Vehicular ad-hoc networks (VANETs) are the crucial part of intelligent transportation systems (ITS), which are brought to enhance the security, efficiency, and comfort of transportation. VANETs have ...aroused extensive attention in the world recently. One of the challenges in practice is real time and low delay, which strongly requires VANETs to be efficient. Existing schemes have properly solved the problem which is how to aggregate the signatures and verify the aggregated signature. However, few solutions are proposed to pinpoint all invalid signatures if existing. The algorithms that can find all invalid signatures are not efficient enough. Following consideration of the above deficiencies of existing approaches, this paper proposes a factorial bitwise divisions (FBD) algorithm and its optimized version and early-stopping factorial bitwise divisions (EFBD) algorithm. Both algorithms are parallel-friendly. Compared with the binary-based batch verification algorithm, the experimental results demonstrate that the proposed algorithms achieve better performance in both theory and practice at low invalid signatures’ rate. Especially, in the parallel condition, when the number of invalid signatures is 1, the proposed algorithms cost only one aggregation-verification delay, while the comparison is more than log2 n times.
Video coding optimization in AVS2 Zhou, Yimin; Xu, Gencheng; Tang, Kaicheng ...
Information processing & management,
March 2022, 2022-03-00, 20220301, Volume:
59, Issue:
2
Journal Article
Peer reviewed
Chinese second generation of the Audio Video Coding Standard, known as the AVS2, competing with HEVC/H.265 and AV1, has become a well-known video compression standard. Many unique tools have been ...developed and incorporated in AVS2. This paper proposes several encoder optimization schemes with respect to rate-distortion optimization (RDO). Specifically, by exploiting the close relationship between the total number of referenced pictures and the hierarchy of reference structure, a reference structure determined parameter (RSDP) algorithm reallocates Lagrange multiplier. Moreover, an adaptive quantization parameter offset (AQPO) algorithm is provided at both picture-level and Groups of Pictures (GoP)-level to adjust quantization parameters adaptively on top of the preassigned ones. Both RSDP algorithm and AQPO algorithm have already been adopted by AVS2 and incorporated in its reference software. Experimental results show that in the low-delay, RSDP and AQPO achieved savings of 1.35% and 1.26% on BDBR, respectively.
•A frame level QP and λ allocation named reference structure determined parameter (RSDP) algorithm is proposed to satisfy GoP length 4, 8, and 16 respectively.•A GoP level QP and λ allocation named adaptive quantization parameter offset (AQPO) algorithm is proposed to deal with low-delay configuration.•Both RSDP and AQPO algorithms have achieved remarkable coding performance under BD-rate statistic units.
•An evidence-based multimodal fusion approach for predicting the helpfulness of reviews is proposed.•The complementary strength between human and machine algorithms can improve prediction ...performance.•Human intelligent is firstly formulated as a piece of evidence with a certain reliability for predicting review helpfulness.•A new dataset is developed for multimodal review helpfulness prediction tasks.•Minimizing the judgment biases of machine and human intelligence can achieve superior prediction power.
Online product reviews have been increasingly adopted by consumers to express their evaluation for products on e-commercial platforms. Consumers are also encouraged to evaluate the quality of reviews by a voting mechanism, according to their human intelligence. Considerable machine learning approaches have been developed to help detect helpful reviews automatically. However, previous studies largely depend on machine intelligence and neglect the complementary strength between machine algorithms and human intelligence. This study proposes an evidence-based multimodal fusion approach for predicting the helpfulness of reviews by aggregating the human intelligence from user votes and machine intelligence from texts and images. Review helpfulness is measured by a belief distribution and represented by the evidence obtained from each modality data. An evidential reasoning rule-based fusion strategy is proposed to combine the hybrid intelligence considering their complementarity. A new dataset is also developed for the task of multimodal review helpfulness prediction by crawling online product reviews from Amazon.com and annotated by human scoring. Experimental results on the dataset show that the proposed approach for predicting review helpfulness has superior predictive power and outperforms existing methods. This study also contributes to e-commerce by providing an enhanced method for predicting review helpfulness from both human and machine intelligence.
Abstract
Vehicular ad-hoc networks (VANETs) are the key technology supporting the intelligent transportation system (ITS), which is composed of vehicle nodes with wireless communication capability ...and roadside infrastructures. One of the obstacles is how to use batch verification to verify signatures simultaneously. To solve the problem of low verification efficiency in VANETs. This paper defines the problem and proposes an early-stopping factorial bitwise divisions (EFBD) algorithm. The proposed parallel-friendly algorithm achieves better performance in both theory and practice at low invalid signatures rate. Especially, in the parallel condition, the proposed algorithm costs only one aggregation-verification delay when the number of invalid signatures is 1.
Summary
Hemp (Cannabis sativa L.) is an annual and typically dioecious crop. Due to the therapeutic potential for human diseases, phytocannabinoids as a medical therapy is getting more attention ...recently. Several candidate genes involved in cannabinoid biosynthesis have been elucidated using omics analysis. However, the gene function was not fully validated due to few reports of stable transformation for Cannabis tissues. In this study, we firstly report the successful generation of gene‐edited plants using an Agrobacterium‐mediated transformation method in C. sativa. DMG278 achieved the highest shoot induction rate, which was selected as the model strain for transformation. By overexpressing the cannabis developmental regulator chimera in the embryo hypocotyls of immature grains, the shoot regeneration efficiency was substantially increased. We used CRISPR/Cas9 technology to edit the phytoene desaturase gene and finally generated four edited cannabis seedlings with albino phenotype. Moreover, we propagated the transgenic plants and validated the stable integration of T‐DNA in cannabis genome.
Development of Internet of Vehicles (IoV) has aroused extensive attention in recent years. The IoV requires an efficient communication mode when the application scenarios are complicated. To reduce ...the verifying time and cut the length of signature, certificateless aggregate signature (CL-AS) is used to achieve improved performance in resource-constrained environments like vehicular ad hoc networks (VANETs), which is able to make it effective in environments constrained by bandwidth and storage. However, in the real application scenarios, messages should be kept untamed, unleashed, and authentic. In addition, most of the proposed schemes tend to be easy to attack by signers or malicious entities which can be called coalition attack. In this paper, we present an improved certificateless-based authentication and aggregate signature scheme, which can properly solve the coalition attack. Moreover, the proposed scheme not only uses pseudonyms in communications to prevent vehicles from revealing their identity but also achieves considerable efficiency compared with state-of-the-art work, certificateless signature (CLS), and CL-AS schemes. Furthermore, it demonstrates that when focused on the existential forgery on adaptive chosen message attack and coalition attack, the proposed schemes can be proved secure. Also, we show that our scheme exceeds existing certification schemes in both computing and communication costs.
Seed germination is the first stage of the plant life cycle, and salinity is a major environmental stress for the inhibition of seed germination in plants. Hemp (
Cannabis sativa
. L) has high ...economic value and is widely used in textiles, building materials, food, health care, and so on. Unfortunately, research on the salt tolerance of hemp is very limited. In this study, 202 hemp accessions from 11 countries were used to conduct a genome-wide association study (GWAS) on salt tolerance at the germination stage. Based on 762,634 high-quality SNPs, 70 SNP loci were identified to be associated with salt tolerance-related traits (RGR-T1, RGR-T2, RSRL-T1, RSRL-T2, RSW-T1 and RSW-T2). Among the 70 SNPs, nine were further analyzed as candidate SNPs, and 55 genes were annotated within 100 kb upstream and downstream of the nine SNPs. Combined with RNA-seq data and qRT–PCR results,
XM_030641043.1
,
XM_030641906.1
,
XM_030648362.1
,
XM_030648308.1
and
XM_030646898.1
may play a key role in regulating salt tolerance of hemp during germination. To our knowledge, this is the first study of hemp GWAS, and the information obtained in this study will be useful for gene cloning and marker-assisted selection (MAS) of salt tolerance in hemp.
Rate-distortion curve is greatly influenced by the texture and motion compensation. Therefore, using a uniform Lagrangian multiplier (lambda, λ to all the LCUs in a picture may not achieve the ...optimal coding performance. To address the challenging problem on how to formulate the appropriate λ to an individual LCU, this paper proposes a LCU-level Lagrangian multiplier adaption (LLMA) algorithm. Firstly, a motion compensation information entropy (MCIE) of 16 × 16 block is calculated by obtaining a simple binary information entropy from the source. Secondly, MCIE is normalized to a standard normal distribution, on the basis of the strong assumption that the video sources obey the Gaussian distribution. Thirdly, an adaption factor is assigned to a LCU, which multiples on the picture-level λ from the system calculation. Experiments show that the proposed LLMA algorithm achieves remarkable performance in low-delay and random-access configurations, with the resulting achievements of 1.81% BD-Rate gains, compared with VTM 13.0 at low-delay common test condition.
Abstract Female inflorescence is the primary output of medical Cannabis. It contains hundreds of cannabinoids that accumulate in the glandular trichomes. However, little is known about the genetic ...mechanisms governing Cannabis inflorescence development. In this study, we reported the map-based cloning of a gene determining the number of inflorescences per branch. We named this gene CsMIKC1 since it encodes a transcription factor that belongs to the MIKC-type MADS subfamily. Constitutive overexpression of CsMIKC1 increases inflorescence number per branch, thereby promoting flower production as well as grain yield in transgenic Cannabis plants. We further identified a plant-specific transcription factor, CsBPC2, promoting the expression of CsMIKC1. CsBPC2 mutants and CsMIKC1 mutants were successfully created using the CRISPR-Cas9 system; they exhibited similar inflorescence degeneration and grain reduction. We also validated the interaction of CsMIKC1 with CsVIP3, which suppressed expression of four inflorescence development-related genes in Cannabis. Our findings establish important roles for CsMIKC1 in Cannabis, which could represent a previously unrecognized mechanism of inflorescence development regulated by ethylene.
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