Pub Date : 2019-02-28DOI: 10.1109/KBEI.2019.8735037
H. Razavi, Hamidreza Sarabadani, Ahmad Karimisefat, Jean-Fabrice Lebraty
Banks are tended to increase their transactions income against the costs of an ATM, which includes installation, setting up and maintenance. Due to dependence of income on various factors such as geography and demography, ATM’s income function is complex. Therefore, understanding its behavior could lead to discover the mathematical relation between ATM installations weighted variables versus ATM’s profitability. In this study based on artificial neural networks (ANNs) prediction model and the real data of 374 ATMs in Tehran, a comprehensive income model is presented which can predict the profitability of an ATM. In order to have accurate analysis and better training for ANNs, statistical methods are used to find out the correlation between ATM installation variables and its profitability. Results show that the feed-forward and Elman networks can predict the income of transactions with minimum error. Applying these analyses will help banks in making optimized decisions to provide ATM services to customers.
{"title":"Profitability Prediction for ATM Transactions Using Artificial Neural Networks: A Data-Driven Analysis","authors":"H. Razavi, Hamidreza Sarabadani, Ahmad Karimisefat, Jean-Fabrice Lebraty","doi":"10.1109/KBEI.2019.8735037","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735037","url":null,"abstract":"Banks are tended to increase their transactions income against the costs of an ATM, which includes installation, setting up and maintenance. Due to dependence of income on various factors such as geography and demography, ATM’s income function is complex. Therefore, understanding its behavior could lead to discover the mathematical relation between ATM installations weighted variables versus ATM’s profitability. In this study based on artificial neural networks (ANNs) prediction model and the real data of 374 ATMs in Tehran, a comprehensive income model is presented which can predict the profitability of an ATM. In order to have accurate analysis and better training for ANNs, statistical methods are used to find out the correlation between ATM installation variables and its profitability. Results show that the feed-forward and Elman networks can predict the income of transactions with minimum error. Applying these analyses will help banks in making optimized decisions to provide ATM services to customers.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129180797","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8734937
Zohreh Razani, M. Keyvanpour
Search-based software engineering has made substantial progress in recent decades. It is an approach to software engineering in which search-based optimization algorithms are used to solve software engineering problems. Search-based software refactoring (SBSR) is used to improve the quality and maintainability of the software by finding a proper sequence of refactorings using search-based optimization algorithms. Fitness functions utilized to evaluate refactoring solutions in search-based algorithms play a vital role. Indeed, the more accurate and more effective the fitness function is, the more reliable the provided solutions will be. In this paper, we plan to accurately assess this area from the perspective of metrics used in fitness functions to evaluate solutions. To this end, first we propose a classification of metrics used for solution evaluation. Then, the challenges of each category are investigated. Understanding the challenges and ways to handle them can lead to an important comparison and assessment of the presented approaches. It will also direct researchers to accurately recognizing and improving existing approaches in the future.
{"title":"SBSR Solution Evaluation: Methods and Challenges Classification","authors":"Zohreh Razani, M. Keyvanpour","doi":"10.1109/KBEI.2019.8734937","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734937","url":null,"abstract":"Search-based software engineering has made substantial progress in recent decades. It is an approach to software engineering in which search-based optimization algorithms are used to solve software engineering problems. Search-based software refactoring (SBSR) is used to improve the quality and maintainability of the software by finding a proper sequence of refactorings using search-based optimization algorithms. Fitness functions utilized to evaluate refactoring solutions in search-based algorithms play a vital role. Indeed, the more accurate and more effective the fitness function is, the more reliable the provided solutions will be. In this paper, we plan to accurately assess this area from the perspective of metrics used in fitness functions to evaluate solutions. To this end, first we propose a classification of metrics used for solution evaluation. Then, the challenges of each category are investigated. Understanding the challenges and ways to handle them can lead to an important comparison and assessment of the presented approaches. It will also direct researchers to accurately recognizing and improving existing approaches in the future.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127504013","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8734942
Narges Hatamzadeh, Hossein Esmailbeygi, M. Lotfizad
This paper introduces a novel structure for the comparator of analog – to -digital convertor with built- in threshold. Thus the resistor string can be eliminated. The proposed comparator is simulated using HSpice in TSMC 0.18μm CMOS process. The proposed structure reduces the power consumption and occupies less area compared to conventional comparators due to the elimination of the resistor string in analog-to-digital converters.
{"title":"A New Built-in-Threshold CMOS Comparator","authors":"Narges Hatamzadeh, Hossein Esmailbeygi, M. Lotfizad","doi":"10.1109/KBEI.2019.8734942","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734942","url":null,"abstract":"This paper introduces a novel structure for the comparator of analog – to -digital convertor with built- in threshold. Thus the resistor string can be eliminated. The proposed comparator is simulated using HSpice in TSMC 0.18μm CMOS process. The proposed structure reduces the power consumption and occupies less area compared to conventional comparators due to the elimination of the resistor string in analog-to-digital converters.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126721029","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8735012
Arezoo Nazerdeylami, Babak Majidi, A. Movaghar
A significant portion of the tourism industry and the fishing communities depend on the health of the seashores for their livelihood. Visual interpretation of this environment provides the required information for autonomous agents for decision support in large-scale operations such as smart beach management. Deep Neural Networks (DNN) are recently used for image classification and scene understanding with very good results. In this paper, a DNN is used for object detection in the scenes from seashore areas. This interpretation is used for decision support for various smart beach applications. The technique used for smart beach scene interpretation is the transfer learning on a pre-trained DNN using VGG architecture. The Single Shot Detector (SSD) technique is used for object detection in the collected dataset from the beach areas. A dataset from the beaches of the Caspian Sea is collected in order to provide an extensive simulation in the real-world setting. The experimental results showed that the accuracy of the presented technique is acceptable for various applications in the seashore environment.
{"title":"Smart Coastline Environment Management Using Deep Detection of Manmade Pollution and Hazards","authors":"Arezoo Nazerdeylami, Babak Majidi, A. Movaghar","doi":"10.1109/KBEI.2019.8735012","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735012","url":null,"abstract":"A significant portion of the tourism industry and the fishing communities depend on the health of the seashores for their livelihood. Visual interpretation of this environment provides the required information for autonomous agents for decision support in large-scale operations such as smart beach management. Deep Neural Networks (DNN) are recently used for image classification and scene understanding with very good results. In this paper, a DNN is used for object detection in the scenes from seashore areas. This interpretation is used for decision support for various smart beach applications. The technique used for smart beach scene interpretation is the transfer learning on a pre-trained DNN using VGG architecture. The Single Shot Detector (SSD) technique is used for object detection in the collected dataset from the beach areas. A dataset from the beaches of the Caspian Sea is collected in order to provide an extensive simulation in the real-world setting. The experimental results showed that the accuracy of the presented technique is acceptable for various applications in the seashore environment.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126777882","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8735065
Samira Sirzadeh Haji Mahmood, Peyman Babaei
The principal objective of this paper is to develop a face matching method based on facial feature extraction. The first stage to build a robust face matching system is to extract corresponding points between a pair of images. A method based on feature vectors has been used to match images. Since the images illumination, motion, rotation, and scale are different, we have used the SIFT algorithm, which is robust to these variations, for extracting Keypoints. After determining Keypoints for both images and calculating their respective feature vectors, the degree of similarity between two images is evaluated. Besides, the feature vectors of the images are compared with the feature vectors of each reference image to determine the overall similarity between two images. In this paper, we use the SIFT algorithm along with the neural network and the Kepenekci approach and compare the results of these two methods.
{"title":"Using SIFT Descriptors for Face Recognition Based on Neural Network and Kepenekci Approach","authors":"Samira Sirzadeh Haji Mahmood, Peyman Babaei","doi":"10.1109/KBEI.2019.8735065","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735065","url":null,"abstract":"The principal objective of this paper is to develop a face matching method based on facial feature extraction. The first stage to build a robust face matching system is to extract corresponding points between a pair of images. A method based on feature vectors has been used to match images. Since the images illumination, motion, rotation, and scale are different, we have used the SIFT algorithm, which is robust to these variations, for extracting Keypoints. After determining Keypoints for both images and calculating their respective feature vectors, the degree of similarity between two images is evaluated. Besides, the feature vectors of the images are compared with the feature vectors of each reference image to determine the overall similarity between two images. In this paper, we use the SIFT algorithm along with the neural network and the Kepenekci approach and compare the results of these two methods.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114287350","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8735043
Hamidreza Damghani, H. Hosseinian, Leila Damghani
The RFID technology is now widely used and combined with everyday life. RFID Tag is a wireless device used to identify individuals and objects, in fact, it is a combination of the chip and antenna that sends the necessary information to an RFID Reader. On the other hand, an RFID Reader converts received radio waves into digital information and then provides facilities such as sending data to the computer and processing them. Radio frequency identification is a comprehensive processing technology that has led to a revolution in industry and medicine as an alternative to commercial barcodes. RFID Tag is used to tracking commodities and personal assets in the chain stores and even the human body and medical science. However, security and privacy problems have not yet been solved satisfactorily. There are many technical and economic challenges in this direction. In this paper, some of the latest technical research on privacy and security problems has been investigated in radio-frequency identification and security bit method, and it has been shown that in order to achieve this level of individual security, multiple technologies of RFID security development should combine with each other. These solutions should be cheap, efficient, reliable, flexible and long-term.
{"title":"Investigating attacks to improve security and privacy in RFID systems using the security bit method","authors":"Hamidreza Damghani, H. Hosseinian, Leila Damghani","doi":"10.1109/KBEI.2019.8735043","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735043","url":null,"abstract":"The RFID technology is now widely used and combined with everyday life. RFID Tag is a wireless device used to identify individuals and objects, in fact, it is a combination of the chip and antenna that sends the necessary information to an RFID Reader. On the other hand, an RFID Reader converts received radio waves into digital information and then provides facilities such as sending data to the computer and processing them. Radio frequency identification is a comprehensive processing technology that has led to a revolution in industry and medicine as an alternative to commercial barcodes. RFID Tag is used to tracking commodities and personal assets in the chain stores and even the human body and medical science. However, security and privacy problems have not yet been solved satisfactorily. There are many technical and economic challenges in this direction. In this paper, some of the latest technical research on privacy and security problems has been investigated in radio-frequency identification and security bit method, and it has been shown that in order to achieve this level of individual security, multiple technologies of RFID security development should combine with each other. These solutions should be cheap, efficient, reliable, flexible and long-term.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122078924","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8734989
Negin Pouyanfar, J. Nourinia, C. Ghobadi, Kioumars Pedram
A printed multiband monopole antenna consists of four composite right/left-handed (CRLH) metamaterial unit cells is presented and discussed in this paper. Employing such CRLH metamaterial loadings have considerably reduced antenna size and increased antenna gain. The proposed antenna has a compact size of 30×25×1.6mm3 and provides multiband operation at 2.5, 4.1, 5.25 and 6.1 GHz, with reflection coefficient of better than -10dB which are within the practical wireless frequency bands. The proposed antenna has been fabricated and experimentally tested and good agreements between measured and simulated results can be observed.
{"title":"A Compact Multiband Metamaterial-Based Antenna for WLAN and WiMAX Applications","authors":"Negin Pouyanfar, J. Nourinia, C. Ghobadi, Kioumars Pedram","doi":"10.1109/KBEI.2019.8734989","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734989","url":null,"abstract":"A printed multiband monopole antenna consists of four composite right/left-handed (CRLH) metamaterial unit cells is presented and discussed in this paper. Employing such CRLH metamaterial loadings have considerably reduced antenna size and increased antenna gain. The proposed antenna has a compact size of 30×25×1.6mm3 and provides multiband operation at 2.5, 4.1, 5.25 and 6.1 GHz, with reflection coefficient of better than -10dB which are within the practical wireless frequency bands. The proposed antenna has been fabricated and experimentally tested and good agreements between measured and simulated results can be observed.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129267386","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8734947
H. Hosseinian, Hamidreza Damghani
Microgrids are low voltage wise dispersion systems including different conveyed vitality asset (DER) which can be worked as interconnected to the primary dissemination network or as islanded on the off chance that it is disengaged from the fundamental circulated matrix. The target of this examination is the ideal planning of a half and half wind-PV-diesel microgrid framework with contemplations for battery vitality stockpiling and vulnerability of sustainable power source asset. To do this, a mixture wind-PV-diesel framework is completely demonstrated with contemplations for the battery as a vitality stockpiling framework. Likewise, the vulnerability related to wind and PV control is considered and the reproduction results are introduced for two cases. In the main case, without diesel generators, it appears mixture wind-PV framework can fulfill need and battery is effectively repay the vulnerability of wind and PV control. For another situation, the absolute expense of mixture framework is expired by utilizing diesel and battery as opposed to purchasing power from the network.
{"title":"Ideal planning of a hybrid wind-PV-diesel microgrid framework with considerations for battery energy storage and uncertainty of renewable energy resources","authors":"H. Hosseinian, Hamidreza Damghani","doi":"10.1109/KBEI.2019.8734947","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734947","url":null,"abstract":"Microgrids are low voltage wise dispersion systems including different conveyed vitality asset (DER) which can be worked as interconnected to the primary dissemination network or as islanded on the off chance that it is disengaged from the fundamental circulated matrix. The target of this examination is the ideal planning of a half and half wind-PV-diesel microgrid framework with contemplations for battery vitality stockpiling and vulnerability of sustainable power source asset. To do this, a mixture wind-PV-diesel framework is completely demonstrated with contemplations for the battery as a vitality stockpiling framework. Likewise, the vulnerability related to wind and PV control is considered and the reproduction results are introduced for two cases. In the main case, without diesel generators, it appears mixture wind-PV framework can fulfill need and battery is effectively repay the vulnerability of wind and PV control. For another situation, the absolute expense of mixture framework is expired by utilizing diesel and battery as opposed to purchasing power from the network.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130362967","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8734949
M. Rostamnia, S. Kianian
The Influence maximization problem is a fundamental problem in social networks analysis which aims to select a small set of nodes, as a seed set, and maximizes influence spread through the seed set under a specific propagation model. In this paper, the effect of performing vertex cover, as a preprocess, has been investigated on the influence maximization algorithms under the independent cascade model. Proposed method eliminates ineffective nodes from the main calculation process to find the most influential nodes. Based on the results, combining the proposed algorithm with several methods on real-world datasets confirms the efficiency of the method.
{"title":"Vertex cover preprocessing for influence maximization algorithms","authors":"M. Rostamnia, S. Kianian","doi":"10.1109/KBEI.2019.8734949","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734949","url":null,"abstract":"The Influence maximization problem is a fundamental problem in social networks analysis which aims to select a small set of nodes, as a seed set, and maximizes influence spread through the seed set under a specific propagation model. In this paper, the effect of performing vertex cover, as a preprocess, has been investigated on the influence maximization algorithms under the independent cascade model. Proposed method eliminates ineffective nodes from the main calculation process to find the most influential nodes. Based on the results, combining the proposed algorithm with several methods on real-world datasets confirms the efficiency of the method.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126812565","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}
Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8734992
M. K. Moridani, Mahdyar Heydar, Seyed Sina Jabbari Behnam
Sleep Apnea Syndrome is one of the most common and dangerous causes of sleep disorder that the suspected patients are tested (examined) by recording various types of vital signals during sleep using polysomnography (PSG). Since human body rhythms have a chaotic and non-linear behavior, the nonlinear analysis of body parameters provides the researchers with valuable information about body behavior during the disease and its comparison with the normal state for a more accurate examination of the diseases. The purpose of this is to diagnose apnea events using linear and nonlinear analyses and combining the EMG, ECG and EEG signals in patients with Obstructive Sleep Apnea (OSA). The research data are obtained by the Physionet database including 25 subjects (21 males and 4 females). After performing the pre-processing phase to remove the noise related to EMG, ECG, EEG and artifact signals based on the corresponding algorithms, the healthy and apnea sleep ranges are separated from one another. Linear and nonlinear analyses in MATLAB environment are performed on signals and conditions which are evaluated in healthy sleep and during sleep apnea at different stages of sleep in patients with OSA by multilayer perceptron classifier. The best result of the proposed algorithm obtained by combining the signals and the specificity, sensitivity and accuracy values are 96.87 ± 1.78, 97.14 ± 2.24 and 98.09 ± 2.15 respectively. The results show that the proposed algorithm can help doctors and nurses as a diagnostic tool with more accuracy than similar techniques.
{"title":"A Reliable Algorithm Based on Combination of EMG, ECG and EEG Signals for Sleep Apnea Detection : (A Reliable Algorithm for Sleep Apnea Detection)","authors":"M. K. Moridani, Mahdyar Heydar, Seyed Sina Jabbari Behnam","doi":"10.1109/KBEI.2019.8734992","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734992","url":null,"abstract":"Sleep Apnea Syndrome is one of the most common and dangerous causes of sleep disorder that the suspected patients are tested (examined) by recording various types of vital signals during sleep using polysomnography (PSG). Since human body rhythms have a chaotic and non-linear behavior, the nonlinear analysis of body parameters provides the researchers with valuable information about body behavior during the disease and its comparison with the normal state for a more accurate examination of the diseases. The purpose of this is to diagnose apnea events using linear and nonlinear analyses and combining the EMG, ECG and EEG signals in patients with Obstructive Sleep Apnea (OSA). The research data are obtained by the Physionet database including 25 subjects (21 males and 4 females). After performing the pre-processing phase to remove the noise related to EMG, ECG, EEG and artifact signals based on the corresponding algorithms, the healthy and apnea sleep ranges are separated from one another. Linear and nonlinear analyses in MATLAB environment are performed on signals and conditions which are evaluated in healthy sleep and during sleep apnea at different stages of sleep in patients with OSA by multilayer perceptron classifier. The best result of the proposed algorithm obtained by combining the signals and the specificity, sensitivity and accuracy values are 96.87 ± 1.78, 97.14 ± 2.24 and 98.09 ± 2.15 respectively. The results show that the proposed algorithm can help doctors and nurses as a diagnostic tool with more accuracy than similar techniques.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126814166","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}
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