Yanman Li¹, Jun Zhang¹, Yang Hu¹, Yingnan Zhao^2,*, Yi Cao³

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1219-1230, 2022, DOI:10.32604/csse.2022.028224 - 09 May 2022

Abstract Safety helmet-wearing detection is an essential part of the intelligent monitoring system. To improve the speed and accuracy of detection, especially small targets and occluded objects, it presents a novel and efficient detector model. The underlying core algorithm of this model adopts the YOLOv5 (You Only Look Once version 5) network with the best comprehensive detection performance. It is improved by adding an attention mechanism, a CIoU (Complete Intersection Over Union) Loss function, and the Mish activation function. First, it applies the attention mechanism in the feature extraction. The network can learn the weight of… More >

Amjad Alsirhani, Mohamed Ezz, Ayman Mohamed Mostafa^*

Computer Systems Science and Engineering, Vol.43, No.3, pp. 967-984, 2022, DOI:10.32604/csse.2022.024854 - 09 May 2022

Abstract Identity management is based on the creation and management of user identities for granting access to the cloud resources based on the user attributes. The cloud identity and access management (IAM) grants the authorization to the end-users to perform different actions on the specified cloud resources. The authorizations in the IAM are grouped into roles instead of granting them directly to the end-users. Due to the multiplicity of cloud locations where data resides and due to the lack of a centralized user authority for granting or denying cloud user requests, there must be several security… More >

Somia Belaidouni^1,2, Moeiz Miraoui^3,4,*, Chakib Tadj¹

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1085-1098, 2022, DOI:10.32604/csse.2022.024056 - 09 May 2022

Abstract A context-aware service in a smart environment aims to supply services according to user situational information, which changes dynamically. Most existing context-aware systems provide context-aware services based on supervised algorithms. Reinforcement algorithms are another type of machine-learning algorithm that have been shown to be useful in dynamic environments through trial-and-error interactions. They also have the ability to build excellent self-adaptive systems. In this study, we aim to incorporate reinforcement algorithms (Q-learning) into a context-aware system to provide relevant services based on a user’s dynamic context. To accelerate the convergence of reinforcement learning (RL) algorithms and More >

Waseem Ullah Khan^*, Safdar Nawaz Khan Marwat, Salman Ahmed

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1297-1313, 2022, DOI:10.32604/csse.2022.024018 - 09 May 2022

Abstract The Internet of Things (IoTs) is apace growing, billions of IoT devices are connected to the Internet which communicate and exchange data among each other. Applications of IoT can be found in many fields of engineering and sciences such as healthcare, traffic, agriculture, oil and gas industries, and logistics. In logistics, the products which are to be transported may be sensitive and perishable, and require controlled environment. Most of the commercially available logistic containers are not integrated with IoT devices to provide controlled environment parameters inside the container and to transmit data to a remote… More >

Jansi Rani Sella Veluswami^*

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1231-1239, 2022, DOI:10.32604/csse.2022.020230 - 09 May 2022

Abstract Most of the internet users connect through wireless networks. Major part of internet traffic is carried by Transmission Control Protocol (TCP). It has some design constraints while operated across wireless networks. TCP is the traditional predominant protocol designed for wired networks. To control congestion in the network, TCP used acknowledgment to delivery of packets by the end host. In wired network, packet loss signals congestion in the network. But rather in wireless networks, loss is mainly because of the wireless characteristics such as fading, signal strength etc. When a packet travels across wired and wireless… More >

Yingnan Zhao^1,*, Peiyuan Ji¹, Fei Chen¹, Guanlan Ji¹, Sunil Kumar Jha²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1001-1016, 2022, DOI:10.32604/iasc.2022.027710 - 03 May 2022

Abstract This paper proposes a spatio-temporal model (VCGA) based on variational mode decomposition (VMD) and attention mechanism. The proposed prediction model combines a squeeze-and-excitation network to extract spatial features and a gated recurrent unit to capture temporal dependencies. Primarily, the VMD can reduce the instability of the original wind speed data and the attention mechanism functions to strengthen the impact of important information. In addition, the VMD and attention mechanism act to avoid a decline in prediction accuracy. Finally, the VCGA trains the decomposition result and derives the final results after merging the prediction result of More >

T. Tamilvizhi¹, R. Surendran^2,*, Carlos Andres Tavera Romero³, M. Sadish Sendil⁴

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1265-1279, 2022, DOI:10.32604/iasc.2022.026331 - 03 May 2022

Abstract VANETs are a subclass of mobile ad hoc networks (MANETs) that enable efficient data transmission between vehicles and other vehicles, road side units (RSUs), and infrastructure. The purpose of VANET is to enhance security, road traffic management, and traveler services. Due to the nature of real-time issues such as reliability and privacy, messages transmitted via the VANET must be secret and confidential. As a result, this study provides a method for privacy-preserving reliable data transmission in a cluster-based VANET employing Fog Computing (PPRDA-FC). The PPRDA-FC technique suggested here seeks to ensure reliable message transmission by… More >

M. Manicka Raja^1,*, S. Manoj Kumar²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1017-1032, 2022, DOI:10.32604/iasc.2022.025665 - 03 May 2022

Abstract Privacy of data in Internet of Things (IoT) over fog networks is the biggest challenge in security of Wireless communication networks. In Wireless Sensor Network (WSN), current research on fog computing with IoT is gaining popularity among IoT devices over network. Moreover, the data aggregation will reduce the energy consumption in WSN. Due to the open and hostile nature of WSN, secure data aggregation is the major issue. The existing data aggregation methods in IoT and its associated approaches are lack of limited aggregation functions, heavyweight, issues related to the performance overhead. Besides, the overload… More >

Tamara al Shloul¹, Usman Azmat², Suliman A. Alsuhibany³, Yazeed Yasin Ghadi⁴, Ahmad Jalal², Jeongmin Park^5,*

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 715-732, 2022, DOI:10.32604/iasc.2022.025421 - 03 May 2022

Abstract The physical and the mental health of a human being largely depends upon his physical life-routine (PLR) and today’s much advanced technological methods make it possible to recognize and keep track of an individual’s PLR. With the successful and accurate recognition of PLR, a sublime service of health education can be made copious. In this regard, smartphones can play a vital role as they are ubiquitous and have utilitarian sensors embedded in them. In this paper, we propose a framework that extracts the features from the smartphone sensors data and then uses the sequential feature… More >

S. Jeevitha^1,*, K. Valarmathi²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1123-1139, 2022, DOI:10.32604/iasc.2022.024746 - 03 May 2022

Abstract Pulmonary Embolism is a blood clot in the lung which restricts the blood flow and reduces blood oxygen level resulting in mortality if it is untreated. Further, pulmonary embolism is evidenced prominently in the segmental and sub-segmental regions of the computed tomography angiography images in COVID-19 patients. Pulmonary embolism detection from these images is a significant research problem in the challenging COVID-19 pandemic in the venture of early disease detection, treatment, and prognosis. Inspired by several investigations based on deep learning in this context, a two-stage framework has been proposed for pulmonary embolism detection which… More >