Cross-Modal Collaboration and Robust Feature Classifier for Open-Vocabulary 3D Object Detection by Hengsong Liu, Tongle Duan

“…In this approach, 2D images provide preliminary regions of interest for novel objects in the 3D point cloud, while the 3D point cloud offers more precise positional information to the 2D images. Through iterative updates between two modalities, the preliminary region and positional information are refined, achieving the accurate localization of novel objects. …”
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Quantitative Risk Assessment of Vibrio parahaemolyticus Toxi Infection Associated with the Consumption of Roasted Shrimp (Penaeus monodon) by Arnaud Carter Keinko Takoundjou, Rhoda Nsen Bughe, Abraham Nkoue Tong, Sylvain Leroy Sado Kamdem, Jean Justin Essia-Ngang

“…This simulation was realized based on 10,000 iterations using the Model Risk software, version 4.0, in combination with Microsoft Excel. …”
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Estimating Network Flowing over Edges by Recursive Network Embedding by Liqun Yu, Hongqi Wang, Haoran Mo

“…To construct the learning problem, we build three subproblems of minimization: (1) the embedding error of each node from the recursive network, (2) the loss of the construction for the amount of value of each node, and (3) the difference between the value amount of each node and the estimated value from the edge flows. We develop an iterative algorithm to learn the node embeddings, edge flows, and node values jointly. …”
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Improved Grey Particle Swarm Optimization and New Luus-Jaakola Hybrid Algorithm Optimized IMC-PID Controller for Diverse Wing Vibration Systems by Nailu Li, Hua Yang, Anle Mu

“…The original GPSO is modified by using small population size/iteration number, employing new grey analysis rule and designing new updating formula of acceleration coefficients. …”
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Sparse Regularization With Reverse Sorted Sum of Squares via an Unrolled Difference-of-Convex Approach by Takayuki Sasaki, Kazuya Hayase, Masaki Kitahara, Shunsuke Ono

“…These include developing an algorithm grounded in theory, not heuristics, reducing computational complexity, enabling the automatic determination of numerous parameters, and ensuring the number of iterations remains feasible. In this study, we propose a novel sparse regularization function called the reverse sorted sum of squares (RSSS) and then construct an unrolled algorithm that addresses both the aforementioned two problems and these four challenges. …”
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Optimized sequential model for superior classification of plant disease by Yogesh Chimate, Sangram Patil, K. Prathapan, Jaydeep Patil, Jayendra Khot

“…Overall, CNN can continuously improve and adapt its performance through iterative training, resulting in higher accuracy rates and reduced false positives in contrast to conventional machine learning methods.…”
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Coregistration of Ultrasonography and Magnetic Resonance Imaging with a Preliminary Investigation of the Spatial Colocalization of Vascular Endothelial Growth Factor Receptor 2 Exp... by Mary E. Loveless, Jennifer G. Whisenant, Kevin Wilson, Andrej Lyshchik, Tuhin K. Sinha, John C. Gore, Thomas E. Yankeelov

“…Tumor volumes from each data set were segmented independently by two investigators and coregistered using an iterative closest point algorithm. In addition to anatomic images, vascular endothelial growth factor receptor 2 (VEGFR2) distribution images from the central tumor slice using VEGFR2-targeted ultrasound contrast agent (UCA) and measurements of perfusion and extravascular-extracellular volume fraction using dynamic contrast-enhanced MRI were acquired from five mice for multiparametric coregistration. …”
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Understanding the current backlash against LGBTIQ+ rights through the lens of heteroactivism: A case study of the International Organization for the Family’s transnational norm dif... by Strand Cecilia, Eriksson Åsa, Svensson Jakob

“…To better understand these actors’ norm diffusion, including their re-styling of anti-gender narratives in contemporary iterations of heteroactivism and its potential threat to LGBTIQ+ rights, in this article we analyse the social media tactics of a key transnational anti-gender actor: the International Organization for the Family (IOF). …”
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Selecting the Best Routing Traffic for Packets in LAN via Machine Learning to Achieve the Best Strategy by Bo Zhang, Rongji Liao

“…This study aims to suggest an efficient algorithm that could help in selecting the shortest path to improve the existing methods using weights derived from packet ID and to change neural network iteration simultaneously. In this study, the design of the efficient neural network of appropriate output is discussed in detail including the principles of the network. …”
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Why Rights are Wrong in ASEAN and Beyond: A Critique of the Foundations of Universal Human Rights by D. Brian Scarnecchia

“…Part Two then examines whether the original axiomatic listing of human rights or an iteration of human rights founded upon the human genome or a Kantian underpinning can legitimise human rights and, if not, whether reference to the human soul made in the image of God with its natural law may substantiate the human rights project, perhaps, articulated as congruent with the purpose and design courts now recognise in the natural laws found in every ecosystem of nature. …”
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Adaptive Image Denoising Method Based on Diffusion Equation and Deep Learning by Shaobin Ma, Lan Li, Chengwen Zhang

“…Then, the threshold function is adaptively designed and improved so that it can automatically control the threshold of the function according to the maximum gray value of the image and the number of iterations, so as to further preserve the important details of the image such as edge and texture. …”
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Load Deflection Analysis of Beam-Column using Total Potential Energy (TPE) Principle by Manar A. Al-Fadul, Haider H. Darwash, Furat Y. Al-Ghalibi

“…Nonlinear analysis of central finite deflection is carried out using Newton-Raphson iteration that includes high order terms of total potential energy (TPE). …”
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Optimal Coordination of TCSC and PSS2B Controllers in Electric Power Systems Using MOPSO Multiobjective Algorithm by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Yahya Gholami Omali, Ilhami Colak, Phatiphat Thounthong, William Holderbaum

“…The simulations were iterated in two scenarios by creating different loading conditions in generators. …”
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Factors for Satisfaction Among Providers of Ancillary Health Services in a Community-Based Cancer Prevention Program: A Pilot Study in Nevada by Emmanuel C. Gorospe, Christopher R. Cochran, Elena E. Cabb

“…We subjected the survey data to factor analysis using iterative principal axis factoring with Varimax rotation. …”
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Multi-Band mm-Wave Wearable Antenna Synthesized with a Genetic Algorithm by Arebu Dejen, Murad Ridwan, Jeevani Jayasinghe, Jaume Anguera

“…The reference patch antenna was etched on a flexible polytetrafluoroethylene (PTFE) fabric substrate with an overall dimension of 18 mm × 18 mm × 0.6 mm and optimized the patch geometry using a binary-coded genetic algorithm. The algorithm iteratively creates a new shape of the path surface, evaluates the cost function, and returns the best-fitted geometry based on the formulated fitness function. …”
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Unsupervised data imputation with multiple importance sampling variational autoencoders by Shenfen Kuang, Yewen Huang, Jie Song

“…The statistical model and variational distributions are iteratively updated by maximizing the Multiple Importance Sampling Evidence Lower Bound (MISELBO) on the joint log-likelihood. …”
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Pedagogical responsiveness: Focus on the Ukuqonda institute’s mode of engagement in mathematics by Satsope Maoto, Manare Setati, Gabriel Mphuthi

“…The findings show that the participants’ pedagogical responsiveness was stimulated by the iterative process of team planning, deliberate implementation, and reflection. …”
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Estimation Markov Decision Process of Multimodal Trip Chain between Integrated Transportation Hubs in Urban Agglomeration Based on Generalized Cost by Min Yue, Shu-Hong Ma, Wei Zhou, Xi-Fang Chen

“…The optimal trip chain can be obtained through a value iteration algorithm. In the case study, multimodal transfer trip chains of different types between Beijing Capital International Airport and Beijingxi Station in Beijing-Tianjin-Hebei urban agglomeration were constructed by MDP to compare the optimal trip chains of various groups. …”
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Improving ICP-Based Scanning Sonar Image Matching Performance Through Height Estimation of Feature Point Using Shaded Area by Gwonsoo Lee, Sukmin Yoon, Yeongjun Lee, Jihong Lee

“…This study presents an innovative method for estimating the height of feature points through shaded area analysis, to enhance the performance of iterative closest point (ICP)-based algorithms for matching scanning sonar images. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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