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Ağ teknolojileri ile ilgili makalelerin bibliyografik yöntemle incelenmesi

Year 2021, Volume: 7 Issue: 3, 141 - 158, 28.07.2021
https://doi.org/10.51948/auad.934157

Abstract

Ağ Teknolojisi, dijital kaynakları bir bilgisayar ağı üzerinden yönetmek ve sunmak için veri sistemlerinin kullanılmasını içerir. Günümüzde kullanıma sunulmuş bir çok teknolojik kavram literatürde bir ağ tabanı üzerinden kendini tanımlamaktadır. Sosyal ağlar, e-devlet uygulamaları, konum bilgileri, online eğitim vb. bir çok hayat dinamiği ağ yapısına dayanmakta olup, bu da toplum için ağ teknolojilerinin ne kadar önemli olduğunu göstermektedir. Ayrıca ağ teknolojilerinin (5G, genişbant, nesnelerin i̇nterneti, blok zincir teknolojisi), Yükseköğretim Kurulu tarafından fen ve mühendislik bilimleri alanında öncelikli alan ilan edilmiş olması konunun önemini bir kez daha ortaya çıkarmıştır. Bu araştırmanın amacı ise ağ teknolojileri ile ilgili makalelerin bibliyografik yöntemle incelenmesidir. Araştırmada kullanılan veriler ScienceDirect veritabanından elde edilmiştir. Toplamda 13.032 makaleden elde edilen veriler yıl, makale tipi, dergi adı, konu ölçütlerine göre analiz edilerek nitel verilerle açıklanmıştır. İstatistiki veriler için frekans-yüzde kullanımı tercih edilmiştir. Araştırmanın sonucunda, çalışmaların büyük bir kısmının 2020 yılında yayınlandığı, çalışmalarda araştırma makalelerinin ön plana çıktığı, araştırmaların en çok; isminde “bilgisayar” kelimesi bulunan 6 dergide yer aldığı, konu olarak da bilgisayar ve mühendislik bilimlerinin tercih edildiği görülmüştür.

References

  • Alian, M., Abulila, A. H. M. O., Jindal, L., Kim, D., & Kim, N. S. (2017, February 1). NCAP: Network-Driven, Packet Context-Aware Power Management for Client-Server Architecture. IEEE Xplore. https://doi.org/10.1109/HPCA.2017.57
  • Apple, M. W. (1991). The New Technology: Computers in the Schools, 8(1-3), 59–82. https://doi.org/10.1300/j025v08n01_07
  • Askari, L., Hmaity, A., Musumeci, F., & Tornatore, M. (2018). Virtual-network-function placement for dynamic service chaining in metro-area networks. IEEE, 136–141.
  • Ayoub, O., Musumeci, F., Tornatore, M., & Pattavina, A. (2018). Energy-efficient video-on-demand content caching and distribution in metro area networks. IEEE Transactions on Green Communications and Networking, 3, 159–169.
  • Chen, M., Challita, U., Saad, W., Yin, C., & Debbah, M. (2019). Artificial neural networks-based machine learning for wireless networks: A tutorial. IEEE Communications Surveys & Tutorials, 21, 3039–3071.
  • Choi, J., Shin, K., Jung, J., Bae, H.-J., Kim, D. H., Byeon, J.-S., & Kim, N. (2020). Convolutional neural network technology in endoscopic imaging: artificial intelligence for endoscopy. Clinical Endoscopy, 53, 117.
  • Chui, H. T., Jackson, J. L., Liu, J., & Hill, C. E. (2012). Annotated bibliography of studies using consensual qualitative research. American Psychological Association.
  • Demetillo, A. T., Japitana, M. V., & Taboada, E. B. (2019). A system for monitoring water quality in a large aquatic area using wireless sensor network technology. Sustainable Environment Research, 29, 1–9.
  • Desai, A., Upadhyaya, T., & Palandoken, M. (2018). Dual band slotted transparent resonator for wireless local area network applications. Microwave and Optical Technology Letters, 60, 3034–3039.
  • Dimitris Uzunidis, Evangelos Kosmatos, Matrakidis, C., Alexandros Stavdas, & Lord, A. (2019). DuFiNet: Architectural considerations and physical layer studies of an agile and cost-effective metropolitan area network. J. Lightwave Technol., 37, 808–814. http://jlt.osa.org/abstract.cfm?URI=jlt-37-3-808
  • Dulock, H. L. (1993). Research design: Descriptive research. Journal of Pediatric Oncology Nursing, 10, 154–157. Effendy, D. A., Kusrini, K., & Sudarmawan, S. (2017). Classification of intrusion detection system (IDS) based on computer network. IEEE, 90–94.
  • Fletcher, C. (2017). Research guides: PS 4990: Election reform: Citing your sources.
  • Fong, D. Y. (2017). Wireless sensor networks. In Internet of things and data analytics handbook (pp. 197–213). Wiley Online Library.
  • Georgiou, O., & Raza, U. (2017). Low power wide area network analysis: Can LoRa scale? IEEE Wireless Communications Letters, 6, 162–165.
  • Goertzen, M. (2019). Multidisciplinary databases outperform specialized and comprehensive databases for agricultural literature coverage. Evidence Based Library and Information Practice, 14, 140–142.
  • Green, B. P., & Choi, J. H. (1997). Assessing the risk of management fraud through neural network technology. Auditing, 16, 14–28.
  • Hua, J., & Shunwuritu, N. (2021). Research on term extraction technology in computer field based on wireless network technology. Microprocessors and Microsystems, 80, 103336.
  • Juszczuk, D., Tarnawski, J., Karla, T., & Duzinkiewicz, K. (2017). Real-time basic principles nuclear reactor simulator based on client-server network architecture with WebBrowser as user interface. Springer, 344–353.
  • Kaback, H. (1970). Transport. Annual Review of Biochemistry, 39, 561–598.
  • Kline, S. J. (1985). What is technology? Bulletin of Science, Technology & Society, 5, 215–218.
  • Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6, 239–242.
  • Luming Tan, & Neng-Ming Wang. (2010). Future internet: The internet of things. 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), 5, V5-376V5-380.
  • Mao, B., Fadlullah, Zubair Md, Tang, F., Kato, N., Akashi, O., Inoue, T., & Mizutani, K. (2017). Routing or computing? The paradigm shift towards intelligent computer network packet transmission based on deep learning. IEEE Transactions on Computers, 66, 1946–1960.
  • Mathur, R., & Dwari, S. (2019). Compact planar reconfigurable UWB-MIMO antenna with on-demand worldwide interoperability for microwave access/wireless local area network rejection. IET Microwaves, Antennas & Propagation, 13, 1684–1689.
  • Maximov, R. V., Sokolovsky, Sergey P, & Gavrilov, Alexey L. (2017). Hiding computer network proactive security tools unmasking features. 2081, 88–92.
  • Mills, D. L. (2017). Computer network time synchronization: the network time protocol on earth and in space. CRC press.
  • Ni, Y., Liang, J., Shi, X., & Ban, D. (2019). Research on key technology in 5G mobile communication network. IEEE, 199–201.
  • Noreen, U., Bounceur, A., & Clavier, L. (2017). A study of LoRa low power and wide area network technology. IEEE, 1–6.
  • Pain, H. (2009). Innovation in qualitative research methodology: annotated bibliography. National Centre for Research Methods.
  • Pathak, V., Jena, B., & Kalra, S. (2013). Qualitative research. Perspectives in Clinical Research, 4, Article 3.
  • Peyré, G., & Cuturi, M. (2019). Computational optimal transport: With applications to data science. Foundations and Trends® in Machine Learning, 11, 355–607.
  • Prensky, M. (2008). The role of technology. Educational Technology, 48, 1–3.
  • Qi, J., Lai, C., Xu, B., Sun, Y., & Leung, K.-S. (2018). Collaborative energy management optimization toward a green energy local area network. IEEE Transactions on Industrial Informatics, 14, 5410–5418.
  • Rahadjeng, Indra Riyana, & Ritapuspitasari, R. (2018). Analisis jaringan local area network (lan) pada PT. Mustika ratu tbk jakarta timur. Prosisko: Jurnal Pengembangan Riset Dan Observasi Sistem Komputer, 5, Article 1.
  • Reingen, P. H. (1987). A word-of-mouth network. In ACR North American Advances.
  • Robert, K. W., Krishnan, Gopal V, Pevzner, M., Shefchik, L. B., & Velury, Uma K. (2013). Audit quality: Insights from the academic literature. Auditing: A Journal of Practice & Theory, 32, 385–421.
  • Robinson, R. S., & Driscoll, M. P. (1993). Qualitative research methods workshops: An introduction, definitions. Readings on qualitative research: An annotated bibliography. ERIC.
  • Sariyannis, M. (2018). Bibliography. Brill.
  • Sharma, A., Verma, R., & Nahar, O. (2019). Managing Security in Client-Server Network Infrastructure. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3356533
  • Silvers, A. (2004). Pedagogy and Polemics: Are Art Educators Qualified to Teach Visual Culture? Arts Education Policy Review, 106(1), 19–24. https://doi.org/10.3200/aepr.106.1.19-24
  • Sunny, S., Patrick, L., & Rob, L. (2019). Impact of cultural values on technology acceptance and technology readiness. International Journal of Hospitality Management, 77, 89–96. https://doi.org/10.1016/j.ijhm.2018.06.017
  • Thummaluru, S. R., Kumar, R., & Chaudhary, R. K. (2019). Isolation and frequency reconfigurable compact MIMO antenna for wireless local area network applications. IET Microwaves, Antennas & Propagation, 13(4), 519–525. https://doi.org/10.1049/iet-map.2018.5895
  • van Gerven, M., & Bohte, S. (2017). Editorial: Artificial Neural Networks as Models of Neural Information Processing. Frontiers in Computational Neuroscience, 11. https://doi.org/10.3389/fncom.2017.00114
  • Wang, Q., & Lu, P. (2019). Research on Application of Artificial Intelligence in Computer Network Technology. International Journal of Pattern Recognition and Artificial Intelligence, 33(05), 1959015. https://doi.org/10.1142/s0218001419590158
  • Wang, R., Wu, J., Qian, Z., Lin, Z., & He, X. (2017). A Graph Theory Based Energy Routing Algorithm in Energy Local Area Network. IEEE Transactions on Industrial Informatics, 13(6), 3275–3285. https://doi.org/10.1109/tii.2017.2713040
  • Yamamoto, B., Wong, A., Agcanas, P. J., Jones, K., Gaspar, D., Andrade, R., & Trimble, A. Z. (2019). Received Signal Strength Indication (RSSI) of 2.4 GHz and 5 GHz Wireless Local Area Network Systems Projected over Land and Sea for Near-Shore Maritime Robot Operations. Journal of Marine Science and Engineering, 7(9), 290. https://doi.org/10.3390/jmse7090290
  • Zador, A. M. (2019). A critique of pure learning and what artificial neural networks can learn from animal brains. Nature Communications, 10(1). https://doi.org/10.1038/s41467-019-11786-6
  • Zhang, Q., Yu, H., Barbiero, M., Wang, B., & Gu, M. (2019). Artificial neural networks enabled by nanophotonics. Light: Science & Applications, 8(1). https://doi.org/10.1038/s41377-019-0151-0

Bibliographic review of articles related to network technologies

Year 2021, Volume: 7 Issue: 3, 141 - 158, 28.07.2021
https://doi.org/10.51948/auad.934157

Abstract

Networking Technology involves the use of data systems to manage and deliver digital resources over a computer network.Today information retrieval through a network database, and many technological concepts are available in the literature through a network database.Social networks, e-government applications, location information, online education, etc. many life dynamics are based on network structure and all of them show how important network technologies are for society. In addition, network technologies (5G, broadband, internet of things, block chain technology) have been declared priority area in the field of science and engineering sciences by the Council of Higher Education has once again revealed the importance of the subject. The aim of this research is to examine articles on network technologies by bibliographic method. The data used in the research were obtained from the Science Direct database. In total, the data obtained from 13,032 articles are analyzed according to year, article type, journal name, subject criteria and explained with qualitative data. Frequency-percentage use was preferred for statistical data.As a result of the research, it is clear that most of the studies were published in 2020,research articles come to the fore in the studies, most of the studies; appeared in 6 journals with the word "computer" in its name, computer and engineering sciences are preferred as a subject.

References

  • Alian, M., Abulila, A. H. M. O., Jindal, L., Kim, D., & Kim, N. S. (2017, February 1). NCAP: Network-Driven, Packet Context-Aware Power Management for Client-Server Architecture. IEEE Xplore. https://doi.org/10.1109/HPCA.2017.57
  • Apple, M. W. (1991). The New Technology: Computers in the Schools, 8(1-3), 59–82. https://doi.org/10.1300/j025v08n01_07
  • Askari, L., Hmaity, A., Musumeci, F., & Tornatore, M. (2018). Virtual-network-function placement for dynamic service chaining in metro-area networks. IEEE, 136–141.
  • Ayoub, O., Musumeci, F., Tornatore, M., & Pattavina, A. (2018). Energy-efficient video-on-demand content caching and distribution in metro area networks. IEEE Transactions on Green Communications and Networking, 3, 159–169.
  • Chen, M., Challita, U., Saad, W., Yin, C., & Debbah, M. (2019). Artificial neural networks-based machine learning for wireless networks: A tutorial. IEEE Communications Surveys & Tutorials, 21, 3039–3071.
  • Choi, J., Shin, K., Jung, J., Bae, H.-J., Kim, D. H., Byeon, J.-S., & Kim, N. (2020). Convolutional neural network technology in endoscopic imaging: artificial intelligence for endoscopy. Clinical Endoscopy, 53, 117.
  • Chui, H. T., Jackson, J. L., Liu, J., & Hill, C. E. (2012). Annotated bibliography of studies using consensual qualitative research. American Psychological Association.
  • Demetillo, A. T., Japitana, M. V., & Taboada, E. B. (2019). A system for monitoring water quality in a large aquatic area using wireless sensor network technology. Sustainable Environment Research, 29, 1–9.
  • Desai, A., Upadhyaya, T., & Palandoken, M. (2018). Dual band slotted transparent resonator for wireless local area network applications. Microwave and Optical Technology Letters, 60, 3034–3039.
  • Dimitris Uzunidis, Evangelos Kosmatos, Matrakidis, C., Alexandros Stavdas, & Lord, A. (2019). DuFiNet: Architectural considerations and physical layer studies of an agile and cost-effective metropolitan area network. J. Lightwave Technol., 37, 808–814. http://jlt.osa.org/abstract.cfm?URI=jlt-37-3-808
  • Dulock, H. L. (1993). Research design: Descriptive research. Journal of Pediatric Oncology Nursing, 10, 154–157. Effendy, D. A., Kusrini, K., & Sudarmawan, S. (2017). Classification of intrusion detection system (IDS) based on computer network. IEEE, 90–94.
  • Fletcher, C. (2017). Research guides: PS 4990: Election reform: Citing your sources.
  • Fong, D. Y. (2017). Wireless sensor networks. In Internet of things and data analytics handbook (pp. 197–213). Wiley Online Library.
  • Georgiou, O., & Raza, U. (2017). Low power wide area network analysis: Can LoRa scale? IEEE Wireless Communications Letters, 6, 162–165.
  • Goertzen, M. (2019). Multidisciplinary databases outperform specialized and comprehensive databases for agricultural literature coverage. Evidence Based Library and Information Practice, 14, 140–142.
  • Green, B. P., & Choi, J. H. (1997). Assessing the risk of management fraud through neural network technology. Auditing, 16, 14–28.
  • Hua, J., & Shunwuritu, N. (2021). Research on term extraction technology in computer field based on wireless network technology. Microprocessors and Microsystems, 80, 103336.
  • Juszczuk, D., Tarnawski, J., Karla, T., & Duzinkiewicz, K. (2017). Real-time basic principles nuclear reactor simulator based on client-server network architecture with WebBrowser as user interface. Springer, 344–353.
  • Kaback, H. (1970). Transport. Annual Review of Biochemistry, 39, 561–598.
  • Kline, S. J. (1985). What is technology? Bulletin of Science, Technology & Society, 5, 215–218.
  • Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6, 239–242.
  • Luming Tan, & Neng-Ming Wang. (2010). Future internet: The internet of things. 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), 5, V5-376V5-380.
  • Mao, B., Fadlullah, Zubair Md, Tang, F., Kato, N., Akashi, O., Inoue, T., & Mizutani, K. (2017). Routing or computing? The paradigm shift towards intelligent computer network packet transmission based on deep learning. IEEE Transactions on Computers, 66, 1946–1960.
  • Mathur, R., & Dwari, S. (2019). Compact planar reconfigurable UWB-MIMO antenna with on-demand worldwide interoperability for microwave access/wireless local area network rejection. IET Microwaves, Antennas & Propagation, 13, 1684–1689.
  • Maximov, R. V., Sokolovsky, Sergey P, & Gavrilov, Alexey L. (2017). Hiding computer network proactive security tools unmasking features. 2081, 88–92.
  • Mills, D. L. (2017). Computer network time synchronization: the network time protocol on earth and in space. CRC press.
  • Ni, Y., Liang, J., Shi, X., & Ban, D. (2019). Research on key technology in 5G mobile communication network. IEEE, 199–201.
  • Noreen, U., Bounceur, A., & Clavier, L. (2017). A study of LoRa low power and wide area network technology. IEEE, 1–6.
  • Pain, H. (2009). Innovation in qualitative research methodology: annotated bibliography. National Centre for Research Methods.
  • Pathak, V., Jena, B., & Kalra, S. (2013). Qualitative research. Perspectives in Clinical Research, 4, Article 3.
  • Peyré, G., & Cuturi, M. (2019). Computational optimal transport: With applications to data science. Foundations and Trends® in Machine Learning, 11, 355–607.
  • Prensky, M. (2008). The role of technology. Educational Technology, 48, 1–3.
  • Qi, J., Lai, C., Xu, B., Sun, Y., & Leung, K.-S. (2018). Collaborative energy management optimization toward a green energy local area network. IEEE Transactions on Industrial Informatics, 14, 5410–5418.
  • Rahadjeng, Indra Riyana, & Ritapuspitasari, R. (2018). Analisis jaringan local area network (lan) pada PT. Mustika ratu tbk jakarta timur. Prosisko: Jurnal Pengembangan Riset Dan Observasi Sistem Komputer, 5, Article 1.
  • Reingen, P. H. (1987). A word-of-mouth network. In ACR North American Advances.
  • Robert, K. W., Krishnan, Gopal V, Pevzner, M., Shefchik, L. B., & Velury, Uma K. (2013). Audit quality: Insights from the academic literature. Auditing: A Journal of Practice & Theory, 32, 385–421.
  • Robinson, R. S., & Driscoll, M. P. (1993). Qualitative research methods workshops: An introduction, definitions. Readings on qualitative research: An annotated bibliography. ERIC.
  • Sariyannis, M. (2018). Bibliography. Brill.
  • Sharma, A., Verma, R., & Nahar, O. (2019). Managing Security in Client-Server Network Infrastructure. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3356533
  • Silvers, A. (2004). Pedagogy and Polemics: Are Art Educators Qualified to Teach Visual Culture? Arts Education Policy Review, 106(1), 19–24. https://doi.org/10.3200/aepr.106.1.19-24
  • Sunny, S., Patrick, L., & Rob, L. (2019). Impact of cultural values on technology acceptance and technology readiness. International Journal of Hospitality Management, 77, 89–96. https://doi.org/10.1016/j.ijhm.2018.06.017
  • Thummaluru, S. R., Kumar, R., & Chaudhary, R. K. (2019). Isolation and frequency reconfigurable compact MIMO antenna for wireless local area network applications. IET Microwaves, Antennas & Propagation, 13(4), 519–525. https://doi.org/10.1049/iet-map.2018.5895
  • van Gerven, M., & Bohte, S. (2017). Editorial: Artificial Neural Networks as Models of Neural Information Processing. Frontiers in Computational Neuroscience, 11. https://doi.org/10.3389/fncom.2017.00114
  • Wang, Q., & Lu, P. (2019). Research on Application of Artificial Intelligence in Computer Network Technology. International Journal of Pattern Recognition and Artificial Intelligence, 33(05), 1959015. https://doi.org/10.1142/s0218001419590158
  • Wang, R., Wu, J., Qian, Z., Lin, Z., & He, X. (2017). A Graph Theory Based Energy Routing Algorithm in Energy Local Area Network. IEEE Transactions on Industrial Informatics, 13(6), 3275–3285. https://doi.org/10.1109/tii.2017.2713040
  • Yamamoto, B., Wong, A., Agcanas, P. J., Jones, K., Gaspar, D., Andrade, R., & Trimble, A. Z. (2019). Received Signal Strength Indication (RSSI) of 2.4 GHz and 5 GHz Wireless Local Area Network Systems Projected over Land and Sea for Near-Shore Maritime Robot Operations. Journal of Marine Science and Engineering, 7(9), 290. https://doi.org/10.3390/jmse7090290
  • Zador, A. M. (2019). A critique of pure learning and what artificial neural networks can learn from animal brains. Nature Communications, 10(1). https://doi.org/10.1038/s41467-019-11786-6
  • Zhang, Q., Yu, H., Barbiero, M., Wang, B., & Gu, M. (2019). Artificial neural networks enabled by nanophotonics. Light: Science & Applications, 8(1). https://doi.org/10.1038/s41377-019-0151-0
There are 48 citations in total.

Details

Primary Language Turkish
Subjects Other Fields of Education
Journal Section Articles
Authors

Ahmet Raşit Petekci 0000-0003-4355-6845

Publication Date July 28, 2021
Published in Issue Year 2021 Volume: 7 Issue: 3

Cite

APA Petekci, A. R. (2021). Ağ teknolojileri ile ilgili makalelerin bibliyografik yöntemle incelenmesi. Açıköğretim Uygulamaları Ve Araştırmaları Dergisi, 7(3), 141-158. https://doi.org/10.51948/auad.934157