Gurwinder Kaur^*, Ashwani Kumar

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 281-296, 2023, DOI:10.32604/iasc.2023.026393

Abstract Blur is produced in a digital image due to low pass filtering, moving objects or defocus of the camera lens during capture. Image viewers are annoyed by blur artefact and the image's perceived quality suffers as a result. The high-quality input is relevant to communication service providers and imaging product makers because it may help them improve their processes. Human-based blur assessment is time-consuming, expensive and must adhere to subjective evaluation standards. This paper presents a revolutionary no-reference blur assessment algorithm based on re-blurring blurred images using a special mask developed with a Markov basis and Laplace filter. The final… More >

Anitha Govindhan^1,*, Karnam Anantha Sunitha², Sivanathan Kandhasamy³

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 351-365, 2023, DOI:10.32604/iasc.2023.026361

Abstract This paper presents a Model-Based Design (MBD) approach for the design and control of a customized manipulator intended for drilling and positioning of dental implants accurately with minimal human intervention. While performing an intra-oral surgery for a prolonged duration within a limited oral cavity, the tremor of dentist's hand is inevitable. As a result, wielding the drilling tool and inserting the dental implants safely in accurate position and orientation is highly challenging even for experienced dentists. Therefore, we introduce a customized manipulator that is designed ergonomically by taking in to account the dental chair specifications and anthropomorphic data such that… More >

Prasanalakshmi Balaji^*

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1-14, 2023, DOI:10.32604/iasc.2023.026341

Abstract Medical image assessment is based on segmentation at its fundamental stage. Deep neural networks have been more popular for segmentation work in recent years. However, the quality of labels has an impact on the training performance of these algorithms, particularly in the medical image domain, where both the interpretation cost and inter-observer variation are considerable. For this reason, a novel optimized deep learning approach is proposed for medical image segmentation. Optimization plays an important role in terms of resources used, accuracy, and the time taken. The noise in the raw medical image are processed using Quasi-Continuous Wavelet Transform (QCWT). Then,… More >

S. Sakthivel¹, V. Vivekanandhan^2,*, M. Manikandan²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 853-866, 2023, DOI:10.32604/iasc.2023.026289

Abstract Irrigation plays a significant role in various agricultural cropping methods deployed in semiarid and arid regions where valuable water applications and managing are considered crucial concerns. Multiple factors such as weather, soil, water, and crop data need to be considered for irrigation maintenance in an efficient besides uniform manner from multifaceted and different information-based systems. A Multi-Agent System (MAS) has been proposed recently based on diverse agent subsystems with definite objectives for attaining global MAS objective and is deployed on Cloud Computing paradigm capable of gathering information from Wireless Sensor Networks (WSNs) positioned in rice, cotton, cassava crops for knowledge… More >

M. Mohan^1,*, P. C. Kishore Raja², P. Velmurugan³, A. Kulothungan⁴

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1151-1163, 2023, DOI:10.32604/iasc.2023.026255

Abstract Prediction of stock market value is highly risky because it is based on the concept of Time Series forecasting system that can be used for investments in a safe environment with minimized chances of loss. The proposed model uses a real time dataset of fifteen Stocks as input into the system and based on the data, predicts or forecast future stock prices of different companies belonging to different sectors. The dataset includes approximately fifteen companies from different sectors and forecasts their results based on which the user can decide whether to invest in the particular company or not; the forecasting… More >

M. P. Karthikeyan^1,*, E. A. Mary Anita²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 567-580, 2023, DOI:10.32604/iasc.2023.026243

Abstract In recent years, there has been a significant increase in the number of people suffering from eye illnesses, which should be treated as soon as possible in order to avoid blindness. Retinal Fundus images are employed for this purpose, as well as for analysing eye abnormalities and diagnosing eye illnesses. Exudates can be recognised as bright lesions in fundus pictures, which can be the first indicator of diabetic retinopathy. With that in mind, the purpose of this work is to create an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis (IM-EDRD) with multi-level classifications. The model uses Support Vector Machine… More >

Hanan A. Hosni Mahmoud¹, Alaaeldin M. Hafez², Eatedal Alabdulkreem^1,*

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 321-334, 2023, DOI:10.32604/iasc.2023.026235

Abstract Languages–independent text tokenization can aid in classification of languages with few sources. There is a global research effort to generate text classification for any language. Human text classification is a slow procedure. Consequently, the text summary generation of different languages, using machine text classification, has been considered in recent years. There is no research on the machine text classification for many languages such as Czech, Rome, Urdu. This research proposes a cross-language text tokenization model using a Transformer technique. The proposed Transformer employs an encoder that has ten layers with self-attention encoding and a feedforward sublayer. This model improves the… More >

M. Ramya Devi^*, I. Jasmine Selvakumari Jeya

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 31-45, 2023, DOI:10.32604/iasc.2023.026152

Abstract Internet of Vehicles (IoV) is an intelligent vehicular technology that allows vehicles to communicate with each other via internet. Communications and the Internet of Things (IoT) enable cutting-edge technologies including such self-driving cars. In the existing systems, there is a maximum communication delay while transmitting the messages. The proposed system uses hybrid Co-operative, Vehicular Communication Management Framework called CAMINO (CA). Further it uses, energy efficient fast message routing protocol with Common Vulnerability Scoring System (CVSS) methodology for improving the communication delay, throughput. It improves security while transmitting the messages through networks. In this research, we present a unique intelligent vehicular… More >

Sonia¹, Kapil Sharma^1,*, Monika Bajaj²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1087-1101, 2023, DOI:10.32604/iasc.2023.026134

Abstract Big Data and artificial intelligence are used to transform businesses. Social networking sites have given a new dimension to online data. Social media platforms help gather massive amounts of data to reach a wide variety of customers using influence maximization technique for innovative ideas, products and services. This paper aims to develop a deep learning method that can identify the influential users in a network. This method combines the various aspects of a user into a single graph. In a social network, the most influential user is the most trusted user. These significant users are used for viral marketing as… More >

Mahmood Al-Bahri¹, Abdelhamied Ateya^2,3, Ammar Muthanna³, Abeer D. Algarni⁴, Naglaa F. Soliman^4,*

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 97-110, 2023, DOI:10.32604/iasc.2023.026115

Abstract The Internet of Things (IoT) is a recent technology, which implies the union of objects, “things”, into a single worldwide network. This promising paradigm faces many design challenges associated with the dramatic increase in the number of end-devices. Device identification is one of these challenges that becomes complicated with the increase of network devices. Despite this, there is still no universally accepted method of identifying things that would satisfy all requirements of the existing IoT devices and applications. In this regard, one of the most important problems is choosing an identification system for all IoT devices connected to the public… More >