Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878726
Nikhil Joshi, Rewanth Tammana
Trained Machine learning models are core components of proprietary products. Business models are entirely built around these ML powered products. Such products are either delivered as a software package (containing the trained model) or they are deployed on cloud with restricted API access for prediction. In ML-as-a-service, users are charged per-query or per-hour basis, generating revenue for businesses. Models deployed on cloud could be vulnerable to Model Duplication attacks. Researchers found ways to exploit these services and clone the functionalities of black box models hidden in the cloud by continuously querying the provided APIs. After successful execution of attack, the attacker does not require to pay the cloud service provider. Worst case scenario, attackers can also sell the cloned model or use them in their business model.Traditionally attackers use convex optimization algorithm like Gradient Descent with appropriate hyper-parameters to train their models. In our research we propose a modification to traditional approach called as GDALR (Gradient Driven Adaptive Learning Rate) that dynamically updates the learning rate based on the gradient values. This results in stealing the target model in comparatively less number of epochs, decreasing the time and cost, hence increasing the efficiency of the attack. This shows that sophisticated attacks can be launched for stealing the black box machine learning models which increases risk for MLaaS based businesses.
{"title":"GDALR: An Efficient Model Duplication Attack on Black Box Machine Learning Models","authors":"Nikhil Joshi, Rewanth Tammana","doi":"10.1109/ICSCAN.2019.8878726","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878726","url":null,"abstract":"Trained Machine learning models are core components of proprietary products. Business models are entirely built around these ML powered products. Such products are either delivered as a software package (containing the trained model) or they are deployed on cloud with restricted API access for prediction. In ML-as-a-service, users are charged per-query or per-hour basis, generating revenue for businesses. Models deployed on cloud could be vulnerable to Model Duplication attacks. Researchers found ways to exploit these services and clone the functionalities of black box models hidden in the cloud by continuously querying the provided APIs. After successful execution of attack, the attacker does not require to pay the cloud service provider. Worst case scenario, attackers can also sell the cloned model or use them in their business model.Traditionally attackers use convex optimization algorithm like Gradient Descent with appropriate hyper-parameters to train their models. In our research we propose a modification to traditional approach called as GDALR (Gradient Driven Adaptive Learning Rate) that dynamically updates the learning rate based on the gradient values. This results in stealing the target model in comparatively less number of epochs, decreasing the time and cost, hence increasing the efficiency of the attack. This shows that sophisticated attacks can be launched for stealing the black box machine learning models which increases risk for MLaaS based businesses.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128428825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878748
E. Thamizhselvi, V. Geetha
This paper provides a brief survey about the anthropometric traits in various fields. The word “anthropo” refers to human and “metric” refers to measurement. Anthropometry is essentially refers to the measurement of human individuals for the purpose of identifying the human physical variations. Anthropometry plays a predominant role in medical science, Forensic medicine and criminology, Biometric, sports etc. Anthropometric is used to access the size, shape and composition of human body. The purpose of anthropometric indicator criteria to select features and they have been justified mainly on the basis of being correlated with other risk factors. Due to its significance, the statistical mean and standard deviation measurements are highly followed to monitor the human body based on its measurement. Since this measurement vary according to the fields, it is indeed important to undergo a detailed analysis of anthropometric traits. Hence, this paper discusses about the potential researches on the use of anthropometric traits for different fields in association with the data mining to solve the complex problem by selecting the best features.
{"title":"A Comparative Study of Anthropometric Measures and its significance on Diverse Applications","authors":"E. Thamizhselvi, V. Geetha","doi":"10.1109/ICSCAN.2019.8878748","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878748","url":null,"abstract":"This paper provides a brief survey about the anthropometric traits in various fields. The word “anthropo” refers to human and “metric” refers to measurement. Anthropometry is essentially refers to the measurement of human individuals for the purpose of identifying the human physical variations. Anthropometry plays a predominant role in medical science, Forensic medicine and criminology, Biometric, sports etc. Anthropometric is used to access the size, shape and composition of human body. The purpose of anthropometric indicator criteria to select features and they have been justified mainly on the basis of being correlated with other risk factors. Due to its significance, the statistical mean and standard deviation measurements are highly followed to monitor the human body based on its measurement. Since this measurement vary according to the fields, it is indeed important to undergo a detailed analysis of anthropometric traits. Hence, this paper discusses about the potential researches on the use of anthropometric traits for different fields in association with the data mining to solve the complex problem by selecting the best features.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130920042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878718
Immanuel Zion Ramdinthara, P. Bala
Agriculture is the backbone of every country. It produces all the necessary needs such as wheat, rice, fruits, grains which are consumed by a human for everyday survival. So, it is important for the country to develop and sustain a productive agricultural system. As demand is increasing for food, food security is very important to sustain and increase yield production at a higher rate and at the same time preserve the ecosystem. So, the technologies in the agricultural domain may be incorporated to enhance food supplies and production. In many countries like the USA, China and Israel have a prominently high implementation of technologies with a high rate of food production and even exported in many parts of the world. These countries have implemented advanced techniques such as the Internet of Things (IoT), Cloud Computing, Machine Learning and Deep Learning algorithm for agriculture domain. Sensor technology used in this domain is highly effective, accurate and productive for precision agriculture. In this topic, agriculture in some developed and developing countries are compared also discusses the way in which these countries could possibly exchange feasible ideas from a different perspective for the development of sustainable agriculture.
{"title":"A Comparative study of IoT Technology in Precision Agriculture","authors":"Immanuel Zion Ramdinthara, P. Bala","doi":"10.1109/ICSCAN.2019.8878718","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878718","url":null,"abstract":"Agriculture is the backbone of every country. It produces all the necessary needs such as wheat, rice, fruits, grains which are consumed by a human for everyday survival. So, it is important for the country to develop and sustain a productive agricultural system. As demand is increasing for food, food security is very important to sustain and increase yield production at a higher rate and at the same time preserve the ecosystem. So, the technologies in the agricultural domain may be incorporated to enhance food supplies and production. In many countries like the USA, China and Israel have a prominently high implementation of technologies with a high rate of food production and even exported in many parts of the world. These countries have implemented advanced techniques such as the Internet of Things (IoT), Cloud Computing, Machine Learning and Deep Learning algorithm for agriculture domain. Sensor technology used in this domain is highly effective, accurate and productive for precision agriculture. In this topic, agriculture in some developed and developing countries are compared also discusses the way in which these countries could possibly exchange feasible ideas from a different perspective for the development of sustainable agriculture.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"123 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128706566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878797
G. Devi, P. Rajesh, S. Sathish, S. Sivaraman, S. Fayaz
This paper presents the performance investigation of Hexagram Inverter for high power applications. It can be used for 3-phase and 6-phase applications. It has many advantages such as less number of switches, easy construction and maintenance, isolated dc buses. Further, due to the module interconnection it has built-in fault tolerant feature. Compared to cascaded H-bridge inverter, it requires low dc energy storage. This well-known quality makes the system in high power applications. Hexagram inverter fed three phase induction motor drive is developed in Matlab/Simulink environment. Simulation is carried out to study the performance of the 3-phase induction motor at different load conditions and the results are presented.
{"title":"Performance Investigation of Hexagram Inverter for High Power Applications","authors":"G. Devi, P. Rajesh, S. Sathish, S. Sivaraman, S. Fayaz","doi":"10.1109/ICSCAN.2019.8878797","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878797","url":null,"abstract":"This paper presents the performance investigation of Hexagram Inverter for high power applications. It can be used for 3-phase and 6-phase applications. It has many advantages such as less number of switches, easy construction and maintenance, isolated dc buses. Further, due to the module interconnection it has built-in fault tolerant feature. Compared to cascaded H-bridge inverter, it requires low dc energy storage. This well-known quality makes the system in high power applications. Hexagram inverter fed three phase induction motor drive is developed in Matlab/Simulink environment. Simulation is carried out to study the performance of the 3-phase induction motor at different load conditions and the results are presented.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122248015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878714
A. Sharmila, P. Dananjayan
Cognitive radio network (CRN) is considered a plausible way out for future 5G applications through its dynamic spectrum access technology. Spectrum sharing being the main objective of CRN, it alleviates the spectrum scarcity problem. In this paper, the manifold techniques for spectrum sharing in CRN are outlined. The distinct advantages and major limiting constraints with relevant to the hybrid spectrum access technology are elaborated thoroughly to enhance the QoS parameters of the users and to achieve better spectral efficiency.
{"title":"Spectrum Sharing Techniques in Cognitive Radio Networks – A Survey","authors":"A. Sharmila, P. Dananjayan","doi":"10.1109/ICSCAN.2019.8878714","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878714","url":null,"abstract":"Cognitive radio network (CRN) is considered a plausible way out for future 5G applications through its dynamic spectrum access technology. Spectrum sharing being the main objective of CRN, it alleviates the spectrum scarcity problem. In this paper, the manifold techniques for spectrum sharing in CRN are outlined. The distinct advantages and major limiting constraints with relevant to the hybrid spectrum access technology are elaborated thoroughly to enhance the QoS parameters of the users and to achieve better spectral efficiency.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124110812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878784
K. Vasu Babu, B. Anuradha
In modern telecommunications system MIMO antenna plays an important role having the capability to radiate wave is extra than one radiation pattern & polarization is also another critical factor. This article describes the design & reduction of isolation between the two symmetrical patches. The separation between the two patches must be maintained to reduce the isolation is 0.02 λ0 The proposed system having a compact size of $38,,mathrm {m}mathrm {m}times 25$ mm with a FR-4 substrate and loss tangent of 0.02 is considered. The MIMO system is resonate at a frequency of 3.98 GHz obtained the reflection coefficient (S11) of −39.71 dB & greatly reducing the isolation (S12) of −50 dB. At the resonant band of frequency the impedance bandwidth of the systems is around 1.76 GHz. The proposed design maintained the VSWR ≤ 2 and ECC < 0.04 is maintained at the resonant band of frequency. The different time domain analysis parameters like group delay, diversity gain, real/ imaginary impedances and peak gain is also measured here. The group delay and diversity gain at the resonant frequency of proposed MIMO structure is observed −2.48 ± 1nsec & 9.999 dBi.
{"title":"Design & Isolation Reduction of Circle Inserted MIMO Antenna","authors":"K. Vasu Babu, B. Anuradha","doi":"10.1109/ICSCAN.2019.8878784","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878784","url":null,"abstract":"In modern telecommunications system MIMO antenna plays an important role having the capability to radiate wave is extra than one radiation pattern & polarization is also another critical factor. This article describes the design & reduction of isolation between the two symmetrical patches. The separation between the two patches must be maintained to reduce the isolation is 0.02 λ0 The proposed system having a compact size of $38,,mathrm {m}mathrm {m}times 25$ mm with a FR-4 substrate and loss tangent of 0.02 is considered. The MIMO system is resonate at a frequency of 3.98 GHz obtained the reflection coefficient (S11) of −39.71 dB & greatly reducing the isolation (S12) of −50 dB. At the resonant band of frequency the impedance bandwidth of the systems is around 1.76 GHz. The proposed design maintained the VSWR ≤ 2 and ECC < 0.04 is maintained at the resonant band of frequency. The different time domain analysis parameters like group delay, diversity gain, real/ imaginary impedances and peak gain is also measured here. The group delay and diversity gain at the resonant frequency of proposed MIMO structure is observed −2.48 ± 1nsec & 9.999 dBi.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122361784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878831
V. Lakshmi, V. Nithya, K. Sripriya, C. Preethi, K. Logeshwari
Nowadays technology has improved the worldwide and has become vital part of our life. It aid for doctors to analyze and diagnose the medical problems and diseases. With help artificial intelligence in medicine science become high demand now. This work focuses on clinical decision support system which aid medical people to diagnose of disease. In this paper first present related work in various aspects of clinical decision support systems to provide diagnosis solutions to medical related problems. In this paper a proposed method to identify patient with diabetes disease risk level is indentified. In this work diabetes patient risk level is been detected by using ontology and machine learning technique. Ontology holds disease symptoms, causes and treatments. In machine learning, nave base algorithm is used to make decision on patient record also it defines possibilities of risk level. The proposed algorithm will be evaluated against the following metrics namely confusion matrix, precision level, mean and this proposed work is found to have better prediction level when compared with existing work.
{"title":"Prediction of Diabetes Patient Stage Using Ontology Based Machine Learning System","authors":"V. Lakshmi, V. Nithya, K. Sripriya, C. Preethi, K. Logeshwari","doi":"10.1109/ICSCAN.2019.8878831","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878831","url":null,"abstract":"Nowadays technology has improved the worldwide and has become vital part of our life. It aid for doctors to analyze and diagnose the medical problems and diseases. With help artificial intelligence in medicine science become high demand now. This work focuses on clinical decision support system which aid medical people to diagnose of disease. In this paper first present related work in various aspects of clinical decision support systems to provide diagnosis solutions to medical related problems. In this paper a proposed method to identify patient with diabetes disease risk level is indentified. In this work diabetes patient risk level is been detected by using ontology and machine learning technique. Ontology holds disease symptoms, causes and treatments. In machine learning, nave base algorithm is used to make decision on patient record also it defines possibilities of risk level. The proposed algorithm will be evaluated against the following metrics namely confusion matrix, precision level, mean and this proposed work is found to have better prediction level when compared with existing work.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"362 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132695625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878728
N. Poonguzhali, Kagne Raveena Rajendra, T. Mageswari, T. Pavithra
Brain Tumor occurs when abnormal cells form within the brain. There are two main types of tumors malignant and benign tumors. So for early precise detection of tumor cells, in conventional methods there are various algorithm which helps to diagnosis the tumor cells though it fails to predict an accurate results. This paper presents a reliable detection method by making use of tensor flow library, Faster R-CNN algorithm and SVM classifier used to predict the likely chances of brain related tumor of the patient. Faster R-CNN algorithm is a capable classification algorithm in which both region proposal generation and objection tasks are all done by the same convolutional networks.
{"title":"Heterogeneous Deep Neural Network for Healthcare Using Metric Learning","authors":"N. Poonguzhali, Kagne Raveena Rajendra, T. Mageswari, T. Pavithra","doi":"10.1109/ICSCAN.2019.8878728","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878728","url":null,"abstract":"Brain Tumor occurs when abnormal cells form within the brain. There are two main types of tumors malignant and benign tumors. So for early precise detection of tumor cells, in conventional methods there are various algorithm which helps to diagnosis the tumor cells though it fails to predict an accurate results. This paper presents a reliable detection method by making use of tensor flow library, Faster R-CNN algorithm and SVM classifier used to predict the likely chances of brain related tumor of the patient. Faster R-CNN algorithm is a capable classification algorithm in which both region proposal generation and objection tasks are all done by the same convolutional networks.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132786903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878698
Aiju Thomas, N. Eldhose
Divergent modulation schemes have been proposed for Internet of Things (IoT). One specific application is sensor networks, where narrow band of data is required to be transferred for long distance and modulated signals are susceptible to interference. Chirps signals can traverse long distance and are resilient to White Gaussian Noise and Doppler effects. We analyze the performance of chirp spread spectrum as used in LoRa™physical layer for noise resilience. We evaluate Chirp Spread Spectrum (CSS) at ISM band 868 MHz for spreading factor 7 to 12 at bandwidth 125 kHz and sampling frequency 125Khz. Signals are transmitted through AWGN channel and are evaluated for Bit Error Rate (BER). Packet collisions and packet error rate were analyzed for simultaneous transmissions.
{"title":"Performance Evaluation of Chirp Spread Spectrum as used in LoRa Physical Layer","authors":"Aiju Thomas, N. Eldhose","doi":"10.1109/ICSCAN.2019.8878698","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878698","url":null,"abstract":"Divergent modulation schemes have been proposed for Internet of Things (IoT). One specific application is sensor networks, where narrow band of data is required to be transferred for long distance and modulated signals are susceptible to interference. Chirps signals can traverse long distance and are resilient to White Gaussian Noise and Doppler effects. We analyze the performance of chirp spread spectrum as used in LoRa™physical layer for noise resilience. We evaluate Chirp Spread Spectrum (CSS) at ISM band 868 MHz for spreading factor 7 to 12 at bandwidth 125 kHz and sampling frequency 125Khz. Signals are transmitted through AWGN channel and are evaluated for Bit Error Rate (BER). Packet collisions and packet error rate were analyzed for simultaneous transmissions.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132149365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878826
L. Raj, K. Roja, J. S. Theresa, M. Sathyavani, M. Sumithra
PCB design plays a vital role in the evolution of modern technology. Dual side PCB has two conductive layers, multi-side PCB should have at least three conductive layers which are buried in the centre of the material. Layers of copper foil, prepreg and core material sandwich together under high temperature and pressure to produce multi-layer. Multilayer board can pack the same amount of power into a PCB that’s half the size of the original or traditional double-sided PCB. The demonstration will be done by using NI Ultiboard 12.0. In this project, the datum we get from our PCB, it is an obvious way to reduce the cost of PCB and to simplify the design of PCB. It can be done by reducing the number of vias and components.
{"title":"Elegant Way of Designing Printed Circuit Board via Multilayer Technique Using Ultiboard 12.0","authors":"L. Raj, K. Roja, J. S. Theresa, M. Sathyavani, M. Sumithra","doi":"10.1109/ICSCAN.2019.8878826","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878826","url":null,"abstract":"PCB design plays a vital role in the evolution of modern technology. Dual side PCB has two conductive layers, multi-side PCB should have at least three conductive layers which are buried in the centre of the material. Layers of copper foil, prepreg and core material sandwich together under high temperature and pressure to produce multi-layer. Multilayer board can pack the same amount of power into a PCB that’s half the size of the original or traditional double-sided PCB. The demonstration will be done by using NI Ultiboard 12.0. In this project, the datum we get from our PCB, it is an obvious way to reduce the cost of PCB and to simplify the design of PCB. It can be done by reducing the number of vias and components.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132941859","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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