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Journal articles on the topic 'Data transmission'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

S., Mrs Bhuvaneswari M. "Secure Data Transmission in VANETs." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 1966–70. http://dx.doi.org/10.31142/ijtsrd11561.

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2

Prompinit, Thitapa, Amonwan Jenjirataworn, and Sarinporn Visitsattapongse. "Healthcare Data Transmission by Using NB-IoT." International Journal of Pharma Medicine and Biological Sciences 9, no. 1 (January 2020): 14–17. http://dx.doi.org/10.18178/ijpmbs.9.1.14-17.

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3

Gowthami, Chebrolu, and S. Kavitha. "Heightening Security for Data Transmission Through Dynamic Routing." International Journal of Information and Education Technology 1, no. 5 (2011): 441–44. http://dx.doi.org/10.7763/ijiet.2011.v1.72.

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4

Ambala, Soujanya, Dr Srinivas Ambala, and Sreedhar Ambala. "M2M Networking Architecture for Data Transmission and Routing." International Journal of Trend in Scientific Research and Development Volume-1, Issue-1 (December 31, 2016): 59–63. http://dx.doi.org/10.31142/ijtsrd79.

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5

qizi, Kosimova Marjona Shakirjon. "APPLICATION OF CODING IN DATA TRANSMISSION AND INFORMATION STORAGE." American Journal of Applied Science and Technology 4, no. 6 (June 1, 2024): 67–70. http://dx.doi.org/10.37547/ajast/volume04issue06-13.

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Coding theory plays a crucial role in modern data transmission and information storage systems, ensuring the efficient and reliable handling of digital information. This article explores the fundamental principles of coding theory, focusing on its applications in both data transmission and storage contexts. Beginning with an introduction to encoding and decoding techniques, the article delves into how various coding methods, such as error detection and correction codes, enhance data integrity during transmission. It further examines the implementation of coding in storage devices to safeguard against data loss and corruption.

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6

K, Dr Anguraj. "Transmission of the Numeric Data Using Light Fidelity Technology." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 1391–94. http://dx.doi.org/10.5373/jardcs/v12sp7/20202241.

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7

Ooki, M. "On a Characteristic of Data Transmission In Bus Network." Journal of Advances in Computer Networks 2, no. 2 (2014): 120–24. http://dx.doi.org/10.7763/jacn.2014.v2.94.

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8

Balachander, Bhuvaneswari. "Laser Based Data Signal Transmission Using Free Space Optics." International Journal of Scientific Research 2, no. 12 (June 1, 2012): 204–5. http://dx.doi.org/10.15373/22778179/dec2013/63.

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9

SUGA, Yutaka. "Data transmission in FMS." Journal of the Japan Society for Precision Engineering 53, no. 9 (1987): 1362–66. http://dx.doi.org/10.2493/jjspe.53.1362.

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10

S, Rajyalakshmi, Lavanya Jyothi M, Kumari M, Venkata Ganga Yasaswini L, Srivani M, Bhargavi M, Chandrakala K, Supriya K, Dora M V V S, and Asha MD. "Data transmission through lasers." South Asian Journal of Engineering and Technology 12, no. 3 (November 3, 2022): 167–70. http://dx.doi.org/10.26524/sajet.2022.12.54.

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In the current era technology in science has recently attracted owing the advancement of applications in lasers. A project on the applications of the laser introduced. The application part of the laser has been applied by simple laser communication system which evolved in its working with the support of solar panel, differential grating. It also provides the information how the data is transmitted through lasers.

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A, Bharathi, Siva C, Suguna Angamuthu, and Thangamani M. "Multi Objective Concerned Network Coding Technique for Optimal Data Transmission." Webology 18, no. 05 (October 29, 2021): 1191–203. http://dx.doi.org/10.14704/web/v18si05/web18300.

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The Internet of Things (IoT) seems to developed in the real-world scenario due to increased utilization of sensor driven technologies. There are various research works has been proposed earlier for the network coding to ensure the reliable data transmission. However, existing research techniques doesn’t focus on the reliable route path selection which might affect the rate of data transmission. These issues are focused in the proposed research method by introducing the method namely Multi-Objective concerned Network Coding Technique (MO-NCT). In this work initially multicast tree construction is performed using Particle Swarm Optimization method. The main goal of this research work is ensuring the reliable and successful data transmission. Here the optimal network nodes will be chosen for constructing the multi cast tree. The multiple objectives considered in this work for the selection of the nodes are residual energy, remaining bandwidth level and throughput of nodes. To ensure the reliable data transmission even with the presence of larger coverage area, this work attempted to select the backup forwarder nodes which will act as intermediate hop relay nodes. The overall analysis of the research work is done in the NS2 simulation environment from which it is proved that the proposed method MO-MRP tends to achieve the optimal data transmission rate.

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12

R, Sindhuja, and Vasuinthira N. "Efficiently Data Analysis and Transmission for consumer using grid computing." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 643–50. http://dx.doi.org/10.31142/ijtsrd10991.

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13

Desai, Ruchita Ashwin, and Raj Bhimashankar Kulkarni. "Energy efficient reliable data transmission for optimizing IoT data transmission in smart city." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 3 (June 1, 2024): 1978. http://dx.doi.org/10.11591/ijeecs.v34.i3.pp1978-1988.

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The rapid proliferation of the internet of things (IoT) technology has significantly transformed urban landscapes, giving rise to smart city frameworks that leverage interconnected devices for enhanced efficiency and functionality. In these environments, vast amounts of data are generated by diverse sensors and devices, necessitating advanced strategies for effective data collection and transmission. This paper introduces a novel approach to address data collection and transmission challenges in IoT-enabled smart city frameworks. The proposed design integrates IoT-Cloud for efficient data collection and employs the energy efficient reliable data transmission (EERDT) model, optimizing IoT data transmission. The enhanced dragonfly routing algorithm, incorporating the firefly algorithm, enhances data routing efficiency. Experimental results demonstrate EERDT's superiority over energy-aware iot-routing (EAIR) and location-centric energy-harvesting aware-routing (LCEHAR), revealing significant improvements in communication overhead, data processing latency, and network lifetime. The EERDT exhibits substantial reductions in communication overhead, enhancing overall network performance. The EERDT model showcases lower data processing latency and energy consumption, highlighting its potential for resource-efficient IoT data transmission. This work contributes an innovative solution for smart city IoT networks, emphasizing performance enhancements and resource efficiency.

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14

Kim, Soke-Hwan, and Chang-Wu Hur. "Data Transmission Specific Simulation of Transmission Line using HSTL." Journal of the Korean Institute of Information and Communication Engineering 15, no. 8 (August 31, 2011): 1777–81. http://dx.doi.org/10.6109/jkiice.2011.15.8.1777.

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15

Bai, Demeng, Xuebin Lv, Jian Wang, and Wenjie Zheng. "Application of Directional Transmission Data Technology for Transmission Lines." Journal of Physics: Conference Series 1584 (July 2020): 012040. http://dx.doi.org/10.1088/1742-6596/1584/1/012040.

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16

Chen, Shang Liang, Sin Ru Wang, You Chen Lin, and Yun Yao Chen. "A Novel Wireless Data Acquisition Infrastructure for Manufacturing Equipment Based on Wi-Fi." Applied Mechanics and Materials 764-765 (May 2015): 788–91. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.788.

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Production information collection is an important issue for manufacturing. Therefore, the data transmission techniques for manufacturing equipment are hot spots for researchers nowadays. Traditional equipment data transmissions are based on Ethernet, which encountered issues such as high maintenance cost and unreal-time data transmission. A wireless data acquisition infrastructure for manufacturing equipment based on Wi-Fi is designed for ensuring the data transmission quality in factories.

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17

Kanta, Vaishnavi, Sneha Singh, Sakshi S, and Sandhya Katiyar. "Secure Data Transmission in MANET." International Journal of Computer Applications 178, no. 22 (June 18, 2019): 23–28. http://dx.doi.org/10.5120/ijca2019918970.

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18

Dixit, AdarshaR, Adithya S, Anirudh R, Naren S, and Lakshmi Bhaskar. "DATA TRANSMISSION USING VISIBLELIGHT COMMUNICATION." International Journal of Advanced Research 4, no. 8 (August 31, 2016): 1821–30. http://dx.doi.org/10.21474/ijar01/1397.

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19

Samoylova, M. "ODU connectors for data transmission." ELECTRONICS: Science, Technology, Business, no. 7 (2018): 88–93. http://dx.doi.org/10.22184/1992-4178.2018.178.7.88.93.

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20

OLANIYAN, O. O., and A. TAIWO. "A new data transmission modem." International Journal of Electronics 62, no. 1 (January 1987): 97–103. http://dx.doi.org/10.1080/00207218708920954.

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21

de Sa, E. S., R. Y. Prabhu Desai, and E. J. D'Sa. "Satellite Transmission of Oceanographic Data." IETE Journal of Education 27, no. 4 (October 1986): 148–54. http://dx.doi.org/10.1080/09747338.1986.11436119.

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22

Bhavani, S., and B. Raviteja. "Secure Data Transmission through RDH." International Journal of Signal Processing, Image Processing and Pattern Recognition 7, no. 6 (December 31, 2014): 261–72. http://dx.doi.org/10.14257/ijsip.2014.7.6.22.

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23

Allen, Jonathan B. "Data over voice transmission arrangement." Journal of the Acoustical Society of America 83, no. 6 (June 1988): 2474. http://dx.doi.org/10.1121/1.396314.

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24

Lind, L. F. "Complex coefficient data transmission filters." Electronics Letters 32, no. 6 (1996): 516. http://dx.doi.org/10.1049/el:19960394.

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25

Page, Ginny. "BSE transmission data cause confusion." Nature 382, no. 6590 (August 1996): 381. http://dx.doi.org/10.1038/382381b0.

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26

Cohen, Aaron E., and Keshab K. Parhi. "Secure Variable Data Rate Transmission." IEEE Transactions on Circuits and Systems II: Express Briefs 58, no. 2 (February 2011): 100–104. http://dx.doi.org/10.1109/tcsii.2011.2106313.

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27

Xiong, Jiang, Qing Ming Yi, Min Shi, and Ting Ting Li. "HDMI Data Transmission System Design." Applied Mechanics and Materials 380-384 (August 2013): 4094–97. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.4094.

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A new HDMI data transmission system is proposed in this paper. To achieve a better data transmission performance, the TMDS codec algorithm of HDMI transmitter and receiver are optimized, thus the precision and practical applicability is improved. Moreover, a color enhanced module and an error correction module are added to the system. The proposed system is implemented using Verilog DHL language and simulated in Modelsim software. The simulation results show that the proposed system exhibits better performance on the functions of data sending and receiving.

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28

Rumpel, D., D. Proske, W. Kempinski, and M. Hummel. "The GDL data transmission experiment." European Transactions on Electrical Power 7, no. 2 (September 7, 2007): 143–46. http://dx.doi.org/10.1002/etep.4450070210.

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29

Fliege, Norbert J. "Orthogonal multiple carrier data transmission." European Transactions on Telecommunications 3, no. 3 (May 1992): 255–64. http://dx.doi.org/10.1002/ett.4460030307.

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30

M., Anugraha, and Dr Krishnaveni S.H. "In Mobile Adhoc Networks, a Trustworithness of Data Transmission Using HTCMR." Webology 19, no. 1 (January 20, 2022): 2152–63. http://dx.doi.org/10.14704/web/v19i1/web19145.

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Mobile Ad hoc Network is a self-configured network, the main responsibility faced in the network is security. Malicious nodes are mostly to blame for the insecurity of MANET. The malicious attacker nodes will disrupt the overall functioning of the network, and many security solution approaches are utilized for safe and reliable communication in MANET to stop such harmful activity. This routing, known as Hybrid Trust Cluster based Multiple Routing (H-TCMR), helps to minimize the amount of messages carried inside the network, lowering the network's total energy usage. It utilizes Hybrid Time Division Multiple Access (HTDMA) for time slots and the Unified Slot Assignment Protocol (USAP) for cluster allocation. Using Hybrid Rider Optimization Algorithm (HROA) approaches, a group of riders will drive together to a specified location in order to obtain the cluster head slot. The suggested approach encrypts the data before sending it to its final destination. It also helps to extend the life of mobile networks. Some of the factors considered in simulation studies include connection, energy, average delay, throughput, as well as overall cluster quality. The simulation result demonstrates a performance study of HTCMR's dependable security, as well as increased system efficiency and improved data transfer security.

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31

Jaiad, Ahmad T., and Dr Seyed Vahab AL-Din Makki. "Implementation of SCADA System for Data Transmission 33/11 Kv Substation." Webology 19, no. 1 (January 20, 2022): 1474–80. http://dx.doi.org/10.14704/web/v19i1/web19098.

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At a time when the world is looking to reduce the levels of electrical energy expenditure and control losses, in this research we will transfer the data of the 33/11 Kv distribution station using the SCADA system and by linking an optical cable instead of the previous wireless methods between the distribution station and the control center, and measure The speed of data transfer and comparison of the two cases, as well as analysis of the data sent to calculate the amount of increased energy and future electrical energy loading, calculate the amount of electrical energy consumption spent by the consumer and compare it with production quantities to know the value of the losses resulting from the process of transferring electrical energy from the source to the consumer.

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32

M, Vincent Bulinda. "Long Distance Data Transmission using Bessel Functions of the First Kind." SIJ Transactions on Computer Networks & Communication Engineering 03, no. 06 (December 15, 2015): 01–04. http://dx.doi.org/10.9756/sijcnce/v3i6/03060110101.

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33

Gokulakrishnan, Jayanthi, and V. Thulasi Bai V. Thulasi Bai. "Performance of Two Dimensional Tunneling for Secure Data Transmission in Vpn." Indian Journal of Applied Research 3, no. 9 (October 1, 2011): 254–57. http://dx.doi.org/10.15373/2249555x/sept2013/76.

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34

Rajesh Kumar Dhanaraj, Rajesh Kumar Dhanaraj, Seifedine Kadry Rajesh Kumar Dhanaraj, Byeong-Gwon Kang Seifedine Kadry, and Yunyoung Nam Byeong-Gwon Kang. "Probit Cryptographic Blockchain for Secure Data Transmission in Intelligent Transportation Systems." 網際網路技術學刊 23, no. 6 (November 2022): 1303–13. http://dx.doi.org/10.53106/160792642022112306013.

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<p>To address the current security challenges, Digital Twin (DT) models and strategies are to be applied to improve security, privacy, and safety in intelligent transportation systems. However, the existing algorithm was failed to address the security and privacy issues for data between the vehicles. To enhance the security of data transmission, a novel Probit Regressive Davis Mayer Kupyna Cryptographic Hash Blockchain (PRDMKCHB) technique is proposed. Initially, the source vehicle finds the nearest vehicle to transmit the data based on the trust value using the probit regression function. After finding the neighboring nodes, the Blockchain is constructed to improve the security of data transmission from the source to the destination. The Blockchain uses the Kupyna Cryptography to generate the hash value for each data. Davis Mayer compression function is to improve the security of data delivery and to minimize packet loss. The comprehensive simulation is carried out to validate the performance of the proposed PRDMKCHB technique and existing Blockchain technology in terms of packet delivery ratio, packet loss rate, and execution time. Simulation results show the performance improvement of the proposed PRDMKCHB technique compared to the previous Blockchain technology in terms of higher packet delivery ratio, minimum packet loss, and execution time with respect to the number of data packets.</p> <p> </p>

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35

Shashidhar, P. K., T. C. Thanuja, and Rajashekar Kunabeva. "Adaptive RPL Routing Optimization Model for Multimedia Data Transmission using IOT." Indian Journal Of Science And Technology 17, no. 5 (January 31, 2024): 436–50. http://dx.doi.org/10.17485/ijst/v17i5.2627.

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Objectives: The main objectives of this research endeavor encompass the development of the Adaptive RPL Optimization (ARPLO) model to enhance data transmission efficiency within IoT networks. This includes constructing a grid-based network structure optimized for data transfer, selecting the most suitable nodes as grid head nodes to maximize network lifespan while minimizing energy consumption, implementing an innovative objective function-driven approach to optimize parent node selection, and integrating an Adaptive Deep Neural Network (ADNN) to accurately classify medical data. Methods: The research methodology entails several key steps. A grid-based network structure is established with IoT nodes and root nodes, where a DODAG process incorporating DIO messages is utilized for node ranking. To enhance energy efficiency, the Trickle algorithm is employed for control message optimization. Grid head nodes are chosen based on metrics such as root node fairness, residual energy, and load influence index. The novel Middle Order Optimal Routing (MOOR) objective function is utilized to optimize routing decisions. ADNN is implemented for precise medical data classification. The proposed model's performance is evaluated through simulation in a Python environment. Findings: The research findings demonstrate that the ARPLO model yields notable benefits compared to existing models. It achieves higher energy efficiency, improved throughput, enhanced packet delivery ratio (PDR), and an extended network lifespan. The Trickle algorithm contributes to efficient control message optimization. The MOOR-based routing approach improves multimedia medical data transfer. Moreover, the integration of ADNN enhances the accuracy of data classification, particularly in healthcare applications. The research outcomes align with the broader field's existing values and reports while offering novel insights that contribute to enhancing the existing knowledge base. ARPLO protocol performance reveals that there is increase of throughput of 31.2%, PDR by 7.12%, lifetime of 10.7 % with reduction of energy consumption by 12.72%, control overhead by 31.01% and end-to-end delay by 33.01%. Novelty: The novelty of this research lies in its comprehensive approach that integrates a grid-based network structure, MOOR-based optimization, and ADNN-based classification. The incorporation of the Trickle algorithm for energy-efficient communication is an innovative feature. The introduction of new metrics for grid head node selection, along with the application of the MOOR objective function for multimedia medical data routing, showcases the research's innovative contributions. Keywords: Internet of Things (IoT), RPL (Routing Protocol for LowPower and Lossy Networks), Optimization, Routing, Multimedia, Healthcare

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36

M, Ravi Kumar, Sanjai S, Shilpashree S, Shreyas N. Kulal, and Tinu M. "A Review of Serdes CMOS Transceiver for High Speed Data Transmission." International Journal of Research Publication and Reviews 5, no. 3 (March 9, 2024): 1519–22. http://dx.doi.org/10.55248/gengpi.5.0324.0706.

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37

Li, Yan Qin, and Chun Fu Li. "Data Acquisition System Design and Data Analysis on Automatic Transmission." Applied Mechanics and Materials 239-240 (December 2012): 861–64. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.861.

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An efficient data acquisition system for electronic automatic transmission test, which makes use of American NI’s data acquisition card, is designed based on Virtual Instrument. The data can be collected by the data acquisition system include automatic transmission oil pressure, solenoid duty, as well as engine speed ，turbine speed ，output shaft speed and throttle degree，and so on. The key problems of the system design are measurement method of automatic transmission solenoid duty, signal conditioning circuit design and multi-signal acquisition synchronization. Test platform is North-Benz dump truck 2627K (Its power-train assembly is replaced), of which transmission and engine use respectively HD4070PR electronic automatic transmission and BF6M1015CP electronic diesel engine. The automatic transmission shift control strategy and oil pressure characteristics of clutch or brake etc can be analyzed through test data acquisition.

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38

Wu, Shuiyan, Xiaofei Min, and Jing Li. "Optimal Data Transmission for WSNs with Data-Location Integration." Symmetry 13, no. 8 (August 16, 2021): 1499. http://dx.doi.org/10.3390/sym13081499.

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Wireless sensor networks (WSNs) have good performance for data transmission, and the data transmission of sensor nodes has the function of symmetry. However, the wireless sensor nodes are facing great pressure in data transmission due to the increasing amount and types of data that easily cause premature energy consumption of some nodes and, thus, affects data transmission. Clustering algorithm is a common method to balance energy consumption, but the existing algorithms fail to balance the network oad effectively for big data transmission. Therefore, an optimal data transmission with data-location integration (ODTD-LI) is proposed for WSNs in this paper. For optimal data transmission, we update the network topology once for one round. In the proposed algorithm, we perform calculations of the optimal cluster heads, clustering and data transmission routing through three steps. We first deploy N homogeneous and symmetry nodes in a square area randomly and calculate the optimal number of cluster heads according to the node ocations. then, the optimal number of cluster heads, energy consumption, the distances and degrees of the nodes are taken into consideration during the clustering phase. Direct communication is carried out within a cluster, and the member nodes of the cluster pass the information directly to the cluster head. Lastly, an optimal hybrid routing from each cluster node to Sink is constructed for data transmission after clustering. The simulations verify the good performance of the proposed algorithm in view of the ifetime, average delay, coverage rate (CR) and oad balance of the network compared with the existing algorithms. Through the research conducted in this paper, we find that our work has good performance for selecting the hybrid routing in the network with the nodes randomly arranged.

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39

Robert, Alexis, Sebastian Funk, and Adam J. Kucharski. "o2geosocial: Reconstructing who-infected-whom from routinely collected surveillance data." F1000Research 10 (January 18, 2021): 31. http://dx.doi.org/10.12688/f1000research.28073.1.

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Reconstructing the history of individual transmission events between cases is key to understanding what factors facilitate the spread of an infectious disease. Since conducting extended contact-tracing investigations can be logistically challenging and costly, statistical inference methods have been developed to reconstruct transmission trees from onset dates and genetic sequences. However, these methods are not as effective if the mutation rate of the virus is very slow, or if sequencing data is sparse. We developed the package o2geosocial to combine variables from routinely collected surveillance data with a simple transmission process model. The model reconstructs transmission trees when full genetic sequences are not available, or uninformative. Our model incorporates the reported age-group, onset date, location and genotype of infected cases to infer probabilistic transmission trees. The package also includes functions to summarise and visualise the inferred cluster size distribution. The results generated by o2geosocial can highlight regions where importations repeatedly caused large outbreaks, which may indicate a higher regional susceptibility to infections. It can also be used to generate the individual number of secondary transmissions, and show the features associated with individuals involved in high transmission events. The package is available for download from the Comprehensive R Archive Network (CRAN) and GitHub.

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40

Robert, Alexis, Sebastian Funk, and Adam J. Kucharski. "o2geosocial: Reconstructing who-infected-whom from routinely collected surveillance data." F1000Research 10 (June 16, 2021): 31. http://dx.doi.org/10.12688/f1000research.28073.2.

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Reconstructing the history of individual transmission events between cases is key to understanding what factors facilitate the spread of an infectious disease. Since conducting extended contact-tracing investigations can be logistically challenging and costly, statistical inference methods have been developed to reconstruct transmission trees from onset dates and genetic sequences. However, these methods are not as effective if the mutation rate of the virus is very slow, or if sequencing data is sparse. We developed the package o2geosocial to combine variables from routinely collected surveillance data with a simple transmission process model. The model reconstructs transmission trees when full genetic sequences are unavailable, or uninformative. Our model incorporates the reported age-group, onset date, location and genotype of infected cases to infer probabilistic transmission trees. The package also includes functions to summarise and visualise the inferred cluster size distribution. The results generated by o2geosocial can highlight regions where importations repeatedly caused large outbreaks, which may indicate a higher regional susceptibility to infections. It can also be used to generate the individual number of secondary transmissions, and show the features associated with individuals involved in high transmission events. The package is available for download from the Comprehensive R Archive Network (CRAN) and GitHub.

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41

MARUYAMA, Takashi, Tatsuya SHIMIZU, Mamoru AKIMOTO, and Kazuki MARUTA. "Data Transmission Using Original Coils in Resonant Wireless Power Transmission." IEICE Transactions on Communications E94-B, no. 11 (2011): 3172–74. http://dx.doi.org/10.1587/transcom.e94.b.3172.

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42

Akin, Sami. "The Interplay Between Data Transmission Power and Transmission Link Utilization." IEEE Communications Letters 19, no. 11 (November 2015): 1953–56. http://dx.doi.org/10.1109/lcomm.2015.2473158.

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43

Ammendola, R., A. Biagioni, O. Frezza, A. Lonardo, F. Lo Cicero, P. S. Paolucci, D. Rossetti, F. Simula, L. Tosoratto, and P. Vicini. "APEnet+ 34 Gbps data transmission system and custom transmission logic." Journal of Instrumentation 8, no. 12 (December 17, 2013): C12022. http://dx.doi.org/10.1088/1748-0221/8/12/c12022.

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44

Hirner, Tomáš, Peter Farkaš, and Srečko Krile. "One Unequal Error Control Method for Telemetric Data Transmission." Journal of Electrical Engineering 62, no. 3 (May 1, 2011): 158–62. http://dx.doi.org/10.2478/v10187-011-0026-y.

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One Unequal Error Control Method for Telemetric Data TransmissionIn wireless sensor networks (WSN) it is necessary to use very simple codes for transmission of information since the nodes in these networks have usually only limited energy available not only for transmission but also for processing. On the other hand, common codes do not usually take into account the fact that in case of telemetric information the weights of individual orders are not equal and errors in different orders cause different deviations from correct value. In this contribution, new very simple codes for transmission of telemetric information on WSN will be presented, which take into account the above-mentioned requirements. Resulting square deviation will be used as a quality evaluation criterion.

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45

Yan, Shufa, Biao Ma, and Changsong Zheng. "Degradation index construction methodology for mechanical transmission based on fusion of multispectral oil data." Industrial Lubrication and Tribology 71, no. 2 (March 11, 2019): 278–83. http://dx.doi.org/10.1108/ilt-04-2018-0154.

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Purpose The purpose of constructing a degradation index (DI) is to better characterize the degradation degree of mechanical transmission compared with relying solely on spectral oil data, which leads to an accurate estimation of the failure time when the transmission no longer fulfills its function. Design/methodology/approach The DI is modeled using a weighted average function with two desirable properties: maximizing the monotonic trend and minimizing the variance of failure threshold between different transmissions. The method includes concentration modification, data selection and data fusion steps that lead to a reasonable mechanical transmission degradation model. The proposed methodology was verified through a case study involving multispectral oil data sampled from several power-shift steering transmissions. Findings The results show that the DI outperforms all spectral oil data. Compared with the existing spectral oil data-based degradation modeling approach for mechanical transmissions, the present methodology provides an accurate RUL prediction. Research limitations/implications There are several important directions for future research: First, more degradation data (i.e. ferrography) that are tailored to the degradation modeling of mechanical transmission need to be involved. Second, more effective degradation data selection methodologies that are applicable for multiple data types need to be developed. Third, kernel methods that can fuse the nonlinear degradation data need to be investigated. Originality/value The novelty of this methodology lies in integrating the multiple degradation data in a unified DI. And the main contribution of this paper is to establish a new direction in degradation modeling and RUL prediction of mechanical transmission.

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Li, Cui-Min, Chun-Ying Li, and Lei Wang. "Reliable data transmission method based on 6LoWPAN for building energy systems." Building Services Engineering Research and Technology 41, no. 5 (November 26, 2019): 623–33. http://dx.doi.org/10.1177/0143624419891521.

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The building energy internet of things is based on radio frequency technology and a wireless sensor network that can collect building energy consumption data in real time. However, with the increasing complexity of wireless sensor network topology, there is a problem of insufficient IP address space relying on IPv4 protocol. In this paper, a design scheme of a building energy system based on 6LoWPAN network is proposed. IPv4/IPv6 address conversion is used to realise the access of IP addresses to each other, so as to monitor building energy consumption information anytime and anywhere. In view of the shortcomings of existing wireless network data transmission methods in low energy consumption and high reliability in building energy monitoring applications, a reliable data transmission method based on multipath routing coding algorithm is proposed. This strategy improves the transmission reliability of the network by increasing the number of redundant packets, and reduces the energy consumption of the network by reducing the number of transmission paths. The simulation results show that the proposed method can effectively improve the success rate of data packet transmission, reduce the standard energy consumption of sensor networks, and provide an effective method for the application of wireless sensor networks in building energy monitoring systems. Practical application: This paper studies how to improve transmission reliability and energy efficiency in cluster-based WSN and proposes a multi-path transmission strategy for selective coding of intermediate cluster head nodes. The strategy improves the transmission reliability of the network by increasing the number of transmissions of redundant packets and reduces the network energy consumption by reducing the number of transmission paths. It has good use value for the actual development and application of the building energy consumption monitoring system.

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Ooki, M. "On a Characteristic of Data Transmission with Priority Processing in Bus Network." Journal of Advances in Computer Networks 3, no. 2 (2015): 87–92. http://dx.doi.org/10.7763/jacn.2015.v3.147.

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Yang, Rui, Ming Deng, Qi Sheng Zhang, and Qi Wang. "Realization of High-Speed Data Transmission in Seismic Data Acquisition." Advanced Materials Research 219-220 (March 2011): 560–64. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.560.

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Data transmission is one of key techniques of acquisition station for seismic data acquisition system. With the development of electronics, computer science and communication science, a good realization method has become available for seismic data transmission. The paper focused on the independent design & development of Manchester encoding module, Manchester decoding module and parallel/serial and serial/parallel conversion module by hardware description language (HDL) with FPGA as main control unit and Manchester code and low-voltage differential signaling as theoretical basis. It can realize data transmission speed of 16Mbps between seismic data acquisition stations. Testing results showed low error rate during data transmission to ensure that seismic data acquisition station can read commands sent by power station and convey seismic data correctly.

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Pang, Songling, Fali Tan, Hailong Zhao, Meng Zhang, Jian Liao, and Yang Peng. "Transmission Attenuation of 110kv Asymmetric Transmission Lines Based on Measured Data." IOP Conference Series: Materials Science and Engineering 486 (July 10, 2019): 012125. http://dx.doi.org/10.1088/1757-899x/486/1/012125.

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Jang, Sung-Il, Seung-Kwon Choi, and Sung-Jin Kim. "Cluster Based Transmission Method for Reliable Multimedia Data Transmission of WMSN." Journal of the Korea Entertainment Industry Association 17, no. 7 (October 31, 2023): 453–64. http://dx.doi.org/10.21184/jkeia.2023.10.17.7.453.

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