Jingquan Zhang^a,b, Kun Zhang^a,b,*

Frontiers in Heat and Mass Transfer, Vol.17, pp. 1-6, 2021, DOI:10.5098/hmt.17.14

Abstract Detailed numerical analysis is presented for flow and heat transfer in sinusoidal-corrugated parallel channel with six discrete heat sources placed under the bottom surface. Three dimensional numerical model are applied for simulating the flow and heat transfer process and the Colburn j factor is applied to evaluate the overall performance of the corrugated liquid cooled channel. The results show that the maximum temperature in the middle section decreases and the pressure loss increases as the wavelength of sinusoidal surface on the bottom decreases, while the increasing wave amplitude of corrugated surface can enhance the heat More >

Zainab Kareem Ghoben^a,*,†, Ahmed Kadhim Hussein^b

Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-11, 2022, DOI:10.5098/hmt.18.6

Abstract he numerical analysis of a V-shaped baffle effect on the natural convection inside a parallelogrammical cavity filled with two different water-based nanofluids (Al2O3 and Cu) were studied in this work. The enclosure walls were maintained at a constant hot and cold temperatures on the left and right walls sequentially. The horizontal walls were isolated, while the baffles located on the right wall and sharing the same cold temperature with it. The finite element method was used to derive and solve the governing equations. The flow and thermal fields computed for different arrangements of: the number… More >

Kamyar Mohammadpour, Ali Chitsazan, Eckehard Specht

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-5, 2022, DOI:10.5098/hmt.19.34

Abstract Understanding the flow pattern of the gas jets in packed beds can have considerable significance in improving reactor design and process optimization. This study researches the fuel diffusion in the radial direction and the flame length in a packed bed of a Parallel Flow Regenerative (PFR) Shaft kiln. This kiln is characterized that the fuel being injected vertically into the packed bed using a lot of lances in the cross-section while the combustion air is distributed continuously. The packed bed approximated as a porous media and the measured values match approximately with those calculated with More >

P.S.S. Nagalakshmi, N. Vijaya^*

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-18, 2022, DOI:10.5098/hmt.19.17

Abstract The main emphasis of this study is to examine the entropy generation of the spatial-temporal state of Bingham visco-plastic nanofluid flow between parallel plates are solved numerically using adequate similarity solutions. Python with BVP solver is used to interpret the results of the adopted model. Heat and mass transfer rate with respect to yield stress was investigated. The results report that the entopy generation of nanofluids exploring single and multiwalled carbon nanotubes dims with the increasing local thermal Peclet number nearer the lower and upper plates. Researchers have established that entropy generation can be reduced More >

Anjani Kumar Singha¹, Swaleha Zubair¹, Areej Malibari², Nitish Pathak³, Shabana Urooj^4,*, Neelam Sharma⁵

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3491-3508, 2023, DOI:10.32604/csse.2023.029165

Abstract Suspicious mass traffic constantly evolves, making network behaviour tracing and structure more complex. Neural networks yield promising results by considering a sufficient number of processing elements with strong interconnections between them. They offer efficient computational Hopfield neural networks models and optimization constraints used by undergoing a good amount of parallelism to yield optimal results. Artificial neural network (ANN) offers optimal solutions in classifying and clustering the various reels of data, and the results obtained purely depend on identifying a problem. In this research work, the design of optimized applications is presented in an organized manner.… More >

Khaled M. Suwais^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2685-2704, 2023, DOI:10.32604/cmc.2023.036161

Abstract Data encryption is essential in securing exchanged data between connected parties. Encryption is the process of transforming readable text into scrambled, unreadable text using secure keys. Stream ciphers are one type of an encryption algorithm that relies on only one key for decryption and as well as encryption. Many existing encryption algorithms are developed based on either a mathematical foundation or on other biological, social or physical behaviours. One technique is to utilise the behavioural aspects of game theory in a stream cipher. In this paper, we introduce an enhanced Deoxyribonucleic acid (DNA)-coded stream cipher More >

Ling Ding¹, Hongyan Wan^2,*, Luokai Hu¹, Yu Chen¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2655-2670, 2023, DOI:10.32604/cmc.2023.035542

Abstract Product detection based on state abstraction technologies in the software product line (SPL) is more complex when compared to a single system. This variability constitutes a new complexity, and the counterexample may be valid for some products but spurious for others. In this paper, we found that spurious products are primarily due to the failure states, which correspond to the spurious counterexamples. The violated products correspond to the real counterexamples. Hence, identifying counterexamples is a critical problem in detecting violated products. In our approach, we obtain the violated products through the genuine counterexamples, which have… More >

Aswathy Ravikumar, Harini Sriraman^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 891-909, 2023, DOI:10.32604/cmc.2023.035848

Abstract Pneumonia is an acute lung infection that has caused many fatalities globally. Radiologists often employ chest X-rays to identify pneumonia since they are presently the most effective imaging method for this purpose. Computer-aided diagnosis of pneumonia using deep learning techniques is widely used due to its effectiveness and performance. In the proposed method, the Synthetic Minority Oversampling Technique (SMOTE) approach is used to eliminate the class imbalance in the X-ray dataset. To compensate for the paucity of accessible data, pre-trained transfer learning is used, and an ensemble Convolutional Neural Network (CNN) model is developed. The More >

Aswathy Ravikumar, Harini Sriraman^*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 563-578, 2023, DOI:10.32604/csse.2023.034710

Abstract Deep neural networks are gaining importance and popularity in applications and services. Due to the enormous number of learnable parameters and datasets, the training of neural networks is computationally costly. Parallel and distributed computation-based strategies are used to accelerate this training process. Generative Adversarial Networks (GAN) are a recent technological achievement in deep learning. These generative models are computationally expensive because a GAN consists of two neural networks and trains on enormous datasets. Typically, a GAN is trained on a single server. Conventional deep learning accelerator designs are challenged by the unique properties of GAN,… More >

Sizhe Tang¹, Mengmeng Cui^1,*, Lianyong Qi², Xiaolong Xu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 5-42, 2023, DOI:10.32604/cmes.2023.023684

Abstract With the rapid development of deep learning, the size of data sets and deep neural networks (DNNs) models are also booming. As a result, the intolerable long time for models’ training or inference with conventional strategies can not meet the satisfaction of modern tasks gradually. Moreover, devices stay idle in the scenario of edge computing (EC), which presents a waste of resources since they can share the pressure of the busy devices but they do not. To address the problem, the strategy leveraging distributed processing has been applied to load computation tasks from a single… More >