UAV-Assisted Cluster-Based Task Allocation for Mobile Crowdsensing in a Space-Air-Ground-Sea Integrated Network

Mobile crowdsensing (MCS), which is a grassroots sensing paradigm that utilizes the idea of crowdsourcing, has attracted the attention of academics. More and more researchers have devoted themselves to adopting MCS in space-air-ground-sea integrated networks (SAGSINs). Given the dynamics of the environmental conditions in SAGSINs and the uncertainty of the sensing capabilities of mobile people, the quality and coverage of the sensed data change periodically. To address this issue, we propose a novel UAV-assisted cluster-based task allocation (UCTA) algorithm for MCS in SAGSINs in a two-stage process. We first introduce the edge nodes and establish a three-layer hierarchical system with UAV-assistance, called "Platform-Edge Cluster-Participants". Moreover, an edge-aided attribute-based cluster algorithm is designed, aiming at organizing tasks into clusters, which significantly diminishes both the communication overhead and computational complexity while enhancing the efficiency of task allocation. Subsequently, a greedy selection algorithm is proposed to select the final combination that performs the sensing task in each cluster. Extensive simulations are conducted comparing the developed algorithm with the other three benchmark algorithms, and the experimental results unequivocally endorse the superiority of our proposed UCTA algorithm.

Nonlinear Strength Reduction Method of Rock Mass in Slope Stability Evaluation

As the strength parameters of rock mass degrade differently during slope instability, different factors should be considered in the strength reduction method. Previous nonlinear reduction methods were essentially implemented based on the Mohr-Coulomb criterion, which was reported not to reflect the nonlinear performance of rock mass. To address this deficiency, in this study, the Hoek-Brown criterion was combined with a nonlinear reduction technique for slope stability evaluation. Firstly, based on the classical definition of safety factors, the relationships that should be satisfied by each parameter of the critical slope were derived. The critical curve of the slope regarding the Hoek-Brown constant m_b and the uniaxial compressive strength of rock mass σ_cmass was then obtained. On the assumption that the slope parameter deterioration conforms to the shortest path theory, the reduction ratio of σ_cmass to m_b was determined. The more objective k-means algorithm was employed to automatically search the potential sliding surface, on which the slope safety factor was calculated as the ratio of sliding resistance to sliding force. Finally, the slopes in published literature were adopted for verification, and the calculated safety factors were compared with those by other methods, which showed better efficacy.

Increase in heterogeneity of biceps brachii activation during isometric submaximal fatiguing contractions: a multichannel surface EMG study

The effects of fatigue emerge from the beginning of sustained submaximal contractions, as shown by an increase in the amplitude of the surface electromyogram (EMG). The increase in EMG amplitude is attributed to an augmentation of the excitatory drive to the motor neuron pool that, more importantly than increasing discharge rates, recruits additional motor units for the contraction. The aim of this study was to determine whether the spatiotemporal distribution of biceps brachii (BB) activity becomes more or less heterogeneous during a fatiguing isometric contraction sustained at a submaximal target force. Multiple electrodes were attached over the entire BB muscle, and principal component analysis (PCA) was used to extract the representative information from multiple monopolar EMG channels. The development of heterogeneity during the fatiguing contraction was quantified by applying a cluster algorithm on the PCA-processed EMG amplitudes. As shown previously, the overall EMG amplitude increased during the sustained contraction, whereas there was no change in coactivation of triceps brachii. However, EMG amplitude did not increase in all channels and even decreased in some. The change in spatial distribution of muscle activity varied across subjects. As found in other studies, the spatial distribution of EMG activity changed during the sustained contraction, but the grouping and size of the clusters did not change. This study showed for the first time that muscle activation became more heterogeneous during a sustained contraction, presumably due to a decrease in the strength of common inputs with the recruitment of additional motor units.

Super paramagnetic clustering of DNA sequences

An unsupervised clustering of 4541 DNA sequences containing active promoter regions from vertebrate and arthropod classes (including their viral genes) was performed. All necessary information was solely gathered a priori from the DNA sequences by measuring frequencies of tri-nucleotides and tetra-nucleotides. We employed Super Paramagnetic Clustering, a novel clustering algorithm based on physical properties of an inhomogeneous granular ferromagnet. This method utilizes Swendsen-Wang cluster Monte Carlo simulations to distinguish clusters by measuring pairs of correlation functions from different resolutions. We identified two strongly separated clusters of human viral genes corresponding to the Epstein-Barr virus and the Herpes Simplex virus type 1. In addition, vertebrate and arthropod sequences were successfully separated into two different classes with merely 9.25% of arthropod sequences being misclassified. From a functional perspective, these sequences have high gene function correlations with sequences from the vertebrate cluster. By tuning a clustering parameter, Super Paramagnetic Clustering was able to classify vertebrate class further into two major clusters, from where a large number of housekeeping genes and tissue-specific genes were found respectively. The indications came from observation of gene expression function and consensus transcription factors which were found grouped together in specific positions of the DNA sequences.