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  • Open Access


    An Overview of Modern Cartographic Trends Aligned with the ICA’s Perspective

    Maan Habib1,*, Maan Okayli2

    Revue Internationale de Géomatique, Vol.32, pp. 1-16, 2023, DOI:10.32604/rig.2023.043399

    Abstract This study provides a comprehensive overview of modern cartography innovations and emerging trends, highlighting the importance of geospatial representation in various fields. It discusses recent advancements in geospatial data collection techniques, including satellite and aerial imagery, Light Detection and Ranging (LiDAR) technology, and crowdsourcing. The research also investigates the integration of big data, machine learning, and real-time processing in Geographic Information Systems (GIS), as well as advances in geospatial visualization. In addition, it examines the role of cartography in addressing global challenges such as climate change, disaster management, and urban planning in line with the International Cartographic Association’s (ICA) perspectives.… More >

  • Open Access


    Real-Time Data Transmission with Data Carrier Support Value in Neighbor Strategic Collection in WSN

    S. Ponnarasi1,*, T. Rajendran2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6039-6057, 2023, DOI:10.32604/cmc.2023.035499

    Abstract An efficient trust-aware secure routing and network strategy-based data collection scheme is presented in this paper to enhance the performance and security of wireless sensor networks during data collection. The method first discovers the routes between the data sensors and the sink node. Several factors are considered for each sensor node along the route, including energy, number of neighbours, previous transmissions, and energy depletion ratio. Considering all these variables, the Sink Reachable Support Measure and the Secure Communication Support Measure, the method evaluates two distinct measures. The method calculates the data carrier support value using these two metrics. A single… More >

  • Open Access


    Human and Machine Vision Based Indian Race Classification Using Modified-Convolutional Neural Network

    Vani A. Hiremani*, Kishore Kumar Senapati

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2603-2618, 2023, DOI:10.32604/csse.2023.027612

    Abstract The inter-class face classification problem is more reasonable than the intra-class classification problem. To address this issue, we have carried out empirical research on classifying Indian people to their geographical regions. This work aimed to construct a computational classification model for classifying Indian regional face images acquired from south and east regions of India, referring to human vision. We have created an Automated Human Intelligence System (AHIS) to evaluate human visual capabilities. Analysis of AHIS response showed that face shape is a discriminative feature among the other facial features. We have developed a modified convolutional neural network to characterize the… More >

  • Open Access


    Artificial Intelligence-Enabled Cooperative Cluster-Based Data Collection for Unmanned Aerial Vehicles

    R. Rajender1, C. S. S. Anupama2, G. Jose Moses3, E. Laxmi Lydia4, Seifedine Kadry5, Sangsoon Lim6,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3351-3365, 2022, DOI:10.32604/cmc.2022.030229

    Abstract In recent times, sixth generation (6G) communication technologies have become a hot research topic because of maximum throughput and low delay services for mobile users. It encompasses several heterogeneous resource and communication standard in ensuring incessant availability of service. At the same time, the development of 6G enables the Unmanned Aerial Vehicles (UAVs) in offering cost and time-efficient solution to several applications like healthcare, surveillance, disaster management, etc. In UAV networks, energy efficiency and data collection are considered the major process for high quality network communication. But these procedures are found to be challenging because of maximum mobility, unstable links,… More >

  • Open Access


    Artificially Generated Facial Images for Gender Classification Using Deep Learning

    Valliappan Raman1, Khaled ELKarazle2,*, Patrick Then2

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1341-1355, 2023, DOI:10.32604/csse.2023.026674

    Abstract Given the current expansion of the computer vision field, several applications that rely on extracting biometric information like facial gender for access control, security or marketing purposes are becoming more common. A typical gender classifier requires many training samples to learn as many distinguishable features as possible. However, collecting facial images from individuals is usually a sensitive task, and it might violate either an individual's privacy or a specific data privacy law. In order to bridge the gap between privacy and the need for many facial images for deep learning training, an artificially generated dataset of facial images is proposed.… More >

  • Open Access


    Energy Aware Data Collection with Route Planning for 6G Enabled UAV Communication

    Mesfer Al Duhayyim1, Marwa Obayya2, Fahd N. Al-Wesabi3,4, Anwer Mustafa Hilal5,*, Mohammed Rizwanullah5, Majdy M. Eltahir6

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 825-842, 2022, DOI:10.32604/cmc.2022.021490

    Abstract With technological advancements in 6G and Internet of Things (IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellular networks has become a hot research topic. At present, the proficient evolution of 6G networks allows the UAVs to offer cost-effective and timely solutions for real-time applications such as medicine, tracking, surveillance, etc. Energy efficiency, data collection, and route planning are crucial processes to improve the network communication. These processes are highly difficult owing to high mobility, presence of non-stationary links, dynamic topology, and energy-restricted UAVs. With this motivation, the current research paper presents a novel Energy Aware Data Collection with… More >

  • Open Access


    An Enhanced Routing and Lifetime Performance for Industrial Wireless Sensor Networks

    J. V. Anchitaalagammai1,*, K. Muthumayil2, D. Kamalraj Subramaniam3, Rajesh Verma4, P. Muralikrishnan5, G. Visalaxi6

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1783-1792, 2022, DOI:10.32604/iasc.2022.020967

    Abstract Industrial Wireless Sensor Networks (IWSNs), especially energy resources, are scarce. Since sensor nodes are usually very dense, and the data sampled by the sensor nodes have high redundancy, data aggregation saves energy, reduces the number of transmissions, and eliminates redundancy. Many applications can be used in IIWSNs, and a new technique is introduced to detect multiple sensors embedded in different sensor nodes. Packets created by different applications have different properties. Sensors are resource-constrained devices because it is necessary to find effective reaction analysis methods and transfer sensed data to base stations. Since sensors are resource-constrained devices, efficient topologies require data… More >

  • Open Access


    Energy Optimization in Multi-UAV-Assisted Edge Data Collection System

    Bin Xu1,2,3, Lu Zhang1, Zipeng Xu1, Yichuan Liu1, Jinming Chai1, Sichong Qin4, Yanfei Sun1,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1671-1686, 2021, DOI:10.32604/cmc.2021.018395

    Abstract In the IoT (Internet of Things) system, the introduction of UAV (Unmanned Aerial Vehicle) as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the limitation of their battery energy. However, the unreasonable distribution of UAVs will still lead to the problem of the high total energy consumption of the system. In this work, to deal with the problem, a deployment model of a mobile edge computing (MEC) system based on multi-UAV is proposed. The goal of the model is to minimize the energy consumption of the… More >

  • Open Access


    An Optimized Data Fusion Paradigm for WSN Based on Neural Networks

    Moath Alsafasfeh1,*, Zaid A. Arida2, Omar A. Saraereh3, Qais Alsafasfeh4, Salem Alemaishat5

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1097-1108, 2021, DOI:10.32604/cmc.2021.018187

    Abstract Wireless sensor networks (WSNs) have gotten a lot of attention as useful tools for gathering data. The energy problem has been a fundamental constraint and challenge faced by many WSN applications due to the size and cost constraints of the sensor nodes. This paper proposed a data fusion model based on the back propagation neural network (BPNN) model to address the problem of a large number of invalid or redundant data. Using three layered-based BPNNs and a TEEN threshold, the proposed model describes the cluster structure and filters out unnecessary details. During the information transmission process, the neural network’s output… More >

  • Open Access


    An Energy-Efficient Mobile-Sink Path-Finding Strategy for UAV WSNs

    Lyk Yin Tan*, Hock Guan Goh, Soung-Yue Liew, Shen Khang Teoh

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3419-3432, 2021, DOI:10.32604/cmc.2021.015402

    Abstract Data collection using a mobile sink in a Wireless Sensor Network (WSN) has received much attention in recent years owing to its potential to reduce the energy consumption of sensor nodes and thus enhancing the lifetime of the WSN. However, a critical issue of this approach is the latency of data to reach the base station. Although many data collection algorithms have been introduced in the literature to reduce delays in data delivery, their performances are affected by the flight trajectory taken by the mobile sink, which might not be optimized yet. This paper proposes a new path-finding strategy, called… More >

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