Pub Date : 2024-07-31DOI: 10.22214/ijraset.2024.63543
Rita B. Patil
Abstract: Brain tumor detection through MRI imaging is a crucial step in medical diagnostics. This paper presents a comparative performance analysis of two feature extraction methods: the Walsh-Hadamard Transform (WHT) based Gabor Filter method and the Gray-Level Co-occurrence Matrix (GLCM) method. We evaluate these techniques based on accuracy, computational efficiency, and robustness using a benchmark MRI dataset. Our results indicate the strengths and limitations of each method, providing insights for their application in automated brain tumor detection systems.
{"title":"Performance Analysis of Walsh-Hadamard Transform-Based Gabor Filter Feature Extraction Method and GLCM Feature Extraction Method for Brain Tumor Detection","authors":"Rita B. Patil","doi":"10.22214/ijraset.2024.63543","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63543","url":null,"abstract":"Abstract: Brain tumor detection through MRI imaging is a crucial step in medical diagnostics. This paper presents a comparative performance analysis of two feature extraction methods: the Walsh-Hadamard Transform (WHT) based Gabor Filter method and the Gray-Level Co-occurrence Matrix (GLCM) method. We evaluate these techniques based on accuracy, computational efficiency, and robustness using a benchmark MRI dataset. Our results indicate the strengths and limitations of each method, providing insights for their application in automated brain tumor detection systems.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"54 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795111","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63505
Chandrakant Soni
Abstract: The current below study examines the effects of adding a Cubic Three-dimensional Geo-synthetics material known as Geo-cells to the foundation layer of flexible Bitumen pavements. In this study, the test of California bearing ratio (CBR) of 5% is used to compare the steel reinforced and unreinforced pavement made sections built on that subgrade. To comprehend the impact of Geo-cell reinforcement upon the pavement section's load-carryings mechanism under static and repetitive loading circumstances, a number of model tests were conducted. The following characteristics were examined: surface deformation profile the test sections, real rut subgrade level, load-settlement response of the pavement sections, and pressure is transmitted into the subgrade soil beneath into the Geo-cell reinforced foundation layer.
{"title":"Effects of 3D Geocells on Flexible Pavement Foundations","authors":"Chandrakant Soni","doi":"10.22214/ijraset.2024.63505","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63505","url":null,"abstract":"Abstract: The current below study examines the effects of adding a Cubic Three-dimensional Geo-synthetics material known as Geo-cells to the foundation layer of flexible Bitumen pavements. In this study, the test of California bearing ratio (CBR) of 5% is used to compare the steel reinforced and unreinforced pavement made sections built on that subgrade. To comprehend the impact of Geo-cell reinforcement upon the pavement section's load-carryings mechanism under static and repetitive loading circumstances, a number of model tests were conducted. The following characteristics were examined: surface deformation profile the test sections, real rut subgrade level, load-settlement response of the pavement sections, and pressure is transmitted into the subgrade soil beneath into the Geo-cell reinforced foundation layer.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"52 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795124","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63536
Farhaz Alam
Abstract: The study compares balanced cantilever and conventional bridge designs, diving into their engineering details like how much weight they can bear, their cost-effectiveness, and their impact on the environment. It looks at real-life examples to give a thorough picture of how well each type of bridge holds up over time and how eco-friendly they are. It also considers things like how they look, how much maintenance they need, and how well they can handle earthquakes, providing a complete view for engineers, planners, and decision-makers in bridge construction. The paper even talks about how the bridges look and how they fit into their surroundings. Plus, it focuses on how well each design can handle earthquakes and heavy traffic. By putting all these aspects together, the report gives a detailed understanding of what each type of bridge does well and where it could use some improvement. Its goal is to help professionals make better choices when they're designing and building bridges.
{"title":"Comparative Study of Conventional Bridge and Balance Centilever Bridge","authors":"Farhaz Alam","doi":"10.22214/ijraset.2024.63536","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63536","url":null,"abstract":"Abstract: The study compares balanced cantilever and conventional bridge designs, diving into their engineering details like how much weight they can bear, their cost-effectiveness, and their impact on the environment. It looks at real-life examples to give a thorough picture of how well each type of bridge holds up over time and how eco-friendly they are. It also considers things like how they look, how much maintenance they need, and how well they can handle earthquakes, providing a complete view for engineers, planners, and decision-makers in bridge construction. The paper even talks about how the bridges look and how they fit into their surroundings. Plus, it focuses on how well each design can handle earthquakes and heavy traffic. By putting all these aspects together, the report gives a detailed understanding of what each type of bridge does well and where it could use some improvement. Its goal is to help professionals make better choices when they're designing and building bridges.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"52 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795131","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63655
M. R. R. Paul
Abstract: In this digital age, phishing attacks are something that are quite prevalent and are on the rise. This paper explores the various avenues for detecting such kind of attacks which will pave way to mitigating such kinds of attacks in the future. We primarily focused on proving that deep learning methods are much more efficient than traditional machine learning models; for this purpose we are evaluating the performance of a traditional machine learning model namely Naive Bayes and two deep learning models which are Convolutional Neural Networks(CNN) and Recurrent Neural Networks(RNN). The process starts with normalizing the input features and then the categorical data is transformed after which the dataset containing the URLs are loaded and are preprocessed. The performance of the models was evaluated against metrics like Accuracy, Precision, Recall and F1-Score.The end results proved that CNN was able to achieve the optimal performance and was capable of outperforming the other two models. Therefore this paper is of the view that such CNN or Neural Network empowered Models are the only way to mitigate these types of attacks and will also act as a catalyst in developing systems or models that are immune to such kinds of attacks.
{"title":"Deep Learning Solutions for Phishing by URL Detection","authors":"M. R. R. Paul","doi":"10.22214/ijraset.2024.63655","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63655","url":null,"abstract":"Abstract: In this digital age, phishing attacks are something that are quite prevalent and are on the rise. This paper explores the various avenues for detecting such kind of attacks which will pave way to mitigating such kinds of attacks in the future. We primarily focused on proving that deep learning methods are much more efficient than traditional machine learning models; for this purpose we are evaluating the performance of a traditional machine learning model namely Naive Bayes and two deep learning models which are Convolutional Neural Networks(CNN) and Recurrent Neural Networks(RNN). The process starts with normalizing the input features and then the categorical data is transformed after which the dataset containing the URLs are loaded and are preprocessed. The performance of the models was evaluated against metrics like Accuracy, Precision, Recall and F1-Score.The end results proved that CNN was able to achieve the optimal performance and was capable of outperforming the other two models. Therefore this paper is of the view that such CNN or Neural Network empowered Models are the only way to mitigate these types of attacks and will also act as a catalyst in developing systems or models that are immune to such kinds of attacks.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"31 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795196","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63750
A. A. Balkhi
Abstract: Solar Tracker is a device designed to optimize the efficiency of solar energy systems by continuously orienting solar panels to track the movement of the sun. The demand for renewable energy sources, particularly solar power, has been growing rapidly in recent years. To maximize the efficiency of solar panels, solar tracking systems have gained significant attention. The work includes the design, development, and implementation of a single-axis solar tracker. The proposed system utilizes two Light Dependent Resistors (LDRs), a servomotor, and an Arduino microcontroller to precisely align the solar panel with the sun's position throughout the day. Experimental results demonstrate the effectiveness of the designed solar tracker in enhancing the power generation efficiency
{"title":"Auto Solar Tracker for Harnessing Maximum Solar Energy","authors":"A. A. Balkhi","doi":"10.22214/ijraset.2024.63750","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63750","url":null,"abstract":"Abstract: Solar Tracker is a device designed to optimize the efficiency of solar energy systems by continuously orienting solar panels to track the movement of the sun. The demand for renewable energy sources, particularly solar power, has been growing rapidly in recent years. To maximize the efficiency of solar panels, solar tracking systems have gained significant attention. The work includes the design, development, and implementation of a single-axis solar tracker. The proposed system utilizes two Light Dependent Resistors (LDRs), a servomotor, and an Arduino microcontroller to precisely align the solar panel with the sun's position throughout the day. Experimental results demonstrate the effectiveness of the designed solar tracker in enhancing the power generation efficiency","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"30 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795206","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63530
Er. Ankit Dwivedi
Abstract: The primary challenge in achieving 3D printable concrete lies in balancing conflicting characteristics of Pumpability and Buildability. On one hand, the concrete must be sufficiently flowable to be pumped through hoses, while on the other hand, it needs to exhibit enough strength for layer-by-layer construction. Overcoming internal shear resistance due to particle interactions is crucial for pumpability, and the material must also retain its shape after extrusion. This thesis presents a comprehensive study on the optimization of mix proportions for Alkali Activated Concrete (AAC) tailored for 3D concrete printing applications, with a focus on the utilization of Agro-Industrial waste. The primary objective is to optimize the mix proportions of AAC by varying the composition of Agro-Industrial waste, thereby contributing to sustainable construction practices
{"title":"A Review on Development of 3D Printable Concrete by Utilizing Agro-Industrial Waste: Evaluation of Fresh Properties","authors":"Er. Ankit Dwivedi","doi":"10.22214/ijraset.2024.63530","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63530","url":null,"abstract":"Abstract: The primary challenge in achieving 3D printable concrete lies in balancing conflicting characteristics of Pumpability and Buildability. On one hand, the concrete must be sufficiently flowable to be pumped through hoses, while on the other hand, it needs to exhibit enough strength for layer-by-layer construction. Overcoming internal shear resistance due to particle interactions is crucial for pumpability, and the material must also retain its shape after extrusion. This thesis presents a comprehensive study on the optimization of mix proportions for Alkali Activated Concrete (AAC) tailored for 3D concrete printing applications, with a focus on the utilization of Agro-Industrial waste. The primary objective is to optimize the mix proportions of AAC by varying the composition of Agro-Industrial waste, thereby contributing to sustainable construction practices","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"45 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795305","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63614
Smit Srivastava
Abstract: This paper presents a groundbreaking analysis of the One Pixel Attack, an insidious adversarial threat that challenges the robustness of state-of-the-art deep neural networks (DNNs). We delve into the intricate mechanics of this deceptively simple yet potent attack, which can cause misclassification by altering just a single pixel in an image. Our research not only unravels the technical underpinnings of the One Pixel Attack but also introduces Adaptive Pixel Resilience (APR), a novel defence mechanism that significantly enhances DNN robustness against this threat. Through extensive experimentation on the CIFAR10 and ImageNet datasets, we demonstrate the remarkable efficacy of APR. Our method substantially outperforms existing defence strategies, setting a new benchmark in adversarial robustness while maintaining competitive clean accuracy. The paper offers several key contributions
{"title":"Adaptive Pixel Resilience: A Novel Defence Mechanism Against One-Pixel Adversarial Attacks on Deep Neural Networks","authors":"Smit Srivastava","doi":"10.22214/ijraset.2024.63614","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63614","url":null,"abstract":"Abstract: This paper presents a groundbreaking analysis of the One Pixel Attack, an insidious adversarial threat that challenges the robustness of state-of-the-art deep neural networks (DNNs). We delve into the intricate mechanics of this deceptively simple yet potent attack, which can cause misclassification by altering just a single pixel in an image. Our research not only unravels the technical underpinnings of the One Pixel Attack but also introduces Adaptive Pixel Resilience (APR), a novel defence mechanism that significantly enhances DNN robustness against this threat. Through extensive experimentation on the CIFAR10 and ImageNet datasets, we demonstrate the remarkable efficacy of APR. Our method substantially outperforms existing defence strategies, setting a new benchmark in adversarial robustness while maintaining competitive clean accuracy. The paper offers several key contributions","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"29 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795335","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63525
Ravula Muralidhar Reddy, N. N. Kumar
Abstract: Nowadays, judging the current transaction based on user history transactions is an important detection method. However, different users have different transaction behaviors, when all users use the same limit to judge whether the transaction is abnormal, it will result in higher misjudgment for some users. Aiming at the above problems, this paper proposes an individual behavior transaction detection method based on hypersphere model. In this model, considering multiple dimensions of normal historical transaction records, the characteristics of user’s transaction behavior is generated with the trend of transaction. Then, the user optimal risk threshold algorithm is proposed to determine the optimal risk threshold for each user. Finally combining the transaction behavior and the optimal risk threshold, the user behavior benchmark is formed, which is used to construct the multidimensional hypersphere model. On this basis, a mapping method for transforming transaction detection into midpoint in multidimensional space is proposed. The experiment proves that the proposed method is superior to other models, and it is found that the characterization effect of user behavior is related to the frequency of users’ transactions. Applied computing → Secure online transactions; Digital cash; Computing methodologies → Instance-based learning; Rule learning
{"title":"Network Based Feature Extraction Method for Fraud Detection Using Label Propagation","authors":"Ravula Muralidhar Reddy, N. N. Kumar","doi":"10.22214/ijraset.2024.63525","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63525","url":null,"abstract":"Abstract: Nowadays, judging the current transaction based on user history transactions is an important detection method. However, different users have different transaction behaviors, when all users use the same limit to judge whether the transaction is abnormal, it will result in higher misjudgment for some users. Aiming at the above problems, this paper proposes an individual behavior transaction detection method based on hypersphere model. In this model, considering multiple dimensions of normal historical transaction records, the characteristics of user’s transaction behavior is generated with the trend of transaction. Then, the user optimal risk threshold algorithm is proposed to determine the optimal risk threshold for each user. Finally combining the transaction behavior and the optimal risk threshold, the user behavior benchmark is formed, which is used to construct the multidimensional hypersphere model. On this basis, a mapping method for transforming transaction detection into midpoint in multidimensional space is proposed. The experiment proves that the proposed method is superior to other models, and it is found that the characterization effect of user behavior is related to the frequency of users’ transactions. Applied computing → Secure online transactions; Digital cash; Computing methodologies → Instance-based learning; Rule learning","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"28 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795346","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63586
Amarpreet Kaur
Abstract: This paper explores the application of chaos in various physical, electrical, chemical, and biological systems, with a specific focus on enzymes-substrate reactions exhibiting ferroelectric behaviour in brain waves. The study conducted by Enjieu Kadji, Chabi Orou, Yamapi, and Woafo (2007) is investi- gated, which examines the dynamic analysis and global chaos synchronization of a 2-D non-autonomous enzymes-substrates system subjected to a cosinusoidal forcing term. The phase portraits of the chaotic behaviousr in the enzymes-substrates system are depicted. Furthermore, novel adaptive control techniques are developed to achieve global synchronization of identical enzyme-substrates systems with uncertain parameters. The main results for global synchronization are derived using backstepping control, and MATLAB plots are included to illustrate these findings.
{"title":"Harnessing Adaptive Synchronization in Enzyme-Substrate Systems with Brain Wave-Like Ferroelectric Behavior","authors":"Amarpreet Kaur","doi":"10.22214/ijraset.2024.63586","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63586","url":null,"abstract":"Abstract: This paper explores the application of chaos in various physical, electrical, chemical, and biological systems, with a specific focus on enzymes-substrate reactions exhibiting ferroelectric behaviour in brain waves. The study conducted by Enjieu Kadji, Chabi Orou, Yamapi, and Woafo (2007) is investi- gated, which examines the dynamic analysis and global chaos synchronization of a 2-D non-autonomous enzymes-substrates system subjected to a cosinusoidal forcing term. The phase portraits of the chaotic behaviousr in the enzymes-substrates system are depicted. Furthermore, novel adaptive control techniques are developed to achieve global synchronization of identical enzyme-substrates systems with uncertain parameters. The main results for global synchronization are derived using backstepping control, and MATLAB plots are included to illustrate these findings.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"24 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795351","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 : 2024-07-31DOI: 10.22214/ijraset.2024.63499
Naina Nimisha, Subrat Pandey, Siddhant Priyadarshi, Dr. Anusha Preetham
Abstract: This project proposes a system for detecting traffic signals, lane layouts, and speed bumps in road infrastructure using video footage through machine learning. Lane detection is performed through region of interest selection and edge detection. Lane lines are extracted based on specific characteristics. A deep learning model is trained to detect lane boundaries and road curvature. The system provides real-time alerts and recommendations to enhance road safety and driving experiences.
{"title":"Road Sense: Intelligent Road Monitoring System","authors":"Naina Nimisha, Subrat Pandey, Siddhant Priyadarshi, Dr. Anusha Preetham","doi":"10.22214/ijraset.2024.63499","DOIUrl":"https://doi.org/10.22214/ijraset.2024.63499","url":null,"abstract":"Abstract: This project proposes a system for detecting traffic signals, lane layouts, and speed bumps in road infrastructure using video footage through machine learning. Lane detection is performed through region of interest selection and edge detection. Lane lines are extracted based on specific characteristics. A deep learning model is trained to detect lane boundaries and road curvature. The system provides real-time alerts and recommendations to enhance road safety and driving experiences.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"44 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795389","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：