EAI Endorsed Trans. e Learn.最新文献

{"title":"The Power of AI-Assisted Diagnosis","authors":"Jiaji Wang","doi":"10.4108/eetel.3772","DOIUrl":"https://doi.org/10.4108/eetel.3772","url":null,"abstract":"The rapid advancements in artificial intelligence (AI) have unleashed a wave of transformative technologies, and one area that has witnessed significant progress is AI-assisted diagnosis in healthcare. With the ability to analyze vast amounts of medical data, learn from patterns, and make accurate predictions, AI systems hold immense potential to revolutionize the diagnostic process, enabling earlier detection, improved accuracy, and personalized treatment recommendations. This review aims to explore the impact of AI in healthcare, specifically focusing on its role in assisting physicians with diagnosis, highlighting the benefits, challenges, and ethical considerations associated with the integration of AI systems into clinical practice. Through the utilization of AI's capabilities, the enhancement of patient outcomes, optimization of resource allocation, and the reshaping of medical professionals' approaches to diagnosis and treatment can be achieved.","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121160692","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}

{"title":"A fast image inpainting algorithm based on an adaptive scanning strategy","authors":"H. .. R. .. Guo, W. .. H. .. Wang","doi":"10.4108/eetel.3141","DOIUrl":"https://doi.org/10.4108/eetel.3141","url":null,"abstract":"OBJECTIVES: In exemplar-based image inpainting algorithms, there are often issues with the calculation of patch similarity for matching, suboptimal strategies for selecting matching patches, and low inpainting speed.METHODS: This paper first uses the variable scale cross-scan block line progressive scan to solve the problem of slow scanning speed and invalid priority formula. Then, an improved weight similarity formula is used for searching to solve the problem of poor computing strategy for similar matching patches. The search range of matching patches gradually increases from small to large until globally searching for similar matching patches to improve the efficiency of inpainting. To further improve the correctness of matching patch selection, this paper uses six levels of priority matching criteria for screening.RESULTS: The experimental results show that the inpainting effect of the proposed method is significantly improved in subjective vision, and the structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and inpainting speed of the inpainting results are all improved.CONCLUSION: For different types of images, the proposed method has a better inpainting effect and higher inpainting speed than the other three advanced methods.","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115768588","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}

{"title":"Gray Level Co-Occurrence Matrix and RVFL for Covid-19 Diagnosis","authors":"Wenhao Tang","doi":"10.4108/eetel.v8i2.3091","DOIUrl":"https://doi.org/10.4108/eetel.v8i2.3091","url":null,"abstract":"As the widespread transmission of COVID-19 has continued to influence human health since late 2019, more intersections between artificial intelligence and the medical field have arisen. For CT images, manual differentiation between COVID-19-infected and healthy control images is not as effective and fast as AI. This study performed experiments on a dataset containing 640 samples, 320 of which were COVID-19-infected, and the rest were healthy controls. This experiment combines the gray-level co-occurrence matrix (GLCM) and random vector function link (RVFL). The role of GLCM and RVFL is to extract image features and classify images, respectively. The experimental results of my proposed GLCM-RVFL model are validated using K-fold cross-validation, and the indicators are 78.81±1.75%, 77.08±0.68%, 77.46±0.73%, 54.22±1.35%, and 77.48±0.74% for sensitivity, accuracy, F1-score, MCC, and FMI, respectively, which also confirms that the proposed model performs well on the COVID-19 detection task. After comparing with six state-of-the-art COVID-19 detection, I ensured that my model achieved higher performance.","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130084605","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}

{"title":"Teaching Physical Exercise with Music - Pedometric Evaluation","authors":"W. W, G. Vinod Kumar, S. Sivachandiran","doi":"10.4108/eetel.v8i2.3073","DOIUrl":"https://doi.org/10.4108/eetel.v8i2.3073","url":null,"abstract":"In everyday life and culture, music can be encountered and experienced in a variety of forms, and it plays a role in mood swings. Numerous studies have shown that listening to music while exercising increases both the amount of time spent exercising as well as the interest level in the activity. It is hypothesised that instructing pupils in physical activities through the medium of music would have a beneficial effect on them. Fifty-five students from the Faculty of Physical Education were chosen to serve as study subjects in order to investigate the impact that music has on the process of learning and doing the activity. This study was carried out over the course of two days, and the data was gathered by counting the number of footsteps that participants made throughout a period of 20 minutes of instruction with or without music. The exercises were demonstrated to the participants over the course of two days; on the first day, they were demonstrated with music, and on the second day, they were demonstrated without music. According to the findings of this study, there is a discernible contrast between instructing activities with and without the use of music. The topic revealed a tremendous amount of interest and vitality when it was practised with music. The pedometric measure improved with musical training, and males did much better than girls in this regard.","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124848470","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}

{"title":"Analyzing the Effects of Eco-Spirituality on Organizational Commitment and Employee Engagement Among Female Academics in Higher Education","authors":"Shaan Gulhar, A. Singh, Priyanka Agarwal","doi":"10.4108/eetel.v8i2.2958","DOIUrl":"https://doi.org/10.4108/eetel.v8i2.2958","url":null,"abstract":"This study investigated the connections between eco-spirituality, organizational commitment, and employee engagement by female academics within higher education institutions. The results of this study indicate that eco-spirituality has an effect on organizational commitment, and organizational commitment has an effect on employee engagement. Both of these relationships were found to be significant. In addition, this research's findings indicate a direct and indirect relationship between employee engagement and eco-spirituality. Even though this relationship has never been investigated in any of the previous studies, the findings of this research show that there is such a relationship. An employee engagement study, an organizational commitment study, and an employee spirituality study were all conducted using regression analysis. We also considered the correlation between the two data sets when analyzing the connection between the dependent and the independent variables. An examination of the construct item's dependability was carried out.","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131972859","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}

{"title":"Effective Tamil Character Recognition Using Supervised Machine Learning Algorithms","authors":"Dr.S. Suriya, S. Nivetha, P. Pavithran, Ajay Venkat S., Sashwath K. G., Elakkiya G.","doi":"10.4108/eetel.v8i2.3025","DOIUrl":"https://doi.org/10.4108/eetel.v8i2.3025","url":null,"abstract":"Computational linguistics is the branch of linguistics in which the techniques of computer science are applied to the analysis and synthesis of language and speech. The main goals of computational linguistics include: Text-to- speech conversion, Speech-to-text conversion and Translating from one language to another. A part of Computational Linguistics is the Character recognition. Character recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. Character recognition methodology mainly focuses on recognizing the characters irrespective of the difficulties that arises due to the variations in writing style. The aim of this project is to perform character recognition for of one of the complex structures of south Indian language ‘Tamil’ using a supervised algorithm that increases the accuracy of recognition. The novelty of this system is that it recognizes the characters of the Predominant Tamil Language. The proposed approach is capable of recognizing text where the traditional character recognition systems fails, notably in the presence of blur, low contrast, low resolution, high image noise, and other distortions. This system uses Convolutional Neural Network Algorithm that are able to exact the local features more accurately as they restrict the receptive fields of the hidden layers to be local. Convolutional Neural Networks are a great kind of multi-layer neural networks that uses back-propagation algorithm. Convolutional Neural Networks are used to recognize visual patterns directly from pixel images with minimal preprocessing. This trained network is used for recognition and classification. The results show that the proposed system yields good recognition rates.","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124201571","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}

{"title":"Design of UML Diagrams for WEBMED - Healthcare Service System Services","authors":"S. D. Suriya, S. Nivetha","doi":"10.4108/eetel.v8i1.3015","DOIUrl":"https://doi.org/10.4108/eetel.v8i1.3015","url":null,"abstract":"Healthcare service has huge demand these days as it really helps in managing a hospital or a medical office. The scope of Healthcare service systems is increasing by each day and it is true for the entire world. Some of these solutions include improved awareness about Healthcare services and health policies. The objective of this system is to provide medical assistance to people instantly with the help of technology. This system eradicates the cultural sensitivity that prevails in many hospitals and improvises the quality of medical assistance. The captivating features of this system are online doctor, medicines at doorstep, bulletin of awareness. The users can also navigate and choose among various insurance schemes that are displayed.Unified Modeling language (UML) is a standardized modeling language enabling developers to specify, visualize, construct and document artifacts of a software system. It uses graphic notation to create visual models of software systems. This paper contains the UML diagrams for better understanding of the system with the help of Star UML tool.Usecase diagrams are used during the analysis phase of a project to identify system functionalities. Class diagram represents the static view of an application.The class diagrams are the only UML diagrams, which can be mapped directly with object-oriented languages.Activity diagram is an important behavioral diagram in UML diagram to describe dynamic aspects of the system. Activity diagram is essentially an advanced version of flow chart that modeling the flow from one activity to another activity.The state machine diagram shows the different states of an entity and focuses more on how it responds to various events by changing from one state to another. Statechart diagram is used to capture the dynamic aspect of a system. State machine diagrams are used to represent the behavior of an application. The sequence diagram focuses on the messages that are passed during an interaction in a time based perspective.A Communication diagram models the interactions between objects or parts in terms of sequenced messages. It describes both the static structure and dynamic behavior of a system. Component diagrams are used to model the physical aspects of a system. It does not describe the functionality of the system but it describes the components used to make those functionalities. Deployment Diagram is a type of diagram that specifies the physical hardware on which the software system will execute. It also determines how the software is deployed on the underlying hardware. UML is a modeling language used by software developers.UML can be used to develop diagrams and provide users with ready-to-use, expressive modeling examples. Some UML tools generate program language code from UML.UML can be used for modeling a system independent of a platform language. UML is a graphical language for visualizing, specifying, constructing, and documenting information about software-intensive systems.UML gi","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125334857","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}

{"title":"A Concept Map based Teaching of Compiler Design for Undergraduate Students","authors":"V. Subramanian, Kalaivany Karthikeyan, P. Venkataram","doi":"10.4108/eetel.v8i1.2550","DOIUrl":"https://doi.org/10.4108/eetel.v8i1.2550","url":null,"abstract":"In undergraduate engineering, most of the subjects do not have the open visibility of the Industry and Research requirements. Students are interested mostly on subjects which are useful for Industry placement. They do not show interest in non-open visibility subjects if an instructor teaches by simply following the textbook. Considering this, we presented a concept map based teaching methodology with Research and Industry assignments and problems. The proposed methodology focus on improving the teaching quality and students’ understanding level. In this paper, we have taken the Compiler Design subject and presented the concept map. To understand the effectiveness of the proposed methodology, the students feedback was collected and evaluated using the sign-test and the students’ submitted problems and assignments were evaluated to understand their level. The analysis results show that most of students studied Compiler Design with interest as a result of proposed teaching methodology.","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129351021","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}

{"title":"COVID-19 Diagnosis by Wavelet Entropy and Extreme Learning Machine","authors":"Xue Han, Zuojin Hu, William Wang","doi":"10.4108/eetel.v8i1.2504","DOIUrl":"https://doi.org/10.4108/eetel.v8i1.2504","url":null,"abstract":"In recent years, COVID-19 has spread rapidly among humans. Chest CT is an effective means of diagnosing COVID-19. However, the diagnosis of CT images still depends on the doctor's visual judgment and medical experience. This takes a certain amount of time and may lead to misjudgment. In this paper, a new algorithm for automatic diagnosis of COVID-19 based on chest CT image data was proposed. The algorithm comprehensively uses WE to extract image features, uses ELM for training, and finally passes k-fold CV validation. After evaluating and detecting performance on 296 chest CT images, our proposed method is superior to state-of-the-art approaches in terms of sensitivity, specificity, precision, accuracy, F1, MCC and FMI. ","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125685399","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}

{"title":"Covid-19 Diagnosis by Gray-level Cooccurrence Matrix and Genetic Algorithm","authors":"Xiaoyan Jiang, Mackenzie Brown, Zuojin Hu, Hei-Ran Cheong","doi":"10.4108/eetel.v8i1.2344","DOIUrl":"https://doi.org/10.4108/eetel.v8i1.2344","url":null,"abstract":"Currently, improving the identification of COVID-19 with the help of computer vision and artificial intelligence has received great attention from researchers. This paper proposes a novel method for automatic detection of COVID-19 based on chest CT to help radiologists improve the speed and reliability of tests for diagnosing COVID-19. Our algorithm is a hybrid approach based on the Gray-level Cooccurrence Matrix and Genetic Algorithm. The Gray-level Cooccurrence Matrix (GLCM) was used to extract CT scan image features, GA algorithm was used as an optimizer, and a feedforward neural network was used as a classifier. Finally, we use 296 chest CT scan images to evaluate the detection performance of our proposed method. To more accurately evaluate the accuracy of the algorithm, 10-run 10-fold cross-validation was introduced. Experimental results show that our proposed method outperforms state-of-the-art methods in terms of Sensitivity, Accuracy, F1, MCC, and FMI.","PeriodicalId":298151,"journal":{"name":"EAI Endorsed Trans. e Learn.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116821451","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}