Cosci Press-Journal of Superintelligence and Computing

Vol.2 2026 - Issue 1

Open Access

18 March 2026

Defining and Measuring High-Quality Employment in the Digital-Intelligence Era: A Case Study of IT Graduates

by Yanglu Wan, Rui Wang, Wei Lu, Zichen Wang and Jingjing Ke

Abstract Against the backdrop of digital-intelligence transformation and rapid industrial restructuring, traditional single-dimension indicators no longer capture the complexity of labor-market change. Focusing on IT graduates and drawing on 4,239 records, this study develops a five-dimension High-Quality Employment (HQE) assessment system encompassing income returns, stability, growth potential, person-j [...] Read more.

Open Access

09 March 2026

Integrated Approach for Mango Leaf Disease Diagnosis Using Wavelet Transform and Support Vector Machines

by Salma N. and Madhuri G. R.

Abstract This study presents an approach, for identifying and categorizing diseases in mango leaves expanding its scope beyond diseases while differentiating between healthy leaves and the impacted by these ailment. Using a process the proposed method involves preparing leaf images by adjusting their size converting them to grayscale and reducing noise with a filter. Subsequently K means segmentation is e [...] Read more.

Open Access

04 March 2026

Fractional Convergence of Symmetrized Neural Network Operators: A Generalized Voronovskaya-Damasclin Approach

by Rômulo Damasclin Chaves dos Santos, Jorge Henrique de Oliveira Sales, Gislan Silveira Santos and Cássio Almeida Lima

Abstract This paper explores the asymptotic behavior of univariate neural network operators, with an emphasis on both classical and fractional differentiation over infinite domains. The analysis leverages symmetrized and perturbed hyperbolic tangent activation functions to investigate basic, Kantorovich, and quadrature-type operators. Voronovskaya-type expansions, along with the novel Voronovskaya-Damascl [...] Read more.

Open Access

10 February 2026

Developing a Model for the Detection of Ethiopian Fake Banknotes Using Deep Learning

by Gebeyehu Belay Gebremeskel, Tariku Asmamaw Tadele and Dagne Walle Girmaw

Abstract Various methods for recognizing and detecting fake banknotes have recently become a major concern in finance and business. Fake detection is an increasingly important approach due to the significance and technological complexity of quickly and accurately processing large amounts of banknote image data, presenting a significant opportunity for data exploration. A proposed deep CNN technique utiliz [...] Read more.

Open Access

24 January 2026

Change Detection in River Point Bars Using Multimodal Remote Sensing Data and Machine Learning

by Franklin N. Okeke, Ayibawari Obiene Egai and Desmond R. Eteh

Abstract This study investigates the temporal evolution and geometric variability of point bars along the Nun River in Kolokuma/Opokuma Local Government Area, Bayelsa State, Nigeria, using remote sensing, machine learning, and geospatial techniques over a 20-year period (2003–2023). Multi-temporal Landsat imagery, rainfall records, and sediment data were integrated to quantify morphometric changes and ass [...] Read more.