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  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted by number of followers
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 310)
Control Systems     Hybrid Journal   (Followers: 250)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 196)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 192)
Electronics     Open Access   (Followers: 132)
Advances in Electronics     Open Access   (Followers: 126)
Electronic Design     Partially Free   (Followers: 125)
Electronics For You     Partially Free   (Followers: 124)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 117)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 94)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 90)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 88)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 84)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 84)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 82)
IET Power Electronics     Open Access   (Followers: 72)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 67)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 63)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 62)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 58)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 53)
Advances in Power Electronics     Open Access   (Followers: 52)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 52)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 46)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 45)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 41)
IET Microwaves, Antennas & Propagation     Open Access   (Followers: 36)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 35)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 33)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 29)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 28)
Electronics Letters     Open Access   (Followers: 28)
Microelectronics and Solid State Electronics     Open Access   (Followers: 27)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 27)
International Journal of Aerospace Innovations     Full-text available via subscription   (Followers: 24)
International Journal of Power Electronics     Hybrid Journal   (Followers: 24)
Journal of Sensors     Open Access   (Followers: 24)
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 22)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 20)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 19)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 18)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 18)
Journal of Artificial Intelligence     Open Access   (Followers: 18)
IET Wireless Sensor Systems     Open Access   (Followers: 17)
Circuits and Systems     Open Access   (Followers: 16)
Machine Learning with Applications     Full-text available via subscription   (Followers: 16)
Archives of Electrical Engineering     Open Access   (Followers: 15)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 14)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 14)
International Journal of Control     Hybrid Journal   (Followers: 14)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 14)
Superconductivity     Full-text available via subscription   (Followers: 13)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 13)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 12)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 12)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 12)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 12)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 12)
Advances in Microelectronic Engineering     Open Access   (Followers: 12)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 11)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
Open Journal of Antennas and Propagation     Open Access   (Followers: 11)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 11)
Solid-State Electronics     Hybrid Journal   (Followers: 10)
IETE Journal of Research     Open Access   (Followers: 10)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 10)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 10)
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access   (Followers: 9)
IETE Technical Review     Open Access   (Followers: 9)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 9)
Nature Electronics     Hybrid Journal   (Followers: 9)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 8)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 8)
Journal of Power Electronics     Hybrid Journal   (Followers: 8)
China Communications     Full-text available via subscription   (Followers: 8)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 8)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 8)
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 8)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
Batteries     Open Access   (Followers: 8)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 8)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 7)
Metrology and Measurement Systems     Open Access   (Followers: 7)
Nanotechnology, Science and Applications     Open Access   (Followers: 7)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 7)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 6)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
International Journal of Electronics     Hybrid Journal   (Followers: 6)
Energy Storage Materials     Full-text available via subscription   (Followers: 6)
Electronic Markets     Hybrid Journal   (Followers: 6)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 6)
Annals of Telecommunications     Hybrid Journal   (Followers: 6)
Journal of Optoelectronics Engineering     Open Access   (Followers: 5)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 5)
IEEE Pulse     Hybrid Journal   (Followers: 5)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Field Robotics     Hybrid Journal   (Followers: 5)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 5)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 4)
Frontiers in Electronics     Open Access   (Followers: 4)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 4)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 4)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Wireless and Mobile Technologies     Open Access   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal   (Followers: 4)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 4)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 4)
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Networks: an International Journal     Hybrid Journal   (Followers: 4)
Advanced Materials Technologies     Hybrid Journal   (Followers: 4)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 4)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 3)
EPJ Quantum Technology     Open Access   (Followers: 3)
Journal of Semiconductors     Full-text available via subscription   (Followers: 3)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Informatik-Spektrum     Hybrid Journal   (Followers: 3)
IETE Journal of Education     Open Access   (Followers: 3)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 3)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 3)
Sensors International     Open Access   (Followers: 3)
Advancing Microelectronics     Hybrid Journal   (Followers: 3)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 3)
e-Prime : Advances in Electrical Engineering, Electronics and Energy     Open Access   (Followers: 3)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 3)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 2)
Journal of Information and Telecommunication     Open Access   (Followers: 2)
ACS Applied Electronic Materials     Open Access   (Followers: 2)
Energy Storage     Hybrid Journal   (Followers: 2)
IET Smart Grid     Open Access   (Followers: 2)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal   (Followers: 2)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 2)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Journal of Nuclear Cardiology     Hybrid Journal   (Followers: 2)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 2)
Open Electrical & Electronic Engineering Journal     Open Access   (Followers: 1)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Transactions on Cryptographic Hardware and Embedded Systems     Open Access   (Followers: 1)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 1)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Електротехніка і Електромеханіка     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 1)
International Journal of Hybrid Intelligence     Hybrid Journal   (Followers: 1)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 1)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Edu Elektrika Journal     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 1)
Automatika : Journal for Control, Measurement, Electronics, Computing and Communications     Open Access  
npj Flexible Electronics     Open Access  
Elektronika ir Elektortechnika     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access  
IEEE Solid-State Circuits Letters     Hybrid Journal  
IEEE Open Journal of Industry Applications     Open Access  
IEEE Open Journal of the Industrial Electronics Society     Open Access  
IEEE Open Journal of Circuits and Systems     Open Access  
Journal of Electronic Science and Technology     Open Access  
Solid State Electronics Letters     Open Access  
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Journal of Engineered Fibers and Fabrics     Open Access  
Jurnal Teknologi Elektro     Open Access  
IET Nanodielectrics     Open Access  
Elkha : Jurnal Teknik Elektro     Open Access  
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Jurnal Teknik Elektro     Open Access  
IACR Transactions on Symmetric Cryptology     Open Access  
Acta Electronica Malaysia     Open Access  
Bioelectronics in Medicine     Hybrid Journal  
Chinese Journal of Electronics     Open Access  
Problemy Peredachi Informatsii     Full-text available via subscription  
Technical Report Electronics and Computer Engineering     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Visión Electrónica : algo más que un estado sólido     Open Access  
Telematique     Open Access  
International Journal of Nanoscience     Hybrid Journal  
International Journal of High Speed Electronics and Systems     Hybrid Journal  

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Similar Journals
Journal Cover
Journal of Sensors
Journal Prestige (SJR): 0.288
Citation Impact (citeScore): 1
Number of Followers: 24  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-725X - ISSN (Online) 1687-7268
Published by Hindawi Homepage  [339 journals]
  • Enhancing the Applicability of Satellite Remote Sensing for Estimation
           Using Machine Learning Models in China

    • Abstract: Numerous studies and monitoring data indicate that fine particle () pollution in China is still comparatively severe. Given the sparse and uneven distribution of air quality monitoring base stations established in China and the limitation of geographical conditions, inversion of aerosol optical depth by satellite remote sensing can achieve low-cost air quality monitoring in global areas. In this study, we use the machine learning algorithm XGBoost to build a prediction model to achieve nationwide average concentration prediction. Meanwhile, we used aerosol data from Moderate Resolution Imaging Spectroradiometer (MODIS) in a specific band, combined with a land use regression (LUR) model as predictors of surface concentrations in China, for the period Dec. 2019-Nov. 2021. In order to provide more accurate concentration prediction, the correspondence between and aerosol optical depth (AOD) under different seasons was studied. The coefficients of determination (R2) for different seasons are 0.86 (spring), 0.80 (summer), 0.90 (autumn), and 0.88 (winter), indicating that the fit is best for autumn and worse for summer. The study shows the potential usefulness of using the LUR model with the XGBoost algorithm for predictive assessment of spatial distribution.
      PubDate: Tue, 27 Sep 2022 14:20:02 +000
  • Construction of Landscape Ecological Planning Evaluation Model Based on
           Sensor Network

    • Abstract: The application of wireless sensor network (WSN) technology promotes the modernization of forestry. WSN application technology in forest areas is an important research topic for the sustainable development of forestry in China and is also a research hotspot for forestry ecological monitoring at present. The application of wireless sensor networks in forest areas, first of all, solves the problem of limited energy supply and low-latency data transmission in the forest environment. Due to the large area of the forest environment and uneven tree density, dynamic changes in forest height, easy to block the signal, and other characteristics, the forest environment is prone to node energy depletion fast, the network life cycle is short, and data transmission delays large dilemma. Second, the application of wireless sensor networks is usually centered on maximum data acquisition, but the contradiction between high data acquisition rate and limited energy supply is inevitable, so it is necessary to construct a maximum data acquisition rate model with limited energy supply as a constraint to guarantee the optimal acquisition conditions for wireless sensor networks. In this paper, from the application of wireless sensor network technology in forest environment, the research on the application of wireless sensor network in forestry is carried out around the analysis of energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision-making fire danger warning process, so as to provide a solution to the overall problem of forest fire warning based on rechargeable wireless sensor network. In this paper, we analyze the dynamic replenishment of energy in rechargeable wireless sensor networks and propose an energy-based transmission control protocol that effectively improves data transmission efficiency. In the rechargeable wireless sensor network, the network E2E (end-to-end) average delay time is calculated based on the number of nodes on the data transmission link. The research idea of this paper starts from the application technology of wireless sensor network in the forest environment, and the design of the energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision fire danger warning process are realized vertically.
      PubDate: Tue, 27 Sep 2022 14:20:01 +000
  • Evaluation Analysis and Key Index System Construction of Urban Public
           Management Service Quality Based on Grey Judgment Method

    • Abstract: The development of today’s society has entered an era dominated by technology and efficiency, leading enterprises and governments to overemphasize the role of efficiency in the process of rapid development, while ignoring the fundamental goal of social development. The degree of urbanization has increased significantly, but the problems existing in the city are becoming more and more serious, especially the neglect of public services, which has caused great dissatisfaction. This paper firstly compares and synthesizes the performance of several methods to obtain that the grey judgment method is more suitable for this paper; that is, the grey judgment method is used to analyze the evaluation of urban public management service quality and to construct the key index system. The two-level indicators are all in line with the standard after screening the indicators by the method; the first-level indicators have the largest weight in the assess of the quality of urban common management services, and equipment management is considered to be the most important, followed by cultural construction, emergency management, greening management, and sanitation management; among the secondary indicators, the public health portfolio has the largest weight value, with a combined weight of 0.0989, followed by timely maintenance, quality of green vegetation, accident treatment, water and sewage treatment, natural disaster treatment, maintenance quality, garbage disposal, daily maintenance, the quality of cultural facilities, the daily maintenance of greening, and the quality of cultural activities; experts scored the indicators to get the highest score for equipment management, with a score of 0.7799, followed by emergency management, sanitation management, greening management, and cultural construction. By examining the quality of urban public services, it can more respond to the needs of national for public serving, and it can more effectively facilitate the future growth of the town and improve the overall level of community services.
      PubDate: Tue, 27 Sep 2022 13:50:01 +000
  • Personalized Recommendation Evaluation of Credit Degree Based on New
           Hybrid Crow Search Algorithm for E-Commerce Live Industry Data Analysis

    • Abstract: With the advent of the era of national live broadcast, the “live broadcast + e-commerce” model reconstructs “people, goods, and fields”, and merchants, platforms, and anchors create a new marketing system around consumers’ perceptions, attitudes, and emotions to enhance consumer willingness. E-commerce live broadcast ultimately brings back the core of marketing, according to retailers. The psychological contract in the live broadcast is a variable, and its commitment or breach will have an effect on the consumer attitude and consumer emotions. From the perspective of the consumer, stronger consumption motivation, content quality, Netflix charm, trust, and highly interactive consumer expectations must exist. Based on the above background, the understanding of business infrastructure in the digital economy era should also be dynamically adjusted in conjunction with the concept of new infrastructure and business innovation practices. This paper investigates personalized recommendation assessment of credit degree based on data analysis of the live e-commerce industry based on new hybrid crow search algorithm in this context, delves into the state of e-commerce in China today, offers a profound discussion on e-commerce as well as credit degree, and concludes the paper with a general summary.
      PubDate: Tue, 27 Sep 2022 12:50:03 +000
  • Optimal Design of Harvesting Speed and Forward Speed of Harvester Based on
           Adaptive Control System

    • Abstract: The working efficiency of the combine harvester is still very low. It is an important way to realize mechanization to optimize the cutting speed of the harvester and the forward speed of the cutter without increasing economic input. In view of this, the present study briefly summarized the current structure of combine harvester systems. A new type of adaptive control system of combine harvesters was designed from the angle of cutting speed and forward speed of cutter. The sugarcane test base was taken as the test field, and the best matching speed was obtained with the goal of high efficiency of combine harvester and minimum sugarcane damage rate. In the test of cutting speed and forward speed of combine harvester, the optimal cutting speed under different forward speed conditions was recorded. The test results showed that the designed adaptive control system of the combine harvester could control the cutting speed and forward speed of the cutter well. The cutting speed and forward speed adaptive control system can realize the response to the input parameters and meet the design requirements of the harvester. This study can improve the economic benefits of the combine harvester and the quality of the harvested crops.
      PubDate: Tue, 27 Sep 2022 12:35:04 +000
  • A Review on the Environment Perception and Control Technologies for the
           Hyperredundant Manipulators in Limited Space

    • Abstract: As a typical kind of special robot with high flexibility and maneuverability, the hyperredundant manipulators (HRM) which can work in the narrow and complex space arose much related research work. Due to the particularity of the environment and the structural complexity of the manipulators, there are many problems for the HRM in specific applications. This paper summarizes some representative research works for HRM, including the mechanical design, environment perception, robotic navigation, and trajectory control. In order to make the design of the HRM systems more suitable for applications, the technical problems of current research are analyzed to address the key issues for the improvement. Finally, the prospect of spatial reachability, structural compactness, operation accuracy, and interaction friendliness of hyperredundant manipulators are presented.
      PubDate: Tue, 27 Sep 2022 09:50:01 +000
  • Software Engineering Code Workshop Based on B-RRTFND Algorithm for Deep
           Program Understanding Perspective

    • Abstract: Developers will perform a lot of search behaviors when facing daily work tasks, searching for reusable code fragments, solutions to specific problems, algorithm designs, software documentation, and software tools from public repositories (including open source communities and forum blogs) or private repositories (internal software repositories, source code platforms, communities, etc.) to make full use of existing software development resources and experiences. This paper first takes a deep programmatic understanding view of the software development process. In this paper, we first define the software engineering code search task from the perspective of deep program understanding. Secondly, this paper summarizes two research paradigms of deep software engineering code search and composes the related research results. At the same time, this paper summarizes and organizes the common evaluation methods for software engineering code search tasks. Finally, the results of this paper are combined with an outlook on future research.
      PubDate: Mon, 26 Sep 2022 11:05:04 +000
  • Artificial Intelligence-Based Interactive Art Design under Neural Network
           Vision Valve

    • Abstract: Interactive art design (IAD) is an organic integration of art and technology. From the perspective of the development of AI machines from ancient times to the present, it has gone through the stages of command interface, graphical interface, and multimedia interface. The development of interactive art has been around for some years. As an art form, it not only brings optimization and enjoyment to people’s quality of life but also meets the needs of human-computer interaction, improves the efficiency of art design, and realizes human-human interaction. The purpose is to bring different feelings and experiences to the works and people’s psychology. In particular, the application of AI in IAD has not only brought great changes to designers. It also derives the interaction of behavioral limbs, which brings a greater experience and interaction to the audience, thereby creating a better interactive effect. Therefore, this paper completes the following work: (1) the research progress of AI in IAD at home and abroad is introduced. (2) The combination of AI and IAD is proposed, and the basic principle of RBF neural network and intelligent optimization algorithm are introduced, and the evaluation index of IAD is constructed. (3) Using the constructed dataset to test two intelligent optimization algorithms, the results show that the PSO-RBF model is more excellent in evaluating the quality of IAD. The trained model is used for experiments, and the output of the model is compared with the expert evaluation results, and the error is very small. Comparing the quality indicators of IAD before and after the integration of AI, the results show that AI has an excellent improvement effect on IAD.
      PubDate: Sun, 25 Sep 2022 09:50:01 +000
  • The Application of Traditional Chinese Woodcut Printmaking Language in
           Digital Painting Based on Intelligent Computing

    • Abstract: With the passage of time, information technology has been implicitly embedded in people’s lives, bringing an important impact on artists’ creations. Modern painting technology is advanced, using electronic products, digital devices, electronic hand-painting tools, and other equipment to simulate the real texture of brush strokes to paint the style and effect the artist seeks. The integration of woodcut prints into digital painting has enriched the form of digital painting, and one of the characteristics of digital illustration is its fast dissemination, which is more powerful to promote the charm of traditional art. In the new era, with new technology, we consider whether we can combine the digital painting style, expression, woodcut language, and cultural connotation of ancient Chinese woodcut prints with digital technology and use new methods and forms to speak about the unique and essential attributes of ancient Chinese woodcut prints to be innovated and continued. The emotional motivation and the implicit, obscure connotations of the art of painting are not as far apart as they seem, although they are more like logical computerized counterparts. The continued development of artificial intelligence has made it possible for computers to create paintings independently. This paper explores a process flow model for digital painting based on intelligent computing and effectively incorporates the language of traditional Chinese woodcut printmaking while looking at future trends in this field.
      PubDate: Sun, 25 Sep 2022 09:05:01 +000
  • Selection of Optimum Internal Control Genes for RT-qPCR Analysis of
           Schisandra chinensis under Four Hormone Treatments

    • Abstract: qRT-PCR technology is now one of the commonly used methods to study gene expression levels. The selection of accurate reference gene detection is an essential work before gene expressing analysis. In the current study, 8 candidate internal control genes (ACTIN, TUBA, GAPDH, UBC, MUB, TIP41, APX, and CAPA) were selected, and four statistical algorithms were used to evaluate their stability under different hormone treatments. The results confirmed that when using one internal control genes, TUBA emerged as the first ranking internal control gene in all experimental groups. When using two internal control genes, TUBA and MUB, were the most acceptable internal control genes for the GA3 treatment group; TUBA and GAPDH were identified as internal control genes in the IAA treatment group; TUBA and ACTIN were the most reliable combination in the ZT and ABA experimental groups; TUBA and TIP41 were recommended most suitable control genes in control group. Furthermore, the reliability of the internal control genes was further verified by the expression of GAG, a gene related to the development of Schisandra chinensis. The conclusion of this work will be helpful for the subsequent research on gene expression analysis of Schisandra chinensis.
      PubDate: Sun, 25 Sep 2022 07:35:02 +000
  • Analysis of Nomadic Civilization in Northern Grassland in Plastic Arts
           Based on Deep Learning

    • Abstract: In this era of rapid development, the exchanges between countries are increasing rapidly, which leads to the integration of multiculturalism and its impact on the local culture, making it diluted. Taking the plastic art features of the nomadic civilization in the northern grasslands as an example, the plastic art features of the nomadic civilization are very rich, including color, texture, shape, and local characteristics; the use of traditional methods will lead to poor feature effects, and it is difficult to obtain high-level information. There will also be problems with image recognition. With the hot development of deep learning, for these problems, its advantages and characteristics are introduced and applied to the characteristics of plastic arts, and a deep and shallow network is constructed as its input and feature recognition, which solves the problem of image feature recognition. At the same time, the convolution idea is introduced to enlarge its features, which is more conducive to feature recognition, extraction, and analysis. For the neural network model of deep learning, the traditional optimization algorithm is changed to the Adam optimization algorithm, which solves the problem of decreasing accuracy, improves the accuracy of prediction, and makes it more stable. From the final experimental results, it is not difficult to find that the feature algorithm greatly improves the accuracy rate under different noises, and the time consumption of the algorithm operation is also reduced. The traditional algorithm of the deep learning neural network model is changed to the Adam optimization algorithm, which also improves the prediction accuracy and makes it more stable. In the future development, the unsaturated function can be used as the activation function to optimize or change the model feature algorithm to make the model easier to build and have better training effects.
      PubDate: Sat, 24 Sep 2022 17:35:04 +000
  • Consumption Behavior Prediction Based on Multiobjective Evolutionary

    • Abstract: Consumption behavior prediction reveals customer attributes, personal preferences, and intrinsic laws. Organizations would benefit from knowing further about customer needs and business desires by monitoring client behavior to provide more precise recommendations and boost acquisition rates. The economics of the customer, buyer groupings, and product quality are only a few of the numerous variables that influence customer behavior. The key issue that has to be resolved at this time is how to filter out useful information from these vast amounts of data to forecast customer behavior. For customer consumption behavior prediction and analysis with an advanced quantitative research process, we proposed the multiobjective evolutionary algorithm, which significantly boosts the accuracy of consumption behavior predictions. The dataset is initially gathered based on consumer preferences and behaviors as the essential information for the entire prediction model. Min-max normalization is used as a component of the preprocessing of the data to get the elimination of redundant and superfluous data. The Word2vec model is utilized for feature extraction, and boosted ant colony optimization (BACO) is employed to choose the best features. Utilizing the suggested multiobjective evolutionary algorithm (MOEA), the predictions are made. The suggested system’s performance is assessed, and the metrics are contrasted with more established methods. The findings demonstrate that the suggested MOEA technique performs well than the traditional ML, XGB, AI, and HNB algorithm methods in terms of accuracy (95 percent), quality of prediction (97 percent), precision (99 percent), recall (93 percent), -score (98 percent), and prediction time (50 seconds). Hence, the outcomes show that the regression model is sustainable. The suggested consumption behavior prediction system has demonstrated its efficiency in boosting profitability.
      PubDate: Sat, 24 Sep 2022 08:35:01 +000
  • Modeling of an Impedimetric Biosensor with Ultrasonic-Assisted Cell
           Alignment for the Detection of Yeast

    • Abstract: Yeast is an integral part of our environment. The detection of yeast is of great significance in many fields. The impedance-based sensor with interdigital microelectrodes is a promising method to establish a simple and portable detection system. However, the positions of yeast cells greatly influence the impedance variation and eventually the sensitivity of detection. In this study, an impedimetric biosensor with ultrasonic-assisted cell alignment for yeast detection was proposed. In order to verify the feasibility of this biosensor, finite element modeling was conducted using the software COMSOL. The acoustic pressure field and the acoustic radiation force exerted on yeast cells were investigated. Cell positions in the microfluidic channel were determined using the fluid particle tracking module. After that, the impedance between the microelectrodes was calculated. Yeast suspensions with different cell concentrations were used as the tested samples for the simulation. The proposed sensor showed a higher sensitivity than the conventional impedimetric biosensor on which the cells were randomly located. It can be used for the detection of microorganisms. This finite element modeling provided an effective approach for the design of biosensors.
      PubDate: Sat, 24 Sep 2022 07:50:01 +000
  • Artificial Intelligence-Based Soccer Sports Training Function Extraction:
           Application of Improved Genetic Algorithm to Soccer Training Path Planning

    • Abstract: Artificial intelligence has given a new dimension to the sport and mentality of soccer by tracking and planning the path of soccer and analyzing the learning process. Along with the rapid development of artificial intelligence technology, it is also used in sports events. Soccer, the world’s number one ball game, has always received worldwide attention. Although soccer is full of realism, it does not mean that its behavior cannot be predicted. By taking advantage of the role of artificial intelligence, model data from training is used to perform a deeper analysis of the correlated role of a soccer team’s players in the game, which is very helpful to improve the team’s training efficiency and tactics. As an emerging intelligent algorithm, the improved genetic algorithm can seek the global optimal solution based on the results of the algorithm execution and apply it to the planning of soccer training paths, which has a strong application value for improving the team’s training level and helping the team to formulate reasonable and effective offensive and defensive strategies. In this paper, we use artificial intelligence as the research background to improve the genetic algorithm by extracting the soccer training function and apply the improved algorithm to the soccer training path planning to get the global optimal solution, so as to help the players find the reasonable and effective optimal path of passing or shooting and help the team to build the tactical planning and winning strategy of offense and defense to meet the earnest expectation of soccer fans.
      PubDate: Sat, 24 Sep 2022 06:05:02 +000
  • Application of Artificial Intelligence-Based Sensor Technology in the
           Recommendation Model of Cultural Tourism Resources

    • Abstract: Aiming at the lack of theoretical basis for the development of cultural tourism resources, an application method of artificial intelligence-based sensor technology in the recommendation model of cultural tourism resources is proposed. Sensor network is an application-based network. Compared with traditional wireless communication network, it has the characteristics of large node scale, self-organized multihop, unattended, and no communication infrastructure. Combined with artificial intelligence sensor technology, this paper attempts to construct an evaluation index system and evaluation model for cultural tourism resources, and uses this model to conduct a comprehensive evaluation of cultural ecotourism resources in the western region. The experimental results show that the value of the evaluation result of cultural tourism resources in the western region is 6.346, which has a good development value. Secondly, from the specific evaluation results of each level, the western region has the highest cultural tourism standard, which has 6.605. Cultural tourism resources, landscape resources, and development conditions scored lower. Among them, cultural tourism resources and landscape resources have the highest score (7.186), and the economic and cultural field has the lowest score (6.092). Among the cultural tourism development conditions, the policy conditions are high (6.823), but the location conditions are very low, only 4.879 points. Therefore, it is found that the model takes cultural tourism landscape resources, cultural tourism environment resources, and cultural tourism development conditions as the content of cultural tourism resources evaluation, which is comprehensive and has strong hierarchy and pertinence; fuzzy comprehensive evaluation method has strong objectivity to determine the weight and the value classification; and weighting evaluation model of cultural tourism resources has rationality and generalizability and can provide a scientific basis for the classification and evaluation of cultural tourism resources and the planning and development of cultural tourism.
      PubDate: Sat, 24 Sep 2022 04:35:03 +000
  • Signal Optimization of Electronic Communication Network Based on Internet
           of Things

    • Abstract: In order to solve the problem that many people communicate at the same time, there are many external interference factors, and the signal is prone to instability in the process of electronic communication, the author proposes a signal optimization method for electronic communication network based on the Internet of Things. The method takes the cloud trust mechanism as the dynamic evolution trust relationship between various Internet of Things electronic communication services, performs explicit and implicit uncertainty conversion, calculates the objective function of data communication network performance, and confirms the control strategy. The positioning information of the network nodes in the communication is added to the communication data packet, and the most stable electronic communication path in the network is obtained to form the network topology structure. The Krasovsky method is adopted, and the working state of the nodes of the communication network is divided into the congested state and the normal state, the probability of the two is calculated, and the range of the transition balance is determined, so as to realize the optimization of the stability of the network topology. Experimental results show that the transmission rate of this method has been maintained at about 180 Kb/s; although there is fluctuation, the fluctuation value is small and the transmission rate is very stable. Conclusion. It can improve the accuracy of electronic communication of the Internet of Things and is less affected by external interference factors, and the communication transmission rate is faster.
      PubDate: Sat, 24 Sep 2022 04:35:03 +000
  • Risks and Opportunities of High-Quality Development of Higher Education
           from the Perspective of ISO45001:2018

    • Abstract: At present, the requirements of the high-quality development of higher education in China make the management and control of occupational health and safety risk in universities highly valued. However, the following problems perplexing the universities are people have always ignored the combination of the safety problems and risk management, and there are few studies on its health risk, which makes the management and control of occupational health and safety risk in universities far lag behind the pace of high-quality development of higher education. Therefore, it is very necessary to build a risk evaluation system for high-quality development of higher education with the help of ISO45001:2018 occupational health and safety management system tools. To reduce the degree of subjective assignment of weights by human evaluators, this study uses improved AHP and 2-tuple linguistic information method to evaluate the impact of eight factors such as safety risk management and health risk activities on the development of higher education. In addition, three-level indicators for each two-level indicator from the compliance of measures from multiple angles and batches. The results of this study will provide a valuable reference for the risk control and performance improvement (i.e., opportunity response) of higher education from the perspective of ISO45001:2018. It will also help to improve the connotation of relevant party management and promote the high-quality development of higher education.
      PubDate: Sat, 24 Sep 2022 04:35:03 +000
  • Application and Analysis of RGB-D Salient Object Detection in Photographic
           Camera Vision Processing

    • Abstract: To identify the most visually salient regions in a set of paired RGB and depth maps, in this paper, we propose a multimodal feature fusion supervised RGB-D image saliency detection network, which learns RGB and depth data by two independent streams separately, uses a dual-stream side-supervision module to obtain saliency maps based on RGB and depth features for each layer of the network separately, and then uses a multimodal feature fusion module to fuse the latter 3 layers of RGB and depth high-dimensional information to generate high-level significant prediction results. Experiments on three publicly available datasets show that the proposed network outperforms the current mainstream RGB-D saliency detection models with strong robustness due to the use of a dual-stream side-surveillance module and a multimodal feature fusion module. We use the proposed RGB-D SOD model for background defocusing in realistic scenes and achieve excellent visual results.
      PubDate: Sat, 24 Sep 2022 04:20:02 +000
  • A Study of Language Use Impact in Radio Broadcasting: A Linguistic and Big
           Data Integration Approach

    • Abstract: Broadcasting more culturally educating and language-reviving contents are ways radio stations can help revitalize indigenous languages in Delta North in Nigeria. The challenges faced in communicating through indigenous dialects on radio stations are majorly caused by the lack of indigenous language professionals and linguists in the broadcast stations. The absence of these professionals is a major constraint to the development of the community. The broadcast media can help manage multilingualism through the introduction of new words which would give little or no room for lexicon dearth but would expand the language lexicon. Using these dialects during broadcast gives relevance to all dialects, reduces language dearth, and keeps people connected to their culture. Programmes anchored in indigenous dialects enhance the vocabulary, comprehension, and language vitality of the language. The study examined the impact of local language used in radio broadcasting using a descriptive big data survey research design. The study’s population comprises of all the inhabitants of Delta North from which a sample of 10 broadcast staff and 120 radio listeners in Delta North Senatorial District in Nigeria was drawn using a stratified random sampling technique. The instrument of data collection was a structured questionnaire with closed questions and a self-structured interview. The sample employed frequency distribution tables, percentages, and charts in the presentation and analysis of data. The results revealed that majority of the respondents in Delta North listened to radio broadcast indicating that the use of indigenous dialects/language can have massive impact on the people. The study also found that majority of the respondents use indigenous languages in their day-to-day activities, with English being used majorly only in schools. The study recommends, among others, that the National Broadcasting Commission review their policy on the allocated time of broadcast in indigenous languages and that more indigenous language experts and linguists should be incorporated into the broadcast system.
      PubDate: Sat, 24 Sep 2022 02:20:00 +000
  • Robot Obstacle Avoidance Controller Based on Deep Reinforcement Learning

    • Abstract: As the core technology in the field of mobile robots, the development of robot obstacle avoidance technology substantially enhances the running stability of robots. Built on path planning or guidance, most existing obstacle avoidance methods underperform with low efficiency in complicated and unpredictable environments. In this paper, we propose an obstacle avoidance method with a hierarchical controller based on deep reinforcement learning, which can realize more efficient adaptive obstacle avoidance without path planning. The controller, with multiple neural networks, contains an action selector and an action runner consisting of two neural network strategies and two single actions. Action selectors and each neural network strategy are separately trained in a simulation environment before being deployed on a robot. We validated the method on wheeled robots. More than 200 tests yield a success rate of up to 90%.
      PubDate: Fri, 23 Sep 2022 16:35:05 +000
  • User Experience Perspectives on the Application of Interactivity Design
           Based on Sensor Networks in Digital Museum Product Display

    • Abstract: This paper designs a model of interactivity design in digital museum product display, constructs a sensor network model, and tests the sensor network-based interactivity design in digital museum product display under the perspective of user experience. This paper makes a museum user experience model based on sensory, behavioral, cognitive, and emotional experiences; establishes a user experience design framework; conducts specific theoretical analysis and research from four aspects; uncovers specific factors affecting museum user experience; analyzes the impact of each experience factor on user system design and possible design entry points; and proposes corresponding user system design strategies to guide subsequent design practice sessions. This paper also completes the hardware circuit and PCB board design of the wireless sensing node based on the CC2430 chip as the core. Tomcat WEB server and J2EE-based Spring MVC Web development framework are used as the leading implementation technology to complete the functions of real-time data query, network parameter setting, and historical data storage. The ideographic practice of visual representation of the digital museum is discussed around its optical system. Knowledge-based model dominates the digital museum representation, and examining the complex constitutive processes and characteristics of images involves not only the production of discursive order but also the production of presentation contexts as well as virtual spaces, which construct a new visual presentation of digital museums. However, the virtual representation practice of digital museums still has paradoxes, the absence of the sense of experience and the flatness of the virtual space, in which the audience cannot have a visual experience under this presentation.
      PubDate: Fri, 23 Sep 2022 16:35:05 +000
  • Research on the Use of Task-Based Language Teaching Method in English
           Language Teaching Based on Big Data 5G IoT Scenario

    • Abstract: The state implemented the compulsory education standard for full-time students in 2001, which clearly stipulates that English teachers should promote special language teaching methods, develop comprehensive language use skills, and propose teaching methods such as practice, cooperation, and communication. The task-based language teaching method has become a commonly used method in English teaching, and it is necessary to study the application of task-based language teaching method in English courses and try to apply the task-based language teaching method effectively. This study analyzes the needs of English teaching in the context of big data 5G IoT scenario, new curriculum reform, and theories related to English teaching methods in order to explore new methods of English teaching, verify its feasibility and necessity, and prepare reference materials for future grammar teaching research.
      PubDate: Fri, 23 Sep 2022 13:20:00 +000
  • Research on Path Planning Method of Unmanned Boat Based on Improved DWA

    • Abstract: Aiming at the problem of local path planning for unmanned surface vehicles, the traditional dynamic window algorithm (DWA) has the problems of uneven obstacle avoidance path and poor adaptability to complex environments. This paper proposes a local path planning method based on improved DWA. The evaluation item that replaces the direction angle difference with the target distance is used to avoid the path from being unsmooth due to vibration. And the fuzzy logic control algorithm is introduced to dynamically adjust the weight value of the trajectory evaluation function to complete the path optimization. The introduction of the A algorithm is designed to preplan the map environment and extract key turning points as subtarget points of the local obstacle avoidance algorithm to enhance the path optimization ability. The simulation results show that the improved DWA algorithm can shorten the planned path length by 23.4% and the path smoothness by 34.8%, enabling USV to find a reasonable, efficient, and smooth path in complex environments.
      PubDate: Fri, 23 Sep 2022 06:20:02 +000
  • Distance Measurement by Neural Network Learning of Near-Field Microwave
           Reflection Spectra

    • Abstract: Microwave-based distance measurements are limited depending on the sensing environment, such as the propagation medium and surrounding obstacles, and the complex environment also affects the measurement performance. To tackle this problem, we propose a method for predicting the distance based on the artificial neural network learning of near-field microwave reflection spectra. In principle, the spectral data is expected to contain a signature of the distance of the target object. Based on this, we proposed a two-step neural network to extend the measurable distance range while ensuring prediction performance. The first step is to predict the coarse range of the target by classification, and the next is to predict the precise distance value through multidimensional regression within that coarse range. The method was verified through experiments to predict the position of an object in an underwater environment, which was difficult to measure with conventional methods.
      PubDate: Thu, 22 Sep 2022 17:35:02 +000
  • Smart Sensor Network Optimization and Line Defect Identification Based on
           UAV Transmission Inspection under 5G Technology

    • Abstract: Transmission line is a key link in the transmission line, as the main equipment in the grid are located in the field; in the long-term harsh environmental conditions, the line is very easy to appear broken strands, broken, and other defects, which need to be regularly monitored and maintained. The traditional manual line inspection operation is not only harsh, labor-intensive, inefficient, and low precision but also has a great impact on the personal safety of the operators due to the complicated operating conditions. This project mainly focuses on 5G, intelligent sensor network technology, and the application of UAVs in high-voltage line inspection, detection, and maintenance. The developed inspection UAVs can effectively improve the efficiency of line inspection and quickly discover fault points, which brings convenience to the construction of power systems. In the 5G environment, the use of UAV transmission inspection technology for line fault identification can overcome the shortcomings of manual faults, but also timely and comprehensive fault detection, and improve the effectiveness and standardization of monitoring work.
      PubDate: Thu, 22 Sep 2022 17:35:02 +000
  • Multisensor Dynamic Alliance Control Problem Based on Fuzzy Set Theory in
           the Mission of Target Detecting and Tracking

    • Abstract: A multisensor alliance is established by the activation of tasks or occurrences. It is also characterized as a multisensor dynamic alliance since it originates with mission development and disintegrates with task accomplishment. To overcome the constraint that a single sensor can only gather a one-sided, little amount of erroneous target information, each sensor in the dynamic alliance has diverse information collection capabilities and implements a cooperative methodology to complete the target mission. This paper emphasizes on alliance formation in multisensor dynamic alliance control under diverse missions. To begin with, we investigate the problem at the sensor recognition level for each target feature, delving into the concepts of alliance formation, renewal, and dissolution and emphasizing the fuzzy relationship in the multisensor dynamic alliance for multitarget. Moreover, dynamic alliance models are constructed using the fuzzy set calculation algorithm, which is powered by target detection, recognition, and tracking tasks in that sequence. Last but not least, simulation experiments demonstrated that the proposed model and algorithm outperform the existing models and algorithms. We may achieve the optimal alliance scheme by introducing the fuzzy set calculation algorithm into the dynamic alliance establishment process, which completely nullifies information redundancy and enhances the monitoring capabilities of the sensor network.
      PubDate: Thu, 22 Sep 2022 17:35:02 +000
  • Application of DC-DC Converter in Sensor and MEMS Device Integration and

    • Abstract: DC-DC (direct current controlled direct current) converter is the core control circuit in the field of power electronics technology. Based on the theory of sensors and MEMS (microelectromechanical systems), this paper constructs a DC-DC converter device integration and packaging model and proposes an enhanced current equalization technology with offset correction function suitable for two-phase DC-DC converters. Aiming at the generation mechanism of the output ripple of the two-phase DC-DC converter, the model adopts the ripple elimination technology based on the interleaved synchronous clock and the self-calibration interleaved time generator, so that each phase of the converter is accurately staggered within the full-load range, and the problem of output ripple amplitude is solved. During the simulation process, a high-performance two-phase DC-DC converter chip is designed and implemented, which includes an adaptive on-time control logic based on ripple feedback, a self-calibrating zero-current turn-off circuit, and a robust power switch transistor drive logic. The experimental results show that the full-load current of the chip reaches 6A, the peak efficiency is 91%, the phase-to-phase current error is
      PubDate: Thu, 22 Sep 2022 08:20:02 +000
  • Automatic Detection of Atrial Fibrillation from ECG Signal Using Hybrid
           Deep Learning Techniques

    • Abstract: In cardiac rhythm disorders, atrial fibrillation (AF) is among the most deadly. So, ECG signals play a crucial role in preventing CVD by promptly detecting atrial fibrillation in a patient. Unfortunately, locating trustworthy automatic AF in clinical settings remains difficult. Today, deep learning is a potent tool for complex data analysis since it requires little pre and postprocessing. As a result, several machine learning and deep learning approaches have recently been applied to ECG data to diagnose AF automatically. This study analyses electrocardiogram (ECG) data from the PhysioNet/Computing in Cardiology (CinC) Challenge 2017 to differentiate between atrial fibrillation (AF) and three other rhythms: normal, other, and too noisy for assessment. The ECG data, including AF rhythm, was classified using a novel model based on a combination of traditional machine learning techniques and deep neural networks. To categorize AF rhythms from ECG data, this hybrid model combined a convolutional neural network (Residual Network (ResNet)) with a Bidirectional Long Short Term Memory (BLSTM) network and a Radial Basis Function (RBF) neural network. Both the F1-score and the accuracy of the final hybrid model are relatively high, coming in at 0.80% and 0.85%, respectively.
      PubDate: Thu, 22 Sep 2022 08:20:02 +000
  • A Smart Campus Implementation Architecture Based on Blockchain Technology

    • Abstract: With the application of 5G technology in the field of education, the construction of smart campus has set off a wave of digital transformation. At the same time, the traditional smart campus is also facing the exponential growth of the number of Internet of Things devices, servers, and application terminals, which makes it difficult to achieve flat management. In view of the current difficulties in the construction of smart campus, this paper proposes smart campus architecture based on blockchain technology. Unlike the traditional smart campus architecture, this paper combines the characteristics of decentralization, high confidentiality, and data sharing of block chain with the Internet of Things technology, which greatly reduces the demand for data storage and physical network equipment. The new smart campus architecture plans the application of smart education based on blockchain, and provides a new solution model and research ideas.
      PubDate: Thu, 22 Sep 2022 07:50:02 +000
  • Improve Performances of Wireless Sensor Networks for Data Transfer Based
           on Fuzzy Clustering and Huffman Compression

    • Abstract: In today’s world, the main challenge is to save use energy optimally. The IoT devices generate a large amount of data for wide applications. Considering the application perspective in the IoT market, in one instance of the IoT technology, that is a wireless sensor network, factors like energy, storage capacity, computation power, and limitations of communication bandwidth resources are the reason for using data fusion. Data fusion and aggregation in wireless sensor networks (WSNs) such that minimum energy is consumed are an essential issue. In most clustering models, data aggregation is carried out by the cluster-head (CH). In the proposed algorithm, data aggregation in the cluster-head is carried out using the lossless cascode Huffman compression algorithm. Due to the correlation among data of nodes, the data sensed by each node is compared with the data of the cluster-head node; after removing redundancy, the coded data is transmitted to the main node. The CH node is selected by an algorithm based on fuzzy logic according to the residual energy of the node and the distance of the node from the sink node. Various fuzzy type-I systems of Mamdani and Takagi-Sugeno and type-II systems are used. In this paper, the CH selection algorithms are evaluated using three scenarios in terms of the number of live nodes, received packets and CHs, proper distribution rate, and other parameters of the LEACH protocol, network lifetime, and network energy. In the following, to demonstrate the performance of this new algorithm, simulations are performed in MATLAB based on the proposed method. The results show that the proposed compression algorithm in environments with high data correlation improves the compression rate by 8% compared to the conventional Huffman compression, while in environments with low data correlation, these two algorithms perform almost the same. This compression helps reduce the energy consumption of the network.
      PubDate: Thu, 22 Sep 2022 07:50:01 +000
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