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Journal of Computational Mathematics, Intelligent and Secure Systems cover
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Open Access ·Peer-reviewed·ISSN (Online): 10.47974/JCMISS
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Half-Yearly Journal: Publishes high-quality research in the fields of computational mathematics, artificial intelligence, intelligent computing, cybersecurity, secure systems, and emerging interdisciplinary technologies.

About the Journal

Half-Yearly Journal: Publishes high-quality research in the fields of computational mathematics, artificial intelligence, intelligent computing, cybersecurity, secure systems, and emerging interdisciplinary technologies.

Aims & Scope

The Journal of Computational Mathematics, Intelligent and Secure Systems aims to publish high-quality research papers that discuss the role of computational mathematics in intelligent systems and mechanism of securing them. The theme of the journal is an intersection of three major domains Mathematical Modeling, Artificial Intelligence & Cyber security. The journal seeks to provide a platform for researchers and practitioners to share their latest findings, innovations, and applications in the development of intelligent and secure systems using computational mathematics.

The Scope of the journal has been aligned into two sections as per current trends in the 3 Major domains and it also covers the future advancements also in these domains to help us making journal more sustainable

The theme of journal is intersection of five main research domains that are primiarly aligned with SDG’s 9 and 16 and secondarily with SDG’s 7, 8 and 11, these research domains are: Computational Mathematics & Foundations, Security, Privacy & Robustness, Network Intelligence & Decentralized Systems, Advanced Intelligent Architectures and Quantum & Post-Quantum Technologies.

Current Issue

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Volume 1, Issue 1 · June 2026

Open Access Research Article·pp. 1–10·Vol. 1, Issue 1Jun 2026

An intelligent deep learning and natural language processing framework for fake news detection and text classification in social media forwarded messages

Ashish Tiwari, Sarvesh Kumar

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06001

In this paper: Social media platforms such as WhatsApp, Facebook, Twitter and Instagram have become primary channels for news dissemination, but they also allow false information to spread quickly and largely unveri...

AbstractReferencesFull Text PDF (564 KB)Views: 10Downloads: 7Citations: 0
Open Access Research Article·pp. 11–31·Vol. 1, Issue 1Jun 2026

SAH-IDA : An explainable, cryptographically secure stacking-ensemble framework for network intrusion detection in cloud environments — measured performance and honest evaluation

Pushpendra Sharma, S. S. Sarangdevot

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06002

In this paper: This paper describes an independent re-executed, artefact-verified assessment of SAHIDA – the unified intrusion-detection approach that incorporates a stacking ensemble of four learners (Naive Bayes,...

AbstractReferencesFull Text PDF (987 KB)Views: 8Downloads: 5Citations: 0
Open Access Research Article·pp. 33–52·Vol. 1, Issue 1Jun 2026

An attention-guided EfficientNetV2S–vision transformer framework for robust histopathological cancer classification

P. R. Anisha, Umaima Qader Mohiuddin

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06003

In this paper: Automatic detection of metastatic cancers from histopathological images still poses great difficulty due to complex cellular structure and contextual dependencies exhibited by cancer, as well as varia...

AbstractReferencesFull Text PDF (1.0 MB)Views: 5Downloads: 3Citations: 0
Open Access Research Article·pp. 53–114·Vol. 1, Issue 1Jun 2026

Polar and radially bounded representations of the Hénon attractor

Mohamed Sadek Ali Pacha, Juan Antonio Lopez Ramos, Seif Eddine Meghezzi

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06004

In this paper: The Hénon map is a canonical discrete chaotic system usually analyzed in Cartesian coordinates. This study compares three representations of the same trajectory: The original Cartesian state, an exact...

AbstractReferencesFull Text PDF (1,006 KB)Views: 5Downloads: 4Citations: 0
Open Access Research Article·pp. 115–131·Vol. 1, Issue 1Jun 2026

Explainable heterogeneous ensemble learning with hybrid feature selection for heart disease prediction

Saba Fatima, M. Arasakumar, P. R. Anisha

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06005

In this paper: The paper introduces an ensemble learning framework for predicting heart disease with a combination of the pre-processing, hybrid feature selection, class-imbalance management, hyper-parameters optimi...

AbstractReferencesFull Text PDF (712 KB)Views: 4Downloads: 4Citations: 0
Open Access Research Article·pp. 133–149·Vol. 1, Issue 1Jun 2026

Adaptive bayesian neural ODE for interpretable continuous-time forecasting with dynamic uncertainty quantification

Valentina E. Balas, Uday Pratap Singh

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06006

In this paper: Neural ordinary differential equations (Neural ODEs) give forecasting a continuous-time substrate, but existing variants are deterministic, and Bayesian extensions add uncertainty only at the initial...

AbstractReferencesFull Text PDF (798 KB)Views: 5Downloads: 3Citations: 0
Open Access Research Article·pp. 151–180·Vol. 1, Issue 1Jun 2026

Spectral population dynamics : Structural dependence of fixation time beyond spectral gap

Apurva Mehta, Niyati Buch

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06008

In this paper: We study how graph structure influences fixation time under a neutral invasion process on undirected connected graphs. Across six graph families, five population sizes, and 15,000 simulation trials, w...

AbstractReferencesFull Text PDF (967 KB)Views: 4Downloads: 4Citations: 0
Open Access Research Article·pp. 181–218·Vol. 1, Issue 1Jun 2026

Quantum-enhanced neuro-symbolic intelligence for secure and adaptive autonomous systems : A computational optimization framework

Indra Kishor, Udit Mamodiya

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06009

In this paper: Autonomous intelligence needs to be predictive, constraint-satisfying, have calibrated uncertainty, and be efficient in decision computation. Neural approaches can be statistically successful, but als...

AbstractReferencesFull Text PDF (1.3 MB)Views: 3Downloads: 3Citations: 0
Open Access Research Article·pp. 219–235·Vol. 1, Issue 1Jun 2026

Calibrated uncertainty and native explainability in adaptive Bayesian neural ODEs : An empirical study on real-world time series

Dharm Singh Jat, Uday Pratap Singh

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06007

In this paper: A companion paper [1] introduces the Adaptive Bayesian Neural ODE (ABNODE), which embeds a learned uncertainty field and a bounded adaptive controller directly inside a latent ODE’s dynamics, dz/dt =...

AbstractReferencesFull Text PDF (606 KB)Views: 4Downloads: 3Citations: 0
Open Access Research Article·pp. 237–271·Vol. 1, Issue 1Jun 2026

Explainable federated intelligence for secure and privacy-preserving distributed systems a mathematical optimization framework

Udit Mamodiya, Indra Kishor

Published Online: 30 Jun 2026DOI: 10.47974/JCMISS-2026-06010

In this paper: Federated learning allows for collaborative model training without the need to share raw data, privacy protection, non-IID data, unreliable participants, and limited interpretability are all complex c...

AbstractReferencesFull Text PDF (1.4 MB)Views: 5Downloads: 6Citations: 0

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