Pub Date : 2024-07-15DOI: 10.13052/jgeu0975-1416.1221
S. Navaneethan, G. Kalamathipriya, M. S. M. Keyasudeen, K. Parthiban
In the era of information technology, securing the real-time digital image is the greatest challenge especially colour image. In this paper, a colour image encryption scheme is introduced to secure the image based on compression-then-encryption concept. Theproposed method is a hybrid combination of the Chaos techniques for key generation, Huffman Encoding/compression for compression and avoiding colour decomposition, scrambling for more confusion and DNA Encoding for reducing storage size. In order to enhance security, scrambled data are converted to the Deoxyribonucleic acid (DNA) sequence, make ADD operation and apply the complementary rules to attain the cipher image. Experimental results have been proved as robustness, accurate and high security against attacks, malicious attacks, differential attacks and statistical attacks. Furthermore, results show that the time speed is faster minimum storage space than the existing colour image encryption scheme.
在信息技术时代，确保实时数字图像的安全是最大的挑战，尤其是彩色图像。本文介绍了一种基于压缩-加密概念的彩色图像加密方案。该方法是混沌技术（用于生成密钥）、哈夫曼编码/压缩技术（用于压缩和避免颜色分解）、混淆技术（用于增加混淆度）和 DNA 编码技术（用于减少存储空间）的混合组合。为了提高安全性，将加扰数据转换为脱氧核糖核酸（DNA）序列，进行 ADD 运算，并应用互补规则获得密码图像。实验结果表明，该方法具有鲁棒性、准确性和高安全性，可抵御各种攻击、恶意攻击、差分攻击和统计攻击。此外，实验结果表明，与现有的彩色图像加密方案相比，该方案的时间速度更快，存储空间更小。
{"title":"A Fast and robustColor Image Encryption Scheme by Huffman Compression, 5D Chaotic Map and DNA Encoding","authors":"S. Navaneethan, G. Kalamathipriya, M. S. M. Keyasudeen, K. Parthiban","doi":"10.13052/jgeu0975-1416.1221","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1221","url":null,"abstract":"In the era of information technology, securing the real-time digital image is the greatest challenge especially colour image. In this paper, a colour image encryption scheme is introduced to secure the image based on compression-then-encryption concept. Theproposed method is a hybrid combination of the Chaos techniques for key generation, Huffman Encoding/compression for compression and avoiding colour decomposition, scrambling for more confusion and DNA Encoding for reducing storage size. In order to enhance security, scrambled data are converted to the Deoxyribonucleic acid (DNA) sequence, make ADD operation and apply the complementary rules to attain the cipher image. Experimental results have been proved as robustness, accurate and high security against attacks, malicious attacks, differential attacks and statistical attacks. Furthermore, results show that the time speed is faster minimum storage space than the existing colour image encryption scheme.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"41 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141645147","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 : 2024-07-15DOI: 10.13052/jgeu0975-1416.1222
Sanjay Kumar Padaliya, Saurabh Sharma, Jasvinder Pal Singh
To understand the phenomena of expanding symmetries Fractals patterns are an important tool which exhibit similar patterns for different scales. In the present paper, establishing an escape criteria by using S-iteration process to visualize fractals namely Julia and Mandelbrot sets for the function F(w)=aewp+c where c,a∈ C and p≥2. The result obtain is a generalization of the existing algorithm and technique providing fractals for different parameter values. Also, the time taken to obtain fractals for different parameters by using computer software MATLAB is computed in seconds.
{"title":"Fractals as Julia and Mandelbrot Sets via S-iteration","authors":"Sanjay Kumar Padaliya, Saurabh Sharma, Jasvinder Pal Singh","doi":"10.13052/jgeu0975-1416.1222","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1222","url":null,"abstract":"To understand the phenomena of expanding symmetries Fractals patterns are an important tool which exhibit similar patterns for different scales. In the present paper, establishing an escape criteria by using S-iteration process to visualize fractals namely Julia and Mandelbrot sets for the function F(w)=aewp+c where c,a∈ C and p≥2. The result obtain is a generalization of the existing algorithm and technique providing fractals for different parameter values. Also, the time taken to obtain fractals for different parameters by using computer software MATLAB is computed in seconds.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"11 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646123","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 : 2024-04-16DOI: 10.13052/jgeu0975-1416.1215
K. Jagtap, Suresh Sanap
Magnesium alloy has qualities that are similar to those of bone, it is now commonly acknowledged as a biodegradable material. Mg-Ca1.0 is a recently developed biodegradable substance that doesn’t cause any harmful substances to be produced in the body. It is frequently utilized in fixation screws and supporting plates for bone implants. To far, very little research has been published on the machining of biodegradable Magnesium Calcium alloy. This investigation’s goal is to evaluate the cutting forces produced during a face milling procedure. The experimental work used a one-factor-at-a-time strategy to assess how process factors affect performance attributes. The current study uses a CVD diamond-coated insert to examine how the depth of cut, feed rate, and cutting speed affect the radial (Fx), tangential (Fy), and axial (Fz) cutting forces during face milling in a dry machining environment.
{"title":"Some Studies on Cutting Force Generation in Machining of Mg-Ca1.0 Alloy","authors":"K. Jagtap, Suresh Sanap","doi":"10.13052/jgeu0975-1416.1215","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1215","url":null,"abstract":"Magnesium alloy has qualities that are similar to those of bone, it is now commonly acknowledged as a biodegradable material. Mg-Ca1.0 is a recently developed biodegradable substance that doesn’t cause any harmful substances to be produced in the body. It is frequently utilized in fixation screws and supporting plates for bone implants. To far, very little research has been published on the machining of biodegradable Magnesium Calcium alloy. This investigation’s goal is to evaluate the cutting forces produced during a face milling procedure. The experimental work used a one-factor-at-a-time strategy to assess how process factors affect performance attributes. The current study uses a CVD diamond-coated insert to examine how the depth of cut, feed rate, and cutting speed affect the radial (Fx), tangential (Fy), and axial (Fz) cutting forces during face milling in a dry machining environment.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140698689","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 : 2024-04-16DOI: 10.13052/jgeu0975-1416.1214
Laxminarayan Sahoo, Rakhi Das
The goal of this work is to provide an effective method for determining the shortest path in random graphs, which are complicated networks with random connectivity patterns. We have developed an algorithm that can identify the shortest path for both weighted and unweighted random graphs to accomplish our objective. As connectivity in these types of structures is changing, the algorithm adjusts to different edge weights and node configurations to provide fast and precise shortest path searching. The study shows that the suggested method performs more successfully in finding the shortest path throughout random graphs using comprehensive computations. Many networks, including social networks, granular networks, road traffic networks, etc., include nodes that can connect to one another and create random graphs in the present-day computational era. The outcomes demonstrate how flexible it is, which makes it a useful tool for practical uses in domains where random graph structures are common, like transportation networks, communication systems, and social networks. For illustration, we have taken into consideration an actual case study of communication road networks here. We have determined the shortest path of the road networks using our proposed algorithm, and the results have been presented. Better decision-making across a range of areas is made possible by this study, which advances effective algorithms designed for complicated and unpredictable network environments.
{"title":"Shortest Path of a Random Graph and its Application","authors":"Laxminarayan Sahoo, Rakhi Das","doi":"10.13052/jgeu0975-1416.1214","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1214","url":null,"abstract":"The goal of this work is to provide an effective method for determining the shortest path in random graphs, which are complicated networks with random connectivity patterns. We have developed an algorithm that can identify the shortest path for both weighted and unweighted random graphs to accomplish our objective. As connectivity in these types of structures is changing, the algorithm adjusts to different edge weights and node configurations to provide fast and precise shortest path searching. The study shows that the suggested method performs more successfully in finding the shortest path throughout random graphs using comprehensive computations. Many networks, including social networks, granular networks, road traffic networks, etc., include nodes that can connect to one another and create random graphs in the present-day computational era. The outcomes demonstrate how flexible it is, which makes it a useful tool for practical uses in domains where random graph structures are common, like transportation networks, communication systems, and social networks. For illustration, we have taken into consideration an actual case study of communication road networks here. We have determined the shortest path of the road networks using our proposed algorithm, and the results have been presented. Better decision-making across a range of areas is made possible by this study, which advances effective algorithms designed for complicated and unpredictable network environments.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"3 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140697846","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}
Accurate demand forecasting is a competitive advantage for all supply chain components, including retailers. Approaches like naïve, moving average, weighted average, and exponential smoothing are commonly used to forecast demand. However, these simple approaches may lead to higher inventory and lost sales costs when the trend in demand is non-linear. Additionally, price strongly influences demand, and we can’t neglect the impact of price on demand. Similarly, the demand for a stock keeping unit (SKU) depends on the price of the competitor for the same SKU and the price of the competitive SKU. We thus propose a demand prediction model that considers historical demand data and the SKU price to forecast the demand. Our approach uses different machine-learning regressor algorithms and identifies the best machine-learning algorithm for the SKU with the lowest forecasting error. We further extend the forecasting model by training a hybrid model from the best two regression algorithms individually for each SKU. Forecasting error minimisation is the driving criterion for our literature. We evaluated the approach on 1000 SKUs, and the result showed that the Random Forest is the best-performing regressor algorithm with the lowest mean absolute percentage error (MAPE) of 8%. Furthermore, the hybrid model resulted in a lower inventory and lost sales cost with a MAPE of 7.74%. Overall, our proposed hybrid demand forecasting model can help retailers make informed decisions about inventory management, leading to improved operational efficiency and profitability.
{"title":"Improved Demand Forecasting of a Retail Store Using a Hybrid Machine Learning Model","authors":"Vinit Taparia, Piyush Mishra, Nitik Gupta, Devesh Kumar","doi":"10.13052/jgeu0975-1416.1212","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1212","url":null,"abstract":"Accurate demand forecasting is a competitive advantage for all supply chain components, including retailers. Approaches like naïve, moving average, weighted average, and exponential smoothing are commonly used to forecast demand. However, these simple approaches may lead to higher inventory and lost sales costs when the trend in demand is non-linear. Additionally, price strongly influences demand, and we can’t neglect the impact of price on demand. Similarly, the demand for a stock keeping unit (SKU) depends on the price of the competitor for the same SKU and the price of the competitive SKU. We thus propose a demand prediction model that considers historical demand data and the SKU price to forecast the demand. Our approach uses different machine-learning regressor algorithms and identifies the best machine-learning algorithm for the SKU with the lowest forecasting error. We further extend the forecasting model by training a hybrid model from the best two regression algorithms individually for each SKU. Forecasting error minimisation is the driving criterion for our literature. We evaluated the approach on 1000 SKUs, and the result showed that the Random Forest is the best-performing regressor algorithm with the lowest mean absolute percentage error (MAPE) of 8%. Furthermore, the hybrid model resulted in a lower inventory and lost sales cost with a MAPE of 7.74%. Overall, our proposed hybrid demand forecasting model can help retailers make informed decisions about inventory management, leading to improved operational efficiency and profitability.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"62 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139254664","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}
Demand forecasting and price optimization are critical aspects of profitability for retailers in a supply chain. Retailers need to adopt innovative strategies to optimize pricing and increase profitability. This research paper proposes a price optimization approach for retailers using machine learning. The approach involves using linear regression to forecast demand incorporating price as an input, followed by price optimization taking into account inventory and perishability costs. The feasibility of using linear regression for price optimization for Stock Keeping Units (SKUs) is assessed using a feasibility index. The linear regression can predict the demand more accurately (23% Mean Absoulute Percentage Error (MAPE)) compared to exponential smoothing with optimised smoothing constant (47.09% MAPE) for 1000 SKUs. Also, the feasibility index can segregate the SKUs with an accuracy of 99%. The machine learning-based demand forecasting can assist retailers in accurately predicting customer demand and improving pricing decisions, while the feasibility index enables retailers to identify SKUs that require alternative pricing strategies.
{"title":"Data-Driven Retail Excellence: Machine Learning for Demand Forecasting and Price Optimization","authors":"Vinit Taparia, Piyush Mishra, Nitik Gupta, Hitesh Chandiramani","doi":"10.13052/jgeu0975-1416.1213","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1213","url":null,"abstract":"Demand forecasting and price optimization are critical aspects of profitability for retailers in a supply chain. Retailers need to adopt innovative strategies to optimize pricing and increase profitability. This research paper proposes a price optimization approach for retailers using machine learning. The approach involves using linear regression to forecast demand incorporating price as an input, followed by price optimization taking into account inventory and perishability costs. The feasibility of using linear regression for price optimization for Stock Keeping Units (SKUs) is assessed using a feasibility index. The linear regression can predict the demand more accurately (23% Mean Absoulute Percentage Error (MAPE)) compared to exponential smoothing with optimised smoothing constant (47.09% MAPE) for 1000 SKUs. Also, the feasibility index can segregate the SKUs with an accuracy of 99%. The machine learning-based demand forecasting can assist retailers in accurately predicting customer demand and improving pricing decisions, while the feasibility index enables retailers to identify SKUs that require alternative pricing strategies.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139255842","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 : 2023-11-20DOI: 10.13052/jgeu0975-1416.1211
D. Ghode, A. A. Wagire, Pravin A. Dwaramwar, Rajesh H. Khobragade
In the global market, consumers have expectations of good quality food products. To provide flawless food products, traceability has become dominant in a complex food supply chain (SC) network. Stakeholders of the food SC hesitate to share their data with each other, as they have different business strategies. Blockchain Technology (BCT) brings all the parties of food SC on single platform to improve interorganizational trust. The implementation of BCT in food SC offers the traceability of products. This paper proposes a framework for traceability of products in food SC using BCT that offers the consumers to trace the origin of the food products. Blockchain enhances the food traceability, minimize the data tampering, and improves data transparency in food SC. BCT enabled food SC framework has been tested using case study of rice SC and found the enhancement in traceability.
{"title":"Blockchain Technology Enabled Traceability Framework: Food Supply Chain Perspective","authors":"D. Ghode, A. A. Wagire, Pravin A. Dwaramwar, Rajesh H. Khobragade","doi":"10.13052/jgeu0975-1416.1211","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1211","url":null,"abstract":"In the global market, consumers have expectations of good quality food products. To provide flawless food products, traceability has become dominant in a complex food supply chain (SC) network. Stakeholders of the food SC hesitate to share their data with each other, as they have different business strategies. Blockchain Technology (BCT) brings all the parties of food SC on single platform to improve interorganizational trust. The implementation of BCT in food SC offers the traceability of products. This paper proposes a framework for traceability of products in food SC using BCT that offers the consumers to trace the origin of the food products. Blockchain enhances the food traceability, minimize the data tampering, and improves data transparency in food SC. BCT enabled food SC framework has been tested using case study of rice SC and found the enhancement in traceability.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139259398","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 biosensor based on the surface plasmon resonance has been theoretically analyzed. The proposed surface plasmon resonance (SPR) sensor consists of a hybrid structure with Ag/Bismuth telluride (Bi2Te3)/Antimonene (An)/Sensing medium layers. BK7 is used as the main coupling prism. The sensor’s sensitivity performance gets enhanced by depositing Bi2Te3 and antimonene layers over the conventional sensor’s configuration. The Ag, Bi2Te3, and antimonene layer optimized thickness were taken as 45 nm, 0.5 nm, and 0.5 nm, respectively. The proposed sensor has been working on attenuated total reflection. The proposed sensor shows the highest sensitivity of 154 degree/RIU, a signal-to-noise ratio of 0.19 degrees-1 with a figure of merit of 29.26 RIU-1. The proposed SPR sensor can be used for bio analyte and biochemical detection.
{"title":"Silver, Bi2Te3 and Antimonene Based Surface Plasmon Resonance Sensor for Enhancement of Sensitivity","authors":"Arun Uniyal, Brajlata Chauhan, A. Pal, Sanjiv Tomar, Priyanka Dobhal Uniyal","doi":"10.13052/jgeu0975-1416.1124","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1124","url":null,"abstract":"A biosensor based on the surface plasmon resonance has been theoretically analyzed. The proposed surface plasmon resonance (SPR) sensor consists of a hybrid structure with Ag/Bismuth telluride (Bi2Te3)/Antimonene (An)/Sensing medium layers. BK7 is used as the main coupling prism. The sensor’s sensitivity performance gets enhanced by depositing Bi2Te3 and antimonene layers over the conventional sensor’s configuration. The Ag, Bi2Te3, and antimonene layer optimized thickness were taken as 45 nm, 0.5 nm, and 0.5 nm, respectively. The proposed sensor has been working on attenuated total reflection. The proposed sensor shows the highest sensitivity of 154 degree/RIU, a signal-to-noise ratio of 0.19 degrees-1 with a figure of merit of 29.26 RIU-1. The proposed SPR sensor can be used for bio analyte and biochemical detection.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130442954","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 : 2023-08-03DOI: 10.13052/jgeu0975-1416.1126
P. Biswas, K. Chakraborty, Pratik Kumar Raha, P. Mandal
Run Out Tables (ROTs) are critical in the metallurgical sector for producing unique steel grade. The cooling rate controls the fine structure of steel, which is influenced by a number of factors such as the convective heat transfer coefficient, mean film temperature and many others. As a result, achieving a new steel grade necessitates the optimum combination of all of these factors. The cooling rate as a function of steel characteristics is obtained employing laboratory data such as convective heat transfer coefficient, mean film temperature, and mass flow rate of coolant at preset upper and lower nozzle distances from the experimental setup. Three Artificial Neural Network programs have been used to validate and check the performance of the experimental setup for optimize the cooling rate.
{"title":"Modelling of Artificial Neural Network to Validate the Experimental Data of a Laboratory Scale ROT","authors":"P. Biswas, K. Chakraborty, Pratik Kumar Raha, P. Mandal","doi":"10.13052/jgeu0975-1416.1126","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1126","url":null,"abstract":"Run Out Tables (ROTs) are critical in the metallurgical sector for producing unique steel grade. The cooling rate controls the fine structure of steel, which is influenced by a number of factors such as the convective heat transfer coefficient, mean film temperature and many others. As a result, achieving a new steel grade necessitates the optimum combination of all of these factors. The cooling rate as a function of steel characteristics is obtained employing laboratory data such as convective heat transfer coefficient, mean film temperature, and mass flow rate of coolant at preset upper and lower nozzle distances from the experimental setup. Three Artificial Neural Network programs have been used to validate and check the performance of the experimental setup for optimize the cooling rate.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133611534","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 : 2023-08-03DOI: 10.13052/jgeu0975-1416.1123
A. Negi, S. Kapoor
The present study adduces the dynamic properties of the propagating Love waves passing through the irregular upper surface of transversely isotropic poroelastic structure. The dispersion relation for scattered Love waves in a closed form and induced reflected displacement caused by scattering of waves have been derived. The impact of the porosity of the upper layer and half-space on the phase velocity and also on the reflected displacement have also been studied. The porosity of both upper layer and half-space have significant effect on the phase velocity of Love waves. Moreover, the nature of induced reflected displacement with the change in vertical irregularity parameter is also analyzed. The vertical irregularity parameter (associated with the vertical depth of irregularity) has escalating impact on the induced reflected displacement. The comparative analysis of reflected displacement in three distinct scenarios of vertical irregularity has also been done.
{"title":"Propagation of Love Waves Through an Irregular Surface of a Layered Poroelastic Rock Structure","authors":"A. Negi, S. Kapoor","doi":"10.13052/jgeu0975-1416.1123","DOIUrl":"https://doi.org/10.13052/jgeu0975-1416.1123","url":null,"abstract":"The present study adduces the dynamic properties of the propagating Love waves passing through the irregular upper surface of transversely isotropic poroelastic structure. The dispersion relation for scattered Love waves in a closed form and induced reflected displacement caused by scattering of waves have been derived. The impact of the porosity of the upper layer and half-space on the phase velocity and also on the reflected displacement have also been studied. The porosity of both upper layer and half-space have significant effect on the phase velocity of Love waves. Moreover, the nature of induced reflected displacement with the change in vertical irregularity parameter is also analyzed. The vertical irregularity parameter (associated with the vertical depth of irregularity) has escalating impact on the induced reflected displacement. The comparative analysis of reflected displacement in three distinct scenarios of vertical irregularity has also been done.","PeriodicalId":142472,"journal":{"name":"Journal of Graphic Era University","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122812451","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：