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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Nite, Sandra B. Erdogan, Niyazi Gray, Trenton Lee, Seonhu Texas A&m University High Performance Research Computing College StationTX United States Educational Achievement College of Engineering Texas A&m University College StationTX United States Texas A&m University Department of Computer Science and Engineering College StationTX United States Allen Academy BryanTX United States

ISBN: (纸本)9798350336429

Spatial awareness, spatial, reasoning, spatial visualization, and spatial abilities are various terms all related to various ideas or aspects of spatial ability. From infancy throughout our life spans spatial awareness is embedded in our lives in ways we do not realize. Spatial reasoning is one of the foundational key concepts in mathematics and has been shown to be highly correlated with success in mathematics overall. higher levels of spatial reasoning are critical in many STEM fields. However, it is an area in which students struggle for competency. Studies have shown that boys generally are better than girls at spatial relationships, beginning at an early age. It is not clear how much is part of the difference in the ways the brain works and how much is part of the environment and experiences of children at play. However, research shows that spatial abilities can definitely be intentionally developed and improved. Thus, children of all ages could benefit from more intentional experiential learning in areas of spatial ability. Assessing various aspects of spatial reasoning is complex, but there are research-based types of activities that support the development of spatial abilities. Our theoretical framework is based on David Kolb's experiential learning theory. In this framework, a holistic approach is envisioned, recognizing the combination of cognition, environmental factors, and emotions in learning experiences. In a week-long summer camp, activities were focused on various aspects of spatial ability. These included flying drones, paper engineering through popups, and a spatial drawing activity. Each of the activities will be discussed in the context of the various aspect of spatial ability development and the importance of those aspects in STEM fields. Students completed a survey about how important they believed spatial skills were in science, mathematics, technology, and engineering. They reflected on the camp activities and their perception of the use of

关键词： spatial reasoning STEM camp

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Self-Supervised Multi-LiDAR Object View Generation Using Single LiDAR 29

Self-Supervised Multi-LiDAR Object View Generation Using Sin...

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29th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2023

作者： Kuo, Yi-Hung Shih, Chi-Sheng Lin, Hsiang-Jui Hung, Shih-Hao Graduate Institute of Networking and Multimedia National Taiwan University Taipei Taiwan National Taiwan University Department of Computer Science and Information Engineering Taipei Taiwan High Performance and Scientific Computing Center National Taiwan University Taipei Taiwan Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350337860

3D object detection using point clouds has been widely used for self-driving vehicles, roadside vehicle detection, and tracking. However, the detection accuracy using single-LiDAR-scanned point clouds suffers from occlusion to have accurate bounding boxes. Several previous works proposed compensating for the point cloud to improve 3D detection. This work designed a self-labeling method that exploits the characteristics of multiple LiDAR-scanned point clouds collected on roadside units. This labeling method allows the point completion model to be trained without human-labeled bounding boxes. The point completion model uses the single-LiDAR-scanned point cloud as input and uses the extracted object points from the fused point cloud as the training target. The voxel IoU and recall of the point-completed point clouds increased by 17% and 22% compared to that of the raw point clouds. Additionally, the detection performance of DBSCAN, i.e., 3D AP@IoU=0.25 increased by 20% after applying the point completion algorithm. © 2023 IEEE.

关键词： Roadsides

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AIF-SFDA: Autonomous Information Filter-driven Source-Free Domain Adaptation for Medical Image Segmentation

arXiv

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arXiv 2025年

作者： Li, Haojin Li, Heng Chen, Jianyu Zhong, Rihan Niu, Ke Fu, Huazhu Liu, Jiang Research Institute of Trustworthy Adaptive Systems Southern University of Science and Technology China Department of Computer Science and Engineering Southern University of Science and Technology China Beijing Information Science & Technology University China Institute of High Performance Computing Agency for Science Technology and Research Singapore

Decoupling domain-variant information (DVI) from domain-invariant information (DII) serves as a prominent strategy for mitigating domain shifts in the practical implementation of deep learning algorithms. However, in medical settings, concerns surrounding data collection and privacy often restrict access to both training and test data, hindering the empirical decoupling of information by existing methods. To tackle this issue, we propose an Autonomous Information Filter-driven Source-free Domain Adaptation (AIF-SFDA) algorithm, which leverages a frequency-based learnable information filter to autonomously decouple DVI and DII. Information Bottleneck (IB) and Self-supervision (SS) are incorporated to optimize the learnable frequency filter. The IB governs the information flow within the filter to diminish redundant DVI, while SS preserves DII in alignment with the specific task and image modality. Thus, the autonomous information filter can overcome domain shifts relying solely on target data. A series of experiments covering various medical image modalities and segmentation tasks were conducted to demonstrate the benefits of AIF-SFDA through comparisons with leading algorithms and ablation studies. The code is available at https://***/JingHuaMan/AIF-SFDA. Copyright © 2025, The Authors. All rights reserved.

关键词： Image segmentation

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Promoting spintronic terahertz radiation via Tamm plasmon coupling

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Photonics Research 2023年第6期11卷 1057-1066页

作者： YUNQING JIANG HONGQING LI XIAOQIANG ZHANG FAN ZHANG YONG XU YONGGUANG XIAO FENGGUANG LIU ANTING WANG QIWEN ZHAN WEISHENG ZHAO School of Integrated Circuit Science and Engineering Hefei Innovation Research InsitituteBeihang UniversityBeijing 100191China Anhui High Reliability Chips Engineering Laboratory Hefei 230013China School of Materials Science and Engineering Xiangtan UniversityXiangtan 411105China Department of Optics and Optical Engineering University of Science and Technology of ChinaHefei 230026China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China

Spectral fingerprint and terahertz(THz)field-induced carrier dynamics demands the exploration of broadband and intense THz signal *** THz emitters(STEs),with high stability,a low cost,and an ultrabroad bandwidth,have been a hot topic in the field of THz *** of the main barriers to their practical application is lack of an STE with strong radiation ***,through the combination of optical physics and ultrafast photonics,the Tamm plasmon coupling(TPC)facilitating THz radiation is realized between spin THz thin films and photonic crystal *** results show that the spectral absorptance can be increased from 36.8%to 94.3%for spin THz thin films with *** coupling with narrowband resonance not only improves the optical-to-spin conversion efficiency,but also guarantees THz transmission with a negligible loss(~4%)for the photonic crystal *** to the simulation,we prepared this structure successfully and experimentally realized a 264%THz radiation ***,the spin THz thin films with TPC exhibited invariant absorptivity under different polarization modes of the pump beam and weakening confinement on an obliquely incident pump *** approach is easy to implement and offers possibilities to overcome compatibility issues between the optical structure design and low energy consumption for ultrafast THz optospintronics and other similar devices.

关键词： pump polarization coupling

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Imputation with Inter-Series Information from Prototypes for Irregular Sampled Time Series

arXiv

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arXiv 2024年

作者： Yu, Zhihao Chu, Xu Ma, Liantao Wang, Yasha Zhu, Wenwu Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China School of Computer Science Peking University Beijing China Department of Computer Science Tsinghua University Beijing China National Engineering Research Center of Software Engineering Peking University Beijing China

Irregularly sampled time series are ubiquitous, presenting significant challenges for analysis due to missing values. Despite existing methods address imputation, they predominantly focus on leveraging intra-series information, neglecting the potential benefits that inter-series information could provide, such as reducing uncertainty and memorization effect. To bridge this gap, we propose PRIME, a Prototype Recurrent Imputation ModEl, which integrates both intra-series and inter-series information for imputing missing values in irregularly sampled time series. Our framework comprises a prototype memory module for learning inter-series information, a bidirectional gated recurrent unit utilizing prototype information for imputation, and an attentive prototypical refinement module for adjusting imputations. We conducted extensive experiments on three datasets, and the results underscore PRIME’s superiority over the state-of-the-art models by up to 26% relative improvement on mean square error. Our code is available at https://***/yzhHoward/PRIME. Copyright © 2024, The Authors. All rights reserved.

关键词： Mean square error

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REFROM: Responsive, Energy-Efficient Frame Rendering for Mobile Devices

REFROM: Responsive, Energy-Efficient Frame Rendering for Mob...

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International Symposium on Low Power Electronics and Design (ISLPED)

作者： Tsung-Yen Hsu Yi-Shen Chen Yun-Chih Chen Yuan-Hao Chang Tei-Wei Kuo Department of Computer Science and Information Engineering National Taiwan University Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Institute of Information Science Academia Sinica Mohamed bin Zayed University of Artificial Intelligence High Performance and Scientific Computing Center National Taiwan University

The increasing demand for high-quality graphics on mobile devices necessitates a high frame rate for display refresh. However, current process scheduling and memory management policies fail to consider the computation demands of frame rendering because they are optimized for saving energy and resource utilization. This leads to unresponsive displays for mobile users due to rendering delays. Accurately estimating computation demands is challenging for the mobile operating system, particularly under memory pressure, without display-specific semantics from user space. Moreover, the complexity of frame rendering makes it infeasible to schedule them with real-time policies. To address these issues, we propose a new framework called REFROM that utilizes a history-based frame time estimator to analyze frame time samples from UI threads and predict the computation requirements of upcoming frames. Experimental results demonstrate that REFROM reduces the number of delayed frames by up to 40% and improves up to 4% energy efficiency compared to the existing approaches.

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FishEye8K: A Benchmark and Dataset for Fisheye Camera Object Detection

FishEye8K: A Benchmark and Dataset for Fisheye Camera Object...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Gochoo, Munkhjargal Otgonbold, Munkh-Erdene Ganbold, Erkhembayar Hsieh, Jun-Wei Chang, Ming-Ching Chen, Ping-Yang Dorj, Byambaa Al Jassmi, Hamad Batnasan, Ganzorig Alnajjar, Fady Abduljabbar, Mohammed Lin, Fang-Pang United Arab Emirates University Department of Computer Science and Software Engineering United Arab Emirates United Arab Emirates University Emirates Center for Mobility Research United Arab Emirates National Yang Ming Chiao Tung University College of AI and Green Energy Taiwan University at Albany - State University of New York NY United States National Yang Ming Chiao Tung University Department of Computer Science Taiwan Mongolian University of Science and Technology Mongolia National Center for High-Performance Computing Taiwan

ISBN: (纸本)9798350302493

With the advance of AI, road object detection has been a prominent topic in computer vision, mostly using perspective cameras. Fisheye lens provides omnidirectional wide coverage for using fewer cameras to monitor road intersections, however with view distortions. To our knowledge, there is no existing open dataset prepared for traffic surveillance on fisheye cameras. This paper introduces an open FishEye8K benchmark dataset for road object detection tasks, which comprises 157K bounding boxes across five classes (Pedestrian, Bike, Car, Bus, and Truck). In addition, we present benchmark results of State-of-The-Art (SoTA) models, including variations of YOLOv5, YOLOR, YOLO7, and YOLOv8. The dataset comprises 8,000 images recorded in 22 videos using 18 fisheye cameras for traffic monitoring in Hsinchu, Taiwan, at resolutions of 1080×1080 and 1280×1280. The data annotation and validation process were arduous and time-consuming, due to the ultra-wide panoramic and hemispherical fisheye camera images with large distortion and numerous road participants, particularly people riding scooters. To avoid bias, frames from a particular camera were assigned to either the training or test sets, maintaining a ratio of about 70:30 for both the number of images and bounding boxes in each class. Experimental results show that YOLOv8 and YOLOR outperform on input sizes 640×640 and 1280×1280, respectively. The dataset will be available on the GitHub link with PASCAL VOC, MS COCO, and YOLO annotation formats. The FishEye8K benchmark will provide significant contributions to the fisheye video analytics and smart city applications. © 2023 IEEE.

关键词： Object detection

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Global scale solar energy harnessing: An advanced intra-hourly diffuse solar irradiance predicting framework for solar energy projects

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Neural Computing and Applications 2024年第18期36卷 10585-10598页

作者： El-kenawy, El-Sayed M. Bailek, Nadjem Bouchouicha, Kada Zerouali, Bilel Hassan, Muhammed A. Kuriqi, Alban Jamil, Basharat Colak, Ilhami Khalil, Adel Ibrahim, Abdelhameed Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura35111 Egypt Laboratory of Mathematics Modeling and Applications Department of Mathematics and Computer Science Faculty of Sciences and Technology Ahmed Draia University of Adrar Adrar01000 Algeria Energies and Materials Research Laboratory Faculty of Sciences and Technology University of Tamanghasset Tamanrasset10034 Algeria MEU Research Unit Middle East University Amman Jordan Adrar01000 Algeria Vegetal Chemistry-Water-Energy Laboratory Faculty of Civil Engineering and Architecture Department of Hydraulic Hassiba Benbouali University of Chlef Ouled Fares Chlef02180 Algeria Mechanical Power Engineering Department Faculty of Engineering Cairo University Giza12613 Egypt School of Architecture University of Waterloo 7 Melville St S CambridgeONN1S 2H4 Canada CERIS Instituto Superior Tecnico Universidade de Lisboa Lisbon Portugal Civil Engineering Department University for Business and Technology PristinaKosovo10000 High Temperature Processes Unit IMDEA Energy Institute Av. Ramón de La Sagra 3 Móstoles Madrid28935 Spain Faculty of Engineering and Architectures Nisantasi University Istanbul Turkey Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura35516 Egypt

Diffuse horizontal irradiance (DHI) forecasts are critical for adopting solar photovoltaic technology. Yet, they can lack reliability given the limited and uncertain meteorological data available for desert areas. This research develops a new sine cosine dipper throated optimization (SCDTO) technique, targeting DHI prediction even given such data constraints. SCDTO uniquely hybridizes sine cosine metaheuristics, adept at exploration, with dipper throat optimization, providing focused exploitation. This hybridization aims to create a robust ensemble model capable of delivering reliable DHI predictions despite climatic uncertainty. The ensemble model, employing various input combinations, was rigorously evaluated across multiple meteorological stations. The SCDTO algorithm exhibited remarkable performance improvements, yielding substantial reductions exceeding 93% in root mean squared error and 98% in mean absolute error at key stations in Morocco, including Tan-Tan, Zagora, Erfoud, and Oujda. Comparative analyses against established optimization algorithms consistently underscored the superior predictive capabilities of SCDTO. Visualizations, including box plots and histograms, demonstrated SCDTO’s efficacy in minimizing prediction errors, particularly for Tan-Tan, Zagora, and Erfoud stations. Also, statistical validation through one-way analysis of variance (ANOVA) further affirmed the significance of the proposed SCDTO method. Therefore, this hybrid metaheuristic optimization enables more accurate DHI predictions from limited meteorological data. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Solar energy

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Image Reconstruction for live 3D Multifocus Super-Resolution Microscopy

Image Reconstruction for live 3D Multifocus Super-Resolution...

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3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2022

作者： Bajor, Antone Hirata-Miyasaki, Eduardo Senftleben, Maximilian Abrahamsson, Sara Department of Electrical and Computer Engineering University of California Santa Cruz 1156 High Street Santa CruzCA95064 United States Department of Applied Physics Science for Life Laboratory Royal Institute of Technology Stockholm Sweden

We have designed and constructed a 3D microscope that combines Multifocus Microscopy with Structured Illumination Microscopy for live 3D super-resolution biological imaging. Imaging multiple focal planes simultaneousl... 详细信息

ISBN: (纸本)9781957171098

关键词： Image reconstruction

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Retention Leveling: Leverage Retention Refreshing and Wear Leveling Techniques to Enhance Flash Reliability with the Awareness of Temperature

Retention Leveling: Leverage Retention Refreshing and Wear L...

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IEEE Non-Volatile Memory Systems and Applications Symposium (NVMSA)

作者： Wei-Chen Wang Chien-Chung Ho Yuan-Hao Chang Tei-Wei Kuo Yu-Ming Chang Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Department of Computer Science and Information Engineering National Cheng Kung University Institute of Information Science Academia Sinica Depanment of Computer Science and Information Engineering National Taiwan University High Performance and Scientific Computing Center National Taiwan University Mohamed bin Zayed University of Artificial Intelligence Wolley Inc.

Wear leveling cannot entirely mitigate retention errors, which have recently become $a$ substantial reliability issue due to cell shrinking. This paper focuses on preserving accurate data by addressing retention errors rather than uniformly distributing erases across blocks, as maintaining accurate data is the true goal for enhancing reliability. We propose the concept of retention leveling, considering $a$ crucial factor, i.e., temperature, and compare it to traditional wear leveling. Experimental results demonstrate that retention leveling can significantly improve flash memory reliability by limiting the number of retention errors to merely 0.0019% of the conventional approach, while substantially alleviating the write amplification problem.

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