership functions in ANFIS are optimized by applying the genetic algorithm. The experiment was conducted on the public UCI heart disease datasets. The experimental result shows that 91.25% accuracy was obtained on the testing set, which was found to be satisfying based on comparison. © Content from this work may be used under the terms of the Creative Commons Attribution 3.0 Licence.

关键词： Genetic algorithms

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Classification of abnormal behavior in the elderly based on Wi-Fi

Classification of abnormal behavior in the elderly based on ...

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2021 International Symposium on Computer Technology and Information Science, ISCTIS 2021

作者： Weiqiong, Wang Yongchun, Cao Qiang, Lin Li, Yifan Northwest Minzu University School of Mathematics and Computer Science Lanzhou China Key Laboratory of Streaming Data Computing and Application Northwest Minzu University Lanzhou China

ISBN: (纸本)9781665414418

Abnormal behavior in daily life is a great threat to the health of the elderly, so it is of great significance to detect the abnormal behavior of the elderly. Using ubiquitous commercial Wi-Fi devices to collect information, behavior detection can be performed in an indoor environment without carrying other devices. The Wi-Fi based abnormal behavior detection for the elderly proposed in this paper is aimed at the fall and wandering behaviors that the elderly are prone to. At the same time, squatting and sitting behaviors those are similar to the fall behaviors are distinguished. Several classical classification models are used to compare the effect and recognition time. The experimental comparison shows that the SVM and KNN machine learning methods after adjusting the model parameters can achieve the same recognition effect as the deep learning model LSTM, shorten the running time and improve the efficiency. © 2021 IEEE.

关键词： Support vector machines

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CNN-Based Automated Classification of SPECT Bone Scan Images

CNN-Based Automated Classification of SPECT Bone Scan Images

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2022 International Conference on Neural Networks, Information, and Communication Engineering, NNICE 2022

作者： Man, Zhengxing Lin, Qiang Cao, Yongchun School of Mathematics and Computer Science Northwest Minzu University Gansu Lanzhou730124 China Key Laboratory of Streaming Data Computing Technologies and Application Northwest Minzu University Gansu Lanzhou730030 China

ISBN: (纸本)9781510655171

Functional medicine imaging has been successfully applied to capture functional changes in pathological tissues of the body in recent years. SPECT nuclear medicine functional imaging has the potential to acquire information about areas of concern (e.g., lesions and organs) in a non-invasive manner, enabling semi-automated or automated decision-making for the purposes of disease diagnosis, treatment, evaluation, and prediction. To reliably identify that whether or not at least one hotspot or lesion presents in a whole-body SPECT image, in this work, we develop a group of CNN-based classifiers. Specifically, we first propose a preprocessing method that transforms each original SPECT file into the required form by deep learning model, including normalization, 3-channel construction, rotation and scaling, size standardization, and size adapting. Second, six different classifiers are constructed by fine-tuning parameters of the standard VGG-16 model. Last, a group of real-world SPECT whole-body bone scan files were utilized to evaluate the developed classifiers. Experiment results shows that our classifiers are workable for the 2-class classification of SPECT images, achieving a best value of 0.7641, 0.6678, 1.000, and 0.6574 for defined evaluation metrics Acc, Pre, Rec, and AUC, respectively. © 2022 SPIE.

关键词： Image classification

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Star coloring for a special class of graphs G1, d

Star coloring for a special class of graphs G1, d

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2021 International Conference on Big data Analysis and Computer Science, BDACS 2021

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

ISBN: (纸本)9781665425612

In this paper we study the star coloring for a special class of graphs whose degree is either 1 or d. They are graphs obtained by generalized corona products of path, circle, star, complete graph complete bipartite graph and complement of complete graph respectively. Vertex coloring theory of graphs is an important part of graph coloring theory. Star coloring is a special vertex coloring with limited conditions.. © 2021 IEEE.

关键词： Stars

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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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