Adaptive Block-Based Compressed Video Sensing Based on Saliency Detection and Side Information

The setting of the measurement number for each block is very important for a block-based compressed sensing system. However, in practical applications, we only have the initial measurement results of the original signal on the sampling side instead of the original signal itself, therefore, we cannot directly allocate the appropriate measurement number for each block without the sparsity of the original signal. To solve this problem, we propose an adaptive block-based compressed video sensing scheme based on saliency detection and side information. According to the Johnson–Lindenstrauss lemma, we can use the initial measurement results to perform saliency detection and then obtain the saliency value for each block. Meanwhile, a side information frame which is an estimate of the current frame is generated on the reconstruction side by the proposed probability fusion model, and the significant coefficient proportion of each block is estimated through the side information frame. Both the saliency value and significant coefficient proportion can reflect the sparsity of the block. Finally, these two estimates of block sparsity are fused, so that we can simultaneously use intra-frame and inter-frame correlation for block sparsity estimation. Then the measurement number of each block can be allocated according to the fusion sparsity. Besides, we propose a global recovery model based on weighting, which can reduce the block effect of reconstructed frames. The experimental results show that, compared with existing schemes, the proposed scheme can achieve a significant improvement in peak signal-to-noise ratio (PSNR) at the same sampling rate.

Complete mtgenome sequences of Anopheles peditaeniatus and An. nitidus and phylogenetic relationships of the genus Anopheles based on mtgenome sequences (Diptera: Culicidae: Anophelinae)

Background: Despite the medical importance of the genus Anopheles in the transmission of malaria and other human diseases, its phylogenetic relationships are not unsettled and the characteristics of mitochondrial genome (mtgenome) are not well understood.Methods: The present study sequenced and analyzed the complete mtgenomes of An. peditaeniatus and An. nitidus, and investigated the characteristics and phylogenetic relationships of 76 complete mtgenome sequences in the genus Anopheles using Illumina sequencing and bioinformatics techniques.Results: The complete mtgenomes of An. peditaeniatus and An. nitidus are 15416 and 15418 bp long, respectively, and include 13 PCGs, 22 tRNAs, two tRNAs and one control region (CR). These 76 mtgenomes are similar as earlier reports in insects in general characteristics, and however the trnR and trnA have a reversal arrangement to form “trnR-trnA” as reported in other mosquito genera. Their variations mainly occur in CR with a length of 493 - 886 bp, and six repeat unit types are identified for the first time and demonstrate some evolutionary signals. The subgenera Lophopodomyia, Stethomyia, Kerteszia, Nyssorhynchus, Anopheles and Cellia, are proposed to be monophyletic with the phylogenetic relationships of (Lophopodomyia + ((Stethomyia + Kerteszia) + (Nyssorhynchus + (Anopheles + Cellia)))). Four series Neomyzomyia, Pyretophorous, Neocellia and Myzomyia in Cellia, and two series Arribalzagia and Myzorhynchus in Anopheles are proposed to be monophyletic, and three sections Myzorhynchella, Argyritarsis and Albimanus and their subdivisions in Nyssorhynchus all appear polyphyletic or paraphyletic. Conclusions: The study comprehensively uncovered the characteristics of mtgenome and the phylogenetics based on mtgenomes in the genus Anopheles, and provided an information frame for further study on the mtgenomes, phylogenetics and taxonomic revision of the genus.

New mental costumes: Leveraging ACRL’s value of information frame in dealing with infodemics in a post-truth era

An infodemic can be defined a disproportionate aggregate of information regarding a problem that makes exposure to reality challenging in a manner that compromises logical thinking. It can also be categorized as a pervasive and deliberate spread of misinformation geared towards deceitfulness. In the 1st WHO Infodemiology Conference, it was affirmed in the context of the coronavirus pandemic that infodemic had heightened deception to the point that necessitates a harmonized response because of the overabundance of misinformation that the world is inundated with, so much so that finding dependable sources and reliable guidance when urgently needed has become an uphill task. Consequently, misinformation blows out of proportion at a remarkably faster pace and further compounded the complexity to health emergency response. The abundance of information on social media oftentimes without authentic sources leads to a dilemma in distinguishing facts, mere opinions, propaganda, or prejudices. Social media has become an avenue for all sorts of misinformation that initially seems credible but later proves fraudulent. Conversely, by the time the authenticity is confirmed to be false, the damage may be irreversible.

EVALUATION OF THE EFFECTIVENESS OF CHANNEL LEVEL PROTOCOLL PARAMETERS

There is justification for a simulation model for assessing channel level protocols. The effect of the data link layer protocol parameters on the data transfer function is analyzed. The data link protocol parameters have been specified and split into two categories, which are customizable and not configurable. In the work, parameters such as the acceptable information frame size are related in detail to the tunable data link protocol parameter; service personnel format; time-out value; unconfirmed frame window size, etc. That nominal data transfer rate, error-correcting codes used, etc. are non-configurable parameters.

The Algorithm of Cyber-physical System Targeting on a Movable Object Using the Smart Sensor Unit

It is known that smart sensor units are one of the main components of the cyber-physical system. One of the tasks, which have been entrusted to such units, are targeting and tracking of movable objects. The algorithm of targeting on such objects using observation equipment has been considered. This algorithm is able to continuously monitor observation results, predict the direction with the highest probability of movement and form a set of commands to maximize the approximation of a moving object to the center of an information frame. The algorithm has been verified on an experimental physical model using a drone. The object recognition module has been developed using YOLOv3 architecture. iOS application has been developed in order to communicate with the drone through WIFI hotspot using UDP commands. Advanced filters have been added to increase the quality of recognition results. The results of experimental research on the mobile platform confirmed the functioning of the targeting algorithm in real-time.