Pub Date : 2023-12-07DOI: 10.30534/ijeter/2023/0911122023
The detection and control of rats in commercial buildings and industries are crucial issues due to the damage they can cause to Godowns and equipment. Traditional methods of rat detection and control can be time-consuming and expensive and may not always be effective. This has brought the exploration of machine learning-based approaches, which can provide more accurate and efficient detection of rats. One such approach is the use of thermal sensors in conjunction with machine learning algorithms to detect rats in commercial buildings, industries, etc. Thermal sensors can detect the body heat of rats, and machine learning algorithms can be trained to analyze thermal data and accurately identify the presence of rats. This approach has several advantages over traditional methods, including higher accuracy, long-range and faster detection. The machine learning algorithms used in this approach can be trained using large datasets of thermal images of rats, which can be obtained using thermal cameras
{"title":"CNN Based Rat Detection using Thermal Sensor","authors":"","doi":"10.30534/ijeter/2023/0911122023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0911122023","url":null,"abstract":"The detection and control of rats in commercial buildings and industries are crucial issues due to the damage they can cause to Godowns and equipment. Traditional methods of rat detection and control can be time-consuming and expensive and may not always be effective. This has brought the exploration of machine learning-based approaches, which can provide more accurate and efficient detection of rats. One such approach is the use of thermal sensors in conjunction with machine learning algorithms to detect rats in commercial buildings, industries, etc. Thermal sensors can detect the body heat of rats, and machine learning algorithms can be trained to analyze thermal data and accurately identify the presence of rats. This approach has several advantages over traditional methods, including higher accuracy, long-range and faster detection. The machine learning algorithms used in this approach can be trained using large datasets of thermal images of rats, which can be obtained using thermal cameras","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":"27 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138592620","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 : 2023-12-07DOI: 10.30534/ijeter/2023/0711122023
In The project aims to develop a human face classification system using TensorFlow and deploying it onto ASIC for Biometrics applications. The Convolutional Neural Networks (CNN) Algorithm is used to classify human faces into predefined categories such as age, gender, and emotion. The CNN model will be trained using a large dataset of labelled images, and the training process will be optimized for ASIC deployment. The trained model will be deployed on an ASIC chip, which is optimized for power and speed. The large dataset will be tested for accuracy and efficiency, and its performance will be evaluated in various engineering applications, such as Security, Biometrics, and Entertainment. The project will demonstrate the feasibility of using TensorFlow Lite and ASIC for developing efficient and accurate human face classification systems for Biometrics applications.
{"title":"Human Face Classification using TensorFlow and Deployment onto ASIC","authors":"","doi":"10.30534/ijeter/2023/0711122023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0711122023","url":null,"abstract":"In The project aims to develop a human face classification system using TensorFlow and deploying it onto ASIC for Biometrics applications. The Convolutional Neural Networks (CNN) Algorithm is used to classify human faces into predefined categories such as age, gender, and emotion. The CNN model will be trained using a large dataset of labelled images, and the training process will be optimized for ASIC deployment. The trained model will be deployed on an ASIC chip, which is optimized for power and speed. The large dataset will be tested for accuracy and efficiency, and its performance will be evaluated in various engineering applications, such as Security, Biometrics, and Entertainment. The project will demonstrate the feasibility of using TensorFlow Lite and ASIC for developing efficient and accurate human face classification systems for Biometrics applications.","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":"34 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138591033","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 : 2023-12-07DOI: 10.30534/ijeter/2023/0511122023
High productivity over time for a company is important, but not enough. Ensuring that the company has a productivity index that gets better over time is more important. A better productivity index means that the company's productivity performance is getting better. That way the productivity index can be used as an indicator of success in making improvements to the Company's production process. This research will measure and analyze the productivity index of PT X in order to evaluate and improve the company's performance. By using the OMAX method, the results show that the productivity index in April 2023 was 106.7%. Furthermore, the month of May was -16.7%, June was 70.0%, July was 36.7%, August was 13.3% and September was 6.7%. And it was not in good condition. From the results of the analysis it turns out that the cause is the low production capacity of many defective products. Various improvements must be made by the Company, especially related to improving employee skills, improving the work environment, planned machine maintenance, and procuring standardized raw materials.
{"title":"Productivity Measurement to Monitor the Performance of Shrimp Cracker Companies","authors":"","doi":"10.30534/ijeter/2023/0511122023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0511122023","url":null,"abstract":"High productivity over time for a company is important, but not enough. Ensuring that the company has a productivity index that gets better over time is more important. A better productivity index means that the company's productivity performance is getting better. That way the productivity index can be used as an indicator of success in making improvements to the Company's production process. This research will measure and analyze the productivity index of PT X in order to evaluate and improve the company's performance. By using the OMAX method, the results show that the productivity index in April 2023 was 106.7%. Furthermore, the month of May was -16.7%, June was 70.0%, July was 36.7%, August was 13.3% and September was 6.7%. And it was not in good condition. From the results of the analysis it turns out that the cause is the low production capacity of many defective products. Various improvements must be made by the Company, especially related to improving employee skills, improving the work environment, planned machine maintenance, and procuring standardized raw materials.","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":"53 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138593122","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 : 2023-12-07DOI: 10.30534/ijeter/2023/0611122023
A construction project is a series of interrelated activities to achieve certain goals (building/construction) within certain time, cost and quality limits. Rehabilitation and Reconstruction is one of the post-disaster disaster management projects. The success of a project can not only be seen from the completion time and final results of the project, but one important factor is the project progress report which is always monitored. E-monitoring is the supervision and monitoring of work processes through the use of information technology. In this research, the system development method used is the waterfall method and the system testing method uses black box testing. The monitoring and evaluation system for construction projects in rehabilitation and reconstruction at the Central Sulawesi Regional Settlement Infrastructure Center can display information about the progress of construction projects for rehabilitation and reconstruction at the Central Sulawesi Regional Settlement Infrastructure Center. This system can also speed up data searches, data processing and can process data
{"title":"Design of E-Monitoring Application for Construction Project Program Evaluation Website Based","authors":"","doi":"10.30534/ijeter/2023/0611122023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0611122023","url":null,"abstract":"A construction project is a series of interrelated activities to achieve certain goals (building/construction) within certain time, cost and quality limits. Rehabilitation and Reconstruction is one of the post-disaster disaster management projects. The success of a project can not only be seen from the completion time and final results of the project, but one important factor is the project progress report which is always monitored. E-monitoring is the supervision and monitoring of work processes through the use of information technology. In this research, the system development method used is the waterfall method and the system testing method uses black box testing. The monitoring and evaluation system for construction projects in rehabilitation and reconstruction at the Central Sulawesi Regional Settlement Infrastructure Center can display information about the progress of construction projects for rehabilitation and reconstruction at the Central Sulawesi Regional Settlement Infrastructure Center. This system can also speed up data searches, data processing and can process data","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":"53 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138593230","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 : 2023-12-07DOI: 10.30534/ijeter/2023/0311122023
The traditional driving system has several disadvantages such as human error, driver fatigue and the inability to handle complex situations. These limitations make traditional driving unsafe and unreliable, leading to accidents and traffic congestion. The necessity for Autonomous Driving of a Rover based on Traffic Signals & Signs is to address these issues by automating the driving process and making it safer and more efficient. A dataset with traffic signs will be used to train a deep-learning model for classifying signs. A transfer learning technique will be used to deploy the trained model on the rover, considering hardware limitations. A camera on the rover captures images and sends them to the model for classification, enabling autonomous navigation based on traffic signs. The required software for the project includes Anaconda, a popular data science platform, and MaixPy, which is a version of MicroPython specifically designed for the Kendryte K210 chipset. The hardware required for the system includes the Zumo Shield for Arduino, which serves as the interface between the rover and the computer vision software, the Maixduino board, which is used to process the image data, and batteries to power the system. The system is designed to detect traffic signs and signals in real-time and respond accordingly, enabling the rover to navigate through traffic safely and efficiently.
{"title":"Autonomous Driving of a Rover Based on Traffic Signals and Signs","authors":"","doi":"10.30534/ijeter/2023/0311122023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0311122023","url":null,"abstract":"The traditional driving system has several disadvantages such as human error, driver fatigue and the inability to handle complex situations. These limitations make traditional driving unsafe and unreliable, leading to accidents and traffic congestion. The necessity for Autonomous Driving of a Rover based on Traffic Signals & Signs is to address these issues by automating the driving process and making it safer and more efficient. A dataset with traffic signs will be used to train a deep-learning model for classifying signs. A transfer learning technique will be used to deploy the trained model on the rover, considering hardware limitations. A camera on the rover captures images and sends them to the model for classification, enabling autonomous navigation based on traffic signs. The required software for the project includes Anaconda, a popular data science platform, and MaixPy, which is a version of MicroPython specifically designed for the Kendryte K210 chipset. The hardware required for the system includes the Zumo Shield for Arduino, which serves as the interface between the rover and the computer vision software, the Maixduino board, which is used to process the image data, and batteries to power the system. The system is designed to detect traffic signs and signals in real-time and respond accordingly, enabling the rover to navigate through traffic safely and efficiently.","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":"17 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138592803","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 : 2023-12-07DOI: 10.30534/ijeter/2023/1011122023
This project aims to develop a system for detecting decay in mushrooms using image processing techniques and Deep Learning. Decay in mushrooms is a significant issue in the food industry, as it can lead to quality deterioration and potentially harmful consumption. The proposed system involves capturing images of mushrooms using a camera and processing these images to detect any signs of decay. The image processing techniques will include pre- processing, feature extraction, and classification using deep learning algorithms. The dataset used for training and testing the system will consist of images of both healthy and decayed mushrooms. The system's performance will be evaluated based on accuracy. The outcome of this project will be a tool that can assist in early detection of decay in mushrooms, thus reducing food waste and improving food safety.
{"title":"Mushroom Decay Detection using Deep Learning","authors":"","doi":"10.30534/ijeter/2023/1011122023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/1011122023","url":null,"abstract":"This project aims to develop a system for detecting decay in mushrooms using image processing techniques and Deep Learning. Decay in mushrooms is a significant issue in the food industry, as it can lead to quality deterioration and potentially harmful consumption. The proposed system involves capturing images of mushrooms using a camera and processing these images to detect any signs of decay. The image processing techniques will include pre- processing, feature extraction, and classification using deep learning algorithms. The dataset used for training and testing the system will consist of images of both healthy and decayed mushrooms. The system's performance will be evaluated based on accuracy. The outcome of this project will be a tool that can assist in early detection of decay in mushrooms, thus reducing food waste and improving food safety.","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":"56 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138593035","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 : 2023-11-10DOI: 10.30534/ijeter/2023/0611112023
Animals’ interference into operation centers has become major headaches for some companies. Although it is a trivial case, the animals’ interference has disrupted major operations of the company. The article takes case of an Indonesian utility company, PN, that has challenges to distribute electricity to nationwide, especially in the rural areas, mountain, and forest areas, and thousand islands. Those areas are surrounded by animal presences that might trespass and interference into distribution sites such as transmission lines and transformers. The common presence of animals’ interference was found such as snakes, birds, and squirrels have created blackouts in some areas. The article proposes the use of intelligence cameras and RFID systems, along with preventive devices to assist animal trespassing in the distribution area. The article takes pilot of project in Payakumbuh area that is in West Sumatera, that has high animal interferences to the distribution system. Since the last decade, PN has promoted digital transformation in all her business units. The use of digital technology is expected to provide solution reference for animal interfere cases around Indonesia area, considering that each area in Indonesia has an un
{"title":"Preventing Animals Interference using Intelligence Camera and RFID System","authors":"","doi":"10.30534/ijeter/2023/0611112023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0611112023","url":null,"abstract":"Animals’ interference into operation centers has become major headaches for some companies. Although it is a trivial case, the animals’ interference has disrupted major operations of the company. The article takes case of an Indonesian utility company, PN, that has challenges to distribute electricity to nationwide, especially in the rural areas, mountain, and forest areas, and thousand islands. Those areas are surrounded by animal presences that might trespass and interference into distribution sites such as transmission lines and transformers. The common presence of animals’ interference was found such as snakes, birds, and squirrels have created blackouts in some areas. The article proposes the use of intelligence cameras and RFID systems, along with preventive devices to assist animal trespassing in the distribution area. The article takes pilot of project in Payakumbuh area that is in West Sumatera, that has high animal interferences to the distribution system. Since the last decade, PN has promoted digital transformation in all her business units. The use of digital technology is expected to provide solution reference for animal interfere cases around Indonesia area, considering that each area in Indonesia has an un","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":" 26","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135186955","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 : 2023-11-10DOI: 10.30534/ijeter/2023/0111112023
The increasing fuel prices and global warming have received worldwide attention regarding the importance of environmental-friendly utilization. Indonesia enjoys the sustainable growth of 4-5% annually also supports the growth the transportation vehicles. The incremental of transportation vehicles poses danger to the national budgets, where high subsidy allocation in national budgets is paid for fuels subsidy. To address this issue, the government has introduced many incentives and supported the use of Electric Vehicles (EVs) nationwide. Supporting EVs nationwide is not an easy task since it involves collaborating with electricity suppliers, EV resellers, and maintenance tasks associated in supply chain management. The article takes case study of a state-own energy company, ICP, that is given mandate to support the EV adoption. The outcome of the article is expected to provide a guideline for a utility company to deliver electricity to charging stations nationwide.
{"title":"Designing Integrated EV Charging Station to Grid Platform","authors":"","doi":"10.30534/ijeter/2023/0111112023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0111112023","url":null,"abstract":"The increasing fuel prices and global warming have received worldwide attention regarding the importance of environmental-friendly utilization. Indonesia enjoys the sustainable growth of 4-5% annually also supports the growth the transportation vehicles. The incremental of transportation vehicles poses danger to the national budgets, where high subsidy allocation in national budgets is paid for fuels subsidy. To address this issue, the government has introduced many incentives and supported the use of Electric Vehicles (EVs) nationwide. Supporting EVs nationwide is not an easy task since it involves collaborating with electricity suppliers, EV resellers, and maintenance tasks associated in supply chain management. The article takes case study of a state-own energy company, ICP, that is given mandate to support the EV adoption. The outcome of the article is expected to provide a guideline for a utility company to deliver electricity to charging stations nationwide.","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":" 25","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135186956","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 : 2023-11-10DOI: 10.30534/ijeter/2023/0411112023
The use of solar energy has gained significant attention due to its ability to provide a sustainable and clean source of power. Solar tracker is a device which is used to collect the solar energy emitted by the sun. Solar tracking system is a device that follows the sun's movement throughout the day to ensure maximum exposure to sunlight. The system comprises a solar panel, servo motor and rechargeable batteries. The solar panel is used to convert the sun's energy into electrical energy, which is then stored in the rechargeable batteries. This was achieved using an Arduino UNO that controls the position of the solar panel based on the sunlight intensity. The Arduino UNO receives information on the sun's position using two Light dependent Resistors (LDRs), and then adjusts the solar panel accordingly. The energy stored in the rechargeable batteries is used to charge a mobile. To achieve this, 5V Boost Converter is used. The use of a solar tracking system for mobile charging is a viable option for providing a sustainable and clean source of power. It is an efficient way to charge mobile devices using solar energy, especially in areas where access to electricity is limited
{"title":"Mobile Charging using Solar Tracking System","authors":"","doi":"10.30534/ijeter/2023/0411112023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0411112023","url":null,"abstract":"The use of solar energy has gained significant attention due to its ability to provide a sustainable and clean source of power. Solar tracker is a device which is used to collect the solar energy emitted by the sun. Solar tracking system is a device that follows the sun's movement throughout the day to ensure maximum exposure to sunlight. The system comprises a solar panel, servo motor and rechargeable batteries. The solar panel is used to convert the sun's energy into electrical energy, which is then stored in the rechargeable batteries. This was achieved using an Arduino UNO that controls the position of the solar panel based on the sunlight intensity. The Arduino UNO receives information on the sun's position using two Light dependent Resistors (LDRs), and then adjusts the solar panel accordingly. The energy stored in the rechargeable batteries is used to charge a mobile. To achieve this, 5V Boost Converter is used. The use of a solar tracking system for mobile charging is a viable option for providing a sustainable and clean source of power. It is an efficient way to charge mobile devices using solar energy, especially in areas where access to electricity is limited","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":" 31","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135187123","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 : 2023-11-10DOI: 10.30534/ijeter/2023/0711112023
An IoT based patient health monitoring system utilising ESP32 is a revolutionary method for enhancing healthcare services by enabling remote and real-time monitoring of patients health parameters.The system uses the ESP32 microcontroller and the Internet of Things (IoT) to effectively send and process data.The system uses numerous wireless sensors and when patient comes in contact with these sensors,It reads and captures critical physiological data like heart rate, blood pressure, body temperature, and oxygen saturation. Data from various sensors is received by the ESP32 microcontroller, which acts as a hub for data gathering, processing, and connection with a cloud-based platform.The cloud platform receives the health data provided by the ESP32 microcontroller.
{"title":"The Future of HealthCare is Connected","authors":"","doi":"10.30534/ijeter/2023/0711112023","DOIUrl":"https://doi.org/10.30534/ijeter/2023/0711112023","url":null,"abstract":"An IoT based patient health monitoring system utilising ESP32 is a revolutionary method for enhancing healthcare services by enabling remote and real-time monitoring of patients health parameters.The system uses the ESP32 microcontroller and the Internet of Things (IoT) to effectively send and process data.The system uses numerous wireless sensors and when patient comes in contact with these sensors,It reads and captures critical physiological data like heart rate, blood pressure, body temperature, and oxygen saturation. Data from various sensors is received by the ESP32 microcontroller, which acts as a hub for data gathering, processing, and connection with a cloud-based platform.The cloud platform receives the health data provided by the ESP32 microcontroller.","PeriodicalId":13964,"journal":{"name":"International Journal of Emerging Trends in Engineering Research","volume":" 30","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135187124","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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