2026 Vol.51 No.22026 Vol.51 No.12026 Vol.50 No.42026 Vol.50 No.32026 Vol.50 No.22026 Vol.50 No.12025 Vol.49 No.42025 Vol.49 No.32025 Vol.49 No.22025 Vol.49 No.12025 Vol.48 No.42025 Vol.48 No.32025 Vol.48 No.22025 Vol.48 No.12025 Vol.47 No.42025 Vol.47 No.32025 Vol.47 No.22025 Vol.47 No.1 Free Access2024 Vol.46 No.42024 Vol.46 No.32024 Vol.46 No.22024 Vol.46 No.12024 Vol.45 No.42024 Vol.45 No.32024 Vol.45 No.22024 Vol.45 No.12024 Vol.44 No.42024 Vol.44 No.32024 Vol.44 No.22024 Vol.44 No.12023 Vol.43 No.42023 Vol.43 No.32023 Vol.43 No.22023 Vol.43 No.12023 Vol.42 No.42023 Vol.42 No.32023 Vol.42 No.22023 Vol.42 No.12023 Vol.41 No.42023 Vol.41 No.32023 Vol.41 No.22023 Vol.41 No.12022 Vol.40 No.42022 Vol.40 No.32022 Vol.40 No.22022 Vol.40 No.12022 Vol.39 No.42022 Vol.39 No.32022 Vol.39 No.22022 Vol.39 No.12022 Vol.38 No.42022 Vol.38 No.32022 Vol.38 No.22022 Vol.38 No.12021 Vol.37 No.42021 Vol.37 No.32021 Vol.37 No.22021 Vol.37 No.12021 Vol.36 No.42021 Vol.36 No.32021 Vol.36 No.22021 Vol.36 No.12021 Vol.35 No.42021 Vol.35 No.32021 Vol.35 No.22021 Vol.35 No.12020 Vol.34 No.42020 Vol.34 No.32020 Vol.34 No.22020 Vol.34 No.12020 Vol.33 No.42020 Vol.33 No.32020 Vol.33 No.22020 Vol.33 No.12020 Vol.32 No.42020 Vol.32 No.32020 Vol.32 No.22020 Vol.32 No.12019 Vol.31 No.42019 Vol.31 No.32019 Vol.31 No.22019 Vol.31 No.12019 Vol.30 No.42019 Vol.30 No.32019 Vol.30 No.22019 Vol.30 No.12019 Vol.29 No.42019 Vol.29 No.32019 Vol.29 No.22019 Vol.29 No.12018 Vol.28 No.42018 Vol.28 No.32018 Vol.28 No.22018 Vol.28 No.12018 Vol.27 No.42018 Vol.27 No.32018 Vol.27 No.22018 Vol.27 No.12018 Vol.26 No.42018 Vol.26 No.32018 Vol.26 No.22018 Vol.26 No.12017 Vol.25 No.42017 Vol.25 No.32017 Vol.25 No.22017 Vol.25 No.12017 Vol.24 No.42017 Vol.24 No.32017 Vol.24 No.22017 Vol.24 No.12017 Vol.23 No.42017 Vol.23 No.32017 Vol.23 No.22017 Vol.23 No.12016 Vol.22 No.42016 Vol.22 No.32016 Vol.22 No.22016 Vol.22 No.12016 Vol.21 No.42016 Vol.21 No.32016 Vol.21 No.22016 Vol.21 No.12016 Vol.20 No.42016 Vol.20 No.32016 Vol.20 No.22016 Vol.20 No.12015 Vol.19 No.3/42015 Vol.19 No.22015 Vol.19 No.12015 Vol.18 No.3/42015 Vol.18 No.1/22015 Vol.17 No.42015 Vol.17 No.32015 Vol.17 No.22015 Vol.17 No.12014 Vol.16 No.42014 Vol.16 No.32014 Vol.16 No.22014 Vol.16 No.12014 Vol.15 No.42014 Vol.15 No.32014 Vol.15 No.22014 Vol.15 No.12013 Vol.14 No.42013 Vol.14 No.32013 Vol.14 No.22013 Vol.14 No.12013 Vol.13 No.42013 Vol.13 No.32013 Vol.13 No.22013 Vol.13 No.12012 Vol.12 No.42012 Vol.12 No.32012 Vol.12 No.22012 Vol.12 No.12012 Vol.11 No.42012 Vol.11 No.32012 Vol.11 No.22012 Vol.11 No.12011 Vol.10 No.42011 Vol.10 No.32011 Vol.10 No.1/22011 Vol.9 No.3/42011 Vol.9 No.22011 Vol.9 No.12010 Vol.8 No.3/42010 Vol.8 No.22010 Vol.8 No.12010 Vol.7 No.42010 Vol.7 No.32010 Vol.7 No.1/22009 Vol.6 No.3/42009 Vol.6 No.22009 Vol.6 No.12009 Vol.5 No.42009 Vol.5 No.32009 Vol.5 No.22009 Vol.5 No.12008 Vol.4 No.42008 Vol.4 No.32008 Vol.4 No.1/22008 Vol.3 No.42008 Vol.3 No.32008 Vol.3 No.22008 Vol.3 No.12007 Vol.2 No.5/62007 Vol.2 No.3/42007 Vol.2 No.1/22006 Vol.1 No.3/42006 Vol.1 No.1/2

International Journal of Sensor Networks (IJSNet)

International Journal of Sensor Networks

2024 Vol.44 No.4


Pages Title and author(s)
193-202Modified UKF for accurate indoor UWB multi-target tracking in the context of SαS NLOS model
Zohra Slimane; Ibrahim Yassine Nouali; Abdelhafid Abdelmalek
DOI: 10.1504/IJSNET.2024.138515
203-213Enhancing VoIP quality in mobile networks through optimised MOS prediction and base station clustering with SDN
Najib Mouhassine; Mohamed Moughit
DOI: 10.1504/IJSNET.2024.138517
214-225Attribute-based proxy signature scheme with dynamic strong forward security
Qingshui Xue; Zixuan Lu; Tianhao Zhang
DOI: 10.1504/IJSNET.2024.138518
226-236Fault diagnostics on railway switches and crossings using a bat-optimised sequence-to-sequence neural model
Xiaoyun Deng
DOI: 10.1504/IJSNET.2024.138516
237-248Remote sensing enabled sustainable tomato plant health and pest surveillance using machine learning techniques
Weijia Yu; Si Li
DOI: 10.1504/IJSNET.2024.138509
249-257A classification and prediction model with the sparrow search-probabilistic neural network algorithm for transformer fault diagnosis
Ling Hu; Lanlan Yin; Feng Mo; Zhixun Liang; Zhong Ruan; Yuting Wang
DOI: 10.1504/IJSNET.2024.138499

 

Return to top