2020 22nd International Conference on Advanced Communication Technology (ICACT)最新文献

The Impact of Zeroconf on the Education System of the Countries in Conflict: The Case of the Central African Republic 零冲突对冲突国家教育制度的影响:以中非共和国为例

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061567

Nadege Gladys Ndassimba, G. M. Kossingou, Edgard Ndassimba, Kéba Gueye, S. Ouya

引用次数: 1

Uplink Performance Analysis of Cell-Free MIMO with Low-Resolution ADCs and ZF Receiver 低分辨率adc和ZF接收机的无小区MIMO上行性能分析

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061355

Xuebing Bai, Meng Zhou, Xu Qiao, Yao Zhang, Longxiang Yang

引用次数: 3

A Proposed Audiovisual Quality Assessment Model Associated with Multiplayer Online Battle Arena Game: A Pilot Study with ROV 基于ROV的多人在线竞技游戏视听质量评估模型研究

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061343

Therdpong Daengsi, Phisit Pornpongtechavanich, Pongpisit Wuttidittachotti

{"title":"A Proposed Audiovisual Quality Assessment Model Associated with Multiplayer Online Battle Arena Game: A Pilot Study with ROV","authors":"Therdpong Daengsi, Phisit Pornpongtechavanich, Pongpisit Wuttidittachotti","doi":"10.23919/ICACT48636.2020.9061343","DOIUrl":"https://doi.org/10.23919/ICACT48636.2020.9061343","url":null,"abstract":"This study proposes an audiovisual quality assessment model for a popular gaming scenario, called the Multiplayer Online Battle Arena (MOBA) gaming. The subjective data about voice quality during conversation of the game players, the video quality, the overall quality, and the weighted percentage of voice and video have been gathered from 40 participants who competed in a small competition event of the Garena ROV (Arena of Valor) in Thailand. Then, three quarters of data have been used to create the model, while the last quarter of data has been used for model evaluation. After creating the model, it has been evaluated using Mean Absolute Percentage Error (MAPE) with three audiovisual quality evaluation models that provide good performances. It has been found that the proposed audiovisual quality assessment model provides better performance than previous works with MAPE of 6.16 %, while other models provide MAPE of 7.67 - 8.54%. Therefore, this evidence supports that the proposed model could be applied for evaluation of audiovisual quality based on the MOBA gaming scenario.","PeriodicalId":296763,"journal":{"name":"2020 22nd International Conference on Advanced Communication Technology (ICACT)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123448124","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

BER Reduction for PSK-Based MM-OFDM-BIM with Two-Level Symbol Power 基于psk的两级符号功率MM-OFDM-BIM误码率降低

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061377

L. Cho, Meng-Fan Chuang, Sheng-Hsiang Fu, Chau-Yun Hsu

引用次数: 0

Security in VANETs: Lightweight Protocol for Group-of-Vehicles Masters (LPGVM) VANETs中的安全性:车辆组主(lpvm)的轻量级协议

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061225

Hamaciré El Hadj Kalil, A. Kora, S. Boumerdassi

引用次数: 0

TB-DNN: A Thin Binarized Deep Neural Network with High Accuracy TB-DNN:一种高精度的薄二值化深度神经网络

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061291

Jie Wang, Xi Jin, Wei Wu

{"title":"TB-DNN: A Thin Binarized Deep Neural Network with High Accuracy","authors":"Jie Wang, Xi Jin, Wei Wu","doi":"10.23919/ICACT48636.2020.9061291","DOIUrl":"https://doi.org/10.23919/ICACT48636.2020.9061291","url":null,"abstract":"Deep neural networks (DNNs) have been widely used in many artificial intelligence (AI) applications. However, due to the huge demand for computing and storage resources as well as the high power consumption, deploying DNN models on embedded devices is full of challenges. Recent works have shown that DNN models can be compressed by removing their inner redundancy without obviously performance decay. In this work, we propose a two stage pipeline way to compress the ResNet-14 model and test it on CIFAR-10 and SVHN dataset respectively. Firstly, we use a filter level pruning method to remove the less important filters with different compression rate, and a considerable computation costs are reduced. Secondly, we binarize the pruned model to further reduce the model size and computational complexity. The training results show that we achieve 87.7% accuracy with only 1.86Mb model size on CIFAR-10 and 96.2% accuracy with 1.34Mb on SVHN. Compared to the original model, we have 57% to 68% FLOPs reduction and 45.6× to 63.1× model size compression at the cost of roughly 4% accuracy drop. Finally, we implement the thin binarized ResNet-14 model on the Xilinx KC705 board with a shared, flexible accumulator, which can save 46.8% logic resources. And the entire network parameters are store into on-chip RAM, which can greatly reduce the energy consumption and memory overhead caused by off-chip accesses. The experimental results show that on CIFAR-10 dataset, we achieve an overall performance of 1200 FPS, energy efficiency of 571 FPS/W, which denote 2.3× and 3.6× improvements over the most recent work.","PeriodicalId":296763,"journal":{"name":"2020 22nd International Conference on Advanced Communication Technology (ICACT)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122637298","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

Design and implementation of real-time information sharing system of IoT using distributed social network 基于分布式社交网络的物联网实时信息共享系统的设计与实现

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061505

Chang-Su Lee, Dongwoog Jung

引用次数: 0

Dynamic ACK skipping in TCP with Network Coding for Power Line Communication Networks 电力线通信网络中基于网络编码的TCP动态ACK跳变

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061477

Nguyen Viet Ha, Le Van Hau, M. Tsuru

{"title":"Dynamic ACK skipping in TCP with Network Coding for Power Line Communication Networks","authors":"Nguyen Viet Ha, Le Van Hau, M. Tsuru","doi":"10.23919/ICACT48636.2020.9061477","DOIUrl":"https://doi.org/10.23919/ICACT48636.2020.9061477","url":null,"abstract":"Transmission Control Protocol (TCP) still plays an essential role in various user applications for end-to-end reliable data transmission. However, TCP cannot get a high goodput performance in the lossy networks because it considers any packet loss to be a congestion signal and decreases the congestion window mistakenly. Therefore, TCP with Network Coding (termed TCP/NC) was proposed to recover the packet loss at the sink without retransmission if the number of coded packets is enough. However, the ACK packet needs to be sent for any arriving coded packet as a feedback of the end-to-end channel condition, resulting in a lower transmission performance in half-duplex networks, e.g., Power Line Communication. Therefore, we propose the ACK-Skipping scheme for TCP/NC to limit the number of ACK packets but still retain the necessary information, e.g., for channel estimation. The simulation result on ns-3 (Network Simulation 3) shows that the proposal achieves a higher goodput on PLC environment compared to TCP with Selective Acknowledgment and TCP Westwood+ as well as the recent variant of TCP/NC.","PeriodicalId":296763,"journal":{"name":"2020 22nd International Conference on Advanced Communication Technology (ICACT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129519274","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: 2

A Underwater Image Enhanced Algorithm combined MSR and Channel Energy 一种结合MSR和信道能量的水下图像增强算法

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061370

Yanying Yang, Xianwei Xu

引用次数: 4

Diseases Detection from Electroencephalogram Signals Using Support Vector Machine 基于支持向量机的脑电图信号疾病检测

2020 22nd International Conference on Advanced Communication Technology (ICACT) Pub Date : 2020-02-01 DOI: 10.23919/ICACT48636.2020.9061414

M. Rana, Md Walid Hasan, A. Abdelhadi

{"title":"Diseases Detection from Electroencephalogram Signals Using Support Vector Machine","authors":"M. Rana, Md Walid Hasan, A. Abdelhadi","doi":"10.23919/ICACT48636.2020.9061414","DOIUrl":"https://doi.org/10.23919/ICACT48636.2020.9061414","url":null,"abstract":"The need and importance of automatic disease recognition such as electroencephalogram has grown over time. Driven by this motivation, this research demonstrates the electroencephalogram (EEG) signals reconstruction process using the finite impulse response, principle component analysis, feature extraction, and support vector machine (SVM). After mentioning related literature, the EEG signals are taken from biomedical database such as Temple University Hospital, Australia. Applying finite impulse filter to the noisy EEG signals, the motion artifacts have been effectively removed. Generally, EEG signal is a multidimensional so it is quite difficult to find out effective channel for different diseases. Applying principle component analysis over filtered EEG signals, dimensional reduced EEG signals are obtained. For classifying EEG signals, different statistical measured such as standard deviation and mean absolute deviation are applied. Moreover, the SVM is used to classify the EEG signal from the selected features. Finally, the system performance is evaluated by 27 patients EEG database. For each disease, it has taken 9 signals. For different signals, the SVM are trained and evaluate the performance. Simulation results show that the SVM provides better performance for higher number of signals.","PeriodicalId":296763,"journal":{"name":"2020 22nd International Conference on Advanced Communication Technology (ICACT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129555281","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