Ahmed Zohair Ibrahim^1,*, P. Prakash², V. Sakthivel², P. Prabu³

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2447-2460, 2023, DOI:10.32604/csse.2023.030134

Abstract In order to research brain problems using MRI, PET, and CT neuroimaging, a correct understanding of brainfunction is required. This has been considered in earlier times with the support of traditional algorithms. Deep learning process has also been widely considered in these genomics data processing system. In this research, brain disorder illness incliding Alzheimer’s disease, Schizophrenia and Parkinson’s diseaseis is analyzed owing to misdetection of disorders in neuroimaging data examined by means fo traditional methods. Moeover, deep learning approach is incorporated here for classification purpose of brain disorder with the aid of Deep Belief Networks (DBN). Images are stored in… More >

G. Maria Jones^1,*, S. Godfrey Winster², P. Valarmathie³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 87-102, 2022, DOI:10.32604/iasc.2022.022972

Abstract Rapid advancement of digital technology has encouraged its use in all aspects of life, including the workplace, education, and leisure. As technology advances, so does the number of users, which leads to an increase in criminal activity and demand for a cyber-crime investigation. Mobile phones have been the epicenter of illegal activity in recent years. Sensitive information is transferred due to numerous technical applications available at one’s fingertips, which play an essential part in cyber-crime attacks in the mobile environment. Mobile forensic is a technique of recovering or retrieving digital evidence from mobile devices so that it may be submitted… More >

G. Maria Jones^1,*, S. Godfrey Winster², P. Valarmathie³

Computer Systems Science and Engineering, Vol.40, No.3, pp. 963-978, 2022, DOI:10.32604/csse.2022.019483

Abstract Mobile devices and social networks provide communication opportunities among the young generation, which increases vulnerability and cybercrimes activities. A recent survey reports that cyberbullying and cyberstalking constitute a developing issue among youngsters. This paper focuses on cyberbullying detection in mobile phone text by retrieving with the help of an oxygen forensics toolkit. We describe the data collection using forensics technique and a corpus of suspicious activities like cyberbullying annotation from mobile phones and carry out a sequence of binary classification experiments to determine cyberbullying detection. We use forensics techniques, Machine Learning (ML), and Deep Learning (DL) algorithms to exploit suspicious… More >

K. Gayathri Devi^*, R. S. Mishra, A. K. Madan

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 429-448, 2022, DOI:10.32604/iasc.2022.019330

Abstract An NP-hard problem like Flexible Job Shop Scheduling (FJSP) tends to be more complex and requires more computational effort to optimize the objectives with contradictory measures. This paper aims to address the FJSP problem with combined and contradictory objectives, like minimization of make-span, maximum workload, and total workload. This paper proposes ‘Hybrid Adaptive Firefly Algorithm’ (HAdFA), a new enhanced version of the classic Firefly Algorithm (FA) embedded with adaptive parameters to optimize the multi objectives concurrently. The proposed algorithm has adopted two adaptive strategies, i.e., an adaptive randomization parameter (α) and an effective heterogeneous update rule for fireflies. The adaptations… More >