Pub Date : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468885
Nabila Shahnaz Khan, Mehedi Hasan Muaz, A. Kabir, M. Islam
With the advancement of information technologies, mobile health (mHealth) technologies can be leveraged for patient self-management, patient diagnosis and determining the probability of being affected by some disease. Diabetes mellitus is a chronic and lifestyle disease and millions of people from all over the world fall victim to it. Although there are some mobile apps keeping track of calories, sugar taken, medicine doses, lifestyle, blood glucose, blood pressure, weight of individuals and giving suggestion about food, exercises to prevent or control diabetes, no application has been found that was explicitly developed to analyze the risk of being a diabetic patient. Therefore, the objective of this paper is to develop an intelligent mHealth application based on machine learning to assess his/her possibility of being diabetic, prediabetic or nondiabetic without the assistance of any doctor or medical tests.
{"title":"Diabetes Predicting mHealth Application Using Machine Learning","authors":"Nabila Shahnaz Khan, Mehedi Hasan Muaz, A. Kabir, M. Islam","doi":"10.1109/WIECON-ECE.2017.8468885","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468885","url":null,"abstract":"With the advancement of information technologies, mobile health (mHealth) technologies can be leveraged for patient self-management, patient diagnosis and determining the probability of being affected by some disease. Diabetes mellitus is a chronic and lifestyle disease and millions of people from all over the world fall victim to it. Although there are some mobile apps keeping track of calories, sugar taken, medicine doses, lifestyle, blood glucose, blood pressure, weight of individuals and giving suggestion about food, exercises to prevent or control diabetes, no application has been found that was explicitly developed to analyze the risk of being a diabetic patient. Therefore, the objective of this paper is to develop an intelligent mHealth application based on machine learning to assess his/her possibility of being diabetic, prediabetic or nondiabetic without the assistance of any doctor or medical tests.","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130177248","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 : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468915
Shalini Pal, Mukesh Kumar, R. Kumar
The demand response approach has become an essential regulatory option to drive the future smart grid. As per the conventional power system with thermal generation, it is not able to meet the future growing energy demand which leads the application of smart grid with an incorporation of renewable energy sources as a solution. The demand response programs offer the inclusion of renewable sources and electric vehicle as a solution to meet the demand at the peak periods when the electricity grid charges are very high. The load demand of user can be managed by employing the electric vehicle for households. This paper presents a demand response framework to build an economic and appropriate approach to meet the user demand in the smart grid structure. The residential user comprises different energy consuming loads in terms of various appliances such as base load, shiftable appliances, EV load, and storage system. The framework present here build a optimization structure where each user gets freedom and privacy to schedule their appliances. The simulation results demonstrate the economic benefits reaped by the customers are highly motivational to execute such approach in practical scenarios.
{"title":"Price Aware Residential Demand Response With Renewable Sources and Electric Vehicle","authors":"Shalini Pal, Mukesh Kumar, R. Kumar","doi":"10.1109/WIECON-ECE.2017.8468915","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468915","url":null,"abstract":"The demand response approach has become an essential regulatory option to drive the future smart grid. As per the conventional power system with thermal generation, it is not able to meet the future growing energy demand which leads the application of smart grid with an incorporation of renewable energy sources as a solution. The demand response programs offer the inclusion of renewable sources and electric vehicle as a solution to meet the demand at the peak periods when the electricity grid charges are very high. The load demand of user can be managed by employing the electric vehicle for households. This paper presents a demand response framework to build an economic and appropriate approach to meet the user demand in the smart grid structure. The residential user comprises different energy consuming loads in terms of various appliances such as base load, shiftable appliances, EV load, and storage system. The framework present here build a optimization structure where each user gets freedom and privacy to schedule their appliances. The simulation results demonstrate the economic benefits reaped by the customers are highly motivational to execute such approach in practical scenarios.","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"34 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114032159","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 : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468918
H. Pathak, B. Kumar
Graphene planted gas sensors have been extensively handled for different gas sensing mechanism exclusively for mapping the chunk of noxious gasses such as carbon dioxide, nitrogen dioxide etc. present in our surrounding. Hence, for its exertion in practical life many designing constraints arise which are dealt on different parameters in this paper. In the adjoining paper we fixate in developing a graphene drooped sensor with varying substrate for better calliberation. The paper reviews on the variety of material and there diverse fabrication techniques to achieve the desired sensitivity on the application of various toxic gasses and correlate them on varying aspects like complexity, sensitivity, material used, calliberation.
{"title":"Graphene Planted Organic Gas Sensor","authors":"H. Pathak, B. Kumar","doi":"10.1109/WIECON-ECE.2017.8468918","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468918","url":null,"abstract":"Graphene planted gas sensors have been extensively handled for different gas sensing mechanism exclusively for mapping the chunk of noxious gasses such as carbon dioxide, nitrogen dioxide etc. present in our surrounding. Hence, for its exertion in practical life many designing constraints arise which are dealt on different parameters in this paper. In the adjoining paper we fixate in developing a graphene drooped sensor with varying substrate for better calliberation. The paper reviews on the variety of material and there diverse fabrication techniques to achieve the desired sensitivity on the application of various toxic gasses and correlate them on varying aspects like complexity, sensitivity, material used, calliberation.","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123297945","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 : 2017-12-01DOI: 10.1109/wiecon-ece.2017.8468931
Divya Atolia, S. Yadav
A planar monopole antenna for ultra-wide band (UWB) application has been presented in this letter. In order to gain an excellent band-rejection characteristic at WLAN band and ITU band, a rectangular shaped patch and a CSRR slot with two resonators near the feed line has been designed. The performance of the proposed antenna is investigated by using the software CST MW Simulator and the results achieve good impedance matching over an operating bandwidth of 3.4 – 13.60 GHz, which meets the requirement of UWB application well. Dual band notch curves have been achieved by inserting a slot in the patch and by location two resonators near the feed lines. The proposed antenna has good return loss graph having two notches first covering the WLAN band and notching the 5.5GHz second at 7.6GHz. Surface current distribution at various frequencies is also shown in the letter with few radiation pattern graphs in Eplane and H-plane
{"title":"A Rectangular Monopole UWB Patch Antenna with CSRR slots having dual band notch Characteristics","authors":"Divya Atolia, S. Yadav","doi":"10.1109/wiecon-ece.2017.8468931","DOIUrl":"https://doi.org/10.1109/wiecon-ece.2017.8468931","url":null,"abstract":"A planar monopole antenna for ultra-wide band (UWB) application has been presented in this letter. In order to gain an excellent band-rejection characteristic at WLAN band and ITU band, a rectangular shaped patch and a CSRR slot with two resonators near the feed line has been designed. The performance of the proposed antenna is investigated by using the software CST MW Simulator and the results achieve good impedance matching over an operating bandwidth of 3.4 – 13.60 GHz, which meets the requirement of UWB application well. Dual band notch curves have been achieved by inserting a slot in the patch and by location two resonators near the feed lines. The proposed antenna has good return loss graph having two notches first covering the WLAN band and notching the 5.5GHz second at 7.6GHz. Surface current distribution at various frequencies is also shown in the letter with few radiation pattern graphs in Eplane and H-plane","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127969977","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 : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468900
Dibya Bharti, M. De
The incorporation of distributed generations and loads as separate cluster is known as microgrid which functions independently or in parallel with conventional electric grid. The configuration of electrical distribution system is changing from conventional radial topology to meshed topology due to integration of distributed energy resources into electric power system. The presence of several microgrids appends challenges in analysis of system for other supplementary services which largely depend on load flow. This paper aims to transform electrical network into an equivalent transportation network for electrical microgrid network. Based on concepts of graph theory and diakoptics, a methodology is developed for transforming a meshed microgrid network into a transportation network which will exhibit all the necessary information about the network. The applicability of proposed method is demonstrated by considering microgrids connected in meshed configuration.
{"title":"A New Graph Theoretic Power Flow Framework for Microgrid","authors":"Dibya Bharti, M. De","doi":"10.1109/WIECON-ECE.2017.8468900","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468900","url":null,"abstract":"The incorporation of distributed generations and loads as separate cluster is known as microgrid which functions independently or in parallel with conventional electric grid. The configuration of electrical distribution system is changing from conventional radial topology to meshed topology due to integration of distributed energy resources into electric power system. The presence of several microgrids appends challenges in analysis of system for other supplementary services which largely depend on load flow. This paper aims to transform electrical network into an equivalent transportation network for electrical microgrid network. Based on concepts of graph theory and diakoptics, a methodology is developed for transforming a meshed microgrid network into a transportation network which will exhibit all the necessary information about the network. The applicability of proposed method is demonstrated by considering microgrids connected in meshed configuration.","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126512344","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 : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468932
N. Garg, S. Bawa
Today cloud computing has emerged as an esteemed Information Technology (IT) platform which offers variety of quality services to its users. Offering storage space is a pivotal cloud computing service where users can outsource their local data and get relieve from its maintenance burden. However, the loss of proprietorship on data creates the need of a mechanism for auditing integrity of outsourced data. Due to expertise and resource limitations, a Third Party Auditor (TPA) is required to perform an integrity audit on user’s sensitive data. Data Integrity Auditing (DIA) protocols proposed so far relies completely on Public Key Infrastructures (PKI). Management of certificates of public keys in PKI is a complex process. In the proposed work, the features of Identity Based Signatures (IBS) are combined with public verification of data to construct an efficient protocol for DIA in cloud storage. Security model for proposed ID-PAPC has been established in a ROM and relies on stability of Computational Diffie Hellman Problem (CDHP).
{"title":"ID-PAPC: Identity based Public Auditing Protocol for Cloud Computing","authors":"N. Garg, S. Bawa","doi":"10.1109/WIECON-ECE.2017.8468932","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468932","url":null,"abstract":"Today cloud computing has emerged as an esteemed Information Technology (IT) platform which offers variety of quality services to its users. Offering storage space is a pivotal cloud computing service where users can outsource their local data and get relieve from its maintenance burden. However, the loss of proprietorship on data creates the need of a mechanism for auditing integrity of outsourced data. Due to expertise and resource limitations, a Third Party Auditor (TPA) is required to perform an integrity audit on user’s sensitive data. Data Integrity Auditing (DIA) protocols proposed so far relies completely on Public Key Infrastructures (PKI). Management of certificates of public keys in PKI is a complex process. In the proposed work, the features of Identity Based Signatures (IBS) are combined with public verification of data to construct an efficient protocol for DIA in cloud storage. Security model for proposed ID-PAPC has been established in a ROM and relies on stability of Computational Diffie Hellman Problem (CDHP).","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134277573","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 : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468891
N. Vinutha, Sonu Sharma, P. D. Shenoy, K. Venugopal
The neuropsychological battery of scores, are the measures of cognitive domains of human brain, that are considered as important features to distinguish healthy subjects from the subjects, suffering from Mild Cognitive Impairment (MCI). The instances of about 5542, with four time visits are separated from the total collected instances of the National Alzheimer’s Coordinating Center (NACC) database. The analysis of the selected data shows that the large number of subjects is identified for 66–75 and 76–85 age groups. The Genetic Algorithms (GA) applied on the neuropsychological scores at the baseline visit, selects the best subset of scores required for the clinical diagnosis, and these scores are evaluated by the logistic regression model using Area Under Curve (AUC), accuracy and Mean Squared Error (MSE) as the metric. Simulations result show that a highest classification accuracy of 0.9427, AUC of 0.9713 and less error rate of 0.041 is achieved for the combination of four neuropsychological scores Global Staging of Clinical Dementia Rating (CDRGLOB), Geriatric Depression Scale (GDS), Logical Memory Delayed (MEMUNITS), Digit Span Forward Length (DIGIFLEN). These scores are predominantly selected by the GA across many runs and thus have significant role for screening MCI subjects at the baseline visit.
神经心理学评分是对人类大脑认知领域的测量，被认为是区分健康受试者与患有轻度认知障碍(MCI)受试者的重要特征。大约5542例，4次访问的实例从国家阿尔茨海默病协调中心(National Alzheimer 's Coordinating Center, NACC)数据库中收集的总实例中分离出来。对所选数据的分析表明，在66-75岁和76-85岁年龄组中确定了大量的受试者。遗传算法(GA)应用于基线访问时的神经心理学分数，选择临床诊断所需分数的最佳子集，并通过以曲线下面积(AUC)，准确度和均方误差(MSE)为度量的逻辑回归模型对这些分数进行评估。仿真结果表明，将临床痴呆总体分期评分(CDRGLOB)、老年抑郁量表(GDS)、逻辑记忆延迟(MEMUNITS)、数字跨距前向长度(DIGIFLEN) 4个神经心理学评分组合在一起，分类准确率最高为0.9427,AUC为0.9713，错误率为0.041。这些分数主要是由GA在许多次运行中选择的，因此在基线访问时筛选MCI受试者具有重要作用。
{"title":"Optimization of Neuropsychological Scores at the Baseline Visit Using Evolutionary Technique","authors":"N. Vinutha, Sonu Sharma, P. D. Shenoy, K. Venugopal","doi":"10.1109/WIECON-ECE.2017.8468891","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468891","url":null,"abstract":"The neuropsychological battery of scores, are the measures of cognitive domains of human brain, that are considered as important features to distinguish healthy subjects from the subjects, suffering from Mild Cognitive Impairment (MCI). The instances of about 5542, with four time visits are separated from the total collected instances of the National Alzheimer’s Coordinating Center (NACC) database. The analysis of the selected data shows that the large number of subjects is identified for 66–75 and 76–85 age groups. The Genetic Algorithms (GA) applied on the neuropsychological scores at the baseline visit, selects the best subset of scores required for the clinical diagnosis, and these scores are evaluated by the logistic regression model using Area Under Curve (AUC), accuracy and Mean Squared Error (MSE) as the metric. Simulations result show that a highest classification accuracy of 0.9427, AUC of 0.9713 and less error rate of 0.041 is achieved for the combination of four neuropsychological scores Global Staging of Clinical Dementia Rating (CDRGLOB), Geriatric Depression Scale (GDS), Logical Memory Delayed (MEMUNITS), Digit Span Forward Length (DIGIFLEN). These scores are predominantly selected by the GA across many runs and thus have significant role for screening MCI subjects at the baseline visit.","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131179976","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 : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468930
Reena Mamgain, Rashi Jain
Signal processor for airborne Active Electronically Scanned Array (AESA) radar has stringent requirement in terms of dynamic load handling, latency and throughput requirement. In this paper, Radar Signal Processor(RSP) realisation for airborne radar is discussed with specific emphasis on S/W architecture for its deployment on multiprocessor based H/W platform using Commercial Off The Shelf(COTS) board. The S/W architecture is based on master slave configuration which leverages parallelism. This architecture is termed as Cluster Of Processors(CoPs). Sizing analysis and benchmarking of computational resources is also done to ascertain the number of processors required to meet realtime performance. In addition to it, a case study for RSP is also carried to outline the realisation of optimised RSP.
{"title":"Airborne Radar Signal Processor Realisation","authors":"Reena Mamgain, Rashi Jain","doi":"10.1109/WIECON-ECE.2017.8468930","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468930","url":null,"abstract":"Signal processor for airborne Active Electronically Scanned Array (AESA) radar has stringent requirement in terms of dynamic load handling, latency and throughput requirement. In this paper, Radar Signal Processor(RSP) realisation for airborne radar is discussed with specific emphasis on S/W architecture for its deployment on multiprocessor based H/W platform using Commercial Off The Shelf(COTS) board. The S/W architecture is based on master slave configuration which leverages parallelism. This architecture is termed as Cluster Of Processors(CoPs). Sizing analysis and benchmarking of computational resources is also done to ascertain the number of processors required to meet realtime performance. In addition to it, a case study for RSP is also carried to outline the realisation of optimised RSP.","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127613069","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 : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468906
Satyajit Anand, Sandeep Jaiswal, P. K. Ghosh
In this paper, we propose an automatic epilepsy diagnosis based on the statistical feature extraction. At outset, EEG signals are recorded from the patient and pre-processed to remove the unwanted signals: Dc drift elimination, high pass and low pass filter techniques are applied to preprocess the EEG signals. The noise is diminished from the signal by the method of Hilbert-Huang Transform (HHT). Empirical mode decomposition is the portion of HHT by which intrinsic mode functions (IMFs) are separated from the signal. In Hilbert spectral analysis, the instant frequency of IMFs is executed using Hilbert transform, which allows the finding of localized features. Empirical wavelet transform (EWT) is applied to acquire EWT components from the EEG signals. These features are further extracted in to five frequency subbands based on clinical interest. Genetic algorithm is structured for displaying the best features from the localized features. Based on the optimized features, support vector machine is applied to classify and evaluated the signals as epileptic seizure and seizure-free EEG signals. An experimental result shows that the proposed method can attain a very high accuracy.
{"title":"Automatic Focal Eplileptic Seizure Detection in EEG Signals","authors":"Satyajit Anand, Sandeep Jaiswal, P. K. Ghosh","doi":"10.1109/WIECON-ECE.2017.8468906","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468906","url":null,"abstract":"In this paper, we propose an automatic epilepsy diagnosis based on the statistical feature extraction. At outset, EEG signals are recorded from the patient and pre-processed to remove the unwanted signals: Dc drift elimination, high pass and low pass filter techniques are applied to preprocess the EEG signals. The noise is diminished from the signal by the method of Hilbert-Huang Transform (HHT). Empirical mode decomposition is the portion of HHT by which intrinsic mode functions (IMFs) are separated from the signal. In Hilbert spectral analysis, the instant frequency of IMFs is executed using Hilbert transform, which allows the finding of localized features. Empirical wavelet transform (EWT) is applied to acquire EWT components from the EEG signals. These features are further extracted in to five frequency subbands based on clinical interest. Genetic algorithm is structured for displaying the best features from the localized features. Based on the optimized features, support vector machine is applied to classify and evaluated the signals as epileptic seizure and seizure-free EEG signals. An experimental result shows that the proposed method can attain a very high accuracy.","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131337587","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 : 2017-12-01DOI: 10.1109/WIECON-ECE.2017.8468871
Shamman Noor, Ehsan Ahmed Dhrubo, A. T. Minhaz, C. Shahnaz, S. Fattah
The better a machine realizes non-verbal ways of communication, such as emotion, better levels of human machine interrelation is achieved. This paper describes a method for recognizing emotions from human Speech and visual data for machine to understand. For extraction of features, videos consisting 6 classes of emotions (Happy, Sad, Fear, Disgust, Angry, and Surprise) of 44 different subjects from eNTERFACE05 database are used. As video feature, Horizontal and Vertical Cross Correlation (HCCR and VCCR) signals, extracted from regions-eye and mouth, are used. As Speech feature, Perceptual Linear Predictive Coefficients (PLPC) and Mel-frequency Cepstral Coefficients (MFCC), extracted from Wavelet Packet Coefficients, are used in conjunction with PLPC and MFCC extracted from original signal. For both types of feature, K-Nearest Neighbour (KNN) multiclass classification method is applied separately for identifying emotions expressed in speech and through facial movement. Emotion expressed in a video file is identified by concatenating the Speech and video features and applying KNN classification method.
机器越能实现非语言的交流方式，如情感，就能达到更好的人机交互水平。本文描述了一种从人类语音和视觉数据中识别情感的方法，以供机器理解。特征提取使用eNTERFACE05数据库中44个不同受试者的6类情绪(Happy, Sad, Fear, Disgust, Angry, and Surprise)视频。视频特征采用了从眼睛和嘴巴区域提取的水平和垂直互相关信号(HCCR和VCCR)。语音特征采用从小波包系数中提取的感知线性预测系数(PLPC)和Mel-frequency倒谱系数(MFCC)与从原始信号中提取的PLPC和MFCC相结合的方法。对于这两种类型的特征，分别应用k -最近邻(KNN)多类分类方法来识别语音中表达的情绪和通过面部运动表达的情绪。将视频文件中的语音特征和视频特征拼接起来，应用KNN分类方法对视频文件中的情感进行识别。
{"title":"Audio Visual Emotion Recognition Using Cross Correlation and Wavelet Packet Domain Features","authors":"Shamman Noor, Ehsan Ahmed Dhrubo, A. T. Minhaz, C. Shahnaz, S. Fattah","doi":"10.1109/WIECON-ECE.2017.8468871","DOIUrl":"https://doi.org/10.1109/WIECON-ECE.2017.8468871","url":null,"abstract":"The better a machine realizes non-verbal ways of communication, such as emotion, better levels of human machine interrelation is achieved. This paper describes a method for recognizing emotions from human Speech and visual data for machine to understand. For extraction of features, videos consisting 6 classes of emotions (Happy, Sad, Fear, Disgust, Angry, and Surprise) of 44 different subjects from eNTERFACE05 database are used. As video feature, Horizontal and Vertical Cross Correlation (HCCR and VCCR) signals, extracted from regions-eye and mouth, are used. As Speech feature, Perceptual Linear Predictive Coefficients (PLPC) and Mel-frequency Cepstral Coefficients (MFCC), extracted from Wavelet Packet Coefficients, are used in conjunction with PLPC and MFCC extracted from original signal. For both types of feature, K-Nearest Neighbour (KNN) multiclass classification method is applied separately for identifying emotions expressed in speech and through facial movement. Emotion expressed in a video file is identified by concatenating the Speech and video features and applying KNN classification method.","PeriodicalId":188031,"journal":{"name":"2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124904240","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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