2019 7th International Conference on Mechatronics Engineering (ICOM)最新文献

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ICOM'19 Keynote Speaker 国际博协2019年主题演讲
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/icom47790.2019.8952031
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引用次数: 0
Deep Learning Methods for Facial Expression Recognition 面部表情识别的深度学习方法
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/ICOM47790.2019.8952056
C. M. M. Refat, N. Azlan
{"title":"Deep Learning Methods for Facial Expression Recognition","authors":"C. M. M. Refat, N. Azlan","doi":"10.1109/ICOM47790.2019.8952056","DOIUrl":"https://doi.org/10.1109/ICOM47790.2019.8952056","url":null,"abstract":"Deep learning is very popular methods for facial expression recognition (FER) and classification. Different types of deep learning algorithms have been used for FER such as deep belief network (DBN) and convolutional neural network (CNN). In this paper, we analyze various deep learning methods and their results. We have chosen Deep convolutional neural network as the best algorithms for facial expression detection and classification. In our study, we have tested the algorithm using Japanese Female facial expressions database (JAFFE) datasets by anaconda software. The deep convolution neural networks with JAFFE datasets accuracy rate around 97.01%.","PeriodicalId":415914,"journal":{"name":"2019 7th International Conference on Mechatronics Engineering (ICOM)","volume":"315 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116382190","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
Assumptions of Lateral Acceleration Behavior Limits for Prediction Tasks in Autonomous Vehicles 自动驾驶汽车预测任务的横向加速度行为极限假设
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/ICOM47790.2019.8952059
Peter Zechel, Ralph Streiter, K. Bogenberger, U. Göhner
{"title":"Assumptions of Lateral Acceleration Behavior Limits for Prediction Tasks in Autonomous Vehicles","authors":"Peter Zechel, Ralph Streiter, K. Bogenberger, U. Göhner","doi":"10.1109/ICOM47790.2019.8952059","DOIUrl":"https://doi.org/10.1109/ICOM47790.2019.8952059","url":null,"abstract":"This paper presents an analysis of the euroFot data set to determine limits for the typical lateral acceleration behavior of drivers. Since recent studies indicate that lateral accelerations close to the physically possible limit are rarely used by drivers, predictions tasks for autonomous driving could consider a smaller, so-called natural lateral acceleration interval (NLAI) instead of all physically possible lateral accelerations. This NLAI should be as small as possible while still fulfilling all safety aspects. Therefore, valid assumptions are required on which the interval can be derived. Since a valid assumption which leads to minimal NLAI is yet unknown, four different assumptions concerning the lateral acceleration behavior are derived and evaluated in this paper. Thereby, detailed examinations regarding the relative frequencies of violations are presented. Finally, two assumptions are recommended for introducing an NLAI, depending on prediction time and safety requirements. Additionally, the advantages of utilizing an NLAI instead of all physically possible lateral accelerations are highlighted by comparing the results of an occupancy prediction approach.","PeriodicalId":415914,"journal":{"name":"2019 7th International Conference on Mechatronics Engineering (ICOM)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114487852","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
Performance Evaluation of Scenerio-aware Protocol for Producer Mobility Support in NDN 面向NDN生产者移动支持的场景感知协议性能评估
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/ICOM47790.2019.8952040
M. Z. Ahmed, A. M. Hassan, A. H. Alkali, A. H. Hashim, O. Khalifa, H. Ramli
{"title":"Performance Evaluation of Scenerio-aware Protocol for Producer Mobility Support in NDN","authors":"M. Z. Ahmed, A. M. Hassan, A. H. Alkali, A. H. Hashim, O. Khalifa, H. Ramli","doi":"10.1109/ICOM47790.2019.8952040","DOIUrl":"https://doi.org/10.1109/ICOM47790.2019.8952040","url":null,"abstract":"A scenario-aware is a type of protocol designed to enable NDN applications have specific interest/data naming convention and specific message exchange. Location update and Handoff analysis are the two basic classes of managing network mobility in both IP and NDN. Location update focus mainly on updating producer's mobility/movement information while handoff focus mainly on ensuring network access as the mobile producer continues to relocate/change its (Point of Attachment) PoA to another. Thus, the frequent mobility of the NDN producer is one high significant features of network mobility in an NDN environment. In this paper, the mobile producer is anchorless and is required to frequently change its Care of Address (CoA) as it relocates between multiple NDN access networks. This then has absolute effect on network performance of the mobility management at mobile producer's handoff. Therefore, a performance analysis for the mobile producer handoff between different NDN access networks using NDN scenario-aware protocol is presented using analytical approach and to be supported with simulation. Simulations were carried out using ndnSim 2.1 NS3-based. Analysis were estimated for delay during handoff and packet loss for interest/data exchange between mobile producers.","PeriodicalId":415914,"journal":{"name":"2019 7th International Conference on Mechatronics Engineering (ICOM)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116812282","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
Pneumatic actuation of a firefighting robot: A theoretical Foundation and an Empirical study 消防机器人气动驱动:理论基础与实证研究
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/ICOM47790.2019.8952050
M. T. Ajala, M. R. Khan, M. Salami, A. Shafie, M. Oladokun, M. Nor
{"title":"Pneumatic actuation of a firefighting robot: A theoretical Foundation and an Empirical study","authors":"M. T. Ajala, M. R. Khan, M. Salami, A. Shafie, M. Oladokun, M. Nor","doi":"10.1109/ICOM47790.2019.8952050","DOIUrl":"https://doi.org/10.1109/ICOM47790.2019.8952050","url":null,"abstract":"In recent times, the need for a self-powered, autonomous firefighting robot, which can cope in fire hot spots, is strongly required in fire emergencies. The obtainable firefighting robots lack efficient performance in such conditions due to less reliability of their electric-powered actuators in the high-temperature environment under fire emergency. Our previous study suggests a gas actuated propulsion system (GAPS) as an alternative to the identified limitations of the existing electric actuated propulsion system. The GAPS drives a carbon dioxide propelled autonomous firefighting robot (CAFFR), which uses dry ice as its power source. However, there still exists a lack of detailed understanding of the working principle of the proposed GAPS. Thus, this study provides a theoretical framework for the novel CAFFR. Upon establishing the working theory and the concept of the CAFFR, the research carried out an empirical analysis of the key influencing design parameters for the CAFFR pneumatic actuation. The study presents a mathematical model of the effects of the design parameters and after that, discusses its implications.","PeriodicalId":415914,"journal":{"name":"2019 7th International Conference on Mechatronics Engineering (ICOM)","volume":"10 14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116212493","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
Long Term Load Forecasting using Grey Wolf Optimizer - Artificial Neural Network 基于灰狼优化器-人工神经网络的长期负荷预测
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/ICOM47790.2019.8952051
Z. M. Yasin, N. A. Salim, N. F. Ab Aziz
{"title":"Long Term Load Forecasting using Grey Wolf Optimizer - Artificial Neural Network","authors":"Z. M. Yasin, N. A. Salim, N. F. Ab Aziz","doi":"10.1109/ICOM47790.2019.8952051","DOIUrl":"https://doi.org/10.1109/ICOM47790.2019.8952051","url":null,"abstract":"This paper presents a new technique namely Grey Wolf Optimizer- Artificial Neural Network (GWO-ANN) as a technique to forecast electrical load. GWO is a meta heuristic technique inspired by the hierarchy of leadership of the grey wolf hunting mechanism in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, the three main steps of hunting, searching for prey, encircling are also imitated in the algorithm. GWO is utilized to determine the optimal momentum rate and learning rate of ANN for accurate prediction. In the ANN configuration, the temperature, humidity, wind speed, maximum power, and average power were used as the input data. While total power was used as the output data. ANN is trained by adjusting the parameters of momentum rate and learning rate until the output data matches the actual data. The performance of GWO-ANN was compared to the performance of ANN and Particle Swarm Optimization - Artificial Neural Network (PSO-ANN). The results showed GWO-ANN provide better result in terms of the Mean Absolute Percentage Error (MAPE) and coefficients of determination (R2) as compared to other methods.","PeriodicalId":415914,"journal":{"name":"2019 7th International Conference on Mechatronics Engineering (ICOM)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124472915","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
State-driven Architecture Design for Safety-critical Software Product Lines 安全关键软件产品线的状态驱动架构设计
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/ICOM47790.2019.8952006
Mozamil Ebnauf, W. Abdelmoez, H. Ammar, Aisha Hassan, M. Abdelhamid
{"title":"State-driven Architecture Design for Safety-critical Software Product Lines","authors":"Mozamil Ebnauf, W. Abdelmoez, H. Ammar, Aisha Hassan, M. Abdelhamid","doi":"10.1109/ICOM47790.2019.8952006","DOIUrl":"https://doi.org/10.1109/ICOM47790.2019.8952006","url":null,"abstract":"The safety is considered one of the most critical issues in the design of cyber-physical systems (CPS). The Software Product-Line (SPL) and reusable software components are suitable approaches for CPS, which are often re-engineered from existing systems. Currently, the influence of architecture in assurance of software safety is being increasingly recognized. However, the safety-based architectural design methods are limited in SPLs because of the complexity and variabilities existing in SPL architectures. A new statechart-based safety pattern and adaptation of our previous SPL Architecture design method are presented in this paper. Also the paper describes a simplified safety assessment model which is used to evaluate the safety improvement in the design of the SPLA after using the proposed safety design pattern. Finally, to illustrate the effect of the design pattern in the PLA design, a simplified automated Electromechanical Braking System (EBS) product line is used as a running example. The results show that there is a considerable improvement in the system safety design after using the proposed safety pattern.","PeriodicalId":415914,"journal":{"name":"2019 7th International Conference on Mechatronics Engineering (ICOM)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116398962","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
Comparison of Machine Learning Classifiers for dimensionally reduced fMRI data using Random Projection and Principal Component Analysis 使用随机投影和主成分分析的机器学习分类器对降维fMRI数据的比较
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/ICOM47790.2019.8952005
Nur Farahana Mohd Suhaimi, Z. Htike
{"title":"Comparison of Machine Learning Classifiers for dimensionally reduced fMRI data using Random Projection and Principal Component Analysis","authors":"Nur Farahana Mohd Suhaimi, Z. Htike","doi":"10.1109/ICOM47790.2019.8952005","DOIUrl":"https://doi.org/10.1109/ICOM47790.2019.8952005","url":null,"abstract":"Machine learning has opened up the opportunity for understanding how the brain works. In this paper, functional magnetic resonance imaging (fMRI) data are analyzed with reduced dimension. We have carried out a performance comparison of random projection (RP) and principal component analysis (PCA) with different number of components of fMRI data. In addition to that, six different types of machine learning algorithm have been used. In particular, the Haxby dataset is chosen for our experiment. The dataset comprises 9 classes for object recognition. 10-fold cross validation step has been employed. We have discovered that RP outperforms PCA when the former is paired with logistic regression, Gaussian Naive Bayes and linear support vector machine. The best pair for this study was found to be PCA and k-nearest neighbors. Nevertheless, each algorithm was found to have its own strengths for fMRI classification approach.","PeriodicalId":415914,"journal":{"name":"2019 7th International Conference on Mechatronics Engineering (ICOM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130415996","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
Securing Medical Data Transmission Systems Based on Integrating Algorithm of Encryption and Steganography 基于加密与隐写集成算法的医疗数据传输系统安全
2019 7th International Conference on Mechatronics Engineering (ICOM) Pub Date : 2019-10-01 DOI: 10.1109/ICOM47790.2019.8952061
M. M. Hashim, Mustafa Sabah Taha, A. Aman, A. H. Hashim, M. Rahim, S. Islam
{"title":"Securing Medical Data Transmission Systems Based on Integrating Algorithm of Encryption and Steganography","authors":"M. M. Hashim, Mustafa Sabah Taha, A. Aman, A. H. Hashim, M. Rahim, S. Islam","doi":"10.1109/ICOM47790.2019.8952061","DOIUrl":"https://doi.org/10.1109/ICOM47790.2019.8952061","url":null,"abstract":"The awareness to secure medical data has significantly increased. Steganographic has binged an important topic especially in this area since it has the capability to avoid medical data breach. This paper proposes a new steganography scheme based on Bit Invert System (BIS) using three control random parameters. The random selection process is performed based on Henon Map Function (HMF). In order to increase the security level, affine cipher and Huffman method is used for encryption as well as to minimize the encrypt data prior to the embedding for high payload ability. This integration is effective due to two main reasons: first, checking, and mapping to determine 0- and 1-bits during embedding, and second, segmenting the secret data to track and map every bit in stego image. The results showed that the presented scheme can assure confidentiality and security of the medical data while maintaining the image quality.","PeriodicalId":415914,"journal":{"name":"2019 7th International Conference on Mechatronics Engineering (ICOM)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126390497","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: 14
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