Yongtao Yu, Guangdong Zou^*

Oncologie, Vol.23, No.2, pp. 293-301, 2021, DOI:10.32604/Oncologie.2021.015520 - 22 June 2021

Abstract Objective: The purpose was to explore the value of multi-slice spiral CT (MSCT) multiplanar reconstruction technique in the diagnosis and clinicopathological analysis of gastrointestinal lymphoma (GIL). Methods: 82 GIL patients treated in our hospital from February 2018 to February 2019 were selected as the experimental group of this study, and 82 patients with other gastrointestinal tumors diagnosed by pathology during the same period were selected as the control group. Both groups of patients were scanned by MSCT and analyzed by multiplanar reconstruction technique to compare the diagnostic results and clinicopathological indexes of the two groups. Results: The… More >

R. J. Salmon^1,2,*

Oncologie, Vol.23, No.2, pp. 173-176, 2021, DOI:10.32604/Oncologie.2021.017020 - 22 June 2021

Abstract This article has no abstract. More >

A. M. Abdullah¹, Hegazy Rezk^2,3,*, A. Hadad¹, Mohamed K. Hassan^1,4, A. F. Mohamed^1,5

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 619-631, 2021, DOI:10.32604/iasc.2021.018289 - 16 June 2021

Abstract The problem of parameter estimation of the proton exchange membrane fuel cell (PEMFC) model plays a significant role in the simulation and optimization of a PEMFC system. In the current research, a moth flame optimization algorithm (MFOA) is used to identify the best parameters of PEMFC. Two different PEMFCs, Nedstack PS6, 6 kW, and SR-12 PEM 500 W are used to demonstrate the accuracy of the MFOA. Throughout the optimization process, seven unidentified parameters (℥₁, ℥₂, ℥₃, ℥₄, λ, ℛ, and B) of PEMFC are appointed to be decision variables. The fitness function, which needed to be… More >

Cheng-Yan Siao¹, Jhe-Wei Lin¹, Ting-Hsuan Chien^2,*, Rong-Guey Chang¹

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 559-569, 2021, DOI:10.32604/iasc.2021.018252 - 16 June 2021

Abstract With the rapid growth of the Fourth Industrial Revolution (or Industry 4.0), five-axis machining has played an important role nowadays. Due to the expensive cost of five-axis machining, how to solve the collision detection for five-axis machining in real-time is very critical. In this paper, we present a parallel method to detect collision for five-axis machining. Moreover, we apply the bounding volume hierarchy technique with two-level bounding volume represent the surface or solid of the object to reduce triangle meshes inside each axis of the five-axis machine tool, and then matching the operating range limit… More >

Hiba Jasim Hadi^*, Mohd Adan Omar, Wan Rozaini Sheik Osman

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 373-386, 2021, DOI:10.32604/iasc.2021.018207 - 16 June 2021

Abstract The public sector of Iraq has been struggling from poor management of resources and numerous difficulties that affect its governmental organization’s development, such as financial issues resulting from corruption, insecurity, and the lack of IT resources and infrastructure. Thus, cloud computing Software as a Service (CC-SaaS) can be a useful solution to help governmental organizations increase their service efficiency through the adoption of low-cost technology and provision of better services. The adoption of CC-SaaS remains limited in Iraqi public organizations due to numerous challenges, including privacy and protection, legal policy, and trust. Trust was found… More >

Hyun Yoo¹, Ji-Won Baek², Kyungyong Chung^3,*

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 319-334, 2021, DOI:10.32604/iasc.2021.018115 - 16 June 2021

Abstract With the convergence and development of the Internet of things (IoT) and artificial intelligence, closed-circuit television, wearable devices, and artificial neural networks have been combined and applied to crime prevention and follow-up measures against crimes. However, these IoT devices have various limitations based on the physical environment and face the fundamental problem of privacy violations. In this study, voice data are collected and emotions are classified based on an acoustic sensor that is free of privacy violations and is not sensitive to changes in external environments, to overcome these limitations. For the classification of emotions… More >

Muhammad Irshad Nazeer^1,2,*, Ghulam Ali Mallah¹, Raheel Ahmed Memon²

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 633-648, 2021, DOI:10.32604/iasc.2021.017771 - 16 June 2021

Abstract Network Coding is a potential technology for the future wireless communications and Internet of Things (IoT) as it reduces the number of transmissions and offers energy efficiency. It is vulnerable to threat and attack that can harm intermediate nodes. Indeed, it exhibits an ability to incorporate security of transmitted data, yet a lot of work needs to be done to provide a safeguard from threats. The purpose of this study is to strengthen the existing Network Coding scheme with a set of generic requirements for Network Coding Protocols by adopting system models and a Genetic… More >

Sehrish Jamil¹, Salma Noor^1,*, Iftikhar Ahmed², Neelam Gohar¹, Fouzia¹

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 511-524, 2021, DOI:10.32604/iasc.2021.017770 - 16 June 2021

Abstract Significant happenings in terms of spatio-temporal factors are called events. In the digital age, these events and their associated features are scattered in various databases on the Internet. The event data are in heterogeneous formats, which are often not machine-readable. This leads to a lack of unification of event-related knowledge across different domains and results in a research gap in terms of event modeling and representation. Specialized event models are needed to overcome this gap and integrate relevant information of different similar events occurring worldwide. Our research explores the problem of heterogeneity in specialized event… More >

Faseeha Matloob¹, Shabib Aftab^1,2, Munir Ahmad², Muhammad Adnan Khan^3,*, Areej Fatima⁴, Muhammad Iqbal², Wesam Mohsen Alruwaili⁵, Nouh Sabri Elmitwally^5,6

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 403-421, 2021, DOI:10.32604/iasc.2021.017562 - 16 June 2021

Abstract Software defect prediction (SDP) is the process of detecting defect-prone software modules before the testing stage. The testing stage in the software development life cycle is expensive and consumes the most resources of all the stages. SDP can minimize the cost of the testing stage, which can ultimately lead to the development of higher-quality software at a lower cost. With this approach, only those modules classified as defective are tested. Over the past two decades, many researchers have proposed methods and frameworks to improve the performance of the SDP process. The main research topics are More >

Yu Xue^1,2,*, Yiling Tong¹, Ziming Yuan¹, Shoubao Su², Adam Slowik³, Sam Toglaw⁴

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 497-509, 2021, DOI:10.32604/iasc.2021.016884 - 16 June 2021

Abstract Because of the characteristics of high redundancy, high parallelism and nonlinearity in the handwritten character recognition model, the convolutional neural networks (CNNs) are becoming the first choice to solve these complex problems. The complexity, the types of characters, the character similarity of the handwritten character dataset, and the choice of optimizers all have a great impact on the network model, resulting in low accuracy, high loss, and other problems. In view of the existence of these problems, an improved LeNet-5 model is proposed. Through increasing its convolutional layers and fully connected layers, higher quality features… More >