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  • Open Access

    ARTICLE

    Modeling and Analysis of UAV-Assisted Mobile Network with Imperfect Beam Alignment

    Mohamed Amine Ouamri1,2, Reem Alkanhel3,*, Cedric Gueguen1, Manal Abdullah Alohali4, Sherif S. M. Ghoneim5

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 453-467, 2023, DOI:10.32604/cmc.2023.031450

    Abstract With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed… More >

  • Open Access

    ARTICLE

    Multi-Agent Dynamic Area Coverage Based on Reinforcement Learning with Connected Agents

    Fatih Aydemir1, Aydin Cetin2,*

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 215-230, 2023, DOI:10.32604/csse.2023.031116

    Abstract Dynamic area coverage with small unmanned aerial vehicle (UAV) systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process. Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved. In this paper, we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems. The proposed decentralized decision-making dynamic area coverage (DDMDAC) method utilizes reinforcement learning (RL) where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable environment. Intelligent agents increase their… More >

  • Open Access

    ARTICLE

    Coverage Control for Underwater Sensor Networks Based on Residual Energy Probability

    Jinglin Liang1,2, Qian Sun1,2,*, Xiaoyi Wang3,2, Jiping Xu1,2, Huiyan Zhang1,2, Li Wang1,2, Jiabin Yu1,2, Jing Li4, Ruichao Wang5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5459-5471, 2022, DOI:10.32604/cmc.2022.029362

    Abstract Underwater sensor networks have important application value in the fields of water environment data collection, marine environment monitoring and so on. It has some characteristics such as low available bandwidth, large propagation delays and limited energy, which bring new challenges to the current researches. The research on coverage control of underwater sensor networks is the basis of other related researches. A good sensor node coverage control method can effectively improve the quality of water environment monitoring. Aiming at the problem of high dynamics and uncertainty of monitoring targets, the random events level are divided into serious events and general events.… More >

  • Open Access

    ARTICLE

    Intelligent Deployment Model for Target Coverage in Wireless Sensor Network

    K. Subramanian*, S. Shanmugavel

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 739-754, 2023, DOI:10.32604/iasc.2023.027248

    Abstract Target coverage and continuous connection are the major recital factors for Wireless Sensor Network (WSN). Several previous research works studied various algorithms for target coverage difficulties; however they lacked to focus on improving the network’s life time in terms of energy. This research work mainly focuses on target coverage and area coverage problem in a heterogeneous WSN with increased network lifetime. The dynamic behavior of the target nodes is unpredictable, because the target nodes may move at any time in any direction of the network. Thus, target coverage becomes a major problem in WSN and its applications. To solve the… More >

  • Open Access

    ARTICLE

    Adaptive Multicale Transformation Run-Length Code-Based Test Data Compression in Benchmark Circuits

    P. Thilagavathi*, S. Karthikeyan

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 2035-2050, 2022, DOI:10.32604/iasc.2022.026651

    Abstract Test data volume reduction and power consumption during testing time outlines are two main problems for Very Large Scale Integration (VLSI) gadgets. Most the code-based arrangements have been utilized to diminish test data volume, although the most notable way that test data volume is high. The switching action that happens between the test carriers leads would expand power consumption. This work presents a compression/decompression methodology for limiting the amount of test data that should be kept on a tester and conveyed to each center in a System on a Chip (SOC) during a test utilizing the Adaptive Multiscale Transformation Run… More >

  • Open Access

    ARTICLE

    Fault Tolerance Techniques for Multi-Hop Clustering in Wireless Sensor Networks

    Adel Rajab*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1743-1761, 2022, DOI:10.32604/iasc.2022.021922

    Abstract Wireless sensor networks (WSN) deploy many nodes over an extended area for traffic surveillance, environmental monitoring, healthcare, tracking wildlife, and military sensing. Nodes of the WSN have a limited amount of energy. Each sensor node collects information from the surrounding area and forwards it onto the cluster head, which then sends it on to the base station (BS). WSNs extend the lifetime of the network through clustering techniques. Choosing nodes with the greatest residual energy as cluster heads is based on the idea that energy consumption is periodically distributed between nodes. The sink node gathers information from its environment that… More >

  • Open Access

    ARTICLE

    Media Coverage of Terrorism and Mental Health Concerns among Youth: Testing Moderated Mediation by Spirituality and Resilience

    Mian Ahmad Hanan1,*, Arooj Arshad2, Noshina Saleem3, Shamaila Asad2

    International Journal of Mental Health Promotion, Vol.23, No.4, pp. 565-575, 2021, DOI:10.32604/IJMHP.2021.011168

    Abstract Previous research on media coverage of terrorism and its associated psychological consequences was explored internationally particularly after 9/11 attacks in the US. Also, the constructive role of resilience in this traumatic era has also been explored internationally. However, some studies have been conducted on the effect of media coverage of national terrorism on people that have endured a nearby terrorist attack. Moreover, knowledge about how the media coverage of terrorism, as a secondary source of evidence, can have devastated effects on native’s mental health and how resilience work in this relationship is rather limited. For example, it is possible that… More >

  • Open Access

    ARTICLE

    Effectiveness Assessment of the Search-Based Statistical Structural Testing

    Yang Shi*, Xiaoyu Song, Marek Perkowski, Fu Li

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2191-2207, 2022, DOI:10.32604/cmc.2022.018718

    Abstract Search-based statistical structural testing (SBSST) is a promising technique that uses automated search to construct input distributions for statistical structural testing. It has been proved that a simple search algorithm, for example, the hill-climber is able to optimize an input distribution. However, due to the noisy fitness estimation of the minimum triggering probability among all cover elements (Tri-Low-Bound), the existing approach does not show a satisfactory efficiency. Constructing input distributions to satisfy the Tri-Low-Bound criterion requires an extensive computation time. Tri-Low-Bound is considered a strong criterion, and it is demonstrated to sustain a high fault-detecting ability. This article tries to… More >

  • Open Access

    ARTICLE

    Improving Routine Immunization Coverage Through Optimally Designed Predictive Models

    Fareeha Sameen1, Abdul Momin Kazi2, Majida Kazmi1,*, Munir A Abbasi3, Saad Ahmed Qazi1,4, Lampros K Stergioulas3,5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 375-395, 2022, DOI:10.32604/cmc.2022.019167

    Abstract Routine immunization (RI) of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe. Pakistan being a low-and-middle-income-country (LMIC) has one of the highest child mortality rates in the world occurring mainly due to vaccine-preventable diseases (VPDs). For improving RI coverage, a critical need is to establish potential RI defaulters at an early stage, so that appropriate interventions can be targeted towards such population who are identified to be at risk of missing on their scheduled vaccine uptakes. In this paper, a machine learning (ML) based predictive model has been proposed to… More >

  • Open Access

    ARTICLE

    SmartCrawler: A Three-Stage Ranking Based Web Crawler for Harvesting Hidden Web Sources

    Sawroop Kaur1, Aman Singh1,*, G. Geetha2, Mehedi Masud3, Mohammed A. Alzain4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2933-2948, 2021, DOI:10.32604/cmc.2021.019030

    Abstract Web crawlers have evolved from performing a meagre task of collecting statistics, security testing, web indexing and numerous other examples. The size and dynamism of the web are making crawling an interesting and challenging task. Researchers have tackled various issues and challenges related to web crawling. One such issue is efficiently discovering hidden web data. Web crawler’s inability to work with form-based data, lack of benchmarks and standards for both performance measures and datasets for evaluation of the web crawlers make it still an immature research domain. The applications like vertical portals and data integration require hidden web crawling. Most… More >

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