2023 4th International Conference on Intelligent Engineering and Management (ICIEM)最新文献_第7页

Patient Context Monitoring With Wireless Networks 用无线网络监测病人情况

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10165972

Charanjeet Singh, Anurag Shrivastava, H. S. Pokhariya, Indradeep Kumar, C. S. Sundar Ganesh, Arun Pratap Srivastava

{"title":"Patient Context Monitoring With Wireless Networks","authors":"Charanjeet Singh, Anurag Shrivastava, H. S. Pokhariya, Indradeep Kumar, C. S. Sundar Ganesh, Arun Pratap Srivastava","doi":"10.1109/ICIEM59379.2023.10165972","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10165972","url":null,"abstract":"It has become increasingly necessary to observe patients in the emergency room, especially in cases of failed patient verification in the clinic, as medical service application innovation advances. Patients' daily activities can be recorded by numerous devices connected to the distant institution. This framework uses the actual framework as well as the application dataset along with the clinical histories of the associated patients so that users can select how simple situations should be handled. The proposed framework makes use of the actual framework, the application dataset, and the clinical histories of the associated patients. An accuracy rate of 95% ensures that this will be a beneficial tool for the clinical office. This will be able to accurately monitor the patient's condition using connected sensor-based networks. Social events and the patient's natural practices are monitored by several sensors. Next, the cloud collects important natural data. By examining sensor data, the system may identify the patient's underlying ailment and is more advanced. This system has the advantage of enabling doctors and other medical personnel to observe patients without having to interact directly with them through pop-up messages. This system then promptly alerts the relevant professionals, carers, and clinic staff. In this context, any clinical document that has web functionality and can monitor at least one indicator of patient health is known as an “IoT-based patient health observation framework”. A patient's condition can be recorded, communicated, and alerted if it changes unexpectedly.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132784957","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}

引用次数: 0

Resumate: A Prototype to Enhance Recruitment Process with NLP based Resume Parsing 简历:一个基于NLP的简历解析增强招聘流程的原型

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10166169

Saswat Mohanty, Anshuman Behera, Sushruta Mishra, A. Alkhayyat, Deepak Gupta, Vandana Sharma

{"title":"Resumate: A Prototype to Enhance Recruitment Process with NLP based Resume Parsing","authors":"Saswat Mohanty, Anshuman Behera, Sushruta Mishra, A. Alkhayyat, Deepak Gupta, Vandana Sharma","doi":"10.1109/ICIEM59379.2023.10166169","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10166169","url":null,"abstract":"The process of reviewing resumes takes time. The unstructured written language can be understood and parsed by natural language processing and machine learning, which can then extract the required information. The goal is to teach the computer to analyze written papers similarly to a human. For assessing and analyzing the unstructured data, various methods including named entity recognition, tokenization, text classification, and approaches of other natural language processing techniques have been explored. A user uploads a resume into the program, which takes it and converts it into a standard text format before parsing it for the necessary information and organizing the extracted data in a standard defined format. After extraction and preprocessing, a predictive model is trained is better and categorize resumes for use in various applications. The k-fold cross validation with k=5 outcome in this case reveals that SVM(0.58 - 0.65) and XG Boost(0.65 - 0.73) have higher ranges of training performance than all other models. Here, the XG Boost outperforms previous trained models, accurately classifying the newly created resume into the target category. The proposed work is novel and presents one of its kind methodology.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115988455","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}

引用次数: 2

An Assessment of Covid19 Using CNN Architecture 基于CNN架构的covid - 19评估

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10166878

Anurag Shrivastava, Roja Boina, Devvret Verma, Y. Kumar, Indradeep Kumar, Annam Takshitha Rao

{"title":"An Assessment of Covid19 Using CNN Architecture","authors":"Anurag Shrivastava, Roja Boina, Devvret Verma, Y. Kumar, Indradeep Kumar, Annam Takshitha Rao","doi":"10.1109/ICIEM59379.2023.10166878","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10166878","url":null,"abstract":"Hundreds of thousands of people have been affected by the COVID-19 epidemic all over the world. The high mortality rate has impacted more than 200 countries. The Corona virus is highly contagious, which means patients are consistently waiting for a diagnosis, resulting in time-consuming radiologists and poor patient care. Using deep learning techniques to recognize COVID-19 from chest X-ray images is important to expedite the process. Our project will use these techniques in order to expedite the process. A patient's chest X-ray will be taken into account, and the output of the model will be labeled as COVID-positive or COVID-negative. Because of its relative speed, greater accuracy is achieved and processing delays are avoided as compared to conventional methods. A novel strain of Coronavirus (COVID-19) was discovered in Wuhan, a city in China, and is rapidly spreading around the globe. There are currently approximately 215 countries with COVID-19 illnesses. WHO reports 11,274,600 cases worldwide. Despite the increasing number of COVID-19 patients in hospitals, there are few resources available to stop the epidemic. For this reason, it is imperative to accurately diagnose COVID-19. In order to prevent the spread of the disease, patients with the disease must be diagnosed immediately. This study suggests a deep learning-based approach to differentiate patients with COVID-19 from those with viral pneumonia, bacterial pneumonia, and those with healthy (normal) lung function.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122530077","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}

引用次数: 0

Artificial Intelligence based Chatbot for promoting Equality in High School Advising 基于人工智能的聊天机器人促进高中咨询中的平等

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10167112

Suha Khalil Assayed, M. Alkhatib, K. Shaalan

{"title":"Artificial Intelligence based Chatbot for promoting Equality in High School Advising","authors":"Suha Khalil Assayed, M. Alkhatib, K. Shaalan","doi":"10.1109/ICIEM59379.2023.10167112","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10167112","url":null,"abstract":"The sustainable development goal 4 (SDG4) aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all”, Therefore., researchers are inspired to study the fairness and equality in different aspects of education. Some studies are focused on social and academic initiatives and others on developing state-of-the-art technology to enhance the education between students equally. Henceforth., in this paper a novel affordable chatbot implemented by using a neural network model and natural language processing (NLP) to assist students in high schools particularly., since high school is one of the most essential stages in students” lives., as in this stage., students have the option to select their academic streams and advanced courses that can shape their career with their passions and interests. The dataset in this study collected from different academic resources such as schools & universities websites., schools” advisers., parents and students. It includes (968) pairs of enquiries and tags. The first column represents the student's enquiry; the second column indicates the tag or the class of each sentence. The model built by connecting the input data into embedding layer., and then the data fed into the LSTM layer with different number of neurons., then authors used sigmoid function for the output layer. The result in this study shows that the performance of the chatbot is improved by increasing the number of neurons from 5 to 8, the model achieved high accuracy ratio with score (96.5%). In future the model will be developed with stacked LSTM layers with using softmax activation function in the output layer, as different classes will be added as well in the dataset.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132498714","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}

引用次数: 1

Facial Recognition for Crime Control: A Machine Learning-based Solution 面部识别用于犯罪控制:基于机器学习的解决方案

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10165907

Archana Singh, Sakshi Mishra, Prateek Sharma, Varsha Singh, Ashima Arya

{"title":"Facial Recognition for Crime Control: A Machine Learning-based Solution","authors":"Archana Singh, Sakshi Mishra, Prateek Sharma, Varsha Singh, Ashima Arya","doi":"10.1109/ICIEM59379.2023.10165907","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10165907","url":null,"abstract":"The criminal record holds detailed information including criminal history and personal information with a photograph of an individual. In order to identify a criminal, eyewitness identification is necessary, despite often having poor image quality and unclear resolution. Identification can be performed through various means like DNA, fingerprint or eyes. Facial identification involves storing full and cropped images of criminals along with their personal and criminal information to create a database. Then another database is created to identify the criminal; eyewitnesses, with the help of a professional, try to piece together the criminal's face using saved cuts stored in a database. Then, using Amazon Recognition, we try to predict the criminal by comparing the created image with the existing database, if the result is 70-80%, we declare this face as a criminal. Amazon Recognition is an image recognition service that identifies objects, faces, etc. and find out the result from the database. This technology also has a feature to compare different faces, which we are using in our project.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115736212","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}

引用次数: 0

Impact of Metaverse in the Near ‘Future’ 超宇宙在不远的“未来”的影响

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10166025

Palakh Gupta, Khusi Bhadani, Anjan Bandyopadhyay, Debajyoty Banik, Sujata Swain

{"title":"Impact of Metaverse in the Near ‘Future’","authors":"Palakh Gupta, Khusi Bhadani, Anjan Bandyopadhyay, Debajyoty Banik, Sujata Swain","doi":"10.1109/ICIEM59379.2023.10166025","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10166025","url":null,"abstract":"Ever since Neel Stephenson's novel ‘Snow Crash’ was published in 1992, the metaverse and its virtual space have been evolving. Because of the growing desire for immersion, this survey article is the first endeavor to offer a comprehensive framework that assesses the contemporary metaverse development under the perspectives of state-of-the-art innovations and digital world ecosystems. So, we re-investigate eight enabling technologies: Extended Reality, User Interactivity, Artificial Intelligence, Blockchain, Computer Vision, IoT and Robots, Future Mobile Networks etcetera. The metaverse environment in application terms means empowering users to interact with and live within a subconscious everlasting and shared reality. A wide range of computer-mediated virtual environments that we have created include social networks, video conferencing, virtual 3D worlds (like VR Chat), augmented reality apps (like Pokemon Go), and non-fungible token games (like Upland).Although transient and unconnected, these virtual environments have brought about various levels of digital change for us. Thus, we propose clear future research for the metaverse's advancement.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116111825","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}

引用次数: 0

Biometric and RFID Passive Tag based Student Identification System for Secure Attendance Management 基于生物识别和RFID被动标签的学生安全考勤管理系统

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10166924

Nagendra R, R. G, Venkata Pavan K, Gopa Niranjan Reddy, B. S. Reddy, Kristam Harsha Vardhan, G. L. Abhinav

{"title":"Biometric and RFID Passive Tag based Student Identification System for Secure Attendance Management","authors":"Nagendra R, R. G, Venkata Pavan K, Gopa Niranjan Reddy, B. S. Reddy, Kristam Harsha Vardhan, G. L. Abhinav","doi":"10.1109/ICIEM59379.2023.10166924","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10166924","url":null,"abstract":"This paper proposes a biometric and RFID passive tag-based student identification system for secure attendance management. The system utilizes the unique biometric features of each student, such as fingerprint, along with an RFID tag embedded in the student ID card to authenticate and track student attendance. The system is designed to overcome the limitations of traditional attendance management systems, such as manual entry errors, proxy attendance, and low accuracy. The proposed system provides an automated and secure attendance management solution that ensures accurate attendance recording and eliminates the possibility of fraudulent activities. A daily brief message service (SMS) delivered by a GSM (Global System for Mobile) module, notifying the guardian as to whether the individual has arrived at the institution. There will be a web application where students and instructors will view a student's current attendance and location on campus. The system has been implemented and tested in a real-world educational setting, and the results demonstrate its efficiency and reliability in managing student attendance.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131591439","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}

引用次数: 1

Analysis of Variation in Mechanical Properties of Glass Fiber with Natural Fiber Reinforced Concrete 玻璃纤维与天然纤维增强混凝土力学性能差异分析

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10167003

P. Duggal, R. K. Tomar, N. Kaushika

{"title":"Analysis of Variation in Mechanical Properties of Glass Fiber with Natural Fiber Reinforced Concrete","authors":"P. Duggal, R. K. Tomar, N. Kaushika","doi":"10.1109/ICIEM59379.2023.10167003","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10167003","url":null,"abstract":"Concrete is a composite material that breaks and scales easily due to drying shrinkage and the effects of plastic and solidified states. Fiber overlays and sheets are now the subject of extensive study for their potential in supporting and sustaining supported heavy people all over the world. The use of Fiber-Reinforced Polymers (FRPs) is an attractive strategy for restoring and fortifying structures that have deteriorated fundamentally over time. As compared to more traditional fixing methods and materials, FRP fixing frameworks are a more cost-effective choice. In this paper, we conduct experimental tests to determine the performance of a composite mix made from Sisal Fibre (SF) of varying lengths 6mm and two different lengths of Glass Fiber (6mm and 12mm) subjected to four different rates of expansion by a full load of cement (0%, 0.75 %, 1.25 %, and 1.75 %). The experimental study employs a Woven Roving Mat of Glass Fiber and 380 GSM Bidirectional Sisal Fiber in concrete at volume fractions of 0.6%, 0.8%, and 1.0%, respectively. The load, pliability, and flexural strength fluctuation data from the trials have been collected.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125970953","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}

引用次数: 0

Health Disease Prediction Using Machine Learning and Internet of Things 利用机器学习和物联网进行健康疾病预测

2023 4th International Conference on Intelligent Engineering and Management (ICIEM) Pub Date : 2023-05-09 DOI: 10.1109/ICIEM59379.2023.10165903

Patil Rahul Ashokrao, Derle Deepak Radhakrishna, Mukesh Sharma, S. Bhad

{"title":"Health Disease Prediction Using Machine Learning and Internet of Things","authors":"Patil Rahul Ashokrao, Derle Deepak Radhakrishna, Mukesh Sharma, S. Bhad","doi":"10.1109/ICIEM59379.2023.10165903","DOIUrl":"https://doi.org/10.1109/ICIEM59379.2023.10165903","url":null,"abstract":"The Analysis of Disease Forecast using Machine Learning may be a framework that makes an exact prediction based on the data or side effects that the user enters into the framework and the infection it will cause. If the understanding isn't very accurate and the client really needs to know the type of illness he or she has experienced, it could be a framework that offers the client the tips and tricks to maintain the client's wellbeing framework and it provides a way to discover the illness using this forecast. The health industry plays a crucial role in treating patients' infections, so there are typically a few types of offer assistance for the health industry. By just getting the client's indications and using the framework, the health business can also profit from it. They will be able to tell in a reasonable amount of time. With the help of machine learning and the Python programming language with Tkinter interface, this Malady Expectation Utilizing Machine Learning has been completed in full. It also uses the dataset that the medical facilities already have access to and uses that to predict the spread of infection. IoT, cloud, and fog computing, which are popular issues in the field of illness detection and prediction, are, on the other hand, attracting the attention of the academic community. The Internet of Things (IoT), cloud computing, and fog computing have all been used to develop a variety of healthcare solutions.","PeriodicalId":397602,"journal":{"name":"2023 4th International Conference on Intelligent Engineering and Management (ICIEM)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115538670","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}

引用次数: 0