Naglaa. F. Soliman^1,*, Samia M. Abd-Alhalem² , Walid El-Shafai² , Salah Eldin S. E. Abdulrahman³, N. Ismaiel³ , El-Sayed M. El-Rabaie² , Abeer D. Algarni¹, Fathi E. Abd El-Samie^1,2

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5907-5927, 2022, DOI:10.32604/cmc.2022.018860 - 11 October 2021

Abstract

Recently, deep learning (DL) became one of the essential tools in bioinformatics. A modified convolutional neural network (CNN) is employed in this paper for building an integrated model for deoxyribonucleic acid (DNA) classification. In any CNN model, convolutional layers are used to extract features followed by max-pooling layers to reduce the dimensionality of features. A novel method based on downsampling and CNNs is introduced for feature reduction. The downsampling is an improved form of the existing pooling layer to obtain better classification accuracy. The two-dimensional discrete transform (2D DT) and two-dimensional random projection (2D RP) methods

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Waqar Hafeez¹, Nazrina Aziz^1,2,*, Zakiyah Zain^1,2, Nur Azulia Kamarudin¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3891-3902, 2022, DOI:10.32604/cmc.2022.019695 - 27 September 2021

Abstract Acceptance sampling is a statistical quality control technique that consists of procedures for sentencing one or more incoming lots of finished products. Acceptance or rejection is based on the inspection of sampled products drawn randomly from the lot. The theory of previous acceptance sampling was built upon the assumption that the process from which the lots are produced is stable and the process fraction nonconforming is a constant. Process variability is inevitable due to random fluctuations, which may inadvertently lead to quality variation. As an alternative to traditional sampling plans, Bayesian approach can be used… More >

Waqar Hafeez¹, Nazrina Aziz^1,2,*, Zakiyah Zain^1,2, Nur Azulia Kamarudin¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4185-4198, 2022, DOI:10.32604/cmc.2022.018146 - 27 September 2021

Abstract Acceptance sampling is a well-established statistical technique in quality assurance. Acceptance sampling is used to decide, acceptance or rejection of a lot based on the inspection of its random sample. Experts concur that the Bayesian approach is the best approach to make a correct decision, when historical knowledge is available. This paper suggests a Bayesian new group chain sampling plan (BNGChSP) to estimate average probability of acceptance. Binomial distribution function is used to differentiate between defective and non-defective products. Beta distribution is considered as a suitable prior distribution. Derivation is completed for the estimation of More >

Saman Hanif Shahbaz, Muhammad Qaiser Shahbaz^*

Computer Systems Science and Engineering, Vol.40, No.1, pp. 287-297, 2022, DOI:10.32604/csse.2022.018219 - 26 August 2021

Abstract Product testing is a key ingredient in maintaining the quality of a production process. The production process is considered an efficient process if it is capable of quick identification of faulty products. The items produced by any production process are usually packed and acceptance or rejection of the pack depends upon its conformity to some specified quality level. Generally, the specified quality level is based upon the number of defective items found in the inspected number of items. Such decisions are based upon some rules and usually acceptance of the pack is based upon a… More >

Da Teng¹, Yunwen Feng^1,*, Cheng Lu^1,2, Chengwei Fei², Jiaqi Liu¹, Xiaofeng Xue^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 1029-1049, 2021, DOI:10.32604/cmes.2021.016945 - 08 October 2021

Abstract Turbine blisks are assembled using blades, disks and casings. They can endure complex loads at a high temperature, high pressure and high speed. The safe operation of assembled structures depends on the reliability of each component. Monte Carlo (MC) simulation is commonly used to analyze structural reliability, but this method needs to run thousands of computations. In order to assess the clearance reliability of assembled structures in an efficient and precise manner, the novel Kriging-based decomposed-coordinated (DC) (DCNK) approach is proposed by integrating the DC strategy, the Kriging model and the importance sampling-based Markov chain… More >

Yuji Saito^*, Keigo Yamada, Naoki Kanda, Kumi Nakai, Takayuki Nagata, Taku Nonomura, Keisuke Asai

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 1-30, 2021, DOI:10.32604/cmes.2021.016603 - 24 August 2021

Abstract A vector-measurement-sensor-selection problem in the undersampled and oversampled cases is considered by extending the previous novel approaches: a greedy method based on D-optimality and a noise-robust greedy method in this paper. Extensions of the vector-measurement-sensor selection of the greedy algorithms are proposed and applied to randomly generated systems and practical datasets of flowfields around the airfoil and global climates to reconstruct the full state given by the vector-sensor measurement. More >

Amer I. Al-Omari¹, Amal S. Hassan², Heba F. Nagy², Ayed R. A. Al-Anzi^3,*, Loai Alzoubi¹

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3795-3811, 2021, DOI:10.32604/cmc.2021.019061 - 24 August 2021

Abstract This paper deals with the Bayesian estimation of Shannon entropy for the generalized inverse exponential distribution. Assuming that the observed samples are taken from the upper record ranked set sampling (URRSS) and upper record values (URV) schemes. Formulas of Bayesian estimators are derived depending on a gamma prior distribution considering the squared error, linear exponential and precautionary loss functions, in addition, we obtain Bayesian credible intervals. The random-walk Metropolis-Hastings algorithm is handled to generate Markov chain Monte Carlo samples from the posterior distribution. Then, the behavior of the estimates is examined at various record values. More >

Masoud Muhammed Hassan¹, Adel Sabry Eesa^1,*, Ahmed Jameel Mohammed², Wahab Kh. Arabo¹

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 451-469, 2021, DOI:10.32604/cmc.2021.018280 - 04 June 2021

Abstract Learning from imbalanced data is one of the greatest challenging problems in binary classification, and this problem has gained more importance in recent years. When the class distribution is imbalanced, classical machine learning algorithms tend to move strongly towards the majority class and disregard the minority. Therefore, the accuracy may be high, but the model cannot recognize data instances in the minority class to classify them, leading to many misclassifications. Different methods have been proposed in the literature to handle the imbalance problem, but most are complicated and tend to simulate unnecessary noise. In this More >

Galimkair Mutanov, Vladislav Karyukin^*, Zhanl Mamykova

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 913-930, 2021, DOI:10.32604/cmc.2021.017827 - 04 June 2021

Abstract The volume of social media data on the Internet is constantly growing. This has created a substantial research field for data analysts. The diversity of articles, posts, and comments on news websites and social networks astonishes imagination. Nevertheless, most researchers focus on posts on Twitter that have a specific format and length restriction. The majority of them are written in the English language. As relatively few works have paid attention to sentiment analysis in the Russian and Kazakh languages, this article thoroughly analyzes news posts in the Kazakhstan media space. The amassed datasets include texts… More >

Harsh Tripathi¹, Amer Ibrahim Al-Omari², Mahendra Saha¹, Ayed R. A. Alanzi^3,*

Computer Systems Science and Engineering, Vol.38, No.3, pp. 381-392, 2021, DOI:10.32604/csse.2021.015624 - 19 May 2021

Abstract Recently, the Darna distribution has been introduced as a new lifetime distribution. The two-parameter Darna distribution represents is a mixture of two well-known gamma and exponential distributions. A manufacturer or an engineer of products conducts life testing to examine whether the quality level of products meets the customer’s requirements, such as reliability or the minimum lifetime. In this article, an attribute modified chain sampling inspection plan based on the time truncated life test is proposed for items whose lifetime follows the Darna distribution. The plan parameters, including the sample size, the acceptance number, and the… More >