Qiang Zhi¹, Xiang Jiang¹, Hangying Zhang², Zhengshu Zhou³, Jianguo Ren¹, Tong Huang^4,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 389-402, 2023, DOI:10.32604/csse.2023.035576 - 20 January 2023

Abstract The lightweight encryption algorithm based on Add-Rotation-XOR (ARX) operation has attracted much attention due to its high software affinity and fast operation speed. However, lacking an effective defense scheme for physical attacks limits the applications of the ARX algorithm. The critical challenge is how to weaken the direct dependence between the physical information and the secret key of the algorithm at a low cost. This study attempts to explore how to improve its physical security in practical application scenarios by analyzing the masking countermeasures of ARX algorithms and the leakage causes. Firstly, we specify a More >

Maha Sabir¹, Jawad Ahmad^2,*, Daniyal Alghazzawi¹

Computer Systems Science and Engineering, Vol.46, No.1, pp. 57-72, 2023, DOI:10.32604/csse.2023.034277 - 20 January 2023

Abstract The Internet of things (IoT) is an emerging paradigm that integrates devices and services to collect real-time data from surroundings and process the information at a very high speed to make a decision. Despite several advantages, the resource-constrained and heterogeneous nature of IoT networks makes them a favorite target for cybercriminals. A single successful attempt of network intrusion can compromise the complete IoT network which can lead to unauthorized access to the valuable information of consumers and industries. To overcome the security challenges of IoT networks, this article proposes a lightweight deep autoencoder (DAE) based… More >

Mesfer Alduhayyem^1,*, Mrim M. Alnfiai^2,3, Nabil Almalki⁴, Fahd N. Al-Wesabi⁵, Anwer Mustafa Hilal⁶, Manar Ahmed Hamza⁶

Computer Systems Science and Engineering, Vol.46, No.1, pp. 475-489, 2023, DOI:10.32604/csse.2023.034067 - 20 January 2023

Abstract Visual impairment is one of the major problems among people of all age groups across the globe. Visually Impaired Persons (VIPs) require help from others to carry out their day-to-day tasks. Since they experience several problems in their daily lives, technical intervention can help them resolve the challenges. In this background, an automatic object detection tool is the need of the hour to empower VIPs with safe navigation. The recent advances in the Internet of Things (IoT) and Deep Learning (DL) techniques make it possible. The current study proposes IoT-assisted Transient Search Optimization with a… More >

Abdullah Alqahtani¹, Shtwai Alsubai¹, Mohemmed Sha^1,*, Muhammad Attique Khan², Majed Alhaisoni³, Syed Rameez Naqvi²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 107-123, 2023, DOI:10.32604/csse.2023.030727 - 20 January 2023

Abstract White blood cells (WBC) are immune system cells, which is why they are also known as immune cells. They protect the human body from a variety of dangerous diseases and outside invaders. The majority of WBCs come from red bone marrow, although some come from other important organs in the body. Because manual diagnosis of blood disorders is difficult, it is necessary to design a computerized technique. Researchers have introduced various automated strategies in recent years, but they still face several obstacles, such as imbalanced datasets, incorrect feature selection, and incorrect deep model selection. We… More >

Donghai Li^1,2, Jiawei Tian¹, Shengwen Shi², Shanchao Wang², Jucai Deng², Shuilong He^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 421-445, 2023, DOI:10.32604/cmes.2023.024133 - 05 January 2023

Abstract To better improve the lightweight and fatigue durability performance of the tractor cab, a multi-objective lightweight design of the cab was carried out in this study. First, the finite element model of the cab with counterweight loading was established and then confirmed by the physical testing, and use the inertial relief method to obtain stress distribution under unit load. The cab-frame rigid-flexible coupling multi-body dynamics model was built by Adams/car software. Taking the cab airbag mount displacement and acceleration signals acquired on the proving ground as the desired signals and obtaining the fatigue analysis load… More > Graphic Abstract

Mahdi Sahlabadi, Ravie Chandren Muniyandi, Zarina Shukur, Faizan Qamar^*, Syed Hussain Ali Kazmi

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5777-5797, 2023, DOI:10.32604/cmc.2023.032504 - 28 December 2022

Abstract This research recognizes the limitation and challenges of adapting and applying Process Mining as a powerful tool and technique in the Hypothetical Software Architecture (SA) Evaluation Framework with the features and factors of lightweightness. Process mining deals with the large-scale complexity of security and performance analysis, which are the goals of SA evaluation frameworks. As a result of these conjectures, all Process Mining researches in the realm of SA are thoroughly reviewed, and nine challenges for Process Mining Adaption are recognized. Process mining is embedded in the framework and to boost the quality of the… More >

Chang Zhang¹, Ruiwen Ni¹, Ye Mu^1,2,3,4, Yu Sun^1,2,3,4,*, Thobela Louis Tyasi⁵

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 983-994, 2023, DOI:10.32604/cmc.2023.027269 - 22 September 2022

Abstract In the field of agricultural information, the identification and prediction of rice leaf disease have always been the focus of research, and deep learning (DL) technology is currently a hot research topic in the field of pattern recognition. The research and development of high-efficiency, high-quality and low-cost automatic identification methods for rice diseases that can replace humans is an important means of dealing with the current situation from a technical perspective. This paper mainly focuses on the problem of huge parameters of the Convolutional Neural Network (CNN) model and proposes a recognition model that combines More >

Yingpeng Dai¹, Junzheng Wang¹, Jing Li^1,*, Lingfeng Meng², Songfeng Wang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 135-156, 2023, DOI:10.32604/cmes.2022.021525 - 24 August 2022

Abstract It is important for the autonomous system to understand environmental information. For the autonomous system, it is desirable to have a strong generalization ability to deal with different complex environmental information, as well as have high accuracy and quick inference speed. Network ensemble architecture is a good choice to improve network performance. However, it is unsuitable for real-time applications on the autonomous system. To tackle this problem, a new neural network ensemble named partial-shared ensemble network (PSENet) is presented. PSENet changes network ensemble architecture from parallel architecture to scatter architecture and merges multiple component networks More >

P. Anantha Prabha^1,*, G. Suchitra², R. Saravanan³

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3065-3079, 2023, DOI:10.32604/iasc.2023.030017 - 17 August 2022

Abstract Cephalopods identification is a formidable task that involves hand inspection and close observation by a malacologist. Manual observation and identification take time and are always contingent on the involvement of experts. A system is proposed to alleviate this challenge that uses transfer learning techniques to classify the cephalopods automatically. In the proposed method, only the Lightweight pre-trained networks are chosen to enable IoT in the task of cephalopod recognition. First, the efficiency of the chosen models is determined by evaluating their performance and comparing the findings. Second, the models are fine-tuned by adding dense layers… More >

Sara A. Alameen^*, Areej M. Alhothali

Computer Systems Science and Engineering, Vol.44, No.1, pp. 895-912, 2023, DOI:10.32604/csse.2023.024643 - 01 June 2022

Abstract Today, fatalities, physical injuries, and significant economic losses occur due to car accidents. Among the leading causes of car accidents is drowsiness behind the wheel, which can affect any driver. Drowsiness and sleepiness often have associated indicators that researchers can use to identify and promptly warn drowsy drivers to avoid potential accidents. This paper proposes a spatiotemporal model for monitoring drowsiness visual indicators from videos. This model depends on integrating a 3D convolutional neural network (3D-CNN) and long short-term memory (LSTM). The 3DCNN-LSTM can analyze long sequences by applying the 3D-CNN to extract spatiotemporal features… More >