Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (21,887)
  • Open Access

    ARTICLE

    An Efficient Intrusion Detection Framework in Software-Defined Networking for Cybersecurity Applications

    Ghalib H. Alshammri1,2, Amani K. Samha3, Ezz El-Din Hemdan4, Mohammed Amoon1,4, Walid El-Shafai5,6,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3529-3548, 2022, DOI:10.32604/cmc.2022.025262

    Abstract Network management and multimedia data mining techniques have a great interest in analyzing and improving the network traffic process. In recent times, the most complex task in Software Defined Network (SDN) is security, which is based on a centralized, programmable controller. Therefore, monitoring network traffic is significant for identifying and revealing intrusion abnormalities in the SDN environment. Consequently, this paper provides an extensive analysis and investigation of the NSL-KDD dataset using five different clustering algorithms: K-means, Farthest First, Canopy, Density-based algorithm, and Exception-maximization (EM), using the Waikato Environment for Knowledge Analysis (WEKA) software to compare extensively between these five algorithms.… More >

  • Open Access

    ARTICLE

    Design of Energy Efficient WSN Using a Noble SMOWA Algorithm

    Avishek Banerjee1, Deepak Garg1, Victor Das2, Laxminarayan Sahoo3, Ira Nath4, Vijayakumar Varadarajan5, Ketan Kotecha6,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3585-3600, 2022, DOI:10.32604/cmc.2022.025233

    Abstract In this paper, the establishment of efficient Wireless Sensor Network (WSN) networks has been projected to minimize the consumption of energy using a new Self-adaptive Multi-Objective Weighted Approach (SMOWA) algorithm for solving a multi-objective problem. The Different WSN nodes deployment policies have been proposed and applied in this paper to design an efficient Wireless Sensor Network to minimize energy consumption. After that, the cluster head for each cluster has been selected with the help of the duty cycle. After configuring the WSN networks, the SMOWA algorithms have been developed to obtain the minimum energy consumption for the networks. Energy minimization,… More >

  • Open Access

    ARTICLE

    Genetic Based Approach for Optimal Power and Channel Allocation to Enhance D2D Underlaied Cellular Network Capacity in 5G

    Ahmed. A. Rosas*, Mona Shokair, M. I. Dessouky

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3751-3762, 2022, DOI:10.32604/cmc.2022.025226

    Abstract With the obvious throughput shortage in traditional cellular radio networks, Device-to-Device (D2D) communications has gained a lot of attention to improve the utilization, capacity and channel performance of next-generation networks. In this paper, we study a joint consideration of power and channel allocation based on genetic algorithm as a promising direction to expand the overall network capacity for D2D underlaied cellular networks. The genetic based algorithm targets allocating more suitable channels to D2D users and finding the optimal transmit powers for all D2D links and cellular users efficiently, aiming to maximize the overall system throughput of D2D underlaied cellular network… More >

  • Open Access

    ARTICLE

    Hybrid Sine Cosine and Stochastic Fractal Search for Hemoglobin Estimation

    Marwa M. Eid1,*, Fawaz Alassery2, Abdelhameed Ibrahim3, Bandar Abdullah Aloyaydi4, Hesham Arafat Ali1,3, Shady Y. El-Mashad5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2467-2482, 2022, DOI:10.32604/cmc.2022.025220

    Abstract The sample's hemoglobin and glucose levels can be determined by obtaining a blood sample from the human body using a needle and analyzing it. Hemoglobin (HGB) is a critical component of the human body because it transports oxygen from the lungs to the body's tissues and returns carbon dioxide from the tissues to the lungs. Calculating the HGB level is a critical step in any blood analysis job. The HGB levels often indicate whether a person is anemic or polycythemia vera. Constructing ensemble models by combining two or more base machine learning (ML) models can help create a more improved… More >

  • Open Access

    ARTICLE

    Modeling and Verification of Aircraft Takeoff Through Novel Quantum Nets

    Maryam Jamal1, Nazir Ahmad Zafar2, Atta-ur-Rahman3,*, Dhiaa Musleh3, Mohammed A. Gollapalli4, Sghaier Chabani4

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3331-3348, 2022, DOI:10.32604/cmc.2022.025205

    Abstract The formal modeling and verification of aircraft takeoff is a challenge because it is a complex safety-critical operation. The task of aircraft takeoff is distributed amongst various computer-based controllers, however, with the growing malicious threats a secure communication between aircraft and controllers becomes highly important. This research serves as a starting point for integration of BB84 quantum protocol with petri nets for secure modeling and verification of takeoff procedure. The integrated model combines the BB84 quantum cryptographic protocol with powerful verification tool support offered by petri nets. To model certain important properties of BB84, a new variant of petri nets… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Data Offloading Technique for Secure MEC Systems

    Fadwa Alrowais1, Ahmed S. Almasoud2, Radwa Marzouk3, Fahd N. Al-Wesabi4,5, Anwer Mustafa Hilal6,*, Mohammed Rizwanullah6, Abdelwahed Motwakel6, Ishfaq Yaseen6

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2783-2795, 2022, DOI:10.32604/cmc.2022.025204

    Abstract Mobile edge computing (MEC) provides effective cloud services and functionality at the edge device, to improve the quality of service (QoS) of end users by offloading the high computation tasks. Currently, the introduction of deep learning (DL) and hardware technologies paves a method in detecting the current traffic status, data offloading, and cyberattacks in MEC. This study introduces an artificial intelligence with metaheuristic based data offloading technique for Secure MEC (AIMDO-SMEC) systems. The proposed AIMDO-SMEC technique incorporates an effective traffic prediction module using Siamese Neural Networks (SNN) to determine the traffic status in the MEC system. Also, an adaptive sampling… More >

  • Open Access

    ARTICLE

    Improved Archimedes Optimization Algorithm with Deep Learning Empowered Fall Detection System

    Ala Saleh Alluhaidan1, Masoud Alajmi2, Fahd N. Al-Wesabi3,4, Anwer Mustafa Hilal5, Manar Ahmed Hamza5,*, Abdelwahed Motwakel5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2713-2727, 2022, DOI:10.32604/cmc.2022.025202

    Abstract Human fall detection (FD) acts as an important part in creating sensor based alarm system, enabling physical therapists to minimize the effect of fall events and save human lives. Generally, elderly people suffer from several diseases, and fall action is a common situation which can occur at any time. In this view, this paper presents an Improved Archimedes Optimization Algorithm with Deep Learning Empowered Fall Detection (IAOA-DLFD) model to identify the fall/non-fall events. The proposed IAOA-DLFD technique comprises different levels of pre-processing to improve the input image quality. Besides, the IAOA with Capsule Network based feature extractor is derived to… More >

  • Open Access

    ARTICLE

    Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

    Mousa Al-Akhras1,2,*, Zainab Darwish2, Samer Atawneh1, Mohamed Habib1,3

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3719-3749, 2022, DOI:10.32604/cmc.2022.025196

    Abstract Association rules’ learning is a machine learning method used in finding underlying associations in large datasets. Whether intentionally or unintentionally present, noise in training instances causes overfitting while building the classifier and negatively impacts classification accuracy. This paper uses instance reduction techniques for the datasets before mining the association rules and building the classifier. Instance reduction techniques were originally developed to reduce memory requirements in instance-based learning. This paper utilizes them to remove noise from the dataset before training the association rules classifier. Extensive experiments were conducted to assess the accuracy of association rules with different instance reduction techniques, namely:… More >

  • Open Access

    ARTICLE

    A Modified-Simplified MPPT Technique for Three-Phase Single-State Grid-Connected PV Systems

    Anuchit Aurairat, Boonyang Plangklang*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2375-2395, 2022, DOI:10.32604/cmc.2022.025122

    Abstract Nowadays, the single state inverter for the grid-connected photovoltaic (PV) systems is becoming more and more popular as they can reduce circuit complexity resulting in less power losses of the inverter. This paper focuses on the use of model predictive control (MPC) to control a 3-phase and 2-level single-state grid-connected inverter in order to regulate the PV maximum power point (MPP). The algorithm of MPC scheme was done to measure the simultaneous current signal including predicting the next sampling current flow. The reference current (Id*) was used to control the distribution of electrical power from the solar cell to the… More >

  • Open Access

    ARTICLE

    Vision-based Recognition Algorithm for Up-To-Date Indoor Digital Map Generations at Damaged Buildings

    Dahyeon Kim1, Chulsu Kim2, Junho Ahn1,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2765-2781, 2022, DOI:10.32604/cmc.2022.025116

    Abstract When firefighters are engaged in search and rescue missions inside a building at a risk of collapse, they have difficulty in field command and rescue because they can only simply monitor the situation inside the building utilizing old building drawings or robots. To propose an efficient solution for fast search and rescue work of firefighters, this study investigates the generation of up-to-date digital maps for disaster sites by tracking the collapse situation, and identifying the information of obstacles which are risk factors, using an artificial intelligence algorithm based on low-cost robots. Our research separates the floor by using the mask… More >

Displaying 8331-8340 on page 834 of 21887. Per Page