Displaying publications 1 - 20 of 766 in total

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  1. Hariri F, Malek RA, Abdullah NA, Hassan SF
    Int J Oral Maxillofac Surg, 2024 Apr;53(4):293-300.
    PMID: 37739816 DOI: 10.1016/j.ijom.2023.08.009
    Midface hypoplasia in syndromic craniosynostosis (SC) may lead to serious respiratory issues. The aim of this study was to analyse the morphometric correlation between midface and cranial base parameters in paediatric SC patients in order to formulate predictive regression models. The computed tomography scans of 18 SC patients and 20 control were imported into Materialise Mimics Medical version 21.0 software for the measurement of multiple craniofacial landmarks and correlation analysis. The results showed a strong correlation of anterior cranial base (SN), posterior cranial base (SBa), and total cranial base (NBa) (r = 0.935) to maxilla length and width (ZMR-ZML) (r = 0.864). The model of NBa = - 1.554 + 1.021(SN) + 0.753(SBa) with R2 = 0.875 is proposed to demonstrate the development of the cranial base that causes a certain degree of midface hypoplasia in SC patients. The formula is supported using a prediction model of ZMR-ZML = 5.762 + 0.920(NBa), with R2 = 0.746. The mean absolute difference and standard deviation between the predicted and true NBa and ZMR-ZML were 2.08 ± 1.50 mm and 3.11 ± 2.32 mm, respectively. The skeletal growth estimation models provide valuable foundation for further analysis and potential clinical application.
    Matched MeSH terms: Software
  2. Tey SN, Syed Mohamed AMF, Marizan Nor M
    J Forensic Sci, 2024 Jan;69(1):189-198.
    PMID: 37706423 DOI: 10.1111/1556-4029.15380
    Recent advances in imaging technologies, such as intra-oral surface scanning, have rapidly generated large datasets of high-resolution three-dimensional (3D) sample reconstructions. These datasets contain a wealth of phenotypic information that can provide an understanding of morphological variation and evolution. The geometric morphometric method (GMM) with landmarks and the development of sliding and surface semilandmark techniques has greatly enhanced the quantification of shape. This study aimed to determine whether there are significant differences in 3D palatal rugae shape between siblings. Digital casts representing 25 pairs of full siblings from each group, male-male (MM), female-female (FF), and female-male (FM), were digitized and transferred to a GM system. The palatal rugae were determined, quantified, and visualized using GMM computational tools with MorphoJ software (University of Manchester). Principal component analysis (PCA) and canonical variates analysis (CVA) were employed to analyze palatal rugae shape variability and distinguish between sibling groups based on shape. Additionally, regression analysis examined the potential impact of shape on palatal rugae. The study revealed that the palatal rugae shape covered the first nine of the PCA by 71.3%. In addition, the size of the palatal rugae has a negligible impact on its shape. Whilst palatal rugae are known for their individuality, it is noteworthy that three palatal rugae (right first, right second, and left third) can differentiate sibling groups, which may be attributed to genetics. Therefore, it is suggested that palatal rugae morphology can serve as forensic identification for siblings.
    Matched MeSH terms: Software
  3. Osman ND, Abdulkadir MK, Shuaib IL, Nasirudin RA
    Radiography (Lond), 2024 Jan;30(1):237-244.
    PMID: 38035439 DOI: 10.1016/j.radi.2023.11.012
    INTRODUCTION: The adoption of size-specific dose estimate (SSDE) in clinical practice is still limited owing to the tedious and complex manual measurement of individual patient size for the clinical calculation of SSDE. Thus, the automation of SSDE is imperative. This study aims to evaluate a predictive equation for the automated calculation of SSDE.

    METHODS: A user-friendly software was developed to accurately predict the individual size-specific dose estimation of paediatric patients undergoing computed tomography (CT) scans of the head, thorax, and abdomen. The software includes a calculation equation developed based on a novel SSDE prediction equation that used a population's pre-determined percentage difference between volume-weighted computed tomography dose index (CTDIvol) and SSDE with age. American Association of Physicists in Medicine (AAPM RPT 204) method (manual) and segmentation-based SSDE calculators (indoseCT and XXautocalc) were used to assess the proposed software predictions comparatively.

    RESULTS: The results of this study show that the automated equation-based calculation of SSDE and the manual and segmentation-based calculation of SSDE are in good agreement for patients. The differences between the automated equation-based calculation of SSDE and the manual and segmentation-based calculation are less than 3%.

    CONCLUSION: This study validated an accurate SSDE calculator that allows users to enter key input values and calculate SSDE.

    IMPLICATION FOR PRACTICE: The automated equation-based SSDE software (PESSD) seems a promising tool for estimating individualised CT doses during CT scans.

    Matched MeSH terms: Software
  4. Yap Abdullah J, Manaf Abdullah A, Zaim S, Hadi H, Husein A, Ahmad Rajion Z, et al.
    Proc Inst Mech Eng H, 2024 Jan;238(1):55-62.
    PMID: 37990963 DOI: 10.1177/09544119231212034
    This study aimed to compare the 3D skull models reconstructed from computed tomography (CT) images using three different open-source software with a commercial software as a reference. The commercial Mimics v17.0 software was used to reconstruct the 3D skull models from 58 subjects. Next, two open-source software, MITK Workbench 2016.11, 3D Slicer 4.8.1 and InVesalius 3.1 were used to reconstruct the 3D skull models from the same subjects. All four software went through similar steps in 3D reconstruction process. The 3D skull models from the commercial and open-source software were exported in standard tessellation language (STL) format into CloudCompare v2.8 software and superimposed for geometric analyses. Hausdorff distance (HD) analysis demonstrated the average points distance of Mimics versus MITK was 0.25 mm. Meanwhile, for Mimics versus 3D Slicer and Mimics versus InVesalius, there was almost no differences between the two superimposed 3D skull models with average points distance of 0.01 mm. Based on Dice similarity coefficient (DSC) analysis, the similarity between Mimics versus MITK, Mimics versus 3D Slicer and Mimics versus InVesalius were 94.1, 98.8 and 98.3%, respectively. In conclusion, this study confirmed that the alternative open-source software, MITK, 3D Slicer and InVesalius gave comparable results in 3D reconstruction of skull models compared to the commercial gold standard Mimics software. This open-source software could possibly be used for pre-operative planning in cranio-maxillofacial cases and for patient management in the hospitals or institutions with limited budget.
    Matched MeSH terms: Software
  5. Bahashwan AA, Anbar M, Manickam S, Issa G, Aladaileh MA, Alabsi BA, et al.
    PLoS One, 2024;19(2):e0297548.
    PMID: 38330004 DOI: 10.1371/journal.pone.0297548
    Software Defined Network (SDN) has alleviated traditional network limitations but faces a significant challenge due to the risk of Distributed Denial of Service (DDoS) attacks against an SDN controller, with current detection methods lacking evaluation on unrealistic SDN datasets and standard DDoS attacks (i.e., high-rate DDoS attack). Therefore, a realistic dataset called HLD-DDoSDN is introduced, encompassing prevalent DDoS attacks specifically aimed at an SDN controller, such as User Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), and User Datagram Protocol (UDP). This SDN dataset also incorporates diverse levels of traffic fluctuations, representing different traffic variation rates (i.e., high and low rates) in DDoS attacks. It is qualitatively compared to existing SDN datasets and quantitatively evaluated across all eight scenarios to ensure its superiority. Furthermore, it fulfils the requirements of a benchmark dataset in terms of size, variety of attacks and scenarios, with significant features that highly contribute to detecting realistic SDN attacks. The features of HLD-DDoSDN are evaluated using a Deep Multilayer Perception (D-MLP) based detection approach. Experimental findings indicate that the employed features exhibit high performance in the detection accuracy, recall, and precision of detecting high and low-rate DDoS flooding attacks.
    Matched MeSH terms: Software
  6. Altharan YM, Shamsudin S, Lajis MA, Al-Alimi S, Yusuf NK, Alduais NAM, et al.
    PLoS One, 2024;19(3):e0300504.
    PMID: 38484005 DOI: 10.1371/journal.pone.0300504
    Direct recycling of aluminum waste is crucial in sustainable manufacturing to mitigate environmental impact and conserve resources. This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. The experimental runs were designed using Full factorial and RSM via Minitab 21 software. RSM-ANN models were employed to examine the effect of factors and their interactions on response and to predict output, while GA-RSM and GA-ANN were used for optimization. The chips of different morphology were cold compressed into billet form and then hot forged. The effect of varying forging temperature (Tp, 450-550°C), holding time (HT, 60-120 minutes), and chip surface area to volume ratio (AS:V, 15.4-52.6 mm2/mm3) on ultimate tensile strength (UTS) was examined. Maximum UTS (237.4 MPa) was achieved at 550°C, 120 minutes and 15.4 mm2/mm3 of chip's AS: V. The Tp had the largest contributing effect ratio on the UTS, followed by HT and AS:V according to ANOVA analysis. The proposed optimization process suggested 550°C, 60 minutes, and 15.4 mm2 as the optimal condition yielding the maximum UTS. The developed models' evaluation results showed that ANN (with MSE = 1.48%) outperformed RSM model. Overall, the study promotes sustainable production by demonstrating the potential of integrating RSM and ML to optimize complex manufacturing processes and improve product quality.
    Matched MeSH terms: Software
  7. Aggarwal A, Court LE, Hoskin P, Jacques I, Kroiss M, Laskar S, et al.
    BMJ Open, 2023 Dec 07;13(12):e077253.
    PMID: 38149419 DOI: 10.1136/bmjopen-2023-077253
    INTRODUCTION: Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%-40% of patients in low-income and middle-income countries (LMICs) have access to it. A shortfall in specialised workforce has been identified as the most significant barrier to expanding radiotherapy capacity. Artificial intelligence (AI)-based software has been developed to automate both the delineation of anatomical target structures and the definition of the position, size and shape of the radiation beams. Proposed advantages include improved treatment accuracy, as well as a reduction in the time (from weeks to minutes) and human resources needed to deliver radiotherapy.

    METHODS: ARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs.

    ETHICS AND DISSEMINATION: The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.

    Matched MeSH terms: Software
  8. Leong ST, Liew SY, Khaw KY, Ahmad Hassali H, Richomme P, Derbré S, et al.
    Bioorg Chem, 2023 Dec;141:106859.
    PMID: 37742494 DOI: 10.1016/j.bioorg.2023.106859
    A bio-assay guided fractionation strategy based on cholinesterase assay combined with 13C NMR-based dereplication was used to identify active metabolites from the bark of Mesua lepidota. Eight compounds were identified with the aid of the 13C NMR-based dereplication software, MixONat, i.e., sitosterol (1), stigmasterol (2), α-amyrin (3), friedelin (6), 3β-friedelinol (7), betulinic acid (9), lepidotol A (10) and lepidotol B (11). Further bio-assay guided isolation of active compounds afforded one xanthone, pyranojacareubin (12) and six coumarins; lepidotol A (10), lepidotol B (11), lepidotol E (13), lepidotin A (14), and lepidotin B (15), including a new Mammea coumarin, lepidotin C (16). All the metabolites showed strong to moderate butyrylcholinesterase (BChE) inhibition. Lepidotin B (15) exhibited the most potent inhibition towards BChE with a mix-mode inhibition profile and a Ki value of 1.03 µM. Molecular docking and molecular dynamics simulations have revealed that lepidotin B (15) forms stable interactions with key residues within five critical regions of BChE. These regions encompass residues Asp70 and Tyr332, the acyl hydrophobic pocket marked by Leu286, the catalytic triad represented by Ser198 and His438, the oxyanion hole (OH) constituted by Gly116 and Gly117, and the choline binding site featuring Trp82. To gauge the binding strength of lepidotin B (15) and to pinpoint pivotal residues at the binding interface, free energy calculations were conducted using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) approach. This analysis not only predicted a favourable binding affinity for lepidotin B (15) but also facilitated the identification of significant residues crucial for the binding interaction.
    Matched MeSH terms: Software
  9. Darmini, Prastanti AD, Daryati S, Kartikasari Y, Sulistiyadi AH, Setiawan DA
    Med J Malaysia, 2023 Dec;78(7):865-869.
    PMID: 38159919
    INTRODUCTION: There are two data acquisition methods for computed tomography (CT) scans, namely sequence and helical. Each of them has two ways of measuring the volume of bleeding in a head CT scan, namely by manual and automatic methods. So, it is necessary to have an analysis for measurement accuracy with these two methods in two data acquisitions. The purpose of this study was to compare and evaluate bleeding volumetric measurement accuracy of sequence and helical on head CT acquisition using manual and automatic methods.

    MATERIALS AND METHODS: This is quantitative research with a true experimental approach. Actual bleeding volume was simulated by an acrylic phantom containing Iodine contrast media (5 ml, 10 ml, 15 ml, and 20 ml). The phantom was scanned using routine CT protocol using the helical and sequence technique. Bleeding volume from each technique was measured manually using the Broderick formula and automatic software (ROI based). Accuracy was assessed by comparing the volume measurement result to the actual bleeding volume. Data was analysed using the Friedman test and by Wilcoxon.

    RESULTS: The standard deviation of measured bleeding volume from the manual and automatic measurements compared to the actual bleeding volume were (0.220; 0.236; 0.351; 0.057) and (0.139; 0.270; 0.315; 0.329) in helical technique, and (0.333; 0.376; 0.447; 0.476) and (0.139; 0.242; 0.288; 0,376) in sequence technique. There are differences in the measurement results from the helical and sequence techniques (p <0.05) and using manual and automatic methods (p <0.05).

    CONCLUSION: The measurement of bleeding volume that has a standard deviation value compared to the actual volume is more accurate in the helical technique using the automatic method, while the sequence technique is the manual method.

    Matched MeSH terms: Software*
  10. Woon LS, Mohd Daud TI, Tong SF
    BMC Med Educ, 2023 Nov 09;23(1):851.
    PMID: 37946151 DOI: 10.1186/s12909-023-04834-9
    BACKGROUND: At the Faculty of Medicine of the National University of Malaysia, a virtual patient software program, DxR Clinician, was utilised for the teaching of neurocognitive disorder topics during the psychiatry posting of undergraduate medical students in a modified team-based learning (TBL) module. This study aimed to explore medical students' learning experiences with virtual patient.

    METHODS: Ten students who previously underwent the learning module were recruited through purposive sampling. The inclusion criteria were: (a) Fourth-year medical students; and (b) Completed psychiatry posting with the new module. Students who dropped out or were unable to participate in data collection were excluded. Two online focus group discussions (FGDs) with five participants each were conducted by an independent facilitator, guided by a questioning route. The data were transcribed verbatim and coded using the thematic analysis approach to identify themes.

    RESULTS: Three main themes of their learning experience were identified: (1) fulfilment of the desired pedagogy (2), realism of the clinical case, and (3) ease of use related to technical settings. The pedagogy theme was further divided into the following subthemes: level of entry for students, flexibility of presentation of content, provision of learning guidance, collaboration with peers, provision of feedback, and assessment of performance. The realism theme had two subthemes: how much the virtual patient experience mimicked an actual patient and how much the case scenario reflected real conditions in the Malaysian context. The technical setting theme entailed two subthemes: access to the software and appearance of the user interface. The study findings are considered in the light of learning formats, pedagogical and learning theories, and technological frameworks.

    CONCLUSIONS: The findings shed light on both positive and negative aspects of using virtual patients for medical students' psychiatry posting, which opens room for further improvement of their usage in undergraduate psychiatry education.

    Matched MeSH terms: Software
  11. Budati AK, Islam S, Hasan MK, Safie N, Bahar N, Ghazal TM
    Sensors (Basel), 2023 May 25;23(11).
    PMID: 37299798 DOI: 10.3390/s23115072
    The global expansion of the Visual Internet of Things (VIoT)'s deployment with multiple devices and sensor interconnections has been widespread. Frame collusion and buffering delays are the primary artifacts in the broad area of VIoT networking applications due to significant packet loss and network congestion. Numerous studies have been carried out on the impact of packet loss on Quality of Experience (QoE) for a wide range of applications. In this paper, a lossy video transmission framework for the VIoT considering the KNN classifier merged with the H.265 protocols. The performance of the proposed framework was assessed while considering the congestion of encrypted static images transmitted to the wireless sensor networks. The performance analysis of the proposed KNN-H.265 protocol is compared with the existing traditional H.265 and H.264 protocols. The analysis suggests that the traditional H.264 and H.265 protocols cause video conversation packet drops. The performance of the proposed protocol is estimated with the parameters of frame number, delay, throughput, packet loss ratio, and Peak Signal to Noise Ratio (PSNR) on MATLAB 2018a simulation software. The proposed model gives 4% and 6% better PSNR values than the existing two methods and better throughput.
    Matched MeSH terms: Software
  12. Manley S
    Account Res, 2023 May;30(4):219-245.
    PMID: 34569370 DOI: 10.1080/08989621.2021.1986018
    Popular text-matching software generates a percentage of similarity - called a "similarity score" or "Similarity Index" - that quantifies the matching text between a particular manuscript and content in the software's archives, on the Internet and in electronic databases. Many evaluators rely on these simple figures as a proxy for plagiarism and thus avoid the burdensome task of inspecting the longer, detailed Similarity Reports. Yet similarity scores, though alluringly straightforward, are never enough to judge the presence (or absence) of plagiarism. Ideally, evaluators should always examine the Similarity Reports. Given the persistent use of simplistic similarity score thresholds at some academic journals and educational institutions, however, and the time that can be saved by relying on the scores, a method is arguably needed that encourages examining the Similarity Reports but still also allows evaluators to rely on the scores in some instances. This article proposes a four-band method to accomplish this. Used together, the bands oblige evaluators to acknowledge the risk of relying on the similarity scores yet still allow them to ultimately determine whether they wish to accept that risk. The bands - for most rigor, high rigor, moderate rigor and less rigor - should be tailored to an evaluator's particular needs.
    Matched MeSH terms: Software*
  13. Huang Z, Wang J, Lu X, Mohd Zain A, Yu G
    Brief Bioinform, 2023 Mar 19;24(2).
    PMID: 36733262 DOI: 10.1093/bib/bbad040
    Single-cell RNA sequencing (scRNA-seq) data are typically with a large number of missing values, which often results in the loss of critical gene signaling information and seriously limit the downstream analysis. Deep learning-based imputation methods often can better handle scRNA-seq data than shallow ones, but most of them do not consider the inherent relations between genes, and the expression of a gene is often regulated by other genes. Therefore, it is essential to impute scRNA-seq data by considering the regional gene-to-gene relations. We propose a novel model (named scGGAN) to impute scRNA-seq data that learns the gene-to-gene relations by Graph Convolutional Networks (GCN) and global scRNA-seq data distribution by Generative Adversarial Networks (GAN). scGGAN first leverages single-cell and bulk genomics data to explore inherent relations between genes and builds a more compact gene relation network to jointly capture the homogeneous and heterogeneous information. Then, it constructs a GCN-based GAN model to integrate the scRNA-seq, gene sequencing data and gene relation network for generating scRNA-seq data, and trains the model through adversarial learning. Finally, it utilizes data generated by the trained GCN-based GAN model to impute scRNA-seq data. Experiments on simulated and real scRNA-seq datasets show that scGGAN can effectively identify dropout events, recover the biologically meaningful expressions, determine subcellular states and types, improve the differential expression analysis and temporal dynamics analysis. Ablation experiments confirm that both the gene relation network and gene sequence data help the imputation of scRNA-seq data.
    Matched MeSH terms: Software*
  14. Ong TS, Lee AS, Latif B, Sroufe R, Sharif A, Heng Teh B
    Environ Sci Pollut Res Int, 2023 Mar;30(11):31711-31726.
    PMID: 36454525 DOI: 10.1007/s11356-022-24280-2
    Consistent with the worldwide call to combat environmental degradation concerns and advance sustainable development, there is increasing pressure on organizations to ensure organizational strategies include green initiatives. In this regard, environmental strategic focus is a relevant concept for scholars and business leaders. Underpinned by dynamic capability and stakeholder theory, the present study hypothesizes that ESF derives environmental performance, coordinated by mediating role of green shared vision that strategic environmental planning and decision making. Additionally, the current study employed ISO 14001 and technological capability as moderators between ESF and the green shared vision link. Methodologically, the data for this study was collected from 162 senior managerial officials working in EMS 14,001-accredited manufacturing firms in Malaysia. The data were analyzed with the AMOS 23 software to perform covariance-based structural equation modeling (CB-SEM), and then hierarchical regression analysis and moderated-mediation analysis were applied with SPSS 25. The findings confirmed that ESF is positively linked to environmental performance. The results validate that green shared vision acts as a positive mediator between ESF and environmental performance, in which the creation and sharing of knowledge embedded in a green shared vision serve as enablers to create higher environmental performance. The current study also validates a significant moderating role of ISO 14001 and technological capability between ESF and green shared vision. The study confirms how environmental strategies are integrated into environmental management processes that can serve as a source of dynamic capabilities.
    Matched MeSH terms: Software
  15. Khalid H, Mekhilef S, Siddique MD, Wahyudie A, Ahmed M, Seyedmahmoudian M, et al.
    PLoS One, 2023;18(1):e0277331.
    PMID: 36638108 DOI: 10.1371/journal.pone.0277331
    Most silicon carbide (SiC) MOSFET models are application-specific. These are already defined by the manufacturers and their parameters are mostly partially accessible due to restrictions. The desired characteristic of any SiC model becomes highly important if an individual wants to visualize the impact of changing intrinsic parameters as well. Also, it requires a model prior knowledge to vary these parameters accordingly. This paper proposes the parameter extraction and its selection for Silicon Carbide (SiC) power N-MOSFET model in a unique way. The extracted parameters are verified through practical implementation with a small-scale high power DC-DC 5 to 2.5 output voltage buck converter using both hardware and software emphasis. The parameters extracted using the proposed method are also tested to verify the static and dynamic characteristics of SiC MOSFET. These parameters include intrinsic, junction and overlapping capacitance. The parameters thus extracted for the SiC MOSFET are analyzed by device performance. This includes input, output transfer characteristics and transient delays under different temperature conditions and loading capabilities. The simulation and experimental results show that the parameters are highly accurate. With its development, researchers will be able to simulate and test any change in intrinsic parameters along with circuit emphasis.
    Matched MeSH terms: Software*
  16. Chong JWR, Khoo KS, Chew KW, Ting HY, Show PL
    Biotechnol Adv, 2023;63:108095.
    PMID: 36608745 DOI: 10.1016/j.biotechadv.2023.108095
    Identification of microalgae species is of importance due to the uprising of harmful algae blooms affecting both the aquatic habitat and human health. Despite this occurence, microalgae have been identified as a green biomass and alternative source due to its promising bioactive compounds accumulation that play a significant role in many industrial applications. Recently, microalgae species identification has been conducted through DNA analysis and various microscopy techniques such as light, scanning electron, transmission electron, and atomic force -microscopy. The aforementioned procedures have encouraged researchers to consider alternate ways due to limitations such as costly validation, requiring skilled taxonomists, prolonged analysis, and low accuracy. This review highlights the potential innovations in digital microscopy with the incorporation of both hardware and software that can produce a reliable recognition, detection, enumeration, and real-time acquisition of microalgae species. Several steps such as image acquisition, processing, feature extraction, and selection are discussed, for the purpose of generating high image quality by removing unwanted artifacts and noise from the background. These steps of identification of microalgae species is performed by reliable image classification through machine learning as well as deep learning algorithms such as artificial neural networks, support vector machines, and convolutional neural networks. Overall, this review provides comprehensive insights into numerous possibilities of microalgae image identification, image pre-processing, and machine learning techniques to address the challenges in developing a robust digital classification tool for the future.
    Matched MeSH terms: Software
  17. Watimin NH, Zanuddin H, Rahamad MS, Yadegaridehkordi E
    PLoS One, 2023;18(10):e0287367.
    PMID: 37851696 DOI: 10.1371/journal.pone.0287367
    Social media has been tremendously used worldwide for a variety of purposes. Therefore, engagement activities such as comments have attracted many scholars due its ability to reveal many critical findings, such as the role of users' sentiment. However, there is a lacuna on how to detect crisis based on users' sentiment through comments, and for such, we explore framing theory in the study herein to determine users' sentiment in predicting crisis. Generic content framing theory consists of conflict, economic, human interest, morality, and responsibility attributes frame as independent variables whilst sentiment as dependent variables. Comments from selected Facebook posting case studies were extracted and analysed using sentiment analysis via Application Programme Interface (API) webtool. The comments were then further analysed using content analysis via Positive and Negative Affect Schedule (PANAS) scale and statistically evaluated using SEM-PLS. Model shows that 44.8% of emotion and reactions towards sensitive issue posting are influenced by independent variables. Only economic consequences and responsibility attributes frame had correlation towards emotion and reaction at p<0.05. News reporting on direction towards economic and responsibility attributes sparks negative sentiment, which proves that it can best be described as pre-crisis detection to assist the Royal Malaysian Police and other relevant stakeholders to prevent criminal activities in their respective social media.
    Matched MeSH terms: Software
  18. Almogahed A, Mahdin H, Omar M, Zakaria NH, Gu YH, Al-Masni MA, et al.
    PLoS One, 2023;18(11):e0293742.
    PMID: 37917752 DOI: 10.1371/journal.pone.0293742
    Refactoring, a widely adopted technique, has proven effective in facilitating and reducing maintenance activities and costs. Nonetheless, the effects of applying refactoring techniques on software quality exhibit inconsistencies and contradictions, leading to conflicting evidence on their overall benefit. Consequently, software developers face challenges in leveraging these techniques to improve software quality. Moreover, the absence of a categorization model hampers developers' ability to decide the most suitable refactoring techniques for improving software quality, considering specific design goals. Thus, this study aims to propose a novel refactoring categorization model that categorizes techniques based on their measurable impacts on internal quality attributes. Initially, the most common refactoring techniques used by software practitioners were identified. Subsequently, an experimental study was conducted using five case studies to measure the impacts of refactoring techniques on internal quality attributes. A subsequent multi-case analysis was conducted to analyze these effects across the case studies. The proposed model was developed based on the experimental study results and the subsequent multi-case analysis. The model categorizes refactoring techniques into green, yellow, and red categories. The proposed model, by acting as a guideline, assists developers in understanding the effects of each refactoring technique on quality attributes, allowing them to select appropriate techniques to improve specific quality attributes. Compared to existing studies, the proposed model emerges superior by offering a more granular categorization (green, yellow, and red categories), and its range is wide (including ten refactoring techniques and eleven internal quality attributes). Such granularity not only equips developers with an in-depth understanding of each technique's impact but also fosters informed decision-making. In addition, the proposed model outperforms current studies and offers a more nuanced understanding, explicitly highlighting areas of strength and concern for each refactoring technique. This enhancement aids developers in better grasping the implications of each refactoring technique on quality attributes. As a result, the model simplifies the decision-making process for developers, saving time and effort that would otherwise be spent weighing the benefits and drawbacks of various refactoring techniques. Furthermore, it has the potential to help reduce maintenance activities and associated costs.
    Matched MeSH terms: Software*
  19. Ghani NSA, Emrizal R, Moffit SM, Hamdani HY, Ramlan EI, Firdaus-Raih M
    Nucleic Acids Res, 2022 Jul 05;50(W1):W375-W383.
    PMID: 35639505 DOI: 10.1093/nar/gkac402
    The GrAfSS (Graph theoretical Applications for Substructure Searching) webserver is a platform to search for three-dimensional substructures of: (i) amino acid side chains in protein structures; and (ii) base arrangements in RNA structures. The webserver interfaces the functions of five different graph theoretical algorithms - ASSAM, SPRITE, IMAAAGINE, NASSAM and COGNAC - into a single substructure searching suite. Users will be able to identify whether a three-dimensional (3D) arrangement of interest, such as a ligand binding site or 3D motif, observed in a protein or RNA structure can be found in other structures available in the Protein Data Bank (PDB). The webserver also allows users to determine whether a protein or RNA structure of interest contains substructural arrangements that are similar to known motifs or 3D arrangements. These capabilities allow for the functional annotation of new structures that were either experimentally determined or computationally generated (such as the coordinates generated by AlphaFold2) and can provide further insights into the diversity or conservation of functional mechanisms of structures in the PDB. The computed substructural superpositions are visualized using integrated NGL viewers. The GrAfSS server is available at http://mfrlab.org/grafss/.
    Matched MeSH terms: Software*
  20. Alu'datt MH, Khamayseh Y, Alhamad MN, Tranchant CC, Gammoh S, Rababah T, et al.
    Food Chem, 2022 Mar 30;373(Pt B):131531.
    PMID: 34823940 DOI: 10.1016/j.foodchem.2021.131531
    The nutrient composition of 50 commonly consumed Jordanian food dishes was determined to support the development of a novel nutrition management system designed to assist with dietary intake assessment and diet management. Composite dishes were selected by interviewing households located in the northern region of Jordan. For each dish, five different recipes were collected from experienced chefs and the typical recipe was formulated based on the average weights of ingredients and net weight of the dish. Proximate composition as well as vitamin and mineral contents were determined and related to ingredient composition and cooking conditions. The newly created food composition database was used to develop a user-centric nutrition management software tailored to reflect the characteristics of the Jordanian diet with representative items from this diet. This novel nutrition management system is customizable, enabling users to build daily meal plans in accordance with personalized dietary needs and goals.
    Matched MeSH terms: Software
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