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arXiv 2024年

作者： Lo, Li-Yu Li, Boyang Wen, Chih-Yung Chang, Ching-Wei AIRo-LAB Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Kowloon Hong Kong Research Centre for Unmanned Autonomous System The Hong Kong Polytechnic University Kowloon Hong Kong School of Engineering The University of Newcastle CallaghanNSW2308 Australia Hong Kong Center for Construction Robotics The Hong Kong University of Science and Technology New Territories Hong Kong

In this work, we propose a dynamic landing solution without the need for onboard exteroceptive sensors and an expensive computation unit, where all localization and control modules are carried out on the ground in a non-inertial frame. Our system starts with a relative state estimator of the aerial robot from the perspective of the landing platform, where the state tracking of the UAV is done through a set of onboard LED markers and an on-ground camera;the state is expressed geometrically on manifold, and is returned by Iterated Extended Kalman filter (IEKF) algorithm. Subsequently, a motion planning module is developed to guide the landing process, formulating it as a minimum jerk trajectory by applying the differential flatness property. Considering visibility and dynamic constraints, the problem is solved using quadratic programming, and the final motion primitive is expressed through piecewise polynomials. Through a series of experiments, the applicability of this approach is validated by successfully landing 18 cm × 18 cm quadrotor on a 43 cm × 43 cm platform, exhibiting performance comparable to conventional methods. Finally, we provide comprehensive hardware and software details to the research community for future reference. © 2024, CC BY.

关键词： Motion planning

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TSU: A Two-stage update approach for persistent skiplist 13th

TSU: A Two-stage update approach for persistent skiplist

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13th Conference on Advanced Computer Architecture, ACA 2020

作者： Wang, Shucheng Cao, Qiang Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology School of Computer Science and Technology Huazhong University of Science and Technology Ministry of Education of China Wuhan China

ISBN: (纸本)9789811581342

Skiplist, a widely used in-memory index structure, could incur crash inconsistency when running on emerging NVRAM (Non-Volatile Random Access Memory). Logging or strict serialization can ensure crash consistency at the cost of severe performance degradation. In this paper, we propose TSU, a Two-stage update approach to improve the performance of persistent skiplist while preserve crash consistency. TSU exploits space locality of skiplist and atomic write of NVRAM, thus effectively reducing expensive cache line flush (clflush) operations. To this end, we category all four crash inconsistent states into two types: recoverable and unrecoverable. TSU could guarantee the crash state is recoverable by constraining the memory access order for insertion and deletion. We further design a persistency algorithm to reduce clflush by preserving the memory persistent order of skiplist update. In addition, we develop a concurrent search for TSU. The evaluation result shows that TSU can reduce cache line flush with up to 47.6%, and decrease the average request latency by up to 36% for insertions compared to the strict serialization. © Springer Nature Singapore Pte Ltd 2020.

关键词： Cache memory

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Cosh-DiT: Co-Speech Gesture Video Synthesis via Hybrid Audio-Visual Diffusion Transformers

arXiv

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arXiv 2025年

作者： Sun, Yasheng Xu, Zhiliang Zhou, Hang Guan, Jiazhi Yang, Quanwei Wang, Kaisiyuan Liang, Borong Li, Yingying Feng, Haocheng Wang, Jingdong Liu, Ziwei Hideki, Koike Center of Excellence for Generative AI King Abdullah University of Science and Technology Jeddah Thuwal23955-6900 Saudi Arabia Baidu VIS Shangdi 10th Street Beijing100085 China School of Computing Tokyo Institute of Technology Ookayama Meguro-ku Tokyo152-8550 Japan Department of Computer Science and Technology Tsinghua University Haidian District Shuangqing Road Beijing100084 China Department of Electronic Engineering and Information Science University of Science and Technology of China Baohe District JinZhai Road Anhui Hefei230026 China S-Lab Nanyang Technological University 50 Nanyang Avenue 639798 Singapore

Co-speech gesture video synthesis is a challenging task that requires both probabilistic modeling of human gestures and the synthesis of realistic images that align with the rhythmic nuances of speech. To address these challenges, we propose Cosh-DiT, a Co-speech gesture video system with hybrid Diffusion Transformers that perform audio-to-motion and motion-to-video synthesis using discrete and continuous diffusion modeling, respectively. First, we introduce an audio Diffusion Transformer (Cosh-DiT-A) to synthesize expressive gesture dynamics synchronized with speech rhythms. To capture upper body, facial, and hand movement priors, we employ vector-quantized variational autoencoders (VQ-VAEs) to jointly learn their dependencies within a discrete latent space. Then, for realistic video synthesis conditioned on the generated speech-driven motion, we design a visual Diffusion Transformer (Cosh-DiT-V) that effectively integrates spatial and temporal contexts. Extensive experiments demonstrate that our framework consistently generates lifelike videos with expressive facial expressions and natural, smooth gestures that align seamlessly with speech. © 2025, CC BY.

关键词： Vector quantization

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Parasitic Beam Steering Antenna loaded with Shorting Vias

Parasitic Beam Steering Antenna loaded with Shorting Vias

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International Symposium on Antennas and Propagation (ISAP)

作者： Rabiatuladawiah Akhbar Nurulazlina Ramli Hajar Ja’Afar Rina Abdullah Nurul Huda Abd Rahman Fatemeh Sadeghikia Centre of Foundation Studies Universiti Teknologi MARA Dengkil Selangor Malaysia Centre for Advanced Electrical and Electronic System (CAEES) Faculty of Engineering Built Environment and Information Technology SEGi University Selangor Malaysia School of Electrical Engineering Universiti Teknologi MARA Dungun Terengganu Malaysia Antenna Research Centre School of Electrical Engineering Universiti Teknologi MARA Shah Alam Selangor ARI Ministry of Science Research and Technology Wireless Telecommunication Group Iran

This paper presents a beam steering patch antenna with two parasitic elements loaded with shorting vias. The proposed antenna consists of a circular driven patch and two circular parasitic elements placed adjacent to the driven patch (upper left and below right). The mutual coupling effect between both driven and parasitic has managed to steer the beam. The parasitic elements electrically shorten the ground plane through shorting vias. ON state condition indicates the activation of the parasitic elements which required a shorting vias connected to the ground plane and vice versa. Based on the ON/OFF state of the shorting vias loaded parasitic elements, the proposed antenna able to steer the main beam to different directions to -7°, 0°, 5° and 12° at the resonant frequency of 3.5 GHz with maximum gain of 7.73 dBi.

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COVIDX: Computer-aided diagnosis of COVID-19 and its severity prediction with raw digital chest X-ray scans

引用

Quantitative Biology 2022年第2期10卷 208-220页

作者： Wajid Arshad Abbasi Syed Ali Abbas Saiqa Andleeb Maryum Bibi Fiaz Majeed Abdul Jaleel Muhammad Naveed Akhtar Computational Biology and Data Analysis Lab Department of Computer Sciences&Information TechnologyKing Abdullah CampusUniversity of Azad Jammu&KashmirMuzaffarabadAJ&K 13100Pakistan Biotechnology Lab Department of ZoologyKing Abdullah CampusUniversity of Azad Jammu&KashmirMuzaffarabadAJ&K 13100Pakistan Department of Software Engineering University of GujratGujrat 50700Pakistan Department of Computer Science (RCET)UETLahore 54000Pakistan Computational and Internet Services Division Pakistan Institute of Engineering and Applied Sciences(PIEAS)Islamabad 44000Pakistan

Background: Coronavirus disease (COVID-19) is a contagious infection caused by severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) and it has infected and killed millions of people across the ***: In the absence or inadequate provision of therapeutic treatments of COVID-19 and the limited convenience of diagnostic techniques, there is a necessity for some alternate spontaneous screening systems that can easily be used by the physicians to rapidly recognize and isolate the infected patients to circumvent onward surge. A chest X-ray (CXR) image can effortlessly be used as a substitute modality to diagnose the ***: In this study, we present an automatic COVID-19 diagnostic and severity prediction system (COVIDX) that uses deep feature maps of CXR images along with classical machine learning algorithms to identify COVID-19 and forecast its severity. The proposed system uses a three-phase classification approach (healthy vs unhealthy, COVID-19 vs pneumonia, and COVID-19 severity) using different conventional supervised classification ***: We evaluated COVIDX through 10-fold cross-validation, by using an external validation dataset, and also in a real setting by involving an experienced radiologist. In all the adopted evaluation settings, COVIDX showed strong generalization power and outperforms all the prevailing state-of-the-art methods designed for this ***: Our proposed method (COVIDX), with vivid performance in COVID-19 diagnosis and its severity prediction, can be used as an aiding tool for clinical physicians and radiologists in the diagnosis and follow-up studies of COVID-19 infected ***: We made COVIDX easily accessible through a cloud-based webserver and python code available at https://***/view/wajidarshad/software and https://***/wajidarshad/covidx, respectively.

关键词： coronavirus COVID-19 radiology machine learning chest X-ray contagious infection

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GaitGCI: Generative Counterfactual Intervention for Gait Recognition

arXiv

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arXiv 2023年

作者： Dou, Huanzhang Zhang, Pengyi Su, Wei Yu, Yunlong Lin, Yining Li, Xi College of Computer Science & Technology Zhejiang University China College of Information Science & Electronic Engineering Zhejiang University China SupreMind China Shanghai Institute for Advanced Study Zhejiang University China Shanghai Ai Laboratory China Zhejiang - Singapore Innovation and Ai Joint Research Lab China

Gait is one of the most promising biometrics that aims to identify pedestrians from their walking patterns. However, prevailing methods are susceptible to confounders, resulting in the networks hardly focusing on the regions that reflect effective walking patterns. To address this fundamental problem in gait recognition, we propose a Generative Counterfactual Intervention framework, dubbed GaitGCI, consisting of Counterfactual Intervention Learning (CIL) and Diversity-Constrained Dynamic Convolution (DCDC). CIL eliminates the impacts of confounders by maximizing the likelihood difference between factual/counterfactual attention while DCDC adaptively generates sample-wise factual/counterfactual attention to efficiently perceive the sample-wise properties. With matrix decomposition and diversity constraint, DCDC guarantees the model to be efficient and effective. Extensive experiments indicate that proposed GaitGCI: 1) could effectively focus on the discriminative and interpretable regions that reflect gait pattern;2) is model-agnostic and could be plugged into existing models to improve performance with nearly no extra cost;3) efficiently achieves state-of-the-art performance on arbitrary scenarios (in-the-lab and in-the-wild). Copyright © 2023, The Authors. All rights reserved.

关键词： Gait analysis

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Pressure-Dependent Compressibility of K2x(Co3)2 (X=Ca, Mg) Under High Pressure

SSRN

引用

SSRN 2023年

作者： Tian, Haitao Li, Yuhong Zhang, Qiang Su, Ningning Sun, Jinlu Xiao, Ningru Liu, Yuyao Zhang, Jianxin Liu, Hongwei Li, Yuqiang Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems School of Electronics and Information Engineering Tiangong University Tianjin300387 China Key Laboratory of Smart Grid of Ministry of Education School of Electrical and Information Engineering Tianjin University Tianjin300072 China School of Semiconductor and Physics North University of China Taiyuan030051 China Engineering Research Center of High Power Solid State Lighting Application System of Ministry of Education Tiangong University Tianjin300387 China School of Physical Science and Technology Tiangong University Tianjin300387 China

The high-pressure phase transition behaviors and pressure-dependent compressibility are investigated on K2X(CO3)2 using first-principles calculation from ambient pressure to 30 GPa. The reversible structural phase transitions of K2X(CO3)2 are determined based on enthalpy difference and cell volume collapses. The pressure point of structural phase transitions of K2Ca(CO3)2 is obtained at around 3.3 GPa and 10.3 GPa, while that is found at about 6.2 GPa and 22.6 GPa for K2Mg(CO3)2. Compared with the high axial rigidity of C-O bonds in [CO3] groups, the Ca+ and Mg+ coordination polyhedron show much more compressible. The displacement behavior of the Ca+ and Mg+ coordination polyhedron occurs simultaneously with the rotation behavior of [CO3] groups during compression, and reverses induced by the structural phase transition. © 2023, The Authors. All rights reserved.

关键词： Crystal structure

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Learning from Symmetry: Meta-Reinforcement Learning with Symmetrical Behaviors and Language Instructions

arXiv

引用

arXiv 2022年

作者： Yao, Xiangtong Bing, Zhenshan Zhuang, Genghang Chen, Kejia Zhou, Hongkuan Huang, Kai Knoll, Alois School of Computation Information and Technology Technical University of Munich Germany School of Computer Science and Engineering Sun Yat-sen University China Pazhou Lab Guangzhou510330 China

Meta-reinforcement learning (meta-RL) is a promising approach that enables the agent to learn new tasks quickly. However, most meta-RL algorithms show poor generalization in multi-task scenarios due to the insufficient task information provided only by rewards. Language-conditioned meta-RL improves the generalization capability by matching language instructions with the agent’s behaviors. While both behaviors and language instructions have symmetry, which can speed up human learning of new knowledge. Thus, combining symmetry and language instructions into meta-RL can help improve the algorithm’s generalization and learning efficiency. We propose a dual-MDP meta-reinforcement learning method that enables learning new tasks efficiently with symmetrical behaviors and language instructions. We evaluate our method in multiple challenging manipulation tasks, and experimental results show that our method can greatly improve the generalization and learning efficiency of meta-reinforcement learning. Videos are available at https://***/symmetry/. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

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Variance-Based Sensitivity Analysis Reveals Relationships between Optimal Operation Decisions and Hydrometeorology Variables for Hydro-Photovoltaic Hybrid Power systems

SSRN

引用

SSRN 2023年

作者： Yang, Zhikai Liu, Pan Xia, Qian Cheng, Lei Li, He State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan University Wuhan430072 China Hubei Provincial Key Lab of Water System Science for Sponge City Construction Wuhan430072 China Hubei Water Resources and Hydropower Science and Technology Promotion Center Hubei Water Resources Research Institute Wuhan430072 China School of Water Conservancy Engineering Zhengzhou University Zhengzhou450001 China

The complementary operation is an essential management mode to ensure effective power benefits for hydro-photovoltaic (PV) hybrid power systems. The intrinsic dynamics connecting optimal decision making, hydrometeorology variables and hybrid power system characteristics are complex for the hydro-PV hybrid power system, and the operating rules are a classic management tool for generalizing this relationship and guiding the power system operation. However, the functional forms of operating rules are often determined in a subjective way, and this subjectivity probably results in poor operating performance in practical making operation decisions. For dealing with this challenge, we try to use variance-based sensitivity analysis to diagnose the influence of hydro-meteorological factors on the optimal decision-making, and identify effective operating rule form to obtain robust operation benefits. China’s Longyangxia hydro-PV hybrid power system was selected as the study site. Our analysis revealed that (1) The optimal operation decisions are dominated by the initial total potential stored energy (SE) that is the main controlling factor, the input of potential energy (IE), and their interaction are secondary controlling factors;(2) The SE and IE should be explicitly expressed as separate items in the complementary operating rules, rather than being combined into one comprehensive item available energy (AE);(3) The derived complementary operating rules are effective in improving system benefits compared with traditional complementary operating rules, where the annual power generation and reliability are enhanced by an average of 1.59% and 1.71% under various climate scenarios, respectively. These findings are meaningful for understanding and deriving robust operation of the hybrid power systems under changing environments. © 2023, The Authors. All rights reserved.

关键词： Potential energy

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Dual-Source CBCT for Larger Longitudinal Coverage: system Design and Image Reconstruction

Dual-Source CBCT for Larger Longitudinal Coverage: System De...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Xusheng Zhang Tianling Lyu Yijie Shi Xinyun Zhong Zhan Wu Yan Xi Shijie Wang Yang Chen Wentao Zhu School of Software Southeast University Nanjing China Zhejiang Lab Hangzhou China Laboratory of Image Science and Technology the School of Computer Science and Engineering Southeast University Nanjing China First-Imaging Tech. Shanghai China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing the Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Nanjing China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The application of CBCT systems in intraoperative environments has become increasingly common, but concurrent CBCT systems are unsuitable for situations that require a large longitudinal imaging FoV, such as orthopedics. To increase longitudinal coverage, we developed a dual-source CBCT (DS-CBCT) system in which two ray sources are symmetrically placed along the central plane. After further analyzing its geometric characteristics, we propose an analytical reconstruction algorithm termed DT-FDK specialized for DS-CBCT, which combines cone-beam rebinning and two rays with smaller cone angles among the four conjugate rays to further suppress cone beam artifacts. The system design and reconstruction algorithm are tested on both simulated and real-scanned data. Results show that the DS-CBCT can expand the effective imaging volume by 37.1% compared to single-source CBCT systems. The reconstructed images by DT-FDK also show improved image quality compared to traditional reconstruction algorithms.

关键词： Image quality Orthopedic surgery Imaging Reconstruction algorithms engineering in medicine and biology Image reconstruction system analysis and design

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