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2019 International Conference on Communication and Signal Processing (ICCSP)最新文献

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Performance Assessment of M-ary ASK, FSK, PSK, QAM and FQAM in AWGN Channel AWGN信道中M-ary ASK、FSK、PSK、QAM和FQAM的性能评估
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8697922
G. S. Kishore, H. Rallapalli
{"title":"Performance Assessment of M-ary ASK, FSK, PSK, QAM and FQAM in AWGN Channel","authors":"G. S. Kishore, H. Rallapalli","doi":"10.1109/ICCSP.2019.8697922","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8697922","url":null,"abstract":"The ever growing demand for high data rates with optimum bandwidth usage and better quality need to be addressed by modern digital communication systems. Choosing a better modulation technique that provides higher immunity to noise and channel distortion along with optimum bandwidth usage could be a possible solution. The main objective of this paper is to give an overview of various digital modulation techniques employed in wireless Communication systems and to conclude with a better modulation technique among them. This paper presents analysis of different modulation techniques such as Amplitude Shift Keying (ASK), Phase Shift Keying (PSK), Frequency Shift Keying (FSK), Quadrature Amplitude Modulation (QAM), and the novel modulation technique: Hybrid Frequency and Quadrature Amplitude Modulation (HFQAM), with the help of MATLAB. These comparisons yield HFQAM as a better choice for communicating in a wireless channel with better efficiency and optimum bandwidth.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121126280","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
Performing Predictive Analysis using Machine Learning on the Information Retrieved from Production Data of Oil & Gas Upstream Segment 利用机器学习对油气上游生产数据信息进行预测分析
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8698107
A. K, R. Ramasree, M. Faisal
{"title":"Performing Predictive Analysis using Machine Learning on the Information Retrieved from Production Data of Oil & Gas Upstream Segment","authors":"A. K, R. Ramasree, M. Faisal","doi":"10.1109/ICCSP.2019.8698107","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8698107","url":null,"abstract":"Machine learning is an area of knowledge, which supports many of the established and reliable techniques in Artificial intelligence. Oil and gas industry involve many sensors to collect data continuously. Especially the main focus, is on the Production data which will help the industry to perform Predictive analysis that will forecast what outputs we may get in future. The current research work focuses on the data produced from an oil well, over a month and then tries to predict the average oil rate, based on certain elements. In order to perform this, a predictive tool RapidMiner is used, and Regression model is applied. This research work helps in predicting the most dependent factor on the predictive variable, which is Average Oil Rate.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121438588","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: 3
Smart Phone as a Controlling Device for Smart Home using Speech Recognition 智能手机作为智能家居的语音识别控制设备
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8697923
Sakshi Bajpai, D. Radha
{"title":"Smart Phone as a Controlling Device for Smart Home using Speech Recognition","authors":"Sakshi Bajpai, D. Radha","doi":"10.1109/ICCSP.2019.8697923","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8697923","url":null,"abstract":"The smart homes are now becoming the requirement of the modern world. The days are now becoming thing of past when Smart Homes were only limited to sci-fi movies, it has gained much achievements and popularity over the last few decades. Home automation has given an entirely new meaning to living as compared to past days. Earlier all our home appliances such as television, AC, lights, fans etc. were operated by a specific remote controller for each appliance. There comes a problem too as handling all those remotes is hectic sometimes especially for the older and the disabled one. In this paper, an overview of a solution to this problem is discussed that all such devices can also be operated by only a single remote controller rather than one remote controller per device. This universal controller can be easily implemented in a cost-effective way by just using any existing smartphone and an Arduino microcontroller via Bluetooth transmission. Thus, smartphone-based controlling devices eliminate the need for carrying many different remote controllers. In addition, controlling devices by speech avoids looking for various buttons/options while operating the devices. The study aims at developing a signal based smart home network for controlling the electronic appliances by the voice recognition system.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128619544","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: 30
Implementation of Deep Learning Algorithm with Perceptron using TenzorFlow Library 基于TenzorFlow库的感知器深度学习算法实现
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8697910
Arshiya Begum, Farheen Fatima, Asfia Sabahath
{"title":"Implementation of Deep Learning Algorithm with Perceptron using TenzorFlow Library","authors":"Arshiya Begum, Farheen Fatima, Asfia Sabahath","doi":"10.1109/ICCSP.2019.8697910","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8697910","url":null,"abstract":"In recent years, Deep Learning, Machine Learning, and Artificial Intelligence are highly focused concepts of data science. Deep learning has achieved success in the field of Computer Vision, Speech and Audio Processing, and Natural Language Processing. It has the strong learning ability that can improve utilization of datasets for the feature extraction compared to traditional Machine Learning Algorithm. Perceptron is the essential building block for creating a deep Neural Network. The perceptron model is the more general computational model. It analyzes the unsupervised data, making it a valuable tool for data analytics. A key task of this paper is to develop and analyze learning algorithm. It begins with deep learning with perceptron and how to apply it using TensorFlow to solve various issues. The main part of this paper is to make perceptron learning algorithm well behaved with non-separable training datasets. This type of algorithm is suitable for Machine Learning, Deep Learning, Pattern Recognition, and Connectionist Expert System.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124068912","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: 10
Wearable Cardiorespiratory Monitoring Device for Heart Attack Prediction 用于心脏病发作预测的穿戴式心肺监测装置
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8698059
P. Sasidharan, T. Rajalakshmi, U. Snekhalatha
{"title":"Wearable Cardiorespiratory Monitoring Device for Heart Attack Prediction","authors":"P. Sasidharan, T. Rajalakshmi, U. Snekhalatha","doi":"10.1109/ICCSP.2019.8698059","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8698059","url":null,"abstract":"The paper aims at developing a wearable cardio respiratory monitoring device that could monitor and display 4 parameters in real time simultaneously on a phone screen or on a computer screen. A prototype system that can evaluate heart rate, respiration rate, peripheral capillary oxygen saturation (SpO2) and temperature is designed. The hardware will be cost effective and of miniaturised in size that can be worn on a daily basis. Individuals who have a history of heart attack is shown to have a constant variation in parameters like heart rate, respiration rate and peripheral capillary oxygen saturation over a time period of 1 week or even 2 weeks. Thus the data taken from individuals are stored and analysed using a mobile application. Using this information the chances of heart attack can be predicted and individuals can be warned beforehand.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116171267","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: 11
Comparative Analysis of Different Machine Learning Algorithms in Classification of Suitability of Renewable Energy Resource 不同机器学习算法在可再生能源适宜性分类中的比较分析
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8697969
Aamir Shahab, M.P. Singh
{"title":"Comparative Analysis of Different Machine Learning Algorithms in Classification of Suitability of Renewable Energy Resource","authors":"Aamir Shahab, M.P. Singh","doi":"10.1109/ICCSP.2019.8697969","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8697969","url":null,"abstract":"Renewable energies are one of the most important energy resources in this modern era not only due to deficiency of other energy resources but also because they are friendly to the environment. Their efficient utilization must be implemented to gain the most out of them. In this paper, a comparative analysis of the performance of different machine learning algorithms is presented for finding the suitable type of renewable resource for a location. A classification model of the best performing algorithm is implemented on the google earth engine, and their results are discussed.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125356694","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: 3
Demand and Revenue Forecasting through Machine Learning 通过机器学习预测需求和收入
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8698011
Narayana Darapaneni, Sreelakshminarayanan Muthuraj, K. Prabakar, M. Sridhar
{"title":"Demand and Revenue Forecasting through Machine Learning","authors":"Narayana Darapaneni, Sreelakshminarayanan Muthuraj, K. Prabakar, M. Sridhar","doi":"10.1109/ICCSP.2019.8698011","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8698011","url":null,"abstract":"In this Contribution, we investigate and explore on logistics data from sensors and real time devices to derive insights and identify the key features which play deterministic role for predicting the demand and revenue. In this contribution we compare the performance of various time series forecasting models and supervised learning algorithms to predict the demand and revenue to maximize the customer experience and yield greater revenue yield. RMSE has used as Key performance indicator for the comparison, From our analysis results we infer that latitude, longitude, hour of the day and day of week are important in predicting the outcome, further our study indicates Multivariate Time Series forecasting seems to be better performing for revenue and random forest seems to be performing in predicting the demand.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126373065","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: 3
An Efficient Data Security in Medical Report using Block Chain Technology 基于区块链技术的高效医疗报告数据安全
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8698058
Mary Subaja Christo, Anigo Merjora A, P. G, P. C., R. M
{"title":"An Efficient Data Security in Medical Report using Block Chain Technology","authors":"Mary Subaja Christo, Anigo Merjora A, P. G, P. C., R. M","doi":"10.1109/ICCSP.2019.8698058","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8698058","url":null,"abstract":"The health care services industry is always showing signs of change and supporting new advancements and advances. One of the predominant requirements in today’s health care systems is to protect the patient's medical report against potential attackers. Hence, it is basic to have secure information that can just approve people can get to the patient's medical report. So, We have proposed Block chain technology as a disbursed approach to grant security in accessing the medical report of a patient. It’s composed of three 1. Authentication, 2. Encryption and 3. Data Retrieval using Block Chain technology. For authentication – Quantum Cryptography, for Encryption – AES and for Data Retrieval – SHA algorithms are used to resist the frequent attacks. This proposed framework may likewise ensure the protection of the patients and moreover keeps up the security and trustworthiness of the health care system.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124316028","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: 18
A Brief Review on: MRI Images Reconstruction using GAN GAN在MRI图像重建中的应用综述
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8698083
Priyanka Shende, M. Pawar, Sandeep Kakde
{"title":"A Brief Review on: MRI Images Reconstruction using GAN","authors":"Priyanka Shende, M. Pawar, Sandeep Kakde","doi":"10.1109/ICCSP.2019.8698083","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8698083","url":null,"abstract":"This paper introduces compressed sensing Magnetic Resonance Imaging (MRI) which gives rapid achievement and it is more advantageous for many clinical application. This reduces the scanning cost as well as patient burden. Each images reconstructed in very less time which is suitable for real time processing. This paper uses the deep learning approach for better construction of edges and texture of the image. We also performed explanatory studies with existing schemes and recently introduced deep learning system. Compared to other method, Generative Adversarial Network (GAN) method provides better reconstruction with original image detail. In Generative adversarial network, a purified learning method is used to balance generator, which provides all over network to make less damages or corruption and discriminator finds prediction of authenticity.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121613581","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: 12
Deep Learning based Pedestrian Detection at all Light Conditions 在所有光照条件下基于深度学习的行人检测
2019 International Conference on Communication and Signal Processing (ICCSP) Pub Date : 2019-04-04 DOI: 10.1109/ICCSP.2019.8698101
Koti Naga Renu Chebrolu, P. Kumar
{"title":"Deep Learning based Pedestrian Detection at all Light Conditions","authors":"Koti Naga Renu Chebrolu, P. Kumar","doi":"10.1109/ICCSP.2019.8698101","DOIUrl":"https://doi.org/10.1109/ICCSP.2019.8698101","url":null,"abstract":"Multispectral pedestrian detection is becoming increasingly important in the field of computer vision due to its applications in driver assistance, surveillance, and monitoring. In this paper, we propose a brightness aware model for pedestrian detection using deep learning. A novel brightness aware mechanism depicts various illumination conditions, so as to enable prediction of day/ night scenario. Based on the detection of the brightness aware mechanism, a color or thermal model is used to detect pedestrians under day or night conditions respectively. The proposed method trained on FLIR-ADAS Thermal dataset and PASCAL VOC Color dataset, has achieved a mAP of ‘81.27%’, which outperforms the current state of the art.","PeriodicalId":194369,"journal":{"name":"2019 International Conference on Communication and Signal Processing (ICCSP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121740294","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: 21
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