Mob. Inf. Syst.最新文献_第9页

Enterprise Financial Leverage and Risk Assessment Based on Mobile Payment under Artificial Intelligence 基于人工智能下移动支付的企业财务杠杆与风险评估

Mob. Inf. Syst. Pub Date : 2021-12-09 DOI: 10.1155/2021/5468397

Xiaoling Xu, Jianghao Song

{"title":"Enterprise Financial Leverage and Risk Assessment Based on Mobile Payment under Artificial Intelligence","authors":"Xiaoling Xu, Jianghao Song","doi":"10.1155/2021/5468397","DOIUrl":"https://doi.org/10.1155/2021/5468397","url":null,"abstract":"To better promote the healthy and long-term development of corporate financial management, the basement is established on the perspective of artificial intelligence (AI). Initially, based on the theories of modern mobile payment (MP) and corporate financial leverage, the corresponding data set is obtained through the questionnaire method as the research data. The reliability coefficients obtained after the test are all above 0.65, indicating that the reliability and stability of the entire data are relatively good. Besides, it is also found from the data of the questionnaire that some residents believe that MP will bring harm such as information leakage. Next, a new multilevel evaluation analysis method is introduced. After evaluating the financial management risk, operation risk, and network security risk existing in enterprise MP, it is found that the financial management risk accounts for the largest proportion of the three, with a risk weight of about 0.54, and the capital risk occupies the main position in the financial management risk. Finally, through the analysis of the risks existing in the whole operation process of the enterprise, it is found that about 50% of the financial management risk of the enterprise in the market belongs to the advanced risk, about 30% of the operational operation risk belongs to the low risk, and about 20% of the network security risk belongs to the advanced risk, which indicates that the financial management risk and network security risk are the top priority of the enterprise MP risk. Although the operational operation risk belongs to the low risk, it cannot be ignored. Subsequently, feasible suggestions and opinions are put forward on these phenomena from the perspectives of the government, enterprises, and residents. Therefore, there is great reference significance for the current financial risk assessment of enterprises based on MP.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"44 1","pages":"5468397:1-5468397:10"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85239851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Development of a Mobile Application for Interaction between Patients and Doctors in Rural Populations

Mob. Inf. Syst. Pub Date : 2021-12-09 DOI: 10.1155/2021/5006151

M. Alazzam, Fawaz Alassery, A. Almulihi

引用次数: 37

Research on the New Model of Aerobics Physical Education under the Background of Artificial Intelligence Era 人工智能时代背景下健美操体育教学新模式研究

Mob. Inf. Syst. Pub Date : 2021-12-08 DOI: 10.1155/2021/3178177

Yi Liu

引用次数: 2

A Network That Balances Accuracy and Efficiency for Lane Detection 一种兼顾车道检测精度和效率的网络

Mob. Inf. Syst. Pub Date : 2021-12-07 DOI: 10.1155/2021/1099434

Ce Zhang, Yuhui Han, Dan Wang, Wei Qiao, Yier Lin

{"title":"A Network That Balances Accuracy and Efficiency for Lane Detection","authors":"Ce Zhang, Yuhui Han, Dan Wang, Wei Qiao, Yier Lin","doi":"10.1155/2021/1099434","DOIUrl":"https://doi.org/10.1155/2021/1099434","url":null,"abstract":"In the automatic lane-keeping system (ALKS), the vehicle must stably and accurately detect the boundary of its current lane for precise positioning. At present, the detection accuracy of the lane algorithm based on deep learning has a greater leap than that of the traditional algorithm, and it can achieve better recognition results for corners and occlusion situations. However, mainstream algorithms are difficult to balance between accuracy and efficiency. In response to this situation, we propose a single-step method that directly outputs lane shape model parameters. This method uses MobileNet v2 and spatial CNN (SCNN) to construct a network to quickly extract lane features and learn global context information. Then, through depth polynomial regression, a polynomial representing each lane mark in the image is output. Finally, the proposed method was verified in the TuSimple dataset. Compared with existing algorithms, it achieves a balance between accuracy and efficiency. Experiments show that the recognition accuracy and detection speed of our method in the same environment have reached the level of mainstream algorithms, and an effective balance has been achieved between the two.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"429 1","pages":"1099434:1-1099434:5"},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86902921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Institutional Teaching Innovation under the Demand of Internet + PE 互联网+体育需求下的制度教学创新

Mob. Inf. Syst. Pub Date : 2021-12-06 DOI: 10.1155/2021/9111924

Dong-Jin Na

引用次数: 3

Detection of Tuberculosis Disease Using Image Processing Technique 利用图像处理技术检测肺结核

Mob. Inf. Syst. Pub Date : 2021-12-03 DOI: 10.1155/2021/7424836

Mohammad Alsaffar, G. Alshammari, Abdullah Alshammari, Saud Aljaloud, Tariq S. Almurayziq, A. A. Hamad, Vishal Kumar, Assaye Belay

{"title":"Detection of Tuberculosis Disease Using Image Processing Technique","authors":"Mohammad Alsaffar, G. Alshammari, Abdullah Alshammari, Saud Aljaloud, Tariq S. Almurayziq, A. A. Hamad, Vishal Kumar, Assaye Belay","doi":"10.1155/2021/7424836","DOIUrl":"https://doi.org/10.1155/2021/7424836","url":null,"abstract":"Machine learning is a branch of computing that studies the design of algorithms with the ability to “learn.” A subfield would be deep learning, which is a series of techniques that make use of deep artificial neural networks, that is, with more than one hidden layer, to computationally imitate the structure and functioning of the human organ and related diseases. The analysis of health interest images with deep learning is not limited to clinical diagnostic use. It can also, for example, facilitate surveillance of disease-carrying objects. There are other examples of recent efforts to use deep learning as a tool for diagnostic use. Chest X-rays are one approach to identify tuberculosis; by analysing the X-ray, you can spot any abnormalities. A method for detecting the presence of tuberculosis in medical X-ray imaging is provided in this paper. Three different classification methods were used to evaluate the method: support vector machines, logistic regression, and nearest neighbors. Cross-validation and the formation of training and test sets were the two classification scenarios used. The acquired results allow us to assess the method’s practicality.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"21 1","pages":"7424836:1-7424836:7"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79064472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

Feature Optimization of Exhaled Breath Signals Based on Pearson-BPSO 基于Pearson-BPSO的呼出信号特征优化

Mob. Inf. Syst. Pub Date : 2021-12-03 DOI: 10.1155/2021/1478384

Lijun Hao, Min Zhang, Gang Huang

{"title":"Feature Optimization of Exhaled Breath Signals Based on Pearson-BPSO","authors":"Lijun Hao, Min Zhang, Gang Huang","doi":"10.1155/2021/1478384","DOIUrl":"https://doi.org/10.1155/2021/1478384","url":null,"abstract":"Feature optimization, which is the theme of this paper, is actually the selective selection of the variables on the input side at the time of making a predictive kind of model. However, an improved feature optimization algorithm for breath signal based on the Pearson-BPSO was proposed and applied to distinguish hepatocellular carcinoma by electronic nose (eNose) in the paper. First, the multidimensional features of the breath curves of hepatocellular carcinoma patients and healthy controls in the training samples were extracted; then, the features with less relevance to the classification were removed according to the Pearson correlation coefficient; next, the fitness function was constructed based on K-Nearest Neighbor (KNN) classification error and feature dimension, and the feature optimization transformation matrix was obtained based on BPSO. Furthermore, the transformation matrix was applied to optimize the test sample’s features. Finally, the performance of the optimization algorithm was evaluated by the classifier. The experiment results have shown that the Pearson-BPSO algorithm could effectively improve the classification performance compared with BPSO and PCA optimization methods. The accuracy of SVM and RF classifier was 86.03% and 90%, respectively, and the sensitivity and specificity were about 90% and 80%. Consequently, the application of Pearson-BPSO feature optimization algorithm will help improve the accuracy of hepatocellular carcinoma detection by eNose and promote the clinical application of intelligent detection.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"3 1","pages":"1478384:1-1478384:9"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78768980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Research on Music Teaching and Creation Based on Deep Learning 基于深度学习的音乐教学与创作研究

Mob. Inf. Syst. Pub Date : 2021-12-02 DOI: 10.1155/2021/1738104

Mingxing Liu

{"title":"Research on Music Teaching and Creation Based on Deep Learning","authors":"Mingxing Liu","doi":"10.1155/2021/1738104","DOIUrl":"https://doi.org/10.1155/2021/1738104","url":null,"abstract":"Under the background of quality education, music learning is also changing, from the original shallow learning to deep learning gradually. In-depth learning is a new teaching concept, which pays full attention to students’ perception and exploration of music so that students can fully experience the charm of music. It can not only help students master more music knowledge and improve their music skills but also cultivate students’ music literacy and enhance their music ability (Świechowski, 2015). Therefore, in junior high school music teaching, teachers should actively apply the deep learning model and then improve the teaching level and comprehensively cultivate students’ music literacy (Whitenack and Swanson, 2003). In this paper, two convolution-based deep learning models, Breath1d and Breath2d, were designed and constructed, and a multilayer perceptron (MLP) was used as a benchmark method for performance evaluation, and a long short-term memory (LSTM) network is applied for the classification task. This paper discusses the value and application strategies of deep learning in junior high school music teaching and hopes to provide some reference for all educational colleagues (Zhang and Nauman 2020).","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"26 1","pages":"1738104:1-1738104:7"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87397832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Research on Fault Diagnosis Model of Generative Adss Based on Improved Semisupervised Diagnosis Algorithm 基于改进半监督诊断算法的生成式Adss故障诊断模型研究

Mob. Inf. Syst. Pub Date : 2021-12-02 DOI: 10.1155/2021/3477667

Yi Qian

{"title":"Research on Fault Diagnosis Model of Generative Adss Based on Improved Semisupervised Diagnosis Algorithm","authors":"Yi Qian","doi":"10.1155/2021/3477667","DOIUrl":"https://doi.org/10.1155/2021/3477667","url":null,"abstract":"With the advent of the era of big data and the rapid development of deep learning and other technologies, people can use complex neural network models to mine and extract key information in massive data with the support of powerful computing power. However, it also increases the complexity of heterogeneous network and greatly increases the difficulty of network maintenance and management. In order to solve the problem of network fault diagnosis, this paper first proposes an improved semisupervised inverse network fault diagnosis algorithm; the proposed algorithm effectively guarantees the convergence of generated against network model, makes full use of a large amount of trouble-free tag data, and obtains a good accuracy of fault diagnosis. Then, the diagnosis model is further optimized and the fault classification task is completed by the convolutional neural network, the discriminant function of the network is simplified, and the generation pair network is only responsible for generating fault samples. The simulation results also show that the fault diagnosis algorithm based on network generation and convolutional neural network achieves good fault diagnosis accuracy and saves the overhead of manually labeling a large number of data samples.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"34 1","pages":"3477667:1-3477667:11"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89435156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Modulation and Signal Detection for Diffusive-Drift Molecular Communication with a Mobile Receiver 移动接收机扩散漂移分子通信的调制和信号检测

Mob. Inf. Syst. Pub Date : 2021-12-02 DOI: 10.1155/2021/9656465

Xuening Liao, Zhen Jia, Zhenqiang Wu, Bo Liu, Xinlei Wang, Xiaohong Jiang

{"title":"Modulation and Signal Detection for Diffusive-Drift Molecular Communication with a Mobile Receiver","authors":"Xuening Liao, Zhen Jia, Zhenqiang Wu, Bo Liu, Xinlei Wang, Xiaohong Jiang","doi":"10.1155/2021/9656465","DOIUrl":"https://doi.org/10.1155/2021/9656465","url":null,"abstract":"Molecular communication (MC), which allows nanomachines to communicate with each other by using chemical molecules, is considered to be a promising method for communications in liquid environment. Available works on MC mainly focus on modulation and signal detection schemes for MC systems with fixed nanomachines, i.e., fixed molecular communication (FMC) systems. However, the more complex systems with mobile nanomachines (i.e., mobile molecular communication (MMC) systems) have been largely unexplored. This paper considers a MMC system with a fixed transmitter and a mobile receiver communicating over diffusive-drift channels of a limited boundary. We first propose a new modulation scheme to address the issue of misalignment in the signal detection of MMC systems by adopting three types of molecules in the signal modulation and modulating the transmitted signals into blocks with equal length to avoid the transferring of a signal error in the current block on the signal detection in other blocks. We then propose a new signal detection scheme of the MMC systems by calculating the distance between the transmitter and the receiver based on a distance prediction method and detecting signals at the receiver based on the decided adaptive concentration threshold in each time interval. To verify the efficiency of our proposed scheme, we then conducted extensive simulations by the Monte Carlo simulation, and comparisons are also made among our proposed schemes, a well-known fixed threshold signal detection scheme, the CATD scheme, the PAD scheme, and a low complexity signal detection scheme for MMC systems in terms of the BER (bit error rate). Results show that our proposed schemes can outperform these schemes regarding the BER.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"60 1","pages":"9656465:1-9656465:17"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85628447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2