Iftikhar Naseer^1,*, Tehreem Masood¹, Sheeraz Akram¹, Arfan Jaffar¹, Muhammad Rashid², Muhammad Amjad Iqbal³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2039-2054, 2023, DOI:10.32604/cmc.2023.032927

Abstract Lung cancer is the most dangerous and death-causing disease indicated by the presence of pulmonary nodules in the lung. It is mostly caused by the instinctive growth of cells in the lung. Lung nodule detection has a significant role in detecting and screening lung cancer in Computed tomography (CT) scan images. Early detection plays an important role in the survival rate and treatment of lung cancer patients. Moreover, pulmonary nodule classification techniques based on the convolutional neural network can be used for the accurate and efficient detection of lung cancer. This work proposed an automatic nodule detection method in CT… More >

Xiaoting Liang¹, Fang Liu^1,*, Linqi Wang¹, Baoying Zheng¹, Yiyuan Sun²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 469-488, 2023, DOI:10.32604/cmc.2023.029641

Abstract Driven by the visions of the Internet of Things (IoT), Artificial Intelligence (AI), and 5G communications, the Internet of Cultural Things (IoCT) realize the comprehensive interconnection among cultural products, cultural services, cultural resources, and cultural platforms, bringing individuals with richer humanistic experience, increasing economic benefits for the cultural sector, and promoting the development of cultural heritage protection and education. At present, IoCT has received widespread attention in both industry and academia. To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications, this survey provides a comprehensive overview of the IoCT components and key technologies.… More >

Ahyoung Lee¹, Jui Mhatre¹, Rupak Kumar Das², Min Hong^3,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 435-452, 2023, DOI:10.32604/cmc.2023.029340

Abstract Healthcare is a fundamental part of every individual’s life. The healthcare industry is developing very rapidly with the help of advanced technologies. Many researchers are trying to build cloud-based healthcare applications that can be accessed by healthcare professionals from their premises, as well as by patients from their mobile devices through communication interfaces. These systems promote reliable and remote interactions between patients and healthcare professionals. However, there are several limitations to these innovative cloud computing-based systems, namely network availability, latency, battery life and resource availability. We propose a hybrid mobile cloud computing (HMCC) architecture to address these challenges. Furthermore, we… 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

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 together to accelerate the inference… More >

Zhengyuan Xu^1,2,#, Junxiao Yu^1,#, Wentao Xiang¹, Songsheng Zhu¹, Mubashir Hussain³, Bin Liu^1,*, Jianqing Li^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 157-177, 2023, DOI: 10.32604/cmes.2022.020035

Abstract In this article, to reduce the complexity and improve the generalization ability of current gesture recognition systems, we propose a novel SE-CNN attention architecture for sEMG-based hand gesture recognition. The proposed algorithm introduces a temporal squeeze-and-excite block into a simple CNN architecture and then utilizes it to recalibrate the weights of the feature outputs from the convolutional layer. By enhancing important features while suppressing useless ones, the model realizes gesture recognition efficiently. The last procedure of the proposed algorithm is utilizing a simple attention mechanism to enhance the learned representations of sEMG signals to perform multi-channel sEMG-based gesture recognition tasks.… More >

Meherab Mamun Ratul, Kazi Ayesha Rahman, Javeria Fazal, Naimur Rahman Abanto, Riasat Khan^*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3641-3658, 2023, DOI:10.32604/iasc.2023.030638

Abstract The coronavirus (COVID-19) is a lethal virus causing a rapidly infectious disease throughout the globe. Spreading awareness, taking preventive measures, imposing strict restrictions on public gatherings, wearing facial masks, and maintaining safe social distancing have become crucial factors in keeping the virus at bay. Even though the world has spent a whole year preventing and curing the disease caused by the COVID-19 virus, the statistics show that the virus can cause an outbreak at any time on a large scale if thorough preventive measures are not maintained accordingly. To fight the spread of this virus, technologically developed systems have become… More >

M. Daniel Nareshkumar^1,*, B. Jaison²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3501-3515, 2023, DOI:10.32604/iasc.2023.027848

Abstract With advancements in computing powers and the overall quality of images captured on everyday cameras, a much wider range of possibilities has opened in various scenarios. This fact has several implications for deaf and dumb people as they have a chance to communicate with a greater number of people much easier. More than ever before, there is a plethora of info about sign language usage in the real world. Sign languages, and by extension the datasets available, are of two forms, isolated sign language and continuous sign language. The main difference between the two types is that in isolated sign… More >

Na Hyoun Kim, Namgyu Kim^*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2667-2682, 2023, DOI:10.32604/csse.2023.029732

Abstract Object detection, one of the core research topics in computer vision, is extensively used in various industrial activities. Although there have been many studies of daytime images where objects can be easily detected, there is relatively little research on nighttime images. In the case of nighttime, various types of noises, such as darkness, haze, and light blur, deteriorate image quality. Thus, an appropriate process for removing noise must precede to improve object detection performance. Although there are many studies on removing individual noise, only a few studies handle multiple noises simultaneously. In this paper, we propose a convolutional denoising autoencoder… More >

Settawit Poochaya^1,*, Peerapong Uthansakul¹, Monthippa Uthansakul¹, Patikorn Anchuen², Kontorn Thammakul³, Arfat Ahmad Khan⁴, Niwat Punanwarakorn⁵, Pech Sirivoratum⁵, Aranya Kaewkrad⁵, Panrawee Kanpan⁵, Apichart Wantamee⁵

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5845-5862, 2022, DOI:10.32604/cmc.2022.031162

Abstract The number of accidents in the campus of Suranaree University of Technology (SUT) has increased due to increasing number of personal vehicles. In this paper, we focus on the development of public transportation system using Intelligent Transportation System (ITS) along with the limitation of personal vehicles using sharing economy model. The SUT Smart Transit is utilized as a major public transportation system, while MoreSai@SUT (electric motorcycle services) is a minor public transportation system in this work. They are called Multi-Mode Transportation system as a combination. Moreover, a Vehicle to Network (V2N) is used for developing the Multi-Mode Transportation system in… More >

N. Penchalaiah¹, Abeer S. Al-Humaimeedy², Mashael Maashi³, J. Chinna Babu^4,*, Osamah Ibrahim Khalaf⁵, Theyazn H. H. Aldhyani⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5349-5365, 2022, DOI:10.32604/cmc.2022.029639

Abstract The expanding amounts of information created by Internet of Things (IoT) devices places a strain on cloud computing, which is often used for data analysis and storage. This paper investigates a different approach based on edge cloud applications, which involves data filtering and processing before being delivered to a backup cloud environment. This Paper suggest designing and implementing a low cost, low power cluster of Single Board Computers (SBC) for this purpose, reducing the amount of data that must be transmitted elsewhere, using Big Data ideas and technology. An Apache Hadoop and Spark Cluster that was used to run a… More >