2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)最新文献_第2页

Human Action Recognition based on Hybrid Deep Learning Model and Shearlet Transform 基于混合深度学习模型和Shearlet变换的人体动作识别

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271687

Nemir Al-Azzawi

{"title":"Human Action Recognition based on Hybrid Deep Learning Model and Shearlet Transform","authors":"Nemir Al-Azzawi","doi":"10.1109/ICITEE49829.2020.9271687","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271687","url":null,"abstract":"The hybrid deep learning model has become common in all recent studies dealing with machine vision and human action recognition. Most of the accuracy in revealing knowledge of machine vision is in extracting important features, including segmentation of the image. This paper proposes a new model for recognizing human actions from video sequences by integrating repetitive, gated recurrent neural networks across multiple scales with shearlet-based image segmentation extraction. Segmentations are the most critical information to distinguish human action. The feature extraction can impact the complexity of the calculation and the performance of the algorithm. The idea is to increase training robustness and improve segmentation through the use of the shearlet transform. Hence, the video classification based on a recurrent neural network and shearlet transform will work optimally. The proposed approach is evaluated on human activity videos using KTH, UCF-101, and UCF Sports Action datasets. The experimental results showed state-of-the-art performance in comparison to current methods. The average resulting classification accuracy is 95.1% for the KTH datasets. That was the optimal case in our proposed model reached.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130420150","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

Recent Trends of Left and Right Ventricle Segmentation in Cardiac MRI Using Deep Learning 基于深度学习的心脏MRI左、右心室分割研究进展

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271750

D. Irmawati, O. Wahyunggoro, I. Soesanti

引用次数: 4

Using Double-Density Dual Tree Wavelet Transform into MFCC for Noisy Speech Recognition 基于双密度对偶树小波变换的MFCC噪声语音识别

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271737

Hay Mar Soe Naing, Risanuri Hidayat, Rudy Hartanto, Y. Miyanaga

{"title":"Using Double-Density Dual Tree Wavelet Transform into MFCC for Noisy Speech Recognition","authors":"Hay Mar Soe Naing, Risanuri Hidayat, Rudy Hartanto, Y. Miyanaga","doi":"10.1109/ICITEE49829.2020.9271737","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271737","url":null,"abstract":"The automatic speech recognition has gained significant progress in technology as well as in many applications. However, speech fluctuations due to noise effects significantly reduce recognition accuracy, and recognition on noisy channels is more difficult to generate correct word sequences than in a clean environment. Extracting meaningful acoustic information from noisy speech utterances has been a challenging task recently. Therefore, we present a combination of Mel frequency cepstrum coefficient (MFCC) and double-density dual tree wavelet transformation denoising algorithm to recognize noisy speech utterances. Hybrid frame-level cross entropy deep neural network-hidden Markov model (DNN-HMM) is used as an acoustic modeling activity. According to a suite of experiments, the proposed denoising method provides better performance without affecting the accuracy of higher sound intensity levels. Experimental results demonstrate that the recognition accuracy reach up to 96.6% in 10dB, 91.84% in 5dB, 78.05% in 0dB and 49.37% in -5dB, respectively.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128557867","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

ICITEE 2020 Cover Page ICITEE 2020封面

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/icitee49829.2020.9271751

引用次数: 0

A Process Checkpoint Evaluation at User Space of Docker Framework on Distributed Computing Infrastructure 分布式计算基础设施上Docker框架用户空间进程检查点评估

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271718

D. Adhipta, S. Sulistyo, Widyawan Widyawan

{"title":"A Process Checkpoint Evaluation at User Space of Docker Framework on Distributed Computing Infrastructure","authors":"D. Adhipta, S. Sulistyo, Widyawan Widyawan","doi":"10.1109/ICITEE49829.2020.9271718","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271718","url":null,"abstract":"This paper presents an evaluation of a process migration checkpoint issues, especially the potential collision of resources usage at user level (space) over a distributed computation infrastructure. In particular, within the docker and its container framework when application checkpointing and restore (resume) occurs quite regularly for shared computing resources. This evaluation will be utilized and be part of larger research titled \"Modelling Fast User Space Mutual Exclusive (FUTEX) Process Threads in Single-System Image (SSI)\". This paper is primarily written from the literature study and simple exploration experiment and are performed to gather preliminary understanding of the potential issues, performance caveats and testbed setup. The continuation future research will involve nondeterministic modelling simulation using Color Petri Net as comparison to the empirical data resulted from the testbed. It is the aim of this paper to serve as an early study of the larger research as an early exploration utilizing docker and container framework.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123816151","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

Reserve Cost Allocation on Wheeling Using Tracing Method 基于追踪法的轮转储备成本分摊

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271724

Yusuf Susilo Wijoyo, Sasongko Pramono Hadi, S. Sarjiya

{"title":"Reserve Cost Allocation on Wheeling Using Tracing Method","authors":"Yusuf Susilo Wijoyo, Sasongko Pramono Hadi, S. Sarjiya","doi":"10.1109/ICITEE49829.2020.9271724","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271724","url":null,"abstract":"Renewable energy has site-specific characteristics and uncertainty in its production. The location of large-scale renewable energy generators, which are generally far from the load location, requires the construction of a transmission network which is relatively difficult to build. Fluctuating production causes the need for backup supplies. These site-specific characteristics and uncertainty problems are opportunities for utility to provide wheeling and reserve services. This reserve service creates additional costs for system operation that must be added to wheeling costs as a component of the reserve cost. The research was conducted on a modified IEEE 30 bus system. The impact of not producing wheeling generators on utility operating costs was observed with optimal power flow. The impact obtained is then allocated to the wheeling entity using the tracing method, which in this study consists of two entities. The calculation results show an increase in utility operating costs by 115.13 $/hr when the wheeling generator is not producing. The first wheeling entity bears costs of 23.20 $/hr and the second wheeling entity bears 91.93 $/hr.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126882193","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

Short-Term Load Forecasting With Long Short-Term Memory: A Case Study of Java-Bali System 基于长短期记忆的短期负荷预测——以Java-Bali系统为例

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271763

Muhammad Fadhil Ainuri, Sarjiya, I. Ardiyanto

引用次数: 1

Variational Feature Extraction of Two-Dimensional Variational Mode Decomposition for Alzheimer’s Disease Classification 二维变分模态分解的变分特征提取用于阿尔茨海默病分类

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271761

Ungsumalee Suttapakti, Peerasak Pianprasit

引用次数: 2

Assessment of High Voltage Power Transformer Aging Condition Based on Health Index Value Considering Its Apparent and Actual Age 考虑视龄和实际龄的高压电力变压器健康指数值老化状况评估

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271778

Winanda Riga Tamma, Rahman Azis Prasojo, S. Suwarno

引用次数: 8

Factors Affecting Intention to Use of Government Websites in Thai Elder: The Webqual Model 影响泰国老年人政府网站使用意向的因素:Webqual模型

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271711

Rattanaporn Nilpong, Bundit Thanasopon

引用次数: 3