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IS and T International Symposium on Electronic Imaging: Media Watermarking, Security, and Forensics, MWSF 2023

作者： Yadav, Amit Kumar Singh Bartusiak, Emily R. Bhagtani, Kratika Delp, Edward J. Video & Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West LafayetteIN United States

The ability to synthesize convincing human speech has become easier due to the availability of speech generation tools. This necessitates the development of forensics methods that can authenticate and attribute speech signals. In this paper, we examine a speech attribution task, which identifies the origin of a speech signal. Our proposed method known as Synthetic Speech Attribution Transformer (SSAT) converts speech signals into mel spectrograms and uses a self-supervised pretrained transformer for attribution. This transformer is pretrained on two large publicly available audio datasets: Audio Set and LibriSpeech. We finetune the pretrained transformer on three speech attribution datasets: the DARPA SemaFor Audio Attribution dataset, the ASVspoof2019 dataset, and the 2022 IEEE SP Cup dataset. SSAT achieves high closed-set accuracy on all datasets (99.8% on ASVspoof2019 dataset, 96.3% on SP Cup dataset, and 93.4% on DARPA SemaFor Audio Attribution dataset). We also investigate the method's ability to generalize to unknown speech generation methods (open-set scenario). SSAT has high performance, achieving an open-set accuracy of 90.2% on the ASVspoof2019 dataset and 88.45% on DARPA SemaFor Audio Attribution dataset. Finally, we show that our approach is robust to typical compression rates used by YouTube for speech signals. © 2023, Society for Imaging Science and Technology.

关键词： Large dataset

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VPx error resilient video coding using duplicated prediction information 7

VPx error resilient video coding using duplicated prediction...

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Visual Information processing and Communication VII 2016

作者： Gadgil, Neeraj Delp, Edward J. Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West LafayetteIN United States

Most real-Time video applications typically demand low endto- end latency and faithful reconstruction of the video sequence. Many popular video coding standards (e.g. VP8, VP9, H.264 and HEVC) aim at achieving high compression efficiencies by exploiting spatial and temporal redundancies. This makes the encoded bitstream vulnerable to errors. Thus, applications especially on mobile phones, tablet PCs and other portable devices that use WiFi or 3G/4G/LTE networks typically suffer from low quality of service typically characterized by frequent delays, jitter, frozen picture, partial/no picture and total loss of connection. Similar scenarios are also often observed while watching live streaming accompanied by service interruptions and a blank screen. Our approach is to investigate error resilient coding control for the VPx encoder to make the bitstream more error resilient for streaming applications under lossy channel conditions. In this paper, we describe an error resilient coding system that uses duplication of frame prediction information. Our "error resilience packet" consists of this prediction information of several frames, that can be used for error concealment in the case of packet loss ©2016 Society for Imaging Science and Technology.

关键词： Forecasting

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Color reproduction for noisy CFA data using directional cycle-spinning

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Journal of Systems engineering and Electronics 2011年第3期22卷 528-533页

作者： Weiyu Yu Jing Tian Yonghao Xiao School of Electronic and Information Engineering South China University of TechnologyGuangzhou 510640P.R.China Provincial Key Laboratory for Computer Information Processing Technology School of Computer Science and TechnologySoochow UniversitySuzhou 215006P.R.China School of Electrical and Electronic Engineering Nanyang Technological UniversityNanyang Avenue 639798Singapore

This paper addresses color filter array（CFA） color reproduction problem where the aim is to utilize an image captured by the CFA to produce an image with full color ***,conventional subband synthesis based color reproduction techniques do not consider the noise during image acquisition and assume that the CFA data are *** tackle the noisy CFA data,a novel approach is proposed by inserting a subband denoising scheme into the conventional subband synthesis ***,conventional subband synthesis based techniques exploit the decimated wavelet transform that is not shift-invariant and could result in ringing artifacts in the *** alleviate these artifacts,the directional cycle-spinning（DCS） technique is ***,a new cycle-spinning pattern is proposed according to the sampling pattern of the Bayer CFA *** experiments are conducted to demonstrate that the proposed approach outperforms several approaches.

关键词： color filter array（CFA） cycle-spinning denoising.

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Experimental analysis of communication/data-conditional aspects of a mixed-mode parallel architecture via synthetic computations 90

Experimental analysis of communication/data-conditional aspe...

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Proceedings of the 1990 ACM/IEEE conference on Supercomputing

作者： Samuel A. Fineberg Thomas L. Casavant Howard Jay Siegel Parallel Processing Laboratory Department of Electrical and Computer Engineering University of Iowa Iowa City IA Parallel Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN

ISBN: (纸本)9780897914123

Experimentation aimed at determining the potential benefit of mixed-mode SIMD/MIMD parallel architectures is reported. The experimentation is based on timing measurements made on the PASM system prototype at Purdue utilizing carefully coded synthetic variations of a well-known algorithm. The synthetic algorithms used to measure and evaluate this system were based on bitonic sorting of sequences stored in the processing elements. This computation was mapped to both the SIMD and MIMD modes of parallelism, as well as two hybrids of the SIMD and MIMD modes. The computations were coded in these four ways and experiments were performed that explore the trade-offs among them. The results of these experiments are presented and are discussed with special consideration of the effects of the system's architecture. The goal is to (as much as possible) obtain implementation independent analyses of the attributes of mixed-mode parallel processing with respect to the computational characteristics of the application being examined. The results are used to gain insight into the impact of computation mode on synchronization and data-conditional aspects of system performance.

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Software Defect Prediction via Deep Belief Network

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Chinese Journal of Electronics 2019年第5期28卷 925-932页

作者： WEI Hua SHAN Chun HU Changzhen ZHANG Yu YU Xiao School of Computer Science and Technology Beijing Institute of Technology China Information Technology Security Evaluation Center Beijing Key Laboratory of Software Security Engineering Technology Beijing Institute of Technology School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture State Key Laboratory in China for Geomechanics and Deep Underground Engineering (Beijing) China University of Mining and Technology School of Computer Science and Technology Shandong University of Technology

Defect distribution prediction is a meaningful topic because software defects are the fundamental cause of many attacks and data loss. Building accurate prediction models can help developers find bugs and prioritize their testing efforts. Previous researches focus on exploring different machine learning algorithms based on the features that encode the characteristics of *** problem of data redundancy exists in software defect data set, which has great influence on prediction *** propose a defect distribution prediction model(Deep belief network prediction model, DBNPM), a system for detecting whether a program module contains defects. The key insight of DBNPM is Deep belief network(DBN)technology, which is an effective deep learning technique in image processing and natural language processing,whose features are similar to defects in source *** results show that DBNPM can efficiently extract and process the data characteristics of source program and the performance is better than Support vector machine(SVM), Locally linear embedding SVM(LLE-SVM), and Neighborhood preserving embedding SVM(NPE-SVM).

关键词： Defect prediction Software security Deep belief network(DBN)

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AN INVESTIGATION OF JPEG IMAGE AND VIDEO COMPRESSION USING parallel processing

AN INVESTIGATION OF JPEG IMAGE AND VIDEO COMPRESSION USING P...

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1994 IEEE International Conference on Acoustics, Speech and Signal processing

作者： COOK, GW DELP, EJ Computer Vision Ond Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN 47907-1285 United States

The problem inherent with any digital image (or digital video) system is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop more complex algorithms that compress images to lower data rates with better fidelity. One approach that can be used to increase the execution speed of these complex algorithms is through the use of parallel processing. In this paper we address one aspect of the parallel implementation of the JPEG still image compression standard on the MasPar MP-1, a massively parallel SIMD computer. We develop a novel byte alignment algorithm used to efficiently output compressed data from the parallel system. © 1994 IEEE.

关键词： Image compression

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Performance Analysis of a Myrinet-Based Cluster

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Cluster Computing 2003年第4期6卷 299-313页

作者： Gunawan, Teddy Surya Cai, Wentong Parallel and Distributed Processing Laboratory School of Computer Engineering Nanyang Technological University Singapore

In recent years, there has been a growing interest in the cluster system as an accepted form of supercomputing, due to its high performance at an affordable cost. This paper attempts to elaborate performance analysis of Myrinet-based cluster. The communication performance and effect of background load on parallel applications were analyzed. For point-to-point communication, it was found that an extension to the Hockney's model was required to estimate the performance. The proposed model suggested that there should be two ranges to be used for the performance metrics to cope with the cache effect. Moreover, based on the extension of the point-to-point communication model, the Xu and Hwang's model for collective communication performance was also extended. Results showed that our models can make better estimation of the communication performance than the previous models. Finally, the interference of other user processes to the cluster system is evaluated by using synthetic background load generation programs.

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Experimental analysis of communication/data-conditional aspects of a mixed-mode parallel architecture via synthetic computations

Experimental analysis of communication/data-conditional aspe...

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Supercomputing Conference

作者： S.A. Fineberg T.L. Casavant H.J. Siegel Parallel Processing Laboratory Department of Electrical and Computer Engineering University of Iowa Iowa IA USA Parallel Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

Experimentation aimed at determining the potential benefit of mixed-mode SIMD/MIMD (single instruction, multiple data/multiple instruction, multiple data) parallel architectures is reported. The experimentation is based on timing measurements made on the PASM (Partitionable SIMD/MIMD) system prototype utilizing carefully coded synthetic variations of a well-known algorithm. The synthetic algorithms used to measure and evaluate this system were based on bitonic sorting of sequences stored in the processing elements. This computation was mapped to both the hybrids of the SIMD and MIMD modes. The computations were coded in these four ways and experiments were performed that explore the tradeoffs among them. The results of these experiments are presented and discussed, with special consideration of the effects of the system's architecture. The goal is to obtain implementation-independent analyses of the attributes of mixed-mode parallel processing with respect to the computational characteristics of the application being examined.< >

关键词： computer architecture Concurrent computing parallel processing Sorting parallel architectures Laboratories Prototypes Performance gain Algorithm design and analysis Switches

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parallel Building: A Complex System Approach for Smart Building Energy Management

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IEEE/CAA Journal of Automatica Sinica 2019年第6期6卷 1452-1461页

作者： Abdulaziz Almalaq Jun Hao Jun Jason Zhang Fei-Yue Wang Department of Electrical Engineering Engineering CollegeUniversity of HailHail 55476Saudi Arabia Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of DenverDenverCO 80208 USA State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 and also with the Research Center for Military Computational Experiments and Parallel Systems TechnologyNational University of Defense TechnologyChangsha 410073China

These days' smart buildings have high intensive information and massive operational parameters, not only extensive power consumption. With the development of computation capability and future 5 G, the ACP theory(i.e., artificial systems,computational experiments, and parallel computing) will play a much more crucial role in modeling and control of complex systems like commercial and academic buildings. The necessity of making accurate predictions of energy consumption out of a large number of operational parameters has become a crucial problem in smart buildings. Previous attempts have been made to seek energy consumption predictions based on historical data in buildings. However, there are still questions about parallel building consumption prediction mechanism using a large number of operational parameters. This article proposes a novel hybrid deep learning prediction approach that utilizes long short-term memory as an encoder and gated recurrent unit as a decoder in conjunction with ACP theory. The proposed approach is tested and validated by real-world dataset, and the results outperformed traditional predictive models compared in this paper.

关键词： ACP theory artificial intelligence data acquisition deep learning(DL) energy consumption machine learning parallel energy prediction prediction algorithms smart grid

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Pedestrian wind flow prediction using spatial-frequency generative adversarial network

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Building Simulation 2024年第2期17卷 319-334页

作者： Pengyue Wang Maozu Guo Yingeng Cao Shimeng Hao Xiaoping Zhou Lingling Zhao School of Architecture and Urban Planning Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing100044China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China School of Computer Science and Technology Harbin Institute of TechnologyHarbin150001China

Pedestrian wind flow is a critical factor in designing livable residential environments under growing complex urban *** pedestrian wind flow during the early design stages is essential but currently suffers from inefficiencies in numerical *** learning,particularly generative adversarial networks(GAN),has been increasingly adopted as an alternative method to provide efficient prediction of pedestrian wind ***,existing GAN-based wind flow prediction schemes have limitations due to the lack of considering the spatial and frequency characteristics of wind flow *** study proposes a novel approach termed SFGAN,which embeds spatial and frequency characteristics to enhance pedestrian wind flow *** the spatial domain,Gaussian blur is employed to decompose wind flow into components containing wind speed and distinguished flow edges,which are used as the embedded spatial *** information of wind flow is obtained through discrete wavelet transformation and used as the embedded frequency *** spatial and frequency characteristics of wind flow are jointly utilized to enforce consistency between the predicted wind flow and ground truth during the training phase,thereby leading to enhanced *** results demonstrate that SFGAN clearly improves wind flow prediction,reducing Wind_MAE,Wind_RMSE and the Fréchet Inception Distance(FID)score by 5.35%,6.52%and 12.30%,compared to the previous best method,*** also analyze the effectiveness of incorporating the spatial and frequency characteristics of wind flow in predicting pedestrian wind *** reduces errors in predicting wind flow at large error intervals and performs well in wake regions and regions surrounding *** enhanced predictions provide a better understanding of performance variability,bringing insights at the early design stage to improve pedestrian wind *** proposed spatial-frequen

关键词： pedestrian wind flow prediction generative adversarial network Gaussian kernel wavelet transform objective function

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