Uncertainty CNNs: A path to enhanced medical image classification performance by Vasileios E. Papageorgiou, Georgios Petmezas, Pantelis Dogoulis, Maxime Cordy, Nicos Maglaveras

“…In this paper, we introduce a low-complexity uncertainty-based CNN architecture for medical image classification, particularly focused on tumor and heart failure (HF) detection. …”
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An Automated Image Segmentation, Annotation, and Training Framework of Plant Leaves by Joining the SAM and the YOLOv8 Models by Lumiao Zhao, Kubwimana Olivier, Liping Chen

“…Recognizing plant leaves in complex agricultural scenes is challenging due to high manual annotation costs and real-time detection demands. …”
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Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…However, these models often struggle to effectively handle the temporal dependencies, complexity, and scalability required for real-time threat detection. …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…These methods struggle to detect complex or subtle patterns associated with early-stage faults. …”
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Drainage Pipeline Multi-Defect Segmentation Assisted by Multiple Attention for Sonar Images by Qilin Jin, Qingbang Han, Jianhua Qian, Liujia Sun, Kao Ge, Jiayu Xia

“…Drainage pipeline construction projects are vulnerable to a range of defects, such as branch concealed joints, variable diameter, two pipe mouth significances, foreign object insertion, pipeline rupture, and pipeline end disconnection, generated during long-term service in a complex environment. This paper proposes two enhancements to multiple attention learning to detect and segment multiple defects. …”
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Technology of automated video observation of a drogue-sensor basket in the problem of autonomous aerial refueling by A. V. Gaidenkov, M. I. Kanevskiy, A. S. Ostrovskiy, O. I. Ganyak, N. Yu. Chizhov

“…A modeling complex for a synthetic vision system operation is presented. …”
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Radar target detector based on banded sample autocovariance matrices by Chang Qu, Xiaoying Wang, Jing Chen, Junping Yin, Jiang Hu, Zhigen Gao

“…Abstract Detecting weak radar targets in complex cluttered environments remains a significant challenge, particularly when attempting to effectively detect low signal-to-clutter ratio (SCR) targets while maintaining a constant false alarm rate (CFAR). …”
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Three-dimensional optical path extended gourd-type photoacoustic cell for highly sensitive trace acetylene sensing by Chuanwen Qian, Wenjun Ni, Chunyong Yang, Zhongke Zhao, Likang Zhang, Sixiang Ran, Chenyu Wang, Ping Lu, Perry Ping Shum

“…GTPAC achieves an exceptionally high sensitivity of up to 3.36 μV/ppm using a distributed feedback butterfly laser with central wavelength of 1532 nm (±1.5 nm) to detect acetylene gas. When the integration time is extended to 100 s, the minimum detection limit is as low as 0.59 ppb. …”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…However, the existence of matrix effects and spectral fluctuations always affects the accuracy of LIBS quantitative analysis, and poor reproducibility and high detection limits also need to be solved.OBJECTIVESTo improve the accuracy of quantitative analysis of complex matrix samples.METHODSA multi-layer classification model based on k-nearest neighbors (kNN) and support vector machine (SVM) algorithms was constructed to identify the rock type of samples. …”
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The influence of the molecular weight of hyaluronic acid on the mangiferin release kinetics from the polymer matrix by P. P. Snetkov, R. O. Shaikenov, V. I. Klimshina, Yu. E. Generalova, S. N. Morozkina

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Digitization of Medical Device Displays Using Deep Learning Models: A Comparative Study by Pedro Ferreira, Pedro Lobo, Filipa Reis, João L. Vilaça, Pedro Morais

“…However, most home-based medical devices are closed systems that do not support straightforward automatic data export and often require complex connections to access or transmit patient information. …”
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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…The vigorous development of urban air mobility (UAM) is reshaping the urban travel landscape, but it also poses severe challenges to the safe and efficient operation of dense and complex airspace. …”
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Comparative analysis of machine learning models for predicting water quality index in Dhaka’s rivers of Bangladesh by Mosaraf Hosan Nishat, Md. Habibur Rahman Bejoy Khan, Tahmeed Ahmed, Syed Nahin Hossain, Amimul Ahsan, M. M. El-Sergany, Md. Shafiquzzaman, Monzur Alam Imteaz, Mohammad T. Alresheedi

“…This study contributes to the field of environmental science by offering a novel integration of feature selection techniques with ML models to enhance efficiency and cost-effectiveness of water quality monitoring. …”
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Pruning automatic sphere decoding algorithm and performance analysis by LI Ying, WEI Ji-bo

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Pruning automatic sphere decoding algorithm and performance analysis by LI Ying, WEI Ji-bo

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Design and Exploitation of a Dual-Channel Direct Injection System by Xiang Dong, Ziyu Li, Mingxiong Ou, Weidong Jia

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OVERVIEW OF METHODS FOR IMPROVING THE VISUAL QUALITY OF IMAGES AND VIDEOS IN ADVERSE WEATHER CONDITIONS by P. A. Lyakhov, A. S. Ionisyan, V. V. Liutova, A. R. Orazaev

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Faster-than-Nyquist transmission based on multi-layer superposition by Shuang-yang LI, Lei PING, Bao-ming BAI, Xiao MA

“…Faster-than-Nyquist (FTN) signaling technique has received much attention recently as an effective way of enhancing the spectral efficiency.In order to reduce the detection complexity for FTN signals,a multi-layer superposition transmission approach was present.In addition,how to calculate upper bounds on the highest information transmission rate was shown and how to choose suitable component codes was suggested.Numerical results show that the system with different code rates and power on each layer outperforms the system with only power variance on each layer,meanwhile results also imply that given the roll-off factor of the pulse shaping function is not zero,the proposed system is superior to the orthogonal system with a higher modulation format.…”
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HYBRID WLS-KF APPROACH FOR REAL-TIME STATE ESTIMATION IN AUTOMATED DISTRIBUTION GRIDS by Abdulrafiu Yusuf, Olalekan Ogunbiyi, Lambe Mutalub Adesina, Bashiru Olalekan Ariyo

“…Aim/Background: The increasing complexity of modern distribution networks, particularly with the integration of Distributed Energy Resources (DERs), presents significant challenges to traditional state estimation techniques. …”
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A Low Computational Cost Deep Learning Approach for Localization and Classification of Diseases and Pests in Coffee Leaves by Clecio Elias Silva E. Silva, Jonatan Borges Fragoso, Thuanne Paixao, Ana Beatriz Alvarez, Facundo Palomino-Quispe

“…In this context, deep learning presents itself as a promising solution for the automatic identification of plant diseases, reducing dependence on human inspection and increasing efficiency in crop management. In this sense, this study proposes a novel two-stage approach, detecting the diseased region of the coffee leaf and classifying the diseases into Miner, Rust, Cercospora and Phoma on coffee leaves. …”
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