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arXiv 2024年

作者： Li, Mingyuan Jia, Tong Wang, Hao Ma, Bowen Lin, Shuyang Cai, Da Chen, Dongyue College of Information Science and Engineering Northeastern University Liaoning Shenyang110819 China Foshan Graduate School of Innovation Northeastern University Guangdong Foshan528311 China Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Liaoning Shenyang110819 China

Prohibited item detection in X-ray images is one of the most essential and highly effective methods widely employed in various security inspection scenarios. Considering the significant overlapping phenomenon in X-ray prohibited item images, we propose an Anti-Overlapping DETR (AO-DETR) based on one of the state-of-the-art general object detectors, DINO. Specifically, to address the feature coupling issue caused by overlapping phenomena, we introduce the Category-Specific One-to-One Assignment (CSA) strategy to constrain category-specific object queries in predicting prohibited items of fixed categories, which can enhance their ability to extract features specific to prohibited items of a particular category from the overlapping foreground-background features. To address the edge blurring problem caused by overlapping phenomena, we propose the Look Forward Densely (LFD) scheme, which improves the localization accuracy of reference boxes in mid-to-high-level decoder layers and enhances the ability to locate blurry edges of the final layer. Similar to DINO, our AO-DETR provides two different versions with distinct backbones, tailored to meet diverse application requirements. Extensive experiments on the PIXray and OPIXray datasets demonstrate that the proposed method surpasses the state-of-the-art object detectors, indicating its potential applications in the field of prohibited item detection. The source code will be released at https://***/Limingyuan001/AO-DETR. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Open-Vocabulary X-ray Prohibited Item Detection via Fine-tuning CLIP

arXiv

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arXiv 2024年

作者： Lin, Shuyang Jia, Tong Wang, Hao Ma, Bowen Li, Mingyuan Chen, Dongyue The College of Information Science and Engineering Northeastern University Liaoning Shenyang110819 China The Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Liaoning Shenyang110819 China The Foshan Graduate School of Innovation Northeastern University Guangdong Foshan528311 China

X-ray prohibited item detection is an essential component of security check and categories of prohibited item are continuously increasing in accordance with the latest laws. Previous works all focus on close-set scenarios, which can only recognize known categories used for training and often require time-consuming as well as labor-intensive annotations when learning novel categories, resulting in limited real-world applications. Although the success of vision-language models (e.g. CLIP) provides a new perspectives for open-set X-ray prohibited item detection, directly applying CLIP to X-ray domain leads to a sharp performance drop due to domain shift between X-ray data and general data used for pre-training CLIP. To address aforementioned challenges, in this paper, we introduce distillation-based open-vocabulary object detection (OVOD) task into X-ray security inspection domain by extending CLIP to learn visual representations in our specific X-ray domain, aiming to detect novel prohibited item categories beyond base categories on which the detector is trained. Specifically, we propose X-ray feature adapter and apply it to CLIP within OVOD framework to develop OVXD model. X-ray feature adapter containing three adapter submodules of bottleneck architecture, which is simple but can efficiently integrate new knowledge of X-ray domain with original knowledge, further bridge domain gap and promote alignment between X-ray images and textual concepts. Extensive experiments conducted on PIXray and PIDray datasets demonstrate that proposed method performs favorably against other baseline OVOD methods in detecting novel categories in X-ray scenario. It outperforms previous best result by 15.2 AP50 and 1.5 AP50 on PIXray and PIDray with achieving 21.0 AP50 and 27.8 AP50 respectively. Furthermore, our model can be directly transferred to different X-ray datasets without fine-tuning, verifying its generalization ability. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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The universal crossover from thermodynamics and dynamics of supercritical RN-AdS black hole

arXiv

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arXiv 2025年

作者： Zhao, Zi-Qiang Nie, Zhang-Yu Zhang, Jing-Fei Zhang, Xin College of Sciences Northeastern University Shenyang110819 China Center for Gravitation and Astrophysics Kunming University of Science and Technology Kunming650500 China Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

We study the properties of supercritical Reissner-Nordström Anti-de Sitter (RN-AdS) black holes in the extended phase space with the pressure defines as the cosmological constant. Supercritical black holes exist in the region where both temperature and pressure exceed the critical point, known as the supercritical region. The conventional view states that black holes in this regime are indistinguishable between large and small phases. However, recent research reveals that the supercritical regime exhibits universal gas-like and liquid-like phase separation, which shed light on the study on the supercritical region of RN-AdS black holes in the extended phase space. In this work, we calculate the thermodynamic potential and quasinormal modes (QNMs) of RN-AdS black holes, and identify transition curves between two different states in supercritical region using thermodynamic and dynamic methods. On one hand, we find the thermodynamic crossover curve (Widom line) by defining the scaled variance Ω (a higher-order derivative of Gibbs free energy). On the other hand, we identify the dynamic crossover curve (Frenkel line) by analyzing transitions between distinct QNM decay modes. Copyright © 2025, The Authors. All rights reserved.

关键词： Gibbs free energy

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Probing a polymerized black hole with the frequency shifts of photons

引用

Physical Review D 2023年第6期107卷 064019-064019页

作者： Qi-Ming Fu Xin Zhang Key Laboratory of Cosmology and Astrophysics (Liaoning Province) College of Sciences Northeastern University Shenyang 110819 China Institute of Physics Shaanxi University of Technology Hanzhong 723000 China Key Laboratory of Data Analytics and Optimization for Smart Industry (Ministry of Education) Northeastern University Shenyang 110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang 110819 China

As is well-known, black hole plays an important role in probing the quantum effects of gravity in the strong-field regime. In this paper, we focus on a polymerized black hole and investigate the quantum effects on the redshift, blueshift, and gravitational redshift of photons emitted by massive particles revolving around this black hole. With a general relativistic formalism, we obtain two elegant and concise expressions for the mass of the black hole and the quantum parameter in terms of few direct observables, and find that all the frequency shifts of photons decrease with the quantum parameter. By expanding the total frequency shift for large orbit of the emitter, low peculiar redshift, and small azimuthal angle, we find that the leading contributions to the frequency shift are originated from the kinematic shift and peculiar shift, and the quantum effects make a negligible contribution. In addition, we study the effects of the plasma on the redshift/blueshift for the first time, and conclude that the presence of plasma results in the decrease of the redshift/blueshift.

关键词： Alternative gravity theories Loop quantum gravity

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Measuring cosmic curvature with non-CMB observations

arXiv

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arXiv 2024年

作者： Wu, Peng-Ju Zhang, Xin School of Physics Ningxia University Yinchuan750021 China Department of Physics College of Sciences Northeastern University Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

The cosmic curvature ΩK is an important parameter related to the inflationary cosmology and the ultimate fate of the universe. In this work, we adopt the non-CMB observations to constrain ΩK in the ΛCDM model and its extensions. The DESI baryon acoustic oscillation, DES type Ia supernova, cosmic chronometer, and strong gravitational lensing time delay data are considered. We find that the data combination favors an open universe in the ΛCDM model, specifically ΩK = 0.108 }0.056 at the 1σ confidence level, which is in 2.6σ tension with the Planck CMB result supporting our universe being slightly closed. In the ΛCDM extensions, the data combination is consistent with a spatially flat universe. However, the central value of ΩK is positive and has a significant deviation from zero. We adopt the Akaike information criterion to compare different cosmological models. The result shows that non-flat models fit the observational data better that the flat ΛCDM model, which adds evidence to the argument that flat ΛCDM is not the ultimate model of cosmology. Copyright © 2024, The Authors. All rights reserved.

关键词： Cosmology

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Analytical modeling of the one-dimensional power spectrum of 21-cm forest based on a halo model method

arXiv

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arXiv 2024年

作者： Shao, Yue Sun, Tian-Yang Zhao, Meng-Lin Zhang, Xin Liaoning Key Laboratory of Cosmology and Astrophysics College of Sciences Northeastern University Shenyang110819 China Theoretical Physics Division Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China MOE Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang110819 China

The 21-cm forest, composed of spectral absorption features from high-redshift background radio sources, provides a unique probe for studying small-scale structures during the epoch of reionization. It is particularly sensitive to detecting small-scale structures and early heating processes. Despite the rich information contained in the 21-cm forest signal, the complexity of directly modeling the signal has led to a lack of effective analytical models. However, the one-dimensional (1D) power spectrum of the 21-cm forest contains valuable information about the matter power spectrum, making analytical modeling feasible. This work employs an analytical modeling approach based on the halo model, which links the distribution of matter to dark matter halos, allowing for effective predictions of cosmic structure formation and its impact on the 21-cm signal. By considering various parameter scenarios within the halo model framework, particularly different dark matter particle masses and varying levels of cosmic heating, we can capture the complexities of small-scale structures and make the 1D power spectrum modeling applicable across a wide range of parameters. This method not only enhances our understanding of the 21-cm forest signal but also provides theoretical support for future observational data. Observing the 21-cm forest with large radio telescopes, such as the Square Kilometre Array, is anticipated to enable simultaneous exploration of dark matter properties and the heating history of the early universe. Copyright © 2024, The Authors. All rights reserved.

关键词： Dark Matter

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Motion-to-Matching: A Mixed Paradigm for 3D Single Object Tracking

arXiv

引用

arXiv 2023年

作者： Li, Zhiheng Lin, Yu Cui, Yubo Li, Shuo Fang, Zheng Faculty of Robot Science and Engineering Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Shenyang110819 China

3D single object tracking with LiDAR points is an important task in the computer vision field. Previous methods usually adopt the matching-based or motion-centric paradigms to estimate the current target status. However, the former is sensitive to the similar distractors and the sparseness of point clouds due to relying on appearance matching, while the latter usually focuses on short-term motion clues (eg. two frames) and ignores the long-term motion pattern of target. To address these issues, we propose a mixed paradigm with two stages, named MTM-Tracker, which combines motion modeling with feature matching into a single network. Specifically, in the first stage, we exploit the continuous historical boxes as motion prior and propose an encoder-decoder structure to locate target coarsely. Then, in the second stage, we introduce a feature interaction module to extract motion-aware features from consecutive point clouds and match them to refine target movement as well as regress other target states. Extensive experiments validate that our paradigm achieves competitive performance on large-scale datasets (70.9% in KITTI and 51.70% in NuScenes). The code will be open soon at https://***/LeoZhiheng/ ***. Copyright © 2023, The Authors. All rights reserved.

关键词： Large dataset

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Probing the sign-changeable interaction between dark energy and dark matter with DESI baryon acoustic oscillations and DES supernovae data

arXiv

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arXiv 2025年

作者： Li, Tian-Nuo Du, Guo-Hong Li, Yun-He Wu, Peng-Ju Jin, Shang-Jie Zhang, Jing-Fei Zhang, Xin Liaoning Key Laboratory of Cosmology and Astrophysics College of Sciences Northeastern University Shenyang110819 China School of Physics Ningxia University Yinchuan750021 China Department of Physics University of Western Australia PerthWA6009 Australia MOE Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

There is a possibility of interaction between dark energy and dark matter, and this interaction may also undergo a sign change during the evolution of the universe. In this paper, we utilize the latest observational data to constrain models of a sign-changeable interaction. The data we employ, in addition to the cosmic microwave background data, also encompass the first-year baryon acoustic oscillation data from DESI and the type Ia supernova data of the full 5-year observation from DES. To achieve high generality, we investigate four interacting dark energy (IDE) models with different forms of the interaction term Q: (i) IDE1 with Q = β(a)Hρde;(ii) IDE2 with Q = β(a)Hρc;(iii) IDE3 with Q = β(a)H0ρde;(iv) IDE4 with Q = β(a)H0ρc. From the analysis, we observe that β(z) > 0 at early times and β(z) Copyright © 2025, The Authors. All rights reserved.

关键词： Supernovae

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Cosmological search for sterile neutrinos after DESI 2024

arXiv

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arXiv 2025年

作者： Du, Guo-Hong Li, Tian-Nuo Wu, Peng-Ju Feng, Lu Zhou, Sheng-Han Zhang, Jing-Fei Zhang, Xin Liaoning Key Laboratory of Cosmology and Astrophysics College of Sciences Northeastern University Shenyang110819 China School of Physics Ningxia University Yinchuan750021 China College of Physical Science and Technology Shenyang Normal University Shenyang110034 China MOE Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

The question of whether the massive sterile neutrinos exist remains a crucial unresolved issue in both particle physics and cosmology. We explore the cosmological constraints on the massive sterile neutrinos using the latest observational data, including the baryon acoustic oscillations data from DESI, the cosmic microwave background data from Planck satellite and ACT, and the 5-year Type Ia supernova data and the 3-year weak-lensing data from DES. We search for the massive sterile neutrinos within the ΛCDM, wCDM, and w0waCDM models. Our analysis shows that when considering massive sterile neutrinos within the w0waCDM model, the combined datasets allow us to infer a non-zero sterile neutrino mass at approximately 2σ confidence level. Specifically, in the w0waCDM+Sterile model, the effective mass of sterile neutrinos and the effective number of relativistic species are constrained to be meffν,sterile = 0.50+0.33−0.27 eV and Neff = 3.076+0.011−0.017, respectively. However, the ΛCDM+Sterile and wCDM+Sterile models could not provide evidence supporting the existence of massive sterile neutrinos. Copyright © 2025, The Authors. All rights reserved.

关键词： Cosmology

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A learning-based solution method for practical slab allocation problem in multiple hot rolling lines

A I I E Transactions

引用

A I I E Transactions 2024年第9期56卷

作者： Ying Meng Qingxin Guo Qingyang Wang Haichao Wang a National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang Chinab Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education China b Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education Chinac Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang China b Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education Chinad Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Northeastern University Shenyang China

Steel slabs are key in-process products in the steel production process. The slab allocation problem is to allocate slabs to suitable orders by considering complicated technical restrictions and multiple management requirements. In practice, thousands of slabs in multiple production lines should be allocated to orders. Due to the complexity and large scale of the problem, it takes planners a long time to make decisions, and the obtained allocation schemes are usually ineffective because of the myopic nature of the rule-based methods. In this article, we present a learning-based solution method for solving a practical slab allocation problem in multiple hot rolling lines. We formulate the problem as an integer programming model, then a data-based method is adopted to evaluate the mismatching cost between slabs and orders. To effectively solve the large-sized problem, a learning-based decomposition strategy is proposed to decompose the original problem into several small-sized subproblems. Then, a branch-and-price algorithm is proposed to optimally solve the subproblems. To further speed up the solution process, a primal heuristics based on column generation is designed to solve the large-sized subproblems. The solution methods have been implemented in a steel company and effectively increased slab utilization and reduced production cost.

关键词： Slab allocation combinatorial optimization branch-and-price learning

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