2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)最新文献_第2页

DTE:Dynamic Traffic Engineering in Software Defined Data Center Networks 软件定义数据中心网络中的动态流量工程

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973350

Farshad Tajedin, M. Farhoudi, Aliehsan Samiei, B. Akbari

{"title":"DTE:Dynamic Traffic Engineering in Software Defined Data Center Networks","authors":"Farshad Tajedin, M. Farhoudi, Aliehsan Samiei, B. Akbari","doi":"10.1109/CENIM48368.2019.8973350","DOIUrl":"https://doi.org/10.1109/CENIM48368.2019.8973350","url":null,"abstract":"Nowadays, data center networks confront a huge amount of data that can cause both network congestion and packet loss; therefore, traffic engineering methods can help to balance the load through the network. In recent years, quite a bit of traffic engineering methods have been proposed in order to reduce network utilization, especially in cloud data center networks. Reducing network utilization; preventing network congestion, which leads to guaranteeing QoS; and optimal using of the existing route are considered as major challenges through all these works. Prevalent traffic engineering algorithms such as ECMP do not have any focus on the current network circumstance, nor do they provide a solution for mice flows. In this work, we propose a novel dynamic traffic engineering method in software-defined data center networks which considers current network circumstance, uses network resources in an optimal manner, and guarantees QoS. The algorithm uses OpenFlow protocol to detect new flow, gather network information in short intervals, and choose the best route for the flow based on network loads. The proposed algorithm selects the best path through the network for each flow based on their existing flows’ type in order to not only improve the QoS but also achieve more customer satisfaction. The evaluation results demonstrate that the DTE algorithm reduces high-priority flows jitter, increase network utilization, and balance loads through the network and path to reach hosts better in comparison with existing traffic engineering methods.","PeriodicalId":106778,"journal":{"name":"2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115760279","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

Disease Classification based on Dermoscopic Skin Images Using Convolutional Neural Network in Teledermatology System 基于远程皮肤科系统中皮肤镜图像的卷积神经网络疾病分类

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973303

I. K. E. Purnama, Arta Kusuma Hernanda, A. A. P. Ratna, I. Nurtanio, A. Hidayati, M. Purnomo, S. M. S. Nugroho, R. F. Rachmadi

引用次数: 12

Facial Model Deformation Based on Landmarks Using Laplacian 基于拉普拉斯标记的人脸模型变形

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973319

Ongki Permono Aji, I. Purnama, E. M. Yuniarno

引用次数: 1

Long-Range Monitoring System with Haze Reducer Tool Based Digital Image and Video Processing 基于数字图像和视频处理的减霾工具远程监测系统

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973246

A. Zaini, E. M. Yuniarno, Bramantio Bani Hilmiawan

引用次数: 0

Explorable Virtual Diorama of Indonesian Prehistoric Human Life using Apple ARKit based Mixed Reality 使用基于苹果ARKit的混合现实探索印度尼西亚史前人类生活的虚拟立体模型

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973326

S. Sumpeno, Bima Panji Yudasmara, D. Purwitasari

{"title":"Explorable Virtual Diorama of Indonesian Prehistoric Human Life using Apple ARKit based Mixed Reality","authors":"S. Sumpeno, Bima Panji Yudasmara, D. Purwitasari","doi":"10.1109/CENIM48368.2019.8973326","DOIUrl":"https://doi.org/10.1109/CENIM48368.2019.8973326","url":null,"abstract":"Prehistoric human diorama which are being diplayed in archaeology museums in Indonesia are still static and inexplorable. This research aims to design a virtual diorama application about Indonesian prehistoric human habitat and life which applies Apple ARKit based Mixed Reality (MR) technology. Virtual diorama application lets users to explore dynamic virtual diorama from their ARKit supported iOS devices. Virtual diorama application has an ability to 3D scan the environment around user by taking point cloud data through ARKit. Scanning result is used to generate virtual environment which its objects are arranged according with real-world object arrangement by using heightmap from scanning result. This application uses “Magic Door” concept which the user can get in and out virtual diorama through a virtual door. Test results show that virtual environment arranger system has a success rate of 89% with average global translation of 5,04 cm and global rotation chance of 13,33%. Questionnaire testing to 30 persons showed that 43,33% of respondents were helped by virtual environment arrangements which were matched with real world environment arrangement in prevention of collisions with objects in the real world. There are 36,67% of respondents agree that the displayed dynamic prehistoric human helps respondents in understanding prehistoric human life and 46,67% of the respondents agree that Mixed Reality provides a new experience in learning prehistoric human life.","PeriodicalId":106778,"journal":{"name":"2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132443247","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

Self-Physical Rehabilitation System based on Hand Motion Sensor 基于手部运动传感器的自我肢体康复系统

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973365

S. M. S. Nugroho, M. Fauzan, I. Purnama

{"title":"Self-Physical Rehabilitation System based on Hand Motion Sensor","authors":"S. M. S. Nugroho, M. Fauzan, I. Purnama","doi":"10.1109/CENIM48368.2019.8973365","DOIUrl":"https://doi.org/10.1109/CENIM48368.2019.8973365","url":null,"abstract":"Stroke is one of the diseases that cause high number of disability and mortality in Indonesia. The number of deaths from stroke in Indonesia reached 15.4% in almost all hospitals in Indonesia. One of the steps to help stroke patients to improve their motor function, speech, cognition, and other impaired functions is to conduct a series of post-stroke rehabilitation. Post-stroke rehabilitation can be done with direct supervision of the physiotherapist or performed alone at home or commonly called self-rehabilitation. Post-stroke rehabilitation has a variety of movements training, one of which is the movement of a finger. MedCap emerged as one of the tools that can help physiotherapists and patients to rehabilitate post-stroke fingers movement. MedCap which uses Leap Motion hand motion sensor can record a predetermined reference movement with a success rate of 62.35%. MedCap can also calculate the conformity of the reference movement and the real time movement of the patient using the Euclidean Distance method as a form of feedback to the physiotherapist and patient. The method used by MedCap can calculate the conformity of movement with real time movement with an average value of 43.2495%.","PeriodicalId":106778,"journal":{"name":"2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"47 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133709035","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

Improving Lightweight Convolutional Neural Network for Facial Expression Recognition via Transfer Learning 基于迁移学习的面部表情识别改进轻量级卷积神经网络

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973312

Anggit Wikanningrum, R. F. Rachmadi, K. Ogata

{"title":"Improving Lightweight Convolutional Neural Network for Facial Expression Recognition via Transfer Learning","authors":"Anggit Wikanningrum, R. F. Rachmadi, K. Ogata","doi":"10.1109/CENIM48368.2019.8973312","DOIUrl":"https://doi.org/10.1109/CENIM48368.2019.8973312","url":null,"abstract":"Image-based facial expression recognition is an important problem especially for analyzing the human emotion or feeling under a specific condition, such as while watching a movie scene or playing a computer game. Furthermore, the convolutional neural network (CNN) is one of the underlying technology proven to be applicable to image-based facial expression recognition problem. Unfortunately, the available CNN architecture that applied for image-based facial expression recognition problem only focuses on the accuracy instead of other factors, such as the number of parameters and the execution time. In this paper, we investigated whether transfer learning from a medium-size and large-size dataset is feasible to improve the performance of lightweight CNN architecture on image-based facial expression recognition problem. We use lightweight residual-based CNN architecture originally used for CIFAR dataset to analyze the effect of the transfer learning from five different datasets, including CIFAR10, CIFAR100, ImageNet32, CINC-10, and CASIA-WebFace. The FER+ (Facial Expression Recognition Plus) dataset is used to evaluate the lightweight CNN architecture performance. Experiments show that our lightweight CNN classifier can also be improved even when the transfer learning performing from middle-size dataset comparing when training the classifier from scratch.","PeriodicalId":106778,"journal":{"name":"2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132942650","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: 8

Design and Implementation Serious Game “Tic Tac Toe Math” 严肃游戏《Tic Tac Toe Math》的设计与实现

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973336

Muhammad H. Garry, Y. Yamasari, S. M. S. Nugroho, M. Purnomo

引用次数: 2

Volumetric Analysis of Brain Tumor Magnetic Resonance Image 脑肿瘤磁共振图像的体积分析

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973300

Hapsari Peni Agustin, H. Hidayati, A. G. Sooai, I. K. E. Purnama, M. Purnomo

{"title":"Volumetric Analysis of Brain Tumor Magnetic Resonance Image","authors":"Hapsari Peni Agustin, H. Hidayati, A. G. Sooai, I. K. E. Purnama, M. Purnomo","doi":"10.1109/CENIM48368.2019.8973300","DOIUrl":"https://doi.org/10.1109/CENIM48368.2019.8973300","url":null,"abstract":"Volumetric analysis of brain tumors is a decisive thing in the detection of brain tumors to determine the patient’s lifetime followed by action to the patient. A few studies had been shown explicitly quantified the brain tumor volume while the analysis of brain tumor volumetric by expert limited with the huge data of brain tumor patient MRI. Thorough the importance of brain tumor analysis in clinical used, the purpose of this research is to evaluate the similarity of a semi-automatic segmentation tool for brain tumor image analysis. The agreement was compared by using differences of means with 95% limits of agreement (LoA). Brain tumor segmentation was obtained by using Fast Marching and Grow Cut segmentation methods. Preoperative MRI images of 20 T2 MRI of low-grade glioma patients from The Cancer Imaging Archive (TCIA) database were used to analyze brain tumor volume. The volume obtained from the two segmentation methods is based on the similarity between the two using the intra-method agreement between two segmentation methods with a 95% limit of agreement (LoA) value and difference volume average of 920 mm3 or 0.92 mL. Its shown that both methods had the same performance.","PeriodicalId":106778,"journal":{"name":"2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122476090","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

Automatic Measurement of Fetal Head Circumference from 2-Dimensional Ultrasound 二维超声胎儿头围的自动测量

2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2019-11-01 DOI: 10.1109/CENIM48368.2019.8973258

Cahya Perbawa Aji, M. Fatoni, T. A. Sardjono

{"title":"Automatic Measurement of Fetal Head Circumference from 2-Dimensional Ultrasound","authors":"Cahya Perbawa Aji, M. Fatoni, T. A. Sardjono","doi":"10.1109/CENIM48368.2019.8973258","DOIUrl":"https://doi.org/10.1109/CENIM48368.2019.8973258","url":null,"abstract":"Two-dimensional (2D) medical ultrasound is the primary imaging modality for the anatomical and functional surveillance of foetus due to its low cost, abundant availability, real-time capability, and the absence of radiation hazards. Head Circumference (HC) is one of the most important foetal biometrics in assessing foetal development during ultrasound examinations. Owing to its low signal-to-noise ratio, clinicians often have difficulty recognizing the foetal plane correctly from ultrasound 2D image. Moreover, clinicians often find difficulty to make the closest ellipse with only three minor and major parameter points provided by the ultrasound machine. The process of measuring HC manually by the clinician is quite an expensive procedure. Research on the automatic measurement of HC has become an active research area. In this study, an automatic measurement system for HC was proposed. The Convolutional Neural Network (CNN) is proposed to semantically segment foetal head from maternal and other foetal tissue. From this result it is expected to be easier to make an elliptical approach to the foetal plane because only the pixels belong to the head plane of the foetal are fed as input. According to the experimental result, in the process of the ellipse approach and its measurement, from thirteen test images the average semantic segmentation accuracy was 0.76 and the average error percentage of ellipse circumference measurement was 14.96%.","PeriodicalId":106778,"journal":{"name":"2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115494983","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: 6