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  • Open Access


    Ensemble Classifier-Based Features Ranking on Employee Attrition

    Yok-Yen Nguwi*

    Journal on Artificial Intelligence, Vol.4, No.3, pp. 189-199, 2022, DOI:10.32604/jai.2022.034064

    Abstract The departure of good employee incurs direct and indirect cost and impacts for an organization. The direct cost arises from hiring to training of the relevant employee. The replacement time and lost productivity affect the running of business processes. This work presents the use of ensemble classifier to identify important attributes that affects attrition significantly. The data consists of attributes related to job function, education level, satisfaction towards work and working relationship, compensation, and frequency of business travel. Both bagging and boosting classifiers were used for testing. The results show that the selected features (nine selected features) achieve the same… More >

  • Open Access


    X-ray Based COVID-19 Classification Using Lightweight EfficientNet

    Tahani Maazi Almutairi*, Mohamed Maher Ben Ismail, Ouiem Bchir

    Journal on Artificial Intelligence, Vol.4, No.3, pp. 167-187, 2022, DOI:10.32604/jai.2022.032974

    Abstract The world has been suffering from the Coronavirus (COVID-19) pandemic since its appearance in late 2019. COVID-19 spread has led to a drastic increase of the number of infected people and deaths worldwide. Imminent and accurate diagnosis of positive cases emerged as a natural alternative to reduce the number of serious infections and limit the spread of the disease. In this paper, we proposed an X-ray based COVID-19 classification system that aims at diagnosing positive COVID-19 cases. Specifically, we adapted lightweight versions of EfficientNet as backbone of the proposed recognition system. Particularly, lightweight EfficientNet networks were used to build classification… More >

  • Open Access


    Evaluating Neural Dialogue Systems Using Deep Learning and Conversation History

    Inshirah Ali AlMutairi*, Ali Mustafa Qamar

    Journal on Artificial Intelligence, Vol.4, No.3, pp. 155-165, 2022, DOI:10.32604/jai.2022.032390

    Abstract Neural talk models play a leading role in the growing popular building of conversational managers. A commonplace criticism of those systems is that they seldom understand or use the conversation data efficiently. The development of profound concentration on innovations has increased the use of neural models for a discussion display. In recent years, deep learning (DL) models have achieved significant success in various tasks, and many dialogue systems are also employing DL techniques. The primary issues involved in the generation of the dialogue system are acquiring perspectives into instinctual linguistics, comprehension provision, and conversation assessment. In this paper, we mainly… More >

  • Open Access


    Research on Early Warning of Customer Churn Based on Random Forest

    Zizhen Qin, Yuxin Liu, Tianze Zhang*

    Journal on Artificial Intelligence, Vol.4, No.3, pp. 143-154, 2022, DOI:10.32604/jai.2022.031843

    Abstract With the rapid development of interest rate market and big data, the banking industry has shown the obvious phenomenon of “two or eight law”, 20% of the high quality customers occupy most of the bank’s assets, how to prevent the loss of bank credit card customers has become a growing concern for banks. Therefore, it is particularly important to establish a customer churn early warning model. In this paper, we will use the random forest method to establish a customer churn early warning model, focusing on the churn of bank credit card customers and predicting the possibility of future churn… More >

  • Open Access


    Applications Classification of VPN Encryption Tunnel Based on SAE-2dCNN Model

    Jie Luo*, Qingbing Ji, Lvlin Ni

    Journal on Artificial Intelligence, Vol.4, No.3, pp. 133-142, 2022, DOI:10.32604/jai.2022.031800

    Abstract How to quickly and accurately identify applications in VPN encrypted tunnels is a difficult technique. Traditional technologies such as DPI can no longer identify applications in VPN encrypted tunnel. Various VPN protocols make the feature engineering of machine learning extremely difficult. Deep learning has the advantages that feature extraction does not rely on manual labor and has a good early application in classification. This article uses deep learning technology to classify the applications of VPN encryption tunnel based on the SAE-2dCNN model. SAE can effectively reduce the dimensionality of the data, which not only improves the training efficiency of 2dCNN,… More >

  • Open Access


    Deep Learning-Based 3D Instance and Semantic Segmentation: A Review

    Siddiqui Muhammad Yasir1, Hyunsik Ahn2,*

    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 >

  • Open Access


    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 Xiaoyu4,*, 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 >

  • Open Access


    Tibetan Sorting Method Based on Hash Function

    AnJian-CaiRang1,2, Dawei Song3,4,*

    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 >

  • Open Access


    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 >

  • Open Access


    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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