Shazia Shamas¹, Surya Narayan Panda^1,*, Ishu Sharma^1,*, Kalpna Guleria¹, Aman Singh^2,3,4, Ahmad Ali AlZubi⁵, Mallak Ahmad AlZubi⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1051-1075, 2024, DOI:10.32604/cmes.2023.030712

Abstract The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis and planning intervention. This research work addresses the major issues pertaining to the field of medical image processing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposes an improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. The better resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In this process, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarm intelligent techniques. The techniques… More >

Weigang Jin¹, Lei Chen^2,*, Yifei Li², Shencong Zheng², Yuqi Jiang², Hongkun Chen²

Energy Engineering, Vol.120, No.11, pp. 2469-2487, 2023, DOI:10.32604/ee.2023.043021

Abstract Along with the increasing integration of renewable energy generation in AC-DC power networks, investigating the dynamic behaviors of this complex system with a proper equivalent model is significant. This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator (DFIG) based wind farms to decrease the simulation scale and computational burden. For the AC-DC power networks, the equivalent modeling strategy in accordance with the physical structure simplification is stated. Regarding the DFIG-based wind farms, the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm (ICCSA) is conducted.… More >

Arkan Kh Shakr Sabonchi^1,*, Zainab Hashim Obaid²

Journal of Information Hiding and Privacy Protection, Vol.5, pp. 1-18, 2023, DOI:10.32604/jihpp.2023.041972

Abstract In the contemporary era, the abundant availability of health information through internet and mobile technology raises concerns. Safeguarding and maintaining the confidentiality of patients’ medical data becomes paramount when sharing such information with authorized healthcare providers. Although electronic patient records and the internet have facilitated the exchange of medical information among healthcare providers, concerns persist regarding the security of the data. The security of Electronic Health Record Systems (EHRS) can be improved by employing the Cuckoo Search Algorithm (CS), the SHA-256 algorithm, and the Elliptic Curve Cryptography (ECC), as proposed in this study. The suggested approach involves using CS to… More >

Arkan Kh Shakr Sabonchi^1,*, Zainab Hashim Obaid²

Journal of Cyber Security, Vol.4, No.4, pp. 269-286, 2022, DOI:10.32604/jcs.2023.041707

Abstract The widespread use of Internet of Things (IoT) devices, such as smart appliances, phones, and watches, has brought about concerns regarding security and privacy. With the increasing prevalence of cyberattacks from both malicious and non-malicious sources, security has become a critical factor in the design of IoT systems. In particular, data security poses a significant challenge due to the growing amount of data stored in IoT systems. Inadequate security measures can allow hackers to take over IoT devices remotely, resulting in significant damage. To address these concerns and improve the security of IoT-based smart door lock systems, this research proposes… More >

Mesfer Al Duhayyim^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2473-2489, 2023, DOI:10.32604/iasc.2023.033585

Abstract Falls are the most common concern among older adults or disabled people who use scooters and wheelchairs. The early detection of disabled persons’ falls is required to increase the living rate of an individual or provide support to them whenever required. In recent times, the arrival of the Internet of Things (IoT), smartphones, Artificial Intelligence (AI), wearables and so on make it easy to design fall detection mechanisms for smart homecare. The current study develops an Automated Disabled People Fall Detection using Cuckoo Search Optimization with Mobile Networks (ADPFD-CSOMN) model. The proposed model’s major aim is to detect and distinguish… More >

P. Ramya^1,*, B. Karthik²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2379-2391, 2023, DOI:10.32604/iasc.2023.026291

Abstract Word Sense Disambiguation has been a trending topic of research in Natural Language Processing and Machine Learning. Mining core features and performing the text classification still exist as a challenging task. Here the features of the context such as neighboring words like adjective provide the evidence for classification using machine learning approach. This paper presented the text document classification that has wide applications in information retrieval, which uses movie review datasets. Here the document indexing based on controlled vocabulary, adjective, word sense disambiguation, generating hierarchical categorization of web pages, spam detection, topic labeling, web search, document summarization, etc. Here the… More >

Weimin Zheng, Mingchao Si, Xiao Sui, Shuchuan Chu, Jengshyang Pan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2173-2196, 2023, DOI:10.32604/cmes.2023.019890

Abstract The meta-heuristic algorithm is a global probabilistic search algorithm for the iterative solution. It has good performance in global optimization fields such as maximization. In this paper, a new adaptive parameter strategy and a parallel communication strategy are proposed to further improve the Cuckoo Search (CS) algorithm. This strategy greatly improves the convergence speed and accuracy of the algorithm and strengthens the algorithm’s ability to jump out of the local optimal. This paper compares the optimization performance of Parallel Adaptive Cuckoo Search (PACS) with CS, Parallel Cuckoo Search (PCS), Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Grey Wolf Optimizer… More >

Pradeep Krishnadoss^*, Vijayakumar Kedalu Poornachary, Parkavi Krishnamoorthy, Leninisha Shanmugam

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2461-2478, 2023, DOI:10.32604/cmc.2023.031614

Abstract Well organized datacentres with interconnected servers constitute the cloud computing infrastructure. User requests are submitted through an interface to these servers that provide service to them in an on-demand basis. The scientific applications that get executed at cloud by making use of the heterogeneous resources being allocated to them in a dynamic manner are grouped under NP hard problem category. Task scheduling in cloud poses numerous challenges impacting the cloud performance. If not handled properly, user satisfaction becomes questionable. More recently researchers had come up with meta-heuristic type of solutions for enriching the task scheduling activity in the cloud environment.… More >

Fahad Alraddady¹, E. A. Zanaty², Aida H. Abu bakr³, Walaa M. Abd-Elhafiez^4,5,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3627-3646, 2023, DOI:10.32604/cmc.2023.027606

Abstract In this paper, we combine decision fusion methods with four meta-heuristic algorithms (Particle Swarm Optimization (PSO) algorithm, Cuckoo search algorithm, modification of Cuckoo Search (CS McCulloch) algorithm and Genetic algorithm) in order to improve the image segmentation. The proposed technique based on fusing the data from Particle Swarm Optimization (PSO), Cuckoo search, modification of Cuckoo Search (CS McCulloch) and Genetic algorithms are obtained for improving magnetic resonance images (MRIs) segmentation. Four algorithms are used to compute the accuracy of each method while the outputs are passed to fusion methods. In order to obtain parts of the points that determine similar… More >

Tao Hou¹, Shan Wang^1,2,*

Energy Engineering, Vol.120, No.1, pp. 87-106, 2023, DOI:10.32604/ee.2022.022122

Abstract The existing Maximum Power Point Tracking (MPPT) method has low tracking efficiency and poor stability. It is easy to fall into the Local Maximum Power Point (LMPP) in Partial Shading Condition (PSC), resulting in the degradation of output power quality and efficiency. It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms, and their performance in tracking the Global Maximum Power Point (GMPP) varies. Thus, a Cuckoo search algorithm (CSA) combined with the Incremental conductance Algorithm (INC) is proposed (CSA-INC) is put forward for the MPPT method of photovoltaic power generation. The method can improve the tracking… More > Graphic Abstract