Pub Date : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653701
M. Gayathri Devi, S. Manjula
This paper is about study of comparative analysis of Spatial and Transform domain fusion techniques under Compressive Sensing or Compressive Sampling principle. The compressive measurements of two source images are obtained using star shaped sampling pattern and fuse the measurements. The output image is reconstructed from 25% of samples using Minimum Total Variation method with equality constraints and with reduced computational time. Finally, for different fusion techniques under Compressive Sensing are performed and compared. Multi focus and Multi modal images are used for simulation and no prior knowledge of source images is required for reconstruction. Based on fusion evaluation metric with reference and without reference image conclude that in spatial domain, simple average & principal component analysis and in transform domain, DCTav and Laplacian Pyramid are performed well.
{"title":"A Comparative Analysis on Image Fusion Algorithms based on Compressive Sensing","authors":"M. Gayathri Devi, S. Manjula","doi":"10.1109/I-SMAC.2018.8653701","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653701","url":null,"abstract":"This paper is about study of comparative analysis of Spatial and Transform domain fusion techniques under Compressive Sensing or Compressive Sampling principle. The compressive measurements of two source images are obtained using star shaped sampling pattern and fuse the measurements. The output image is reconstructed from 25% of samples using Minimum Total Variation method with equality constraints and with reduced computational time. Finally, for different fusion techniques under Compressive Sensing are performed and compared. Multi focus and Multi modal images are used for simulation and no prior knowledge of source images is required for reconstruction. Based on fusion evaluation metric with reference and without reference image conclude that in spatial domain, simple average & principal component analysis and in transform domain, DCTav and Laplacian Pyramid are performed well.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"2012 1","pages":"295-301"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86399877","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653686
P. Rajarapollu, V. Mankar
Video have a basic and non basic features, where basic features includes e. g. color, shape, size and non basic features include orientation of a image. Whereas Video Sequences is a series of shots/frames on a subject that are edited together to tell a story. Visual features describes the details about the image contents, which are used in various applications like, visual search, object recognition, image registration and object tracking. Many visual analysis task requires the features to be transmitted, thus it calls for the different coding algorithms to attain a target level of efficiency. Here an effort has been taken to implement a coding algorithm for local features extraction such as SIFT (Scale Invariant Feature Transform). The first stage comprises of using the SIFT algorithm property to find the ‘point of interest’ of an image. Further the use Kalman Filter algorithm is done as an application purpose of motion based single or multiple object detection and tracking.
{"title":"Extraction of Visual Features from Video Sequences for Better Visual Analysis","authors":"P. Rajarapollu, V. Mankar","doi":"10.1109/I-SMAC.2018.8653686","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653686","url":null,"abstract":"Video have a basic and non basic features, where basic features includes e. g. color, shape, size and non basic features include orientation of a image. Whereas Video Sequences is a series of shots/frames on a subject that are edited together to tell a story. Visual features describes the details about the image contents, which are used in various applications like, visual search, object recognition, image registration and object tracking. Many visual analysis task requires the features to be transmitted, thus it calls for the different coding algorithms to attain a target level of efficiency. Here an effort has been taken to implement a coding algorithm for local features extraction such as SIFT (Scale Invariant Feature Transform). The first stage comprises of using the SIFT algorithm property to find the ‘point of interest’ of an image. Further the use Kalman Filter algorithm is done as an application purpose of motion based single or multiple object detection and tracking.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"16 1","pages":"220-223"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80073098","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653742
S. Poorna, S. Anjana, P. Varma, Anjana Sajeev, K. Arya, S. Renjith, G. Nair
Recognizing emotions from facial images has become one of the major fields in affective computing arena since it has wide spread applications in robotics, medicine, surveillance, defense, e-learning, gaming, customer services etc. The study used Ekman model with 7 basic emotions- anger, happy, disgust, sad, fear, surprise and neutral acquired from subjects of Indian ethnicity. The acquired data base, Amritaemo consisted of 700 still images of Indian male and female subjects in seven emotions. The images were then cropped manually to obtain the region of analysis i.e. the face and converted to grayscale for further processing. Preprocessing techniques, histogram equalization and median filtering were applied to these after resizing. Discrete Wavelet Transform (DWT) was applied to these pre-processed images. The 2 D Haar wavelet coefficients (WC) were used to obtain the feature parameters. The maximum 2D correlation of mean value of one specific emotion versus all others was considered as the similarity feature. The squared difference of the emotional and neutral images in the transformed domain was considered as the difference feature. Supervised learning methods, K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANN) were used to classify these features separately as well as together. The performance of these parameters were evaluated based on the measures accuracy, sensitivity and specificity.
{"title":"Facial Emotion Recognition using DWT based Similarity and Difference features","authors":"S. Poorna, S. Anjana, P. Varma, Anjana Sajeev, K. Arya, S. Renjith, G. Nair","doi":"10.1109/I-SMAC.2018.8653742","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653742","url":null,"abstract":"Recognizing emotions from facial images has become one of the major fields in affective computing arena since it has wide spread applications in robotics, medicine, surveillance, defense, e-learning, gaming, customer services etc. The study used Ekman model with 7 basic emotions- anger, happy, disgust, sad, fear, surprise and neutral acquired from subjects of Indian ethnicity. The acquired data base, Amritaemo consisted of 700 still images of Indian male and female subjects in seven emotions. The images were then cropped manually to obtain the region of analysis i.e. the face and converted to grayscale for further processing. Preprocessing techniques, histogram equalization and median filtering were applied to these after resizing. Discrete Wavelet Transform (DWT) was applied to these pre-processed images. The 2 D Haar wavelet coefficients (WC) were used to obtain the feature parameters. The maximum 2D correlation of mean value of one specific emotion versus all others was considered as the similarity feature. The squared difference of the emotional and neutral images in the transformed domain was considered as the difference feature. Supervised learning methods, K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANN) were used to classify these features separately as well as together. The performance of these parameters were evaluated based on the measures accuracy, sensitivity and specificity.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"35 12 1","pages":"524-527"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77080863","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653600
Niranjan R Pandeshwar, Preeti Jagadev
The splitting of data using DFSORT utility contributes hugely to MIPS which is an acronym for "Million Instructions Per Second". The MIPS has evolved to determine the processing power and CPU resource consumption. This study investigates and provides an optimized way of performing a balanced splitting of data and makes an effort to reduce the CPU consumption by decreasing the number of instructions needed to perform the same task. The three methods that are used for the same are the SUM FIELDS method, the EASYTRIEVE method and the ORD-MIN functions method. The three data split methods mentioned above have been compared for a large amount of input data and it has been shown that the ORD-MIN function aids MIPS reduction.
{"title":"MIPS reduction using ORD-MIN function in COBOL","authors":"Niranjan R Pandeshwar, Preeti Jagadev","doi":"10.1109/I-SMAC.2018.8653600","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653600","url":null,"abstract":"The splitting of data using DFSORT utility contributes hugely to MIPS which is an acronym for \"Million Instructions Per Second\". The MIPS has evolved to determine the processing power and CPU resource consumption. This study investigates and provides an optimized way of performing a balanced splitting of data and makes an effort to reduce the CPU consumption by decreasing the number of instructions needed to perform the same task. The three methods that are used for the same are the SUM FIELDS method, the EASYTRIEVE method and the ORD-MIN functions method. The three data split methods mentioned above have been compared for a large amount of input data and it has been shown that the ORD-MIN function aids MIPS reduction.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"45 1","pages":"196-199"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87553371","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653647
Raghavi K. Bhujang, Suma V Dean
Software development is a process of well planned and defined steps that contains many series of systematic tasks to deliver the expected product or service to the client. While doing the same, it is likely that there can be many ups and downs in the tasks that are defined starting from the planning stage to completion of deliverable. Also, the series of planned tasks related to product/service delivery in the software development process is likely to fluctuate in terms of Cost, Time, People and Process due to various external factors. These fluctuations should be taken care at the right time with the right mitigation strategy as it spans up further ending with serious obstructions. This paper focuses on how the risk propagates further through the phases of software development with the increase in level of severity. A sample of empirical data taken from existing software development projects throws more light on propagation of severity from the lowest to the highest. This knowledge further aids software personnel and all potential stakeholders to accordingly formulate strategies to effectively manage risk.
{"title":"Propagation of Risk across the Phases of Software Development","authors":"Raghavi K. Bhujang, Suma V Dean","doi":"10.1109/I-SMAC.2018.8653647","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653647","url":null,"abstract":"Software development is a process of well planned and defined steps that contains many series of systematic tasks to deliver the expected product or service to the client. While doing the same, it is likely that there can be many ups and downs in the tasks that are defined starting from the planning stage to completion of deliverable. Also, the series of planned tasks related to product/service delivery in the software development process is likely to fluctuate in terms of Cost, Time, People and Process due to various external factors. These fluctuations should be taken care at the right time with the right mitigation strategy as it spans up further ending with serious obstructions. This paper focuses on how the risk propagates further through the phases of software development with the increase in level of severity. A sample of empirical data taken from existing software development projects throws more light on propagation of severity from the lowest to the highest. This knowledge further aids software personnel and all potential stakeholders to accordingly formulate strategies to effectively manage risk.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"13 1","pages":"508-512"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88738400","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653694
R. Shalini, S. Sasikala
Visual perception is very important for human life. Although several medical conditions can cause retinal disease, the most common cause is diabetes. Diabetic Retinopathy (DR) can be identified using retinal fundus images. Detection and classification of deformation in Diabetic retinopathy is a challenging task since it is symptomless. Several algorithms were analyzed for the identification of abnormality. The analysis of different models in detecting the abnormalities from the image is done which includes various preprocessing techniques to standardize the image and post-processing techniques are applied for morphological adjustments, segmentation algorithms for segmenting the Lesion of Interest(LOI ) namely white lesions and red lesions, further feature extraction methods extracts the features like Micro Aneurysms, Hemorrhages, Exudates and Cotton Wool Spots and so on finally, classification methods were utilized which concludes the presence or absence of DR symptoms along with the severity based on the count of the features extracted in the given retinal image. This survey study aims to develop a novel algorithm to identify and detect types of above mentioned diseases and find out the severity of those diseases also examine with 100% accuracy.
{"title":"A Survey on Detection of Diabetic Retinopathy","authors":"R. Shalini, S. Sasikala","doi":"10.1109/I-SMAC.2018.8653694","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653694","url":null,"abstract":"Visual perception is very important for human life. Although several medical conditions can cause retinal disease, the most common cause is diabetes. Diabetic Retinopathy (DR) can be identified using retinal fundus images. Detection and classification of deformation in Diabetic retinopathy is a challenging task since it is symptomless. Several algorithms were analyzed for the identification of abnormality. The analysis of different models in detecting the abnormalities from the image is done which includes various preprocessing techniques to standardize the image and post-processing techniques are applied for morphological adjustments, segmentation algorithms for segmenting the Lesion of Interest(LOI ) namely white lesions and red lesions, further feature extraction methods extracts the features like Micro Aneurysms, Hemorrhages, Exudates and Cotton Wool Spots and so on finally, classification methods were utilized which concludes the presence or absence of DR symptoms along with the severity based on the count of the features extracted in the given retinal image. This survey study aims to develop a novel algorithm to identify and detect types of above mentioned diseases and find out the severity of those diseases also examine with 100% accuracy.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"75 1","pages":"626-630"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85771428","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653653
Mandeep Kumar, S. Mini, T. Panigrahi
Rapid industrialization has caused an increase in the pollution levels. The release of harmful gases, particulate matter, dust and detritus into the atmosphere leads to air pollution. One can reduce air-borne diseases by controlling the air pollution. In this paper, we design an Internet of Things (IoT) system to monitor the air quality at desired location(s). The IoT system monitors five different gases with the help of air quality monitoring sensors. The system detects the concentration of gases and sends the data to the ThingSpeak cloud for storage. The results of such a system may be useful for alerting the people and the authorities, in case of high air pollution.
{"title":"A scalable approach to monitoring air pollution using IoT","authors":"Mandeep Kumar, S. Mini, T. Panigrahi","doi":"10.1109/I-SMAC.2018.8653653","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653653","url":null,"abstract":"Rapid industrialization has caused an increase in the pollution levels. The release of harmful gases, particulate matter, dust and detritus into the atmosphere leads to air pollution. One can reduce air-borne diseases by controlling the air pollution. In this paper, we design an Internet of Things (IoT) system to monitor the air quality at desired location(s). The IoT system monitors five different gases with the help of air quality monitoring sensors. The system detects the concentration of gases and sends the data to the ThingSpeak cloud for storage. The results of such a system may be useful for alerting the people and the authorities, in case of high air pollution.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"88 1","pages":"42-47"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85849133","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653718
Manish Nair, Samineni Rohith Kumar, N. A, Nihal Mohan, Anudev J
Physical activity is closely related to one’s health status. Man has always maintained a good health, improved blood circulation and has often come across through some superlative ideas while ambulating. Movement, meditation, health of blood pumping and rhythm of footsteps has been a primeval way of connecting with one’s deeper self. However, this seldom explains the importance of walking and tracking our health parameters. This paper is an attempt in the development of a prototype of a wearable fitness band with advance pedometer applications. Usually, pedometers are just designed to calculate the number of steps taken by the user or calculate the number of calories burnt. The prototype illustrated in the paper is an extension to the very same. Along with the above mentioned features, it also calculates the walking speed of the user and gives a vibration feedback if the current speed is below a certain threshold level.This system also contains a heart rate monitoring system along with a GPS and Bluetooth module. An Android app was also developed using MIT app inventor. The Bluetooth module is paired with the user’s smart phone. If the user experiences a sudden cardiac emergency, an SMS alert and call is made to his relatives with the app. The text message consists the latitude and longitude value where user is present. This band is not just a fitness tracker, but also an effort to contribute something towards a humanitarian cause.
{"title":"INSTANTANEOUS FEEDBACK PEDOMETER WITH EMERGENCY GPS TRACKER","authors":"Manish Nair, Samineni Rohith Kumar, N. A, Nihal Mohan, Anudev J","doi":"10.1109/I-SMAC.2018.8653718","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653718","url":null,"abstract":"Physical activity is closely related to one’s health status. Man has always maintained a good health, improved blood circulation and has often come across through some superlative ideas while ambulating. Movement, meditation, health of blood pumping and rhythm of footsteps has been a primeval way of connecting with one’s deeper self. However, this seldom explains the importance of walking and tracking our health parameters. This paper is an attempt in the development of a prototype of a wearable fitness band with advance pedometer applications. Usually, pedometers are just designed to calculate the number of steps taken by the user or calculate the number of calories burnt. The prototype illustrated in the paper is an extension to the very same. Along with the above mentioned features, it also calculates the walking speed of the user and gives a vibration feedback if the current speed is below a certain threshold level.This system also contains a heart rate monitoring system along with a GPS and Bluetooth module. An Android app was also developed using MIT app inventor. The Bluetooth module is paired with the user’s smart phone. If the user experiences a sudden cardiac emergency, an SMS alert and call is made to his relatives with the app. The text message consists the latitude and longitude value where user is present. This band is not just a fitness tracker, but also an effort to contribute something towards a humanitarian cause.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"78 1","pages":"122-126"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79744255","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653702
T. Suresh, A. Murugan
Considering current evolving technology and the way data are growing, IT consulting and outsourcing industry expected to be strategic partner for technology innovation in addition to support on-going business with reduced operational cost. Data Center is backbone for digital economy, big data, cloud, artificial intelligence, IoT or wearable technology. Data growth and on-demand data access changed the focus of data center as storage and disaster recovery to access data instantly from cloud without compromising security controls and data quality. These technology transformations create demand for latency. Every organization like Facebook, Equinix, Amazon, and Google are having their own data centers and expanding their business on cloud services. Data Center plays major critical on success of digital business. It is important to find possible options to optimize infrastructure and improve efficiency and productivity of Data Center. At the same time, we need to make sure that environment is up and running without compromising quality and security of data. This paper gives few solutions to get more from Data Center, reduce operational cost and optimize infrastructure utilization.
{"title":"Strategy for Data Center Optimization : Improve Data Center capability to meet business opportunities","authors":"T. Suresh, A. Murugan","doi":"10.1109/I-SMAC.2018.8653702","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653702","url":null,"abstract":"Considering current evolving technology and the way data are growing, IT consulting and outsourcing industry expected to be strategic partner for technology innovation in addition to support on-going business with reduced operational cost. Data Center is backbone for digital economy, big data, cloud, artificial intelligence, IoT or wearable technology. Data growth and on-demand data access changed the focus of data center as storage and disaster recovery to access data instantly from cloud without compromising security controls and data quality. These technology transformations create demand for latency. Every organization like Facebook, Equinix, Amazon, and Google are having their own data centers and expanding their business on cloud services. Data Center plays major critical on success of digital business. It is important to find possible options to optimize infrastructure and improve efficiency and productivity of Data Center. At the same time, we need to make sure that environment is up and running without compromising quality and security of data. This paper gives few solutions to get more from Data Center, reduce operational cost and optimize infrastructure utilization.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"113 1","pages":"184-189"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80528481","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653674
N. Radha, M. Maheswari
Now-a-days majority of practical applications such as valet car parking, larger temples necessitate, seven segment displays to give a visual token of the numbers. Digital counters are the one which are used for these applications. The four bit Binary Coded decimal form will normally be the output states of digital counters and thus they are not relevant for straightly activating 7 segment displays. The special BCD to 7 segment display decoder ICs are used in converting the incoming BCD signal to a form convenient for activating these displays. In this paper, an efficient BCD to seven segment converter is designed using Modified Gate Diffusion Input Technique (MGDI). The suggested MGDI based BCD to seven segment converter is contrasted with the conventional Complementary CMOS gates based BCD to seven segment converter. Both the implementations are done by means of Cadence 180 nm technology. Simulation result shows that the MGDI based BCD to seven segment display decoder consumes 51 % less area, 98.97 % power and 98.8 % delay compared with the conventional Complementary CMOS gates based BCD to seven segment display decoder.
{"title":"An Efficient Implementation of BCD to Seven Segment Decoder using MGDI","authors":"N. Radha, M. Maheswari","doi":"10.1109/I-SMAC.2018.8653674","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653674","url":null,"abstract":"Now-a-days majority of practical applications such as valet car parking, larger temples necessitate, seven segment displays to give a visual token of the numbers. Digital counters are the one which are used for these applications. The four bit Binary Coded decimal form will normally be the output states of digital counters and thus they are not relevant for straightly activating 7 segment displays. The special BCD to 7 segment display decoder ICs are used in converting the incoming BCD signal to a form convenient for activating these displays. In this paper, an efficient BCD to seven segment converter is designed using Modified Gate Diffusion Input Technique (MGDI). The suggested MGDI based BCD to seven segment converter is contrasted with the conventional Complementary CMOS gates based BCD to seven segment converter. Both the implementations are done by means of Cadence 180 nm technology. Simulation result shows that the MGDI based BCD to seven segment display decoder consumes 51 % less area, 98.97 % power and 98.8 % delay compared with the conventional Complementary CMOS gates based BCD to seven segment display decoder.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"57 1","pages":"475-479"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90171801","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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