Browsing by Author "Wijesinghe, R. E"

Now showing 1 - 4 of 4

Open Access
Dense Convolutional Neural Network-Based Deep Learning Pipeline for Pre-Identification of Circular Leaf Spot Disease of Diospyros kaki Leaves Using Optical Coherence Tomography
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-08) Kalupahana, D; Kahatapitiya, N.S; Silva, B.N; Kim, J; Jeon, M; Wijenayake, U; Wijesinghe, R. E
Circular leaf spot (CLS) disease poses a significant threat to persimmon cultivation, leading to substantial harvest reductions. Existing visual and destructive inspection methods suffer from subjectivity, limited accuracy, and considerable time consumption. This study presents an automated pre-identification method of the disease through a deep learning (DL) based pipeline integrated with optical coherence tomography (OCT), thereby addressing the highlighted issues with the existing methods. The investigation yielded promising outcomes by employing transfer learning with pre-trained DL models, specifically DenseNet-121 and VGG-16. The DenseNet-121 model excels in differentiating among three stages of CLS disease (healthy (H), apparently healthy (or healthy-infected (HI)), and infected (I)). The model achieved precision values of 0.7823 for class-H, 0.9005 for class-HI, and 0.7027 for class-I, supported by recall values of 0.8953 for class-HI and 0.8387 for class-I. Moreover, the performance of CLS detection was enhanced by a supplemental quality inspection model utilizing VGG-16, which attained an accuracy of 98.99% in discriminating between low-detail and high-detail images. Moreover, this study employed a combination of LAMP and A-scan for the dataset labeling process, significantly enhancing the accuracy of the models. Overall, this study underscores the potential of DL techniques integrated with OCT to enhance disease identification processes in agricultural settings, particularly in persimmon cultivation, by offering efficient and objective pre-identification of CLS and enabling early intervention and management strategies. © 2024 by the authors.
Open Access
Development of Computer-Aided Semi-Automatic Diagnosis System for Chronic Post-Stroke Aphasia Classification with Temporal and Parietal Lesions: A Pilot Study
(Multidisciplinary Digital Publishing Institute, 2020-01) Silva, B. N; Khan, M; Wijesinghe, R. E; Thelijjagoda, S
Survivors of either a hemorrhagic or ischemic stroke tend to acquire aphasia and experience spontaneous recovery during the first six months. Nevertheless, a considerable number of patients sustain aphasia and require speech and language therapy to overcome the difficulties. As a preliminary study, this article aims to distinguish aphasia caused from a temporoparietal lesion. Typically, temporal and parietal lesions cause Wernicke’s aphasia and Anomic aphasia. Differential diagnosis between Anomic and Wernicke’s has become controversial and subjective due to the close resemblance of Wernicke’s to Anomic aphasia when recovering. Hence, this article proposes a clinical diagnosis system that incorporates normal coupling between the acoustic frequencies of speech signals and the language ability of temporoparietal aphasias to delineate classification boundary lines. The proposed inspection system is a hybrid scheme consisting of automated components, such as confrontation naming, repetition, and a manual component, such as comprehension. The study was conducted involving 30 participants clinically diagnosed with temporoparietal aphasias after a stroke and 30 participants who had experienced a stroke without aphasia. The plausibility of accurate classification of Wernicke’s and Anomic aphasia was confirmed using the distinctive acoustic frequency profiles of selected controls. Accuracy of the proposed system and algorithm was confirmed by comparing the obtained diagnosis with the conventional manual diagnosis. Though this preliminary work distinguishes between Anomic and Wernicke’s aphasia, we can claim that the developed algorithm-based inspection model could be a worthwhile solution towards objective classification of other aphasia types
Open Access
Electromagnetic Continuously Variable Transmission (EMCVT) System for Precision Torque Control in Human-Centered Robotic Applications
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-09-08) Madusankha, I; Jayaweera, P. N; Kahatapitiya, N. S; Sampath, P; Weeraratne, A; Subasinghage, K; Liyanage, C; Wijethunge, A; Ravichandran, N. K; Wijesinghe, R. E
In human-centered robotic applications, safety, efficiency, and adaptability are critical for enabling effective interaction and performance. Incorporating electromagnetic continuously variable transmission (EM-CVT) systems into robotic designs enhances both safety and precise, adaptable motion control. The flexible power transmission offered by CVTs allows robots to operate across diverse environments, supporting various tasks, human interaction, and safe collaboration. This study presents a CVT-based mechanical subsystem developed using two cones and an intermediate belt-driven transmission mechanism, providing efficient power and motion transfer. The control subsystem consists of six strategically positioned electromagnets energized by signals from a microcontroller. This electromagnetic actuation enables rapid and precise adjustments to the transmission ratio, enhancing overall system performance. A linear relationship between slip percentage and gear ratio was observed, indicating that the control system achieves stable and efficient operation, with a measured power consumption of 2.95 W per electromagnet. Future work will focus on validating slip performance under dynamic loading conditions, integrating the system into robotic platforms, and optimizing materials and control strategies to enable broader real-world deployment.
Embargo
Environmental forensics of the X-press pearl disaster: Uncovering the internal micro-structural transformations in marine microplastics
(Elsevier B.V., 2025-07-15) Jayasekara, P.M; Abhishek, P; Kahatapitiya, N. S; Weerasinghe, M; Kahandawala, B. S; Silva, B. N; Wijenayake, U; Rajapaksha, A.U; Wijesinghe, R. E; Vithanage, M
The MV X-Press Pearl (XPP) maritime disaster on May 25, 2021, released approximately 75 billion microplastic (MP) nurdles into the Indian Ocean and degraded due to the elevated temperatures, a cocktail of chemicals, physical abrasions, and environmental factors. While degradation-induced surface-level chemical and morphological changes were well documented, internal degradation remains largely unexplored. This study highlights the utilization of high-resolution optical coherence tomography (OCT) as a purely non-destructive imaging modality to discover profound internal alterations in the micrometer range, such as internal hollow regions, cracks, and voids in MP nurdles subjected to different degrees of degradation. The dark pixel intensity probability density corresponds to the degraded areas, increased from 0.0019 (pristine nurdle) to 0.0135–0.5252 for thermal degradation, 0.0878–0.3134 for chemical degradation, and 0.1291–0.2179 for mechanical degradation, indicating progressive internal degradation. Attenuated total reflectance fourier transform infrared (ATR-FTIR) spectroscopy analysis confirmed that all the nurdles are polyethylene (PE) and revealed that extreme conditions lead to the formation of new functional groups, including hydroxyl bands and carbonyl bands, even though PE is highly resistant to degradation. The integration of high-resolution OCT imaging with FTIR analysis provides novel insights into the interconnection between micrometer-scale internal physical alterations and associated chemical modifications of MP nurdles resulting from environmental degradation. These findings highlight the potential of this OCT-FTIR integrated approach for advancing the understanding of MP degradation and its long-term environmental impacts.