Pub Date : 2018-02-01DOI: 10.1109/ICCMC.2018.8487517
S. Bharkad
This paper presents a technique for detection of hard exudates in fundus images. Hard exudates is one of the anomaly formed in retina due to diabetic retinopathy. Early detection of hard exudates may prevent the vision loss of diabetic retinopathy patient. In this work, optic disc (OD) is extracted with the help of morphological operators. OD is masked in green component image to avoid the misclassification between OD region and hard exudates region. Then features of green component image are computed and applied to neural network for detection of hard exudates. Experimental results show the better competency of algorithm on DIARETDB0 and DIARETDB1 databases.
{"title":"Morphological and Neural Network Based Approach for Detection of Exudates in Fundus Images","authors":"S. Bharkad","doi":"10.1109/ICCMC.2018.8487517","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487517","url":null,"abstract":"This paper presents a technique for detection of hard exudates in fundus images. Hard exudates is one of the anomaly formed in retina due to diabetic retinopathy. Early detection of hard exudates may prevent the vision loss of diabetic retinopathy patient. In this work, optic disc (OD) is extracted with the help of morphological operators. OD is masked in green component image to avoid the misclassification between OD region and hard exudates region. Then features of green component image are computed and applied to neural network for detection of hard exudates. Experimental results show the better competency of algorithm on DIARETDB0 and DIARETDB1 databases.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"24 1","pages":"891-894"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72890097","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.2018.8487526
Atefeh Aghaei
Cellular automata (CA) refer to a simple and conventional method which performs parallel processing, thereby exhibiting better performance than serial processing in certain contexts, particularly in terms of reduced time complexity. Edge detection is widely used in image processing and numerous methods have been proposed for this purpose. However, most of existing methods are serial techniques and fail to take into consideration noise content of the image. In this paper, an edge detection technique was proposed for noisy images based on a four-neighborhood under Null boundary cellular automata (FNNBCA) for noise elimination and a two-dimensional twenty-five neighborhoods under Null Boundary cellular automata (TFNNBCA) for edge detection. This method considers linear CA rules under null boundary conditions only. Efficiency of the proposed method was further compared to those of existing methods, indicating much promising performance of the proposed method for binary images, so that all edges were well detected even on complex images. Finally, results of implementing the method in MATLAB are presented.
{"title":"A cellular Automata approach for noisy images edge detection under null boundary conditions","authors":"Atefeh Aghaei","doi":"10.1109/ICCMC.2018.8487526","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487526","url":null,"abstract":"Cellular automata (CA) refer to a simple and conventional method which performs parallel processing, thereby exhibiting better performance than serial processing in certain contexts, particularly in terms of reduced time complexity. Edge detection is widely used in image processing and numerous methods have been proposed for this purpose. However, most of existing methods are serial techniques and fail to take into consideration noise content of the image. In this paper, an edge detection technique was proposed for noisy images based on a four-neighborhood under Null boundary cellular automata (FNNBCA) for noise elimination and a two-dimensional twenty-five neighborhoods under Null Boundary cellular automata (TFNNBCA) for edge detection. This method considers linear CA rules under null boundary conditions only. Efficiency of the proposed method was further compared to those of existing methods, indicating much promising performance of the proposed method for binary images, so that all edges were well detected even on complex images. Finally, results of implementing the method in MATLAB are presented.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"65 1","pages":"771-777"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74477428","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.2018.8487916
Surbhi, Oshin, Mahesh Chandra Bhatt
Hadoop is a popular model used in shared-nothing clusters for data-intensive parallel computing. The MapReduce-algorithm is a model that operates on distributed, parallel systems. Hadoop has different implementation of this MapReduce-algorithm. Some of the implementations during execution produce an imbalance of work on the cluster. The performance of MapReduce mainly depends on data distribution which is one of the main issues as the load is not balanced among nodes. FIFO job scheduler that serves the jobs in their submission order is used by MapReduce to balance the load but unfortunately it is inefficient in real world cases as it missed many important factors that impact the performance such as heterogeneity factor and data skewness, so Load balancing is important to make all resources utilized evenly and more efficiently. Load balancing is an approach of improving the system’s performance by redistributing the load among nodes.The main goal of this work is to execute various load balancing algorithms in hadoop framework. In this dissertation various load balancing algorithms such as Randomized Hydrodynamic Load Balancing, Cogset Load Balance, Block-based Load Balancing for Entity Resolution, Ant colony Optimization, Shortest Path are simulated and comparisons being made on the basis of various parameters like delay time, response time, throughput, turnaround time and threshold to find the best that solve the data distribution problem.
{"title":"Performance Evaluation of Load Balancing Algorithms in Hadoop","authors":"Surbhi, Oshin, Mahesh Chandra Bhatt","doi":"10.1109/ICCMC.2018.8487916","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487916","url":null,"abstract":"Hadoop is a popular model used in shared-nothing clusters for data-intensive parallel computing. The MapReduce-algorithm is a model that operates on distributed, parallel systems. Hadoop has different implementation of this MapReduce-algorithm. Some of the implementations during execution produce an imbalance of work on the cluster. The performance of MapReduce mainly depends on data distribution which is one of the main issues as the load is not balanced among nodes. FIFO job scheduler that serves the jobs in their submission order is used by MapReduce to balance the load but unfortunately it is inefficient in real world cases as it missed many important factors that impact the performance such as heterogeneity factor and data skewness, so Load balancing is important to make all resources utilized evenly and more efficiently. Load balancing is an approach of improving the system’s performance by redistributing the load among nodes.The main goal of this work is to execute various load balancing algorithms in hadoop framework. In this dissertation various load balancing algorithms such as Randomized Hydrodynamic Load Balancing, Cogset Load Balance, Block-based Load Balancing for Entity Resolution, Ant colony Optimization, Shortest Path are simulated and comparisons being made on the basis of various parameters like delay time, response time, throughput, turnaround time and threshold to find the best that solve the data distribution problem.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"150 1","pages":"491-496"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72842732","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.2018.8488153
J. Cheltha. C, R. K. Jha, Mohit Jain, P. K. Sharma
In contemporary planet we are distributing lot of particulars through electronic media. In innumerable fields this information should be protected. Few examples in which the particular should be protected are military, industries, scientific research etc. In proposed effort we encompass three parts. In first part, we are using CLEFIA to encrypt images, and in second part we are using CLEFIA to decrypt images and in third part we are using error rectification and recognition technique using Low Density Parity Check convention. CLEFIA is the block cipher algorithm. The block size of CLEFIA is 16 bytes and the key size is 16 bytes, 24 bytes and 32 bytes. After Encryption of images using CLEFIA the images will be sent to the recipient in the form of binary bits. While transmitting these binary bits through communication channel, particulars may get distressed due to noise and to tenacity; Low Density Parity Check Convention is used in the receiver side.
{"title":"Contemporary Encryption Technique for Images using CLEFIA","authors":"J. Cheltha. C, R. K. Jha, Mohit Jain, P. K. Sharma","doi":"10.1109/ICCMC.2018.8488153","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8488153","url":null,"abstract":"In contemporary planet we are distributing lot of particulars through electronic media. In innumerable fields this information should be protected. Few examples in which the particular should be protected are military, industries, scientific research etc. In proposed effort we encompass three parts. In first part, we are using CLEFIA to encrypt images, and in second part we are using CLEFIA to decrypt images and in third part we are using error rectification and recognition technique using Low Density Parity Check convention. CLEFIA is the block cipher algorithm. The block size of CLEFIA is 16 bytes and the key size is 16 bytes, 24 bytes and 32 bytes. After Encryption of images using CLEFIA the images will be sent to the recipient in the form of binary bits. While transmitting these binary bits through communication channel, particulars may get distressed due to noise and to tenacity; Low Density Parity Check Convention is used in the receiver side.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"34 1","pages":"468-471"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74073282","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.2018.8487817
G. Prutha, G. Anitha
This paper presents maximum power point tracking (MPPT) using an intelligence system (IS) based single-ended primary-inductor (SEPIC) converter to operate photovoltaic (PV) system. This paper represents the comparison and improvisation of efficiency with two controllers. The suggested IS is showed to get faster response when compared to the traditional PI controller. It showed high precision during current and irradiation variation and retains the voltage without any changes in the system. The proposed IS based system makes sure that the favorable use of PV system and demonstrates its intended results in different irradiation functions at the output part. The execution of the converter is been tested at different constraints. The execution of the proposed IS based MPP operation of converter will be comparing with the conventional PI based converter. The results in this work is shown that the IS based MPP scheme for SEPIC will be tracking the accurate reference signal and as well as the transfer power more than that of the conventional PI based system. Compare to the PI based system the FLC has improved its efficiency about 3% in this work. In this paper the Simulink model is been built in MATLAB 2013a Version is used to get the result.
{"title":"MPP tracking using IS controller based SEPIC converter","authors":"G. Prutha, G. Anitha","doi":"10.1109/ICCMC.2018.8487817","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487817","url":null,"abstract":"This paper presents maximum power point tracking (MPPT) using an intelligence system (IS) based single-ended primary-inductor (SEPIC) converter to operate photovoltaic (PV) system. This paper represents the comparison and improvisation of efficiency with two controllers. The suggested IS is showed to get faster response when compared to the traditional PI controller. It showed high precision during current and irradiation variation and retains the voltage without any changes in the system. The proposed IS based system makes sure that the favorable use of PV system and demonstrates its intended results in different irradiation functions at the output part. The execution of the converter is been tested at different constraints. The execution of the proposed IS based MPP operation of converter will be comparing with the conventional PI based converter. The results in this work is shown that the IS based MPP scheme for SEPIC will be tracking the accurate reference signal and as well as the transfer power more than that of the conventional PI based system. Compare to the PI based system the FLC has improved its efficiency about 3% in this work. In this paper the Simulink model is been built in MATLAB 2013a Version is used to get the result.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"34 1","pages":"270-275"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79828151","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.2018.8487895
H. Mercy, P. Thangavel
Computer aided mammogram image cancer segmentation is more complex in intensity mapping to predict the normal and infected region. Generally, image thresholding and static feature based clustering deals with the fixed level of intensity mapping to segment it. Since, the pattern structure of given testing image must need to analyse the cancer level. In this paper, the Enhanced Hopfield Neural Network model with Edge Preserving (EHNN-EP) technique is used for segmenting the cancer region from mammogram image which is to enhance the prediction range of image clustering. Initially, the additive noise can be eliminating by median filter which makes the image smoothening and improve the intensity level. This type of enhancing the image leads to provide the edge details of that image. Also, the HNN performs the repeated learning od image feature which improves the image clustering. The performance report of this proposed method of EHNN can be validate by referring the comparison result of traditional state-of-art methods in two different mammogram image databases. The comparison result represents the performance level of EHNN-EP method that achieves the accuracy percentage as 98.56%.
{"title":"Enhanced Hopfield Neural Network with Edge Preserving (EHNN-EP) based severity diagnosis of Ductal Carcinoma in Situ (DCIS)","authors":"H. Mercy, P. Thangavel","doi":"10.1109/ICCMC.2018.8487895","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487895","url":null,"abstract":"Computer aided mammogram image cancer segmentation is more complex in intensity mapping to predict the normal and infected region. Generally, image thresholding and static feature based clustering deals with the fixed level of intensity mapping to segment it. Since, the pattern structure of given testing image must need to analyse the cancer level. In this paper, the Enhanced Hopfield Neural Network model with Edge Preserving (EHNN-EP) technique is used for segmenting the cancer region from mammogram image which is to enhance the prediction range of image clustering. Initially, the additive noise can be eliminating by median filter which makes the image smoothening and improve the intensity level. This type of enhancing the image leads to provide the edge details of that image. Also, the HNN performs the repeated learning od image feature which improves the image clustering. The performance report of this proposed method of EHNN can be validate by referring the comparison result of traditional state-of-art methods in two different mammogram image databases. The comparison result represents the performance level of EHNN-EP method that achieves the accuracy percentage as 98.56%.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"17 1","pages":"426-431"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84501014","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.2018.8487898
Md. Asibul Islam, Amir Hamza, M. Rahaman, J. Bhattacharjee, M. Rahman
At the advent of human age analysis of emotion is one of the most mysterious and unsolved matters. The emotion and thinking pattern are like a paradox. To understand the mental state of a person only the facial expression is not sufficient. So along with facial expression decoding the signals of brain wave completely can be the key of exposure of emotion. This paper focuses on a system to unveil the nature of emotion with the help of two process cases and then comparing both emotions, the fluctuation were calculated if exists any. Additionally combining data of both process cases more accurate emotional state is achieved. First process case is the facial expression recognition technology and the other one is the extraction of EEG signal data from brain. Evaluating and analyzing data of these two processes were combined in this system to gain the fluctuation of emotional state. The outcome values of the combination of these two process cases were also included in this paper. Therefore the proposed system can pave the way of fully transparent emotion recognition in near future and would contribute a lot in the field of medical science, neuroscience, artificial intelligence and defense security.
{"title":"Mind Reader : A Facial Expression and EEG Based Emotion Recognizer","authors":"Md. Asibul Islam, Amir Hamza, M. Rahaman, J. Bhattacharjee, M. Rahman","doi":"10.1109/ICCMC.2018.8487898","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487898","url":null,"abstract":"At the advent of human age analysis of emotion is one of the most mysterious and unsolved matters. The emotion and thinking pattern are like a paradox. To understand the mental state of a person only the facial expression is not sufficient. So along with facial expression decoding the signals of brain wave completely can be the key of exposure of emotion. This paper focuses on a system to unveil the nature of emotion with the help of two process cases and then comparing both emotions, the fluctuation were calculated if exists any. Additionally combining data of both process cases more accurate emotional state is achieved. First process case is the facial expression recognition technology and the other one is the extraction of EEG signal data from brain. Evaluating and analyzing data of these two processes were combined in this system to gain the fluctuation of emotional state. The outcome values of the combination of these two process cases were also included in this paper. Therefore the proposed system can pave the way of fully transparent emotion recognition in near future and would contribute a lot in the field of medical science, neuroscience, artificial intelligence and defense security.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"41 1","pages":"101-107"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82495172","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.2018.8487698
Piyush Sharma, Dr. Arti Vaish
Federal Communications Commission (FCC) has released frequency from 3.1GHz to 10.6GHz (bandwidth of 7.5GHz) for ultra wideband (UWB) wireless communications. High data rate wireless, low power consumption and low cost communication technology gives a further scope for research and development in UWB antennas. There are many challenges in designing of UWB antenna than a wide/narrow band antenna. The main characteristic i.e. return loss, radiation properties, impedance and gain are required satisfactory over the entire bandwidth. This paper focuses on extensive investigations carried out on the different type of UWB antennas and their developments. The Design and characteristic of portable UWB antenna like Planar Monopoles, Printed Monopoles, Printed wide slot, Band Notched, Hybrid and Dielectric Resonator Antenna are reviewed and summarized.
{"title":"DEVELOPMENTS IN ULTRAWIDEBAND(UWB) ANTENNAS","authors":"Piyush Sharma, Dr. Arti Vaish","doi":"10.1109/ICCMC.2018.8487698","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487698","url":null,"abstract":"Federal Communications Commission (FCC) has released frequency from 3.1GHz to 10.6GHz (bandwidth of 7.5GHz) for ultra wideband (UWB) wireless communications. High data rate wireless, low power consumption and low cost communication technology gives a further scope for research and development in UWB antennas. There are many challenges in designing of UWB antenna than a wide/narrow band antenna. The main characteristic i.e. return loss, radiation properties, impedance and gain are required satisfactory over the entire bandwidth. This paper focuses on extensive investigations carried out on the different type of UWB antennas and their developments. The Design and characteristic of portable UWB antenna like Planar Monopoles, Printed Monopoles, Printed wide slot, Band Notched, Hybrid and Dielectric Resonator Antenna are reviewed and summarized.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"73 1","pages":"380-385"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83349862","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.2018.8487687
Shibam Swarup Das, Ruby Mishra
This paper explores a new full-adder (FA) cell which works in low power. Here the FA architecture is designed using pass transistor logic (PTL) style with 14 transistors and implemented using Cadence Virtuous Tools in 90 nm technology node. The investigation has been carried out through anatomizing the FA cell into sub modules. The different design metrics are compared with the existing design. The result shows an average power and delay of 1.494 μW and 0.003612 ns respectively, which is less compared with the existing FA.
{"title":"Design & Performance Analysis of Low Power 1-bit Full Adder at 90 nm node using PTL Logic","authors":"Shibam Swarup Das, Ruby Mishra","doi":"10.1109/ICCMC.2018.8487687","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8487687","url":null,"abstract":"This paper explores a new full-adder (FA) cell which works in low power. Here the FA architecture is designed using pass transistor logic (PTL) style with 14 transistors and implemented using Cadence Virtuous Tools in 90 nm technology node. The investigation has been carried out through anatomizing the FA cell into sub modules. The different design metrics are compared with the existing design. The result shows an average power and delay of 1.494 μW and 0.003612 ns respectively, which is less compared with the existing FA.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"15 1","pages":"636-639"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78799743","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.2018.8488089
P. Madhusudan, DB Rathankumar, K. Aishwarya, G. Anitha
Hundreds of deaths take place every year in developing countries like India due to improperly operated railway gates. Today, majority of level crossings are operated manually. This has several drawbacks, both social and economical. This paper proposes two algorithms that are meant to completely automate level crossings using Static and Doppler methods. Dynamic error correction methods have also been simulated. Socio-economic impacts have been analyzed. The algorithms developed here are designed to operate railway gates automatically, with minimal loss of time for the commuters on the road, without compromising on safety. Additional time based safety measures have also been incorporated. The static algorithm has also been theorized as ASIC hardware, where the entire automation process may be converted to circuitry. Functional block diagrams have been developed for the ASIC implementation.
{"title":"Computationally Efficient Algorithms and High-Speed ASIC design for Railway Gate Automation","authors":"P. Madhusudan, DB Rathankumar, K. Aishwarya, G. Anitha","doi":"10.1109/ICCMC.2018.8488089","DOIUrl":"https://doi.org/10.1109/ICCMC.2018.8488089","url":null,"abstract":"Hundreds of deaths take place every year in developing countries like India due to improperly operated railway gates. Today, majority of level crossings are operated manually. This has several drawbacks, both social and economical. This paper proposes two algorithms that are meant to completely automate level crossings using Static and Doppler methods. Dynamic error correction methods have also been simulated. Socio-economic impacts have been analyzed. The algorithms developed here are designed to operate railway gates automatically, with minimal loss of time for the commuters on the road, without compromising on safety. Additional time based safety measures have also been incorporated. The static algorithm has also been theorized as ASIC hardware, where the entire automation process may be converted to circuitry. Functional block diagrams have been developed for the ASIC implementation.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"140 Suppl 1 1","pages":"972-975"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89375920","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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