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Sequential Frame-Interpolation And Dct-Based Video Compression Framework, Yeganeh Jalalpour, Wu-Chi Feng, Feng Liu Dec 2022

Sequential Frame-Interpolation And Dct-Based Video Compression Framework, Yeganeh Jalalpour, Wu-Chi Feng, Feng Liu

Computer Science Faculty Publications and Presentations

Video data is ubiquitous; capturing, transferring, and storing even compressed video data is challenging because it requires substantial resources. With the large amount of video traffic being transmitted on the internet, any improvement in compressing such data, even small, can drastically impact resource consumption. In this paper, we present a hybrid video compression framework that unites the advantages of both DCT-based and interpolation-based video compression methods in a single framework. We show that our work can deliver the same visual quality or, in some cases, improve visual quality while reducing the bandwidth by 10--20%.


A Simpler Machine Learning Model For Acute Kidney Injury Risk Stratification In Hospitalized Patients, Yirui Hu, Kunpeng Liu, Kevin Ho, David Riviello, Jason Brown, Alex R. Chang, Gurmukteshwar Singh, H. Lester Kirchner Oct 2022

A Simpler Machine Learning Model For Acute Kidney Injury Risk Stratification In Hospitalized Patients, Yirui Hu, Kunpeng Liu, Kevin Ho, David Riviello, Jason Brown, Alex R. Chang, Gurmukteshwar Singh, H. Lester Kirchner

Computer Science Faculty Publications and Presentations

Background: Hospitalization-associated acute kidney injury (AKI), affecting one-in-five inpatients, is associated with increased mortality and major adverse cardiac/kidney endpoints. Early AKI risk stratification may enable closer monitoring and prevention. Given the complexity and resource utilization of existing machine learning models, we aimed to develop a simpler prediction model. Methods: Models were trained and validated to predict risk of AKI using electronic health record (EHR) data available at 24 h of inpatient admission. Input variables included demographics, laboratory values, medications, and comorbidities. Missing values were imputed using multiple imputation by chained equations. Results: 26,410 of 209,300 (12.6%) inpatients developed AKI during …


Quantum Algorithms For Attacking Hardness Assumptions In Classical And Post‐Quantum Cryptography, J.-F. Biasse, X. Bonnetain, E. Kirshanova, A. Schrottenloher, Fang Song Aug 2022

Quantum Algorithms For Attacking Hardness Assumptions In Classical And Post‐Quantum Cryptography, J.-F. Biasse, X. Bonnetain, E. Kirshanova, A. Schrottenloher, Fang Song

Computer Science Faculty Publications and Presentations

In this survey, the authors review the main quantum algorithms for solving the computational problems that serve as hardness assumptions for cryptosystem. To this end, the authors consider both the currently most widely used classically secure cryptosystems, and the most promising candidates for post-quantum secure cryptosystems. The authors provide details on the cost of the quantum algorithms presented in this survey. The authors furthermore discuss ongoing research directions that can impact quantum cryptanalysis in the future.


The Db Community Vis-À-Vis Environmental, Health, And Societal Grand Challenges: Innovation Engine, Plumber, Or Bystander?, Anastasia Ailamaki, Leilani Battle, Johannes Gehrke, Masaru Kitsuregawa, David Maier, Christopher Re, Meihui Zhang, Magdalena Balazinska Jun 2022

The Db Community Vis-À-Vis Environmental, Health, And Societal Grand Challenges: Innovation Engine, Plumber, Or Bystander?, Anastasia Ailamaki, Leilani Battle, Johannes Gehrke, Masaru Kitsuregawa, David Maier, Christopher Re, Meihui Zhang, Magdalena Balazinska

Computer Science Faculty Publications and Presentations

This panel considers the role of the database research community in addressing humanity's greatest challenges. Are we an innovation engine, tool providers, or are we standing on the side while other research communities take the lead?


Sl-Cyclegan: Blind Motion Deblurring In Cycles Using Sparse Learning, Ali Syed Saqlain, Li-Yun Wang, Zhiyong Liu May 2022

Sl-Cyclegan: Blind Motion Deblurring In Cycles Using Sparse Learning, Ali Syed Saqlain, Li-Yun Wang, Zhiyong Liu

Computer Science Faculty Publications and Presentations

In this paper, we introduce an end-to-end generative adversarial network (GAN) based on sparse learning for single image motion deblurring, which we called SL-CycleGAN. For the first time in image motion deblurring, we propose a sparse ResNet-block as a combination of sparse convolution layers and a trainable spatial pooler k-winner based on HTM (Hierarchical Temporal Memory) to replace non-linearity such as ReLU in the ResNet-block of SL-CycleGAN generators. Furthermore, we take our inspiration from the domain-to-domain translation ability of the CycleGAN, and we show that image deblurring can be cycle-consistent while achieving the best qualitative results. Finally, we perform extensive …


Rate Maximization In A Uav Based Full-Duplex Multi-User Communication Network Using Multi-Objective Optimization, Syed Muhammad Hashir, Sabyasachi Gupta, Gavin Megson, Ehsan Aryafar, Joseph Camp Feb 2022

Rate Maximization In A Uav Based Full-Duplex Multi-User Communication Network Using Multi-Objective Optimization, Syed Muhammad Hashir, Sabyasachi Gupta, Gavin Megson, Ehsan Aryafar, Joseph Camp

Computer Science Faculty Publications and Presentations

In this paper, we study an unmanned-aerial-vehicle (UAV) based full-duplex (FD) multi-user communication network, where a UAV is deployed as a multiple-input–multiple-output (MIMO) FD base station (BS) to serve multiple FD users on the ground. We propose a multi-objective optimization framework which considers two desirable objective functions, namely sum uplink (UL) rate maximization and sum downlink (DL) rate maximization while providing quality-of-service to all the users in the communication network. A novel resource allocation multi-objective-optimization-problem (MOOP) is designed which optimizes the downlink beamformer, the beamwidth angle, and the 3D position of the UAV, and also the UL power of the …