Pub Date : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566072
V. Singh, Jyoti Agarwal, M. Kumar
Aphasia may be defined as a disorder that causes problems in the language of a human, its loss the production of human or grasp of speech and the ability to write language or reading Language. your ability to write can be affected, expression of words and problems in both communication and written language. It is always happening due to the injury to the brain in the human mind it brings from stroke, particularly in order in a single person. Brain injuries are occurring from the tumor in the head, also from brain tumors caused in the brain or any type of infections. According to an all-country survey 2016 About 75 thousand strokes happen per year in the USA and there are at least two lakh fifty thousand people in Britain with aphasia disease.84.1% of people generally confuse stroke and injury caused in the brain that also causes problems in communication. 84.5 percentage of people don’t know term Aphasia disease, 8.8 percentage of people nothing any idea about the disease aphasia disease and also think this disease as a disorder which is caused due to communication or written disorder and 34.7% of affected of Aphasia disease that are "aphasia aware" thinks it as indivisible that does. Aphasia disease treatment is caused by the speech-language pathologist (SLP) or a speech and language therapist. In this paper we presented the different use of machine learning Algorithms for Aphasia patient, types of Aphasia and present different types of treatment Approaches for aphasia.
{"title":"Analyzing Machine Learning Algorithms for Speech Impairment Related Issues","authors":"V. Singh, Jyoti Agarwal, M. Kumar","doi":"10.1109/SPIN52536.2021.9566072","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566072","url":null,"abstract":"Aphasia may be defined as a disorder that causes problems in the language of a human, its loss the production of human or grasp of speech and the ability to write language or reading Language. your ability to write can be affected, expression of words and problems in both communication and written language. It is always happening due to the injury to the brain in the human mind it brings from stroke, particularly in order in a single person. Brain injuries are occurring from the tumor in the head, also from brain tumors caused in the brain or any type of infections. According to an all-country survey 2016 About 75 thousand strokes happen per year in the USA and there are at least two lakh fifty thousand people in Britain with aphasia disease.84.1% of people generally confuse stroke and injury caused in the brain that also causes problems in communication. 84.5 percentage of people don’t know term Aphasia disease, 8.8 percentage of people nothing any idea about the disease aphasia disease and also think this disease as a disorder which is caused due to communication or written disorder and 34.7% of affected of Aphasia disease that are \"aphasia aware\" thinks it as indivisible that does. Aphasia disease treatment is caused by the speech-language pathologist (SLP) or a speech and language therapist. In this paper we presented the different use of machine learning Algorithms for Aphasia patient, types of Aphasia and present different types of treatment Approaches for aphasia.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116890047","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566056
R. Sakile, A. Bhanuchandar, Kasoju Bharath Kumar, D. Vamshy, Bandela Supriya, Kowstubha Palle
In this paper, a Nearest Level Control (NLC) scheme for Reduced Switch Count (RSC) cascaded half-bridge based Multilevel DC-Link (MLDCL)inverter topology with three different source configurations (1:1:1:1, 1:2:3:4 and 1:2:4:8) have been explained clearly. For generating particular level in the inverter output, NLC technique has been utilized. The NLC technique is generally a low switching frequency technique thereby switching losses are greatly reduces and it is suitable for any kind of inverter topology. The MLDCL topology consists of 8 unidirectional switches in the level generator side, 4 unidirectional switches in the polarity generator side and 4 dc sources. For generating P-level output, only P+3 switches are required then the requirement of gate driver circuits, protection circuits have been reduced. Basically, NLC technique is more suitable for higher level inverter topologies and provides best harmonic performance as compared with conventional Pulse Width Modulation (PWM) techniques. The operation and feasibility of the topology with control scheme have been validated through the MATLAB/Simulink platform.
{"title":"A Nearest Level Control Scheme for Reduced Switch Count Cascaded Half-Bridge Based Multilevel DC Link Inverter Topology","authors":"R. Sakile, A. Bhanuchandar, Kasoju Bharath Kumar, D. Vamshy, Bandela Supriya, Kowstubha Palle","doi":"10.1109/SPIN52536.2021.9566056","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566056","url":null,"abstract":"In this paper, a Nearest Level Control (NLC) scheme for Reduced Switch Count (RSC) cascaded half-bridge based Multilevel DC-Link (MLDCL)inverter topology with three different source configurations (1:1:1:1, 1:2:3:4 and 1:2:4:8) have been explained clearly. For generating particular level in the inverter output, NLC technique has been utilized. The NLC technique is generally a low switching frequency technique thereby switching losses are greatly reduces and it is suitable for any kind of inverter topology. The MLDCL topology consists of 8 unidirectional switches in the level generator side, 4 unidirectional switches in the polarity generator side and 4 dc sources. For generating P-level output, only P+3 switches are required then the requirement of gate driver circuits, protection circuits have been reduced. Basically, NLC technique is more suitable for higher level inverter topologies and provides best harmonic performance as compared with conventional Pulse Width Modulation (PWM) techniques. The operation and feasibility of the topology with control scheme have been validated through the MATLAB/Simulink platform.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123399789","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566087
Navanit Pankaj Dubey, A. Rani, Vijander Singh
This paper focuses on finding the shortest and correct path for the robots without any collision with the objects in its environment. Generally global (static) and local environments are used for path planning of mobile robots. In this work, static environment is considered and an optimized path is evaluated for efficient robot movement from the start position to the end position. Different classical and evolutionary based path search algorithms are used so as to find the optimized path, with reduced computation time and path length of the mobile robot. The results reveal that evolutionary-based algorithms provide a more effective solution to the problem under consideration.
{"title":"Path Planning of a Multi Dimensional Robot in Static Environment Using Meta Heuristic Techniques","authors":"Navanit Pankaj Dubey, A. Rani, Vijander Singh","doi":"10.1109/SPIN52536.2021.9566087","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566087","url":null,"abstract":"This paper focuses on finding the shortest and correct path for the robots without any collision with the objects in its environment. Generally global (static) and local environments are used for path planning of mobile robots. In this work, static environment is considered and an optimized path is evaluated for efficient robot movement from the start position to the end position. Different classical and evolutionary based path search algorithms are used so as to find the optimized path, with reduced computation time and path length of the mobile robot. The results reveal that evolutionary-based algorithms provide a more effective solution to the problem under consideration.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125255310","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565979
Neetu Singla, Jyotsna Singh, Sushama Nagpal
In this paper, we propose feature-based machine learning models for detecting frame deletion tampering in videos. The work investigates inconsistency in correlations between adjacent frames that occurs when frames are dropped from a continuous sequence. As a result, the correlation pattern of the original and counterfeit videos differs slightly. Three machine learning models namely Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Convolution Neural Network (CNN) have been implemented to predict the authenticity of video shots. Experiments have been conducted on a large dataset of 600 videos each of 25-frame deletion and 100-frame deletion. The results show that the CNN model can classify between authentic and forged sequences more accurately than SVM and MLP with the highest accuracy of 97% for 100-frame deletion.
{"title":"Video Frame Deletion Detection using Correlation Coefficients","authors":"Neetu Singla, Jyotsna Singh, Sushama Nagpal","doi":"10.1109/SPIN52536.2021.9565979","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565979","url":null,"abstract":"In this paper, we propose feature-based machine learning models for detecting frame deletion tampering in videos. The work investigates inconsistency in correlations between adjacent frames that occurs when frames are dropped from a continuous sequence. As a result, the correlation pattern of the original and counterfeit videos differs slightly. Three machine learning models namely Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Convolution Neural Network (CNN) have been implemented to predict the authenticity of video shots. Experiments have been conducted on a large dataset of 600 videos each of 25-frame deletion and 100-frame deletion. The results show that the CNN model can classify between authentic and forged sequences more accurately than SVM and MLP with the highest accuracy of 97% for 100-frame deletion.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126925367","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565958
A. Priya, Abhinav Kumar
Social media networks such as Facebook and Twitter are overwhelmed with COVID-19-related posts during the outbreak. People have also posted several fake news among the massive COVID-19-related social media posts. Fake news has the potential to create public fear, weaken government credibility, and pose a serious threat to social order. This paper provides a deep ensemble-based method for detecting COVID-19 fake news. An ensemble classifier is made up of three different classifiers: Support Vector Machine, Dense Neural Network, and Convolutional Neural Network. The extensive experiments with the proposed ensemble model and eight different conventional machine learning classifiers are carried out using the character and word n-gram TF-IDF features. The results of the experiments show that character n-gram features outperform word n-gram features. The proposed deep ensemble classifier performed better, with a weighted F1-score of 0.97 in contrast to numerous conventional machine learning classifiers and deep learning classifiers.
{"title":"Deep Ensemble Approach for COVID-19 Fake News Detection from Social Media","authors":"A. Priya, Abhinav Kumar","doi":"10.1109/SPIN52536.2021.9565958","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565958","url":null,"abstract":"Social media networks such as Facebook and Twitter are overwhelmed with COVID-19-related posts during the outbreak. People have also posted several fake news among the massive COVID-19-related social media posts. Fake news has the potential to create public fear, weaken government credibility, and pose a serious threat to social order. This paper provides a deep ensemble-based method for detecting COVID-19 fake news. An ensemble classifier is made up of three different classifiers: Support Vector Machine, Dense Neural Network, and Convolutional Neural Network. The extensive experiments with the proposed ensemble model and eight different conventional machine learning classifiers are carried out using the character and word n-gram TF-IDF features. The results of the experiments show that character n-gram features outperform word n-gram features. The proposed deep ensemble classifier performed better, with a weighted F1-score of 0.97 in contrast to numerous conventional machine learning classifiers and deep learning classifiers.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114928774","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566002
Pawan Kumar, Nihal Manzoor, Chhavi Dhiman
In an unhindered environment, the detection of face and alignment are more challenging due to a variety of poses, illuminations, and occlusions. To better understand and boost, a deep cascaded multi-task framework is proposed in this paper, which exploits alignment and detection inherent correlation. In a coarse and fine prediction of landmark location of the face, the proposed framework leverages Multi-task Cascaded Convolution Neural network [1] (MTCNN) followed by FaceNet [2] to recognize the face identities efficiently. The work has been extended in the form of a real-time attendance marking system. The proposed technique achieves better recognition performance compared to the other state-of-the-arts. Three publicly available datasets: ORL, AR, LFW, datasets are used for experimentation.
{"title":"A Deep Cascaded Multi-task Face Recognition Framework","authors":"Pawan Kumar, Nihal Manzoor, Chhavi Dhiman","doi":"10.1109/SPIN52536.2021.9566002","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566002","url":null,"abstract":"In an unhindered environment, the detection of face and alignment are more challenging due to a variety of poses, illuminations, and occlusions. To better understand and boost, a deep cascaded multi-task framework is proposed in this paper, which exploits alignment and detection inherent correlation. In a coarse and fine prediction of landmark location of the face, the proposed framework leverages Multi-task Cascaded Convolution Neural network [1] (MTCNN) followed by FaceNet [2] to recognize the face identities efficiently. The work has been extended in the form of a real-time attendance marking system. The proposed technique achieves better recognition performance compared to the other state-of-the-arts. Three publicly available datasets: ORL, AR, LFW, datasets are used for experimentation.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115332544","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566119
Anubhav Kumar, A. De, R. Jain
The Two-port antenna with modified open slot and high isolation is presented for 5G and wearable applications. The |S11| in dB varies from 3.15 GHz to 3.95 GHz of the two-port antenna with more than 22 dB isolation. The modified open slot is used to diminish the surface current as well as isolate the antenna elements. The Modified Open slot enhances the isolation up to 18 dB at 3.7 GHz. The MIMO parameters are used to evaluate the diversity performance where the Envelope Correlation Coefficient (ECC) and Channel Capacity Loss (CCL) are less than 0.004 and 0.35 hits/sec/Hz and can be applicable to 5G and wearable applications.
{"title":"Modified Open slot based Two-Element Compact Antenna for 5G and wearable applications","authors":"Anubhav Kumar, A. De, R. Jain","doi":"10.1109/SPIN52536.2021.9566119","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566119","url":null,"abstract":"The Two-port antenna with modified open slot and high isolation is presented for 5G and wearable applications. The |S11| in dB varies from 3.15 GHz to 3.95 GHz of the two-port antenna with more than 22 dB isolation. The modified open slot is used to diminish the surface current as well as isolate the antenna elements. The Modified Open slot enhances the isolation up to 18 dB at 3.7 GHz. The MIMO parameters are used to evaluate the diversity performance where the Envelope Correlation Coefficient (ECC) and Channel Capacity Loss (CCL) are less than 0.004 and 0.35 hits/sec/Hz and can be applicable to 5G and wearable applications.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116122133","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566122
Soumyo Das, Tejas Mantri, R.A. Tembhurkar
This paper explores the way to maneuver the autonomous vehicle from one lane to another. In the advent of automating the ground vehicle, lateral control pays a pivotal role in determining the navigation of vehicles. The lane change feature is designed to aid drivers during maneuver from one lane to the adjacent lane. It involves a high-level interaction when an autonomous vehicle steer from one lane to another. The lane change is a standout amongst the most altogether researched programmed driving tasks that can be utilized by a self-driving vehicle. Many the exploration has been done beforehand to carry out lane change in driverless cars with the help of machine vision and complex controllers. In this work, the PD controller is used, and to check the favorable conditions, sensor topology is studied. To deal with dynamics, the bicycle model and constant acceleration models are verified and simulated. This trajectory has been designed using a polynomial equation method to increase the reliability of results which is efficient than other conventional methods. The inventive steps are illustrated in adopting polynomial-based path planning with constraints of vehicle dynamics and further aided with integrated lateral position control with predictive heading control. The proposed lateral control is an illustration of predictive motion control with weighted steer profiling considering non-linear vehicle dynamics to track planned path during automated maneuver. The performance of the lane change maneuver has been verified in simulation-based environment with the help of Simulink model and Carmaker vehicle dynamics in loop.
{"title":"Trajectory Planning and Maneuver Control to Assist Lane Change","authors":"Soumyo Das, Tejas Mantri, R.A. Tembhurkar","doi":"10.1109/SPIN52536.2021.9566122","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566122","url":null,"abstract":"This paper explores the way to maneuver the autonomous vehicle from one lane to another. In the advent of automating the ground vehicle, lateral control pays a pivotal role in determining the navigation of vehicles. The lane change feature is designed to aid drivers during maneuver from one lane to the adjacent lane. It involves a high-level interaction when an autonomous vehicle steer from one lane to another. The lane change is a standout amongst the most altogether researched programmed driving tasks that can be utilized by a self-driving vehicle. Many the exploration has been done beforehand to carry out lane change in driverless cars with the help of machine vision and complex controllers. In this work, the PD controller is used, and to check the favorable conditions, sensor topology is studied. To deal with dynamics, the bicycle model and constant acceleration models are verified and simulated. This trajectory has been designed using a polynomial equation method to increase the reliability of results which is efficient than other conventional methods. The inventive steps are illustrated in adopting polynomial-based path planning with constraints of vehicle dynamics and further aided with integrated lateral position control with predictive heading control. The proposed lateral control is an illustration of predictive motion control with weighted steer profiling considering non-linear vehicle dynamics to track planned path during automated maneuver. The performance of the lane change maneuver has been verified in simulation-based environment with the help of Simulink model and Carmaker vehicle dynamics in loop.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116440796","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566043
Anum Khan, Subodh Wairya
In this paper, a highly efficient ALU architecture is designed using Carbon Nanotube Field effect Transistor(CNTFET) and conventional MOSFET. High performing Multiplexer (Mux) based full adder is used for this purpose. First the performance of Transmission gate(TG) based Multiplexer and Pass transistor logic(PTL) based multiplexer are compared. Extensive performance analysis of several low transistor count hybrid adders has been done based on their power, delay, and PDP and thereby establishing Mux based Full Adder(FA) as the more efficient adder topology. The 4 bit ALU is implemented using the Mux based adder and its performance is compared with its CNTFET implementation. All the simulations are done using Cadence Virtuoso by 45nm technology for MOSFET and 10nm technology for CNTFET at 27°C for a supply voltage range of 0.6V to 1.2V. The CNTFET based circuits were designed to appraise their compatibility with conventional transistors and show considerable performance improvement.
{"title":"An Efficient ALU Architecture Topology for Nanotechnology Applications","authors":"Anum Khan, Subodh Wairya","doi":"10.1109/SPIN52536.2021.9566043","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566043","url":null,"abstract":"In this paper, a highly efficient ALU architecture is designed using Carbon Nanotube Field effect Transistor(CNTFET) and conventional MOSFET. High performing Multiplexer (Mux) based full adder is used for this purpose. First the performance of Transmission gate(TG) based Multiplexer and Pass transistor logic(PTL) based multiplexer are compared. Extensive performance analysis of several low transistor count hybrid adders has been done based on their power, delay, and PDP and thereby establishing Mux based Full Adder(FA) as the more efficient adder topology. The 4 bit ALU is implemented using the Mux based adder and its performance is compared with its CNTFET implementation. All the simulations are done using Cadence Virtuoso by 45nm technology for MOSFET and 10nm technology for CNTFET at 27°C for a supply voltage range of 0.6V to 1.2V. The CNTFET based circuits were designed to appraise their compatibility with conventional transistors and show considerable performance improvement.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124554330","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565977
V. Prakash, C. Manimegalai
Radio communication (RF) is the older communication technology which has many standards to form an updated version of 5G and above. It is a cost effective system for experimenting and implementing because of its available equipment. Under higher order and higher spectrum level it may harm human beings because it can penetrate through walls. This effect can be overcome by the growing technology like light communication. It has more benefits than conventional RF systems. Here, a high security module reduces data loss for the new technology system and also derive analytical expression. In the proposed model chaotic sequence is generated using Rossler algorithm. These sequences would look like a noise to cover the message signal. To improve the encryption strength it uses Lorenz and tent algorithm as a multi-threaded algorithm (MTA). This chaotic system is a dynamic spreading of sequence that are more sensitive and so authenticated users can retrieve the information during the transmission. The data security is given in such a way that even malicious attacker cannot retrieve the data when they do the snooping. Through the simulation using multi-threaded algorithm, the results have proved that it is a validated security algorithm. The obtained values from the analysis would provide high security information transmission for the VLC model with the better BER of 10-6 to 10-4.
{"title":"Secure data Communication using Chaos Synch Sequence on VLC Systems","authors":"V. Prakash, C. Manimegalai","doi":"10.1109/SPIN52536.2021.9565977","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565977","url":null,"abstract":"Radio communication (RF) is the older communication technology which has many standards to form an updated version of 5G and above. It is a cost effective system for experimenting and implementing because of its available equipment. Under higher order and higher spectrum level it may harm human beings because it can penetrate through walls. This effect can be overcome by the growing technology like light communication. It has more benefits than conventional RF systems. Here, a high security module reduces data loss for the new technology system and also derive analytical expression. In the proposed model chaotic sequence is generated using Rossler algorithm. These sequences would look like a noise to cover the message signal. To improve the encryption strength it uses Lorenz and tent algorithm as a multi-threaded algorithm (MTA). This chaotic system is a dynamic spreading of sequence that are more sensitive and so authenticated users can retrieve the information during the transmission. The data security is given in such a way that even malicious attacker cannot retrieve the data when they do the snooping. Through the simulation using multi-threaded algorithm, the results have proved that it is a validated security algorithm. The obtained values from the analysis would provide high security information transmission for the VLC model with the better BER of 10-6 to 10-4.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123453093","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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