Firas Abedi¹, Hayder M. A. Ghanimi², Abeer D. Algarni³, Naglaa F. Soliman^3,*, Walid El-Shafai^4,5, Ali Hashim Abbas⁶, Zahraa H. Kareem⁷, Hussein Muhi Hariz⁸, Ahmed Alkhayyat⁹

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3127-3144, 2023, DOI:10.32604/csse.2023.038959 - 09 November 2023

Abstract Computational intelligence (CI) is a group of nature-simulated computational models and processes for addressing difficult real-life problems. The CI is useful in the UAV domain as it produces efficient, precise, and rapid solutions. Besides, unmanned aerial vehicles (UAV) developed a hot research topic in the smart city environment. Despite the benefits of UAVs, security remains a major challenging issue. In addition, deep learning (DL) enabled image classification is useful for several applications such as land cover classification, smart buildings, etc. This paper proposes novel meta-heuristics with a deep learning-driven secure UAV image classification (MDLS-UAVIC) model… More >

Rakhshan Zulfiqar^1,2, Tariq Javed¹, Zain Anwar Ali^2,*, Eman H. Alkhammash³, Myriam Hadjouni⁴

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 985-1000, 2023, DOI:10.32604/iasc.2023.037248 - 29 April 2023

Abstract The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance. The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’ access network. The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness. Coverage and energy usage are mostly determined by successful sensor placement strategies. Nature-inspired algorithms are the most effective solution for short sensor lifetime. The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks (WSNs’) maximum network More >

Aoqi Xu¹, Khalid A. Alattas², Nasreen Kausar³, Ardashir Mohammadzadeh⁴, Ebru Ozbilge^5,*, Tonguc Cagin⁵

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 17-32, 2023, DOI:10.32604/iasc.2023.036623 - 29 April 2023

Abstract In many problems, to analyze the process/metabolism behavior, a model of the system is identified. The main gap is the weakness of current methods vs. noisy environments. The primary objective of this study is to present a more robust method against uncertainties. This paper proposes a new deep learning scheme for modeling and identification applications. The suggested approach is based on non-singleton type-3 fuzzy logic systems (NT3-FLSs) that can support measurement errors and high-level uncertainties. Besides the rule optimization, the antecedent parameters and the level of secondary memberships are also adjusted by the suggested square More >

Mohammad Yamin¹, Abdullah M. Basahel¹, Mona Abusurrah², Sulafah M Basahel³, Sachi Nandan Mohanty⁴, E. Laxmi Lydia^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 409-425, 2023, DOI:10.32604/cmc.2023.032432 - 06 February 2023

Abstract White blood cells (WBC) or leukocytes are a vital component of the blood which forms the immune system, which is accountable to fight foreign elements. The WBC images can be exposed to different data analysis approaches which categorize different kinds of WBC. Conventionally, laboratory tests are carried out to determine the kind of WBC which is erroneous and time consuming. Recently, deep learning (DL) models can be employed for automated investigation of WBC images in short duration. Therefore, this paper introduces an Aquila Optimizer with Transfer Learning based Automated White Blood Cells Classification (AOTL-WBCC) technique.… More >

Ademola Olusola Adesina¹, Patrick Seun Ayobioloja², Ibidun Christiana Obagbuwa³, Tola John Odule¹, Adenrele A. Afolorunso², Sunday Adeola Ajagbe^4,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2661-2675, 2023, DOI:10.32604/cmc.2023.031245 - 31 October 2022

Abstract CAPTCHA is an acronym that stands for Completely Automated Public Turing Test to tell Computers and Humans Apart (CAPTCHA), it is a good example of an authentication system that can be used to determine the true identity of any user. It serves as a security measure to prevent an attack caused by web bots (automatic programs) during an online transaction. It can come as text-based or image-based depending on the project and the programmer. The usability and robustness, as well as level of security, provided each of the varies and call for the development of… More >

Wenjun Zhang¹, Wenfeng Wang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1597-1619, 2023, DOI:10.32604/cmes.2022.020517 - 20 September 2022

Abstract Face recognition has been rapidly developed and widely used. However, there is still considerable uncertainty in the computational intelligence based on human-centric visual understanding. Emerging challenges for face recognition are resulted from information loss. This study aims to tackle these challenges with a broad learning system (BLS). We integrated two models, IR³C with BLS and IR³C with a triplet loss, to control the learning process. In our experiments, we used different strategies to generate more challenging datasets and analyzed the competitiveness, sensitivity, and practicability of the proposed two models. In the model of IR3C with BLS, More >

Jinsu Kim¹, Sungwook Ryu², Namje Park^1,3,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4169-4184, 2022, DOI:10.32604/cmc.2022.019277 - 27 September 2021

Abstract A significant number of cloud storage environments are already implementing deduplication technology. Due to the nature of the cloud environment, a storage server capable of accommodating large-capacity storage is required. As storage capacity increases, additional storage solutions are required. By leveraging deduplication, you can fundamentally solve the cost problem. However, deduplication poses privacy concerns due to the structure itself. In this paper, we point out the privacy infringement problem and propose a new deduplication technique to solve it. In the proposed technique, since the user’s map structure and files are not stored on the server, More >

Fahad Alotaibi¹, Muhammad Attique^2,3, Yaser Daanial Khan^2,*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1039-1055, 2021, DOI:10.32604/cmc.2021.017297 - 04 June 2021

Abstract Several autoimmune ailments and inflammation-related diseases emphasize the need for peptide-based therapeutics for their treatment and established substantial consideration. Though, the wet-lab experiments for the investigation of anti-inflammatory proteins/peptides (“AIP”) are usually very costly and remain time-consuming. Therefore, before wet-lab investigations, it is essential to develop in-silico identification models to classify prospective anti-inflammatory candidates for the facilitation of the drug development process. Several anti-inflammatory prediction tools have been proposed in the recent past, yet, there is a space to induce enhancement in prediction performance in terms of precision and efficiency. An exceedingly accurate anti-inflammatory prediction… More >

Fatmah Baothman^*, Kawther Saeedi, Khulood Aljuhani, Safaa Alkatheri, Mashael Almeatani, Nourah Alothman

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 625-639, 2021, DOI:10.32604/iasc.2021.014827 - 01 March 2021

Abstract Blockchain is an innovative technology that disrupts different industries and offers decentralized, secure, and immutable platforms. Its first appearance is connected with monetary cryptocurrency transactions, followed by adaptation in several domains. We believe that blockchain can provide a reliable environment by utilizing its unique characteristics to offer a more secure, costless, and robust mechanism suitable for a voting application. Although the technology has captured the interest of governments worldwide, blockchain as a service is still limited due to lack of application development experience, technology complexity, and absence of standardized design, architecture, and best practices. Therefore,… More >

Abdul Hannan Khan^1,2, Muhammad Adnan Khan^3,*, Sagheer Abbas², Shahan Yamin Siddiqui^1,2, Muhammad Aanwar Saeed⁴, Majed Alfayad⁵, Nouh Sabri Elmitwally^6,7

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1399-1412, 2021, DOI:10.32604/cmc.2021.012737 - 05 February 2021

Abstract Artificial intelligence (AI) is expanding its roots in medical diagnostics. Various acute and chronic diseases can be identified accurately at the initial level by using AI methods to prevent the progression of health complications. Kidney diseases are producing a high impact on global health and medical practitioners are suggested that the diagnosis at earlier stages is one of the foremost approaches to avert chronic kidney disease and renal failure. High blood pressure, diabetes mellitus, and glomerulonephritis are the root causes of kidney disease. Therefore, the present study is proposed a set of multiple techniques such… More >