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  • Open Access

    ARTICLE

    A New Four-Parameter Moment Exponential Model with Applications to Lifetime Data

    Abdullah Ali H. Ahmadini1, Amal S. Hassan2, Rokaya E. Mohamed3,*, Shokrya S. Alshqaq4, Heba F. Nagy5

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 131-146, 2021, DOI:10.32604/iasc.2021.017652

    Abstract In this research article, we propose and study a new model the so-called Marshal-Olkin Kumaraswamy moment exponential distribution. The new distribution contains the moment exponential distribution, exponentiated moment exponential distribution, Marshal Olkin moment exponential distribution and generalized exponentiated moment exponential distribution as special sub-models. Some significant properties are acquired such as expansion for the density function and explicit expressions for the moments, generating function, Bonferroni and Lorenz curves. The probabilistic definition of entropy as a measure of uncertainty called Shannon entropy is computed. Some of the numerical values of entropy for different parameters are given. The method of maximum likelihood… More >

  • Open Access

    ARTICLE

    Performance Evaluation of Medical Segmentation Techniques for Cardiac MRI

    Osama S. Faragallah1,*, Ghada Abdel-Aziz2, Walid El-Shafai3, Hala S. El-sayed4, S.F. El-Zoghdy5, Gamal G.N. Geweid6,7

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 15-29, 2021, DOI:10.32604/iasc.2021.017616

    Abstract The process of segmentation of the cardiac image aims to limit the inner and outer walls of the heart to segment all or portions of the organ’s boundaries. Due to its accurate morphological information, magnetic resonance (MR) images are typically used in cardiac segmentation as they provide the best contrast of soft tissues. The data acquired from the resulting cardiac images simplifies not only the laboratory assessment but also other conventional diagnostic techniques that provide several useful measures to evaluate and diagnose cardiovascular disease (CVD). Therefore, scientists have offered numerous segmentation schemes to remedy these issues for producing more accurate… More >

  • Open Access

    ARTICLE

    An Adaptive SAR Despeckling Method Using Cuckoo Search Algorithm

    Memoona Malik*, Iftikhar Azim, Amir Hanif Dar, Sohail Asghar

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 165-182, 2021, DOI:10.32604/iasc.2021.017437

    Abstract Despeckling of SAR imagery is a crucial step prior to their automated interpretation as information extraction from noisy images is a challenging task. Though a huge despeckling literature exists in this regard, there is still a room for improvement in existing techniques. The contemporary despeckling techniques adversely affect image edges during the noise reduction process and are thus responsible for losing the significant image features. Therefore, to preserve important features during the speckle reduction process, a two phase hybrid despeckling filter is proposed in this study. The first phase of the hybrid filter focuses on edge preservation by employing a… More >

  • Open Access

    ARTICLE

    Analysis of Security Testing Techniques

    Omer Bin Tauqeer1, Sadeeq Jan1,*, Alaa Omar Khadidos2, Adil Omar Khadidos3, Fazal Qudus Khan3, Sana Khattak1

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 291-306, 2021, DOI:10.32604/iasc.2021.017260

    Abstract In the past decades, a significant increase has been observed in cyber-attacks on the web-based systems used for financial purposes. Such individual systems often contain security weaknesses, called vulnerabilities that can be exploited for malicious purposes. The exploitation of such vulnerabilities can result in disclosure and manipulation of sensitive data as well as have destructive effects. To protect such systems, security testing is required on a periodic basis. Various detection and assessment techniques have been suggested by developers and researchers to address these security issues. In this paper, we survey the contributions of academia in the field of security testing… More >

  • Open Access

    ARTICLE

    Optimizing the Software Testing Problem Using Search-Based Software Engineering Techniques

    Hissah A. Ben Zayed, Mashael S. Maashi*

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 307-318, 2021, DOI:10.32604/iasc.2021.017239

    Abstract Software testing is a fundamental step in the software development lifecycle. Its purpose is to evaluate the quality of software applications. Regression testing is an important testing methodology in software testing. The purpose of regression testing is to validate the software after each change of its code. This involves adding new test cases to the test suite and running the test suite as the software changes, making the test suite larger. The cost and time of the project are affected by the test suite size. The challenge is to run regression testing with a smaller number of test cases and… More >

  • Open Access

    ARTICLE

    Key Frame Extraction of Surveillance Video Based on Frequency Domain Analysis

    Yunzuo Zhang1,*, Shasha Zhang1, Jiayu Zhang1, Kaina Guo1, Zhaoquan Cai2

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 259-272, 2021, DOI:10.32604/iasc.2021.017200

    Abstract Video key frame extraction, reputed as an essential step in video analysis and content-based video retrieval, and meanwhile, also serves as the basis and premise of generating video synopsis. Video key frame extraction means extracting the meaningful parts of the video by analyzing their content and structure to form a concise and semantically expressive summary. Up to now, people have achieved many research results in key frame extraction. Nevertheless, because the surveillance video has no specific structure, such as news, sports games, and other videos, it is not accurate enough to directly extract the key frame with the existing effective… More >

  • Open Access

    ARTICLE

    Chinese Q&A Community Medical Entity Recognition with Character-Level Features and Self-Attention Mechanism

    Pu Han1,2, Mingtao Zhang1, Jin Shi3, Jinming Yang4, Xiaoyan Li5,*

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 55-72, 2021, DOI:10.32604/iasc.2021.017021

    Abstract With the rapid development of Internet, the medical Q&A community has become an important channel for people to obtain and share medical and health knowledge. Online medical entity recognition (OMER), as the foundation of medical and health information extraction, has attracted extensive attention of researchers in recent years. In order to further improve the research progress of Chinese OMER, LSTM-Att-Med model is proposed in this paper to capture more external semantic features and important information. First, Word2vec is used to generate the character-level vectors with semantic features on the basis of the unlabeled corpus in the medical domain and open… More >

  • Open Access

    ARTICLE

    Adaptive Multi-Layer Selective Ensemble Least Square Support Vector Machines with Applications

    Gang Yu1,4,5, Jian Tang2,*, Jian Zhang3, Zhonghui Wang6

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 273-290, 2021, DOI:10.32604/iasc.2021.016981

    Abstract Kernel learning based on structure risk minimum can be employed to build a soft measuring model for analyzing small samples. However, it is difficult to select learning parameters, such as kernel parameter (KP) and regularization parameter (RP). In this paper, a soft measuring method is investigated to select learning parameters, which is based on adaptive multi-layer selective ensemble (AMLSEN) and least-square support vector machine (LSSVM). First, candidate kernels and RPs with K and R numbers are preset based on prior knowledge, and candidate sub-sub-models with K*R numbers are constructed through utilizing LSSVM. Second, the candidate sub-sub-models with same KPs and… More >

  • Open Access

    ARTICLE

    Leveraging Convolutional Neural Network for COVID-19 Disease Detection Using CT Scan Images

    Mehedi Masud*, Mohammad Dahman Alshehri, Roobaea Alroobaea, Mohammad Shorfuzzaman

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 1-13, 2021, DOI:10.32604/iasc.2021.016800

    Abstract In 2020, the world faced an unprecedented pandemic outbreak of coronavirus disease (COVID-19), which causes severe threats to patients suffering from diabetes, kidney problems, and heart problems. A rapid testing mechanism is a primary obstacle to controlling the spread of COVID-19. Current tests focus on the reverse transcription-polymerase chain reaction (RT-PCR). The PCR test takes around 4–6 h to identify COVID-19 patients. Various research has recommended AI-based models leveraging machine learning, deep learning, and neural networks to classify COVID-19 and non-COVID patients from chest X-ray and computerized tomography (CT) scan images. However, no model can be claimed as a standard… More >

  • Open Access

    ARTICLE

    Emotional Analysis of Arabic Saudi Dialect Tweets Using a Supervised Learning Approach

    Abeer A. AlFutamani, Heyam H. Al-Baity*

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 89-109, 2021, DOI:10.32604/iasc.2021.016555

    Abstract Social media sites produce a large amount of data and offer a highly competitive advantage for companies when they can benefit from and address data, as data provides a deeper understanding of clients and their needs. This understanding of clients helps in effectively making the correct decisions within the company, based on data obtained from social media websites. Thus, sentiment analysis has become a key tool for understanding that data. Sentiment analysis is a research area that focuses on analyzing people’s emotions and opinions to identify the polarity (e.g., positive or negative) of a given text. Since we need to… More >

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