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- Tran, Quoc Cuong, et al.
(författare)
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Novel Ensemble Landslide Predictive Models Based on the Hyperpipes Algorithm : A Case Study in the Nam Dam Commune, Vietnam
- 2020
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Ingår i: Applied Sciences. - Switzerland : MDPI. - 2076-3417. ; 10:11
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Tidskriftsartikel (refereegranskat)abstract
- Development of landslide predictive models with strong prediction power has become a major focus of many researchers. This study describes the first application of the Hyperpipes (HP) algorithm for the development of the five novel ensemble models that combine the HP algorithm and the AdaBoost (AB), Bagging (B), Dagging, Decorate, and Real AdaBoost (RAB) ensemble techniques for mapping the spatial variability of landslide susceptibility in the Nam Dan commune, Ha Giang province, Vietnam. Information on 76 historical landslides and ten geo-environmental factors (slope degree, slope aspect, elevation, topographic wetness index, curvature, weathering crust, geology, river density, fault density, and distance from roads) were used for the construction of the training and validation datasets that are the prerequisites for building and testing the proposed models. Using different performance metrics (i.e., the area under the receiver operating characteristic curve (AUC), negative predictive value, positive predictive value, accuracy, sensitivity, specificity, root mean square error, and Kappa), we verified the proficiency of all five ensemble learning techniques in increasing the fitness and predictive powers of the base HP model. Based on the AUC values derived from the models, the ensemble ABHP model that yielded an AUC value of 0.922 was identified as the most efficient model for mapping the landslide susceptibility in the Nam Dan commune, followed by RABHP (AUC = 0.919), BHP (AUC = 0.909), Dagging-HP (AUC = 0.897), Decorate-HP (AUC = 0.865), and the single HP model (AUC = 0.856), respectively. The novel ensemble models proposed for the Nam Dan commune and the resultant susceptibility maps can aid land-use planners in the development of efficient mitigation strategies in response to destructive landslides.
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| 2. |
- Vo, Van Nhan, et al.
(författare)
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Performance Analysis of an Energy-Harvesting IoT System Using a UAV Friendly Jammer and NOMA Under Cooperative Attack
- 2020
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Ingår i: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 8, s. 221986-222000
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we consider the information leakage and outage probabilities of a multiple-input single-output (MISO) energy-harvesting (EH) Internet of Things (IoT) system in which a multiantenna ground base station (GBS) transmits messages to legitimate IoT destinations (LIDs) with the help of IoT relays (IRs) using non-orthogonal multiple access (NOMA) in the presence of a malicious jammer (MJ) and eavesdroppers (EAVs). The communication protocol is separated into two phases. In the EH phase, the IRs harvest energy from a power beacon (PB). In the information transmission (IT) phase, the communication process is further divided into two subphases: 1) The GBS broadcasts signals to the IRs using NOMA. Simultaneously, the MJ sends interfering signals to attack the IRs while the EAVs steal the confidential signals from the GBS, in a process called a cooperative attack. On the other hand, to protect the legitimate communication, an unmanned aerial vehicle (UAV) is used as a friendly jammer to defend against the EAVs. 2) A selected IR employs the time-switching-based relaying (TSR) technique to forward the received signal to the LIDs using NOMA. Similar to the first subphase, the LIDs are subjected to a cooperative attack, and the UAV attacks the EAVs in return. The secrecy performance of this communication protocol is characterized by deriving expressions for the information leakage probabilities (ILPs) for the LIDs' signals. A UAV altitude optimization algorithm is also proposed to achieve the best possible secrecy performance. Furthermore, we evaluate the system performance by deriving closed-form expressions for the outage probabilities (OPs). Accordingly, an algorithm is proposed to guarantee both the secrecy and system performance (in terms of the ILPs and OPs). Monte Carlo simulations are presented to verify our analytical results.
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