Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1,767)
  • Open Access

    ARTICLE

    An Experimental Approach to Diagnose Covid-19 Using Optimized CNN

    Anjani Kumar Singha1, Nitish Pathak2,*, Neelam Sharma3, Abhishek Gandhar4, Shabana Urooj5, Swaleha Zubair6, Jabeen Sultana7, Guthikonda Nagalaxmi8

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1065-1080, 2022, DOI:10.32604/iasc.2022.024172

    Abstract The outburst of novel corona viruses aggregated worldwide and has undergone severe trials to manage medical sector all over the world. A radiologist uses x-rays and Computed Tomography (CT) scans to analyze images through which the existence of corona virus is found. Therefore, imaging and visualization systems contribute a dominant part in diagnosing process and thereby assist the medical experts to take necessary precautions and to overcome these rigorous conditions. In this research, a Multi-Objective Black Widow Optimization based Convolutional Neural Network (MBWO-CNN) method is proposed to diagnose and classify covid-19 data. The proposed method comprises of four stages, preprocess… More >

  • Open Access

    ARTICLE

    Early DDoS Detection and Prevention with Traced-Back Blocking in SDN Environment

    Sriramulu Bojjagani1, D. R. Denslin Brabin2,*, K. Saravanan2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 805-819, 2022, DOI:10.32604/iasc.2022.023771

    Abstract The flow of information is a valuable asset for every company and its consumers, and Distributed Denial-of-Service (DDoS) assaults pose a substantial danger to this flow. If we do not secure security, hackers may steal information flowing across a network, posing a danger to a business and society. As a result, the most effective ways are necessary to deal with the dangers. A DDoS attack is a well-known network infrastructure assault that prevents servers from servicing genuine customers. It is necessary to identify and block a DDoS assault before it reaches the server in order to avoid being refused services.… More >

  • Open Access

    ARTICLE

    Dark and Bright Channel Priors for Haze Removal in Day and Night Images

    U. Hari, A. Ruhan Bevi*

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 957-967, 2022, DOI:10.32604/iasc.2022.023605

    Abstract Removal of noise from images is very important as a clear, denoised image is essential for any application. In this article, a modified haze removal algorithm is developed by applying combined dark channel prior and multi-scale retinex theory. The combined dark channel prior (DCP) and bright channel prior (BCP) together with the multi-scale retinex (MSR) algorithm is used to dynamically optimize the transmission map and thereby improve visibility. The proposed algorithm performs effective denoising of images considering the properties of retinex theory. The proposed method removes haze on an image scene through estimation of the atmospheric light and manipulating the… More >

  • Open Access

    ARTICLE

    Crack Detection in Composite Materials Using McrowDNN

    R. Saveeth1,*, S. Uma Maheswari2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 983-1000, 2022, DOI:10.32604/iasc.2022.023455

    Abstract In the aerospace industry, composite materials are becoming more common. The presence of a crack in an aircraft makes it weaker and more dangerous, and it can lead to complete fracture and catastrophic failure. To predict the position and depth of a crack, various methods have been developed. For aircraft repair, crack diagnosis is extremely important. Even then, due to uncertainties arising from sources such as environmental conditions, packing, and intrinsic material property changes, accurate diagnosis in real engineering applications remains a challenge. Deep learning (DL) approaches have demonstrated powerful recognition potential in a variety of fields in recent years.… More >

  • Open Access

    ARTICLE

    Person Re-Identification Using LBPH and K-Reciprocal Encoding

    V. Manimaran*, K. G. Srinivasagan

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1109-1121, 2022, DOI:10.32604/iasc.2022.023145

    Abstract Individual re-identification proof (Re-ID) targets recovering an individual of interest across different non-covering cameras. With the recent development of technological algorithm and expanding request of intelligence video observation, it has acquired fundamentally expanded interest in the computer vision. Person re-identification is characterized as the issue of perceiving an individual caught in different occasions and additionally areas more than a few nonoverlapping camera sees, thinking about a huge arrangement of up-and-comers. This issue influences essentially the administration of disseminated, multiview observation frameworks, in which subjects should be followed across better places, either deduced or on-the-fly when they travel through various areas.… More >

  • Open Access

    ARTICLE

    Deep Reinforcement Extreme Learning Machines for Secured Routing in Internet of Things (IoT) Applications

    K. Lavanya1,*, K. Vimala Devi2, B. R. Tapas Bapu3

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 837-848, 2022, DOI:10.32604/iasc.2022.023055

    Abstract Multipath TCP (SMPTCP) has gained more attention as a valuable approach for IoT systems. SMPTCP is introduced as an evolution of Transmission Control Protocol (TCP) to pass packets simultaneously across several routes to completely exploit virtual networks on multi-homed consoles and other network services. The current multipath networking algorithms and simulation software strategies are confronted with sub-flow irregularity issues due to network heterogeneity, and routing configuration issues can be fixed adequately. To overcome the issues, this paper proposes a novel deep reinforcement-based extreme learning machines (DRLELM) approach to examine the complexities between routes, pathways, sub-flows, and SMPTCP connections in different… More >

  • Open Access

    ARTICLE

    A Novel Controller for Microgrid Interactive Hybrid Renewable Power Sources

    P. Kavitha*, P. Subha Karuvelam

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 821-836, 2022, DOI:10.32604/iasc.2022.023035

    Abstract In this paper, a self-sufficient electric power generation is proposed by using hybrid renewable sources like solar and wind turbines to favor a smart and green environment. This distributed generation unit is connected to the grid through an 3Φ inverter. The power drawn from the hybrid unit is stored in the batteries to transfer power during the non-availability of power sources. This standalone power conversion and storage system are developed by using power electronic converters and controllers to ensure balanced power flow operation. A PI (Proportional Integral) controller is utilized for generating the PWM (Pulse Width Modulation) pulses for the… More >

  • Open Access

    ARTICLE

    Multi-Classification and Distributed Reinforcement Learning-Based Inspection Swarm Offloading Strategy

    Yuping Deng1, Tao Wu1, Xi Chen2,*, Amir Homayoon Ashrafzadeh3

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1157-1174, 2022, DOI:10.32604/iasc.2022.022606

    Abstract In meteorological and electric power Internet of Things scenarios, in order to extend the service life of relevant facilities and reduce the cost of emergency repair, the intelligent inspection swarm is introduced to cooperate with monitoring tasks, which collect and process the current scene data through a variety of sensors and cameras, and complete tasks such as emergency handling and fault inspection. Due to the limitation of computing resources and battery life of patrol inspection equipment, it will cause problems such as slow response in emergency and long time for fault location. Mobile Edge Computing is a promising technology, which… More >

  • Open Access

    ARTICLE

    Field Programmable Gate Arrays (FPGA) Based Computational Complexity Analysis of Multicarrier Waveforms

    C. Ajitha1,*, T. Jaya2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1033-1048, 2022, DOI:10.32604/iasc.2022.021984

    Abstract Multicarrier waveforms with enhanced spectral efficiency, low latency, and high throughput are required for 5G wireless networks. The Orthogonal Frequency Division Multiplexing (OFDM) method is well-known in research, but due to its limited spectral efficiency, various alternative waveforms are being considered for 5G systems. In the recent communication world, NOMA (non-orthogonal multiple access) plays a significant part due to its wider transmission of data with less bandwidth allocation. Even if a high data rate can be attained, the transmission problem will arise due to the spread of multiple paths. In order to reduce complexity and area utilization, a novel PL-based… More >

  • Open Access

    ARTICLE

    Secure Multi-Party Quantum Summation Based on Quantum Homomorphic Encryption

    Gang Xu1,2, Fan Yun1, Xiu-Bo Chen3,*, Shiyuan Xu1, Jingzhong Wang1, Tao Shang4, Yan Chang5, Mianxiong Dong6

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 531-541, 2022, DOI:10.32604/iasc.2022.028264

    Abstract Secure multi-party computation has been playing a fundamental role in terms of classical cryptography. Quantum homomorphic encryption (QHE) could compute the encrypted data without decryption. At present, most protocols use a semi-honest third party (TP) to protect participants’ secrets. We use a quantum homomorphic encryption scheme instead of TP to protect the privacy of parties. Based on quantum homomorphic encryption, a secure multi-party quantum summation scheme is proposed in which N participants can delegate a server with strong quantum computing power to assist computation. By delegating the computation and key update processes to a server and a semi-honest key center,… More >

Displaying 771-780 on page 78 of 1767. Per Page