Journal of Artificial Intelligence

Journal on Artificial Intelligence

ISSN: 2579-0021 (print)
ISSN: 2579-003X (online) Publication Frequency: Quarterly

About the Journal

Artificial Intelligence (AI) techniques have been attracted increasing attention around the world and are now being widely used to solve a whole range of hitherto intractable problems. This journal welcomes foundational and applied papers describing mature work involving AI methods.

Current Issue - Vol.4, No.2, 2022 Most Viewed

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ARTICLE
Predict the Chances of Heart Abnormality in Diabetic Patients Through Machine Learning
Monika Saraswat^*, A. K. Wadhwani, Sulochana Wadhwani
Journal on Artificial Intelligence, Vol.4, No.2, pp. 61-76, 2022, DOI:10.32604/jai.2022.028140
Abstract Today, more families are affected by Diabetes Mellitus (DM) disease on account of its continually increasing occurrence. Most patients remain unknown about their health quality or the DM’s risk factors prior to diagnosis. The medical world has witnessed that individuals are affected by two different diabetes namely a) Type-1 diabetes (T1D), as well as b) Type-2 diabetes (T2D). As Type 2 Diabetes affects the other organs of the body, the proposed system concentrates specifically on Type 2 Diabetes. This work aims to ascertain the cardiac disorder in T2D patients. As of the ECG dataset, the requisite data is gathered it… More
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ARTICLE
Research on Higher Education Collaborative Management Platform Based on Relationship Graph
Wu Aiyan^*
Journal on Artificial Intelligence, Vol.4, No.2, pp. 77-84, 2022, DOI:10.32604/jai.2022.028511
Abstract According to the current problems of higher education management informatization, this paper puts forward a development scheme of collaborative platform on education management. The main technology includes three parts. First, integrate the distributed database and use two-tier linked list to realize dynamic data access. Second, the relation graph is used to display the data of each student, so as to realize the visual sharing of data. Third, realize the collaborative information security mechanism from three aspects to ensure the legal sharing of data. Finally, the platform development is completed with Java. It can help to improve the effectiveness of educating… More
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ARTICLE
Tibetan Sorting Method Based on Hash Function
AnJian-CaiRang^1,2, Dawei Song^3,4,*
Journal on Artificial Intelligence, Vol.4, No.2, pp. 85-98, 2022, DOI:10.32604/jai.2022.029141
Abstract Sorting the Tibetan language quickly and accurately requires first identifying the component elements that make up Tibetan syllables and then sorting by the priority of the component. Based on the study of Tibetan text structure, grammatical rules and syllable structure, we present a structure-based Tibetan syllable recognition method that uses syllable structure instead of grammar. This method avoids complicated Tibetan grammar and recognizes the components of Tibetan syllables simply and quickly. On the basis of identifying the components of Tibetan syllables, a Tibetan syllable sorting algorithm that conforms to the language sorting rules is proposed. The core of the Tibetan… More
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REVIEW
Deep Learning-Based 3D Instance and Semantic Segmentation: A Review
Siddiqui Muhammad Yasir¹, Hyunsik Ahn^2,*
Journal on Artificial Intelligence, Vol.4, No.2, pp. 99-114, 2022, DOI:10.32604/jai.2022.031235
Abstract The process of segmenting point cloud data into several homogeneous areas with points in the same region having the same attributes is known as 3D segmentation. Segmentation is challenging with point cloud data due to substantial redundancy, fluctuating sample density and lack of apparent organization. The research area has a wide range of robotics applications, including intelligent vehicles, autonomous mapping and navigation. A number of researchers have introduced various methodologies and algorithms. Deep learning has been successfully used to a spectrum of 2D vision domains as a prevailing A.I. methods. However, due to the specific problems of processing point clouds… More
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ARTICLE
Research on the Dissemination and Influencing Factors of Big Data and Artificial Intelligence Related Courses in Colleges and Universities-Taking MOOC as an Example
Zhu Junyan¹, Min Yuguo², Li Yudi³, Chen Xiaoyu^4,*, Zhou Yu⁵
Journal on Artificial Intelligence, Vol.4, No.2, pp. 115-132, 2022, DOI:10.32604/jai.2022.030353
Abstract The rapid development of information technologies such as artificial intelligence, Internet and big data has promoted the deep integration of technology and education, especially the rise of large-scale online courses, which provides a great opportunity for curriculum teaching reform in colleges and universities. At the same time, artificial intelligence, as a cutting-edge technology, has good development prospects and has become a popular professional course in colleges and universities, artificial intelligence technology has become the focus of subject education in many universities. The combination of online education and AI courses will also greatly enhance the enthusiasm of users and expand the… More
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ARTICLE
Survey of Knowledge Graph Approaches and Applications
Hangjun Zhou¹, Tingting Shen^{1, *}, Xinglian Liu¹, Yurong Zhang¹, Peng Guo^{1, 2}, Jianjun Zhang³
Journal on Artificial Intelligence, Vol.2, No.2, pp. 89-101, 2020, DOI:10.32604/jai.2020.09968
Abstract With the advent of the era of big data, knowledge engineering has received extensive attention. How to extract useful knowledge from massive data is the key to big data analysis. Knowledge graph technology is an important part of artificial intelligence, which provides a method to extract structured knowledge from massive texts and images, and has broad application prospects. The knowledge base with semantic processing capability and open interconnection ability can be used to generate application value in intelligent information services such as intelligent search, intelligent question answering and personalized recommendation. Although knowledge graph has been applied to various systems, the… More
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ARTICLE
Sentiment Analysis Using Deep Learning Approach
Peng Cen¹, Kexin Zhang¹, Desheng Zheng^{1, *}
Journal on Artificial Intelligence, Vol.2, No.1, pp. 17-27, 2020, DOI:10.32604/jai.2020.010132
Abstract Deep learning has made a great breakthrough in the field of speech and image recognition. Mature deep learning neural network has completely changed the field of nat ural language processing (NLP). Due to the enormous amount of data and opinions being produced, shared and transferred everyday across the Internet and other media, sentiment analysis has become one of the most active research fields in natural language processing. This paper introduces three deep learning networks applied in IMDB movie reviews sent iment analysis. Dataset was divided to 50% positive reviews and 50% negative reviews. Recurrent Neural Network (RNN) and Long Short-Term… More
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ARTICLE
An Entropy-Based Model for Recommendation of Taxis’ Cruising Route
Yizhi Liu^{1, 2}, Xuesong Wang^{1, 2}, Jianxun Liu^{1, 2, *}, Zhuhua Liao^{1, 2}, Yijiang Zhao^{1, 2}, Jianjun Wang^{1, 2}
Journal on Artificial Intelligence, Vol.2, No.3, pp. 137-148, 2020, DOI:10.32604/jai.2020.010620
Abstract Cruising route recommendation based on trajectory mining can improve taxidrivers' income and reduce energy consumption. However, existing methods mostly recommend pick-up points for taxis only. Moreover, their performance is not good enough since there lacks a good evaluation model for the pick-up points. Therefore, we propose an entropy-based model for recommendation of taxis' cruising route. Firstly, we select more positional attributes from historical pick-up points in order to obtain accurate spatial-temporal features. Secondly, the information entropy of spatial-temporal features is integrated in the evaluation model. Then it is applied for getting the next pick-up points and further recommending a series… More
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ARTICLE
Impolite Pedestrian Detection by Using Enhanced YOLOv3-Tiny
Yanming Wang^{1, 2, 3}, Kebin Jia^{1, 2, 3}, Pengyu Liu^{1, 2, 3, *}
Journal on Artificial Intelligence, Vol.2, No.3, pp. 113-124, 2020, DOI:10.32604/jai.2020.010137
Abstract In recent years, the problem of “Impolite Pedestrian” in front of the zebra crossing has aroused widespread concern from all walks of life. The traffic sector’s governance measures have become more serious. The traditional way of governance is onsite law enforcement, which requires a lot of manpower and material resources and is low efficiency. An enhanced YOLOv3-tiny model is proposed for pedestrians and vehicle detection in traffic monitoring. By modifying the backbone network structure of YOLOv3- tiny model, introducing deep detachable convolution operation, and designing the basic residual block unit of the network, the feature extraction ability of the backbone… More
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ARTICLE
Research on Intelligent Technology Management and Service Platform
Ning Chen¹, Hui Li², Xinxin Fan^{3, 4}, Weiliang Kong¹, Yonghong Xie^{3, 4, *}
Journal on Artificial Intelligence, Vol.2, No.3, pp. 149-155, 2020, DOI:10.32604/jai.2020.09888
Abstract In recent years, there are some problems in science and technology management, such as untimely task supervision and independent information system, which makes it difficult to achieve accurate, quantitative and standardized management. The storage of scientific research test data is scattered, and there are many deficiencies in the management, promotion and use of existing intellectual property. In this paper, on the basis of the knowledge economy, intelligence economy under the conditions of knowledge management concept and cutting-edge technology, technology management and service management related data, information, knowledge, method of blend together. Based on science and technology management, knowledge management as… More
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ARTICLE
Vehicle Target Detection Method Based on Improved SSD Model
Guanghui Yu¹, Honghui Fan¹, Hongyan Zhou¹, Tao Wu¹, Hongjin Zhu^{1, *}
Journal on Artificial Intelligence, Vol.2, No.3, pp. 125-135, 2020, DOI:10.32604/jai.2020.010501
Abstract When we use traditional computer vision Inspection technology to locate the vehicles, we find that the results were unsatisfactory, because of the existence of diversified scenes and uncertainty. So, we present a new method based on improved SSD model. We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model. Meanwhile, the new method optimizes the loss function, such as the loss function of predicted offset, and makes the loss function drop more smoothly near zero points. In addition, the new method improves cross entropy loss function of category prediction,… More
Views:1517 Downloads:1095 Cited by:4 Download PDF