A near-optimal resource allocation strategy for minimizing the worse-case impact of malicious attacks on cloud networks by Yu-Fang Chen, Frank Yeong-Sung Lin, Kuang-Yen Tai, Chiu-Han Hsiao, Wei-Hsin Wang, Ming-Chi Tsai, Tzu-Lung Sun

“…The proposed model integrates Virtual Machine (VM) initiation decisions and employs the Contest Success Function (CSF) within a two-player max–min game framework to dynamically allocate resources. …”
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Research Progress on Dual Function Radar and Communication Signal Design and its Application in Typical Detection Scenarios by Yaping HE, Longfei SHI, Dong WANG, Jianglan TANG, Junxian CHEN, Jiazhi MA, Jialei LIU

“…Dual Function Radar and Communication (DFRC)-integrated electronic equipment platform, which combines detection and communication functions, effectively addresses issues such as platform limitations, resource constraints, and electromagnetic compatibility by sharing hardware platforms and transmitting waveforms. …”
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Wood Panel Defect Detection Based on Improved YOLOv8n by Rui Li, Shilu Zhong, Xuemei Yang

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Hybrid Islanding Detection of an Inverter-Based High-Noise Microgrid by Hossein Amini, Ali Mehrizi-Sani, Reza Noroozian

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Multimodal Fusion Framework for Urban functional zone change detection using Remote Sensing and Social Sensing Data by B. Fang, B. Fang, B. Fang, B. Fang, X. Chen, X. Chen, X. Chen, X. Chen, H. Chen, H. Chen, Z. Xiang, Z. Xiang, B. Hu, B. Hu, Z. Hu, Z. Hu, Z. Hu, Z. Hu, W. Tu, W. Tu, W. Tu, W. Tu

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Design and Validation of a Lightweight Entropy-Based Intrusion Detection Algorithm for Automotive CANs by Jiacheng Chen, Zhifu Wang

“…Experimental results demonstrate robust performance under low computational resources, achieving high detection accuracy with high recall (>80%) even at 10% bus load fluctuation thresholds. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…For the detection head, a Generalized Wasserstein Distance Loss (GWDLoss) function is proposed to quantify positional and scale discrepancies, improving the adaptability of bounding box regression to geometric variations. …”
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Segmentation-Based Detection for Luffa Seedling Grading Using the Seg-FL Model by Sheng Jiang, Fangnan Xie, Jiangbo Ao, Yechen Wei, Jingye Lu, Shilei Lyu, Zhen Li

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DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model by Panpan Jiang, Xiaohua Yang, Yaping Wan, Tiejun Zeng, Mingxing Nie, Zhenghai Liu

“…Achieving real-time detection with high accuracy, while accommodating the limited resources of edge-computing devices poses a significant challenge for anti-UAV detection. …”
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Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model by Yuan Liu, Yilong Liu, Xiaoyan Guo, Xi Ling, Qingyi Geng

“…Abstract This paper addresses the industrial demand for precision and efficiency in metal surface defect detection by proposing SLF-YOLO, a lightweight object detection model designed for resource-constrained environments. …”
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Engineering functionally-optimized aptamers against SARS-Cov-2 for blocking spike-ACE2 interaction and aptasensor detection by Xiangdong Lai, Weiwei Zhao, Lihua Jiang, Jing Li, Muhammad Faizan Munawer, Jiejuan Lai, Jesus Alejandro Martinez Juarez, Miraj Ud din, Xiaoyang Zhang, Zhongquan Song, Tao Wu, Yiyue Ge, Hui Jiang, Xiaohui Liu, Xuemei Wang

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Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

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Using hyperspectral reflectance to detect changes in photosynthetic activity in Atractylodes chinensis leaves as a function of decreasing soil water content by J. LIU, Y. WANG, X.M. LIN, Z.C. XUE, F.R. ZENG

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LFN-YOLO: precision underwater small object detection via a lightweight reparameterized approach by Mingxin Liu, Mingxin Liu, Yujie Wu, Ruixin Li, Cong Lin, Cong Lin

“…Underwater object detection plays a significant role in fisheries resource assessment and ecological environment protection. …”
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An Optimized FPGA-Based FDIR System for Sensor Fault Detection in Satellite Attitude Estimation by Xianliang Chen, Zhicheng Xie, Jiashu Wu, Xiaofeng Wu

“…To solve this problem, a Fault Detection, Isolation, and Recovery (FDIR) was proposed, which integrates an adaptive unscented Kalman filter (AUKF), a radial basis function (RBF) neural network for fault detection, and a QUEST-based estimator. …”
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KronNet a lightweight Kronecker enhanced feed forward neural network for efficient IoT intrusion detection by Saeed Ullah, Junsheng Wu, Mian Muhammad Kamal, Abdul Khader Jilani Saudagar

“…Abstract The rapid expansion of Internet of Things (IoT) networks necessitates efficient intrusion detection systems (IDS) capable of operating within the stringent resource constraints of IoT devices. …”
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Western spotted skunk spatial ecology in the temperate rainforests of the Pacific Northwest by Marie I. Tosa, Damon B. Lesmeister, Taal Levi

“…Using these home ranges, we fitted a resource selection function using environmental covariates that we assigned to various hypotheses such as resources, predator avoidance, thermal tolerance, and disturbance. …”
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Assessing variability and detecting the effective traits on yield of chickpea (Cicer arietinum L.) promising lines under drought stress condition by Sayyed Saeed Moosavi, Mohammad Reza Abdollahi, Fatemeh Abdi, Homayoun Kanouni

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YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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Using an ensemble approach to predict habitat of Dusky Grouse ( Dendragapus obscurus ) in Montana, USA by Elizabeth A Leipold, Claire N Gower, Lance McNew

“…Consensus between the resource selection function and random forest models was high (93%) and the ensemble map had higher predictive accuracy when classifying the independent dataset than the other two models. …”
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