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Advancements and Challenges in Real-Time Electronic Vision Technologies for Canned Fish Quality Inspection: A Comprehensive Review
(European Modern Studies Journal, 2024-09) Mahatheesan, A. J.; Sharmilan, T.
The global demand for high-quality canned fish products has driven the adoption of advanced inspection technologies to ensure consistency, safety, and compliance with industry standards. This paper provides a comprehensive review of real-time electronic vision technologies employed in the inspection of canned fish quality. It traces the evolution of the canned fish industry from manual inspection methods to sophisticated automated systems, emphasizing the role of technologies such as hyperspectral imaging, machine learning algorithms, and electronic vision systems. The effectiveness of these technologies in detecting defects, assessing quality parameters, and maintaining product integrity is critically analyzed. Despite their benefits, challenges such as high costs, the need for specialized skills, and integration complexities with existing production processes are significant barriers. This review addresses these challenges and proposes solutions, including cost-reduction strategies, workforce training, and the development of adaptable systems. The paper concludes by outlining future research directions, particularly in validating these technologies in real-world scenarios and enhancing their accessibility to the industry. The findings offer valuable insights for researchers and industry stakeholders aiming to advance the quality control of canned fish products through innovative technological solutions.
Advancements and Challenges in Real-Time Electronic Vision Technologies for Canned Fish Quality Inspection: A Comprehensive Review
(2024) Sharmilan, Tharaga; Mahatheesan, Anis Jeluxsha
The global demand for high-quality canned fish products has driven the adoption of advanced inspection technologies to ensure consistency, safety, and compliance with industry standards. This paper provides a comprehensive review of real-time electronic vision technologies employed in the inspection of canned fish quality. It traces the evolution of the canned fish industry from manual inspection methods to sophisticated automated systems, emphasizing the role of technologies such as hyperspectral imaging, machine learning algorithms, and electronic vision systems. The effectiveness of these technologies in detecting defects, assessing quality parameters, and maintaining product integrity is critically analyzed. Despite their benefits, challenges such as high costs, the need for specialized skills, and integration complexities with existing production processes are significant barriers. This review addresses these challenges and proposes solutions, including cost-reduction strategies, workforce training, and the development of adaptable systems. The paper concludes by outlining future research directions, particularly in validating these technologies in real-world scenarios and enhancing their accessibility to the industry. The findings offer valuable insights for researchers and industry stakeholders aiming to advance the quality control of canned fish products through innovative technological solutions.
Anti-Counterfeit Method for Computer Hardware using Blockchain
(International Journal of Computer Applications, 2022) Britto, C.D.; Dias, N.G.J.
Counterfeited computer hardware are products designed looks exactly the same as their genuine products. Most of the people are tricked by the counterfeiters using online markets. This influences the need for a secure and efficient mechanism to identify fake/counterfeited products. The proposed method is implemented using the Blockchain technology. Each Block represents a product and the hash key of that product, calculated using the specified Block attributes. The buyer details were updated by a verified retailer. Thereafter any user can check the validity of the product using the hash key and retailer name. Tampered Block is notified to the customer and then the product is invalid. This system can be upgraded by hosting the application on a web server for distribution and separating the application functions according to the user levels (Manufacturer, retailer, and buyer). Therefore, the proposed method provides a more secure and reliable way to handle computer hardware counterfeits.
Biofilm formation by Staphylococcus spp. in different media and influence of hexavalent chromium
(International Conference of the Biotechnology Society of Nepal (ICBSN), 2021, 2021) Aththanayake, K.C.B.; Rathnayake, I.V.N; Deeyamulla, M.P; Mallavarapu, Megharaj
An aggregated community of prokaryotic and eukaryotic microorganisms (bacteria, fungi and algal etc.) which have adhered to substance/matrix surface and submerged/embedded in self-produced extracellular polymeric substances ...
Blood Pressure Estimation from Photoplethysmography with Motion Artifacts using Long Short Term Memory Network
(Journal of Biomimetics, Biomaterials and Biomedical Engineering (Volume 54), 2022) Welhenge, Anuradhi; Taparugssanagorn, Attaphongse
Continuous measurement of the Blood Pressure (BP) is important in hypertensive patientsand elderly population. Traditional cuff based methods are difficult to use since it is uncomfortable towear a cuff throughout the day. A more suitable method is to estimate the BP using the Photoplethysmography(PPG) signal. However, it is difficult to estimate a BP when the PPG is corrupted withMotion Artifacts (MAs). In this paper, Long Short Term Memory (LSTM) an extension of RecurrentNeural Networks (RNN) is used used to improve the accuracy of the estimation of the BP from thecorrupted PPG. It shows that an accuracy of 97.86 is achieved.
Characterising the Mould Rectification Process for Designing Scoliosis Braces: Towards Automated Digital Design of 3D-Printed Braces
(MDPI AG, 2021) Sanz-Pena, I.; Arachchi, S.; Halwala-Vithanage, D.; Mallikarachchi, S.; Kirumbara-Liyanage, J.; McGregor, A.; Silva, P.
The plaster-casting method to create a scoliosis brace consists of mould generation and rectification to obtain the desired orthosis geometry. Alternative methods entail the use of 3D scanning and CAD/CAM. However, both manual and digital design entirely rely on the orthotist expertise. Characterisation of the rectification process is needed to ensure that digital designs are as efficient as plaster-cast designs. Three-dimensional scans of five patients, pre-, and post-rectification plaster moulds were obtained using a Structure Mark II scanner. Anatomical landmark positions, transverse section centroids, and 3D surface deviation analyses were performed to characterise the rectification process. The rectification process was characterised using two parameters. First, trends in the external contours of the rectified moulds were found, resulting in lateral tilt angles of 81 ± 3.8° and 83.3 ± 2.6° on the convex and concave side, respectively. Second, a rectification ratio at the iliac crest (0.23 ± 0.04 and 0.11 ± 0.02 on the convex and concave side, respectively) was devised, based on the pelvis width to estimate the volume to be removed. This study demonstrates that steps of the manual rectification process can be characterised. Results from this study can be fed into software to perform automatic digital rectification.
Characterization of toluene degrading bacterial species isolated from soil
(International Conference of the Biotechnology Society of Nepal (ICBSN), 2021, 2021) Gunasinghe, Y.H.K.I.S. Y.H.K.I.S.; Rathnayake, I.V.N; Deeyamulla, M.P.
Natural environmental sources around us are actively participating in the bioremediation of hazardous contaminants. Prolonged inhalation of Volatile Organic Compounds (VOC) like toluene affects individual’s health conditions. ...
Deep learning based breast cancer detection system using fog computing
(Journal of Discrete Mathematical Sciences & Cryptography, 2022) Welhenge, Anuradhi
Among the different types of cancers, more women are suffering from breast cancer. Breast cancer can be identified by mammograms or using ultrasounds. Early detection of the cancer can be used to minimize the complexities the women will face. Deep learning based techniques such as convolutional neural networks (CNN) are used to detect the cancer from mammograms or ultrasound scans. In this study, VGGNet based CNN is used to detect the cancer cells. A novel architecture for collecting, processing and storing of patient data is proposed in this study involving a fog layer. This study achieved a high accuracy, sensitivity and specificity compared to previous studies.
Electronic Technologies for Quality Control in the Biscuit Manufacturing Process
(Lomaka & Romina Publisher, 2024) Lakshani, K.W.I.; Tharaga, Sharmilan
By 2030, the biscuit industry may go global due to advancements in electronic tools like eNose, eTongue, and eVision. This shift is governed by precision, productiveness, and regulatory compliance. Ultimately, the automation increase is driven by this consequence. This article will critically look at the issues and benefits arising within the biscuit production field after the shift towards the use of electronic control systems. It analyses the present situation and figures out the ineffectiveness on the part of conventional tools in solving the problem as it currently exists and shows how electronic instruments can be better in aiding visual and sensory inspections. While there have been remarkable achievements, these are persisting, of course, and they include high investment costs, specific skills requirements, and less flexibility when adapting to different production conditions. Without thorough research and development, the challenges in the production of the electronic control systems will still stand and no technology will be created to resolve the problems of the system. This study further reaffirms the need for the invention of modern and improved quality control processes for biscuit manufacturing plants. Through identifying previous methods and approaches and, the advantageous features of each, as well as highlighting shortcomings of current quality control strategies, this paper serves as an effective driving force for the future evolution and further improvement of quality control practices during biscuit production. Comprehensive product evaluation is attended to by employed approaches that analyse future benefits and opportunities as well as drawbacks and risks of the application of electronic quality control systems in the biscuit industry.
Energy Efficient Simple and Anonymous Crypto currency Management with Crypto Identities
(Journal of Green Engineering, 2021) Gamage, H.T.M.; Weerasinghe, H. D.; Dias, N. G. J.
Since the introduction of bitcoin, thousands of cryptocurrencies have been developed and adopted all over the world. Nevertheless, we believe they still have a long way to go in order to replace regular currencies in day-to-day activities. A separate cryptocurrency wallet is required to hold coins and tokens of its type, which is also one of the complicated problems concerning managing multiple cryptocurrencies. Every wallet has at least one unique alphanumeric identifier address, usually twenty-six or more characters in length. Since the blockchain ledger is public, the user’s anonymity is protected using this address when transferring e-money. Communicating this address is also a difficult process. The current method to resolve the communicating complexity without compromising anonymity is to use a QR code, requiring a QR scanner app. Transacting with different coins with the same user requires communicating all of the different wallet addresses. With this research, we propose a solution to the multifaceted problems of executing peer-to-peer cryptocurrency transactions and managing varied cryptocurrencies, without compromising anonymity. We introduce secure and anonymous crypto identities with an open protocol to securely communicate identities over a communication medium, tied to any number of different cryptocurrencies.
Fog computing based ultrasound nerve segmentation system using deep learning for mIoT
(2022) Welhenge, Anuradhi
Internet of Things is an ever expanding field and applications can be used for medical field. Patient monitoring and diagnosis can be done with the help of IoT and the problems of storing large amount of data can be solved by using cloud computing. However, when transmitting large amount of data through the network, the latency will be impacted. This can be eliminated by introducing a fog layer for the processing of data and processed data later can be stored in the cloud. This study proposes a novel architecture for a hospital ultrasound system and deep learning algorithm is used for the nerve segmentation and a good accuracy is achieved.
Grammatical Structure Oriented Automated Approach for Surface Knowledge Extraction from Open Domain Unstructured Text
(Journal of Information and Communication Convergence Engineering, 2022) Tissera, M.; Weerasinghe, R.
News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.
Impact of Climate Change and Variability on Spatiotemporal Variation of Forest Cover; World Heritage Sinharaja Rainforest, Sri Lanka
(Forest and Society, 2022) Samarasinghe, Jayanga T.; Gunathilake, Miyuru B.; Makubura, Randika K.; Arachchi, Shanika M.A.; Rathnayake, Upaka
Rainforests are continuously threatened by various anthropogenic activities. In addition, the ever-changing climate severely impacts the world’s rainforest cover. The consequences of these are paid back to human at a higher cost. Nevertheless, little or no significant attention was broadly given to this critical environmental issue. The World Heritage Sinharaja Rainforest in Sri Lanka is originating news on its forest cover due to human activities and changing climates. The scientific analysis is yet to be presented on the related issues. Therefore, this paper presents a comprehensive study on the possible impact on the Sinharaja Rainforest due to changing climate. Landsat images with measured rainfall data for 30 years were assessed and the relationships are presented. Results showcased that the built-up areas have drastically been increased over the last decade in the vicinity and the declared forest area. The authorities found the issues are serious and a sensitive task to negotiate in conserving the forest. The rainfall around the forest area has not shown significant trends over the years. Therefore, the health of forest cover was not severely impacted. Nevertheless, six cleared-up areas were found inside the Singaraja Rainforest under no human interactions. This can be due to a possible influence from the changing climate. This was justified by the temporal variation of Land Surface Temperature (LST) assessments over these six cleared-up areas. Therefore, the World Heritage rainforest is threatened due to human activities and under the changing climate change. Hence, the conservation of the Sinharaja Rainforest would be challenging in the future.
Inherent variability assessment from sparse property data of overburden soils and intermediate geomaterials using random field approaches
(Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 2022) Oluwatuyi, O. E.; Holt, R.; Rajapakshage, R.; Wulff, S. S.; Ng, K.
This study assesses the inherent variability in the geomaterial parameter by quantifying the parameter uncertainty and develops a site investigation plan with a low degree of uncertainty. A key research motivation was using sparse borehole data to predict a site geomaterial configuration in order to determine the design of a site investigation plan. This study develops a systematic methodology for carrying out a study of inherent variability in light of the limitations posed by borehole data. The data in this study was provided by the Iowa Department of Transportation which consisted of eight boreholes from which 92 associated SPT N-values was considered as the geomaterial parameter of interest. The systematic methodology then involved the following steps. A general linear model was employed to fit and compare various spatial covariance models with and without a nugget. These spatial covariance models were also evaluated with variograms. Predicted SPT N-values were generated using universal kriging. Simulations were performed conditionally and unconditionally to identify optimal site investigation plans. The results identified site investigation plans with reduced parameter uncertainty. The proposed approach can produce site investigation plans that target any or all geomaterial layers to reduce uncertainty with respect to any geomaterial parameter of interest.
Microbial Remediation Technologies for Mining Waste Management
(Springer, Singapore, 2024) Samarasekere, P.W.
Mining activities have significantly contributed to pollution and environmental degradation, generating vast amounts of waste that pose substantial risks to ecosystems. Conventional remediation methods often fail to address the complex nature of pollutants in mining wastes. Alternative approaches, such as microbial remediation, have emerged as promising solutions for sustainable remediation of contaminated sites. This chapter provides a detailed overview of microbial remediation technologies specifically tailored to mining and industrial waste. It explores the diversity of microorganisms capable of degrading various pollutants commonly found in these waste, including heavy metals, organic pollutants, and toxic chemicals. Additionally, it examines factors that affect microbial activity and the optimization of remediation processes. Furthermore, it highlights the advantages, limitations, and applicability of microbial remediation techniques for different types of mining and industrial waste. The chapter also discusses the challenges and considerations regarding the real-world implementation of microbial remediation. Additionally, it reviews the synergistic effects of combining different antimicrobial approaches to enhance overall efficacy and efficiency. Overall, this chapter presents a valuable resource for interested parties seeking to understand and apply microbial remediation technologies for mining and industrial waste. By harnessing the power of microbes, these techniques offer promising prospects for restoring contaminated sites, reducing environmental impacts, and promoting sustainable development.
Obtaining Patient Torso Geometry for the Design of Scoliosis Braces. A Study of the Accuracy and Repeatability of Handheld 3D Scanners
(Prosthetics and orthotics international, 2022) Sanz-Pena, I.; Arachchi, S.; Curtis-Woodcock, N.; Silva, P.; McGregor, A. H.; Newell, N.
Objective: Obtaining patient geometry is crucial in scoliosis brace design for patients with adolescent idiopathic scoliosis. Advances in 3D scanning technologies provide the opportunity to obtain patient geometries quickly with fewer resources during the design process compared with the plaster-cast method. This study assesses the accuracy and repeatability of such technologies for this application. Methods: The accuracy and repeatability of three different handheld scanners and phone-photogrammetry was assessed using different mesh generation software. Twenty-four scans of a single subject's torso were analyzed for accuracy and repeatability based on anatomical landmark distances and surface deviation maps. Results: Mark II and Structure ST01 scanners showed maximum mean surface deviations of 1.74 ± 3.63 mm and 1.64 ± 3.06 mm, respectively. Deviations were lower for the Peel 1 scanner (maximum of -0.35 ± 2.8 mm) but higher with the use of phone-photogrammetry (maximum of -5.1 ± 4.8 mm). The mean absolute errors of anatomical landmark distance measurements from torso meshes obtained with the Peel 1, Mark II, and ST01 scanners were all within 9.3 mm (3.6%), whereas phone-photogrammetry errors were as high as 18 mm (7%). Conclusions: Low-cost Mark II and ST01 scanners are recommended for obtaining torso geometries because of their accuracy and repeatability. Subject's breathing/movement affects the resultant geometry around the abdominal and anterolateral regions.
Optimal Site Investigation Through Combined Geological and Property Uncertainties Analysis
(Geotechnical and Geological Engineering, 2023) Oluwatuyi, O. E.; Ng, K.; Wulff, S. S.; Rajapakshage, R.
Site investigation is crucial in character- izing the geomaterial profile for the design of bridge pile foundations. A site investigation plan should be conducted to maximize geomaterial information and minimize uncertainty. Thus, both geological and property uncertainties should be explicitly incorpo- rated into a site investigation plan. This leads to the question of how to choose the corresponding optimal number and location of boreholes in a multiphase site investigation plan in order to reduce these uncer- tainties. This study addresses these problems using multinomial categorical prediction and universal kriging on a random field with multiple simulations. Site investigation data for this study are taken from a bridge project in Iowa, USA, which consists of four boreholes, each within the proximity of the pile foundation location. Subsequent numbers of recom- mended boreholes and their associated locations are determined to minimize the combined uncertain- ties. The effectiveness of this combined analysis for determining an optimal site investigation plan (OSIP) is validated and compared to an analysis done solely on property uncertainty. The proposed OSIP yields a lower prediction error, improves the prediction of geomaterial type and property, and reduces the sub- surface uncertainties. The incorporation of OSIP invariably improves the design efficiency and perfor- mance of bridge pile foundations
Parents' and Students’ Perceptions of the Education System of Sri Lanka
(SLTC Research University, 2022) Manjaree HS, Bhagya; Tillekaratne, Aashani; Rupasinghe, Thilini P.; Liyanage, Laalitha S.I.
Twenty-first-century skills such as critical thinking, communication, collaboration, and creativity, are widely accepted as skills in high demand within modern working environments. National school curricula reforms in Sri Lanka attempt to propose pedagogies that disseminate content and design assessments to promote twentyfirst- century skills. However, whether all stakeholders of the national school education agree to include such skills should be investigated before changes to curricula, policies and practices are implemented. The purpose of this study is to survey the perceptions of the main stakeholders of the national education system in Sri Lanka. The perceptions of parents, and students were investigated in this study. Seventeen (17) participants including nine (09) parents; three (03) school students, and five (05) vocational/degree level students) representing different social and educational backgrounds participated in the study. A standardized, semi-structured, open-ended questionnaire was conducted through virtual meeting mode. The 'Naturalized' transcription method was adopted in this study. Open coding of data revealed that more than 80% of the participants exhibited awareness of global 'good' practices and believed in the vital need for a change of policy and/or practice within the existing system. In addition, the participants expressed the need to improve students' emotional and attitudinal aspects within school setups. Interestingly some highlighted the need to consider external and control factors affecting policy/practice changes in education.
Plant and Plant Associated Microflora: Potential Bioremediation Option of Indoor Air Pollutants.
(Nepal Journal of Biotechnology, 2021, 2021) Gunasinghe, Y. H. K. I. S.; Rathnayake, I.V.N.; Deeyamulla, M. P.
Indoor air pollution is a significant problem today because the release of various contaminants into the indoor air has created a major health threat for humans occupying indoors. Volatile Organic Compounds (VOCs) are ...
Proposed hybrid approach for three-dimensional subsurface simulation to improve boundary determination and design of optimum site investigation plan for pile foundations
(Soils and Foundations, 2023) Oluwatuyi, O. E.; Rajapakshage, R.; Wulff, S. S.; Ng, K.
Geological uncertainty refers to the changeability of a geomaterial category embedded in another. It arises from predicting a geomaterial category at unobserved locations using categorical data from a site investigation (SI). In the design of bridge foundations, geological uncertainty is often not considered because of the difficulties of assessing it using sparse borehole data, validating the quality of predictions, and incorporating such uncertainties into pile foundation design. To overcome these problems, this study utilizes sparse borehole data and proposes a hybrid approach of various spatial Markov Chain (spMC) models and Monte Carlo simulation to predict three-dimensional (3D) geomaterial categories and assess geological uncertainties. The 3D analysis gives realistic and comprehensive information about the site. Characteristics of the proposed hybrid approach include the estimation of transition rates, prediction of 3D geomaterial categories, and simulation of multiple realizations to propagate the uncertainties quantified by information entropy. This proposed hybrid approach leads to specific novelties that include the development of optimal SI plans to reduce geological uncertainty and the determination of geomaterial layer boundaries according to the quantified geological uncertainty. Reducing the geological uncertainties and accurately determining spatial geomaterial boundaries will improve the design reliability and safety of bridge foundations. The hybrid approach is applied to the Lodgepole Creek Bridge project site in Wyoming to demonstrate the application of the hybrid approach and the associated novelties. Outcomes are cross-validated to evaluate the geomaterial prediction accuracy of the hybrid approach.