Qianqi Sun, Fenhua Bai^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1733-1754, 2024, DOI:10.32604/cmes.2023.044558

Abstract Blockchain technology has witnessed a burgeoning integration into diverse realms of economic and societal development. Nevertheless, scalability challenges, characterized by diminished broadcast efficiency, heightened communication overhead, and escalated storage costs, have significantly constrained the broad-scale application of blockchain. This paper introduces a novel Encode-and CRT-based Scalability Scheme (ECSS), meticulously refined to enhance both block broadcasting and storage. Primarily, ECSS categorizes nodes into distinct domains, thereby reducing the network diameter and augmenting transmission efficiency. Secondly, ECSS streamlines block transmission through a compact block protocol and robust RS coding, which not only reduces the size of broadcasted blocks but also ensures transmission… More >

Haiqi Feng¹, Wei Huang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-2, 2023, DOI:10.32604/icces.2023.09347

Abstract Intensive dynamic loadings are the main threats to the structural damage of protective structures and inner equipment, which has attracted a lot of attention in the field of advance impulsive resistance. Nanofluidic liquid foam (NLF) has become a novel and efficient energy absorption system due to its reusable energy absorption, ultra-high load transfer, and high energy absorption ratio [1-7]. In order to solve the current problem that the energy absorption mechanism of NLF is still unclear, this paper conducted a systematic experimental study on the dynamic compression and energy absorption behaviours of NLF. The quasi-static cyclic compression experiments with different… More >

Xuanjie Li, Yuedong Xu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 459-481, 2024, DOI:10.32604/cmes.2023.043247

Abstract We are investigating the distributed optimization problem, where a network of nodes works together to minimize a global objective that is a finite sum of their stored local functions. Since nodes exchange optimization parameters through the wireless network, large-scale training models can create communication bottlenecks, resulting in slower training times. To address this issue, CHOCO-SGD was proposed, which allows compressing information with arbitrary precision without reducing the convergence rate for strongly convex objective functions. Nevertheless, most convex functions are not strongly convex (such as logistic regression or Lasso), which raises the question of whether this algorithm can be applied to… More >

Hassen Louati^1,2, Ali Louati^3,*, Elham Kariri³, Slim Bechikh²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2519-2547, 2024, DOI:10.32604/cmes.2023.030806

Abstract Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues, particularly in the field of lung disease diagnosis. One promising avenue involves the use of chest X-Rays, which are commonly utilized in radiology. To fully exploit their potential, researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems. However, constructing and compressing these systems presents a significant challenge, as it relies heavily on the expertise of data scientists. To tackle this issue, we propose an automated approach that utilizes an evolutionary algorithm (EA) to optimize the design and compression of a convolutional neural network… More >

Biswajit De^*, Rajsekhar Panua

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-4, 2014, DOI:10.5098/hmt.5.10

Abstract As the world is facing crisis due to the dwindling resources of fossil fuels, rapid depletion of conventional energy is a matter of serious concern for the mankind. So there is a necessity to find alternate fuels. Vegetable oils, because of their agricultural origin, due to less carbon content compared to mineral diesel are producing less CO₂ emissions to the atmosphere is used as an alternate fuel in substitute to diesel fuel. In the present study optimum compression ratio for VCR diesel engine fuelled with Jatropha oil blends with diesel (30%) has been determined at 203 bars injector opening pressure,… More >

Biswajit De^*, Rajsekhar Panua

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-6, 2014, DOI:10.5098/hmt.5.7

Abstract This paper presents a pre-mixed combustion model for diesel and Jatropha oil blends combustion studies. Jatropha oil blends are considered as a mixture of diesel and Jatropha oil. CFD package, FLUENT 6.3 is used for modeling the complex combustion phenomenon in compression ignition engine. The experiments are carried out on a single cylinder, four strokes, water cooled direct injection compression ignition engine at compression ratio of 17.5 at full load condition at constant speed of 1500 rpm fuelled with diesel and jatropha oil blends with diesel. The numerical model is solved by considering pressure based, implicit and unsteady solver and… More >

Biswajit De^*, Rajsekhar Panua

Frontiers in Heat and Mass Transfer, Vol.6, pp. 1-6, 2015, DOI:10.5098/hmt.6.11

Abstract An incorporated arithmetical model has been urbanized and investigated for CFD replication of a solitary cylinder, four stroke, straight inoculation, compressed ignition diesel engine of 3.5 kW for in-cylinder combustion analysis and authenticated under engine simulations at full load functioning conditions with foundation fuel diesel and 10% JME (volume basis) blend with diesel at invariable speed of 1500 rpm. For advancing the exactness of the exertion, a number of sub models, such as species transport model explaining the actual biodiesel energy content and molecular structure as soon as fuel blend is initiated, spray break-up model, wave model and pre-mixed combustion… More >

Yu-Rim Lee¹, Na-Eun Park¹, Seo-Yi Kim², Il-Gu Lee^1,2,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3465-3482, 2023, DOI:10.32604/cmc.2023.041196

Abstract With the introduction of 5G technology, the application of Internet of Things (IoT) devices is expanding to various industrial fields. However, introducing a robust, lightweight, low-cost, and low-power security solution to the IoT environment is challenging. Therefore, this study proposes two methods using a data compression technique to detect malicious traffic efficiently and accurately for a secure IoT environment. The first method, compressed sensing and learning (CSL), compresses an event log in a bitmap format to quickly detect attacks. Then, the attack log is detected using a machine-learning classification model. The second method, precise re-learning after CSL (Ra-CSL), comprises a… More >

Binbin Yang^1,*, Leilei Liu¹, Yan Zhang¹, Jingyu Gong¹, Fan Zhang², Tiezhu Zhang¹

Energy Engineering, Vol.120, No.10, pp. 2233-2250, 2023, DOI:10.32604/ee.2023.028898

Abstract Gasoline compression ignition (GCI) has been considered as a promising combustion concept to yield ultra-low NO_X and soot emissions while maintaining high thermal efficiency. However, how to improve the low-load performance becomes an urgent issue to be solved. In this paper, a GCI engine model was built to investigate the effects of internal EGR (i-EGR) and pre-injection on in-cylinder temperature, spatial concentration of mixture and OH radical, combustion and emission characteristics, and the control strategy for improving the combustion performance was further explored. The results showed an obvious expansion of the zone with an equivalence ratio between 0.8~1.2 is realized… More >

Noora S. Ekab¹, Ahmed Q. Salam², Ali O. Abd³, Miqdam T. Chaichan^4,*

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.11, pp. 2847-2861, 2023, DOI:10.32604/fdmp.2023.028874

Abstract To improve the performances of diesel engines and to reduce the pollutants they emit, aluminum oxide nanoparticles in varying quantities (50, 100, 150 ppm) have been added to conventional diesel fuel. The results of such experimental tests have revealed that the addition of nano-Al₂O₃ particles to the diesel fuel reduces its consumption by 0.488%, 1.02%, and 1.377%, respectively and increases the brake thermal efficiency by 1.4%, 2.6%, and 3.8%, respectively. The concentrations of undesired gases decrease accordingly by 1.5%, 1.7%, and 2.8% for HC and by 5.88%, 11.7%, and 17.6%, respectively, for CO. For the same percentages of nanoparticles, NOx… More >