A Lightweight and Accurate Face Detection Algorithm Based on Retinaface

In this paper, we propose a lightweight and accurate face detection algorithm LAFD (Light and accurate face detection) based on Retinaface. Backbone network in the algorithm is a modified MobileNetV3 network which adjusts the size of the convolution kernel, the channel expansion multiplier of the inverted residuals block and the use of the SE attention mechanism. Deformable convolution network(DCN) is introduced in the context module and the algorithm uses focal loss function instead of cross-entropy loss function as the classification loss function of the model. The test results on the WIDERFACE dataset indicate that the average accuracy of LAFD is 94.1%, 92.2% and 82.1% for the "easy", "medium" and "hard" validation subsets respectively with an improvement of 3.4%, 4.0% and 8.3% compared to Retinaface and 3.1%, 4.1% and 4.1% higher than the well-performing lightweight model, LFFD. If the input image is pre-processed and scaled to 1560px in length or 1200px in width, the model achieves an average accuracy of 86.2% on the 'hard' validation subset. The model is lightweight, with a size of only 10.2MB.Comment: 14 pages, 5 figures, 7 table

Semigroup approach to the stability of a direct strain feedback control system of elastic vibration with structure damping

AbstractIn this paper, we relate a kind of second order hyperbolic system to an analytic semigroup, which is most often applied to the direct strain feedback (DSFB) control of flexible robot arms. The spectrum analysis is presented to confirm the positive function of DSFB

Event-based multi-objective filtering for multi-rate time-varying systems with random sensor saturation

summary:This paper focuses on the multi-objective filtering of multirate time-varying systems with random sensor saturations, where both the variance-constrained index and the $H_\infty$ index are employed to evaluate the filtering performance. According to address issues, the high-frequency period of the internal state of the system is nondestructively converted to the low-frequency period, which determined by the measurement devices. Then the saturated output of multiple sensors is modeled as a sector bounded nonlinearity. At the same time, in order to reduce the communication frequency between sensors and filters, a communication scheduling rule is designed by the utilization of an event-triggered mechanism. By means of random analysis technology, the sufficient conditions are given to guarantee the preset $H_\infty$ performance and variance constraint performance indexes of the system, and then the solution of the desired filter is obtained by using linear matrix inequalities. Finally, the validity and effectiveness of the proposed filter scheme are verified by numerical simulation

Multi-fault diagnosis for rolling element bearings based on intrinsic mode function screening and optimized least squares support vector machine

Multi-fault diagnosis of rolling element bearing is significant to avoid serious accidents and huge economic losses effectively. However, due to the vibration signal with the character of nonstationarity and nonlinearity, the detection, extraction and classification of the fault feature turn into a challenging task. This paper presents a novel method based on redundant second generation wavelet packet transform (RSGWPT), ensemble empirical mode decomposition (EEMD) and optimized least squares support vector machine (LSSVM) for fault diagnosis of rolling element bearings. Firstly, this method implements an analysis combining RSGWPT-EEMD to extract the crucial characteristics from the measured signal to identify the running state of rolling element bearings, the vibration signal is adaptively decomposed into a number of modified intrinsic mode functions (modified IMFs) by two step screening processes based on the energy ratio; secondly, the matrix is formed by different level modified IMFs and singular value decomposition (SVD) is used to decompose the matrix to obtain singular value as eigenvector; finally, singular values are input to LSSVM optimized by particle swarm optimization (PSO) in the feature space to specify the fault type. The effectiveness of the proposed multi-fault diagnosis technique is demonstrated by applying it to both simulated signals and practical bearing vibration signals under different conditions. The results show that the proposed method is effective for the condition monitoring and fault diagnosis of rolling element bearings

Peanut gene expression profiling in developing seeds at different reproduction stages during Aspergillus parasiticus infection

<p>Abstract</p> <p>Background</p> <p>Peanut (<it>Arachis hypogaea </it>L.) is an important crop economically and nutritionally, and is one of the most susceptible host crops to colonization of <it>Aspergillus parasiticus </it>and subsequent aflatoxin contamination. Knowledge from molecular genetic studies could help to devise strategies in alleviating this problem; however, few peanut DNA sequences are available in the public database. In order to understand the molecular basis of host resistance to aflatoxin contamination, a large-scale project was conducted to generate expressed sequence tags (ESTs) from developing seeds to identify resistance-related genes involved in defense response against <it>Aspergillus </it>infection and subsequent aflatoxin contamination.</p> <p>Results</p> <p>We constructed six different cDNA libraries derived from developing peanut seeds at three reproduction stages (R5, R6 and R7) from a resistant and a susceptible cultivated peanut genotypes, 'Tifrunner' (susceptible to <it>Aspergillus </it>infection with higher aflatoxin contamination and resistant to TSWV) and 'GT-C20' (resistant to <it>Aspergillus </it>with reduced aflatoxin contamination and susceptible to TSWV). The developing peanut seed tissues were challenged by <it>A. parasiticus </it>and drought stress in the field. A total of 24,192 randomly selected cDNA clones from six libraries were sequenced. After removing vector sequences and quality trimming, 21,777 high-quality EST sequences were generated. Sequence clustering and assembling resulted in 8,689 unique EST sequences with 1,741 tentative consensus EST sequences (TCs) and 6,948 singleton ESTs. Functional classification was performed according to MIPS functional catalogue criteria. The unique EST sequences were divided into twenty-two categories. A similarity search against the non-redundant protein database available from NCBI indicated that 84.78% of total ESTs showed significant similarity to known proteins, of which 165 genes had been previously reported in peanuts. There were differences in overall expression patterns in different libraries and genotypes. A number of sequences were expressed throughout all of the libraries, representing constitutive expressed sequences. In order to identify resistance-related genes with significantly differential expression, a statistical analysis to estimate the relative abundance (<it>R</it>) was used to compare the relative abundance of each gene transcripts in each cDNA library. Thirty six and forty seven unique EST sequences with threshold of <it>R </it>> 4 from libraries of 'GT-C20' and 'Tifrunner', respectively, were selected for examination of temporal gene expression patterns according to EST frequencies. Nine and eight resistance-related genes with significant up-regulation were obtained in 'GT-C20' and 'Tifrunner' libraries, respectively. Among them, three genes were common in both genotypes. Furthermore, a comparison of our EST sequences with other plant sequences in the TIGR Gene Indices libraries showed that the percentage of peanut EST matched to <it>Arabidopsis thaliana</it>, maize (<it>Zea mays</it>), <it>Medicago truncatula</it>, rapeseed (<it>Brassica napus</it>), rice (<it>Oryza sativa</it>), soybean (<it>Glycine max</it>) and wheat (<it>Triticum aestivum</it>) ESTs ranged from 33.84% to 79.46% with the sequence identity ≥ 80%. These results revealed that peanut ESTs are more closely related to legume species than to cereal crops, and more homologous to dicot than to monocot plant species.</p> <p>Conclusion</p> <p>The developed ESTs can be used to discover novel sequences or genes, to identify resistance-related genes and to detect the differences among alleles or markers between these resistant and susceptible peanut genotypes. Additionally, this large collection of cultivated peanut EST sequences will make it possible to construct microarrays for gene expression studies and for further characterization of host resistance mechanisms. It will be a valuable genomic resource for the peanut community. The 21,777 ESTs have been deposited to the NCBI GenBank database with accession numbers <ext-link ext-link-type="gen" ext-link-id="ES702769">ES702769</ext-link> to <ext-link ext-link-type="gen" ext-link-id="ES724546">ES724546</ext-link>.</p

Mechanisms of Resistance to Aflatoxin Accumulation by Aspergillus Flavus in Maize Genotype GT-MAS:gk.

Maize genotype differences in aflatoxin production were observed when kernels of resistant GT-MAS:gk and thirteen susceptible commercial hybrids were inoculated with Aspergillus flavus using a laboratory kernel screening assay. GT-MAS:gk supported the lowest levels of aflatoxin in both intact and endosperm-wounded kernels. Treating intact kernels with KOH effected substantial increases in aflatoxin accumulation in GT-MAS:gk, but only marginal increases in Pioneer 3154. Removing wax from the surface of GT-MAS:gk kernels greatly increased aflatoxin accumulation. These results indicated that GT-MAS:gk resistance was associated with an intact pericarp (wax and cutin layers), acting as a physical barrier, along with internal biochemical factors. Kernels of GT-MAS:gk and Pioneer 3154 were tested for resistance to aflatoxin accumulation by A. flavus under different relative humidities (RH). Resistance in GT-MAS:gk was consistent across all RH levels. Preincubation at 100% RH for three days increased germination. In germinated kernels, aflatoxin levels decreased markedly in Pioneer 3154 but not GT-MAS:gk. When eight susceptible hybrids were evaluated under preincubation conditions, seven supported significantly lower aflatoxin levels than kernels not subjected to preincubation. Data suggested that an inhibitor of aflatoxin biosynthesis may be induced during kernel germination process. A. flavus can utilize cutin as sole carbon source, which suggests production of extracellular cutinase in vitro. This production was optimal at pH 8.0. Two esterases (cutinases) (36 kD and 22-23 kD) were isolated from A. flavus liquid cultures. Treatments with exogenous cutinase or DFP, an fungal cutinase inhibitor, markedly increased or decreased aflatoxin production, respectively. Results suggested that A. flavus produces cutinase and that this enzyme may play an important role in pathogenicity of A. flavus. Studies demonstrated that GT-MAS:gk kernels have more surface wax than do susceptible hybrids, and that this wax has antifungal activity against A. flavus. Wax from GT-MAS:gk kernels had a unique component, visualized using thin layer chromatography. This component was purified and examined using gas chromatography and mass spectrometry. A peak was identified that was absent in other genotypes. This compound may be a triterpenoid

Robust Nash Dynamic Game Strategy for User Cooperation Energy Efficiency in Wireless Cellular Networks

Recently, there is an emerging trend of addressing “energy efficiency” aspect of wireless communications. It has been shown that cooperating users relay each other\u27s information to improve data rates. The energy is limited in the wireless cellular network, but the mobile users refuse to relay. This paper presents an approach that encourages user cooperation in order to improve the energy efficiency. The game theory is an efficient method to solve such conflicts. We present a cellular framework in which two mobile users, who desire to communicate with a common base station, may cooperate via decode-and-forward relaying. In the case of imperfect information assumption, cooperative Nash dynamic game is used between the two users\u27 cooperation to tackle the decision making problems: whether to cooperate and how to cooperate in wireless networks. The scheme based on “cooperative game theory” can achieve general pareto-optimal performance for cooperative games, and thus, maximize the entire system payoff while maintaining fairness

The Research on Strategy of Building Campus Network Security Based on University Management

AbstractCampus network play a crucial role in the study and management of the daily work of schools. With the rapid development and popularization of the campus network, the security issues become increasingly prominent. How to make safe and efficient operation of the campus network, give full play to its teaching, management and service functions, has become an issue cannot be ignored. On the basis of the analysis of the characteristics and common threats to the campus network security management, network security commonly used techniques such as firewalls, VLAN, and so on, made a series of security policy for the campus network characteristics