Classification of skin diseases with deep learning based approaches by Merve Okumuş Sarı, Kübra Keser

“…Abstract Skin diseases are one of the most common health problems that affect people of all ages around the world and significantly reduce the quality of life of individuals. …”
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A multi-factor integration-based semi-supervised learning for address resolution protocol attack detection in SDIIoT by Zhong Li, Huimin Zhuang

“…These advantages prompt us to propose a multi-factor integration-based semi-supervised learning address resolution protocol detection method deployed in software-defined networking, called MIS, to specially solve the problems of limited labeled training data and incomplete features extraction in the traditional address resolution protocol detection methods. …”
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Dense-Fusion2Net a more efficient and lightweight short speech speaker recognition system with time-frequency channel attention by Fei Deng, Rui Huang, Peifan Jiang, Lin Yu, Lihong Deng

“…We propose the Dense-Fusion2Net network architecture to more efficiently utilize the limited acoustic features in short speech segments. We designed the Time-Frequency Channel Attention (TFCA). …”
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Lagrangian transport based on the winds of the icosahedral nonhydrostatic model (ICON) by Jonas Sonnabend, Jens-Uwe Grooß, Felix Ploeger, Lars Hoffmann, Patrick Jöckel, Bastian Kern, Rolf Müller

“…When transport is represented employing Lagrangian methods, numerical problems representing transport barriers may be obviated. …”
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Research on learning achievement classification based on machine learning. by Jianwei Dong, Ruishuang Sun, Zhipeng Yan, Meilun Shi, Xinyu Bi

“…Research has shown that the RBFN model based on educational habit features performs the best after using GDO data augmentation. …”
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Development of enriced butter by N. S. Bezverkhaya, O. A. Ogneva

“…A characteristic feature of a modern person’s life is a constant lack of free time, inadequate sleep, a sedentary lifestyle and, most importantly, an unbalanced diet. …”
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VICTIMOLOGICAL ASPECT OF A CORRUPTION DEAL by A. A. Ivanova

“…The conclusion is made about the feasibility of a legal assessment of corruption deals as a qualifying feature of a criminal offense.Scientific novelty: the article justifies the author's position in relation to an assessment of corruption victimization of the deal; victimological characteristic of a corrupt deals victim are given; critical analysis of basic victimological concepts is made to identify the potential corrupt deals victims and ensure victim safety.Practical significance: the idea is expressed of reorienting public consciousness, views on corruption as a way of solving problems; of changing tolerance to corruption, due to which the legal subjects become victims of corrupt deals; of amending the anti-corruption policies towards more careful attention to the protection of the legal relations subjects against the corruption threat.…”
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A Deep Reinforcement Learning Approach for Portfolio Management in Non-Short-Selling Market by Ruidan Su, Chun Chi, Shikui Tu, Lei Xu

“…Some risk-return balanced studies extract features from price and volume data only, which is highly correlated and missing representation of risk features. …”
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IMRMB-Net: A lightweight student behavior recognition model for complex classroom scenarios. by Caihong Feng, Zheng Luo, Deyao Kong, Yunhong Ding, Jingyu Liu

“…To address the above problems, this study proposes a lightweight student behavior recognition model based on Inverted Residual Mobile Block (IMRMB-Net). …”
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A Study of Potential Applications of Student Emotion Recognition in Primary and Secondary Classrooms by Yimei Huang, Wei Deng, Taojie Xu

“…Emotion recognition is critical to understanding students’ emotional states. However, problems such as crowded classroom environments, changing light, and occlusion often affect the accuracy of recognition. …”
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Multi-Sensor Information Fusion Positioning of AUKF Maglev Trains Based on Self-Corrected Weighting by Qian Hu, Hong Tang, Kuangang Fan, Wenlong Cai

“…Aiming at magnetic levitation train positioning, there are problems such as being easily interfered with by external noise, the single positioning method, and traditional weighting affected by historical data, which lead to the deviation of positioning fusion results. …”
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Silent speech recognition using visual cascading fusion of tongue-lip movements based on pre-trained and fine-tuned model by Chongchong Yu, Xuening Wang, Zhaopeng Qian

“…Besides, the pre-trained and fine-tuned frameworks based on Visual-HuBERT using masked technology are used to address the overfitting problems of model due to a lack of training data. The proposed model is evaluated based on the TaL and self-made Chinese data corpus. …”
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Severnaya Zemlya – geography with history at the turn of times by V. M. Kotlyakov, F. D. Zhokhov, N. V. Zhokhova, M. G. Ushakova

“…«Not-simultaneous» shore opening and land surveying all over the archipelago led to divergent assessments of the events and facts.Preservation of historic names as a cultural and historical heritage, the inadmissibility of the historical names abolition are supported by the acting Russian Federation Law on the names of geographic features. The authors emphasize the need to return to the historical names with the application of national legislation and with justification of solutions Russian Arctic toponymy problems from international practices.…”
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A Rhythm-Based Authentication Scheme for Smart Media Devices by Jae Dong Lee, Young-Sik Jeong, Jong Hyuk Park

“…In this paper, an original security-locking scheme using a rhythm-based locking system (RLS) is proposed to overcome the existing security problems of smart devices. RLS is a user-authenticated system that addresses vulnerability issues in the existing locking features and provides secure confidentiality in addition to convenience.…”
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Spatial–Spectral Interaction Super-Resolution CNN–Mamba Network for Fusion of Satellite Hyperspectral and Multispectral Image by Guangwei Zhao, Haitao Wu, Dexiang Luo, Xu Ou, Yu Zhang

“…However, these methods do not fully utilize the characteristics of data for network design, and cannot guarantee effective computational efficiency in extracting local and global features. To solve the above problems, we designed a spatial–spectral interaction super-resolution convolutional neural network (CNN)–Mamba fusion network for satellite HSI and MSI, which uses mutual guidance to improve the spatial and spectral resolution of different data, and obtains the final fused image through feature fusion. …”
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Intelligent Fault Diagnosis of Hydraulic System Based on Multiscale One-Dimensional Convolutional Neural Networks with Multiattention Mechanism by Jiacheng Sun, Hua Ding, Ning Li, Xiaochun Sun, Xiaoxin Dong

“…The proposed method first extracts features from multirate data samples using a parallel 1DCNN with different receptive fields. …”
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A Multimodel Decision Fusion Method Based on DCNN-IDST for Fault Diagnosis of Rolling Bearing by Weixiao Xu, Luyang Jing, Jiwen Tan, Lianchen Dou

“…The DCNN model can learn features from the original data and carry out adaptive feature extraction for multiple sensor information. …”
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Multi-UAVs task allocation method based on MPSO-SA-DQN by Peng Pengfei, Gong Xue, Zheng Yalian

“…Although many methods are proposed to solve the Multi-UAV task allocation, there still existing the problems of complex time constraints and uncertain solution space. …”
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Traffic sign detection method based on improved YOLOv8 by Gaihua Wang, Peng Jin, Zhiwei Qi, Xiaohuan Li

“…Firstly, the Neck part of YOLOv8 is improved by designing a module that combines Attention Scale Sequence Fusion with the P2 small target detection layer (AFP) to enhance the feature extraction capability of the YOLOv8 network, enabling it to capture more small target features. …”
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RRBM-YOLO: Research on Efficient and Lightweight Convolutional Neural Networks for Underground Coal Gangue Identification by Yutong Wang, Ziming Kou, Cong Han, Yuchen Qin

“…Coal gangue identification is the primary step in coal flow initial screening, which mainly faces problems such as low identification efficiency, complex algorithms, and high hardware requirements. …”
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