ORCID Profile
0000-0002-7914-7296
Current Organisations
Kharkiv National Medical University
,
Jiangsu University
,
National University of Sciences and Technology
,
Харьковский национальный университет им. В. Н. Каразина
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Publications
TrustWalker: An Efficient Trust Assessment in Vehicular Internet of Things (VIoT) with Security Consideration
Publisher: MDPI AG
Date: 16-07-2020
DOI: 10.3390/S20143945
Abstract: The Internet of Things (IoT) is a world of connected networks and modern technology devices, among them vehicular networks considered more challenging due to high speed and network dynamics. Future trends in IoT allow these inter networks to share information. Also, the previous security solutions to vehicular IoT (VIoT) much emphasize on privacy protection and security related issues using public keys infrastructure. However, the primary concern about efficient trust assessment, authorized users malfunctioning, and secure information dissemination in vehicular wireless networks have not been explored. To cope with these challenges, we propose a trust enhanced on-demand routing (TER) scheme, which adopts TrustWalker (TW) algorithm for efficient trust assessment and route search technique in VIoT. TER comprised of novel three-valued subjective logic (3VSL), TW algorithm, and ad hoc on-demand distance vector (AODV) routing protocol. The simulated results validate the accuracy of the proposed scheme in term of throughput, packet drop ratio (PDR), and end to end (E2E) delay. In the simulation, the execution time of the TW algorithm is analyzed and compared with another route search algorithm, i.e., Assess-Trust (AT), by considering real-world online datasets such as Pretty Good Privacy and Advogato. The accuracy and efficiency of the TW algorithm, even with a large number of vehicle users, are also demonstrated through simulations.
Elastic caching solutions for content dissemination services of ip-based internet technologies prospective
Publisher: Springer Science and Business Media LLC
Date: 10-09-2020
Deep Learning (DL) Based Joint Resource Allocation and RRH Association in 5G-Multi-Tier Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Detection of fetal arrhythmias in non-invasive fetal ECG recordings using data-driven entropy profiling
Publisher: IOP Publishing
Date: 28-02-2022
Abstract: Objective. Fetal arrhythmias are a life-threatening disorder occurring in up to 2% of pregnancies. If identified, many fetal arrhythmias can be effectively treated using anti-arrhythmic therapies. In this paper, we present a novel method of detecting fetal arrhythmias in short length non-invasive fetal electrocardiography (NI-FECG) recordings. Approach. Our method consists of extracting a fetal heart rate time series from each NI-FECG recording and computing an entropy profile using a data-driven range of the entropy tolerance parameter r . To validate our approach, we apply our entropy profiling method to a large clinical data set of 318 NI-FECG recordings. Main Results. We demonstrate that our method ( TotalS En ) provides strong performance for classifying arrhythmic fetuses (AUC of 0.83) and outperforms entropy measures such as S En (AUC of 0.68) and FuzzyEn (AUC of 0.72). We also find that NI-FECG recordings incorrectly classified using the investigated entropy measures have significantly lower signal quality, and that excluding recordings of low signal quality (13.5% of recordings) increases the classification performance of TotalS En (AUC of 0.90). Significance. The superior performance of our approach enables automated detection of fetal arrhythmias and warrants further investigation in a prospective clinical trial.
Correction to: Elastic caching solutions for content dissemination services of ip-based internet technologies prospective
Publisher: Springer Science and Business Media LLC
Date: 03-10-2020
Related Organisations
Харьковский Национальный Университет Им. В. Н. Каразина
Location: Ukraine
Related Funding Activities
No related grants have been discovered for Igor Lakhno.