Displaying publications 41 - 60 of 162 in total

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  1. Enhancing the three-dimensional visualization of a foreign object using Mimics software
    Asif MK, Nambiar P, Khan IM, Aziz ZABCA, Noor NSBM, Shanmuhasuntharam P, et al.
    Radiol Case Rep, 2019 Dec;14(12):1545-1549.
    PMID: 31719943 DOI: 10.1016/j.radcr.2019.10.001
    A patient was referred to the Oral and Maxillofacial Imaging Division and the attending dental specialist suspected a foreign object at the anterior region of the maxilla. The region was scanned using Kodak 9000 3D cone-beam computed tomography (CBCT) extraoral imaging system (Carestream Health, Inc.) to determine the type and morphometric characteristic of foreign object. The CBCT images failed to determine the identity and nature of the foreign object. CBCT images were then exported to the Materialise Interactive Medical Image Control System (Mimics) software to evaluate whether this software can help in enhancing the visualization of the foreign object in the maxillofacial region. The findings showed that there was an improved visualization of the foreign body and the type of the object could be determined with certainty. The object was identified as an endodontic file and was clearly visible when visualized as a reconstructed 3D model in Mimics software. Although the identification of abnormalities has been dramatically improved using 3D scans, the visualization can be further enhanced using image processing software like Mimics.
    Matched MeSH terms: Computers
  2. Fulltext Surface Thermo-Dynamic Characterization of Poly (Vinylidene Chloride-Co-Acrylonitrile) (P(VDC-co-AN)) Using Inverse-Gas Chromatography and Investigation of Visual Traits Using Computer Vision Image Processing Algorithms
    Kakani V, Kim H, Basivi PK, Pasupuleti VR
    Polymers (Basel), 2020 Jul 23;12(8).
    PMID: 32717780 DOI: 10.3390/polym12081631
    The Inverse Gas Chromatography (IGC) technique has been employed for the surface thermo-dynamic characterization of the polymer Poly(vinylidene chloride-co-acrylonitrile) (P(VDC-co-AN)) in its pure form. IGC attributes, such as London dispersive surface energy, Gibbs free energy, and Guttman Lewis acid-base parameters were analyzed for the polymer (P(VDC-co-AN)). The London dispersive surface free energy ( γ S L ) was calculated using the Schultz and Dorris-Gray method. The maximum surface energy value of (P(VDC-co-AN )) is found to be 29.93 mJ·m - 2 and 24.15 mJ·m - 2 in both methods respectively. In our analysis, it is observed that the γ S L values decline linearly with an increase in temperature. The Guttman-Lewis acid-base parameter K a , K b values were estimated to be 0.13 and 0.49. Additionally, the surface character S value and the correlation coefficient were estimated to be 3.77 and 0.98 respectively. After the thermo-dynamic surface characterization, the (P(VDC-co-AN)) polymer overall surface character is found to be basic. The substantial results revealed that the (P(VDC-co-AN)) polymer surface contains more basic sites than acidic sites and, hence, can closely associate in acidic media. Additionally, visual traits of the polymer (P(VDC-co-AN)) were investigated by employing Computer Vision and Image Processing (CVIP) techniques on Scanning Electron Microscopy (SEM) images captured at resolutions ×50, ×200 and ×500. Several visual traits, such as intricate patterns, surface morphology, texture/roughness, particle area distribution ( D A ), directionality ( D P ), mean average particle area ( μ a v g ) and mean average particle standard deviation ( σ a v g ), were investigated on the polymer's purest form. This collective study facilitates the researches to explore the pure form of the polymer Poly(vinylidene chloride-co-acrylonitrile) (P(VDC-co-AN )) in both chemical and visual perspective.
    Matched MeSH terms: Computers
  3. Fulltext SMARTbot: A Behavioral Analysis Framework Augmented with Machine Learning to Identify Mobile Botnet Applications
    Karim A, Salleh R, Khan MK
    PLoS One, 2016;11(3):e0150077.
    PMID: 26978523 DOI: 10.1371/journal.pone.0150077
    Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.
    Matched MeSH terms: Computers; Microcomputers
  4. Fulltext Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm
    Al-Saffar A, Awang S, Tao H, Omar N, Al-Saiagh W, Al-Bared M
    PLoS One, 2018;13(4):e0194852.
    PMID: 29684036 DOI: 10.1371/journal.pone.0194852
    Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with the help of more than one Malay native speaker, and the polarity is manually allotted with a score. In addition, the supervised machine learning approaches and lexicon knowledge method are combined for Malay sentiment classification with evaluating thirteen features. Finally, three individual classifiers and a combined classifier are used to evaluate the classification accuracy. In experimental results, a wide-range of comparative experiments is conducted on a Malay Reviews Corpus (MRC), and it demonstrates that the feature extraction improves the performance of Malay sentiment analysis based on the combined classification. However, the results depend on three factors, the features, the number of features and the classification approach.
    Matched MeSH terms: Attitude to Computers
  5. Fulltext The association of dietary behaviors and practices with overweight and obesity parameters among Saudi university students
    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
  6. Fulltext An enhanced dynamic transmission opportunity scheme to support varying traffic load over wireless campus networks
    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
  7. Fulltext Technique for Early Reliability Prediction of Software Components Using Behaviour Models
    Ali A, N A Jawawi D, Adham Isa M, Imran Babar M
    PLoS One, 2016 Sep 26;11(9):e0163346.
    PMID: 27668748 DOI: 10.1371/journal.pone.0163346
    Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For example, most of the current reliability techniques do not provide fine-grained sequential behaviour models of individual components and fail to consider the loop entry and exit points in the reliability computation. Moreover, some of the current techniques do not tackle the problem of operational data unavailability and the lack of analysis results that can be valuable for software architects at the early design stage. This paper proposes a reliability prediction technique that, pragmatically, synthesizes system behaviour in the form of a state machine, given a set of scenarios and corresponding constraints as input. The state machine is utilized as a base for generating the component-relevant operational data. The state machine is also used as a source for identifying the nodes and edges of a component probabilistic dependency graph (CPDG). Based on the CPDG, a stack-based algorithm is used to compute the reliability. The proposed technique is evaluated by a comparison with existing techniques and the application of sensitivity analysis to a robotic wheelchair system as a case study. The results indicate that the proposed technique is more relevant at the early design stage compared to existing works, and can provide a more realistic and meaningful prediction.
    Matched MeSH terms: Computers
  8. Fulltext Comparison of computer-key-hold-time and alternating-finger-tapping tests for early-stage Parkinson's disease
    Lan BL, Yeo JHW
    PLoS One, 2019;14(6):e0219114.
    PMID: 31247037 DOI: 10.1371/journal.pone.0219114
    Giancardo et al. recently introduced the neuroQWERTY index (nQi), which is a novel motor index derived from computer-key-hold-time data using an ensemble regression algorithm, to detect early-stage Parkinson's disease. Here, we derive a much simpler motor index from their hold-time data, which is the standard deviation (SD) of the hold-time fluctuations, where fluctuation is defined as the difference between successive natural-log of hold time. Our results show the performance of the SD and nQi tests in discriminating early-stage subjects from controls do not differ, although the SD index is much simpler. There is also no difference in performance between the SD and alternating-finger-tapping tests.
    Matched MeSH terms: Computers
  9. Fulltext DC-based smart PV-powered home energy management system based on voltage matching and RF module
    Sabry AH, Hasan WZW, Ab Kadir M, Radzi MAM, Shafie S
    PLoS One, 2017;12(9):e0185012.
    PMID: 28934271 DOI: 10.1371/journal.pone.0185012
    The main tool for measuring system efficiency in homes and offices is the energy monitoring of the household appliances' consumption. With the help of GUI through a PC or smart phone, there are various applications that can be developed for energy saving. This work describes the design and prototype implementation of a wireless PV-powered home energy management system under a DC-distribution environment, which allows remote monitoring of appliances' energy consumptions and power rate quality. The system can be managed by a central computer, which obtains the energy data based on XBee RF modules that access the sensor measurements of system components. The proposed integrated prototype framework is characterized by low power consumption due to the lack of components and consists of three layers: XBee-based circuit for processing and communication architecture, solar charge controller, and solar-battery-load matching layers. Six precise analogue channels for data monitoring are considered to cover the energy measurements. Voltage, current and temperature analogue signals were accessed directly from the remote XBee node to be sent in real time with a sampling frequency of 11-123 Hz to capture the possible surge power. The performance shows that the developed prototype proves the DC voltage matching concept and is able to provide accurate and precise results.
    Matched MeSH terms: Computers
  10. Fulltext A functional pipeline framework for landmark identification on 3D surface extracted from volumetric data
    Zheng P, Belaton B, Liao IY, Rajion ZA
    PLoS One, 2017;12(11):e0187558.
    PMID: 29121077 DOI: 10.1371/journal.pone.0187558
    Landmarks, also known as feature points, are one of the important geometry primitives that describe the predominant characteristics of a surface. In this study we proposed a self-contained framework to generate landmarks on surfaces extracted from volumetric data. The framework is designed to be a three-fold pipeline structure. The pipeline comprises three phases which are surface construction, crest line extraction and landmark identification. With input as a volumetric data and output as landmarks, the pipeline takes in 3D raw data and produces a 0D geometry feature. In each phase we investigate existing methods, extend and tailor the methods to fit the pipeline design. The pipeline is designed to be functional as it is modularised to have a dedicated function in each phase. We extended the implicit surface polygonizer for surface construction in first phase, developed an alternative way to compute the gradient of maximal curvature for crest line extraction in second phase and finally we combine curvature information and K-means clustering method to identify the landmarks in the third phase. The implementations are firstly carried on a controlled environment, i.e. synthetic data, for proof of concept. Then the method is tested on a small scale data set and subsequently on huge data set. Issues and justifications are addressed accordingly for each phase.
    Matched MeSH terms: Computers
  11. Fulltext The communication of artificial intelligence and deep learning in computer tomography image recognition of epidemic pulmonary infectious diseases
    Wang W, Zhao X, Jia Y, Xu J
    PLoS One, 2024;19(2):e0297578.
    PMID: 38319912 DOI: 10.1371/journal.pone.0297578
    The objectives are to improve the diagnostic efficiency and accuracy of epidemic pulmonary infectious diseases and to study the application of artificial intelligence (AI) in pulmonary infectious disease diagnosis and public health management. The computer tomography (CT) images of 200 patients with pulmonary infectious disease are collected and input into the AI-assisted diagnosis software based on the deep learning (DL) model, "UAI, pulmonary infectious disease intelligent auxiliary analysis system", for lesion detection. By analyzing the principles of convolutional neural networks (CNN) in deep learning (DL), the study selects the AlexNet model for the recognition and classification of pulmonary infection CT images. The software automatically detects the pneumonia lesions, marks them in batches, and calculates the lesion volume. The result shows that the CT manifestations of the patients are mainly involved in multiple lobes and density, the most common shadow is the ground-glass opacity. The detection rate of the manual method is 95.30%, the misdetection rate is 0.20% and missed diagnosis rate is 4.50%; the detection rate of the DL-based AI-assisted lesion method is 99.76%, the misdetection rate is 0.08%, and the missed diagnosis rate is 0.08%. Therefore, the proposed model can effectively identify pulmonary infectious disease lesions and provide relevant data information to objectively diagnose pulmonary infectious disease and manage public health.
    Matched MeSH terms: Computers
  12. Fulltext Observing Consistency in Online Communication Patterns for User Re-Identification
    Adeyemi IR, Razak SA, Salleh M, Venter HS
    PLoS One, 2016;11(12):e0166930.
    PMID: 27918593 DOI: 10.1371/journal.pone.0166930
    Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.
    Matched MeSH terms: Computers
  13. Fulltext Critical Factors Influencing Decision to Adopt Human Resource Information System (HRIS) in Hospitals
    Alam MG, Masum AK, Beh LS, Hong CS
    PLoS One, 2016;11(8):e0160366.
    PMID: 27494334 DOI: 10.1371/journal.pone.0160366
    The aim of this research is to explore factors influencing the management decisions to adopt human resource information system (HRIS) in the hospital industry of Bangladesh-an emerging developing country. To understand this issue, this paper integrates two prominent adoption theories-Human-Organization-Technology fit (HOT-fit) model and Technology-Organization-Environment (TOE) framework. Thirteen factors under four dimensions were investigated to explore their influence on HRIS adoption decisions in hospitals. Employing non-probability sampling method, a total of 550 copies of structured questionnaires were distributed among HR executives of 92 private hospitals in Bangladesh. Among the respondents, usable questionnaires were 383 that suggesting a valid response rate of 69.63%. We classify the sample into 3 core groups based on the HRIS initial implementation, namely adopters, prospectors, and laggards. The obtained results specify 5 most critical factors i.e. IT infrastructure, top management support, IT capabilities of staff, perceived cost, and competitive pressure. Moreover, the most significant dimension is technological dimension followed by organisational, human, and environmental among the proposed 4 dimensions. Lastly, the study found existence of significant differences in all factors across different adopting groups. The study results also expose constructive proposals to researchers, hospitals, and the government to enhance the likelihood of adopting HRIS. The present study has important implications in understanding HRIS implementation in developing countries.
    Matched MeSH terms: Attitude to Computers
  14. Fulltext Word learning from a tablet app: Toddlers perform better in a passive context
    Ackermann L, Lo CH, Mani N, Mayor J
    PLoS One, 2020;15(12):e0240519.
    PMID: 33259476 DOI: 10.1371/journal.pone.0240519
    In recent years, the popularity of tablets has skyrocketed and there has been an explosive growth in apps designed for children. Howhever, many of these apps are released without tests for their effectiveness. This is worrying given that the factors influencing children's learning from touchscreen devices need to be examined in detail. In particular, it has been suggested that children learn less from passive video viewing relative to equivalent live interaction, which would have implications for learning from such digital tools. However, this so-called video deficit may be reduced by allowing children greater influence over their learning environment. Across two touchscreen-based experiments, we examined whether 2- to 4-year-olds benefit from actively choosing what to learn more about in a digital word learning task. We designed a tablet study in which "active" participants were allowed to choose which objects they were taught the label of, while yoked "passive" participants were presented with the objects chosen by their active peers. We then examined recognition of the learned associations across different tasks. In Experiment 1, children in the passive condition outperformed those in the active condition (n = 130). While Experiment 2 replicated these findings in a new group of Malay-speaking children (n = 32), there were no differences in children's learning or recognition of the novel word-object associations using a more implicit looking time measure. These results suggest that there may be performance costs associated with active tasks designed as in the current study, and at the very least, there may not always be systematic benefits associated with active learning in touchscreen-based word learning tasks. The current studies add to the evidence that educational apps need to be evaluated before release: While children might benefit from interactive apps under certain conditions, task design and requirements need to consider factors that may detract from successful performance.
    Matched MeSH terms: Computers, Handheld
  15. Fulltext Software development for real-time weed colour analysis
    Wan Ishak, W.I., Khairuddin Abdul Rahman
    Pertanika Journal of Science & Technology, 2010;18(2):-.
    MyJurnal
    The application of computer and machines for agricultural production has been one of the outstanding
    developments in Malaysian agriculture, especially in overcoming labour shortages in Oil Palm plantations. The on-line automated weedicide sprayer system was developed at Universiti Putra
    Malaysia to locate the existence and intensity of weeds in real-time environment and to spray the
    weedicides automatically and precisely. During the start of the spraying operation, the web camera
    will initially capture the image of weeds. The computer programme will compute the red, green, blue (RGB) values in the form of computer pixel. These values will be used as reference RGB values to be compared with the RGB values of the weeds captured real-time during the spraying operation. The sprayer nozzle will be turned ‘on’ or ‘off’, depending on the percentage or intensity of the green colour pixel value of weeds. The sprayer valve will open the nozzle/s when the camera detected the presence of weeds. The purpose is to reduce wastage, reduce labour, reduce cost, and control environment hazard.
    Matched MeSH terms: Computers
  16. Fulltext Rootkit guard (RG) - an architecture for rootkit resistant file-system implementation based on TPM
    Yew, Teh Jia, Khairulmizam Samsudin, Nur Izura Udzir, Shaiful Jahari Hashim
    Pertanika Journal of Science & Technology, 2013;21(2):507-520.
    MyJurnal
    Recent rootkit-attack mitigation work neglected to address the integrity of the mitigation tool itself. Both detection and prevention arms of current rootkit-attack mitigation solutions can be given credit for the advancement of multiple methodologies for rootkit defense but if the defense system itself is compromised, how is the defense system to be trusted? Another deficiency not addressed is how platform integrity can be preserved without availability of current RIDS or RIPS solutions, which operate only upon the loading of the kernel i.e. without availability of a trusted boot environment. To address these deficiencies, we present our architecture for solving rootkit persistence – Rootkit Guard (RG). RG is a marriage between TrustedGRUB (providing trusted boot), IMA (Integrity Measurement Architecture) (serves as RIDS) and SELinux (serves as RIPS). TPM hardware is utilised to provide total integrity of our platform via storage of the aggregate of the clean snapshot of our platform OS kernel into TPM hardware registers (i.e. the PCR) – of which no software attacks have been demonstrated to date. RG solves rootkit persistence by leveraging on one vital but simple strategy: the mounting of rootkit defense via prevention of the execution of configuration binaries or build initialisation scripts. We adopted the technique of rootkit persistence prevention via thwarting the initialisation of a rootkit’s installation procedure; if the rootkit is successfully installed, proper deployment via thwarting of the rootkit’s
    configuration is prevented. We had subjected the RG to 8 real world Linux 2.6 rootkits and the RG was successful in solving rootkit persistence in all 8 evaluated rootkits. In terms of performance, the RG introduced a maximum of 11% overhead and an average of 4% overhead, hence permitting deployment in production environments.
    Matched MeSH terms: Computers
  17. Fulltext Application of computer vision in the detection of chilling injury in bananas
    Norhashila Hashim, Rimfiel B. Janius, Russly Abdul Rahman, Azizah Osman, Zude, Manuela, Shitan, Mahendran
    Pertanika Journal of Science & Technology, 2013;21(1):111-118.
    MyJurnal
    Bananas were chilled at 6oC and the appearance of brown spots when exposed to ambient air, a
    phenomenon known as chilling injury (CI), was detected using computer vision. The system consisted of a digital colour camera for acquiring images, an illumination set-up for uniform lighting, a computer for receiving, storing and displaying of images and software for analyzing the images. The RGB colour space values of the images were transformed into that of HSI colour space which is intuitive to human vision. Visual assessment of CI by means of a browning scale was used as a reference and correlation between this reference values and hue was investigated. Results of the computer vision study successfully demonstrate the potential of the system in substituting visual assessment in the evaluation of CI in bananas. The results indicate significant influence, at α=0.05, of treatment days and temperature on hue. A strong correlation was also found between hue and visual assessment with R>0.85.
    Matched MeSH terms: Computers
  18. Pixel-based skin colour detection techniques evaluation
    Alnned M. Mharib, Mohammad Hamiruce Marhaban, Abdul Rahman Ramli
    Pertanika Journal of Science & Technology, 2007;15(2):131-137.
    MyJurnal
    Skin detection has gained popularity and importance in the computer vision community. It is an essential step for important vision tasks such as the detection, tracking and recognition of face, segmentation of hand for gesture analysis, person identification, as well as video surveillance and filtering of objectionable web images. All these applications are based on the assumption that the regions of the human skin are already located. In the recent past, numerous techniques for skin colour modeling and recognition have been proposed. The aims of this paper are to compile the published pixel-based skin colour detection techniques to describe their key concepts and try to find out and summarize their advantages, disadvantages and characteristic features.
    Matched MeSH terms: Computers
  19. Fulltext Geospatial Water Productivity Index (WPI) for rice
    Md Rowshon Kamal, Mohd Amin Mohd Soom, Abdul Rashid Mohamed Shariff
    Pertanika Journal of Science & Technology, 2012;20(2):381-399.
    MyJurnal
    A GIS-based user-interface programme was developed to compute the geospatial Water ProductivityIndex (WPI) of a river-fed rice irrigation scheme in Northwest Selangor, Malaysia. The spatial analysisincludes irrigation blocks with sizes ranging from 20 to 300 ha. The amount of daily water use for eachirrigation block was determined using irrigation delivery model and stored in the database for both mainseason (August to December) and off season (February to May). After cut-off of the irrigation supply,a sub-module was used to compute the total water use including rainfall for each irrigation block. Therice yield data for both seasons were obtained from DOA (Department of Agriculture, Malaysia) of thescheme. Then, the Water Productivity Index (WPI) was computed for each irrigation block and spatialthematic map was also generated. ArcObjects and Visual Basic Application (VBA) programminglanguages were used to structure user-interface in the ArcGIS software. The WPI, expressed in termsof crop yield per unit amount of water used (irrigation and effective rainfall), ranged from 0.02 to 0.57kg/m3 in the main season and 0.02 to 0.40 in off season among irrigation blocks, respectively. Thedevelopment of the overall system and the procedure are illustrated using the data obtained from thestudy area. The approach could be used to depict the gaps between the existing and appropriate watermanagement practices. Suitable interventions could be made to fill the gaps and enhance water useefficiency at the field level and also help in saving irrigation water through remedial measures in theseason. The approach could be useful for irrigation managers to rectify and enhance decision-makingin both the management and operation of the next irrigation season.
    Matched MeSH terms: Computers
  20. Fulltext Integrated partial match query in Geographic Information Retrieval
    Rosilawati Zainol, Sayed Jamaludin Sayed Ali, Zainab Abu Bakar
    Pertanika Journal of Science & Technology, 2011;19(3):41-49.
    MyJurnal
    This paper presents the evaluation of integrated partial match query in Geographic Information Retrieval (GIR). To facilitate the evaluation, Kuala Lumpur tourist related data is used as test collection and is stored in SuperWeb, a map server. Then the map server is customized to enhance its query capability to recognize word in partial or case sensitive between layers of spatial data. Query keyword is tested using the system and results are evaluated using experiments on sample data. Findings show that integrated partial match query provides more flexibility to tourist in determining search results.
    Matched MeSH terms: Computers
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