The advancement in the field of aerial robotics and control engineering has created many opportunities for the utilization of Unmanned Aerial Vehicles (UAVs). Applications of UAVs from precision agriculture to delivering medicines and products at our doorsteps cannot be ignored. Quadrotors are the widely studied as sub-category of the rotor-type UAVs. Their ability to hover, vertical take-off and landing along with their small size and simple design make them suitable for many real-life applications like medicine delivery in containment zones struck with COVID-19. But under actuation caused due to four rotors to control six inputs creates instability in their flight. In this paper, Quadrotors and various Quadrotor applications are discussed. The various modeling and control techniques are discussed. Controlling techniques like LQR, LQG, PID and robust control is implemented for position, attitude and altitude control. Results for Proportional Integral and Derivative (PID) and Model Reference Adaptive Control (MRAC) of model generated using force-moment mathematical model are analyzed and compared using MATLAB Simulink. These control techniques are implemented for position, attitude and altitude control. In this paper, it has been concluded that MRAC performs better as compared to PID controller for position, attitude and Altitude control of Quadrotor.
{"title":"QUADROTORS IN THE PRESENT ERA: A REVIEW","authors":"Ritika Thusoo, Sheilza Jain, S. Bangia","doi":"10.17762/ITII.V9I1.116","DOIUrl":"https://doi.org/10.17762/ITII.V9I1.116","url":null,"abstract":"The advancement in the field of aerial robotics and control engineering has created many opportunities for the utilization of Unmanned Aerial Vehicles (UAVs). Applications of UAVs from precision agriculture to delivering medicines and products at our doorsteps cannot be ignored. Quadrotors are the widely studied as sub-category of the rotor-type UAVs. Their ability to hover, vertical take-off and landing along with their small size and simple design make them suitable for many real-life applications like medicine delivery in containment zones struck with COVID-19. But under actuation caused due to four rotors to control six inputs creates instability in their flight. In this paper, Quadrotors and various Quadrotor applications are discussed. The various modeling and control techniques are discussed. Controlling techniques like LQR, LQG, PID and robust control is implemented for position, attitude and altitude control. Results for Proportional Integral and Derivative (PID) and Model Reference Adaptive Control (MRAC) of model generated using force-moment mathematical model are analyzed and compared using MATLAB Simulink. These control techniques are implemented for position, attitude and altitude control. In this paper, it has been concluded that MRAC performs better as compared to PID controller for position, attitude and Altitude control of Quadrotor.","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80318430","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}
In this competitive and constantly changing world, meeting the customer requirements within less time by providing less cost is extremely tricky task. This is only possible by optimizing all the different parameters in its life cycle. Here Optimizing the inventory plays a major role.Maintaining the exact amount of inventory, at proper place, in appropriate level is a challenging task for production managers. When we work on Multi level environments this problem becomes even more complex.So, to optimize this kind of problems we applied binary form of Flower Pollination algorithm to solve this complex problem. we solved different inventory lot sizing problems with this FP algorithm and compared the results with genetic algorithm and other algorithms. In all the scenarios our simulation results shown that FP algorithm is better than other algorithms.
{"title":"FLOWER POLLINATION ALGORITHM FOR MULTI LEVEL LOT SIZING OPTIMIZATION","authors":"V. Sahithi, M. S. Rao, C. Rao","doi":"10.17762/ITII.V9I1.110","DOIUrl":"https://doi.org/10.17762/ITII.V9I1.110","url":null,"abstract":"In this competitive and constantly changing world, meeting the customer requirements within less time by providing less cost is extremely tricky task. This is only possible by optimizing all the different parameters in its life cycle. Here Optimizing the inventory plays a major role.Maintaining the exact amount of inventory, at proper place, in appropriate level is a challenging task for production managers. When we work on Multi level environments this problem becomes even more complex.So, to optimize this kind of problems we applied binary form of Flower Pollination algorithm to solve this complex problem. we solved different inventory lot sizing problems with this FP algorithm and compared the results with genetic algorithm and other algorithms. In all the scenarios our simulation results shown that FP algorithm is better than other algorithms. \u0000 ","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81506462","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}
In few previous decades around the globe the reason for extensive number of deaths is cardiovascular disease or Heart related disease and not only in India but all around the world has emerged as a life-threatening disease. So for the correct treatment and in time diagnosis for this disease the need of feasible, accurate and reliable system is encountered. For automation of analysis of the sophisticated and huge data, to the various medical dataset of Machine Learning techniques and methods are applied. In recent times many researchers for the health care industry assistance with the help of various techniques of Machine Learning, this in turn helps the professionals in the procedure of the heart related disease diagnosis. A survey of various models that accepts such techniques and algorithms and their performance analysis is presented in this paper. Within the researchers few very fashionable Model supported supervised learning algorithms are Random forest (RF), Decision Tree (DT), Naïve Bayes, ensemble models, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM).
{"title":"HEART DISEASE PREDICTION USING MACHINE LEARNING TECHNIQUES","authors":"K. Yadav, Anurag Sharma, Abhishek Badholia","doi":"10.17762/ITII.V9I1.120","DOIUrl":"https://doi.org/10.17762/ITII.V9I1.120","url":null,"abstract":"In few previous decades around the globe the reason for extensive number of deaths is cardiovascular disease or Heart related disease and not only in India but all around the world has emerged as a life-threatening disease. So for the correct treatment and in time diagnosis for this disease the need of feasible, accurate and reliable system is encountered. For automation of analysis of the sophisticated and huge data, to the various medical dataset of Machine Learning techniques and methods are applied. In recent times many researchers for the health care industry assistance with the help of various techniques of Machine Learning, this in turn helps the professionals in the procedure of the heart related disease diagnosis. A survey of various models that accepts such techniques and algorithms and their performance analysis is presented in this paper. Within the researchers few very fashionable Model supported supervised learning algorithms are Random forest (RF), Decision Tree (DT), Naïve Bayes, ensemble models, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM). \u0000 ","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76748094","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}
Adverse effects can be seen in the entire body due to the major disorders known as Diabetes. The risk of dangers like diabetic nephropathy, cardiac stroke and other disorders can increase severally because of the undiagnosed diabetes. Around the globe the people are suffering from this disease. For a healthy life early detection of this disease is very curtail. As the causes of the diabetes is increasing rapidly this disease might turn up as a reason for worldwide concern. Increasing the chances for a more accurate predictions and form experiences automatic learning by computational method may be provided by Machine Learning (ML). With the help of R data manipulation tool for trends development and with risk factor patterns detection in Pima Indian diabetes technique of machine learning is been used in the current researches. With the use of R data manipulation tool analysis and development five different predictive models is done for the categorization of patients into diabetic and non- diabetic. supervised machine learning algorithms namely multifactor dimensionality reduction (MDR), k-nearest neighbor (k-NN), artificial neural network (ANN) radial basis function (RBF) kernel support vector machine and linear kernel support vector machine (SVM-linear) are used for this purpose.
{"title":"PREDICTIVE MODELLING AND ANALYTICS FOR DIABETES USING A MACHINE LEARNING APPROACH","authors":"P. Mishra, D. Sharma, Abhishek Badholia","doi":"10.17762/ITII.V9I1.121","DOIUrl":"https://doi.org/10.17762/ITII.V9I1.121","url":null,"abstract":"Adverse effects can be seen in the entire body due to the major disorders known as Diabetes. The risk of dangers like diabetic nephropathy, cardiac stroke and other disorders can increase severally because of the undiagnosed diabetes. Around the globe the people are suffering from this disease. For a healthy life early detection of this disease is very curtail. As the causes of the diabetes is increasing rapidly this disease might turn up as a reason for worldwide concern. Increasing the chances for a more accurate predictions and form experiences automatic learning by computational method may be provided by Machine Learning (ML). With the help of R data manipulation tool for trends development and with risk factor patterns detection in Pima Indian diabetes technique of machine learning is been used in the current researches. With the use of R data manipulation tool analysis and development five different predictive models is done for the categorization of patients into diabetic and non- diabetic. supervised machine learning algorithms namely multifactor dimensionality reduction (MDR), k-nearest neighbor (k-NN), artificial neural network (ANN) radial basis function (RBF) kernel support vector machine and linear kernel support vector machine (SVM-linear) are used for this purpose.","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73802371","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 leadership style and its practice can be considered as the foundation of overall nations development. So, this paper majorly aims to explore the leadership style among academic leaders in his/her education sectors in overall. For this, a semi- structured interview questionnaire was applied to investigate and obtained opinion from the respondents. The results of this study exposed that extraordinary collaboration, responsibility, correspondence, and nurturing and strengthening are the major things that leads to the efficient academic operations. Thus, the paper concludes that academics of Nepal were favor of five leadership methods besides the task-oriented authority in Nepalese context. Finally, the finding of this research would anticipate a more extensive sense of direction towards successful academic’s sectors operations.
{"title":"COVID-19 PANDEMIC AND HUMAN RESOURCE DEVELOPMENT PRACTICE IN NEPALESE COMMERCIAL BANKS","authors":"M. K. Chaudhary, Ajay Prasad Dhakal","doi":"10.17762/ITII.V9I2.294","DOIUrl":"https://doi.org/10.17762/ITII.V9I2.294","url":null,"abstract":"A leadership style and its practice can be considered as the foundation of overall nations development. So, this paper majorly aims to explore the leadership style among academic leaders in his/her education sectors in overall. For this, a semi- structured interview questionnaire was applied to investigate and obtained opinion from the respondents. The results of this study exposed that extraordinary collaboration, responsibility, correspondence, and nurturing and strengthening are the major things that leads to the efficient academic operations. Thus, the paper concludes that academics of Nepal were favor of five leadership methods besides the task-oriented authority in Nepalese context. Finally, the finding of this research would anticipate a more extensive sense of direction towards successful academic’s sectors operations. \u0000 ","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72677395","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 leadership style and its practice can be considered as the foundation of overall nations development. So, this paper majorly aims to explore the leadership style among academic leaders in his/her education sectors in overall. For this, a semi-structured interview questionnaire was applied to investigate and obtained opinion from the respondents. The results of this study exposed that extraordinary collaboration, responsibility, correspondence, and nurturing and strengthening are the major things that leads to the efficient academic operations. Thus, the paper concludes that academics of Nepal were favor of five leadership methods besides the task-oriented authority in Nepalese context. Finally, the finding of this research would anticipate a more extensive sense of direction towards successful academic’s sectors operations.
{"title":"COVID-19 PANDEMIC AND HUMAN RESOURCE DEVELOPMENT PRACTICE IN NEPALESE COMMERCIAL BANKS","authors":"Manoj Kumar Chaudhary, Ajay Prasad Dhakal","doi":"10.17762/itii.v9i1.88","DOIUrl":"https://doi.org/10.17762/itii.v9i1.88","url":null,"abstract":"A leadership style and its practice can be considered as the foundation of overall nations development. So, this paper majorly aims to explore the leadership style among academic leaders in his/her education sectors in overall. For this, a semi-structured interview questionnaire was applied to investigate and obtained opinion from the respondents. The results of this study exposed that extraordinary collaboration, responsibility, correspondence, and nurturing and strengthening are the major things that leads to the efficient academic operations. Thus, the paper concludes that academics of Nepal were favor of five leadership methods besides the task-oriented authority in Nepalese context. Finally, the finding of this research would anticipate a more extensive sense of direction towards successful academic’s sectors operations. ","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"161 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88005788","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}
Chistyakova T. B, Makaruk R. V, Sadykov I. A, Kohlert C
This article considers the problem of protecting pharmaceutical products with polymer packaging from counterfeiting. This issue has grown vital in almost the entire world, as the significant harm can come not only to the producer, but the legitimate producer, but the consumers as well. Due to this, the issue of protecting these products against forgery, and creating and improving existing approaches to anti-forgery protection, becomes a crucial one. The authors suggest methods and technologies for protecting pharmaceutical products’ polymer packaging based on modern ideas from IT and manufacturing such as image recognition, client-server software architecture, mobile apps, digital signatures, luminophores, and PVC film. Testing the authors’ approach showed the effectiveness of the presented methods and technologies. The results should be of interest to companies producing pharmaceuticals.
{"title":"Methods and Technologies for Protecting Pharmaceutical Products in Polymer Packaging from Counterfeiting","authors":"Chistyakova T. B, Makaruk R. V, Sadykov I. A, Kohlert C","doi":"10.17762/itii.v7i3.72","DOIUrl":"https://doi.org/10.17762/itii.v7i3.72","url":null,"abstract":"This article considers the problem of protecting pharmaceutical products with polymer packaging from counterfeiting. This issue has grown vital in almost the entire world, as the significant harm can come not only to the producer, but the legitimate producer, but the consumers as well. Due to this, the issue of protecting these products against forgery, and creating and improving existing approaches to anti-forgery protection, becomes a crucial one. The authors suggest methods and technologies for protecting pharmaceutical products’ polymer packaging based on modern ideas from IT and manufacturing such as image recognition, client-server software architecture, mobile apps, digital signatures, luminophores, and PVC film. Testing the authors’ approach showed the effectiveness of the presented methods and technologies. The results should be of interest to companies producing pharmaceuticals.","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"144 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77948547","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 Fog Computing architecture consists of edge nodes that generate and possibly pre-process (sensor) data, fog nodes that do some processing quickly and do any actuations that may be needed, and cloud nodes that may perform further detailed analysis for long-term and archival purposes. Processing of a batch of input data is distributed into sub-computations which are executed at the different nodes of the architecture. In many applications, the computations are expected to preserve the order in which the batches arrive at the sources. In this paper, we discuss mechanisms for performing the computations at a node in correct order, by storing some batches temporarily and/or dropping some batches. The former option causes a delay in processing and the latter option affects Quality of Service (QoS). We bring out the trade-offs between processing delay and storage capabilities of the nodes, and also between QoS and the storage capabilities.
{"title":"Order Preserving Stream Processing in Fog Computing Architectures","authors":"K. Vidyasankar","doi":"10.17762/ITII.V7I1.63","DOIUrl":"https://doi.org/10.17762/ITII.V7I1.63","url":null,"abstract":"A Fog Computing architecture consists of edge nodes that generate and possibly pre-process (sensor) data, fog nodes that do some processing quickly and do any actuations that may be needed, and cloud nodes that may perform further detailed analysis for long-term and archival purposes. Processing of a batch of input data is distributed into sub-computations which are executed at the different nodes of the architecture. In many applications, the computations are expected to preserve the order in which the batches arrive at the sources. In this paper, we discuss mechanisms for performing the computations at a node in correct order, by storing some batches temporarily and/or dropping some batches. The former option causes a delay in processing and the latter option affects Quality of Service (QoS). We bring out the trade-offs between processing delay and storage capabilities of the nodes, and also between QoS and the storage capabilities.","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"286 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78887565","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}
Today we have large amounts of textual data to be processed and the procedure involved in classifying text is called natural language processing. The basic goal is to identify whether the text is positive or negative. This process is also called as opinion mining. In this paper, we consider three different data sets and perform sentiment analysis to find the test accuracy. We have three different cases- 1. If the text contains more positive data than negative data then the overall result leans towards positive. 2. If the text contains more negative data than positive data then the overall result leans towards negative. 3. In the final case the number or positive and negative data is nearly equal then we have a neutral output. For sentiment analysis we have several steps like term extraction, feature selection, sentiment classification etc. In this paper the key point of focus is on sentiment analysis by comparing the machine learning approach and lexicon-based approach and their respective accuracy loss graphs.
{"title":"Predictive Analysis using Convolution Network on Sentiment Analysis of Text Classification using Machine Learning","authors":"Vanitha kakollu, Et. al.","doi":"10.17762/itii.v9i2.349","DOIUrl":"https://doi.org/10.17762/itii.v9i2.349","url":null,"abstract":"Today we have large amounts of textual data to be processed and the procedure involved in classifying text is called natural language processing. The basic goal is to identify whether the text is positive or negative. This process is also called as opinion mining. In this paper, we consider three different data sets and perform sentiment analysis to find the test accuracy. We have three different cases- 1. If the text contains more positive data than negative data then the overall result leans towards positive. 2. If the text contains more negative data than positive data then the overall result leans towards negative. 3. In the final case the number or positive and negative data is nearly equal then we have a neutral output. For sentiment analysis we have several steps like term extraction, feature selection, sentiment classification etc. In this paper the key point of focus is on sentiment analysis by comparing the machine learning approach and lexicon-based approach and their respective accuracy loss graphs.","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88700105","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 : 2020-09-03DOI: 10.36227/techrxiv.12911321
A. Massaro, Vincenzo Maritati, Nicola Savino, A. Galiano, Ugo Picciotti
The proposed work describes a new approach based on supply chain traceability by blockchain (BC). The basic BC network has been designed and applied for vegetables process monitoring and tracing. The paper proposes some results of an industry research project by describing the whole scenario, the architectures implementing BC, the sequence diagram principle, and the prototype network embedding blocks and transactions. The discussion is also addressed on the possibility to combine different technique such as artificial intelligence, and image processing to improve pre-cut vegetable quality. The paper proposed preliminary results proves that the adopted technologies and the methodologies found in the literature are suitable for the sanitation process certification and for quality traceability. The mentioned approaches are useful to apply the suggested frameworks for other supply chains.
{"title":"Blockchain and Technologies Matching with the Case of Study of Vegetables Production","authors":"A. Massaro, Vincenzo Maritati, Nicola Savino, A. Galiano, Ugo Picciotti","doi":"10.36227/techrxiv.12911321","DOIUrl":"https://doi.org/10.36227/techrxiv.12911321","url":null,"abstract":"The proposed work describes a new approach based on supply chain traceability by blockchain (BC). The basic BC network has been designed and applied for vegetables process monitoring and tracing. The paper proposes some results of an industry research project by describing the whole scenario, the architectures implementing BC, the sequence diagram principle, and the prototype network embedding blocks and transactions. The discussion is also addressed on the possibility to combine different technique such as artificial intelligence, and image processing to improve pre-cut vegetable quality. The paper proposed preliminary results proves that the adopted technologies and the methodologies found in the literature are suitable for the sanitation process certification and for quality traceability. The mentioned approaches are useful to apply the suggested frameworks for other supply chains.","PeriodicalId":40759,"journal":{"name":"Information Technology in Industry","volume":"76 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75002640","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：