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Integument Neoplasm Detection using Convolution Neural Network 基于卷积神经网络的外皮肿瘤检测
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080189
Jamalapurapu Yamini, Ranga Rao Jalleda, Naragam Vennela, Narepalem Padmavathi
{"title":"Integument Neoplasm Detection using Convolution Neural Network","authors":"Jamalapurapu Yamini, Ranga Rao Jalleda, Naragam Vennela, Narepalem Padmavathi","doi":"10.1109/ICONAT57137.2023.10080189","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080189","url":null,"abstract":"Nowadays, skin cancer, especially melanoma skin cancer, is a serious health concern. In general, most skin cancers can be treated if they are found in their earliest stages. The best way to deal with this issue is to try to spot it as early as possible and have some little surgery to fix it. The proposed approach, which uses images, could help a dermatologist diagnose this kind of skin cancer early. An advanced convolutional neural network (CNN), a type of deep learning model, is fed the augmented images. The classifier, which is trained using a huge number of training data, is capable of predicting certain types of skin cancer, including melanoma, benign keratosis, vascular lesions, and dermatofibroma.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133073500","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}
引用次数: 0
A Feed-Forward and Back Propagation Neural Network Approach for Identifying Network Anomalies 一种用于网络异常识别的前馈和反向传播神经网络方法
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080784
A. Prashanthi, R. Reddy
{"title":"A Feed-Forward and Back Propagation Neural Network Approach for Identifying Network Anomalies","authors":"A. Prashanthi, R. Reddy","doi":"10.1109/ICONAT57137.2023.10080784","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080784","url":null,"abstract":"The internet’s ability to link all of our gadgets together has a profound impact on our daily routines. Numerous industries, including medicine, smart buildings, and commerce, all make use of network-based technologies. These programmers cater to big populations and offer a wide variety of services. As a result, the security of network-based applications has continuously attracted attention from academics and business leaders. Thanks to deep learning’s development, we can now probe previously inaccessible topics. Hackers take advantage of security holes in networks to access protected resources. This kind of knowledge and access to systems can do irreparable harm and inflict incalculable losses. Therefore, it is crucial that these network attacks be uncovered. While systematically probing every conceivable set of network features, the few inputs required by deep learning-based algorithms are a major selling point. In light of this, in this research, we provide a deep learning architecture based on feed-forward back propagation neural networks for the purpose of detecting anomalies into a network. Our investigation uncovered 14 unique forms of malicious network activity. The studies were conducted using the standard-setting CICIDS2017 dataset, and the findings show an accuracy of 91.02%.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133563927","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}
引用次数: 0
Language Identification System: Employing ReLu for India’s Regional Languages (ReLu) 语言识别系统:为印度地区语言(ReLu)使用ReLu
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080570
Lekhraj Saini
{"title":"Language Identification System: Employing ReLu for India’s Regional Languages (ReLu)","authors":"Lekhraj Saini","doi":"10.1109/ICONAT57137.2023.10080570","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080570","url":null,"abstract":"In this paper, I provide a model for language identification that makes use of neural networks. The approach is intended to distinguish between Indian regional and dialectal languages. Individuals of Indian descent are the target population for this model. I train the model using a variety of data sources, including corpora of written and spoken material in a variety of languages. In addition, I use a variety of additional data sources. As a result, we can train the model to be more accurate. When I compare the performance of our model to that of a naive Bayes classifier, I find that the results produced by our model are superior to those produced by the naive Bayes classifier. This is because our model considers more information than the naïve Bayes classifier. The ReLu activation function is employed on each neuron throughout our simulation, and the neural network design comprises several layers. Each neuron receives the ReLu activation function. This allows the model to capture the relationships and correlations that exist between the input data, which improves its capacity to recognize the language employed in a specific sentence. Furthermore, our technology can deal with ambiguous cases, such as sentences written in the devnagri script, which is utilized in a number of Indian languages. This is a benefit provided by our software. Using our system has several advantages, and this is only one of them.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133176730","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}
引用次数: 0
ShEnc: A Versatile Secure Multi-Party Data Sharing Framework 一个通用的安全多方数据共享框架
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080762
Yusuke Namiki, Akihito Nakamura
{"title":"ShEnc: A Versatile Secure Multi-Party Data Sharing Framework","authors":"Yusuke Namiki, Akihito Nakamura","doi":"10.1109/ICONAT57137.2023.10080762","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080762","url":null,"abstract":"Secure data sharing via public Internet or local networks is absolutely vital for people today. Confidential information is stored as a file in most settings and shared via intermediate systems, including email, file hosting service, and portable devices. Cyberattacks (malicious) and human errors (non-malicious) are potential threats in these intermediate systems which may result in information leakage, impersonation, and repudiability. This is also true for communication networks. This paper presents a new method and system, called ShEnc, for end-to-end (E2E) secure multi-party data sharing. E2E encryption provides secure transmission of data from one end to the other while the intermediate systems may not be especially trustworthy. The system depends neither on prior secret sharing nor a dedicated server, secure communication channel, and special devices. Instead, we utilize the public key encryption: RSA and ECC. That is, only the public keys of the participants are disseminated beforehand, and robust confidentiality of shared data and authenticity of the sender are ensured. Furthermore, the system introduces a unique file format, enabling multi-party data sharing with a single file. The results of performance evaluation revealed that the overhead of the encrypted file size is about 2+n KB for RSA and 1+0.3n KB for ECC for the number of participants n. The processing time is less than one second under the condition where sharing 128 MiB file with 16 participants and 4 MiB file with 100 participants.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131899435","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}
引用次数: 0
Dog Breed Classification using Inception-ResNet-V2 使用Inception-ResNet-V2进行犬种分类
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080065
S. Manivannan, N. Venkateswaran
{"title":"Dog Breed Classification using Inception-ResNet-V2","authors":"S. Manivannan, N. Venkateswaran","doi":"10.1109/ICONAT57137.2023.10080065","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080065","url":null,"abstract":"Dogs are one of the most faithful and loyal animals in the world.They are also the favourite pets for most of the pet lovers.Many feel relieved from stress and tension when they spent time with their pet dogs.So these special creatures are spread into various breeds across the world.It is very much essential to distinguish the breeds at many occasions.With the advent of development of artificial intelligence the methods to classify such large scale of breeds had become easier.This paper proposes a transfer learning based pretrained deep CNN architecture for classification of 120 breeds.The proposed model was trained on Stanford dogs dataset and the model achieved a training accuracy of 95.03% and a validation accuracy of 92.92% after training.The model performance and robustness had been inferred after testing with test images from internet.The network predicted correct breeds with a test accuracy of 88.92%.This paper provides an optimal solution for fine grained dog breed classification.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115675591","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}
引用次数: 1
Performance Analysis of AlGaN/GaN FINFET for Different Temperatures, Gate Oxide dielectric’s and Work functions 不同温度、栅极氧化物介电和功函数下AlGaN/GaN FINFET的性能分析
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080795
M. Reddy, D. Panda
{"title":"Performance Analysis of AlGaN/GaN FINFET for Different Temperatures, Gate Oxide dielectric’s and Work functions","authors":"M. Reddy, D. Panda","doi":"10.1109/ICONAT57137.2023.10080795","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080795","url":null,"abstract":"The work presented is a simulation study of the AlGaN/GaN Heterostructure vertical FINFET. The proposed structure has been investigated by adding an AlGaN layer at source channel junction. From, the findings of our study it is clear that the drain current rises after adding the polarization layer at the source channel interface because of the increase in the charge concentration(2DEG) at the interface. We have done a rigorous investigation for various gate oxide material dielectric’s, gate metal’s work function and at different temperatures. The various DC Figure of merits (FOM) such as SS, Ion/Ioff have shown improvement for the higher dielectric constant value, higher work function, and higher temperature. Apart, various analog/RF parameters such as gm, gd, Intrinsic gain (Av) have been analyzed and the linearity metrics like gm2, gm3, VIP2, VIP3, IIP3, IMD3 and 1-dB compression point are also analyzed and are proved for enhancing the device structure’s linearity.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114795488","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}
引用次数: 0
Speed Control of BLDC Motor Using PI Controller 基于PI控制器的无刷直流电动机速度控制
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080074
B. Bairwa, Madan Murari, Mahammadgous Shahapur, K. R, Md.Firdosh Khan
{"title":"Speed Control of BLDC Motor Using PI Controller","authors":"B. Bairwa, Madan Murari, Mahammadgous Shahapur, K. R, Md.Firdosh Khan","doi":"10.1109/ICONAT57137.2023.10080074","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080074","url":null,"abstract":"Permanent Magnet Brushless DC (BLDC) motors have major application in industries like E-mobility (Electrical vehicles, Electric bicycle), Industrial robots, CNC machine tools in the last decade. BLDC motors are at the core of many industrial automation applications, but they face major problems when performing speed control. Because brushless DC motors are compact, they are highly efficient and have high torque-to-power ratios. Brushless DC motors require little maintenance since they run brushless rather than on a rotor. FPGA based speed controllers are used to control speed of BLDC motors in this paper. The Hall Effect sensors are used to commutate the BLDC motor in the presented technique. An algorithm for closed-loop PWM speed control of BLDC motors with FPGA is proposed. A predefined value or user control is used to control the motor speed.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124123787","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}
引用次数: 1
Decentralized Society: Student’s Soul Using Soulbound Tokens 去中心化的社会:学生的灵魂使用灵魂绑定代币
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080658
U. Tejashwin, S. J. Kennith, Rohit Manivel, K. C. Shruthi, M. Nirmala
{"title":"Decentralized Society: Student’s Soul Using Soulbound Tokens","authors":"U. Tejashwin, S. J. Kennith, Rohit Manivel, K. C. Shruthi, M. Nirmala","doi":"10.1109/ICONAT57137.2023.10080658","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080658","url":null,"abstract":"While the web3 is used to form a decentralized society and focuses particularly on financial transactions in the form of transferable tokens rather than ensuring trust among its entities. With this paper we discuss how non-transferable tokens referred as soulbound tokens (SBTs) can be used to make individuals more credible by having their affiliations encoded in the form of souls to ensure trust within the network. More specifically we discuss how the credentials of students regards to their academic achievements and their credibility can be stored and verified in an decentralized society which shall provide more privacy and security than a centralized system which shall eventually lead to have a higher credibility of data.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124664830","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}
引用次数: 2
Noise Margin analysis of Efficient CNTFET- based Standard Ternary Inverter 基于CNTFET的高效标准三元逆变器噪声裕度分析
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080321
Katyayani Chauhan, Shobhit Mittra, Rasika Sinha, Deepika Bansal
{"title":"Noise Margin analysis of Efficient CNTFET- based Standard Ternary Inverter","authors":"Katyayani Chauhan, Shobhit Mittra, Rasika Sinha, Deepika Bansal","doi":"10.1109/ICONAT57137.2023.10080321","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080321","url":null,"abstract":"Low-power circuit designs are required for battery-operated devices. A transistor needs to be small enough to be integrated onto a single chip. Therefore, CNTFET technology has been widely used to design nanoscale circuits for energy-efficient integration. Multiple-valued logic is utilised to reduce the circuit complexity by minimizing the interconnections. Compared to binary circuits, MVL circuits are more noise sensitive. As a result, it’s essential to consider noise margin into account when designing sustainable and reliable ternary circuits. The paper proposes a standard ternary inverter and compares noise margin, power consumption, delay, and PDP measurements with existing standard ternary inverters. The proposed STI has a 68.6% higher noise margin than the existing designs and 82%, 80%, and 91% improvements in power consumption, PDP, and delay, respectively, over existing circuits.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129758274","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}
引用次数: 0
Analysis and Optimization of Clustering-based Privacy Preservation using Machine Learning 基于机器学习的聚类隐私保护分析与优化
2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080207
C. Sowmyarani, L. G. Namya, G. K. Nidhi, P. Ramakanth Kumar
{"title":"Analysis and Optimization of Clustering-based Privacy Preservation using Machine Learning","authors":"C. Sowmyarani, L. G. Namya, G. K. Nidhi, P. Ramakanth Kumar","doi":"10.1109/ICONAT57137.2023.10080207","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080207","url":null,"abstract":"Over the years, there has been an increase in the influx of data collected. With the advancements in Machine Learning, Deep Learning and Data Visualization techniques, leveraging these to perform predictive analysis to make data-driven decisions has risen to importance. In order to utilize the collected data to its maximum potential, it needs to be published and made available to a wider audience. This may pose a breach of privacy for the subjects of the data. In order to curb such a breach, it is necessary to anonymize the dataset.This work uses the SAC Algorithm [1] to anonymize the dataset acquired. A Predictive Analysis has been carried out by choosing the model most appropriate for the given input data. Further, a Comparative Analysis between the results obtained from Private and Anonymized data is done to study how anonymization may affect overall data analysis. This work also puts forth a technique leveraging Machine Learning that can perform optimal grouping of records to minimize the loss of data quality during anonymization.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128653538","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}
引用次数: 0
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