Mortality prediction has a role to play in the development of a descriptive measure of the quality of care that provides a fair and equitable means of comparing and evaluating hospitals. This article describes a study of a medical text analysis algorithm for mortality prediction that used big data in the form of unstructured medical notes. The article describes the concept of using text mining technology for medical systems, a method for preprocessing medical data to predict patient mortality, an algorithm for predicting patient deaths based on the logistic regression classifier and presents a software module for implementing the proposed algorithm.
{"title":"Research and implementation of the medical text analysis algorithm for predicting mortality","authors":"Zhenisgul Rakhmetullina, Saule Belginova, Alibekkyzy Karlygash, Aigerim Ismukhamedova, Shynar Tezekpaeva","doi":"10.11591/ijeecs.v34.i3.pp1965-1977","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp1965-1977","url":null,"abstract":"Mortality prediction has a role to play in the development of a descriptive measure of the quality of care that provides a fair and equitable means of comparing and evaluating hospitals. This article describes a study of a medical text analysis algorithm for mortality prediction that used big data in the form of unstructured medical notes. The article describes the concept of using text mining technology for medical systems, a method for preprocessing medical data to predict patient mortality, an algorithm for predicting patient deaths based on the logistic regression classifier and presents a software module for implementing the proposed algorithm.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"47 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141232489","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 : 2024-06-01DOI: 10.11591/ijeecs.v34.i3.pp2045-2054
Ferdi Ahmed Yassine, Ghazli Abdelkader
Advances in the fields of neuroscience and computer science have greatly enhanced the human brain’s ability to communicate and interact with the surrounding environment. In addition, recent steps in machine learning (ML) have increased the use of electroencephalography (EEG)-based BCIs for artificial intelligence (AI) applications. The prevailing challenge in recording EEG sensor data is that the captured signals are mixed with noise, which makes their effective use difficult. Therefore, strengthening the classification stage becomes extremely important and plays a major role in addressing this problem. In this study, we chose five most widely used classification models that obtained the best results in this field and tested them on two open-source databases. We also focused on improving the hyperparameters of each algorithm to obtain best results. Our results indicate excellent results on the first dataset and acceptable for most models on the second, while RF showed superior performance on both with an accuracy of 100% on the first dataset and 86.47% on the second. This was achieved with the lowest training costs, and better performance compared to previous works we evaluated that used the same databases. These results provide valuable insights and advance the development of brain-computer interface (BCI) technology and design.
{"title":"Enhancing EEG-based brain-computer interface systems through efficient machine learning classification techniques","authors":"Ferdi Ahmed Yassine, Ghazli Abdelkader","doi":"10.11591/ijeecs.v34.i3.pp2045-2054","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp2045-2054","url":null,"abstract":"Advances in the fields of neuroscience and computer science have greatly enhanced the human brain’s ability to communicate and interact with the surrounding environment. In addition, recent steps in machine learning (ML) have increased the use of electroencephalography (EEG)-based BCIs for artificial intelligence (AI) applications. The prevailing challenge in recording EEG sensor data is that the captured signals are mixed with noise, which makes their effective use difficult. Therefore, strengthening the classification stage becomes extremely important and plays a major role in addressing this problem. In this study, we chose five most widely used classification models that obtained the best results in this field and tested them on two open-source databases. We also focused on improving the hyperparameters of each algorithm to obtain best results. Our results indicate excellent results on the first dataset and acceptable for most models on the second, while RF showed superior performance on both with an accuracy of 100% on the first dataset and 86.47% on the second. This was achieved with the lowest training costs, and better performance compared to previous works we evaluated that used the same databases. These results provide valuable insights and advance the development of brain-computer interface (BCI) technology and design.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"70 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141230947","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 : 2024-06-01DOI: 10.11591/ijeecs.v34.i3.pp1814-1822
Rabie Mahdaoui, Manar Sais, J. Abouchabaka, N. Rafalia
Distributed storage systems play a pivotal role in modern data-intensive applications, with Hadoop distributed file system (HDFS) being a prominent example. However, optimizing the efficiency of such systems remains a complex challenge. This research paper presents a novel approach to enhance the efficiency of distributed storage by leveraging multi-agent systems (MAS). Our research is centered on enhancing the efficiency of the HDFS by incorporating intelligent agents that can dynamically assign storage tasks to nodes based on their performance characteristics. Utilizing a decentralized decision-making framework, the suggested approach based on MAS considers the real-time performance of nodes and allocates storage tasks adaptively. This strategy aims to alleviate performance bottlenecks and minimize data transfer latency. Through extensive experimental evaluation, we demonstrate the effectiveness of our approach in improving HDFS performance in terms of data storage, retrieval, and overall system efficiency. The results reveal significant reductions in job execution times and enhanced resource utilization, there by offering a promising avenue for enhancing the efficiency of distributed storage systems.
分布式存储系统在现代数据密集型应用中发挥着举足轻重的作用，Hadoop 分布式文件系统（HDFS）就是一个突出的例子。然而，优化此类系统的效率仍然是一项复杂的挑战。本研究论文提出了一种利用多代理系统（MAS）提高分布式存储效率的新方法。我们的研究重点是通过纳入智能代理来提高 HDFS 的效率，这些智能代理可以根据节点的性能特征将存储任务动态分配给节点。基于 MAS 的建议方法利用分散决策框架，考虑节点的实时性能，并自适应地分配存储任务。这一策略旨在缓解性能瓶颈，最大限度地减少数据传输延迟。通过广泛的实验评估，我们证明了我们的方法在提高 HDFS 的数据存储、检索和整体系统效率方面的有效性。结果表明，作业执行时间大幅缩短，资源利用率得到提高，从而为提高分布式存储系统的效率提供了一条大有可为的途径。
{"title":"Enhancing Hadoop distributed storage efficiency using multi-agent systems","authors":"Rabie Mahdaoui, Manar Sais, J. Abouchabaka, N. Rafalia","doi":"10.11591/ijeecs.v34.i3.pp1814-1822","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp1814-1822","url":null,"abstract":"Distributed storage systems play a pivotal role in modern data-intensive applications, with Hadoop distributed file system (HDFS) being a prominent example. However, optimizing the efficiency of such systems remains a complex challenge. This research paper presents a novel approach to enhance the efficiency of distributed storage by leveraging multi-agent systems (MAS). Our research is centered on enhancing the efficiency of the HDFS by incorporating intelligent agents that can dynamically assign storage tasks to nodes based on their performance characteristics. Utilizing a decentralized decision-making framework, the suggested approach based on MAS considers the real-time performance of nodes and allocates storage tasks adaptively. This strategy aims to alleviate performance bottlenecks and minimize data transfer latency. Through extensive experimental evaluation, we demonstrate the effectiveness of our approach in improving HDFS performance in terms of data storage, retrieval, and overall system efficiency. The results reveal significant reductions in job execution times and enhanced resource utilization, there by offering a promising avenue for enhancing the efficiency of distributed storage systems.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"10 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141233196","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 : 2024-06-01DOI: 10.11591/ijeecs.v34.i3.pp1593-1602
Yasmina Zine, M. Boumehed, N. H. Said
Reversible data hiding within encrypted images reversible data hiding in encrypted images (RDH-EI) is a highly effective technique for image processing in the field of encryption. This paper, propose a RDH-EI technique, which utilizes bit-plane compression and various image scanning directions to generate vacant space for data embedding, referred to as vacating room. Initially, the prediction error of the pre-processed image is computed. Subsequently, each bit-plane image is converted into a bit-stream by following the pixel scan order employed before compression. The compressed image is then encrypted employing a stream cipher. Through the process of substitution, the secret data and additional information are incorporated into the acquired image without any knowledge of the original content or the encrypted key. Finally, the generated image is transmitted or archived. The experiments provide evidence that the proposed method surpasses the most advanced methods currently available.
{"title":"Encrypted image processing using compression and reversible data hiding","authors":"Yasmina Zine, M. Boumehed, N. H. Said","doi":"10.11591/ijeecs.v34.i3.pp1593-1602","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp1593-1602","url":null,"abstract":"Reversible data hiding within encrypted images reversible data hiding in encrypted images (RDH-EI) is a highly effective technique for image processing in the field of encryption. This paper, propose a RDH-EI technique, which utilizes bit-plane compression and various image scanning directions to generate vacant space for data embedding, referred to as vacating room. Initially, the prediction error of the pre-processed image is computed. Subsequently, each bit-plane image is converted into a bit-stream by following the pixel scan order employed before compression. The compressed image is then encrypted employing a stream cipher. Through the process of substitution, the secret data and additional information are incorporated into the acquired image without any knowledge of the original content or the encrypted key. Finally, the generated image is transmitted or archived. The experiments provide evidence that the proposed method surpasses the most advanced methods currently available.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"12 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141233570","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 : 2024-06-01DOI: 10.11591/ijeecs.v34.i3.pp1718-1729
Clive Lai Yi Cheng, Goh Eg Su, J. Ahmad, Tole Sutikno
The augmented reality (AR) technology had been proliferating for years. However, the implementation of AR technology still has room to be explored, especially in the form of cultural heritage preservation. The aim of this study is to enhance AR technology in game-based cultural heritage and history preservation in Sarawak, as well as supplement the gamified experiences in learning James Brooke’s history. Three research objectives are proposed: to design an AR game prototype for the history of James Brooke; to develop an AR game prototype with a collaborative learning element; and to evaluate an AR game prototype for enhancing cultural heritage preservation. This study proposes a game-based prototype that contains AR markers to assign each with different game features. Furthermore, collaborative learning theory is enhanced through AR experiences with multiplayer support. The game-based prototype is evaluated by a group of participants through prototype measuring and testing. The participants feel mediocre about the challenge and knowledge factors of the prototype. Overall, this study highlights the enhancement of cultural heritage preservation through AR game-based experiences intensively learned from James Brooke’s history in Sarawak. These implementations have an apparent promising contribution to make in protecting the available cultural heritage in Sarawak and extensively to the country’s cultural heritage preservation.
多年来，增强现实（AR）技术一直在蓬勃发展。然而，AR 技术的应用仍有探索空间，尤其是在文化遗产保护方面。本研究的目的是加强 AR 技术在沙捞越州以游戏为基础的文化遗产和历史保护中的应用，并补充学习詹姆斯-布鲁克历史的游戏化体验。本研究提出了三个研究目标：为詹姆斯-布鲁克的历史设计一个 AR 游戏原型；开发一个具有协作学习元素的 AR 游戏原型；以及评估一个用于加强文化遗产保护的 AR 游戏原型。本研究提出了一个基于游戏的原型，其中包含 AR 标记，每个标记都具有不同的游戏功能。此外，还通过支持多人游戏的 AR 体验增强了协作学习理论。一组参与者通过原型测量和测试对基于游戏的原型进行了评估。参与者对原型的挑战性和知识因素感觉一般。总之，本研究强调了通过从沙捞越詹姆斯-布鲁克的历史中深入学习的基于 AR 的游戏体验来加强文化遗产保护。这些实施方案在保护沙捞越现有文化遗产和广泛促进国家文化遗产保护方面做出了明显的贡献。
{"title":"Game-based augmented reality learning of Sarawak history in enhancing cultural heritage preservation","authors":"Clive Lai Yi Cheng, Goh Eg Su, J. Ahmad, Tole Sutikno","doi":"10.11591/ijeecs.v34.i3.pp1718-1729","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp1718-1729","url":null,"abstract":"The augmented reality (AR) technology had been proliferating for years. However, the implementation of AR technology still has room to be explored, especially in the form of cultural heritage preservation. The aim of this study is to enhance AR technology in game-based cultural heritage and history preservation in Sarawak, as well as supplement the gamified experiences in learning James Brooke’s history. Three research objectives are proposed: to design an AR game prototype for the history of James Brooke; to develop an AR game prototype with a collaborative learning element; and to evaluate an AR game prototype for enhancing cultural heritage preservation. This study proposes a game-based prototype that contains AR markers to assign each with different game features. Furthermore, collaborative learning theory is enhanced through AR experiences with multiplayer support. The game-based prototype is evaluated by a group of participants through prototype measuring and testing. The participants feel mediocre about the challenge and knowledge factors of the prototype. Overall, this study highlights the enhancement of cultural heritage preservation through AR game-based experiences intensively learned from James Brooke’s history in Sarawak. These implementations have an apparent promising contribution to make in protecting the available cultural heritage in Sarawak and extensively to the country’s cultural heritage preservation.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"31 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141234782","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 : 2024-06-01DOI: 10.11591/ijeecs.v34.i3.pp1643-1653
Fredelino A. Galleto Jr., Aaron Don M. Africa, Alyssa Joie F. Tablada, John Ernesto G. Amadora Jr., Ira Third L. Burgos, Alliyah Mae K. Borebor, Rocelle Andrea S. Belandres, Rafael Dominic L. Montaño
In this comparative study, seven different microstrip antenna shapes, including rectangular, elliptical, triangular, inset fed, H-notch, and E-notch, were observed and analyzed, focusing on their suitability for global positioning system (GPS) application in microsatellites. To enable meaningful comparison, the study utilized the optimal resonant frequency in GPS applications, which is 1.57542 GHz. All the antenna designs have been generated using MATLAB’s Antenna Toolbox and are 100% efficient under ideal conditions with zero polarization loss, which is assumed in the link budget analysis. The results show that each antenna shape has been found to offer distinct advantages and limitations. Along with this, the circular and elliptical patch antenna presented a well-balanced performance, which is suitable for GPS applications. However, the elliptical shape falls behind the circular shape, which was determined to be the most optimal choice for GPS application, providing excellent isotropic antenna gain, return loss, voltage standing wave ratio (VSWR), and strong link budget analysis results.
{"title":"Microstrip antenna system for communication capabilities applications","authors":"Fredelino A. Galleto Jr., Aaron Don M. Africa, Alyssa Joie F. Tablada, John Ernesto G. Amadora Jr., Ira Third L. Burgos, Alliyah Mae K. Borebor, Rocelle Andrea S. Belandres, Rafael Dominic L. Montaño","doi":"10.11591/ijeecs.v34.i3.pp1643-1653","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp1643-1653","url":null,"abstract":"In this comparative study, seven different microstrip antenna shapes, including rectangular, elliptical, triangular, inset fed, H-notch, and E-notch, were observed and analyzed, focusing on their suitability for global positioning system (GPS) application in microsatellites. To enable meaningful comparison, the study utilized the optimal resonant frequency in GPS applications, which is 1.57542 GHz. All the antenna designs have been generated using MATLAB’s Antenna Toolbox and are 100% efficient under ideal conditions with zero polarization loss, which is assumed in the link budget analysis. The results show that each antenna shape has been found to offer distinct advantages and limitations. Along with this, the circular and elliptical patch antenna presented a well-balanced performance, which is suitable for GPS applications. However, the elliptical shape falls behind the circular shape, which was determined to be the most optimal choice for GPS application, providing excellent isotropic antenna gain, return loss, voltage standing wave ratio (VSWR), and strong link budget analysis results.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"26 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141234819","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 : 2024-06-01DOI: 10.11591/ijeecs.v34.i3.pp1787-1799
Hamid El Bourakkadi, Abdelhakim Chemlal, Hassan Tabti, Mourad Kattass, A. Jarjar, A. Benazzi
This paper presents an improved method for encrypting color images, surpassing the effectiveness of genetic crossover and substitution operations. The technique incorporates dynamic random functions to enhance the integrity of the resulting vector, increasing temporal complexity to thwart potential attacks. The improvement involves integrating genetic crossover and utilizing two extensive pseudorandom replacement tables derived from established chaotic maps in cryptography. Following the controlled vectorization of the original image, our approach initiates with a first genetic crossover inspired by deoxyribonucleic acid (DNA) behavior at the pixel level. This genetic crossover is succeeded by a confusion-diffusion lap, reinforcing the connection between encrypted pixels and their neighboring counterparts. The confusion-diffusion process employs dynamic pseudorandom affine functions at the pixel level. Then a second genetic crossover operator is applied. Simulations conducted on a diverse set of images with varying sizes and formats showcase the robustness of our method against statistical, brute-force, and differential attacks.
{"title":"Improved vigenere using affine functions surrounded by two genetic crossovers for image encryption","authors":"Hamid El Bourakkadi, Abdelhakim Chemlal, Hassan Tabti, Mourad Kattass, A. Jarjar, A. Benazzi","doi":"10.11591/ijeecs.v34.i3.pp1787-1799","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp1787-1799","url":null,"abstract":"This paper presents an improved method for encrypting color images, surpassing the effectiveness of genetic crossover and substitution operations. The technique incorporates dynamic random functions to enhance the integrity of the resulting vector, increasing temporal complexity to thwart potential attacks. The improvement involves integrating genetic crossover and utilizing two extensive pseudorandom replacement tables derived from established chaotic maps in cryptography. Following the controlled vectorization of the original image, our approach initiates with a first genetic crossover inspired by deoxyribonucleic acid (DNA) behavior at the pixel level. This genetic crossover is succeeded by a confusion-diffusion lap, reinforcing the connection between encrypted pixels and their neighboring counterparts. The confusion-diffusion process employs dynamic pseudorandom affine functions at the pixel level. Then a second genetic crossover operator is applied. Simulations conducted on a diverse set of images with varying sizes and formats showcase the robustness of our method against statistical, brute-force, and differential attacks.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"42 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141232723","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 : 2024-06-01DOI: 10.11591/ijeecs.v34.i3.pp1915-1923
Adil Marouan, Morad Badrani, Nabil Kannouf, Abderrahim Zannou, Abdelaziz Chetouani
The blockchain-based electronic voting (e-voting) system, offers universities a safe, easy-to-use platform that enhances accuracy and integrity. Despite that, it is challenging to integrate the blockchain-based e-voting system with current platforms and private data. Managing latency is another requirement during the blockchain transactions (votes/elections). In this work, we suggested a novel system that uses smart contracts on the consortium blockchain to address these constraints. The voters and electors in a university can vote and elect respecting the rules established in smart contracts. The miners validate transactions using proof of work (PoW) and proof of stake (PoS). Data integrity and voter validity are ensured via the SHA-256 hash algorithm and the ECDSA signature. The implementation results demonstrate that the suggested method works better than the state-of-the-art. exceeds the state-of-the-art in terms of gas cost and execution time.
{"title":"Blockchain-based e-voting system in a university","authors":"Adil Marouan, Morad Badrani, Nabil Kannouf, Abderrahim Zannou, Abdelaziz Chetouani","doi":"10.11591/ijeecs.v34.i3.pp1915-1923","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp1915-1923","url":null,"abstract":"The blockchain-based electronic voting (e-voting) system, offers universities a safe, easy-to-use platform that enhances accuracy and integrity. Despite that, it is challenging to integrate the blockchain-based e-voting system with current platforms and private data. Managing latency is another requirement during the blockchain transactions (votes/elections). In this work, we suggested a novel system that uses smart contracts on the consortium blockchain to address these constraints. The voters and electors in a university can vote and elect respecting the rules established in smart contracts. The miners validate transactions using proof of work (PoW) and proof of stake (PoS). Data integrity and voter validity are ensured via the SHA-256 hash algorithm and the ECDSA signature. The implementation results demonstrate that the suggested method works better than the state-of-the-art. exceeds the state-of-the-art in terms of gas cost and execution time.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141234741","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}
Tourism has become an integral part of social and economic development across the globe. It does not only serve as a recreational activity but also as a source of revenue for the nation. The paper systematically explores the potential enhancements in the tourist experience through cutting-edge technology. Employing deep learning methods, the study specifically concentrates on refining augmented reality encounters for visitors. The proposed approach utilizes deep learning algorithms to optimize and tailor tourists’ augmented reality experiences, addressing current sectoral challenges like customization and engagement shortcomings. The methodology’s selection is predicated on it is capability to elevate user experience, accurately identify objects, offer visual guided tours, integrate historical context, and ultimately propel augmented reality adoption in tourism. Notably, the investigation culminates in a noteworthy average accuracy of 99% when incorporating deep learning to enhance augmented reality in tourism.
{"title":"Revolutionization of augmented reality in tourism via deep learning","authors":"Yasmin Chuupa Essa, Saumya Chaturvedi, Shiraz Khurana","doi":"10.11591/ijeecs.v34.i3.pp2055-2064","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp2055-2064","url":null,"abstract":"Tourism has become an integral part of social and economic development across the globe. It does not only serve as a recreational activity but also as a source of revenue for the nation. The paper systematically explores the potential enhancements in the tourist experience through cutting-edge technology. Employing deep learning methods, the study specifically concentrates on refining augmented reality encounters for visitors. The proposed approach utilizes deep learning algorithms to optimize and tailor tourists’ augmented reality experiences, addressing current sectoral challenges like customization and engagement shortcomings. The methodology’s selection is predicated on it is capability to elevate user experience, accurately identify objects, offer visual guided tours, integrate historical context, and ultimately propel augmented reality adoption in tourism. Notably, the investigation culminates in a noteworthy average accuracy of 99% when incorporating deep learning to enhance augmented reality in tourism.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"41 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141232668","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 : 2024-06-01DOI: 10.11591/ijeecs.v34.i3.pp1582-1592
Manh-Hung Ha, Duc-Chinh Nguyen, Manh-Tuan Do, Dinh-Thai Kim, X. Le, Ngoc-Thanh Pham
Deep learning plays a crucial role in addressing the challenge of plant disease identification in the field of agriculture. Detecting diseases in plants requires extensive effort, along with a comprehensive understanding of various plant diseases and increased processing time. Balancing both speed and accuracy in predicting leaf diseases in plants can significantly improve crop production and reduce environmental damage. In this paper, we examined deseases on popular plants in agriculture. We proposed a novel model to predict crop pathology on a feature space of global-local based on transformer aggregation. Paticular, we use refined feature of different layer to correlate semantics from high-level feature and low-level feature. Besides, to capture the extended temporal scale across the entire image, we employ a transformer to discern long-range dependencies among frames. Subsequently, the enhanced features incorporating these dependencies are inputted into a classifier for preliminary crop pathology prediction. The plant village dataset and VietNam strawberry disease (VNStr) dataset were utilized for training and disease classification in the experiments. Extensive experiments show that the proposed method outperforms by 99.18% and 94.05% accuracy in plant village and VNStr, respectivly. The model after being judged was applied on Android devices and therefore is easy to use.
{"title":"Plant pathology identification using local-global feature level based on transformer","authors":"Manh-Hung Ha, Duc-Chinh Nguyen, Manh-Tuan Do, Dinh-Thai Kim, X. Le, Ngoc-Thanh Pham","doi":"10.11591/ijeecs.v34.i3.pp1582-1592","DOIUrl":"https://doi.org/10.11591/ijeecs.v34.i3.pp1582-1592","url":null,"abstract":"Deep learning plays a crucial role in addressing the challenge of plant disease identification in the field of agriculture. Detecting diseases in plants requires extensive effort, along with a comprehensive understanding of various plant diseases and increased processing time. Balancing both speed and accuracy in predicting leaf diseases in plants can significantly improve crop production and reduce environmental damage. In this paper, we examined deseases on popular plants in agriculture. We proposed a novel model to predict crop pathology on a feature space of global-local based on transformer aggregation. Paticular, we use refined feature of different layer to correlate semantics from high-level feature and low-level feature. Besides, to capture the extended temporal scale across the entire image, we employ a transformer to discern long-range dependencies among frames. Subsequently, the enhanced features incorporating these dependencies are inputted into a classifier for preliminary crop pathology prediction. The plant village dataset and VietNam strawberry disease (VNStr) dataset were utilized for training and disease classification in the experiments. Extensive experiments show that the proposed method outperforms by 99.18% and 94.05% accuracy in plant village and VNStr, respectivly. The model after being judged was applied on Android devices and therefore is easy to use.","PeriodicalId":13480,"journal":{"name":"Indonesian Journal of Electrical Engineering and Computer Science","volume":"33 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141231844","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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