Relevant bibliographies by topics / Tensor core

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Tensor core'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Tensor core"

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Wang, Hai Jun, Fei Yun Xu, and Fei Wang. "Tensor Factorization and Clustering for the Feature Extraction Based on Tucker3 with Updating Core." Advanced Materials Research 308-310 (August 2011): 2517–22. http://dx.doi.org/10.4028/www.scientific.net/amr.308-310.2517.

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Aiming at the problems of Tucker3 to large-scale tensor when applied to feature extraction, a new factorization based on Tucker3 is proposed to extract feature from the tensors. First, the large-scale tensor is divided into multiple sub-tensors so as to conveniently compute cores of sub-tensors in parallel mode with Matlab Parallel Computing Toolbox; Then, the cores of each sub-tensor are updated for reducing deviation in calculating and the similar characteristics of sub-tensors are clustered to obtain the features. Experiment results show that this methods is able to extract features rapidly
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Zhou, Ruofei, Gang Wang, Bo Li, Jinlong Wang, Tianzhu Liu, and Chungang Liu. "Key-Frame Detection and Super-Resolution of Hyperspectral Video via Sparse-Based Cumulative Tensor Factorization." Mathematical Problems in Engineering 2020 (July 14, 2020): 1–20. http://dx.doi.org/10.1155/2020/9548749.

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Thanks to the rapid development of hyperspectral sensors, hyperspectral videos (HSV) can now be collected with high temporal and spectral resolutions and utilized to handle invisible dynamic monitoring missions, such as chemical gas plume tracking. However, using such sequential large-scale data effectively is challenged, because the direct process of these data requires huge demands in terms of computational loads and memory. This paper presents a key-frame and target-detecting algorithm based on cumulative tensor CANDECOMP/PARAFAC (CP) factorization (CTCF) to select the frames where the targ
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Chen, Zhengyu, Ziqing Xu, and Donglin Wang. "Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 5 (2021): 4010–18. http://dx.doi.org/10.1609/aaai.v35i5.16521.

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Tensor decomposition is one of the most effective techniques for multi-criteria recommendations. However, it suffers from data sparsity when dealing with three-dimensional (3D) user-item-criterion ratings. To mitigate this issue, we consider effectively incorporating the side information and cross-domain knowledge in tensor decomposition. A deep transfer tensor decomposition (DTTD) method is proposed by integrating deep structure and Tucker decomposition, where an orthogonal constrained stacked denoising autoencoder (OC-SDAE) is proposed for alleviating the scale variation in learning effectiv
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Khoromskij, B. N. "Structured Rank-(r1, . . . , rd) Decomposition of Function-related Tensors in R_D." Computational Methods in Applied Mathematics 6, no. 2 (2006): 194–220. http://dx.doi.org/10.2478/cmam-2006-0010.

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AbstractThe structured tensor-product approximation of multidimensional nonlocal operators by a two-level rank-(r1, . . . , rd) decomposition of related higher-order tensors is proposed and analysed. In this approach, the construction of the desired approximant to a target tensor is a reminiscence of the Tucker-type model, where the canonical components are represented in a fixed (uniform) basis, while the core tensor is given in the canonical format. As an alternative, the multilevel nested canonical decomposition is presented. The complexity analysis of the corresponding multilinear algebra
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Shi, Qiquan, Jiaming Yin, Jiajun Cai, et al. "Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 5758–66. http://dx.doi.org/10.1609/aaai.v34i04.6032.

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This work proposes a novel approach for multiple time series forecasting. At first, multi-way delay embedding transform (MDT) is employed to represent time series as low-rank block Hankel tensors (BHT). Then, the higher-order tensors are projected to compressed core tensors by applying Tucker decomposition. At the same time, the generalized tensor Autoregressive Integrated Moving Average (ARIMA) is explicitly used on consecutive core tensors to predict future samples. In this manner, the proposed approach tactically incorporates the unique advantages of MDT tensorization (to exploit mutual cor
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Tang, Tao, and Gangyao Kuang. "SAR Image Reconstruction of Vehicle Targets Based on Tensor Decomposition." Electronics 11, no. 18 (2022): 2859. http://dx.doi.org/10.3390/electronics11182859.

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Due to the imaging mechanism of Synthetic Aperture Radars (SARs), the target shape on an SAR image is sensitive to the radar incidence angle and target azimuth, but there is strong correlation and redundancy between adjacent azimuth images of SAR targets. This paper studies multi-angle SAR image reconstruction based on non-negative Tucker decomposition using adjacent azimuth images reconstructed to form a sparse tensor. Sparse tensors are used to perform non-negative Tucker decomposition, resulting in non-negative core tensors and factor matrices. The reconstruction tensor is obtained by calcu
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Maruszewski, B. "On a Dislocation Core Tensor." physica status solidi (b) 168, no. 1 (1991): 59–66. http://dx.doi.org/10.1002/pssb.2221680105.

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Arora, Jai, Sirui Lu, Devansh Jain, et al. "TensorRight: Automated Verification of Tensor Graph Rewrites." Proceedings of the ACM on Programming Languages 9, POPL (2025): 832–63. https://doi.org/10.1145/3704865.

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Tensor compilers, essential for generating efficient code for deep learning models across various applications, employ tensor graph rewrites as one of the key optimizations. These rewrites optimize tensor computational graphs with the expectation of preserving semantics for tensors of arbitrary rank and size. Despite this expectation, to the best of our knowledge, there does not exist a fully automated verification system to prove the soundness of these rewrites for tensors of arbitrary rank and size. Previous works, while successful in verifying rewrites with tensors of concrete rank, do not
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Jin, Hongwei, Mengyu He, and Yuzhen Wang. "The expressions of the generalized inverses of the block tensor via the C-product." Filomat 37, no. 26 (2023): 8909–26. http://dx.doi.org/10.2298/fil2326909j.

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In this paper, we present the expressions of the generalized inverses of the third-order 2 ? 2 block tensor under the C-Product. Firstly, we give the necessary and sufficient conditions to present some generalized inverses and the Moore-Penrose inverse of the block tensor in Banachiewicz-Schur forms. Next, some results are generalized to the group inverse and the Drazin inverse. Moreover, equivalent conditions for the existence as well as the expressions for the core inverse of the block tensor are obtained. Finally, the results are applied to express the quotient property and the first Sylsve
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Yang, Chuhong, Bin Li, and Nan Wu. "SPAC: Sparse Partitioning and Adaptive Core Tensor Pruning Model for Knowledge Graph Completion." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 14 (2025): 15230–38. https://doi.org/10.1609/aaai.v39i14.33671.

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Tensor decomposition (TD) models are promising solutions for knowledge graph completion due to their simple structures but powerful representation capacities. The TD models typically adopt Tucker decomposition with a structured core tensor. Some models with a sparse core tensor, such as DistMult and ComplEx, are too simple and thus limit the interaction between embedding components, while other models with a dense core tensor are too complex and may lead to significant overfitting. To address these issues, we propose a new TD model called SPAC (Sparse Partitioning and Adaptive Core tensor prun
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Dissertations / Theses on the topic "Tensor core"

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Arnroth, Lukas. "Speeding up PARAFAC : Approximation of tensor rank using the Tucker core." Thesis, Uppsala universitet, Statistiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-353287.

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In this paper, the approach of utilizing the core tensor from the Tucker decomposition, in place of theuncompressed tensor, for nding a valid tensor rank for the PARAFAC decomposition is considered.Validity of the proposed method is investigated in terms of error and time consumption. As thesolutions of the PARAFAC decomposition are unique, stability of the solutions through split-halfanalysis is investigated. Simulated and real data are considered. Although, no general validity ofthe method could be observed, the results for some datasets look promising with 10% compressionin all modes. It is
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Gao, Xiaoyang. "Integrated compiler optimizations for tensor contractions." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1198874631.

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Farabegoli, Nicolas. "Implementazione ottimizata dell'operatore di Dirac su GPGPU." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20356/.

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Nelle applicazioni Lattice QCD l'operatore di Dirac rappresenta una delle principali operazioni, ottimizzarne l'efficienza si riflette in un incremento delle prestazioni globali dell'algoritmo. In tal senso i Tensor Core rappresentano una soluzione che incrementa le prestazioni del calcolo dell'operatore di Dirac ottimizzando in particolare la moltiplicazione tra matrici e vettori. Si è analizzata nel dettaglio l'architettura dei Tensor Core studiando il modello di esecuzione e il layout della memoria. Sono quindi state formulate e analizzate in dettaglio alcune soluzioni che sfruttano i Tenso
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Barakat, Nadia. "Diffusion Tensor Imaging (DTI) of the Pediatric Spinal Cord." Diss., Temple University Libraries, 2012. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/190288.

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Bioengineering<br>Ph.D.<br>Diffusion Tensor Imaging (DTI) is a technique for noninvasively examining diffusion of water molecules in each voxel of an image in directions parallel and transverse to the plane of neuronal axons. The quantitative characteristic of DTI allows for the characterization of physical properties of tissues. The unique characteristic architecture of the spinal cord allows DTI to characterize cord white matter, separate white from gray matter and assess structural damage of the cord. While studies on diffusion imaging of the spinal cord in adults, as well as in animal mode
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Kim, Jinsung. "Optimizing Tensor Contractions on GPUs." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1563237825735994.

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Li, Ting-hung Darrell. "Ultrastructural imaging of the cervical spinal cord." Click to view the E-thesis via HKUTO, 2010. http://sunzi.lib.hku.hk/hkuto/record/B43572285.

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Chan, Tin-yan, and 陳天恩. "Diffusion tensor imaging of the cervical spinal cord in Chinese healthy population." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206563.

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Magnetic Resonance Imaging (MRI) has been applied in diagnosing Cervical Spondylosis Myelopathy (CSM) clinically. However, morphometric and signal change of MRI have not shown consistent relations with neurological function or outcome after surgical intervention. Diffusion Tensor Imaging (DTI) is an advanced MRI technology, which uses the principle of anisotropic water diffusion property. Recent studies indicated that DTI could be used as diagnostic tools for Cervical Spondylosis Myelopathy (CSM). The study aims to establish a Region of Interest (ROI)-based database. 65 healthy Chinese subject
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Middleton, Devon. "Characterization of metal artifacts in diffusion tensor imaging for spinal cord applications." Master's thesis, Temple University Libraries, 2013. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/214807.

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Mechanical Engineering<br>M.S.M.E.<br>Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) technique used to measure in-vivo anisotropic water diffusion. This can give useful information regarding white matter integrity and has the potential to provide important biomarkers in spinal cord injury. One of the largest challenges in DTI of the spinal cord is the presence of metal which causes geometric distortions, signal pile-up, and signal voids. Because most patients with spinal cord injury have some amount of metal hardware implanted for stabilization, it is important to confron
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Li, Ting-hung Darrell, and 李廷雄. "Ultrastructural imaging of the cervical spinal cord." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B43572285.

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Yang, Sen. "Tension variation reduction in high speed cone winding." Thesis, Loughborough University, 1992. https://dspace.lboro.ac.uk/2134/14572.

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The research work was concened with the design of tension compensators for spinning-winding machines for the purposes of reducing winding tension variation during high speed cone winding. Initially, the research was directed to investigating the 'winding error', i.e. the difference between yarn supply and demand, which was the main cause of winding tension variation. Mathematical models were established to analyse the winding velocity variation and yarn path length variation. Several methods have been investigated to reduce winding tension variation and to develop tension compensators. These i
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Books on the topic "Tensor core"

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Gotti, Gino Giovannelli. Ricordi del mio passato artistico come tenore lirico. Cantagalli, 1996.

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Cau, Tonino. D@e coro: Tenores di Neoneli dal 1976 anno dopo anno. S'Alvure, 2003.

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Colter, Cara. Their Christmas Wish Come True. Harlequin, 2007.

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McDonough, Darryl D. Annotated take-overs code. 2nd ed. Law Book Co., 1989.

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Canada, Atomic Energy of. Tables of Tensor Feynman Integrals in the Light-Cone Gauge with the Mandelstam-Leibbrandt Prescription. s.n, 1985.

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Finance, Singapore Ministry of, ed. The Singapore Code on take-over and mergers. Ministry of Finance, 1985.

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Schuster, Stephan. Takeover law: Text of the German takeover code and of the takeover laws of the European Union, of Switzerland and of the United Kingdom, with annotations. Knapp, 1996.

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T, Papageorgiou Demetrios, Smyrlis Yiorgos S, and Institute for Computer Applications in Science and Engineering., eds. Nonlinear stability of oscillatory core-annular flow: A generalized Kuramoto-Sivashinsky equation with time periodic coefficients. Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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Wilson, August. Joe Turner's come and gone: A play in two acts. New American Library, 1988.

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Wilson, August. Joe Turner's come and gone. Samuel French, 1990.

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Book chapters on the topic "Tensor core"

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Ma, Xiu, Linbo Wang, Linting Bai, Kai Che, and Xingyu Cao. "CUDA Core Meets Tensor Core: Characterizing the Performance of Tensor Computation on Modern GPU." In Lecture Notes in Mechanical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-9774-5_30.

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D. Ahle, Thomas, and Francesco Silvestri. "Similarity Search with Tensor Core Units." In Similarity Search and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60936-8_6.

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Zouzias, Anastasios, and William F. McColl. "A Parallel Scan Algorithm in the Tensor Core Unit Model." In Euro-Par 2023: Parallel Processing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39698-4_33.

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Zhou, Honghui, Ruyi Qin, Zihan Liu, Ying Qian, and Xiaoming Ju. "Optimizing Performance of Image Processing Algorithms on GPUs." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_95.

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AbstractThe application of machine learning algorithms in the field of power grid improves the service level of power enterprises and promotes the development of power grid. NVIDIA Volta and Turing GPUs powered by Tensor Cores can accelerate training and learning performance for these algorithms. With Tensor Cores enabled, FP32 and FP16 mixed precision matrix multiplication dramatically accelerates the throughput and reduces AI training times. In order to explore the cause of this phenomenon, we choose a convolutional neural network (CNN), which is widely used in computer vision, as an example
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Xu, Hongyan, Jiajia Tang, Jianhai Zhang, and Li Zhu. "Emotion Recognition Using Multi-core Tensor Learning and Multimodal Physiological Signal." In Human Brain and Artificial Intelligence. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1288-6_10.

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Rao, P. Kiran, P. Suman Prakash, N. Jaswanth Kumar, V. Kartheek Reddy, and Arigela Satheesh Kumar. "Efficient Sparse Tensor Core Networks for Real-Time Insect Classification in Agriculture." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83790-6_11.

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Ruda, Dustin, Stefan Turek, and Dirk Ribbrock. "Fast Semi-iterative Finite Element Poisson Solvers for Tensor Core GPUs Based on Prehandling." In Lecture Notes in Computational Science and Engineering. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86169-7_33.

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Ghadekar, Premanand P., and Nilkanth B. Chopade. "Higher-Order Nonlinear Analysis with Core Tensor and Frame-Wise Approach for Dynamic Texture Synthesis." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6872-0_2.

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Zahradník, Jiří, and Efthimios Sokos. "ISOLA Code for Multiple-Point Source Modeling—Review." In Moment Tensor Solutions. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77359-9_1.

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Yoo, Roh-Eul. "Diffusion Tensor Imaging." In Surgery of Spinal Cord Tumors Based on Anatomy. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-7771-0_16.

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Conference papers on the topic "Tensor core"

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Gao, Yixuan, Jianan Li, Xiaonan Chai, Junxiang Wang, and Dong Zhang. "Optimization of Triton matrix multiplication for tensor core." In 4th International Conference on Electronic Information Engineering and Data Processing (EIEDP 2025), edited by Azlan Bin Mohd Zain and Lei Chen. SPIE, 2025. https://doi.org/10.1117/12.3066960.

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Schwartz, Russell L. T., Hangbo Yang, Nicola Peserico, and Volker J. Sorger. "The Von Neumann Bottleneck in Photonic Tensor Core Systems." In 2024 IEEE Photonics Society Summer Topicals Meeting Series (SUM). IEEE, 2024. http://dx.doi.org/10.1109/sum60964.2024.10614519.

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Ogiwara, Yushi, and Hideyuki Kawashima. "Sparse Ternary Matrix Multiplication with Tensor Core for Transformer." In 2024 Twelfth International Symposium on Computing and Networking Workshops (CANDARW). IEEE, 2024. https://doi.org/10.1109/candarw64572.2024.00031.

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Jiao, Wenting, Yang Gao, Lei Zhang, Kun Yin, and Hui Yu. "High-speed Photonic Tensor Core Utilizing Lithium Niobate Modulator Array." In Frontiers in Optics. Optica Publishing Group, 2024. https://doi.org/10.1364/fio.2024.fd1.3.

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We present a photonic tensor core for convolution computation utilizing modulator arrays on lithium niobate platform, enabling significant enhancements in computational speed and integration capabilities.
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Liu, Jun, Shulin Zeng, Junbo Zhao, et al. "TB-STC: Transposable Block-wise N:M Structured Sparse Tensor Core." In 2025 IEEE International Symposium on High Performance Computer Architecture (HPCA). IEEE, 2025. https://doi.org/10.1109/hpca61900.2025.00075.

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Nada, Abubakr, Giuseppe Maria Sarda, and Erwan Lenormand. "Cooperative Warp Execution in Tensor Core for RISC-V GPGPU." In 2025 IEEE International Symposium on High Performance Computer Architecture (HPCA). IEEE, 2025. https://doi.org/10.1109/hpca61900.2025.00107.

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Jiang, Yue, Wenjia Zhang, Han Wang, Jiayuan Guo, Jiangbing Du, and Zuyuan He. "Photonic 4D-Convolution Tensor Core based on Micro-Ring Mesh Architecture." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.w3d.3.

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We propose a 4D-photonic convolution tensor core leveraged by the micro-ring mesh that enabling parallel batch processing and parallel multi-kernel computation. The equivalent computing power is up to 2.24 Tera-operations per second (TOPs) per second with over 90% recognition accuracy.
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Wang, Lin, Xinyu Huang, Lei Zhang, Kun Yin, and Hui Yu. "Scalable Incoherent Optical Tensor Core Based on Thin-film Lithium Niobate Platform." In Frontiers in Optics. Optica Publishing Group, 2024. https://doi.org/10.1364/fio.2024.fd1.1.

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Shafiee, Amin, Linhong Chen, Sudeep Pasricha, Jie Yao, and Mahdi Nikdast. "Enabling Scalable Photonic Tensor Cores with Polarization-Domain Photonic Computing." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.w2a.42.

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We present a silicon-photonic tensor core using 2D ferroelectric materials to enable wavelength- and polarization-domain computing. Results, based on experimentally characterized material properties, show up to 83% improvement in computation accuracy compared to coherent networks.
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Prapas, A., M. Moralis-Pegios, A. Tsakyridis, et al. "A Time-Space-Wavelength Multiplexed AWGR-based Photonic Tensor Core using WDM SiGe EAM array chiplets." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.w4d.2.

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We demonstrate experimentally an 8×8 AWGR-based photonic accelerator that leverages a SiGe EAM array chiplet as its computational core. The experimental implementation of a MNIST classifier at 20 Gbaud revealed a Cohen’s kappa-score of 0.7421.
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Reports on the topic "Tensor core"

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Bader, Brett William, and Tamara Gibson Kolda. MATLAB tensor classes for fast algorithm prototyping : source code. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/974874.

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Weatherby, J. R., R. D. Krieg, and C. M. Stone. Incorporation of surface tension into the structural finite element code SANCHO. Office of Scientific and Technical Information (OSTI), 1989. http://dx.doi.org/10.2172/6185598.

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Broome, Scott Thomas, and Moo Y. Lee. Dynamic Brazilian Tension Results on Core from Borehole U-15n NNSS in support of SPE. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1488327.

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Dehart, Brenda M. IMEC (Item Mission Essentiality Code) Implementation in TARSLLS (Tender and Repair Ship Load Lists). Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada171776.

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Dacre, Nicholas, David Eggleton, Vasilis Gkogkidis, and Bernardo Cantone. Dynamic Conditions for Project Success. Association for Project Management, 2021. http://dx.doi.org/10.61175/fxcu4654.

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In 2015, we published a report which sought to identify the core factors which lead to project success. These conditions, subject to the situation and the judgement of the project professional, can be implemented with any project, programme or portfolio and help to best ensure project success. However, despite widespread usage we identified at the end of this research that dynamic conditions at the organisational, professional, and socio-economic levels existed that could help to shape successful project-based organisations. With this in mind and through a commissioned tender we sought with th
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Lins, Cesar, and Judith Morrison. Raça e Gênero nas Grandes Empresas: Um perfil da força de trabalho do Brasil. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003767.

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Esta publicaçao traz um perfil da força de trabalho formal brasileira, a partir de um levantamento dos registros administrativos de mais de 2 mil empresas, englobando mais de 5 milhes de empregados no país. Foi constatado que fatores de raça e genero impactam significativamente a populaçao trabalhadora, tendo a mulher negra como a mais vulnerável em questoes de carreira, remuneraçao e estabilidade, mesmo quando alcança posiçoes de chefia. Além disso, o estudo mostrou que homens e mulheres negros estao em posiçao desfavorável quando comparados a mulheres e homens brancos, o que indica a cor da
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Sylla, Richard, and Robert E. Wright. Scale and Scope in Early American Business History: The “Fortune 500” of 1812. Institute for New Economic Thinking Working Paper Series, 2024. http://dx.doi.org/10.36687/inetwp224.

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Fortune magazine began publishing annual rankings of U.S. corporations by revenue in 1955. Ever since, scholars and forecasters have analyzed changes in the Fortune 500 to help inform their judgments about industry concentration and the relative importance of different sectors of the economy. Unfortunately, earlier data are scarce, especially before the Civil War. Through extensive research we have created a sort of historical “Fortune 500” going back to 1812, ranked by corporate capitalization, which we share here. Numerous insights can be drawn from this dataset, including the historical dom
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Dueñas, Ximena, Gregory Elacqua, Luis Eduardo Jaramillo Flechas, and Juan Francisco Margitic. Pérdidas de aprendizaje debido al COVID-19: desafíos y hallazgos en el caso de Colombia. Banco Interamericano de Desarrollo, 2022. http://dx.doi.org/10.18235/0004662.

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El COVID-19 afectó a los sistemas educativos de todo el mundo. América Latina ya enfrentaba problemas importantes en términos de calidad educativa y se espera que el cierre prolongado de las escuelas haya afectado aún más el aprendizaje y las trayectorias de los estudiantes. Este documento contribuye a la discusión al analizar el caso de Colombia, uno de los países donde más duró el cierre de las escuelas, no obstante, mantuvo en 2020 la aplicación de las pruebas estandarizadas Saber 11 que rinden los estudiantes de último grado de bachillerato. Los resultados indican que los colegios con mayo
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Tow Leong, Tiang, Mohd Saufi Ahmad, Ang Qian Yee, et al. HANDBOOK OF ELECTRICAL SYSTEM DESIGN FOR NON-DOMESTIC BUILDING. Penerbit Universiti Malaysia Perlis, 2023. http://dx.doi.org/10.58915/techrpt2023.001.

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This technical report presents the electrical system installation design for development of a factory with 1 storey and 2 storey of offices. Firstly, the general methodology of designing the electrical system are elaborated in this report. As overall, the methodologies in designing the components of the electrical system are explained and elaborated, which included: (a) load and maximum demand estimation; (b) miniature circuit breaker (MCB) selection; (c) moulded case circuit breaker (MCCB) selection; (d) air circuit breaker (ACB) selection, (e) residual current device (RCD) selection; (f) pro
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Malej, Matt, and Fengyan Shi. Suppressing the pressure-source instability in modeling deep-draft vessels with low under-keel clearance in FUNWAVE-TVD. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40639.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) documents the development through verification and validation of three instability-suppressing mechanisms in FUNWAVE-TVD, a Boussinesq-type numerical wave model, when modeling deep-draft vessels with a low under-keel clearance (UKC). Many large commercial ports and channels (e.g., Houston Ship Channel, Galveston, US Army Corps of Engineers [USACE]) are traveled and affected by tens of thousands of commercial vessel passages per year. In a series of recent projects undertaken for the Galveston District (USACE), it was discovered tha
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