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  • Open Access

    ARTICLE

    Color Image Compression and Encryption Algorithm Based on 2D Compressed Sensing and Hyperchaotic System

    Zhiqing Dong1, Zhao Zhang1,*, Hongyan Zhou2, Xuebo Chen2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1977-1993, 2024, DOI:10.32604/cmc.2024.047233

    Abstract With the advent of the information security era, it is necessary to guarantee the privacy, accuracy, and dependable transfer of pictures. This study presents a new approach to the encryption and compression of color images. It is predicated on 2D compressed sensing (CS) and the hyperchaotic system. First, an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong security. Then, the processed images are concurrently encrypted and compressed using 2D CS. Among them, chaotic sequences replace traditional random measurement matrices to increase the system’s security. Third, the processed images are re-encrypted using a combination of… More >

  • Open Access

    ARTICLE

    An Encode-and CRT-Based Scalability Scheme for Optimizing Transmission in Blockchain

    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 >

  • Open Access

    PROCEEDINGS

    Dynamic Compression and Energy Absorption Behaviours of a Nanofluidic Liquid Foam

    Haiqi Feng1, Wei Huang1,*

    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 >

  • Open Access

    ARTICLE

    Distributed Stochastic Optimization with Compression for Non-Strongly Convex Objectives

    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 >

  • Open Access

    ARTICLE

    Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression

    Hassen Louati1,2, Ali Louati3,*, 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 >

  • Open Access

    ARTICLE

    OPTIMIZATION OF COMPRESSION RATIO OF JATROPHA OIL BLEND WITH DIESEL FUELLED ON VARIABLE COMPRESSION RATIO ENGINE

    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 >

  • Open Access

    ARTICLE

    CFD MODELLING AND VALIDATION OF COMBUSTION IN DIRECT INJECTION COMPRESSION IGNITION ENGINE FUELLED WITH JATROPHA OIL BLENDS WITH DIESEL

    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 >

  • Open Access

    ARTICLE

    MODELLING AND EXPERIMENTAL VALIDATION OF COMBUSTION IN STRAIGHT INOCULATION COMPRESSION IGNITION ENGINE FUELLED WITH DIESEL AND JATROPHA METHYL ESTER BLEND

    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 >

  • Open Access

    ARTICLE

    Malicious Traffic Compression and Classification Technique for Secure Internet of Things

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

    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 >

  • Open Access

    ARTICLE

    Effects of I-EGR and Pre-Injection on Performance of Gasoline Compression Ignition (GCI) at Low-Load Condition

    Binbin Yang1,*, 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 NOX 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 >

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