Open Access

REVIEW

Zain Anwar Ali^1,2,*, Dingnan Deng¹, Muhammad Kashif Shaikh³, Raza Hasan⁴, Muhammad Aamir Khan²
Computer Systems Science and Engineering, Vol.48, No.1, pp. 1-34, 2024, DOI:10.32604/csse.2023.041866 - 26 January 2024
Abstract Technological advances in unmanned aerial vehicles (UAVs) pursued by artificial intelligence (AI) are improving remote sensing applications in smart agriculture. These are valuable tools for monitoring and disease identification of plants as they can collect data with no damage and effects on plants. However, their limited carrying and battery capacities restrict their performance in larger areas. Therefore, using multiple UAVs, especially in the form of a swarm is more significant for monitoring larger areas such as crop fields and forests. The diversity of research studies necessitates a literature review for more progress and contribution in… More >

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Hayder Makki Shakir, Jaber Karimpour^*, Jafar Razmara
Computer Systems Science and Engineering, Vol.48, No.1, pp. 35-55, 2024, DOI:10.32604/csse.2023.038545 - 26 January 2024
Abstract As the volume of data and data-generating equipment in healthcare settings grows, so do issues like latency and inefficient processing inside health monitoring systems. The Internet of Things (IoT) has been used to create a wide variety of health monitoring systems. Most modern health monitoring solutions are based on cloud computing. However, large-scale deployment of latency-sensitive healthcare applications is hampered by the cloud’s design, which introduces significant delays during the processing of vast data volumes. By strategically positioning servers close to end users, fog computing mitigates latency issues and dramatically improves scaling on demand, resource… More >

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462

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ARTICLE

P. Nandakumar, R. Subhashini^*
Computer Systems Science and Engineering, Vol.48, No.1, pp. 57-75, 2024, DOI:10.32604/csse.2023.042294 - 26 January 2024
Abstract Heart disease is a major cause of death for many people in the world. Each year the death rate of people affected with heart disease increased a lot. Machine learning models have been widely used for the prediction of heart disease from the different University of California Irvine (UCI) Machine Learning Repositories. But, due to certain data, it predicts less accurately, whereas, for large data, its sub-model deep learning is used. Our literature work has identified that only traditional methods are used for the prediction of heart disease. It will produce less accuracy. To produce… More >

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476

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ARTICLE

Nadir Omer^1,*, Ahmed H. Samak², Ahmed I. Taloba^3,4, Rasha M. Abd El-Aziz^3,5
Computer Systems Science and Engineering, Vol.48, No.1, pp. 77-95, 2024, DOI:10.32604/csse.2023.039265 - 26 January 2024
（This article belongs to the Special Issue: Explainable AI and Cybersecurity Techniques for IoT-Based Medical and Healthcare Applications)
Abstract Today’s world depends on the Internet to meet all its daily needs. The usage of the Internet is growing rapidly. The world is using the Internet more frequently than ever. The hazards of harmful attacks have also increased due to the growing reliance on the Internet. Hazards to cyber security are actions taken by someone with malicious intent to steal data, destroy computer systems, or disrupt them. Due to rising cyber security concerns, cyber security has emerged as the key component in the fight against all online threats, forgeries, and assaults. A device capable of… More >

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510

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ARTICLE

Manar Ahmed Hamza^1,*, Hala J. Alshahrani², Najm Alotaibi³, Mohamed K. Nour⁴, Mahmoud Othman⁵, Gouse Pasha Mohammed¹, Mohammed Rizwanullah¹, Mohamed I. Eldesouki⁶
Computer Systems Science and Engineering, Vol.48, No.1, pp. 97-114, 2024, DOI:10.32604/csse.2023.034520 - 26 January 2024
Abstract Computational linguistics is the scientific and engineering discipline related to comprehending written and spoken language from a computational perspective and building artefacts that effectively process and produce language, either in bulk or in a dialogue setting. This paper develops a Chaotic Bird Swarm Optimization with deep ensemble learning based Arabic poem classification and dictarization (CBSOEDL-APCD) technique. The presented CBSOEDL-APCD technique involves the classification and dictarization of Arabic text into Arabic poetries and prose. Primarily, the CBSOEDL-APCD technique carries out data pre-processing to convert it into a useful format. Besides, the ensemble deep learning (EDL) model More >

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336

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ARTICLE

A. Vikram¹, J. Akshya², Sultan Ahmad^3,4, L. Jerlin Rubini⁵, Seifedine Kadry^6,7,8, Jungeun Kim^9,*
Computer Systems Science and Engineering, Vol.48, No.1, pp. 115-130, 2024, DOI:10.32604/csse.2023.037928 - 26 January 2024
Abstract Traffic monitoring through remote sensing images (RSI) is considered an important research area in Intelligent Transportation Systems (ITSs). Vehicle counting systems must be simple enough to be implemented in real-time. With the fast expansion of road traffic, real-time vehicle counting becomes essential in constructing ITS. Compared with conventional technologies, the remote sensing-related technique for vehicle counting exhibits greater significance and considerable advantages in its flexibility, low cost, and high efficiency. But several techniques need help in balancing complexity and accuracy technique. Therefore, this article presents a deep learning-based vehicle detection and counting system for ITS More >

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ARTICLE

Jameel Almalki^*
Computer Systems Science and Engineering, Vol.48, No.1, pp. 131-152, 2024, DOI:10.32604/csse.2023.038085 - 26 January 2024
（This article belongs to the Special Issue: Explainable AI and Cybersecurity Techniques for IoT-Based Medical and Healthcare Applications)
Abstract The recent global pandemic has resulted in growth in the medical and healthcare sectors. Applications used in these domains have become more advanced and digitally integrated. Sensor-based Internet of Things (IoT) devices are increasing in healthcare and medical units. The emerging trend with the use of IoT devices in medical healthcare is termed as Internet of Medical Things (IoMT). The instruments used in these healthcare units comprise various sensors that can record patient body observations. These recorded observations are streamed across Internet-based channels to be stored and analyzed in centralized servers. Patient diagnostics are performed… More >

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389

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ARTICLE

Noman Khan^1,2, Samee Ullah Khan^1,2, Sung Wook Baik^1,2,*
Computer Systems Science and Engineering, Vol.48, No.1, pp. 153-173, 2024, DOI:10.32604/csse.2023.039407 - 26 January 2024
（This article belongs to the Special Issue: Metaheuristics Optimization for Real-World Applications)
Abstract Energy management systems for residential and commercial buildings must use an appropriate and efficient model to predict energy consumption accurately. To deal with the challenges in power management, the short-term Power Consumption (PC) prediction for household appliances plays a vital role in improving domestic and commercial energy efficiency. Big data applications and analytics have shown that data-driven load forecasting approaches can forecast PC in commercial and residential sectors and recognize patterns of electric usage in complex conditions. However, traditional Machine Learning (ML) algorithms and their features engineering procedure emphasize the practice of inefficient and ineffective… More >

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448

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ARTICLE

Nesreen M. Alharbi^*, Ahmed Hamza Osman, Arwa A. Mashat, Hasan J. Alyamani
Computer Systems Science and Engineering, Vol.48, No.1, pp. 175-198, 2024, DOI:10.32604/csse.2023.041044 - 26 January 2024
Abstract Recent years have witnessed significant advancements in the field of character recognition, thanks to the revolutionary introduction of machine learning techniques. Among various types of character recognition, offline Handwritten Character Recognition (HCR) is comparatively more challenging as it lacks temporal information, such as stroke count and direction, ink pressure, and unexpected handwriting variability. These issues contribute to a poor level of precision, which calls for the adoption of anomaly detection techniques to enhance Optical Character Recognition (OCR) schemes. Previous studies have not researched unsupervised anomaly detection using MLP for handwriting recognition. Therefore, this study proposes… More >

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309

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Ahmad Almadhor¹, Chitapong Wechtaisong^2,*, Usman Tariq³, Natalia Kryvinska^4,*, Abdullah Al Hejaili⁵, Uzma Ghulam Mohammad⁶, Mohana Alanazi⁷
Computer Systems Science and Engineering, Vol.48, No.1, pp. 199-216, 2024, DOI:10.32604/csse.2023.039546 - 26 January 2024
Abstract Thermal comfort is an essential component of smart cities that helps to upgrade, analyze, and realize intelligent buildings. It strongly affects human psychological and physiological levels. Residents of buildings suffer stress because of poor thermal comfort. Buildings frequently use Heating, Ventilation, and Air Conditioning (HVAC) systems for temperature control. Better thermal states directly impact people’s productivity and health. This study revealed a human thermal comfort model that makes better predictions of thermal sensation by identifying essential features and employing a tuned Extra Tree classifier, MultiLayer Perceptron (MLP) and Naive Bayes (NB) models. The study employs More >

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400

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ARTICLE

Xiaodan Wang^*, Peng Wang, Yafei Song, Qian Xiang, Jingtai Li
Computer Systems Science and Engineering, Vol.48, No.1, pp. 217-246, 2024, DOI:10.32604/csse.2023.039846 - 26 January 2024
（This article belongs to the Special Issue: Pattern Recognition Based on Machine Learning)
Abstract High-resolution range profile (HRRP) automatic recognition has been widely applied to military and civilian domains. Present HRRP recognition methods have difficulty extracting deep and global information about the HRRP sequence, which performs poorly in real scenes due to the ambient noise, variant targets, and limited data. Moreover, most existing methods improve the recognition performance by stacking a large number of modules, but ignore the lightweight of methods, resulting in over-parameterization and complex computational effort, which will be challenging to meet the deployment and application on edge devices. To tackle the above problems, this paper proposes… More >

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297

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ARTICLE

Sanxiu Jiao¹, Lecai Cai^2,*, Jintao Meng³, Yue Zhao³, Kui Cheng²
Computer Systems Science and Engineering, Vol.48, No.1, pp. 247-265, 2024, DOI:10.32604/csse.2023.040194 - 26 January 2024
（This article belongs to the Special Issue: Security and Privacy Challenges in Smart City)
Abstract Federated learning is a distributed machine learning framework that solves data security and data island problems faced by artificial intelligence. However, federated learning frameworks are not always secure, and attackers can attack customer privacy information by analyzing parameters in the training process of federated learning models. To solve the problems of data security and availability during federated learning training, this paper proposes an Efficient Differential Privacy Federated Learning Algorithm based on early stopping mechanism (Efficient DP-FL). This method inherits the advantages of differential privacy and federated learning and improves the performance of model training while More >

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390

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CORRECTION

L. Maria Michael Visuwasam^1,*, D. Paul Raj²
Computer Systems Science and Engineering, Vol.48, No.1, pp. 267-267, 2024, DOI:10.32604/csse.2023.047461 - 26 January 2024
Abstract This article has no abstract. More >

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317

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CORRECTION

Anuj Singh^*, Raman Kumar, Arvind Kumar Tiwari
Computer Systems Science and Engineering, Vol.48, No.1, pp. 269-269, 2024, DOI:10.32604/csse.2023.047533 - 26 January 2024
Abstract This article has no abstract. More >

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701

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330

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CORRECTION

Mariem Belhor^1,2,3, Adnen El-Amraoui^1,*, Abderrazak Jemai², François Delmotte¹
Computer Systems Science and Engineering, Vol.48, No.1, pp. 271-271, 2024, DOI:10.32604/csse.2023.048573 - 26 January 2024
Abstract This article has no abstract. More >

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