Mental health issues are a growing concern worldwide, and seeking support for these issues can be difficult due to various reasons. Chatbots have emerged as a promising solution to provide accessible and confidential support to individuals facing mental health issues. With recent advances in technology, digital interventions designed to supplement or replace in-person mental health services have proliferated, including the emergence of mental health chatbots that claim to provide assistance through automated natural language processing (NLP) therapeutic approaches. A chatbot can be described as a computer program capable of providing intelligent answers to user input by understanding natural language using one or more NLP techniques. In this study, we discuss the use of NLP in psychotherapy and compare the responses provided by chatbots to a set of predefined user inputs related to well-being and mental health queries and compare existing systems. A general analysis was performed. The general approach to building such chatbots includes basic NLP techniques such as word embedding, sentiment analysis, sequence-by-sequence models, and attention mechanisms. We also looked at Mental Ease, a mobile app that uses NLP technology not only to provide conversational assistance but also to tool up useful features for maintaining mental health. Incorporating mental health assessment tools into the chatbot interface, it can help patients cope with mild anxiety and depression alongside conventional therapy. It can also overcome some barriers to mental health, such as waiting lists and geographical barriers to face-to-face consultations.
{"title":"Chatbot for Mental health support using NLP","authors":"Vanshika Gupta, Varun Joshi, Akshat Jain, Inakshi Garg","doi":"10.1109/INCET57972.2023.10170573","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170573","url":null,"abstract":"Mental health issues are a growing concern worldwide, and seeking support for these issues can be difficult due to various reasons. Chatbots have emerged as a promising solution to provide accessible and confidential support to individuals facing mental health issues. With recent advances in technology, digital interventions designed to supplement or replace in-person mental health services have proliferated, including the emergence of mental health chatbots that claim to provide assistance through automated natural language processing (NLP) therapeutic approaches. A chatbot can be described as a computer program capable of providing intelligent answers to user input by understanding natural language using one or more NLP techniques. In this study, we discuss the use of NLP in psychotherapy and compare the responses provided by chatbots to a set of predefined user inputs related to well-being and mental health queries and compare existing systems. A general analysis was performed. The general approach to building such chatbots includes basic NLP techniques such as word embedding, sentiment analysis, sequence-by-sequence models, and attention mechanisms. We also looked at Mental Ease, a mobile app that uses NLP technology not only to provide conversational assistance but also to tool up useful features for maintaining mental health. Incorporating mental health assessment tools into the chatbot interface, it can help patients cope with mild anxiety and depression alongside conventional therapy. It can also overcome some barriers to mental health, such as waiting lists and geographical barriers to face-to-face consultations.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131108307","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170043
Diya Theresa Sunil, Seema Safar, Abhijit Das, Amijith M M, Devika M Joshy
Image captioning is the task of generating a textual description that accurately represents the content of an image. This task involves combining computer vision techniques, such as object recognition and scene understanding, with natural language processing to produce a human-like description of an image. Over time, various models have been introduced to perform image captioning, all aiming to accurately describe the content of an image. These models have practical applications such as improving the accessibility of multimedia content, assisting individuals with visual impairments, medical image captioning, and enhancing image search and retrieval. This paper explores some of the models and studies their efficiency using different evaluation metrics.
{"title":"A Comparative Analysis of Image Captioning Techniques","authors":"Diya Theresa Sunil, Seema Safar, Abhijit Das, Amijith M M, Devika M Joshy","doi":"10.1109/INCET57972.2023.10170043","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170043","url":null,"abstract":"Image captioning is the task of generating a textual description that accurately represents the content of an image. This task involves combining computer vision techniques, such as object recognition and scene understanding, with natural language processing to produce a human-like description of an image. Over time, various models have been introduced to perform image captioning, all aiming to accurately describe the content of an image. These models have practical applications such as improving the accessibility of multimedia content, assisting individuals with visual impairments, medical image captioning, and enhancing image search and retrieval. This paper explores some of the models and studies their efficiency using different evaluation metrics.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131127083","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10169940
Jaiwin Shah, Rishabh Jain, Vedant Jolly, D. Kalbande
According to recent studies, a large number of data scientists spend most of their time on tasks like data cleaning and organizing data. They need to memorize big complex syntaxes for all the major tasks in the data science life cycle. Often these tasks are redundant. Therefore, we propose to build an intelligent system that enables data scientists to perform all the tedious and time-consuming tasks such as EDA, data cleansing, data preprocessing, data visualization, modeling, and data science lifecycle evaluation. Just state the logic of your query in natural language the system will automatically output all relevant Python code snippets. Existing applications involving the text-to-code generation and code search are limited and a lot of them do not work in non-ideal conditions. The reason behind it is the data set on which the existing models have been built. These datasets do not consider real-world factors such as slang, acronyms, and paraphrases. Therefore, a new dataset was created consisting of real-world user queries, representing the scenarios a user is most likely to face daily. We plan to build a logic-oriented system that only needs to convey the logic correctly in text in natural language. It saves a lot of time, allowing data scientists to spend most of their time building logic instead of focusing on code.
{"title":"Smart Intelligent System that can Code Like a Human Being","authors":"Jaiwin Shah, Rishabh Jain, Vedant Jolly, D. Kalbande","doi":"10.1109/INCET57972.2023.10169940","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10169940","url":null,"abstract":"According to recent studies, a large number of data scientists spend most of their time on tasks like data cleaning and organizing data. They need to memorize big complex syntaxes for all the major tasks in the data science life cycle. Often these tasks are redundant. Therefore, we propose to build an intelligent system that enables data scientists to perform all the tedious and time-consuming tasks such as EDA, data cleansing, data preprocessing, data visualization, modeling, and data science lifecycle evaluation. Just state the logic of your query in natural language the system will automatically output all relevant Python code snippets. Existing applications involving the text-to-code generation and code search are limited and a lot of them do not work in non-ideal conditions. The reason behind it is the data set on which the existing models have been built. These datasets do not consider real-world factors such as slang, acronyms, and paraphrases. Therefore, a new dataset was created consisting of real-world user queries, representing the scenarios a user is most likely to face daily. We plan to build a logic-oriented system that only needs to convey the logic correctly in text in natural language. It saves a lot of time, allowing data scientists to spend most of their time building logic instead of focusing on code.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128064628","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170698
M. Reddy, Swaroop Bhat, Nandana Chandrashekar, Sethupathy Venkatraman, P. Kanwal
Conformance analysis is a crucial part of software development that is used for the verification of software systems. Most of the prominent techniques for testing are based on dynamic analysis. Although dynamic analysis handles run-time integration, it does not address the quality of the code and hence the maintainability of the software. Static analysis, which is the analysis of code without execution, can be used to mitigate these issues. Using this technique, the adherence of code to a coding standard can be ascertained. The use of a specific standard improves readability and code maintainability. Traditional methods used for this purpose have been language-specific, and support for user-specified guidelines has been poor.This paper presents a tool that checks the conformance of the source code with user-curated guidelines. A simple, intuitive, and concise manner to specify guidelines is introduced. These guidelines are language-agnostic, thus allowing a uniform style to express them for multiple languages. A library of predefined guidelines has been provided to facilitate rapid development, and methods to add new guidelines are also expounded. Additionally, these guidelines can be used to verify if certain programming constructs have been used. Thus, it brings the codebase closer to the requirement specification document, allowing the programmer to effortlessly implement the code without worrying about its conformance. Lastly, an universal coding metric and benchmarking tool named LAPCA Score is provided which quantifies the extent of guideline violations that can be used to measure the degree of code compliance.
{"title":"Language Agnostic Program Conformance Analysis","authors":"M. Reddy, Swaroop Bhat, Nandana Chandrashekar, Sethupathy Venkatraman, P. Kanwal","doi":"10.1109/INCET57972.2023.10170698","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170698","url":null,"abstract":"Conformance analysis is a crucial part of software development that is used for the verification of software systems. Most of the prominent techniques for testing are based on dynamic analysis. Although dynamic analysis handles run-time integration, it does not address the quality of the code and hence the maintainability of the software. Static analysis, which is the analysis of code without execution, can be used to mitigate these issues. Using this technique, the adherence of code to a coding standard can be ascertained. The use of a specific standard improves readability and code maintainability. Traditional methods used for this purpose have been language-specific, and support for user-specified guidelines has been poor.This paper presents a tool that checks the conformance of the source code with user-curated guidelines. A simple, intuitive, and concise manner to specify guidelines is introduced. These guidelines are language-agnostic, thus allowing a uniform style to express them for multiple languages. A library of predefined guidelines has been provided to facilitate rapid development, and methods to add new guidelines are also expounded. Additionally, these guidelines can be used to verify if certain programming constructs have been used. Thus, it brings the codebase closer to the requirement specification document, allowing the programmer to effortlessly implement the code without worrying about its conformance. Lastly, an universal coding metric and benchmarking tool named LAPCA Score is provided which quantifies the extent of guideline violations that can be used to measure the degree of code compliance.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133195438","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170280
S. Marlin, S. D. S. Sundarsingh Jebaseelan
Recent years have seen a rise in the use of solar Photovoltaic (PV) systems in numerous application systems because of their effectiveness and affordability. One of the main challenges is producing the maximum energy from PV panels under various environmental circumstances. In order to achieve the highest energy output, numerous optimization-based MPPT controlling systems have been devised in traditional works. Low convergence, computational complexity, the length of time required to discover the optimum solution, and inefficiency are major drawbacks. In order to put a recently created optimization technique called Mongoose Optimization (MO) for MPPT regulating into practise that is the aim of this study. With superior tracking efficiency and enhanced speed, it facilitates obtaining the maximum power from the PV panels. Moreover, a bi-directional converter is employed to control PV output while decreasing switching stress and loss. Also, the voltage source inverter is employed to lower harmonic distortion levels in order to guarantee improved power quality. Performance study evaluates and compares the simulation outcomes and the efficacy of the suggested regulating architecture using a variety of metrics.
{"title":"A New MPPT Controlling Mechanism based on Adaptive Mongoose Optimization (MO) Algorithm for Grid-PV Systems","authors":"S. Marlin, S. D. S. Sundarsingh Jebaseelan","doi":"10.1109/INCET57972.2023.10170280","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170280","url":null,"abstract":"Recent years have seen a rise in the use of solar Photovoltaic (PV) systems in numerous application systems because of their effectiveness and affordability. One of the main challenges is producing the maximum energy from PV panels under various environmental circumstances. In order to achieve the highest energy output, numerous optimization-based MPPT controlling systems have been devised in traditional works. Low convergence, computational complexity, the length of time required to discover the optimum solution, and inefficiency are major drawbacks. In order to put a recently created optimization technique called Mongoose Optimization (MO) for MPPT regulating into practise that is the aim of this study. With superior tracking efficiency and enhanced speed, it facilitates obtaining the maximum power from the PV panels. Moreover, a bi-directional converter is employed to control PV output while decreasing switching stress and loss. Also, the voltage source inverter is employed to lower harmonic distortion levels in order to guarantee improved power quality. Performance study evaluates and compares the simulation outcomes and the efficacy of the suggested regulating architecture using a variety of metrics.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134237563","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170098
Anand Mohan, Abhilash Sharma Somayajula
Most ships that carry cargo from one place to another are underactuated. Therefore, controlling such vessels is challenging, and even a few major accidents in the industry can be attributed to ineffective control by a human operator. Automated control can significantly aid in the prevention of such incidents. This paper demonstrates the practical implementation of a path-following algorithm for an underactuated scaled model of a container ship. In this research, two different control strategies have been compared against each other: Proportional Derivative Control (PD) and Sliding Mode Control (SMC). The underactuated vessel is made to track a given set of waypoints, and the performance of the controllers is measured. For this study, a 1:75.5 scaled free-running model of the KRISO Container Ship (KCS) is chosen as the test ship. Simulations were done using a numerical model of the vessel’s dynamics and the controllers are compared for their accuracy and robustness.
{"title":"Analyzing Robustness and Accuracy of Different Controllers for Underactuated Ships","authors":"Anand Mohan, Abhilash Sharma Somayajula","doi":"10.1109/INCET57972.2023.10170098","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170098","url":null,"abstract":"Most ships that carry cargo from one place to another are underactuated. Therefore, controlling such vessels is challenging, and even a few major accidents in the industry can be attributed to ineffective control by a human operator. Automated control can significantly aid in the prevention of such incidents. This paper demonstrates the practical implementation of a path-following algorithm for an underactuated scaled model of a container ship. In this research, two different control strategies have been compared against each other: Proportional Derivative Control (PD) and Sliding Mode Control (SMC). The underactuated vessel is made to track a given set of waypoints, and the performance of the controllers is measured. For this study, a 1:75.5 scaled free-running model of the KRISO Container Ship (KCS) is chosen as the test ship. Simulations were done using a numerical model of the vessel’s dynamics and the controllers are compared for their accuracy and robustness.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115028001","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170511
N. Nimbarte, Huzaif Khan, Mangesh Dilip Sendre, Kiran Ramteke, Sonali Wairagade
This study proposes a baby cry detection system using Mel Frequency Cepstral Coefficients (MFCC) and K-Nearest Neighbor (KNN) algorithm. The review of a wide variety of literature focuses primarily on data gathering, processing of signals in cross domain, and classification using machine learning algorithms. When using various apps to monitor a baby’s condition, automatic voice detection of a baby’s cry is crucial. This hypothesized concept involves the detection of a baby’s scream. To distinguish infant sounds of crying in a range of settings which are residential under challenging circumstances, this system uses a machine learning technique. The proposed method extracts MFCC features from the audio signals of the baby cries and applies KNN to classify the cries based on their features. The results are based on a classification-related investigation of the performance of cry-detection using KNN. A baby’s cry may be automatically detected in a few circumstances including different environmental noises. The suggested technique demonstrated high accuracy in identifying cry types when tested using a freely accessible dataset.
{"title":"New Born Baby Cry Analysis and Classification","authors":"N. Nimbarte, Huzaif Khan, Mangesh Dilip Sendre, Kiran Ramteke, Sonali Wairagade","doi":"10.1109/INCET57972.2023.10170511","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170511","url":null,"abstract":"This study proposes a baby cry detection system using Mel Frequency Cepstral Coefficients (MFCC) and K-Nearest Neighbor (KNN) algorithm. The review of a wide variety of literature focuses primarily on data gathering, processing of signals in cross domain, and classification using machine learning algorithms. When using various apps to monitor a baby’s condition, automatic voice detection of a baby’s cry is crucial. This hypothesized concept involves the detection of a baby’s scream. To distinguish infant sounds of crying in a range of settings which are residential under challenging circumstances, this system uses a machine learning technique. The proposed method extracts MFCC features from the audio signals of the baby cries and applies KNN to classify the cries based on their features. The results are based on a classification-related investigation of the performance of cry-detection using KNN. A baby’s cry may be automatically detected in a few circumstances including different environmental noises. The suggested technique demonstrated high accuracy in identifying cry types when tested using a freely accessible dataset.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114281547","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170736
Akhtar I. Nadaf, S. Pardeshi
The use of machine learning technologies for the identification of sign language has gained popularity recently. This arises from the recognition of sign language as a valuable means of communication specifically designed for individuals who are mute or hearing-impaired. In order to build an optimised model based on sEMG, accelerometer, gyro, and magnetometer data, this research article compares decision tree classifiers, notably J48, Random tree, REPTree, and Random forest. This data is collected through the Myo arm band worn on both forearms of the user. The experiment is designed using the open-source Waikato Environment for Knowledge Analysis (WEKA) framework. To evaluate the effectiveness of the four algorithms, three attribute selection techniques information gain-based, correlation-based, and learner-based feature selection were used. The trial results showed that, among the investigated algorithms, the Random Forest method had the highest accuracy, measuring 97.9472%.
最近，机器学习技术在识别手语方面的应用越来越受欢迎。这是因为人们认识到手语是专门为哑巴或听障人士设计的一种宝贵的交流手段。为了构建基于表面肌电信号、加速度计、陀螺仪和磁力计数据的优化模型，本文比较了决策树分类器，特别是J48、Random tree、REPTree和Random forest。这些数据是通过佩戴在用户前臂上的Myo臂带收集的。实验是使用开源的Waikato Environment for Knowledge Analysis (WEKA)框架设计的。为了评估四种算法的有效性，使用了基于信息增益、基于相关性和基于学习者的特征选择三种属性选择技术。试验结果表明，在所研究的算法中，随机森林方法的准确率最高，为97.9472%。
{"title":"Classifying Sign Language Gestures using Decision Trees: A Comparison of sEMG and IMU Sensor Data","authors":"Akhtar I. Nadaf, S. Pardeshi","doi":"10.1109/INCET57972.2023.10170736","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170736","url":null,"abstract":"The use of machine learning technologies for the identification of sign language has gained popularity recently. This arises from the recognition of sign language as a valuable means of communication specifically designed for individuals who are mute or hearing-impaired. In order to build an optimised model based on sEMG, accelerometer, gyro, and magnetometer data, this research article compares decision tree classifiers, notably J48, Random tree, REPTree, and Random forest. This data is collected through the Myo arm band worn on both forearms of the user. The experiment is designed using the open-source Waikato Environment for Knowledge Analysis (WEKA) framework. To evaluate the effectiveness of the four algorithms, three attribute selection techniques information gain-based, correlation-based, and learner-based feature selection were used. The trial results showed that, among the investigated algorithms, the Random Forest method had the highest accuracy, measuring 97.9472%.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114612228","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170052
Shaik. Pathima, Gude. SindhuPriya, Gudavalli. Lakshmi Yesaswini, S. Suhasini
It can be challenging to access information about books and users quickly. In any Catalogue systems, there is a sizable collection of books and other materials that are available for users to access. For the academic institutions, it serves as the brain. Mistakes can happen during the processing of documenting, cataloguing, and stacking books, and they may not be able to find the books they are looking for. It is difficult to keep track of all the books and users manually. If the book may be misplaced or stolen, this leads to a loss of revenue for the catalogue management system. Automated catalogue administration systems have several advantages, including expensive upkeep, technical challenges, the necessity for training courses, dependency on technology, and customizability. Yet, they also provide several advantages, such as improved information access, data management, and efficiency. The current application is a free and open-source web application developed using the MERN stack and hosts into the firebase up to a server. The goal of this paper is to develop a system that effectively handles all of the activities that take place in the catalogue system, enabling all users to access it whenever it is most convenient for them. Two factor authentications is carried out in the proposed system for handling users, email verification, notifications, book access, returns etc. admin handles security about users and other information to maintain effectiveness, confidentiality, integrity in the proposed system. Firebase is used to deploy the proposed web application and its operability. Real time updates, analytics are part of the proposed system
{"title":"Digitalization of Catalogue Automation System with Firebase","authors":"Shaik. Pathima, Gude. SindhuPriya, Gudavalli. Lakshmi Yesaswini, S. Suhasini","doi":"10.1109/INCET57972.2023.10170052","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170052","url":null,"abstract":"It can be challenging to access information about books and users quickly. In any Catalogue systems, there is a sizable collection of books and other materials that are available for users to access. For the academic institutions, it serves as the brain. Mistakes can happen during the processing of documenting, cataloguing, and stacking books, and they may not be able to find the books they are looking for. It is difficult to keep track of all the books and users manually. If the book may be misplaced or stolen, this leads to a loss of revenue for the catalogue management system. Automated catalogue administration systems have several advantages, including expensive upkeep, technical challenges, the necessity for training courses, dependency on technology, and customizability. Yet, they also provide several advantages, such as improved information access, data management, and efficiency. The current application is a free and open-source web application developed using the MERN stack and hosts into the firebase up to a server. The goal of this paper is to develop a system that effectively handles all of the activities that take place in the catalogue system, enabling all users to access it whenever it is most convenient for them. Two factor authentications is carried out in the proposed system for handling users, email verification, notifications, book access, returns etc. admin handles security about users and other information to maintain effectiveness, confidentiality, integrity in the proposed system. Firebase is used to deploy the proposed web application and its operability. Real time updates, analytics are part of the proposed system","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114539052","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170481
Yun Miao
English learning application based on Android platform is one of the best ways to learn English. This is a good tool for those who are interested in learning English. With this application, you can have fun learning English. This application is designed for everyone. No matter what their age or gender, it is easy to learn English through this application. Android means it is an operating system that runs on mobile devices such as smartphones and tablets. This study aims to develop an Android platform application to help students learn English. The main purpose of this study is to analyze and evaluate the effectiveness of the application in improving students' English language skills. This application will be developed using Android SDK version 4.0 (API level 15), with a minimum requirement of 1 GB ram and 512 MB storage space. The touch screen device runs on Android 2.2 or later, and Java 5 or later installed on the computer.
{"title":"Research on Application of English Learning App based on Android Platform","authors":"Yun Miao","doi":"10.1109/INCET57972.2023.10170481","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170481","url":null,"abstract":"English learning application based on Android platform is one of the best ways to learn English. This is a good tool for those who are interested in learning English. With this application, you can have fun learning English. This application is designed for everyone. No matter what their age or gender, it is easy to learn English through this application. Android means it is an operating system that runs on mobile devices such as smartphones and tablets. This study aims to develop an Android platform application to help students learn English. The main purpose of this study is to analyze and evaluate the effectiveness of the application in improving students' English language skills. This application will be developed using Android SDK version 4.0 (API level 15), with a minimum requirement of 1 GB ram and 512 MB storage space. The touch screen device runs on Android 2.2 or later, and Java 5 or later installed on the computer.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117063580","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：