Wei Wu¹, Weigong Zhang^1,*, Dong Wang¹, Lydia Zhu², Xiang Song³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3811-3828, 2023, DOI:10.32604/cmc.2023.029787 - 31 October 2022

Abstract An increase in car ownership brings convenience to people’s life. However, it also leads to frequent traffic accidents. Precisely forecasting surrounding agents’ future trajectories could effectively decrease vehicle-vehicle and vehicle-pedestrian collisions. Long-short-term memory (LSTM) network is often used for vehicle trajectory prediction, but it has some shortages such as gradient explosion and low efficiency. A trajectory prediction method based on an improved Transformer network is proposed to forecast agents’ future trajectories in a complex traffic environment. It realizes the transformation from sequential step processing of LSTM to parallel processing of Transformer based on attention mechanism. More >

Naixin Kang¹, Zhenhu Ning^1,*, Shiqiang Zhang¹, Sadaqat ur Rehman², Muhammad Waqas^1,3

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3931-3943, 2023, DOI:10.32604/cmc.2023.029711 - 31 October 2022

Abstract With the development of sensor technology and wireless communication technology, edge computing has a wider range of applications. The privacy protection of edge computing is of great significance. In the edge computing system, in order to ensure the credibility of the source of terminal data, mobile edge computing (MEC) needs to verify the signature of the terminal node on the data. During the signature process, the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance. Therefore, it is very necessary to improve efficiency through computational offloading. Therefore,… More >

Bich Nguyen¹, Binh Nguyen¹, Hai Tran², Vuong Pham¹, Le Nhi Lam Thuy¹, Pham The Bao^1,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2431-2441, 2023, DOI:10.32604/cmc.2023.029618 - 31 October 2022

Abstract 3-dimension (3-D) printing technology is growing strongly with many applications, one of which is the garment industry. The application of human body models to the garment industry is necessary to respond to the increasing personalization demand and still guarantee aesthetics. This paper proposes a method to construct 3-D human models by applying deep learning. We calculate the location of the main slices of the human body, including the neck, chest, belly, buttocks, and the rings of the extremities, using pre-existing information. Then, on the positioning frame, we find the key points (fixed and unaltered) of More >

Mohammad Alamgeer¹, Amal Al-Rasheed², Ahmad Alhindi³, Manar Ahmed Hamza^4,*, Abdelwahed Motwakel⁴, Mohamed I. Eldesouki⁵

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2725-2738, 2023, DOI:10.32604/cmc.2023.029163 - 31 October 2022

Abstract Data mining process involves a number of steps from data collection to visualization to identify useful data from massive data set. the same time, the recent advances of machine learning (ML) and deep learning (DL) models can be utilized for effectual rainfall prediction. With this motivation, this article develops a novel comprehensive oppositional moth flame optimization with deep learning for rainfall prediction (COMFO-DLRP) Technique. The proposed CMFO-DLRP model mainly intends to predict the rainfall and thereby determine the environmental changes. Primarily, data pre-processing and correlation matrix (CM) based feature selection processes are carried out. In More >

Sakda Noinang¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Soheil Salahshour⁴, Wajaree Weera^5,*, Thongchai Botmart⁵

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2575-2588, 2023, DOI:10.32604/cmc.2023.029046 - 31 October 2022

Abstract The current investigations are presented to solve the fractional order HBV differential infection system (FO-HBV-DIS) with the response of antibody immune using the optimization based stochastic schemes of the Levenberg-Marquardt backpropagation (LMB) neural networks (NNs), i.e., LMBNNs. The FO-HBV-DIS with the response of antibody immune is categorized into five dynamics, healthy hepatocytes (H), capsids (D), infected hepatocytes (I), free virus (V) and antibodies (W). The investigations for three different FO variants have been tested numerically to solve the nonlinear FO-HBV-DIS. The data magnitudes are implemented 75% for training, 10% for certification and 15% for testing More >

Souvik Pal^1,2,*, Hannah VijayKumar³, D. Akila⁴, N. Z. Jhanjhi^5,6, Omar A. Darwish⁷, Fathi Amsaad⁸

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3865-3880, 2023, DOI:10.32604/cmc.2023.029038 - 31 October 2022

Abstract Smart farming has become a strategic approach of sustainable agriculture management and monitoring with the infrastructure to exploit modern technologies, including big data, the cloud, and the Internet of Things (IoT). Many researchers try to integrate IoT-based smart farming on cloud platforms effectively. They define various frameworks on smart farming and monitoring system and still lacks to define effective data management schemes. Since IoT-cloud systems involve massive structured and unstructured data, data optimization comes into the picture. Hence, this research designs an Information-Centric IoT-based Smart Farming with Dynamic Data Optimization (ICISF-DDO), which enhances the performance More >

Muhammad Nadeem¹, Ali Arshad², Saman Riaz², SyedaWajiha Zahra¹, Muhammad Rashid², Shahab S. Band^3,*, Amir Mosavi^4,5,6

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2641-2659, 2023, DOI:10.32604/cmc.2023.028796 - 31 October 2022

Abstract Cloud computing is one of the most attractive and cost-saving models, which provides online services to end-users. Cloud computing allows the user to access data directly from any node. But nowadays, cloud security is one of the biggest issues that arise. Different types of malware are wreaking havoc on the clouds. Attacks on the cloud server are happening from both internal and external sides. This paper has developed a tool to prevent the cloud server from spamming attacks. When an attacker attempts to use different spamming techniques on a cloud server, the attacker will be More >

Guangjun Liang^1,2, Jianfang Xin^3,*, Linging Xia¹, Xueli Ni^1,4, Yi Cao⁵

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2981-2998, 2023, DOI:10.32604/cmc.2023.028597 - 31 October 2022

Abstract In this work, we consider the performance analysis of state dependent priority traffic and scheduling in device to device (D2D) heterogeneous networks. There are two priority transmission types of data in wireless communication, such as video or telephone, which always meet the requirements of high priority (HP) data transmission first. If there is a large amount of low priority (LP) data, there will be a large amount of LP data that cannot be sent. This situation will cause excessive delay of LP data and packet dropping probability. In order to solve this problem, the data… More >

Lojain Nahhas¹, Marwan Albahar^1,*, Abdullah Alammari², Anca Jurcut³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3997-4014, 2023, DOI:10.32604/cmc.2023.028316 - 31 October 2022

Abstract There has been an increase in attacks on mobile devices, such as smartphones and tablets, due to their growing popularity. Mobile malware is one of the most dangerous threats, causing both security breaches and financial losses. Mobile malware is likely to continue to evolve and proliferate to carry out a variety of cybercrimes on mobile devices. Mobile malware specifically targets Android operating system as it has grown in popularity. The rapid proliferation of Android malware apps poses a significant security risk to users, making static and manual analysis of malicious files difficult. Therefore, efficient identification… More >

Peizhu Gong¹, Jin Liu¹, Zhongdai Wu², Bing Han², Y. Ken Wang³, Huihua He^4,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4203-4220, 2023, DOI:10.32604/cmc.2023.028291 - 31 October 2022

Abstract Speech emotion recognition, as an important component of human-computer interaction technology, has received increasing attention. Recent studies have treated emotion recognition of speech signals as a multimodal task, due to its inclusion of the semantic features of two different modalities, i.e., audio and text. However, existing methods often fail in effectively represent features and capture correlations. This paper presents a multi-level circulant cross-modal Transformer (MLCCT) for multimodal speech emotion recognition. The proposed model can be divided into three steps, feature extraction, interaction and fusion. Self-supervised embedding models are introduced for feature extraction, which give a… More >