Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…At the same time, the ReLU transfer function ensures robustness, mainly when dealing with noisy or incomplete image segments. …”
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Hand-aware graph convolution network for skeleton-based sign language recognition by Juan Song, Huixuechun Wang, Jianan Li, Jian Zheng, Zhifu Zhao, Qingshan Li

“…Skeleton-based sign language recognition (SLR) is a challenging research area mainly due to the fast and complex hand movement. …”
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A distributed week-ahead scheduling method for the charging / discharging of plug-in electric vehicles integrated into the grid by Yan Cui, Zechun Hu, Yujian Wan, Junsong Li, Chengcheng Shao, Zhiyuan Bao, Xiaoyu Duan

“…However, the existing research works on GVI are mainly limited to day-ahead or intra-day schedules which may not fully utilize the EVs' potential in charging/discharging arrangements for the power grid. …”
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Detection of Access Point Spoofing in the Wi-Fi Fingerprinting Based Positioning by Juraj Machaj, Clément Safon, Slavomír Matúška, Peter Brída

“…In this paper filtering algorithms are proposed to minimize the impact of access point spoofing. …”
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Enhanced Rapid Mangrove Habitat Mapping Approach to Setting Protected Areas Using Satellite Indices and Deep Learning: A Case Study of the Solomon Islands by Hyeon Kwon Ahn, Soohyun Kwon, Cholho Song, Chul-Hee Lim

“…Mangroves, as a key component of the blue-carbon ecosystem, have exceptional carbon sequestration capacity and are mainly distributed in tropical coastal regions. In the Solomon Islands, ongoing degradation of mangrove forests, primarily due to land conversion and timber exploitation, highlights an urgent need for high-resolution spatial data to inform effective conservation strategies. …”
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Eosinophilic Fasciitis: A Review of Research and Therapeutic Possibilities by Julia Biernikiewicz, Anna Wilewska, Bartosz Pomirski, Agata Pomirska, Milena Biernikiewicz, Konstanty Alabrudziński, Agnieszka Borowiec, Kinga Borowiec, Paulina Kwaśniewska, Patryk Graczyk

“…Diagnosis often involves biopsies, lab analyses, and imaging techniques. Current treatment mainly consists of corticosteroids, but further research is needed to assess various therapeutic strategies. …”
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Time series forecasting of infant mortality rate in India using Bayesian ARIMA models by Anuj Singh, Tripti Tripathi, Rakesh Ranjan, Abhay K. Tiwari

“…A Random Walk Metropolis algorithm has been used to deal with analytically intractable posterior results from the ARIMA model. …”
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Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network by Liming Li, Shubin Zheng, Chenxi Wang, Shuguang Zhao, Xiaodong Chai, Lele Peng, Qianqian Tong, Ji Wang

“…This work presents a new method for sleeper crack identification based on cascade convolutional neural network (CNN) to address the problem of low efficiency and poor accuracy in the traditional detection method of sleeper crack identification. The proposed algorithm mainly includes improved You Only Look Once version 3 (YOLOv3) and the crack recognition network, where the crack recognition network includes two modules, the crack encoder-decoder network (CEDNet) and the crack residual refinement network (CRRNet). …”
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Node-Based Steady-State and Dynamic Gas Grid Calculation Method With Electrical Analogies by Daniela Vorwerk, Detlef Schulz

“…While the steady-state electric equivalent circuit diagram of a gas pipeline mainly consists of an ohmic resistance, the transient flow characteristics also show inductive and capacitive behavior. …”
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Node Classification Method Based on Hierarchical Hypergraph Neural Network by Feng Xu, Wanyue Xiong, Zizhu Fan, Licheng Sun

“…The HCHG combines the high-order relationship-capturing capability of hypergraphs, uses the Louvain community detection algorithm to identify community structures within the network, and constructs hypergraphs layer by layer. …”
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ML‐UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper by Warren G. Hill, Bryce MacIver, Gary A. Churchill, Mariana G. DeOliveira, Mark L. Zeidel, Marcelo Cicconet

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A Recognition Method for Adzuki Bean Rust Disease Based on Spectral Processing and Deep Learning Model by Longwei Li, Jiao Yang, Haiou Guan

“…Second, the competitive adaptive reweighted sampling (CARS) algorithm was implemented in the range of 425–825 nm to determine the optimal characteristic wavenumbers, thereby reducing data redundancy. …”
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Diaphragm injuries in a mature trauma system: still a diagnostic challenge by S. Karhof, R. K. J. Simmermacher, P. Gerbranda, K. J. P. van Wessem, L. P. H. Leenen, F. Hietbrink

“…The majority of injuries was seen following blunt trauma (72%). Mortality was 21%, mainly due to concomitant injuries. One patient died due to the consequences of an unrecognized diaphragm injury. …”
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Temporal-spatial change characteristics of sunshine duration in Tibet based on spatial interpolation technique and its influence factors by YU Haijing, CHEN Tingfu, ZHANG Qingguo, ZHANG Ning, DONG Shijie, CHENG Mengdi

“…Results showed that the interpolation algorithm of Kriging spherical model could simulate Tibet sunshine duration quite well. …”
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Key technologies and equipment for intelligent sensor network by optical media by Qiang GAO, Wenzhuo LI, Daiyong ZHOU

“…At present, coal mine sensor network mainly adopts industrial Ethernet + fieldbus technology, which has the characteristics of differential signal transmission, collection polling and convenient application, but there are problems such as insufficient anti-interference ability, contradictory communication speed and distance, and difficult communication between nodes. …”
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Hard-coded backdoor detection method based on semantic conflict by Anxiang HU, Da XIAO, Shichen GUO, Shengli LIU

“…The current router security issues focus on the mining and utilization of memory-type vulnerabilities, but there is low interest in detecting backdoors.Hard-coded backdoor is one of the most common backdoors, which is simple and convenient to set up and can be implemented with only a small amount of code.However, it is difficult to be discovered and often causes serious safety hazard and economic loss.The triggering process of hard-coded backdoor is inseparable from string comparison functions.Therefore, the detection of hard-coded backdoors relies on string comparison functions, which are mainly divided into static analysis method and symbolic execution method.The former has a high degree of automation, but has a high false positive rate and poor detection results.The latter has a high accuracy rate, but cannot automate large-scale detection of firmware, and faces the problem of path explosion or even unable to constrain solution.Aiming at the above problems, a hard-coded backdoor detection algorithm based on string text semantic conflict (Stect) was proposed since static analysis and the think of stain analysis.Stect started from the commonly used string comparison functions, combined with the characteristics of MIPS and ARM architectures, and extracted a set of paths with the same start and end nodes using function call relationships, control flow graphs, and branching selection dependent strings.If the strings in the successfully verified set of paths have semantic conflict, it means that there is a hard-coded backdoor in the router firmware.In order to evaluate the detection effect of Stect, 1 074 collected device images were tested and compared with other backdoor detection methods.Experimental results show that Stect has a better detection effect compared with existing backdoor detection methods including Costin and Stringer: 8 hard-coded backdoor images detected from image data set, and the recall rate reached 88.89%.…”
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Quantitative evaluation and obstacle factor diagnosis of drug regulatory capacity in China. by Mingming Zhai, Liwen Huang, Shijie Sun, Liying Cao, Xueqiong Yue, Yuanxia Hu

“…From the perspective of obstacle factors, they were mainly in the aspects of learning development and functional performance. …”
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DRR-YOLO: A Study of Small Target Multi-Modal Defect Detection for Multiple Types of Insulators Based on Large Convolution Kernel by Mingming Hu, Jun Liu, Junfu Liu

“…The existing insulator defect detection algorithms are mainly characterized by their ability to identify only a single type of defect, accompanied by relatively low accuracy, a Dilated Re-parameterized Residual-YOLO (DRR-YOLO) algorithm is proposed, which is capable of identifying four defects of each of the four insulator types. …”
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Implicit Is Not Enough: Explicitly Enforcing Anatomical Priors inside Landmark Localization Models by Simon Johannes Joham, Arnela Hadzic, Martin Urschler

“…Currently, Anatomical Landmark Localization (ALL) is mainly solved by deep-learning methods, which cannot guarantee robust ALL predictions; there may always be outlier predictions that are far from their ground truth locations due to out-of-distribution inputs. …”
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Advanced parameter extraction optimization technique for the four-diode model approach by Bhanu Prakash Saripalli, Bharati Gamgula, Revathi Ravilisetty, Prashant Kumar, Gagan Singh, Sonika Singh

“…However, these models mainly focus on the fundamental mechanism of diffusion and Shockley-Read-Hall recombination. …”
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