Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157473
P. Kalyanasundaram, S. Ramesh, Ravikumar Gurusamy, V. Rajmohan, S. Hamsanandhini
This research involves to develop an innovative irrigation system to evaluate sand quality by comparing different sands and securing agriculture land using Internet of Things and Wireless Sensor Network. In this innovative irrigation method, three soils, sandy soil with normal moisture content of 60 %, earth soil with normal moisture content 76 %, silt soil with normal moisture content 56 % are taken based on the previous study. In each group 10 number of are taken for the analysis. The G Power statistical tool is employed for the sample size estimation with a confidence interval of 80% probability. The error rate of is 0.05. From the observations from the soil moisture sensors, the mean value of moisture content in clay soil is 63 %, in sandy soil is 83 % and Silt soil is 55 %. On comparing the three soils, the silt soil maintains the high-water content, because it contains low soil moisture value. The water content is inversely proportional to the soil moisture. The significance value of soil moisture and humidity are 0.021 and 0.0005 respectively. From this research, it is concluded that Silt soil is superior to sandy and clay soil in terms of holding moisture content. The customary issues in drip water irrigation systems are overcome by inventive water system framework. Security to the farmland is provided with this proposed system using an ultrasonic sensor, to get rid of attacks from animals.
{"title":"Internet of Things based Innovative Irrigation System for the evaluation of Sand Quality with Security measures for Agriculture Land using Wireless Sensor Network","authors":"P. Kalyanasundaram, S. Ramesh, Ravikumar Gurusamy, V. Rajmohan, S. Hamsanandhini","doi":"10.1109/ICEEICT56924.2023.10157473","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157473","url":null,"abstract":"This research involves to develop an innovative irrigation system to evaluate sand quality by comparing different sands and securing agriculture land using Internet of Things and Wireless Sensor Network. In this innovative irrigation method, three soils, sandy soil with normal moisture content of 60 %, earth soil with normal moisture content 76 %, silt soil with normal moisture content 56 % are taken based on the previous study. In each group 10 number of are taken for the analysis. The G Power statistical tool is employed for the sample size estimation with a confidence interval of 80% probability. The error rate of is 0.05. From the observations from the soil moisture sensors, the mean value of moisture content in clay soil is 63 %, in sandy soil is 83 % and Silt soil is 55 %. On comparing the three soils, the silt soil maintains the high-water content, because it contains low soil moisture value. The water content is inversely proportional to the soil moisture. The significance value of soil moisture and humidity are 0.021 and 0.0005 respectively. From this research, it is concluded that Silt soil is superior to sandy and clay soil in terms of holding moisture content. The customary issues in drip water irrigation systems are overcome by inventive water system framework. Security to the farmland is provided with this proposed system using an ultrasonic sensor, to get rid of attacks from animals.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114987722","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 : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157592
N. Adhikari
In this study, partial discharge measurements are carried out on the HV cable joint subjected to the lightning impulse voltage. XLPE insulated cables are prominently used for medium and high voltage power transmission, and the cable joints and terminations are the significant regions for the defects. Experimental test have been carried out to study the characteristics of the power cable joint and end terminations. A 6.35/11kV XLPE insulated power cable with the heat shrinkable joint is subjected to the lightning impulse voltage. Partial discharge measurements on the cable before and after the imposed impulse voltage are presented. The measurement result obtained validates the effectiveness of PD measurements to assess the effects of voltage transients on the cable on the HV cable joint.
{"title":"Studies on the Characteristics of Partial Discharges in High-Voltage XLPE Cable Joints exposed to Lightning Impulse Voltages","authors":"N. Adhikari","doi":"10.1109/ICEEICT56924.2023.10157592","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157592","url":null,"abstract":"In this study, partial discharge measurements are carried out on the HV cable joint subjected to the lightning impulse voltage. XLPE insulated cables are prominently used for medium and high voltage power transmission, and the cable joints and terminations are the significant regions for the defects. Experimental test have been carried out to study the characteristics of the power cable joint and end terminations. A 6.35/11kV XLPE insulated power cable with the heat shrinkable joint is subjected to the lightning impulse voltage. Partial discharge measurements on the cable before and after the imposed impulse voltage are presented. The measurement result obtained validates the effectiveness of PD measurements to assess the effects of voltage transients on the cable on the HV cable joint.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115126050","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 : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157300
Akshay Dhiman, O. P. Rahi, Nishant Sharma
Power transformers are crucial component of electrical system for reliable and effective electric power transfer. Dissolved gas analysis (DGA) of transformer oil is currently the mostly used method for online diagnostics of power transformers. The International Electrotechnical Commission (IEC) three ratio method, that was established via extensive research on gases created from specific faults, is just one of the interpretive techniques used to diagnose the incipient faults based on DGA results. This technique fails to detect the fault type if the measured ratio of gases are slightly diverged from the crisp boundaries of ranges assigned by this technique. The present paper introduces a fuzzy logic approach to overcome the limitation of the conventional IEC technique. This approach demonstrates a significant improvement in diagnostic accuracy of DGA results. The approach provides more accurate evaluation of transformer problems, thereby assisting power utilities in deciding whether to repair, replace, or refurbish a transformer.
{"title":"Fuzzy Logic-Based Incipient Fault Detection in Power Transformers Using IEC Method","authors":"Akshay Dhiman, O. P. Rahi, Nishant Sharma","doi":"10.1109/ICEEICT56924.2023.10157300","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157300","url":null,"abstract":"Power transformers are crucial component of electrical system for reliable and effective electric power transfer. Dissolved gas analysis (DGA) of transformer oil is currently the mostly used method for online diagnostics of power transformers. The International Electrotechnical Commission (IEC) three ratio method, that was established via extensive research on gases created from specific faults, is just one of the interpretive techniques used to diagnose the incipient faults based on DGA results. This technique fails to detect the fault type if the measured ratio of gases are slightly diverged from the crisp boundaries of ranges assigned by this technique. The present paper introduces a fuzzy logic approach to overcome the limitation of the conventional IEC technique. This approach demonstrates a significant improvement in diagnostic accuracy of DGA results. The approach provides more accurate evaluation of transformer problems, thereby assisting power utilities in deciding whether to repair, replace, or refurbish a transformer.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"712 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115127001","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 : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157830
D. Sathish, Sathish Kabekody, R. J
Classification and detection of the brain tumour at early stages have always been a concern to reduce the mortality rate. Though the brain tumour detection is possible in Magnetic Resonance Imaging (MRI), the detailed detection of the tumour type has been a concern. This article proposed a comparatively efficient method to detect the dangerous malignant tumour and hence begin the treatment at an early stage. At first, MRI images are filtered by cascading mean, median and Weiner filter. Due to the high density and texture, skull tends to appear as a detected region, which is often mistaken as part of a tumour. The stripping of the skull is done to isolate the Region of Interest (ROI) of the brain from the background. Once an abnormality in the image is confirmed for a tumour, its' classification into Low-Grade Glioma (LGG) and High-Grade Glioma (HGG) are done using Open by Reconstruction followed by thresholding segmentation method & Convolution Neural Networks (CNNs). An accuracy of 92.3% is obtained by first CNN in classifying abnormal brain MRI with normal brain MRI. An accuracy of 98.4% is obtained by second CNN in distinguishing HGG with LGG.
脑肿瘤的早期分类和检测一直是降低死亡率的一个重要问题。虽然磁共振成像(MRI)可以检测脑肿瘤，但肿瘤类型的详细检测一直是一个问题。本文提出了一种相对有效的方法来发现危险的恶性肿瘤，从而在早期开始治疗。首先，采用均值、中值和韦纳滤波器对MRI图像进行级联滤波。由于高密度和质地，头骨往往表现为一个被检测到的区域，经常被误认为是肿瘤的一部分。剥离颅骨是为了从背景中分离大脑的感兴趣区域(ROI)。一旦确认图像中存在肿瘤异常，则使用Open by Reconstruction然后使用阈值分割方法和卷积神经网络(cnn)将其分为Low-Grade Glioma (LGG)和High-Grade Glioma (HGG)。第一次CNN对异常脑MRI与正常脑MRI进行分类，准确率达到92.3%。第二种CNN对HGG和LGG的区分准确率达到98.4%。
{"title":"Early Detection of Brain Tumour in MRI Images using Open by Reconstruction and Convolution Neural Networks","authors":"D. Sathish, Sathish Kabekody, R. J","doi":"10.1109/ICEEICT56924.2023.10157830","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157830","url":null,"abstract":"Classification and detection of the brain tumour at early stages have always been a concern to reduce the mortality rate. Though the brain tumour detection is possible in Magnetic Resonance Imaging (MRI), the detailed detection of the tumour type has been a concern. This article proposed a comparatively efficient method to detect the dangerous malignant tumour and hence begin the treatment at an early stage. At first, MRI images are filtered by cascading mean, median and Weiner filter. Due to the high density and texture, skull tends to appear as a detected region, which is often mistaken as part of a tumour. The stripping of the skull is done to isolate the Region of Interest (ROI) of the brain from the background. Once an abnormality in the image is confirmed for a tumour, its' classification into Low-Grade Glioma (LGG) and High-Grade Glioma (HGG) are done using Open by Reconstruction followed by thresholding segmentation method & Convolution Neural Networks (CNNs). An accuracy of 92.3% is obtained by first CNN in classifying abnormal brain MRI with normal brain MRI. An accuracy of 98.4% is obtained by second CNN in distinguishing HGG with LGG.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125053951","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 : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157615
G. Jain, R. Sawhney, Ravinder Kumar
In this article, a comparative analysis of vertically stacked nanosheet field effect transistor (VSN-FET) with vertically stacked nanosheet tunnel field effect transistor (VSN-TFET) is done. VSN-FET is doped with N-I-N, while VSN-TFET uses a P-I-N configuration. VSN-TFET has a reduced leakage current of 1.17E-16A compared to VSN-FET's OFF current (4.53E-11A). VSN-TFET has an incredible switching ratio of 9.38E+11, while VSN-FET possesses a meagre switching ratio of 8.05E+06. The VSN-TFET structure ameliorates subthreshold swing (SSw) by 69.43 percent compared to the VSN-FET. Additionally, the temperature evaluation of the VSN-TFET is performed. The device's performance is examined at temperatures ranging from 200 to 400 kelvin. The results demonstrate that the temperature dependency of ON-current is minimal, but it rises in the OFF-state domain. The effect of temperature on subthreshold swing, DIBL, and total gate capacitance has been analysed. All the simulations have been carried out using the Visual TCAD tool.
{"title":"Impact of temperature on the DC performance of Nanosheet TFET","authors":"G. Jain, R. Sawhney, Ravinder Kumar","doi":"10.1109/ICEEICT56924.2023.10157615","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157615","url":null,"abstract":"In this article, a comparative analysis of vertically stacked nanosheet field effect transistor (VSN-FET) with vertically stacked nanosheet tunnel field effect transistor (VSN-TFET) is done. VSN-FET is doped with N-I-N, while VSN-TFET uses a P-I-N configuration. VSN-TFET has a reduced leakage current of 1.17E-16A compared to VSN-FET's OFF current (4.53E-11A). VSN-TFET has an incredible switching ratio of 9.38E+11, while VSN-FET possesses a meagre switching ratio of 8.05E+06. The VSN-TFET structure ameliorates subthreshold swing (SSw) by 69.43 percent compared to the VSN-FET. Additionally, the temperature evaluation of the VSN-TFET is performed. The device's performance is examined at temperatures ranging from 200 to 400 kelvin. The results demonstrate that the temperature dependency of ON-current is minimal, but it rises in the OFF-state domain. The effect of temperature on subthreshold swing, DIBL, and total gate capacitance has been analysed. All the simulations have been carried out using the Visual TCAD tool.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125070200","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 : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157692
R. Grace, M. I. Priyadharshini
A cluster of wind turbines in the same site that generates power. Using turbines perform effectively with severe winds and optimal wind speed. For a wind farm, the wind direction and speed can be projected that wind turbines would operate efficiently. So, the wind generators' output will be having increased effectiveness. Big data and machine learning are defined as a large collection of datasets that are advanced to process. Wind speed forecasting is one of the most critical responsibilities in a wind farm. Machine learning approaches are frequently used to forecast time series non-linear wind behavior. This research provides a wind dataset prediction model that relies on the Extra Tree classifier in this context. The proposed model has the benefit of being simple, quick, and well-suited to the short term. The accuracy of the project is then compared with bagging classifier and Ada boost Classifier algorithms in their regression mode, and then the project aims to illustrate how wind direction may affect power generation and why it is vital to anticipate it. A real-time series data collection contains past values of characteristics like speed of wind, temperature, and atmospheric pressure, they are used to forecast the speed of the wind. The suggested model Extra Tree classifier will be evaluated using Mean Absolute, Mean Square Error values, and its performance will be compared to that of bagging classifier and Ada boost Classifier algorithm models.
{"title":"Wind Speed Prediction using Extra Tree Classifier","authors":"R. Grace, M. I. Priyadharshini","doi":"10.1109/ICEEICT56924.2023.10157692","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157692","url":null,"abstract":"A cluster of wind turbines in the same site that generates power. Using turbines perform effectively with severe winds and optimal wind speed. For a wind farm, the wind direction and speed can be projected that wind turbines would operate efficiently. So, the wind generators' output will be having increased effectiveness. Big data and machine learning are defined as a large collection of datasets that are advanced to process. Wind speed forecasting is one of the most critical responsibilities in a wind farm. Machine learning approaches are frequently used to forecast time series non-linear wind behavior. This research provides a wind dataset prediction model that relies on the Extra Tree classifier in this context. The proposed model has the benefit of being simple, quick, and well-suited to the short term. The accuracy of the project is then compared with bagging classifier and Ada boost Classifier algorithms in their regression mode, and then the project aims to illustrate how wind direction may affect power generation and why it is vital to anticipate it. A real-time series data collection contains past values of characteristics like speed of wind, temperature, and atmospheric pressure, they are used to forecast the speed of the wind. The suggested model Extra Tree classifier will be evaluated using Mean Absolute, Mean Square Error values, and its performance will be compared to that of bagging classifier and Ada boost Classifier algorithm models.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122355708","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}
A compressed small width square in shape aerial with fractal characteristics that exhibits minimal delay, cost and better speed with wide band characteristics is modeled. Minkowski fractal is taken as initiator and iterations are done. Patch size taken is 30*40 mm2, Simulation analysis has been done with software named CST Microwave studio. Substrate material used for fabrication is easily available FR-4 (εr =4.4) with 1.59 mm as thickness of sheet. Resonant frequency obtained is 2.3 GHz and from 7.9 GHz to 14.88 GHz. Aerial finds application in WiFi, X and initial K band.
{"title":"Design of Minkowski Fractal Antenna for Multiband Utilizations","authors":"Vinita Mathur, P. Tyagi, Rakesh Kardam, Ritu Vyas, Mangilal, Ashish Kulshrestha","doi":"10.1109/ICEEICT56924.2023.10157281","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157281","url":null,"abstract":"A compressed small width square in shape aerial with fractal characteristics that exhibits minimal delay, cost and better speed with wide band characteristics is modeled. Minkowski fractal is taken as initiator and iterations are done. Patch size taken is 30*40 mm2, Simulation analysis has been done with software named CST Microwave studio. Substrate material used for fabrication is easily available FR-4 (εr =4.4) with 1.59 mm as thickness of sheet. Resonant frequency obtained is 2.3 GHz and from 7.9 GHz to 14.88 GHz. Aerial finds application in WiFi, X and initial K band.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122650842","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 : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157594
Savita Rawat, Nikhil Shrivastav, Jaya Madan
The MASnPbI3-based perovskite solar cells were thoroughly analysed in the SCAPS study, which revealed their high power conversion efficiency and low production cost, making them a promising technology for photovoltaic applications. The study reports a remarkable achievement in the field, with a PCE of 26.17%, Jsc of 35.93 mA/cm2, Voc of 0.9 V, and FF of 87.13%. The study also found that the performance of the cells is significantly influenced by the thickness and defect of the MASnPbI3 layer. The highest PCE was achieved when the MASnPbI3 layer was 3 µm thick with a low defect density of 1×1018/cm3. This result emphasizes the importance of optimizing the thickness of the MASnPbI3 material to enhance the performance of perovskite-based solar cells. Optimizing the thickness of the MASnPbI3 layer is critical to improving the PCE of MASnPbI3 based solar cells, which is vital for their widespread commercialization and deployment. Also the bulk defect density (BDD) of the MASnPbI3 layer should be as low as possible for the best PV characteristics of the cell. The results of the SCAPS study serve as a basis for future research in advancing the development of high-performance perovskite solar cells and their integration into photovoltaic systems.
{"title":"Analysis and Optimization of MASnPbI3-based Single Junction Solar Cells for High Power Conversion Efficiency","authors":"Savita Rawat, Nikhil Shrivastav, Jaya Madan","doi":"10.1109/ICEEICT56924.2023.10157594","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157594","url":null,"abstract":"The MASnPbI3-based perovskite solar cells were thoroughly analysed in the SCAPS study, which revealed their high power conversion efficiency and low production cost, making them a promising technology for photovoltaic applications. The study reports a remarkable achievement in the field, with a PCE of 26.17%, Jsc of 35.93 mA/cm2, Voc of 0.9 V, and FF of 87.13%. The study also found that the performance of the cells is significantly influenced by the thickness and defect of the MASnPbI3 layer. The highest PCE was achieved when the MASnPbI3 layer was 3 µm thick with a low defect density of 1×1018/cm3. This result emphasizes the importance of optimizing the thickness of the MASnPbI3 material to enhance the performance of perovskite-based solar cells. Optimizing the thickness of the MASnPbI3 layer is critical to improving the PCE of MASnPbI3 based solar cells, which is vital for their widespread commercialization and deployment. Also the bulk defect density (BDD) of the MASnPbI3 layer should be as low as possible for the best PV characteristics of the cell. The results of the SCAPS study serve as a basis for future research in advancing the development of high-performance perovskite solar cells and their integration into photovoltaic systems.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"658 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122958631","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}
3D models have taken centre stage in a variety of applications across numerous industries as a outcome of the enormous advancements in multimedia communications. As a result, these images are used in steganography as safe and trustworthy cover media for hiding secret data. The confidential material in this document is encrypted using the AES technique for increased protection. Next, using depth first search, a geometric domain oriented steganography technique is used, in which triangular meshes' each vertex of several 3D images are subtly altered to hold the hidden data. A geometrical attack on a 3D model, such as translation, uniform scaling, or rotation, is found to be resistant to our proposed method. Also, it is capable of blindly disclosing the confidential information. Our proposed algorithm's 9 bpv embedding performance is evaluated and contrasted with compare to existing literature. The numerical results oblige as an excellent benchmark for higher payload data security solution.
{"title":"Hiding Secret Data Using AES Encryption and DFS Graph Traversal in 3D Images","authors":"Sakhi Bandyopadhyay, Sunita Sarkar, Somnath Mukhopadhyay","doi":"10.1109/ICEEICT56924.2023.10156957","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10156957","url":null,"abstract":"3D models have taken centre stage in a variety of applications across numerous industries as a outcome of the enormous advancements in multimedia communications. As a result, these images are used in steganography as safe and trustworthy cover media for hiding secret data. The confidential material in this document is encrypted using the AES technique for increased protection. Next, using depth first search, a geometric domain oriented steganography technique is used, in which triangular meshes' each vertex of several 3D images are subtly altered to hold the hidden data. A geometrical attack on a 3D model, such as translation, uniform scaling, or rotation, is found to be resistant to our proposed method. Also, it is capable of blindly disclosing the confidential information. Our proposed algorithm's 9 bpv embedding performance is evaluated and contrasted with compare to existing literature. The numerical results oblige as an excellent benchmark for higher payload data security solution.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114404701","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 : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157857
R. Baghel, Rajendra Kumar Sahu
Gas sensors are frequently used to identify hazardous and toxic gases and are essential to maintaining both the environments and human's quality of life. First-principle calculations are used to find the adsorption mechanism of monoxide gases on S2 system. In order to prospect its capability to use like a gas sensor, we investigated the sensing of nitrogen based small gas molecules like NO, NO2 and NH3 on pristine SnSe2 monolayer in our work. According to the findings, these monolayer can be applied as a productive nominee in the field of gas sensing. Here, the structural models of all cases in adsorption are first modelled and developed in order to obtain the extent of sensing features of SnSe2 monolayer in the presence of gas molecules, and the structural and electronic characteristics are analyzed using density functional theory (DFT) method.
{"title":"Gas Sensor device based on SnSe2 Monolayer: Ab-initio Modelling","authors":"R. Baghel, Rajendra Kumar Sahu","doi":"10.1109/ICEEICT56924.2023.10157857","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157857","url":null,"abstract":"Gas sensors are frequently used to identify hazardous and toxic gases and are essential to maintaining both the environments and human's quality of life. First-principle calculations are used to find the adsorption mechanism of monoxide gases on S2 system. In order to prospect its capability to use like a gas sensor, we investigated the sensing of nitrogen based small gas molecules like NO, NO2 and NH3 on pristine SnSe2 monolayer in our work. According to the findings, these monolayer can be applied as a productive nominee in the field of gas sensing. Here, the structural models of all cases in adsorption are first modelled and developed in order to obtain the extent of sensing features of SnSe2 monolayer in the presence of gas molecules, and the structural and electronic characteristics are analyzed using density functional theory (DFT) method.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128467585","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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