Yu Xue^*, Ziming Yuan

Journal on Internet of Things, Vol.4, No.1, pp. 57-67, 2022, DOI:10.32604/jiot.2022.025327 - 17 May 2022

Abstract The attention mechanism is one of the most important priori knowledge to enhance convolutional neural networks. Most attention mechanisms are bound to the convolutional layer and use local or global contextual information to recalibrate the input. This is a popular attention strategy design method. Global contextual information helps the network to consider the overall distribution, while local contextual information is more general. The contextual information makes the network pay attention to the mean or maximum value of a particular receptive field. Different from the most attention mechanism, this article proposes a novel attention mechanism with… More >

Yanman Li¹, Jun Zhang¹, Yang Hu¹, Yingnan Zhao^2,*, Yi Cao³

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1219-1230, 2022, DOI:10.32604/csse.2022.028224 - 09 May 2022

Abstract Safety helmet-wearing detection is an essential part of the intelligent monitoring system. To improve the speed and accuracy of detection, especially small targets and occluded objects, it presents a novel and efficient detector model. The underlying core algorithm of this model adopts the YOLOv5 (You Only Look Once version 5) network with the best comprehensive detection performance. It is improved by adding an attention mechanism, a CIoU (Complete Intersection Over Union) Loss function, and the Mish activation function. First, it applies the attention mechanism in the feature extraction. The network can learn the weight of… More >

Amjad Alsirhani, Mohamed Ezz, Ayman Mohamed Mostafa^*

Computer Systems Science and Engineering, Vol.43, No.3, pp. 967-984, 2022, DOI:10.32604/csse.2022.024854 - 09 May 2022

Abstract Identity management is based on the creation and management of user identities for granting access to the cloud resources based on the user attributes. The cloud identity and access management (IAM) grants the authorization to the end-users to perform different actions on the specified cloud resources. The authorizations in the IAM are grouped into roles instead of granting them directly to the end-users. Due to the multiplicity of cloud locations where data resides and due to the lack of a centralized user authority for granting or denying cloud user requests, there must be several security… More >

Yingnan Zhao^1,*, Peiyuan Ji¹, Fei Chen¹, Guanlan Ji¹, Sunil Kumar Jha²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1001-1016, 2022, DOI:10.32604/iasc.2022.027710 - 03 May 2022

Abstract This paper proposes a spatio-temporal model (VCGA) based on variational mode decomposition (VMD) and attention mechanism. The proposed prediction model combines a squeeze-and-excitation network to extract spatial features and a gated recurrent unit to capture temporal dependencies. Primarily, the VMD can reduce the instability of the original wind speed data and the attention mechanism functions to strengthen the impact of important information. In addition, the VMD and attention mechanism act to avoid a decline in prediction accuracy. Finally, the VCGA trains the decomposition result and derives the final results after merging the prediction result of More >

DOMENICO MARIA CARRETTA^1,§, MARINA DI DOMENICO^2,§, ROBERTO LOVERO³, ROBERTO ARRIGONI⁴, ANGELIKA ELZBIETA WEGIERSKA⁵, MARIAROSARIA BOCCELLINO^2,*, ANDREA BALLINI^2,6,*, IOANNIS ALEXANDROS CHARITOS^7,#, LUIGI SANTACROCE^5,#

BIOCELL, Vol.46, No.8, pp. 1779-1788, 2022, DOI:10.32604/biocell.2022.020009 - 22 April 2022

Abstract The existence of an inflammatory process in the heart muscle, related to a progressive worsening of myocardial function, different etiopathogenetic mechanisms concur and often overlap, thus making the diagnosis and the therapeutic approach complex. As the COVID-19 pandemic progresses, the effects of the disease on the organ systems and in particular on the cardiovascular system are becoming more and more profound. Cardiac involvement is a well-known event with a high percentage of findings in the heart’s magnetic field, even in asymptomatic areas. There are numerous uncertainties regarding their evolution, in the long and short term,… More >

PRANAB DUTTA^1,*, GOMATHY MUTHUKRISHNAN^2,*, SABARINATHAN KUTALINGAM GOPALASUBRAMAIAM², RAJAKUMAR DHARMARAJ², ANANTHI KARUPPAIAH³, KARTHIBA LOGANATHAN⁴, KALAISELVI PERIYASAMY⁵, M. ARUMUGAM PILLAI², GK UPAMANYA⁶, SARODEE BORUAH⁷, LIPA DEB¹, ARTI KUMARI¹, MADHUSMITA MAHANTA¹, PUNABATI HEISNAM⁸, AK MISHRA⁹

BIOCELL, Vol.46, No.8, pp. 1843-1859, 2022, DOI:10.32604/biocell.2022.019291 - 22 April 2022

Abstract

Plant growth-promoting rhizobacteria (PGPR) are specialized bacterial communities inhabiting the root rhizosphere and the secretion of root exudates helps to, regulate the microbial dynamics and their interactions with the plants. These bacteria viz., Agrobacterium, Arthobacter, Azospirillum, Bacillus, Burkholderia, Flavobacterium, Pseudomonas, Rhizobium, etc., play important role in plant growth promotion. In addition, such symbiotic associations of PGPRs in the rhizospheric region also confer protection against several diseases caused by bacterial, fungal and viral pathogens. The biocontrol mechanism utilized by PGPR includes direct and indirect mechanisms direct PGPR mechanisms include the production of antibiotic, siderophore, and hydrolytic enzymes,

… More >

Wei Fang^1,2,*, Liang Shen¹, Victor S. Sheng³, Qiongying Xue¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4867-4877, 2022, DOI:10.32604/cmc.2022.027197 - 21 April 2022

Abstract Precipitation nowcasting is of great significance for severe convective weather warnings. Radar echo extrapolation is a commonly used precipitation nowcasting method. However, the traditional radar echo extrapolation methods are encountered with the dilemma of low prediction accuracy and extrapolation ambiguity. The reason is that those methods cannot retain important long-term information and fail to capture short-term motion information from the long-range data stream. In order to solve the above problems, we select the spatiotemporal long short-term memory (ST-LSTM) as the recurrent unit of the model and integrate the 3D convolution operation in it to strengthen… More >

Yingnan Zhao^1,*, Guanlan Ji¹, Fei Chen¹, Peiyuan Ji¹, Yi Cao²

Computer Systems Science and Engineering, Vol.43, No.2, pp. 719-735, 2022, DOI:10.32604/csse.2022.027288 - 20 April 2022

Abstract Improving short-term wind speed prediction accuracy and stability remains a challenge for wind forecasting researchers. This paper proposes a new variational mode decomposition (VMD)-attention-based spatio-temporal network (VASTN) method that takes advantage of both temporal and spatial correlations of wind speed. First, VASTN is a hybrid wind speed prediction model that combines VMD, squeeze-and-excitation network (SENet), and attention mechanism (AM)-based bidirectional long short-term memory (BiLSTM). VASTN initially employs VMD to decompose the wind speed matrix into a series of intrinsic mode functions (IMF). Then, to extract the spatial features at the bottom of the model, each More >

Jian Geng^1,*, Shaoyuan Yu¹, Ailin Chen¹, Hao Wang², Bo Yan³, Liang Li³, Lei Song³, Qirun Wang⁴

Computer Systems Science and Engineering, Vol.43, No.2, pp. 559-571, 2022, DOI:10.32604/csse.2022.026948 - 20 April 2022

Abstract With the development and application of energy Internet technology, the collaborative interaction of “source network, load and storage” has become the development trend of power grid dispatching. The large-scale access of renewable energy on the load side, the unified management of adjustable loads, and the participation of multiple parties in energy operations have put forward requirements for the safety, credibility, openness, and transparency of the load dispatching environment. Under the environment of carbon emission reduction, the paper proposed an architecture of the scheduling data blockchain, based on the in-depth study of blockchain. Moreover, smart contracts… More >

Weiwei Cai^1,2, Yaping Song¹, Huan Duan¹, Zhenwei Xia¹, Zhanguo Wei^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1539-1555, 2022, DOI:10.32604/cmes.2022.019785 - 19 April 2022

Abstract In the smart logistics industry, unmanned forklifts that intelligently identify logistics pallets can improve work efficiency in warehousing and transportation and are better than traditional manual forklifts driven by humans. Therefore, they play a critical role in smart warehousing, and semantics segmentation is an effective method to realize the intelligent identification of logistics pallets. However, most current recognition algorithms are ineffective due to the diverse types of pallets, their complex shapes, frequent blockades in production environments, and changing lighting conditions. This paper proposes a novel multi-feature fusion-guided multiscale bidirectional attention (MFMBA) neural network for logistics… More >