International Conference on Network, Communication and Computing最新文献_第5页

Analysis on the Effect of Term-Document's Matrix to the Accuracy of Latent-Semantic-Analysis-Based Cross-Language Plagiarism Detection 术语-文档矩阵对基于潜在语义分析的跨语言剽窃检测准确性的影响分析

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033300

A. A. P. Ratna, F. A. Ekadiyanto, Mardiyah, Prima Dewi Purnamasari, Muhammad Salman

引用次数: 2

An MCMC Based Course to Teaching Assistant Allocation 基于MCMC的课程教学助理分配

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033297

Saurabh Kumar, Shana Moothedath, P. Chaporkar, M. Belur

引用次数: 0

Effect of Doppler Shift on the MIMO-OFDM Systems in Troposcatter Fading Channels 对流层散射衰落信道中多普勒频移对MIMO-OFDM系统的影响

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033315

Zedong Xie, Xihong Chen, Xiaopeng Liu

引用次数: 1

Fault Tolerance for Web Service Based on Component Importance in Service Networks 业务网络中基于组件重要性的Web服务容错

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033328

Lu Chen, Lianchen Liu, Jiaxing Shang

引用次数: 3

Spatial-Temporal Based Traffic Speed Imputation for GPS Probe Vehicles 基于时空的GPS探测车交通速度估算

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033339

Jun-Dong Chang

引用次数: 3

Feature Fusion Methods for Robust Speech Emotion Recognition Based on Deep Belief Networks 基于深度信念网络的鲁棒语音情感识别特征融合方法

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033295

Ao Wu, Yongming Huang, Guobao Zhang

{"title":"Feature Fusion Methods for Robust Speech Emotion Recognition Based on Deep Belief Networks","authors":"Ao Wu, Yongming Huang, Guobao Zhang","doi":"10.1145/3033288.3033295","DOIUrl":"https://doi.org/10.1145/3033288.3033295","url":null,"abstract":"The speech emotion recognition accuracy of prosody feature and voice quality feature declines with the decrease of SNR (Signal to Noise Ratio) of speech signals. In this paper, we propose novel sub-band spectral centroid weighted wavelet packet cepstral coefficients (W-WPCC) for robust speech emotion recognition. The W-WPCC feature is computed by combining the sub-band energies with sub-band spectral centroids via a weighting scheme to generate noise-robust acoustic features. And Deep Belief Networks (DBNs) are artificial neural networks having more than one hidden layer, which are first pre-trained layer by layer and then fine-tuned using back propagation algorithm. The well-trained deep neural networks are capable of modeling complex and non-linear features of input training data and can better predict the probability distribution over classification labels. We extracted prosody feature, voice quality features and wavelet packet cepstral coefficients (WPCC) from the speech signals to combine with W-WPCC and fused them by Deep Belief Networks (DBNs). Experimental results on Berlin emotional speech database show that the proposed fused feature with W-WPCC is more suitable in speech emotion recognition under noisy conditions than other acoustics features and proposed DBNs feature learning structure combined with W-WPCC improve emotion recognition performance over the conventional emotion recognition method.","PeriodicalId":253625,"journal":{"name":"International Conference on Network, Communication and Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130324999","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: 4

A Kind of De-noising and Segmentation Method for Hollow CAPTCHAs with Noise Arcs 一种含噪声弧线的空心验证码去噪分割方法

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033353

Zhao Wang, Yuan Xi

引用次数: 0

Comparison of Neural Networks Based Direct Inverse Control Systems for a Double Propeller Boat Model 基于神经网络的双螺旋桨船模型直接逆控制系统比较

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033299

K. Priandana, Wahidin Wahab, B. Kusumoputro

引用次数: 8

Graph Clustering-Based Emerging Event Detection from Twitter Data Stream 基于图聚类的Twitter数据流新兴事件检测

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033312

Bundit Manaskasemsak, Bodin Chinthanet, A. Rungsawang

引用次数: 12

Service-Oriented Virtual Resource Management Framework for Satellite Network 面向服务的卫星网络虚拟资源管理框架

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033352

Zhiguo Liu, Li Qin, L. Yao

{"title":"Service-Oriented Virtual Resource Management Framework for Satellite Network","authors":"Zhiguo Liu, Li Qin, L. Yao","doi":"10.1145/3033288.3033352","DOIUrl":"https://doi.org/10.1145/3033288.3033352","url":null,"abstract":"Satellite network resources appear heterogeneous, distributed, autonomous, extended, and dynamic characteristics, making traditional satellite network resource management technologies cannot meet the increasing needs of a variety of services with significant differences in the characteristics. Therefore, the introduction of technology of virtual network resource management is to achieve service-oriented resource management and scheduling. The premise of realizing the virtual resource management is to establish the framework of resource management. For this purpose, this paper establishes a service- oriented virtual resource management framework. The structure adopts a hierarchical partition management mechanism, and the virtual network is divided into subnets by the LNMC (logical network management center) while its resources are mapped by the LRMC(logical resource management center) according to the restrictive conditions of service. The centralized management and distributed control system is designed to take into account the characteristics of high dynamics and large scale of topological space of satellite network, which can improve the efficiency of resource utilization and the quality of service.","PeriodicalId":253625,"journal":{"name":"International Conference on Network, Communication and Computing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131988917","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