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  • Open Access

    ARTICLE

    Unknown Attack Detection: Combining Relabeling and Hybrid Intrusion Detection

    Gun-Yoon Shin1, Dong-Wook Kim1, Sang-Soo Kim2, Myung-Mook Han3,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3289-3303, 2021, DOI:10.32604/cmc.2021.017502 - 06 May 2021

    Abstract Detection of unknown attacks like a zero-day attack is a research field that has long been studied. Recently, advances in Machine Learning (ML) and Artificial Intelligence (AI) have led to the emergence of many kinds of attack-generation tools developed using these technologies to evade detection skillfully. Anomaly detection and misuse detection are the most commonly used techniques for detecting intrusion by unknown attacks. Although anomaly detection is adequate for detecting unknown attacks, its disadvantage is the possibility of high false alarms. Misuse detection has low false alarms; its limitation is that it can detect only… More >

  • Open Access

    ARTICLE

    A Hybrid Approach for Performance and Energy-Based Cost Prediction in Clouds

    Mohammad Aldossary*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3531-3562, 2021, DOI:10.32604/cmc.2021.017477 - 06 May 2021

    Abstract With the striking rise in penetration of Cloud Computing, energy consumption is considered as one of the key cost factors that need to be managed within cloud providers’ infrastructures. Subsequently, recent approaches and strategies based on reactive and proactive methods have been developed for managing cloud computing resources, where the energy consumption and the operational costs are minimized. However, to make better cost decisions in these strategies, the performance and energy awareness should be supported at both Physical Machine (PM) and Virtual Machine (VM) levels. Therefore, in this paper, a novel hybrid approach is proposed, which… More >

  • Open Access

    ARTICLE

    Hybrid Trainable System for Writer Identification of Arabic Handwriting

    Saleem Ibraheem Saleem*, Adnan Mohsin Abdulazeez

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3353-3372, 2021, DOI:10.32604/cmc.2021.016342 - 06 May 2021

    Abstract Writer identification (WI) based on handwritten text structures is typically focused on digital characteristics, with letters/strokes representing the information acquired from the current research in the integration of individual writing habits/styles. Previous studies have indicated that a word’s attributes contribute to greater recognition than the attributes of a character or stroke. As a result of the complexity of Arabic handwriting, segmenting and separating letters and strokes from a script poses a challenge in addition to WI schemes. In this work, we propose new texture features for WI based on text. The histogram of oriented gradient… More >

  • Open Access

    ARTICLE

    Hybrid Swarm Intelligence Based QoS Aware Clustering with Routing Protocol for WSN

    M. S. Maharajan1, T. Abirami2, Irina V. Pustokhina3, Denis A. Pustokhin4, K. Shankar5,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2995-3013, 2021, DOI:10.32604/cmc.2021.016139 - 06 May 2021

    Abstract Wireless Sensor Networks (WSN) started gaining attention due to its wide application in the fields of data collection and information processing. The recent advancements in multimedia sensors demand the Quality of Service (QoS) be maintained up to certain standards. The restrictions and requirements in QoS management completely depend upon the nature of target application. Some of the major QoS parameters in WSN are energy efficiency, network lifetime, delay and throughput. In this scenario, clustering and routing are considered as the most effective techniques to meet the demands of QoS. Since they are treated as NP… More >

  • Open Access

    ARTICLE

    A New Hybrid Feature Selection Method Using T-test and Fitness Function

    Husam Ali Abdulmohsin1,*, Hala Bahjat Abdul Wahab2, Abdul Mohssen Jaber Abdul Hossen3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3997-4016, 2021, DOI:10.32604/cmc.2021.014840 - 06 May 2021

    Abstract

    Feature selection (FS) (or feature dimensional reduction, or feature optimization) is an essential process in pattern recognition and machine learning because of its enhanced classification speed and accuracy and reduced system complexity. FS reduces the number of features extracted in the feature extraction phase by reducing highly correlated features, retaining features with high information gain, and removing features with no weights in classification. In this work, an FS filter-type statistical method is designed and implemented, utilizing a t-test to decrease the convergence between feature subsets by calculating the quality of performance value (QoPV). The approach utilizes

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  • Open Access

    ARTICLE

    Suppression Effects on Pineapple Soil-Borne Pathogens by Crotalaria juncea, Dolomitic Lime and Plastic Mulch Cover on MD-2 Hybrid Cultivar

    Luis Alfonso Aguilar Pérez1,*, Daniel Nieto Ángel1,*, Moisés Roberto Vallejo Pérez2, Daniel Leobardo Ochoa Martínez1, David Espinosa Victoria3, Andrés Rebolledo Martinez4, Abel Rebouças São José5

    Phyton-International Journal of Experimental Botany, Vol.90, No.4, pp. 1205-1216, 2021, DOI:10.32604/phyton.2021.015109 - 27 April 2021

    Abstract The development and implementation of sustainable and environmentally friendly agricultural practices are indispensable as alternatives to pesticide use and to keep populations of soil-borne plant pathogens at levels that do not affect crop productivity. The present research evaluates the incidence of soil-borne phytopathogens on the pineapple variety MD-2, which was subjected to different treatments: Incorporation of Crotalaria juncea into the soil (organic amendment), application of dolomitic lime to soil (inorganic amendment), and the use of plastic mulch covering the soil. During the crop cycle (15 months), the following variables were evaluated: plant height (cm), fruit weight (kg·plant−1More >

  • Open Access

    ARTICLE

    Improved Hybrid Precoding Technique with Low-Resolution for MIMO-OFDM System

    Seulgi Lee1, Ji-Sung Jung1, Young-Hwan You2, Hyoung-Kyu Song1,*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2205-2219, 2021, DOI:10.32604/cmc.2021.017008 - 13 April 2021

    Abstract This paper proposes an improved hybrid beamforming system based on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. The proposed beamforming system improves energy efficiency compared to the conventional hybrid beamforming system. Both sub-connected and full-connected structure are considered to apply the proposed algorithm. In the conventional hybrid beamforming, the usage of radio frequency (RF) chains and phase shifter (PS) gives high power and hardware complexity. In this paper, the phase over sampling (POS) with switches (SW) is used in hybrid beamforming system to improve the energy efficiency. The POS-SW structure samples the value of… More >

  • Open Access

    ARTICLE

    System Performance of Wireless Sensor Network Using LoRa–Zigbee Hybrid Communication

    Van-Truong Truong1, Anand Nayyar2,*, Showkat Ahmad Lone3

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1615-1635, 2021, DOI:10.32604/cmc.2021.016922 - 13 April 2021

    Abstract Wireless sensor network (WSN) is considered as the fastest growing technology pattern in recent years because of its applicability in varied domains. Many sensor nodes with different sensing functionalities are deployed in the monitoring area to collect suitable data and transmit it to the gateway. Ensuring communications in heterogeneous WSNs, is a critical issue that needs to be studied. In this research paper, we study the system performance of a heterogeneous WSN using LoRa–Zigbee hybrid communication. Specifically, two Zigbee sensor clusters and two LoRa sensor clusters are used and combined with two Zigbee-to-LoRa converters to… More >

  • Open Access

    ARTICLE

    A Novel Hybrid Tag Identification Protocol for Large-Scale RFID Systems

    Ye Mu1,2,3,4, Ruiwen Ni1, Yuheng Sun1, Tong Zhang1, Ji Li1, Tianli Hu1,2,3,4, He Gong1,2,3,4, Shijun Li1,2,3,4,*, Thobela Louis Tyasi5

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2515-2527, 2021, DOI:10.32604/cmc.2021.016570 - 13 April 2021

    Abstract

    Radio frequency identification technology is one of the main technologies of Internet of Things (IoT). Through the transmission and reflection of wireless radio frequency signals, non-contact identification is realized, and multiple objects identification can be realized. However, when multiple tags communicate with a singleton reader simultaneously, collision will occur between the signals, which hinders the successful transmissions. To effectively avoid the tag collision problem and improve the reading performance of RFID systems, two advanced tag identification algorithms namely Adaptive M-ary tree slotted Aloha (AMTS) based on the characteristics of Aloha-based and Query tree-based algorithms are proposed.

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  • Open Access

    ARTICLE

    HLR-Net: A Hybrid Lip-Reading Model Based on Deep Convolutional Neural Networks

    Amany M. Sarhan1, Nada M. Elshennawy1, Dina M. Ibrahim1,2,*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1531-1549, 2021, DOI:10.32604/cmc.2021.016509 - 13 April 2021

    Abstract

    Lip reading is typically regarded as visually interpreting the speaker’s lip movements during the speaking. This is a task of decoding the text from the speaker’s mouth movement. This paper proposes a lip-reading model that helps deaf people and persons with hearing problems to understand a speaker by capturing a video of the speaker and inputting it into the proposed model to obtain the corresponding subtitles. Using deep learning technologies makes it easier for users to extract a large number of different features, which can then be converted to probabilities of letters to obtain accurate results.

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