Displaying publications 1 - 20 of 99 in total

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  1. Fulltext Digital signature schemes with strong existential unforgeability
    Chia J, Chin JJ, Yip SC
    F1000Res, 2021;10:931.
    PMID: 36798451 DOI: 10.12688/f1000research.72910.1
    Digital signature schemes (DSS) are ubiquitously used for public authentication in the infrastructure of the internet, in addition to their use as a cryptographic tool to construct even more sophisticated schemes such as those that are identity-based. The security of DSS is analyzed through the existential unforgeability under chosen message attack (EUF-CMA) experiment which promises unforgeability of signatures on new messages even when the attacker has access to an arbitrary set of messages and their corresponding signatures. However, the EUF-CMA model does not account for attacks such as an attacker forging a different signature on an existing message, even though the attack could be devastating in the real world and constitutes a severe breach of the security system. Nonetheless, most of the DSS are not analyzed in this security model, which possibly makes them vulnerable to such an attack. In contrast, a better security notion known as strong EUF-CMA (sEUF-CMA) is designed to be resistant to such attacks. This review aims to identify DSS in the literature that are secure in the sEUF-CMA model. In addition, the article discusses the challenges and future directions of DSS. In our review, we consider the security of existing DSS that fit our criterion in the sEUF-CMA model; our criterion is simple as we only require the DSS to be at least secure against the minimum of existential forgery. Our findings are categorized into two classes: the direct and indirect classes of sEUF-CMA. The former is inherently sEUF-CMA without any modification while the latter requires some transformation. Our comprehensive  review contributes to the security and cryptographic research community by discussing the efficiency and security of DSS that are sEUF-CMA, which aids in selecting robust DSS in future design considerations.
  2. MSTCN: A multiscale temporal convolutional network for user independent human activity recognition
    Raja Sekaran S, Pang YH, Ling GF, Yin OS
    F1000Res, 2021;10:1261.
    PMID: 36896393 DOI: 10.12688/f1000research.73175.2
    Background: In recent years, human activity recognition (HAR) has been an active research topic due to its widespread application in various fields such as healthcare, sports, patient monitoring, etc. HAR approaches can be categorised as handcrafted feature methods (HCF) and deep learning methods (DL). HCF involves complex data pre-processing and manual feature extraction in which the models may be exposed to high bias and crucial implicit pattern loss. Hence, DL approaches are introduced due to their exceptional recognition performance. Convolutional Neural Network (CNN) extracts spatial features while preserving localisation. However, it hardly captures temporal features. Recurrent Neural Network (RNN) learns temporal features, but it is susceptible to gradient vanishing and suffers from short-term memory problems. Unlike RNN, Long-Short Term Memory network has a relatively longer-term dependency. However, it consumes higher computation and memory because it computes and stores partial results at each level. Methods: This work proposes a novel multiscale temporal convolutional network (MSTCN) based on the Inception model with a temporal convolutional architecture. Unlike HCF methods, MSTCN requires minimal pre-processing and no manual feature engineering. Further, multiple separable convolutions with different-sized kernels are used in MSTCN for multiscale feature extraction. Dilations are applied to each separable convolution to enlarge the receptive fields without increasing the model parameters. Moreover, residual connections are utilised to prevent information loss and gradient vanishing. These features enable MSTCN to possess a longer effective history while maintaining a relatively low in-network computation. Results: The performance of MSTCN is evaluated on UCI and WISDM datasets using subject independent protocol with no overlapping subjects between the training and testing sets. MSTCN achieves F1 scores of 0.9752 on UCI and 0.9470 on WISDM. Conclusion: The proposed MSTCN dominates the other state-of-the-art methods by acquiring high recognition accuracies without requiring any manual feature engineering.
  3. Modified recurrent equation-based cubic spline interpolation for missing data recovery in phasor measurement unit (PMU)
    Thangaraj S, Goh VT, Yap TTV
    F1000Res, 2022;11:246.
    PMID: 38152076 DOI: 10.12688/f1000research.73182.3
    BACKGROUND: Smart grid systems require high-quality Phasor Measurement Unit (PMU) data for proper operation, control, and decision-making. Missing PMU data may lead to improper actions or even blackouts. While the conventional cubic interpolation methods based on the solution of a set of linear equations to solve for the cubic spline coefficients have been applied by many researchers for interpolation of missing data, the computational complexity increases non-linearly with increasing data size.

    METHODS: In this work, a modified recurrent equation-based cubic spline interpolation procedure for recovering missing PMU data is proposed. The recurrent equation-based method makes the computations of spline constants simpler. Using PMU data from the State Load Despatch Center (SLDC) in Madhya Pradesh, India, a comparison of the root mean square error (RMSE) values and time of calculation (ToC) is calculated for both methods.

    RESULTS: The modified recurrent relation method could retrieve missing values 10 times faster when compared to the conventional cubic interpolation method based on the solution of a set of linear equations. The RMSE values have shown the proposed method is effective even for special cases of missing values (edges, continuous missing values).

    CONCLUSIONS: The proposed method can retrieve any number of missing values at any location using observed data with a minimal number of calculations.

  4. Fulltext In-air Hand Gesture Signature Recognition: An iHGS Database Acquisition Protocol
    Khoh WH, Pang YH, Yap HY
    F1000Res, 2022;11:283.
    PMID: 37600220 DOI: 10.12688/f1000research.74134.2
    Background: With the advances in current technology, hand gesture recognition has gained considerable attention. It has been extended to recognize more distinctive movements, such as a signature, in human-computer interaction (HCI) which enables the computer to identify a person in a non-contact acquisition environment. This application is known as in-air hand gesture signature recognition. To our knowledge, there are no publicly accessible databases and no detailed descriptions of the acquisitional protocol in this domain. Methods: This paper aims to demonstrate the procedure for collecting the in-air hand gesture signature's database. This database is disseminated as a reference database in the relevant field for evaluation purposes. The database is constructed from the signatures of 100 volunteer participants, who contributed their signatures in two different sessions. Each session provided 10 genuine samples enrolled using a Microsoft Kinect sensor camera to generate a genuine dataset. In addition, a forgery dataset was also collected by imitating the genuine samples. For evaluation, each sample was preprocessed with hand localization and predictive hand segmentation algorithms to extract the hand region. Then, several vector-based features were extracted. Results: In this work, classification performance analysis and system robustness analysis were carried out. In the classification analysis, a multiclass Support Vector Machine (SVM) was employed to classify the samples and 97.43% accuracy was achieved; while the system robustness analysis demonstrated low error rates of 2.41% and 5.07% in random forgery and skilled forgery attacks, respectively. Conclusions: These findings indicate that hand gesture signature is not only feasible for human classification, but its properties are also robust against forgery attacks.
  5. Fulltext Playing Edcraft at Home: Gamified Online Learning for Recycling Intention during Lockdown
    Cheng KM, Koo AC, Mohd Nasir JS, Wong SY
    F1000Res, 2021;10:890.
    PMID: 35035889 DOI: 10.12688/f1000research.72761.2
    Background: Gamification is an innovative approach to engaging in activities that people believe as less interesting. Recycling has been an issue not taken aware by the people in environmental sustainability. There are substantial studies on recycling intention due to the continual growth of unethical and unsustainable waste disposal. Creative approaches to recycling awareness activities should be made to fulfil youths' increasing interest in and demand for recycling. The main objective of this study is to explore the factors related to youths' recycling intentions after experiencing a gamified online recycling learning activity, Edcraft Gamified Learning (EGL). Gamified recycling education is believed to be a practical and engaging approach for youths. Methods: 100 students participated in EGL, consisting of two levels of plastic crafting and recycling activities. They experienced online EGL at home between May and September in 2020, during the COVID-19 pandemic total lockdown in Malaysia, namely, Movement Control Order (MCO). 29 participants were selected to participate in five focus group discussions (FGDs) with five to eight participants per session to explore their opinions towards gamified learning, motivation and recycling intention. Results: This paper reports the findings of the FGDs. A codebook was developed based on the codes from the FGD feedback. The codes were rated by two raters, followed by an assessment of inter-rater reliability and thematic analysis. The findings emerged and were confirmed with four themes as factors that influence recycling intention. They are gameful experience, social influence, intrinsic motivation, and extrinsic motivation. Conclusion: The dependent variable, recycling intention, was connected to the four themes to verify the conceptual framework. One limitation of the study was the design of the EGL activity, which was only carried out over two days with two levels of gamified recycling education, as students had concurrent academic online classes during that period.
  6. Fulltext One- and Five-Ringgit Malaysia banknotes reader with counterfeit detection for visually impaired person using backlight mechanism and image processing techniques
    Salem TK, Wong WK, Min TS, Wong EK
    F1000Res, 2021;10:1098.
    PMID: 38618192 DOI: 10.12688/f1000research.58446.2
    Visually impaired persons face challenges in running business activities, especially in handling banknotes. Malaysia researchers had proposed some Ringgit banknotes recognition systems to aid visually impaired persons recognize and classify Ringgit banknotes. However, these electronic banknote readers can only recognize Malaysian Banknotes' Ringgit value, they have no counterfeit detection features. The purpose of this study is to develop a banknote reader that not only can help visually impaired persons recognize the banknote value, but also to detect the counterfeit of the banknote, safeguarding their losses. This paper proposed a Malaysian banknote reader using backlight mechanism and image processing techniques to read and detect counterfeit for one Ringgit and five Ringgit Malaysian banknotes. The developed handheld banknote reader used visual type sensor to capture banknote image, passed to raspberry pi controller to perform image processing on banknote value and the extracted watermarks features. The developed image processing algorithm will trace out the region of interests: 1)see-thru windows, 2)Crescent and Star, 3)Perfect see though register and detect the watermarks features accordingly. The processed result will be passed back to the handheld banknote reader and broadcast on an attached mini speaker to aid the visually impaired understand the holding banknote, whether it is a real one Ringgit, real five Ringgit or none of them. The experimental result shown by this approach able to accomplish numerous round of banknote reading attempts with successful outcomes. Confusion matrix is further employed to study the performance of the banknote reader, in terms of true positive, true negative, false positive and false negative. Details analysis had been focused on the critical false positive cases (predicted real banknote and actually is fake banknote) and false negative cases (predicted fake banknote and it is actually real banknote).
  7. Fulltext Behavioural and emotional issues among primary school pupils with congenital colour vision deficiency in the Federal Territory of Kuala Lumpur, Malaysia: A case-control study
    Thomas BAWM, Kaur S, Hairol MI, Ahmad M, Wee LH
    F1000Res, 2018;7:1834.
    PMID: 30815251 DOI: 10.12688/f1000research.17006.1
    Background: Congenital colour vision deficiency (CCVD) is an untreatable disorder which has lifelong consequences. Increasing use of colours in schools has raised concern for pupils with CCVD. This case-control study was conducted to compare behavioural and emotional issues among age, gender and class-matched pupils with CCVD and normal colour vision (NCV). Methods: A total of 1732 pupils from 10 primary schools in the Federal Territory of Kuala Lumpur were screened, of which 46 pupils (45 males and 1 female) had CCVD. Mothers of male pupils with CCVD (n=44) and NCV (n=44) who gave consent were recruited to complete a self-administered parent report form, Child Behaviour Checklist for Ages 4-18 (CBCL/ 4-18) used to access behavioural and emotional problems. The CBCL/ 4-18 has three broad groupings: Internalising, Externalising and Total Behaviour Problems. Internalising Problems combines the Withdrawn, Somatic Complaints and Anxiety/ Depression sub constructs, while Externalising Problems combines the Delinquent and Aggressive Behaviour sub constructs. Results: Results from CBCL/ 4-18 showed that all pupils from both groups had scores within the normal range for all constructs. However, results from the statistical analysis for comparison, Mann-Whitney U test, showed that pupils with CCVD scored significantly higher for Externalising Problems (U=697.50, p=0.02) and Total Behaviour Problems (U=647.00, p= 0.01). Significantly higher scores were observed in Withdrawn (U=714.00, p=0.02), Thought Problems (U=438.50, p<0.001) and Aggressive Behaviour (U=738.00, p=0.04). Odds ratios, 95% CI, showed significant relative risk for high Total Behaviour Problem (OR:2.39 ,CI:1.0-5.7), Externalising Problems (OR:2.32, CI:1.0-5.5), Withdrawn (OR:2.67, CI:1.1-6.5), Thought Problems (OR:9.64, CI:3.6-26.1) and Aggressive Behaviour (OR:10.26, CI:3.4-31.0) scores among pupils with CCVD. Conclusion: Higher scores among CCVD pupils indicates that they present more behavioural and emotional problems compared to NCV pupils. Therefore, school vision screenings in Malaysia should also include colour vision to assist in the early clinical management of CCVD children.
  8. Fulltext Pancreatic cancer grading in pathological images using deep learning convolutional neural networks
    Mohamad Sehmi MN, Ahmad Fauzi MF, Wan Ahmad WSHM, Wan Ling Chan E
    F1000Res, 2021;10:1057.
    PMID: 37767358 DOI: 10.12688/f1000research.73161.2
    Background: Pancreatic cancer is one of the deadliest forms of cancer. The cancer grades define how aggressively the cancer will spread and give indication for doctors to make proper prognosis and treatment. The current method of pancreatic cancer grading, by means of manual examination of the cancerous tissue following a biopsy, is time consuming and often results in misdiagnosis and thus incorrect treatment. This paper presents an automated grading system for pancreatic cancer from pathology images developed by comparing deep learning models on two different pathological stains. Methods: A transfer-learning technique was adopted by testing the method on 14 different ImageNet pre-trained models. The models were fine-tuned to be trained with our dataset. Results: From the experiment, DenseNet models appeared to be the best at classifying the validation set with up to 95.61% accuracy in grading pancreatic cancer despite the small sample set. Conclusions: To the best of our knowledge, this is the first work in grading pancreatic cancer based on pathology images. Previous works have either focused only on detection (benign or malignant), or on radiology images (computerized tomography [CT], magnetic resonance imaging [MRI] etc.). The proposed system can be very useful to pathologists in facilitating an automated or semi-automated cancer grading system, which can address the problems found in manual grading.
  9. Fulltext Detecting industrial motor faults with current signatures
    Krishnan S, Vengadasalam V
    F1000Res, 2021;10:903.
    PMID: 36398279 DOI: 10.12688/f1000research.54266.1
    Background: A major player in industry is the induction motor. The constant motion and mechanical nature of motors causes much wear and tear, creating a need for frequent maintenance such as changing contact brushes. Unmannered and infrequent monitoring of motors, as is common in the industry, can lead to overexertion and cause major faults. If a motor fault is detected earlier through the use of automated fault monitoring, it could prevent minor faults from developing into major faults, reducing the cost and down-time of production due the motor repairs. There are few available methods to detect three-phase motor faults. One method is to analyze average vibration signals values of V, I, pf, P, Q, S, THD and frequency. Others are to analyze instantaneous signal signatures of V and I frequencies, or V and I trajectory plotting a Lissajous curve. These methods need at least three sensors for current and three for voltage for a three-phase motor detection. Methods: Our proposed method of monitoring faults in three-phase industrial motors uses Hilbert Transform (HT) instantaneous current signature curve only, reducing the number of sensors required. Our system detects fault signatures accurately at any voltage or current levels, whether it is delta or star connected motors. This is due to our system design, which incorporates normalized curves of HT in the fault analysis database. We have conducted this experiment in our campus laboratory for two different three-phase motors with four different fault experiments. Results: The results shown in this paper are a comparison of two methods, the V and I Lissajous trajectory curve and our HT instantaneous current signature curve. Conclusion: We have chosen them as our benchmark as their fault results closely resemble our system results, but our system benefits such as universality and a cost reduction in sensors of 50%.
  10. Fulltext The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies
    Angers-Loustau A, Petrillo M, Bengtsson-Palme J, Berendonk T, Blais B, Chan KG, et al.
    F1000Res, 2018;7.
    PMID: 30026930 DOI: 10.12688/f1000research.14509.2
    Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a "One Health" approach.
  11. Academic entrepreneurial engagement for frugal innovation in higher education institutions: a systematic literature review
    Toyin Ojo O, Dorasamy M, W Migin M, Jayabalan J, R R, Tung SS
    F1000Res, 2021;10:1078.
    PMID: 37593130 DOI: 10.12688/f1000research.73312.2
    Higher education institutions (HEI) are faced with increasing challenges related to shrinking resources, high operation costs, the COVID-19 pandemic, decreasing student enrolment rates, and pressure to contribute to regional development and economic growth. To overcome such challenges, academics must move beyond their traditional functions of research and teaching and engage in entrepreneurial activities. Through engagement in entrepreneurial activities, academics can contribute to frugal innovation (FI) in private HEI (PHEI). The literature in this context emphasizes that academic entrepreneurial engagement (AEE) will lead to innovation, the identification of opportunities for new business ventures, financial rewards for institutions and academics, an impact on the economy, and the enhancement of social welfare. This study presents a systematic review of the literature and adopts the Transfield five-phase strategy to review the literature on AEE from the past two decades (2000-2020). A total of 1,067 papers on FI are obtained, only five of which focus on AEE. Moreover, papers related to AEE for FI are few. The study presents the research gaps, challenges, and potential factors for further research in this context. We conclude that FI for AEE in PHEI can be a game-changer for future sustainability. Moreover, we believe that the outcome of this review warrants further research.
  12. Integrating augmented reality technology in education: vector personal computer augmented reality
    Tan SY, Tay NNW
    F1000Res, 2021;10:987.
    PMID: 37767360 DOI: 10.12688/f1000research.72948.2
    Background: Educators often face difficulties in explaining abstract concepts such as vectors. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, fully online classes have also caused additional challenges to using conventional teaching methods. To explain a vector concept of more than 2 dimensions, visualization becomes a problem. Although Microsoft PowerPoint can integrate animation, the illustration is still in 2-dimensions. Augmented reality (AR) technology is recommended to aid educators and students in teaching-learning vectors, namely via a vector personal computer augmented reality system (VPCAR), to fulfil the demand for tools to support the learning and teaching of vectors. Methods: A PC learning module for vectors was developed in a 3-dimensional coordinate system by using AR technology. Purposive sampling was applied to get feedback from educators and students in Malaysia through an online survey. The supportiveness of using VPCAR based on six items (attractiveness, easiness, visualization, conceptual understanding, inspiration and helpfulness) was recorded on 5-points Likert-type scales. Findings are presented descriptively and graphically. Results: Surprisingly, both students and educators adapted to the new technology easily and provided significant positive feedback that showed a left-skewed and J-shaped distribution for each measurement item, respectively. The distributions were proven significantly different among the students and educators, where supportive level result of educators was higher than students. This study introduced a PC learning module other than mobile apps as students mostly use laptops to attend online class and educators also engage other IT tools in their teaching. Conclusions: Based on these findings, VPCAR provides a good prospect in supporting educators and students during their online teaching-learning process. However, the findings may not be generalizable to all students and educators in Malaysia as purposive sampling was applied. Further studies may focus on government-funded schools using the newly developed VPCAR system, which is the novelty of this study.
  13. Fulltext HR practices and turnover intention; the mediating role of organizational commitment in Tehran: a cross-sectional study
    Hassanpour MK, Chong CW, Chong SC, Ibrahim Okour MK, Behrang S, Tan XY
    F1000Res, 2021;10:1130.
    PMID: 36312528 DOI: 10.12688/f1000research.73351.2
    Background: Employees are increasingly being recognised as a valuable source of information, especially in knowledge-based businesses. Businesses, however, suffer financial and organisational memory losses related to re-hiring and training new staff, and lost productivity and intellectual property because of employee turnover. Hence, employee turnover should be considered an essential part of human resource management. Furthermore, employees' trust in management and human resource (HR) practices substantially impact organisational commitment (OC). Thus, anticipating employee commitment and turnover intentions is crucial, as people are the sole source for knowledge-based firms to maintain their competitive advantage. In the context of selected Tehran Renewable Energy (RE) firms, this study investigated the mediating impact of OC on the relationship between HR practices (recruitment and selection; training and development opportunities; performance appraisal and evaluation; teamwork; compensation and pay; and job security) and employee turnover intention. Methods: This is a cross-sectional study in Tehran that involved 90 experts and knowledgeable employees from four of Tehran's top RE businesses. A questionnaire was distributed to collect data which was later analysed with correlation, regression and bootstrapping analyses. Results: All six dimensions of HR practices were discovered to have an indirect impact on turnover intention and a direct impact on OC. OC among employees has an indirect effect on turnover intention. It was also revealed that the training and development opportunity has the most considerable effect on OC and turnover intention. OC was not found as a mediator between HR practices and turnover intention. Conclusions: The outcomes of this study showed that both training and development opportunities; and pay and compensation structure were found to be two significant components of HR practices in the relationship with OC. RE managers should employ appropriate HR strategies, particularly in these two dimensions, to improve an individual's degree of OC and reduce turnover intention.
  14. Fulltext BioHackathon 2015: Semantics of data for life sciences and reproducible research
    Vos RA, Katayama T, Mishima H, Kawano S, Kawashima S, Kim JD, et al.
    F1000Res, 2020;9:136.
    PMID: 32308977 DOI: 10.12688/f1000research.18236.1
    We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.
  15. Thermal performance of gasifier cooking stoves: A systematic literature review
    Rabby MII, Uddin MW, Sheikh MR, Bhuiyan HK, Mumu TA, Islam F, et al.
    F1000Res, 2023;12:38.
    PMID: 37484517 DOI: 10.12688/f1000research.126890.2
    A systematic literature review was conducted to summarize the overall thermal performance of different gasified cooking stoves from the available literature. For this purpose, available studies from the last 14 years (2008 to 2022) were searched using different search strings. After screening, a total of 28 articles were selected for this literature review. Scopus, Google Scholar, and Web of Science databases were used as search strings by applying "Gasifier cooking stove" AND "producer gas cooking stove" AND "thermal performance" keywords. This review uncovers different gasified cooking stoves, cooking fuels, and fabrication materials besides overall thermal performances. The result shows that the overall thermal performance of different gasified cooking stoves was 5.88% to 91% depending on the design and burning fuels. The premixed producer gas burner with a swirl vane stove provided the highest overall thermal performance range, which was 84% to 91%, and the updraft gasified stove provided the lowest performance, which was 5.88% to 8.79%. The result also demonstrates that the wood pellets cooking fuel provided the highest thermal performance and corn straw briquette fuel provided the lowest for gasified cooking stoves. The overall thermal performance of wood pellets was 38.5% and corn straw briquette was 10.86%.
  16. Fulltext A hybrid recommender system based on data enrichment on the ontology modelling
    Chew LJ, Haw SC, Subramaniam S
    F1000Res, 2021;10:937.
    PMID: 34868563 DOI: 10.12688/f1000research.73060.1
    Background: A recommender system captures the user preferences and behaviour to provide a relevant recommendation to the user. In a hybrid model-based recommender system, it requires a pre-trained data model to generate recommendations for a user. Ontology helps to represent the semantic information and relationships to model the expressivity and linkage among the data. Methods: We enhanced the matrix factorization model accuracy by utilizing ontology to enrich the information of the user-item matrix by integrating the item-based and user-based collaborative filtering techniques. In particular, the combination of enriched data, which consists of semantic similarity together with rating pattern, will help to reduce the cold start problem in the model-based recommender system. When the new user or item first coming into the system, we have the user demographic or item profile that linked to our ontology. Thus, semantic similarity can be calculated during the item-based and user-based collaborating filtering process. The item-based and user-based filtering process are used to predict the unknown rating of the original matrix. Results: Experimental evaluations have been carried out on the MovieLens 100k dataset to demonstrate the accuracy rate of our proposed approach as compared to the baseline method using (i) Singular Value Decomposition (SVD) and (ii) combination of item-based collaborative filtering technique with SVD. Experimental results demonstrated that our proposed method has reduced the data sparsity from 0.9542% to 0.8435%. In addition, it also indicated that our proposed method has achieved better accuracy with Root Mean Square Error (RMSE) of 0.9298, as compared to the baseline method (RMSE: 0.9642) and the existing method (RMSE: 0.9492). Conclusions: Our proposed method enhanced the dataset information by integrating user-based and item-based collaborative filtering techniques. The experiment results shows that our system has reduced the data sparsity and has better accuracy as compared to baseline method and existing method.
  17. Fulltext Improving the support for XML dynamic updates using a hybridization labeling scheme (ORD-GAP)
    Haw SC, Amin A, Wong CO, Subramaniam S
    F1000Res, 2021;10:907.
    PMID: 35106138 DOI: 10.12688/f1000research.69108.1
    Background : As the standard for the exchange of data over the World Wide Web, it is important to ensure that the eXtensible Markup Language (XML) database is capable of supporting not only efficient query processing but also capable of enduring frequent data update operations over the dynamic changes of Web content. Most of the existing XML annotation is based on a labeling scheme to identify each hierarchical position of the XML nodes. This computation is costly as any updates will cause the whole XML tree to be re-labelled. This impact can be observed on large datasets. Therefore, a robust labeling scheme that avoids re-labeling is crucial. Method: Here, we present ORD-GAP (named after Order Gap), a robust and persistent XML labeling scheme that supports dynamic updates. ORD-GAP assigns unique identifiers with gaps in-between XML nodes, which could easily identify the level, Parent-Child (P-C), Ancestor-Descendant (A-D) and sibling relationship. ORD-GAP adopts the OrdPath labeling scheme for any future insertion. Results: We demonstrate that ORD-GAP is robust enough for dynamic updates, and have implemented it in three use cases: (i) left-most, (ii) in-between and (iii) right-most insertion. Experimental evaluations on DBLP dataset demonstrated that ORD-GAP outperformed existing approaches such as ORDPath and ME Labeling concerning database storage size, data loading time and query retrieval. On average, ORD-GAP has the best storing and query retrieval time. Conclusion: The main contributions of this paper are: (i) A robust labeling scheme named ORD-GAP that assigns certain gap between each node to support future insertion, and (ii) An efficient mapping scheme, which built upon ORD-GAP labeling scheme to transform XML into RDB effectively.
  18. Fulltext Improving the data access control using blockchain for healthcare domain
    Tahir Yinka O, Haw SC, Yap TTV, Subramaniam S
    F1000Res, 2021;10:901.
    PMID: 34858590 DOI: 10.12688/f1000research.72890.3
    Introduction: Unauthorized access to data is one of the most significant privacy issues that hinder most industries from adopting big data technologies. Even though specific processes and structures have been put in place to deal with access authorization and identity management for large databases nonetheless, the scalability criteria are far beyond the capabilities of traditional databases. Hence, most researchers are looking into other solutions, such as big data management. Methods: In this paper, we firstly study the strengths and weaknesses of implementing cryptography and blockchain for identity management and authorization control in big data, focusing on the healthcare domain. Subsequently, we propose a decentralized data access and sharing system that preserves privacy to ensure adequate data access management under the blockchain. In addition, we designed a blockchain framework to resolve the decentralized data access and sharing system privacy issues, by implementing a public key infrastructure model, which utilizes a signature cryptography algorithm (elliptic curve and signcryption). Lastly, we compared the proposed blockchain model to previous techniques to see how well it performed. Results: We evaluated the blockchain on four performance metrics which include throughput, latency, scalability, and security. The proposed blockchain model was tested using a sample of 5000 patients and 500,000 observations. The performance evaluation results further showed that the proposed model achieves higher throughput and lower latency compared to existing approaches when the workload varies up to 10,000 transactions. Discussion: This research reviews the importance of blockchains as they provide infinite possibilities to individuals, companies, and governments.
  19. Fulltext Correlation between salivary estrogen levels and oral epithelial cytokeratin 5 expression
    Handajani J, Effendi N, Sosroseno W
    F1000Res, 2020;9:186.
    PMID: 32399205 DOI: 10.12688/f1000research.22536.2
    Background: Estrogen expression levels may be associated with age and may affect keratinization of the hard palate. Keratinized epithelium expresses cytokeratin 5 and 14 in the basal layer. The aim of this study was to determine the correlation between the levels of salivary estrogen and number of cytokeratin 5-positive oral epithelial cells. Methods: A total of 30 female subjects were recruited and divided into children, adults and elderly (N=10 per group). Salivary estrogen levels and cytokeratin 5-expressing oral epithelial cells were assessed using ELISA and immunohistological methods, respectively. Data were analyzed using ANOVA with post hoc LSD test and Pearson's correlation coefficient. Results: The results showed that both the number of cytokeratin 5-positive cells and the level of salivary estrogen were significantly higher in adults but decreased in the elderly, as compared with those in children (p<0.05). Furthermore, the levels of salivary estrogen were significantly correlated with the number of cytokeratin 5-positive cells (r=0.815). The ANOVA result showed significance difference cytokeratin 5 expression and estrogen level (p<0.05). The post hoc LSD test revealed cytokeratin 5 expression and estrogen level to be significantly different in children, adults, and elderly participants (p<0.05). Conclusions: These results suggest that the profile of salivary estrogen and oral epithelial cell-expressed cytokeratin 5 may be positively correlated with age and depend on age.
  20. Fulltext The impact factor of an open access journal does not contribute to an article's citations
    Chua SK, Qureshi AM, Krishnan V, Pai DR, Kamal LB, Gunasegaran S, et al.
    F1000Res, 2017;6:208.
    PMID: 28649365 DOI: 10.12688/f1000research.10892.1
    Background Citations of papers are positively influenced by the journal's impact factor (IF). For non-open access (non-OA) journals, this influence may be due to the fact that high-IF journals are more often purchased by libraries, and are therefore more often available to researchers, than low-IF journals. This positive influence has not, however, been shown specifically for papers published in open access (OA) journals, which are universally accessible, and do not need library purchase. It is therefore important to ascertain if the IF influences citations in OA journals too. Methods 203 randomized controlled trials (102 OA and 101 non-OA) published in January 2011 were included in the study. Five-year citations for papers published in OA journals were compared to those for non-OA journals. Source papers were derived from PubMed. Citations were retrieved from Web of Science, Scopus, and Google Scholar databases. The Thompson-Reuter's IF was used. Results OA journals were found to have significantly more citations overall compared to non-OA journals (median 15.5 vs 12, p=0.039). The IF did not correlate with citations for OA journals (Spearman's rho =0.187, p=0.60). The increase in the citations with increasing IF was minimal for OA journals (beta coefficient = 3.346, 95% CI -0.464, 7.156, p=0.084). In contrast, the IF did show moderate correlation with citations for articles published in non-OA journals (Spearman's rho=0.514, p<0.001). The increase in the number of citations was also significant (beta coefficient = 4.347, 95% CI 2.42, 6.274, p<0.001). Conclusion It is better to publish in an OA journal for more citations. It may not be worth paying high publishing fees for higher IF journals, because there is minimal gain in terms of increased number of citations. On the other hand, if one wishes to publish in a non-OA journal, it is better to choose one with a high IF.
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