Displaying publications 1 - 20 of 2315 in total

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  1. Rezaiy R, Shabri A
    Water Sci Technol, 2024 Feb;89(3):745-770.
    PMID: 38358500 DOI: 10.2166/wst.2024.028
    This study introduces ensemble empirical mode decomposition (EEMD) coupled with the autoregressive integrated moving average (ARIMA) model for drought prediction. In the realm of drought forecasting, we assess the EEMD-ARIMA model against the traditional ARIMA approach, using monthly precipitation data from January 1970 to December 2019 in Herat province, Afghanistan. Our evaluation spans various timescales of standardized precipitation index (SPI) 3, SPI 6, SPI 9, and SPI 12. Statistical indicators like root-mean-square error, mean absolute error (MAE), mean absolute percentage error (MAPE), and R2 are employed. To comprehend data features thoroughly, each SPI series initially computed from the original monthly precipitation time series. Subsequently, each SPI undergoes decomposition using EEMD, resulting in intrinsic mode functions (IMFs) and one residual series. The next step involves forecasting each IMF component and residual using the corresponding ARIMA model. To create an ensemble forecast for the initial SPI series, the predicted outcomes of the modeled IMFs and residual series are finally added. Results indicate that EEMD-ARIMA significantly enhances drought forecasting accuracy compared to conventional ARIMA model.
    Matched MeSH terms: Time Factors
  2. Adam MS, Por LY, Hussain MR, Khan N, Ang TF, Anisi MH, et al.
    Sensors (Basel), 2019 Aug 29;19(17).
    PMID: 31470520 DOI: 10.3390/s19173732
    Many receiver-based Preamble Sampling Medium Access Control (PS-MAC) protocols have been proposed to provide better performance for variable traffic in a wireless sensor network (WSN). However, most of these protocols cannot prevent the occurrence of incorrect traffic convergence that causes the receiver node to wake-up more frequently than the transmitter node. In this research, a new protocol is proposed to prevent the problem mentioned above. The proposed mechanism has four components, and they are Initial control frame message, traffic estimation function, control frame message, and adaptive function. The initial control frame message is used to initiate the message transmission by the receiver node. The traffic estimation function is proposed to reduce the wake-up frequency of the receiver node by using the proposed traffic status register (TSR), idle listening times (ILTn, ILTk), and "number of wake-up without receiving beacon message" (NWwbm). The control frame message aims to supply the essential information to the receiver node to get the next wake-up-interval (WUI) time for the transmitter node using the proposed adaptive function. The proposed adaptive function is used by the receiver node to calculate the next WUI time of each of the transmitter nodes. Several simulations are conducted based on the benchmark protocols. The outcome of the simulation indicates that the proposed mechanism can prevent the incorrect traffic convergence problem that causes frequent wake-up of the receiver node compared to the transmitter node. Moreover, the simulation results also indicate that the proposed mechanism could reduce energy consumption, produce minor latency, improve the throughput, and produce higher packet delivery ratio compared to other related works.
    Matched MeSH terms: Time Perception
  3. Nur Atikah Arbain, Mohd Sanusi Azmi, Sharifah Sakinah Syed Ahmad, Azah Kamilah Muda, Intan Ermahami A. Jalil, King Ming Tiang
    MyJurnal
    In recent years, many classification models have been developed and applied to increase their accuracy. The concept of distance between two samples or two variables is a fundamental concept in multivariate analysis. This paper proposed a tool that used different similarity distance approaches with ranking method based on Mean Average Precision (MAP). In this study, several similarity distance methods were used, such as Euclidean, Manhattan, Chebyshev, Sorenson and Cosine. The most suitable distance measure was based on the smallest value of distance between the samples. However, the real solution showed that the results were not accurate as and thus, MAP was considered the best approach to overcome current limitations.
    Matched MeSH terms: Time
  4. You HW
    Heliyon, 2018 Oct;4(10):e00848.
    PMID: 30386825 DOI: 10.1016/j.heliyon.2018.e00848
    The side sensitive group runs (SSGR) chart is better than both the Shewhart and synthetic charts in detecting small and moderate process mean shifts. In practical circumstances, the process parameters are seldom known, so it is necessary to estimate them from in-control Phase-I samples. Research has discovered that a large number of in-control Phase-I samples are needed for the SSGR chart with estimated process parameters to behave similarly to a chart with known process parameters. The common metric to evaluate the performance of the control chart is average run length (ARL). An assumption for the computation of the ARL is that the shift size is assumed to be known. In reality however, the practitioners may not know the following shift size in advance. In light of this, the expected average run length (EARL) will be considered to measure the performance of the SSGR chart. Moreover, the standard deviation of the ARL (SDARL) will be studied, which is used to quantify the between-practitioner variability in the SSGR chart with estimated process parameters. This paper proposes the optimal design of the estimated process parameters SSGR chart based on the EARL criterion. The application of the optimal SSGR chart with estimated process parameters is demonstrated with actual data taken from a manufacturing company.
    Matched MeSH terms: Time
  5. Hashimoto T, Ozaki A, Bhandari D, Sawano T, Murayama A, Shrestha S, et al.
    Travel Med Infect Dis, 2021;43:102145.
    PMID: 34298174 DOI: 10.1016/j.tmaid.2021.102145
    Matched MeSH terms: Real-Time Polymerase Chain Reaction
  6. Chughtai JU, Haq IU, Islam SU, Gani A
    Sensors (Basel), 2022 Dec 12;22(24).
    PMID: 36560104 DOI: 10.3390/s22249735
    Travel time prediction is essential to intelligent transportation systems directly affecting smart cities and autonomous vehicles. Accurately predicting traffic based on heterogeneous factors is highly beneficial but remains a challenging problem. The literature shows significant performance improvements when traditional machine learning and deep learning models are combined using an ensemble learning approach. This research mainly contributes by proposing an ensemble learning model based on hybridized feature spaces obtained from a bidirectional long short-term memory module and a bidirectional gated recurrent unit, followed by support vector regression to produce the final travel time prediction. The proposed approach consists of three stages-initially, six state-of-the-art deep learning models are applied to traffic data obtained from sensors. Then the feature spaces and decision scores (outputs) of the model with the highest performance are fused to obtain hybridized deep feature spaces. Finally, a support vector regressor is applied to the hybridized feature spaces to get the final travel time prediction. The performance of our proposed heterogeneous ensemble using test data showed significant improvements compared to the baseline techniques in terms of the root mean square error (53.87±3.50), mean absolute error (12.22±1.35) and the coefficient of determination (0.99784±0.00019). The results demonstrated that the hybridized deep feature space concept could produce more stable and superior results than the other baseline techniques.
    Matched MeSH terms: Time Factors
  7. Maziyah Mohamed M, Yap MJ, Chee QW, Jared D
    Mem Cognit, 2023 Apr;51(3):647-665.
    PMID: 35705853 DOI: 10.3758/s13421-022-01337-8
    Morphological processing in visual word recognition has been extensively studied in a few languages, but other languages with interesting morphological systems have received little attention. Here, we examined Malay, an Austronesian language that is agglutinative. Agglutinative languages typically have a large number of morphemes per word. Our primary aim was to facilitate research on morphological processing in Malay by augmenting the Malay Lexicon Project (a database containing lexical information for almost 10,000 words) to include a breakdown of the words into morphemes as well as morphological properties for those morphemes. A secondary goal was to determine which morphological variables influence Malay word recognition. We collected lexical decision data for Malay words that had one prefix and one suffix, and first examined the predictive power of 15 morphological and four lexical variables on response times (RT). Of these variables, two lexical and three morphological variables emerged as strong predictors of RT. In GAMM models, we found a facilitatory effect of root family size, and inhibitory effects of prefix length and prefix percentage of more frequent words (PFMF) on RT. Next, we explored the interactions between overall word frequency and several of these predictors. Of particular interest, there was a significant word frequency by root family size interaction in which the effect of root family size is stronger for low-frequency words. We hope that this initial work on morphological processing in Malay inspires further research in this and other understudied languages, with the goal of developing a universal theory of morphological processing.
    Matched MeSH terms: Reaction Time
  8. LLEWELLYN-JONES D
    Med J Malaya, 1958 Sep;13(1):43-8.
    PMID: 13589368
    Matched MeSH terms: Time Factors*
  9. Nathan, Nivethiny
    MyJurnal
    The timing of ABG procedure in a cleft patient is crucial to provide room and bony
    support for the eruption of canine. However, there seems to be a delay in execution of this
    procedure in certain centres. Material and Methods: Sample consists of records of cleft patients
    treated from 2000-2016. The date and age for commencement of active orthodontic treatment,
    date referred for ABG and date ABG done were retrieved. The centres that conducted these
    surgeries identified. (Copied from article).
    Matched MeSH terms: Time Factors*
  10. Ahmad BA, Khairatul K, Farnaza A
    Malays Fam Physician, 2017;12(1):14-21.
    PMID: 28503269 MyJurnal
    Waiting is a common phenomenon in the doctor's waiting room. The purpose of this audit is to assess patient waiting time and doctor consultation time in a primary healthcare clinic and to formulate strategies for improvement. This audit was conducted at a primary care clinic for 4 weeks using the universal sampling method. All patients who attended the clinic during this period was included in the study except for those who required more time to be seen such as those who were critically ill, aggressive or those who came for repeat medication or procedures only without needing to see the doctor. The time of arrival was captured using the queue management system (QMS) and then the patient was given a timing chit which had to be manually filled by the staff at every station. The waiting time for registration, pre-consultation, consultation, appointment, payment and pharmacy were recorded as well as consultation time. The data were entered into the statistical software SPSS version 17 for analysis. version 17. Results showed that more than half of the patients were registered within 15 minutes (53%) and the average total waiting time from registration to seeing a doctor was 41 minutes. Ninety-nine percentage of patients waited less than 30 minutes to get their medication. The average consultation time was 18.21 minutes. The problems identified in this audit were addressed and strategies formulated to improve the waiting and consultation time were carried out including increasing the number of staff at the registration counter, enforcing the staggered appointment system for follow-up patients and improving the queuing system for walk-in patients.
    Matched MeSH terms: Time Factors*
  11. Shafizadeh M, Davids K, Correia V, Wheat J, Hizan H
    J Sports Sci, 2016 Sep;34(17):1596-601.
    PMID: 26652039 DOI: 10.1080/02640414.2015.1125011
    The aim of this study was to examine whether perceptual variables can provide informational constraints for the goalkeepers to intercept the ball successfully in 1v1 dyads. Video images of 42 actions (1v1 in direct shots) were selected randomly from different matches and divided into conceded goals (n = 20) and saved actions (n = 22) to investigate interceptive actions of 20 goalkeepers in the English Premier League in season 2013-2014. Time to Contact (TTC) of the closing distance gap between shooter and goalkeeper was obtained by digitising actions in the 18-yard penalty box. Statistical analyses revealed that, in sequences of play resulting in an intercepted shot at goal, goalkeepers closed down outfield players in the X axis, whereas when a goal was conceded, there was a significantly delayed movement by goalkeepers toward the shooters in this plane. The results of canonical correlations showed that a decreasing distance between a shooter and goalkeeper, and accompanied reduction in relative interpersonal velocity followed a temporal pattern. Findings of this study showed how perception of key informational constraints on dyadic system relations, such as TTC, interpersonal distance and relative velocity, constrain elite goalkeepers' interceptive actions, playing an important role in successful performance.
    Matched MeSH terms: Reaction Time; Time Perception/physiology*
  12. Asiaweek, 1995 Sep 29.
    PMID: 12290445
    Matched MeSH terms: Time Factors*
  13. Azlin, I., Hafiza, A., Azma, R.Z., Aidifitrina, R.K., Hamidah, N.H.
    Medicine & Health, 2011;6(1):68-72.
    MyJurnal
    Centrifugation of blood samples to produce platelet-poor plasma is one of the important steps for coagulation testing. Reduction of the time required for specimen processing without affecting quality of results should be ideal for tests which require immediate results. Centrifugation of platelet-poor plasma (3580 rpm) for 15 minutes performed for routine coagulation tests would prolong the turn-around time for an urgent test (30 minutes). This study was done to determine the effect of reducing centrifugation time for routine coagulation tests in order to meet the turn-around time (TAT) for urgent tests. Seventy-nine blood samples sent for routine coagulation tests, were assayed for prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen level and platelet counts, using two different centrifugation speed for plasma preparation: centrifugation at 3580 rpm for 15 minutes and rapid centrifugation at 4000 rpm for five minutes. Paired sample t-test showed that there was a significant
    difference in the platelet count between the two groups (p=0.001). However, there was no significant difference in the normal APTT (p=0.16), abnormal APTT (p=0.80), abnormal PT (p=0.43) and the results of fibrinogen levels (p=0.36). In conclusion, rapid centrifugation at 4000 rpm for five minutes does not modify results of routine coagulation tests (PT, APTT and fibrinogen). It would be beneficial in providing rapid results for urgent coagulation tests.
    Matched MeSH terms: Partial Thromboplastin Time; Prothrombin Time
  14. LAU KS, SINGH N
    Med J Malaysia, 1963 Dec;18:107-15.
    PMID: 14117278
    Matched MeSH terms: Prothrombin Time*
  15. Miraj M, Chuntian L, Rehman RU, Osei-Bonsu R, Mohd Said R, Ali R, et al.
    Work, 2022;73(4):1365-1378.
    PMID: 36093656 DOI: 10.3233/WOR-205237
    BACKGROUND: Research is essential and necessary for those who love learning, whether they belong to a research institution or not. Numerous elements influence researchers' attitudes towards good research work, but in this study we focus on the most significant ones: advisor support, intrinsic motivation, timing, and planning.

    OBJECTIVES: The current study aims at motivating readers to help improve students' attitudes towards research work within the university context.

    METHOD: The target demographic of the current research comprises masters and doctoral students from three major public institutions in Xi'an, China. We aimed to examine the effects of the variables and the study employed correlation and stepwise regression.

    RESULTS: The results show that advisor support influences attitudes towards research positively and significantly (β= 0.20, p Time attitudes significantly influenced attitudes towards research (β= 0.14, p time planning also positively and significantly influenced the attitude towards research (β= 0.15, p time and be equipped with time management skills.

    Matched MeSH terms: Time Management*
  16. Ullah S, Daud H, Dass SC, Fanaee-T H, Khalil A
    PLoS One, 2018;13(6):e0199176.
    PMID: 29920540 DOI: 10.1371/journal.pone.0199176
    Identifying the abnormally high-risk regions in a spatiotemporal space that contains an unexpected disease count is helpful to conduct surveillance and implement control strategies. The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. However, the main problem with the EigenSpot method is that it cannot be adapted to detect more than one spatiotemporal hotspot. This is an important limitation, since, in reality, we may have multiple hotspots, sometimes at the same level of importance. We propose an extension of the EigenSpot algorithm, called Multi-EigenSpot that is able to handle multiple hotspots by iteratively removing previously detected hotspots and re-running the algorithm until no more hotspots are found. In addition, a visualization tool (heatmap) has been linked to the proposed algorithm to visualize multiple clusters with different colors. We evaluated the proposed method using the monthly data on measles cases in Khyber-Pakhtunkhwa, Pakistan (Jan 2016- Dec 2016), and the efficiency was compared with the state-of-the-art methods: EigenSpot and Space-time scan statistic (SaTScan). The results showed the effectiveness of the proposed method for detecting multiple clusters in a spatiotemporal space.
    Matched MeSH terms: Space-Time Clustering*
  17. Kamarudin K, Mamduh SM, Shakaff AY, Zakaria A
    Sensors (Basel), 2014;14(12):23365-87.
    PMID: 25490595 DOI: 10.3390/s141223365
    This paper presents a performance analysis of two open-source, laser scanner-based Simultaneous Localization and Mapping (SLAM) techniques (i.e., Gmapping and Hector SLAM) using a Microsoft Kinect to replace the laser sensor. Furthermore, the paper proposes a new system integration approach whereby a Linux virtual machine is used to run the open source SLAM algorithms. The experiments were conducted in two different environments; a small room with no features and a typical office corridor with desks and chairs. Using the data logged from real-time experiments, each SLAM technique was simulated and tested with different parameter settings. The results show that the system is able to achieve real time SLAM operation. The system implementation offers a simple and reliable way to compare the performance of Windows-based SLAM algorithm with the algorithms typically implemented in a Robot Operating System (ROS). The results also indicate that certain modifications to the default laser scanner-based parameters are able to improve the map accuracy. However, the limited field of view and range of Kinect's depth sensor often causes the map to be inaccurate, especially in featureless areas, therefore the Kinect sensor is not a direct replacement for a laser scanner, but rather offers a feasible alternative for 2D SLAM tasks.
    Matched MeSH terms: Operative Time
  18. Abdul Razak F, Jensen HJ
    PLoS One, 2014;9(6):e99462.
    PMID: 24955766 DOI: 10.1371/journal.pone.0099462
    'Causal' direction is of great importance when dealing with complex systems. Often big volumes of data in the form of time series are available and it is important to develop methods that can inform about possible causal connections between the different observables. Here we investigate the ability of the Transfer Entropy measure to identify causal relations embedded in emergent coherent correlations. We do this by firstly applying Transfer Entropy to an amended Ising model. In addition we use a simple Random Transition model to test the reliability of Transfer Entropy as a measure of 'causal' direction in the presence of stochastic fluctuations. In particular we systematically study the effect of the finite size of data sets.
    Matched MeSH terms: Time Factors
  19. Mohammed Saghir SA, Al-Hassan FM, Alsalahi OS, Abdul Manaf FS, Baqir HS
    J Coll Physicians Surg Pak, 2012 May;22(5):294-7.
    PMID: 22538033 DOI: 05.2012/JCPSP.294297
    To determine the optimum storage temperature and time for prothrombin time and activated partial thromboplastin time at various intervals at both room temperature and refrigerator.
    Matched MeSH terms: Partial Thromboplastin Time*; Prothrombin Time*
  20. Lan BL, Borondo F
    Phys Rev E Stat Nonlin Soft Matter Phys, 2011 Mar;83(3 Pt 2):036201.
    PMID: 21517569
    Newtonian and special-relativistic predictions, based on the same model parameters and initial conditions for the trajectory of a low-speed scattering system are compared. When the scattering is chaotic, the two predictions for the trajectory can rapidly diverge completely, not only quantitatively but also qualitatively, due to an exponentially growing separation taking place in the scattering region. In contrast, when the scattering is nonchaotic, the breakdown of agreement between predictions takes a very long time, since the difference between the predictions grows only linearly. More importantly, in the case of low-speed chaotic scattering, the rapid loss of agreement between the Newtonian and special-relativistic trajectory predictions implies that special-relativistic mechanics must be used, instead of the standard practice of using Newtonian mechanics, to correctly describe the scattering dynamics.
    Matched MeSH terms: Time Factors
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