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  • Hindawi Limited  (16)
  • Economics  (16)
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  • Hindawi Limited  (16)
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  • Economics  (16)
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  • 1
    Online Resource
    Online Resource
    QoS-Aware Mobile Service Selection Algorithm
    Hindawi Limited ; 2016
    In:  Mobile Information Systems Vol. 2016 ( 2016), p. 1-6
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2016 ( 2016), p. 1-6
    Abstract: For the problem of mobile service selection, this paper gives a context-aware service selection algorithm based on Genetic Algorithm. In this algorithm, a tree encoding method, a fitness function, and a fitness-better strategy were proposed. The tree encoding mode made Genetic Algorithm support selection of various types of service combinations, for example, sequence composition, concurrence composition, probability composition, and loop composition. According to the encoding method, a fitness function was designed specially. The fitness-better strategy gives the direction of population evolution and avoids the degradation of population fitness. Some experiments analyses show that the provided service selection algorithm can get better service composition.
    Type of Medium: Online Resource
    ISSN: 1574-017X , 1875-905X
    URL: Article
    DOI: 10.1155/2016/4968279
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2016
    detail.hit.zdb_id: 2187808-0
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  • 2
    Online Resource
    Online Resource
    Motion Attitude Recognition and Behavior Prediction Algorithm Based on Wireless Sensor Network
    Hindawi Limited ; 2021
    In:  Mobile Information Systems Vol. 2021 ( 2021-10-27), p. 1-10
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2021 ( 2021-10-27), p. 1-10
    Abstract: The wireless sensor network is an integral part of the physical information system. Disperse sensors through a set of special spaces track and record the natural state of the environment and manage the information collected in a central location. The sensors use wireless connections to create their own networks. Wireless sensor network technology has the advantages of flexible deployment and convenient use and has played an important role in the field of user behavior recognition. By deploying wireless sensor network technology, users can collect daily information, capture users’ behavior habits, and analyze users’ health status. In the deployment and application of this type of technology, it is very important to build an effective model of the logical sequence relationship of the monitored person’s behavior. The sensor data can be sent to the target user through wireless transmission. Action recognition is often based on a single feature for learning and judgment, so there are many difficulties in practical applications. This article aims to study motion shake awareness and action prediction algorithms based on wireless sensor networks. Aiming at the research of human pose recognition algorithm, to optimize the overall performance of the model, this article suggests the use of multimodal input, uses a 2D and 3D network structure, and finally, proposes two network weighted fusion strategies. Aiming at the research of pedestrian motion discrimination, this article offers a behavior prediction algorithm based on multifeature joint learning. The algorithm adds the feature vectors output by gesture recognition and mask prediction and uses a cross-entropy cost function to jointly learn and predict classification. The results of the survey show that the pedestrian gesture recognition and motion recognition algorithm based on the wireless sensor network proposed in this paper has good performance and can be widely used in real scenes such as video surveillance. The accuracy of the gesture recognition algorithm in the UCF101 dataset and the HMDB51 dataset was 96% and 72%, respectively.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2021/3994003
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2187808-0
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Artificial Intelligence-Based Joint Movement Estimation Method for Football Players in Sports Training
    Hindawi Limited ; 2021
    In:  Mobile Information Systems Vol. 2021 ( 2021-5-3), p. 1-9
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2021 ( 2021-5-3), p. 1-9
    Abstract: Football is a product in the process of human socialization; it can strengthen the body and enhance the ability of teamwork. The introduction of artificial intelligence into football training is an inevitable trend; this trend must be bound to intensify, but how to apply artificial intelligence to solve the problem of the joint movement estimation method for football players in sports training is still the main difficulty now. The basic principle of football training action pattern recognition is to determine the type of football player’s action by processing and analyzing the movement information obtained by the sensor. Due to the complex movements towards football players and the changeable external environment, there are still many problems with action recognition. Focusing on the detailed classification of different sports modes, this article conducts research on the recognition of the joint movement estimation method for football players in sports training. This paper uses the recognition algorithm based on the multilayer decision tree recognizer to identify the joint movement; the experiment shows that the method used in this paper accurately identified joint movement for football players in sports training.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2021/9956482
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2187808-0
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    Online Resource
  • 4
    Online Resource
    Online Resource
    Detecting Boundary Nodes and Coverage Holes in Wireless Sensor Networks
    Hindawi Limited ; 2016
    In:  Mobile Information Systems Vol. 2016 ( 2016), p. 1-16
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2016 ( 2016), p. 1-16
    Abstract: The emergence of coverage holes in wireless sensor networks (WSNs) means that some special events have broken out and the function of WSNs will be seriously influenced. Therefore, the issues of coverage holes have attracted considerable attention. In this paper, we focus on the identification of boundary nodes and coverage holes, which is crucially important to preventing the enlargement of coverage holes and ensuring the transmission of data. We define the problem of coverage holes and propose two novel algorithms to identify the coverage holes in WSNs. The first algorithm, Distributed Sector Cover Scanning (DSCS), can be used to identify the nodes on hole borders and the outer boundary of WSNs. The second scheme, Directional Walk (DW), can locate the coverage holes based on the boundary nodes identified with DSCS. We implement the algorithms in various scenarios and fully evaluate their performance. The simulation results show that the boundary nodes can be accurately detected by DSCS and the holes enclosed by the detected boundary nodes can be identified by DW. The comparisons confirm that the proposed algorithms outperform the existing ones.
    Type of Medium: Online Resource
    ISSN: 1574-017X , 1875-905X
    URL: Article
    DOI: 10.1155/2016/8310296
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2016
    detail.hit.zdb_id: 2187808-0
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  • 5
    Online Resource
    Online Resource
    Performance Evaluation of the Transmission Quality of the Internet of Things in Farmland Environmental Monitoring Based on ns-3
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-5-5), p. 1-11
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-5-5), p. 1-11
    Abstract: The Internet of Things (IoT) technology focuses on the application of information-sensing equipment, transmission network, and intelligent information processing technology. Through scientific management, it can achieve the rational use of agricultural resources, thus improving the ecological environment, reducing production costs, and improving the yield and quality of agricultural products. At present, the application of agricultural IoT technology faces problems including small network coverage, limited monitoring projects, high transmission cost, and short power supply time, which limit the popularity and ability of farmland environmental monitoring. In this paper, ns-3 is used to simulate the IoT for farmland environmental monitoring based on the long-range wide-area network (LoRaWAN) protocol. The simulation results show the transmission distance with good transmission quality under the LoRaWAN protocol. Furthermore, we analyze the comparison of the combination range of network transmission quality parameters under the two acknowledgment (ACK) mechanisms. Finally, we present the parameter combination range and suggestions to improve the network transmission quality, which provide a new basis for guiding the farmland environmental monitoring system.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2022/3148348
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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  • 6
    Online Resource
    Online Resource
    Feature Extraction Method of Snowboard Starting Action Using Vision Sensor Image Processing
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-1-19), p. 1-9
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-1-19), p. 1-9
    Abstract: There is a lot of noise in the snowboard starting action image, which leads to the low accuracy of snowboard starting action feature extraction. We propose a snowboard starting action feature extraction using visual sensor image processing. Firstly, the overlapping images are separated by laser fringe technology. After separation, the middle point of the image is taken as the feature point, and the interference factors are filtered by laser. Secondly, the three-dimensional model is established by using visual sensing image technology, the action feature images are input in the order of recognition, and all actions are reconstructed and assembled to complete the action feature extraction of snowboard. The interference factors are filtered by laser, the middle part of the action image is extracted according to the common features of multiple images, and its definition is described. The movement change and moving distance are used to count the most features and clarity. Finally, the edge recognition effect of snowboard starting action image and the action recognition effect under multiple complex images are taken as experimental indexes. The results show that the method has a good effect on image edge extraction, the extraction effect is as high as 95%, and the accuracy is as high as 2.1%. In addition, under multiple complex images, the action feature recognition rate is also high, which can prove that the method studied has better accuracy in snowboard starting action feature extraction.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2022/2829547
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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    Online Resource
  • 7
    Online Resource
    Online Resource
    A YOLOv3-Based Industrial Instrument Classification and Reading Recognition Method
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-10-11), p. 1-10
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-10-11), p. 1-10
    Abstract: Aiming at the demand of industrial instrument reading, this study proposes a method of industrial instrument classification and reading recognition based on YOLOv3. Given that industrial meters can be divided into pointer meters and digital meters according to the dial type, this method conducts a reading study for each of the two types of meters. Firstly, the YOLOv3 model is trained to recognize and detect the meter types and classify the meters according to the values of the obtained classes. The pointer meter uses a Hough circle to detect the dial, extracts the scale and the pointer, calculates the angle between the 0 scale line and the pointer, and obtains the reading of the pointer meter. The digital meter extracts the digits by finding the contours of the dial and the digit area and then uses a support vector machine (SVM) to identify the extracted digits and output the readings of the digital meter. Through the test, the mean average precision (mAP) of the recognition model in this study is 93.73%. The absolute error of pointer meter reading is less than 0.1 in general, and the maximum relative error is 0.35%. The accuracy of the digital meter reading is 99.7%. The proposed method can accurately read the value of the instrument and meet the needs of industrial production.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2022/7817309
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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  • 8
    Online Resource
    Online Resource
    Designing Data Visualization Using Artificial Intelligence for Urban Intelligent Transportation Scenarios
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-8-27), p. 1-11
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-8-27), p. 1-11
    Abstract: Artificial intelligence refers to a simulation extension and expansion technology that has found its presence in various applications and research domains. Artificial intelligence allows the related theories to portray similar to human intelligence. It combines developments in several fields, including computer science, statistics, and linguistics. The research objects of data visualization can be divided into three aspects: data, visualization technology, and visualization performance. This paper aims to study the data visualization design of artificial intelligence in urban intelligent transportation scenarios. It predicts the traffic flow via the traffic control method using neural network. It provides an effective way for timely dredging and alleviating problems, such as traffic jams and establishing alternative routes. This paper firstly analyzes the methods of artificial intelligence, traffic control methods, and data visualization and then designs the visualization based on artificial intelligence in traffic scenarios. By comparing the accuracy analysis of different models, the experimental results show that the error of the peak traffic flow is less than 10% and the lowest error value is 2.2%.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2022/3967267
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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    Online Resource
  • 9
    Online Resource
    Online Resource
    The Practical Application of Agricultural Genetic Breeding Technology in Elm Cultivation Based on Big Data Analysis
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-8-8), p. 1-9
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-8-8), p. 1-9
    Abstract: In order to explore the role of agricultural genetic breeding technology in elm cultivation, this paper improves the big data technology. According to the test data verification requirements, based on the Monte Carlo idea, a TDSTI statistical test method is proposed, and a set of judgment criteria for the significance of spatio-temporal autocorrelation is given. Moreover, in order to make the observed variables of the time lag series have a clearer geographical significance, the obtained spatio-temporal weight matrix is subjected to row standardization. In addition, this paper combines big data technology and agricultural genetic breeding technology to study the cultivation of elm trees. Finally, this paper conducts a correlation analysis between the distance matrix generated by cluster analysis of leaf shape traits and the distance matrix generated by cluster analysis of SSR molecular markers. The research results show that agricultural genetic breeding technology can play an important role in the cultivation of elm.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2022/2441292
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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    Online Resource
  • 10
    Online Resource
    Online Resource
    A Violent Video Detection Method Based on Image Semantic Segmentation
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-6-24), p. 1-12
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-6-24), p. 1-12
    Abstract: With the rapid growth of the network user base and the number of short videos, a large number of videos related to terrorism and violence have emerged in the Internet, which has brought great challenges to the governance of the network environment. At present, most short-video platforms still adopt manual-review and user-report mechanisms to filter videos related to terrorism and violence, which cannot adapt to the development trend of short-video business in terms of recognition accuracy and timeliness. In the single-mode recognition method of violent video, this paper mainly studies the scene recognition mode. Firstly, the U-Net network is improved with the SE-block module. After pretraining on the Cityscapes dataset, semantic segmentation of video frames is carried out. On this basis, semantic features of scenes are extracted using the VGG16 network loaded with ImageNet pretraining weights. SE-U-Net-VGG16 scene recognition model is constructed. The experimental results show that the prediction accuracy of SE-U-Net model is much higher than that of the FCN model and U-Net model. SE-U-Net model has significant advantages in the modal research of scene recognition.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2022/7454397
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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