ResearchSpace

Communities in ResearchSpace

Welcome to ResearchSpace, the institutional repository of the CSIR. ResearchSpace is an open access electronic archive collecting, preserving and distributing scholarly digital materials created by the CSIR.

Recent Submissions

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The effects of platform altitude and terrain type on the false alarm rate in infrared small target detection

(2025-10) Malatji, Tsholofelo M; Du Plessis, WP; Bezuidenhout, DF; Nana, Muhammad A

There are many challenges in the field of infrared (IR) small target detection due to the noise-like characteristics of the target. While the development of detection algorithms continues, very little research has sought to understand what creates false targets in IR scenes. The aim of this research is to identify the main factors that contribute to false target generation in the field of IR small target detection. Scenarios with cluttered backgrounds were used to evaluate the effect of a flying platform on the false alarm rate. Both urban and rural scenes were evaluated at different platform altitudes. The study found that IR clutter is generally higher in urban scenes than in rural scenes and that an increase in altitude results in increased false targets. Future work for this study involves the investigation of specific materials in the urban scene that result in the generation of false targets, and scenario conditions such as weather, view angle, time of day, etc. that lead to higher false targets.

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Advancing Innovative Cybersecurity Solutions and Approaches to Protect Digital Ecosystems

(2025-12) Mtsweni, Jabu S; Kanyane, M; Phahlamohlaka, Jackie; Munyoka, W; Thomson, K-L; Lynn Futcher, L; Jansen van Vuuren, J

It was our great pleasure to welcome researchers, practitioners, and policymakers to the first IFIP-UNIVEN-CSIR International Conference in Cybersecurity (IFIP-UNIVEN CSIR ICC 2025), held in Pretoria, South Africa, from December 11 to 12, 2025. The conference was jointly organized by the University of Venda (UNIVEN) and the Coun cil for Scientific and Industrial Research (CSIR) under the auspices of the International Federation for Information Processing (IFIP) and focused on the theme: “Advancing innovative cybersecurity solutions and approaches to protect digital ecosystems.” This proceedings volume, published in the esteemed IFIP Advances in Information and Com munication Technology (IFIP-AICT) series, focuses on the technical papers presented at the main conference. The selection process for the research papers was highly rigorous, following quality checks in place. The conference received a total of 43 full-paper submissions. Each paper underwent a thorough double-blind peer-review process with an average of three reviews via the EasyChair system to ensure the highest quality, integrity, and relevance. Based on the reviewers’ recommendations, only 17 papers were accepted for publication and presentation, resulting in an acceptance rate of approximately 39.5%. Following the technical acceptance, all papers were subjected to a final quality check, which included similarity reporting using Turnitin and iThenticate. Six (6) accepted papers required subsequent corrections to address issues identified in the similarity reports, and all issues were addressed to the satisfaction of the editorial team. After the initial reviews and feedback sent by authors, two (2) rejected papers were withdrawn by the authors.

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Response surface modelling and optimization of oleic acid yield from Sclerocarya birrea kernel oil in supercritical carbon dioxide extraction

(2026-03) Reddy, Trishen; Seodigeng, T

This study investigated the potential for maximizing oleic acid (C18:1) yield from Sclerocarya birrea (Marula) kernel oil using supercritical carbon dioxide (CO2) extraction. The investigation utilised a unique dataset comprising nine experimental runs derived from existing literature on Marula oil. Response Surface Methodology (RSM) was employed to evaluate the influence of the two primary independent variables viz. extraction pressure (varied between 250 bar and 450 bar) and extraction temperature (varied between 40 °C and 75 °C). During all runs, the CO2 flow rate, extraction time, and particle size were held constant. A significant second-order polynomial model was developed to predict the yield of oleic acid. To achieve a practical and economically viable outcome, the Optimal (Custom) option within Design-Expert Version 13 software was specifically utilised to optimise the combined effects of temperature and pressure. This customized approach identified the most desirable set of operating conditions viz. temperature of 60 °C and pressure of 250 bar for achieving maximal oleic acid recovery, thus providing a foundational model for sustainable industrial applications.

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Reinforcement learning-guided de novo drug design: A comparative study of RL algorithms for small molecule generation

(2025) Mpofu, Kelvin T; Thwala, Nomcebo L; Thobakgale, Setumo L; Mthunzi-Kufa, P

We present a comparative study on the application of reinforcement learning (RL) algorithms for de novo drug design. Using a custom molecular environment, we benchmarked five RL methods, DQN, PPO, A2C, REINFORCE, and DoubleDQN, for their ability to generate small, drug-like molecules from atomic building blocks. The models were evaluated based on chemical validity, drug-likeness (QED), molecular complexity, compliance with Lipinski’s Rule of Five, and structural similarity to known pharmaceuticals such as Aspirin and Ibuprofen. Among the tested algorithms, REINFORCE and PPO outperformed others by generating chemically diverse and pharmacologically relevant compounds, achieving the highest QED scores and producing molecules with complex ring structures and higher scaffold novelty. All models successfully generated fully Lipinski compliant molecules, demonstrating their utility in producing viable drug candidates. This work offers insights into the performance dynamics of RL models in chemical space and provides a foundation for developing AI-driven pipelines for accelerated drug discovery. This study highlights the benchmarking gap in RL-based molecule generation and systematically evaluates five algorithms under identical conditions to identify strengths and trade-offs.

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Ferrocene-based hybrid drugs as potential anticancer and antibacterial therapeutic agents for incorporation into nanocarriers: In silico, in vitro, molecular docking evaluations

(2025-05) Peter, S; Morifi, E; Nwamadi, M; Oselusi, SO; Tantoh, Asongwe LA; Fonkui, TY; Ndinteh, DT; Aderibigbe, BA

Background/Objectives: Cancer and bacterial cases are increasing. Hence, new drugs to treat these diseases are paramount. Ferrocene-based hybrid compounds were synthesizedas potential cancer and bacteria therapeutics. Methods: The synthesized compounds were characterized via FTIR, NMR, and LC-MS and evaluated against different cancer cells and bacterial strains. Moreover, computational studies of these compounds were conducted using several silico tools. Results: Among the synthesized compounds, hybrid 10 was the most promising compound, displaying promising anticancer activity with IC50 values between 42.42 and 45.37 and 50.64 and 73.37 µg/mL against HeLa and CHO cancer cells, respectively, with a selective index greater than one on HeLa cancer cells. Compounds 22–26 displayed promising antibacterial activity with a MIC value of 7.8125 µg/mL against most bacterial strains in vitro. The in silico results revealed that this compound has strong binding affinities for 4qtb, 3eqm, and 2w3l cervical cancer proteins, exhibiting binding energies of −7.3, −8.7, and 7.4 kcal/mol, respectively. Furthermore, hybrid 10 showed promising pharmacokinetics and drug-like properties, including high GI absorption, moderate water solubility, favoring the oral administration route, nontoxicity, and is a P-gp substrate. Conclusions: The findings obtained in this study illustrate that hybrid compounds are potential therapeutics that need to be explored. The compounds also contained functionalities relevant for incorporating into nanocarriers to improve their biological activities further. Therefore, further studies are recommended for the most effective compounds to reinforce these findings.