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  • Open Access

    ARTICLE

    Constructional Cyber Physical System: An Integrated Model

    Tzer-Long Chen1, Chien-Yun Chang2, Yung-Cheng Yao3, Kuo-Chang Chung4,*

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 73-82, 2021, DOI:10.32604/iasc.2021.015980

    Abstract Artificial intelligence, machine learning, and deep learning have achieved great success in the fields of computer vision and natural language processing, and then extended to various fields, such as biology, chemistry, and civil engineering, including big data in the field of logistics. Therefore, many logistics companies move towards the integration of intelligent transportation systems. Only virtual and physical development can support the sustainable development of the logistics industry. This study aims to: 1.) collect timely information from the block chain, 2.) use deep learning to build a customer database so that sales staff in physical… More >

  • Open Access

    ARTICLE

    Filter-Based Feature Selection and Machine-Learning Classification of Cancer Data

    Mohammed Farsi*

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 83-92, 2021, DOI:10.32604/iasc.2021.015460

    Abstract Microarray cancer data poses many challenges for machine-learning (ML) classification including noisy data, small sample size, high dimensionality, and imbalanced class labels. In this paper, we propose a framework to address these problems by properly utilizing feature-selection techniques. The most important features of the cancer datasets were extracted with Logistic Regression (LR), Chi-2, Random Forest (RF), and LightGBM. These extracted features served as input columns in an applied classification task. This framework’s main advantages are reducing time complexity and the number of irrelevant features for the dataset. For evaluation, the proposed method was compared to… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Language Translation Platform

    Manjur Kolhar*, Abdalla Alameen

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 1-9, 2021, DOI:10.32604/iasc.2021.014995

    Abstract The use of computer-based technologies by non-native Arabic-speaking teachers for teaching native Arabic-speaking students can result in higher learner engagement. In this study, a machine translation (MT) system is developed as a learning technology. The proposed system can be linked to a digital podium and projector to reduce multitasking. A total of 25 students from Prince Sattam Bin Abdulaziz University, Saudi Arabia participated in our experiment and survey related to the use of the proposed technology-enhanced MT system. An important reason for using this framework is to exploit the high service bandwidth (up to several… More >

  • Open Access

    ARTICLE

    Parallel Optimization of Program Instructions Using Genetic Algorithms

    Petre Anghelescu*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3293-3310, 2021, DOI:10.32604/cmc.2021.015495

    Abstract This paper describes an efficient solution to parallelize software program instructions, regardless of the programming language in which they are written. We solve the problem of the optimal distribution of a set of instructions on available processors. We propose a genetic algorithm to parallelize computations, using evolution to search the solution space. The stages of our proposed genetic algorithm are: The choice of the initial population and its representation in chromosomes, the crossover, and the mutation operations customized to the problem being dealt with. In this paper, genetic algorithms are applied to the entire search… More >

  • Open Access

    ARTICLE

    Analyzing Some Elements of Technological Singularity Using Regression Methods

    Ishaani Priyadarshini1,*, Pinaki Ranjan Mohanty2, Chase Cotton1

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3229-3247, 2021, DOI:10.32604/cmc.2021.015250

    Abstract Technological advancement has contributed immensely to human life and society. Technologies like industrial robots, artificial intelligence, and machine learning are advancing at a rapid pace. While the evolution of Artificial Intelligence has contributed significantly to the development of personal assistants, automated drones, smart home devices, etc., it has also raised questions about the much-anticipated point in the future where machines may develop intelligence that may be equal to or greater than humans, a term that is popularly known as Technological Singularity. Although technological singularity promises great benefits, past research works on Artificial Intelligence (AI) systems… More >

  • Open Access

    ARTICLE

    Predicting Drying Performance of Osmotically Treated Heat Sensitive Products Using Artificial Intelligence

    S. M. Atiqure Rahman1,*, Hegazy Rezk2,3, Mohammad Ali Abdelkareem1,4, M. Enamul Hoque5, Tariq Mahbub6, Sheikh Khaleduzzaman Shah7, Ahmed M. Nassef2,8

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3143-3160, 2021, DOI:10.32604/cmc.2021.015048

    Abstract The main goal of this research is to develop and apply a robust Artificial Neural Networks (ANNs) model for predicting the characteristics of the osmotically drying treated potato and apple samples as a model heat-sensitive product in vacuum contact dryer. Concentrated salt and sugar solutions were used as the osmotic solutions at 27C. Series of experiments were performed at various temperatures of 35C, 40C, and 55C for conduction heat input under vacuum ( −760 mm Hg) condition. Some experiments were also performed in a pure vacuum without heat addition. Dimensionless moisture content (DMC), effective moisture… More >

  • Open Access

    ARTICLE

    A Hybrid Artificial Intelligence Model for Skin Cancer Diagnosis

    V. Vidya Lakshmi1,*, J. S. Leena Jasmine2

    Computer Systems Science and Engineering, Vol.37, No.2, pp. 233-245, 2021, DOI:10.32604/csse.2021.015700

    Abstract Melanoma or skin cancer is the most dangerous and deadliest disease. As the incidence and mortality rate of skin cancer increases worldwide, an automated skin cancer detection/classification system is required for early detection and prevention of skin cancer. In this study, a Hybrid Artificial Intelligence Model (HAIM) is designed for skin cancer classification. It uses diverse multi-directional representation systems for feature extraction and an efficient Exponentially Weighted and Heaped Multi-Layer Perceptron (EWHMLP) for the classification. Though the wavelet transform is a powerful tool for signal and image processing, it is unable to detect the intermediate More >

  • Open Access

    ARTICLE

    Social Media and Stock Market Prediction: A Big Data Approach

    Mazhar Javed Awan1,2,*, Mohd Shafry Mohd Rahim2, Haitham Nobanee3,4,5, Ashna Munawar2, Awais Yasin6, Azlan Mohd Zain 7

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2569-2583, 2021, DOI:10.32604/cmc.2021.014253

    Abstract Big data is the collection of large datasets from traditional and digital sources to identify trends and patterns. The quantity and variety of computer data are growing exponentially for many reasons. For example, retailers are building vast databases of customer sales activity. Organizations are working on logistics financial services, and public social media are sharing a vast quantity of sentiments related to sales price and products. Challenges of big data include volume and variety in both structured and unstructured data. In this paper, we implemented several machine learning models through Spark MLlib using PySpark, which More >

  • Open Access

    ARTICLE

    COVID-19 Pandemic Data Predict the Stock Market

    Abdulaziz Almehmadi*

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 451-460, 2021, DOI:10.32604/csse.2021.015309

    Abstract Unlike the 2007–2008 market crash, which was caused by a banking failure and led to an economic recession, the 1918 influenza pandemic triggered a worldwide financial depression. Pandemics usually affect the global economy, and the COVID-19 pandemic is no exception. Many stock markets have fallen over 40%, and companies are shutting down, ending contracts, and issuing voluntary and involuntary leaves for thousands of employees. These economic effects have led to an increase in unemployment rates, crime, and instability. Studying pandemics’ economic effects, especially on the stock market, has not been urgent or feasible until recently.… More >

  • Open Access

    ARTICLE

    Decision Support System Tool for Arabic Text Recognition

    Fatmah Baothman*, Sarah Alssagaff, Bayan Ashmeel

    Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 519-531, 2021, DOI:10.32604/iasc.2021.014828

    Abstract The National Center for Education Statistics study reported that 80% of students change their major or institution at least once before getting a degree, which requires a course equivalency process. This error-prone process varies among disciplines, institutions, regions, and countries and requires effort and time. Therefore, this study aims to overcome these issues by developing a decision support tool called TiMELY for automatic Arabic text recognition using artificial intelligence techniques. The developed tool can process a complete document analysis for several course descriptions in multiple file formats, such as Word, Text, Pages, JPEG, GIF, and… More >

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