Muhammad Azam¹, Tanvir Ahmed¹, Rehan Ahmad², Ateeq Ur Rehman³, Fahad Sabah¹, Rao Muhammad Asif^4,*

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 853-867, 2021, DOI:10.32604/iasc.2021.019101

Abstract Sentiment analysis is a method for assessing an individual’s thought, opinion, feeling, mentality, and conviction about a specific subject on indicated theme, idea, or product. The point could be a business association, a news article, a research paper, or an online item, etc. Opinions are generally divided into three groups of positive, negative, and unbiased. The way toward investigating different opinions and gathering them in every one of these categories is known as Sentiment Analysis. The enormously growing sentiment data on the web especially social media can be a big source of information. The processing of this unstructured data is… More >

Neha Malhotra^1,2,*, Manju Bala³

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 945-960, 2021, DOI:10.32604/iasc.2021.019082

Abstract In mobile computing systems, nodes in the network take checkpoints to survive failures. Certain characteristics of mobile computing systems such as mobility, low bandwidth, disconnection, low power consumption, and limited memory make these systems more prone to failures. In this paper, a novel minimum process communication-induced checkpointing algorithm that makes full use of the computation ability and implementation of effective stable storage in a mobile computing system is proposed. The said approach initiates by taking spontaneous checkpoints by each node in phase 1 using a logistic function that is specifically used to estimate the time interval between two checkpoints and… More >

I.-Hung Wang¹, Mahardi², Kuang-Chyi Lee^2,*, Shinn-Liang Chang¹

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 995-1005, 2021, DOI:10.32604/iasc.2021.019020

Abstract The images classification is one of the most common applications of deep learning. Images of dogs and cats are mostly used as examples for image classification models, as they are relatively easy for the human eyes to recognize. However, classifying the breed of a dog or a cat has its own complexity. In this paper, a fine-tuned pre-trained model of a Keras’ application was built with a new dataset of dogs and cats to predict the breed of identified dogs or cats. Keras applications are deep learning models, which have been previously trained with general image datasets from ImageNet. In… More >

Morshedul Bari Antor¹, A. H. M. Shafayet Jamil¹, Maliha Mamtaz¹, Mohammad Monirujjaman Khan^1,*, Sultan S. Alshamrani², Mehedi Masud³

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 899-915, 2021, DOI:10.32604/iasc.2021.018914

Abstract In the Covid-19 pandemic, people have been very concerned about the safety and are avoiding crowded places like hospitals. An online telemedicine web-based technology can help to overcome this situation. This paper presents an online telemedicine system that helps to promote collaboration between doctors, hospitals, and patients. The system allows doctors to serve patients from remote areas. The system also allows both doctors and patients to communicate through video calls or text messages. Patients using the system can store information about their health, search for doctors, and consult medical professionals using text messages and video calls. Doctors can also register… More >

Praveenkumar Babu, Eswaran Parthasarathy^*

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 1063-1071, 2021, DOI:10.32604/iasc.2021.018903

Abstract Advancements in image and video processing are growing over the years for industrial robots, autonomous vehicles, indexing databases, surveillance, medical imaging and computer-human interaction applications. One of the major challenges in real-time image and video processing is the execution of complex functions and high computational tasks. In this paper, the hardware acceleration of different filter algorithms for both image and video processing is implemented on Xilinx Zynq^®-7000 System on-Chip (SoC) device. It consists of Dual-core Cortex^™-A9 processors which provide computing ability to perform I/O and processing functions and software libraries using Vivado^® High-Level Synthesis (HLS). In the proposed work, Sobel-Feldman… More >

Mahmoud Oglah Al Hasan Baniata^*, Sohail Asghar

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 821-836, 2021, DOI:10.32604/iasc.2021.018612

Abstract The advancement in electronic devices and communication technologies in social media have introduced major changes in today’s communication and people have accepted such communicational habits at a rapid pace. The changes involve the way people started interacting with each other, and modern mean of discovering new groups of people, and individuals with similar mindsets, mutual interests, and ideas to share with. As far as the communities are concerned, there are so many social drives (such as “Say No to Plastic”) that need to be discussed on a certain platform for their promotion. Although, it’s quit is challenging, but with the… More >

Animesh Kumar Dubey^*, Kavita Choudhary, Richa Sharma

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 929-943, 2021, DOI:10.32604/iasc.2021.018382

Abstract Heart disease is a major health concern worldwide. The chances of recovery are bright if it is detected at an early stage. The present report discusses a comparative approach to the classification of heart disease data using machine learning (ML) algorithms and linear regression and classification methods, including logistic regression (LR), decision tree (DT), random forest (RF), support vector machine (SVM), SVM with grid search (SVMG), k-nearest neighbor (KNN), and naive Bayes (NB). The ANOVA F-test feature selection (AFS) method was used to select influential features. For experimentation, two standard benchmark datasets of heart diseases, Cleveland and Statlog, were obtained… More >

S. A. Al blowi¹, M. El Sayed², M. A. El Safty^3,*

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 961-972, 2021, DOI:10.32604/iasc.2021.018242

Abstract Real-world applications are now dealing with a huge amount of data, especially in the area of high-dimensional features. Trait reduction is one of the major steps in decision making problems. It refers to the determination of a minimum subset of attributes which preserves the final decision based on the entire set of attributes. Unfortunately, most of the current features are irrelevant or redundant, which makes these systems unreliable and imprecise. This paper proposes a new paradigm based on fuzzy soft relationship and level fuzzy soft relationship, called Union - Intersection decision making method. Using these new principles, the decision-making strategy… More >

Rihem Farkh^1,2, Yasser Fouad^1,*, Haykel Marouani¹

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 837-851, 2021, DOI:10.32604/iasc.2021.018214

Abstract In industrial practice, certain processes are unstable, such as different types of reactors, distillation columns, and combustion systems. To ensure greater maneuverability and improve the speed of response command, certain systems in the military and aviation fields are purposely configured to be unstable. These systems are often more difficult to control than stable systems and are of particular interest to designers and control engineers. Despite all advances in process control over the past six decades, the proportional–integral–derivative (PID) controller is still the most common. The main reasons are the simplicity, robustness, and successful applications provided by PID-based control structures. The… More >

Muhammad Alyas Khan¹, Mushtaq Ali¹, Mohsin Shah², Toqeer Mahmood³, Muneer Ahmad⁴, NZ Jhanjhi⁵, Mohammad Arif Sobhan Bhuiyan^6,*, Emad Sami Jaha⁷

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 771-785, 2021, DOI:10.32604/iasc.2021.018039

Abstract Fungi disease affects walnut trees worldwide because it damages the canopies of the trees and can easily spread to neighboring trees, resulting in low quality and less yield. The fungal disease can be treated relatively easily, and the main goal is preventing its spread by automatic early-detection systems. Recently, machine learning techniques have achieved promising results in many applications in the agricultural field, including plant disease detection. In this paper, an automatic machine learning-based detection method for identifying walnut diseases is proposed. The proposed method first resizes a leaf’s input image and pre-processes it using intensity adjustment and histogram equalization.… More >