Pub Date : 2019-03-27DOI: 10.1109/ICCMC.2019.8819663
G. Nagaraj, C. SumanthSimha, R. HarishChandraG, M. Indiramma
Diabetic Retinopathy (DR) is one of the foremost causes for the presence of blindness in the recent times. Ophthalmologists usually diagnose the presence and severity of DR through visual assessment of the retinal fundus images by manual examination. This process of manual diagnosis of DR is a very laborious and time consuming task. With the increasing rate of diabetic retinopathy patients in the world, the number of color fundus images generated has increased exponentially. Due to this large number, there is a huge delay in recognizing the early symptoms of DR and providing timely treatment. Hence, to address this unmet and increasing need, there is a need for developing an automated framework of Diabetic Retinopathy diagnosis. Hence, in this study, we have proposed a Deep Learning framework for DR diagnosis. The study uses a modified version of one of the standard Convolutional Neural Network (CNN) for solving DR fundus image classification problems. The proposed framework efficiently and quickly report whether the person has DR or not and if present, reports the severity of the disease. The framework implemented helps in giving timely treatment to the patients irrespective of geographical and economic constraints.
{"title":"Deep Learning Framework for Diabetic Retinopathy Diagnosis","authors":"G. Nagaraj, C. SumanthSimha, R. HarishChandraG, M. Indiramma","doi":"10.1109/ICCMC.2019.8819663","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819663","url":null,"abstract":"Diabetic Retinopathy (DR) is one of the foremost causes for the presence of blindness in the recent times. Ophthalmologists usually diagnose the presence and severity of DR through visual assessment of the retinal fundus images by manual examination. This process of manual diagnosis of DR is a very laborious and time consuming task. With the increasing rate of diabetic retinopathy patients in the world, the number of color fundus images generated has increased exponentially. Due to this large number, there is a huge delay in recognizing the early symptoms of DR and providing timely treatment. Hence, to address this unmet and increasing need, there is a need for developing an automated framework of Diabetic Retinopathy diagnosis. Hence, in this study, we have proposed a Deep Learning framework for DR diagnosis. The study uses a modified version of one of the standard Convolutional Neural Network (CNN) for solving DR fundus image classification problems. The proposed framework efficiently and quickly report whether the person has DR or not and if present, reports the severity of the disease. The framework implemented helps in giving timely treatment to the patients irrespective of geographical and economic constraints.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"54 1","pages":"648-653"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79417030","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 : 2019-03-27DOI: 10.1109/ICCMC.2019.8819852
D. D’souza, V. D. Shastrimath
Sound effects play an important role in today’s music industry. The various effects, modulations to the voice is done. here we present a musical sound effects processing system based on virtual analog modelling and Digital Signal Processing techniques. The modelling is using in matlab and the order of effects are sequenced depending on the musicians choice. The various techniques of Digital signal processing are used .The comparison of results obtained are done with the available system.
{"title":"Modelling of Audio Effects for Vocal and Music Synthesis in Real Time","authors":"D. D’souza, V. D. Shastrimath","doi":"10.1109/ICCMC.2019.8819852","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819852","url":null,"abstract":"Sound effects play an important role in today’s music industry. The various effects, modulations to the voice is done. here we present a musical sound effects processing system based on virtual analog modelling and Digital Signal Processing techniques. The modelling is using in matlab and the order of effects are sequenced depending on the musicians choice. The various techniques of Digital signal processing are used .The comparison of results obtained are done with the available system.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"679 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76867336","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819642
N. HemaRajini.
Customized healthcare models offer online health care services to satisfy the medicinal and assisting requirements of the elderly people. The evolution of IoT redesigns the advanced medicare with hopeful technical, financial, and communal projection. In the paper, we review the advancements in the IoT-based healthcare methodologies. Additionally, this paper investigates the individual IoT security and privacy characteristics such as security needs and threat models from the health care aspects. Additionally, this review explains the way how various technologies like big data, ambient intellect, and wearable can be influenced in a healthcare framework; it resolves different eHealth policies and IoT guidelines globally to identify how they support economy and society with respect to sustainable development; and allows new research directions on IoT based healthcare sector.
{"title":"A Comprehensive Survey on Internet of Things Based Healthcare Services and its Applications","authors":"N. HemaRajini.","doi":"10.1109/ICCMC.2019.8819642","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819642","url":null,"abstract":"Customized healthcare models offer online health care services to satisfy the medicinal and assisting requirements of the elderly people. The evolution of IoT redesigns the advanced medicare with hopeful technical, financial, and communal projection. In the paper, we review the advancements in the IoT-based healthcare methodologies. Additionally, this paper investigates the individual IoT security and privacy characteristics such as security needs and threat models from the health care aspects. Additionally, this review explains the way how various technologies like big data, ambient intellect, and wearable can be influenced in a healthcare framework; it resolves different eHealth policies and IoT guidelines globally to identify how they support economy and society with respect to sustainable development; and allows new research directions on IoT based healthcare sector.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75132597","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819666
S. Akshayaa, R. Vidhya, M. HimavyshnaviA, K. KrishnanNambooriP
Chronic pain is one of the major health issues which affects wellbeing of casualties ranging from orthopedic damages to unbearable cancer pain. Though analgesics aids in reducing pain sensitization, it has its own defect of causing side effects such as drug resistance and habit formation. Evolutionary research has evidenced that by mutating "ZFHX2" gene, one can achieve pain insensitivity. This work emphases on 1) Designing an early mutation detection tool to identify the presence of pain inducing gene ZFHX2 among various patients from pathological biopsy images using deep convolution neural network. 2) Pharmacogenomic analysis comprising of genomics, epigenomics, metagenomics, environmental genomics has been performed in ZFHX2 gene to identify genetic signature, one of the reasons behind causing chronic pain. 3) Block chain algorithm has been used to secure valuable patient clinical data obtained from pharmacogenomic and other analysis to maintain records in order to avoid clinical theft.
{"title":"Exploring Pain Insensitivity Inducing Gene ZFHX2 by using Deep Convolutional Neural Network","authors":"S. Akshayaa, R. Vidhya, M. HimavyshnaviA, K. KrishnanNambooriP","doi":"10.1109/ICCMC.2019.8819666","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819666","url":null,"abstract":"Chronic pain is one of the major health issues which affects wellbeing of casualties ranging from orthopedic damages to unbearable cancer pain. Though analgesics aids in reducing pain sensitization, it has its own defect of causing side effects such as drug resistance and habit formation. Evolutionary research has evidenced that by mutating \"ZFHX2\" gene, one can achieve pain insensitivity. This work emphases on 1) Designing an early mutation detection tool to identify the presence of pain inducing gene ZFHX2 among various patients from pathological biopsy images using deep convolution neural network. 2) Pharmacogenomic analysis comprising of genomics, epigenomics, metagenomics, environmental genomics has been performed in ZFHX2 gene to identify genetic signature, one of the reasons behind causing chronic pain. 3) Block chain algorithm has been used to secure valuable patient clinical data obtained from pharmacogenomic and other analysis to maintain records in order to avoid clinical theft.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80374920","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819643
L. Naveen, S. MohanH
Generally, weather is comprised of numerous parameters including rainfall, precipitation, wind speed, etc. Environmental weather forecast is a testing errand for researchers and it has drawn a great deal of research enthusiasm in the recent years. Our study considers a wide variety of weather figure methods which can observe weather in the midst, or month to month or annually by considering the available meteorological information. So the precise forecast of weather parameters is emerging as a challenging task due to their dynamic environment conditions. Different machine learning systems are connected to foresee air parameters. Along with weather prediction, various applications based on Numerical Weather Prediction outputs are also analyzed.
{"title":"Atmospheric Weather Prediction Using various machine learning Techniques: A Survey","authors":"L. Naveen, S. MohanH","doi":"10.1109/ICCMC.2019.8819643","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819643","url":null,"abstract":"Generally, weather is comprised of numerous parameters including rainfall, precipitation, wind speed, etc. Environmental weather forecast is a testing errand for researchers and it has drawn a great deal of research enthusiasm in the recent years. Our study considers a wide variety of weather figure methods which can observe weather in the midst, or month to month or annually by considering the available meteorological information. So the precise forecast of weather parameters is emerging as a challenging task due to their dynamic environment conditions. Different machine learning systems are connected to foresee air parameters. Along with weather prediction, various applications based on Numerical Weather Prediction outputs are also analyzed.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81783442","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 : 2018-10-09DOI: 10.1109/ICCMC.2018.8487519
S. G. Nayak
In the present day knowledge, there is an massive requisite of developing appropriate data communication interfaces for real time embedded systems. Field Programmable Gate Array (FPGA) gives various means, which can be programmed for constructing an effective embedded unit. The FPGA configuration is generally specified using a hardware description language (HDL). VHDL (VHSIC hardware description language) is a hardware description language used in electronic design automation to explain digital and mixed-signal structures such as field programmable gate arrays (FPGA) and integrated circuits. This work proposes a technique to design and implement a 32 bit ALU which is a digital circuit that performs arithmetic and logical operations on Xilinx ISE using VHDL.
{"title":"Implementation of 32-Bit Arithmetic Logic Unit on Xilinx using VHDL","authors":"S. G. Nayak","doi":"10.1109/ICCMC.2018.8487519","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487519","url":null,"abstract":"In the present day knowledge, there is an massive requisite of developing appropriate data communication interfaces for real time embedded systems. Field Programmable Gate Array (FPGA) gives various means, which can be programmed for constructing an effective embedded unit. The FPGA configuration is generally specified using a hardware description language (HDL). VHDL (VHSIC hardware description language) is a hardware description language used in electronic design automation to explain digital and mixed-signal structures such as field programmable gate arrays (FPGA) and integrated circuits. This work proposes a technique to design and implement a 32 bit ALU which is a digital circuit that performs arithmetic and logical operations on Xilinx ISE using VHDL.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"142 1","pages":"525-529"},"PeriodicalIF":0.0,"publicationDate":"2018-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76432881","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 : 2018-02-01DOI: 10.1109/ICCMC.2018.8487230
Shalu Mall, A. Sharma
A frequent research in the area of cloud computing is due to its rapid demand and growth. Visualizing the development, it could be said that the upcoming time of technology is mostly depends on cloud technique. It make available to us "as a service" on user request. It could be an IAAS, SAAS or PAAS. The CSP bounding with the customers are highly rely upon how efficiently or smoothly the customers is using the cloud services, which is in succession rely on the powerful cloud managing. Other services, like data mining are more demanding, might worsen the speed due to more traffic on the cloud nodes. This requires the balance of load on cloud server by sharing the job to the suitable cloud cluster on the server. This review paper represents a correlation of existing methods for stack adjusting in distributed computing.
{"title":"Analyzing Load on Cloud: A Review","authors":"Shalu Mall, A. Sharma","doi":"10.1109/ICCMC.2018.8487230","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487230","url":null,"abstract":"A frequent research in the area of cloud computing is due to its rapid demand and growth. Visualizing the development, it could be said that the upcoming time of technology is mostly depends on cloud technique. It make available to us \"as a service\" on user request. It could be an IAAS, SAAS or PAAS. The CSP bounding with the customers are highly rely upon how efficiently or smoothly the customers is using the cloud services, which is in succession rely on the powerful cloud managing. Other services, like data mining are more demanding, might worsen the speed due to more traffic on the cloud nodes. This requires the balance of load on cloud server by sharing the job to the suitable cloud cluster on the server. This review paper represents a correlation of existing methods for stack adjusting in distributed computing.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"19 1","pages":"651-653"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74601056","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 : 2018-02-01DOI: 10.1109/ICCMC.2018.8487832
Prachi R. Gondane, Rukhsar M. Sheikh, Kajol A. Chawre, Vivian V. Wasnik, A. Badar, M. Hasan
In this paper, wavelet transform and artificial neural network (ANN) is used for processing current waveforms and distinguish between inrush current, fault and normal situation. Wavelet transform is used to analyze and detect various frequency components present in the signal. ANN is a tool which is utilized for classification of data based on specific properties. Different types of power system combinations are used in simulation. Fault detection is an important part for safety of electric power system. For the synthesis of signals and the classification of current conditions, WT and ANN are used in collectively.
{"title":"INRUSH CURRENT DETECTION USING WAVELET TRANSFORM AND ARTIFICIAL NEURAL NETWORK","authors":"Prachi R. Gondane, Rukhsar M. Sheikh, Kajol A. Chawre, Vivian V. Wasnik, A. Badar, M. Hasan","doi":"10.1109/ICCMC.2018.8487832","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487832","url":null,"abstract":"In this paper, wavelet transform and artificial neural network (ANN) is used for processing current waveforms and distinguish between inrush current, fault and normal situation. Wavelet transform is used to analyze and detect various frequency components present in the signal. ANN is a tool which is utilized for classification of data based on specific properties. Different types of power system combinations are used in simulation. Fault detection is an important part for safety of electric power system. For the synthesis of signals and the classification of current conditions, WT and ANN are used in collectively.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"88 1","pages":"866-868"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75416183","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 : 2018-02-01DOI: 10.1109/ICCMC.2018.8487514
K. Angelo
Image processing is an ever increasing research scope area where real time surveillance systems will increases the opportunity to the researchers for developing new modules for all the problems. Particularly in complex video processing operations security, intelligence processing is much needed in the society to satisfy the individuals. Basic object detection and tracking has different techniques and many automated systems are available now days to analyze the particular portion or object from the video. Estimation of moving object from the video sequence provides robustness for same colors for object and the background. In view of reducing the robustness and improving the performance of object detecting and tracking system the proposed model used Markov model based background subtraction. It uses neighborhood method to improve the background performance and Markov random field is used to estimate the energy function to optimize the real time experimental results. Generating saliency map combines the texture and cues to explore the linearly generated objects and tracked using component labeling.
{"title":"A novel approach on object detection and tracking using adaptive background subtraction method","authors":"K. Angelo","doi":"10.1109/ICCMC.2018.8487514","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487514","url":null,"abstract":"Image processing is an ever increasing research scope area where real time surveillance systems will increases the opportunity to the researchers for developing new modules for all the problems. Particularly in complex video processing operations security, intelligence processing is much needed in the society to satisfy the individuals. Basic object detection and tracking has different techniques and many automated systems are available now days to analyze the particular portion or object from the video. Estimation of moving object from the video sequence provides robustness for same colors for object and the background. In view of reducing the robustness and improving the performance of object detecting and tracking system the proposed model used Markov model based background subtraction. It uses neighborhood method to improve the background performance and Markov random field is used to estimate the energy function to optimize the real time experimental results. Generating saliency map combines the texture and cues to explore the linearly generated objects and tracked using component labeling.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"109 1","pages":"1055-1059"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77854357","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 : 2018-02-01DOI: 10.1109/ICCMC.2018.8488114
P. Balamurali Krishna, P. Sinha
Nonlinear loads are the source of harmonic injections in power system. These are complains in distortion of sinusoidal voltage and current waveforms. This paper objective is to detect harmonic sources and calculations of their injection levels to enhance power quality. For the proposed methodology the Niche Binary Particle Swarm optimization (NBPSO) technique is used to place optimally Harmonic Measurement Analyzer (HMA) units in power system to make entire system observable and worthwhile.
{"title":"Detection of Power System Harmonics Using NBPSO Based Optimally Placed Harmonic Measurement Analyser Units","authors":"P. Balamurali Krishna, P. Sinha","doi":"10.1109/ICCMC.2018.8488114","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8488114","url":null,"abstract":"Nonlinear loads are the source of harmonic injections in power system. These are complains in distortion of sinusoidal voltage and current waveforms. This paper objective is to detect harmonic sources and calculations of their injection levels to enhance power quality. For the proposed methodology the Niche Binary Particle Swarm optimization (NBPSO) technique is used to place optimally Harmonic Measurement Analyzer (HMA) units in power system to make entire system observable and worthwhile.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"87 21 1","pages":"369-373"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84043398","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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