Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987835
B. Siddartha, G. Ravikumar
Providing security for diagnostic and medical data is very essential for preserving privacy and safety of patients. This work present a chaos and DNA based encryption method for securing health care data. Recently, number of chaos and DNA based method has been presented by various researcher to safeguard diagnostic and medical image. However, these models are not efficient against cropping attack. As there exist high correlation among neighboring pixel. Thus, for resisting against cropping attack effective bit scrambling method is required. Firstly, this work present an efficient bit scrambling using logistic sine map and pseudorandom sequence using chaotic system. Then, DNA substitution is performed among them to resist against differential, statistical and cropping attack. Experiment are conducted on standard Lena and medical image. The outcome achieved shows proposed image security model is efficient when compared to existing image security models.
{"title":"A Novel Data Masking Method for Securing Medical Image","authors":"B. Siddartha, G. Ravikumar","doi":"10.1109/ICSSIT46314.2019.8987835","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987835","url":null,"abstract":"Providing security for diagnostic and medical data is very essential for preserving privacy and safety of patients. This work present a chaos and DNA based encryption method for securing health care data. Recently, number of chaos and DNA based method has been presented by various researcher to safeguard diagnostic and medical image. However, these models are not efficient against cropping attack. As there exist high correlation among neighboring pixel. Thus, for resisting against cropping attack effective bit scrambling method is required. Firstly, this work present an efficient bit scrambling using logistic sine map and pseudorandom sequence using chaotic system. Then, DNA substitution is performed among them to resist against differential, statistical and cropping attack. Experiment are conducted on standard Lena and medical image. The outcome achieved shows proposed image security model is efficient when compared to existing image security models.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121418279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987741
S. Barath, Madhumitha V, Kusuma S, K. Navya, B. Meghana
Many detection methods for the identification of Alzheimer's disease (AD) had been proposed in the past several decades. As there is no heal for AD to reverse its advancement, it is of key significance for early diagnosis and supervising of AD at its early introductory stage, i.e., mild cognitive impairment (MCI). New applications and methodologies are required for analyzing and to provide immediate early stage treating. Different biomarkers and clinical signs are used to assess the progression of AD depending on the patient's condition and disease stage. The current technology aims to help the drug in the treatment and care of patients with symptoms and biological properties. These parameters will assist in prior medication, and prevention could be ascertained in order to prevent the disease in reaching further stages.
{"title":"Detection and Analysis of Alzheimer's Disease from Medical Images: A Survey","authors":"S. Barath, Madhumitha V, Kusuma S, K. Navya, B. Meghana","doi":"10.1109/ICSSIT46314.2019.8987741","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987741","url":null,"abstract":"Many detection methods for the identification of Alzheimer's disease (AD) had been proposed in the past several decades. As there is no heal for AD to reverse its advancement, it is of key significance for early diagnosis and supervising of AD at its early introductory stage, i.e., mild cognitive impairment (MCI). New applications and methodologies are required for analyzing and to provide immediate early stage treating. Different biomarkers and clinical signs are used to assess the progression of AD depending on the patient's condition and disease stage. The current technology aims to help the drug in the treatment and care of patients with symptoms and biological properties. These parameters will assist in prior medication, and prevention could be ascertained in order to prevent the disease in reaching further stages.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128845488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987934
Alfred Bert Paul
This paper presents wireless charging setup for electric vehicles based on resonant inductive power transfer topology. Since the input power is fed from DC microgrid, this charging topology encourages the use of renewable energy sources like solar and wind. The wireless charging setup consists of different components such as DC microgrid, switching and power amplifier, transmitter-receiver setup and rectifier. A wireless charging setup based on resonant inductive power transfer is implemented and the performance of the prototype is analyzed using relevant waveforms.
{"title":"Switched Amplifier Resonant Inductive Wireless Charging Setup for Electric Vehicles","authors":"Alfred Bert Paul","doi":"10.1109/ICSSIT46314.2019.8987934","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987934","url":null,"abstract":"This paper presents wireless charging setup for electric vehicles based on resonant inductive power transfer topology. Since the input power is fed from DC microgrid, this charging topology encourages the use of renewable energy sources like solar and wind. The wireless charging setup consists of different components such as DC microgrid, switching and power amplifier, transmitter-receiver setup and rectifier. A wireless charging setup based on resonant inductive power transfer is implemented and the performance of the prototype is analyzed using relevant waveforms.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126381480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987777
V. K. Daliya, T. K. Ramesh
An IoT based healthcare system promises the implementation of high-quality healthcare services in a time bound and accurate manner. But the varieties of data coming from various sources will make the system more heterogeneous and hence it is challenging to process them further. These data coming from sensors are usually collected from the sensor's web and stored in Electronic Health Records (EHR). Data in EHR consists of each patients' details with respect to his hospital visits, previous treatment history, medication used, medical history etc. An error free and understandable data handling process enhances data interoperability among various EHRs, which use different ways of representing data. To handle these multiple types of data stored in different EHRs, data interoperability enhancement techniques such as semantic and syntactic methods play major roles. But, Syntactic method fails in tapping the meaning of the data while semantic method does not consider the format of the data. These shortcomings are overcome by the proposed hybrid method which can tap the meaning of data from heterogeneous sources while bringing uniformity for the data format as well. The proposed technique is analyzed in healthcare domain and is proven to be more efficient than using each method separately.
{"title":"Data Interoperability Enhancement of Electronic Health Record data using a hybrid model","authors":"V. K. Daliya, T. K. Ramesh","doi":"10.1109/ICSSIT46314.2019.8987777","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987777","url":null,"abstract":"An IoT based healthcare system promises the implementation of high-quality healthcare services in a time bound and accurate manner. But the varieties of data coming from various sources will make the system more heterogeneous and hence it is challenging to process them further. These data coming from sensors are usually collected from the sensor's web and stored in Electronic Health Records (EHR). Data in EHR consists of each patients' details with respect to his hospital visits, previous treatment history, medication used, medical history etc. An error free and understandable data handling process enhances data interoperability among various EHRs, which use different ways of representing data. To handle these multiple types of data stored in different EHRs, data interoperability enhancement techniques such as semantic and syntactic methods play major roles. But, Syntactic method fails in tapping the meaning of the data while semantic method does not consider the format of the data. These shortcomings are overcome by the proposed hybrid method which can tap the meaning of data from heterogeneous sources while bringing uniformity for the data format as well. The proposed technique is analyzed in healthcare domain and is proven to be more efficient than using each method separately.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126815628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987583
P. Sreenivasulu, S. Varadharajan
Nowadays, there is an increase in the volume of data produced and stored in the medical field. Therefore for the efficient handling of these large data there needs the compression technique to re-explore by considering the algorithm's complexity. In this research work, a narrative medical image compression approach is implanted by means of intelligent techniques and is composed of three main stages like Segmentation, Image compression, and Image decompression. From the start, the division procedure is started by parting the picture's Region of Interest (ROI) and Non-ROI areas by Modified Region Growing (MRG) calculation. Further, for ROI regions, Discrete Cosine Transform (DCT) model and SPHIT encoding method are deployed for compression, whereas the Non-ROI region uses the Discrete Wavelet Transform (DWT) and Merge-based Huffman encoding (MHE) methods for doing compression process. Mainly, this research work employs the optimization concept for the optimal selection of filter coefficients from DWT and DCT approaches. For this purpose, a new Improvised Steering angle and Gear-based ROA (ISG-ROA) is proposed, which is the modification of Rider Optimization Algorithm (ROA). To the last, decompression process is handled by reversing the compression process using the same optimized coefficients. The filter coefficient is adapted to finalize the result with reduced compression Ratio (CR).
{"title":"Medical Image Compression Using DCT based MRG Algorithem","authors":"P. Sreenivasulu, S. Varadharajan","doi":"10.1109/ICSSIT46314.2019.8987583","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987583","url":null,"abstract":"Nowadays, there is an increase in the volume of data produced and stored in the medical field. Therefore for the efficient handling of these large data there needs the compression technique to re-explore by considering the algorithm's complexity. In this research work, a narrative medical image compression approach is implanted by means of intelligent techniques and is composed of three main stages like Segmentation, Image compression, and Image decompression. From the start, the division procedure is started by parting the picture's Region of Interest (ROI) and Non-ROI areas by Modified Region Growing (MRG) calculation. Further, for ROI regions, Discrete Cosine Transform (DCT) model and SPHIT encoding method are deployed for compression, whereas the Non-ROI region uses the Discrete Wavelet Transform (DWT) and Merge-based Huffman encoding (MHE) methods for doing compression process. Mainly, this research work employs the optimization concept for the optimal selection of filter coefficients from DWT and DCT approaches. For this purpose, a new Improvised Steering angle and Gear-based ROA (ISG-ROA) is proposed, which is the modification of Rider Optimization Algorithm (ROA). To the last, decompression process is handled by reversing the compression process using the same optimized coefficients. The filter coefficient is adapted to finalize the result with reduced compression Ratio (CR).","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"529 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127061891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987946
G. P. Sarmila, N. Gnanmbigai, P. Dinadayalan
Cloud Computing (CC) has become an appealing computing criterion in both academic and business establishments. Fault tolerance is the key challenge faced by the CSP to provide guaranteed service to its users. Prior works proposed various algorithms for guaranteeing fault tolerance using job scheduling by assigning deadlines via time sliding (TS) and bandwidth scaling (BS). Job scheduling has proven to be an effective method to reduce fault occurrence and to address scalable user requests by balancing the incoming load. This paper proposes Hexagonal Chebyshev Gaussian and Discrete Time Organized Map-based (HCG-DTOM) job scheduling method which is an adaptive fault tolerance method based on Self organizing map. The HCG-DTOM method involves four steps. They are Hexagonal Lattice Structure Initialization model that performs initialization of cloud users, jobs to be assigned, virtual machines and job scheduler. Second, the virtual manager checks resource availability for a given set of input jobs using Chebyshev Discriminant Competitive model. Third, scheduling is performed by the job scheduler via Gaussian Neighbourhood Cooperative model. Finally, the resources are updated with the corresponding jobs for the appropriate cloud users are performed using the Discrete Time Adaptation model.
{"title":"Self Scheduling Based on Hexagonal Chebysev Gaussian and Discrete Time Organized Mapping in Cloud","authors":"G. P. Sarmila, N. Gnanmbigai, P. Dinadayalan","doi":"10.1109/ICSSIT46314.2019.8987946","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987946","url":null,"abstract":"Cloud Computing (CC) has become an appealing computing criterion in both academic and business establishments. Fault tolerance is the key challenge faced by the CSP to provide guaranteed service to its users. Prior works proposed various algorithms for guaranteeing fault tolerance using job scheduling by assigning deadlines via time sliding (TS) and bandwidth scaling (BS). Job scheduling has proven to be an effective method to reduce fault occurrence and to address scalable user requests by balancing the incoming load. This paper proposes Hexagonal Chebyshev Gaussian and Discrete Time Organized Map-based (HCG-DTOM) job scheduling method which is an adaptive fault tolerance method based on Self organizing map. The HCG-DTOM method involves four steps. They are Hexagonal Lattice Structure Initialization model that performs initialization of cloud users, jobs to be assigned, virtual machines and job scheduler. Second, the virtual manager checks resource availability for a given set of input jobs using Chebyshev Discriminant Competitive model. Third, scheduling is performed by the job scheduler via Gaussian Neighbourhood Cooperative model. Finally, the resources are updated with the corresponding jobs for the appropriate cloud users are performed using the Discrete Time Adaptation model.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127422445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987882
P. Saranya, Dr. P. Asha
Massive amount of data in different forms need to be handled in any healthcare applications. Type of data, size of data, data security and other features has more significance in handling the data. The term big data refers to data with certain characteristics, volume, velocity, value, veracity and variability. Such big data need to be stored, processed, and analyzed for required results. Medical data has more complexity in predicting the results from it, which will have more significance in patient's treatment. Because of its significance, there is need of developing efficient and better performing algorithms, techniques and tools to analyze medical big data. Whereas, the traditional algorithms are not capable for analyzing such complex data. Machine learning algorithms well fit for these kinds of data and analytics. In this Keywords: Big data, Health care, disease prediction, SVM, CNN survey paper, we discussed about characteristic of big data, features of big data, how to represent big data, different types of machine learning algorithms used in big data analytics. We discussed about big data analytics in major healthcare areas like EHR maintenance, disease diagnose, prediction of emergency condition of patients, etc.,. Also stated different machine algorithms usage in disease diagnose and patient's data analysis and discussed about importance of various machine learning algorithms. Here, we have highlighted the areas where big data analytics have been applied in healthcare sectors. It describes the characteristics and features of big data, importance of big data analytics in healthcare sectors, various machine learning algorithms used in big data analytics and their efficiency.
{"title":"Survey on Big Data Analytics in Health Care","authors":"P. Saranya, Dr. P. Asha","doi":"10.1109/ICSSIT46314.2019.8987882","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987882","url":null,"abstract":"Massive amount of data in different forms need to be handled in any healthcare applications. Type of data, size of data, data security and other features has more significance in handling the data. The term big data refers to data with certain characteristics, volume, velocity, value, veracity and variability. Such big data need to be stored, processed, and analyzed for required results. Medical data has more complexity in predicting the results from it, which will have more significance in patient's treatment. Because of its significance, there is need of developing efficient and better performing algorithms, techniques and tools to analyze medical big data. Whereas, the traditional algorithms are not capable for analyzing such complex data. Machine learning algorithms well fit for these kinds of data and analytics. In this Keywords: Big data, Health care, disease prediction, SVM, CNN survey paper, we discussed about characteristic of big data, features of big data, how to represent big data, different types of machine learning algorithms used in big data analytics. We discussed about big data analytics in major healthcare areas like EHR maintenance, disease diagnose, prediction of emergency condition of patients, etc.,. Also stated different machine algorithms usage in disease diagnose and patient's data analysis and discussed about importance of various machine learning algorithms. Here, we have highlighted the areas where big data analytics have been applied in healthcare sectors. It describes the characteristics and features of big data, importance of big data analytics in healthcare sectors, various machine learning algorithms used in big data analytics and their efficiency.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127338475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987765
Bharath Ravi Prakash, S. Megha, Mervin K Francis, S. Niharika, M. Megha
In this era of advancing technology, street lights are the most commonly needed requirement for a common man to commute. Street lights provide safety while a person is walking on the road. While they help a person to safely reach the destination the lights will be ON and it can be turned OFF in a smart way when there are nobody using it. This can be done with the help of advanced sensors, which can effectively determine whether the light should be ON or not. The power of IoT can be used to track and monitor the status of the devices. This paper discusses an efficient and cost-effective way to detect any unusual or strange behavior and an acknowledgment will be sent to the governing body to take the required action.
{"title":"Intelligent Management of Street Lights using Internet of Things and Power Management","authors":"Bharath Ravi Prakash, S. Megha, Mervin K Francis, S. Niharika, M. Megha","doi":"10.1109/ICSSIT46314.2019.8987765","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987765","url":null,"abstract":"In this era of advancing technology, street lights are the most commonly needed requirement for a common man to commute. Street lights provide safety while a person is walking on the road. While they help a person to safely reach the destination the lights will be ON and it can be turned OFF in a smart way when there are nobody using it. This can be done with the help of advanced sensors, which can effectively determine whether the light should be ON or not. The power of IoT can be used to track and monitor the status of the devices. This paper discusses an efficient and cost-effective way to detect any unusual or strange behavior and an acknowledgment will be sent to the governing body to take the required action.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121862338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987937
Amit Gupta, Abhishek Kumar, M. Mamatha, Shravani Kalkonda
Microstrip patch antenna is adopted considering domestic along with utilization, popularly for mobile as it is light weight, simple to build and low cost. The proposed antenna consists of six dipoles on single common feed, FR-4 Epoxy whose proportionate dielectric function is 4.4 and destruction tangent is 0.02 is used for proposed design. The dimensions for the substrate are 15.1794mm x 18.25mm x 1.5 mm. It is intended to be operated in 1 GHz–75GHz i.e., from L band to V band with a maximum return loss of −43.67 dB and with a maximum Gain of 5.72dB. For the same design, Rogers whose approximate permittivity is 2.2 and casualty tangent is 0.0009 and Arlon whose contingent permittivity is 6.15 and catastrophe tangent is 0.03 used as substrate materials for the optimal characteristics. Patch aerial potential characteristics are in same manner with resonant frequencies, return loss, gain, bandwidth, VSWR, directivity are taken into account for the analysis of proposed antenna. In Rogers material, maximum return loss of −23.51dB with a maximum gain of 8.66dB and in Arlon material, maximum return loss of −34.64dB with a maximum gain of 9.82dB are measured from HFSS software. The newly generated antenna can therefore, be helpful for multiple wide band utilization depending on the particular substrate material.
{"title":"Design and Simulation of Microstrip Patch Antenna for Next Generation Communication Applications","authors":"Amit Gupta, Abhishek Kumar, M. Mamatha, Shravani Kalkonda","doi":"10.1109/ICSSIT46314.2019.8987937","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987937","url":null,"abstract":"Microstrip patch antenna is adopted considering domestic along with utilization, popularly for mobile as it is light weight, simple to build and low cost. The proposed antenna consists of six dipoles on single common feed, FR-4 Epoxy whose proportionate dielectric function is 4.4 and destruction tangent is 0.02 is used for proposed design. The dimensions for the substrate are 15.1794mm x 18.25mm x 1.5 mm. It is intended to be operated in 1 GHz–75GHz i.e., from L band to V band with a maximum return loss of −43.67 dB and with a maximum Gain of 5.72dB. For the same design, Rogers whose approximate permittivity is 2.2 and casualty tangent is 0.0009 and Arlon whose contingent permittivity is 6.15 and catastrophe tangent is 0.03 used as substrate materials for the optimal characteristics. Patch aerial potential characteristics are in same manner with resonant frequencies, return loss, gain, bandwidth, VSWR, directivity are taken into account for the analysis of proposed antenna. In Rogers material, maximum return loss of −23.51dB with a maximum gain of 8.66dB and in Arlon material, maximum return loss of −34.64dB with a maximum gain of 9.82dB are measured from HFSS software. The newly generated antenna can therefore, be helpful for multiple wide band utilization depending on the particular substrate material.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125955655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987789
Reshali Crystal Rebello, Vasudeva Pai, K. Pai
Wireless/Remote Sensor Networks (WSNs) contains sensor hubs and a base station. The role of sensor nodes is to acquire the data from the surrounding in which they are placed and then report the data to base station or sink. While the data gathering, data processing, data reporting and maintaining, it requires a lot of security measures for the data as well as motes(nodes) to be well protected from attacks. Intrusion detection systems (IDs) is a way to detect any anomalies or attacks in the network and also helps to tackle it. The paper focuses on the comparison of the types of intrusion detection systems used against the various attacks in WSNs.
{"title":"A Review: Intrusion Detection Systems in Remote Sensor Network","authors":"Reshali Crystal Rebello, Vasudeva Pai, K. Pai","doi":"10.1109/ICSSIT46314.2019.8987789","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987789","url":null,"abstract":"Wireless/Remote Sensor Networks (WSNs) contains sensor hubs and a base station. The role of sensor nodes is to acquire the data from the surrounding in which they are placed and then report the data to base station or sink. While the data gathering, data processing, data reporting and maintaining, it requires a lot of security measures for the data as well as motes(nodes) to be well protected from attacks. Intrusion detection systems (IDs) is a way to detect any anomalies or attacks in the network and also helps to tackle it. The paper focuses on the comparison of the types of intrusion detection systems used against the various attacks in WSNs.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126252117","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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