2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)最新文献_第2页

Accelerating the Analytical Modeling of Memory Level Parallelism by the Probability Analysis 用概率分析加速内存级并行性的解析建模

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985073

Yunhao Yan, Ming Ling

{"title":"Accelerating the Analytical Modeling of Memory Level Parallelism by the Probability Analysis","authors":"Yunhao Yan, Ming Ling","doi":"10.1109/PACRIM47961.2019.8985073","DOIUrl":"https://doi.org/10.1109/PACRIM47961.2019.8985073","url":null,"abstract":"Memory level parallelism (MLP), which refers to the number of memory requests concurrently held by Miss Status Handling Registers (MSHRs), is an indispensable factor to estimate cache performance. Unfortunately, due to the complexity of obtaining the maximum number of memory instructions or cache misses among all dependence paths, previous works in MLP modeling are very time-consuming in trace profiling. In this paper, we propose a fast model for evaluating MLP without analyzing all dependence paths in the instruction windows. Instead, we construct a probability model to estimate the maximum number of cache misses among all dependence paths in the instruction windows fed with some easily obtained inputs. By doing so, we greatly reduce the time overhead of the MLP model with a slight drop in accuracy. Twelve benchmarks chosen from Spec2006 are adopted for evaluating the accuracy and time overhead of our model. The average error of our model compared with the results of Gem5 simulations is around 9%, while the time overhead of the MLP evaluation process can be decreased to about half of previous models.","PeriodicalId":152556,"journal":{"name":"2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131038543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Cure Dataset: Ladder Networks for Audio Event Classification Cure数据集:音频事件分类的阶梯网络

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985061

Harishchandra Dubey, Dimitra Emmanouilidou, I. Tashev

{"title":"Cure Dataset: Ladder Networks for Audio Event Classification","authors":"Harishchandra Dubey, Dimitra Emmanouilidou, I. Tashev","doi":"10.1109/PACRIM47961.2019.8985061","DOIUrl":"https://doi.org/10.1109/PACRIM47961.2019.8985061","url":null,"abstract":"Audio event classification is an important task for several applications such as surveillance, audio, video and multimedia retrieval etc. There are approximately 340 million people with hearing loss who can’t perceive events happening around them. This paper establishes the CURE dataset which contains curated set of specific audio events most relevant for people with hearing loss. It is formatted as 5 sec sound recordings derived from the Freesound project. We propose a ladder network based audio event classifier. We adopted the state-of-the-art convolutional neural network (CNN) embeddings as audio features for this task. We start with signal and feature normalization that aims to reduce the mismatch between different recordings scenarios. Initially, a CNN is trained on weakly labeled Audioset data. Next, the pre-trained model is adopted as feature extractor for proposed CURE corpus. We also explore the performance of extreme learning machine (ELM) and use support vector machine (SVM) as baseline classifier. As a second evaluation set we incorporate ESC-50. Results and discussions validate the superiority of Ladder network over ELM and SVM classifier in terms of robustness and increased classification accuracy.","PeriodicalId":152556,"journal":{"name":"2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124166684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Graph Regularized Non-negative Matrix Factorization with Long-tail Constraint 具有长尾约束的图正则化非负矩阵分解

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985119

Lu You, R. Liu, He Zhang, Z. Shan

{"title":"Graph Regularized Non-negative Matrix Factorization with Long-tail Constraint","authors":"Lu You, R. Liu, He Zhang, Z. Shan","doi":"10.1109/PACRIM47961.2019.8985119","DOIUrl":"https://doi.org/10.1109/PACRIM47961.2019.8985119","url":null,"abstract":"How to dig out long tail topics is a great challenge in text mining. In previous research, most of non-hierarchical topic models were based on a hypothesis that the topics in documents follow polynomial distribution, ignoring the topics at the tail of distribution curve. Hierarchical topic model have the ability to mine long tail topics by introducing the hierarchical relationship among topics, but leading to a higher computational complexity. In this article, we propose a new method to mine long tail topics, which is called graph regularized non-negative matrix factorization with long-tail constraint. It uses KL divergence to measure the difference between matrices, and use neighbor graph to preserve the intrinsic geometrical and discriminating structure between original samples in low-dimensional space. Experiment shows, the algorithm we proposed can mine more long tail topic information in document, and make improvement in the task of data mining, comparing to other method, such as classical dirichlet distribution, non-negative matrix, hierarchical matrix, hierarchical latent dirichlet distribution.","PeriodicalId":152556,"journal":{"name":"2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116801677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Detection And Localization Of Splicing Attacks On Videos Using Block Correlation 基于块相关的视频拼接攻击检测与定位

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985120

Ernesto Aparicio-Díaz, R. Cumplido, Lázaro Bustio-Martínez, C. F. Uribe

引用次数: 0

Lightweight Key Establishment for WSNs wsn的轻量级密钥建立

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985101

Carlos Andres Lara-Nino, M. Morales-Sandoval, A. Díaz-Pérez

引用次数: 0

Development and evaluation of an OFDM Radar in a FPGA 基于FPGA的OFDM雷达的研制与评价

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985109

Juliana Carvalho, M. Violas, D. Castanheira, A. Gameiro

引用次数: 0

Fast Nonnegative Matrix Factorization Using Nested ADMM Iterations 基于嵌套ADMM迭代的快速非负矩阵分解

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985049

Wu-Sheng Lu

引用次数: 0

On the Ergodic Secrecy Rate of Massive MIMO Transmission with Partial Legitimate User CSI 部分合法用户CSI下大规模MIMO传输的遍历保密率研究

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985112

Tingnan Bao, Hong-Chuan Yang, M. Hasna

引用次数: 0

PACRIM 2019 Technical Program Committee PACRIM 2019技术计划委员会

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/pacrim47961.2019.8985075

引用次数: 0

Adaptive Server and Path Switching Scheme for Content Delivery Network 内容分发网络的自适应服务器和路径交换方案

2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Pub Date : 2019-08-01 DOI: 10.1109/PACRIM47961.2019.8985085

Hiroyuki Nishimuta, Daiki Nobayashi, T. Ikenaga

{"title":"Adaptive Server and Path Switching Scheme for Content Delivery Network","authors":"Hiroyuki Nishimuta, Daiki Nobayashi, T. Ikenaga","doi":"10.1109/PACRIM47961.2019.8985085","DOIUrl":"https://doi.org/10.1109/PACRIM47961.2019.8985085","url":null,"abstract":"Due to increases in the number of providers providing large-capacity content, multimedia products such as videos, images, and music now account for most of the traffic flowing over the Internet, and content delivery networks (CDNs) that can guarantee the load distribution and communication quality of related products on the Internet are in use around the world. However, with current CDN technologies, it is difficult to change the server or the path between a user and a server after a user has established a connection with a distribution server. Therefore, when dealing with long duration CDN communications, the conventional path control and distribution server selection methods related to CDNs cannot respond flexibly to changes in communication quality once communication has started. In response to this issue, this paper proposes a path and server switching scheme based on the estimated available throughput of each path as a way to improve CDN communication performance. Furthermore, via network simulations, we show that our proposed method can provide higher throughput performance than existing methods.","PeriodicalId":152556,"journal":{"name":"2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129985790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0