Displaying publications 21 - 40 of 162 in total

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  1. Onwude DI, Hashim N, Abdan K, Janius R, Chen G
    J Sci Food Agric, 2018 Mar;98(4):1310-1324.
    PMID: 28758207 DOI: 10.1002/jsfa.8595
    BACKGROUND: Drying is a method used to preserve agricultural crops. During the drying of products with high moisture content, structural changes in shape, volume, area, density and porosity occur. These changes could affect the final quality of dried product and also the effective design of drying equipment. Therefore, this study investigated a novel approach in monitoring and predicting the shrinkage of sweet potato during drying. Drying experiments were conducted at temperatures of 50-70 °C and samples thicknesses of 2-6 mm. The volume and surface area obtained from camera vision, and the perimeter and illuminated area from backscattered optical images were analysed and used to evaluate the shrinkage of sweet potato during drying.

    RESULTS: The relationship between dimensionless moisture content and shrinkage of sweet potato in terms of volume, surface area, perimeter and illuminated area was found to be linearly correlated. The results also demonstrated that the shrinkage of sweet potato based on computer vision and backscattered optical parameters is affected by the product thickness, drying temperature and drying time. A multilayer perceptron (MLP) artificial neural network with input layer containing three cells, two hidden layers (18 neurons), and five cells for output layer, was used to develop a model that can monitor, control and predict the shrinkage parameters and moisture content of sweet potato slices under different drying conditions. The developed ANN model satisfactorily predicted the shrinkage and dimensionless moisture content of sweet potato with correlation coefficient greater than 0.95.

    CONCLUSION: Combined computer vision, laser light backscattering imaging and artificial neural network can be used as a non-destructive, rapid and easily adaptable technique for in-line monitoring, predicting and controlling the shrinkage and moisture changes of food and agricultural crops during drying. © 2017 Society of Chemical Industry.

    Matched MeSH terms: Computers*; Neural Networks (Computer)*
  2. Fornace KM, Surendra H, Abidin TR, Reyes R, Macalinao MLM, Stresman G, et al.
    Int J Health Geogr, 2018 06 18;17(1):21.
    PMID: 29914506 DOI: 10.1186/s12942-018-0141-0
    BACKGROUND: Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information.

    RESULTS: Using Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42-368) in Rizal and 493 m (IQR 258-886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.

    CONCLUSIONS: Results demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.

    Matched MeSH terms: Computers, Handheld*
  3. Liew, Amy Kia Cheen, Hazem Dabbour, Dalia Abdullah
    MyJurnal
    Demonstration of the access cavity preparation procedures to dental students is
    challenging due to the limited operating field and detailed nature of the procedures. It is especially
    difficult to visualize how instruments are functioning inside the pulp space. The aim of this study
    was to develop and compare two different views of video demonstration in teaching access cavity
    preparation. (Copied from article).
    Matched MeSH terms: Computers
  4. Ali S, Ghatwary N, Jha D, Isik-Polat E, Polat G, Yang C, et al.
    Sci Rep, 2024 Jan 23;14(1):2032.
    PMID: 38263232 DOI: 10.1038/s41598-024-52063-x
    Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-dependent procedures and occur in a highly complex organ topology. There exists a high missed detection rate and incomplete removal of colonic polyps. To assist in clinical procedures and reduce missed rates, automated methods for detecting and segmenting polyps using machine learning have been achieved in past years. However, the major drawback in most of these methods is their ability to generalise to out-of-sample unseen datasets from different centres, populations, modalities, and acquisition systems. To test this hypothesis rigorously, we, together with expert gastroenterologists, curated a multi-centre and multi-population dataset acquired from six different colonoscopy systems and challenged the computational expert teams to develop robust automated detection and segmentation methods in a crowd-sourcing Endoscopic computer vision challenge. This work put forward rigorous generalisability tests and assesses the usability of devised deep learning methods in dynamic and actual clinical colonoscopy procedures. We analyse the results of four top performing teams for the detection task and five top performing teams for the segmentation task. Our analyses demonstrate that the top-ranking teams concentrated mainly on accuracy over the real-time performance required for clinical applicability. We further dissect the devised methods and provide an experiment-based hypothesis that reveals the need for improved generalisability to tackle diversity present in multi-centre datasets and routine clinical procedures.
    Matched MeSH terms: Computers
  5. Al-Quraishi MS, Elamvazuthi I, Tang TB, Al-Qurishi M, Adil SH, Ebrahim M
    Brain Sci, 2021 May 27;11(6).
    PMID: 34071982 DOI: 10.3390/brainsci11060713
    Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have temporal and spatial characteristics that may complement each other and, therefore, pose an intriguing approach for brain-computer interaction (BCI). In this work, the relationship between the hemodynamic response and brain oscillation activity was investigated using the concurrent recording of fNIRS and EEG during ankle joint movements. Twenty subjects participated in this experiment. The EEG was recorded using 20 electrodes and hemodynamic responses were recorded using 32 optodes positioned over the motor cortex areas. The event-related desynchronization (ERD) feature was extracted from the EEG signal in the alpha band (8-11) Hz, and the concentration change of the oxy-hemoglobin (oxyHb) was evaluated from the hemodynamics response. During the motor execution of the ankle joint movements, a decrease in the alpha (8-11) Hz amplitude (desynchronization) was found to be correlated with an increase of the oxyHb (r = -0.64061, p < 0.00001) observed on the Cz electrode and the average of the fNIRS channels (ch28, ch25, ch32, ch35) close to the foot area representation. Then, the correlated channels in both modalities were used for ankle joint movement classification. The result demonstrates that the integrated modality based on the correlated channels provides a substantial enhancement in ankle joint classification accuracy of 93.01 ± 5.60% (p < 0.01) compared with single modality. These results highlight the potential of the bimodal fNIR-EEG approach for the development of future BCI for lower limb rehabilitation.
    Matched MeSH terms: Computers
  6. Syed NK, Syed MH, Meraya AM, Albarraq AA, Al-Kasim MA, Alqahtani S, et al.
    PLoS One, 2020;15(9):e0238458.
    PMID: 32911507 DOI: 10.1371/journal.pone.0238458
    BACKGROUND: Western dietary habits, coupled with a sedentary lifestyle, are potential contributors to the prevalence and rapid increase in the incidence of obesity in Saudi Arabia. This study aimed to investigate the association between students' weight status and their eating behaviors and practices. Another aim was to assess students' awareness of the health risks associated with obesity.

    METHODS: A cross-sectional survey was conducted among a sample of 416 (53% male and 47% female) undergraduate students, aged 18-26 years old, between January 6 and April 6, 2019, from colleges of Health Sciences at Jazan University in the Kingdom of Saudi Arabia (K.S.A). Students completed a self-administered questionnaire and recorded their measured anthropometric parameters.

    RESULTS: The prevalence of overweight (20.4%) and obesity (14.9%) were relatively high among the participants. There were statistically significant associations between Body Mass Index (BMI) and the different settings of food consumption (i.e., dining on a table (or) in the Islamic way: squatting on the ground) (p<0.001)). BMI was also associated with students' dietary habits regarding consuming food, snacks, and drinking carbonated beverages while watching television (p<0.001), as well as consuming the same pattern of food/drink while watching television, playing video games on mobile phones or computers (p<0.001). Nearly most of the students were oblivious to the fact that metabolic syndrome, reproductive disorders, respiratory disorders along with liver and gallbladder diseases are some of the health risks associated with obesity.

    CONCLUSION: The prevalence of obesity and overweight were reasonably high in our study sample and were affected by several factors related to students' eating behaviors and practices. This warrants the need for rigorous and frequent health education interventions on healthy eating behaviors, dietary practices, with an emphasis on the importance of adopting an active, healthy lifestyle.

    Matched MeSH terms: Computers
  7. Aznan A, Gonzalez Viejo C, Pang A, Fuentes S
    Sensors (Basel), 2021 Sep 23;21(19).
    PMID: 34640673 DOI: 10.3390/s21196354
    Rice quality assessment is essential for meeting high-quality standards and consumer demands. However, challenges remain in developing cost-effective and rapid techniques to assess commercial rice grain quality traits. This paper presents the application of computer vision (CV) and machine learning (ML) to classify commercial rice samples based on dimensionless morphometric parameters and color parameters extracted using CV algorithms from digital images obtained from a smartphone camera. The artificial neural network (ANN) model was developed using nine morpho-colorimetric parameters to classify rice samples into 15 commercial rice types. Furthermore, the ANN models were deployed and evaluated on a different imaging system to simulate their practical applications under different conditions. Results showed that the best classification accuracy was obtained using the Bayesian Regularization (BR) algorithm of the ANN with ten hidden neurons at 91.6% (MSE = <0.01) and 88.5% (MSE = 0.01) for the training and testing stages, respectively, with an overall accuracy of 90.7% (Model 2). Deployment also showed high accuracy (93.9%) in the classification of the rice samples. The adoption by the industry of rapid, reliable, and accurate methods, such as those presented here, may allow the incorporation of different morpho-colorimetric traits in rice with consumer perception studies.
    Matched MeSH terms: Computers
  8. Othman A, Umar R, Gopir G
    In the past, simulating charge dynamics in solid state devices, such as current mobility, transient current drift velocities are done on mainframe systems or on high performance computing facilities. This is due to the fact that, such simulations are costly in terms of computational requirements when implemented on a single processor-based personal computers (PCs). When simulating charge dynamics, large ensembles of particles are usually preferred, such as exceeding 40000 particles, to ensure a numerically sound result. When implementing this type of simulation on a single processor PCs using the conventional ensemble or single particle Monte Carlo method, the computational time is very long even on the fast 2.0 MHz PCs. Lately, a more efficient, easily made available tools and cost effective solution to this problem is the application of an array of PCs employed in a parallel application. This is done using a computer cluster network in a master-slave model. In this paper we report the development of a LINUX cluster for the purpose of implementing parallel ensemble Monte Carlo modelling for solid states device. We have proposed the use of Parallel Virtual Machine (PVM) standards when running the parallel algorithm of the ensemble MC simulation. Some results of the development are also presented in this paper.
    Matched MeSH terms: Computers; Microcomputers
  9. Ahmad Fauzi MF, Khansa I, Catignani K, Gordillo G, Sen CK, Gurcan MN
    Comput Biol Med, 2015 May;60:74-85.
    PMID: 25756704 DOI: 10.1016/j.compbiomed.2015.02.015
    An estimated 6.5 million patients in the United States are affected by chronic wounds, with more than US$25 billion and countless hours spent annually for all aspects of chronic wound care. There is a need for an intelligent software tool to analyze wound images, characterize wound tissue composition, measure wound size, and monitor changes in wound in between visits. Performed manually, this process is very time-consuming and subject to intra- and inter-reader variability. In this work, our objective is to develop methods to segment, measure and characterize clinically presented chronic wounds from photographic images. The first step of our method is to generate a Red-Yellow-Black-White (RYKW) probability map, which then guides the segmentation process using either optimal thresholding or region growing. The red, yellow and black probability maps are designed to handle the granulation, slough and eschar tissues, respectively; while the white probability map is to detect the white label card for measurement calibration purposes. The innovative aspects of this work include defining a four-dimensional probability map specific to wound characteristics, a computationally efficient method to segment wound images utilizing the probability map, and auto-calibration of wound measurements using the content of the image. These methods were applied to 80 wound images, captured in a clinical setting at the Ohio State University Comprehensive Wound Center, with the ground truth independently generated by the consensus of at least two clinicians. While the mean inter-reader agreement between the readers varied between 67.4% and 84.3%, the computer achieved an average accuracy of 75.1%.
    Matched MeSH terms: Computers
  10. Hari Krishnan, T.
    MyJurnal
    Introductions: Call center has been defined as a working environment in which uses telephone and computer for the purpose of marketing and manage communication with prospect clients or existing clients (Rocha, Glina, Morinho and Nakasato, 2005; Sprigg, Smith and Jackson, 2003).
    Methodology: The study was conducted via observation of working condition and face to face interview with call center operators. Measurement of anthropometrics was also conducted.
    Results: Ergonomics issues found at call center were inappropriate work condition and workstation which lead to awkward sitting posture (sitting with forward leaning posture, raised shoulder, feet not supported on floor). Besides that organizational policy which required high job demand and subsequently lead to prolonged sitting and static posture (very minimal posture changes). Combination all these factors lead to musculoskeletal symptoms and the operators reported of having neck, shoulder, upper back and lower back pain compared to other body parts.
    Conclusion: The management should embark on organization wide ergonomics management program and should review the current policy and create safe and healthy working environment by providing suitable workstation for the operators in order to prevent musculoskeletal.
    Matched MeSH terms: Computers
  11. Ismail A, Ahmad SA, Che Soh A, Hassan MK, Harith HH
    Data Brief, 2020 Oct;32:106268.
    PMID: 32984464 DOI: 10.1016/j.dib.2020.106268
    A fully labelled image dataset serves as a valuable tool for reproducible research inquiries and data processing in various computational areas, such as machine learning, computer vision, artificial intelligence and deep learning. Today's research on ageing is intended to increase awareness on research results and their applications to assist public and private sectors in selecting the right equipments for the elderlies. Many researches related to development of support devices and care equipment had been done to improve the elderly's quality of life. Indoor object detection and classification for autonomous systems require large annotated indoor images for training and testing of smart computer vision applications. This dataset entitled MYNursingHome is an image dataset for commonly used objects surrounding the elderlies in their home cares. Researchers may use this data to build up a recognition aid for the elderlies. This dataset was collected from several nursing homes in Malaysia comprises 37,500 digital images from 25 different indoor object categories including basket bin, bed, bench, cabinet and others.
    Matched MeSH terms: Computers
  12. Alwi, M.N.M., Roslaili, R., Noraniza Hayati, M.N., Harris, A.W.F.
    MyJurnal
    The aim of the study was to acquire background information on computer literacy among schizophrenia patients in Kota Bharu, Malaysia, prior to the introduction of a computerised cognitive remediation programme in the local setting.
    Method: Fifty consenting consecutive patients with schizophrenia attending the Universiti Sains Malaysia Hospital psychiatric clinic were surveyed using the Computer Literacy Scale (CLS), a scale designed to specifically look at their level of computer knowledge, confidence and attitude towards computers.
    Results: The majority of the patients studied have had schizophrenia for 5 years or less. While the majority of them have used computers befoie, about half had a poor level of knowledge, although they showed reasonable confidence and a positive attitude towards computers. Few played computer games.
    Conclusions: Implementation of a computerised cognitive remediation programme in the Malaysian setting has a promising potential based on the results of this study but the programme needs to be adapted in light of the negative attitudes towards the use of games.
    Study site: Psychiatric clinc, Hospital Universiti Sains Malaysia (HUSM), Kelantan, Malaysia
    Matched MeSH terms: Computers
  13. Purnamasari P, Amran NA, Hartanto R
    F1000Res, 2022;11:559.
    PMID: 36474997 DOI: 10.12688/f1000research.121674.2
    Background: This study aims to examine public sector auditors' tendency to use somputer assisted audit techniques (CAATs) in managing their audit works. Methods: A total of 400 questionnaires were distributed to auditors working in the public sectors in Central Java, West Java, and East Java. From the total, 225 questionnaires were returned and completed.  The Structural Equation Modelling (SEM) and Partial Least Square (PLS) were used to analyze the data. Results: The empirical findings reveal that performance expectation and facilitating conditions have encouraged auditors to use CAATs in their works. Further, there is a positive influence between the intention to use and CAATs audit. This implies that auditors with an intention will be more open to using the CAATs optimally in achieving effective and efficient work. The utilization of CAATs in public services needs to have strong support from the government and positive attitudes from the auditors as the users of the system. Conclusion: This study covers broad areas of Central Java, West Java, and East Java. Further, the findings add to the literature on emerging markets specifically for Indonesian government auditors' intention and appropriateness of using CAATs. The use of CAATs help to provide auditors information on the highest number of auditees involved in corruption.
    Matched MeSH terms: Computers
  14. Zaili MA, Kuppuswamy R, Harun H
    Forensic Sci Int, 2007 Aug 24;171(1):27-32.
    PMID: 17088038
    It is known that restoration of erased engraved identification marks on the engine and the chassis of a car or on a firearm has low success rate. Unlike stamping, engraving on a metal surface leaves no pronounced, permanent subsurface deformation in the crystalline structure, also called dislocation that can be revealed by suitable methods. Hence, the current research work investigated whether metallographic reagents used in the restoration of stamp (compression) marks could be applied to recover engraved marks on steel surfaces and also to establish the sensitivity and effectiveness of some of these reagents for the restoration of the marks. Experiments were conducted by mechanically engraving alphanumeric characters on several steel plates using a computer controlled engraving machine called Gravograph. The markings were later erased from the above steel plates by removing the metal in stages of 0.01 mm through 0.04 mm below the bottom of the engraving. Several plates were thus prepared wherein each one had been abraded to a specific depth. Then eight metallographic reagents were tested on each one of the above erased plates using a swabbing technique. The results had shown that while most of the reagents were able to restore marks up to certain levels of erasure, the reagent 5 g copper sulphate, 60 ml water, 30 ml concentrated ammonium hydroxide and 60 ml concentrated hydrochloric acid restored marks erased to a depth of 0.04 mm below the engraving depth, thus presenting itself the most sensitive reagent. Quite significantly, the above reagent was also able to decipher successfully the original engraved marks that had been erased and engraved with a new number, or obliterated by centre punching. The results of this research work should benefit the forensic practitioners engaged in the serial number recovery on vehicles, firearms and other objects.
    Matched MeSH terms: Computers
  15. Salahuddin L, Ismail Z, Abd Ghani MK, Mohd Aboobaider B, Hasan Basari AS
    J Eval Clin Pract, 2020 Oct;26(5):1416-1424.
    PMID: 31863517 DOI: 10.1111/jep.13326
    OBJECTIVES: The objective of this study was to identify the factors influencing workarounds to the Hospital Information System (HIS) in Malaysian government hospitals.

    METHODS: Semi-structured interviews were conducted among 31 medical doctors in three Malaysian government hospitals on the implementation of the Total Hospital Information System (THIS) between March and May 2015. A thematic qualitative analysis was performed on the resultant data to deduce the relevant themes.

    RESULTS: Five themes emerged as the factors influencing workarounds to the HIS: (a) typing skills, (b) system usability, (c) computer resources, (d) workload, and (e) time.

    CONCLUSIONS: This study provided the key factors as to why doctors were involved in workarounds during the implementation of the HIS. It is important to understand these factors in order to help mitigate work practices that can pose a threat to patient safety.

    Matched MeSH terms: Computers
  16. May Z, Alam MK, Husain K, Hasan MK
    PLoS One, 2020;15(8):e0238073.
    PMID: 32845901 DOI: 10.1371/journal.pone.0238073
    Transmission opportunity (TXOP) is a key factor to enable efficient channel bandwidth utilization over wireless campus networks (WCN) for interactive multimedia (IMM) applications. It facilitates in resource allocation for the similar categories of multiple packets transmission until the allocated time is expired. The static TXOP limits are defined for various categories of IMM traffics in the IEEE802.11e standard. Due to the variation of traffic load in WCN, the static TXOP limits are not sufficient enough to guarantee the quality of service (QoS) for IMM traffic flows. In order to address this issue, several existing works allocate the TXOP limits dynamically to ensure QoS for IMM traffics based on the current associated queue size and pre-setting threshold values. However, existing works do not take into account all the medium access control (MAC) overheads while estimating the current queue size which in turn is required for dynamic TXOP limits allocation. Hence, not considering MAC overhead appropriately results in inaccurate queue size estimation, thereby leading to inappropriate allocation of dynamic TXOP limits. In this article, an enhanced dynamic TXOP (EDTXOP) scheme is proposed that takes into account all the MAC overheads while estimating current queue size, thereby allocating appropriate dynamic TXOP limits within the pre-setting threshold values. In addition, the article presents an analytical estimation of the EDTXOP scheme to compute the dynamic TXOP limits for the current high priority traffic queues. Simulation results were carried out by varying traffic load in terms of packet size and packet arrival rate. The results show that the proposed EDTXOP scheme achieves the overall performance gains in the range of 4.41%-8.16%, 8.72%-11.15%, 14.43%-32% and 26.21%-50.85% for throughput, PDR, average ETE delay and average jitter, respectively when compared to the existing work. Hence, offering a better TXOP limit allocation solution than the rest.
    Matched MeSH terms: Computers
  17. Mahmud N, Kenny DT, Md Zein R, Hassan SN
    Malays J Med Sci, 2011 Apr;18(2):16-26.
    PMID: 22135582 MyJurnal
    Musculoskeletal disorders are commonly reported among computer users. This study explored whether these disorders can be reduced by the provision of ergonomics education.
    Matched MeSH terms: Computers
  18. Schwartz TM, Hillis SL, Sridharan R, Lukyanchenko O, Geiser W, Whitman GJ, et al.
    J Med Imaging (Bellingham), 2020 Mar;7(2):022408.
    PMID: 32042859 DOI: 10.1117/1.JMI.7.2.022408
    Purpose: Computer-aided detection (CAD) alerts radiologists to findings potentially associated with breast cancer but is notorious for creating false-positive marks. Although a previous paper found that radiologists took more time to interpret mammograms with more CAD marks, our impression was that this was not true in actual interpretation. We hypothesized that radiologists would selectively disregard these marks when present in larger numbers. Approach: We performed a retrospective review of bilateral digital screening mammograms. We use a mixed linear regression model to assess the relationship between number of CAD marks and ln (interpretation time) after adjustment for covariates. Both readers and mammograms were treated as random sampling units. Results: Ten radiologists, with median experience after residency of 12.5 years (range 6 to 24) interpreted 1832 mammograms. After accounting for number of images, Breast Imaging Reporting and Data System category, and breast density, the number of CAD marks was positively associated with longer interpretation time, with each additional CAD mark proportionally increasing median interpretation time by 4.35% for a typical reader. Conclusions: We found no support for our hypothesis that radiologists will selectively disregard CAD marks when they are present in larger numbers.
    Matched MeSH terms: Computers
  19. Hearn RL
    Asian Pac Cens Forum, 1985 May;11(4):1-4, 9-14, 16.
    PMID: 12267276
    Matched MeSH terms: Computers*
  20. Dugdale AE, Chen ST, Hewitt G
    Am J Clin Nutr, 1970 Oct;23(10):1280-7.
    PMID: 5475659
    Matched MeSH terms: Computers
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