Eungyu Lee, Yongsoo Lee, Taejin Lee^*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1919-1935, 2023, DOI:10.32604/csse.2023.039599 - 28 July 2023

Abstract Artificial Intelligence (AI) technology has been extensively researched in various fields, including the field of malware detection. AI models must be trustworthy to introduce AI systems into critical decision-making and resource protection roles. The problem of robustness to adversarial attacks is a significant barrier to trustworthy AI. Although various adversarial attack and defense methods are actively being studied, there is a lack of research on robustness evaluation metrics that serve as standards for determining whether AI models are safe and reliable against adversarial attacks. An AI model’s robustness level cannot be evaluated by traditional evaluation… More >

Wenshun Sheng^*, Xiongfeng Yu, Jiayan Lin, Xin Chen

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1549-1569, 2023, DOI:10.32604/csse.2023.039410 - 28 July 2023

Abstract Small targets and occluded targets will inevitably appear in the image during the shooting process due to the influence of angle, distance, complex scene, illumination intensity, and other factors. These targets have few effective pixels, few features, and no apparent features, which makes extracting their efficient features difficult and easily leads to false detection, missed detection, and repeated detection, affecting the performance of target detection models. An improved faster region convolutional neural network (RCNN) algorithm (CF-RCNN) integrating convolutional block attention module (CBAM) and feature pyramid networks (FPN) is proposed to improve the detection and recognition… More >

Zeyu Zhang¹, Han Zhu¹, Wei Zhang¹, Zhiming Cai^2,*, Linkai Zhu², Zefeng Li²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1901-1917, 2023, DOI:10.32604/csse.2023.039395 - 28 July 2023

Abstract With the rapid development of urban road traffic and the increasing number of vehicles, how to alleviate traffic congestion is one of the hot issues that need to be urgently addressed in building smart cities. Therefore, in this paper, a nonlinear multi-objective optimization model of urban intersection signal timing based on a Genetic Algorithm was constructed. Specifically, a typical urban intersection was selected as the research object, and drivers’ acceleration habits were taken into account. What’s more, the shortest average delay time, the least average number of stops, and the maximum capacity of the intersection… More >

Arfat Ahmad Khan¹, Shtwai Alsubai², Chitapong Wechtaisong^3,*, Ahmad Almadhor⁴, Natalia Kryvinska^5,*, Abdullah Al Hejaili⁶, Uzma Ghulam Mohammad⁷

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1733-1750, 2023, DOI:10.32604/csse.2023.039296 - 28 July 2023

Abstract A cataract is one of the most significant eye problems worldwide that does not immediately impair vision and progressively worsens over time. Automatic cataract prediction based on various imaging technologies has been addressed recently, such as smartphone apps used for remote health monitoring and eye treatment. In recent years, advances in diagnosis, prediction, and clinical decision support using Artificial Intelligence (AI) in medicine and ophthalmology have been exponential. Due to privacy concerns, a lack of data makes applying artificial intelligence models in the medical field challenging. To address this issue, a federated learning framework named CD-FL… More >

Jingtong Peng^*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2275-2291, 2023, DOI:10.32604/csse.2023.039272 - 28 July 2023

Abstract When applied to Unmanned Aerial Vehicles (UAVs), existing Simultaneous Localization and Mapping (SLAM) algorithms are constrained by several factors, notably the interference of dynamic outdoor objects, the limited computing performance of UAVs, and the holes caused by dynamic objects removal in the map. We proposed a new SLAM system for UAVs in dynamic environments to solve these problems based on ORB-SLAM2. We have improved the Pyramid Scene Parsing Network (PSPNet) using Depthwise Separable Convolution to reduce the model parameters. We also incorporated an auxiliary loss function to supervise the hidden layer to enhance accuracy. Then… More >

Athena George¹, Bejoy Abraham², Neetha George³, Linu Shine³, Sivakumar Ramachandran^4,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2097-2118, 2023, DOI:10.32604/csse.2023.039262 - 28 July 2023

Abstract Neurodegeneration is the gradual deterioration and eventual death of brain cells, leading to progressive loss of structure and function of neurons in the brain and nervous system. Neurodegenerative disorders, such as Alzheimer’s, Huntington’s, Parkinson’s, amyotrophic lateral sclerosis, multiple system atrophy, and multiple sclerosis, are characterized by progressive deterioration of brain function, resulting in symptoms such as memory impairment, movement difficulties, and cognitive decline. Early diagnosis of these conditions is crucial to slowing down cell degeneration and reducing the severity of the diseases. Magnetic resonance imaging (MRI) is widely used by neurologists for diagnosing brain abnormalities.… More >

Hanmin Ye^1,2, Yinghui Zhou¹, Xiaomei Tao^3,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1709-1732, 2023, DOI:10.32604/csse.2023.039186 - 28 July 2023

Abstract With the popularity of online learning and due to the significant influence of emotion on the learning effect, more and more researches focus on emotion recognition in online learning. Most of the current research uses the comments of the learning platform or the learner’s expression for emotion recognition. The research data on other modalities are scarce. Most of the studies also ignore the impact of instructional videos on learners and the guidance of knowledge on data. Because of the need for other modal research data, we construct a synchronous multimodal data set for analyzing learners’… More >

Ahmad Almadhor^1,*, Arfat Ahmad Khan², Chitapong Wechtaisong^3,*, Iqra Yousaf⁴, Natalia Kryvinska⁵, Usman Tariq⁶, Haithem Ben Chikha¹

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1775-1791, 2023, DOI:10.32604/csse.2023.039007 - 28 July 2023

Abstract Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse, causing air to enter the pleural cavity, the area close to the lungs and chest wall. The most persistent disease, as well as one that necessitates particular patient care and the privacy of their health records. The radiologists find it challenging to diagnose pneumothorax due to the variations in images. Deep learning-based techniques are commonly employed to solve image categorization and segmentation problems. However, it is challenging to employ it in the medical field due to privacy issues and a lack of data.… More >

Rundong Yang^1,*, Kangfeng Zheng¹, Xiujuan Wang², Bin Wu¹, Chunhua Wu¹

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2153-2170, 2023, DOI:10.32604/csse.2023.038917 - 28 July 2023

Abstract Social engineering attacks are considered one of the most hazardous cyberattacks in cybersecurity, as human vulnerabilities are often the weakest link in the entire network. Such vulnerabilities are becoming increasingly susceptible to network security risks. Addressing the social engineering attack defense problem has been the focus of many studies. However, two main challenges hinder its successful resolution. Firstly, the vulnerabilities in social engineering attacks are unique due to multistage attacks, leading to incorrect social engineering defense strategies. Secondly, social engineering attacks are real-time, and the defense strategy algorithms based on gaming or reinforcement learning are… More >

Tomader Almeshal^1,*, Jawad Berri¹, Tarifa Almulhim², Areej Alhogail¹, Emam Ahmed³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1665-1690, 2023, DOI:10.32604/csse.2023.038871 - 28 July 2023

Abstract Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency. The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems, as well as the possibility to create new business models which can increase a firm’s competitiveness. Due to the novelty of the technology, whereby many companies are still exploring potential use cases, and considering the complexity of blockchain technology, which may require huge changes to a company’s existing systems and processes, it is important for companies… More >