自主智能(英文)最新文献_第2页

Optimal DG allocation by Garra Rufa optimization for power loss reduction Garra Rufa优化DG分配以降低功率损耗

自主智能(英文) Pub Date : 2023-08-23 DOI: 10.32629/jai.v6i3.779

R. K. Chillab, M. Smida, Aqeel S. Jaber, A. Sakly

引用次数: 1

Characterization of ink-based phantoms with deep networks and photoacoustic method 基于深度网络和光声方法的墨水体模表征

自主智能(英文) Pub Date : 2023-08-23 DOI: 10.32629/jai.v6i3.621

Hui Ling Chua, A. Huong, X. Ngu

引用次数: 0

A novel credit scoring system in financial institutions using artificial intelligence technology 一种基于人工智能技术的金融机构信用评分系统

自主智能(英文) Pub Date : 2023-08-22 DOI: 10.32629/jai.v6i2.824

Geethamanikanta Jakka, Amrutanshu Panigrahi, Abhilash Pati, M. N. Das, Jyotsnarani Tripathy

{"title":"A novel credit scoring system in financial institutions using artificial intelligence technology","authors":"Geethamanikanta Jakka, Amrutanshu Panigrahi, Abhilash Pati, M. N. Das, Jyotsnarani Tripathy","doi":"10.32629/jai.v6i2.824","DOIUrl":"https://doi.org/10.32629/jai.v6i2.824","url":null,"abstract":"In order to evaluate a person’s or a company’s creditworthiness, financial institutions must use credit scoring. Traditional credit scoring algorithms frequently rely on manual and rule-based methods, which can be tedious and inaccurate. Recent developments in artificial intelligence (AI) technology have opened up possibilities for creating more reliable and effective credit rating systems. The data are pre-processed, including scaling using the 0–1 normalization method and resolving missing values by imputation. Information gain (IG), gain ratio (GR), and chi-square are three feature selection methodologies covered in the study. While GR normalizes IG by dividing it by the total entropy of the feature, IG quantifies the reduction in total entropy by adding a new feature. Based on chi-squared statistics, the most vital traits are determined using chi-square. This research employs different ML models to develop a hybrid model for credit score prediction. The ML algorithms support vector machine (SVM), neural networks (NNs), decision trees (DTs), random forest (RF), and logistic regression (LR) classifiers are employed here for experiments along with IG, GR, and chi-square feature selection methodologies for credit prediction over Australian and German datasets. The study offers an understanding of the decision-making process for informative characteristics and the functionality of machine learning (ML) in credit prediction tasks. The empirical analysis shows that in the case of the German dataset, the DT with GR feature selection and hyperparameter optimization outperforms SVM and NN with an accuracy of 99.78%. For the Australian dataset, SVM with GR feature selection outperforms NN and DT with an accuracy of 99.98%.","PeriodicalId":70721,"journal":{"name":"自主智能(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41735944","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

Future transportation computing model with trifold algorithm for real-time multipath networks 实时多路径网络未来交通计算模型的三重算法

自主智能(英文) Pub Date : 2023-08-22 DOI: 10.32629/jai.v6i2.618

Bharanidharan Chandrakasan, M. Subramanian, H. Manoharan, S. Selvarajan, Dr Rajanikanth Aluvalu

{"title":"Future transportation computing model with trifold algorithm for real-time multipath networks","authors":"Bharanidharan Chandrakasan, M. Subramanian, H. Manoharan, S. Selvarajan, Dr Rajanikanth Aluvalu","doi":"10.32629/jai.v6i2.618","DOIUrl":"https://doi.org/10.32629/jai.v6i2.618","url":null,"abstract":"Purpose: In the past ten years, research on Intelligent Transportation Systems (ITS) has advanced tremendously in everyday situations to deliver improved performance for transport networks. To prevent problems with vehicular traffic, it is essential that alarm messages be sent on time. The truth is that an ITS system in and of itself could be a feature of a vehicular ad hoc network (VANET), which is a wireless network extension. As a result, a previously investigated path between two nodes might be destroyed over a short period of time. Design: The Time delay-based Multipath Routing (TMR) protocol is presented in this research which efficiently determines a route that is optimal for delivering packets to the target vehicle with the least amount of time delay. Using the TMR method, data flow is reduced, especially for daily communication. As a result, there are few packet retransmissions. Findings: To demonstrate how effective the suggested protocol is, several different protocols, including AOMDV, FF-AOMDV, EGSR, QMR, and ISR, have been used to evaluate the TMR. Simulation outcomes show how well our suggested approach performs when compared to alternative methods. Originality: Our method would accomplish two objectives as a consequence. First, it would increase the speed of data transmission, quickly transfer data packets to the target vehicle, especially warning messages, and prevent vehicular issues like automobile accidents. Second, to relieve network stress and minimize network congestion and data collisions.","PeriodicalId":70721,"journal":{"name":"自主智能(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44792850","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

Indian sign language recognition and search results 印度手语识别和搜索结果

自主智能(英文) Pub Date : 2023-08-22 DOI: 10.32629/jai.v6i3.1000

S. Musale, Kalyani Gargate, Vaishnavi Gulavani, Samruddhi Kadam, S. Kothawade

{"title":"Indian sign language recognition and search results","authors":"S. Musale, Kalyani Gargate, Vaishnavi Gulavani, Samruddhi Kadam, S. Kothawade","doi":"10.32629/jai.v6i3.1000","DOIUrl":"https://doi.org/10.32629/jai.v6i3.1000","url":null,"abstract":"Sign language is a medium of communication for people with hearing and speaking impairment. It uses gestures to convey messages. The proposed system focuses on using sign language in search engines and helping specially-abled people get the information they are looking for. Here, we are using Marathi sign language. Translation systems for Indian sign languages are not much simple and popular as American sign language. Marathi language consists of words with individual letters formed of two letter = Swara + Vyanjan (Mulakshar). Every Vyanjan or Swara individually has a unique sign which can be represented as image or video with still frames. Any letter formed of both Swara and Vyanjan is represented with hand gesture signing the Vyanjan as above and with movement of signed gesture in shape of Swara in Devnagari script. Such letters are represented with videos containing motion and frames in particular sequence. Further the predicted term can be searched on google using the sign search. The proposed system includes three important steps: 1) hand detection; 2) sign recognition using neural networks; 3) fetching search results. Overall, the system has great potential to help individuals with hearing and speaking impairment to access information on the internet through the use of sign language. It is a promising application of machine learning and deep learning techniques.","PeriodicalId":70721,"journal":{"name":"自主智能(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47006751","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

Comparative analysis of various global maximum power point tracking techniques for fuel cell frameworks 燃料电池框架各种全局最大功率点跟踪技术的比较分析

自主智能(英文) Pub Date : 2023-08-18 DOI: 10.32629/jai.v6i2.703

Mohammad Junaid Khan, Rashid Mustafa, Pushparaj Pal

引用次数: 0

Secure transmission of grayscale images with triggered error visual sharing 通过触发错误视觉共享实现灰度图像的安全传输

自主智能(英文) Pub Date : 2023-08-17 DOI: 10.32629/jai.v6i2.957

John Blesswin, S. Mary, Shubhangi Suryawanshi, Vanita G. Kshirsagar, Sarika Y. Pabalkar, Mithra Venkatesan, Catherine Esther Karunya

{"title":"Secure transmission of grayscale images with triggered error visual sharing","authors":"John Blesswin, S. Mary, Shubhangi Suryawanshi, Vanita G. Kshirsagar, Sarika Y. Pabalkar, Mithra Venkatesan, Catherine Esther Karunya","doi":"10.32629/jai.v6i2.957","DOIUrl":"https://doi.org/10.32629/jai.v6i2.957","url":null,"abstract":"In the digital era, data transfer plays a crucial role in various industries such as banking, healthcare, marketing, and social media. Images are widely used as a means of communication. The presence of cyber attackers poses a significant risk to data integrity and security during transmission. According to the cost of data breach report 2021, the healthcare industry has experienced the highest costs associated with data breaches, highlighting the need for robust security measures. Visual cryptography (VC) is a technique used to secure image data during transmission. It involves encrypting the image and dividing it into shares, which are then communicated to the intended recipients. Each individual share does not reveal any classified information. At the destination, the shares are digitally combined to reconstruct the original image. When implementing VC, several factors need to be considered, including security, computational complexity, and the quality of the reconstructed image. In this paper, a new method called progressive meaningful visual cryptography (PMVC) is proposed for transferring secret images. The PMVC method introduces an error instance that triggers meaningful shares generation. The proposed method ensures the quality of the reconstructed image by achieving a peak signal-to-noise ratio (PSNR) of up to 37 dB.","PeriodicalId":70721,"journal":{"name":"自主智能(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47141490","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

An extensive study of facial expression recognition using artificial intelligence techniques with different datasets 使用不同数据集的人工智能技术进行面部表情识别的广泛研究

自主智能(英文) Pub Date : 2023-08-15 DOI: 10.32629/jai.v6i2.631

Sridhar Reddy Karra, Arun L. Kakhandki

{"title":"An extensive study of facial expression recognition using artificial intelligence techniques with different datasets","authors":"Sridhar Reddy Karra, Arun L. Kakhandki","doi":"10.32629/jai.v6i2.631","DOIUrl":"https://doi.org/10.32629/jai.v6i2.631","url":null,"abstract":"Machine and deep learning (DL) algorithms have advanced to a point where a wide range of crucial real-world computer vision problems can be solved. Facial Expression Recognition (FER) is one of these applications; it is the foremost non-verbal intentions and a fascinating study of symmetry. A prevalent application of deep learning has become the area of vision, where facial expression recognition has emerged as one of the most promising new frontiers. Latterly deep learning-based FER models have been plagued by technical problems, including under-fitting and over-fitting. Probably inadequate information is used for training and expressing ideas. With these considerations in mind, this article gives a systematic and complete survey of the most cutting-edge AI strategies and gives a conclusion to address the aforementioned problems. It is also a scheme of classification for existing facial proposals in compact. This survey analyses the structure of the usual FER method and discusses the feasible technologies that may be used in its respective elements. In addition, this study provides a summary of seventeen widely-used FER datasets that reviews functioning novel machine and DL networks suggested by academics and outline their benefits and liability in the context of facial expression acknowledgment based on static replicas. Finally, this study discusses the research obstacles and open consequences of that well-conditioned face expression recognition scheme.","PeriodicalId":70721,"journal":{"name":"自主智能(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41915872","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

Blended learning pedagogy and its implementation in the tertiary education: Bangladesh perspectives 混合学习教学法及其在高等教育中的实施:孟加拉国视角

自主智能(英文) Pub Date : 2023-08-15 DOI: 10.32629/jai.v6i2.744

Shrabonti Mitra, MD. Abdul Malek, Tanzin Sultana, Abhijit Pathak, Md. Jainal Abedin, Khadizatul Kobra, Md. Habib Ullah, Mayeen Uddin Khandaker

{"title":"Blended learning pedagogy and its implementation in the tertiary education: Bangladesh perspectives","authors":"Shrabonti Mitra, MD. Abdul Malek, Tanzin Sultana, Abhijit Pathak, Md. Jainal Abedin, Khadizatul Kobra, Md. Habib Ullah, Mayeen Uddin Khandaker","doi":"10.32629/jai.v6i2.744","DOIUrl":"https://doi.org/10.32629/jai.v6i2.744","url":null,"abstract":"This paper reviews the theoretical foundations and components of blended learning (BL) in higher education globally, analyzing six articles from five countries published between January 2016 and December 2020. The study identified challenges faced by instructors, including workload, timeliness, and lack of academic and technical skills to manage BL. Balancing face-to-face and online learning was also challenging. To address these issues, the importance of staff training, support, and networking was emphasized, proposing a modified BL model for tertiary education in Bangladesh, which could be implemented post-pandemic using a machine-learning approach. The mixed BL model was recommended for Bangladeshi institutions, utilizing machine learning algorithms to facilitate outcome-based learning through technological applications. A preliminary survey of 120 students from BGC Trust University in Bangladesh was conducted using statistical data obtained from machine learning algorithms to explore the applicability of the mixed-learning approach. Machine learning proved beneficial for data analysis, drawing valuable insights for educators and policymakers seeking effective teaching strategies that incorporate technology. This research underscores the potential of machine learning in conducting surveys and analyzing data related to blended learning in tertiary education, offering significant contributions to the field.","PeriodicalId":70721,"journal":{"name":"自主智能(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45979720","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

HDevChaRNet: A deep learning-based model for recognizing offline handwritten devanagari characters HDevChaRNet:一个基于深度学习的离线手写德文字符识别模型

自主智能(英文) Pub Date : 2023-08-15 DOI: 10.32629/jai.v6i2.679

Bharati Yadav, Ajay Indian, Gaurav Meena

引用次数: 0