NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors

Many real-world data are naturally represented as a sparse reorderable matrix, whose rows and columns can be arbitrarily ordered (e.g., the adjacency matrix of a bipartite graph). Storing a sparse matrix in conventional ways requires an amount of space linear in the number of non-zeros, and lossy compression of sparse matrices (e.g., Truncated SVD) typically requires an amount of space linear in the number of rows and columns. In this work, we propose NeuKron for compressing a sparse reorderable matrix into a constant-size space. NeuKron generalizes Kronecker products using a recurrent neural network with a constant number of parameters. NeuKron updates the parameters so that a given matrix is approximated by the product and reorders the rows and columns of the matrix to facilitate the approximation. The updates take time linear in the number of non-zeros in the input matrix, and the approximation of each entry can be retrieved in logarithmic time. We also extend NeuKron to compress sparse reorderable tensors (e.g. multi-layer graphs), which generalize matrices. Through experiments on ten real-world datasets, we show that NeuKron is (a) Compact: requiring up to five orders of magnitude less space than its best competitor with similar approximation errors, (b) Accurate: giving up to 10x smaller approximation error than its best competitors with similar size outputs, and (c) Scalable: successfully compressing a matrix with over 230 million non-zero entries.Comment: Accepted to WWW 2023 - The Web Conference 202

TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions

Many real-world datasets are represented as tensors, i.e., multi-dimensional arrays of numerical values. Storing them without compression often requires substantial space, which grows exponentially with the order. While many tensor compression algorithms are available, many of them rely on strong data assumptions regarding its order, sparsity, rank, and smoothness. In this work, we propose TENSORCODEC, a lossy compression algorithm for general tensors that do not necessarily adhere to strong input data assumptions. TENSORCODEC incorporates three key ideas. The first idea is Neural Tensor-Train Decomposition (NTTD) where we integrate a recurrent neural network into Tensor-Train Decomposition to enhance its expressive power and alleviate the limitations imposed by the low-rank assumption. Another idea is to fold the input tensor into a higher-order tensor to reduce the space required by NTTD. Finally, the mode indices of the input tensor are reordered to reveal patterns that can be exploited by NTTD for improved approximation. Our analysis and experiments on 8 real-world datasets demonstrate that TENSORCODEC is (a) Concise: it gives up to 7.38x more compact compression than the best competitor with similar reconstruction error, (b) Accurate: given the same budget for compressed size, it yields up to 3.33x more accurate reconstruction than the best competitor, (c) Scalable: its empirical compression time is linear in the number of tensor entries, and it reconstructs each entry in logarithmic time. Our code and datasets are available at https://github.com/kbrother/TensorCodec.Comment: Accepted to ICDM 2023 - IEEE International Conference on Data Mining 202

MEASUREMENTS OF PRESSURE DISTRIBUTIONS ON A ROTOR BLADE USING PSP TECHNIQUES

Surface pressure distributions on a rotating blade were measured by using pressure sensitive paint (PSP) to understand aerodynamic characteristics of a rotor blade. The present study was conducted to investigate the PSP techniques for measuring the pressure distributions on a rotor blade. In order to perform the experiment, the PSP was required to response very fast due to rapid pressure fluctuations on a rotor blade. High energy excitation light source was also needed to acquire proper intensity images in a short excitation time. The techniques were based on a lifetime method. Qualitative pressure distributions on an upper surface of small scale rotor in hovering condition were measured as a preliminary experiment prior to forward flight conditions in the KARI low speed wind tunnel laboratory. From measured pressure distributions, striking pressure gradient was observed on an upper surface of rotor blade and the resulting pressure showed expected gradient depending on different collective pitch angles. ABSTRAK : Pengagihan tekanan permukaan ke atas berbilah putar disukat menggunakan cat sensitive tekanan (pressure sensitive paint (PSP)) untuk memahami sifat-sifat aerodinamik suatu berbilah putar. Kajian telah dijalankan untuk menyelidik teknik-teknik PSP dengan mengukur agihan tekanan ke atas suatu berbilah putar. Agar eksperimen dapat dijalankan dengan baik, PSP harus bertindak cepat kerana tekanan naik turun dengan pantas ke atas berbilah putar. Sumber cahaya ujaan tenaga tinggi diperlukan untuk mendapatkan imej keamatan wajar dalam jangka masa ujaan yang pendek. Teknik-teknik tersebut terhasil daripada kajian semasa hayat. Agihan tekanan kualitatif ke permukaan atas berskala kecil pemutar dalam keadaan mengapung diukur sebagai permulaan eksperimen, sebelum penerbangan kehadapan dalam makmal terowong angin laju rendah KARI. Daripada agihan tekanan yang disukat, kecerunan tekanan yang ketara diperolehi daripada permerhatian terhadap permukaan atas berbilah putar dan tekanan yang didapati menunjukkan tekanan kecerunan yang dijangka, bergantung kepada sudut himpunan anggul yang berbeza

BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning

Continual Learning (CL) is the process of learning ceaselessly a sequence of tasks. Most existing CL methods deal with independent data (e.g., images and text) for which many benchmark frameworks and results under standard experimental settings are available. Compared to them, however, CL methods for graph data (graph CL) are relatively underexplored because of (a) the lack of standard experimental settings, especially regarding how to deal with the dependency between instances, (b) the lack of benchmark datasets and scenarios, and (c) high complexity in implementation and evaluation due to the dependency. In this paper, regarding (a) we define four standard incremental settings (task-, class-, domain-, and time-incremental) for node-, link-, and graph-level problems, extending the previously explored scope. Regarding (b), we provide 31 benchmark scenarios based on 20 real-world graphs. Regarding (c), we develop BeGin, an easy and fool-proof framework for graph CL. BeGin is easily extended since it is modularized with reusable modules for data processing, algorithm design, and evaluation. Especially, the evaluation module is completely separated from user code to eliminate potential mistakes. Regarding benchmark results, we cover 3X more combinations of incremental settings and levels of problems than the latest benchmark. All assets for the benchmark framework are publicly available at https://github.com/ShinhwanKang/BeGin

Experimental investigation of wing tip vortex

Particle image velocimetery was used in a low-speed wind tunnel to investigate and characterize wing tip vortex structures. A rectangular wing of a SWIM model was used as a vortex generator in two different configurations, (i) plain wing and (ii) flapped wing with trailing edge flap extended at 20 degrees. Vortex flow quantities and their dependence on angle of attack at a chord base Reynolds Number of 32.8x103 and 43.8x103 were evaluated. Assessment of measured data reveals that the peak values of tangential velocities, vortex strength and vorticities are directly proportional to the angle of attack. The vortex core radius value grows slowly as the angle of attack is increased. Both plain and flapped configurations showed similar trends. The peak tangential velocities and circulation distribution doubled when the flapped configuration was used instead of the plain wing

Experimental investigation of plain- and flapped-wing tip vortices

Particle image velocimetry was used in a low-speed wind tunnel to investigate and characterize wing tip vortex structures. A rectangular wing of a subsonic wall interference model was used as a vortex generator in two different configurations: 1) plain wing and 2) flapped wing with the trailing-edge flap extended at 20 degrees. Vortex flow quantities and their dependence on angle of attack at Reynolds numbers of 32:8 � 103 and 43:8 � 103 were evaluated. Assessment of measured data reveals that the peak values of tangential velocities, vortex strength, and vorticities are directly proportional to the angle of attack. The vortex core radius value grows slowly as the angle of attack is increased. Both plain and flapped configurations showed similar trends. The peak tangential velocities and circulation almost doubled when the flapped configuration was used instead of the plain wing

Evolution of NACA23012 wake vortices structure using PIV

The formation and development of a wing‐tip vortex in a near and extended near field were studied experimentally. A swept‐back tapered wing with a NACA23012 cross‐section was used as a vortex generator. Particle image velocimetry as a whole field velocity measurement technique was used in a low‐speed wind tunnel to measure and characterize the wing tip vortex. Wake structures at successive downstream planes crosswise to the axis of the wake vortices were evaluated in terms of internal and external core radius, maximum tangential velocities, vorticity and circulation distributions. The effect of angle of attack on vortex parameters was examined at one downstream location. Internal core radius and circulation distributions were nearly constant along the downstream direction. A direct dependence of the circulation and tangential velocity distribution on the angle of attack was evident. The centers of the wing tip vortices scatter in a circle of radius nearly equal to 1% of the mean wing chord. Meandering amplitudes showed no direct dependence on the vortex strength but increase along the downstream direction. Good agreement was obtained between the theoretical exponential vortex model and the measured data. Computed induced rolling moment coefficients generated by the wing are within the full roll control capability of a follower aircraft

Influence of differential spoiler settings on the wake the vortex characterization and alleviation

Experimental investigations using particle image velocimetry technique have been carried out for the evaluation of the differential spoiler setting capabilities in modifying the spanwise wing load and further reduce the wake vortex hazard. The aircraft half model (at high lift configuration) was investigated for two differential spoiler settings. Results reveal a noticeable inboard shift of spanwise wing loading. Implementation of a differential spoiler setting results in a substantial redistribution of the flap tip vortex circulation with an increase in the diameter of the merged vortex by a factor of up to 2.72 relative to the undisturbed flap tip vortex. Inspection of the cross-stream distribution of axial vorticity shows a reduction by a factor of up to 2.33 in the peak vorticity value. A 44% decrease of the maximum crossflow velocity relative to the undisturbed flap tip vortex crossflow velocity was recorded for the case of deployed spoilers. Finally assessment of the differential spoiler setting capabilities as a wake vortex attenuation device reveals that, while position of the maximum induced rolling moments in the flap tip area is little influenced by the differential spoiler setting, the maximum induced rolling moment coefficient was reduced to nearly one third of the undisturbed flap tip vortex value